Advertisement

© 2020

Neural Control of Renewable Electrical Power Systems

Book
  • 2.1k Downloads

Part of the Studies in Systems, Decision and Control book series (SSDC, volume 278)

Table of contents

  1. Front Matter
    Pages i-xxv
  2. Edgar N. Sánchez, Larbi Djilali
    Pages 1-7
  3. Edgar N. Sánchez, Larbi Djilali
    Pages 9-21
  4. Edgar N. Sánchez, Larbi Djilali
    Pages 23-40
  5. Edgar N. Sánchez, Larbi Djilali
    Pages 41-108
  6. Edgar N. Sánchez, Larbi Djilali
    Pages 109-153
  7. Edgar N. Sánchez, Larbi Djilali
    Pages 155-183
  8. Edgar N. Sánchez, Larbi Djilali
    Pages 185-187
  9. Back Matter
    Pages 189-206

About this book

Introduction

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.

Keywords

Renewable Electrical Power Systems Neural Control Wind System Modeling Neural Control Synthesis Microgrid Control

Authors and affiliations

  1. 1.Centro de Investigación y de Estudios Avanzadosdel Instituto Politécnico Nacional (Cinvestav)ZapopanMexico
  2. 2.Centro de Investigación y de Estudios Avanzadosdel Instituto Politécnico Nacional (Cinvestav)ZapopanMexico

Bibliographic information

Industry Sectors
Automotive
Chemical Manufacturing
Biotechnology
Electronics
IT & Software
Telecommunications
Aerospace
Pharma
Materials & Steel
Oil, Gas & Geosciences
Engineering