Parameter Extraction of Photovoltaic Cell and Module with Four Diode Model Using Flood Algorithm DOI Creative Commons
İpek Çetinbaş

Gazi Üniversitesi Fen Bilimleri Dergisi Part C Tasarım ve Teknoloji, Год журнала: 2024, Номер unknown

Опубликована: Дек. 5, 2024

Photovoltaic (PV) cells exhibit a nonlinear characteristic. Before modeling these cells, obtaining accurate parameters is essential. During the phase, using crucial for accurately characterizing and reflecting behavior of PV structures. Therefore, this article focuses on parameter extraction. A cell module were selected modeled four-diode model (FDM). This problem, consisting eleven unknown related to FDM, was solved with flood algorithm (FLA). To compare algorithm’s performance same polar lights optimizer (PLO), moss growth optimization (MGO), walrus (WO), educational competition (ECO) also employed. These five metaheuristic algorithms used first time in study, both solving extraction problem FDM. The objective function aimed at smallest root mean square error (RMSE) evaluated compared through assessment metrics, computational accuracy, time, statistical methods. minimum RMSE obtained FLA, calculated as 9.8251385E-04 FDM-C 1.6884311E-03 FDM-M. statistically demonstrate reinforce FLA’s success over other algorithms, Friedman test Wilcoxon signed-rank utilized. According tests, FLA produced significantly better results than outperformed them pairwise comparisons. In conclusion, has proven be successful promising extraction, its validated.

Язык: Английский

Space mission trajectory optimization via competitive differential evolution with independent success history adaptation DOI
Rui Zhong, Abdelazim G. Hussien,

Shawei Zhang

и другие.

Applied Soft Computing, Год журнала: 2025, Номер unknown, С. 112777 - 112777

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

0
Comprehensive Adaptive Enterprise Optimization Algorithm and Its Engineering Applications DOI Creative Commons
Shuxin Wang, Yingcai Zheng, Li Cao

и другие.

Biomimetics, Год журнала: 2025, Номер 10(5), С. 302 - 302

Опубликована: Май 9, 2025

In this study, a brand-new algorithm called the Comprehensive Adaptive Enterprise Development Optimizer (CAED) is proposed to overcome drawbacks of (ED) in complex optimization tasks. particular, it aims tackle problems slow convergence and low precision. To enhance algorithm’s ability break free from local optima, lens imaging reverse learning approach incorporated. This creates solutions by utilizing concepts optical imaging. As result, expands search range boosts probability finding superior beyond optima. Moreover, an environmental sensitivity-driven adaptive inertial weight developed. dynamically modifies equilibrium between global exploration, which enables for new promising areas solution space, development, centered on refining close currently best-found areas. evaluate efficacy CAED, 23 benchmark functions CEC2005 are chosen testing. The performance CAED contrasted with that nine other algorithms, such as Particle Swarm Optimization (PSO), Gray Wolf (GWO), Antlion (AOA). Experimental findings show unimodal functions, standard deviation almost 0, reflects its high accuracy stability. case multimodal optimal value obtained notably better than those further emphasizing outstanding performance. also applied engineering challenges, like design cantilever beams three-bar trusses. For beam problem, achieved 13.3925, merely 0.0098. truss 259.805047, extremely small 1.11 × 10−7. These results much traditional ED comparative algorithms. Overall, through coordinated implementation multiple strategies, exhibits precision, strong robustness, rapid when searching spaces. such, offers efficient solving various problems.

Язык: Английский

Процитировано

0
Investigating the Impact of Surface Textured Solar Photovoltaic Dummies for Soiling Mitigation: A Computational Fluid Dynamics Study DOI Creative Commons
Kudzanayi Chiteka, Christopher C. Enweremadu

Case Studies in Thermal Engineering, Год журнала: 2024, Номер 64, С. 105407 - 105407

Опубликована: Ноя. 6, 2024

Язык: Английский

Процитировано

1
Parameter Extraction of Photovoltaic Cell and Module with Four Diode Model Using Flood Algorithm DOI Creative Commons
İpek Çetinbaş

Gazi Üniversitesi Fen Bilimleri Dergisi Part C Tasarım ve Teknoloji, Год журнала: 2024, Номер unknown

Опубликована: Дек. 5, 2024

Photovoltaic (PV) cells exhibit a nonlinear characteristic. Before modeling these cells, obtaining accurate parameters is essential. During the phase, using crucial for accurately characterizing and reflecting behavior of PV structures. Therefore, this article focuses on parameter extraction. A cell module were selected modeled four-diode model (FDM). This problem, consisting eleven unknown related to FDM, was solved with flood algorithm (FLA). To compare algorithm’s performance same polar lights optimizer (PLO), moss growth optimization (MGO), walrus (WO), educational competition (ECO) also employed. These five metaheuristic algorithms used first time in study, both solving extraction problem FDM. The objective function aimed at smallest root mean square error (RMSE) evaluated compared through assessment metrics, computational accuracy, time, statistical methods. minimum RMSE obtained FLA, calculated as 9.8251385E-04 FDM-C 1.6884311E-03 FDM-M. statistically demonstrate reinforce FLA’s success over other algorithms, Friedman test Wilcoxon signed-rank utilized. According tests, FLA produced significantly better results than outperformed them pairwise comparisons. In conclusion, has proven be successful promising extraction, its validated.

Язык: Английский

Процитировано

0