Robust MPPT And DFIG-Based Control Of GridConnected Wind Energy Systems Using Multi-Objective Genetic Algorithm Optimization

Wind energy systems have seen the increasing numbers of installation around the world following the growing demand of green renewable energy market. This paper introduces a novel control scheme for grid-connected WECS based on Doubly-Fed Induction Generator (DFIG) integrating Robust MPPT strategy reinforced by MOGA. The purpose of the proposed approach is to tackle the problems of fluctuating wind speed, grid disturbances, and nonlinear dynamic characteristics of the system by optimal power extraction and fulfilling the grid code requirements. The control scheme consists of two main elements, a robust MPPT control algorithm able to track real time wind profile and vector control DF conversion to control RSC and GSC of DFIG separately. For better dynamic performance, less steady state error and stability under wide range of operating conditions the control parameters are optimized by a Multi Objective Genetic Algorithm (MOGA) approach. It also takes several performance objectives including tracking accuracy, voltage stability, Total Harmonic Distortion (THD), and reactive power support into account simultaneously. Simulation is performed using MATLAB/Simulink in diverse cases such as wind gusts, grid faults and load variations. Results indicate that the designed system exhibits better performance than conventional PI, and single-tuned controllers in terms of an MPPT efficiency of more than 98%, THD, and PFC. Parameter uncertainties also have little impact on the system and the performance of the proposed controller under the cases of grid disturbances demonstrate its robustness and adaptability. This study highlights the applicability of MOGA-tuned robust control for contemporary WECS and paves the way for real-time practical application in smart grid scenarios. This approach provides a scalable and smart solution that is entirely consistent with the worldwide direction headed for clean and robust renewable energy systems.