Experimental Investigation of efficiency enhancement in Solar Photovoltaic Systems under Partial Shading Conditions using Discrete Time Slime Mould Optimization

Abstract

The Solar PhotoVoltaic (SPV) systems are the trending and commercially reputable power source abundantly served by the nature to the mankind. Partial Shading Conditions (PSC) are one of the critical concepts in the SPV maximum power extraction. PSC’s are nonlinear and fuzzy in its attributes, as it is unpredictable. Hence, it has numerous Local Maximum Peak Power (LMPP) points. Although, a wide spread of Maximum Power Point Tracking (MPPT) algorithms are doing justice in locating the peak power points and stabilize the system, they are inadequate to locate the LMPP’s and the Global Maximum Peak Power (GMPP) point. This paper proposes a discrete time-based Slime Mould Optimization (SMO), providing an effective support to the buck converter based MPPT controller for SPV systems. The analysis and testament of buck converter in discrete domain alleviates the optimization in discrete samples, which accelerates the computation speed in locating the LMPP and GMPP. The proposed methodology is validated from the predominant parametric results like tracking time, power efficiency and the stability of the system under various PSC’s. The experimental implementations are performed in MATLAB simulations and experimented with dSPACE-MicroLabBox.