A performance analysis of a hybrid golden section search methodology and a nature-inspired algorithm for MPPT in a solar PV system

Abstract

This research presents a comparative study for maximum power point tracking (MPPT) methodologies for a photovoltaic (PV) system. A novel hybrid algorithm golden section search assisted perturb and observe (GSS-PO) is proposed to solve the problems of the conventional PO (CPO). The aim of this new methodology is to boost the efficiency of the CPO. The new algorithm has a very low convergence time and a very high efficiency. GSS-PO is compared with the intelligent nature-inspired multi-verse optimization (MVO) algorithm by a simulation validation. The simulation study reveals that the novel GSS-PO outperforms MVO under uniform irradiance conditions and under a sudden change in irradiance.

Keywords

• hybrid optimization
• golden sections search
• multi-verse optimization algo-rithm
• maximum power point tracking
• perturb and observe
• photovoltaic (pv)