Enhancement of grid-connected photovoltaic systems using artificial intelligence / Amal M. Abd El- Hameid, Adel A. Elbaset, Mohamed Ebeed, Montaser Abdelsattar.

Unlimited

Authorized users

Can lend chapters, not whole ebooks

Enhancement of grid-connected photovoltaic systems using artificial intelligence / Amal M. Abd El- Hameid, Adel A. Elbaset, Mohamed Ebeed, Montaser Abdelsattar.

9783031296925 (electronic bk.)
3031296923 (electronic bk.)
9783031296918 (print)
3031296915

Cham : Springer, 2023.

English

1 online resource (xxiii, 226 pages) : illustrations

10.1007/978-3-031-29692-5 doi

TK1087

621.31/244

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. Covers developments to enhance the integration of renewable energy sources; Presents simulation results, including standard IEEE bus test systems; Includes MATLAB M-file codes.

Includes bibliographical references and index.

Access limited to authorized users.

Online resource; title from PDF title page (SpringerLink, viewed May 19, 2023).

Print version: 9783031296918

Online Resources > Ebooks
All Resources