The new edition of this reference on fuzzy logic for energy systems offers a review of fuzzy logic, and examples in Matlab-Simulink. The new edition covers new topics like shading in PV, and day-ahead estimation of sun and wind data.
Fuzzy models have the capability of recognising, representing, and working with data that is vague or lacks certainty, making them suitable for managing electrical energy systems involving intermittent distributed generation and varying distributed loads.
The second edition of Fuzzy Logic Control in Energy Systems has been revised and updated with new topics including shade and integration issues in PV, microgrids, cybersecurity in power systems, and day-ahead estimation of sun and wind data. Starting with a review of fuzzy logic, chapters cover fuzzy sets and partitioning, fuzzy decision making, fuzzy logic controllers (FLC), and system modelling and control. The application of FLC in power systems, wind energy, PV energy systems and microgrids is then explored.
Several examples of fuzzy logic control and management are discussed including DC motor control, multi area load-frequency control, and wind and PV energy management. The book presents a fuzzy logic controller design in Matlab-Simulink enabling the reader to study every step and to develop their own fuzzy processor library and toolbox.
Providing thorough and logical coverage of fuzzy logic control and its use in energy systems, this book provides valuable insights for researchers and practicing engineers involved with power system design and control, grid operators, PV and wind turbine manufacturers, as well as advanced students in EE.
