Amal M. Abd El- Hameid, Adel A. Elbaset, Mohamed Ebeed

Enhancement of Grid-Connected Photovoltaic Systems Using Artificial Intelligence

• Gebundenes Buch

Produktbeschreibung

Enhancement of Grid-Connected Photovoltaic Systems Using Artificial Intelligence presents methods for monitoring transmission systems and enhancing distribution system performance using modern optimization techniques considering different multi-objective functions such as voltage loss sensitivity indexes, reducing total annual cost, and voltage deviation. The authors offer a comprehensive survey of distributed energy resources (DERs), explain the backward/forward sweep (BFS) power flow algorithm, and present simulation results on the optimal integration of photovoltaic-based distributed generators (PV-DG) and distribution static synchronous compensators (DSTATCOM) in different transmission and distribution systems. This book will be a valuable academic and industry resource for electrical engineers, students, and researchers working on optimization techniques, photovoltaic systems, energy engineering, and artificial intelligence.

Produktdetails

• Verlag: Springer / Springer Nature Switzerland / Springer, Berlin
• Artikelnr. des Verlages: 978-3-031-29691-8
• 2023
• Seitenzahl: 252
• Erscheinungstermin: 12. Mai 2023
• Englisch
• Abmessung: 241mm x 160mm x 20mm
• Gewicht: 547g
• ISBN-13: 9783031296918
• ISBN-10: 3031296915
• Artikelnr.: 67508370

Autorenporträt

Amal Mohamed Abd El-Hameid, Ph.D., received her B.Sc. and M.Sc. degrees from the Electrical Engineering Department at Sohag University, Egypt, in 2012 and 2016, respectively. She is currently pursuing a Ph.D. Since May 2016, she has worked as an Assistant Lecturer in the Electrical Engineering Department for the Faculty of Industrial Education at Sohag University. Her research interests include renewable energy, power quality, photovoltaics, and optimization techniques. Adel A Elbaset, Ph.D., is a Full Professor with the Faculty of Engineering at Minia University, Egypt. He received his B.S., M.Sc., and Ph.D. from University in 1995, 2000, and 2006, respectively. Dr. Elbaset is a Full Professor with the Faculty of Engineering at Heliopolis University, where he is also Vice-Dean for Student Affairs and Head of the Department of Electromechanics. He has published over 120 technical papers in international journals and conferences and has supervised and examined more than 50 M.Sc. and Ph.D. theses at Minia and other Egyptian universities. His research interests are wind energy systems, photovoltaics, renewable energy systems, power electronics, power system protection and control, power quality and harmonics, and applications of neural networks and fuzzy systems. He has published 14 international books in the field of renewable energy. Mohamed Ebeed Hussein, Ph.D., received a B.S. from Aswan University in 2005 and an M.Sc. in electrical engineering from South Valley University in 2013. He received the jointly-supervised Ph.D. From the Department of Electrical Engineering, Faculty of Engineering, Aswan University, and University of Jaen, Spain, in 2018. Currently, he is a Lecturer in the Department of Electrical Engineering, Faculty of Engineering at Sohag University, Egypt. From 2008 to 2009, he was a lecturer at the Aswan Technical Institute. From 2009 to 2017, he was a maintenance engineer with EFACO Company.  Montaser Abd El Sattar Mohammed, Ph.D., received a B.Sc. from the Faculty of Engineering, Department of Electrical Engineering at Al-Azhar University, Egypt, in 2006 and an M.Sc., and Ph.D. from the Department of Electrical Engineering, Faculty of Engineering at Minia University, Egypt, in 2011 and 2015, respectively. Dr, Mohammed has been working as a Lecturer at the El-Minia High Institute of Engineering and Technology, El-Minia, Egypt, since 2015. His research interests are renewable energy sources, power electronics, power quality, and harmonics.

Inhaltsangabe

Introduction.- Power Quality Issues.- Stochastic Optimal Planning of Distribution System Considering Integrated Photovoltaic-Based DG and D-STATCOM.- Optimal Allocation of Distributed Energy Resources Using Modern Optimization Techniques.- Results and Discussion.- Conclusions and Future Work.