Optimal Control of PV System to Extract Maximum Power under Non-Uniform Environmental Conditions

In Photovoltaic modules various power point tracking methods are used to obtain maximum power under changing weather conditions. In case of uniform irradiance conventional MPPT techniques give good results. However, under partial shading conditions tracking process become complex due to multiple power peaks on Power-Voltage curve of Photovoltaic array. Due to presence of multiple peaks conventional MPPT methods may fail to track global maxima. Therefore, a novel MPPT method named sine-cosine chimp optimization algorithm (SChoA) is used in this paper to track optimal power point. Effectiveness of algorithm is verified by building MPPT model of PV system in MATLAB. Simulation results show that SChoA gives better efficiency, less tracking time and negligible oscillations around global maxima. In order to further validate effectiveness of results, SChoA is compared with particle swarm optimization and sine-cosine optimization. Afterward a low-cost microcontroller-based hardware setup is developed to test performance of SChoA. Results clearly demonstrate that SChoA gives better power output, less settling time and little or no oscillations.