TY - JOUR
T1 - Stochastic Optimal Wind Power Bidding Strategy in Short-Term Electricity Market
AU - Hu, Weihao
AU - Chen, Zhe
AU - Bak-Jensen, Birgitte
PY - 2012/2
Y1 - 2012/2
N2 - Due to the fluctuating nature and non-perfect forecast of the wind power, the wind power owners are penalized for the imbalance costs of the regulation, when they trade wind power in the short-term liberalized electricity market. Therefore, in this paper a formulation of an imbalance cost minimization problem for trading wind power in the short-term electricity market is described, to help the wind power owners optimize their bidding strategy. Stochastic optimization and a Monte Carlo method are adopted to find the optimal bidding strategy for trading wind power in the short-term electricity market in order to deal with the uncertainty of the regulation price, the activated regulation of the power system and the forecasted wind power generation. The Danish short-term electricity market and a wind farm in western Denmark are chosen as study cases due to the high wind power penetration here. Simulation results show that the stochastic optimal bidding strategy for trading wind power in the Danish short-term electricity market is an effective measure to maximize the revenue of the wind power owners.
AB - Due to the fluctuating nature and non-perfect forecast of the wind power, the wind power owners are penalized for the imbalance costs of the regulation, when they trade wind power in the short-term liberalized electricity market. Therefore, in this paper a formulation of an imbalance cost minimization problem for trading wind power in the short-term electricity market is described, to help the wind power owners optimize their bidding strategy. Stochastic optimization and a Monte Carlo method are adopted to find the optimal bidding strategy for trading wind power in the short-term electricity market in order to deal with the uncertainty of the regulation price, the activated regulation of the power system and the forecasted wind power generation. The Danish short-term electricity market and a wind farm in western Denmark are chosen as study cases due to the high wind power penetration here. Simulation results show that the stochastic optimal bidding strategy for trading wind power in the Danish short-term electricity market is an effective measure to maximize the revenue of the wind power owners.
KW - Optimal bidding strategy
KW - Short-Term electricity market
KW - Stochastic optimization
KW - Wind power generation
KW - Monte Carlo method
UR - http://www.scopus.com/inward/record.url?scp=84860186986&partnerID=8YFLogxK
M3 - Journal article
SN - 1827-6660
VL - 7
JO - International Review of Electrical Engineering
JF - International Review of Electrical Engineering
IS - 1
ER -