Experimental Implementation of Improved P&O MPPT Algorithm based on Fuzzy Logic for Solar Photovoltaic Applications

In this work, a literature review of the maximum power point tracking (MPPT) perturb and observe (P&O) technique for photovoltaic (PV) systems is first developed. The P & O algorithms available in the literature are distributed through three groups: a modification of the basic structure of P&O method, a combination of P&O techniques with a classical technique (FSCC, FOCV, SMC) and a combination with another smart technique (FLC, ANN, PSO). Subsequently, the experimental implementation of an improved MPPT P&O algorithm based on fuzzy logic (FL) for solar PV applications is proposed. The conventional P&O algorithm is widely used in PV generation systems due to its easy implementation and low cost. Notwithstanding, its main limitation is the trade-off between dynamic response and steady state oscillation. In order to overcome the limitations existing in the implementations of the conventional P&O algorithm, a FL based controller block is used to provide a variable step. The experimental results show that the response time of the proposed technique is better than the conventional P&O technique. In addition, it is found that the power oscillations and stability of the proposed control are almost eliminated. The improved P&O control based on FLC is accurate, simple and allows a faster optimization towards the maximum power point (MPP) relative to the suggested P&O algorithms found in the literature.