Abstract
A new photovoltaic cell modeling based on an electronically tunable edge filter is presented in this paper. The new model is subjected to temperature, illumination, and resistance variations. In addition, an MPPT (Maximum Power Point Tracker) command was exposed with a calculation algorithm based on a microcontroller card that used the behavior of an electronically tunable edge filter. The results confirm those published in the literature, showing the influence of the position of the leakage variation in our model, which can give more power. The simulation results show that the proposed command is efficient to determine the MPP point.
Highlights
Today, renewable energies, such as photovoltaic, wind, or hydraulic energy appear to be inexhaustible and exploitable
The design of a PV cell may have a negative effect on the performance and the results delivered to the load charge [3], that’s why a new model of PV cell is proposed in this paper where a leakage resistance is inserted in series with the diode of the cell
In order to extract the maximum power at each instant from the solar cell terminals and transfer it to the load, an adaptation stage is used between the solar cell and the load [5]
Summary
Renewable energies, such as photovoltaic, wind, or hydraulic energy appear to be inexhaustible and exploitable. In the first scheme category, we find ripple-based extremum seeking control [6], Neural Networks [7], dissimilation particle swarm optimization [8], and the Takagi-Sugeno fuzzy model [9]. The method of particle swarm optimization gives good results, it is complex because it is based on neural networks. All the presented approaches and methods aim to advance the PV system efficiency. They suffer from certain stability problems, especially in rapid climate changes. The implementation of the calculation algorithm that finds the MPPT is presented and investigated This method is based on an electronic card, and to the best of our knowledge, has not been presented before.
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