Day-ahead electricity market price forecasting based on Panel Cointegration

• Published in: IEEE PES General Meeting pp. 1 - 7
• Main Authors: Li, Xuran Ivan, Yu, C W, Shuyun Ren, Ke Meng, Guozhong Liu
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.07.2010
• Subjects: Autoregressive processes; Biological system modeling; Data models; Electricity; Electricity Market; Forecasting; Panel Cointegration; PJM; Predictive models; Price Forecasting; Time series analysis
• ISBN: 1424465494; 9781424465491
• ISSN: 1932-5517
• DOI: 10.1109/PES.2010.5589977

This paper proposes a novel technique to forecast day-ahead electricity prices based on Panel Cointegration (PC). The current researches on the electricity price forecasting focus on the analysis of unstable economic time series. However, due to the difference of the allocation of power resource and consumption in different regions, the time series of electricity consumption and sales price in a single region cannot contain all information in different regions. In view of the disadvantages of the time series, the panel data is introduced to investigate the long-term equilibrium relationship and the short-term adjustment relationship between electricity consumption and sales price in the paper. The fundamental and novel contribution of the paper is to apply the PC to forecast accurately in day-ahead energy market price. The whole forecasting framework shows the use of PC model in predicting price behavior. Results from the electricity market of PJM in year 2008 are reported.