TY - GEN
T1 - Medium-term Trading Portfolio for Coordinated Wind and Thermal Energy
AU - Wu, Zechen
AU - Ma, Li
AU - Hu, Yuan
AU - Wang, Xiuli
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/8
Y1 - 2019/8
N2 - Coordinated trading of wind and thermal energy has been proved to be an effective way to mitigate the trading risk of wind power in short-term electricity market. In medium-term market, energy provider needs to allocate energy among different submarkets to maximize the total expected profit while restrict the trading risk. This paper proposes a medium-term optimal trading portfolio model for coordinated wind and thermal energy. The proposed model allows energy providers to determine bilateral contract volume, day-ahead bidding volume, commitment schedules and actual output of thermal units based on their risk aversion attitude. Conditional value at risk (CVaR) is used for risk measurement. The model is solved through a multi-stage stochastic programming approach, considering the uncertainty of wind power output and spot price. The results in case study prove that coordinated trading could elevate contract volume, improve the expected profit and restrict the CVaR of trading portfolios.
AB - Coordinated trading of wind and thermal energy has been proved to be an effective way to mitigate the trading risk of wind power in short-term electricity market. In medium-term market, energy provider needs to allocate energy among different submarkets to maximize the total expected profit while restrict the trading risk. This paper proposes a medium-term optimal trading portfolio model for coordinated wind and thermal energy. The proposed model allows energy providers to determine bilateral contract volume, day-ahead bidding volume, commitment schedules and actual output of thermal units based on their risk aversion attitude. Conditional value at risk (CVaR) is used for risk measurement. The model is solved through a multi-stage stochastic programming approach, considering the uncertainty of wind power output and spot price. The results in case study prove that coordinated trading could elevate contract volume, improve the expected profit and restrict the CVaR of trading portfolios.
KW - Bilateral contract
KW - coordinated trading
KW - electricity market
KW - mixed integer stochastic programming
KW - optimal trading portfolio
UR - https://www.scopus.com/pages/publications/85079034685
U2 - 10.1109/PESGM40551.2019.8973783
DO - 10.1109/PESGM40551.2019.8973783
M3 - 会议稿件
AN - SCOPUS:85079034685
T3 - IEEE Power and Energy Society General Meeting
BT - 2019 IEEE Power and Energy Society General Meeting, PESGM 2019
PB - IEEE Computer Society
T2 - 2019 IEEE Power and Energy Society General Meeting, PESGM 2019
Y2 - 4 August 2019 through 8 August 2019
ER -
