A Novel TSA-PSO Based Hybrid Algorithm for GMPP Tracking under Partial Shading Conditions

In this paper, a new hybrid TSA-PSO algorithm is proposed that combines tunicate swarm (TSA) with the particle optimization (PSO) technique for efficient maximum power extraction from photovoltaic (PV) system subjected to partial shading conditions (PSCs). The performance of was enhanced by incorporating PSO algorithm, which improves exploitation capability TSA. response TSA-PSO-based MPPT investigated performing detailed comparative study other recently published algorithms, such as (TSA), (PSO), grey wolf (GWO), flower pollination (FPA), and perturb observe (P&O). A quantitative qualitative analysis carried out based on three distinct conditions. It observed had remarkable success in locating point quick convergence at global point. presented achieved PV tracking efficiency 97.64%. Furthermore, two nonparametric tests, Friedman ranking Wilcoxon rank-sum, were also employed validate effectiveness method.