Flux Linkage Profile Estimation of Switched Reluctance Generator for Wind Energy Conversion System

Generation of electrical energy from the abundantly available wind power is gaining increasing importance throughout the world in the field of renewable energy. The major machineries used in the Wind Energy Conversion System (WECS) are generator and turbine units. The efficiency of WECS greatly depends on the performance of the generator used. In recent years, Switched Reluctance Generator (SRG) is replacing conventional induction generators and permanent magnet synchronous generators in the field of wind energy generation system. The performance accuracy of switched reluctance generator significantly relies on the precision of its machine modeling. The three modeling parameters of SRG are its phase flux linkage, phase inductance and rotor position. This paper presents the fuzzy logic based flux linkage modeling technique for switched reluctance generator. The main objective of this work is to determine the suitable membership function for modeling the SRM. The various types of membership functions available in fuzzy logic such as Trapezoidal, Gbell, Gaussian, Psigmoid and Triangular functions are used to develop the SRM flux linkage model. The flux linkage profiles modeled from all these membership functions are compared. The results of these comparisons are analyzed and presented in detail. From the analysis of results, it has been proved that the triangular membership function has developed a good SRG model compared with the other models. The kind of non-linearity exhibited by SRG is well handled by triangular membership function. The developed SRG model is persuaded to act as a potential candidate in real time wind energy conversion system.