Developing Feasible Maximum Power Point Tracker with Fuzzy Logic Microcontroller

This work aims to develop a feasible fuzzy logic based maximum power point tracking (MPPT) controller in a microcontroller. The efficiency of a photovoltaic (PV) module is mainly affected by ambient irradiance and temperature. Due to the rapid changes in the environmental conditions, MPPT is used to manipulate the operating voltage of PV module to maximize the harvested energy. Conventionally, perturb and observe (P&O) algorithm is introduced to track the maximum power point (MPP). However, due to its inherent fixed size of voltage perturbation, the algorithm has poor transition performance when using small perturbation size while huge power losses in steady-state when using large perturbation size. Thus, fuzzy logic is proposed to auto tune perturbation size improve the transient and steady-state performances of the P&O, or known as FP&O. Both developed FP&O and P&O are coded into microcontrollers and their transition and steady-state performances are tested using the simulated PV platform in Matlab. The results show that the proposed FP&O has improve the overall performance by 61.7 % as compared to the P&O under standard test conditions. The proposed FP&O can improve the tracking speed in the transition state, while minimizing power fluctuation in the steady state.