Medium- and long-term electric power demand forecasting based on the big data of smart city

被引：6
|
作者：
Wei, Zhanmeng [1 ]
Li, Xiyuan [1 ]
Li, Xizhong [1 ]
Hu, Qinghe [2 ]
Zhang, Haiyang [2 ]
Cui, Pengjie [3 ]
机构：
[1] Natl Grid Yingkou Co, East 40,Bohai St, Zhanqian Destrict 115000, Yingkou, Peoples R China
[2] Northeastern Univ, 3-11 Wenhua Rd, Shenyang 110819, Peoples R China
[3] Northeastern Univ, Software Coll, 195 Chuangxin Rd, Shenyang 110169, Peoples R China
来源：
2ND ANNUAL INTERNATIONAL CONFERENCE ON INFORMATION SYSTEM AND ARTIFICIAL INTELLIGENCE (ISAI2017) | 2017年 / 887卷
关键词：
ENERGY-CONSUMPTION; PANEL COINTEGRATION; ECONOMIC-GROWTH;
D O I：
10.1088/1742-6596/887/1/012025
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Based on the smart city, this paper proposed a new electric power demand forecasting model, which integrates external data such as meteorological information, geographic information, population information, enterprise information and economic information into the big database, and uses an improved algorithm to analyse the electric power demand and provide decision support for decision makers. The data mining technology is used to synthesize kinds of information, and the information of electric power customers is analysed optimally. The scientific forecasting is made based on the trend of electricity demand, and a smart city in north-eastern China is taken as a sample.
引用
收藏
页数：7
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