研究目的
To fast and accurately extract the ?ve parameters of the one-diode photovoltaic model from experimental data using a modi?ed version of the directional bat algorithm (DBA) that includes a random ?ight step based on the L′evy distribution and a dynamic procedure to correct any solution found which violates the established parameters bounds.
研究成果
The LDBA algorithm was found to be more fast, accurate, and robust than the DBA and BHCS techniques for extracting the parameters of the one-diode photovoltaic model from experimental data. The modifications introduced in the DBA, including the random flight step based on the L′evy distribution and the dynamic correction process, significantly improved the algorithm's performance.
研究不足
The study is limited to two commercial photovoltaic devices, and the effectiveness of the LDBA algorithm in extracting parameters for more complex photovoltaic models or under different conditions was not explored.
1：Experimental Design and Method Selection:
The study employs a modi?ed version of the directional bat algorithm (DBA) named L′evy ?ight directional bat algorithm (LDBA), which introduces a random ?ight step based on the L′evy distribution and a dynamic procedure to correct any solution found which violates the established parameters bounds.
2：Sample Selection and Data Sources:
Tests were carried out on two commercial photovoltaic devices: the RTC France silicon cell and the STP6-120/36 polycristalline module.
3：List of Experimental Equipment and Materials:
The study uses experimental datasets of I and V measurements from the photovoltaic devices.
4：Experimental Procedures and Operational Workflow:
The LDBA algorithm was applied to extract the parameters of the one-diode model from the experimental data, with comparisons made to DBA and biogeography based heterogeneous cuckoo search (BHCS) techniques.
5：Data Analysis Methods:
The root mean square error (RMSE) was used as the error metric to evaluate the accuracy of the parameter extraction.
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