A modified Marine Predator Algorithm based on opposition based learning for tracking the global MPP of shaded PV system

作者：

Highlights：

• A new MPPT method for PV system, called MPAOBL-GWO is proposed.

• The MPAOBL-GWO improves the MPA using GWO in conjunction with OBL.

• The MPAOBL-GWO exhibits outstanding MPP capability, good transient performance and fast convergence.

• MPAOBL-GWO method is analyzed and compared using various analysis metrics.

• Comparisons illustrate the improvement on the performance of MPAOBL-GWO.

摘要

•A new MPPT method for PV system, called MPAOBL-GWO is proposed.•The MPAOBL-GWO improves the MPA using GWO in conjunction with OBL.•The MPAOBL-GWO exhibits outstanding MPP capability, good transient performance and fast convergence.•MPAOBL-GWO method is analyzed and compared using various analysis metrics.•Comparisons illustrate the improvement on the performance of MPAOBL-GWO.

论文关键词：Engineering design problems,Grey Wolf Optimizer (GWO),Meta-heuristics optimization,Marine Predator Algorithm (MPA),Opposition Based Learning (OBL),PV system,MPP

论文评审过程：Received 18 August 2020, Revised 8 March 2021, Accepted 17 May 2021, Available online 11 June 2021, Version of Record 11 June 2021.

论文官网地址：https://doi.org/10.1016/j.eswa.2021.115253