Developing Fuzzy Maximum Power Point Tracking (MPPT) and Perturb and Observe (P&O) MPPT Battery Charging Control in MATLAB involves creating two distinct algorithms for optimizing the charging process of batteries connected to photovoltaic (PV) systems.
In the Fuzzy MPPT algorithm, engineers use fuzzy logic to dynamically adjust the operating parameters of the MPPT algorithm based on input variables such as solar irradiance and temperature. The fuzzy logic system evaluates linguistic variables to determine the optimal operating point for the PV system, ensuring maximum power extraction under varying environmental conditions.
In the P&O MPPT algorithm, the system constantly perturbs the operating point of the PV system and observes the resulting change in power output. By comparing the power output before and after the perturbation, the algorithm determines the direction that leads to maximum power and adjusts the operating point accordingly.
By simulating both MPPT algorithms in MATLAB, engineers can evaluate their effectiveness in accurately tracking the maximum power point of the PV system and optimizing battery charging. They can also compare the performance of the two algorithms under different environmental conditions and system configurations to determine the most suitable approach for specific applications.
This approach facilitates the design and optimization of battery charging control strategies for PV systems, enabling efficient utilization of solar energy and enhancing the performance and reliability of renewable energy systems.