Synopses & Reviews
Synopsis
This book is about fuzzy logic control and its applications in managing, controlling and operating electrical energy systems. It aims to convey an understanding of design approaches to fuzzy logic controllers in MATLAB(R) and MATLAB/Simulink(R) environments, and includes a basic theory of fuzzy sets and fuzzy logic required for designing fuzzy logic controllers.
It discusses the following examples of fuzzy logic control and management: DC motor speed and torque control; excitation and load-frequency control in power systems; multi-area load-frequency control in power systems; wind energy control systems (WECS); photovoltaic (PV) solar energy control systems; maximum power point tracking in PV systems; energy management in WECS; energy management in PV systems. It also includes a novel fuzzy logic controller design approach, in both MATLAB(R) and in MATLAB/Simulink(R), so that users can study every step of the fuzzy logic processor, with the ability to modify the code in MATLAB(R).m files and in Simulink(R)'s operational blocks.
Fuzzy Logic Control in Energy Systems will enable readers to develop their own fuzzy processor library and fuzzy logic toolbox for the particular problems they study. This is an essential text for researchers and practicing engineers working in power engineering, particularly in control and the design of controllers, and advance students in the topic.
Synopsis
Modern electrical power systems are facing complex challenges, arising from distributed generation and intermittent renewable energy. Fuzzy logic is one approach to meeting this challenge and providing reliability and power quality. The book is about fuzzy logic control and its applications in managing, controlling and operating electrical energy systems. It provides a comprehensive overview of fuzzy logic concepts and techniques required for designing fuzzy logic controllers, and then discusses several applications to control and management in energy systems. The book incorporates a novel fuzzy logic controller design approach in both Matlab and in Matlab Simulink so that the user can study every step of the fuzzy logic processor, with the ability to modify the code.