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- W4387676015 abstract "The parameters of solar cells for five PV models are identified using an Improved Archimedes Optimization Algorithm (IAOA) in this paper. Two modifications are made to the original Archimedes Optimization Algorithm (AOA). To control the unequal exploration and exploitation phases, the initial adjustment is to incorporate an augmented density decreasing factor. A random average calculation between the current object position and the best object position is implemented for the second modification to solve the local optima issue. The proposed IAOA is then used to tackle the problem of identifying PV model parameters from experimental I-V data. Different PV models, such as the one-diode model (ODM), the two-diode model (TDM), and the PV module model (PMM), have been distinguished using the suggested IAOA. The proposed IAOA outperforms other present algorithms and even outperforms the original AOA based on the revealed results. As closely as feasible to the experimental I-V data of real PV solar cells and module models, the proposed IAOA can choose the best parameter values for PV models." @default.
- W4387676015 created "2023-10-17" @default.
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- W4387676015 date "2023-10-01" @default.
- W4387676015 modified "2023-10-17" @default.
- W4387676015 title "Parameter Identification of Solar Cells Using Improved Archimedes Optimization Algorithm" @default.
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- W4387676015 doi "https://doi.org/10.1016/j.ijleo.2023.171465" @default.
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