Thermal exchange optimization based control of a doubly fed induction generator in wind energy conversion systems

Abstract

This paper presents a novel design method to attain the optimal parameters of proportional integral (PI) controllers for a doubly fed induction generator (DFIG) in wind energy based on a thermal exchange optimization (TEO) algorithm. Since the gains of PI controllers are usually selected by classical and tedious trials-errors based procedures, their tuning for such a wind energy converter is formulated as a constrained nonlinear optimization problem. Inspired by Newton’s law of cooling, the TEO algorithm is successfully applied to solve such a control problem under time-domain performances and operational constraints in order to extract the maximum available power. In order to assess the performances of the proposed TEO algorithm, a comparative study between the TEO algorithm and homologues ones is performed. Moreover, a statistical analysis using Friedman and Bonferroni-Dunn’s tests indicates that the TEO lgorithm gives very competitive results in comparison to the other reported metaheuristic algorithms.