Spatial Estimation of Electricity Consumption Using Socio-demographic Information

被引:0
|
作者
Mei, Jiali [1 ,2 ]
Goude, Yannig [1 ,2 ]
Hebrail, Georges [1 ]
Kong, Nicolas [3 ]
机构
[1] Elect France, EDF Lab, Palaiseau, France
[2] Univ Paris Sud, Dept Math Orsay, Orsay, France
[3] Enedis, Direct Tech, Paris, France
关键词
Spatio-temporal modeling; Spatial load forecasting; Clustering; Time series; Electric grid management;
D O I
暂无
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Electric power consumption is known at fine temporal scales (e. g. hourly) for geographical zones corresponding to the electric network service divisions (e. g. substations). In several applications, there is a strong need to estimate the past or to forecast future consumption at different divisions, for example the town, district or city block levels. The deployment of smart meters only gives a partial answer to this problem because they usually do not provide exhaustive measures at such temporal scales. We propose in this paper a generic approach to estimate electric consumption on any geographical zones from source zones where fine-grained consumption data is available, using in addition socio-demographic information. The approach is evaluated on both real and simulated data.
引用
收藏
页码:753 / 757
页数:5
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