Energy Management Systems for Microgrids With Wind, Pv and Battery Storage
Language: English
Published by Inst of Engineering & Technology, 2025
- Hardcover
- New

Seller: Revaluation Books, Exeter, United KingdomRevaluation Books
AbeBooks seller since January 6, 2003
Condition: New
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300 pages. 9.21x6.14x9.21 inches. In Stock.
Seller Inventory # x-1837240906
- Title
- Energy Management Systems for Microgrids With Wind, Pv and Battery Storage
- Author
- Bossoufi, Badre (Editor)
- Publisher
- Inst of Engineering & Technology
- Publication year
- 2025
- Condition
- Brand New
- Binding
- Hardcover
- Language
- English
- ISBN 10
- 1837240906
- ISBN 13
- 9781837240906
- Item weight
- 0.75 kilograms
Growing shares of intermittent clean generation as well as variable loads lead to challenges for distribution systems at all levels. Energy management systems (EMS) are systems of computer-aided tools used by operators of electric utility grids to monitor, control, and optimize the performance of the generation, distribution or transmission system. EMS help to ensure grid stability and power quality, and can also be used in smaller scale systems such as microgrids.
Energy Management Systems for Microgrids with Wind, PV and Battery Storage gives a broad overview of EMS technologies for researchers, designers, operators at electric utilities involved with managing power systems, as well as advanced energy engineering students working on power systems.
Chapters cover AC network performance with flexible alternating current transmission system (FACTS) devices, metaheuristic optimization and hidden neuron count effect on microgrid management. Ensuing chapters will focus on microgrids with storage, with control of microgrids with renewables and storage, while several chapters look at wind energy in smart grids, battery charge in wind turbines, field-programmable gate array for wind turbines, fuzzy logic for wind energy, and classical Boolean methods for hybrid systems with wind, PV and batteries. Later chapters convey model predictive control and particle swarm optimization, and integration of and energy management for EV with support vector regression.
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About the Author
Badre Bossoufi (https://orcid.org/0009-0009-6506-8464) (Eng., Ph.D., IEEE Senior Member) received his Ph.D. in electrical engineering from the Faculty of Sciences at Sidi Mohamed Ben Abdellah University in Fez, and a joint Ph.D. from the Faculty of Electronics and Computer at the University of Piteşti, Romania, and the Montefiore Institute of Electrical Engineering in Liège, Belgium, in 2012. He was a professor of electrical engineering at the Faculty of Sciences Dhar El Mahraz at Sidi Mohamed Ben Abdellah University. His research interests include static converters, electrical motor drives, power electronics, smart grids, renewable energy, and artificial intelligence. He has published numerous papers in journals and conferences over the past few years, most of which relate to wind power control and microgrid systems. He has edited several books and served as a guest editor for various special issues and topical collections. He is a reviewer and is on the editorial boards of several journals. He has been associated with more than 20 international conferences as a program committee member, advisory board member, or review board member.
"About the title" may belong to another edition of this title.
Revaluation Books
Exeter, United Kingdom
AbeBooks seller since January 6, 2003
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