Improved krill herd algorithm based sliding mode MPPT controller for variable step size P&O method in PV system under simultaneous change of irradiance and temperature

摘要

In recent years, Photovoltaic (PV) systems have been received great attention all over the words as they are sustainable, unlimited and environmentally friendly energy. However, it is required for the PV system to apply a tracking controller to guarantee efficient operation by extracting the maximum power, which named maximum power point tracking (MPPT) method. Due to the simple structure, the conventional perturb and observe (P&O) MPPT algorithm is very popular in the literature. Nevertheless, conventional methods show inaccurate performance, particularly when high variations occur in irradiance, resulting in fluctuations around the MPP. To deal with these challenges, a novel technique on the basis of the variable-step size of P&O MPPT and sliding mode controller (SMC) adjusted by the theta-modified krill herd (theta-MKH) algorithm is presented. The theta-MKH algorithm is utilized to fine-tune the optimal SMC parameters to drive the variable step of the classical P&O algorithm. Simulations are prepared to compare the performance of the suggested scheme with conventional methods by considering simultaneous fast changes of irradiance and temperature. The results show that the suggested scheme have proper performance in both transient and steady-state, particularly under quickly varying climate circumstances. (C) 2021 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.