DocumentCode :
690619
Title :
The research of power market patterns incorporation of large-scale wind power
Author :
Hua, D. ; Zhang, Y.T. ; Wang Zengyu ; Dang Xiaojing ; Chen Haoyong
Author_Institution :
Sch. of Electr. Power, South China Univ. of Technol., Guangzhou, China
fYear :
2013
fDate :
8-11 Dec. 2013
Firstpage :
1
Lastpage :
4
Abstract :
With the publication of EU Renewable Energy Guide and the release of the 2020 energy goals, the wind power is incorporated into the power market on a large scale has become an inevitable trend. However, with a substantial increase of wind power proportion to the overall power generation capacity, the cost of wind power connected to the power grid increased accordingly and the impact of wind power generation on electricity market and power grid will become crucial. The article summarizes the wind power subsidies policy in several European countries, analyzed the market cost changes derived from the large-scale wind power incorporated into the power market. And then the paper proposed several market design patterns for wind power participation in the electricity market. Finally, the paper adopted support vector machine (SVM) algorithm for wind speed prediction, which proved wind power manufacturers bidding near the trading time, the closer can effectively improve the accuracy of the wind power prediction, thus reducing market transaction costs.
Keywords :
power engineering computing; power grids; power markets; support vector machines; wind power plants; EU Renewable Energy Guide; SVM algorithm; electricity market; large-scale wind power; power grid; power market patterns; support vector machine; wind power generation; wind power manufacturers; wind power subsidies policy; Educational institutions; Electricity supply industry; Forecasting; Support vector machines; Wind forecasting; Wind power generation; Wind speed; Power market; Support vector machine; Wind power; Wind speed prediction;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power and Energy Engineering Conference (APPEEC), 2013 IEEE PES Asia-Pacific
Conference_Location :
Kowloon
Type :
conf
DOI :
10.1109/APPEEC.2013.6837121
Filename :
6837121
Link To Document :
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