Study On MPPT Control Strategy Of PV Based On Swarm Intelligence Algorithm

Photovoltaic(PV) is a hot research topic in today’s world. As one of the important ways to improve the conversion efficiency of PV, MPPT(maximum power point tracking) technology has become the hot research topic of PV. However, the P-V curve is not only characterized by multiple maxima points, but also characterized by the measurement noise caused by the restriction of actual application under the complex environments, which was ignored by most of the recent literature on MPPT algorithms and make them failed. To overcome the impact of complex application environment and maximize the light energy into electrical energy, the thesis has made the following studies to look for a suitable MPPT strategy:1) Analyzed the full output characteristics of PV via the PV shade experiment in actual application, established the simulation model that can simulate the full output characteristics of PV under complex application environment by Matlab and studied the effect of the measurement noise and outliers to the existing MPPT algorithm by simulation;2) As to the problem of the existing MPPT strategies, proposed the MPPT strategy based on SIA(swarm intelligence algorithms) combined with recursive least squares filtering which inspired by the MPPT strategy of P&O combined with least squares filter. Recursive least square filtering was used to weaken or inhibit the measurement noise and outliers and SIA was used to the global MPPT control.3) Built a MPPT experimental platform with low power to verify effectiveness of the proposed strategy.