Mid-Long Term Algerian Electric Load Forecasting Using Regression Approach

被引:0
|
作者
Nezzar, Mohamed Reda [1 ]
Farah, Nadir [1 ]
Khadir, Tarek [1 ]
机构
[1] Badji Mokhtar Univ, LabGED Lab, Annaba, Algeria
关键词
regression approaches; medium-long term forecasting; multiple linear regressions; multiple exponential regressions; SUPPORT VECTOR REGRESSION; NEURAL-NETWORK;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Electrical load is a major input factor in economic development. To support economic growth and meet the demands in the future, the load forecasting has become a very important task for electric power stations. Therefore, several techniques have been used to accomplish this task. In this study, our interest is focused on the multiple regression approach, especially, linear and exponential regression for medium-long term load forecasting. The choice of this approach is due to the lack of data does not allow us to use artificial intelligence approaches such as neural networks. In addition to the regression approach, we used a system of electric load profile that allows us to obtain the power has a smaller scale (hour, day, week) to get the peaks. Data that has been used in this work represent electric load consumption and were taken from the Algerian national electricity company.
引用
收藏
页码:121 / 126
页数:6
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