Advances in Green Energies and Materials Technology: Selected Articles from the Algerian Symposium on Renewable Energy and Materials (ASREM-2020) (Springer Proceedings in Energy) [1st ed. 2021] 9811603774, 9789811603778

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Table of contents :
Preface
Contents
About the Editors
1 Fabrication of Flexible Photovoltaic Cells
1.1 Introduction
1.2 Fabrication Method of the Flexible Cell
1.2.1 ITO Etched by Photolithography
1.2.2 Realization of the Flexible Solar Cells
1.3 Results and Discussion
1.4 Conclusion
References
2 Effect of Solution Concentration in the Optical and Electrical Properties of Copper Oxide Thin Films
2.1 Introduction
2.2 Experimental Procedure
2.3 Results and Discussions
2.4 Conclusion
References
3 IR Spectroscopy and Computational Study of Structural, Vibrational and Electronic Properties of Hydrindantin Dihydrate
3.1 Introduction
3.2 Experimental Details
3.3 Computational Details
3.4 Results and Discussion
3.4.1 Structural Optimization
3.4.2 Vibrational Properties
3.4.3 Electronic Properties
3.5 Conclusion
References
4 Thermal Behavior Study of a Fresnel Concentrator Solar Receiver
4.1 Introduction
4.2 Thermal Receiver Modelling
4.2.1 Modeled Receiver Geometry
4.2.2 Heat Loss Calculation
4.3 Simulation Software (Fluent) Presentation
4.4 Simulation Results
4.4.1 Basic Conditions
4.4.2 Temperature Distribution
4.4.3 Tube Heat Losses Evolution
4.5 Conclusion
References
5 Analysis Study and Design of Optimal Control MPPT Strategy for a Photovoltaic Solar Energy System
5.1 Introduction
5.1.1 Problem Formulation
5.2 Results and Discussions
5.3 Conclusion
References
6 Physico-mechanical Characterizations of the Compressed Earth Block (CEB) Stabilized with Lime-Based Fibers (Waste Tyre Rubber-Glass)
6.1 Introduction
6.2 Experimental Study
6.2.1 Mixtures Design
6.3 Results and Discussions
6.3.1 Compression Strength Test
6.3.2 The Tensile Strength of CEB
6.4 Conclusion
References
7 Modeling, Simulation and Control of a Standalone Photovoltaic System
7.1 Introduction
7.2 Mathematical Modeling of the Solar System
7.2.1 Photovoltaic Generator
7.2.2 Boost Converter Modeling
7.2.3 Maximum Power Point Tracker MPPT
7.2.4 Storage Battery Modeling
7.2.5 Three Phase DC-AC Inverter Modeling
7.3 Results and Discussions
7.4 Conclusion
References
8 Algerian Energy Building Policy in the Context of Sustainable Development by 2030
8.1 Introduction
8.1.1 Problem Formulation
8.1.2 Goals
8.2 Results and Discussions
8.3 Conclusion
References
9 Power Improvement of DFIG Wind Turbine System Using Fuzzy-Feedback Linearization Control
9.1 Introduction
9.2 System Modeling
9.2.1 DFIG Modeling
9.3 Feedback Linearization Control Design
9.4 Fuzzy-Feedback Linearization Control Design
9.5 Results and Discussions
9.6 Conclusion
References
10 The Effect of Freeze-Thaw Cycles on Properties of Concrete with Recycling Aggregate Pavements
10.1 Introduction
10.2 Experimental Program
10.2.1 Materials
10.2.2 Identification of Mixtures
10.2.3 Method
10.3 Results and Discussions
10.3.1 Visual Examination
10.3.2 Weight Loss
10.3.3 Compressive Strength
10.4 Conclusion
References
11 Steady-State Stability Regions Analysis of Different Amplitudes of Doubly Fed Induction Generators
11.1 Introduction
11.2 Electric Equations
11.3 Steady State Machine Operation
11.4 Results and Discussions
11.5 Conclusion
References
12 Pumping FOC-DFIM System Supplied with PVG and Based on FLC Type-2
12.1 Introduction
12.2 PV Module
12.3 MPPT Control
12.4 MPPT Control Based on FLC Type-2
12.5 Direct Field Oriented Control
12.6 Digital Simulation
12.7 Conclusion
References
13 Investigation the Optical Intersubband Absorption in Double Barriers of Resonant Tunneling Superlattice
13.1 Introduction
13.2 Theory
13.2.1 Intersubband Absorption Coefficient
13.3 Results and Discussions
13.4 Conclusion
References
14 Non-linear Control Based on Sliding Mode of a Wind Energy System
14.1 Introduction
14.2 Second-Order Sliding Mode Power Control of the DFIG
14.3 Simulations Results and Discussions
14.4 Conclusion
References
15 A Comparison State of Charge Estimation Between Kalman Filter and Sliding Mode Observer for Lithium Battery
15.1 Introduction
15.2 Battery Modeling
15.3 State of Charge Estimation
15.3.1 Kalman Filters
15.3.2 Sliding Mode Observer
15.4 Simulation and Results Discussion
15.5 Conclusion
References
16 Short Circuit Fault Detection in Photovoltaic Inverter Using FRA Analysis and FFT Method
16.1 Introduction
16.1.1 The Equivalent High Frequency Model of PV Inverter
16.1.2 Fault Detection with FRA Analysis
16.1.3 Discussion of Obtained Results by RFA Analysis
16.1.4 Fault Detection Using FFT Current Signal Analysis
16.1.5 Discussion of Obtained Results by FFT Analysis
16.2 Conclusion
References
17 Charge and Discharge of Electrochemical Storage by a Photovoltaic Field
17.1 Introduction
17.2 Protocol Experimental
17.3 Results and Discussions
17.4 Conclusion
References
18 An Artificial Intelligence Approach to Forecast Wind Speeds in Algeria
18.1 Introduction
18.2 Wind Data Collection
18.3 Results and Discussions
18.4 Conclusion and Recommendations
References
19 Study and Characterization of a Biomaterial: Animal Bone. Application to the Treatment of an Industrial Effluent
19.1 Introduction
19.2 Material and Methods
19.2.1 Product Used
19.2.2 Method
19.3 Results and Discussions
19.3.1 Static Adsorption
19.3.2 Study of Some Types of Adsorption Isotherms
19.4 Conclusion
References
20 Numerical Simulation of a Shallow Solar Pond Operating Under the Batch Mode of Heat Extraction
20.1 Introduction
20.2 Problem Formulation
20.3 Results and Discussions
20.4 Conclusion
References
21 Numerical Simulation of a Flat-Plate Solar Collector Operating Under Open Cycle Mode of Heat Extraction
21.1 Introduction
21.2 Problem Formulation
21.3 Results and Discussions
21.4 Conclusion
References
22 A Discussion About Hydrogen Diffusion in n+pp+ Polysilicon Solar Cells Following Analysis of Both Dopant Deactivation and Defects Passivation
22.1 Introduction
22.2 Experimental
22.3 Results and Discussion
22.3.1 Plasma Hydrogenation Effect on Boron Activation Profile and Open-Circuit Voltage Evolution
22.3.2 Hydrogen Diffusion Process in n+pp+ Poly-Si Solar Cell
22.4 Conclusion
References
23 Structural and Optical Properties of Cu(In,Ga)Se2 Thin Films Grown by CSVT Technique Annealed Under Argon Atmosphere for Thin Films Solar Cells
23.1 Introduction
23.2 Photoacoustic Spectroscopy Principle
23.3 Experimental Details
23.3.1 Samples Preparation
23.3.2 Characterization
23.3.3 Photoacoustic Spectrometer Description
23.4 Results and Discussions
23.5 Conclusion
References
24 Control by Fuzzy Logic Associated with the Flow Oriented Command of the Dual Star Asynchronous Generator Integrated into a Wind Turbine
24.1 Introduction
24.1.1 Optimization of the Energy Conversion of a Wind Turbine by MPPT Strategy
24.1.2 Wind Turbine Based on a Double Star Asynchronous Generator
24.1.3 Indirect Vector Control by Orienting the Rotor Flow of the GASDS
24.2 MPPT Strategy Modeling Based on FLC
24.3 Association of FLC and FOC to the Control of the GASDE Dedicated to Wind System
24.4 Interpretations of the Results
24.5 Conclusion
References
25 Numerical Investigation of an InGaP/GaAs Heterojunction Solar Cell by AMPS-1D
25.1 Introduction
25.2 Modelling and Simulation
25.2.1 About AMPS-1D
25.2.2 Structure and Materials
25.3 Results and Discussions
25.3.1 The Thickness Effect of the Absorber on the Characteristics of the InGaP/GaAs Heterojunction Solar Cell
25.3.2 he Doping Effect of the Absorber on the Characteristics of the InGaP/GaAs Heterojunction Solar Cell
25.3.3 Optimization of the Spectral Response
25.3.4 Optimization of Electrical Characteristics:
25.4 Conclusion
References
26 Energy Flow Management in Standalone Hybrid Electric Generation System
26.1 Introduction
26.2 Architecture of the Installation Studied
26.3 Energy Management Strategy Proposed
26.4 Simulation Results and Discussions
26.5 Conclusion
References
27 Synthesis and Characterization of Fe-doped ZnO Thin Films Deposited by Spin Coating
27.1 Introduction
27.2 Experimental Details
27.2.1 Materials and Procedures
27.3 Results and Discussion
27.3.1 Structural Properties
27.3.2 Optical Properties
27.4 Conclusion
References
28 Sliding Mode Control of Voltage Source Converter Based High Voltage Direct Current System
28.1 Introduction
28.2 Modeling of VSC-HVDC
28.3 Sliding Mode Control of VSC-HVDC Station
28.4 Simulation Result
28.5 Conclusion
References
29 UV-visible Spectroscopy Study of TiO2: X (X = Ni, Mn or Cu) Films Synthetized by Dip-Coating Technique for Solar Cells Applications
29.1 Introduction
29.2 Experimental Details
29.3 Results and Discussions
29.4 Conclusion
References
30 Recycling of Floor Tile Waste as Fine Aggregate in Flowable Sand Concrete
30.1 Introduction
30.2 Experimental Work
30.2.1 Materials
30.2.2 Mix Design
30.2.3 Tests Procedures
30.3 Results and Discussions
30.3.1 Properties of FSC in Fresh State
30.3.2 Properties of FSC in Hardened State
30.4 Conclusion
References
31 Structural and Mechanical Properties of NiCoMnSn Compound for Magnetic Refrigeration Close to Ambient Temperature
31.1 Introduction
31.2 Materials Synthesis and Characterization
31.2.1 Schrödinger’s Equation
31.2.2 Ground State
31.3 Results and Discussions
31.3.1 Structural Properties
31.3.2 Mechanical, Elastic Properties
31.4 Conclusion
References
32 A Photovoltaic Generator System Based on Three-Level Neutral-Point-Clamping Power Inverter
32.1 Introduction
32.2 System Structure
32.2.1 PV Generator System
32.2.2 Batteries Source
32.3 Three-Level NPC Power Converter
32.4 Validation Results
32.5 Conclusion
References
33 Ecological and Geochemical Assessment of the Environment in the Zinc Ore Recovery Zone; Case of CHAABET EL-HAMRA Mining Complex (Algeria)
33.1 Introduction
33.2 Problem Formulation
33.3 Results and Discussions
33.3.1 Discussion
33.4 Conclusion
References
34 Comparative Study of Solar Pumping with Connection to Electric Networks for Irrigation of a Plant Nursery
34.1 Introduction
34.2 Site and Data Description
34.2.1 Geographical Data
34.2.2 Meteorological Data
34.3 Sizing of the Pumping Station
34.3.1 Evaluation of the Load Profile Used for Water Pumping
34.3.2 Tank Capacity
34.3.3 Description of PV Modules Used
34.3.4 Description of Converter Used
34.4 Result and Discussion of the Optimal System
34.5 Analysis of the Minimum Distance of the Network for the Breakeven Point
34.6 Conclusion
References
35 Enhancement of Extracted Photovoltaic Power Using Artificial Neural Networks MPPT Controller
35.1 Introduction
35.2 PV Generator Modeling
35.3 DC-DC Boost Converter
35.4 Perturb and Observe MPPT Algorithm
35.5 MPPT Based on Artificial Neural Networks
35.6 Prediction of MPP Based on ANN
35.7 ANN Test Results
35.8 Conclusion
References
36 Assessment of Parabolic Trough Solar Thermal Plant in Algeria
36.1 Introduction
36.2 Methodology
36.3 Results and Discussions
36.4 Comparison of LCOE of Plants
36.5 Conclusion
References
37 Analysis of Hybrid Photovoltaic System Performance
37.1 Introduction
37.2 Description of the Analyzed System
37.3 Methodology
37.3.1 Presentation of the Installation Site of the Hybrid System
37.3.2 Evaluation of the Energy Resource Available on the Site
37.3.3 Evaluation of Energy Demand (the Load Profile)
37.3.4 Manual Pre-sizing of Equipment
37.3.5 Enter the Necessary Data into the Software
37.4 Results and Discussions
37.4.1 Comparison of HES with PV Alone
37.4.2 Comparison of HES with PV Alone
37.5 Conclusion
References
38 Optimization Method of a Wind Turbine Blade Based on Proper Generalized Decomposition
38.1 Introduction
38.2 Problem Formulation
38.2.1 Calculating W(r) from the Known Functions S(ct )andR(u )
38.3 Results and Discussions
38.4 Conclusion
References
39 Direct Power Control Approach for a Grid-Connected Photovoltaic Power System
39.1 Introduction
39.2 System Structure
39.2.1 Modeling of the Photovoltaic Cells
39.2.2 Boost Converter and MPPT
39.3 Direct Power Control
39.4 DC Bus Control
39.5 Validation Results
39.6 Conclusion
References
40 Classification of Energies Storage Capacitors Values Based on Fuzzy Logic Approach (Case of a Planar Capacitor)
40.1 Introduction
40.2 Energy Storage in a Capacitor [1–6]
40.3 Mathematical Model of Fuzzy Logic C-Means Clustering (FLCM) [7, 8]
40.4 Simulation Results
40.5 Conclusion
References
41 The use of Grey Wolf Optimizer for Cost Reduction and Optimal Configuration of Hybrid Wind-PV-Diesel with Battery Storage
41.1 Introduction
41.2 The Selected Site
41.2.1 Location
41.2.2 The Climate
41.2.3 Site Coordinates
41.3 Wind-PV-Diesel-Battery Hybrid Power System
41.4 Results and Discussion
41.5 Conclusion
Reference
42 Fuzzy Logic Type-2 Controller Design for Maximum Power Point Tracking in Photovoltaic System
42.1 Introduction
42.2 Maximum Power Point Tracking Technique Type-2 FLC
42.3 Results and Discussion
42.4 Conclusion
References
43 A Software Application Developed for the PV System Monitoring
43.1 Introduction
43.2 Methods and Materials
43.2.1 PV Station and Used Data Acquisition System
43.2.2 Developed Software Application Description
43.3 Results and Discussions
43.4 Conclusion
References
44 Modeling and Simulation of a Photovoltaic System Connected to the Electrical Network
44.1 Introduction
44.2 System Description
44.3 Modeling of a Photovoltaic Cell
44.4 Modeling a Photovoltaic Generator
44.5 Simulation of the Photovoltaic Generator
44.6 BOOST Chopper
44.7 The Three-Phase Inverter
44.8 Vector MLI Control of Three-Phase Inverter
44.9 BOOST Converter Simulation
44.10 Results and Discussions
44.11 Complete System Simulation
44.12 Conclusion
References
45 Comparative Study of SVC-STATCOM Devices on Voltage Stability Applied on PV-Wind System
45.1 Introduction
45.2 Facts Devices
45.2.1 The Static Var Compensator (SVC)
45.2.2 Static Synchronous Compensator (STATCOM)
45.3 Simulation Results
45.3.1 System Description
45.3.2 Results of Simulation of the System in the Absence of Compensation Devices
45.3.3 Results of Simulation in the Presence of Static Var Compensator (SVC)
45.3.4 Results of Simulation in the Presence of Static Synchronous Compensator (STATCOM)
45.4 Conclusion
References
46 ZnO Films Elaborated by D.C. Magnetron Sputtering
46.1 Introduction
46.2 Experimental Detail
46.3 Results and Discussion
46.4 Conclusion
References
47 First Principles Electro Optical Characterization of Semiconductors Perovskites
47.1 Introduction
47.2 Problem Formulation
47.3 Results and Discussion
47.3.1 Structural Properties
47.3.2 Electronic Properties
47.3.3 Electronic Properties
47.3.4 Optical Properties
47.3.5 Photoconduction Properties
47.4 Conclusion
References
48 Thermal Investigation of a Solar Chimney Power Plant System: CFD Approach
48.1 Introduction
48.1.1 Computational Modelling
48.1.2 Results and Discussions
48.1.3 Conclusion
References
49 Effects of Rim Angle on Performance Predictions of a Parabolic Trough Solar Collector
49.1 Introduction
49.2 Model and Methodology
49.2.1 Physical Model Description
49.2.2 Coupled Model
49.3 Results and Discussions
49.3.1 Validation of the Optical Model
49.3.2 Effect of Rim Angle
49.3.3 Thermal Part
49.4 Conclusion
References
50 Thermal Performances Investigation of Two ISCC Layouts
50.1 Introduction
50.2 Description of ISCC Systems
50.2.1 Solar Field
50.2.2 Rankine Cycle
50.2.3 Results and Discussions
50.3 Conclusion
References
51 Effect of Turbulence on Wind Turbine Farm Power Production
51.1 Introduction
51.2 Ishihara Wake Model
51.3 Characteristics of the ENERCON E2 Wind Turbine
51.4 Results and Discussion
51.4.1 Ambient Turbulence
51.4.2 Added Turbulence
51.4.3 Effect of Added Turbulence on the Power
51.5 Conclusion
References
52 Maximum Power Point Tracking Method Using Sliding Mode Extremum-Seeking Algorithm for Residential Wind Turbine
52.1 Introduction
52.2 System Structure
52.3 Sliding Mode Extremum Seeking Control for Wind MPPT
52.4 Simulations Results
52.5 Conclusion
References
53 Thermal Investigation of an Electrocaloric Refrigeration Systems
53.1 Introduction
53.2 Active Electrocaloric Refrigerator System Description AER
53.3 Thermodynamics of Electrocaloric Effects
53.4 Results and Discussions
53.5 Conclusion
References
54 Electronic and Thermoelectric Properties of Lead Sulfide PbS: DFT Approach
54.1 Introduction
54.2 Computational Methods
54.3 Results and Discussion
54.3.1 Structural properties
54.3.2 Electronic properties
54.3.3 Thermoelectric Properties
54.4 Conclusion
References
55 Comparison Between Methanol and Methane Steam Reforming Reactors for Hydrogen Production
55.1 Introduction
55.2 Steam Reforming
55.3 Mathematical Model
55.4 Physical Model
55.5 Results and Discussion
55.6 Conclusion
References
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Springer Proceedings in Energy

Younes Chiba Abdelhalim Tlemçani Arezki Smaili   Editors

Advances in Green Energies and Materials Technology Selected Articles from the Algerian Symposium on Renewable Energy and Materials (ASREM-2020)

Springer Proceedings in Energy

The series Springer Proceedings in Energy covers a broad range of multidisciplinary subjects in those research fields closely related to present and future forms of energy as a resource for human societies. Typically based on material presented at conferences, workshops and similar scientific meetings, volumes published in this series will constitute comprehensive state-of-the-art references on energy-related science and technology studies. The subjects of these conferences will fall typically within these broad categories: • • • • • • •

Energy Efficiency Fossil Fuels Nuclear Energy Policy, Economics, Management & Transport Renewable and Green Energy Systems, Storage and Harvesting Materials for Energy

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More information about this series at http://www.springer.com/series/13370

Younes Chiba · Abdelhalim Tlemçani · Arezki Smaili Editors

Advances in Green Energies and Materials Technology Selected Articles from the Algerian Symposium on Renewable Energy and Materials (ASREM-2020)

Editors Younes Chiba Department of Mechanical Engineering University Yahia Fares of Medea Médéa, Algeria

Abdelhalim Tlemçani Department of Electrical Engineering University Yahia Fares of Medea Médéa, Algeria

Arezki Smaili Department of Mechanical Engineering National Polytechnic School-ENP Algiers, Algeria

ISSN 2352-2534 ISSN 2352-2542 (electronic) Springer Proceedings in Energy ISBN 978-981-16-0377-8 ISBN 978-981-16-0378-5 (eBook) https://doi.org/10.1007/978-981-16-0378-5 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Singapore Pte Ltd. The registered company address is: 152 Beach Road, #21-01/04 Gateway East, Singapore 189721, Singapore

Preface

This proceeding contains selected papers presented in the Algerian Symposium on Renewable Energy and Materials (ASREM-2020), which was held at University of Medea, Medea city, Algeria. The symposium aims to provide a platform for students, engineers, researchers and scientists to share their knowledge and ideas in the recent trends in the field of renewable energy and materials. Various aspects of clean energy are covered in this symposium, including (but not limited to) renewable energy systems, materials engineering, numerical modeling, hydrogen energy and conventional energy systems. The photothermal and photovoltaic can be considered the hot topic at the symposium. This is because Algeria has one of the most important solar energy resources in the world, and the recent government renewable energy and energy-saving development program. Over 250 submitted papers were received, and after a rigorous peer-reviewed process, 150 papers have been accepted, of which 100 for oral presentation and the remaining for a poster presentation. We would like to take this opportunity to thank our sponsors (Medea University, Djelfa University, LAADI, ESLI, ENTEC, SINALE, CARSI, SONELGAZ, ATRST, DGRSDT) and Springer. Also, we offer our sincere thanks to the members of organizing and steering committees of the symposium, dean of technology faculty and rector of the university for their help, ongoing and enthusiastic support. Médéa, Algeria Médéa, Algeria Algiers, Algeria October 2020

Younes Chiba Abdelhalim Tlemçani Arezki Smaili

v

Contents

1

Fabrication of Flexible Photovoltaic Cells . . . . . . . . . . . . . . . . . . . . . . . . Ourida Ourahmoun

2

Effect of Solution Concentration in the Optical and Electrical Properties of Copper Oxide Thin Films . . . . . . . . . . . . . . . . . . . . . . . . . L. Herissi, L. Hadjeris, Z. Moussa, L. Hafsa, S. Djebabra, B. Herissi, A. Sari, and S. Bouchrit

3

4

5

6

7

8

1

9

IR Spectroscopy and Computational Study of Structural, Vibrational and Electronic Properties of Hydrindantin Dihydrate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Abdelali Boukaoud, Younes Chiba, Khoukha Fatimi, Nassima Yahimi, Fatima Zohra Meguellati, and Souad Bouguettaya

17

Thermal Behavior Study of a Fresnel Concentrator Solar Receiver . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Hani Beltagy, Sofiane Mihoub, and Said Noureddine

25

Analysis Study and Design of Optimal Control MPPT Strategy for a Photovoltaic Solar Energy System . . . . . . . . . . . . . . . . . Mouhoub Birane, Abdelghani Chahmi, and Tahar Merizgui

33

Physico-mechanical Characterizations of the Compressed Earth Block (CEB) Stabilized with Lime-Based Fibers (Waste Tyre Rubber-Glass) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Mohamed Rabehi and Rachid Rabehi Modeling, Simulation and Control of a Standalone Photovoltaic System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Mokhtar Kobbi, Moubarek Saada, Mohammed Chenafa, and Abdelkerim Souahlia Algerian Energy Building Policy in the Context of Sustainable Development by 2030 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Nabil Meftah and Zine labidine Mahri

41

49

57

vii

viii

9

Contents

Power Improvement of DFIG Wind Turbine System Using Fuzzy-Feedback Linearization Control . . . . . . . . . . . . . . . . . . . . . . . . . . Kada Boureguig, Ahmed Chouya, and Abdellah Mansouri

63

10 The Effect of Freeze-Thaw Cycles on Properties of Concrete with Recycling Aggregate Pavements . . . . . . . . . . . . . . . . . . . . . . . . . . . . Settari Chafika, Irki Ilyes, and Debieb Farid

73

11 Steady-State Stability Regions Analysis of Different Amplitudes of Doubly Fed Induction Generators . . . . . . . . . . . . . . . . . Benyoucef Koudri and Abdelhafidh Moualdia

81

12 Pumping FOC-DFIM System Supplied with PVG and Based on FLC Type-2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Fethia Hamidia, Amel Abbadi, and Mohamed Redha Skender

87

13 Investigation the Optical Intersubband Absorption in Double Barriers of Resonant Tunneling Superlattice . . . . . . . . . . . . . . . . . . . . . Djamel Sebbar, Bouzid Boudjema, Abdelali Boukaoud, Younes Chiba, and Oussama Houhou

95

14 Non-linear Control Based on Sliding Mode of a Wind Energy System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101 Abdelhafidh Moualdia, Saleh Boulkhrachef, and Ahmed Medjber 15 A Comparison State of Charge Estimation Between Kalman Filter and Sliding Mode Observer for Lithium Battery . . . . . . . . . . . . 107 Maamar Souaihia, Bachir Belmadani, Fayçal Chabni, and Abdelatif Gadoum 16 Short Circuit Fault Detection in Photovoltaic Inverter Using FRA Analysis and FFT Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115 Ghania Ouadfel, Hamza Houassine, and Abdrrazak Gacemi 17 Charge and Discharge of Electrochemical Storage by a Photovoltaic Field . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123 Amina Maria Laoufi, Hamou Soualmi, Rachid Khelfaoui, and Benmoussa Dennai 18 An Artificial Intelligence Approach to Forecast Wind Speeds in Algeria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131 Abdelhamid Bouhelal and Arezki Smaili 19 Study and Characterization of a Biomaterial: Animal Bone. Application to the Treatment of an Industrial Effluent . . . . . . . . . . . . 139 Nedjhioui Mohammed, Hamidi Nadjia, Grini Amina, Brahami Yamina, and Omari Souhila

Contents

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20 Numerical Simulation of a Shallow Solar Pond Operating Under the Batch Mode of Heat Extraction . . . . . . . . . . . . . . . . . . . . . . . 147 Abdelkrim Terfai, Younes Chiba, and Mohamed Najib Bouaziz 21 Numerical Simulation of a Flat-Plate Solar Collector Operating Under Open Cycle Mode of Heat Extraction . . . . . . . . . . . 153 Abdelkrim Terfai, Younes Chiba, Mounir Zirari, and Mohamed Najib Bouaziz 22 A Discussion About Hydrogen Diffusion in n+ pp+ Polysilicon Solar Cells Following Analysis of Both Dopant Deactivation and Defects Passivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 159 Djamel Madi and Djamel Eddine Belfennache 23 Structural and Optical Properties of Cu(In,Ga)Se2 Thin Films Grown by CSVT Technique Annealed Under Argon Atmosphere for Thin Films Solar Cells . . . . . . . . . . . . . . . . . . . . . . . . . . 167 Rania Mahdadi, Meryem Lasladj, and Abdesselam Bouloufa 24 Control by Fuzzy Logic Associated with the Flow Oriented Command of the Dual Star Asynchronous Generator Integrated into a Wind Turbine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 175 Zekraoui Said and Moualdia Abdelhafidh 25 Numerical Investigation of an InGaP/GaAs Heterojunction Solar Cell by AMPS-1D . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183 Mohammed Zakaria Missouri, Ahmed Benamara, and Hassane Benslimane 26 Energy Flow Management in Standalone Hybrid Electric Generation System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 193 S. Bentouati, N. Henini, A. Tlemcani, and Y. Chiba 27 Synthesis and Characterization of Fe-doped ZnO Thin Films Deposited by Spin Coating . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 201 Abdelkader Mohammedi, Miloud Ibrir, and Omar Meglali 28 Sliding Mode Control of Voltage Source Converter Based High Voltage Direct Current System . . . . . . . . . . . . . . . . . . . . . . . . . . . . 209 Randa Babouche, Nourelddine Henini, Kamel Saoudi, and Taki Eddine Ameur 29 UV-visible Spectroscopy Study of TiO2 : X (X = Ni, Mn or Cu) Films Synthetized by Dip-Coating Technique for Solar Cells Applications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 215 Abdelmalek Kharroubi and Abdelkader Ammari 30 Recycling of Floor Tile Waste as Fine Aggregate in Flowable Sand Concrete . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 223 Mohamed Guendouz, Djamila Boukhelkhal, and Alexandra Bourdot

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31 Structural and Mechanical Properties of NiCoMnSn Compound for Magnetic Refrigeration Close to Ambient Temperature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 231 Meriem Boudoukhani, Younes Chiba, and Malika Amari 32 A Photovoltaic Generator System Based on Three-Level Neutral-Point-Clamping Power Inverter . . . . . . . . . . . . . . . . . . . . . . . . . 239 Farid Hadjou, Bekheira Tabbache, Noureddine Henini, Samir. Noui, Mohamed Benbouzid, and El-Madjid Berkouk 33 Ecological and Geochemical Assessment of the Environment in the Zinc Ore Recovery Zone; Case of CHAABET EL-HAMRA Mining Complex (Algeria) . . . . . . . . . . . . . . . . . . . . . . . . . 249 Rima Omara 34 Comparative Study of Solar Pumping with Connection to Electric Networks for Irrigation of a Plant Nursery . . . . . . . . . . . . 257 Mohamed Dekkiche and Sofiane Abaidia 35 Enhancement of Extracted Photovoltaic Power Using Artificial Neural Networks MPPT Controller . . . . . . . . . . . . . . . . . . . . 265 Zerglaine Abdelaziz, Mohammedi Ahmed, Bentata Khadidja, Rekioua Djamila, Oubelaid Adel, and Mebarki Nasser Eddine 36 Assessment of Parabolic Trough Solar Thermal Plant in Algeria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 273 Mihoub Sofiane, Hani Beltagy, and Mohamed Belhocine 37 Analysis of Hybrid Photovoltaic System Performance . . . . . . . . . . . . . 279 Abdelkader Gourbi, Mohamed Miloudi, and Mostefa Brahami 38 Optimization Method of a Wind Turbine Blade Based on Proper Generalized Decomposition . . . . . . . . . . . . . . . . . . . . . . . . . . 287 Nacer Eddine Boumezbeur and Arezki Smaili 39 Direct Power Control Approach for a Grid-Connected Photovoltaic Power System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 295 Mohamed Zine Zizoui, Bekheira Tabbache, Nouredine hannini, and Mohamed Benbouzid 40 Classification of Energies Storage Capacitors Values Based on Fuzzy Logic Approach (Case of a Planar Capacitor) . . . . . . . . . . . 303 Bakhti Mimene, Younes Chiba, and Abdelhalim Tlemçani 41 The use of Grey Wolf Optimizer for Cost Reduction and Optimal Configuration of Hybrid Wind-PV-Diesel with Battery Storage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 311 Adel Yahiaoui and Abdelhalim Tlemçani

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42 Fuzzy Logic Type-2 Controller Design for Maximum Power Point Tracking in Photovoltaic System . . . . . . . . . . . . . . . . . . . . . . . . . . 319 N. Ould Cherchali, B. Bentchikou, M. S. Boucherit, A. Tlemçani, and A. Morsli 43 A Software Application Developed for the PV System Monitoring . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 327 Rachid Dabou, Abderrezzaq Ziane, Ahmed Bouraiou, Ammar Neçaibia, Nordine Sahouane, Abdelkarim Rouabhia, and Seyfallah Khelifi 44 Modeling and Simulation of a Photovoltaic System Connected to the Electrical Network . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 335 Slama Abdelhamid, Hamouda Messaoud, and Chaker Abdelkader 45 Comparative Study of SVC-STATCOM Devices on Voltage Stability Applied on PV-Wind System . . . . . . . . . . . . . . . . . . . . . . . . . . . 343 Souheyla Ben Achour and Omar Bendjeghaba 46 ZnO Films Elaborated by D.C. Magnetron Sputtering . . . . . . . . . . . . 351 Lamia Radjehi, Linda Aissani, and Abdelkader Djelloul 47 First Principles Electro Optical Characterization of Semiconductors Perovskites . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 359 Ahmed Redha Benrekia, Ayoub Nassour, and Sébastien Lebegue 48 Thermal Investigation of a Solar Chimney Power Plant System: CFD Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 367 Hadda Nouar, Toufik Tahri, Younes Chiba, and Abdelghani Azizi 49 Effects of Rim Angle on Performance Predictions of a Parabolic Trough Solar Collector . . . . . . . . . . . . . . . . . . . . . . . . . . . 375 Belkacem Agagna and Arezki Smaili 50 Thermal Performances Investigation of Two ISCC Layouts . . . . . . . 383 Madjid Amani and Arezki Smaili 51 Effect of Turbulence on Wind Turbine Farm Power Production . . . . 393 Said Zergane and Arezki Smaili 52 Maximum Power Point Tracking Method Using Sliding Mode Extremum-Seeking Algorithm for Residential Wind Turbine . . . . . . 401 A. Abbadi, F. Hamidia, Y. Chiba, and A. Tlemcani 53 Thermal Investigation of an Electrocaloric Refrigeration Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 409 Brahim Kehileche, Younes Chiba, and Abdelhalim Tlemçani 54 Electronic and Thermoelectric Properties of Lead Sulfide PbS: DFT Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 417 Fatma Zohra Fouddad, Latifa Bouzid, and Said Hiadsi

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55 Comparison Between Methanol and Methane Steam Reforming Reactors for Hydrogen Production . . . . . . . . . . . . . . . . . . . 427 Abou Houraira Abaidi and Brahim Madani

About the Editors

Younes Chiba is currently an associate professor on Mechanical Engineering Department, Faculty of Technology, University of Médéa, Algeria, since 2006. He specializes in Clean Energy and Materials. He received his M.Sc. in HVAC systems from Constantine University, Algeria, in 2005 and his Ph.D. in Mechanical Engineering from the National Polytechnic School, Algiers, in collaboration with the university of Western Switzerland from 2011, 2012 and 2013. He is the supervisor of many Ph.D. theses and masters in Algeria. Recently, he is reviewer in certain prestigious international journal. He has published more than 50 papers, and his research interests include the renewable energies, energy conversion and magnetocaloric materials. Abdelhalim Tlemçani received the B.Sc. and M.Sc. degrees in power electronics and the Ph.D. degree in electrical engineering from the National Polytechnic School of Algiers, Algeria, in 1997, 1999 and 2007, respectively. In 2002, he was a lecturer and researcher with the Department of Electrical Engineering, Université Docteur Yahia Farès de Médéa, Médéa, Algeria, where he is currently a professor. He is the Director of the Control and Power Electronics Research Group. His research interests include power electronics, electrical drives, robust and nonlinear control, and fuzzy systems. Arezki Smaili is a full professor of Mechanical Engineering and Director of Research Laboratory of Mechanical Engineering (Laboratoire de Génie Mécanique et Développement, LGMD), at Ecole Nationale Polytechnique (ENP), Algiers. He received his M.Sc. in Mechanical Engineering from Laval University, Québec (Canada), in 1991 and his Ph.D. in Energy Sciences from Université du Québec (Canada) in 1998. He joined the ENP in 2006. He was formerly research scientist in the Wind Energy Laboratory at Ecole de technologie supérieure, Montreal (Canada). He has been involved with wide range of energy conversion applications, particularly in the area of thermal analysis of renewable energy systems and aerodynamics of wind turbines since the 1992. He has supervised more than 10 Ph.D. theses, and his research has produced more than 100 technical papers published in international journals and proceedings. xiii

Chapter 1

Fabrication of Flexible Photovoltaic Cells Ourida Ourahmoun

Abstract Etching of Indium Tin Oxide (ITO) is an important step in the realization of organic photovoltaic cells. In the case of a glass substrate, the etching is carried out by hiding the areas that are to be preserved by varnish, then the samples are put in hydrochloric acid HCl, after that the samples will be cleaned in alcohols baths: acetone, ethanol and isopropanol. In the case of flexible substrates, the use of acetone to remove the varnish damages the plastic substrate. The solution to remedy this degradation is to use new technic which is photolithography. Flexible solar cells are made. The transparent electrode consists of ITO deposited on polyethylene terephthalate (PET). The active layer is composed on poly (3-hexylthiophene-2,5diyl) (P3HT) and methyl ester of butyric acid [6,6]-phenyl C61 (PCBM). Poly (3,4ethylenedioxythiophene)-polystyrene sulfonate of aluminum. The structure of the final device is: PET/ITO/PEDOT:PSS/P3HT:PCBM/Al. the results obtained show that photolithography etching is an efficient technic for determining the geometry of the electrodes without causing damage to the plastic substrates. Keywords Photolithography · Flexible substrates · PET · Organic solar cells · Etching

1.1 Introduction Organic solar cells have attracted much attention in the recent years due to their many intrinsic advantages: flexibility, low cost, solution processing, large quantities and easy device fabrication. Power conversion efficiency of 13% is achieved in devices with bilayer interlayer [1]. The reliability of organic solar cells is improved by using hybrid materials for electron transport [2]. A conversion efficiency of 8% is achieved using new small molecule donor [3]. Cells with electrodes without indium are produced, with a yield of about 3.5% [4]. Purely plastic cells are developed using PEDOT:PSS electrodes. The use of nanoparticles such as SiO2 improves the O. Ourahmoun (B) Electronic Department, University of Mouloud Mammeri of Tizi-Ouzou, 15000 Tizi Ouzou, Algeria © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 Y. Chiba et al. (eds.), Advances in Green Energies and Materials Technology, Springer Proceedings in Energy, https://doi.org/10.1007/978-981-16-0378-5_1

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performances of organic cells [5]. Replacing the hole transport layer PEDOT:PSS with the hydrophobic P3HT-Si improves the lifetime of the organic devices [6]. The electrical and optical properties of P3HT are very sensitive to the presence of oxygen and water, as well as in contact with the different metals and oxides that are used as electrodes [7]. It is necessary to encapsulate the cells to improve their stability and protect them against the causes of degradation. The conventional organic photovoltaic cell consists of a stack of five layers: the transparent anode (ITO), which is covered with a hole transport layer (HTL), the active layer, electron transport layer (ETL) and metallic cathode (Al). There are different TCOs used as electrodes, such as, ITO, ZnO, SnO2 , FTO Al-doped ZnO (AZO) and In-doped ZnO (IZO) [8]. To made purely flexible solar cells, conductive polymers are used such as graphene oxide (GO) and silver nanowire (AgNW) deposited on PET [9]. The flexible solar cells fabricated using the roll-to-roll technology exhibited a power conversion efficiency of 1.88% [10]. Multilayer structure anode structure enhances the performances of the cells [11]. The argon ion treatment of the polyethylene terephthalate (PET) substrate improve the flexibility of the ITO electrode [10]. The internal quantum efficiency of a solar cell depends on its intrinsic material properties, such as its crystallinity, energy band gap, carrier transport behavior and the number of defects and impurities [12]. Thermal annealing improves photocurrent as well as interface between organic layers and metal electrodes due to the reduction of interface defects [13]. Metallic nanogratings integrated with an indium tin oxide electrode is a possible approach to improve light absorption property in the active layer [14]. Several techniques are used to deposit the polymer layers onto flexible or glass substrates. Spin coating, doctor blading, printing, brush painting and roll-to-roll-technology [15]. Flexible tandem solar cells with polyether sulfone (PES) substrate showed the same efficiency with device on glass substrate [16]. The parameters of ITO such as resistivity, carrier concentration, transmittance, surface morphology and work function depend on the surface treatments and significantly influence the performances of the solar cells [17]. In this study the photolithography is used to define the electrode geometry of the flexible solar cells. A new Etching technology by photolithography for plastic substrate (PET/ITO) is presented. The parameters of the organic solar cells PET/ITO/P3HT:PCBM/Al and Glass/ITO/P3HT:PCBM/Al such as current density J(V), open circuit voltage VOC , Fill Factor (FF), and the short current density (Jsc) are giving.

1.2 Fabrication Method of the Flexible Cell 1.2.1 ITO Etched by Photolithography Polyethylene Terephthalate (PET) is used as substrate for flexible solar cells. The photolithographic process follows the following steps as shown in Fig. 1.1:

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Fig. 1.1 Steps of photolithography process used to etch ITO

• The PET/ITO substrate is spin coated with a photoresist (resin S1828) to form uniform ~3 μm thin film on the surface. • The substrate is exposed with ultraviolet light through a mask which contains a desired design of the electrodes. The photolithography device (Insolator) used to harden the resin is shown in Fig. 2A.

Fig. 1.2 A Insolator used to harden the photoresist S1828, B Influence of the emersion time of the resin PRP 200 in developer (sodium hydroxide) on the quality of the development; (a) t = 180 s, (b) t = 120 s and (c) t = 90 s

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Fig. 1.3 Transmittance of the PET/ITO substrate after photolithography etching

• The photoresist is developed. • The samples are etching with HCl heated at 90 °C. • The samples were immersed in the developer to remove the photoresist. Finally, substrates were cleaned with isopropanol. The advantages of this method is that acetone is not used. Because acetone damages the organic layers. For a concentration developer 1.5 g of sodium hydroxide in 200 ml of water, if the development time is greater than 90 s, there is overdevelopment as shown in Fig. 2B.a. The disadvantages of the resin PRP 200 is the presence of holes in ITO layer after etching, from which we opted for the use of the photosensitive resin S 1828 used in clean room. The optical properties of ITO etched using photolithography method are measured by means of UV transmittance device. The transmittance is taken about 90% in visible spectrum as shown in Fig. 1.3.

1.2.2 Realization of the Flexible Solar Cells The flexible solar cell is based on a blend of poly(3-hexylthiophene-2,5-diyl) (P3HT) and [6,6]-phenyl C61 butyric acid methyl ester (PCBM). The PET substrate covered by transparent electrode indium tin oxide (ITO) are etched with photolithography technic, then treated by UV ozone for 30 min. Afterwards, polyethylene dioxythiophene:polystyrene sulfonate (PEDOT:PSS) was spin coated on the substrate in order to form a hole transport layer (HTL). A film about 180 nm thick of blend of P3HT:PCBM with a weight ratio of (1:1) in chlorobenzene was further spin coated on Pedot. Finally, an Al cathode (90 nm thick) was evaporated at 3.10−6 mbar, through

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Fig. 1.4 a Structure of the organic solar cell with flexible substrate: PET/ITO/PEDOT:PSS/P3HT:PCBM/Al, b J-V characteristics under illumination of organic solar cells with Glass ITO substrate and PET/ITO substrate

a shadow mask delimiting à 0.18 cm2 solar cell area. The cells are annealed at 110 °C for 30 min in the glove box. To compare between performances of organic solar cells with flexible substrate and cells with glass substrates, a structure with glass substrate is realized. The direct structure of the flexible solar cell realized is illustrated in Fig. 4a.

1.3 Results and Discussion The J-V characteristics under standard AM1.5 illumination of the representative P3HT:PCBM cell with PET/ITO or Glass/ITO substrates were measured in the glove box. The light intensity of the solar simulator is 100 mW/cm2 . The results presented in Fig. 4b show that cells with glass substrates have better performances than with PET substrates. The difference in the performances is attributed to a decrease in current density (JSC ). JSC of glass/ITO substrate is 8.87 mA/cm2 and the JSC of cells with PET/ITO is 6.67 mA/cm2 . The photocurrent generated is limited by transparency of the substrate, because the transparency of the glass substrate is slightly higher than the transparency of the flexible PET substrates. Even if the yield of flexible cells is lower than the yield of cells deposited on glass, flexible cells have several advantages. The advantage of using flexible substrates is the production of cheaper, lightweight, flexible photovoltaic cells with larges areas and unbreakable.

1.4 Conclusion The use of acetone to remove the varnish and the cleaning of plastic substrates is unhelpful as the acetone damages the organic layers. The solution found for etching

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the ITO deposited on PET without using acetone is photolithography. This method is non-destructive and gives interesting results. Results show that photolithography is an efficient technic for the realization of flexible organic solar cells. to improve the performance of flexible photovoltaic cells it is necessary to optimize the etching parameters of the ITO, such as: the thickness of the photoresist, the duration of the development, the concentration of the developer, the thermal annealing, the duration of exposure to the UV radiation of the insolator. Photovoltaic devices including dye solar cells, organic solar cells and perovskite solar cells can be made flexible using plastic substrates (PET or PEN), so it is necessary to understand and master the manufacturing technology including the etching of substrates.

References 1. M.B. Upama, N.K. Elumalai, M.A. Mahmud, C. Xu, D. Wang, M. Wright, A. Uddin, Enhanced electron transport enables over 12% efficiency by interface engineering of non-fullerene organic solar cells. Solar Energy Mater. Sol. Cells 187, 273–282 (2018) 2. Z. Li, Z.C. Liu, J. Guo, Y. Zhou, I. Shen, W. Guo, Passivation effect of composite organic interlayer on polymer solar cells. Org. Electron. 63, 129–136 (2018) 3. C. Ye, Y. Wang, Z. Bi, X. Guo, Q. Fan, J. Chen, M. Zhang, High-performance organic solar cells based on a small molecule with thieno [3, 2-b] thiophene as π-bridge. Org. Electron. 53, 273–279 (2018) 4. U.J. Lee, S.H. Lee, J.J. Yoon, S.J. Oh, S.H. Lee, J.K. Lee, Surface interpenetration between conducting polymer and PET substrate for mechanically reinforced ITO-free flexible organic solar cells. Sol. Energy Mater. Sol. Cells 108, 50–56 (2013) 5. P. Shao, X. Chen, X. Guo, W. Zhang, F. Chang, Q. Liu, D. He, Facile embedding of SiO2 nanoparticles in organic solar cells for performance improvement. Org. Electron. 50, 77–81 (2017) 6. H. Awada, G. Mattana, A. Tournebize, L. Rodriguez, D. Flahaut, L. Vellutini, S. Chambon, Surface engineering of ITO electrode with a functional polymer for PEDOT: PSS-free organic solar cells. Org. Electron. 57, 186–193 (2018) 7. G.C. Faria, D.J. Coutinho, H. Von Seggern, R.M. Faria, Doping mechanism in organic devices: effects of oxygen molecules in poly (3-hexylthiophene) thin films. Org. Electron. 57, 298–304 (2018) 8. M. Murugesan, D. Arjunraj, J. Mayandi, V. Venkatachalapathy, J.M. Pearce, Properties of Aldoped zinc oxide and In-doped zinc oxide bilayer transparent conducting oxides for solar cell applications. Mater. Lett. 222, 50–53 (2018) 9. K. Naito, R. Inuzuka, N. Yoshinaga, W. Mei, Transparent conducting films composed of graphene oxide/Ag nanowire/graphene oxide/PET. Synth. Met. 237, 50–55 (2018) 10. K.H. Choi, J.A. Jeong, J.W. Kang, D.G. Kim, J.K. Kim, S.I. Na, H.K. Kim, Characteristics of flexible indium tin oxide electrode grown by continuous roll-to-roll sputtering process for flexible organic solar cells. Sol. Energy Mater. Sol. Cells 93(8), 1248–1255 (2009) 11. H.W. Tsai, Z. Pei, C. Chen, S.J. Cheng, W.S. Hsieh, P.W. Li, Y.J. Chan, Anode engineering for photocurrent enhancement in a polymer solar cell and applied on plastic substrate. Sol. Energy Mater. Sol. Cells 95(2), 611–617 (2011) 12. S.Y. Chuang, C.C. Yu, H.L. Chen, W.F. Su, C.W. Chen, Exploiting optical anisotropy to increase the external quantum efficiency of flexible P3HT: PCBM blend solar cells at large incident angles. Sol. Energy Mater. Sol. Cells 95(8), 2141–2150 (2011)

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13. S. Kim, S. Ryu, Efficiency of flexible organic solar cells as a function of post-annealing temperatures. Curr. Appl. Phys. 10(4), 181–184 (2010) 14. D.A. Gollmer, F. Walter, C. Lorch, J. Novák, R. Banerjee, J. Dieterle, M. Fleischer, Fabrication and characterization of combined metallic nanogratings and ITO electrodes for organic photovoltaic cells. Microelectron. Eng. 119, 122–126 (2014) 15. S.W. Heo, K.W. Song, M.H. Choi, T.H. Sung, D.K. Moon, Patternable solution process for fabrication of flexible polymer solar cells using PDMS. Sol. Energy Mater. Sol. Cells 95(12), 3564–3572 (2011) 16. B.J. Lee, H.J. Kim, W.L. Jeong, J.J. Kim, A transparent conducting oxide as an efficient middle electrode for flexible organic tandem solar cells. Sol. Energy Mater. Sol. Cells 94(3), 542–546 (2010) 17. Y.T. Cheng, J.J. Ho, C.K. Wang, W.L. Lee, C.C. Lu, B.S. Yau, K.L. Wang, Improvement of organic solar cells by flexible substrate and ITO surface treatments. Appl. Surf. Sci. 256(24), 7606–7611 (2010)

Chapter 2

Effect of Solution Concentration in the Optical and Electrical Properties of Copper Oxide Thin Films L. Herissi, L. Hadjeris, Z. Moussa, L. Hafsa, S. Djebabra, B. Herissi, A. Sari, and S. Bouchrit Abstract The aim of this work is the study of the effect of solution concentration in the optical and electrical properties of copper oxide thin films deposited by ultrasonic spray pyrolysis technique in order to obtain good photoelectric properties which makes it an important candidate in many technological applications. These films are elaborated onto glass substrates from an aqueous solution of copper (II) chloride dihydrate with different solution concentrations. Substrate temperature, nozzle-substrate distance, and deposition time were kept constant during the whole deposition process. After the deposition, we annealed these films in air at 400 °C for 120 min. UV-Visible spectrophotometry and the four-point method were used to evaluate the optical and electrical properties, the films obtained are p-type semiconductors, high optical absorption in the UV-Visible domains, rough surface with good adhesion to the substrate. Optical and electrical properties of undoped copper oxide thin films varied by the variation of solution concentration. Keywords Thin films · Copper oxide · Spray pyrolysis · Annealing · Solution concentration · Electrical properties · Optical absorption

2.1 Introduction Copper forms two different oxides such as cupric oxide (CuO) and cuprous oxide (Cu2 O). CuO is a black color material, n-type semiconductor with bandgap of 1.21– 1.51 eV [1, 2]. Cu2 O is a brown yellowish material, p-type semiconductor and has a bandgap of 2.1 eV [1]. Spray pyrolysis deposition (SPD) has the advantages of setup easiness, cost-effective, and flexibility over the plasma film deposition methods L. Herissi (B) · A. Sari · S. Bouchrit Matter Sciences Department, Larbi Tebessi University, 12000 Tebessa, Algeria L. Herissi · L. Hadjeris · Z. Moussa · L. Hafsa · S. Djebabra LMSSEF, Larbi Ben M’Hidi University, 04000 Oum El Bouaghi, Algeria B. Herissi Department of Electronic and Telecommunication, University 8 May 1945, 24000 Guelma, Algeria © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 Y. Chiba et al. (eds.), Advances in Green Energies and Materials Technology, Springer Proceedings in Energy, https://doi.org/10.1007/978-981-16-0378-5_2

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[3]. Large surface CuO films can thus be deposited under atmospheric conditions on substrates from low-priced chemicals, while monitoring the preparation process step by step [4]. However, the physical and chemical properties of the films thus prepared depend on the process parameters [5]. The aim of this work is to study the experimental conditions in order to obtain optimum deposition parameters yielding CuO films with the desired physical properties for particular applications.

2.2 Experimental Procedure The copper oxide films were deposited by ultrasonic spray pyrolysis technique (Fig. 2.1) from solution of copper (II) chloride dihydrate (CuCl2 ·2H2 O) dissolved in doubly distilled water onto glass substrates with different solution concentration (0.02, 0.04, 0.05, 0.08, and 0.1 mol/l). Substrate temperature, nozzle-substrate distance, and deposition time were kept constant during the whole deposition process at 300 °C, 3 cm, and 5 min, respectively. After the deposition, we annealed these films in air at 400 °C for 120 min. The transmittance of the films deposited on glass was measured in the UV-Visible region using a double beam spectrophotometer (Shimadzu 3101PC). The gap energy E g of the ZnO films deposited on glass substrates was determined from their transmittance T (λ). The absorption coefficient α (λ), in the spectral region of absorption of the light, was deduced from the Beer-Lambert law [6]:

Fig. 2.1 Experimental device used to deposit thin films by ultrasonic spray pyrolysis technique; 1. Glass substrates on an electrical resistance, 2. Digital thermocouple, 3. Solution to deposit, 4. Flow rate controller, 5. Nozzle, and 6. Ultrasonic generator

2 Effect of Solution Concentration in the Optical and Electrical …

α=

  100 1 ln d T (%)

11

(2.1)

That according to the Tauc’s theory for the direct allowed transitions such as those occurring in the direct gap of CuO, α (hν) close to the band edge is [3]: (αhυ)n = A(hυ − E g )

(2.2)

where A is a constant of proportionality and hν is the energy of the incidental light photons. Eg can be estimated by extrapolating to the hν—axis the linear part of the (αhν)2 curve. The film thickness and refractive index were deduced from the Swanepoel’s envelope method that are deduced from the variation of the optical transmittance as a function of the wavelength for each film which gives very convergent values [7]. The typical variation of (Lnα) versus photon energy of copper oxide thin film for deduce the Urbach energy, which is related to the disorder in the film network, is expressed as [8]:  α = α0 . exp

hυ E 00

 (2.3)

Electrical conductivity were measured using four-point-probe method by the following expression [8]: σ =

ln 2 I . π. d V

(2.4)

2.3 Results and Discussions Figure 2.2 shows the typical spectra of the variation of the optical transmittance of copper oxide thin films as a function of the wavelength of incident photon in the UV-Vis-NIR range (200–1100 nm) obtained from the solution of copper (II) chloride dihydrate prepared by ultrasonic spray pyrolysis technique with precise experimental conditions after annealing under air for tR = 120 min at TR = 400 °C. In this work, the values of the optical transmittance at 1100 nm are decreased before annealing from 53 to 22% and 51 to 16% after annealing with the increase of the solution concentration from 0.02 to 0.08 mol/l. The decrease in optical transmittance by increasing the solution concentration may be due to the increase in the thickness of the thin films and its surface roughness [9], and also the color change of our films [2]. The optical transmittance of the sample of 0.1 mol/l and more transparent compared to the sample of 0.08 mol/l since the film made with a high molarity (0.1 mol/l) is more porous than the sample of 0.08 mol/l [10]. As can also be note that

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Fig. 2.2 Variation of optical transmittance of copper oxide thin films versus wavelength for different values of the solution concentration after annealing under air

the increase of the solution concentration leads to a displacement of the absorption threshold towards the long wavelengths. By annealing, the optical transmittance at λ = 1100 nm of all films is decreased slightly by comparing with the spectrum of the optical transmittance before annealing, this decrease can be explained by the decrease of the porosity, the surface roughness and the vacuum in the layers “T(λ < 300 nm) = 0%” by annealing. It is also observed that the annealing decrease difference (δT) is decreased with the increase in energy of the incident photons. Figure 2.3 shows the variation of the film thickness and refractive index of copper oxide (Cux O) after annealing under air as a function of the solution concentration. 2.8

400

After annealing)

380

2.6

360

2.4

340

2.2

320

2.0

300

0.02

0.04

0.06

0.08

0.10

Refractive index

Film thickness (nm)

Copper oxide

1.8

Solution concentration (mol/l)

Fig. 2.3 Variation of the film thickness and refractive index of copper oxide thin films versus wavelength for different values of the solution concentration after annealing under air

2 Effect of Solution Concentration in the Optical and Electrical …

13

2.2

0.52

After annealing)

Copper oxide

0.50 0.48

2.0

0.46

1.9

0.44 1.8 0.42 1.7

0.40

1.6

0.38

1.5 1.4

Urbach energy (eV)

Optical gap energy (eV)

2.1

0.36 0.02

0.04

0.06

0.08

0.10

0.34

Solution concentration (mol/l)

Fig. 2.4 Variation of the optical gap energy and Urbach energy of copper oxide thin films versus wavelength for different values of the solution concentration after annealing under air

With the increase the concentration of solution from 0.02 to 0.1 mol/l, the both increase of the film thickness and refractive index of copper oxide (Cux O) from 336 to 393 nm and 1.9 to 2.7, respectively. As can be interpreted these increases by the increase in the quantity of material deposited (there is more material which contributes to the formation of the film), the existence of the porosity in the film, the gradation in color (light brown to black) with the increase in the concentration of solution [9, 11]. Figure 2.4 shows the variation of the optical gap energy and Urbach energy of copper oxide (Cux O) after annealing under air as a function of the solution concentration. With the increase the concentration of solution from 0.02 to 0.1 mol/l, the E g decreasing is due to the increase in both the Urbach energy and the refractive index, several authors have found an indirect correlation between the Urbach energy and the optical gap energy [11]. This remark can be explained by the decrease of the grain size, more disorder, the gradation in color (light brown to black) with the increase in the solution concentration [9–11]. The E g is decrease with the increase of the concentration of solution, it is noted that the optical gap values indicate that the films deposited at 0.02 and 0.04 mol/l have cuprous oxide (Cu2 O) phase structures, whereas the films deposited at 0.05 and 0.08, and 0.1 mol/l have cupric oxide (CuO) phase structures [2]. This phase difference is due to the kinetics of the formation of copper oxides during thin film deposition which depends on a number of factors such as the solution concentration and the amount of deposited materials [11]. The minimum value of the Urbach energy of the film deposited at 0.1 mol/l is logical, reason why this sample has a single crystalline phase and its optical gap is closer to the solid state of CuO [12]. Figure 2.5 shows the influence of the solution concentration on the electrical conductivity of thin films.

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Copper oxide Electrical conductivity ((Ω.cm)-1)

After annealing

2.5x10-3

2.0x10-3

1.5x10-3

0.02

0.04

0.06

0.08

0.10

Solution concentration (mol/l)

Fig. 2.5 Variation of the electrical conductivity of copper oxide thin films as a function of solution concentration

The electrical conductivity of the films increases with the increase of the concentration of solution. These increases can be interpreted by increasing the concentration of charge carriers [10, 11], and also the effect of phase change in the sample structure (from Cu2 O to CuO) [2].

2.4 Conclusion Copper oxide thin films deposited onto glass substrates by ultrasonic spray pyrolysis technique with different solution concentrations. The films obtained are p-type semiconductors, high optical absorption in the UV-Visible domains, rough surface with good adhesion to the substrate. Optical and electrical properties of copper oxide thin films varied by the variation of solution concentration.

References 1. R.P. Wijesundera, M. Hidaka, K. Koga, J.Y. Choi, N.E. Sung, Structural and electronic properties of electrodeposited heterojunction of CuO/Cu2 O. Ceramics-Silikàty 54, 19–25 (2010) 2. A.H. Jayatissa, K.A. Guo, C. Jayasuriya, Fabrication of cuprous and cupric oxide thin films by heat treatment. Appl. Surface Sci. 255, 9474–9479 (2009) 3. L. Herissi, L. Hadjeris, M.S. Aida, J. Bougdira, Properties of (NiO)1–x (ZnO)x thin films deposited by spray pyrolysis. Thin Solid Films 605, 116–120 (2016) 4. S. Roy, S. Basu, Improved zinc oxide film for gas sensor applications. Bull. Mater. Sci. 25, 513–515 (2002)

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5. W.T. Seeber, M.O. Abou-Helala, S. Bartha, D. Beila, T. HoÈ chea, H.H. Afify, S.E. Demian, Transparent semiconducting ZnO:Al thin films prepared by spray pyrolysis. Mater. Sci. Semicond. Process. 2, 45–55 (1999) 6. A. Bougrine, A. El Hichou, M. Addou, J. Ebothé, A. Kachouna, M. Troyon, Structural, optical and cathodoluminescence characteristics of undoped and tin-doped ZnO thin films prepared by spray pyrolysis. Mater. Chem. Phys. 80, 438–445 (2003) 7. L. Herissi, L. Hadjeris, M.S. Aida, S. Azizi, A. Hafdallah, A. Ferdi, Ni-doped ZnO thin films deposited by pneumatic spray pyrolysis. Nano Hybrids Compos. 27, 21–29 (2019) 8. L. Mustafa, S. Anjum, S. Waseem, S. Bashir, K. Mahmood, M. Saleem, E. Ahmad, Structural and optical properties of ZnO co-doped with Co and Ni thin films deposited by pulse laser deposition technique. Optik 161, 54–63 (2018) 9. F.Z. Chafi, A. Hadri, C. Nassiri, B. Fares, L. Laanab, N. Hassanain, A. Mzerd, Undoped CuO deposited by spray pyrolysis technique. J. Mater. Environ. Sci. 7, 170–175 (2016) 10. L. Herissi, L. Hadjeris, H. Moualkia, N. Abdelmalek, N. Attaf, M.S. Aida, J. Bougdira, Realization and study of ZnO thin films intended for optoelectronic applications. J. New Technol. Mater. 1, 39–43 (2011) 11. L. Herissi, L. Hadjeris, N. Attaf, M.S. Aida, A. Hafdallah, W. Daranfad, Réalisation et étude de couches minces de ZnO transparentes et conductrices. Alger. J. Adv. Mater. 4, 415–418 (2008) 12. A. Jareeze, Optical properties, structure, and morphology of CuO grown by thermal oxidation of Cu thin film on glass substrate. J. Kufa Phys. 6, 36–41 (2014)

Chapter 3

IR Spectroscopy and Computational Study of Structural, Vibrational and Electronic Properties of Hydrindantin Dihydrate Abdelali Boukaoud, Younes Chiba, Khoukha Fatimi, Nassima Yahimi, Fatima Zohra Meguellati, and Souad Bouguettaya Abstract The experimental FT-IR spectrum of hydrindantin dihydrate (C18 H10 O6 . 2H2 O) has been investigated for the first time. The vibrational spectral signatures of OH stretching modes have been analyzed by using the results of density functional theory (DFT) calculations performed in the solid state. These results have shown that the IR bands due to the asymmetric (υas OH) and symmetric (υs OH) stretching modes of water molecules are overlapped in the large band centered at 3433 cm−1 in the experimental spectrum. While, the stretching bands due to the OH groups of hydrindantin molecules are red shifted to 2831 cm−1 owing to the formation of strong inter-molecular O–H···O hydrogen bonds with adjacent water molecules. Moreover, this study has been extended to reveal some calculated electronic properties of the isolated hydrindantin molecule. Keywords Hydrindantin dihydrate · IR spectroscopy · DFT calculations · H-bonds

A. Boukaoud (B) Laboratoire de Physique des Techniques Expérimentales et ses Applications, Université de Médéa, Medea, Algeria e-mail: [email protected] Y. Chiba Department of Mechanical Engineering, Faculty of Science and Technology, University of Medea, Medea, Algeria A. Boukaoud · K. Fatimi · N. Yahimi · F. Z. Meguellati · S. Bouguettaya Département des Sciences de la Matière, Faculté des Sciences, Université de Médéa, Medea, Algeria © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 Y. Chiba et al. (eds.), Advances in Green Energies and Materials Technology, Springer Proceedings in Energy, https://doi.org/10.1007/978-981-16-0378-5_3

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3.1 Introduction Hydrindantin dihydrate (C18 H10 O6 . 2H2 O) can be used as a reagent for the determination of amino acids [1]. In the solid state, the hydrindantin and water molecules are linked by inter-molecular O–H···O hydrogen bonds (H-bonds) to form a three dimensional molecular arrangement. These interacting molecules are also linked by inversion centers which coincide with the symmetry centers of hydrindantin molecules [2]. The incorporation of H2 O molecules into the crystal structure of the underinvestigated compound will certainly complicate the assignment of the observed IR bands in the OH stretching region. In some cases, the knowledge of crystallographic information, especially the H-bond geometries, can to some extent facilitate the assignment of the IR bands arising from the OH stretching vibrations [3]. However, the best way to assign such bands is to compare the results of DFT performed in the solid state with the experimental ones obtained from the vibrational spectra [4]. Here, a combination of theoretical and experimental studies is performed to explore the OH stretching region of the experimental IR spectrum of the titled compound. To the best of our knowledge, the current study is the first which analyses the vibrational behavior and electronic properties of hydrindantin dihydrate using IR spectroscopy and DFT calculations. Thus, we hope here to achieve two main aims: the first one is to better understand the H-bonding effects on the vibrational modes in order to properly assign the measured IR bands situated in the region 1400–3400 cm−1 . The second aim is devoted to study theoretically some electronic properties of the isolated hydrindantin molecule.

3.2 Experimental Details A commercial sample of hydrindantin dihydrate, in powder form, was used without further purification to prepare a mixture containing 1% of hydrindantin dihydrate and 99% of potassium bromide (KBr). The mixture was then pressed to form a pellet for the IR spectral measurements. The obtained spectrum was recorded at room temperature in the wavenumber range of 400–4000 cm−1 , using a FTIR-8400 Spectrometer. The spectral resolution of the spectrometer was 4 cm−1 .

3.3 Computational Details All the periodic DFT calculations presented here were carried out by using the GGA (generalized gradient approximation) at the PBE (Perdew–Burke–Ernzerhof) functional [5]. The norm-conserving pseudopoentials were used to describe the ionelectron interactions and a kinetic energy cutoff of 830 eV of the plane-wave basis

3 IR Spectroscopy and Computational Study of Structural, …

19

set was used. The harmonic vibrational wavenumbers are calculated at the G point employing the DFPT (density functional perturbation theory) [6]. On the other hand, all the non-periodic DFT calculations were preformed in the gas phase using the B3LYP functional [7, 8] and the 6-311G(d,p) basis set.

3.4 Results and Discussion 3.4.1 Structural Optimization Figure 3.1a shows the optimized molecular structure of hydrindantin in the gas phase obtained by the B3LYP functional. The optimized crystal structure of hydrindantin2H2 O in the solid phase is presented in Fig. 3.1b. In agreement with the experimental results [2], our calculations show that hydrindantin-2H2 O adopts the monoclinic system with the space group P21 /c. The calculated lattice parameters in comparison with the experimental ones are listed in Table 3.1. The H-bonds present in hydrindantin-2H2 O crystal are clearly shown in Fig. 3.1b. In accordance with the previously reported crystal structure [2], each molecule, hydrindantin/water, is hydrogen donor in two inter-molecular O–H···O H-bonds. Table 3.2 shows a comparison between the calculated H-bond geometries and the corresponding ones obtained from the X-Ray experiment.

Fig. 3.1 Optimized structures obtained by DFT calculations: a optimized molecular structure of hydrindantin in the gas phase; b optimized unit cell of hydrindantin-2H2 O in the solid phase

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Table 3.1 Predicted lattice parameters for hydrindantin-2H2 O in comparison with the experimental results

Lattice parameters

Theoretical

Experimental [2]

a (Å)

8.4376

8.4479 (4)

b (Å)

12.5633

12.4759 (6)

c (Å)

7.7256

β(°)

100.304

7.9293 (4) 100.634 (3)

Table 3.2 Predicted H-bond parameters for hydrindantin-2H2 O in comparison with the experimental results A-H···B

A···B (Å)

H···B (Å)

DFT/PBE

X-raya

O2 -H… O1W

2.561

O1W -H1W… O3 O1W -H2W… O1

0, C44 > 0 and C11 − C12 > 0, these conditions are observed for KNO, and CTO.

47.3.2 Electronic Properties 47.3.2.1

Bandstructures

Like in our previous paper [1], the bandstructure for CTO and KNO are along the high symmetry lines -X-M--R-X. We have the same behavior structures for KTO and STO. For all the compounds the top of the valence band is at R point and the bottom of the conduction band is at  point, this means that the gap in indirect. The results of our calculated with PBE, GW, the results of other authors and the experimental values are giving in Table 47.2. These are the triplets of PBE, GW calculated and

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Table 47.2 Direct and indirect gap in eV Compound

KNbO3

KTaO3

CaTiO3

SrTiO3

Direct PBE

1.54

2.70 [1]

2.15

2.10 [1]

Direct GW

3.50

4.32 [1]

4.28

4.38 [1]

Other

2.40 [5]

3.10 [1]

4.11 GW [9]

5.42 GW [1]

Experimental

4.35 [1]

3.75 [1]

Indirect PBE

0.95

2.08 [1]

1.73

1.76 [1]

Indirect GW

2.78

3.57 [1]

3.78

3.82 [1]

Other

1.46 [5]

2.51 [1]

3.62 GW [9]

5.05 [1]

Experimental

3.30 [5]

3.64 [1]

3.57 [9]

3.25 [1]

experimental values of the gap energies in eV (0.95:2.78:3.30), (2.08:3.57:3.64), (1.73:3.78:3.50) and (1.76:3.82:3.25). As mentioned in the introduction, the results with DFT are lower than the real and the difference exceeds 1.5 eV. However, the difference between the GW calculated values and the real one is around 0.5 eV.

47.3.3 Electronic Properties 47.3.3.1

Partial Density of States

To study the partial densities of states, we consider the range [−20:10] eV which covers the states from the lowest valence bands (LVB) to the highest conduction bands (HCB). KNbO3 : In the lowest part of the valence bands, there is a band from −17.0 to −15.8 eV dominated by O (2 s) state and slightly hybridized with Nb (4d) states, followed by a sharp band with a 0.25 eV bandwidth around −11.0 eV corresponding to K (3p) states. Closer to the band gap (from −5.2 to 0.0 eV), the bands are mainly made of Nb (4d) and O (2p) states hybridized with p states from K and Nb. The conduction bands are made of two structures, dominated by the Nb (4d) states hybridized with O (2p) states. CaTiO3 : In LVB, we observe a band from −17.6 to −16.0 eV dominated by O (2 s) states hybridized with few Ti (4 s), (3p) in and (3d) states. Then at higher energy we find the upper valence bands from −4.8 eV to 0 eV, which correspond to O (2p) and Ti (3d, 3p and 4 s) states. Above the gap, there are bands from 1.8 to 4.5 eV dominated by Ti (3d t2g ) states and few Ca (3d) states, while from 4.9 to 6.4 eV the states correspond to Ca (3d) and Ti (3 deg) states. These results are in line with the experimental data [10].

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47.3.4 Optical Properties The optical functions such as the real (ε1 ) and the imaginary (ε2 ) parts of the dielectric function are calculated using the PBE functional. A scissor shift is applied to the calculated spectrum due to the underestimation of the band gap by the PBE approximation. This shift is equal to the difference between the two direct gaps obtained from DFT(PBE) and the one from GW. The shift is about is 1.83 eV for KNO and 1.49 eV 2.05 eV for CTO. The knowledge of the imaginary ε2 , and therefore, the real ε1 dielectric function allows the evaluation of electron energy loss spectroscopy (EELS). The EELS calculated in such a way, can be compared to the experimental one where the peaks can be ascribed to transitions in the band structure. In order to get the optical evolution, we use the dielectric function ε(ω) = ε1 (ω) + iε2 (ω) as defined in [1]. KNbO3 for KNO, the edge of ε2 is at 3.5 eV and corresponds to the direct band gap. The observed peaks can be ascribed to direct transitions among the bands. We notice that peaks at 4.7, 5.2, 6.6 and 13.8 eV, it’s 13.6 eV in [5] correspond to the following transitions: Nb-5d t2g > O (2p) and Nb (4d eg ) > O (2p). The peak at17.6 eV can be ascribed to Nb (4d eg ) > K (4p) transitions. CaTiO3 for CTO, the edge of ε2 is at 4.3 eV and corresponds to the direct band gap ( > ) in the band structure. The peaks at 6.4 and 7.3 eV can be attributed to the electronic transitions from the Ti (3d-t2g ) to the O (2p) energy levels and those at 8.8, 9.7, and 10.6 eV can be associated with transitions from the Ti (3d eg ) to the O (2p) levels. The peaks reported in the experimental study are located at 4.0, 5.3, 6.8, 7.5, 8.4, and 9.9 eV [11].

47.3.5 Photoconduction Properties The electric answer of a dielectric material to an electromagnetic wave with a pulsation ω named photoconductivity is shown by the increase of its electrical conductivity due to the increase of free electrons and holes. Its function σ(ω) is connected to the dielectric ε(ω) function and defined by: σ (ω) = σ1 (ω) + iσ2 (ω) = −iε0 ω(ε(ω) − 1)

(47.2)

In Table 47.3, we give the energies of the peaks of the σ1 (ω) which represents the current in phase with the electric field.

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Table 47.3 Peak’s energy of the photoconductivity (S m−1 ) Compound

KNbO3

KTaO3

CaTiO3

SrTiO3

Peak’s energy (eV)

4.10, 5.96, 7.38, 8.90, 9.98, 11.84, 13.31, 14.73, 16.74, 17.58, 22.72, 23.90, 25.42, 25.45, 26.5, 31.20, 34.54, 35.96, 36.70, 37.43, 38.95

4.54, 6.50, 8.66, 10.08, 11.11, 14.49, 16.65, 18.56, 19.34, 22.09, 23.66, 25.18, 26.35, 27.87, 28.75, 29.69, 30.91, 37.87, 39.34

6.41, 8.90, 9.63, 11.74, 15.12, 22.14, 28.90, 38.71

4.59, 6.35, 7.87, 8.95, 10.18, 11.45, 12.33, 18.21, 21.45, 24.88, 27.77, 30.08, 36.74, 38.31, 38.75, 39.74

47.4 Conclusion In this paper, we presented the results of first principles studies of four semiconductor perovskites in their paraelectric phase. We proved the stability of the structures and corrected the gap default of the DFT by the GW approximation. We also gave the electronic structures and the optical properties of those compounds. The results seem acceptable and the photoconductivity part proves that those materials can be used in optoelectronic for some particular applications.

References 1. A.R. Benrekia, N. Benkhettou, A. Nassour, M. Driz, M. Sahnoun, S. Lebègue, Structural, electronic and optical properties of cubic SrTiO3 and KTaO3 : Ab initio and GW calculations. Phys. B 407, 2632–2636 (2012) 2. V. Reymond, Nouvelles couches minces et multicouches dérivées de BaTiO3 : optimisation des propriétés diélectriques. Doctorat thesis, Bordeaux I University (2004) 3. N. Russo, D. Mescia, D. Fino, G. Saracco, V. Specchia, N2 O decomposition over perovskite catalysts. Ind. Eng. Chem. Res. 46, 4226–4231 (2007) 4. Y. Masatomo, A. Roushown, Structural phase transition and octahedral tilting in the calcium titanate perovskite CaTiO3 . Solid State Ionics 180, 120–126 (2009) 5. S. Cabuk, Electronic structure and optical properties of KNbO3 : first principles study. OAM-RC 3(1), 100–107 (2007) 6. P.W.M. Jacobs, E.A. Kotomin, R.I. Eglitis, Semi-empirical defect calculations for the perovskite KNbO3. J. Phys.: Condens. Matter 12, 569–574 (2000) 7. X. Wu, Y. Dong, S. Qin, M. Abbas, Z. Wu, First-principles study of the pressure-induced phase transition in CaTiO3 . Solid State Commun. 136, 416–420 (2005) 8. A.P. Sakhya, J. Maibam, S. Saha, S. Chanda, A. Dutta, B.I. Sharma, R.K. Thapa, T.P. Sinha, Electronic structure and elastic properties of ATiO3 (A = Ba, Sr, Ca) perovskites: A first principles study. Indian J. Pure Appl. Phys. 53, 102–109 (2015)

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9. A. Gierlich, All-electron GW calculations for perovskite transition-metal oxides. doctoral thesis Aachen University, Bonn, Germany (2011) 10. K. Ueda, H. Yanagi, H. Hosono, H. Kawazoe, Study on electronic structure of CaTiO3 by spectroscopic measurements and energy band calculations. J. Phys.: Condens. Matter 11, 3535– 3545 (1999) 11. K. Ueda, H. Yanagi, R. Noshiro, H. Hosono, H. Kawazoe, Vacuum ultraviolet reflectance and electron energy loss spectra of CaTiO3. J. Phys.: Condens. Matter 10, 3669–3677 (1998)

Chapter 48

Thermal Investigation of a Solar Chimney Power Plant System: CFD Approach Hadda Nouar, Toufik Tahri, Younes Chiba, and Abdelghani Azizi

Abstract In this research, thermal investigation was performed on a solar chimney power plant system. 2D numerical model was developed using RANS equations with k-epsilon turbulence model to investigate air flow behavior in the system. The effects of chimney height and heat flux on the flow parameters were analyzed. The results of this study showed that the chimney height and heat flux are important factors for enhancement the performance of solar chimney power plant system. Keywords Solar chimney power plant · Computational Fluid Dynamic · Chimney height

48.1 Introduction Solar chimney power plant (SCPP) is the novel technology which uses the solar energy to produce electricity (Fig. 48.1). It uses the combination of three simple technologies that is collector, chimney and turbine [1]. Solar collector features a transparent roof that heats the air with the radiant energy of the sun, the chimney in the collector center transforms the produced hot air into kinetic energy that is converted into electrical energy by using a combination of a wind turbine and a generator [2].First SCPP prototype constructed in 1982 at Manzanares, Spain. It is distinguished by 200 m of chimney height, 10 m of chimney diameter, 244 m of

H. Nouar (B) · T. Tahri · A. Azizi University of Hassibba Ben Bouali, 02000 Chlef, Algeria e-mail: [email protected] T. Tahri e-mail: [email protected] A. Azizi e-mail: [email protected] Y. Chiba University of Yahia Fares, 26000 Medea, Algeria e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 Y. Chiba et al. (eds.), Advances in Green Energies and Materials Technology, Springer Proceedings in Energy, https://doi.org/10.1007/978-981-16-0378-5_48

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Fig. 48.1 Scheme of solar chimney power plant

collector diameter and 2 m of collector height. This prototype can generate 50 kW of electric power [3]. In the literature study, it is found that several studies focus on flow parameters and its analysis of Solar Chimney Power Plant (SCPP) by numerical models. Computational Fluid Dynamic (CFD) methods are adopted by many researchers because of high constructional cost of these power plants. Guellouz et al. [4] developed and validated A 3D CFD (Computational fluid dynamics) model of a Solar Chimney Power Plant (SCPP) through comparison with the experimental data of the Manzanares plant. Then, it was employed to study the SCPP performance for locations throughout Tunisia. Sarmad et al. [5] investigated The performance of the solar updraft tower system (SUTS) numerically by comparing between two quarters circular thermal solar collectors (with and without porous absorber plate). The numerical study was analyzed by using ANSYS FLUENT program to solve the governing equations. Wahhab et al. [6] described an analytical study of solar chimney power plant in a greenhouse environment. The investigation was based on experimental calculations, the modelling was carried out in an ANSYS environment and the simulation of solar plant used a FLUENT k-ε Module for solving and post-processing the problem. In this study, 2D numerical model was developed using RANS equations with kepsilon turbulence model to investigate air flow behavior in the system. The impact of chimney height and heat flux on the air velocity and air temperature was investigated.

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48.1.1 Computational Modelling Computational fluid dynamic (CFD) analysis techniques are efficient tools in engineering applications. In this paper, a CFD model was performed using COMSOL software to modeling and analysis the flow behavior. Assumptions • The airflow through the solar chimney power plant is considered as steady and turbulent • Two dimensional • The solar flux is considered and temperature variation throughout the day in June. Governing equations Continuity Equation ∂ρ + ∇ · (ρu) = 0 ∂t

(48.1)

Navier–Stokes Equation ρ

   ∂u + ρ(u · ∇)u = ∇ · −P I + (μ + μT ) ∇u + (∇u)T ∂t  2 2 − (μ + μT )(∇ · u)I − ρ K I + F 3 3

(48.2)

Energy Equation ρC p

∂T + ρC p u · ∇T = ∇ · (K ∇T ) + Q + Q vh + W P ∂t

(48.3)

The k − ε turbulence model equations are given by: Equation for the turbulent kinetic energy k is given by Eq: ρ

∂k + ρ(u · ∇)k = ∇ · ∂t

   μT ∇k + Pk − ρε μ+ σk

(48.4)

Equation for the energy dissipation ε is given by Eq: ∂ε + ρ(u · ∇)ε = ∇ · ρ ∂t 2



  μT ε ε2 ∇ε + Cε1 Pk − Cε2 ρ μ+ σε k k 3/2

(48.5)

k where μT = ρCμ kε is the turbulent viscosity and ε = C3/4 μ LT is the energy dissipation (Table 48.1). Boundary condition

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Table 48.1 Boundary conditions Surface

Type

Value

Collector inlet

Inlet pressure

Pci = Patm , T = Tam = 302 K

Chimney outlet

Outlet pressure

P = patm

Collector surface

Semi-transparent wall

Solar irradiation; h = 10.45 W/m2

Chimney surface

Adiabatic condition

q = 0 W/m2

Collector inlet

Inlet pressure

Pci = Patm , T = Tam = 302 K

48.1.2 Results and Discussions The geometry of the University of Islamic Azad, Iran used in this work to study the airflow parameters. The main dimensions of the Iranian prototype selected as the physical model are listed in Table 48.2. In Fig. 48.2, solar radiation and the ambient air temperature the environmental parameters are shown in for typical day in Jun. It shows that the ambient air temperature varies between 19.1 °C to 25.2 °C, although the solar irradiance increases after sunrise and reaches the maximum value of 901 W/m2 at 13:30 pm. Figure 48.3 illustrates the velocity and temperature contours in the SCPP. The value of magnitude velocity is very low at the entrance of the collector zone, there is velocity increases gradually to maximum values at the chimney base to 1.62 m/s. So, the result of the air velocity direction was identified as being mainly towards the chimney base, due the overstock effect. Figure 48.3a shows the profiles of the temperature along the collector centerline. There is minimum temperature at the collector entrance and gradually increases to maximum values at the collector centre to 315.32 K and constant temperature at the chimney pipe is observed. Figure 48.4 shows the variation of air velocity at chimney height of collector from 3 to 5.5 m. It is plotted at different locations such as inlet, outlet, chimney base and also 1 and 2 m above chimney base. At the inlet, the velocity of air is weak and remains constant with increases of chimney height, while the maximum velocity is located at the chimney base and increases with increases the chimney height. In addition, the velocity is constant along the chimney pipe to outlet and. Figure 48.5 shows the variation of air temperature rise at different chimney height from 3 to 5.5 m. It is plotted at different locations such as inlet, outlet, 0.5 collector Table 48.2 Geometrical parameters of the solar chimney Parameters

Value (m)

Collector radius rc

1.5

Chimney radius rch

0.125

Collector height Hc

0.04

Chimney height Hch

3

48 Thermal Investigation of a Solar Chimney Power … solar radiaon (W/m^2)

371 temperature (°C)

35

1000

30

800

25

700 600

20

500 15

400 300

10

200

5

100 0

0:00

0

4:48

9:36 14:24 Time(hour)

19:12

0:00

Fig. 48.2 Solar radiation and ambient air temperature variations for typical day in Jun

Fig. 48.3 Air velocity and temperature contours

Temperature(°C)

Solar radiaon(W/m^2)

900

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H. Nouar et al. 2 inlet 1.8 1.6

chimney base

air velocity(m/s)

1.4 1.2

1m above chimney base

1

2m above chimney base

0.8 0.6

outlet

0.4 0.2 0 3

3.5

4 4.5 Chimney Height(m)

5

5.5

Fig. 48.4 Effect of chimney height on the air velocity in the system of SCPP

18

inlet

16 0.5m collector radius chimney base

temperature rise(°c)

14 12 10

1m above chimney

8 6

2mabove chimney

4

outlet

2 0 3

3.5

4

4.5

5

5.5

chimney height(m) Fig. 48.5 Effect of chimney height on air temperature rise in the system ofSCPP

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45 inlet 43

Temperature(°C)

41 0.5m collector radius

39 37

chimney base

35 33

1m above chimney base

31 29 27 3

3.5

4

4.5

5

5.5

outlet

chimney height(m) Fig. 48.6 Effect of chimney height on air temperature in the system of SCPP

radius, chimney base and also 1 and 2 m above chimney base. It is observed that as chimney height decreases, the air temperature decreases for different locations, while at the inlet remain constant. Also in Fig. 48.6, the air temperature decreases with increases of chimney height for different locations, while at the inlet remain constant. The effects of heat flux on the air velocity and temperature rise were analyzed, and the results are shown in Fig. 48.7. Both the air velocity and temperature rise showed an appreciable increase with increasing the heat flux. This means that the transition is achieved at the collector by convection and at the chimney by the conduction.

48.1.3 Conclusion Numerical simulation is studied to investigate the effects chimney height and heat flux on the flow parameters. It was found that, due to the overstock effect, the direction of air velocity was defined as being mainly towards the base of the chimney. Furthermore, the variation in chimney height has a direct effect on SCPP system flow parameters. The air velocity increase as the height of the chimney increases while the air temperature and temperature changes in the collector are adversely influenced by the change in the height of the chimney. Also the increases of heat flux impact

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3.3

air velocity(m/s)

temperature rise (°C)

air velocity(m/s)

50

3.1

40 3 30 2.9

20

2.8

temperature rise(°C)

60

3.2

10

2.7

0 40 0

600

800

Heat flux(W/m^2) Fig. 48.7 Effect of heat flux on air temperature rise and velocity in the system of SCPP

means that the transfer is done at the collector by convection and at the chimney by the conduction.

References 1. P.J. Bansod, S.B. Thakre, N.A. Wankhade, Solar chimney power plant—a review. Int. J. Modern Eng. Res. (IJMER). 4(11), 18–33 (2014) 2. A.O. Dhahri, O. Ahmed, A review of solar chimney power generation technology. Int. J. Eng. Adv. Technol. 2(3), 1–17 (2013) 3. W. Haaf, K. Friedrich, G. Mayr, J. Schlaich, Solar chimneys part I: principle and construction of the pilot plant in Manzanares. Int. J. Solar Energy 2(1), 3–20 (1983) 4. M.S. Guellouz, M. Sahraoui, S. Kaddeche, A numerical study of solar chimney power plants in Tunisia. J. Phys. Conf. Ser. 596(1). 012006 (2015). 5. S.A. Abdal Hussein, M.A. Nima, Investigation of air inlet height on the performance of solar tower system utilized with flat plate and porous absorber. J. Mech. Continua Math. Sci. 15(2), 253-269 (2020). 6. H.A.A. Wahhab, W.A.K. Al-Maliki, Application of a solar chimney power plant to electrical generation in covered agricultural fields. IOP Conf. Ser. Mater. Sci. Eng. 671(1), 012137 (2020)

Chapter 49

Effects of Rim Angle on Performance Predictions of a Parabolic Trough Solar Collector Belkacem Agagna and Arezki Smaili

Abstract Nowadays the largest part of installed solar thermal power plants are based on the Parabolic Trough solar Collector (PTC). The efforts in R&D areas for the development of new components and materials for this kind of collectors make parabolic trough technology a mature and clean solution for electricity generation. The distribution of incident solar rays around the absorber tube constitutes a key element in the study of optical and thermal performances of PTCs. In this paper, we propose to study the effect of rim angle on the performance of the PTC taking into account the non-uniformity of solar flux. Firstly, a detailed optical model based on Monte Carlo Ray Tracing method (MCRT) has been developed using Matlab software. The simulations have been carried out through the LS2 collector of Solar Thermal Electric Generation System (SEGS). Then, the results of the MCRT code has been coupled with Finite Volume Method (FVM) using ANSYS software to analyze the heat flux distribution on the absorber tube under some rim angle values. Keywords Parabolic trough solar collector · Monte Carlo ray tracing method · Heat flux distribution · Finite Volume Method · Rim angle

49.1 Introduction Solar thermal technology is based on a simple principle to generate electricity in a clean manner. It concentrates solar energy to generate steam that powers a turbine. In order to complete this process, different types of solar collectors are used, among them parabolic trough [1]. One of the most important experimental tests for a PTC is the work of Dudley et al. [2]. These tests are applied on the PTC named LS-2 installed in Sandia National Laboratory (SNL). Dudley et al. proposed also a one-dimensional model validated with their experimental results. Forristall [3] established both 1D and 2D simplified models programmed in Engineering Equation Solver (EES) to predict the performance of parabolic trough system. Few years later, and in order B. Agagna (B) · A. Smaili Laboratoire de Génie Mécanique et Développement-LGMD-National Polytechnic School-ENP-B.P., 182 El-Harrach, 16200 Algiers, Algeria e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 Y. Chiba et al. (eds.), Advances in Green Energies and Materials Technology, Springer Proceedings in Energy, https://doi.org/10.1007/978-981-16-0378-5_49

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to improve the efficiency of the PTC system, García-Valladares and Velásquez [4] have proposed to compare the configuration of single pass solar receiver with double pass using detailed numerical model. After that, Padilla [5] proposed a detailed model (1D) based on some new correlations to study the LS-2 PTC cited above. This later model prove that the obtained results are more close to the experimental data compared with other models. Then, Kalogirou [6] presented a thermal analysis model implemented in EES software. Recently, Agagna et al. have developed an improved model for predicting the performance of PTC with higher accuracy [7]. Previous studies have neglected the non-uniformity of absorbed flux on the Heat Collection Element (HCE). In contrast, a number of researchers have discussed the non-uniformity of heat flux to be close as possible to the PTC system installed under real conditions. For this reason, Jeter [8, 9] proposed an analytical model to calculate this non-uniform distribution of heat flux. Many researchers have cited Jeter’s results to validate their models. Such as, He et al. [10–12] and Cheng et al. [13], when they adopted MCRT method to analyze the PTC. Hachicha et al. [14] carried out a numerical model using FVM validated and compared with Jeter’s paper. Recently, Agagna et al. [15, 16] have combined MCRT technique with FVM to investigate the effect of some important factors like incidence angle and tracking errors on the performance of PTC. Also, experimental and numerical study based on this coupled method has been proposed by Agagna et al. [17] to analyze the PTC performances of MicroSol-R platform. The distribution of solar rays, the resulting LCR and optical efficiency are three important parameters, which serve to characterize the optical performance of a PTC. These parameters are affected directly by various optical and physical factors. The effects of these factors on the performance of the PTC system have been investigated in this study using a MCRT code. The developed model has been validated and applied to analyze the LS2 collector of SEGS. Then, and in order to predict the thermal performance of the PTC under both non-uniform solar flux and various rim angles, the obtained results of MCRT technique were used as a boundary condition in ANSYS software.

49.2 Model and Methodology 49.2.1 Physical Model Description Parabolic trough collectors are formed by a cylindrical surface of mirrors with a parabolic shape that concentrates solar radiation on a receiver tube located at the focal point of the parabola (Fig. 49.1). A fluid, normally synthetic oil, circulates inside the receiver tubes and is heated up by the sun (around 400 °C). The fluid is then pumped through heat exchangers to generate steam, which is thus used to produce electricity in a conventional turbine.

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Fig. 49.1 Schematic of a parabolic trough solar collector

Fig. 49.2 Schematic of coupled method (MCRT + CFD)

49.2.2 Coupled Model To take into account the optical proprieties of the PTC, a mathematical model based on MCRT method has been programmed in Matlab. The flow chart of this technique can be found in Refs [15, 16]. This optical allows to present the non-homogeneous distribution of solar flux model as a boundary conditions in Fluent using a UDF. Figure 49.2 illustrates the modeling approach. Note that in this paper, and as used in Jeter’s work, dimensionless parameter (relative and similar to the distribution of heat flux) called Local Concentration Ratio (LCR) has been used.

49.3 Results and Discussions 49.3.1 Validation of the Optical Model Figure 49.3 shows the validation of the optical model with Jeter’s results [8] when good agreement has been observed. As it can be seen, the present model follows the

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Fig. 49.3 Curve of LCR distribution

same trend as Jeter’s analytical model. Moreover, it is more accurate than Y.L. He model especially for the shadow effect zone.

49.3.2 Effect of Rim Angle The rim angle is a very important trait for the construction of the PTC. It has an effect on the concentration ratio and on the total irradiance. It is expressed by:  θrim = 2 arctan

Wa 4f

 (49.1)

For the same aperture width (Wa = 5 m), and according to Eq. 49.1, the focal length should change with rim angle. Rim angles of 45°, 60° and 90° with the focal lengths of 3.017 m, 2.165 m and 1.25 m, respectively, have been chosen to represent the geometry. Figure 49.4 shows the results (3D) obtained by in house MATLAB code illustrating various finite parabolas as having a common focus and the same aperture. The collector’s surface area decreases as the rim angle is decreased. It can be seen that a parabola with a small rim angle is relatively flat and the focal length is long. Figure 49.5a shows the variation of LCR on the absorber tube’s circumference at various rim angles. At high rim angles (θrim ≥ 60°), the path of the reflected radiation from the outer parts of the mirror is very long and the beam has a wider spread, hence reducing the LCR as seen in Fig. 49.5a. Whereas, at very low rim angles (θrim < 60°), the shadow effect area does not exist because only a small portion of the absorber tube receives concentrated solar rays and the distance between the absorber and the parabola increases. Figure 49.5b shows the variation of optical efficiency

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Fig. 49.4 PTCs in 3D with various rim angles

Fig. 49.5 a LCR distribution for different rim angles, b Optical efficiency versus rim angles

of different incidence angles under various rim angles. The optical efficiency of the trough collector decreases with the increase of the incidence angle, when the maximum value of optical efficiency is 84.25% with incidence angle of zero. The figure shows that the optical efficiency is lower when the rim angle is smaller.

49.3.3 Thermal Part The predicted results obtained by the developed model have been compared to the experimental data from SNL. In Table 49.1, the comparison is illustrated, when good agreement was found. So that the numerical results of the HTF outlet temperature, thermal efficiency agree well with the experimental data. In the same table, these cited parameters are obtained for various rim angles. There is no significant difference in outlet temperature each time. It seems that the influence of rim angle to heat transfer process is also small. As expected, the efficiency changes in every case. This is mainly

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Table 49.1 Comparison between SNL data and the proposed model Parameters of test conditions DNI = 933.7 Wind speed = 2.6 m/s Flow rate = 50.3 l/mn Tamb = 21.2 °C Tinlet = 102.2 °C Toutlet = 124.0 °C η = 72.51% W/m2

Rim angle (°)

Present model Tout (°C)

η(%)

68.38

124.4

72.43

45

126.31

71.94

60

125.99

72.09

90

127.03

71.83

Fig. 49.6 3D heat flux distribution of different rim angles

due to the energy losses with different rim angles, which reduce the efficiency of the PTC system. Figure 49.6 shows the heat flux distribution on the tube absorber with some rim angles. The obtained distribution of heat flux in Fig. 49.6 is mainly obtained from the previous plotted curve in Fig. 49.5a. With rim angle rising, the maximum value of heat flux become lower and the curve moves towards the direction of 90°. This model is able to predict the difference between the cold part and the hot part of the tube. As a consequence, the fluid may overheat near the wall.

49.4 Conclusion In this paper, a coupled method of MCRT and FVM has been presented to simulate the optical-thermal process of PTC system in order to investigate the effects of rim angle on PTC performances. The coupled model was applied to simulate the LS-2 solar collector. The following conclusions can be made; (i) The influence of rim angle to heat transfer process is small; (ii) With rim angle rising, the maximum value of heat flux become lower and the curve moves towards the direction of 90°.

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Based on the results obtained, it is concluded that this analyze is of great importance for the predictions of the performances of PTCs under different operating conditions and various rim angles. Good agreement was found which confirm the potential of the coupled method developed in this paper. Acknowledgements The support from Directorate-General for Scientific Research and Technological Development (DG-RSDT) of Algerian government in the form of research grant is gratefully acknowledged.

References 1. H. Price, E. Lüpfert, D. Kearney, E. Zarza, G. Cohen, R. Gee, R. Mahoney, Advances in parabolic trough solar power technology. J. Solar Energy Eng. Trans. ASME 124(2), 109–125 (2002) 2. V.E. Dudley, G.J. Kolb, M. Sloan, D. Kearney, Test results: SEGS LS-2 solar collector. Report of Sandia National Laboratories (1994). 3. R. Forristall, Heat Transfer Analysis and Modeling of a Parabolic Trough Solar Receiver Implemented in Engineering Solver Equation. Technical Report (National Renewable Energy Laboratory, Colorado, 2003). 4. O. García-Valladares, N. Velázquez, Numerical simulation of parabolic trough solar collector: improvement using counter flow concentric circular heat exchangers. Int. J. Heat Mass Trans. 52, 597–609 (2009) 5. R.V. Padilla, Simplified Methodology for Designing Parabolic Trough Solar Power Plants. PhD Thesis. Ann Arbor. 6. S. Kalogirou, A detailed thermal model of a parabolic trough collector receiver. J. Energy 48, 298–306 (2012) 7. B. Agagna, A. Smaili, O. Behar, An improved model for predicting the performance of parabolic trough solar collectors. Int. J. Energy Res. 42, 4512–4521 (2018) 8. S.M. Jeter, Calculation of the concentrated flux density distribution in parabolic trough collectors by a semi finite formulation. Sol. Energy 37(5), 335–345 (1986) 9. S.M. Jeter, Analytical determination of the optical performance of practical parabolic trough collectors from design data. Sol. Energy 39(1), 11–21 (1987) 10. Z.D. Cheng, Y.L. He, F.Q. Cui, Three-dimensional numerical study of heat transfer characteristics in the receiver tube of parabolic trough solar collector. Int. Commun. Heat Mass Trans. 37(7), 782–787 (2010) 11. Y.L. He, J. Xia, Z.D. Cheng, Y.B. Tao, A MCRT and FVM coupled simulation method for energy conversion process in parabolic trough solar collector. Renew. Energy 36(3), 976–985 (2011) 12. Z.D. Cheng, Y.L. He, F.Q. Cui, R.J. Xu, Y.B. Tao, Numerical simulation of a parabolic trough solar collector with non-uniform solar flux conditions by coupling FVM and MCRT method. J. Sol. Energy 86, 1770–1784 (2012) 13. Z.D. Cheng, Y.L. He, F.Q. Cui, A new modelling method and unified code with MCRT for concentrating solar collectors and its applications. Appl. Energy 101, 686–698 (2013) 14. A.A. Hachicha et al., Heat transfer analysis and numerical simulation of a parabolic trough. Appl. Energy 111, 581–592 (2013) 15. B. Agagna, A. Smaili, Q. Falcoz, Optical and Thermal Analysis of a Parabolic Through Solar Collector Through Coupling MCRT and FVM Techniques. IRSEC, Morocco. IEEE 1–6. https:// doi.org/10.1109/IRSEC.2017.8477343 (2017)

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16. B. Agagna, A. Smaili, Q. Falcoz, Coupled simulation method by using MCRT and FVM techniques for performance analysis of a parabolic trough solar collector. CPESE, Germany. J. Energy Proc. 141, 34–38 (2017). 17. B. Agagna, A. Smaili, Q. Falcoz, O. Behar, Experimental and numerical study of parabolic trough solar collector of MicroSol-R tests platform. J. Exp. Thermal Fluid Sci. 98, 251–266 (2018)

Chapter 50

Thermal Performances Investigation of Two ISCC Layouts Madjid Amani and Arezki Smaili

Abstract The present study investigates the thermal performances of two ISCC configurations which one integrates a parabolic trough collector technology with a conventional combined cycle (ISCC-PTC) and the other one integrates a solar tower power (ISCC-ST) with more attention is paid to solar electric conversion. The results have shown high thermal performances for both ISCC systems while the ISCC-ST exhibits a constant value of 0.21 of solar to electric efficiency conversion for the two selected days but the ISCC-PTC value is 0.16 for the spring day which is 31% lesser than that one of ISCC-ST. This investigation allows concluding that the configuration of ISCC-ST integrating a solar tower power is a good option for integration of solar energy into a conventional combined cycle. Keywords Integrated solar combined cycle · Thermal performances · Solar tower power · Solar parabolic trough power

50.1 Introduction Currently, Integrated Solar Combined Cycle (ISCC) using parabolic trough collector (PTC) technology is considered a mature and a promising technology for solar electricity production and many configurations existed which some are commercialized or underdevelopment [1]. Calise et al. [2] investigated the thermo-economic of an ISCC with three pressure level Rankine cycle, thus a dynamic model is carried out for the present investigation. Elmohlawy et al. [3] also studied and compared the performances of two proposed configurations of ISCC with triple pressure combined cycle (CC). Achour et al. [4] and Abdelhafidi et al. [5] developed a detailed model to predict the thermal performances of an ISCC type Hassi R’mel configuration, then validation model is carried out under the same conditions. Additional to ISCC-PTC power plants using PTC technology, there exist also those using central receiver systems (CRS) where the solar irradiation is reflected M. Amani (B) · A. Smaili Laboratoire de Génie Mécanique et Développement -LGMD-National Polytechnic School -ENP-,BP, 182 El-Harrach16200, Algiers, Algeria e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 Y. Chiba et al. (eds.), Advances in Green Energies and Materials Technology, Springer Proceedings in Energy, https://doi.org/10.1007/978-981-16-0378-5_50

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by heliostats to the receiver located in the top of a solar tower (ST). Spelling et al. [6] developed a dynamic model to optimize the thermodynamic performances and economic assessment of solar power tower (SPT) plant integrated with a combined cycle then a trade-off is found. Peterseim et al. [7] investigated a new ISCC which is hybridization of solar tower molten salt with a combined cycle gas turbine. In this concept of ISCC-ST using solar tower technology, very limited research attentions have been devoted to develop such solar thermal plants [8] and most of SPT systems commercialized or under development work in topping or bottoming cycles [9– 11]. The most operating ISCC power plants through the world are those using PTC technology [8]. This present work investigates thermal performances of two configurations of ISCC concept which one adopts the PTC technology (ISCC-PTC) and the second uses the SPT system (ISCC-ST). The former is with the same Hassi R’mel ISCC concept where the solar heat is introduced as heat latent in parallel to evaporator of the heat recovery steam generator (HRSG) via a heat solar steam generator (HSSG) but this plant runs with one gas turbine (GT) and one HSSG, and the latter consists of integration of solar heat to heat up the exhaust gases of the GT before entering the HRSG via the volumetric receiver of the solar tower system, thus the receiver plays the role of supplementary firing. The aim of this study is to look for the most efficient conversion of solar energy to electricity between these two different layouts of ISCC.

50.2 Description of ISCC Systems In the present work, two ways of solar integration for ISCC system using two different technologies are investigated as presented in Fig. 50.1a, b. Simulations of these ISCC power plants are studied under the geographical site of Hassi R’mel (Algeria) for the climate conditions of 21st of March and 21st of June days. The maximum direct normal irradiation (DNI) and mean ambient temperature (Ta ) of 21 °C for 21st of March is considered as the design point. The variation of DNI during the day leading to off design operation. HRSG is considered as the main subsystem where all the thermal energy is transferred to generate the superheated steam. The heat loss factor and the blow down for HRSG are considered in the calculation, but the pressure loss of steam is neglected. In the other side, the pressure drop through the flue gas cleaner and HRSG are taken into account but neglected through the receiver. We note that ISCC-PTC runs with one GT and one solar field and all the developed thermodynamic models are implemented under MATLAB.

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50.2.1 Solar Field Two kinds of solar field technology are used for these present ISCC systems. The ISCC-PTC configuration integrates parabolic trough collectors oriented north–south to maximize solar energy collection. The second ISCC-ST system integrates a number of heliostats tracking the sun in two axes to reflect the DNI onto the receiver. The same size of solar field area (ASF ) is used for both systems which is equal to 117,720 m2 and this is based on the quantity of solar energy that can be reflected from the heliostats field toward the open volumetric and required to heat up the quantity of flues gases form the GT till a fired temperature of 850 °C for maximum DNI of the design point. The Hottel model is adopted for this simulation to evaluate the DNI [12]. D N I = τb Iso cos θz

(50.1)

The solar field performance is the useful solar energy and the solar system optical efficiency. The total useful energy QC gained by the PTC and SPT receivers is given by: Q C = α Q S F − Q loss

(50.2)

The optical efficiency of the solar system ηGlob−opt is the ratio of the net useful energy gained by the receiver and the total quantity of solar beam reaching the mirrors of the solar field (Table 50.1): ηGlob−opt =

QC D N I AS F

(50.3)

Table 50.1 Solar field operation parameters [1, 4, 8] Parameters

Symbols

Value

Unit

Optical efficiency

ηoptic

73

%

HTF inlet temperature

TH T F,i

293

°C

HTF outlet temperature

TH T F,o

393

°C

ηoptic

63

%

Latitude

φ

33.8

degree

Solar constant

Isc

1367

W/m2

Relative humidity

RH

58

%

Mean ambient temperatures of 21st March & June

Ta

21 and 36

°C

PTC type of LS-3

Heliostat field Optical efficiency Hassi R’mel data

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50.2.2 Rankine Cycle The steam cycle consists of HRSG with a single pressure integrating a solar heat via HSSG in case of ISCC-PTC and via a volumetric receiver in ISCC-ST case as displayed by Fig. 50.1 where the solar is injected as a heat latent in parallel to the HRSG evaporator and injected as supplementary firing to heat up the flue gases before entering the HRSG respectively, an oversized steam turbine and a cooling system. In the present study, the Rankine cycle is the crucial part and has a direct impact on ISCC performance since HRSG is the main subsystem to generate steam, thus a thermodynamic method developed by Ganapathy [13] is adopted for this section analysis. The steam pressure and the pinch point have a crucial role and the exit gas temperature from the economizer is not arbitrarily assumed [13]. The analysis of HRSG performance is achieved by determining the gas–steam temperature profiles, duty of each component, steam generation and exit gas temperature. Once the design mode is established and in order to predict the Rankine cycle off design performance under DNI and mean ambient temperature of the selected days, several guessed values and iterations steps are required before arriving at the final heat balance, steam flow generation and duty. The net solar electricity is the difference of the plant output between sunny and night periods. Therefore, solar electric efficiency is given as follows: ηsol−to−elec =

(a)

Wsol−to−elec D N I AS F

(50.5)

(b)

Fig. 50.1 ISCC systems: a hybridization of PTC with CC (ISCC-PTC); b hybridization of SPT with CC (ISCC-ST)

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where,Wsol−to−elec = PI SCC − PCC ,with PI SCC and Pcc are the plant output during day and plant output during night respectively. η Rank−cycle =

Wsol−to−elec QC

(50.6)

50.2.3 Results and Discussions Two Modeling results are presented by focusing on two representative days (Sunny day of 21st March and 21st July), then thermal performances are compared with each other to evaluate the impact of solar technology on solar-to-electric conversion. All the hours of timing used in the present work are given in solar time (ST). Figure 50.2 shows that more solar energy collected by PTC receiver in summer day compared to SPT one due to the high overall optical efficiency of PTC system (Fig. 50.3) but it is the same for the spring day for both systems since they have the same optical efficiency. It’s shown also in Fig. 50.3 that overall optical efficiency of the SPT system is constant for the spring and summer periods and it is different for PTC system which the latter exhibits more efficiency in summer than spring. In any solar thermal plant, solar conversion to electricity is an important parameter that should be investigated since it gives an idea how much the electricity is generated and efficiently converted from the solar energy, thereby as it shows in Fig. 50.4 that electricity generated by solar is about 23 MWe for both ISCC configurations and this is for 21st of June which means with less solar energy available in the SPT receiver compared to that available in PTC receiver the solar electricity is the same Fig. 50.2 Solar thermal transferred into the receiver

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Fig. 50.3 Overall optical efficiency of solar system

Fig. 50.4 The net electricity produced by solar

for summer and spring days where ISCC-ST produces more electricity than that ISCC-PTC about 18 MWe and 14 MWe respectively. Figure 50.5 displays a constant value of solar to electric efficiency for ISCC-ST about 0.21 for the two selected days which is the same value for ISCC-PTC in summer day but the latter exhibits less efficiency in spring day. This is can be explained by the fact that Rankine cycle of ISCC-ST system exhibits more efficiency of solar conversion into electricity than that ISCC-PTC one (Fig. 50.6) which is about 0.41 compared to 0.31 respectively and this is for both spring and summer selected days. Consequently, the ISCC-ST configuration exhibits important performances in terms

50 Thermal Performances Investigation of Two ISCC Layouts

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Fig. 50.5 Sol-to-elec Efficiency

Fig. 50.6 Rank-cycle Efficiency

of solar energy conversion into electricity compared to ISCC-PTC configuration; this is due to that the volumetric receiver played the role of supplementary firing which is a good way to generate additional steam in HRSG with single pressure since the latter operates in fired mode.

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50.3 Conclusion Thermodynamic simulations for two ISCC systems which one adopts a SPT and the other one adopts a PTC technology are investigated in terms of thermal performances and solar to electric conversion with the same solar field area. However the obtained results for such thermal power plants integrating a solar energy with a conventional CC are interesting, the solar energy conversion to electricity for the ISCC-ST system is more important with constant value of 0.21 for both spring and summer periods than that of ISCC-ST system with a value of 0.16, 31% lesser than that of ISCC-ST value. Consequently, even though more solar energy is transferred to the PTC receiver the ISCC-ST configuration exhibits the same or high performances as the case for spring day and this due to the high Rankine efficiency of solar thermal conversion to electricity. All these outcomes allow concluding that the present configuration of ISCC integrating a SPT could be a promising option for solar electricity generation. Acknowledgements The support from Directorate-General for Scientific Research and Technological Development (DG-RSDT) of Algerian government in the form of research grant is gratefully acknowledged.

References 1. O. Behar, A. Khellaf, K. Mohammedi, S. Ait-Kaci, A review of integrated solar combined cycle system (ISCCS) with a parabolic trough technology. Renew. Sustain. Energy Rev. 9, 223–250 (2014) 2. F. Calise, M. Denticed’Accadia, L. Libertini, M. Vicidomini, Thermoeconomic analysis of an integrated solar combined cycle power plant. Energy Convers. Manage. 171, 1038–1051 (2018) 3. A. Elmohlawy, V. Ochkov, B. Kazandzhana, Thermal performance analysis of a concentrated solar power system (CSP) integrated with natural gas combined cycle (NGCC) power plant. Case Stud. Thermal Eng. 14, 100–458 (2019) 4. L. Achour, M. Bouharkat, O. Behar, Performance assessment of an integrated solar combined cycle in the southern of Algeria. Energy Rep. 4, 207–217 (2018) 5. N. Abdelhafidi, N. Bachari, Z. Abdelhafidi, A. Cheknane, Modeling of integrated solar combined cycle power plant (ISCC) of HassiR’mel, Algeria. Int. J. Energy Sector Manage. 14, 505–525 (2019) 6. J. Spelling, D. Favrat, A. Martin, G. Augsburger, Thermoeconomic optimization of a combinedcycle solar tower power plant. Energy 41, 113–120 (2012) 7. J. Peterseim, A. Tadros, U. Hellwig, S. White, Integratedsolar combined cycle plants using solar towers with thermal storage to increase plant performance, in Power conference POWER2103. ASME, Massachusetts, USA (2013) 8. E. Okoroigwe, A. Madhlopa, An integrated combined cycle system driven by a solar tower: a review. Renew. Sustain. Energy Rev. 57, 337–350 (2018) 9. K. Mohammadia, J. McGowana, M. Saghafifarb, Thermoeconomic analysis of multi-stage recuperative Brayton power cycles: Part I- hybridization with a solar power tower system. Energy Convers. Manage. 185, 898–919 (2019) 10. F. Sorgulu, I. Dincer, Design and analysis of a solar tower power plant integrated with thermal energy storage system for cogeneration. Int. J. Energy Res. 1–10 (2018)

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11. T. Neises, C. Turchi, Supercritical carbon dioxide power cycle design and configuration optimization to minimize levelized cost of energy of molten salt powertowers operating at 650 °C. Solar Energy 181, 27–36(1991) 12. A.J. Duffie, A.W. Beckman, Solar Engineering of Thermal Processes, 2nd edn (Wiley, New York, 1991) 13. V. Ganapathy, Steam Generators and Waste Heat Boilers for Process and Plant Engineers (Taylor & Francis Group, USA, 2015).

Chapter 51

Effect of Turbulence on Wind Turbine Farm Power Production Said Zergane and Arezki Smaili

Abstract Turbulence is a phenomenon associated with the flow of wind in wind farms. It has a significant effect on the performance of wind turbines, causes a strong load on the blades and modifies the evolution of the profile of the wind speed in the increasing wake. In order to investigate this phenomenon and describe in a much more precise way the effect of wind turbulence on the produced power of a wind turbine, we present in this work, a study which aims at the effect of turbulence on a wind turbine in downstream in the wake of another front wind turbine, for a given wind farm. This study is based on the use of the complete Ishihara wake model which takes into account the ambient and generated wind turbulence and on the input of data and characteristics of the ENERCON E2 commercial wind turbine. The simulation results obtained from the power developed with turbulence have been presented and compared to those without turbulence. Keywords Turbulence · Wind farm · Ischihara Wake model · Wind energy · Wind flow

51.1 Introduction The wind, defined as a mass of air that moves between two different pressure zones, can be converted into mechanical energy, and then into electrical energy by the generator in the nacelle of the wind turbine. Wind energy is renewable, sustainable, and inexhaustible and produces no greenhouse gases or toxic waste. With the necessary effects of exploiting fossil fuels such as oil and natural gas on environmental change and global warming, this type of energy can be the alternative to conventional energy. With modern wind turbines greater than 100 m in height and with a power rating S. Zergane (B) Mechanical Department, University of Mohamed Boudiaf-Msila, 28000 M’sila, Algeria e-mail: [email protected] A. Smaili Laboratoire de Génie Mécanique et Développement-LGMD, National Polytechnic School-ENP, P.B. 182, El-Harrach, 16200 Algiers, Algeria © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 Y. Chiba et al. (eds.), Advances in Green Energies and Materials Technology, Springer Proceedings in Energy, https://doi.org/10.1007/978-981-16-0378-5_51

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well in excess of 2 MW, large wind farms have been installed worldwide in recent decades. However, the performance of wind farms depends mainly on the location of the turbines [1]. Under the effect of the wake, significant reductions in wind speed can be noted, also the power produced suffers a deficit in the downstream area of a wind turbine. To this end, several wake models have been proposed to simulate the wind speed after the wind turbine that generates the wake of which the Ishihara model [2] is one. This model is more complete compared to the other models, it is characterized by taking into account of the turbulence associated with the flow of the wind in the wake, a turbulence due to the state of ground and a turbulence due to the presence of an obstacle in the park like a wind turbine. To study the effect of turbulence on the power of a wind turbine downstream of another front turbine, a study based on the introduction of the Ishihara model [2] and the characteristics of the ENERCON E2 wind turbine in a program for calculating the power produced. The effect of turbulence is obtained by comparing the results with and without turbulence effects.

51.2 Ishihara Wake Model The simplest illustration of Ishihara’s physical wake model [2] is shown in Fig. 51.1. It is clear that moving away from the front turbine, the speed deficit becomes less important and the wake thickness is gradually increasing. Based on the ideal Betz model, the expression of the wind speed U W in the wake of such a model is given by the following relation [3]: Uw = U (1 − ax )

(51.1)

√    2  C T 1.666 2  x − p r exp ax = 32 K1 D Dw2

(51.2)

In the Ischihara model;

The wake diameter is defined as follows 1

K 1 C T4 1− P P D 2x2 Dw = D + 0.833

(51.3)

The parameter p is a function of the ambient and added turbulence intensity given by: P = k2 (Ia + Iw )

(51.4)

where I a and I w represent the ambient turbulence and the added turbulence respectively expressed as follows:

51 Effect of Turbulence on Wind Turbine Farm Power Production

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Fig. 51.1 Ichihara wake model

0.5  

Ia = ln

Z Z0

(51.5)

and     x 2 k3 C T 1 − ex p −4 Iw = max(Ia , 0.03) 10D

(51.6)

the coefficients k 1 ,k 2 , and k 3 are respectively equal to 0.27, 6.0 and 0.004 [4].

51.3 Characteristics of the ENERCON E2 Wind Turbine The numerical simulation is performed for the ENERCON E2 wind turbine. The characteristics and output power curve of this turbine are shown in Fig. 51.2 and Table 51.1 The developed power of the turbine is modelled by the following relation:

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Fig. 51.2 Power curve of ENERCON E2 [5]

Table 51.1 Characteristics of ENERCON E2 [5] Rotor diameter

Hub height

Nominal power

Wind speed nominal

82 m

85 m

2050 kW

13 m/s

P(U ) =

I 

αi U i

(51.7)

i=1

where αi and U represent integers and wind speed respectively.

51.4 Results and Discussion At first, an investigation is made into the characteristics of the ambient turbulence, then the turbulence added.

51.4.1 Ambient Turbulence This turbulence is strongly related to the roughness of the soil and the height of the turbine [6]. Therefore, to determine the effect of the ground and the height Z on the ambient turbulence I a , the height Z is varied for values of the roughness of the park and each time the value of the ambient turbulence is calculated. The simulation results are shown in Fig. 51.3.

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Fig. 51.3 Evolution of the ambient turbulence as a function of the height Z

From Fig. 51.3, the following points can be drawn: • Ambient turbulence is greater near the ground than in height due to the presence of obstacles. • The ambient turbulence varies proportionally with the roughness of the ground, the rougher the terrain of the park is, the greater the ambient turbulence. • The turbulence is independent of the flow velocity.

51.4.2 Added Turbulence The added (generated) turbulence is additional turbulence to ambient turbulence, as it is generated by the presence of the onshore wind turbines. In a wind farm, all the turbines in the wake of another front turbine are affected by this turbulence, which affects the energy production and the loads imposed on the blades. As a result, for a series of roughness values, the dimensionless distance x/D downstream of an impeller is varied and the resulting turbulence generated is calculated. Figure 51.4 shows the evolution of the turbulence generated (added) as a function of the dimensionless distance x/D. Note that in the immediate positions, wind turbines are little influenced by the turbulence generated, then the curves show a significant increase to stabilize to constant values. It can be noted that for roughness values ranging from 0.001 m to 1.6 m, in the infinite downstream, the added turbulence tends to values ranging from 0.0191 to 0.0050 respectively. We also note that the roughness of the ground is inversely proportional to the turbulence added, the more the site is rigorous, the I w is lower.

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Fig. 51.4 Evolution of turbulence added as a function of distance x/D

51.4.3 Effect of Added Turbulence on the Power To study the effect of turbulence on the power output of a turbine, Fig. 51.5a– d, present the power calculation results performed for the different uniform and unidirectional speeds on the active disk; ranging from 6 m/s to 9 m/s with and without turbulence generated. For a roughness of 0.3 m of agricultural land with many hedgerows, comparing the results obtained from each figure show that the power with turbulence is greater than that without turbulence. The difference between these two powers is greater in the turbines furthest away in the turbulent flow compared to the turbine that generates the wake. The gap reaches its maximum value at the dimensionless distance x/D = 8. Table 51.2 summarizes the differences recorded.

51.5 Conclusion As it can be seen in this study with the Ishihara model, turbulence associated with wind flow is strongly related to the soil condition and the presence of obstacles in a wind farm, it acts significantly on the power of a wind turbine. In general, it has been concluded that an increase in the level of ambient turbulence generated on a turbine that produces energy systematically results in: • An increase in the mechanical power of the turbine. • An increase in the loads on the blades.

51 Effect of Turbulence on Wind Turbine Farm Power Production

Fig. 51.5 Effect of added turbulence on power Table 51.2 Effect of turbulence on the power of a wind turbine obtained at x/D = 8 U (m/s)

Maximum difference P (kW)

6

10.22

7

18.70

8

29.03

9

41.28

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Acknowledgements The support from Directorate-General for Scientific Research and Technological Development (DGSRDT) of Algerian government in the form of research grant is gratefully acknowledged.

References 1. S. Zergane, A. Smaili, C. Masson, Optimization of wind turbine placement in a wind farm using a new pseudo-random number generation method. Renew. Energy 125, 166–171 (2018) 2. T. Ishihara, A. Yamaguchi, Y. Fujino, Development of a new wake model based on a wind tunnel experiment. Tech. Rep., Global wind power (2004) 3. M.O.L. Hansen, Aerodynamic of wind turbines, Second edition by Earthscan in the the UK and USA (2008) 4. C. Krishnaswami, Experimental Analysis of Near and Transitional Wind Turbine Wake Using Stereo Particle Image Velocimetry, Master of Science Thesis, Faculty of Aerospace Engineering Delft University of Technology (2013) 5. N. Nguyen, Big Thunder Wind Park, Draft Wind Turbine Specification Report, For Renewable Energy Approval Application. M. K. INCE and Associates Ltd (2011) 6. P.L. Chamorro, F. Porté-Agel, A wind-tunnel investigation of wind-turbine wakes: boundarylayer turbulence effects. Bound.-Layer Meteorol. 132(1), 129–149 (2009)

Chapter 52

Maximum Power Point Tracking Method Using Sliding Mode Extremum-Seeking Algorithm for Residential Wind Turbine A. Abbadi, F. Hamidia, Y. Chiba, and A. Tlemcani

Abstract This paper discusses a control strategy that allows maximum energy extraction from a variable speed wind power conversion system based on a sliding mode extremum seeking control scheme. The main purpose is to supply 230 V/60 Hz domestic appliances through a single-phase inverter. The required power can be effectively supplied by the proposed wind turbine with the proposed MPPT controller. This MPPT system allows to changes the VDC reference signal (VdcRef ) of the inverter VDC regulator. A second controller regulates the DC link voltage to its reference value and the third controller regulates active and reactive grid current components. The active current reference is the output of the DC voltage controller. The simulation of the system operating in variable wind conditions shows the performance of the developed MPPT controller based on the sliding mode extremum seeking control algorithm. Keywords Wind turbine · PMSG · Sliding mode extremum seeking control · Residential wind system

52.1 Introduction Many remote communities throughout the world are supplied with electrical energy produced by diesel generators. In many of these communities, the cost of energy is largely determined by the landed cost of the diesel fuel. The urgent need to reduce the cost of energy has led to the investigation of the use of renewable energy sources, such as the wind, to replace some or all of the fuel consumed [1].

A. Abbadi (B) · F. Hamidia · A. Tlemcani Electrical Engineering and Automatic Laboratory LREA, Electrical Engineering Department, Faculty of Technology, University of Medea, Medea, Algeria Y. Chiba Departement of Mechanical Engineering, Faculty of Technology, University of Medea, Medea, Algeria © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 Y. Chiba et al. (eds.), Advances in Green Energies and Materials Technology, Springer Proceedings in Energy, https://doi.org/10.1007/978-981-16-0378-5_52

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Small wind turbines (SWT) are defined as wind turbines not exceeding 50 kW and which can be installed near inhabited areas where large-scale wind turbines cannot be built. In countries where high wind speeds are common, renewable electricity generating systems are gaining ground in residential sector for the purpose of diminishing the electricity bills or to reaching some degree of energy independence. Indeed on both on and off the grid, wind energy system can help houses become energy self-sufficient by generating electricity on site using clean, quiet, reliable and sustainable technology [2]. The most common configuration for residential wind -grid-connected systems of powers less than 50 kW normally consist of permanent magnet synchronous generator (PMSG) feeding a three phase rectifier followed by a residential grid system connected single phase AC inverter [1, 3]. The most critical and complex part of the AC grid-connected residential wind system is the control of the voltage amplitude at the terminals of the PMSG while allowing a maximum power transfer. Generally, there are three traditional types of the wind MPPT techniques: (1) Power Curve Characteristic Control, (2) tip speed ratio control, and (3) perturbation and observation (P&O) control [4, 5]. The first two methods have got a better dynamic response making them suitable for situations of rapid wind variations. On the other hand, the third method is parameter independent, simple to implement and can be applied more to a wide range of different types of SWTs [2]. In this paper, the Sliding Mode Extremum Seeking Control (SM-ESC) scheme [6, 7] was proposed to maximize the output power capture from wind generation system. SM-ESC is a non-model-based self-optimizing control strategy that aims to search for unknown input in real-time varying systems by finding the extreme point. This work discusses the control of the VDC reference signal of the VDC controller of the inverter based on sliding mode extremum seeking control scheme. The proposed MPPT controller automatically varies the VDC reference signal of the inverter’s to obtain a DC voltage that will extract the maximum of the power wind. This paper is organized as follows. In Sect. 2, the system under study is described. The sliding mode extremum seeking controller design is presented in Sect. 3. In Sect. 4, the proposed control is validated by means of simulation. Finally, the conclusions are summarized in Sect. 5.

52.2 System Structure The block diagram of the proposed system is illustrated in Fig. 52.1. The residential wind turbine system entails of a wind turbine, an inverter control module, a residential load and a distribution network. As illustrated in Fig. 52.1, the major components include: the wind turbine, PMSG, rectifiers, and MPPT controller; VDC Regulator: Determine the required Id (active current) reference for the current regulator; Current Regulator: The regulation defines

52 Maximum Power Point Tracking Method …

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Fig. 52.1 General block diagram of a single-stage single-phase wind topology

the intended reference voltages for the inverter; PLL is used for synchronization; PWM Generator. The output power of the wind-turbine is described as [8]:  PT ur bine = ρπ R 2 C p (λ, β)v 3 2

(52.1)

where, ρ is the air density ( kg/m3 ), R is the blade radius (m), C P is the performance coefficient of the turbine which is a function of the pitch angle of rotor blades β (in degrees) and v is the wind speed (in m/s). The tip-speed ratio λ is given by:  λ = ωm R v

(52.2)

where ωm is the wind turbine rotor speed (in rad/s). The mechanical torque output of the wind turbine T m is given as: Tm =

1 1 ρ AC p (λ, β)v 3 2 ωm

(52.3)

The coefficient of power conversion C p (λ,β) is described in [8] as: 

 c  c2 − 5 − c3 β − c4 e λi + c6 λ λi 0.035 1 1 − 3 = λi λ + 0.08β β +1

C p = c1

(52.4)

The coefficient c1 to c6 are: c1 = 0.5176, c2 = 116, c3 = 0.4, c4 = 5, c5 = 21 and c6 = 0.0068. The coefficient of power conversion and the power are maximums at a certain value of tip speed ratio called optimum tip speed ratio λopt [9, 10].

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a. Bloc diagram for SM ESC

b. The cost function curve

Fig. 52.2 Block diagram and the cost function characteristic curve of wind turbine generator of sliding mode extremum seeking control algorithm

52.3 Sliding Mode Extremum Seeking Control for Wind MPPT The Maximum Power Point Tracking (MPPT) controller is based on sliding mode extremum seeking algorithm. This MPPT system allows to changes the VDC reference signal (V dcRef ) of the inverter VDC regulator in order to draw the maximum of the power wind which mean that C p reached the C pmax . The objective of the sliding mode extremum-seeking controller (Fig. 52.2a) is to steer the cost function of the system to follow a non-predetermined optimal operating point (the maximum (minimum)). The optimal operating point in our case is the maximum point of the output power of the wind turbine ( Fig. 52.2b). The sliding variable s(t) is defined as: s(t) = y(t) − g(t)

(52.5)

where y(t) is the cost function, g(t) is a function satisfying g(t ˙ ) = ρ, with ρ is a positive constant. The parameter θ is designed to satisfy:     θ˙ = K sign sin π s(t) α

(52.6)

where K and α are positive constants.

52.4 Simulations Results The simulation considered the operation of the SWT connected to residential system operating at 230 V/60 Hz and with varying wind speed conditions. Performance of the of generator side control is carried out with different wind velocities as shown in Fig. 52.3.

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Fig. 52.3 Performance of generator side control

It is evident from the results that the generator speed increases with an increase in wind velocity and vice versa (Fig. 52.3). The wind power coefficient is tuned under the wind speed variation as illustrated in Fig. 52.3. The DC-link power and voltage are illustrated in Fig. 52.4. The DC-link voltage is maintained at 425 V under the wind speed variation. Figure 52.5 represents the residential load voltage and the residential load current. The total harmonic distortions (THD) of the residential load voltage current are shown in Fig. 52.6. The Fig. 52.7 shows the wind and the active power of the residential load. The difference in the curves represents the losses in the converter.

Fig. 52.4 Performance in DC-link

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Fig. 52.5 Residential load voltage and current

a.Volatge harmonics spectra

b.Current harmonics spectra

Fig. 52.6 Voltage and current harmonics spectra of residential load

52.5 Conclusion In this paper, sliding mode extremum seeking controller is proposed to regulate the VDC reference signal of the inverter VDC structure. The developed control strategy is checked via simulation studies on wind turbine system for residential application. The performance of system has been demonstrated under varying wind conditions. The voltage THD and the current THD of the residential load meet the required power quality norms recommended by IEEE. It is finally shown that the results proved the effectiveness of the employed control strategies.

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Fig. 52.7 Active power of the residential load

References 1. L. Barote, C. Marinescu, PMSG wind turbine system for residential applications, in SPEEDAM 2010 International Symposium on Power Electronics,Electrical Drives, Automation and Motion, pp.772–777 (2020) 2. D. Zammit, C. Spiteri Staines, A. Micallef, M. Apap, MPPT with current control for a PMSG small wind turbine in a grid-connected DC microgrid, in TUrbWind 2017 (Research and Innovation on Wind Energy Exploitation in Urban Environment) Colloquium, Riva del Garda, Italy (2017) 3. L. Bisenieks, D. Vinnikov, I. Galkin, Wind turbines: PMSG based residential possibilities and challenges, in Agronomy Research, pp. 295–306 (2013) 4. R. Kot, M. Rolak, M. Malinowski, Comparison of maximum peak power tracking algorithms for a small wind turbine. Elsevier J. Math. Comput. Simul., 29–40 (2013) 5. M.A. Abdullaha, A.H.M. Yatima, C.W. Tana, R. Saidurb, A review of maximum power point tracking algorithms for wind energy systems. Renew. Sustain. Energy Rev. 3220–3227 (2012) 6. D. Shen, P. Khayyer, A. Izadian, Sliding mode extremum seeking control for maximum power point tracking in wind system, in IEEE Power Energy Conf Illinois IEEE, pp. 1–6 (2016) 7. M. Safanah, R.H. Rafaat, Power maximization and control of variable-speed wind turbine system using extremum seeking. J. Power Energy Eng. 1–7 (2018) 8. K. Patil, B. Mehta, Modeling and control of variable speed wind turbine with permanent magnet synchronous generator, in IEEE International Conference on Advances in Green Energy (ICAGE’14), pp. 1–7 (2017) 9. Y. Erramia, M. Ouassaid, M. Maaroufia, Control of a PMSG based wind energy generation system for power maximization and grid fault conditions, in Energy Procedia: Mediterranean Green Energy Forum MGEF-13, pp. 220–229 (2013)

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10. Y. Xia, K.H. Ahmed, B.W. Williams, A new maximum power point tracking technique for permanent magnet synchronous generator based wind energy conversion system, in IEEE Transation on Power Electronics, pp. 3609–3622 (2011)

Chapter 53

Thermal Investigation of an Electrocaloric Refrigeration Systems Brahim Kehileche, Younes Chiba, and Abdelhalim Tlemçani

Abstract Electrocaloric cooling based on electrocaloric materials (ferroelectrics materials) is an environmentally friendly refrigeration technology with high cooling power and tempurature span. Electrocaloic refrigeration is based on the ECE (electrocaloric effect); The electrocaloric effect is an intrinsic property of certain materials having the particularity of being ferroelectric (ceramics, single crystals and polymers).The principle of the electrocaloric effect is based on an adiabatic and reversible polarization/depolarization of the electric dipoles under the action of an electric field.Thus, the application and stopping of the electric field induces an electrocaloric cooling cycle composed of four stages. In this paper, we studied the effect of regenerator geometry (parallel plates, packed bed (cylinder) and perforated plates) in an electrocaloric refrigeration systems. Keywords Electrocaloric effect · Parallel plates · Packed bed · Perforated plates

53.1 Introduction The cold occupies a very important place in our daily life. It is used in many applications such as automotive or building air conditioning, industrial or domestic refrigeration, food or medical conservation, etc. production today relies mainly on classic compression techniques [1–3] and gas expansion such as chlorofluorocarbons (CFCs), hydrofluorocarbons (HFCs) and hydrochlorofluorocarbons (HCFCs). The latter, unfortunately, are gases greenhouse effect, which contributes to global warming. Work is being carried out today to overcome this problem by following two parallel paths. In the first, we seeks to maintain conventional technology and find new fluids less polluting refrigerators such as carbon dioxide, propane, butane, etc. The second is to achieve a technological breakthrough and find new means making it possible to achieve high energy efficiency systems while having an impact low B. Kehileche (B) · A. Tlemçani Department of Electrical Engineering, LREA, University of Medea, Medea, Algeria Y. Chiba Department of Mechanical Engineering, University of Medea, Medea, Algeria © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 Y. Chiba et al. (eds.), Advances in Green Energies and Materials Technology, Springer Proceedings in Energy, https://doi.org/10.1007/978-981-16-0378-5_53

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environmental. This is the case with electrocaloric refrigeration around the ambient temperature which is the subject of this study [4–6]. Electrocaloric refrigeration around room temperature is a technology emergence that has aroused the interest of researchers around the world. In materials with an electrocaloric effect, a significant change in entropy can be done by applying or removing an electric field E. The ECE then depends only on the initial temperature of the material T and the electric field E. The ECE can be interpreted as the isothermal change entropy or the adiabatic change in temperature. The problem was solved by taking BaTiO3 as the electrocaloric material and water as an exchange fluid [6–11] The exchange coefficient is calculated from Reynolds, Prandtl and Nusselt numbers following correlations corresponding to our configuration(parallel plates, packed bed (cylinder) and perforated plates); implemented in COMSOL multiphysics.

53.2 Active Electrocaloric Refrigerator System Description AER The Active Electrocaloric Refrigerator (AER), shown in Fig. 53.1; with CHEX and HHEX; the cold heat exchanger and the hot heat exchanger; respectively. The regenerator made in parallel plates, packed bed (cylinder) and perforated plates, shown in Fig. 53.2. The velocity (water) U = 0.06 m/s, and the frequency f = 2 Hz.

Fig. 53.1 Schematic diagram of the AER

53 Thermal Investigation of an Electrocaloric Refrigeration Systems

(1): Parallel plates

(2): Packed bed (cylinder)

411

(3): Perforated plates

Fig. 53.2 The regenerator geometry AER

53.3 Thermodynamics of Electrocaloric Effects We can calculate the properties of AER (water and electrocaloric material) by the following formulas: Maxwell’s relations [1, 3, 12]: 

∂S ∂E



 = T

∂P ∂T

 (53.1) E

where S is the entropy, E is the electric field, P is the polarization, T is the temperature. Navier- Stokes, and energy equations [12–14]:  ρf

dU + (U · ∇)U dt

 − μ f ∇2 + ∇ p = 0

∇ ·U = 0 ∂ Ts − ks ∇ 2 Ts = 0 ∂t   ∂Tf + (U · ∇)T f − k f ∇ 2 T f = 0 ρ f c p, f ∂t ρ p,s

(53.2) (53.3) (53.4) (53.5)

53.4 Results and Discussions We have developed a 2D model of AER with COMSOL multiphysics which can support any electrocaloric regenerator (parallel plates, packed bed (cylinder) and perforated plates). In the investigation introduced in this work, the Active Electrocaloric Refrigerator has been tested with many geometry (parallel plates, packed bed (cylinder) and perforated plates) Fig. 53.3.

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(1): Parallel plates (TC=270 K)

(2): Packed bed (cylinder) (TC=278 K)

(3): Perforated plates (TC=281 K) Fig. 53.3 Temperature distribution during: The cold blow at t = 50 s

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In Fig. 53.4 we can observe the evolution of the temperatures distribution. At t = 50 s; the TC = 270 K, TC = 278 K, and TC = 281 K„ for AER made in parallel plates, packed bed (cylinder) and perforated plates; respectively. The system is initially at a T = 298 K. the best resultat obtained in regeneratore made in parallel plates. Figures 53.5 and 53.6 Show the coefficient of performance COP as function of time and temperature span. Which parallel plates configuration (COP = 5) has to be preferred to packed bed (COP = 3.5) and perforated plates (COP = 2.5). Figures 53.7 and 53.8 shows the theoretical cooling power as function temperature span and time, the best performance was in the AER based on parallel plates regenerator.

Fig. 53.4 The temperatures distribution of AER, during the first 50 s

Fig. 53.5 Coefficient of performance COP as function of time

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Fig. 53.6 Coefficient of performance COP as function of temperature span

Fig. 53.7 Cooling power as function of time

53.5 Conclusion Electrocaloric refrigeration is an environmentally friendly and promising technology. Unlike conventional compression refrigeration systems which use polluting gases, it uses solids as the refrigerant. Electrocaloric refrigeration has the potential to provide more efficient refrigeration systems. The cold power produced depends primarily on the performance of the material, the strength of the electric field and the thermal cycle.The technological mastery of electrocaloric refrigeration calls on many disciplines such as fluid

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Fig. 53.8 Cooling power as function of temperature span

mechanics, thermodynamics, thermics, material physics, electromagnetism and all are intertwined.

References 1. M. Ožbolt, A. Kitanovski, J. Tušek, A. Poredoš, Electrocaloric refrigeration: thermodynamics, state of the art and future perspectives. Int. J. Refrig 40, 174–188 (2014) 2. J.F. Scott, Electrocaloric materials. Annu. Rev. Mater. Res. 41, 229–240 (2011) 3. T. Correia, Q. Zhang, Electrocaloric materials. New Generation of Coolers, 34 (2014) 4. G. Zhang, Q. Li, H. Gu, S. Jiang, K. Han, M.R. Gadinski, Q. Wang, Ferroelectric polymer nanocomposites for room-temperature electrocaloric refrigeration. Adv. Mater. 27(8), 1450– 1454 (2015) 5. C. Aprea, A. Greco, A. Maiorino, C. Masselli, Electrocaloric refrigeration: an innovative, emerging, eco-friendly refrigeration technique. J. Phys. Conf. Ser. 796(1), 012019 (2017, January) IOP Publishing 6. D. Guo, J. Gao, Y.J. Yu, S. Santhanam, A. Slippey, G.K. Fedder, S.C. Yao, Design and modeling of a fluid-based micro-scale electrocaloric refrigeration system. Int. J. Heat Mass Transf. 72, 559–564 (2014) 7. Y. Jia, Y. Sungtaek Ju, A solid-state refrigerator based on the electrocaloric effect. Appl. Phys. Lett. 100(24), 242901 (2012) 8. G. Suchaneck, G. Gerlach, Materials and device concepts for electrocaloric refrigeration. Phys. Scr. 90(9), 094020 (2015) 9. M. Valant, Electrocaloric materials for future solid-state refrigeration technologies. Prog. Mater. Sci. 57(6), 980–1009 (2012) 10. S.G. Lu, Q. Zhang, Electrocaloric materials for solid-state refrigeration. Adv. Mater. 21(19), 1983–1987 (2009) 11. M. Ožbolt, A. Kitanovski, J. Tušek, A. Poredoš, Electrocaloric vs. magnetocaloric energy conversion. Int. J. Refrig. 37, 16–27 (2014) 12. Y. Bai, X. Han, K. Ding, L. Qiao, Electrocaloric refrigeration cycles with large cooling capacity in barium titanate ceramics near room temperature. Energy Technol. 5(5), 703–707 (2017)

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13. C. Aprea, A. Greco, A. Maiorino, C. Masselli, A comparison between electrocaloric and magnetocaloric materials for solid state refrigeration. Int. J. Heat Technol. 35(1), 225–234 (2017) 14. S. Hirasawa, T. Kawanami, K. Shirai, Electrocaloric refrigeration using multi-layers of electrocaloric material films and thermal switches. Heat Transf. Eng. 39(12), 1091–1099 (2018)

Chapter 54

Electronic and Thermoelectric Properties of Lead Sulfide PbS: DFT Approach Fatma Zohra Fouddad, Latifa Bouzid, and Said Hiadsi

Abstract This paper aims to investigate the structural, electronic, optical and thermoelectric properties of lead sulfide using the first principles calculations. The exchange–correlation potential is treated by two approximations, the local density approximation (LDA) and the generalized gradient approximation (GGA) to calculate the structural and electronic properties. The optical and thermoelectric properties of PbS sample are well predicted by GGA. The calculated band structure and density of states (DOS) show that lead sulfide is a semiconductor with gap energy of 0.082 and 0.47 eV for LDA and GGA respectively. The real and imaginary parts of dielectric function, refractive index, reflectivity and absorption coefficient are discussed in detail, where the results obtained are predictive and serve as good references for future experimental work. Finally, temperature dependent thermoelectric properties like electrical and thermal conductivity, Seebeck coefficient and power factor were calculated in detail by employing the Boltzmann transport theory under the BoltzTraP code. The PbS compound has a large power factor at high temperature reaches 2.51 × 1011 (W/mK2 s) with a positive Seebeck coefficient which indicates that lead sulfide is an intrinsic p-type semiconductor, and the major carrier is predominated by holes. Therefore, it reveals that PbS can be used as promising materials for high potential thermoelectric. Keywords Lead chalcogenide · DFT · Electronic properties · Optical properties · Thermoelectric properties

54.1 Introduction PbS is a promising semiconductor material for various technological applications, it is used successfully in infrared detectors and light emitting devices. They are also used as infrared lasers in optical fibers and as thermoelectric materials in solar panels [1, 2], quantum containment devices evolved with PbS, which allows the F. Z. Fouddad (B) · L. Bouzid · S. Hiadsi Department of Engineering Physics, University of Science and Technology, USTO- MB, Oran, Algeria © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 Y. Chiba et al. (eds.), Advances in Green Energies and Materials Technology, Springer Proceedings in Energy, https://doi.org/10.1007/978-981-16-0378-5_54

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operation of devices in a technologically important optical range [3], also it presents various interesting properties such as large dielectric constant, a low energy gap [4, 5]. Furthermore, to date a large variety of Ag2S nanostructures are synthesized [6– 11], due to their potential applications in nanocrystals [12], photovoltaic absorber material [13, 14], …. Earlier theoretical studies of the electronic structure of these material were made by many groups, using a semi-empirical tight-binding (TB) method [15], augmented plane waves (APW) [16], the Green function method [17], orthogonalized plane waves [18], and the emperical-pseudopotentiel method [19, 20]. Some volume properties [21], and optical constants [22] were calculated using the Mixed k.p-(APW) and linear combination of atomic orbitals [23] methods. The optical spectra of lead salt have already been calculated using the empirical pseudo-potential method [24]. Ab-initio calculations were also conducted on these materials using the linearized muffin- tin Orbital (LMTO) [25] and the Linearized Augmented Plane Wave (FPLAPW) methods [26, 27]. These theoretical calculations identified a direct band gap at the L point of the Brillouin zone for PbS lead chalchogenide. At ambient temperature and pressure, these compounds crystallize in the NaCl structure. The FP-LAPW method in the framework of the theory of density functional theory (DFT) [28, 29] is performed to investigate the structural, electronic and thermoelectric properties of PbS compound.We firstly computed the ground state properties of lead sulfide sample, such as lattice constant and bulk modulus. Then, we calculated the electronic structure including band structure and density of states. Finally, we studied the temperature dependent thermoelectric properties of PbS compound.

54.2 Computational Methods The structural, electronic and thermoelectric properties of cubic PbS are performed by using a Full-Potential Linearized Augmented Plane Wave (FP-LAPW) method within the framework of density functional theory (DFT) [28, 29] implemented in WIEN2K code [30]. The exchange–correlation potential for structural and electronic properties is calculated by the local density approximation (LDA) based on the method established by Perdew and Wang [31] and the generalized gradient approximation (GGA) based on the Perdew et al. [32] method. The optical and thermoelectric properties are computed using the GGA exchange potential. The wave functions, charge density and potential inside the muffin-tin (MT) spheres are expanded with an angular momentum lmax = 10. In the interstitial regions, the wave functions are expanded in plane wave with a cut-off of RMTKmax = 9, where RMT is the smallest muffintin radius and Kmax is the largest k vector in the plane wave’s expansion. The Pb (5d106p2), S (3s2 3p4), states are treated as valence electrons. The muffin-tin radius for Pb and S are taken as 2.50, 2.39 a.u. The irreducible Brillouin-zone integration is performed using Monkorst-Pack mesh [33] of 47 special k-points (grid of 10 10 10) alloys. Both of plane wave cut-off and the number of k-points were chosen in order to ensure total energy convergence. In the current research, we have taken the

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structure of the PbS in NaCl type (space group Fm-3 m, number 225). Primarily, we have calculated the equilibrium lattice constant (a0), the equilibrium volume (V0), the bulk modulus (B0) at zero pressure. These parameters are computed by fitting the total energy versus volume to the Murnaghan’s equation of state [34]. Then, the electronic band structure, at the equilibrium lattice constant for studied material is calculated along the high-symmetry directions in the face centered cubic-Brillouin Zone (fcc-BZ) and the total and partial density of states is graphed. Furthermore, we evaluated the thermoelectric properties by means of the semiclassical Boltzmann theory within the constant scattering time approximation (CSTA), as employed in the BoltzTraP code [16] centered cubic-Brillouin Zone (fcc-BZ), and the total and partial density of states is graphed. Furthermore, the optical properties are investigated within the GGA exchange potential, and we have compared all of the obtained results with other theoretical and experimental studies, we evaluated the thermoelectric properties employing the semiclassical Boltzmann theory within the constant scattering time approximation (CSTA), as employed in the BoltzTraP code [16].

54.3 Results and Discussion 54.3.1 Structural properties Figure 54.1 presents the cubic PbS structure (space group Fm-3 m, number 225). The calculated total energy of PbS, (NaCl) phase compound using LDA and GGA approximations is fitted with the Murnaghan equation of states to obtain structural parameters which are reported in Table 54.1. The lattice parameters for PbS are found to be 5.8537 and 6.0144 Å for LDA and GGA respectively. The LDA approximation calculations show an underestimation of 1.37% of the mesh parameters compared to the experimental values and an overestimation of 1.33% by GGA approximation. Fig. 54.1 Crystal structure of cubic (NaCl phase) PbS sample

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Table 54.1 Structural parameters and bulk modulus of PbS compound Lattice constant (Å) Exp

Theoretical

Present

LDA

GGA

5.929a

5.860a

6.012a

5.936b,c

5.906e

6.012e

5.940d

5.854f

LDA

GGA

5.8537

6.0144

Bulk modulus (GPa) Exp

52.9a

Theoretical

Present

LDA

GGA

64.8a

53.3a

66.3e

53.2f

LDA

GGA

65.65

53.04

67.3f a

Ref.[35], b Ref.[36], c Ref.[37], d Ref.[38], e Ref.[39], f Ref.[40]

Our calculated structural parameter for PbS material are in good agreement with other theoretical results [32, 35–41]. Bulk modulus is overestimated by the both approximations LDA and GGA. This over-estimation about the experiment is in the order of 0.14%, 24.1%, for LDA and GGA respectively. So, our result obtained by GGA approximation is in very good agreement with previous theoretical studies and experiment results.

54.3.2 Electronic properties The PbS compound is a semiconductor with a low energy gap, the bond between Pb and S is considered to be predominantly ionic [36]. The electronic band structures for PbS along the high symmetry directions in the Brillouin Zone (BZ) are obtained by using it’s equilibrium lattice parameters in the NaCl structure is shown in Fig. 54.2. It is clearly seen that PbS has a direct bandgap with a value of 0.082, 0.474 eV at L point for LDA and GGA approaches, respectively. Our results are compared with experimental and theoretical data available in Table 54.2. It should be noted that the results obtained by LDA and GGA disagree with those of the experience. The value of the gap is underestimated by LDA and overestimated by GGA, where, the experimental gap is very low compared with that determined by ab-initio methods. Generally speaking, these controversial values can be explained by the low energy gap value of this lead chalcogenide. Moreover, the difference between our calculated energy gaps values, and those calculated in the other works using the same method, is due to the fact that they introduced the interaction spin–orbit in their calculations, which resulted in a shift of the Conduction band. To better understand the band structure, it is interesting to determine the spectra of the total and partial

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(a)

(b)

Eg = 0.082 eV

Eg = 0.47 eV

LDA

GGA

Fig. 54.2 Electronic band structure of PbS compound, a LDA and b GGA approaches

Table 54.2 Energy gap of PbS semiconductor compound Gap energy E L→L (ev) of PbS compound Exp

Theoretical

Present

FP-LAPW

LMTO

LDA

GGA

LDA

LDA

GGA

0.286j, k

0.26l

0.38a

0.069d

0.082

0.47

0.29k

0.22a

0.44h

0.29m a Ref.[35], h Ref.[26], j Ref.[42], k Ref.[43], l Ref.[44], m Ref.[45].

state densities in order to analyze and know the type of hybridization and the states responsible for the liaison. The density of states (DOS) of PbS was calculated by GGA approximation. The projected total and partial DOS calculated are illustrated in Fig. 54.3. The deepest part of the valence band in the PbS compound is located in the range of energies (−13.23 → −11.75 eV), this region is essentially formed of the s states of the Chalcogen atom (S) as shown in the partial density curve (Fig. 54.3), this peak corresponds to the lowest valence band shown on the band structure curve (Fig. 54.2), and its width comes from the area surrounding the  point in the Brillouin area, where dispersion is quite appreciable. The structure centered at 8 eV below the Fermi level is predominated by the s states of lead, with a slight contribution of the s states of the chalcogen atom. For conduction strips that are located above the Fermi level, the dominant component is the p state of lead. Our analyses of the density of states are perfectly consistent with those of a. Delin et al. [22] and Lach-hab et al. [35].

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Partial DOS ( sates / ev)

Partial DOS ( sates / ev)

1,50

Pb Pb-s Pb-p Pb-d

1,25 1,00 0,75 0,50 0,25 0,00 -14 -12 -10

2,0 1,5 1,0 0,5 0,0

-8

-6

-4

-2

0

2

4

6

S S -s S -p

2,5

8

-14

-12

-10

-8

-6

-4

-2

0

2

4

6

8

Energy(ev)

Energy(ev)

Total DOS ( states / ev )

4 ,0

Tot PbS Tot Pb Tot S

3 ,5 3 ,0 2 ,5 2 ,0 1 ,5 1 ,0 0 ,5 0 ,0 -1 4 -1 2 -1 0

-8

-6

-4

-2

0

2

4

6

8

Energy(ev)

Fig. 54.3 Calculated total and partial density of states (DOS) of PbS compound within GGA approach

54.3.3 Thermoelectric Properties The group IV-VI (narrow-gap semiconducting) compounds show good electrical transport properties, due to its low thermal conductivities at high temperature and high values of thermoelectric figure of merits (ZT). This unique characteristic has made them useful thermoelectric (TE) materials for such a long time [11]. The energy conversion efficiency of thermoelectric material is characterized by the dimensionless figure of merit (ZT = S2 σ T /κ), where T, S, σ and κ are the operating temperature, Seebeck coefficient (thermopower), electrical conductivity and thermal conductivity. This (ZT) values can be improved by decreasing the κ. In this paper, the electronic transport properties are calculated in the temperature range from 100–800 K using the BoltzTraP program based on semi-classical transport theory within the constant scattering time approximation (CSTA), as employed in the BoltzTraP code [16]. Figure 54.4a–d shows the electrical transport properties as a function of temperature for PbS, including electrical conductivity, electronic thermal conductivity, Seebeck coefficient and power factor. Based on the calculated electronic structure (band structure and density of states), it’s easy to investigate the σ/τ (electrical conductivity) versus temperature (T) under constant relaxation time (τ) (see Fig. 54.4a). The electrical conductivity shows a semiconductor transport behavior dependent temperature, which increases linearly with increasing temperature and attains maximum value at temperature 850 K. The

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Fig. 54.4 Calculated the electrical transport properties as a function of temperature for PbS within GGA approach, including; a electrical conductivity, b Seebeck coefficient, c electronic thermal conductivity, and d power factor

linear increase in σ/τ is due to the excitation of the carrier from the occupied band to the unoccupied band, this excitation of the carrier occurs with an increase in temperature that gives rise to an increase in the number of carrier concentrations to the unoccupied band. At 100 K, the binary compound PbS has electrical conductivity (σ/τ) with a value of 0.014 × 1019 ( m s)−1 , whereas, at room temperature (300 K), the electrical conductivity (σ/τ) reaches 0.07×1019 ( m s)−1 , those values are small in front of 1.35 × 1019 and 1.28 × 1019 ( m s)−1 found by [50], these results can be interpreted by the difference in energy gap which has a significant influence on the electrical conductivity of the material. Thermoelectric materials have the ability to convert heat into electrical power and materials with high thermopower or Seebeck coefficient (S) are more efficient for the conversion of maximum heat to generate electrical power. In Fig. 54.4b, the positive Seebeck coefficient indicates PbS sample is an intrinsic p-type semiconductor, and the major carrier is predominated by holes, this result agrees well with that found

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by [11]. The values of the Seebeck coefficients for PbS show an increasing up-turn curve with increasing temperature. It should be noted that the two up-turn points of PbS is about 250 and 500 K. Therefore, these up-turn behaviors should be related to the intrinsic excitation of a given narrowband semiconductor. The Seebeck coefficient takes a minimum value of 242 μV/K at 100 K, 250 μV/K at room temperature (300 K) and a maximum value of 262 μV/K at 800 K. We notice a large value calculated at high temperature of the Seebeck coefficient comparing to that found by [11]. This maximum value of thermopower (S) for binary compound makes it more suitable for thermoelectric device applications at high temperature. The total thermal conductivity (k/τ )tot contribution comes from the lattice and electronic parts. Thermal conductivity varies with electrical conductivity, carrier concentration and mobility of the carrier [11]. The BoltzTraP code calculates only part. the electronic *( The temperature dependent electronic thermal conductivity is summarized in is increasing with the temperFig. 54.4c. As is clear from the figure that the ( ature and gain maximum value of 2.77 × 1014 (W/mKs) at 800 K, this increase is related to the carrier contribution to thermal conductivity. In thermoelectric properties, the power factor is an important part, which influences directly the thermoelectric performance. The average of power factor (PF = S2 σ/τ) as a function of temperature is shown in Fig. 54.4d. The power factor increases with increasing temperature from 100 to 800 K and reaches a maximum   value of 2.51 × 1011 W/mK2 s . This high value of (PF) of PbS sample is due to the high values of σ/τ. Hence, lead sulfide can be used as promising materials for high potential thermoelectric device applications.

54.4 Conclusion We have studied structural, electronic and thermoelectric properties of PbS using the LDA and GGA approximations within the density functional theory as implemented in the WIEN2k code. The structural result for our material is in general agreement with previous studies of PbS sample. The calculations prove that PbS has a direct bandgap with a value of 0.082, 0.474 eV at L point for LDA and GGA approaches, respectively. The study of the optical properties shows that the PbS compound has low absorption in the infrared range. Also, it has very strong absorption in the ultraviolet spectrum reaching 16.5 × 105 cm−1 , which can be used as a window layer in solar cell devices and as an ultraviolet radiation absorber. The thermoelectric study shows that PbS has large Seebeck coefficients and a high thermoelectric power factor values at a high temperature, with a positive Seebeck coefficient which indicates that lead sulfide is an intrinsic p-type semiconductor. Therefore, it reveals that PbS can be used as promising materials for high potential thermoelectric.

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References 1. G.P. Agrawal, N.K. Dutta, in Semiconductors Lazers, Van Nostrand Rein-hold, New York, p. 547 (1993) 2. P.K. Nair, M. Ocampo, A. Fernandez, M.T.S. Nair, Sol. Energy Mater. 20(1990) 235. P.K. Nair, A. Fernandez, M.T.S. Nair, Proc. SPIE Int. Soc. Opt. Eng. 1149 88 (1989) 3. E. Lipovskii, V. Kolovkova, I. Petricov, A. Kang, T. Olkhovets, M. Krauss, J. Thomas, F. Silcox, Q. Wise, S.K. Shen, Appl. Phys. Lett. 71, 3406 (1997) 4. R. Dalven, in Solid State Physics, ed. by H. Ehrenreich, F. Seitz, D. Turnbull, vol. 28, Academic, New York, p. 179 (1973) 5. R.A. Cowley, Philos. Mag. 11, 673 (1965); K. Murase, J. Phys. Soc. Jpn. Suppl. 49, 725 (1980) 6. M.-T. Liu, W. Li, Superlattices Microstruct. 120, 727–731 (2018) 7. J. Bai, Y. He, K. Wang, R. Wane, L.Z. Li, J. Lumin. 192, 675 (2017) 8. D.K. Sonavane, S.K. Jare, R.V. Kathare, R.N. Bulakhe, J.-J. Shim, Mater. Today Proc. 5, 7743–7747 (2018) 9. E. Akbay, Tufan Gür Ölmez. Mater. Lett. 215(15), 263–267 (2018) 10. M. Molaei, S. Abbasi, M. Karimipour, F. Dehghan, Mater. Chem. Phys. 216(1), 186–190 (2018) 11. S.A. Khan, S. Azam, Electronic structure and thermoelectric properties of PbS1-xTex (x=0, 0.25, 0.50, 0.75, and 1.0) alloys: ab initio study. Superlattices Microstruct. (2018). https://doi. org/10.1016/j.spmi.2018.04.031 12. R.S.S. Saravanan, M. Meena, D. Pukazhselvan, C.K. Mahadevan, J. Alloy. Compd. 627, 69 (2015) 13. R. Bai, D. Kumar, S. Chaudhary, D.K. Pandya, Acta Mater. 131, 11 (2017) 14. R. Bai, S. Chaudhary, D.K. Pandya, Mat. Sci. Semicon. Proc. 75, 301 (2018) 15. D.L. Mitchell, R.F. Wallis, Phys. Rev. 151, 581 (1966) 16. J.H. Conklin, L.E. Johnson, G.W. Pratt Jr., Phys. Rev. 137, 1282 (1965) 17. H. Overhof, U. Rossler, Phys. Stat. Sol. 37, 691 (1970) 18. F. Herman, R.L. Kortum, I.B. Ortenburger, J.P. Van Dyke, J. Phys. (Paris) 29, c4–c62 (1968) 19. G. Martinez, M. Schluter, Cohen. Phys. Rev. B 11, 651 (1975) 20. Y.W. Tung, Cohen. Phys. Rev. 180, 823 (1969) 21. V. Hinkel, H. Hoak, C. Mariana, L. Sorba, K. Horn, N.E. Christensen, Phys. Rev. B 40, 5549 (1989) 22. D.D. Buss, N.J. Parada, Phys. Rev. B 12692 (1970) 23. J.A. Valdivia, G.E. Barberis, J. Phys. Chem. Solids 56, 1141 (1995) 24. S.E. Kohn, P.Y. Yu, Y. Petroff, Y.R. Shen, Y. Tsang, Cohen. Phys. Rev. B 8, 1477 (1973) 25. L.G. Ferreira, Phys. Rev. 167, 801 (1965) 26. S. Wei, A. Zunger, Phys. Rev. B 55, 13605 (1977) 27. E.A. Albanesi, E.L. Peltzer y Blanca, A.G. Petukhov, Comput. Mat. Sci 32, 85 (2005) 28. W. Kohn, L.J. Sham, Phys. Rev. A 140, 1133 (1965) 29. P. Hohenberg, W. Kohn, Phys. Rev. B 136, 864 (1964) 30. P. Blaha, K. Schwarz, J. Luitz, WIEN2K (Vienna University of Technology, Austria, 2001). 31. J.P. Perdew, Y. Wang, Phys. Rev. 46, 12947 (1992) 32. J.P. Perdew, K. Burke, M. Ernzerhof, Phys. Rev. Lett. 77, 3865 (1996) 33. H.J. Monkhorst, J.D. Pack, Phys. Rev. 13, 5188 (1976) 34. F.D. Murnaghan, Proc. Natl. Acad. Sci. U.S.A. 30, 244 (1944) 35. O. Madelung, M. Schulz, H. Weiss (eds.), Numerical Data and Functional Relationships in Science and Technology, Landolt-Bornstei, New Series, vol. 17 (Springer, Berlin, 1983) 36. R. Dalven, in Solid State Physics ed. by H. Ehrenreich, F. Seitz, D. Turnbull, vol. 28, Academic, New York , p. 179 (1973) 37. M.L. Cohen, J.R. Chelikowsky, Electronic Structure and Optical Properties of Semiconductors, 2nd edn. Springer Series in Solids States Sciences, vol. 75, Springer, Berlin (1989) 38. P. Delin, O. Ravindran, J.M. Eriksson, Wills, Int. J. Quantum Chem. 69, 349 (1998) 39. E.A. Albanesi, C.M.I. Okoye, C.O. Rodriguez, E.L. Peltzer y Blanca, A.D. Petukhov, Phys. Rev. B 61, 16589 ((2000))

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Chapter 55

Comparison Between Methanol and Methane Steam Reforming Reactors for Hydrogen Production Abou Houraira Abaidi and Brahim Madani

Abstract This paper represents a comparison study between two fluids methanol and methane, to produce hydrogen from the procedure of steam reforming. Fluent was used for simulations of Methanol and Methane steam reforming. The aim of this work is to show the evolution of heat and mass transfers inside the reactors and their efficiencies. The results showed in the methanol steam reforming part; the consumptions of the main reactant CH3 OH and productions of the base element H2 . The methanol reformer efficiency is near to 42%, and in the methane steam reforming part; the consumptions of CH4 and productions of H2 . Also, the methane reformer efficiency is more than 46%. Keywords Methanol Steam Reforming · Methane Steam Reforming · Heat and Mass Transfer · Comparison Study

55.1 Introduction The search for an alternative clean and renewable energy source has become an urgent matter. One such energy-saving technology is fuel cell; it uses fuel as a source of energy to produce electricity directly and the by-products formed are not as voluminous and environmentally harmful. The conventional low temperature fuel cells use hydrogen as the fuel which is produced from conventional fuels via reforming. In this study, simple hydrocarbon fuels, namely methanol and methane are tested. The production of hydrogen from methanol steam reforming is way of many ways to have hydrogen. Number of papers interest to this topic; in [1] they show that axial heat flux by conduction plays an important role in the heat transfer characteristics and in the reactor efficiency to produce the hydrogen. The thinner the catalytic layer, the A. H. Abaidi (B) · B. Madani Laboratory of Polyphasic Transport and Porous Media, Faculty of Mechanical Engineering and Process Engineering, University Of Sciences and Technology Houari Boumediene, USTHB BP32 El Alia. 16111, Algiers, Algeria e-mail: [email protected] B. Madani e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 Y. Chiba et al. (eds.), Advances in Green Energies and Materials Technology, Springer Proceedings in Energy, https://doi.org/10.1007/978-981-16-0378-5_55

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higher the hydrogen production performance. In another work [2], carried out tests on a reactor that they considered themselves. This reactor consists of three functional parts: heating, vaporization of fuel and reaction of steam reforming of methanol. The experimental results indicate that the reactor performance depends on the reaction temperature, and on the molar feed rate of (MeOH/water) [3]. The results showed that the increase in the airflow rate in the heating side was beneficial to methanol conversion and hydrogen production [4]. The chemical conversion of methanol can reach levels higher than 90%, and the volumetric concentration of hydrogen in the gas products can account for 66-74%. The production of hydrogen from methane steam reforming is another way. In paper [5], a numerical simulation of catalyst wall-coated steam methane reformer for hydrogen production is carried out. The obtained results show that the CH4 conversion rate is estimated to 48.43%. The temperature gradient in [6] near the reformer inlet has a maximum value, because the temperature drop between catalyst and reaction mixture is maximum and maximum rate of steam methane reforming reaction takes place in this section of the reformer. The temperature gradient slows down to the outlet of the reformer, because the catalyst temperature decreases due to the endothermic steam methane reforming reaction, and also to the increase in the steam-to-methane ratio from inlet to outlet due to the methane consumption. As the reaction temperature increases [7], the rate of CO formation increases and that of CO2 decreases. At 800 °C, almost all CH4 is converted to CO and H2 , and the methane conversion rate (XCH4 ), the hydrogen production rate (YH2 ), and the CO selectivity (SCO ) are 92.28%, 3.34, and 0.99, respectively. The effects of the steamto-carbon ratio (S/C), inlet velocity, and preheating temperature at different reaction temperatures are simulated using the FLUENT software package. As S/C increases, XCH4 and YH2 increase, but SCO decreases. The higher the reaction temperature, the less S/C promotes XCH4 and YH2 . When the reaction temperature is 700 °C and the inlet velocity is 0.2 m/s (residence time is 0.5 s), XCH4 is above 95%, and changes in the inlet velocity strongly influence the formation of CO. With increasing preheating temperature, XCH4 , YH2 , and SCO all increase gradually. The analysis [8] indicated that the energy efficiency of induction-heated steam reforming systems scaled to larger H2 capacities may be above 80%. The aim of this work is to show heat and mass transfers inside the reactors, and evolutions of each chemical species, and efficiencies of reactors. Also, the difference between the two processes: the methanol steam reforming and methane steam reforming, and this from the heat and mass transfer points of view.

55.2 Steam Reforming (a)

Methanol Steam Reforming Reaction The global reaction of methanol steam reforming is carried out over CuO/ZnO/Al2 O3 catalyst [9, 10]:

55 Comparison Between Methanol and Methane Steam …

CH3 OH + H2 O → CO2 + 3H2 DHSMR = 49.5 kJ/mo1

429

(55.1)

It is assumed that carbon monoxide is generated first (methanol decomposition) and then reacts with water to form carbon dioxide (water-gas shift):

CH3 OH → CO + 2H2 DHM = 90.5 kJ/mo1

(55.2)

CO + H2 OCO2 + H2 DHWGS = −41 kJ/mo1

(55.3)

To calculate the reaction rate [9, 10], the flowing equation represents the power law kinetic expression, it’s based at the partial pressions for reactant, activation energy of reaction steam reforming and pre-exponential factor:  −E PCn 1H 3O H PHn 22 O = k0 ex p RT 

rM SR

(55.4)

Such as: n1 = 0.26. n2 = 0.03. E = 105.1 [kJ.mol−1 ] (Activation Energy) k0 = 2.85.109 [mol CH3 OH kgcat −1 .s−1 .kPa− ni ] (Pre-exponential factor). (b)

Methane Steam Reforming Reaction

The mix of steam and methane is converted into carbon monoxide and hydrogen by endothermic reaction (55.5) [6, 9]. This is accompanied by the reverse water gas shift Reaction (55.6), finally the reverse methanation (55.7), it represents the global methane steam reforming reaction: Methane steam reforming reaction: CH4 + H2 OCO + 3H2 DH = 206.15 kJ/mo1

(55.5)

Water-gas shift reaction: CO + H2 OCO2 + H2 DH = −41.16 Kj/mo1

(55.6)

Global methane steam reforming reaction: CH4 + 2H2 OCO2 + 4H2 DH = −165 KJ/mo1

(55.7)

Concerning the kinetic model of methane steam reforming [11, 12], the catalyst wall reaction rate expression can be simplified by a power law kinetic expression such as equation (55.8):

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 r = kexp

−Ea RT

 PaCH4 PbH2 O

(55.8)

Such as: • • • •

a = 0.47. b = − 0.01. Ea = 43.2 (kJ.mol−1 ) (Activation Energy). k = 0.392 (molCH4 kgcat −1 s−1 . kPa− ni ) (Pre-exponential factor).

55.3 Mathematical Model The fluid flow is governed by the Navies-Stokes equations and the temperature and mass fields are governed by the energy equation and the equation of species, repressively. The governing equations are given as follows: Continuity ∂ρv ∂ρu + =0 ∂x ∂y Navies-Stokes        ∂ρu ∂ρu ∂p ∂ ∂u ∂ ∂u u +v =− + μ + μ ∂x ∂y ∂x ∂x ∂x ∂x ∂y        ∂ρv ∂ρv ∂p ∂ ∂v ∂ ∂v u +v =− + μ + μ ∂x ∂y ∂y ∂x ∂x ∂x ∂y

(55.8)

(55.9) (55.10)

Energy       ∂ρC p T ∂ρC p T ∂ ∂T ∂ ∂T u = λ + λ + SW G S ∂x ∂y ∂x ∂x ∂x ∂y

(55.11)

Species u

    ∂ρwi ∂ρwi ∂ ∂ ∂ρwi ∂ρwi +v = Di + Di ∂x ∂y ∂x ∂x ∂x ∂y

(55.12)

Such as: Di represents the mass diffusivity of the species (i = CH3 OH, CH4 , CO2 , H2O, H2 and CO). The mass-diffusion model in this work is based on the Lewis number which is considered equal to the unit for all species; Di =

λ ρ.Lei .C p

(55.13)

55 Comparison Between Methanol and Methane Steam …

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55.4 Physical Model (a)

Methanol steam reforming reactor The first physical model is clearly shown in Fig. 55.1, which is defined as a two-dimensional rectangular channel having a length of 10 mm and a height of 0.6 mm. The direction of flow is along the axis X, the upper wall and defined as the active wall, where the location of the catalytic layer is located, and the lower wall is an adiabatic wall.

(b)

Methane steam reforming reactor The second physical model is shown in Fig. 55.2, which is defined as a twodimensional, rectangular channel too, it has 20 mm of length and 3.1 mm a height. The direction of flow is along the axis X. The lower wall is defined as the support of catalyst, which has 10 mm of length. The bottom wall is an impermeable wall, who has a constant temperature.

The following assumptions are considered: • Flow regime is laminar and steady. • Gases are considered perfect gases. • Pressure drop is zero; the operating pressure considered is the atmospheric pressure. • Gases physical characteristics are constant. • Gases can be modelled as incompressible fluids (constant density).

Fig. 55.1 Description of methanol steam reforming reactor

Fig. 55.2 Description of methane steam reforming reactor

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55.5 Results and Discussion (a)

Methanol steam reforming reactor Figure 55.3a represents the temperature field inside the methanol steam reforming reactor. After this picture, it’s noted the rapid increase in the heat transfer, particulary in the 10% firstly length of reactor, because the temperature in the inlet is 120 °C, and the walls temperature is equal to 180 °C, also the starting of reaction or the activation of reaction, such as the active wall is the upper wall, the place that the consumption and production of several chimical species. And in the 90% rest of reactor, there is just one color that means the stability of phenomena inside the reactor, or the phenomena is established. The next Fig. 55.3b, c display the evolution of mass fraction of methanol and hydrogen, respectively. After the figures, it is remarked the consumptions of main reactant CH3 OH, and the production of the principal element H2 , in chemical terms the reaction is activated. As well as the heat filed, there is big mass transfer, that’s due to the starting of reaction of methanol steam reforming, for the rest of the reactor there is a stability in mass transfer look like the heat field, that explained by the mass transfer is established else. For this case, the reactor represents more than 42 % of efficiency, or the percentage of methanol consumption.

(b)

Methane steam reforming reactor: Figure 55.4a represents the temperature field inside the second reactor of methane steam reforming. It’s shown that in the first part of reactor there is no heat transfert phenomena, after that the zone near the catalyst, a large heat transfer is noted, that is due to the consumption of thermal energy, that is logically, because the reaction of steam reforming is endothermic reaction, or reaction needs thermal energy to occur. The next Fig. 55.3b, c display the evolution of mass fraction of methanol and hydrogen, respectively. After the previous figures, it is remarked that in the first part like the heat field, there is no mass transfer, after that nearby the catalyst zone, there is an important mass transfer, another mean a consumptions of main regnant CH4 , and the production of the principal element H2 , chemically the reaction is activated. Concerning the efficiency of the second reactor in those conditions, it’s more than 46 %.

(c)

Comparison After the obtained results, the heat and mass transfers are big nearby the catalyst. And the efficiencies for the two models are adjacents despite the difference in the operating conditions. The main differences between the two fluids are; in the heat side, the methane steam reforming demands more thermal energy than methanol steam reforming, and in mass side the methane steam reforming reactor produces one molar plus than the methanol steam reforming. Also, at the inlet the methane is in gas form, while methanol is in liquid form, therefore it demands further thermal energy to change from liquid to gas phase.

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Fig. 55.3 a Temperature field inside methanol steam reformer. b Distribution of methanol mass fraction. c Distribution of hydrogen mass fraction inside methanol steam reformer

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Fig. 55.4 a Temperature field inside methane steam reformer. b Distribution of methane mass fraction inside methane steam reformer. c Distribution of hydrogen mass fraction inside methane steam reformer

55 Comparison Between Methanol and Methane Steam …

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55.6 Conclusion This paper represents a comparison between two fluids methanol and methane to produce hydrogen, using steam reforming process. The software Ansys Fluent has been used for the several simulations. The paper represents the two mechanisms of fuel steam reforming. The results show that the heat and mass transfers are big nearby the catalyst. And the efficiencies for the two reactions are 42% and 46%, respectively.

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