Communication Dans Un Congrès Année : 2023

Identification of static and dynamic parameters of PV models through multi-objective optimization

Résumé

The accuracy of photovoltaic models used to de- scribe the characteristics of photovoltaic panels is crucial to evaluate the performance and to ensure safety, cost-effectiveness and compliance of photovoltaic systems. In particular, when the parameters for static and dynamic models are optimized independently, it has been shown that they might be not consistent across different environmental conditions. By exploiting the dependency of common parameters between the two models, the fitting problem is transformed into a multi-objective optimization problem, which is solved using evolutionary algorithms. The results showed that selecting a tradeoff solution from the Pareto front obtained, leads to a more consistent set of parameters for each environmental condition analyzed.

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Dates et versions

hal-04364790 , version 1 (27-12-2023)

Identifiants

Citer

Luis Enrique Garcia Marrero, Rudy Alexis Guejia-Burbano, Giovanni Petrone, Michel Piliougine, Eric Monmasson. Identification of static and dynamic parameters of PV models through multi-objective optimization. 2023 IEEE 17th International Conference on Compatibility, Power Electronics and Power Engineering (CPE-POWERENG), Jun 2023, Tallinn, Estonia. pp.1-6, ⟨10.1109/CPE-POWERENG58103.2023.10227400⟩. ⟨hal-04364790⟩
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