Cauchy distribution optimizer for photovoltaic model parameter extraction and numerical optimization

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Authors: D.Z. Fang, Quan Zhou, Yan Jun, Suping Guo, Ping Guo
Cited by: 0
References: 53

Abstract

The Cauchy distribution optimizer (CDO), a revolutionary nature-inspired metaheuristic method for engineering design, is developed in this study. To prevent early convergence, find a balance between exploration and exploitation in the answer space, CDO method primarily mimics the position parameter and scale parameter behavior of the Cauchy distribution. 29 common CEC2017 unconstrained benchmark functions were used to confirm the CDO’s efficacy and competitiveness. The experimental results show that CDO ranked first overall, with an average ranking of 1.862. Additionally, the approach is applied to five real-world restricted optimization problems including the extraction of solar system key parameters in order to further validate its efficacy. According to the simulation results, the created CDO is a very promising technology that can outperform other cutting-edge competing technologies. The source code for the CDO algorithm is publicly accessible at https://ww2.mathworks.cn/matlabcentral/fileexchange/182811-cauchy-distribution-optimizer .

Fields of Study & Subjects

Optimal Power Flow Distribution Solar Radiation and Photovoltaics Hybrid Renewable Energy Systems

Publication details

Journal / source
Scientific Reports
Volume
16
Issue
1
Pages
3756–3756
Publication date
2 January 2026
Language
EN