TY - GEN
T1 - Energy uncertainty risk management of hydropower generators
AU - Zhang, Xian
AU - Wang, Xifan
AU - Wang, Xiuli
AU - Chen, Haoyong
PY - 2005
Y1 - 2005
N2 - The output of a hydropower generator without a regulatable reservoir is determined by the streamflow, thus the output is stochastic. Hydropower generators are confronted with the energy-uncertainty risk. A risk-management framework combined with one forward contract and two electricity real options is proposed to manage the energy-uncertainty risk. Suppose a hydropower generator signs a forward contract with an electric utility. The hydropower generator can manage the energy uncertainty risk by one electricity call option and one electricity put option, this strategy is called straddle. With this risk-management framework, the hydropower generator can avoid the energy-surplus risk and energy-shortage risk. By modeling the price process and streamflow process with stochastic model, the option price is calculated based on Monte Carlo simulation. An actual hydropower generator is selected in case study to testify the effectiveness of this framework, and the influences of the hydrological variation, contract price and contract volume on the real option price and social benefit are analyzed.
AB - The output of a hydropower generator without a regulatable reservoir is determined by the streamflow, thus the output is stochastic. Hydropower generators are confronted with the energy-uncertainty risk. A risk-management framework combined with one forward contract and two electricity real options is proposed to manage the energy-uncertainty risk. Suppose a hydropower generator signs a forward contract with an electric utility. The hydropower generator can manage the energy uncertainty risk by one electricity call option and one electricity put option, this strategy is called straddle. With this risk-management framework, the hydropower generator can avoid the energy-surplus risk and energy-shortage risk. By modeling the price process and streamflow process with stochastic model, the option price is calculated based on Monte Carlo simulation. An actual hydropower generator is selected in case study to testify the effectiveness of this framework, and the influences of the hydrological variation, contract price and contract volume on the real option price and social benefit are analyzed.
KW - Electricity market
KW - Energy-uncertainty risk
KW - Monte Carlo Simulation
KW - No-arbitrage pricing
KW - Real option
KW - Risk management
UR - https://www.scopus.com/pages/publications/33746494418
U2 - 10.1109/TDC.2005.1546787
DO - 10.1109/TDC.2005.1546787
M3 - 会议稿件
AN - SCOPUS:33746494418
SN - 0780391144
SN - 9780780391147
T3 - Proceedings of the IEEE Power Engineering Society Transmission and Distribution Conference
SP - 1
EP - 6
BT - Proceedings - 2005 IEEE/PES Transmission and DistributionConference and Exhibition - Asia and Pacific
T2 - 2005 IEEE/PES Transmission and DistributionConference and Exhibition - Asia and Pacific
Y2 - 15 August 2005 through 18 August 2005
ER -