Multi‐Objective Fuzzy‐Optimization Control Strategy of Rotor Converter for Doubly‐Fed Induction Generators under Grid Voltage Unbalance

Abstract

Under unbalanced grid voltages, the output active power, reactive power, and current in the stator of a doubly fed induction generator (DFIG) exhibit harmonic frequency fluctuations and distortion. Conventional control strategies to eliminate these effects only focus on one control objective at a time. This paper proposes a genetic algorithm‐based multi‐objective coordinated control strategy to eliminate multiple undesired effects in DFIGs under unbalanced power supply conditions. In order to enhance its low‐voltage ride‐through (LVRT) capability and effectively reduce the impact of the grid current on the power grid, this strategy first introduces adjustment coefficients when calculating the directive current of the rotor, and constructs a unified analytic expression for multiple control objectives. Next, the multi‐objective optimization model is constructed using the minimization of the fluctuations in active and reactive powers as the control objective and the total harmonic distortion (THD) of the stator current as the constraint condition. Finally, the adjustment coefficients are optimized using the multi‐objective genetic algorithm. From the perspective of the overall requirements of generators under a voltage unbalance fault condition, the optimized adjustment coefficients aim to limit the THD of the stator current within an acceptable safety range while simultaneously minimizing the fluctuations in the active and reactive powers. The effectiveness and feasibility of the proposed control strategy are proven by both simulation and experimental results. © 2018 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.