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Neural Control of Renewable Electrical Power Systems

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Neural Control of Renewable Electrical Power Systems/ by Edgar N. Sánchez, Larbi Djilali.
作者:	Sánchez, Edgar N.
其他作者:	Djilali, Larbi.
面頁冊數:	XXV, 206 p. 218 illus., 208 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Computational Intelligence. -
電子資源:	https://doi.org/10.1007/978-3-030-47443-0
ISBN:	9783030474430

Neural Control of Renewable Electrical Power Systems
Sánchez, Edgar N.

Neural Control of Renewable Electrical Power Systems[electronic resource] /by Edgar N. Sánchez, Larbi Djilali. - 1st ed. 2020. - XXV, 206 p. 218 illus., 208 illus. in color.online resource. - Studies in Systems, Decision and Control,2782198-4182 ;. - Studies in Systems, Decision and Control,27.

Introduction -- Mathematical Preliminaries -- Wind System Modeling -- Neural Control Synthesis -- Experimental Results -- Microgrid Control -- Conclusions and Future Work.

This book presents advanced control techniques that use neural networks to deal with grid disturbances in the context renewable energy sources, and to enhance low-voltage ride-through capacity, which is a vital in terms of ensuring that the integration of distributed energy resources into the electrical power network. It presents modern control algorithms based on neural identification for different renewable energy sources, such as wind power, which uses doubly-fed induction generators, solar power, and battery banks for storage. It then discusses the use of the proposed controllers to track doubly-fed induction generator dynamics references: DC voltage, grid power factor, and stator active and reactive power, and the use of simulations to validate their performance. Further, it addresses methods of testing low-voltage ride-through capacity enhancement in the presence of grid disturbances, as well as the experimental validation of the controllers under both normal and abnormal grid conditions. The book then describes how the proposed control schemes are extended to control a grid-connected microgrid, and the use of an IEEE 9-bus system to evaluate their performance and response in the presence of grid disturbances. Lastly, it examines the real-time simulation of the entire system under normal and abnormal conditions using an Opal-RT simulator.

ISBN: 9783030474430

Standard No.: 10.1007/978-3-030-47443-0doiSubjects--Topical Terms:

768837
Computational Intelligence.

LC Class. No.: TJ212-225

Dewey Class. No.: 629.8

Neural Control of Renewable Electrical Power Systems
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