适用于光伏发电系统的神经网络最大功率点跟踪控制器研究（英文）

Research on neural network maximum power point tracking controller for photovoltaic power generation system

针对基于BP神经网络的光伏最大功率点跟踪(MPPT)控制存在的问题,提出了一种适用于光伏发电系统的改进型神经网络MPPT控制器。首先对太阳能光伏发电系统中的电池工作原理及其等效电路进行了分析。然后采用BP神经网络和模糊控制相结合对来实现光伏MPPT控制。此外,采用自适应参数对模糊控制器进行了改进。最后,基于BOOST转换电路建构建了光伏电池的matlab/simulink仿真模型。实验结果显示:提出的最大功率点跟踪控制器具有较高的准确性和反应速度,且稳定性较好。

Aiming at the problems of photovoltaic power point tracking (MPPT) control based on BP neural network, an improved neural network MPPT controller for photovoltaic power generation system is proposed. Firstly, the working principle and equivalent circuit of the battery in the solar photovoltaic power generation system are analyzed. Then, the combination of BP neural network and fuzzy control is used to realize photovoltaic MPPT control. In addition, the fuzzy controller is improved with adaptive parameters. Finally, based on the BOOST conversion circuit, the matlab/simulink simulation model of the photovoltaic cell was established. The experimental results show that the proposed maximum power point tracking controller has higher accuracy and response speed, and the stability is better.