Title: Adaptive differential evolution with linear population reduction for parameter estimation of solar cell models

Authors: Zhen Yan; Wenyin Gong; Shuijia Li

Addresses: School of Computer Science, China University of Geosciences, Wuhan, 430074, China ' School of Computer Science, China University of Geosciences, Wuhan, 430074, China ' School of Computer Science, China University of Geosciences, Wuhan, 430074, China

Abstract: Parameter estimation of solar cell models is an important part of photovoltaic power generation system. However, it is still a challenging problem. In this study, an adaptive differential evolution with linear population reduction, called LRJADE, is developed to accurately estimate solar cell models parameters. In LRJADE, the linear population reduction strategy is employed to accelerate convergence speed. Additionally, the crossover rate repairing is also used. The performance of proposed LRJADE is verified by 13 benchmark functions and two solar cell model parameter estimation problems. Simulated results show that LRJADE not only obtains promising results in benchmark functions, but also achieves the very accurate solutions to solar cell model parameter estimation problems.

Keywords: parameter estimation; solar cell models; differential evolution; adaptation.

DOI: 10.1504/IJAAC.2022.126084

International Journal of Automation and Control, 2022 Vol.16 No.6, pp.716 - 739

Received: 04 Mar 2021
Accepted: 25 Mar 2021
Published online: 11 Oct 2022 *

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