A Review of Maximum Power Point Tracking Algorithms for Photovoltaic Systems under Uniform and Non-uniform Irradiances

AbstractThe global demand for electrical energy is constantly increasing while the production of fossil fuel based energy is declinin g and therefore the obvious choice of clean energy source which is abundant and could provide security for the future development is sun's energy. This paper summarizes the modeling of PV module and PV characteristics under shaded conditions. The power- voltage characteristic of photovoltaic array is non-linear and it exhibits multiple peaks including many local peaks and one global peak under non-uniform irradiances. In order to track the global peak, MPPT is the important component of PV systems. Though many review papers discussed the conventional techniques such as P&O, incremental conductance, ripple correlation control and only very few attempts have been made with intelligence MPPT techniques. This paper also discusses the various algorithms based on Fuzzy Logic, Artificial Neural Network, Ant Colony Optimization, Genetic Algorithm and Particle Swarm Optimization applied to maximum power point tracking in photovoltaic systems under changing irradiance conditions. This paper is intended to introduce a conceptual MPPT technique based on Firefly Algorithm (FA)