Estimating PV models using multi-group salp swarm algorithm

<span id="docs-internal-guid-ea798321-7fff-3e0c-24d7-776c9b1165b3"><span>In this paper, a multi-group salp swarm algorithm (MGSSA) is presented for estimating the photovoltaic (PV) solar cell models. The SSA metaheuristic technique that mimics social behavior of salp. salps work in group follow certain leader. leader approaches food source and rest follows it, hence resulting slow convergence toward solution. For several groups, searching mechanism going to be improved. In work, recently developed based on groups implemented estimate single-, double-, triple-, Quadruple-, Quintuple-diode models PV cell. Six versions MGSSA algorithms are with different chain numbers; one, two, four, six, eight half number salps. results compared regular particle optimization (PSO) some its newly forms. show has faster rate, shorter settling time than SSA. Similar inspired actual chain, most important member chain; less significant effect algorithm. Therefore, it highly recommended increase leaders reduce length. Increasing (number groups) can root mean squared error (RMSE) maximum absolute (MAE) by 50% value.</span></span>