Application of New Optimization Algorithm for Parameters Estimation in Photovoltaic Modules

Chaib, Lakhdar; Choucha, Abdelghani; Tadj, Mohammed; Khemili, Fatima Zahra

doi:10.1007/978-3-031-21216-1_80

Cited by 1 publication

(1 citation statement)

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“…When the results of the proposed method were compared with the results of newly proposed algorithms in the literature, it was stated that the suggested method proved its superiority in terms of accuracy and robustness. Chaib et al [49] estimated the parameters of various photovoltaic models using the Harris hawks algorithm, which has the advantages of good search ability, high convergence speed, and high efficiency compared to classical methods. Estimation procedures were carried out according to various weather conditions.…”

Section: Related Workmentioning

confidence: 99%

I-CPA: An Improved Carnivorous Plant Algorithm for Solar Photovoltaic Parameter Identification Problem

Beşkirli,

Dağ

2023

Biomimetics

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The carnivorous plant algorithm (CPA), which was recently proposed for solving optimization problems, is a population-based optimization algorithm inspired by plants. In this study, the exploitation phase of the CPA was improved with the teaching factor strategy in order to achieve a balance between the exploration and exploitation capabilities of CPA, minimize getting stuck in local minima, and produce more stable results. The improved CPA is called the I-CPA. To test the performance of the proposed I-CPA, it was applied to CEC2017 functions. In addition, the proposed I-CPA was applied to the problem of identifying the optimum parameter values of various solar photovoltaic modules, which is one of the real-world optimization problems. According to the experimental results, the best value of the root mean square error (RMSE) ratio between the standard data and simulation data was obtained with the I-CPA method. The Friedman mean rank statistical analyses were also performed for both problems. As a result of the analyses, it was observed that the I-CPA produced statistically significant results compared to some classical and modern metaheuristics. Thus, it can be said that the proposed I-CPA achieves successful and competitive results in identifying the parameters of solar photovoltaic modules.

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Section: Related Workmentioning

confidence: 99%