A Novel Nature-Inspired Maximum Power Point Tracking (MPPT) Controller Based on SSA-GWO Algorithm for Partially Shaded Photovoltaic Systems

• DOI: 10.3390/electronics8060680
• Publication Date: 2019-06-17T07:24:41Z
• Authors: Yihao Wan; Mingxuan Mao; Lin Zhou; Qianjin Zhang; Xinze Xi; Chen Zheng
• Keywords: Benchmark (surveying); Maximum power principle

To overcome the real-time problem of maximum power point tracking (MPPT) for partially shaded photovoltaic (PV) systems, a novel nature-inspired MPPT controller with fast convergence and high accuracy is proposed in this paper. The achieved by combining salp swarm algorithm (SSA) grey wolf optimizer (GWO) (namely, SSA-GWO). leader structure GWO introduced into basic SSA to enhance global search capability. Numerical simulation on 13 benchmark functions was done evaluate SSA-GWO algorithm. Finally, performance PV system under static dynamic partial shading conditions investigated compared conventional algorithms. quantitative results validated effectiveness superiority method.