DocumentCode
816351
Title
Mixed Models for Short-Run Forecasting of Electricity Prices: Application for the Spanish Market
Author
García-Martos, Carolina ; Rodríguez, Julio ; Sánchez, María Jesús
Author_Institution
Univ. Politecnica de Madrid
Volume
22
Issue
2
fYear
2007
fDate
5/1/2007 12:00:00 AM
Firstpage
544
Lastpage
552
Abstract
Short-run forecasting of electricity prices has become necessary for power generation unit schedule, since it is the basis of every profit maximization strategy. In this article a new and very easy method to compute accurate forecasts for electricity prices using mixed models is proposed. The main idea is to develop an efficient tool for one-step-ahead forecasting in the future, combining several prediction methods for which forecasting performance has been checked and compared for a span of several years. Also as a novelty, the 24 hourly time series has been modelled separately, instead of the complete time series of the prices. This allows one to take advantage of the homogeneity of these 24 time series. The purpose of this paper is to select the model that leads to smaller prediction errors and to obtain the appropriate length of time to use for forecasting. These results have been obtained by means of a computational experiment. A mixed model which combines the advantages of the two new models discussed is proposed. Some numerical results for the Spanish market are shown, but this new methodology can be applied to other electricity markets as well
Keywords
load forecasting; power generation economics; power generation scheduling; power markets; time series; Spanish market; electricity price forecasting; power generation unit schedule; profit maximization strategy; short-run forecasting; time series; Computer aided manufacturing; Economic forecasting; Electricity supply industry; Forward contracts; Neural networks; Power generation; Prediction methods; Predictive models; Processor scheduling; Time series analysis; Design of experiments; electricity markets; forecasting; marginal price; time series analysis;
fLanguage
English
Journal_Title
Power Systems, IEEE Transactions on
Publisher
ieee
ISSN
0885-8950
Type
jour
DOI
10.1109/TPWRS.2007.894857
Filename
4162593
Link To Document