LAUSR

Abstract In this paper, a nature-inspired optimization algorithm is employed for parametric tuning of proportional-integral controllers in the vector control of a grid-linked doubly-fed induction generator energy system. The optimization approach is based on the nature-inspired computing technique from the water cycle. The vector control system includes loops for dc-link voltage control at the grid side converter and the rotor current at the rotor side converter. The water cycle optimization is implemented to tune six control parameters by minimizing a cost function carried out using the tracking errors. The cost function value, required in the optimization process, is carried out from a simulated grid-linked doubly-fed induction generator energy system. The optimized control parameters are tested on an experimental setup. Experimental results, obtained for a grid-linked doubly-fed induction generator energy system in terms of different optimization methods and conditions, are provided to demonstrate the effectiveness of water cycle optimization technique. As a result of the comparative analysis, it is observed that water cycle technique offers better results in minimizing the overshoot and the response time.