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- W4313204323 abstract "Several maximum power point tracking (MPPT) strategies have been developed to enhance PV cell design parameters to maximize efficiency. Thus far, all MPPT methods used are based on crisp values, but in reality, the data are frequently imprecise if they originate from measuring instruments such as sensors that lack accuracy. To this end, the fuzzy regression model is presented in this paper to determine the maximum power point of the PV module by considering the imprecise model parameters and the output. The model presented in this paper is developed using two methods, namely the fuzzy linear regression and the fuzzy least squares approach. Additionally, a comparison was made between the measurement (PV voltage) and its reference point (Predicted PV voltage) using the principle of α-cut, and the projection of α on the output interval of the duty cycle was processed to the DC-DC converter through PWM. The methods are evaluated using simulation by Matlab/Simulink under changing atmospheric conditions, load variation and partial shading conditions; real test measurements of one day in Bouzareah Algiers, Algeria in 2013 were used to calculate the MPPT efficiency under a real change of weather conditions. The results obtained showed that the two techniques are very similar; they are robust, have no drift, and present high accuracy in the tracking of the MPP with almost negligible oscillations and excellent efficiency compared with classic methods P&O and INC." @default.
- W4313204323 created "2023-01-06" @default.
- W4313204323 creator A5016841756 @default.
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- W4313204323 date "2023-04-01" @default.
- W4313204323 modified "2023-09-29" @default.
- W4313204323 title "New approach based on a fuzzy regression model for a photovoltaic system" @default.
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- W4313204323 doi "https://doi.org/10.1016/j.epsr.2022.109091" @default.
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