Stream-based Short-term Demand Forecasting Model using ARIMA

被引：1
|
作者：
Liu, Tao [1 ]
Chen, Ruimin [1 ]
Xiao, Yong [1 ]
Yang, Jinfeng [1 ]
机构：
[1] Guangdong Power Grid Corp, Elect Power Res Inst, Guangzhou, Guangdong, Peoples R China
来源：
ADVANCES IN MANUFACTURING TECHNOLOGY, PTS 1-4 | 2012年 / 220-223卷
关键词：
stream forecast; demand side management; time series;
D O I：
10.4028/www.scientific.net/AMM.220-223.315
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
Short-term load forecasting for streaming load data is an important issue for power system planning, operation and control. Smart meters of Advanced Meter Infrastructure distributed around the distribution power grid produce streams of load at high-speed. The collected data can be characterized as a non-stationary continuous flow. A stream-based short-term demand forecasting model based on ARIMA is proposed. This method is used to forecast hourly electricity demand for next few days ahead. The performance of this methodology is validated with streaming data collected in real-time from the power grid.
引用
收藏
页码：315 / 318
页数：4
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