Currently, photovoltaic system has gained importance in electrical power generation system, since it is a clean and renewable energy source. An important characteristic of photovoltaic panels is that the available maximum power is provided only in a single operating point called maximum power point. But the position of maximum power point is not fixed and it moves according to the varying irradiance, varying temperature and the load. This requires a mechanism called maximum power point tracking (MPPT) so that maximum power is obtained effectively. In the literature, many classical methods have been developed and implemented to track the maximum power point. The main objective of this paper is to study and analyze the classical techniques such as Perturb and Observe (P&O), Incremental Conductance (IC) and Fuzzy Logic Control (FLC) algorithms and propose an Adaptive Fuzzy Logic Control (AFLC) for MPPT. The performance of AFLC is compared with the conventional MPPT techniques for varying irradiance. The significance of these methods are studied by implementing the algorithm in MATLAB. The experimental results show the effectiveness and feasibility of the proposed method and the results are verified. The results reveal that the adaptive FLC can quickly track change of MPP for various light intensity and delivers higher power compared to the classical algorithms.
Comparative analysis of Maximum Power Point Tracking Algorithms for Photovoltaic Applications
