1st Edition

Intelligent Automatic Generation Control

By Hassan Bevrani, Takashi Hiyama Copyright 2011
    308 Pages 139 B/W Illustrations
    by CRC Press

    308 Pages 139 B/W Illustrations
    by CRC Press

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    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.

    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


    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