DESIGN OF MAXIMUM POWER POINT TRACKER CONTROLLER FOR BOOST CONVERTER PHOTOVOLTAIC ARRAY SYSTEM BASED ON FUZZY MAMDANI LOGIC

This paper discusses the analysis for a proposed design of a maximum power point tracker (MPPT) controller for a photovoltaic (PV) array solar system. Deploying a fuzzy Mamdani logic to track the maximum- power for the PV system when the atmospheric conditions are changed. The fuzzy Mamdani logic controller techniques have high efficiency, rapid response to new environmental factors, and are unaffected by circuit parameter changes. This controller able to adjust the duty cycle fed switching circuit of DC/DC boost to increase the output voltage of the system. By using a Simulink MATLAB, the system with the controller is stimulated and studied for different atmospheric conditions. We choose three irradiation levels of 1000, 800, and 600 W/m2 at a certain temperature of 25 ℃ and three values for the temperature of 20, 30,35 ℃ at irradiation level of 1000 W/m2 to calculate the efficiency of the algorithm. The extracted efficiency results are compared with the usual Perturb and Observe algorithm MPPT topology (P&O) for the same system design and atmospheric conditions. It was found to be the controller efficiency of the proposed algorithm is improved up to 99%. This improvement maximizes performance and reduces costs, provides adequate current and voltage, and minimizes booster losses, and improves booster reliability.

Enhancement of Solar Cell Modeling with MPPT Command Practice with an Electronic Edge Filter

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.