A Research Study and Comparative Analysis of MPPT Controllers for PV Cells with Algorithmatic Structures

Due to continues increase in usage of various sources of Energies, Solar energy becomes very popular source of renewable energy due to its several advantages. Systems such as Photovoltaic (PV) power systems have been widely used in many applications of generation and utilization of energy in many countries. But also, there are many urgent problems to cop up with the applications of PV Cells for the purpose of Power Generation and in the power systems such as low efficiency, high cost etc. The main Concentration is to how to improve efficiency. Since generally Photovoltaic (PV) arrays exhibit a nonlinear power–voltage (P–V) characteristic curve which have a variation with isolation and temperature. To achieve good efficiency, Maximum Power Point Tracking (MPPT) is a very important technology. There are various conventional MPPT schemes have been proposed and working on including Hill-Climbing (HC) , Perturb and Observe (P&O) , and Incremental Conductance (INC) etc. In this research work, the optimization methods for efficient tracking such as PSO and GSA are explored. The very essential and considered issue of this type of control (MPPT) is to how to achieve the best optimized status and this can be achieved by using evolutionary algorithms. PSO algorithm owns the characteristics methods like parallel processing, good robustness, and high probability of finding global optimal solution. By adding GSA with PSO ,it can be improved. Advantage of adding proposed GSAPSO algorithm greatly shortens the searching time, helpful in reducing the fluctuation of output waveform and thus improves the optimization and efficiency through particles dormancy and activation control, optimal number of particles algorithm and search sequence selection. It achieves a smooth starting for maximum power and achieves it in less time than the widely used other methods.