Hybrid photovoltaic maximum power point tracking of Seagull optimizer and modified perturb and observe for complex partial shading

<span>Due to natural randomness, partial shading conditions (PSCs) photovoltaic (PV) power generation significantly drop the generation. Metaheuristic based maximum point tracking (MPPT) can handle PSCs by searching PV panels’ global (GMPP). However, trapped at local maxima, sluggishness, continuous oscillations around GMPP and inaccuracy are main disadvantages of metaheuristic algorithm. Therefore, development algorithm under complex has been continuously attracting many researchers yield more satisfying results. In this paper, several algorithms including conventional selected for candidate, such as perturb observe (P&O), firefly (FF), differential evolution (DE), grey wolf optimizer (GWO) Seagull (SO). From preliminary study, SO shown best performance among other candidates. Then, is improved rapid optimizer. Modified variable step sizes (MVSPO) applied enhance accuracy SO. To evaluate performances, high complexity multipeak used test algorithms. Statistical results also provided analyze trend performances. The proposed method performances better fast-tracking time settling time, accuracy, higher energy harvesting low steady-state than candidates.</span>