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A robust experimental-based artificial neural network approach for photovoltaic maximum power point identification considering electrical, thermal and meteorological impact
Published 2020“…Nonetheless, the consideration of irradiance, electrical, thermal, and weather parameters (scenario IV) yielded higher identification accuracy. The results showed a decrease in the MSE of Vmp by 74.3% (from 1.6 V to 0.411 V), and in the MSE of Imp by 95% (from 4.4e−6 A to 2.16e−7 A), respectively. …”
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Get full text