Authors:
- Presents recent research on neural control of renewable electrical power systems
- Describes robust control schemes based on neural network identification
- Intended for researchers and students with a control background wishing to expand their knowledge of wind power generation and distributed energy resources installed into a grid-connected microgrid
Part of the book series: Studies in Systems, Decision and Control (SSDC, volume 278)
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Table of contents (7 chapters)
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Front Matter
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Back Matter
About this book
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 abnormalgrid 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.
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Authors and Affiliations
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Centro de Investigación y de Estudios Avanzados, del Instituto Politécnico Nacional (Cinvestav), Zapopan, Mexico
Edgar N. Sánchez, Larbi Djilali
Bibliographic Information
Book Title: Neural Control of Renewable Electrical Power Systems
Authors: Edgar N. Sánchez, Larbi Djilali
Series Title: Studies in Systems, Decision and Control
DOI: https://doi.org/10.1007/978-3-030-47443-0
Publisher: Springer Cham
eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2020
Hardcover ISBN: 978-3-030-47442-3Published: 10 May 2020
Softcover ISBN: 978-3-030-47445-4Published: 11 May 2021
eBook ISBN: 978-3-030-47443-0Published: 09 May 2020
Series ISSN: 2198-4182
Series E-ISSN: 2198-4190
Edition Number: 1
Number of Pages: XXV, 206
Number of Illustrations: 10 b/w illustrations, 208 illustrations in colour
Topics: Control and Systems Theory, Renewable and Green Energy, Computational Intelligence