DocumentCode :
1828662
Title :
Price Forecasting in the Spanish Day-Ahead Electricity Market Using Preconditioned Wind Power Information
Author :
Geidel, C. ; Zareipour, Hamidreza
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., Tech. Univ. Berlin, Berlin, Germany
Volume :
2
fYear :
2013
fDate :
4-7 Dec. 2013
Firstpage :
203
Lastpage :
210
Abstract :
In this paper, short-term electricity price forecasting using residual demand under predefined wind power generation conditions is performed. Residual demand is defined as the total electricity demand subtracted by hard to predict renewable energy sources. Focus of this paper lies on wind power generation as the main renewable energy source. First, the long-term influence of wind power on the electricity market price is investigated. Second, the short-term dependency between electricity market price and wind power generation is examined by applying the similar day method to the Spanish day-ahead market as well as data association mining. Third, a novel method of how to use wind power information is introduced.
Keywords :
data mining; demand side management; power markets; wind power; Spanish day-ahead electricity market; data association mining; electricity demand; preconditioned wind power information; renewable energy source; residual demand; short-term electricity price forecasting; wind power generation; Data mining; Electricity; Electricity supply industry; Forecasting; Pragmatics; Support vector machines; Wind power generation; Price forecasting; residual demand; wind power;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Applications (ICMLA), 2013 12th International Conference on
Conference_Location :
Miami, FL
Type :
conf
DOI :
10.1109/ICMLA.2013.124
Filename :
6786109
Link To Document :
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