RESUMEN
Photovoltaic (PV)-based power generation systems are becoming increasingly popular as a due to its high performance and cleanliness. Several factors influence the performance of a PV system, including shadowing effects. PV systems employ MPPT methodologies to obtain the power from PV array. Conventional MPPTs works well under normal conditions when there is no shadow effects or partial shading. The presence of partial shading affects the system performance and generates several power peaks. This complicates the process of finding out of the global peak (GMPP) with improved tracking efficiency and reduced settling time including conversion efficiency. This work proposes three hybrid MPPT techniques: Water Cycle Optimisation-Perturb and Observe (WCO-PO), Artificial Neural Network Supported Adaptable Stepped-Scaled Perturb and Observe (ANN-ASSPO), Grey Wolf Optimisation-Modified Fast Terminal Sliding Mode Controller (GWO-MFTSMC), and two conventional MPPT techniques WCO and P&O have been implemented. The proposed system utilizes interleaved boost converter with three phase. The performances of proposed hybrid MPPTs strategies were compared in terms of output voltage, output current and extracted power. The comparison also includes conversion efficiency and average settling time. To analyse the performances, four different cases have been used to test the efficacy of hybrid MPPTs under changing climatic conditions. The MATLAB/Simulink tool has been used to analyze the PV system performances. In the three hybrid MPPT techniques, WCO-PO has performed better when compared to other two hybrid MPPTs in terms of conversion efficiency (99.56%) and settling time (1.4 m).
