TY - JOUR

T1 - Stochastic Optimal Wind Power Bidding Strategy in Short-Term Electricity Market

A1 - Hu,Weihao

A1 - Chen,Zhe

A1 - Bak-Jensen,Birgitte

AU - Hu,Weihao

AU - Chen,Zhe

AU - Bak-Jensen,Birgitte

PB - Praise Worthy Prize

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?eid=2-s2.0-84860186986&partnerID=40&md5=cbee66e4d2530e01094f95777b99a08e

JO - International Review of Electrical Engineering

JF - International Review of Electrical Engineering

SN - 1827-6660

IS - 1

VL - 7

ER -