Genetic Algorithm Based Performance Analysis of 3-phase Self Excited Induction Generator

Abstract — This paper analyzes the steady state performance of an isolated 3-phase self excited induction generator (SEIG) feeding balanced resistive load. The effects of load admittance and excitation capacitance on magnetizing reactance, frequency, terminal voltage, currents have been shown in this paper. The equivalent circuit of SEIG has been analyzed by loop impedance method to develop circuit equation which is non-linear in nature. This can be easily solved by genetic algorithm (GA) optimization technique. The simulated results obtained using genetic algorithm help in understanding the steady state performance of SEIG. Keywords—equivalent circuit, GA, magnetizing reactance, SEIG and steady state performance. List of Symbols R1 = Stator resistance per phase R2 = Rotor resistance per phase RL = Load resistance per phase X1 = Stator leakage reactance per phase X2 = Rotor leakage reactance per phase XL = Load reactance per phase Xm = Magnetizing reactance per phase Xc = Shunt excitation capacitive reactance per phase C = Shunt excitation capacitance per phase a = per unit generated frequency b = per unit speed YL = Load admittance per phase ZL = Load impedance per phase Eg = Generated air gap voltage per phase VL = Load voltage per phase IL = Load current per phase IS = Stator current per phase IR = Rotor current per phase I