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Cover: Class Fuzzy-Neural Solar Panel MPPT #1: Mathematical Model of Cells & Solar Panels: I-V and P-V Curves
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Here is the final result, the mathematical model of a 200 Watt solar module whose curve matches the data shared by the manufacturer, complete with the effects of irradiance and temperature. This model is the basis for all MPPT simulations in this series, up to the shadow-resistant neural phase method. Let's start. Hello, welcome to the tutorial series on research-based MPPT solar panel using a neural network under partial shading conditions. MPPT or Maximum Power Point Tracking is an algorithm in inverters and charge controllers that continuously searches for the operating point with the maximum power. When part of the panel is shaded, the power curve has multiple peaks and conventional MPPT often gets stuck. In this 6-episode series, we build everything using Python, the panel model, partial shading, classical MPPT, fuzzy logic, ANFIS, and comparisons of all methods. In the first episode, we model the solar panel.
We open the terminal through the terminal menu, new terminal, and then install numpy and matplotlib. All algorithms are written from scratch. The modeled module is Kyocera KAC200GT, a 200 Watt module that is very commonly used in papers because its parameters are fully published by Vilalfa and colleagues.
Create the file pv-model.py Model 1 diode consists of a light current source, a diode, series resistance, and shunt resistance. The constants come from the data sheet, 54 series cells, short-circuit current of 8.21 amperes, open-circuit voltage of 32.9 volts, and temperature coefficient. The parameter function calculates the light current proportional to irradiance, the diode saturation current that sharply increases with temperature, and the thermal voltage. The current equation is implicit, as current appears on both sides, so the current function solves it using Newton-Raphson for multiple voltages at once. Create the file curve_underscore_pv.py and run it.
Under standard conditions of 1000 W/m² and 25 degrees, the maximum power of the 200.13 Watt model is at 26.35 volts. The short-circuit current and open-circuit voltage are exactly the same as the data sheet. Our model has been validated.
Now the curve. IV curve on the left. Current is almost constant and then sharply drops near the open-circuit voltage. The red dot is the maximum power point. Middle graph. Power drops almost proportionally with irradiance. Meanwhile, the peak voltage only shifts slightly. Right graph. Rising temperature causes voltage to drop and power to decrease. From about 225 watts at 0 degrees to about 150 watts at 75 degrees. Because the peak point keeps moving, We need an MPPT.
Done. We have already modeled the KAC200GT solar module using the one-diode model. Solving it using Newton-Raphson, Validate it with the data sheet, and observe the effect of irradiance and temperature. In the next episode, we will assemble 3 series modules with bypass diode and simulating partial shedding. Working on a thesis, thesis, Or are you involved in research in the field of solar energy and renewable energy? Cerdas Inovasi Digital helps implement solar panel simulation from the 1 diode model, partial shedding, MPPT perturbo and observe and incremental conductance, fuzzy logic, until ANVIS, as well as opening a Python programming course for electrical engineering. Want to master the entire series? From solar panel model to comparison of all MPPT methods? All 6 episodes, complete with step-by-step PDF guide and source code, available for premium tutorial subscribers. Subscribe starting at Rp69.000 per month, save 28% with the 12-month package, or one-time payment of Rp999.000 for lifetime access. Thank you for watching, see you in the next episode. Thank you for watching,
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