Name: Neural Control of Renewable Electrical Power Systems (en Inglés)
Price: 185220.00 CLP
Availability: InStock
Author: Sánchez, Edgar N. ; Djilali, Larbi
ISBN: 9783030474423

portada Neural Control of Renewable Electrical Power Systems (en Inglés)

Formato

Libro Físico

Autor

Edgar N. Sánchez

Larbi Djilali

Editorial

Springer

Idioma

Inglés

N° páginas

206

Encuadernación

Tapa Dura

Dimensiones

23.4 x 15.6 x 1.4 cm

Peso

0.50 kg.

ISBN13

9783030474423

Categorías

Ingeniería: general
Tecnología y fuentes de energía alternativa y renovable
Ingeniería de control automático

Neural Control of Renewable Electrical Power Systems (en Inglés)

Edgar N. Sánchez (Autor) · Larbi Djilali (Autor) · Springer · Tapa Dura

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Origen: Estados Unidos (Costos de importación incluídos en el precio)

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Reseña del libro "Neural Control of Renewable Electrical Power Systems (en Inglés)"

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.