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

Abstract

This paper introduces a recent design method to acquire the best gains of proportional-integral (PI) regulators for a doubly-fed induction generator (DFIG) in wind energy based on a thermal exchange optimization (TEO) algorithm. Since the gains of PI regulators are generally tuned by traditional and tedious trials-errors based method, their adjusting for such a wind energy converter is built as a constrained nonlinear optimization issue. Inspired by Newton's law of cooling, the TEO method is successfully adopted to process such a control problem under time-domain performances and operational constraints in order to catch more quantity from the available power. In order to assess the power of the proposed TEO method, a comparative study between the TEO algorithm and homologues ones is performed. In addition, a statistical measurement via Friedman and Bonferroni-Dunn's tests indicates that the TEO method presents high meaningful results in comparison to the other reported metaheuristic methods.