Renewable Energy Systems
Modelling, Optimization and Control
- 1st Edition - September 13, 2021
- Latest edition
- Editors: Ahmad Taher Azar, Nashwa Ahmad Kamal
- Language: English
Renewable Energy Systems: Modelling, Optimization and Control aims to cross-pollinate recent advances in the study of renewable energy control systems by bringing together… Read more
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.
- 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
Academia, Postgraduate students, Professional Engineers in Mathematicians, Engineering Mathematics, Biomedical Engineering, Computer science. Computational Physics
1. Efficiency maximization of wind turbines using data-driven Model-Free Adaptive Control
2. Advanced control design based on sliding modes technique for power extraction maximization in variable speed wind turbine
3. Generic modeling and control of wind turbines following IEC 61400-27-1
4. Development of a nonlinear backstepping approach of gridconnected PMSG wind farm Structure
5. Model predictive control-based energy management strategy for grid-connected residential photovoltaic_wind_battery system
6. Efficient maximum power point tracking in fuel cell using the fractional-order PID controller
7. Robust adaptive nonlinear controller of wind energy conversion system based on permanent magnet synchronous generator
8. Improvement of fuel cell MPPT performance with a fuzzy logic controller
9. Control strategies of wind energy conversion system-based doubly fed induction generator
10. Modeling of a high-performance three-phase voltage-source boost inverter with the implementation of closed-loop control
11. Advanced control of PMSG-based wind energy conversion system applying linear matrix inequality approach
12. Fractional-order controller design and implementation for maximum power point tracking in photovoltaic panels
13. Technoeconomic modeling of standalone and hybrid renewable energy systems for thermal applications in isolated areas
14. Solar thermal system—an insight into parabolic trough solar collector and its modelling
15. Energy hub: modeling, control, and Optimization
16. Simulation of solar-powered desiccant-assisted cooling in hot and humid climates
17. Recent optimal power flow Algorithms
18. Challenges for the optimum penetration of photovoltaic systems
19. Modeling and optimization of performance of a straight bladed HDarrieus vertical-axis wind turbine in low wind speed condition: a hybrid multicriteria decision-making approach
20. Maximum power point tracking design using particle swarm optimization algorithm for wind energy conversion system connected to the grid
21. Multiobjective optimization-based energy management system considering renewable energy, energy storage systems, and electric vehicles
22. Fuel cell parameters estimation using optimization techniques
23. Optimal allocation of distributed generation/shunt capacitor using hybrid analytical/metaheuristic techniques
24. Optimal appliance management system with renewable energy integration for smart homes
25. Solar cell parameter extraction using the Yellow Saddle Goatfish Algorithm
26. Reactive capability limits for wind turbine based on SCIG for optimal integration into the grid
27. Demand-side strategy management using PSO and BSA for optimal dayahead load shifting in smart grid
28. Optimal power generation and power flow control using artificial intelligent techniques
29. Nature-inspired computational intelligence for optimal sizing of hybrid renewable energy system
30. Optimal design and techno-socioeconomic analysis of hybrid renewable system for gird-connected system
31. Stand-alone hybrid system of solar photovoltaics/wind energy resources: an eco-friendly sustainable approach
- Edition: 1
- Latest edition
- Published: September 13, 2021
- Language: English
AT
Ahmad Taher Azar
Prof. Ahmad Azar is a full Professor at Prince Sultan University, Riyadh, Kingdom Saudi Arabia. He is the leader of Automated Systems and Computing Lab (ASCL), Prince Sultan University, Saudi Arabia.
Prof. Azar is the Editor in Chief of the International Journal of Intelligent Engineering Informatics (IJIEI), Inderscience Publishers, Olney, UK. He is also the Editor in Chief of International Journal of Service Science, Management, Engineering, and Technology (IJSSMET) and International Journal of Sociotechnology and Knowledge Development (IJSKD) published by IGI Global, USA. From 2013 to 2017, Prof. Azar was an associate editor of ISA Transactions, Elsevier.
He is currently an editor for IEEE Transactions on Fuzzy Systems, IEEE Systems Journal, IEEE Transactions on Neural Networks and Learning Systems, Springer's Human-centric Computing and Information Sciences.
Prof. Azar specializes in artificial intelligence (AI), robotics, machine learning, control theory and applications, computational intelligence, reinforcement learning, and dynamic system modeling. He has published or co-published over 550 research papers, book chapters, and conference proceedings in prestigious peer-reviewed journals.
Dr. Ahmad Azar has received several awards, including the Benha University Prize for Scientific Excellence (2015, 2016, 2017, and 2018) and the Benha University Highest Citation Award (2015, 2016, 2017, and 2018).
In June 2018, he was awarded the Egyptian State Encouragement Award in Engineering Sciences by the Ministry of Higher Education and Scientific Research. In August 2018, he was elected as a senior member of the International Rough Set Society (IRSS).
Prof. Azar was named one of the top computer scientists in Saudi Arabia by Research.com since December 2019.
He was awarded the Egyptian President's Distinguished Egyptian Order of the First Class in February 2020.
In October 2020, Prof. Azar received Abdul Hameed Shoman Arab Researchers Award in Machine Learning and Big Data Analytics.
From October 2020 to September 2023, Prof. Azar was recognized as a Distinguished researcher at Prince Sultan University, Riyadh, Saudi Arabia.
In November 2020, October 2021, October 2022, October 2023, September 2024, and September 2025 Prof. Azar was named one of the top 2% of scientists in the world in Artificial Intelligence by Stanford University, based on single-year impact and career-long impact. These rankings were published by Stanford University in the PLOS journal and were based on the SCOPUS database.
Prof. Ahmad Azar has been recognized as one of the top ten researchers at Prince Sultan University, based on his Scopus H-index. He has also received a university award for being among his top publication of research.
Prof. Azar has received Prince Sultan University’s Research Excellence Award. He is also the recipient of the university’s Highest Impact Researcher Award, based on his H-index. Additionally, he has earned a PSU research award for having publications ranked among the top five by impact factor.
Prof. Ahmad Azar is the Vice Chair of the International Federation of Automatic Control (IFAC) Technical Committee of Control Design, Vice chair of IFAC Technical committee 4.3 Robotics, Vice chair of IFAC Technical committee 9.3 “Control for Smart Cities”. He is a technical Committee Member of Data Mining and Big Data Analytics of IEEE Computational Intelligence Society (CIS), IFAC Technical committee Member TC 2.2. Linear Control Systems, IFAC Technical committee Member TC 1.2. Adaptive and Learning Systems.