Parameter Extraction of Photovoltaic Module Using Tunicate Swarm Algorithm

In the renewable energy sector, extraction of parameters for solar photovoltaic (PV) cells is a widely studied area research. Parameter non-linear complex optimization problem PV cells. this research work, authors have implemented Tunicate swarm algorithm (TSA) to estimate optimized value unknown cell/module under standard temperature conditions. The simulation results been compared with four different, pre-existing algorithms: gravitational search (GSA), hybrid particle and (PSOGSA), sine cosine (SCA), whale (WOA). comparison broadly demonstrates that TSA outperforms existing algorithms in terms root mean square error (RMSE) convergence rate. Furthermore, statistical confirm better average robustness precision. Friedman ranking test also carried out demonstrate competency reliability approach.