A new meerkat optimization algorithm based maximum power point tracking for partially shaded photovoltaic system

Abstract

The output power of solar photovoltaic (PV) system is intermittent in nature with a non-linear output voltage. This has peak power points in accordance with varying irradiation and temperature. Hence a Maximum Power Point Tracker (MPPT), which is power extraction technique is essential in PV power systems to ensure maximum power delivery for a given point of time. Thenonlinear power voltage curve gets more intense when shading of PV panels takes place, as the panels receive irregular and different solar irradiation, which alters the profile of power –voltage (P-V) curves. Due to the partial shading, the panels exhibit peculiar multiple power peaks instead of one single peak as in the case of uniform irradiation and as a result the conventional MPPT schemes could attain only local maxima and the global one. This research article proposes a new intelligent, bio inspired Meerkat optimization algorithm (MOA) which is capabale finding the global power peak and ensured maximum power delivery. ThisMOA MPPT technique is employed for a 120 W PV system and the versatility of the said scheme is tested by subjecting the PV panel for three different partially shaded conditions. The results reveal that the MOA exhibits fast tracking speed of with improved efficiencyof 99.8% when compared with particle swarm optimization (PSO) and differential evolution algorithm (DE)MPPT schemes.

Keywords

• Photovoltaic
• MPPT
• Particle swarm optimistion
• Differential evoution (DE)
• Meerkat algorithm
• Partially shading