A cuckoo search algorithm optimizer for steady-state analysis of self-excited induction generator

Abstract

© 2017 Ain Shams University. Renewable energy systems especially the wind energy grows worldwide continuously. Also, installations of the wind farms increase in remote area applications. The self-excited induction generator (SEIG) is an effective choice for using in these applications due to its merits. This paper presents a cuckoo search algorithm (CSA) optimizer for steady state analysis of the SEIG. The mathematical model of the SEIG is based on equivalent circuit loop impedance method. The target of optimization is to minimize the total equivalent circuit impedance of the generator in order to obtain the frequency and any other unknown parameter of the SEIG. In this study, the frequency and magnetizing reactance define the search space for the optimization problem. The MATLAB CSA optimization toolbox is used to solve optimization problem. The effectiveness of the proposed optimizer is evaluated on a 220. V, 0.75. kW induction generator for various operating conditions. The effectiveness of the CSA model is then compared with other conventional optimization models. The validity of the proposed optimizer is verified by experimental results. With this proposed CSA optimization technique, a faster and an accurate prediction for steady state analysis of the SEIG are achieved.