Water cycle algorithm-tuned PI control of a doubly fed induction generator for wind energy conversion

Abstract

This paper presents one novel design procedure to attain the optimal parameters of Proportional-Integral (PI) controllers for a 1.5 MW Doubly Fed Induction Generator (DFIG) for wind turbine systems. Since the parameters of PI controllers are usually selected by classical and tedious trials-errors procedures, an optimization-based tuning problem has been formulated and successfully solved based on a proposed advanced meta-heuristics algorithm, called Water Cycle Algorithm (WCA). Inspired from the water cycle process and how rivers and streams flow towards the sea in the real world, the proposed WCA has been improved and adapted to solve such a hard optimization problem under time-domain criteria and nonlinear operational constraints. The obtained results from WCA are examined by a comparative study with other classical optimizers such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Harmony Search Algorithm (HSA). These results show the superiority and effectiveness of the proposed method in terms of solution qualities, exploration and exploitation capabilities and convergence fastness. Symmetrical voltage dip scenario is also further considered for all algorithms. Demonstrative results show the effectiveness of the proposed WCA-tuned PI control structures.