Renewable Energy Systems

Renewable Energy Systems

Modelling, Optimization and Control

1st Edition - September 9, 2021

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  • Editors: Ahmad Azar, Nashwa Kamal
  • Paperback ISBN: 9780128200049
  • eBook ISBN: 9780128203989

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Description

Renewable Energy Systems: Modelling, Optimization and Control aims to cross-pollinate recent advances in the study of renewable energy control systems by bringing together diverse scientific breakthroughs on the modeling, control and optimization of renewable energy systems by leading researchers. The book brings together the most comprehensive collection of modeling, control theorems and optimization techniques to help solve many scientific issues for researchers in renewable energy and control engineering. Many multidisciplinary applications are discussed, including new fundamentals, modeling, analysis, design, realization and experimental results. The book also covers new circuits and systems to help researchers solve many nonlinear problems. This book fills the gaps between different interdisciplinary applications, ranging from mathematical concepts, modeling, and analysis, up to the realization and experimental work.

Key Features

  • Covers modeling, control theorems and optimization techniques which will solve many scientific issues for researchers in renewable energy
  • Discusses many multidisciplinary applications with new fundamentals, modeling, analysis, design, realization and experimental results
  • Includes new circuits and systems, helping researchers solve many nonlinear problems

Readership

Academia, Postgraduate students, Professional Engineers in Control Engineering; Electrical and Electronics Engineering; Power Engineering; Mathematics and Applied Mathematics; Physics; Computer Engineering. Academia, Postgraduate students, Professional Engineers in Mathematicians, Engineering Mathematics, Biomedical Engineering, Computer science. Computational Physics

Table of Contents

  • Cover image
  • Title page
  • Table of Contents
  • Copyright
  • List of contributors
  • Preface
  • About the book
  • Objectives of the book
  • Organization of the book
  • Book features
  • Audience
  • Acknowledgments
  • Chapter 1. Efficiency maximization of wind turbines using data-driven Model-Free Adaptive Control
  • Abstract
  • 1.1 Introduction
  • 1.2 Problem statement
  • 1.3 Control design
  • 1.4 Simulation study using FAST
  • 1.5 Conclusions
  • References
  • Chapter 2. Advanced control design based on sliding modes technique for power extraction maximization in variable speed wind turbine
  • Abstract
  • 2.1 Introduction
  • 2.2 Modeling variable speed wind turbine
  • 2.3 Sliding mode control design
  • 2.4 Simulation results
  • 2.5 Conclusion and future directions
  • Acknowledgments
  • Nomenclature
  • References
  • Appendix
  • Chapter 3. Generic modeling and control of wind turbines following IEC 61400-27-1
  • Abstract
  • 3.1 Introduction
  • 3.2 Literature review
  • 3.3 Modeling, simulation and validation of the Type 3 WT model defined by Standard IEC 61400-27-1
  • 3.4 Model validation results
  • 3.5 Conclusions
  • References
  • Chapter 4. Development of a nonlinear backstepping approach of grid-connected permanent magnet synchronous generator wind farm structure
  • Abstract
  • 4.1 Introduction
  • 4.2 Related work
  • 4.3 Mathematical model of wind turbine generator
  • 4.4 Control schemes of wind farm
  • 4.5 Simulation result analysis
  • 4.6 Conclusions
  • Appendix
  • References
  • Further reading
  • Chapter 5. Model predictive control-based energy management strategy for grid-connected residential photovoltaic–wind–battery system
  • Abstract
  • 5.1 Introduction
  • 5.2 Related works
  • 5.3 The architecture of original grid-tied PV–WT–battery and optimal control strategy
  • 5.4 Energy management strategy and the model of the open-loop control
  • 5.5 Model predictive control for the PV/wind turbine/battery system
  • 5.6 Results and discussion
  • 5.7 Conclusion
  • References
  • Chapter 6. Efficient maximum power point tracking in fuel cell using the fractional-order PID controller
  • Abstract
  • 6.1 Introduction
  • 6.2 PEMFC system description
  • 6.3 MPPT control configuration
  • 6.4 Design and implementation of FOPID MPPT control technique
  • 6.5 Controller tuning using GWO
  • 6.6 MPPT performance analysis
  • 6.7 Conclusion
  • References
  • Chapter 7. Robust adaptive nonlinear controller of wind energy conversion system based on permanent magnet synchronous generator
  • Abstract
  • 7.1 Introduction
  • 7.2 Speed-reference optimization: power to optimal speed
  • 7.3 Modeling of the association “permanent magnet synchronous generator–AC/DC/AC converter”
  • 7.4 State-feedback nonlinear controller design
  • 7.5 Output-feedback nonlinear controller design
  • 7.6 Digital implementation
  • 7.7 Conclusion
  • References
  • Chapter 8. Improvement of fuel cell MPPT performance with a fuzzy logic controller
  • Abstract
  • 8.1 Introduction
  • 8.2 Modeling of proton-exchange membrane fuel cells
  • 8.3 Mathematical model of DC–DC converter
  • 8.4 Proposed algorithm
  • 8.5 Results and analysis
  • 8.6 Discussion
  • 8.7 Conclusion and perspectives
  • References
  • Chapter 9. Control strategies of wind energy conversion system-based doubly fed induction generator
  • Abstract
  • 9.1 Introduction
  • 9.2 Modeling with syntheses of PI controllers of wind system elements
  • 9.3 Results and discussions
  • 9.4 Conclusion
  • Appendix
  • References
  • Chapter 10. Modeling of a high-performance three-phase voltage-source boost inverter with the implementation of closed-loop control
  • Abstract
  • 10.1 Introduction
  • 10.2 Mathematical analysis of the three-phase boost inverter
  • 10.3 System description
  • 10.4 Results and discussions
  • 10.5 Conclusion
  • References
  • Chapter 11. Advanced control of PMSG-based wind energy conversion system applying linear matrix inequality approach
  • Abstract
  • 11.1 Introduction
  • 11.2 Recent research on control in wind energy conversion systems
  • 11.3 Model of the PMSG-based WECS
  • 11.4 Controller design of the PMSG-based WECS
  • 11.5 Simulation results and discussion
  • 11.6 Conclusion
  • Appendix
  • References
  • Chapter 12. Fractional-order controller design and implementation for maximum power point tracking in photovoltaic panels
  • Abstract
  • 12.1 Introduction
  • 12.2 Related work
  • 12.3 Problem formulation
  • 12.4 Fractional-order design techniques for MPPT of photovoltaic panels
  • 12.5 Numerical experiments
  • 12.6 Discussion
  • 12.7 Conclusion
  • References
  • Chapter 13. Techno-economic modeling of stand-alone and hybrid renewable energy systems for thermal applications in isolated areas
  • Abstract
  • 13.1 Introduction
  • 13.2 Materials and methods
  • 13.3 Results and discussions
  • 13.4 Technoeconomic analysis of the hybrid energy-based cooling system
  • 13.5 Sensitivity analysis
  • 13.6 Conclusion
  • References
  • Chapter 14. Solar thermal system—an insight into parabolic trough solar collector and its modeling
  • Abstract
  • 14.1 Introduction
  • 14.2 Related work
  • 14.3 Parabolic trough solar collector—history
  • 14.4 Parabolic trough solar collector—an overview
  • 14.5 Performance evaluation of PTSC
  • 14.6 Analytical thermal models
  • 14.7 1-D heat transfer model
  • 14.8 Potential applications
  • 14.9 Discussion
  • 14.10 Conclusion
  • Nomenclature
  • References
  • Chapter 15. Energy hub: modeling, control, and optimization
  • Abstract
  • 15.1 Introduction
  • 15.2 Energy management systems
  • 15.3 Concept of energy hub
  • 15.4 Mathematical modeling of energy hub
  • 15.5 Energy hub with storage capacities
  • 15.6 Integration of renewable resources to energy hub
  • 15.7 Simulations
  • 15.8 Optimization of energy hub in GAMS
  • 15.9 Conclusion
  • References
  • Chapter 16. Simulation of solar-powered desiccant-assisted cooling in hot and humid climates
  • Abstract
  • 16.1 Introduction
  • 16.2 Literature survey
  • 16.3 System description
  • 16.4 Measurements
  • 16.5 Data reduction and uncertainty analysis
  • 16.6 Results and discussion
  • 16.7 Prediction of system performance by use of TRNSYS simulation
  • 16.8 Conclusion
  • Nomenclature
  • References
  • Chapter 17. Recent optimal power flow algorithms
  • Abstract
  • 17.1 Introduction
  • 17.2 Moth-flame optimization technique
  • 17.3 Moth swarm algorithm
  • 17.4 Multiverse optimization
  • 17.5 Wale optimization algorithm
  • 17.6 Objective functions
  • 17.7 Results and discussions
  • 17.8 Conclusion
  • Appendix A (Tables 17.A1–17.A5)
  • References
  • Chapter 18. Challenges for the optimum penetration of photovoltaic systems
  • Abstract
  • Nomenclature
  • 18.1 Introduction
  • 18.2 PV system management
  • 18.3 PV system grid connection
  • 18.4 Future technical regulatory aspects
  • 18.5 Conclusions
  • Acknowledgments
  • References
  • Chapter 19. Modeling and optimization of performance of a straight bladed H-Darrieus vertical-axis wind turbine in low wind speed condition: a hybrid multicriteria decision-making approach
  • Abstract
  • 19.1 Introduction
  • 19.2 Related work
  • 19.3 Turbine design and experimental description
  • 19.4 Integrated entropy–multicriteria ratio analysis method
  • 19.5 Modeling of vertical-axis wind turbine using integrated entropy–multicriteria ratio analysis method
  • 19.6 Results and discussion
  • 19.7 Conclusions and scope for future work
  • References
  • Chapter 20. Maximum power point tracking design using particle swarm optimization algorithm for wind energy conversion system connected to the grid
  • Abstract
  • 20.1 Introduction
  • 20.2 Wind energy conversion system modeling
  • 20.3 Control strategies of the maximum power point tracking
  • 20.4 Field-oriented control technique of the active and reactive power
  • 20.5 Simulation results and discussion
  • 20.6 Conclusion
  • Appendix A
  • References
  • Chapter 21. Multiobjective optimization-based energy management system considering renewable energy, energy storage systems, and electric vehicles
  • Abstract
  • 21.1 Introduction
  • 21.2 System description
  • 21.3 Proposed scheduling and optimization model
  • 21.4 Results and discussion
  • 21.5 Conclusion
  • References
  • Chapter 22. Fuel cell parameters estimation using optimization techniques
  • Abstract
  • 22.1 Introduction
  • 22.2 Mathematical model of proton exchange membrane fuel cell stacks
  • 22.3 Optimization techniques
  • 22.4 Case study
  • 22.5 Results and discussion
  • 22.6 Conclusion
  • References
  • Chapter 23. Optimal allocation of distributed generation/shunt capacitor using hybrid analytical/metaheuristic techniques
  • Abstract
  • 23.1 Introduction
  • 23.2 Objective function
  • 23.3 Mathematical formulation of the analytical technique
  • 23.4 Metaheuristic technique
  • 23.5 Simulation results
  • 23.6 Conclusion
  • References
  • Chapter 24. Optimal appliance management system with renewable energy integration for smart homes
  • Abstract
  • 24.1 Introduction
  • 24.2 Related work
  • 24.3 System architecture
  • 24.4 The proposed approach for scheduling the home appliances
  • 24.5 Results and discussion
  • 24.6 Conclusion
  • References
  • Chapter 25. Solar cell parameter extraction using the Yellow Saddle Goatfish Algorithm
  • Abstract
  • 25.1 Introduction
  • 25.2 Solar cell mathematical modeling
  • 25.3 Yellow Saddle Goatfish Algorithm-based solar cell extraction
  • 25.4 Results and discussion
  • 25.5 Experimental data measurement of 250 Wp PV module (SVL0250P) using SOLAR-4000 analyzer
  • 25.6 Conclusion
  • References
  • Chapter 26. Reactive capability limits for wind turbine based on SCIG for optimal integration into the grid
  • Abstract
  • 26.1 Introduction
  • 26.2 Literature survey and grid code requirements
  • 26.3 Reactive capability limits for squirrel cage induction generator
  • 26.4 Estimation of reactive power limits for the grid side system
  • 26.5 Reactive capability for DC bus capacitor
  • 26.6 Validation results
  • 26.7 Conclusion
  • Abbreviations
  • Appendix A
  • References
  • Chapter 27. Demand-side strategy management using PSO and BSA for optimal day-ahead load shifting in smart grid
  • Abstract
  • 27.1 Introduction
  • 27.2 DSM driven approaches
  • 27.3 Mathematical formulation of the problem
  • 27.4 Proposed demand management optimization algorithm
  • 27.5 Energy management of the proposed system
  • 27.6 Results and discussion
  • 27.7 Conclusion
  • References
  • Chapter 28. Optimal power generation and power flow control using artificial intelligence techniques
  • Abstract
  • 28.1 Introduction
  • 28.2 Conventional methods
  • 28.3 Artificial neural network and fuzzy logic to optimal power flow
  • 28.4 Genetic algorithm
  • 28.5 Application of expert system to power system
  • 28.6 Assessment of optimal power flow by game playing concept
  • References
  • Chapter 29. Nature-inspired computational intelligence for optimal sizing of hybrid renewable energy system
  • Abstract
  • 29.1 Introduction
  • 29.2 Mathematical hybrid system model
  • 29.3 Optimization formulation
  • 29.4 Nature-inspired algorithms
  • 29.5 Advantages and limitations of the algorithms
  • 29.6 Numerical data
  • 29.7 Results and discussion
  • 29.8 Findings of the study
  • 29.9 Conclusion and future directions
  • Acknowledgments
  • References
  • Chapter 30. Optimal design and techno-socio-economic analysis of hybrid renewable system for gird-connected system
  • Abstract
  • 30.1 Introduction
  • 30.2 Motivation and potential benefits of hybrid renewable sources
  • 30.3 Hybrid renewable energy system design and optimization
  • 30.4 Availability of renewable sources and utilization for case study
  • 30.5 Modeling of hybrid renewable system components
  • 30.6 Explanation of problem and methodology for case study
  • 30.7 Results and discussion
  • 30.8 Conclusion
  • Acknowledgment
  • References
  • Chapter 31. Stand-alone hybrid system of solar photovoltaics/wind energy resources: an eco-friendly sustainable approach
  • Abstract
  • 31.1 Introduction
  • 31.2 Renewable energy sources
  • 31.3 Hybrid renewable energy systems
  • 31.4 Modeling of SPV/wind HRES
  • 31.5 Optimization and sizing of SPV/wind HRES
  • 31.6 Future of SPV/wind HRES
  • 31.7 Conclusion
  • References
  • Index

Product details

  • No. of pages: 732
  • Language: English
  • Copyright: © Academic Press 2021
  • Published: September 9, 2021
  • Imprint: Academic Press
  • Paperback ISBN: 9780128200049
  • eBook ISBN: 9780128203989

About the Editors

Ahmad Azar

Prof. Ahmad Azar has received the M.Sc. degree in 2006 and Ph.D degree in 2009 from Faculty of Engineering, Cairo University, Egypt. He is a research associate Professor at Prince Sultan University, Riyadh, Kingdom Saudi Arabia. He is also an associate professor at the Faculty of Computers and Artificial intelligence, Benha University, Egypt. Prof. Azar is the Editor in Chief of International Journal of System Dynamics Applications (IJSDA) and International Journal of Service Science, Management, Engineering, and Technology (IJSSMET) published by IGI Global, USA. Also, he is the Editor in Chief of International Journal of Intelligent Engineering Informatics (IJIEI), Inderscience Publishers, Olney, UK. Prof. Azar has worked as associate editor of IEEE Trans. Neural Networks and Learning Systems from 2013 to 2017. He is currently Associate Editor of ISA Transactios, Elsevier and IEEE systems journal. Dr. Ahmad Azar has worked in the areas of Control Theory & Applications, Process Control, Chaos Control and Synchronization, Nonlinear control, Renewable Energy, Computational Intelligence and has authored/coauthored over 200 research publications in peer-reviewed reputed journals, book chapters and conference proceedings. He is an editor of many books in the field of fuzzy logic systems, modeling techniques, control systems, computational intelligence, chaos modeling and machine learning. Dr. Ahmad Azar is closely associated with several international journals as a reviewer. He serves as international programme committee member in many international and peer-reviewed conferences. Dr. Ahmad Azar has been a senior member of IEEE since December 2013 due to his significant contributions to the profession. Dr. Ahmad Azar is the recipient of several awards including: Benha University Prize for Scientific Excellence (2015, 2016, 2017 and 2018), the paper citation award from Benha University (2015, 2016, 2017 and 2018). In June 2018, Prof. Azar was awarded the Egyptian State Prize in Engineering Sciences, the Academy of Scientific Research and Technology of Egypt, 2017. In July 2018 he was selected as a member of Energy and Electricity Research council, Academy of Scientific Research, Ministry of Higher Education. In August 2018 he was selected as senior member of International Rough Set Society (IRSS).

Affiliations and Expertise

Research Associate Professor, Prince Sultan University, Riyadh, Kingdom Saudi Arabia; Associate Professor, Faculty of Computers and Artificial intelligence, Benha University, Egypt

Nashwa Kamal

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