Robust variable step P&O algorithm based MPPT for PMSG wind generation system using estimated wind speed compensation technique

Abstract

To expedite the cost recovery of the wind energy conversion system (WECS), maximizing power availability at all times is of utmost importance. Therefore, the primary objective of Maximum Power Point Tracking (MPPT) algorithms is to optimize power output by ensuring the achievement of maximum power under varying wind speeds. The perturbation and observation algorithm are widely recognized as the most well-known technique used in wind energy conversion systems (WECS) due to its versatility. Although this algorithm is valued for its simplicity and cost-effectiveness, it does have a significant drawback. Peculiarly, it is insensitive to fluctuations in instantaneous wind speed conditions and lacks accurate step size estimation. To address these limitations, a novel approach called the Robust Variable Step P&O (RVS-P&O) technique has been proposed. The RVS-P&O technique aims to overcome the aforementioned drawbacks. The control strategy employed by the proposed RVS-P&O-MPPT algorithm is based on three fundamental concepts: a new normalization of the selection of the step size, a novel correction procedure to estimate the power variation and wind speed estimation (WSE) algorithm based on the artificial neural network (ANN) controller. Simulations have been carried out by means of MATLAB/Simulink environment. The findings indicate the superiority of the proposed RVS-P&O algorithm compared to several P&O implementations: fixed Large Step (LS), fixed Small Step (SS), Variable Step (VS) and Modified (M)-P&O. The developed algorithm allows reaching 99.79% of wind energy conversion system (WECS) efficiency. This allows obtaining an enhancement of 2.19% in comparison to VS-P&O technique which is the most competing algorithm. Further, the response speed is clearly improved compared to the various P&O versions, as the settling time (sec) is of 0.0074 while that of VS and M−P&O is of 0.0157 and 0.0079, respectively. Indeed, to enhance the quality of the injected power into the grid, a Second Order Sliding Mode Controller (SOSMC) based Super Twisting Algorithm (STA) is proposed. The results show the suggested technique outperforms the PI and First Order (FO)-SMC for current THD minimization by attenuating the odd harmonics without chattering phenomenon.