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Evaluation of Wind Energy Parameter Optimization of A DFIG Controller Based on Cultural Algorithms

In a wind energy conversion system (WECS), the characteristics are nonlinear and capturing maximum available power from the wind is a demanding task. The challenges in the WECS can be enhanced with optimal controller parameters of a doubly-fed induction generator (DFIG) to attain appreciable efficiency and improved dynamic response of the system. In this article, two research scenarios of wind dynamics based on the gust changes in the WECS with respect to voltage, current, power, rotor speed, and pitch angle have been analyzed. To explore the superiority of the proposed cultural algorithm-based controller optimization, its performance was compared with that of other well-established optimization techniques such as genetic algorithm and particle swarm optimization. The simulations were carried out in MATLAB software with appreciable system efficiency and improved dynamic response of the system. This proposed technique can also be extended for other complicated power system optimization problems.