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This paper designs a new 5 × 7 optimized FLC-coupled Hopfield Neural Network (NN) maximum tracking technique.
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The proposed maximum power point tracking technique concurrently uses photovoltaic voltage and current deviations to find the maximum power point.
This paper presents the optimum photovoltaic (PV) water pumping system using maximum power point tracking technique (MPPT).
Another point developed in this paper presents the optimization of a photovoltaic (PV) water pumping system using maximum power point tracking technique (MPPT).
A maximum power point tracking technique based on the open-circuit voltage is adopted in the boost converter for high efficiency.
To improve this characteristic, maximum power point tracking technique is used and results in an open circuit voltage of 13.8 V.
Two cases are considered on the basis of receiver rotation according to sun movement, to study the annual behaviour of present system, case (i): fixed position and case (ii): manual maximum power point tracking technique (M-MPPT).
A simplified maximum power point tracking technique is adopted to take advantages of the simpler structure of the circuit and the shorter charge time than those of the conventional solar charger.
In the presented work, the Buck-Boost is used as a second converter after a Single-Ended Primary-Inductance Converter (SEPIC) that is controlled with a maximum power point tracking technique (MPPT); Incremental Conductance MPPT algorithm is chosen to be used because of its simplicity and easy implementation.
In this paper, a Maximum Power Point (MPP) tracking technique is proposed for the Fuel Cell (FC) stacks based on a modified Extremum Seeking (mES) control that slightly improves the performances of the classical ES control schemes.
In this paper is proposed a Maximum Power Point (MPP) tracking technique for the Fuel Cell (FC) stacks based on advanced Extremum Seeking (aES) control that improves the basic performances of the ES control schemes: a guaranteed convergence and proved internal robustness.
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