GeneticAlgorithm based Analysis of Six-phase Self-excited Induction Generators for Wind Energy Conversion

This paper presents the application of genetic algorithm for the analysis of six-phase self-excited induction generators (SPSEIG) by means of series compensation. A new, simple and generalized mathematical model for the steady-state analysis of SPSEIG with series compensation is proposed. The mathematical model is formed directly from the equivalent circuit of SPSEIG using nodal admittance method based on inspection. The proposed model completely avoids lengthy derivations of nonlinear equations which are followed so far. Since the model results in matrix form, inclusion or elimination of any equivalent circuit elements can be carried out easily. Moreover, this model can be used to find any combination of unknown quantities of the equivalent circuit. The matrix equation is solved by Genetic Algorithm (GA) to predict the steady-state performance of SPSEIG with three capacitor excitation configuration such as simple shunt, short shunt and long shunt. Comparative performance evaluation of SPSEIG with simple shunt, short shunt and long shunt configurations is also presented. Computed results are experimentally verified to validate the analytical approach presented in the paper.