A novel benchmark shading pattern for PV maximum power point trackers evaluation

Partial shading conditions (PSC) drive the P-V characteristics of the PV system to have multiple local peaks (LPs) and one global peak (GP). Conventional maximum power point tracker (MPPT) techniques may be trapped in one of the LPs and miss the GP, which substantially reduces the efficiency of the PV systems. Metaheuristic opti-mization algorithms (MOAs) have been widely used recently to avoid this limitation. Although, the robustness of the MOAs in tracking the GP, still they have many challenges that should be overcome. This paper shed light on the most important problems and solutions provided associated with the use of MOAs as an MPPT of PV systems. Moreover, this paper introduced benchmark shading patterns (BSP) that contain most of the important chal-lenges that may occur in the PSC of PV systems. This BSP can be used as an evaluation benchmark for all MPPT techniques. The problem of stagnation of search agents within a certain LP is investigated and solutions are provided and evaluated. A novel flying search agent (FSA) strategy is used to detect any change in GP position without sacrificing the stability or the ripple contents in the PV system waveforms. The proposed FSA sends a search agent to the position of the anticipated peaks and compares its power with the current GP power. If the power generated from the FSA is higher than the current GP, it will move the particles to search around the position of the FSA.