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

2nd Annual International Conference on Information System and Artificial Intelligence

物理学;计算机科学

Wei, Zhanmeng^1 ; Li, Xiyuan^1 ; Li, Xizhong^1 ; Hu, Qinghe^2 ; Zhang, Haiyang^1 ; Cui, Pengjie^3

National Grid Yingkou Company, East 40 Bohai Street, Zhanqian Destrict, Yingkou

115000, China^1

Northeastern University, No. 3-11 Wenhua Road, Heping District Shenyang

110819, China^2

Software College, Northeastern University, No.195, Chuangxin Road, Hunnan District Shenyang

110169, China^3

关键词: Data mining technology;    Decision makers;    Decision supports;    Economic information;    Electric power demands;    Electricity demands;    Geographic information;    Meteorological information;   

Others  :  https://iopscience.iop.org/article/10.1088/1742-6596/887/1/012025/pdf
DOI  :  10.1088/1742-6596/887/1/012025

学科分类：计算机科学（综合）

来源: IOP

【 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.