A new fuzzy control method based on PSO for Maximum Power Point Tracking of photovoltaic system

Maximum Power Point Tracking (MPPT) is the key technology in the solar energy photovoltaic system, which plays an important role in enhancing energy utilization effectively. Aiming at problems existing in traditional fuzzy tracking method, such as pre-confirmation of control parameters, weak self-study ability, and effective tracking cannot be organized under the circumstance that the environment condition is changed greatly, a kind of fuzzy control method based on Particle Swarm Optimization algorithm (PSO) was put forward in this paper, adjusting the membership function parameters of fuzzy control with the use of PSO's self-adaptation mechanism, so that the controller can adjust the tracking step through real-time study and that the photovoltaic system can gain the maximum power point(MPP) more rapidly and accurately when the outer environment changes. The experiment comparative analysis was carried out with the use of the emulation model of photovoltaic batteries, and results proved the validity and robustness of this method.