Modelling photovoltaic modules with enhanced accuracy using particle swarm clustered optimization

Authors

  • Mouncef El Marghichi Intelligent Systems Design Laboratory (ISDL), Faculty of Science, Abdelmalek Essaadi University, Tetouan 93000, Morocco
  • Abdelilah Hilali Faculty of Sciences, Moulay Ismail University, Meknes 11201, Morocco
  • Azeddine Loulijat Faculty of Sciences and Technology, Hassan first University, FST of Settat, Morocco
  • Abdelhak Essounaini Laboratory of Analysis, Modeling and Simulation, Department of Mathematics and Computer Science, Faculty of Sciences Ben M’Sik Sidi Othman, Hassan II University, Casablanca, Morocco
  • Abdelkhalek Chellakhi Laboratory of Engineering Sciences for Energy (LabSIPE), National School of Applied Sciences of El Jadida, Chouaib Doukkali University, 24000, El Jadida, Morocco

DOI:

https://doi.org/10.21014/actaimeko.v13i2.1699

Keywords:

Particle Swarm Clustered Optimization (PSCO), PV parameter extraction, PV modelling, solar PV

Abstract

Accurately simulating and operating photovoltaic (PV) modules is vital for thoroughly analyzing their performance under different conditions. The main focus of this paper is to address the inherent nonlinearity in solar PV systems. To achieve this, the particle swarm clustered optimization (PSCO) is applied to extract parameters of solar modules, allowing for a more comprehensive understanding of their behavior. PSCO aims to enhance the accuracy and effectiveness of PV module analysis. For that, PSCO utilizes clusters within the particle population, enabling localized communication and information sharing. By doing so, it effectively facilitates efficient exploration and exploitation of diverse regions, fostering a comprehensive understanding of the behavior of PV modules under different conditions. Through this approach, PSCO maximizes the accuracy and effectiveness of parameter extraction, contributing to advancements in PV system analysis and performance evaluation. The effectiveness of PSCO is demonstrated in extracting parameters for the three-diode model (TDM) of the STP6-120/36 and Photowatt-PWP201 PV modules. PSCO surpasses state-of-the-art algorithms with significantly low root mean square error (RMSE) values of 0.0145 A and 0.0019 A, showcasing its superior accuracy. Additionally, PSCO achieves the lowest power errors of 0.16054 W and 0.01484 W for the respective modules, emphasizing its excellent performance.

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Published

2024-05-16

Issue

Vol. 13 No. 2 (2024)

Section

Research Papers

License

Copyright (c) 2024 Mouncef El Marghichi, Abdelilah Hilali, Azeddine Loulijat, Abdelhak Essounaini, Abdelkhalek Chellakhi

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