1. Stream-Based Short-Term Demand Forecasting Model Using ARIMA
- Author
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Rui Min Chen, Jin Feng Yang, Yong Xiao, and Tao Liu
- Subjects
Electric power system ,Computer science ,Load forecasting ,Real-time computing ,General Medicine ,Power grid ,Autoregressive integrated moving average ,Demand forecasting ,Term (time) - Abstract
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.
- Published
- 2012
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