Design and performance evaluation of a fuzzy-logic-based variable-speed wind generation system

Artificial intelligence techniques, such as fuzzy logic, neural networks and genetic algorithms, have recently shown promise in the application of power electronic systems. The paper describes the control strategy development, design and experimental performance evaluation of a fuzzy logic-based variable-speed wind generation system that uses a cage-type induction generator and double-sided PWM power converters. The system can feed a utility grid maintaining unity power factor at all conditions or can supply an autonomous load. The fuzzy logic-based control of the system helps to optimize efficiency and enhance performance. A complete 3.5 kW generation system has been developed, designed and thoroughly evaluated by laboratory tests in order to validate the predicted performance improvements. The system gives excellent performance and can easily be translated to a larger size in the field