No abstract

A fast-growing population, rising number of smart cities, and exponential usage of electronic gadgets have all contributed to a growing demand for electricity, possibly causing menacingly high levels of carbon emissions and atmospheric pollution in India. These energy sources do not release any greenhouse gases into the atmosphere. India as a sunshine country is an ideal place for harnessing solar energy which will help us to overcome pollution problems. Nowadays photovoltaic systems are popular due to their various advantages like sustainability, less maintenance, no complex part, possesses longer life, and many more. Solar photovoltaic systems have become the most ideal option for conventional energy sources that can develop energy sustainably. The power-voltage characteristics of a PV panel are non-linear and depend on the irradiance of sunlight and the atmosphere's temperature. The performance of a PV power plant mainly depends on various factors: the conversion efficiency of the PV system, the efficiency of the power electronics converter, and the maximum power extraction algorithm. Various tracking methods have been proposed in the literature to obtain maximum power from PV systems. Conventional methods like perturb and observe (P&O), incremental conductance method and improved perturb and observe method, etc. have advantages and disadvantages in terms of precision, speed, and power loss under changing weather conditions. In this regard, the utilization of optimization algorithms to track the MPP of PV panels under changing environmental conditions. This has motivated the present study to use the search-based Particle swarm optimization (PSO) technique for solar photovoltaic systems to extract maximum output under non-uniform weather conditions.