基于深度学习的主配网设备运行状态监测与预测研究
Research on the Operation State Monitoring and Prediction of the Main Distribution Network Equipment Based on Deep Learning
张靖萱1
作者信息
- 1. 国网河南省电力公司淮滨县供电公司,河南信阳 464400
- 折叠
摘要
为提升电网的运行安全性和效率,提出了一种基于深度学习的主配网设备运行状态监测和预测方法.该方法能自动从主配网设备运行参数中学习特征,精准判断当前状态,并预测其未来状态.同时,它在状态监测和预测任务上均具有较高的准确率,能为电网运营提供强有力的支持,保障电网稳定运行.
Abstract
To improve the operational safety and efficiency of the power grid,a deep learning based method for monitoring and predicting the operational status of main distribution network equipment is proposed.This method can automatically learn features from the operating parameters of the main distribution network equipment,accurately judge the current state,and predict its future state.At the same time,it has high accuracy in state monitoring and prediction tasks,providing strong support for power grid operation and ensuring stable operation of the power grid.
关键词
主配网/深度学习/电力系统Key words
main distribution network/deep learning/power system引用本文复制引用
出版年
2024
NETL
NSTL
万方数据