Fractional chaotic ensemble particle swarm optimizer for identifying the single, double, and three diode photovoltaic models� parameters
Heuristic algorithms; Particle swarm optimization (PSO); Photovoltaic cells; Renewable energy resources; Solar power generation; Commercial applications; Environmental conditions; Fast convergence rate; Meta heuristic algorithm; Optimization algorithms; Parameters estimation; Particle swarm optimize...
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2023
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my.uniten.dspace-255392023-05-29T16:10:38Z Fractional chaotic ensemble particle swarm optimizer for identifying the single, double, and three diode photovoltaic models� parameters Yousri D. Thanikanti S.B. Allam D. Ramachandaramurthy V.K. Eteiba M.B. 56688582500 56267551500 55940454800 6602912020 6603527538 Heuristic algorithms; Particle swarm optimization (PSO); Photovoltaic cells; Renewable energy resources; Solar power generation; Commercial applications; Environmental conditions; Fast convergence rate; Meta heuristic algorithm; Optimization algorithms; Parameters estimation; Particle swarm optimizers; PV models; Diodes; algorithm; alternative energy; electrode; model; optimization; parameter estimation; photovoltaic system; temperature effect Solar Photovoltaic is a widely used renewable energy resource, and hence, the accurate and effective modeling of the PV system is crucial in real-time. The accurate PV modeling helps to predict the performance of the PV plant. In this paper, authors have proposed a novel optimization algorithm named Fractional Chaotic Ensemble Particle Swarm Optimizer (FC-EPSO) to model solar PV modules accurately. This article focused on the modeling of single, double, and three diodes models based on experimental data under different environmental conditions. In FC-EPSO, a new approach in the meta-heuristic algorithms is proposed, where fractional chaos maps are incorporated into the algorithm to enhance its accuracy and reliability. FC-EPSO variants performance is evaluated based on three-different experimental datasets, in which two are widely utilized for commercial applications, while the third is measured in the laboratory under four different irradiance and temperature levels. For validation purposes, several statistical analyses and comparisons are carried out with the recent state-of-the-art algorithms. The statistical measures and comparative studies illustrate the accuracy and consistency of the proposed algorithm. The introduced technique is capable of emulating the experimental datasets with less deviation, a fast convergence rate, and short execution time. � 2020 Elsevier Ltd Final 2023-05-29T08:10:38Z 2023-05-29T08:10:38Z 2020 Article 10.1016/j.energy.2020.116979 2-s2.0-85078659941 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85078659941&doi=10.1016%2fj.energy.2020.116979&partnerID=40&md5=42326f66a948d0b45a39731193a4d6c0 https://irepository.uniten.edu.my/handle/123456789/25539 195 116979 Elsevier Ltd Scopus |
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Heuristic algorithms; Particle swarm optimization (PSO); Photovoltaic cells; Renewable energy resources; Solar power generation; Commercial applications; Environmental conditions; Fast convergence rate; Meta heuristic algorithm; Optimization algorithms; Parameters estimation; Particle swarm optimizers; PV models; Diodes; algorithm; alternative energy; electrode; model; optimization; parameter estimation; photovoltaic system; temperature effect |
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56688582500 |
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56688582500 Yousri D. Thanikanti S.B. Allam D. Ramachandaramurthy V.K. Eteiba M.B. |
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Article |
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Yousri D. Thanikanti S.B. Allam D. Ramachandaramurthy V.K. Eteiba M.B. |
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Yousri D. Thanikanti S.B. Allam D. Ramachandaramurthy V.K. Eteiba M.B. Fractional chaotic ensemble particle swarm optimizer for identifying the single, double, and three diode photovoltaic models� parameters |
| author_sort |
Yousri D. |
| title |
Fractional chaotic ensemble particle swarm optimizer for identifying the single, double, and three diode photovoltaic models� parameters |
| title_short |
Fractional chaotic ensemble particle swarm optimizer for identifying the single, double, and three diode photovoltaic models� parameters |
| title_full |
Fractional chaotic ensemble particle swarm optimizer for identifying the single, double, and three diode photovoltaic models� parameters |
| title_fullStr |
Fractional chaotic ensemble particle swarm optimizer for identifying the single, double, and three diode photovoltaic models� parameters |
| title_full_unstemmed |
Fractional chaotic ensemble particle swarm optimizer for identifying the single, double, and three diode photovoltaic models� parameters |
| title_sort |
fractional chaotic ensemble particle swarm optimizer for identifying the single, double, and three diode photovoltaic models� parameters |
| publisher |
Elsevier Ltd |
| publishDate |
2023 |
| _version_ |
1806426176885882880 |
| score |
13.188404 |