基于BP神经网络的输电线路山火风险评估模型

发布时间：2018-06-18 08:20

本文选题：输电线路 + 山火灾害　；参考：《电力系统保护与控制》2017年17期

【摘要】：近年来,输电线路因山火引起的跳闸停电事故越来越多,严重影响了电网的安全稳定,山火风险防控俨然已成为电网防灾减灾的重要研究课题。考虑到输电线路山火风险的影响因素多而复杂,提出了一种基于BP神经网络的山火风险评估模型。通过研究分析220 k V及以上输电线路山火灾害高发的实际情况,确定山火主要影响因子作为模型的输入,将山火风险等级作为模型的输出,利用Matlab建立基于BP神经网络的山火风险评估模型。实验结果表明该模型能有效地预测山火风险,对及时发布预警消息具有重要意义。
[Abstract]:In recent years, there are more and more tripping blackouts caused by hill fire on transmission lines, which seriously affect the safety and stability of power grid. The prevention and control of mountain fire risk has become an important research topic of power grid disaster prevention and mitigation. Considering that there are many and complex factors affecting mountain fire risk in transmission lines, a BP neural network based mountain fire risk assessment model is proposed. By studying and analyzing the actual situation of high incidence of mountain fire disaster on 220 kV and above transmission lines, the main influencing factors of mountain fire are determined as the input of the model, and the risk level of mountain fire is taken as the output of the model. The model of mountain fire risk assessment based on BP neural network is established by Matlab. The experimental results show that the model can effectively predict the mountain fire risk, and it is of great significance to issue early warning information in time.
【作者单位】：南瑞集团公司(国网电力科学研究院);国网电力科学研究院武汉南瑞有限责任公司;武汉大学动力与机械学院;
【分类号】：TM752;TP183

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