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Hybrid optimization based on the analytical approach and the particle swarm optimization algorithm (Ana-PSO) for the extraction of single and double diode models parameters

Author

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  • Choulli, Imade
  • Elyaqouti, Mustapha
  • Arjdal, El hanafi
  • Ben hmamou, Dris
  • Saadaoui, Driss
  • Lidaighbi, Souad
  • Elhammoudy, Abdelfattah
  • Abazine, Ismail

Abstract

Mathematical Modelling is one of the approved strategies for simulating the performances of photovoltaic devices. Each proposed model contains several parameters; and the accurate determination of these parameters remains a significant challenge for photovoltaic researchers. To this end, in this article, we propose a hybrid analytical/metaheuristic technique for extracting the parameters of single and double diode models. The proposed method estimates some parameters analytically. The other parameters are determined using the particle swarm optimization (PSO) algorithm. This proposed approach is validated by applying it to different types of PV cells and modules. The quality of the obtained solutions is evaluated by comparison with the results proposed by other optimization algorithms. The minimum RMSE values found (7.8093×10−4 for R.T.C France, 3.1491×10−4 for PVM 752, 2.1547×10−3 for Photo-watt-PWP 201, 1.7920×10−3 for STM6-40/36 and 1.5330×10−2 for STP6-120/36) demonstrate the high reliability of the approach used compared to other approaches and validate the performance of our approach. Furthermore, the analysis of convergence, speed, and robustness reveals the superiority of our proposed algorithm over the standard PSO algorithm.

Suggested Citation

  • Choulli, Imade & Elyaqouti, Mustapha & Arjdal, El hanafi & Ben hmamou, Dris & Saadaoui, Driss & Lidaighbi, Souad & Elhammoudy, Abdelfattah & Abazine, Ismail, 2023. "Hybrid optimization based on the analytical approach and the particle swarm optimization algorithm (Ana-PSO) for the extraction of single and double diode models parameters," Energy, Elsevier, vol. 283(C).
    • Handle: RePEc:eee:energy:v:283:y:2023:i:c:s0360544223024374
    DOI: 10.1016/j.energy.2023.129043
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