A Novel Hybrid Arithmetic-Based Grey Wolf Optimization Method for Tracking the Global Maximum Power Point of Photovoltaic Systems Under Unequal Irradiance Patterns

Sand cat swarm optimization (SCSO) is a recently introduced popular swarm intelligence metaheuristic algorithm, which has two significant limitations low convergence accuracy and the tendency to get stuck in local optima. To alleviate the abovementioned issues, this paper proposes an improved SCSO based on the arithmetic optimization algorithm (AOA), the refracted opposition-based learning and crisscross strategy, called the sand cat arithmetic optimization algorithm (SC-AOA), which introduced AOA to balance the exploration and exploitation and reduce the possibility of falling into the local optimum, used crisscross strategy to enhance convergence accuracy. The effectiveness of SC-AOA is benchmarked on ten benchmark functions, CEC 2014, CEC 2017, CEC 2022, and eight engineering problems. The results show that the SC-AOA has a competitive performance.

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A Novel Hybrid Arithmetic-Based Grey Wolf Optimization Method for Tracking the Global Maximum Power Point of Photovoltaic Systems Under Unequal Irradiance Patterns

Cited by 3 publications

References 31 publications

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