Research and Test of Power-Loop-Based Dynamic Multi-Peak MPPT Algorithm

Common heuristic search-based multi-peak maximum power point tracking (MPPT) algorithms, such as a particle swarm optimizer and a perturb, observe, and check algorithm, can find the global maximum power point (GMPP) of a multi-peak photovoltaic (PV) characteristic curve and improve the efficiency under partial shading situation. However, these methods have issues, including sharp fluctuations, poor dynamic performance, and low efficiency, under unstable environments and the EN50530 process. As a result, they are rarely used in practice. A novel dynamic multi-peak MPPT algorithm based on improved power loop is proposed in this paper. The algorithm provides a practical approach maintaining advantages of other algorithms, while providing multiple modes such as tracking, scanning, and optimizing in order to reduce the number of reboot and achieve smooth tracking. This method can not only determine the GMPP of multi-peak characteristic, but also provides superior dynamic performance. Experiments have proved that the algorithm have a better performance in the EN50530 test and a high efficiency. The feasibility of the proposed method is verified in a laboratory and a rooftop PV power station.