In this work, different model identification metrics are compared for the extraction of the circuit parameters of the one diode model of Photovoltaic (PV) devices. The identification procedure exploits a high performing approach based on the reduction of the dimensionality for the solution space, referred as "reduced forms". This approach is among the methods usually considered as state of the art for parameters extraction and are often used as comparison for novel identification techniques. The reduction of the solution dimensionality introduced by the reduced forms increase the convergence and accuracy of the identification process, creating repeatable and comparable results for the process. The numerical tests performed highlights the difference between the metrics on the voltage-current relationship, resulting in some metrics with very low variance on the identified parameters and other metrics exhibiting outliers solution, which pose an interesting basis for further multi-objective identification formulation.

Laudani, A., Riganti Fulginei, F., Palermo, M., Quercio, M., Corti, F., Lozito, G.M. (2023). On the Identification of One diode PV model by reduced forms and different metrics. In International Conference on Electrical, Computer, Communications and Mechatronics Engineering, ICECCME 2023 (pp.1-7). Institute of Electrical and Electronics Engineers Inc. [10.1109/ICECCME57830.2023.10252294].

On the Identification of One diode PV model by reduced forms and different metrics

Laudani A.
;
Riganti Fulginei F.;Palermo M.;Quercio M.;
2023-01-01

Abstract

In this work, different model identification metrics are compared for the extraction of the circuit parameters of the one diode model of Photovoltaic (PV) devices. The identification procedure exploits a high performing approach based on the reduction of the dimensionality for the solution space, referred as "reduced forms". This approach is among the methods usually considered as state of the art for parameters extraction and are often used as comparison for novel identification techniques. The reduction of the solution dimensionality introduced by the reduced forms increase the convergence and accuracy of the identification process, creating repeatable and comparable results for the process. The numerical tests performed highlights the difference between the metrics on the voltage-current relationship, resulting in some metrics with very low variance on the identified parameters and other metrics exhibiting outliers solution, which pose an interesting basis for further multi-objective identification formulation.
2023
979-8-3503-2297-2
Laudani, A., Riganti Fulginei, F., Palermo, M., Quercio, M., Corti, F., Lozito, G.M. (2023). On the Identification of One diode PV model by reduced forms and different metrics. In International Conference on Electrical, Computer, Communications and Mechatronics Engineering, ICECCME 2023 (pp.1-7). Institute of Electrical and Electronics Engineers Inc. [10.1109/ICECCME57830.2023.10252294].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11590/456227
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