摘要
配网运行状态随时间变化,线损情况也会随之波动,因此电网需要实时或近实时的数据处理和分析能力,以适应动态变化的环境,为此提出一种电力物联网环境下的配网线损智能诊断方法。首先,对配网运行数据进行分层融合处理,利用改进随机森林算法预测配网线损率;其次,基于半监督学习框架与径向基函数神经网络,构建线损诊断模型,实现配网线损智能诊断;最后,通过试验结果显示,研究方法对电力物联网环境的配网线损率的预测具有较高精度,且能够精准诊断出不同设备的线损故障。
The operation status of the distribution network changes over time,and the line loss situation also fluctuates accordingly.Therefore,it needs real-time or near real time data processing and analysis capabilities to adapt to the dynamically changing power grid environment.Therefore,an intelligent diagnosis method for distribution network line loss in the context of the power Internet of Things is proposed.Firstly,it processes the operation data of distribution network by hierarchical fusion,using improved random forest algo-rithm to predict distribution network line loss rate.Secondly,based on a semi supervised learning framework and radial basis function neural network,it constructs a line loss diagnosis model to achieve intelligent diagnosis of distribution network line loss.Finally,the experimental results show that the research method has high accuracy in predicting the distribution network line loss rate in the power Internet of Things environment,and can accurately diagnose line loss faults of different devices.
作者
刘骞
LIU Qian(Marketing Service Center of State Grid Henan Electric Power Company,Zhengzhou,Henan 450052,China)
出处
《东北电力技术》
2025年第2期15-18,共4页
Northeast Electric Power Technology
关键词
电力物联网
配网
线损
智能诊断
power Internet of Things
distribution network
line loss
intelligent diagnosis
作者简介
刘骞(1990),男,学士,工程师,从事数据管理和人工智能技术等方向研究。
