基于深度神经网络的电网负荷预测与异常检测方法研究
Research on Load Forecasting and Anomaly Detection Methods for Power Grids Based on Deep Neural Networks
潘志宇1
作者信息
- 1. 国电南瑞南京控制系统有限公司,江苏 南京 210000
- 折叠
摘要
在实际工作中,电网负荷预测与异常检测模型精度不高,导致预测和检测结果存在不同程度的偏差,尤其是时段内容的电网负荷预测与异常检测情况尤为明显.因此,深度神经网络的电网负荷预测和异常检测研究,对于提高电网负荷预测与异常检测方法,具备有效的理论意义和实践价值.通过阐述相关理论的方式,为研究提供理论依据,分别介绍深度神经网络的电网负荷预测与异常检测2种方法,进一步推动电网运行安全性与稳定性发展与建设.
Abstract
In practical work,the accuracy of power grid load forecasting and anomaly detection model is not enough,which leads to different degrees of deviation in the prediction and detection results,especially in the time content of power grid load forecasting and anomaly detection.Therefore,the research on power grid load forecasting and anomaly detection based on deep neural network has effective theoretical significance and practical value for improving power grid load forecasting and anomaly detection methods.By expounding the relevant theories,this paper provides a theoretical basis for the research,and introduces two methods of power grid load forecasting and anomaly detection based on deep neural network,so as to further promote the development and construction of power grid operation safety and stability.
关键词
深度神经网络/电网负荷预测/异常检测Key words
deep neural network/power grid load forecasting/anomaly detection引用本文复制引用
出版年
2024
NETL
NSTL
万方数据