Title :
Short-term Electricity Price Forecasting Based on Grey System Theory and Time Series Analysis
Author_Institution :
Sch. of Comput. & Inf. Eng., Anyang Normal Univ., Anyang, China
Abstract :
Under deregulated environment, accurate price forecasting provides crucial information for electricity market participants to make reasonable competing strategies. With comprehensive consideration of the influencing factors and the varying rules of the day-ahead electricity price of the PJM electricity market, a short-term electricity price forecasting method based on GM(1,2) and ARMA is proposed, in which the equal-dimension and new-information GM(1,2) model is firstly used to the raw data of electricity price series, and then the ARMA model is used to the gray residuals. The numerical example based on the historical data of the PJM market shows that the method can reflect the characteristics of electricity price better and the forecasting accuracy can be improved virtually compared with the conventional GM(1,2) model.
Keywords :
autoregressive moving average processes; grey systems; power markets; pricing; time series; ARMA; autoregressive moving average; deregulated environment; electricity market; grey system theory; short-term electricity price forecasting; time series analysis; Accuracy; Autoregressive processes; Economic forecasting; Electricity supply industry; Electricity supply industry deregulation; Information analysis; Load forecasting; Predictive models; Production; Time series analysis;
Conference_Titel :
Power and Energy Engineering Conference (APPEEC), 2010 Asia-Pacific
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-4812-8
Electronic_ISBN :
978-1-4244-4813-5
DOI :
10.1109/APPEEC.2010.5448651