基于改进BP神经网络的输电线路覆冰预测技术研究  

Research on Transmission Line Icing Prediction Technology Based on Improved BP Neural Network

作　　者：汪勋婷 丁津津 张峰 孙辉 WANG Xun-ting;DING Jin-jin;ZHANG Feng;SUN Hui(Electric Power Research Institute of State Grid Anhui Electric Power Co.,Ltd.,Anhui Hefei 230001,China)

机构地区：[1]国网安徽省电力有限公司电力科学研究院,安徽合肥230001

出　　处：《机械设计与制造》2024年第9期306-310,共5页Machinery Design & Manufacture

基　　金：国网总部科技支持项目(SGAHDK00DJJS1900076)。

摘　　要：针对输电线路距离长、覆盖面广,其安全稳定运行直接关系到电网的运行状态,覆冰已成为威胁输电线路安全运行的重要因素。这里从覆冰厚度预测的角度出发,结合思想进化算法和BP神经网络算法,对输电线路的短期覆冰厚度进行预测。基于六个微气象因子的输入向量,建立了输电线路覆冰厚度短期预测模型。通过仿真对该模型的准确性和稳定性进行验证。结果表明,该方法具有较高的准确性和稳定性。该研究为我国输电线路覆冰预测技术的发展提供一定的参考和借鉴。For the long distance and wide coverage of transmission lines,its safe and stable operation is directly related to the op⁃eration state of the power grid,icing has become an important factor threatening the safe operation of transmission lines.From the perspective of ice thickness prediction,combining the idea of evolutionary algorithm and BP neural network algorithm,the short-term icing thickness of the transmission line is predicted.Based on the input vector of six micro meteorological factors,a short-term prediction model of transmission line icing thickness is established.The accuracy and stability of the model are verified by simulation.The results show that the method has high accuracy and stability.This study provides a certain reference for the devel⁃opment of transmission line icing prediction technology in China.

关 键 词：短期预测 输电线路 微气象 覆冰厚度 思维进化 BP神经网络 

分 类 号：TH16[机械工程—机械制造及自动化]