Power system short-term load forecasting

被引:0
作者
Wang, Jingyao [1 ]
机构
[1] North China Elect Power Univ, Sch Elect Power Engn, Baoding 071000, Peoples R China
来源
PROCEEDINGS OF THE 2017 5TH INTERNATIONAL CONFERENCE ON MACHINERY, MATERIALS AND COMPUTING TECHNOLOGY (ICMMCT 2017) | 2017年 / 126卷
关键词
Short-term load forecasting; Multiple linear regression; Residual standard deviation;
D O I
暂无
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
In modern power system, the influence of meteorological factors on the load is increasingly prominent. In order to make the decision-making in power system more scientific, we should consider the meteorological factors, to improve the short-term load forecasting accuracy. Due to the weather factors influencing the load are multiple, with the method of multiple linear regression analysis, we respectively deal with daily maximum load and daily minimum load and daily average load and the relationship between meteorological factors and regression analysis, to get the regression coefficients and residual standard deviation of equation. Combined with the regression coefficient, we get a different degree of the meteorological factors influence on the load, and determine the forecasting meteorological factors to improve the accuracy.
引用
收藏
页码:250 / 253
页数:4
相关论文
共 3 条
[1]  
Gang Mu, 2001, P CSEE, V10, P97
[2]  
Li Hailong, 2015, CONSIDERING REAL TIM
[3]  
Li Xiaoyan, 2013, METEOROLOGICAL FACTO