Boltzmann’s Constant

Abstract

This paper proposes a new Hybrid MPPT algorithm combining Grey Wolf Optimization (GWO) and Perturb & Observe (P&O) technique for efficient extraction of maximum power from a Photovoltaic (PV) system subjected to rapid variation of solar irradiance and partial shading conditions (PSCs). GWO handles the initial stages of maximum power point (MPP) tracking followed by application of the P&O algorithm at the final stage in view of achieving faster convergence to the global peak (GP). This MPPT thus overcomes the computational overhead as encountered in the case of a GWO based MPPT algorithm reported earlier [15]. The idea behind using the hybrid technique is to scale down the search space of GWO which helps to speed up for achieving convergence towards the GP. The proposed MPPT algorithm is first implemented using MATLAB/SIMULINK and subsequently an experimental setup is prepared for its practical implementation. From the obtained results, it is confirmed that the proposed MPPT provides superior tracking performance in any weather conditions compared to both GWO and PSO+PO based MPPT algorithms. Index Terms-Grey Wolf Optimization (GWO), Maximum Power Point (MPP), Perturb and Observe (P&O), Partial Shading Conditions (PSCs). NOMENCLATURE , pv II photovoltaic and output current 0 0, , n II saturation and nominal saturation current t V thermal voltage D diode connected in parallel with current source a diode ideality constant s R resistances which comes in path of current p R shunt resistance 0 , GG irradiance and nominal irradiance 0 g I current at 0 G 0 J temperature coefficient of pv I , ref TT actual and nominal temperature of the cell V output voltage q charge of electron g E bandgap energy