基于BPNN的太阳能板双轴自动跟踪控制系统设计与应用

Design and Application of Double-Axis Automatic Tracking Control System for Solar Panel Based on the BPNN

太阳电池板日照利用效率是光伏发电规划中备受关注的问题,为了实现光跟踪的精确控制,采用了PID控制方法,建立了BPNNPID太阳能双轴自动跟踪控制模型,利用BP神经网络对PID控制中的比例、积分、微分等关键参数进行了优化整定。基于日照强度传感器实现了闭环控制,修正了天文年历计算数据的偏差,完成了实物模型的设计与制作。试验表明:基于BP神经网络PID参数整定的控制策略具有良好的自适应性能,提高了光跟踪系统的响应速度、稳定性及准确性,提高了太阳能板的日照利用效率。研究成果对太阳能光伏发电效能提升应用提供了一定的技术参考。

The solar panel sunshine utilization efficiency is a matter of great concern in the photovoltaic power generation planning.In order to achieve accurate control of light tracking,a PID control method is adopted to establish the automatic tracking control model for BPNNPID solar panels.The BP neural network is used to optimize the key parameters such as proportion,integral and differential in PID control.The closed-loop control is realized based on sunshine intensity sensor,the deviation of calculation data of astronomical calendar is corrected,and the physical model is designed and made.The experiment shows that the control strategy based on BP neural network PID parameter tuning has good adaptive performance,which could improve the response speed,stability and accuracy of optical tracking system,and could improve the sunshine utilization efficiency of solar panels.The research results provide a technical reference for improving the efficiency of solar photovoltaic power generation.