The book covers recent developments in applications of fuzzy logic techniques in power system control, planning, operation and design including problems of incorporating human expert knowledge in modeling, simulation and optimization. It gives readers a complete picture of fuzzy sets implementation in power systems demonstrating benefits by presentation of practical application and case studies.
This book introduces power system engineers and managers, researchers, undergraduate and postgraduate students to fuzzy logic techniques by offering new solution for practical power system problems. It also aims at the fuzzy logic and computer societies presenting their members a new, attractive, field fuzzy logic application and computation.
Reihe
Sprache
Verlagsort
Zielgruppe
Für höhere Schule und Studium
Für Beruf und Forschung
Illustrationen
79
330 s/w Abbildungen, 79 s/w Tabellen
330 figures, 79 tables
Maße
Höhe: 23.5 cm
Breite: 15.5 cm
Gewicht
ISBN-13
978-3-7908-1044-8 (9783790810448)
Schweitzer Klassifikation
Introduction: Fuzzy Sets Theory: A New Wave in Power System Design and Calculation; Introduction to Fuzy Sets and Fuzzy Systems.- Fuzzy Control: Fuzzy Logic Stabilizing Control of Electric Power Systems; Fuzzy Logic Based Power System Stabilizer; Application of Fuzzy Logic Controllers to a Solar Power Plant.- Distribution System Planning: Application of Fuzzy Sets Theory to Distribution Systems Planning; Computer Intelligence in Long Range Expansion Planning.- Load Modelling and Forecasting: Fuzzy Logic Approach to Load Modelling and Forecasting; Fuzzy Load Modelling, Management and Forecasting; Fuzzy Modelling of Load Demand in the Residential Sector.- Fault Location: Using Fuzzy Sets to Fault Location in Distribution Networks; A Study for the Application of Fuzzy-Logic Techniques to Fault-Type Identification in Digital Relaying.- Reliability and Availability Calculation: Fuzzy Clustering Application in reliability Calculation; Reliability Calculation for Generating Systems Using a Fuzzy Concept; Fuzzy Approach to Deal with Uncertain Data in Spare Parts Management.
