A new robust, mutated and fast tracking LPSO method for solar PV maximum power point tracking under partial shaded conditions

Mounting demand for energy and accumulation of hazardous nuclear wastes has invited the world to reduce their addiction to conventional power generation. Having established its global potential to replace fossil fuels, solar PV is increasingly installed worldwide. Yet PV is ill-starred due to its non-linear characteristics and hence, PV systems employ Maximum Power Point (MPP) controllers. Even though enough research progress is kept at the forefront in the MPP research area, the necessity to improvise the existing methods becomes mandatory to improve the energy conversion efficiency. Hence, in this paper, a global maximum power point tracking (GMPPT) algorithm based on Leader Particle Swarm Optimization (LPSO) is proposed for PV system. Apart from the conventional PSO, exclusive mutations strategies are employed to obtain the global best leader that helps the algorithm to differentiate between local and global MPPs. The simulation results are validated under numerous test conditions in which partial shading conditions are analyzed over a wide extent and in validation, the results of LPSO method is compared with PSO and P&O methods as well. Interestingly LPSO method has an inherent exploration and exploitation quality that made it to produce hasty converge within 0.5s under any shade conditions. Acknowledging to the promise shown in simulation, the mutation based LPSO method has managed to excel even in hardware experimentation which in turn justifies its suitability for MPPT application.