Application of Grey Wolf Optimization Algorithm for Improving Inertia Constant Selection in Wind Farm Deployments

This paper presents a Grey Wolf Optimization (GWO) algorithm for doubly fed induction generator (DFIG)-based wind turbine generators. In order to address the system operability challenges that have arisen as a result of the continuous reduction of system inertia caused by the increasing penetration of renewable power generation. The GWO algorithm that has been makes it possible for individual DFIG generators to contribute an efficient inertial response. This response helps to stabilize the rate at which the frequency is changing and minimizes the large frequency deviations, when disturbance occurs. The DC voltage of the DFIG runs at different levels in accordance with the changes in the inertia constant to facilitate energy exchange with the associated ac grid. Additionally, the standard control system for the DFIG has been updated to accommodate the implementation of the GWO algorithm. The proposed model utilized GWO in order to evaluate optimum values of inertia constant, that assists in improving output power efficiency levels. Concerning the DFIG, practical challenges such as maximizing active power while minimizing reactive power are examined, and pertinent solutions are offered for a variety of different cases