fuzzy logic to track MPP of the PV

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fuzzy logic to track MPP of the PV

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Fuzzy Logic for PV Maximum Power Point Tracking

Maximum Power Point Tracking (MPPT) is a crucial technique in photovoltaic (PV) systems to ensure optimal energy extraction under varying environmental conditions. Traditional MPPT methods like Perturb and Observe or Incremental Conductance can struggle with rapid changes in irradiance or partial shading. Fuzzy logic offers an intelligent alternative by handling uncertainty and nonlinearity more effectively.

The core idea behind fuzzy logic-based MPPT is to use linguistic rules instead of precise mathematical models. Input variables typically include PV voltage/current changes or power derivatives, which are fuzzified into membership functions (e.g., "Negative Big", "Positive Small"). A rule base then determines the appropriate duty cycle adjustment for the DC-DC converter. For example: "If power change is Positive Big, then slightly increase the duty cycle".

Key advantages include robust performance during cloud transients and lower oscillations near the MPP compared to conventional methods. The system doesn't require exact PV panel parameters, making it adaptable to different installations. Defuzzification converts the fuzzy output into a crisp value that drives the power converter.

This approach demonstrates how soft computing techniques can solve complex optimization problems in renewable energy systems where traditional control theories reach limitations.

(Note: The actual implementation would involve tuning membership functions and rule bases specific to the PV system characteristics)