PERFORMANCE ANALYSIS OF SELF-EXCITED INDUCTION GENERATOR USING ARTIFICIAL NEURAL NETWORK

Abstract

Self-excited induction machines seem to be the most suitable generators for wind energy conversion in remote and windy areas. Steady state analysis for such machines is essential to estimate the behavior under actual operating conditions. This paper presents a new technique for the steady-state analysis of a three-phase self-excited induction generator feeding balanced unity power factor load. Iterative technique has been used to find the generated frequency and Artificial Neural Network (ANN) has been applied to capture the nonlinear magnetization characteristics of induction machine in place of piecewise linear approximation as used by other research persons. The results have been compared with experimental results. The comparison confirms the validity and accuracy of the ANN based modeling of induction generator.