Genetic Algorithm for Generation of PV Panel Curves From Datasheets

Marinov, Angel; Zahariev, Svetlozar; Ivanov, Ivelin; Papanchev, Toncho

doi:10.1109/elma52514.2021.9502981

Cited by 4 publications

(1 citation statement)

References 7 publications

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“…On the other hand, ref. [22] proposes an algorithm for datasheet parameter extraction of photovoltaic modules using the SDM, where the extracted parameters are obtained by approximation using a GA. Authors in [23] present the implementation of a continuous population genetic optimization algorithm (CGA) as a solution method for the parameter estimation of the diode model (SDM) in a PV panel from experimental data.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Electrical Models for Photovoltaic Cells under Uniform and Partial Shading Conditions

et al. 2022

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This paper compares the performance of three electrical models (the single diode model, the Bishop model, and the Direct–Reverse model) in representing photovoltaic cells. Such comparison is performed in both the first quadrant (positive cell voltage and current—Q1) and the second quadrant (negative cell voltage and positive cell current—Q2). The analysis conducted here is based on the I–-V curves of a PV cell obtained experimentally. The parameters of each model are estimated using a Genetic Algorithm. The root mean square error and the mean absolute percentage error are computed to validate the estimation stage. Likewise, the behavior of each parameter of the models is analyzed by calculating their mean and standard deviation. Some places of interest on the I–V curve, such as the short–circuit point, the open–circuit point, and the maximum power point, are also estimated and compared.

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Section: Introductionmentioning

confidence: 99%