Short - term load forecasting of power system

被引：0
|
作者：
Jiang, Zongheng [1 ]
机构：
[1] North China Elect Power Univ Baoding, Baoding 071000, Peoples R China
来源：
PROCEEDINGS OF THE ADVANCES IN MATERIALS, MACHINERY, ELECTRICAL ENGINEERING (AMMEE 2017) | 2017年 / 114卷
关键词：
the partial least squares regression analysis; ARMA time series; BP neural network;
D O I：
暂无
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
Short-term load forecasting is of great significance to the operation and analysis of power system to improve the accuracy of load forecasting. An Important Means to Guarantee the Scientific Decision of Power System Optimization. This paper aims to analyze the load fluctuation of the two regions and the relationship between meteorological factors, holiday factors and periodicity, and set up the least squares regression analysis model, time series model and BP neural network model to short - term load forecasting of power system.
引用
收藏
页码：445 / 447
页数：3
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