A direct adaptive neural control with voltage traverse for maximum power point tracking of photovoltaic system

作者：Xiaoqiang Zhang, Ke Chen, Yingquan Zou, Cuifang Zhang, Guang-Chao Ren · 年份：2017 · DOI：10.1109/ccdc.2017.7979290 · 被引用次数：5 · 研究领域：Photovoltaic System Optimization Techniques、solar cell performance optimization、Solar Radiation and Photovoltaics

In view of the 3×3 PV array and a DC-DC circuit connection of the photovoltaic system maximum power tracking (MPPT) problem, according to the output characteristics of photovoltaic array under partially shadowing conditions(PSC), this paper proposes a new algorithm of adaptive neural network control with the feedback load voltage traverse. First, the feedback load voltage traversal method is used to quickly reach the reference voltage, and then the DANC online learning algorithm is used to stabilize the peak value, and finally through the comparison of the peak value, the global optimal solution is obtained. The simulation results show that the proposed method can track the global maximum power point (GMPP) of the PV array before and after under PSC. Compared with other traditional algorithms, the algorithm is simple and has better tracking accuracy, rapidity and stability.