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Table of contents :
Contents
Preface
Acknowledgments
Chapter 1
Lithium-Ion Batteries - Fundamental to Applications
Abstract
Introduction to Li-Ion Batteries (LIBs)
Thermodynamics of Li-ion Battery
Working Principle of LIB
Major Components of LIBs
Cathode Materials
Properties of Cathodes
Various Kinds of Cathodes
Transition Metal Oxide-Based Cathodes
Lithium Cobalt Oxide (LiCoO2)
Lithium Nickel Oxide (LiNiO2)
Lithium Manganese Oxide (LiMnO2)
Lithium Nickel Manganese Cobalt Oxide (NMC) ─ LiNi1-y-zMnyCozO2
Lithium–Manganese Rich Ni-Mn-Co Oxides (LMR-NMC)
Li-V-O Layered Cathodes
Three-Dimensional LixMn2O4 Spinel
Polyanionic Type Cathodes
One-Dimensional Olivine
Silicates
Tavorites
Lithium Excess Disordered Rock-Salt Cathodes
Conversion Type Cathodes
Type 1-Category Conversion Cathodes
Type 2-Category Conversion Cathodes
Safety Aspects of Layered Oxides vs. Olivines (LiCoO2 vs LiFePO4)
Anode Materials
Features of Anodes for Lithium-Ion Batteries
Intercalation Type Anodes
Conversion Type Anodes
Composites and Alloy Type Anodes
Solid Electrolyte Interface (SEI) layer Formation Phenomenon on the Anode
Electrolytes
Electrolytes Based on Carbonate Solvents
Ionic Liquid-Based Electrolytes
Polymer-Based Electrolytes
Solid-State Electrolytes
Separator
Commercial Designing of Lithium-Ion Cells
Mechanisms of Degradation of Cell Components
Self-Discharge
Structural and Chemical Changes in the Cathode Active Materials
Structural and Chemical Changes in the Anode Active Materials
Degradation of Electrolytes in LIB
Overcharge of LIBs
Corrosion of Current Collectors
Degradation of Separator
Thermal Exploitation
Battery Management System
Problem Mitigation Strategies of Cell Components
Problem Mitigation for Cathodes
Mitigation Strategies for Anodes
Problem Mitigation for Electrolytes
Problem Mitigation for Separator
Conclusion
Acknowledgments
References
Chapter 2
Combined Nuclear Reactor Thermal Energy Storage Systems
Abstract
Introduction
Nuclear Energy Systems
History
Share of Nuclear Power
Economic and Environmental Perspectives
Social Costs
Nuclear System Design
Thermal Energy Storage (TES)
The Categorization of the TES Technologies
Sensible Heat Storage
Latent Heat Storage
Thermochemical Storage
Thermal Storage Design
Methods and Analysis
Transitional Analysis
Transitional System Model Description
Reactor Kinetics Unit
Reactor Hydraulic, Thermal Unit
Reactor Decomposition Heat Unit
Thermal Energy Storage Unit
Temporary Results for the Model
Normal Operation
Loss of Forced Circulation Accident
Conclusion and Summary
Market and Economy
Market Designs
Economic Restrictions
Technical Strategies
Baseload Electricity (Black Lines and Stripes)
Peak Electricity Production
Turbine Waste Heat Recovery
Add Steam Using the Stored Heat of HRSG
Policy Implications
References
Chapter 3
Latent Heat Storage with Embedded Porous Media
Abstract
Introduction
PCM Embedded Porous Media
Mathematical Modeling of PCM Embedded Porous Media
Melting and Solidification of PCM Embedded Porous Media
Conclusion
References
Chapter 4
Integrated Energy Storage Systems with Solar Collectors
Abstract
Introduction
Expérimentation
Mathematical Solution
Numerical Solution for 1-D Heat Transfer
Thermal Performance Parameters
Numerical Modeling of Transient 2-D Laminar Model Using CFD Tools
Modeling of Phase Change Material: Melting and Solidification (2D)
Conclusion
References
Chapter 5
Optimal CCHP Combined with Thermal Energy Storage System Design Using Genetic Algorithm
Abstract
Introduction
Combined Cooling, Heating and Power (CCHP)
Distributed Energy Demand
Improvement Design Strategies
Technical Review
Extraction Condensing
Backpressure Power Plants
Industrial Backpressurere Power Plants
Backpressure Power Plants for Use in District Heating
Gas Turbine and Heat Recycling Boiler
Combined Cycle Power Plants
Power Plants Equipped with Reciprocating Motors
Methods
Genetic Algorithm
Operators of a Genetic Algorithm
Genetic Algorithm Applications
Termination Conditions for Genetic Algorithms Are
CCHP Modeling
Operational Strategies
System Model
Performance Factors
Performance and Optimal Point Modeling
System Constraints
Implementation Method
GA Modelling
Calculate the Fit Function
Case Study
Conclusion
Appendix 1
References
Chapter 6
Natural Convection Grain Dryer
Abstract
Introduction
Materials and Methods
Theoretical Analysis
Effect of Sensible Heat Storage Material on Non-Dimensional Numbers and Heat Transfer Coefficient
Conclusion
Acknowledgments
References
Chapter 7
Exergy Analysis of a Natural Convection Grain Dryer
Abstract
Introduction
Experimental Set-Up and Procedure
Mathematical Model
Effect of Sensible Heat Storage Material on the Exergy in the Rectangular Chamber
Conclusion
Acknowledgments
References
About the Editor
Index
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ENERGY SCIENCE, ENGINEERING AND TECHNOLOGY

ENERGY STORAGE SYSTEMS AN INTRODUCTION

No part of this digital document may be reproduced, stored in a retrieval system or transmitted in any form or by any means. The publisher has taken reasonable care in the preparation of this digital document, but makes no expressed or implied warranty of any kind and assumes no responsibility for any errors or omissions. No liability is assumed for incidental or consequential damages in connection with or arising out of information contained herein. This digital document is sold with the clear understanding that the publisher is not engaged in rendering legal, medical or any other professional services.

ENERGY SCIENCE, ENGINEERING AND TECHNOLOGY Additional books and e-books in this series can be found on Nova’s website under the Series tab.

ENERGY SCIENCE, ENGINEERING AND TECHNOLOGY

ENERGY STORAGE SYSTEMS AN INTRODUCTION

SATYENDER SINGH EDITOR

Copyright © 2021 by Nova Science Publishers, Inc. All rights reserved. No part of this book may be reproduced, stored in a retrieval system or transmitted in any form or by any means: electronic, electrostatic, magnetic, tape, mechanical photocopying, recording or otherwise without the written permission of the Publisher. We have partnered with Copyright Clearance Center to make it easy for you to obtain permissions to reuse content from this publication. Simply navigate to this publication’s page on Nova’s website and locate the “Get Permission” button below the title description. This button is linked directly to the title’s permission page on copyright.com. Alternatively, you can visit copyright.com and search by title, ISBN, or ISSN. For further questions about using the service on copyright.com, please contact: Copyright Clearance Center Phone: +1-(978) 750-8400 Fax: +1-(978) 750-4470 E-mail: [email protected]

NOTICE TO THE READER The Publisher has taken reasonable care in the preparation of this book, but makes no expressed or implied warranty of any kind and assumes no responsibility for any errors or omissions. No liability is assumed for incidental or consequential damages in connection with or arising out of information contained in this book. The Publisher shall not be liable for any special, consequential, or exemplary damages resulting, in whole or in part, from the readers’ use of, or reliance upon, this material. Any parts of this book based on government reports are so indicated and copyright is claimed for those parts to the extent applicable to compilations of such works. Independent verification should be sought for any data, advice or recommendations contained in this book. In addition, no responsibility is assumed by the Publisher for any injury and/or damage to persons or property arising from any methods, products, instructions, ideas or otherwise contained in this publication. This publication is designed to provide accurate and authoritative information with regard to the subject matter covered herein. It is sold with the clear understanding that the Publisher is not engaged in rendering legal or any other professional services. If legal or any other expert assistance is required, the services of a competent person should be sought. FROM A DECLARATION OF PARTICIPANTS JOINTLY ADOPTED BY A COMMITTEE OF THE AMERICAN BAR ASSOCIATION AND A COMMITTEE OF PUBLISHERS. Additional color graphics may be available in the e-book version of this book.

Library of Congress Cataloging-in-Publication Data ISBN: 978-1-53618- H%RRN

Published by Nova Science Publishers, Inc. † New York

CONTENTS Preface

vii

Acknowledgments

xi

Chapter 1

Chapter 2

Lithium-Ion Batteries Fundamental to Applications Udita Bhattacharjee, Madhushri Bhar, Sourav Ghosh and Surendra K. Martha Combined Nuclear Reactor Thermal Energy Storage Systems Nima Norouzi and Saeed Talebi

Chapter 3

Latent Heat Storage with Embedded Porous Media Satyender Singh, Shailendra Kumar Chaurasiya and Subhash Chnader

Chapter 4

Integrated Energy Storage Systems with Solar Collectors Bharat Singh Negi, Satyender Singh and Subhash Chander

Chapter 5

Optimal CCHP Combined with Thermal Energy Storage System Design Using Genetic Algorithm Nima Norouzi and Maryam Fani

1

129 169

183

203

vi

Contents

Chapter 6

Natural Convection Grain Dryer Dhananjay Kumar, Pinakeswar Mahanta and Pankaj Kalita

Chapter 7

Exergy Analysis of a Natural Convection Grain Dryer Dhananjay Kumar, Pinakeswar Mahanta and Pankaj Kalita

243

255

About the Editor

267

Index

269

PREFACE Thermal energy storage has gained every attention across the world due to increasing global needs. Increasing population and changing lifestyle have increased the energy demand which is difficult to provide sustainably using any source, and hence requires energy storage and its supply when needed. Literature on the energy storage is largely available at present and many attractive systems are reported. In this direction, this book covers an overview and applications of the thermal energy storage systems that can be efficiently used for thermal energy storage. As thermal energy can be stored in many forms, the content of this book covers almost every form of thermal energy storage and systems design for the same. The book in detail summarized various aspects of thermal energy storage systems (TESS) such as lithium-Ion Batteries, Nuclear reactor, Latent heat storage with PCM embedded porous media, CCHP with TESS, PCM in solar collectors, and grain dryer. The early development of lithium batteries began with the development of lithium metal batteries. The research and development of LIBs had begun with primary LIBs such as lithium-poly carbon monofluoride (Li//(CFx)n) cells by Matsushita in 1973, lithium-manganese oxide (Li//MnO2) cells by Sanyo in 1975, Lithium-copper oxide (Li//CuO) cells, lithium-iodine (Li//(P2VP)In) cells in 1972, molten salt systems (LiCl-KCl eutectic) using a Li-Al alloy anode and FeS2 as the cathode, etc.

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Satyender Singh

Lithium-iodine cells were used to power cardiac pacemakers. Li/MnO2 cells were used in solar rechargeable calculators. Around the 1970s, Bell Laboratories, USA reported the intercalation properties into NbSe3 or TiS3 based dichalcogenide host material. The first chapter in this book offers a systematic overview of the development timeline, operating principles, cathodes, anodes, electrolytes, separators, and manufacturing processes of Lithium-ion batteries. Chapter present an outlook of the development of various kinds of cathodes such as layered, olivines, spinels, conversion type materials is discussed thoroughly. Similarly, materials developments in terms of the anodes are classified and presented as intercalation, conversion, and alloy type anodes. The requirement of a conductive ion matrix between the cathode and anode of a cell with a wider voltage range and minimum spillage, various types of electrolytes (organic, ionic-liquid, polymer, and Solid-state electrolytes) which has been explored in literature are articulated systematically. In short, this Chapter is an outline of the development stages of Li-ion battery electrochemistry, including the commercial success and current challenges in the field with mitigation strategies and the future of Li-ion batteries are explored. Nuclear power plants operate most economically at a constant level of electricity, providing a baseload power portfolio. Thermal energy storage is significantly important for moderate to high thermal applications. In an energy grid containing a large proportion of renewable energy sources, nuclear reactors can be advanced to significant energy changes. These varying capacity requirements can adversely affect the reactor usable capacity factor and result in severe economic penalties. Attaching a nuclear reactor to a large thermal energy storage unit will allow the reactor to respond better to different energy needs. In the system described in Chapter 2, the high-nuclear high-temperature reactor supplies constant power to the thermal energy storage unit of the molten lithium chloride salt, which provides the required thermal energy for a closed energy conversion system of the Bryton cycle. During regular operation, the thermal energy storage unit stores heat during the night for use during peak demand periods during the day. In this case, the nuclear reactor remains at a constant level of thermal capacity.

Preface

ix

A details of energy storage in PCM embedded with porous media is presented in Chapter 3 and application of such systems is presented in Chapter 4. PCM have gained many attention of the researchers due to longer thermal recycling and chamical stablity. Moreover, high latent heat copacity is one of the most significant aspect towards the polularity of PCMs. Though, low thermal conductivity of PCMs limits their usage in many thermal applications and can be improved by using porous media as a embeeded material in PCM. Chapter 5 delineated the the optimal working point of a system consisting of several independent units, capable of trading electricity, based on the consumption of various fuels, and utilization of heat storage tank was determined using genetic algorithm, and modeling accuracy were compared. Chapters 6 and 7 present a clear understading of working and investigation procedure of natural convection grain dryers. This book is a summerization of overview and applications of energy storage systems and will be helpful to readers to understand fundaments, working, concept of many thermal energy storage systems.

ACKNOWLEDGMENTS First and above all, I thank God, for providing me this opportunity and granting me the capability to proceed successfully. This book has been kept on track and been seen through to completion with the support and encouragement of numerous people including authors from various institutions who contributed excellent chapters for this book. I would therefore like to offer my sincere thanks to all of them. I cannot forget to acknowledge my family members. My father Sh. Balwant Singh and mother Smt. Hima Devi, sister Ms. Meenakshi, wife Mrs. Ritika Kondal and daughter Ms. Satvika Singh have given me their unequivocal support throughout, as always, for which my mere expression of thanks likewise does not suffice. I would like to pay high regards to my loving grandfather Late Dr. Karam Singh and grandmother Late Smt. Tara Devi, who have always been a driving force behind my achievements and whose sheer affection has nurtured my spirit throughout the life. Last but not least, I would like to share my joy of learning at NIT Hamirpur during my PhD under the guidance of my supervisor Dr. Prashant Dhiman (Assoc. Prof. NIT Hamirpur) and IIT Bombay during Post-Doctorate under the guidance of my supervisor Prof. Atul Sharma (Prof. IIT Bombay). Without their

xii

Satyender Singh

continuous guidance and support many things would not have happened in my life. Dr Satyender Singh Post Doctorate, PhD, MTech, BTech Assistant Professor, Department of Mechanical Engineering, Dr B R Ambedkar National Institute of Technology Jalandhar, India

In: Energy Storage Systems: An Introduction ISBN: 978-1-53618-873-8 Editor: Satyender Singh © 2021 Nova Science Publishers, Inc.

Chapter 1

LITHIUM-ION BATTERIES FUNDAMENTAL TO APPLICATIONS Udita Bhattacharjee†, Madhushri Bhar†, Sourav Ghosh and Surendra K. Martha‡ Department of Chemistry, Indian Institute of Technology Hyderabad, Kandi, Sangareddy, Telangana, India

ABSTRACT This chapter offers a systematic overview of the development timeline, operating principles, cathodes, anodes, electrolytes, separators, and manufacturing processes of Lithium-ion batteries. Even though the research and advancement in the cathodes and anodes for LIBs have reached many high echelons, the possible replacement of state-of-art LiCoO2//graphite system in terms of availability, cost-effectiveness, low redox potential, cycling stability, and capacity performance is challenging. In this chapter, the development of various kinds of cathodes such as layered, olivines, spinels, conversion type materials is discussed thoroughly. Similarly, materials developments in terms of the anodes are †

Equal contributing author. Equal contributing author. ‡ Corresponding Author’s Email: [email protected]

2

Udita Bhattacharjee, Madhushri Bhar, Sourav Ghosh et al. classified and presented as intercalation, conversion, and alloy type anodes. The requirement of a conductive ion matrix between the cathode and anode of a cell with a wider voltage range and minimum spillage, various types of electrolytes (organic, ionic-liquid, polymer, and Solidstate electrolytes) which has been explored in literature are articulated systematically. The recent advancements in electrode architecture using nanotechnology from an electrochemistry point of view and their impact on improving energy as well as power density are discussed. Furthermore, Lithium-ion batteries undergo degradation on cycling as well as storage for a prolonged period. This degradation or gradual fading in the performance of LIBs in terms of capacity, nominal voltage, etc. can be attributed to a series of auxiliary chemical and electrochemical reactions taking place between the active components of the cell. Some of the reasons and their mitigation strategies are briefly discussed here. In short, this Chapter is an outline of the development stages of Li-ion battery electrochemistry, including the commercial success and current challenges in the field with mitigation strategies and the future of Li-ion batteries are explored.

Keywords: Li-ion battery, electrochemistry, cathodes, anodes, electrolytes, degradation mechanism

INTRODUCTION TO LI-ION BATTERIES (LIBS) The early development of lithium batteries began with the development of lithium metal batteries. The research and development of LIBs had begun with primary LIBs such as lithium-poly carbon monofluoride (Li//(CFx)n) cells by Matsushita in 1973, lithium-manganese oxide (Li//MnO2) cells by Sanyo in 1975, Lithium-copper oxide (Li//CuO) cells, lithium-iodine (Li//(P2VP)In) cells in 1972, molten salt systems (LiCl-KCl eutectic) using a Li-Al alloy anode and FeS2 as the cathode, etc. [1]. Lithium-iodine cells were used to power cardiac pacemakers. Li/MnO2 cells were used in solar rechargeable calculators [2]. Around the 1970s, Bell Laboratories, USA reported the intercalation properties into NbSe3 or TiS3 based dichalcogenide host material [3]. Several studies reveal that alkali metals, such as Li are the most common in this context- can move rapidly through electronically

Lithium-Ion Batteries - Fundamental to Applications

3

conducting lattice of transition metals. The concept of LIBs was clarified in the late 1970s by Armand. He proposed to use two different intercalation compounds as cathode and anode so that Li-ions can be transferred to both electrodes reversibly and maintain structural stability [4]. Armand tried to incorporate transition metal oxides such as CrO3 between graphite layers [5-6]. Besides, Dey et al. observed reactivity of lithium on several metals like aluminum, etc. [7]. Whittingham while system working at Exxon Research and Engineering Company during 1976 has demonstrated Li/TiS2 of energy density 280 Wh L-1 (130 Wh kg-1) [89]. TiS2 has hexagonal closed pack sulfur lattice, and titanium resides in the octahedral sites with the alternate layered structure of Ti and S sheets (ABAB stacking), which enhances Li+ intercalation (specific capacity 240 mAh g-1). It undergoes a single-phase change to LiTiS2 over the possible range of LixTiS2 (0≤x≤1) [9]. It is a semi-metal, and thus, no other conductive additives are required with active cathode material [10]. But the disadvantage was the low nominal voltage of ~2V and spontaneous release of H2S from the cell. It was only limited to coin cell level and application of watch batteries. Then Moli Energy Ltd. in Canada manufactured Li/ MoS2 in the late 1980s [11-12]. It was having an energy density of 60-65 Wh kg-1 at a discharge rate of C/3 (~ 800 mA) in the working potential range between 2.3 and 1.3 V. It was used as the power source for pocket telephones. But all the products were recalled due to the reports of catching fires [1]. Li-metal based anode forms dendrite on repeated charging resulting in an internal short circuit and even explosion. Thus, the initial effort on LIB in the market was abruptly terminated. Though it was unfortunate, it made the researchers think of the next-generation battery technologies of high energy density with safety concerns. A few years later, in the 1980s, Godshall et al. published an article on LiCoO2 (LCO) a cathode material that can be operated at a high voltage of 3.7 V. The cell was operated by heating the electrolyte at elevated temperature region from 350 to 500°C, which is above the melting point of the molten salt electrolyte used [13]. A few days back, Goodenough et al. explored a room temperature LCO cathode with organic electrolytes, i.e., 1M LiBF4 solution in propylene carbonate solvent [14-15]. In the

4

Udita Bhattacharjee, Madhushri Bhar, Sourav Ghosh et al.

meantime, Rachid Yazami reported reversible Li+ intercalation into graphite layers, which overcomes the problem of dendrite formation [16]. Using both the concepts, the first LIB was assembled with discharged LCO cathode and discharged carbon anode [17]. Sony Energy Tec Inc. introduced the first 18650 type Li-ion cells in June 1991 in the market using LCO cathode and non-graphitic carbon (lithiated coke, LiC6) anode with LiPF6 in propylene carbonate/diethyl carbonate electrolyte. The energy density was 253 Wh L-1, and the aim was to use it on powering mobile phones [18].

2019: The Nobel Prize in chemistry awarded to M.S. Whittingham, J.B. Goodenough and Akira Yoshino for the development of LIBs 2010-2015: LFP cathode, modified graphite anode, organic electrolyte 4V. d) The material should be of low weight, high tap density, and high specific energy (high gravimetric and volumetric capacity). Specific capacity is the amount of charge transferred during a redox reaction by 1 g eq. of active material involved in the process. Theoretically, the specific capacity of a material is defined as the charge (q in mAh) generated by the redox activity of 1 g. eq. of the material. i.e., gm eq. (N) of material delivers a capacity of 26.8 Ah 1 g eq. of material delivers a capacity of

26.8 𝑁

Ah g-1.

e) The process of lithiation-delithiation to the host material should be very quick to obtain high power density. f) The material should be a good electronic conductor so that the addition and removal of electron on the charge-discharge process will be easy. This minimizes the use of conductive diluents that decreases the overall energy density.

Lithium-Ion Batteries - Fundamental to Applications

11

g) The material does not degrade or change the structure on overdischarge and over-charge. h) It should be chemically stable so that it does not react with electrolyte over the entire operating voltage range. i) The cycle-life of a cathode should be >1000 cycles with stable capacity retention. j) The material should be of low-cost, eco-friendly, and abundant in nature. k) The synthetic route of the cathode active compound should be feasible and fast to make it practically viable. Further, the scale-up process should not impact the electrode performance. l) The liberation of heat on a fully charged or overcharged state should be minimum to be a safe material in terms of thermal stability.

Various Kinds of Cathodes Rechargeable Li-ion battery cathode can be broadly classified into four major sections based on their lithiation- delithiation characteristics during charge-discharge cycling. a) b) c) d)

Transition metal oxide-based cathodes Polyanionic type cathodes Lithium excess disordered rock-salt cathodes Conversion type cathodes

Insertion type cathodes, especially LiCoO2 have gained most importance in rechargeable LIBs since from its application in the 1990s [14, 18]. The unique process of insertion and deinsertion of Li-ion inside the crystal lattice reversibly maintains the structural integrity. Layered LiMO2 (M = Co, Ni, Mn), LiNi1-y-zMnyCozO2 (Li-NMC), Lithium– Manganese rich NMC, and LiMn2O4 type spinel and polyanionic based transition metal phosphates (e.g., LiFePO4), silicates, tavorites have been

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Udita Bhattacharjee, Madhushri Bhar, Sourav Ghosh et al.

reported so far in the insertion type cathode family [8, 22]. Conversion type cathodes have higher energy density compare to insertion cathodes as it involves two to six electrons in the electrochemical process. This type of cathode material includes MXZ where, M= Transition metal ions such as Fe, Ni, Mn, or Cu and X= halogen atom such as F, Cl, Br, I; like FeF3, FeF2, NiF2, etc. Li-sulfur and Li-air batteries are the emerging technology in conversion cathode families towards the future generation of Li-ion battery [23]. The above-mentioned four types of cathodes are briefly discussed in the following section.

Transition Metal Oxide-Based Cathodes 5.5

Fig. 6

5.0

Voltage (V)

4.5 4.0 3.5 3.0 2.5 2.0 0

50

100

150

200

250

300

Discharge capacity (mAh g-1)

Figure 5. Discharge profile of layered transition metal oxides cathodes such as LCO, Li-NMC, and LMR-NMC (crystal structure inset.) Reproduced with permission from [24].

Lithium Cobalt Oxide (LiCoO2) LiCoO2 (LCO) is the most commonly used insertion type cathode material in rechargeable LIBs since its discovery in 1976 by Goodenough et al. [14] and later commercialized by SONY in 1990 [18, 25]. It has

Lithium-Ion Batteries - Fundamental to Applications

13

excellent structural stability, facile synthesis on a large scale with high quality, high working voltage (>3.7 V), high theoretical capacity (274 mAh g-1), low self-discharge rate, and high cycling stability (>500 chargedischarge cycles). LCO has two crystal structures: cubic spinel structure at low temperature (350°C) and layered hexagonal structure when calcined at 750°C. The electrochemical behavior is observed to be more promising when it exists as layered hexagonal structure in which edge-sharing CoO6 octahedral layers are separated by interstitial Li layers [26]. Even though the theoretical capacity of LCO is calculated to be 274 mAh g-1 (considering 1 e- redox process), the oxidation of Co3+ and the corresponding structural phase change limits the Li-ion extraction to 50% from LCO, resulting in the practical/achievable capacity of 140 mAh g-1 (when the upper cut-off potential is restricted to 4.2 V). The number of Liions participating in the electrochemical cell reaction could be increased by extending the upper cut-off potential to 4.5 V in LCO [27]. However, more than 50% removal of Li from the parent compound in highly delithiated state (>4.2V) undergo structural distortion from hexagonal to the tetragonal lattice, oxygen release, and Co dissolution resulting in degradation of battery performance [28]. Further, overcharging of LCO, i.e., Lix→0CoO2, forms Co3O4 and O2, resulting in a highly exothermic reaction with organic electrolyte [29]. 𝐿𝑖0.5 𝐶𝑜𝑂2 =

1 2

𝐿𝑖𝐶𝑜𝑂2 +

1 6

𝐶𝑜3 𝑂4 +

1 6

𝑂2

(7)

LCO is commonly prepared by solid-state reaction using different precursors Li2O-CoO, LiOH-Co3O4, Li2CO3-Co, Li2CO3-Co3O4, etc. followed by calcination at 850-900°C [30-31]. LiCoO2 is formed via an intermediate material Co3O4. Alternatively, various synthesis methods such as combustion synthesis [32-33], a sol-gel technique [34-35], molten salt synthesis [36], complex formation method [37], co-precipitation method [38], hydrothermal synthesis [39], mechano-chemical, and microwave synthesis are reported in the literature to synthesized LCO [40]. Nanocrystalline LCO synthesized by a surfactant-assisted modified sol-gel method (50-100 nm size) could deliver an initial discharge capacity of 150

14

Udita Bhattacharjee, Madhushri Bhar, Sourav Ghosh et al.

mAh g-1 with good cycling capacity retention. The disadvantage of nanosized LCO is the tendency of agglomeration that inhibits the proper mixing of binder and conductive additive to the active material [31]. Conductive carbon coating enhances the electrochemical performance by increasing electronic conductivity and suppressing the dissolution of transition metal. Thin layer plate-shaped graphite-LCO composite prepared by ball-milling delivers specific capacities of 230 and 200 mAh g-1 at C/10 and C/5, respectively [41]. The thermal stability of LCO is found to be poor. It is reported in the literature that LCO based battery could catch fire >200°C due to the exothermic reaction between organic electrolytes and released oxygen. It was the main reason for calling off all batteries from Boeing airlines in 2003 [42]. The thermal runaway of LCO can be diminished by coating with several materials such as FePO4, Al2O3, ZrO2, B2O3, etc. [43-46]. It increases mechanical and chemical stability in LCO by decreasing the side reactions and improving interfacial stability. Al2O3 coated layered oxide cathode prepared by hydrothermal method delivers a discharge capacity of 154 mAh g-1 and 80% capacity retains after 50 cycles [47]. Uniform AlPO4 coated LCO shows superior performance compared to pristine metal oxide coating due to a strong P=O bond that is resistant to chemical attack. Further, it decreases the irreversible cation exchange of Li and Co in the octahedral layers, resulting in a discharge capacity of 150 mAh g-1 at 1 C rate with 99% capacity retention after 20 cycles [48]. Besides, cationic doping such as Cr, Mo [49], B [50], and Ti [51] have also been employed to improve phase purity with high crystallinity. Doped LCO materials exhibit better electrochemical performance compare to bare LCO with good cycling stability, low irreversible capacity loss in the 1st cycle, and improve Coulombic efficiency. LCO batteries are commercially used in cell phones, laptops, computers, tablets, cameras, etc. However, limited availability of cobalt resources and its high-cost limits large-scale applications like EVs, HEVs. Even though LCO is used mostly till today since from its discovery, research is still going on development of newer cathode material of low

Lithium-Ion Batteries - Fundamental to Applications

15

cost, reduced cobalt content, highly safe with good electrochemical performance.

Lithium Nickel Oxide (LiNiO2) Lithium Nickel Oxide (LNO) is isostructural to LCO. LNO is comparatively cheaper and eco-friendly than cobalt-based materials with its theoretical specific capacity of 275 mAh g-1 [52]. Even though practically LNO could deliver 20-30% more reversible capacity than LCO by participating 70% of lithium from the parent LiNiO2 in electrochemical cell reaction during the charge-discharge process. The challenge lies in difficulty to synthesize layered structured LNO in the laboratory as Ni 2+ to Ni3+ conversions is not feasible. The actual structure of LNO seems to be Li deficient, i.e., Li1-yNi1+yO2 as Ni2+ is found in both the Li layer and NiO2 layer together (cation mixing). Irreversible capacity loss and poor cycling stability arise due to hindrance in Li intercalation during cycling. Li/Ni disorders in transition metal layers lower the electrochemical activity and degrade battery performance. LNO synthesized by heating the mixture of LiOH.H2O and Ni(OH)2 at 700°C in air, delivers a discharge capacity of 200 mAh g-1 in 3-4.3V for the structural transformation of Li1-xNiO2, 0.15250 mAh g-1 in the wide voltage range of 2.5 – 4.8 V with the energy density of ~1000 Wh kg-1. It faces several challenges that limit its high energy density application. Above 4.4 V, Li2MnO3 is activated with the release of oxygen as Li2O, forms MnO2, and resulting in a mostly irreversible capacity loss in the first cycle. Additionally, vacancies created in the crystal cause

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structural non-stoichiometry. To mitigate the stability, Ni migrates from the transition metal layer to the lithium layer, and the layered structure changes to spinel structure that results in voltage decay to below 3V [87]. Besides, the electrolyte gets decompose on the cathode surface due to high operational voltage reduces interfacial stability. The chemical composition of the surface film was analyzed by electrochemical impedance, X-ray Photoelectron, and micro-Raman spectroscopies. After prolonged cycling, alkyl carbonate-based electrolytes were reduced to ROCO2Li, (ROCO2)yM, ROLi, (RO)xM and LixPFy, LixPOyFz surface species. This passivation layer on the cathode surface increases the internal cell impedance leading to cell death [88]. Further, the electronic and ionic conductivity of LMRNMC is less in comparison to NMC. The electronic conductivity of the material can be increased by introducing carbon additives such as graphenes, graphitic carbon nanofibers (CNF)/ nanotubes, etc. 1.5 wt. % of highly graphitic CNF to the electrode composition improves the reversible capacity from 250 mAh g1 (without CNF additive) to 280 mAh g-1 with good cycling stability over 200 cycles [87]. Further, metal oxide coating such as ZrO2, MgO, Al2O3, Co3(PO4)2 can enhance the interfacial stability [89-93]. Al2O3 coated Li[Li0.05Ni0.4Co0.15Mn0.4]O2 delivers the capacity of 175 mAh g-1 at 30 mA g-1 with the good electrochemical performance [93]. In another report, LiPON coated Li-rich NMC, i.e., Li1.2Mn0.525Ni0.175Co0.1O2 was processed by RF-magnetron sputtering method. It improves cycling performance at room temperature and 60oC during high voltage cycling to 4.9 V as the LiPON layer (1–2 nm) provides interfacial stability. LiPON is electrically insulating solid electrolyte with Li-ion conductivity of 10-6 S cm-1, stable till 5.5 V, hence facilitates high voltage cycling of LMR-NMC. It delivers reversible capacities of >275 mAh g-1 for more than 300 cycles. The rate performance improves to 4-5 fold in LiPON coated electrodes compared to the conventional electrode [94]. Still, research is going on this attractive cathode material to boost up its electrochemical performance towards its commercial application in high energy density. Neither these surface coatings nor electronic conductivity helps to reduce the structural transition associate with the material. The structural transition from layered to the

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spinel structure reduces energy density from 1000 Wh kg-1 during the initial cycle to 700 Wh kg-1 during the 200th cycle, respectively.

Figure 7. (a) Discharge profile of LMR NMC and F-LMR NMC; Capacity vs cycle number of pristine LMR-NMC, F-LMR-NMC at C/10 and C/5 rate (as indicated) (b) Al-foil current collector, and (c) on carbon fibre current collector; (d) C rate performance of pristine and F doped LMR NMC on CF. Reproduced with permission from [95].

Cation doping such as Fe, Mg, Cr, etc. or anion doping such as Fluorine or even simultaneous cation and anion dopings suppress the layered to spinel transformation and improve the energy loss [95-99]. The synergistic effect of both magnesium (0.02 mole %) and fluorine (1:50 wt. %- LiF) doping in LMR-NMC show excellent electrochemical performance with stable capacity retention and minimized voltage decay, delivers capacity ~300 mAh g-1 at C/20 rate, and pristine LMR-NMC shows the initial capacity around 250 mAh g-1 in the voltage range between 2.5 and 4.7 V. [99]. Ni2+ is partially substituted with Mg2+ as they are of the same ionic radii (0.69Å for Ni2+ and 0.72 Å for Mg2+). Mg2+ does not participate in the redox process and maintains the interlayer spacing during repetitive Li+ de/intercalation and fluorine improves the interfacial stability

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by partially replacing M-O bonds with M-F bonds [99]. Furthermore, aluminum foil current collector was replaced by 3D carbon fiber to improve the electronic conductivity and complete utilization of the active material. The 3D electrode architecture of fluorine-doped LMR-NMC shows a high capacity of >200 mAh g-1 at 1C rate, stable cycling capacity retention over 200 cycles, and ~300 mAh g-1 at C/10 rate (10-20% greater than the conventional LMR-NMC electrodes), as shown in Figure 7 [95].

Li-V-O Layered Cathodes This class of materials consists of LiVO3, LiV2O5, VO2, V2O5, V6O13, and Li1+xV3O8, etc., which could deliver a discharge capacity up to 400 mAh g-1. Vanadium exists in several stable oxidation states such as V5+, V4+, V3+, and forms close-packed oxygen distribution [100-101]. The conventional cathode materials used are orthorhombic V2O5 [102-105] and monoclinic LiV3O8 [106-110]. Though they have a high capacity (~ 400 mAh g-1), they have low nominal voltage ≤3 V. But severe capacity degradation is observed due to a decrease in Li-ion diffusivity during Li+ extraction and migration of vanadium ions.

Three-Dimensional LixMn2O4 Spinel LixMn2O4 is one of the most established cathode material because of its lower cost, toxicity, high natural abundance of ‘Mn’, and higher thermal stability concerning LiCoO2 [111]. This compound forms a spinel structure, and the anion lattice has α-NaFeO2 type structure in which lithium and manganese occupy tetrahedral and octahedral sites, respectively. The stable 3D crystal geometry helps to diffuse Li+ easily and offer high rate capability by providing a well-connected framework during the insertion and extraction process. The maximum lithium extraction from the spinel is 0.6 (Li1-xMn2O4, 0≤x≤0.6) with a theoretical capacity of 148 mAh g-1 [112]. In LixMn2O4 when 0≤x≤1, discharge occurs at 4V and it is

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structurally stable on Li-ion insertion and deinsertion. But when 1≤x≤2, discharge happens at 3V, and the average oxidation state of Mn falls below 3.5 V that leads to Jahn Teller distortion and structural destabilization [113-114]. Mn3+ (when x=1 in LixMn2O4) is having d4 electronic configuration and degeneracy of electronic states is disturbed. Structural stabilization occurs by elongation of MnO6 symmetry from cubic to tetragonal symmetry. Higher synthesis temperature improves capacity in the 4 V region and lower synthesis temperature at the 3 V region [115]. The degradation in electrochemical behavior of LixMn2O4 cathode is due to (a) instability of electrolyte at high voltage operation, (b) Structural phase transition by Jahn Teller distortion in LixMn2O4 when 0≤x≤1, (c) On fully discharged state, i.e., below 3V, the following disproportion reaction takes place: LiMn2O4 → LiMnO3 + MnO, i.e., Mn3+ disproportionate to Mn4+ and Mn2+. Mn2+ underwent dissolution from the cathode-electrolyte interface and deposited on the anode surface. Carbonate electrolytes containing fluorinated salts generate HF on trace amount of moisture which initiates Mn dissolution (d) At fully charged state, λ-MnO2 react with electrolyte decomposed products and forms a passivation layer of side products such as MnF2, LiF, Li0.5MnO2, etc. [113, 116-117]. It increases internal cell impedance and degrades the electrochemical cell performance [118-119]. The weight loss of the spinel in LiPF6 based electrolyte in a discharged condition is 1.1% at 80°C in 2 days due to Mn dissolution [120]. The average oxidation state of Mn can be maintained above 3.5 by [113, 120-129] a) Substituting manganese with multi-valent metal cation like LixMyMn2-yO4 (M = Ti, Ge, Fe, Co, Zn, Ni, Mg, Zn), e.g., In LiMg0.0125Mn1.975O4, Mn valency is 3.54. b) Substituting manganese with lithium to form Li-rich spinel, e.g., Li1+xMn2O4, Mny+: y>3.5. c) Synthesizing cation deficient spinel e.g., Lil-xMn2-2xO4, when x=0.025, Mny+: y=3.6.

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Figure 8. (a)Charge-Discharge profile of LiMn2O4 spinel cathodes; (b) corresponding cycling stability. BLMO and EGLMO stand for bare LiMn2O4 and epitaxially grown layer coated LiMn2O4, respectively. Reproduced with permission from [130].

The theoretical capacity of Li1+xMn2O4 will be increased on extra lithiation as more number of charge carrier (Li+) will be participating in electrochemical cell reaction. Excess lithium or replacement of Mn by foreign ions increases average Mn valency, suppress Jahn Teller effect. Among them, newly developed spinel LiMn1.5Ni0.5O4 has attained great importance due to its high reversible capacity of 148 mAh g-1 at high voltage ~4.7 V vs Li/Li+ resulting high energy density. The average oxidation state of Mn is ~4, which reduces structural deformation and exhibits improved electrochemical behavior than LiMn2O4 [122, 126, 128]. Sub-nanometer coatings of amorphous thin-film electrolyte (LiPON) improve the cycling stability of LiMn1.5Ni0.5O4 spinel at both room temperature and 60°C when charged to high voltage ~4.9 V with a standard LiPF6 carbonate electrolyte. LiPON acts as an impurity scavenger and blocks active sites to decrease electrolyte decomposition [131]. But the main problem in capacity degradation is due to the formation of LixNi1-xO impurity. To minimize the impurity phase formation, double doping is done, such as LiMn1.42Ni0.42Co0.16O4, which increases structural stability and enhance capacity retention during charge-discharge cycling [132]. Doped spinels like LiM0.5Mn1.5O4 (M = Cr, Ni, Cu, Co, Fe) [120-129], and initial capacities of 120-125 mAh g-1 is observed for the Fe- and Nisubstituted spinels [124]. Ni-substituted spinel provides most of its capacity at a voltage of 4.5 V.

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Polyanionic Type Cathodes One-Dimensional Olivine LiMPO4 (M = Fe, Mn, Ni, Co, theoretical capacity ~ 170 mAh g-1) type olivines are the emerging promising cathode materials for LIBs with high structural and thermal stability, good abuse tolerance, flat voltage plateau, low cost and environmentally benign. In LiMPO4, the tetrahedral unit of phosphate anion (PO4)3- separates two corner-sharing distinct octahedra of metal oxide (MO6) and lithium oxide (LiO6) and the overall lattice structure is of rhombohedral type with a space group of Pnma [133]. Li-ion diffusion happens in two neighboring octahedra by intermediate tetrahedral along with the [0 1 0] direction. The strong M-P-O covalent bond guarantees safe operation at high temperatures resulting from short circuit or even overcharges when it is misused. Among all lithium phospho-olivines, LiFePO4 has received much attention [133]. LiFePO4 can be synthesized by hydrothermal [134], sol-gel [135], co-precipitation [136], microwave [137], solid-state reaction [138] and mechanical activation [139]. It is commercially used in batteries for power tools, small vehicles, and PHEVs. LiFePO4 forms isostructural FePO4 on delithiation by oxidizing Fe2+ to Fe3+ [140]. The active material undergoes little structural changes in cycling and has excellent cycling performance with good capacity retention. Volume decreases by 6.81% and density increases by 2.59% during lithium-ion deintercalation. Fe ion can occupy Li sites to neutralize the charge by creating lithium deficiency [141-143]. It has a flat discharge profile at ~3.5V vs Li, and the two-phase electrochemical process is involved. Olivine structure is less dense compared to spinel or layered cathodes leading to lower volumetric energy density. The theoretical density of LiFePO4 is 3.6 g cm-3, which is much lower compared to other materials like LiCoO2 (5.1 g cm-3) [19]. However, low energy density due to low working voltage, poor electronic conductivity (10-9 S cm-1), and Li+ diffusion (10-11–10-13 cm-2 s-1) limit its high-energy applications such as those directed to EVs.

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Figure 9. Voltage profiles of the LFP composite electrodes measured with (a) carbon fibre, (b) Al current collector galvanostatically at various discharge rates between 4.0 and 2.0 V vs Li/Li+; C-rate performance of the LFP composite electrodes measured with (c) carbon fibre, (d) Al current collector 4.0 and 2.0 V. Reproduced with permission from [152].

The electronic and ionic conductivity can be improved by carbon coating, reducing particle size to the nanometer level, substitution or doping, etc. 3-5% carbon coating is generally done which enhances the conductivity as well as maintains the balance between gravimetric and volumetric energy density. Nazar et al. synthesized LiFePO4/C nanocomposite by the sol-gel method, which delivers 90% and 70% of theoretical capacity at C/2 and 5C rate respectively [144]. But, Porous structure coating increases the gap among primary particles results in low tap density. Research is also focused on increasing tap density to 1.50 g cm-3 by modifying the synthesis method via a combination of carbothermal reduction and molten salt methods, increasing the secondary particle size and it delivers a discharge capacity of 141 mAh g-1 at a C/5 rate [145]. It shows a discharge capacity of 110 mAh g-1 at the end of the 800th cycle at 5C [144]. The researchers of NTT and SONY discovered that on

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decreasing the synthesis temperature, the particle size also decreases (ranging from ~0.2-30 µm) with an increase in surface area (~10 m2 g-1). They observed that a material synthesized at 550 °C delivers 160 mAh g-1 capacities with good cycling stability [146-147]. Elemental doping in Liand Fe- sites by K, Al, Na with small ionic radii also improve intrinsic electronic conductivity and lithium-ion diffusion [148-150]. Solid-solution doping by metals such as Mg, Al, Zr, Nb, Ti, W supervalent to Li+ with controlled cation non-stoichiometry, increases the electronic conductivity of LiFePO4 by a factor of ~108 resulting near-theoretical energy density at low charge/discharge rates [151]. Martha et. al. prepared LiFePO4 cathode with highly conductive carbon fibers of 10–20 µm in diameter as a current collector and compared the electrochemical performance with convention Al-foil electrode (Figure 9). The carbon fiber composite cathodes have a much longer cycle life, higher thermal stability, and high capacity utilization at rates to 6C [152]. LiMnPO4 is structurally very similar to LiFePO4. It is having comparatively high operating voltage ~4.1V and the potential working window lies within the stability region of common non-aqueous electrolyte. But it exhibits poor electrochemical behavior due to low electronic conductivity (250 mAh g-1 in the wide voltage range of 2.5 – 4.8 V with an energy density of 1000 Wh kg-1. Moreover, a LiMn2O4 spinel-type cathode offers a 3D networkconducting channel of Li+ kinetics that enhances the electrochemical performance. The higher working potential >4V requires a stable high voltage electrolyte for spinel LiMn2O4 cathode. Typically, all Li-Mn based cathodes face the common problem of Mn dissolution to the electrolyte resulting in structural non-stoichiometry. Phospho-olivines i.e., LiFePO4, LiMnPO4, LiNiPO4, LiCoPO4 have the highest structural stability, good abuse tolerance, flat voltage plateau voltage, and high rate capability. LiFePO4 (3.3 V) is one of the robust cathode material ever developed for LIBs, but the low working voltage limits its high energy density applications such as EVs.

Safety Aspects of Layered Oxides vs. Olivines (LiCoO2 vs LiFePO4) LIBs can ignite or explode when exposed to a high-temperature environment due to short circuit or even overcharge. LiFePO4 is a comparatively safer cathode material than layered and spinel-type cathodes. The comparisons based on their energy density are shown in Figure 10. i.

ii.

iii.

Fe-P-O bond is much stronger than the Co-O bond, so the removal of oxygen atoms is much harder when it is mishandled, i.e., shortcircuited or overheated. The lithiated and delithiated states of LiFePO4 are iso-structural, but during delithiation of LiCoO2, CoO2 undergoes non-linear expansion which leads to structural instability. No lithium remains in fully charged LiFePO4 cathode whereas ~50% Li remains in LiCoO2. LiFePO4 is highly resilient during oxygen loss which results in an exothermic reaction in LiCoO2

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based lithium cells. Thus, LiFePO4 is structurally more stable cathode material than LiCoO2. Fluorosulfate and fluorophosphate based tavorites are highly ionic/electronic conductive. Conversion type cathodes mitigate the criteria of high energy density application. Li excess disordered rock salt cathode is a combination of high voltage operation and high valence charge compensator redox-active transition metals and partial substitution of oxygen by fluorine facilitate Li+ diffusion with minimum oxygen loss from the parent compound during cycling. Currently, NMC and LFP are dominating in the market owing to low-cost, safety, and long cycle life. Worldwide research and development are directly focused on future generation cathodes replacing LiCoO2 with an alternative material of low cost, high-capacity, high-energy-density as well as high-power density with a safer long-life affordable system.

ANODE MATERIALS Anodes also are known as negative electrodes are the electrodes that undergo oxidation in an electrochemical cell during the spontaneous process of discharge. The performance parameters of a battery largely depend on the characteristic behavior of its anode materials. The basic characteristics required for a sustainable anode of an electrochemical cell include high reducing character, high conductivity, high specific capacity, the stability of electrode-electrolyte interface, maximum active mass utilization for the electrode, ease of availability of material, low cost and environ benign, etc. [78, 195-197].

Features of Anodes for Lithium-Ion Batteries The anode used for the first lithium rechargeable battery was pristine lithium metal due to its very high theoretical capacity (~3.86 Ah g-1) and

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also high reducing power because of extremely low reduction potential (3.04 V vs. S.H.E). Though lithium metal satisfied the two very important criteria of high reducing power and high theoretical capacity it suffered various other practical disadvantages of volume change (pulverization), explosivity (as lithium dendrites formed during cycling are very reactive), etc. [78]. During the development phase of these batteries, the cathode used was an intercalation type material (metal oxides); thus, the idea of an intercalation type anode also catered to the interest of researchers. Intercalation type carbon anodes came into the scenario at that time as the formation of those intercalation compounds was reversible electrochemically as suggested by researchers studying graphite intercalations [16]. The redox potential for the formation of these compounds was also very low, almost nearing the values for the pristine lithium metal anode. The problem of volume change was not prevalent in carbon materials, and also carbon compounds are eco-friendly and costeffective [195]. The only disadvantage in the case of these intercalation type carbon materials is the low theoretical capacity. For example, graphite shows a theoretical capacity of 372 mAh g-1 for the formation of LiC6, which is almost just 10% of the theoretical capacity offered by pristine lithium metal. But looking upon the longevity and electrochemical reversibility of these Li-carbon compounds, commercial batteries were introduced with these carbon materials as active anode material. They were advancing along the way various other intercalations, conversion, and an alloy containing reversible Li-ion have been utilized for its ability of functioning as an anode. Thus, the features that are prioritized while choosing anode materials for LIBs are as discussed below [78, 195-197]. a) The high theoretical capacity of the compound: The active anode material should possess an inherent high specific capacity. b) Low reduction half-cell potential: High reducing power of an electrode signifies that the redox potential of the electrode should be as low as possible such that the cell voltage is high when assembled with the highly oxidizing cathode. This will enhance energy density as well as power density as they depend on both

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specific capacity and voltage. Lithium is one of the strongest reducing agents with a standard potential of -3.04 V vs SHE has always been a center of interest for the researchers as the anode since the 1970s. c) The conductivity of the compound: The active electrode material should be highly conducting in nature. So that the charge acceptance is higher and the process of charging and discharging is more feasible which ensures higher reversibility for chargedischarge cycling. d) Minimized secondary reactions: Lesser the number of secondary reactions, more amount of the energy consumed by the system is used up for the redox reactions and thus, the energy loss is minimal as most of the electrochemical energy is convertible.. The reduced secondary reactions increase the shelf life of the batteries.

Figure 12. Comparison of different kinds of anodes reported based on capacity and Liion insertion potential. Reproduced with permission from [198].

e) High active mass utilization: To ensure optimum utilization of active mass, the contact between the current collector and the active material should be maintained properly so that the charge

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Udita Bhattacharjee, Madhushri Bhar, Sourav Ghosh et al. acceptance for the electrochemical reaction is higher. Thus, the maximum amount of active material gets involved in the reaction, and the theoretical capacity becomes more achievable practically, and thus, more energy outcomes can be expected from applicative devices. f) Considering the criteria that are needed to be satisfied by any compound to act as an active anode material, anodes are mainly divided into three categories based on the mechanism of lithiation and delithiation, as shown in Figure 12. They are (i) Intercalation type, (ii) Conversion type, and (iii) composite alloy type anodes are enumerated above.

Intercalation Type Anodes These materials were the earliest type of anodes reported as a replacement for pristine lithium metal anodes. During the 1980s, the metal intercalation compounds of carbon, such as graphite were studied widely. The intercalation compound formed by the reaction of lithium with graphite (LiC6) and the electrochemical reversibility of the process was the source of inspiration for finding the utility of graphite as the anode of LIBs [16, 78]. The mechanism of lithium insertion-deinsertion followed in these anodes is such that the skeleton structure of the host matrix of the material is least disturbed while lithium-ion is inserted or removed from the matrix (Figure 13). The matrix behaves as if with lithium mobility to and fro the matrix, the neighboring chemical environment is not disturbed, and hence, the stabilization energy of the host matrix is not affected [196]. The two types of insertion type anodes reported primarily are carbon compounds that allow Li-ion intercalation and metal oxides with a lower redox potential of Li insertion de-insertion.

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Figure 13. Schematic representation of lithiation de-lithiation in intercalation type anodes.

The carbon compounds with intercalation possibilities had all the desired qualities required for a satisfactorily functional anode like low redox potential, highly reversible lithiation-delithiation process, structural stability of the host matrix for long cyclability and inherent specific capacity. Carbons are lightweight material, easily available, less expensive, and hence, have considerable research interest [199]. Another important feature of the carbonaceous electrode is the formation of a solid electrolyte interface as their lithiation potential versus lithium is very low. The lithium reacts with carbonate-based electrolytes usually at a voltage below 1V vs Li to form a layer (SEI) which acts as a permeable layer for Li+ cations and regulates the intercalation-deintercalation process of lithium ions (Figure 19). This layer comprises of compounds like Li2CO3, Li2(CH=CH), and thickness is not supposed to exceed a few 10s of nanometers; otherwise, the layer becomes a hindrance to the passage of Lithium ions [200]. This layer further protects the active carbon material from rapid decomposition as it acts as a barrier between the electrolyte and the electrode interface. The SEI formation and its characteristics required for the optimum cycling performance of LIBs are discussed in the latter part of this section. For example, graphite which is sp2 hybridized carbon sheets stacked one above another forms LiC6 (an intercalation compound of Li encapsulated by six carbon atoms from the graphite matrix) at a potential of ~0.1 V. The charge-discharge curve of graphite (Figure 14a) depicts Li+ intercalation into graphite layers at low voltage region (0.4-0.01V) with the stepwise formation of LiC36→LiC12→LiC6. The cyclic voltammetry curve is shown in Figure 14b further confirms the corresponding intercalation peaks LiC12 and LiC6 at 0.12 V and 0.08 V respectively. The broad reduction peak ~0.8 V appears due to the formation of SEI in the first cycle. The layered

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structure of graphite is not disturbed in the process (~16% stress) and also graphite is available throughout the world almost uniformly.

Figure 14. (a) Charge-discharge profile of graphite anode and the corresponding (b) CV curves.

Since, the introduction of carbon material as anode for lithium-ion batteries commercially by Sony in 1991, a new field of research on carbonaceous materials and their other suitable alternatives emerged successfully. The carbonaceous materials which are reported as anode materials include graphitic carbons, non-graphitic soft carbon (calcined at very high temperature till 3000°C), hard carbons (disordered structure formed by calcination at temperatures below 1000oC), graphene sheets, carbon nanotube, fullerenes, etc. [201]. The capacity in graphite is contributed by the formation of LiC6 compound whereas the capacity delivered by hard carbons is attributed to the voids and defects present in the crystalline structure and a stable reversible capacity ≥350 mAh g-1 is reported for the hard carbons synthesized from various sources [202-204]. The main advantages of using hard carbons are higher specific capacity, higher rate capability, and low production cost of active material, but the irreversible capacity is very high [202-203]. Hard carbon usually is prepared from inexpensive materials, including bio-wastes. Hard carbon prepared from coal tar delivers an initial reversible capacity of 576 mAh/g at 0.1C rate [204] and that derived from orange peel delivered a capacity of 301 mAh/g after 100 cycles at 1C rate [205]. Graphite on oxidation forms graphene oxide, which results in the formation of micropores as compared

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to graphite and hence results in a considerable increase of capacity. Reduced graphene oxide has been reported to deliver a capacity of 561 mAh g-1 at a current density of 100 mAg-1 [206]. Exfoliated graphite sheets using methods like bulky ion interaction were also reported as anodes with improved electrochemical capacity. Graphene sheets being loosely spaced and non-bonded unlike graphite were analyzed to accommodate more than one lithium-ion per one six-membered ring. Graphene nanosheets prepared from artificial graphite delivered an initial reversible capacity of 672 mAh g-1 [207]. Various structural and morphological modifications of graphene sheets were tested as anode for LIBs. Fullerenes, single-walled carbon nanotubes, multi-walled carbon nanotubes, carbon nanospheres, etc. were reported because of enhanced porosity in the hollow nanostructures resulting in an enhanced capacity of the electrochemical reaction [199]. Among the fullerenes, C60 was found to be capable of accommodating 1 Li per 5 C atoms [208] whereas hydrogenated C70 delivered a higher capacity of >1000 mAh g-1 and an increase in the capacity was observed with increase the amount of hydrogenation [209-210]. The utility of fullerene in LIBs was mostly explored in a composite form with other anode materials like Si, metal oxides, etc. [199]. Carbon nanotube was extensively studied as anode both in pristine form and composite form. MWCNTs were found to deliver better performance in terms of rate capability, cyclability, high rate cycling, etc compared to SWCNTs owing to the metallic character of the MWCNTs and semi-conducting nature of the SWCNTs [211]. MWCNTs were found to deliver capacities in the range of 350-780 mAh g1 with considerably high irreversible capacities [212-214]. Heteroatom doped graphene sheets like boron, nitrogen, sulfur, phosphorous doped sheets were used as anode because the electronic conductivity in the matrix is improved with the doping of the electronically unbalanced atoms and also the electronically charged atoms help in keeping away the graphene sheets from adhering or agglomerating together. They are known to facilitate faster kinetics at higher current rates. Chemically and thermally prepared B-doped graphene and N-doped graphene synthesized from graphite flakes using a top-down method have been reported to deliver capacities of 235 mAh g-1 and 199 mAh g-1 respectively at a current

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density of 25 Ag-1 [215]. But these carbonaceous compounds have a very high and functionalized surface areas which results in a very high initial capacity but a very high irreversible loss in capacity is observed due to high degree of surface reactions and hence this issue limits their applicability in commercial anodes as more dead inactive mass will be created at the anode after initial cycling of LIBs leading to sacrifice in the energy density of the battery. Thus, graphite still stands as the choice of anode for commercial LIBs for various applications. Apart from intercalation type carbonaceous materials, intercalation type metal oxides were reported. The Li-ion intercalation type metal oxide with low reduction half-cell potential and little structural changes during the process were reported. In these materials, the lithium either occupies the sites between the layers in the host matrix or is inserted into the voids of the 3D networks with minimum effect in the structural skeleton of the matrix. For example, LTO, Lithium titanate (Li4Ti5O12) has a redox potential of 1.5V for the lithiation reaction, and also lithium-ion gets inserted into the empty octahedral voids in the matrix in such a manner that the structural stability is not compromised [216]. Though the redox potential is higher compared to the carbon intercalation compounds, the feasibility of intercalation and low structural deformation of the host matrix became the reason for finding its utility as the anode of LIBs. The disadvantages of this type of anode are the higher lithium insertion potential and lower conductivity compared to carbonaceous compounds. The conventional intercalation type transition metal oxide framework is lithium titanate (Li4Ti5O12) which delivers a capacity of around 150 mAh g1 (theoretical capacity = 175 mAh g-1) [217-218] and cycles with minimum structural stress but the electrical conductivity of the matrix is very low (~10-13 S cm-1) [216, 219]. Various attempts were made towards improving the conductivity of this matrix. The approaches which attracted the attention of the researchers were doping other metals in the metal sites, composite formation with highly conductive compounds, and the nanostructuring of the compound into various conducting and porous morphologies. The composites of LTO with carbonaceous compounds like CNTs were widely studied, and an LTO/CNT composite anode was found

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to deliver a capacity of 135 mAh g-1 even at a high current rate of 10C [220-221]. A composite of LTO with conducting Zn layers delivered an initial discharge capacity of 183 mAh g-1 at a current density of 0.2 Ag-1 [222]. Doping titanium sites with aliovalent metal cations like Mg2+, Sn2+, V5+, Nb5+, Ta5+, etc. have been reported to increase the conductivity of the spinel matrix [223]. Nano-structuring of LTO can be done into various morphologies like nanospheres, nanowires, nanocubes. Nano spherical LTO anode delivered a capacity of 163 mAh g-1 at 10C [224], and mesoporous LTO gave a capacity of 175 mAh g-1 at 10C current rate [225]. By using LTO anode – LiMnPO4 cathode demonstrated as a suitable LIB system for load leveling applications having cell voltage on 2.5 V and energy density of > 100 Wh kg-1 [226]. Similarly, metal oxide like TiO2 in an anatase phase was reported for this intercalation type electrode, but the insertion potential is quite higher. Micro-sized TiO2 is reported to deliver an initial discharge capacity of around 150 mAh g-1 and TiO2 anatase nanotubes were found to deliver an initial reversible discharge capacity of 239 mAh g-1 at 36 mAg-1 current density, but the lithium insertion potential is >1.7V [227]. Composites of TiO2 with nano carbons have been identified to further improve the performance. The layered vanadium oxides like VO2 [228], V3O5, V2O5 [229-230] were reported to deliver capacity following mechanism similar to LTO. Though the structures suffer an almost negligible change in volume and can be cycled for thousands of cycles, the higher insertion potential limits their performance as the anode because the nominal voltage of the cell drops and the energy parameter of the cell becomes restricted. Another compound Li3VO4 delivered a capacity of around 310 mAh g-1 through intercalation and deintercalation of lithium ions in the range of 0.2 – 3 V [231]. Various modifications of this vanadium oxide by inserting metals like Cu (LiCuVO4, Cu3V2O8) into the skeleton to improve the conductivity and hence the capacity [232].

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Conversion Type Anodes This type of anode derives the capacity of lithium insertion from the chemical conversion of the host material to other compounds by reacting with lithium metal during the lithiation process (Figure 15). Commonly used conversion type anodes are the transition metal oxides, sulfides, and phosphides [233]. The compound formed after reacting with lithium on insertion is reduced metal oxide or an alloy of the metal with lithium encapsulated by a matrix of LinX [234-235]. A dependable contact between the encapsulated reduced metal and the LinX matrix formed was necessary to ensure the reversibility of the redox process. The intimate contact will result in the availability of oxygen from LinX for the oxidation of the transition metal (oxygen recovery process) while de-lithiation is taking place from the host matrix. The capacity deliverable through these types of electrodes reaction is much higher as compared to the intercalation type electrode, but the disadvantages of volume change and hence lesser cyclability is prominent. The reaction potential for this type of conversion lies in the range of 0.5-1V [235]. The conversion type of electrodes may be further classified into pure conversion type electrode (e.g., oxides of Fe, Co, etc.) and the conversion-alloying type where the metal undergoes after the conversion reaction takes place (e.g., oxides of Sn, Sb, Zn, etc.). The conversion-alloying type anode delivers more capacity compared to the pure conversion type [236]. One of the first transition metal oxide used for this purpose was α-Fe2O3.

Figure 15. Schematic representation of lithiation de-lithiation in conversion type anodes.

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As mentioned earlier, one of the traditionally used metal oxides for this kind of anode is the α-Fe2O3 which has a theoretical capacity of 1006 mAh g-1 which is much higher than intercalation type carbonaceous as well as metal oxide electrodes. But these electrodes are subjected to a very high volume change (~96%) and also the insertion potential of Li is higher. Some other oxides like Fe3O4, Co3O4, -MnO2, nickel oxides behave similarly [233]. Nanostructuring of the active electrode materials and composite formation with carbon and other metal oxides are the strategies through which the issue of volume change was resolved to a considerable extent [233, 237-239]. Nanostructure mixed transition metal oxides have also garnered interest from the researchers [233, 237]. This composite formation enhances the structural stability and strength of the host skeleton and also, the insertion potential is decreased as an effect of the other components of the composite. Hence, the cycle life and nominal voltage can be enhanced, and the energy performance of the cell can be improved. Nanorods of -Fe2O3 delivered a stable capacity of 908 mAh g-1 at 0.2C rate till 100 cycles with high capacity retention [238] whereas composite electrode of Fe3O4-C nano spindles delivered a stable capacity of ~745 mAh g-1 at 0.2C rate with stable SEI formation [239]. Another composite electrode reported is RGO/Fe2O3 composite, which delivers a stable discharge capacity of 982 mAh g-1 till 30 cycles [240]. Also, -MnO2 nanorods synthesized by one-step microwave-assisted solvothermal method delivered a capacity of 1000 mAh g-1 after 200 cycles after delivering a minimum capacity of 550 mAh g-1 in the 50th cycle due to the formation of a gel-like structure after the destruction of MnO2 matrix during the conversion reaction taking place [241]. The increase in capacity is attributed to the increase in pseudocapacitive contribution to the overall charge storage from 31% to 75% during 50th to 1000th cycles, respectively. Various nitrides and phosphides are also used as conversion type anode, but cycling stability is very low. Nitrides like Li7MnN4 and Li3FeN2 show electrochemical behavior toward lithium insertion at around 1.2 V show reversible capacity in the range of 300 -350 mAh g-1 [242-243]. Some other 1st-row transition metal base nitrides having layered and antifluorite structures were tested, but the disadvantages with this type of electrode are

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the amorphization of the structure while cycling and also, nitrides are highly hygroscopic. On the other hand, the formation of the SEI layer and cycling stability limit the usage of phosphides. An example of conversionalloying metal oxide is reported to be SnO2 which possesses a theoretical capacity of 1494 mAh g-1 combing two processes; one being the reduction of tin oxide (irreversible) and the other alloying of tin with lithium but the problem of volume changes (~250%) and pulverization exist in a similar to phophites [244-245]. Similar approaches like nano-structuring and composite formation were the strategies that were followed to mitigate the issues of this type of electrode [246]. Nanorods of SnO2 showed capacity retention of ~300 mAh g-1 after 50 cycles [247]. Many other such structures like thin-film, nanowires, sheets, hollow cages were studied, and improvement in the performance has been reported in a similar manner [247]. Composites of SnO2 were tested in full cell configuration and some of these like SnO2/N, S-doped graphene, [248] SnO2/Fe2O3/C, [249] etc. have been reported to deliver stabilized capacities of 356.4 mAh g-1 (100 cycles), and 412 mAh g-1 (20 cycles), respectively.

Composites and Alloy Type Anodes Alloying is a phenomenon that is widely studied for various applications from the mechanical engineering perspective. It is the process of mixing a metal to one or more other substances (usually metals) to modify their properties. In the case of LIBs, the first studied anode was pristine lithium metal due to its high theoretical capacity. But as these suffered from serious disadvantages of large volume expansion and lithium metal plating on prolonged cycling, alternatives to the use of pristine metal gathered much interest [78]. To achieve the high theoretical capacity of lithium keeping at bay, the disadvantage of Li metal plating, alloying of lithium with other metals was analyzed [7]. Thus, the metals with very low potential of alloying with lithium were tested, and it was observed that the alloys of lithium metal with other metals like Aluminum, Tin, Antimony, etc. All these materials suffered from a similar disadvantage of high

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volume expansion (>200%) in the matrix and consequent pulverization due to constant insertion and removal of lithium from the matrix (Figure 16) [250]. Thus, binary alloys (consisting of two metals) were introduced where one of the metals (usually transition metal, e.g., Iron) forms an encapsulating layer or network around any of the lithium alloying metal elements (e.g., Sn, Sb). The outer metallic network needs to inactive in the process of alloying but needs to be permeable to Li+ cations. Thus, in this case, the inactive metal holds the host structure together and the probability of volume expansion is lessened. The potential of alloying depends on the ratio of the elements mixed and its thermodynamic stability. Another type of alloy matrix which was developed was the active-active matrix in which both the metals involved were active in alloying with the Li (e.g., Sb-Sn) [78]. Another form of alloy used as the anode is the one that undergoes insertion and removal from a metal-metal alloy matrix via a topotactic reaction [251]. Composites of other non-metallic elements were also considered as anode candidates for LIBs such as silicides, nitrides, halides, and phosphides [19, 252]. The element which gathered a lot of attention other than carbon in the later years was silicon as silicon had a high theoretical capacity of 4200 mAh g-1 [253]. But Silicon is poorly conducting in nature as a result of which very little percentage of the calculated gravimetric capacity is achievable. Silicides of many materials including carbon with varying stoichiometry were studied, apart from high volume change in case of composite electrode another disadvantage in the formation of unstable and less conducting SEI formation over negative electrode resulting in hindrance in the ion passage [78].

Figure 16. Schematic representation of lithiation de-lithiation in alloy type anodes.

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When Sn is lithiated till a lithium-rich state of Li17Sn4, it has a theoretical capacity of 960 mAh g-1, and tin powder delivered a capacity of 550 mAh g-1 whereas electrodeposited Sn delivered a capacity of ~940 mAh g-1 which is near to the theoretical capacity, but the cycling stability was still low [254]. Binary alloys of metals like Sn as the active metal which undergoes alloying with lithium and an inactive metal (mostly transition metal) like Fe, Co forms the skeletal framework were investigated as the anode. One of the initially tested binary alloys was SnFe2 which exhibited an initial capacity of 800 mAh g-1 compared to 944 mAh g-1 for Sn as an anode [255]. Though the initial loss in capacity was minimized, the cyclability was still not improved considerably. To improve these performances, composites of SnFe2 and SnFe3C were studied [256]. Similarly, Mo1-xSnx was studied as the anode, and this showed electrochemical stability during cycling [78]. Nano Sn2Fe also reported delivering a capacity of ~450mAhg-1 after 20 cycles [257]. Composite formation of metal with carbon was also employed to improve the cyclability of the alloy anode. Composite of Sn with amorphous carbon was found to deliver a stable capacity of 674 mAh g-1 till 50 cycles [258]. Such compounds with Sb and Co were also analyzed in a similar manner delivering an irreversible capacity of ~400 mAh g-1 after 1st cycle [259]. Apart from this inactive-active matrix composite, active-matrix composites were also studied like Sb-Sn [260], Sb-In [251, 261-263], Sb-Ag [264], etc. Even though this type of matrices has both the elements which can alloy with lithium; still they show lower performance because of lesser reversibility. Intermetallics introduced by Thackeray et al. which undergoes topotactic reaction as a result of lithium insertion were also analyzed as a candidate for the anode. The intermetallic compound Cu6Sn5 undergoes Li insertion at a voltage near 0.4V to undergo the conversion into Li2CuSn type structure which further decomposes to give Li2+xCu1-ySn and finally results in the formation of an alloy with Sn at fully lithiated stated with a capacity of 360 mAhg-1 and 61% volume change in the topotactic reaction. Similar processes are involved for utilizing Cu-Sb intermetallics as anode [78, 254, 263, 265-268]. In addition to the binary alloys, ternary alloys like Sb-Sn-Co were also examined as both Sb-Co and

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Sn-Co served as binary alloy anodes. This ternary alloy showed a better performance initially compared to the binary ones because of more structural stability. Nanostructured array of this ternary alloy showed even better stability of ~ 512.8 mAh g-1 after 150 cycles at 1C rate [269].

Figure 17. (a) SEM image of 3D architecture of Si-C composite; (b) TEM image of corresponding C-coated Si-C composite; (c) cycling stability of Si-C composite fabricated at various temperature; (c) C-rate performance of Si-C composite fabricated at 900oC. Reproduced with permission from [270].

One of the most interesting non-metallic material as a candidate for the anode is silicon as mentioned earlier which has a theoretical capacity of 4200 mAh g-1 owing to the formation of the lithium composite Li4.4Si [253]. But lithium insertion and removal from Si results in a very high volume change almost 400% and the low conductivity results in fading of the electrochemical capacity and decay of the cell gradually. Thus, to achieve the capacity near to pristine Si and overcome the disadvantages of conductivity and structural strength of the host skeleton, various nanostructured morphologies of Si, composites of silicon with carbon from

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various sources in various composition percentages were tested as an anode. The composite thin film of Si with fullerenes delivered a stable capacity of 2800-3000 mAh g-1 till 50 cycles [199]. Also, a composite of SWCNT, graphite, and Si was reported to achieve the capacity of ~900 mAh g-1 [271]. Nanostructured porous Si with SWCNT was found to deliver a stable capacity of ~2220 mAh g-1 with 82% capacity retention till 40 cycles [272]. Even composites of silicon with metals like Al, Mg, Ca, etc. are used to enhance the conductivity, but the cyclability was not improved even then [273]. The in-situ prepared silicon-silica-carbon fiber composites delivered capacities >700 mAh g-1 with coulombic efficiencies >99.5% [274]. One other way of improving the performance of the alloys and composites is by introducing a porous host current collector and electrodepositing or binding the composite over the current collector. As shown in Figure 17, a 3D architecture of Si-C composite in which the Cu foil is replaced by porous carbon fiber delivers capacities of ~1000 mAh g1 at 5C rate till 250 cycles in a half cell assembly (Figure 17 c) [270]. Also, to account for the volume expansion and poor conductivity issues, the usage of nanostructured active material is preferred over the micro-sized ones. The anodes involving composites sized in the nano range are even found to deliver a stable performance until many cycles. Table 3. Comparison between the different types of anodes Anode types Properties Volume change Theoretical capacity Reversibility Conductivity

Intercalation type

Cycle life

Very high

Very Low (~10%) Low High High for carbonaceous, Graphite (~103 Scm-1) Low for metal oxide, LTO (~10-7 Scm-1)

Conversion type High (200%) Very High Low High for alloy (Al~ 105 Scm-1), & Low for nonmetallic composites, e.g., Si (10-2 S cm-1) for the electrochemical reaction of the system. Thus, electrolytes should contain at least one ion common to the ion to be transported between both the electrodes. b) High operating voltage: Electrolytes should be able to operate over a wider range of voltage to ensure higher energy density of the system. The electrolyte should be stable and should not undergo any decomposition during the functioning of the cell. c) Minimum chemical reactivity with the electrode: The electrolyte should not react with the electrode other than the primary electrochemical reaction. The electrolyte should be chemically unreactive towards the electrode either in a free-standing condition or when any voltage is applied. Otherwise, the reversible capacity decreases, and also the shelf life becomes limited. d) Safety: The electrolytes are required to be less flammable, and there should be minimum to no spillage to ensure its applicability in mobile applications. The electrolytes used in the initially assembled LIB was a salt of Li+ cation like LiPF6 dissolved in an organic carbonate-based solvent (DEC) or ethers. The idea of LIBs was conceptualized to overcome the disadvantage of aqueous rechargeable battery, which has a low working potential range (99.98% at 5 V and stable cycling of >90% retention for 10 000 cycles [330]. They are thought to find applications in thin film battery but not in bulk batteries due to low ionic conductivity [331]. Li3N compounds which have a 2D tunnel structure of Li2N hexagonal layers connected by Li forming N-Li-N bridge were also studied as solid-state electrolyte [332]. Although the lithium nitrides prepared at temperatures higher than 750oC are highly conducting in nature (conductivity in the order of 10-4 S cm-1) [333], the nitrides decompose at a low potential and thus could not be used successfully as the solid-state electrolyte. Sulfide type solid electrolytes can be classified as glass, glass-ceramics, and ceramics. The sulfides having the highest utility as solid-state electrolyte include glass/glassceramic Li2S-P2S5 and ceramic thio-LISICON Li4-xGe1-xPxS4 [305, 310]. For a ceramic thio-LISICON (Li4-xGe1-xPxS4), the ionic conductivity increases with an increase in the content of phosphorus [334]. Li10GeP2S12 has a high ionic conductivity but is stable electrochemically until below 5V [335-336]. The ionic conductivity can be further enhanced by two doping mechanisms; interstitial doping and vacancy creating doping. Doping with silicon and chlorine was reported to give Li9.54Si1.74P1.44S11.7Cl0.3 which

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shows one of the highest ionic conductivity reported for this type of electrolytes in LIBs [337]. Glass/glass-ceramic 70Li2S-30P2S5 was reported as sulfide solid-state electrolyte [338]. They have high ionic conductivity but they react with air to produce H2S exists. But 75:25 of Li2S and P2S5 compositions are highly stable and hence, the performance of this type of sulfide compounds as electrolyte largely depends on the compositional stability [339]. Another form of solid state electrolyte reported are the argyrodite type electrolytes which can be represented as Li6PS5X (X=Cl, Br, I). This type of solid electrolyte was first introduced by Deiseroth et al. [340]. In these structures, the six sulfur and halogen forms 136 tetrahedral voids of which 4 are occupied by P atoms and 132 are partially occupied by lithium ions. Among these compounds, Li6PS5Br has a mixture of ordered and disordered arrangement resulting to the highest ionic mobility. Argyrodites have high ionic conductivity depending on the method of synthesis of the compound but are reactive similar to the previously mentioned sulfides which in turn restricts their applicability. Anti-perovskite type of solid electrolyte (e.g., Li3OCl) can be structurally represented as A-B2-X3+ where A is a halogen, B is oxygen and X is Li [341]. The mechanism of conduction is reported to be through a low barrier hoping with an interstitial dumbbell for Li+ diffusion [342]. Li3OCl0.5Br0.5 shows a high ionic conductivity of the order 10-3 S cm-1 and even higher conductivity can be achieved through doping. Due to this highly efficient ionic conduction mechanism, the anti-perovskite type solid electrolytes show a possible scope of application, but precautions are required to be taken for the issues like hygroscopic nature of the compounds [305, 310-311]. The electrolyte still being used in commercial LIBs are the liquid electrolytes due to their easy availability, cost effectiveness ionic conductivity and chemical and electrochemical stability. Also, in some applications gel polymer electrolytes are being used as the choice of electrolytes.

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Electrolyte Properties Ionic conductivity

Carbonate based High (10-1 – 10-2 Scm-1) High

Ionic liquids

Polymer-based

Ceramic

Low (10-5 Scm-1)

Moderate (10-4 – 10-3 Scm-1)

Electrochemical stability

Till 4.2 V

Till 4-6 V

Spillage Structural stability

high high

high high

Low for SPE Moderate (10-3 Scm-1) for GPE Low (SPE) High (GPE) Similar to the carbonate-based electrolyte. low Stability is reduced for GPEs

Flammability

low

nil Varies over a range 0 – 5V with some exceptions nil High except for some exceptions like antifluorite

SEPARATOR The separator is a porous membrane placed between cathode and anode and prevents the direct contact of electrodes. It is permeable to ionic diffusion but resists the electronic transport. Microporous polypropylene (PP), polyethylene (PE) tri-layer separator (PP/PE/PP) is used in commercial LIBs [343]. Different composition of polyolefin separators is used in either single layer or multi-layer depending on manufacturers. The separator failure results in internal short circuits and thermal runaway leading to cell death. (i) Properties of a separator [344] a) It should be chemically non-reactive against the electrode materials and electrolyte. b) It must have excellent mechanical strength, should not shrink during operation of cells or storage, and should have excellent electrical resistance. c) It should have a wide range of thermal stability.

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d) The thickness should be uniform, and the standard width is 25.4µm. e) The pore size should be smaller than the particle size of the electrode components (active materials, additives, etc.). The range of pore size is 0.03-0.1 µm with 30-50% porosity. f) It should have good wettability properties so that the electrolyte easily wet the separator. g) It should have high puncture strength so that penetration of electrode material through the separator can be avoided. (ii) Advantages of separators a) Prevent short-circuit – separator keeps an even spacing between cathode and anode. It only permits the passage of Li+ during charge-discharge cycling. b) Overheating safety - when the cell is overheated, the porous film melts (~ 130°C) and seals the electrodes irreversibly from each other (separator shutdown) [345].

COMMERCIAL DESIGNING OF LITHIUM-ION CELLS There are four common types of Li-ion cells available in the market: (a) cylindrical, (b) prismatic, (c) pouch, and (d) button cells as shown in Figure 20. Cylindrical type cell designs have huge varieties of applications from portable electronics to electric vehicles (EVs) for good mechanical stability and easy in manufacturing. The most manufactured cell is R18650 [21, 346]. Typical design parameters of commercial C/LiCoO2 18650 cylindrical cells are shown in Figure 22. Commercially available other cylindrical cell formats are 20700, 21700, and 22700. It is equipped with a pressure relief mechanism, current interrupt device (CID), and positive temperature coefficient (PTC) resistor switch. When excessive current pass CID discontinues the current flow and PTC breaks the conductive path and acts as short circuit protection [346-347]. Commercial button cells are mostly non-rechargeable (Figure 20 d). It is small in size and inexpensive. It is used in watches, memory back up, car

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keys, and medical implants. Prismatic cells are thinner and rectangular in geometry with minimized space by using a stacking layered approach of electrodes. These cells are used in cell phones and laptops ranging capacities from 800 mAh to 4000 mAh. However, it compromises safety and swells up from 5 mm (0.2”) to 8 mm (0.3”) after 500 cycles [349]. Pouch cells are lightweight, flexible, and commonly lithium-polymer. It utilizes most of the internal free space and has the highest packaging efficiency ~90-95% among all battery packs [349-350]. It has applications in ultra-thin minimum space usages like mobile phones or tablet computers and high load current requirements like drones, military, and automotive fields. The design follows the “Swiss roll” concept where cathode, separator, and anode are alternatively wound altogether, as shown in Figure 21. The stacking electrodes are placed in a steel cylindrical case for cylindrical cells, a flat mandrel for prismatic cell and heat sealable aluminum laminated multilayer foil is used for pouch cell case. The electrolyte is filled under vacuum condition and evenly distributed among electrodes and separators followed by completely sealing. The finished cell is rechecked its proper sealing, wielding, and electrode positions by X-ray studies. Further, voltage and impedance are also checked to detect any kind of short circuit before going to the market [349]. The formation cycle is very important for a cell to give the best electrochemical performance over its lifetime. A slow charging method is followed in the formation process at low current density. The pulse charging method at a constant current- constant voltage (CC-CV) offers an additional benefit to it. The formation step forms stable SEI on the anode and proper distribution of electrolytes in the electrodes. The current is slowly increased in one or two cycles after the formation step. The cells are kept in rest for 2-4 weeks. The cells are sorted before going to the market if any ambiguity is found in voltage deviation due to short circuits. An ideal cell should pass in all abuse tolerance test [352]. A brief description of the abuse tolerance test is presented in flow chart 1.

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Figure 20. Schematic drawing of four types of commercially manufactured lithium-ion battery (a) cylindrical, (b) prismatic, (c) pouch and (d) coin cell.

Figure 21. Schematic of the Swiss-roll assembly of separator-cathode-separator-anode [348].

Figure 22. Typical design parameters of commercial C/LiCoO2 186500 cylindrical cell [351].

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Flow chart 1. A brief description of the abuse tolerance test.

MECHANISMS OF DEGRADATION OF CELL COMPONENTS Lithium-ion batteries undergo degradation on cycling as well as storage for a prolonged period. This degradation or gradual fading in the performance of LIBs in terms of capacity, nominal voltage, etc. can be attributed to a series of auxiliary chemical and electrochemical reactions taking place between the active components of the cell. Some of the reasons are briefly discussed here.

Self-Discharge Self-discharge is a phenomenon that takes place when the cell is in open circuit condition, i.e., no external load is connected to the cell. Both reversible and irreversible processes sum up for the total self-discharge a battery undergoes. But the contribution to degradation is a result of the irreversible processes because the capacity loss due to reversible process can be recovered through subsequent cycling [353]. The process of irreversible self-discharge is mainly attributed to the oxidation of organic solvent on reaction with electrolyte. The free electrons formed from the oxidation reaction react with transition metal oxide and lithium in the

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cathode to form a reduction product without any external energy source [354]. electrolyte + Lix MO2 + yLi+ → ox. electrolyte + Lix+y MO2 (19) Also, the products formed were found to deposit on the positive electrode and thus blocks the passage for Li+ ions during cycling and results in further sluggish kinetics of the process. The self-oxidation of electrolyte plays a key role in the self-discharge process. Other prospective mechanisms of degradation include the dissolution of positive electrode material in the electrolyte, irreversible, and spontaneous lithium insertion into the cathode matrix [353, 355]. Thus, the stability of electrolytes is an important factor to increase the shelf life of a cell. The commercial batteries manufactured by Sony were also found to report a loss in its initial charged state and capacity with prolonged storage in an unutilized condition (~97.5% of initial charge is maintained after 30 days storage) [356].

Structural and Chemical Changes in the Cathode Active Materials The reason for cathode failure in LIB is due to a) Structure disordering: On delithiation, redox-active transition metal cation changes their oxidation state and the overall charge balance in the molecular integrity leads to structural reorientation. The crystal structure collapse and Li-ion face difficulty entering into cathode host during lithiation process. Cathode degradation method implies the consumption of active mass and electrolyte accompanied by gas evolution. Example: more than 50% Li removal from LiCoO2 in highly delithiated state (>4.2V) undergo structural distortion from hexagonal to tetragonal lattice along with the release of oxygen. LiMn2O4 undergoes a cubic spinel structure

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b)

c)

d)

e)

f)

to tetragonal structure as the degeneracy of electronic states in Mn+3 is disturbed (Jahn Teller distortion) [28, 114]. Cation mixing: Similar sized transition metal cation can be present in both the Li layer and MO2 layer. E.g., Li+/Ni+2 cationic disorderliness is observed in Ni-rich cathodes [357]. Dissolution of transition metal: The acid-induced dissolution of transition metal cation (e.g., Mn+2) from cathode-electrolyte interface and deposit on anode surface resulting in cathode active material loss. HF produced due to the presence of a trace amount of water in fluorinated electrolyte promotes the reaction and generate LiF. The insoluble LiF on the electrode surface increases the cell resistance with loss of capacity during charge-discharge cycling [113, 117]. Corrosion of current collector: Electrochemical oxidation of LiPF6 based electrolyte generates proton leading to thinning of Al2O3 layer and promotes the conversion of to AlF3 for more passivation of Al-foil current collector. The degradation mechanism is coupled with the parasitic reaction at high potential [358]. Binder decomposition: Polymer binders sometimes decompose due to exothermic heat generation on electrochemical cell reactions. Cathode active material loosens from Al-foil current collector resulting in degradation of cell performance [359]. A detachment of current collector: Cathode active material leach out from Al-foil current collector due to high structural volume changes on rapid insertion and deinsertion of Li-ions during cycling process [359].

Structural and Chemical Changes in the Anode Active Materials Degradation of LIB upon cycling is mostly contributed by the degradation of anode materials [353, 360]. The most widely used anode materials are the different forms of carbons like graphite, graphene, hard carbons, etc. Carbonaceous anode materials undergo dissolution with the

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electrolyte even with the presence of a solid electrolyte interphase layer. Thus, it can be understood that the passivation of the reactivity of anode with electrolyte is not optimum, and the SEI formation needs to be optimized. Even if the hydrolyzed electrolyte contains the acidic element (HF) [361], the SEI layer disrupts destroying the passivation with constant cycling. The other factor which contributes to the decay in anodic capacity is the volume change in the case of graphite. As the graphene sheets bound together in graphite are pulled apart as a result of continuous intercalation and de-intercalation of graphite during cycling, a more non-passivated area susceptible to surface reactions is exposed resulting in the fading of capacity [118]. A stable SEI formation may be considered to be the solution of such a fading of performance. This can be ensured by the usage of electrolyte additives that result in the formation of a stable SEI and also the ones which cannot result in the formation of HF (acidic component) on dissociation. Further the metal oxide type anodes and alloy type anodes suffer from capacity fading on prolonged cycling because of the low conductivity and large volume expansion respectively [359, 362].

Degradation of Electrolytes in LIB The electrolyte used mostly in commercial LIBs is the carbonate solvent-based electrolytes with Li+ salts, i.e., LiPF6 in EC: DMC. The thermal stability of this type of electrolyte is considerably low only till 8085°C [363], which is a concern in case of any overheating issues inside the batteries. The most prominent methods of degradation of electrolytes are the hydrolysis of the electrolyte salt [363], electro-reduction of the electrolyte at the anode, and consequent gassing and the deposition of inactive lithium salts formed through chemical disintegration [364-365]. Any little content of moisture in the electrolyte results in the hydrolysis of LiPF6 salt which exists in an equilibrium (LiPF6 ⇌ LiF + PF5 ). The hydrolysis results in the formation of acidic component HF and POF3. The HF component results in many side reactions as mentioned previously harmful for the LIBs during cycling and resulting in performance decay.

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The electro-reduction of the electrolytes at the negative electrode results in the formation of SEI combined with the release of gases like propylene, ethylene, etc. at the anode which might result in the breakage of seal of the battery after cycling for a prolonged time period. This process of electroreduction also leads to the loss of electrolyte ions and solvent molecules. Also, in some cases the electrolyte salts containing fluorine reacts to produce LiF like insoluble compounds and deposits on the electrode surface to inhibit the process of charge-discharge and make the kinetics of the battery more sluggish [359].

Overcharge of LIBs Overcharging of LIBs leads to a series of irreversible reactions resulting in the gradual decay in the performance of the batteries. Overcharging of the negative electrolyte leads to the formation of metallic lithium on the anode. As a result of this accumulation of metallic lithium, lithium reacts with the carbonate electrolytes. It forms inactive mass clogging the pores of the anode for further lithium-ion passage [366]. The main issue with overcharge is suspected of developing as a result of the imbalance in mass between the cathode and anode concerning lithium and also forced charging. Thus, to prevent the batteries from degradation process a good balance between the electrodes in terms of capacity, mass, size, and shape is required to be achieved [367]. The problem of overcharging of cathodes leads to the increase in the potential beyond or till 4.5V as a result of which electrolyte undergoes exothermic reaction at the positive electrode and forms insoluble solid or gaseous compounds blocking the pores of electrodes. This also leads to overheating of the system and further decomposition of electrolytes [368]. Thus, additives were introduced to stabilize the electrolyte till a higher potential limit as well as towards the oxidation process (e.g., LiI) [369-370]. Also, to protect the batteries from forced overcharging, electronic circuits are used to shut down the process as soon as the fully charged state is reached.

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Corrosion of Current Collectors The use of copper as negative and aluminum as a positive current collector is already understood. The corrosion method of aluminum at higher potential required for the charging of positive electrode is localized corrosion, and the copper current collector at lower potential undergoes cracking corrosion [371]. With cycling, the extent of corrosion on aluminum current collector increases as a result of which the internal impedance increases. The factor governing the corrosion process of aluminum is an electrolyte, and therefore the electrolyte solvent combinations like PC-DEC and electrolyte additives live LiBF4 which retard the process should be favored. On the other hand, corrosion of copper current collector in charged state at negative potential is usually dependent on the preliminary method of extraction of copper metal [372]. Protective coatings on Al like chromate coatings can be employed to reduce the corrosion activity of the current collector [373].

Degradation of Separator The reasons behind separator failure in rechargeable LIBs are [374375] a) Bi-products clogging: the side products formed due to the parasitic chemical reactions among the electrode materials and electrolyte block the pores of the separator and resist Li+ kinetics. b) Separator aging: mechanical strength of separator weakens on continuous charge-discharge cycling due to volume change in electrodes, chemical oxidation of polymeric film, physical degradation of the polymer chain, temperature effect, deposition of decomposed products, etc. c) Separator puncture: the deformation of the separator arising due to the aging mechanism may result in separator puncture. The malfunctioning of separator leads to cell death.

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Thermal Exploitation LIBs do not perform beyond an optimal temperature range (below 20 C and above 60oC). They fail to perform for a longer time at lower temperatures than room temperature (towards negative temperature) as the rate of lithium diffusion decreases with lowering the temperature because the conductivity of the carbonate-based electrolyte decreases with a decrease in temperature. The issue of non-performance at low temperatures may also be attributed to the lithium deposition on the negative electrode [376-377]. On the other hand, the failure of LIBs at higher temperatures might be attributed to the decomposition of electrolytes as a result of which unwanted insoluble products get deposited on the electrode surface blocking the pores and hence, the passage of lithium ions gets inhibited. Also, the passivating SEI layer on the negative electrode surface decomposes at temperatures beyond 40 °C as a result of which the cycling capacity fades away. o

Battery Management System Li-ion batteries require a battery management system (BMS) for the safe operation of the cell. It controls max-charge, min-charge, safe temperature ranges during operation of the cell and to balance cells to eliminate the state of charge mismatches. BMS significantly improves battery efficiency and capacity. In a battery pack as the number of cells and load currents increases, the potential for a mismatch in cells increases. There are two kinds of mismatch arises in the battery such as state-ofcharge (SOC) and capacity/energy ("C/E"). SOC is more commonly used in battery systems.

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PROBLEM MITIGATION STRATEGIES OF CELL COMPONENTS Problem Mitigation for Cathodes The electrochemical performance of LIB cathodes largely depends on their structures, particle size, morphology, synthesis method, and annealing temperature. It is possible to modify the morphology, shape, size of the battery materials and the behavior of the modified material is surprisingly different in most cases. a) Architectural design: Planer to spherical 3D design enhances Li-ion diffusion in multiple directions, improve the structural integrity of the cathode on continuous Li insertion and deinsertion process. Sometimes, non-spherical particles show better performance, which is attributed to high tap density. Short Li-ion diffusion distance and isotropic Li diffusion are generally desired for high C rate performances [111]. b) Conductive composite: Transition metals generally have very low electronic and ionic conductivity. The addition of conductive diluents enhances the conductivity, act as a buffer on volume expansion, and reduce the dissolution of transition metals in the electrolyte. Carbon is the most commonly used conductive additive. Improve in electrochemical performance strongly depends on the amount and type of carbon used. A thin carbon coating provides an effective path of electrons without blocking access to Li-ions. Graphitic carbon composite provides higher conductivity. Besides carbon, conducting polymers (e.g., polypyrrole (PPy) [378-379], and polyaniline [380-381] have also been used as additives in cathodes. c) Microstructure and particle morphology: Higher crystallinity material improves the electrode performance. The volume changes during the cycling process will be better accommodated by

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Udita Bhattacharjee, Madhushri Bhar, Sourav Ghosh et al. nanoparticles compared to bulk material because of faster stress relaxation. Nanomaterial offers a short Li-ion diffusion path. Too small nano-sized particles can be disadvantageous due to low tap density and other surface reactions on more exposed surfaces. So intermediate particle sizes such as primary particles are nano-size and secondary micron-size particles are beneficial for optimal electrochemical performance. Commercially available LiCoO2 that delivers high capacity with stable cycling performance is of micronsize [382]. The surface morphology of a particle also plays a leading role. Rod-shaped particle, which has a high surface to volume ratio, generally show good performance at the high current rate. d) Compositional control: The combination of two or more metals or electrode materials in a composite cathode improve the electrochemical behavior. Mixed transition metal oxide cathodes LiNixMnyCozO2 (x+y+z =1) shows better performance in both structural and electrochemical aspects. The presence of both small and large microparticles in a bi-phasic material improves the morphological and structural geometry. Carbon coated LiMnPO4 (C-LMP) in lithium-rich Li1.2Mn0.55Ni0.15Co0.1O2 (LMR-NMC) material provides interfacial stability under high current rate and voltage with the decrease in energy loss over cycle life in comparison to the pristine LMR-NMC [383]. Incorporation of LiFePO4 to LiCoO2 [43] or Li-NMC [384] cathode enhance stable capacity retention at high discharge current density. e) Effect of doping: The performance of cathode can be improved by elemental doping. The beneficial effects of dopants are (a) It stabilizes the crystal structure; (b) Sometimes, it participates in electrochemical redox reactions during the charge-discharge process; (c) Reduce dissolution of the electrode material. Eg. aluminum is commonly used as a dopant for improved cycle stability in LiNiO2 along with cobalt (i.e., LiNi0.8Co0.15Al0.05O2, NCA) [385].

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f) Interface engineering: Protective coating on cathode may act as an impurity scavenger or block the active surfaces that promote electrolyte decomposition. Sub-nanometer coatings of an amorphous thin-film electrolyte on LiMn1.5Ni0.5O4 spinel show excellent performance. LiPON coating is stable up to 5.5V, and it slows down the cathode-electrolyte interfacial resistance [131].

Mitigation Strategies for Anodes The main approaches towards controlling the characteristics of the anode for improving the performance of the LIBs can be enumerated as follows [359]: a) Increasing the conductivity of metal oxide hosts: The metal oxide hosts (intercalation type as well as conversion type) are less conductive (e.g., LTO has conductivity 200% and a Cu-Sn intermetallic matrix undergoing topotactic lithium insertion involves a volume change of ~61% [196, 268]. c) Increasing the intrinsic electrochemical capacity of the active material: Compounds with practical applicability like the intercalation type carbonaceous compounds as well as metal oxides often lack in achieving Li storage capacities as high as the metallic alloys or conversion type materials. Thus, practically applicable compounds with a high tendency for lithium storage are needed. Even extra capacities can be induced by doping to create voids as well as by increasing the conductivity. Graphene or exfoliated graphite sheets have higher Li storage capacity (~ 744 mAh g-1 for graphene) almost double as compared to graphite, but the cyclability is low due to more surface reactions. Even different morphologies of active materials with enhanced porosity and conductivity can result in the enhancement of lithium storage property [199, 216]. d) Decreasing the potential of lithium insertion: The metal oxides have a disadvantage of higher insertion potential towards lithium (1.5V vs Li/Li+ for LTO) compared to carbonaceous compounds (0.6V vs Li/Li+ for graphite). Thus, if certain composites are formed in such a manner that the insertion potential is lowered, then these compounds can be used in practical applications. e) Accounting for the rapid loss in capacity due to instability of the electrode-electrolyte interface: Anode is protected from the dissolution in the electrolyte by the formation of a solid electrolyte interface layer as mentioned earlier. Capacity fading due to the anode is observed due to the consequent cycling of LIBs. This is a direct consequence of the dissolution of the SEI layer [21, 275277]. Thus, a stable SEI layer is essential for retaining the performance of a LIB during cycling. A stable SEI layer can be formed by modulating the composition of the liquid electrolyte solvent. Electrolyte additives like VC, FEC are used to form a

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stable SEI, and also the acidic content of the electrolyte (HF) needs to be minimized to ensure that no further dissolution of the SEI.

Problem Mitigation for Electrolytes The electrolyte plays an important role in ion transport between the two electrodes in a battery. Thus, improving the performance of an electrolyte can positively influence the performance of a battery. The following strategies can be employed for this purpose: a) A nonflammable, non-spillage alternative to liquid electrolytes: As the commercially used liquid electrolytes are carbonate-based, they are highly flammable (due to low boiling point), and because of the liquid nature they are prone to spillage while being used in mobile applications. To overcome the disadvantage of spillage gel polymer electrolytes (GPEs) were used but due to the presence of a considerable amount of liquid component, the problem of flammability is not mitigated. Thus, ceramic electrolytes were used, but the difficulty with ceramic electrolytes is to find a stable metal-ligand combination which is both considerably conducting towards lithium ions and is stable in ambient conditions so, that the LIBs can cycle stably. b) Improving the ionic conductivity of polymer and solid electrolytes: The low ionic conductivity is a major issue for the polymer electrolytes and thus, liquid infusion to form gel polymer electrolytes was introduced. GPEs have considerably high ionic conductivities compared to SPEs. The stable ceramic electrolytes like NASICON type, perovskite-type, etc. have lower ionic conductivity. Thus, introducing dopants for the metal ions in the framework was strategized to increase the ionic conductivity [305, 310, 312]. Also, the ionic liquid type electrolytes have low ionic

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Udita Bhattacharjee, Madhushri Bhar, Sourav Ghosh et al. mobility due to very high viscosity resulting in lesser cycling stability. Thus, the RTILs with comparatively low viscosity are preferred [299] c) Improving the ion transport number: The lithium-ion transport number for the polymer electrolytes are required to be close to 1. But most SPEs have transport numbers even less than 0.5, which restricted their application. Thus, plasticizers were used to improve the ionic transport number in SPEs [301]. d) Improving the electrochemical stability: Various ceramic electrolytes containing Ti4+ ion in the framework undergo electrochemical decomposition at around 2.5 V. Thus, keeping the same structure and replacing Ti4+ with Ti5+ and Zr3+, the electrochemical stability was achieved without hampering the ionic conductivity. Even Li3N type ceramic electrolyte has a very high conductivity but is not stable beyond a potential limit. To achieve its applicability, the decomposition potential needs to be shifted to higher values [311]. Also, the carbonate-based liquid electrolytes were not stable beyond ~4.5V. Thus, various additives that can stabilize the electrolytes above this potential were analyzed as discussed previously in this chapter [291].

Problem Mitigation for Separator Commercial polyolefin separators provide limited heat resistance. Various researches are going on new materials such as silicone rubber, aromatic polyamide resin, liquid crystalline polyester resin, etc. that will provide superior ion transport property at high current along with high thermal stability and safety [386-388]. The inorganic material coating on separator such as alumina, silica, titania prevents from separator rupture.

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CONCLUSION a) Extensive research during the last few decades has developed Liion batteries with high energy density (200 Wh kg-1), high cycle life (>1000 cycles), and high-efficiency (>99%). The cathode materials are of having capacities in the range of 150-200 mAh g-1 and graphite is still the choice of anode having a practical capacity of 350 mAh g-1 b) The research and development continue by focusing the development of high energy electrode materials (high capacity and high voltage), fast coating and packaging approaches which could overcome the constraints of cost ( 200 Wh kg-1), cycle life, power density, and safety. c) Anode and cathode materials with promising electrochemical performances have been developed but the intrinsic issues related to limited electrical conductivity, slow kinetics of Li transport, chemical instability when in contact with the electrolyte, low stability in thermal abuse conditions, high structural deformation on prolonged cycling and low mechanical strength restrict their commercialization. Many intercalation cathodes and Si/Sn-based composite anodes have been introduced to the market and also conversion-type material technology is gradually pacing up to widespread commercialization. d) The solid-state batteries may play a paradigm shift in terms of both technology and applicability. e) Besides Solid-state LIBs, lithium metal-based batteries such as LiS are expected to evolve soon having improvements in energy density, safety, and greater cycle life with reduced cost. f) The last couple of decades have made tremendous progress in the field of Li-ion battery electrode materials. However, the impact of Li-ion batteries on the societal development of modern civilization is expected to increase many folds in the years to come.

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ACKNOWLEDGMENTS Udita acknowledges DST-SERB under Sanction Order No CRG/2018/003543, Madhushri acknowledges DST- INSPIRE under Code No: IF180708, Sourav acknowledges DST-UKIERI program under grant no. DST/INT/UK/P-173/2017, Govt. of India for fellowships. Martha acknowledges the NRB (DRDO) under sanction no. NRB/4003/PG/381 Government of India and IIT Hyderabad for financial support to this work.

REFERENCES [1] [2] [3]

[4] [5] [6]

[7] [8] [9]

Julien, C., Mauger, A., Vijh, A., Zaghib, K. (2016). Lithium batteries. In Lithium Batteries, Springer:29-68. Goodenough, J. (2013). Battery components, active materials for. In Batteries for Sustainability, Springer:51-92. Murphy, D. W., Trumbore, F. A. (1976). The chemistry of TiS3 and NbSe3 cathodes. Journal of The Electrochemical Society, 123 (7): 960. Broadhead, J., Murphy, D., Steele, B. (1980). Materials for advanced batteries. Plenum Press. Armand, M., Steele, B., Fast Ion Transport in Solids, ed. W. Van Gool. North-Holland, New York: 1973. Armand, M., Touzain, P. (1977). Graphite intercalation compounds as cathode materials. Materials Science and Engineering, 31: 319329. Dey, A. (1971). Electrochemical alloying of lithium in organic electrolytes. Journal of The Electrochemical Society, 118 (10): 1547. Whittingham, M. S. (2004). Lithium batteries and cathode materials. Chemical Reviews, 104 (10): 4271-4302. Whittingham, M. S. (1976). Electrical energy storage and intercalation chemistry. Science, 192 (4244): 1126-1127.

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[10] Thompson, A. (1975). Electron-Electron Scattering in TiS2. Physical Review Letters, 35 (26): 1786. [11] Brandt, K., Laman, F. (1989). Reproducibility and reliability of rechargeable lithium/molybdenum disulfide batteries. Journal of Power Sources, 25 (4): 265-276. [12] Fouchard, D., Taylor, J. (1987). The molicel® rechargeable lithium system: Multicell aspects. Journal of Power Sources, 21 (3-4): 195205. [13] Godshall, N., Raistrick, I., Huggins, R. (1980). Thermodynamic investigations of ternary lithium-transition metal-oxygen cathode materials. Materials Research Bulletin, 15 (5): 561-570. [14] Mizushima, K., Jones, P., Wiseman, P., Goodenough, J. B. (1980). LixCoO2(0 𝑇𝑠

After determining its value, it is possible to calculate the phase and the temperature of the material.

CONCLUSION The SAH is one of the best mediums for space heating, crop dying, timber seasoning and whatnot. The limited availability of sunshine restricts it from reaching its full potential. The integration of PCM, enhances the thermal performance of SAH as the PCM acts as latent heat storage media and provides thermal backup during off-sunshine and nocturnal hours. The variety of experimental analysis showed that the energy can be well sustained in PCM integrated models. The disadvantage of PCM having low thermal conductivity can be enhanced at the expanse of its chemical life cycle. Having PCM as the thermal energy storage medium, resulted to perform better than the other storage mediums. The average thermal

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backup provided by a SAH integrated with PCM is generally of 8-10 hours until it reaches the point where it gives thermal backup in sensible state, the temperature difference drops, making it useless. Therefore, PCM improves the thermal efficiency of SAH by acting as a thermal backup medium.

REFERENCES [1] [2]

[3]

[4]

[5]

[6]

[7]

Abhat, A. (1983). Low temperature latent heat thermal energy storage: heat storage materials. Solar Energy, Vol. 30(4), pp. 313-33. Moradi, R., Kianifar, A., and Wongwises, S. (2017). Optimization of a solar air heater with phase change materials: Experimental and numerical study. Experimental Thermal and Fluid Science, Vol. 89, pp. 41-49. Josyula, T., Singh, S., and Dhiman, P. (2018). Numerical investigation of a solar air heater comprising longitudinally finned absorber plate and thermal energy storage system. Journal of Renewable and Sustainable Energy, Vol. 10(5), pp. 055901. Reddy, K. S. (2007). Thermal Modeling of PCM-Based Solar Integrated Collector Storage Water Heating System. Journal of Solar Energy Engineering, Vol. 129(4), pp. 458-464. doi:10.1115/1.277075 Charvát, P., Klimeš, L., and Ostrý, M. (2014). Numerical and experimental investigation of a PCM-based thermal storage unit for solar air systems. Energy and Buildings, Vol. 68, pp. 488-497. El Khadraoui, A., Bouadila, S., Kooli, S., Farhat, A., and Guizani, A. (2017). Thermal behavior of indirect solar dryer: Nocturnal usage of solar air collector with PCM. Journal of cleaner production, Vol. 148, pp. 37-48. Kabeel, A., Khalil, A., Shalaby, S., and Zayed, M. (2016). Experimental investigation of thermal performance of flat and vcorrugated plate solar air heaters with and without PCM as thermal energy storage. Energy Conversion and management, Vol. 113, pp. 264-272.

202 [8] [9] [10] [11]

[12]

[13] [14]

[15] [16]

Bharat Singh Negi, Satyender Singh and Subhash Chander K. Reddy, J. Sol. Energy Eng. 129, 458–464 (2007). Gerald, C. F. (2004). Applied numerical analysis: Pearson Education India. P. Naphon, Int. Commun. Heat Mass Transfer (2015), Vol. 32, pp. 140–150. Naphon, P. (2005). On the performance and entropy generation of the double-pass solar air heater with longitudinal fins. Renewable Energy, Vol. 30(9), pp. 1345-1357. Singh, S., and Dhiman, P. (2014). Thermal and thermohydraulic performance evaluation of a novel type double pass packed bed solar air heater under external recycle using an analytical and RSM (response surface methodology) combined approach. Energy, Vol. 72, pp. 344-359. Sartori, E. (1987). Advances in Solar Energy Technology: Pergamon Press, Oxford, UK. Kuznik, F., Virgone, J., and Roux, J.-J. (2008). Energetic efficiency of room wall containing PCM wallboard: A full-scale experimental investigation. Energy and Buildings, Vol. 40(2), pp. 148-156. P. Dhiman and S. Singh, Int. J. Sustainable Energy (2017), Vol. 36, pp. 78–100. P. Dhiman, N. Thakur, A. Kumar, and S. Singh, Appl. Energy (2011), Vol. 88, pp. 2157–2167.

In: Energy Storage Systems: An Introduction ISBN: 978-1-53618-873-8 Editor: Satyender Singh © 2021 Nova Science Publishers, Inc.

Chapter 5

OPTIMAL CCHP COMBINED WITH THERMAL ENERGY STORAGE SYSTEM DESIGN USING GENETIC ALGORITHM Nima Norouzi and Maryam Fani* Energy and physics Department, Amirkabir University of Technology, Tehran, Iran

ABSTRACT In recent years, cogeneration systems have been considered to increase the efficiency and optimal use of energy sources for the production of electrical energy and heat energy. Electricity and heat energy cogeneration systems can achieve up to 70% efficiency, and at the realistic and subsidized rates of energy carriers, the beneficiaries of these systems supply the demand and supply sectors. In Iran, due to its comparative advantage, different subsidies are awarded to energy carriers, achieving the potential of these systems requires the appropriate modeling, selection, and mixing of cogeneration system components as well as the wise utilization of them. Changes in electric and heat loads and electricity tariffs at different times of the day make it challenging to *

Corresponding Author’s Email: [email protected]

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Nima Norouzi and Maryam Fani determine the optimal point of cogeneration systems. Research in this area is mostly focused on systems without a heat storage tank, and the costs of setting up and leaving the system are not considered. Therefore, in this study, the optimal working point of a system consisting of several independent units, capable of trading electricity, based on the consumption of various fuels, and utilization of heat storage tank was determined using genetic algorithm, and modeling accuracy were compared. Other references have also been made. The simulation results show that in the temperate seasons and summer, the cogeneration system meets all electrical and thermal requirements during the 22-23 hours due to the high electricity grid rate and at the end of 24 hours, the total cogeneration cost For almost all seasons 50% less than the conventional production system. It has also been shown that the use of absorption chillers has improved the ratio of electrical and heat loads, and the efficiency of the cogeneration system has increased compared to the previous state, and the heat energy loss has also decreased.

Keywords: CCHP, thermal storage, combined conversion and storage, CCS, optimum design

INTRODUCTION The efficiency of cogeneration systems and their relative superiority over individual generation systems depends on the operating point of the system and the amount of electrical and heat energy utilized in an optimal combination. Technical specifications of the cogeneration system, electric and heat load curves, access to the electricity distribution network, access to other heat sources (auxiliary boilers, city heating systems), and the costs of supplying electricity from each of these sources are effective on the designated point. Work affects. As can be seen in Figure (5), in general, the cogeneration system is capable of being connected to the electricity distribution network and exchanged with it. In this case, the electricity shortage will be purchased from the grid, or the surplus will be sold to the grid. In this case, the operating point of the system can fluctuate between the minimum point to the maximum power. The required heat energy is provided by both the auxiliary boiler and the cogeneration system [1].

Optimal CCHP Combined with Thermal Energy Storage System 205 In this case, the electrical power generated by the system is determined by minimizing the cost of providing electricity and heat, as well as the amount of environmental pollution of the system. One of the critical points in the operation of cogeneration systems is to determine the optimal operating point of the system according to the operating conditions of the system, which has been studied in numerous articles. In Reference [2], the optimal working point of a steam turbine primary propulsion system is determined using auxiliary programming. Since the steam turbine start-up and exit time is long, it does not take into account the costs of operating the system in optimization, and it is assumed that the system is always connected to the grid. In Reference [3], the optimal working point of the cogeneration system is also determined using parallel programming. In this study, in addition to the cost of production, the environmental contamination of the co-generation system has been considered, and an algorithm has been proposed to determine the optimal operating point of the system. In [2], the mathematical modeling of the cogeneration system has been studied to determine the optimal working point of the system, but no method has been provided to determine the optimal working point. Reference [5] using complex linear programming has provided a method to optimize the performance of the cogeneration system by assuming constant mechanical drive efficiency over the long term. In Reference [2], a cogeneration system with thermal energy storage capability is examined, and the amount of electrical energy generated by the system is determined by the grid operator. In this study, the distribution of electricity demand between different generators in order to reduce the final cost of production is investigated. In references [6] and [7], the effect of thermal energy storage capability on the performance and environmental contamination rate of the cogeneration system has been investigated. Activities undertaken in the discussion of determining the optimal operating point are mainly focused on systems without a heat storage tank, and the costs of operating and leaving the system are not taken into account. In this study, for a system with the capability of buying and selling electric energy, using different fuels, the heat storage tank, and

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considering the system efficiency as a function dependent on the operating point and the costs associated with setting up and leaving the system. The optimal working point of the system is determined. In the case of cogeneration systems with the heat storage tank, it is important to note how the boiler operates [8]. In this study, it is assumed that the auxiliary boiler works at constant power. Lowering the fluid temperature of the tank will light up the auxiliary boiler. Turning on and off the auxiliary boiler, the thermal energy storage system, as well as turning on and off each cogeneration unit, converts the energy supply cost function into a discrete, nonlinear, and derivative function. Given these conditions, the genetic algorithm was used to determine the optimal working point of the cogeneration system [1].

COMBINED COOLING, HEATING AND POWER (CCHP) Distributed Energy Demand The rapid rise in global energy demand, coupled with the expected decline in fossil fuel energy sources and their impact on global climate change, has called for urgent and creative ways to resolve the energy crisis [1]. Figure 1 provides an idea of the world's energy production numbers, fuel consumption, emissions, and fuel prices. Along with the shift to clean renewable energy technologies, distributed and locally sustainable energy systems are the way forward because they are more effective in the long run. They can help the central grid, especially in times of emergency such as sudden demand, natural disasters, terrorism, etc. A proven approach to distributed energy generation is the use of Refrigeration, Heating, and Energy Systems (CCHP), which combines the use of traditional techniques with newly developed technologies to meet modern needs in energy, economic and environmental policies. Compared to a centralized approach to save electricity, CCHP systems use thermal energy from fossil fuelbased electric power generation for heating, ventilation, and cooling

Optimal CCHP Combined with Thermal Energy Storage System 207 (HVAC) [2]. Since HVAC represents a large part of energy consumption in residential and industrial sectors (Figure 2), this method can save much energy.

(a)

(c)

(e)

(b)

(d)

(f)

Figure 1. (a) World electric generation by fuel (TWh). (b) Rotterdam oil product spot price (USD/barrel) (c) World primary energy supply by fuel (Mtoe) (d) Steam coal or electricity generation (USD/tonne) (e) World CO2 emissions by fuel (Mt of CO2) (f) natural gas import price USD/Million BTU [8].

The global power of CHP systems is presented in Table 1. These systems are used in a wide range of institutions such as universities (Pennsylvania State University), airports (Shanghai Pudong International

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Airport, China), seawater desalination plants (Iran), for district heating (Finland, Denmark, Germany), Internal hospitals, supermarkets have been installed. Supermarket, textile mills, etc. The economical, efficient, and low-cost design of this system requires full attention to the energy needs of a particular region. Table 2 shows an idea of the scale of the system in terms of energy capacity and typical usage [3]. Table 1. Installed CHP capacity by country in MW [8] Country Australia Austria Belgium Brazil Bulgaria Canada China Czech Denmark Estonia Finland France Poland

Capacity 1864 3250 1890 1316 1190 6765 28153 5200 5690 1600 5830 6600 8310

Country Greece Hungary India Indonesia Ireland Italy Japan Korea Latvia Lithuania Mexico Netherlands

Capacity 240 2050 10012 1203 110 5890 8723 4522 590 1040 2838 7160

Country Portugal Romania Russia Singapore Slovakia Spain Sweden Taiwan Turkey UK US Germany

Capacity 1080 5250 65100 1602 5410 6045 3490 7378 790 5440 84707 20840

Table 2. Power system scale concerning power capacity and application area [8] Configuration Micro-scale Small-scale

Capacity 10 MW

Application Area Distributed Energy System Supermarkets, retail stores, hospitals, office buildings, universities Large factories, hospitals, schools Large industries. Waste heat used in universities, district heating

Optimal CCHP Combined with Thermal Energy Storage System 209

(a)

(b) Figure 2. (a) Breakdown of energy consumption for a household over the years. (b) Breakdown of energy consumption in manufacturing for a single year [8].

Improvement Design Strategies The primary purpose of any power plant design is to achieve more work efficiency to provide specific heat (or fuel energy). This plant should be designed to simulate the nearest possible period, the Carnot cycle [4]: 𝜂𝑐𝑎𝑟𝑛𝑜𝑡 =

𝑊 𝑄0

=1−

𝑇min 𝑇max

(1)

In a conventional thermal power plant, approximately one-third of the input fuel energy usually appears as electrical energy; two-thirds of the energy as lukewarm water is transferred to the rivers or the sea in cooling towers. Therefore, in order to increase thermal efficiency, other design

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adjustments are required. Heat exited from the turbine can be reused by one or a combination of the following methods: (1) regeneration, (2) the combined gas and steam cycle, or (3) co-generation (i.e., CHP) and its development systems, Production (i.e., CCHP). Individual adjustments were made to increase the plant's thermal efficiency locally in the initial investigation of the Rankin and Jules Burton cycle power plants (Figure 3). The regeneration procedure, which involves reusing the heat lost in the cycle, may be performed by boiler bleeding or heat exchangers. However, the scope of this amendment is limited [5].

(a)

(b) Figure 3. Temperature-entropy diagram showing modifications to basic (a) Rankine cycle and (b) Joule-Brayton cycle to increase thermal efficiency [9].

Optimal CCHP Combined with Thermal Energy Storage System 211

(a)

(b)

Figure 4. Gas turbine/Steam turbine combined power plant (a) schematic and (b) block diagram [10].

In a combined cycle plant (Figure 4), the two rotating stations are combined so that the QHL heat from the "top" (top cycle) plant (JouleBryton gas turbine cycle) of the efficiency ηH source and "The bottom plant "(bottom) is used with an efficiency of ηL (steam turbine cycle). These two plants are cyclic and use two different working fluids. A brief analysis of this plant to determine thermal efficiency is provided as follows [5]: 𝑊𝐻 = 𝜂𝐻 𝑄𝐵

(2)

𝑊𝐿 = 𝜂𝐿 𝑄𝐻𝐿

(3)

𝑄𝐻𝐿 = 𝑄𝐵 (1 − 𝜂𝐻 )

(4)

𝜂𝑡ℎ =

𝑊𝐻 +𝑊𝐿 𝑄𝐵

= 𝜂𝐻 + 𝜂𝐿 − 𝜂𝐻 𝜂𝐿

(5)

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Figure 5. (a) Separate generation of heat and electricity for industrial plants. (b) Co-generation of heat and electricity for industrial plant [12].

As a result, higher cycle efficiency is increased by η L (1 - ηH) using the waste heat to generate energy in the lower cycle [10]. CHP enables the use of wasted steam in the combined cycle power plant. Figure 5. Simplified configuration of CHP facilities against separate heat and power generation is shown. The plant requires E1 and Q1 values of electricity and heat, respectively. CHP Energy provides E and Q values of energy and heat. Extra fuel and fuel can be purchased to meet factory requirements. The CHP station's overall efficiency can be as follows [7]: 𝜂𝐶𝐻𝑃 =

𝑄+𝐸 𝑄0

(6)

The ηCHP is also referred to as the Energy utilization Factor (EUF). Since all the heat used in power generation is not used to provide heat, the overall efficiency of the CHP system can reach 90% compared to 35-40% for the individual power plant [12].

Technical Review Combined Cool, Heat, and Power is a combination of axial power and useful heat produced by a system using two different forms of useful energy using a primary energy source [8].

Optimal CCHP Combined with Thermal Energy Storage System 213 The technology was first used in steam cycle power plants, using steam extracted from the cycle for heating purposes in the plant and surrounding units. Although this would reduce the efficiency of such power plants, it would save a great deal on fuel consumption. In recent years, the application of these systems, which results in high energy consumption, has not been limited to steam power plants and has been extended to other power generators, whether mechanical or electric, so that any power generating system can be used to any size today. It was designed and implemented as a single unit, making it possible to utilize the heat generated by the generator or motor in addition to generating electrical or mechanical power by the device. Combined plants can be divided into five general categories:     

Recovery from Extraction Condensing; Recovery from Back-Pressure Turbines; Recovery from gas turbine heat recovery; Recycling from the Combined Cycle; Recycling from Reciprocating Engines.

The most unaffected cogeneration plants are those using Back-pressure turbines. These power plants generate electricity and heat in a steam turbine. Another significant component of Back-pressure power plants is a boiler designed to burn solid, liquid, or gaseous fuels [9].

Extraction Condensing Heat generation by dispersed production can be done in plants equipped with Extraction Condensing. By removing some of the steam before reaching the final stage of the turbine. Central heating can be used for industrial use by steam extracted from the turbine. The steam pressure reduction station is used when the steam turbine is not in use. In this case, reliable steam will be provided to heat the processes. Note that this steam generating system does not apply if the steam turbine is not used. In a conventional power plant, only electricity is produced, but in an Extraction

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Condensing plant, some of the steam is generated from the turbine to generate heat [10].

Backpressure Power Plants In conventional steam power plants, high-pressure steam is produced in the boiler, so-called live steam. This vapor passes through the turbine, and, after full expansion, low pressure enters a condenser. In this section, the residual heat in this steam is transferred by air or water. In a backpressure turbine, steam is driven out of the middle parts of the turbine by higher pressure, and this steam is used for heating purposes. This steam can be used directly as process steam (for example, in paper machines) or as a hot fluid in a heat exchanger to heat water in district heating systems [11]. Industrial Backpressurere Power Plants At industrial back-pressure power plants, the backpressure of the turbine is usually maintained at full and partial loads with constant process conditions. Some of the higher quality steam can also be extracted from the middle parts of the turbine. This steam can be used in industrial processes or can be consumed indoors. CHP will not apply if the steam reaches the internal consumption of the plant. The higher the steam extracted from the turbine, the less electricity produced [12]. Backpressure Power Plants for Use in District Heating In conventional district heating systems, hot water, which carries energy, is passed through heat exchangers. The temperature of this water will vary with the ambient temperature changes. Depending on the design of the grid, the outlet temperature of the power plant is assumed to be between 120 and 150°C. For example, if the average outlet water temperature is between 80 and 85 degrees, the return water temperature will be about 50 to 55 degrees Celsius. In some cases, boilers in series with heat exchangers are considered to increase the temperature of the outlet water. It should be noted that the increase in heat due to the passage of these boilers should not be included in the calculation of the total

Optimal CCHP Combined with Thermal Energy Storage System 215 efficiency of the CHP system. The higher the water temperature of the outlet than the district heating system, the lower the power output [12].

Gas Turbine and Heat Recycling Boiler A simple, low-cost system for generating scattered heat and power can generate heat recovery by combining a gas turbine and a boiler. Hot exhaust gases pass through a gas recycling boiler and provide the steam required for the process or heating required. In these types of power plants, hot air from the gas turbine outlet passes the heat recovery boiler and transfers its heat to the carrier fluid (water). In many cases, natural gas is used as fuel, but diesel or a combination of gas and diesel is also used as fuel. The amount of heat recovered depends on the type of fuel consumed and the temperature of the heat recovered. If natural gas is used as a gas turbine fuel, the temperature of the exhaust gas from the recycling boiler can be reduced to about 60 to 100°C. Be controlled [11]. In some cases, the power plant is equipped with an auxiliary burner that uses exhaust gas from the gas turbine instead of the combustion air. Naturally, the heat generated from auxiliary burners should not be taken into account in calculating the heat generated from CHP. In some cases, the exhaust from the gas turbines will be equipped with a by-pass, which can only be used when the boiler is recycled and unnecessarily removed from the system. Combined Cycle Power Plants Recently, combined cycle power plants, including one or more gas turbines, including heat recovery boilers and steam turbines, have become commonplace. A combined cycle power plant consists of one or more gas turbines and steam turbines. Depending on the type of steam turbine, the power plant can be either conventional or dispersed. These units can be used as CHP units if the auxiliary coolers are not used to cool the steam turbine outlet. The characteristic of all combined cycle power plants is the heat recovery from the exhaust gas of the gas turbines [13]. This heat is used by recycling boilers to produce the steam needed for steam turbines. Auxiliary boilers are commonly used to heat auxiliary boilers to increase

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the steam quality of auxiliary burners that use gas turbine exhaust gas as inlet air. Combined cycle systems in which the condenser output fluid is used to heat form the basis of the combined cycle dispersed generation systems [9].

Power Plants Equipped with Reciprocating Motors This method is similar to the gas-dispersed generation method, with the use of reciprocating internal combustion engines instead of gas turbines. In power plants using reciprocating motors, heat can be recovered from engine oil or engine coolant water from the heat of the exhaust gases. The electrical efficiency of reciprocating motors is between 35% and 42%, and if the environmental regulations require a significant reduction in nitrogen oxides, this efficiency is reduced by 1%. Given that advanced engines have cooler exhaust gases (about 400), heat recovery can only be steam; for example, a 4.2 MW diesel engine can produce 1.5 MW steam and 1.3 MW hot and cold. Given that the total fuel consumption for this engine will be about 10 MW, the total efficiency of the complex is about 88% [10].

METHODS Genetic Algorithm Genetic Algorithm (Genetic Algorithm - GA) is a computer science search technique for finding an approximate solution to search optimization and problems. A genetic algorithm is a particular type of evolutionary algorithm that uses biological techniques such as inheritance and mutation [1]. The genetic algorithm, known as one of the random optimization methods, was invented by John Holland in 1967. Later, with the efforts of Goldberg 1989, this method found its place, and today, due to its capabilities, it is well-positioned, among other methods.

Optimal CCHP Combined with Thermal Energy Storage System 217 Genetic algorithms are usually implemented as a computer simulator in which the population of an abstract sample (chromosomes) of the solution candidates of an optimization problem leads to a better solution. Traditionally solutions have been in the form of strings of 0 and 1 but have been implemented in other ways today. The hypothesis begins with a completely random population and continues for generations. In each generation, the capacity of the entire population is evaluated, several individuals are randomly selected from the current generation (based on competencies) and modified (deducted or reconfigured) to form the new generation, and the algorithm is transformed into the current generation in the next iteration [13]. For example, if we want to model oil price fluctuations using external factors and simple linear regression, we will produce the following formula: Oil price at time t = Factor 1 Interest rate at time t + Factor 2 Unemployment rate at time t + Constant 1. We will then use a criterion to find the best set of coefficients and constants to model oil prices. There are two essential points to this method. The first is that the method is linear, and the second is that we specify the parameters used instead of searching through the “parameter space[12].” Using the Genetic Algorithm, we set up a formula or scheme, which expresses something like “Oil prices at time t are a function of maximum four variables.” The genetic algorithm will then be executed, which will search for the best function and variables. The genetic algorithm’s work is deceptively simple, very understandable, and remarkably the way we believe animals have evolved. Following the above, one follows the population of possible formulas. The variables that specify each given formula are shown as a set of numbers that make up the individual’s DNA [11]. The genetic algorithm engine generates an initial population of formulas. Each person is tested against a set of data and remains the most relevant (perhaps 10% of the most appropriate); the rest are excluded. And change (random change of DNA elements). It is observed that over many generations, the genetic algorithm tends to formulate more precise formulas. While neural networks are both nonlinear and nonparametric, the

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great attraction of genetic algorithms is that the final results are more noticeable than the other methods. The final formula will be visible to the human user, and standard formulas can be applied to these formulas to provide a level of confidence. The technology of genetic algorithms is continually improving, for example, by equating viruses that are produced alongside formulas to break weak formulas and thus make the population stronger overall. In short, the genetic algorithm (or GA) is a programming technique that uses genetic evolution as a problem-solving paradigm. Evaluates the candidate solution, most of which are selected at random [9]. Genetic Algorithm (GA) is a computer science search technique for finding optimal solutions and search problems. Genetic algorithms are one of a variety of evolutionary algorithms inspired by the science of biologics such as inheritance, mutation, natural selection, natural selection, and composition. Solutions are generally represented as 2s of 0s and 1s, but there are other display methods. Evolution starts from a completely random set of entities and is repeated over the next generations. In each generation, the best are chosen, not the best. A solution to the problem is shown by a list of parameters called chromosomes or genomes. Chromosomes are generally represented as a simple sequence of data, although other data structure types can also be used. Initially, several features are randomly generated to create the first generation. During each generation, each attribute is evaluated, and fitness is measured by the function of fitness [12]. The next step is the creation of the second generation of the population, based on selection processes, based on characteristics selected by genetic operators: linking chromosomes to each other and changing. For each individual, a pair of parents is selected. The choices are such that the most appropriate elements are selected so that even the weakest elements have the chance of being selected to avoid approaching the local answer. There are several patterns to choose from Roulette, Tournament, etc. [13].

Optimal CCHP Combined with Thermal Energy Storage System 219

Figure 6. The flowchart of the GA [14].

Genetic algorithms usually have a probability of being between 0.6 and 1, indicating the probability of a child being born. The organisms are reunited with this probability. Binding creates two child chromosomes, which are added to the next generation. These are done until the right candidates are found for the next generation. The next step is to change the new offspring. Genetic algorithms have a small, constant change probability, usually of a degree of about 0.01 or less. Based on this probability, the child’s chromosomes change randomly or mutate, especially with the bits mutated in the chromosome of our data structure [12]. This process creates a new generation of chromosomes, which is different from the previous generation. The whole process is repeated for the next generation, and the pairs are selected for the mix; the third

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generation populations are created, and so on. This process is repeated until we reach the final stage [11].

Operators of a Genetic Algorithm Each problem requires two elements before a genetic algorithm can be used to find an answer: First, a method is needed to provide an answer that the genetic algorithm can work on that. Traditionally, an answer is represented as a string of bits, numbers, or characters. The second is a way to calculate the quality of each proposed answer using proportional functions. For example, if the problem considers any possible weight for a backpack without breaking the backpack (see the backpack problem), a method of answering can be considered as a sequence of bits 1 and 2, which; or Whether or not the weight is added to the backpack is measured. The proportion of response is measured by determining the total weight for the proposed answer [10]. The optimization procedure in the genetic algorithm is based on a random-directed procedure. This method is based on the theory of gradual evolution and Darwin’s fundamental ideas. In this method, a set of random parameters is randomly generated for several constants called populations, after executing a numerical simulator that represents the standard deviation and Or we fit that set of information to that member of that population. Repeat this process for each of the created members, then formulate the genetic algorithm operators, including fertilization, mutation, and nextgeneration selection, and continue this process until the convergence criterion is met. Commonly, three criteria are considered as a stop criterion [9]: 1. Algorithm execution time. 2. The number of generations created. 3. Error Criterion Convergence

Genetic Algorithm Applications 

Hydrological Routing of Runoff in Dry River Network

Optimal CCHP Combined with Thermal Energy Storage System 221   

Help solve multi-criteria decision-making problems Multi-objective optimization in water resources management Optimization and re-design of power distribution networks

Termination Conditions for Genetic Algorithms Are      

To a fixed number of generations. Finish allotted budget (calculation time/money). Find an individual (child produced) that meets the minimum (minimum) criterion. Obtain the highest degree of fitness for children or no other better results. Manual inspection. Top combinations.

CCHP Modeling The modeling approach for analyzing and improving Discrete Production (SP) and CCHP plants is described in this chapter. The design of CCHP systems should consider the best strategies for load demand, trade-offs between cost savings, energy savings, and net pollutant emissions. Several performance standards and operational strategies have been discussed for this purpose [8].

Operational Strategies The CCHP operational strategy dictates system loading and fuel consumption. You can use the following strategies to control CCHP systems: 1. After Electric Charge (FEL): Here, the PGU generates all the electricity needed to meet the electrical need and uses the lost heat to provide the maximum amount of convection possible. If the

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Nima Norouzi and Maryam Fani recovery heat is not sufficient, an auxiliary boiler is used to supply the heat required by the facility. This strategy is also called electricity demand management (EDM) [6]. 2. After Transmission (FTL): The system provides all the thermal and electricity demand generated to meet the highest possible electrical demand. Extra electricity from the grid may be needed if needed. Also referred to as thermal demand management (TDM). 3. Essential Load Operation: The system only covers a certain amount of electrical and thermal load of the facility. Any additional needs should be purchased from the power grid or boiler.

EDM and TDM strategies may not guarantee the best performance of the system. This is due to factors such as differences in demand and fuel prices. Some optimization techniques must be considered to maximize system performance [5].

System Model The typical SP system providing cooling, heating, and power is shown in Figure 7(a). Except for some heat energy provided by burning fuel (FSPb), all the energy demand is satisfied by the electric grid. Total energy from the grid is given as, 𝑆𝑃 𝐸𝑔𝑟𝑖𝑑 = 𝐸 + 𝐸𝑐 + 𝐸𝑝𝑆𝑃

(7)

where energy consumed by the chiller can be replaced by, 𝐸𝑐 =

𝑄𝑐 𝐶𝑂𝑃𝑒

(8)

The fuel energy used to provide ESP grid is, 𝐸 𝑆𝑃

𝐹𝑒𝑆𝑃 = 𝜂𝑆𝑃𝑔𝑟𝑖𝑑 𝜂 𝑒

𝑔𝑟𝑖𝑑

(9)

Optimal CCHP Combined with Thermal Energy Storage System 223 Similarly, the fuel energy used to provide Qh is, 𝐹𝑏𝑆𝑃 =

𝑄ℎ

(10)

𝜂𝑏𝑆𝑃 𝜂ℎ

Finally, the total fuel energy consumed is, 𝐸

𝐹 𝑆𝑃 = 𝜂𝑆𝑃 𝜂 𝑒

𝑔𝑟𝑖𝑑

𝐸 𝑆𝑃

+ 𝜂𝑆𝑃 𝜂𝑝 𝑒

𝑔𝑟𝑖𝑑

𝑄

+ 𝐶𝑂𝑃 .𝜂𝑆𝑃𝑐 .𝜂 𝑒

𝑒

𝑔𝑟𝑖𝑑

+

𝑄ℎ 𝑆𝑃 𝜂𝑏𝑆𝑃 .𝜂ℎ

(a)

(b) Figure 7. (a) SP system flow diagram. (b) CCHP system flow diagram [6].

(11)

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The schematic for a CCHP system is shown in Figure 7(b) The electrical energy balance yields the expression [7]. 𝐸𝑔𝑟𝑖𝑑 + 𝐸𝑝𝑔𝑢 = 𝐸 + 𝐸𝑝

(12)

The fuel energy consumed to provide 𝐸𝑝𝑔𝑢 𝑖𝑠 𝐹𝑝𝑔𝑢 =

𝐸𝑝𝑔𝑢 𝜂𝑒

(13)

The recovered waste heat is given as 𝑄𝑟 = 𝐹𝑝𝑔𝑢 𝜂𝑟𝑒𝑐 (1 − 𝜂𝑒 )

(14)

The heat balance equation between the cooling system and heating coil yields 𝑄𝑟 + 𝑄𝑏 = 𝑄𝑟𝑐 + 𝑄𝑟ℎ

(15)

The heat consumed by the cooling system and the heating coil is estimated as 𝑄

𝑄𝑟𝑐 = 𝐶𝑂𝑃𝑐

𝑐ℎ

𝑄𝑟ℎ =

𝑄ℎ 𝜂ℎ

(16) (17)

The additional fuel energy that the auxiliary boiler uses is given as 𝐹𝑏 =

𝑄𝑟𝑐 +𝑄𝑟ℎ −𝑄𝑟 𝜂𝑏

(18)

Finally, the total fuel energy consumed is 𝐹 = 𝐹𝑝𝑔𝑢 + 𝐹𝑏

(19)

Optimal CCHP Combined with Thermal Energy Storage System 225 For the EDM operation strategy, Egrid = 0 is substituted in the above equations as all the electric requirement is fulfilled by the CCHP system. Similarly, for the TDM operation strategy, Qb = 0 as no heat is required from the boiler [9].

Performance Factors In order to quantify the benefits achieved by the CCHP system over the separated production (SP) system, the energy efficiency criteria described in this Chapter are not enough. Therefore, additional performance criteria have been formulated as follows [16]: Energy Savings: Primary Energy Savings (PES) is the ratio of energy saved by the CCHP system in comparison with an SP system to the energy consumed by the SP system. 𝑃𝐸𝑆 =

𝐹 𝑆𝑃 −𝐹 𝐹 𝑆𝑃

𝐹

= 1 − 𝐹𝑆𝑃

(20)

where F is the fuel energy required by the CCHP system, PES is measured relative to a reference system. The primary energy ratio (PER) is a criterion with an absolute value. It is defined as the ratio of the energy demand to the fuel energy required to satisfy the demand [17]. 𝑃𝐸𝑅 =

𝐸+𝑄𝑐 +𝑄ℎ 𝐹

(21)

where E is the electricity demand, Qh is the heat energy demand, and Qc is the demand for cooling energy [18]. Exergy Efficiency: Exergy analysis is used to identify sources of irreversibility losses, both internal and external, to the system. The exergy of electricity, cooling and heating is defined respectively as, 𝐸𝑋𝑒 = 𝐸

(22) 𝑇0 𝑇𝑐

𝐸𝑋𝑐 = (

− 1) 𝑄𝑐

(23)

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Nima Norouzi and Maryam Fani 𝑇

𝐸𝑋ℎ = (1 − 𝑇0 ) 𝑄ℎ

(24)



where T0 is the ambient temperature, Tc and Th are the cold water and hot water temperatures, respectively. The exergy of fuel is given as [5], 𝐸𝑋𝑓 = 𝛾𝑓 𝑉𝑓 𝐻𝐻𝑉𝑓 = 𝛾𝑓 𝑉𝑓 𝑅𝑓 𝐿𝐻𝑉𝑓 = 1.03𝐹

(25)

Where γf denotes the exergy grade function for the fuel, defined as the ratio of fuel chemical exergy to fuel higher heating value HHVf and Vf is the gas consumption. LHVf is the low heating value of gas, and Rf is the ratio of HHVf to LHVf. For natural gas, the product of γf and Rf is 1.03 and VfLHVf is the same as F. [19] Based on the above definitions of component exergies, the exergy efficiency of the CCHP system is defined as [9], 𝜂𝑒𝑥 =

𝐸𝑋𝑒 +𝐸𝑋𝑐 +𝐸𝑋ℎ 𝐸𝑋𝑓

(26)

CO2 Emission Reduction (CO2ER): The amount of CO2 emission (CO2E) from the system can be determined using the emission conversion factor of fuel as, 𝐶𝑂2𝐸 = µ𝐶𝑂2,𝑔 𝐹 + µ𝐶𝑂2,𝑒 𝐸𝑔𝑟𝑖𝑑

(27)

where µCO2,g, and µCO2,e are the CO2 emission conversion factors for gas and electricity from the grid (Egrid). In comparison to the SP system, CO2 emission reduction CO2 ER by using CCHP is defined as, 𝐶𝑂2 𝐸𝑅 =

𝐶𝑂2 𝐸 𝑆𝑃 −𝐶𝑂2 𝐸 𝐶𝑂2 𝐸 𝑆𝑃

𝐶𝑂2 𝐸 𝑆𝑃 2𝐸

= 1 − 𝐶𝑂

(28)

CO2ER shows the environmental benefits achieved by the use of a CCHP system over an SP system [21].

Optimal CCHP Combined with Thermal Energy Storage System 227 Annual Total Cost Saving (ATCS): Here to the performance of the CCHP system is compared to a reference SP system. The annual total cost is a sum of the capital cost of the equipment (Ce) and the energy charge (Cm). The equations are defined as [6], 𝐴𝑇𝐶 = 𝐶𝑒 + 𝐶𝑚 𝐴𝑇𝐶𝑆 =

𝐴𝑇𝐶 𝑆𝑃 −𝐴𝑇𝐶 𝐴𝑇𝐶 𝑆𝑃

(29) (30)

Performance and Optimal Point Modeling In this study, the objective function is defined based on maximizing revenue or minimizing the cost of a cogeneration system concerning the ability of electricity exchange with the grid and the possibility of storing and retrieving heat energy in the tank. The objective function consists of two parts: income and cost. Proceeds from the sale of electricity to the grid: 𝐽1 = ∑𝑡𝜖𝑇 𝑃𝐸𝑙,𝑠𝑒𝑙𝑙 (𝑡)𝑃𝑟𝑖𝑐𝑒(𝑡)

(31)

In this study, it is assumed that the cogeneration system has several independent (U) units, and each unit is capable of consuming various fuels such as natural gas, furnace oil, diesel, etc. Costs include fuel costs for cogeneration units and the cost of electricity purchased from the grid. Cost of fuel for cogeneration units: 𝐽2 = ∑𝑡𝜖𝑇 ∑𝑢𝜖𝑈 ∑𝑟𝜖𝑅 𝐶𝑜𝑠𝑡𝑟 𝑃𝑟,𝑢 (𝑡)

(32)

Cost of purchased electricity: 𝐽3 = ∑𝑡𝜖𝑇 𝑃𝐸𝑙,𝐵𝑢𝑦 (𝑡)𝐶𝑜𝑠𝑡𝑒 (𝑡) Cost of alternative-burner Fuel:

(33)

228

Nima Norouzi and Maryam Fani 𝑠𝑖𝑔𝑛(𝑃𝑡ℎ −∑𝑢𝜖𝑈 𝑄𝑢 (𝑡))+1 )} ∗ 2

𝐽4 = ∑𝑟𝜖𝑅 ∑𝑡𝜖𝑇 {[𝑃𝑡ℎ − ∑𝑢𝜖𝑈 𝑄𝑢 (𝑡)] ∗ ( 𝐶𝑜𝑠𝑡𝑟 )

(34)

The cost of turning off each unit of cogeneration system: 𝐽5 = ∑𝑡𝜖𝑇 ∑𝑢𝜖𝑈 𝐶𝑜𝑠𝑡𝑠,𝑢 ∗ 𝐼𝑢

(35)

Finally, the objective function, which consists of all revenues and expenses, is given below. 𝐽 = 𝑀𝑎𝑥{𝐽1 + 𝐽2 − 𝐽3 − 𝐽4 − 𝐽5 }

(36)

System Constraints 

Provision for the complete supply of electric and heat loads

Because all the electrical and heat energy needed must be supplied. The relevant constraint is as follows. 𝑃𝑒,𝑑𝑒𝑚𝑎𝑛𝑑 = 𝑃𝑒,𝑐𝑜 − 𝑃𝐸𝑙,𝑠𝑒𝑙𝑙 + 𝑃𝐸𝑙,𝑏𝑢𝑦

(37)

𝑃𝑄,𝑑𝑒𝑚𝑎𝑛𝑑 = 𝑃𝑄,𝑐𝑜 − 𝑃𝑄,𝐵 + 𝑃𝑄,𝑇

(38)



Capacity Generation Limit

The electrical and thermal power produced by the cogeneration system has limitations that are considered inequalities in optimization. 𝑃𝑒𝑖,𝑚𝑖𝑛 < 𝑃𝑒𝑖,𝑐𝑜 < 𝑃𝑒𝑖,𝑚𝑎𝑥

(39)

𝑃𝑄𝑖,𝑚𝑖𝑛 < 𝑃𝑄𝑖,𝑐𝑜 < 𝑃𝑄𝑖,𝑚𝑎𝑥

(40)

Optimal CCHP Combined with Thermal Energy Storage System 229 The efficiency of the cogeneration system, in addition to the above inequality, also includes zero, which represents the system’s exit from the consumption grid. As the system enters and exits, the startup cost and system exit will also be considered in the objective function. 

Fluid Tank Limitations

The hot fluid reservoir has a temperature and pressure limit. If the fluid is liquid, the fluid temperature must always be within a certain range. If the fluid is a vapor in addition to temperature, the vapor pressure will be a limiting factor. 𝑃𝑇,𝑚𝑖𝑛 < 𝑃𝑇 < 𝑃𝑇,𝑚𝑎𝑥

(41)

𝑇𝑇,𝑚𝑖𝑛 < 𝑇𝑇 < 𝑇𝑇,𝑚𝑎𝑥

(42)

If the tank temperature drops below the minimum TT, min, the auxiliary boiler is switched on and increases the tank temperature to a certain T T, b, and then switches off. If the reservoir temperature exceeds the maximum value, the heat recovery from the converter is stopped, and the exhaust gases enter the environment directly [20].

IMPLEMENTATION METHOD In the next step, different steps of the genetic algorithm are implemented to determine the optimal working point of the cogeneration system. As mentioned in the introduction, the cost function is discrete, nonlinear, and indivisible, and according to the specific features of the genetic algorithm mentioned below, the genetic algorithm is used. Generally, programming and implementation of optimization are relatively more straightforward, and by applying different methods of chromosome coding, the problem can be reduced. The algorithm has relatively good convergence speed, lower side computation, the ability to find the absolute

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optimum, and local optimum points can also be found by limiting the initial generation.

GA Modelling The first step in the genetic algorithm is the search space coding. The interfaces of each of the units of the cogeneration systems constitute the search space. Thus, each chromosome contains information about the output power of each unit of the co-production system. The coding of the search space is done according to the following relation [21]. 𝑆𝑡𝑒𝑝 =

𝑃𝑒𝑖,𝑚𝑎𝑥 −𝑃𝑒𝑖,𝑚𝑖𝑛 2𝑁 −2

(43)

where N is the number of genes per chromosome. The interval is divided between the minimum and maximum amount of power output per unit. Based on the above relation, the power output is coded and decoded as relationships [18]. 𝑃𝑒𝑖 = 𝑃𝑒𝑖,𝑚𝑖𝑛 + 𝑛𝑖 ∗ 𝑆𝑡𝑒𝑝

(44)

where ni is rounded to the nearest integer, then the power output changes of each unit in steps of one-step length is the binary value of ni, which is considered as the values of the chromosomes. The advantage of this method is that new generations always remain within the permitted range of each generator, and there is no need to modify the new generation. The only exception to the coding is the power of zero (shutdown of a system), which is modeled as a chromosome with zero values [19].

Calculate the Fit Function Since the genetic algorithm of the selected chromosomes must have high fitness, therefore, the fitness rate is considered to be the objective function inverse. Since the values of the objective function can be positive or negative, they are subtracted from the number M always to be positive [12].

Optimal CCHP Combined with Thermal Energy Storage System 231 1

𝐹𝑢𝑛𝑐𝑡𝑖𝑜𝑛𝐹𝑖𝑡𝑛𝑒𝑠𝑠 = 𝑀−𝑜𝑏𝑗.𝑓

(45)

In some cases, especially in systems that have similar units, working in the absolute optimum may require significant variations in the power output of each unit. For example, the power changes of each unit in a system that has two generating units can be modified as follows. Table 3. The Example initial points PL 5 5.2

P1 3 1.5

P2 2 3.7

example 1 2

For such a system to operate at absolute optimum, it is necessary to reduce the power of the first unit from 1.5 MW to 3 MW and increase the power of the second unit from 2 MW to 37 MW. One can find a local optimum for the new load by limiting the search space to the neighborhood of the first task. If the cost difference between the two points is negligible, the local optimal point can be selected as the new work point. Changes in the power output of each unit can also be considered as a penalty factor in the fitness calculations [17]. ∑𝑖𝜖𝑈(𝑃𝑖 −𝑃𝑖′ )

𝑃𝑒𝑛𝑎𝑙𝑡𝑦𝑓𝑎𝑐𝑡𝑜𝑟 = 𝑘(

2

(𝑃𝐿 −𝑃𝐿′ )

2

)

(46)

k is the constant P’i and P’L, respectively, the output of unit i and the electrical power required. In this case, the fitness function changes as follows [21]. 1

𝐹𝑢𝑛𝑐𝑡𝑖𝑜𝑛𝐹𝑖𝑡𝑛𝑒𝑠𝑠 = 𝐴−𝑜𝑏𝑗.𝑓+𝑃𝑒𝑛𝑎𝑙𝑡𝑦𝑓𝑎𝑐𝑡𝑜𝑟

(47)

In this case, the optimum operating point will be close to the current operating point to be selected for priority. In each generation, after decoding the chromosomes, the value of the target function is determined, and consequently, the amount of fitness for each chromosome is

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calculated. Following the application of genetic operators to the current generation, a new generation will be produced. Here, two active and passive methods are employed to stop the algorithm [22].

CASE STUDY Appendix 1 provides information on a cogeneration system. With the above method, the optimal working point of this system is determined at different times. The amount of electricity and heat required and the amount of electricity and heat produced by the cogeneration system for load consumption in temperate and warm seasons are shown in Figures (8) (10).

Figure 8. Electricity demand vs. system’s production in the mild seasons.

Figure 9. Heat demand vs. system’s production in the mild seasons.

Optimal CCHP Combined with Thermal Energy Storage System 233

Figure 10. CCHP fuel cost vs. conventional system fuel cost in the mild seasons.

In temperate seasons, due to the equilibrium amount of electrical and heat energy, the heat generated by the cogeneration system is not produced except in peak load times. As shown in Figures (8) and (9), in the temperate seasons, the system is switched off during the early hours (1-6) and the electrical and thermal energy production is equal to zero [23]. From 7 am to 13 pm, the cogeneration system supplies more than half of the electrical and heat loads, and from then until 22 pm, it supplies all electrical loads and simultaneously all heat loads due to high electricity rates. It can be seen in Figure 6 that at the end of the 24 hours, the total cost of the cogeneration system is approximately 50% lower than that of the conventional production system.

Figure 11. Electricity demand vs. system’s production in the summer season.

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Figure 12. Heat demand vs. system’s production in the summer season.

Figure 13. CCHP fuel cost vs. conventional system fuel cost in the summer season.

Figure 14. Electricity demand vs. system’s production (Absorption chiller) in the summer season.

Optimal CCHP Combined with Thermal Energy Storage System 235

Figure 15. Heat demand vs. system’s production (Absorption chiller) in the summer season.

Figure 16. CCHP (absorption chiller) fuel cost vs. conventional system fuel cost in the summer season.

A comparison of the performance of the systems during the summer is shown in Figures (11) - (13). As can be seen, the optimum operating time for the cogeneration system is from 13 to 22 hours, which fulfills all the electrical energy needs, saves a great deal of heat generated, and operates the conventional system during the rest of the time [24]. It is done. Finally, during the summer, it can be seen from Figure 13 that the total cost of the cogeneration system, such as the temperate seasons, is approximately 50% lower than that of the conventional production system. In the summer, as the temperature rises, and as a result of the increase in cold requirements, the amount of electricity needed increases. Increasing the electric charge and decreasing the heat charge increase the PHR ratio. More significant PHR Consumption than PHR generation generates additional heat energy,

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which is quite evident in Figure 16. In this case, due to the mismatch of production and the need for heat energy, the cogeneration system is more regarded as a local production system than the cogeneration system. Absorption chillers can also be used to meet the cold needs. Absorbing chillers use heat energy as input energy and do not require electricity. For the case study of the previous section, it is assumed that the cooling needs are met by an absorption chiller. In this case, the amount of electrical and heat energy required and the amount of electrical and heat energy produced by the co-generation system are shown in Figures (15) and (16). In this case, the ratio of electricity and heat load is more balanced, and the efficiency of the cogeneration system is increased compared to the previous state, and the heat energy loss is reduced compared to the previous state.

CONCLUSION In this study, it was shown that the efficiency and efficiency of cogeneration systems depended on the operating point of the system and the PHR of production and consumption. For optimal operation of coproduction systems, it is necessary to be as close as possible to PHR production and PHR consumption. The availability of an auxiliary boiler, especially in cases where the PHR of production is higher than the PHR of consumption and the system of co-generation with the electricity needed to produce the required heat energy, will significantly increase the efficiency of the co-generation system. Heat storage tank To avoid heat loss, in cases where surplus heat is generated on demand, it will increase the efficiency of the co-generation system. It has also been shown that absorption chillers are useful in balancing the electrical and heat loads and increasing the efficiency of the cogeneration system and reducing heat loss. The results of this study show that in Iran, cogeneration systems can be economically beneficial. If the tariffs for electricity and natural gas are increased and their subsidies reduced by the government, it can be expected that this type of operation can be exploited. Systems lead to the protection of national

Optimal CCHP Combined with Thermal Energy Storage System 237 reserves. In general, the optimum working point of co-generation systems with electrical efficiency above 25% and heat efficiency above 50% can be determined as follows.   

Complete supply of electricity through the city's electricity grid during off-hours. Complete supply of electricity through the cogeneration system at peak hours. Supply a fraction of the electrical load through the cogeneration system to provide all the required heat load.

APPENDIX 1 The mechanical efficiency of the turbine and the amount of heat recovered from the exhaust gases are considered as a quadratic function of the mechanical power produced by the turbine [4]. ℎ𝑡 = 𝑎𝑃2 + 𝑏𝑃 + 𝑐 𝑄 = 𝐴𝑃2 + 𝐵𝑃 + 𝐶 Table (4) gives the coefficients related to the efficiency function and the heat output of the turbine. Electricity tariffs at different times are based on the 2012 Tehran Regional Electricity Tariffs shown in Table (5). The price of natural gas is 0.04 $/m3 based on the National Iranian Gas Company tariff. Table 4. Turbine power coefficient [3] a 0.0051 A -0.0246

b 3.2293 B 3.1610

c 16.5098 C -5.3224

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Nima Norouzi and Maryam Fani Table 5. Energy Tariff [3]

Hour day Price ($/kwh)

1-7 0.01

7-14 0.03

14-20 0.09

20-24 0.03

REFERENCES [1]

[2]

[3]

[4]

[5]

[6]

[7]

[8]

Ming-Tong Tsay and Whei-Min Lin. “Application of evolutionary programming to optimal operation system under time-of-use rates.” Electrical Power and Energy System 32(2000)367-373. M. T. Tsay, W. M. Lin. “Interactive best-compromise approach for operation dispatch of cogeneration systems.” IEE, Proceeding online No.20010163. S. Ashok and Rangan Banerjee. “Optimal operation of industrial cogeneration for load management.” IEEE Transaction on power systems. Vol. 18, No. 2, MAY 2003. Eva Thorin, Heike Brand, Christoph Weber, “Long-term optimization of cogeneration systems in a competitive market environment”. Applied Energy 81 (2005) 152-169. C. Maifredi, L. Puzzi, G. P. Beretta, “optimal power production scheduling in a complex cogeneration system with heat storage”. IEEE 2000-2978. Per J. Agrell, Peter Bogetoft “Economic and environmental efficiency of district heating plants.” Energy Policy 33 (2005) 1351– 1362. Dries Haeseldonckx, Leen Peeters, Lieve Helsen, William D’haeseleer “The impact of thermal storage on the operational behaviour of residential CHP facilities and the overall CO2 emissions.” Renewable and Sustainable Energy Reviews. 2005. Afzal S. Siddiqui; Chris Marnay; Ryan M. Firestone; and Nan Zhou “Distributed Generation with Heat Recovery and Storage.” Journal of Energy Engineering, 133.

Optimal CCHP Combined with Thermal Energy Storage System 239 [9]

[10]

[11]

[12]

[13]

[14]

[15]

Maryam Fani, Amirhassan Sadreddin, Solar assisted CCHP system, energetic, economic and environmental analysis, case study: Educational office buildings, Energy and Buildings, Volume 136, 2017, Pages 100-109, ISSN 0378-7788. Amirhassan Sadreddini, Maryam Fani, Muhammadali Ashjari Aghdam, Amin Mohammadi, Exergy analysis and optimization of a CCHP system composed of compressed air energy storage system and ORC cycle, Energy Conversion and Management, Volume 157, 2018, Pages 111-122, ISSN 0196-8904. Xi Chen, Haowei Zhou, Zhengkun Yu, Wenbin Li, Jian Tang, Chunwen Xu, Yuejiao Ding, Zhongmin Wan, Thermodynamic and economic assessment of a PEMFC-based micro-CCHP system integrated with geothermal-assisted methanol reforming, International Journal of Hydrogen Energy, Volume 45, Issue 1, 2020, Pages 958-971, ISSN 0360-3199. Zhihui Song, Tao Liu, Yanju Liu, Xuedan Jiang, Qizhao Lin, Study on the optimization and sensitivity analysis of CCHP systems for industrial park facilities, International Journal of Electrical Power & Energy Systems, Volume 120, 2020, 105984, ISSN 0142-0615. Huailiang You, Jitian Han, Yang Liu, Conventional and advanced exergoeconomic assessments of a CCHP and MED system based on solid oxide fuel cell and micro gas turbine, International Journal of Hydrogen Energy, 2020, ISSN 0360-3199. Hossein Nami, Ahmad Arabkoohsar, Amjad Anvari-Moghaddam, Thermodynamic and sustainability analysis of a municipal wastedriven combined cooling, heating and power (CCHP) plant, Energy Conversion and Management, Volume 201, 2019, 112158, ISSN 0196-8904. Mahmood Chahartaghi, Mohammad Sheykhi, Energy, environmental and economic evaluations of a CCHP system driven by Stirling engine with helium and hydrogen as working gases, Energy, Volume 174, 2019, Pages 1251-1266, ISSN 0360-5442.

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[16] Sayyed Faridoddin Afzali, Vladimir Mahalec, Novel performance curves to determine optimal operation of CCHP systems, Applied Energy, Volume 226, 2018, Pages 1009-1036, ISSN 0306-2619. [17] Jinming Jiang, Weijun Gao, Xindong Wei, Yanxue Li, Soichiro Kuroki, Reliability and cost analysis of the redundant design of a combined cooling, heating and power (CCHP) system, Energy Conversion and Management, Volume 199, 2019, 111988, ISSN 0196-8904. [18] Peiyu Chen, Yu Lan, Dan Wang, Weiliang Wang, Weikang Liu, Zhiqiang Chong, Xudong Wang, Optimal Planning and Operation of CCHP System Considering Renewable Energy Integration and Seawater Desalination, Energy Procedia, Volume 158, 2019, Pages 6490-6495, ISSN 1876-6102. [19] Di Wu, Jifeng Zuo, Zhijian Liu, Zhonghe Han, Yulong Zhang, Qiaomei Wang, Peng Li, Thermodynamic analyses and optimization of a novel CCHP system integrated organic Rankine cycle and solar thermal utilization, Energy Conversion and Management, Volume 196, 2019, Pages 453-466, ISSN 0196-8904. [20] Lejun Feng, Xiaoye Dai, Junrong Mo, Lin Shi, Performance assessment of CCHP systems with different cooling supply modes and operation strategies, Energy Conversion and Management, Volume 192, 2019, Pages 188-201, ISSN 0196-8904. [21] Mehdi Mehrpooya, Milad Sadeghzadeh, Ali Rahimi, Mohammadhosein Pouriman, Technical performance analysis of a combined cooling heating and power (CCHP) system based on solid oxide fuel cell (SOFC) technology – A building application, Energy Conversion and Management, Volume 198, 2019, 111767, ISSN 0196-8904. [22] Tao Zhang, Minli Wang, Peihong Wang, Jiangqi Gu, Weidong Zheng, Yihua Dong, Bi-stage stochastic model for optimal capacity and electric cooling ratio of CCHPs—a case study for a hotel, Energy and Buildings, Volume 194, 2019, Pages 113-122, ISSN 0378-7788.

Optimal CCHP Combined with Thermal Energy Storage System 241 [23] Haosheng Lin, Changzhi Yang, Xiaoqin Xu, A new optimization model of CCHP system based on genetic algorithm, Sustainable Cities and Society, Volume 52, 2020, 101811, ISSN 2210-6707. [24] Yang Liu, Jitian Han, Huailiang You, Exergoeconomic analysis and multi-objective optimization of a CCHP system based on LNG cold energy utilization and flue gas waste heat recovery with CO2 capture, Energy, Volume 190, 2020, 116201, ISSN0360-5442.

In: Energy Storage Systems: An Introduction ISBN: 978-1-53618-873-8 Editor: Satyender Singh © 2021 Nova Science Publishers, Inc.

Chapter 6

NATURAL CONVECTION GRAIN DRYER Dhananjay Kumar1,*, Pinakeswar Mahanta1,2 and Pankaj Kalita3 1

Department of Mechanical Engineering, Indian Institute of Technology Guwahati, Guwahati, India 2 Department of Mechanical Engineering, National Institute of Technology Arunachal Pradesh, Itanagar, India 3 Centre for Energy, Indian Institute of Technology Guwahati, Guwahati, India

ABSTRACT In the present study, non-dimensional numbers and heat transfer coefficient analysis were performed for the conical furnace in a natural convection crop dryer. In this study, biomass is burnt for three hours at the rate of 1.6 kg/h in the conical furnace. The study was performed in the rectangular chamber for two cases; (i) without sensible heat storage medium (pebbles), and (ii) with sensible heat storage medium. Grashof number ( Gr ), Rayleigh number ( Ra ), Nusselt number ( Nu ), and heat transfer coefficient ( h ) have been evaluated for the conical furnace in the *

Corresponding Author’s Email: [email protected]

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Dhananjay Kumar, Pinakeswar Mahanta and Pankaj Kalita rectangular chamber. The variations of all parameters were analyzed in the present study. The value of Grashof number and Rayleigh number were obtained in the range of 3.2 × 1073.73 × 109 and 2.24 × 107 2.61 × 109 for the caseI and 3.95 × 1084.83 × 109 and 2.77 × 108 3.39 × 109 for the caseII, respectively. The value of Nusselt number and heat transfer coefficient were obtained in the range of 28.19137.66 and 1.768.61W/m2 K for the caseI and 65.12150.1 and 4.079.39 W/m2 K for the caseII, respectively. The average value of the heat transfer coefficients was obtained as 5.69 W/m2 and 7.74 W/m2, respectively.

Keywords: biomass, Grashof number, Rayleigh number, Nusselt number, heat transfer coefficient

INTRODUCTION Nowadays the major problem faced by mankind is, the balance of food production and consumption in the day by day increasing population of the world. From the studies, it is found that 10% to 40% of food loss occurs due to various reasons in the developing countries like India. Preservation of food and agricultural products is important for food security and safety. In India, open sun drying is the most commonly used drying process in the village for drying agricultural products. Bala and Wood [1] performed the simulation of an indirect type natural convection solar for the rough rice drying process. The temperature along the collector was described by a numerical solution. The drying of the grain was described by the introduction of the deep-bed solution procedure. Due to variation in temperature of the collector and across the air bed thermal buoyancy effect was observed. It was observed that the over-drying takes place in a bottom layer hence continuous mixing is essential. Bena and Fuller [2] studied the natural convection dryer with biomass back-up heater. A direct-type natural convection solar dryer and a simple biomass dryer were combined to demonstrate a drying technology. This dryer is suitable for small scale processors of dry fruits and vegetables in non-electrified areas of developing countries. The overall drying efficiency of the unit was found to be 9%. During the same trial, the drying efficiency of the solar dryer

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alone was found to be 22% and the burner alone was 27%. Pangavhane et al. [3] studied the design development and performance testing of a natural convection solar dryer. The thermal performance of the solar air heater and the drying chamber were evaluated for the natural convection mode under no-load conditions and the complete solar drying unit was also tested under grape load conditions. It was found that the daily mean efficiency of the solar air collector varies from 48% to 56% during the experimentation. Prasad and Vijay [4] performed the experimental study on drying of ginger, turmeric, and Guduchi. An integral type of natural convection solar dryer has been developed and coupled with a biomass stove. Drying of these products had also been studied under solar drying only and open sun in the same climatic conditions. The results indicate that for all the products, drying was faster in hybrid. Kumar et al. [5] performed the thermodynamic analysis of a natural convection dryer. In this study, energy loss through the rectangular chamber and in the flue gas through the exhaust pipe was analyzed. A huge amount of energy lost through the exhaust pipe was observed. Jain and Tewari [6] studied the performance of indirect through pass natural convective solar crop dryer with phase change thermal energy storage. The system works in such a manner that the (PCM) stores the thermal energy during sunshine hours and releases after sunset. The thermal efficiency of the dryer was found to be 28.2%. Kumar et al. [7] performed the energy and exergy analysis of a natural convection dryer and found that the sensible energy storage material reduces the exergy destruction in the rectangular chamber. Sekyere et al. [8] studied the experimental investigation of the drying characteristics of a mixed-mode natural convection solar crop dryer with a backup heater. In this study, a mixed-mode natural convection solar crop dryer with a backup heater was designed and constructed from locally available materials and used to dry freshly prepared pineapples. Syahrul et al. [9] studied the quality drying of the products with the help of energy and exergy analysis of the fluidized bed dryer. Midilli and Kucuk [10] analyzed the energy and exergy of the drying process of shelled and unshelled pistachios using a solar drying

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cabinet. Energy analysis was carried to estimate the amounts of energy gained from solar air collectors and the ratios of energy utilization. In the present study, non-dimensional number analysis has been performed to evaluate the heat transfer coefficient for the conical furnace in the rectangular chamber of the natural convection biomass operated dryer.

MATERIALS AND METHODS In the present paper, study is performed for a natural convection dryer consists of a rectangular chamber (brick wall) 1.25 × 0.95 × 0.9 m, conical furnace (MS) 0.6 × 0.3 × 0.68 m, exhaust pipe (MS) 0.635 m diameter, paraffin wax tray (MS), drying chamber, drying tray (MS wire mesh), biomass feeding pipe (MS) 0.1 m diameter etc. as shown in the Figure 1. In the present study, performance analysis in the rectangular chamber below the paraffin wax tray has been done for two cases; (i) there is no sensible heat storage material present in the rectangular chamber, and (ii) sensible heat storage materials are present in the rectangular chamber. For the proper analysis, this rectangular chamber is divided into four sections and 20 J-type thermocouples are kept at each section in the rectangular chamber for the temperature measurement with the help of a data acquisition system. For rectangular wall temperature measurement, a laser light temperature sensor (temperature gun) is used. In this study, biomass is burnt in the conical furnace to generate heat. The biomass feeding rate for this study is 1.6 kg/h for three hours. Due to heat generation in the furnace, the surface of the conical furnace gets heated-up, surrounding air/pebbles in the chamber which is in contact with the furnace gain heat from the furnace outer surface. Due to buoyancy force, hot air from the rectangular chamber flows into the drying chamber through the cylindrical tubes in the paraffin wax tray and it melts the paraffin wax in the tray after melting, paraffin wax supply uniform heat in the drying chamber for the drying of food/agricultural products. Schematic representation of the natural convection dryer is shown in Figure 1.

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(1) Fresh air enters into the furnace (2) Conical furnace (3) Exhaust pipe (4) Biomass feeding pipe (5) Ambient air enters into the rectangular chamber (6) Rectangular chamber (7) Paraffin wax tray (8) Drying chamber (9) Drying tray (10) Cover plate. Figure 1. Schematic of the Experimental setup (all dimensions are in meter).

THEORETICAL ANALYSIS Non-dimensional number evaluation such as Gr, Pr, Ra, and Nu is the most important parameter to find the heat transfer coefficient for the natural convection heat transfer. Grashof number (Gr) for the furnace and the brick wall is written as in Eq. (1) [11]:

Gr 

g    T  L3

2

(1)

248

Dhananjay Kumar, Pinakeswar Mahanta and Pankaj Kalita Prandtl number (Pr) can be calculated by using the Eq. (2):

Pr 

  cp

(2)

k

Rayleigh number (Ra) can be calculated by using Eq. (3):

Ra  Gr  Pr

(3)

Nusselt number (Nu) for the natural convection can be written as in Eq. (4) for 10  Ra  10 [12]: 9

13

Nu  0.10  Ra0.333

(4)

Convective heat transfer coefficient (h) for the furnace outer surface and the rectangular chamber is calculated as in Eq. (5) [11]:

h

Nu  k L

(5)

EFFECT OF SENSIBLE HEAT STORAGE MATERIAL ON NON-DIMENSIONAL NUMBERS AND HEAT TRANSFER COEFFICIENT In the present study, subscripts 1 and 2 used for the cases (I&II) and all the data have been recorded at an interval of 30 minutes. In this paper, the study is performed for the furnace outer surface in the rectangular chamber. The variations in the Grashof number are shown in Figure 2. During the study, it is observed that the value of Grashof number is higher at the biomass burning period for both the cases. The cause of higher value

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of the Grashof number is the temperature difference between conical surface and rectangular chamber. From the study it can be seen that its value is relatively higher for the caseII. The maximum value of Grashof number was obtained as 3.73×109 and 4.83×109 for the cases (I&II), respectively. The variations in the Rayleigh number are shown in Figure 3. From the figure, it can be seen that the variations of the Rayleigh number are similar for both the cases and a relatively higher values of the Rayleigh number were obtained in the caseII during the experiment. From the results it can be seen that the value of Rayleigh number is relatively higher for both cases during the biomass burning period and decrease sharply when biomass burning stop. The cause of the higher value of the Rayleigh number is the higher values of the Grashof number during the biomass burning. The highest value of the Rayleigh numbers was obtained as 2.61×109 and 3.39×109 for the cases (I&II), respectively. Figure 4 shows the Nusselt number variations with time. From the Figure, it was observed that the variations in the Nusselt number are almost similar for both cases and relatively higher values of the Nusselt number were obtained in the caseII. A relatively higher value of the Nusselt numbers was obtained during the biomass burning period. The cause of the higher value of the Nusselt number is the higher values of the Rayleigh numbers during the biomass burning. The maximum value of the Nusselt numbers were obtained as 137.66 and 150.1 for the cases (I&II), respectively. The variations in the heat transfer coefficient for the cases (I&II) are shown in Figure 5. From the figure it can be seen that a relatively higher value of the heat transfer coefficient was obtained in the case-II. That means it can allow more heat to the rectangular chamber for the same energy input in the conical furnace. Hence, a relatively high amount of energy will utilize in the rectangular chamber in the case-II. The maximum value of heat transfer coefficients was obtained as 8.61 W/m2K and 9.39 W/m2K for the cases (I&II), respectively.

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Figure 2. Grashof number variations with time.

Figure 3. Rayleigh number variations with time.

Natural Convection Grain Dryer

Figure 4. Nusselt number variations with time.

Figure 5. The variations of heat transfer coefficients with time.

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CONCLUSION In the present work, non-dimensional numbers and heat transfer coefficient have been evaluated for the conical furnace in the rectangular chamber of the natural convection biomass operated grain dryer. From the study, it is observed that all the non-dimensional numbers and heat transfer coefficient varied in a similar trend for both the cases and relatively higher values are achieved in the case-II. Hence, using the sensible heat storage material in the rectangular chamber will enhance the performance of the natural convection dryer. It will reduce the biomass consumption for the drying process hence it is the better condition for the drying of agricultural product.

ACKNOWLEDGMENTS The authors express sincere gratitude to the Department of Mechanical Engineering, Indian Institute of Technology Guwahati for financial support to develop the experimental set-up.

REFERENCES [1] [2] [3]

[4]

Bala BK, Woods JL. Simulation of the indirect natural convection solar drying of rough rice. Solar Energy 1994;53:259–66. Bena B, Fuller RJ. Natural convection solar dryer with biomass backup heater. Solar Energy 2002;72:75–83. Pangavhane DR, Sawhney RL, Sarsavadia PN. Design, development and performance testing of a new natural convection solar dryer. Energy 2002;27:579–90. Prasad J, Vijay VK. Experimental studies on drying of Zingiber officinale, Curcuma longa l. and Tinospora cordifolia in solarbiomass hybrid drier. Renewable Energy 2005;30:2097–109.

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Kumar D, Mahanta P, Kalita P. Thermodynamic analysis of a natural convection dryer. In: Yengkhom Disco Singh, Helen Soibam PH and BNH, editor. Post Harvest Technology and Value Addition. Vol-1, Iss, The Dean, College of Hoticulture & Forestry, Central Agricultural University, Pasighat-791102, Arunachal Pradesh.; 2019, p. 156–61. [6] Jain D, Tewari P. Performance of indirect through pass natural convective solar crop dryer with phase change thermal energy storage. Renewable Energy 2015;80:244–50. [7] Kumar D, Mahanta P, Kalita P. Energy and exergy analysis of a natural convection dryer with and without sensible heat storage medium. Journal of Energy Storage 2020;29. [8] Sekyere CKK, Forson FK, Adam FW. Experimental investigation of the drying characteristics of a mixed mode natural convection solar crop dryer with back up heater. Renewable Energy 2016;92:532–42. [9] Syahrul S, Hamdullahpur F, Dincer I. Thermal analysis in fluidized bed drying of moist particles. Applied Thermal Engineering 2002; 22:1763–75. [10] Midilli A, Kucuk H. Energy and exergy analyses of solar drying process of pistachio. Energy 2003; 28:539–56. [11] Nag, PK, Heat and Mass Transfer. Third Edit. New Delhi: McGraw Hill Education (India) Private Limited,; 2014. [12] Evangelisti L, Guattari C, Gori P, Bianchi F. Heat transfer study of external convective and radiative coefficients for building applications. Energy and Buildings 2017;151:429–38.

In: Energy Storage Systems: An Introduction ISBN: 978-1-53618-873-8 Editor: Satyender Singh © 2021 Nova Science Publishers, Inc.

Chapter 7

EXERGY ANALYSIS OF A NATURAL CONVECTION GRAIN DRYER Dhananjay Kumar1,*, Pinakeswar Mahanta1,2 and Pankaj Kalita3 1

Department of Mechanical Engineering, Indian Institute of Technology Guwahati, Guwahati, India 2 Department of Mechanical Engineering, National Institute of Technology Arunachal Pradesh, Itanagar, India 3 Centre for Energy, Indian Institute of Technology Guwahati, Guwahati, India

ABSTRACT Exergy analysis of an energy consumable system/dryer is essential. This analysis helps to optimize the energy consumption in the energy consumable system/dryer. Present work deals the exergy analysis of an

*

Corresponding Author’s Email: [email protected]

256

Dhananjay Kumar, Pinakeswar Mahanta and Pankaj Kalita indirect type of natural convection grain dryer. In the present study, exergy analysis has been done for four sections in the rectangular chamber below the paraffin wax tray. The study is performed for two cases: (I) without sensible heat storage material (pebbles) and (II) with sensible heat storage material. In this study, biomass (lebbeck) is burnt in the conical furnace at a rate of 1.6 kg/h for three hours. Sensible heat storage helps to control the exergy in the rectangular chamber and retain it for a longer period in the drying chamber for the drying process. The present study helps to reduce the exergy losses from the rectangular chamber. Results obtained from the present study shows that the exergy destruction in the corresponding sections of the rectangular chamber and exergy loss through the wall is less in the case-II. Hence, this study improves the performance of the dryer.

Keywords: biomass, natural convection, exergy analysis, Sensible heat storage, latent heat storage

INTRODUCTION Energy and exergy analysis of an energy consumable system is essential. At the current age, world is facing a scarcity of energy, energy resources are decreasing as we are fully dependent on natural resources. During this crucial time, energy and exergy analysis will help to optimize the energy consumption in the energy consumable system. Energy and exergy analysis of any power-producing plants/dryers is an alternative to reduce the energy consumption. This analysis will help to utilize most of the energy from the burnt biomass. Hence, this study is an attempt to reduce the wastage of available energy in the rectangular chamber. Ramadan et al. [1] reported the performance enhancement of a heat pump by utilizing the waste heat of drain water. This study enhances the coefficient of performance (COP) of the heat pump by 4 times the initial COP. Jouhara et al. [2] reported the experimental analysis of the waste heat recovery by using a heat exchanger pipe in the steel industry. This study performed in both laboratory and industry and a theoretical study was also

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performed parallelly and obtained a good agreement between experimental and theoretical study. Abuska et al. [3] studied the performance of a solar air heater with and without sensible heat storage and obtained a high performance in the case of sensible heat storage material. Senthil and Cheralathan [4] performed the experimental analysis of a solar air heater with phase change materials. This study was an attempt to improve the capacity of the solar air heater. Performance of the solar air heater was improved by varying flow rate of the heat transfer fluid through the solar receiver. Khadraoui et al. [5] investigated a solar air heater with and without latent heat storage material and observed that the use of energy storage retains hot air temperature above the ambient temperature for the whole night. Kumar et al. [6] performed the thermodynamic analysis of a natural convection dryer and found that the use of sensible thermal storage material reduces the energy losses from the chamber. Natarajan et al. [7] designed a solar dryer with sensible heat storage material and found that the thermal efficiency of the dryer with sensible heat storage was 2-3% higher as compared to without sensible heat storage. Singh and Sethi [8] designed a solar dryer integrated with mirror booster for the drying agricultural product and cooking. The designed dryer attains 15-20C higher air temperature than the ambient condition. Carapellucci [9] performed the thermodynamic analysis for the power generation from the woody crops. In this study, biomass drying was performed by utilizing waste heat from the plant. Energy recovery increases the efficiency of the plant by 25-30%. Kumar et al. [10] performed the energy and exergy analysis of a natural convection dryer and found that the temperature retain by the hot air in the rectangular chamber is higher and for the longer period in the case of sensible heat storage medium. In the literature, many researchers conducted the experimental study to analyse the performance of the sensible heat storage in the dryers with the help of exergy methodology. In the present paper, exergy losses through the rectangular brick wall and the exergy destruction in the corresponding section of the rectangular chamber below the paraffin wax tray have been

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performed. Hence, the exergy methodology has been used for the present study.

EXPERIMENTAL SET-UP AND PROCEDURE In the present paper, a natural convection dryer consist of rectangular chamber (brick wall) 125 cm × 95 cm × 90 𝑐𝑚, conical furnace (MS) 60 cm × 30 cm × 68 cm, exhaust pipe (MS) 6.35 cm diameter, paraffin wax tray (MS) 125 cm × 95 cm × 12 𝑐𝑚, drying chamber, drying tray (MS wire mesh), biomass feeding pipe (MS) 10 cm diameter, etc. as shown in the Figure 1. In this study, biomass is burnt in the conical furnace to generate heat. The biomass (lebbeck) feeding rate for this study is 1.6 kg/h for three hours. Due to heat generation in the furnace, the surface of the furnace gets heated-up, surrounding air/pebbles in the chamber which is in contact with the furnace gains heat from the furnace outer surface. Due to buoyancy force, hot air from the rectangular chamber flows into the drying chamber through the hollow tubes in the paraffin wax tray and after melting, paraffin wax supply uniform heat for the drying of agricultural products. And due to pressure difference, ambient air enters into the rectangular chamber through the holes at the bottom of the chamber. In the present study, exergy analysis in the rectangular chamber below the paraffin wax tray has been done for two cases; (i) there is no sensible heat storage material (pebbles) present in the rectangular chamber, and (ii) sensible heat storage material is present in the rectangular chamber. For the proper analysis, this study has been performed for four sections in the rectangular chamber and 20 J-type thermocouples are kept in each section in the chamber for the temperature measurement with the help of a data acquisition system. For rectangular wall temperature measurement, a laser light temperature sensor (temperature gun) is used.

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Figure 1. Schematic of the Experimental setup (all dimensions are in meter). (1) Fresh air enters into the furnace (2) Conical furnace (3) Exhaust pipe (4) Biomass feeding pipe (5) Ambient air enters into the rectangular chamber (6) Rectangular chamber (7) Paraffin wax tray (8) Drying chamber (9) Drying tray (10) Cover plate.

MATHEMATICAL MODEL For the negligible changes in K. E. and P. E. available energy (exergy) at the corresponding sections in the rectangular chamber can be calculated by using Eq. (1) [10, 11]:

Ex.   hi  h0   T0   si  s0 

(1)

where, Ex., h, T and s are the exergy, enthalpy, temperature and entropy respectively at the sections. The subscript i represent the corresponding sections and 0 represent the ambient condition. Exergy balance [10]:

Ex.in  Ex.out  Ex.loss  Ex.destruction

(2)

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Eq. (3) is used for the exergy destruction in the rectangular chamber [11]: 0  T  I   1  0 Q j   Ex.i  Ex.i 1   T  j  j 

(3)

where

 Vi 2  Vi 21  Ex.i  Ex.i 1   hi  hi 1   T0   si  si 1      g   zi  zi 1  2  

EFFECT OF SENSIBLE HEAT STORAGE MATERIAL ON THE EXERGY IN THE RECTANGULAR CHAMBER In the Results, subscript 1, 2, 3, 4 represent the corresponding sections in the rectangular chamber and w1, w2, w3, w4 represent the corresponding sections in the rectangular wall. Figures (2&3) represent the exergy curve of the hot air at the corresponding sections in the rectangular chamber for the cases (I&II). Figure 2 shows that the exergy variations of the hot air at the corresponding sections is higher at the period of biomass burning, once biomass burning stop, the exergy of hot air at the corresponding section in the chamber drops sharply. From Figure 3, it can be seen that the exergy at the corresponding sections is lesser for the burning period than that of the case-I but it retains for a longer time as compared to the case-I. Hence, the exergy retaining capability of the air in the case-II is higher. It has also been seen that the exergy at the fourth section in the case-II is relatively higher than that of the lower sections. That is because the sensible heat storage material captures heat from the hot air and retains it for further drying of the agricultural products.

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Figure 2. Exergy at the corresponding sections for case-I.

Figure 3. Exergy at the corresponding sections for case-II.

Figures (4&5) shows the exergy loss rate profile from the rectangular chamber to the ambient for the cases (I&II). From the curves, it is observed that the exergy loss rate through the corresponding sections of the

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rectangular brick wall is higher for the case-I as compared to the case-II. Hence from the results, it is clear that the sensible heat storage material (pebbles) reduces the exergy loss from the rectangular brick wall. Hence the use of sensible energy storage material improves the performance of the natural convection dryer. From Figure 5, it can be seen that the exergy loss through the rectangular chamber increases from bottom to top sections. That is because, pebbles at the lower sections release the stored energy and that released energy also received by the hot air. Due to buoyancy action, the hot air reaches to the upper section. This is the cause due to which energy at the upper section increases which leads to more exergy loss through the wall. Figures (6&7) shows the exergy destruction at the corresponding sections in the rectangular chamber for the cases (I&II). From the results, it is found that the exergy destruction in the corresponding sections is lower in the case-II. That is because the sensible heat storage material in the rectangular chamber controls the heat in an organized way. While in the case-I, heat is not properly controlled by the air and due to random motion of the hot air in the chamber, irreversibility increases, which is a cause of high exergy destruction in the rectangular chamber. From the study, it has been observed that a huge amount of exergy destruction is taking place in the case-I as compared to case-II.

CONCLUSION In the present study, it is observed that the use of sensible heat storage material reduces the exergy loss from the rectangular chamber (brick wall) and retains heat in the chamber for a longer time. It also reduces the exergy destruction in the rectangular chamber. Reducing the exergy destruction means improving the performance of the natural convection dryer. Hence, the use of sensible heat storage material will reduce the energy consumption in the food/agricultural products drying process. Hence, the case-II is a better drying condition for the agricultural products as compared to the case-I.

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Figure 4. Exergy loss rate through the wall from the corresponding sections for case-I.

Figure 5. Exergy loss rate through the wall from the corresponding sections for case-II.

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Figure 6. Exergy destruction at the corresponding sections for case-I.

Figure 7. Exergy destruction at the corresponding sections for case-II.

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ACKNOWLEDGMENTS The authors express sincere gratitude to the Department of Mechanical Engineering, Indian Institute of Technology Guwahati for financial support to develop the experimental set-up.

REFERENCES [1]

[2]

[3]

[4]

[5]

[6]

M. Ramadan, R. Murr, M. Khaled, A. G. Olabi, Mixed numerical Experimental approach to enhance the heat pump performance by drain water heat recovery, Energy. 149 (2018) 1010-1021. H. Jouhara, S. Almahmoud, A. Chauhan, B. Delpech, G. Bianchi, S. A. Tassou, R. Llera, F. Lago, J. J. Arribas, Experimental and theoretical investigation of a flat heat pipe heat exchanger for waste heat recovery in the steel industry, Energy. 141 (2017) 1928-1939. M. Abuşka, S. Şevik, Energy, exergy, economic and environmental (4E) analyses of flat-plate and V-groove solar air collectors based on aluminium and copper, Solar Energy. 158 (2017) 259-277. R. Senthil, M. Cheralathan, Enhancement of the thermal energy storage capacity of a parabolic dish concentrated solar receiver using phase change materials, Journal of Energy Storage. 25 (2019) 100841. A. El Khadraoui, S. Bouadila, S. Kooli, A. Farhat, A. Guizani, Thermal behavior of indirect solar dryer: Nocturnal usage of solar air collector with PCM, Journal of Cleaner Production. 148 (2017) 3748. D. Kumar, P. Mahanta, P. Kalita, Thermodynamic analysis of a natural convection dryer, In: P. H. and B. N. H. Yengkhom Disco Singh, Helen Soibam (Ed.), Post Harvest Technology and Value Addition, Vol-1, Iss, The Dean, College of Hoticulture & Forestry, Central Agricultural University, Pasighat-791102, Arunachal Pradesh., 2019: pp. 156-61.

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K. Natarajan, S. S. Thokchom, T. N. Verma, P. Nashine, Convective solar drying of Vitis vinifera & Momordica charantia using thermal storage materials, Renewable Energy. 113 (2017) 1193-1200. [8] M. Singh, V. P. Sethi, On the design, modelling and analysis of multi-shelf inclined solar cooker-cum-dryer, Solar Energy. 162 (2018) 620-636. [9] R. Carapellucci, Power generation using dedicated woody crops: Thermodynamics and economics of integrated plants, Renewable Energy. 27 (2002) 143-159. [10] D. Kumar, P. Mahanta, P. Kalita, Energy and exergy analysis of a natural convection solar dryer, Energy and Exergy Analysis of a Natural Convection Dryer with and without Sensible Heat Storage Medium. 29 (2020). [11] P. K. Nag, Basic and Applied Thermodynamics, Second Edi, McGra Hill Education (India) Private Limited, New Delhi, 2013.

ABOUT THE EDITOR Dr. Satyender Singh Assistant Professor Department of Mechanical Engineering, Dr B R Ambedkar National Institute of Technology Jalandhar Dr. Satyender Singh is working as an assistant professor in the Department of Mechanical Engineering, Dr B R Ambedkar National Institute of Technology Jalandhar (INDIA). He obtained his Maters and PhD from NIT Hamirpur, India. He worked as a Post-Doctoral Fellow in CFD Lab, IIT Bombay (India). His area of research is "Experimental, analytical and CFD investigations of microfluidics devices using hydrophobic and superhydrophobic surfaces for pressure drop reduction and heat transfer enhancement; Thermal performance analysis of solar air heaters, Earth to air heat exchangers; Design and optimization of thermal systems; Energy conversion and thermal transport, and its applications in energy storage and heat transfer; Development of analytical and CFD solutions for single, Multiphase Flow and PCM; Technology for Rural Development". He has published more than 25 SCI research papers.

INDEX A abuse, 26, 38, 55, 70, 72, 85 acid, 30, 74, 89, 142, 156 acidic, 59, 75, 83 additives, 3, 21, 31, 58, 60, 69, 75, 76, 77, 79, 81, 82, 84, 117, 125 advancement(s), 1, 2, 54, 170, 186 air heater, 183, 184, 201, 202, 245, 257, 267 air temperature, 158, 188, 189, 191, 192, 257 algorithm, ix, 204, 205, 206, 216, 217, 218, 220, 229, 230, 232, 241 aluminium, 58, 171, 265 anodes, viii, 1, 2, 39, 40, 41, 42, 43, 45, 48, 50, 51, 53, 54, 56, 75, 81, 85, 107, 109, 111, 112, 114, 115, 116, 117, 124 assessment, 167, 239, 240 atmosphere, 91, 97, 122, 162 atoms, 6, 33, 38, 45, 67, 131

B base, 49, 148, 151, 153, 159, 201

batteries, vii, 1, 2, 3, 4, 8, 12, 14, 19, 26, 36, 40, 41, 44, 57, 58, 60, 63, 72, 73, 75, 76, 78, 85, 86, 87, 88, 89, 90, 91, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123,124, 125, 126, 127, 143, 150, 156, 163 Belgium, 132, 135, 208 biomass, 243, 244, 246, 247, 248, 252, 256, 257, 258, 259, 260 boilers, 204, 214, 215

C candidates, 51, 66, 217, 219 carbon, vii, 2, 4, 8, 14, 21, 22, 23, 27, 28, 30, 34, 35, 36, 37, 40, 42, 43, 44, 46, 49, 51, 52, 53, 79, 81, 87, 89, 96, 101, 102, 105, 106, 107, 108, 109, 113, 115, 117, 118, 123, 126, 134, 136, 140, 153, 155, 161, 163, 184 carbon nanotubes, 45, 96, 108, 109 case study, 236, 239, 240

270

Index

cathode materials, 23, 26, 33, 35, 85, 86, 87, 89, 91, 92, 93, 94, 96, 97, 98, 99, 101, 102, 103, 104, 106, 126 cathodes, viii, 1, 2, 4, 10, 11, 12, 18, 19, 20, 23, 25, 26, 28, 29, 31, 32, 33, 34, 35, 36, 37, 38, 39, 74, 76, 79, 80, 85, 86, 88, 89, 90, 91, 96, 97, 99, 100, 101, 102, 104, 105, 123 cation, 14, 15, 18, 20, 22, 24, 28, 32, 57, 58, 59, 61, 64, 73, 74, 105 CCHP, v, vii, 203, 204, 206, 210, 221, 223, 224, 225, 226, 227, 233, 234, 235, 239, 240, 241 CCS, 204 cell death, 21, 68, 77 ceramic(s), 65, 83, 84, 91, 160 challenges, viii, 2, 20, 111, 122, 156 charging-discharging, 170, 184, 185, 186 chemical, 2, 5, 6, 13, 14, 21, 33, 42, 48, 56, 57, 67, 72, 75, 77, 85, 96, 142, 143, 144, 165, 200, 226 chromosome, 219, 229, 230, 231 circulation, 130, 139, 150, 152, 153, 165 CNS system, 130 CO2, 65, 135, 207, 226, 238, 241 coal, 44, 108, 131, 134, 207 coatings, 21, 25, 77, 81, 90, 98, 99 cobalt, 14, 15, 16, 18, 19, 34, 80, 88, 89, 91, 103, 105, 124 cogeneration, 164, 203, 204, 205, 206, 213, 227, 228, 229, 230, 232, 233, 235, 236, 237, 238 combined conversion and storage, 204 combined nuclear and storage, 130, 137 combustion, 13, 15, 18, 20, 88, 89, 91, 99, 159, 160, 215, 216 commercial, viii, 2, 16, 19, 21, 40, 46, 58, 63, 67, 68, 69, 71, 73, 75, 143, 159, 172, 176, 199 communities, 5, 140, 143 composites, 46, 52, 53, 54, 60, 81, 82, 102, 106, 112, 113

composition, 21, 32, 54, 56, 65, 68, 82, 94, 95, 116, 124, 136, 140, 218 compounds, 3, 8, 20, 29, 31, 40, 42, 43, 46, 48, 52, 55, 59, 63, 76, 81, 82, 86, 93, 101, 104, 106, 185 computer, 196, 216, 217, 218 conduction, 55, 56, 64, 119, 120, 148, 171 conductivity, ix, 8, 14, 17, 20, 21, 23, 26, 27, 28, 30, 31, 34, 35, 36, 37, 39, 41, 45, 46, 53, 55, 57, 58, 59, 60, 63, 68, 75, 78, 79, 81, 82, 83, 84, 119, 120, 121, 122, 148, 169, 171, 178, 179, 180, 183, 185, 191, 200 conductor(s), 10, 63, 64, 119, 120, 121 configuration, 24, 50, 172, 191, 194, 212 construction, 131, 132, 133, 144, 185 consumers, 140, 141, 143 consumption, ix, 73, 144, 204, 209, 214, 226, 229, 232, 236, 244, 252, 256 conversion reaction, 48, 49, 111 cooling, 139, 143, 145, 158, 206, 209, 222, 224, 225, 236, 239, 240 copper, vii, 2, 8, 77, 171, 181, 265 correlation(s), 103, 107, 196 corrosion, 77, 123, 144 cost, 1, 11, 14, 18, 19, 23, 26, 38, 39, 40, 44, 55, 58, 65, 85, 122, 132, 133, 135, 136, 144, 153, 154, 155, 156, 157, 162, 163, 171, 204, 205, 206, 208, 215, 221, 227, 228, 229, 231, 233, 234, 235, 240 crop(s), 184, 200, 243, 245, 253, 257, 266 crystal structure, 12, 13, 73, 80, 97 crystalline, 13, 18, 33, 44, 84, 96, 97, 122 crystallinity, 14, 18, 79 cycles, 11, 13, 14, 17, 19, 21, 23, 28, 30, 34, 36, 37, 44, 46, 49, 52, 54, 59, 66, 70, 85, 158, 163 cycling, 1, 8, 11, 13, 14, 15, 16, 17, 18, 19, 21, 23, 25, 26, 28, 30, 31, 32, 33, 35, 37, 39, 40, 41, 43, 45, 49, 50, 52, 53, 55, 58, 60, 66, 69, 72, 73, 74, 75, 77, 78, 79, 81, 82, 84, 85, 93, 106, 117, 125

Index D decay, 21, 22, 29, 53, 61, 75, 76, 139, 147, 148, 165 decomposition, 25, 28, 30, 34, 37, 43, 55, 56, 57, 59, 74, 76, 78, 81, 84, 147, 148, 149 defects, 17, 44, 56, 101 deformation, 25, 46, 77, 85 degradation, 2, 13, 23, 24, 25, 28, 32, 33, 55, 72, 73, 74, 75, 76, 77, 116, 123, 147 degradation mechanism, 2, 74, 116 deposition, 35, 37, 75, 77, 78, 125 destruction, 49, 245, 256, 257, 260, 262, 264 diffusion, 26, 28, 30, 32, 34, 39, 64, 68, 78, 79, 80, 94, 113, 166, 197 disorder, 16, 17, 92, 155 distribution, 23, 70, 172, 173, 175, 178, 179, 190, 204, 205, 221 district heating, 208, 214, 238 dopants, 80, 81, 83 doping, 14, 15, 22, 25, 27, 30, 45, 46, 64, 80, 81, 82, 90, 95, 96, 102, 103 drying, 183, 192, 244, 245, 246, 252, 253, 256, 257, 258, 260, 262, 266

E electricity, viii, ix, 129, 130, 131, 132, 133, 135, 136, 145, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 203, 204, 205, 206, 207, 212, 213, 214, 221, 222, 225, 226, 227, 232, 233, 235, 236, 237 electrochemical behavior, 13, 16, 24, 25, 28, 30, 49, 80, 113, 115 electrochemistry, viii, 2, 88, 91, 93, 97, 98, 101, 103, 105, 108, 114, 118, 119, 123, 125, 126 electrode surface, 7, 74, 76, 78

271

electrodes, 3, 6, 8, 18, 21, 23, 27, 34, 39, 48, 49, 57, 60, 68, 69, 70, 76, 77, 83, 87, 92, 93, 94, 98, 99, 102, 105, 106, 109, 110, 113, 114, 115, 116, 123, 126 electrolyte(s), viii, 1, 2, 3, 6, 8, 9, 11, 13, 14, 16, 17, 21, 24, 25, 28, 30, 34, 35, 36, 37, 38, 39, 43, 55, 56, 57, 58, 59, 60, 63, 64, 68, 69, 70, 72, 73, 74, 75, 76, 77, 78, 79, 81, 82, 83, 84, 85, 86, 88, 95, 100, 105, 106, 107, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125 electron(s), 6, 10, 12, 29, 33, 34, 35, 72, 79, 92 emergency, 139, 150, 206 energy, vii, viii, ix, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 17, 19, 20, 21, 22, 25, 26, 27, 33, 34, 35, 36, 38, 39, 40, 41, 42, 46, 47, 49, 57, 64, 73, 78, 80, 85, 86, 87, 88, 90, 95, 113, 118, 129, 130, 131, 132, 133, 134, 135, 136, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 160, 162, 163, 164, 165, 166, 167, 169, 170, 171, 172, 173, 176, 181, 183, 184, 185, 187, 192, 193, 194, 195, 196, 199, 200, 203, 204, 205, 206, 207, 208, 209, 212, 213, 214, 221, 222, 223, 224, 225, 227, 228, 233, 235, 236, 239, 241, 245, 249, 255, 256, 257, 259, 262, 267 energy consumption, 155, 207, 209, 213, 255, 256, 262 energy density, 3, 4, 9, 10, 12, 19, 20, 21, 25, 26, 27, 33, 35, 36, 38, 39, 40, 46, 47, 57, 85, 87, 95, 136, 144 energy efficiency, 34, 141, 160, 187 energy supply, 133, 135, 136, 206, 207 engineering, 50, 81, 122 entropy, 5, 165, 166, 202, 210, 259 environment, 32, 38, 42, 134, 191, 229, 238 equilibrium, 5, 75, 147, 151, 175, 233 ethylene, 8, 36, 61, 76, 115, 117, 118, 124 evolution, 19, 28, 73, 141, 218, 220

272

Index

exergy analysis, 225, 239, 245, 253, 255, 256, 257, 258, 266 extraction, 13, 19, 23, 30, 77, 189

F factories, 154, 155, 208 fiber(s), 23, 28, 34, 35, 54, 102 financial, 86, 130, 252, 265 financial support, 86, 252, 265 fitness, 218, 221, 230, 231 flammability, 58, 59, 61, 64, 83 fluid, 149, 150, 166, 175, 176, 194, 196, 199, 206, 214, 215, 216, 229, 257 fluorine, 22, 32, 39, 76, 95, 96 food, 244, 246, 262 force, xi, 6, 7, 173, 246, 258 formation, 4, 13, 17, 25, 28, 33, 35, 36, 40, 43, 44, 46, 49, 51, 52, 53, 55, 60, 64, 70, 75, 76, 81, 82, 117 formula, 20, 30, 32, 217, 218 France, 132, 133, 135, 208 fuel consumption, 206, 213, 216, 221 fuel prices, 133, 206, 222 fusion, 144, 146, 147, 176, 185, 198, 200

G gel, 13, 49, 56, 61, 67, 83, 97, 118 geometry, 23, 70, 80, 172, 174, 179, 180 Germany, 133, 135, 208 glycol, 36, 61, 125 graphene sheet, 44, 75, 109 graphite, 1, 3, 4, 5, 8, 14, 20, 40, 42, 43, 44, 54, 74, 82, 85, 87, 88, 115, 116, 124, 130, 136, 139, 147, 150, 151, 153 Grashof number, 243, 244, 247, 248, 250

H halogen, 12, 33, 67 heat capacity, 141, 146, 171, 188, 195, 200 heat loss, 144, 199, 236 heat transfer, 139, 145, 148, 158, 171, 173, 175, 176, 188, 189, 192, 194, 195, 196, 197, 199, 243, 244, 246, 247, 248, 249, 251, 252, 257, 267 heat transfer coefficient, 188, 192, 196, 197, 199, 243, 244, 246, 247, 248, 249, 251, 252 height, 32, 136, 138 host, viii, 2, 10, 17, 42, 43, 46, 48, 49, 51, 53, 73 human, 134, 169, 170, 218 hybrid, 64, 118, 245, 252 hydrogen, 140, 160, 161, 164, 239 hydrothermal synthesis, 13, 16, 96, 100, 101

I improvements, 35, 85, 160, 185 income, 155, 160, 227 India, xii, 1, 86, 133, 169, 183, 184, 202, 208, 243, 244, 253, 255, 266, 267 industry/industries, 159, 170, 208, 256 insertion, 11, 12, 23, 31, 41, 42, 47, 48, 49, 51, 52, 74, 79, 82, 97, 98, 103, 108, 109, 110 integrity, 11, 73, 79 interface, 24, 37, 39, 43, 55, 58, 62, 74, 82, 123, 175, 176 interphase, 75, 115, 116, 117 ion transport, 55, 58, 62, 83, 84 ions, 3, 8, 12, 13, 23, 25, 30, 33, 43, 47, 55, 56, 59, 62, 64, 73, 74, 76, 78, 79, 83 Iran, 129, 203, 208, 236 iron, 16, 34, 101, 105, 106 issues, 19, 28, 34, 50, 54, 59, 67, 75, 85, 134, 135

Index K kinetics, 17, 30, 34, 38, 45, 55, 73, 76, 77, 85, 147, 148

L latent heat storage, vii, 142, 145, 169, 170, 180, 184, 189, 200, 256, 257 lead, 30, 130, 145, 156, 158, 173, 236 light, 172, 206, 246, 258 Li-ion battery, viii, 2, 5, 11, 12, 85, 88, 97, 104, 110 liquid phase, 146, 175, 199 liquids, 56, 59, 68, 117, 118 lithium, vii, viii, 2, 3, 4, 6, 8, 10, 15, 16, 19, 20, 21, 23, 24, 25, 26, 28, 29, 30, 35, 36, 38, 39, 42, 43, 44, 46, 48, 49, 50, 52, 53, 55, 58, 59, 60, 64, 70, 71, 72, 73, 75, 76, 78, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 94, 95, 96, 97, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 129, 130, 145, 149, 151, 156 lithium insertion, 42, 46, 48, 49, 52, 53, 73, 81, 82 lithium ion batteries, 88, 89, 103, 107, 108, 109, 110, 111, 117, 124

M magnesium, 22, 91, 96, 145 management, 78, 140, 180, 201, 221, 222, 238 manganese, vii, 2, 16, 18, 23, 24, 96, 97, 98, 107, 124 manufacturing, viii, 1, 5, 19, 69, 89, 209

273

mass, 7, 29, 39, 41, 46, 73, 76, 98, 138, 144, 146, 147, 149, 150, 151, 187, 189, 192, 193 materials, viii, 1, 5, 6, 9, 10, 14, 15, 16, 18, 23, 26, 28, 29, 31, 32, 33, 34, 39, 40, 42, 44, 46, 49, 50, 55, 56, 61, 68, 69, 74, 77, 79, 80, 82, 84, 85, 86, 88, 91, 95, 100, 101, 103, 105, 107, 108, 109, 110, 111, 112, 113, 114, 115, 118, 119, 122, 123, 141, 142, 143, 144, 145, 146, 149, 160, 164, 170, 181, 184, 185, 201, 245, 246, 257, 265, 266 matrix, viii, 2, 33, 42, 43, 45, 46, 48, 49, 51, 52, 57, 64, 73, 82, 102, 136, 178, 180, 181, 197 measurement, 118, 246, 258 media, vii, ix, 170, 171, 173, 175, 184, 200 melting, 3, 139, 142, 145, 149, 151, 158, 172, 175, 176, 177, 178, 180, 181, 185, 189, 190, 192, 199, 246, 258 melting temperature, 142, 145, 149, 190 metal ion, 12, 33, 83, 118 metal oxides, 3, 40, 42, 45, 46, 49, 81, 82, 115 metals, 2, 28, 46, 50, 52, 54, 65, 79, 80 methodology, 167, 202, 257 Mg2+, 22, 47, 64 migration, 23, 32, 64 mixing, 14, 15, 18, 19, 20, 50, 74, 203, 244 modelling, 172, 181, 266 models, 147, 152, 166, 173, 176, 184, 200 modifications, 45, 47, 56, 171 moisture, 16, 24, 65, 75 morphology, 18, 29, 36, 56, 79, 80, 89, 94, 99, 107, 116 mutation, 216, 218, 220

N nanocomposites, 30, 105, 126 nanometer(s), 25, 27, 43, 81, 99

274

Index

nanoparticles, 28, 34, 36, 80, 89, 98, 104, 112, 113 nanorods, 49, 92, 97, 111, 112 nanostructures, 45, 96, 107 nanotube, 44, 108, 115 nanowires, 47, 50, 105, 107 natural convection, ix, 173, 175, 191, 243, 244, 245, 246, 247, 248, 252, 253, 256, 257, 258, 262, 265, 266 natural gas, 153, 158, 160, 161, 162, 207, 215, 226, 227, 236, 237 NCA, 4, 19, 38, 80, 93 nickel, 18, 19, 34, 49, 91, 105, 124, 156, 171 nitrides, 49, 51, 66, 113 nitrogen, 45, 134, 216 NPS system, 130 nuclear power, viii, 129, 130, 131, 132, 133, 134, 135, 153, 158, 160, 163, 165, 167, 168 nuclear power and storage, 130 nuclear thermal storage, 130 Nusselt number, 243, 244, 248, 249, 251

O oil, 131, 136, 207, 216, 217, 227 operating costs, 133, 153, 154, 163 optimization, 89, 100, 144, 165, 166, 167, 191, 205, 216, 217, 220, 221, 222, 228, 229, 238, 239, 240, 241, 267 optimum design, 204 oxidation, 13, 18, 23, 24, 25, 39, 44, 48, 55, 72, 73, 74, 76, 77, 156 oxide electrodes, 49, 91, 96 oxygen, 13, 14, 20, 23, 32, 37, 38, 39, 48, 67, 73, 87, 98, 162

P parallel, 172, 180, 205

passivation, 21, 24, 36, 58, 74, 75 PCM, vii, ix, 142, 145, 169, 170, 171, 172, 173, 175, 178, 179, 180, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 197, 198, 199, 200, 201, 202, 245, 265, 267 permission, 12, 18, 22, 25, 27, 29, 35, 41, 53, 63 phosphate(s), 11, 26, 59, 101, 103, 119 phosphorus, 45, 66, 121 physics, 170, 173, 176, 184, 203 plants, viii, 129, 130, 131, 132, 133, 134, 135, 153, 154, 155, 158, 160, 163, 167, 168, 184, 208, 211, 212, 213, 215, 221, 238, 256, 266 pollution, 134, 135, 205 polymer, viii, 2, 8, 55, 56, 59, 60, 67, 70, 77, 83, 84, 118, 119 polymer electrolytes, 56, 61, 67, 83, 84, 118, 119 polymers, 58, 60, 79, 81, 122, 126 population, vii, 217, 218, 220, 244 porosity, 45, 69, 81, 82, 170, 171, 172, 173, 175, 177, 178, 180, 181 porous media, vii, ix, 170, 171, 173, 175 power generation, 131, 132, 144, 164, 206, 212, 257 power plants, viii, 129, 130, 131, 132, 133, 134, 135, 136, 153, 154, 157, 158, 163, 167, 168, 170, 210, 213, 214, 215, 216 precipitation, 13, 15, 16, 20, 26, 28, 89, 92, 100 preparation, 94, 102, 109 principles, viii, 1, 104, 121 programming, 205, 218, 229, 238 propylene, 3, 8, 76, 117 protection, 56, 58, 69, 125, 134, 236

R radiation, 184, 185, 188, 190, 192, 194, 195

Index Rayleigh number, 243, 244, 248, 249, 250 reaction mechanism, 33, 35, 105 reactions, 2, 5, 6, 9, 14, 33, 41, 59, 65, 72, 74, 75, 76, 80, 114 reactivity, 3, 75, 124 recovery, 48, 156, 158, 161, 162, 213, 215, 216, 222, 229, 241, 256, 257, 265 recycling, ix, 162, 170, 215 reliability, 87, 90, 167 renewable energy, viii, 129, 140, 141, 144, 153, 170, 206 requirement(s), viii, 2, 10, 55, 57, 61, 70, 129, 130, 135, 144, 153, 154, 170, 204, 212, 225, 235 RES, 140, 141, 142 researchers, ix, 3, 27, 40, 41, 46, 49, 63, 170, 172, 175, 179, 184, 193, 196, 257 reserves, 136, 156, 237 resistance, 7, 55, 74, 81, 84, 173 resources, 14, 136, 153, 256 response, 147, 156, 163, 202, 220 revenue, 156, 161, 227 room temperature, 3, 8, 21, 25, 59, 66, 78, 101

S safety, 3, 28, 39, 59, 63, 69, 70, 84, 85, 88, 90, 104, 130, 133, 134, 139, 145, 151, 152, 167, 244 salts, 24, 32, 55, 58, 61, 75, 116, 118, 125, 142, 145, 161, 185 science, 87, 134, 216, 218 sensible heat storage, 141, 144, 146, 170, 243, 246, 252, 253, 256, 257, 258, 260, 262 shape, 60, 76, 79, 166, 195, 199 shelf life, 41, 57, 73 silica, 30, 54, 84, 126 silicon, 51, 53, 66, 113, 115, 137

275

simulation, 144, 147, 149, 153, 164, 173, 175, 178, 190, 204, 244 skeleton, 42, 46, 49, 53, 65 sodium, 108, 145, 156 solar collector, vii, 170, 180, 183, 184, 186, 189, 192, 198 sol-gel, 13, 26, 27, 30, 88, 100 solidification, 172, 175, 178, 180, 192 solution, 3, 16, 28, 61, 75, 89, 98, 116, 124, 166, 175, 176, 179, 193, 216, 217, 218, 244 species, 6, 21, 64, 131 specific heat, 141, 190, 195, 200, 209 spectroscopy, 88, 97, 117, 125 stability, 1, 3, 6, 13, 14, 15, 16, 17, 19, 21, 22, 25, 28, 37, 39, 43, 46, 49, 51, 52, 53, 55, 56, 58, 59, 61, 63, 68, 69, 73, 80, 84, 85, 88, 120, 122, 142, 149, 165, 167 stabilization, 24, 42, 116 state(s), viii, 1, 5, 11, 13, 15, 16, 18, 23, 24, 25, 26, 29, 30, 32, 33, 34, 36, 38, 52, 59, 60, 63, 73, 74, 76, 77, 78, 85, 97, 100, 104, 110, 111, 113, 119, 120, 121, 130, 140, 150, 151, 153, 155, 160, 163, 172, 190, 200, 201, 204, 236 steel, 70, 171, 256, 265 stoichiometry, 21, 28, 38, 51, 98 storage, vii, viii, ix, 2, 5, 33, 49, 61, 68, 72, 73, 82, 86, 96, 102, 105, 108, 109, 112, 113, 115, 118, 119, 129, 130, 137, 140, 141, 142, 143, 144, 145, 146, 147, 149, 150, 151, 152, 155, 156, 157, 158, 159, 161, 162, 163, 164, 165, 169, 170, 171, 172, 180, 181, 183, 184, 185, 186, 189, 190, 191, 192, 200, 201, 204, 205, 206, 236, 238, 239, 243, 245, 246, 252, 253, 256, 257, 258, 260, 262, 265, 266, 267 storage media, 144, 145, 200 stress, 44, 46, 80 structural changes, 26, 30, 46 structure, 3, 10, 11, 13, 15, 17, 19, 21, 22, 23, 26, 27, 31, 32, 33, 35, 42, 44, 49, 51,

276

Index

52, 56, 61, 64, 73, 81, 84, 93, 98, 101, 115, 120, 144, 171, 175, 178 substitution, 16, 17, 19, 27, 32, 39, 64, 96, 120 sulfur, 3, 12, 35, 36, 37, 45, 67, 106, 134 Sun, 91, 95, 97, 106, 110, 115, 117, 167 surface area, 28, 37, 46, 149, 171, 188 surface reaction, 46, 75, 80, 82 sustainable energy, 122, 135, 140, 206 synthesis, 13, 15, 16, 24, 27, 30, 66, 79, 88, 89, 90, 91, 92, 93, 96, 100, 104, 110

T techniques, 153, 156, 158, 161, 165, 173, 184, 206, 216, 222 technology/technologies, 3, 12, 36, 85, 87, 88, 122, 126, 131, 135, 136, 141, 143, 144, 153, 155, 156, 157, 158, 160, 161, 163, 165, 169, 183, 206, 213, 218, 240, 244 temperature, viii, 3, 4, 5, 13, 17, 18, 24, 28, 38, 44, 53, 59, 69, 77, 78, 79, 91, 92, 98, 102, 113, 116, 118, 122, 125, 126, 129, 130, 136, 138, 139, 141, 142, 143, 144, 145, 146, 147, 148, 149, 151, 152, 158, 159, 160, 161, 162, 164, 175, 184, 185, 186, 188, 189, 192, 195, 196, 197, 199, 200, 201, 206, 214, 215, 226, 229, 235, 244, 246, 249, 257, 258, 259 testing, 192, 245, 252 thermal energy, vii, viii, ix, 129, 130, 142, 144, 145, 147, 148, 149, 150, 152, 157, 164, 169, 170, 171, 172, 180, 181, 183, 184, 185, 189, 191, 200, 201, 205, 206, 233, 245, 253, 265 thermal energy storage, vii, viii, ix, 129, 130, 144, 147, 149, 150, 152, 157, 164, 169, 170, 171, 172, 180, 181, 183, 185, 200, 201, 205, 206, 245, 253, 265

thermal stability, 11, 14, 15, 16, 19, 23, 26, 28, 30, 38, 64, 68, 75, 84, 90, 126, 144 thermal storage, 141, 145, 147, 149, 150, 157, 158, 162, 164, 190, 201, 204, 238, 257, 266 tin, 50, 52, 112, 113 titanate, 46, 109, 120 titanium, 3, 47, 109, 119 transformation, 15, 17, 22, 93 transition metal, 3, 8, 10, 11, 12, 14, 16, 17, 19, 21, 29, 32, 33, 39, 46, 48, 49, 51, 52, 72, 73, 74, 79, 80, 87, 94, 104, 112, 113 transport, 28, 34, 36, 55, 58, 68, 84, 85, 109, 119, 122, 143, 267

U uniform, 56, 69, 89, 190, 246, 258 United Kingdom, 131, 132, 135 United States (USA), viii, 2, 122, 131, 132, 157 uranium, 131, 137, 148

V vanadium, 23, 31, 47, 96, 103, 110, 156 vapor, 145, 214, 229 variations, 65, 231, 244, 248, 250, 251, 260 vehicles, 5, 26, 37, 64, 69

W waste, 7, 134, 135, 212, 224, 239, 241, 256, 257, 265 waste heat, 7, 212, 224, 241, 256, 257, 265 water, 57, 59, 74, 140, 141, 142, 163, 166, 183, 186, 189, 190, 209, 214, 215, 216, 221, 226, 256, 265