DocumentCode :
744305
Title :
Maximizing Profit of a Wind Genco Considering Geographical Diversity of Wind Farms
Author :
Songbo Qiao ; Peng Wang ; Tao Tao ; Shrestha, G.B.
Author_Institution :
Power Dispatching Center, State Grid Zhejiang Hangzhou Power Supply Co., Hangzhou, China
Volume :
30
Issue :
5
fYear :
2015
Firstpage :
2207
Lastpage :
2215
Abstract :
Uncertainty and geographical diversity of wind speeds create risk for a wind power generation company (WGenco) to make the maximum profit from power market trading. A probabilistic approach is proposed to estimate the profit of a WGenco considering geographical diversity and uncertainty of wind speeds and market prices. The objective of the optimization problem is to assist a WGenco to do the optimal bidding in market trading in order to make the maximum profit under various market and wind speed uncertainties. The point estimate method (PEM) has been improved to facilitate stochastic modeling of the aggregated power output of wind turbine generators in different locations in the problem formulation. The principal component analysis (PCA) is used to manage correlated wind speeds.
Keywords :
geography; power generation economics; power markets; principal component analysis; tendering; wind power plants; wind turbines; PCA; WGenco; geographical diversity; market prices; maximum profit; optimal bidding; point estimate method; power market trading; principal component analysis; stochastic model; wind Genco; wind farms; wind power generation company; wind speeds; wind turbine generators; Monte Carlo methods; Power markets; Principal component analysis; Wind farms; Wind power generation; Wind speed; Monte Carlo simulation (MCS); point estimate method; power market; principal component analysis; wind farms diversity; wind power bidding;
fLanguage :
English
Journal_Title :
Power Systems, IEEE Transactions on
Publisher :
ieee
ISSN :
0885-8950
Type :
jour
DOI :
10.1109/TPWRS.2014.2361064
Filename :
6923501
Link To Document :
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