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Enhancement of grid-connected photovoltaic systems using artificial intelligence

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Enhancement of grid-connected photovoltaic systems using artificial intelligenceby Amal M. Abd El- Hameid ... [et al.].
其他作者:	El-Hameid, Amal M. Abd.
出版者:	Cham :Springer Nature Switzerland :2023.
面頁冊數:	1 online resource (xxiii, 226 p.) :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Photovoltaic power generation.
電子資源:	https://doi.org/10.1007/978-3-031-29692-5
ISBN:	9783031296925$q(electronic bk.)

Enhancement of grid-connected photovoltaic systems using artificial intelligence
Enhancement of grid-connected photovoltaic systems using artificial intelligence[electronic resource] /by Amal M. Abd El- Hameid ... [et al.]. - Cham :Springer Nature Switzerland :2023. - 1 online resource (xxiii, 226 p.) :ill., digital ;24 cm.

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.

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.

ISBN: 9783031296925$q(electronic bk.)

Standard No.: 10.1007/978-3-031-29692-5doiSubjects--Topical Terms:

184746
Photovoltaic power generation.

LC Class. No.: TK1087

Dewey Class. No.: 621.31244

Enhancement of grid-connected photovoltaic systems using artificial intelligence
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505 0 $a 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.
520 $a 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.
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