Intelligent Automatic Generation Control  book cover
1st Edition

Intelligent Automatic Generation Control

ISBN 9781138076235
Published March 29, 2017 by CRC Press
308 Pages 139 B/W Illustrations

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Book Description

Automatic generation control (AGC) is one of the most important control problems in the design and operation of interconnected power systems. Its significance continues to grow as a result of several factors: the changing structure and increasing size, complexity, and functionality of power systems, the rapid emergence (and uncertainty) of renewable energy sources, developments in power generation/consumption technologies, and environmental constraints.

Delving into the fundamentals of power system AGC, Intelligent Automatic Generation Control explores ways to make the infrastructures of tomorrow smarter and more flexible. These frameworks must be able to handle complex multi-objective regulation optimization problems, and they must be highly diversified in terms of policies, control strategies, and wide distribution in demand and supply sources—all via an intelligent scheme. The core of such intelligent systems should be based on efficient, adaptable algorithms, advanced information technology, and fast communication devices to ensure that the AGC systems can maintain generation-load balance following serious disturbances.

This book addresses several new schemes using intelligent control techniques for simultaneous minimization of system frequency deviation and tie-line power changes, which is required for successful operation of interconnected power systems. It also concentrates on physical and engineering aspects and examines several developed control strategies using real-time simulations. This reference will prove useful for engineers and operators in power system planning and operation, as well as academic researchers and students in field of electrical engineering.

Table of Contents

Intelligent Power System Operation and Control: Japan Case Study

Application of Intelligent Methods to Power Systems

Application to Power System Planning

Application to Power System Control and Restoration

Future Implementations

Automatic Generation Control (AGC): Fundamentals and Concepts

AGC in a Modern Power System

Power System Frequency Control

Frequency Response Model and AGC Characteristics

A Three-Control Area Power System Example

Intelligent AGC: Past Achievements and New Perspectives

Fuzzy Logic AGC

Neuro-Fuzzy and Neural-Networks-Based AGC

Genetic-Algorithm-Based AGC

Multiagent-Based AGC

Combined and Other Intelligent Techniques in AGC

AGC in a Deregulated Environment

AGC and Renewable Energy Options

AGC and Microgrids

Scope for Future Work

AGC in Restructured Power Systems

Control Area in New Environment

AGC Configurations and Frameworks

AGC Markets

AGC Response and an Updated Model

Neural-Network-Based AGC Design

An Overview

ANN-Based Control Systems

Flexible Neural Network

Bilateral AGC Scheme and Modeling

FNN-Based AGC System

Application Examples

AGC Systems Concerning Renewable Energy Sources

An Updated AGC Frequency Response Model

Frequency Response Analysis

Simulation Study

Emergency Frequency Control and RESs

Key Issues and New Perspectives

AGC Design Using Multiagent Systems

Multiagent System (MAS): An Introduction

Multiagent Reinforcement-Learning-Based AGC

Using GA to Determine Actions and States

An Agent for β Estimation

Bayesian-Network-Based AGC Approach

Bayesian Networks: An Overview

AGC with Wind Farms

Proposed Intelligent Control Scheme

Implementation Methodology

Application Results

Fuzzy Logic and AGC Systems

Study Systems

Polar-Information-Based Fuzzy Logic AGC

PSO-Based Fuzzy Logic AGC

Frequency Regulation Using Energy Capacitor System

Fundamentals of the Proposed Control Scheme

Study System

Simulation Results

Evaluation of Frequency Regulation Performance

Application of Genetic Algorithm in AGC Synthesis

Genetic Algorithm: An Overview

Optimal Tuning of Conventional Controllers

Multiobjective GA

GA for Tracking Robust Performance Index

GA in Learning Process

Frequency Regulation in Isolated Systems with Dispersed Power Sources

Configuration of Multiagent-Based AGC System

Configuration of Laboratory System

Experimental Results

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H. Bevrani was born in Kurdistan, Iran. He received Ph.D. degree from Osaka University, Osaka, Japan, in 2004, in electrical engineering. From 2004 to 2006, he was a Postdoctoral Fellow at Kumamoto University, Kumamoto, Japan. From 2007 to 2008, he was a Senior Research Fellow at Queensland University of Technology, Brisbane, Australia. From 2000, he has been an academic member of University of Kurdistan. At time of writing this book, he was a professor in Kumamoto University. His special fields of interest include intelligent and robust control applications in Power system and Power electronic industry. Prof. Bevrani is a senior member of Institute of Electrical and Electronics Engineers (IEEE), member of the Institute of Electrical Engineers of Japan (IEEJ) and the Institution of Engineering and Technology (IET).

T. Hiyama was born in Japan on March 14, 1947. He received the B.E., M.S., and Ph.D. degrees all in electrical engineering from Kyoto University, Kyoto, Japan, in 1969, 1971, and 1980, respectively. Since 1989, he has been a Professor in the Department of the Electrical and Computer Engineering, Kumamoto University, Kumamoto, Japan. His current research interests include the application of intelligent systems to power system operation, management, and control. Prof. Hiyama is a senior member of Institute of Electrical and Electronics Engineers (IEEE), a member of the Institute of Electrical Engineers of Japan (IEEJ) and the Japan Solar Energy Society.


"I enjoyed reading the book and found it informative. It is certainly a book I would recommend to postgraduate students and researchers in the area of intelligent control systems and their application to power system control. My congratulations to the authors."
—Pouyan Pourbeik, IEEE Power and Energy Magazine