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Modeling and parameters extraction of photovoltaic cell and modules using the genetic algorithms with lambert W-function as objective function
摘要： In this paper, a method based on genetic algorithms is proposed for improving the accuracy of solar cell parameters extracted using novel technique. We propose a computational based binary-coded genetic algorithm (GA) to extract the parameters (I0, Iph, n, Rs and Rsh) for a single diode model of solar cell from its current-voltage (I–V) characteristic. The algorithm was implemented using Matlab as a programming tool and validated by applying it to the I–V curve synthesized from the literature using reported values. The characterization, current-voltage data used was generated by simulating a one-diode solar cell model of speci?ed parameters. The new approach is based on formulating I–V equation of solar cell, with Lambert function, the parameter extraction as a search and optimization problem. Compared with other optimization techniques in literatures, the approach proposed for the determination of parameters are in good agreement.
关键词： Photovoltaic solar cell,genetic algorithm,optimization,parameter extraction,Lambert function
更新于2025-09-23 15:21:01
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[IEEE 2019 IEEE PES Innovative Smart Grid Technologies Conference - Latin America (ISGT Latin America) - Gramado, Brazil (2019.9.15-2019.9.18)] 2019 IEEE PES Innovative Smart Grid Technologies Conference - Latin America (ISGT Latin America) - Method to trace the photovoltaic characteristic curves under partial shading conditions
摘要： The I-V curve is an important parameter, because it has the characteristics of PV panel. It shows compactly that happens in the module due external variations. In this article presents a method to trace the photovoltaic curves under partial shading conditions. Also, it mentions the effects of the bypass diode. Lastly, it makes comparisons between curves of shaded panels and panels with regular irradiance.
关键词： Photovoltaic systems,Lambert function,Newton-Raphson,PV partial shading
更新于2025-09-16 10:30:52