由于风电出力和平衡市场价格的不确定性,风电商在日前市场投标时将面临较大的风险。为此,提出风电商通过看涨期权以控制平衡市场价格风险,从而减小日前市场投标风险的方法。为了研究风电商的期权合同对其日前市场投标行为的影响,建立一个考虑风电商看涨期权合同的日前市场随机均衡模型,其中采用场景削减技术计入风速和平衡市场价格的不确定性。算例分析验证了模型的合理性和有效性,并表明看涨期权合同可降低风电商参与日前市场竞争时收益的波动,减小风电商的投标偏差,且风电商通过合适的看涨期权合同交易可达到效用最大化。
Abstract
Due to the uncertainties in wind power and the balancing market prices, WPPs will face great risk when bidding in the day-ahead market. Therefore, a call-option-based method is proposed to control the balancing market price risk and reduce WPPs' risk in the day-ahead market bidding. To investigate the impacts of the call option contract on a WPP's day-ahead market bidding behaviors, a stochastic Cournot equilibrium model of the day-ahead wholesale electricity market is developed, taking considerations of the WPP's call option contract. In this model, a scenario reduction technique is employed to describe the uncertainties in wind power and the balancing market prices. Numerical examples are presented to verify the reasonableness and effectiveness of the proposed model. It is shown that the call option contract can help to reduce the WPP's profit fluctuation and its bid deviations in the day-ahead market. In addition, the WPP can maximize its utility by choosing an appropriate call option contract volume.
关键词
风电 /
电力市场 /
风险管理 /
期权合同 /
博弈论
Key words
wind power /
power markets /
risk management /
option contract /
game theory
{{custom_sec.title}}
{{custom_sec.title}}
{{custom_sec.content}}
参考文献
[1] ASENSIO M, CONTRERAS J.Risk-constrained optimal bidding strategy for pairing of wind and demand response resources[J]. IEEE transactions on smart grid, 2017, 8(1): 200-208.
[2] VASIRANI M, KOTA R, CAVALCANTE R L G, et al. An agent-based approach to virtual power plants of wind power generators and electric vehicles[J]. IEEE transactions on smart grid, 2013, 4(3): 1314-1322.
[3] 王晛, 张凯, 张少华, 等. 风电参与投标竞争的多能源市场博弈分析[J]. 太阳能学报, 2021, 42(1): 279-285.
WANG X, ZHANG K, ZHANG S H, et al.Game analysis of multi-energy markets considering wind power bidding[J]. Acta energiae solaris sinica, 2021, 42(1): 279-285.
[4] 王晛, 黄蒙涛, 张少华. 考虑风电投标偏差惩罚的电力市场均衡分析[J]. 电网技术, 2016, 40(2): 602-607.
WANG X, HUANG M T, ZHANG S H.Equilibrium analysis of electricity market considering penalties for wind power's bidding deviation[J]. Power system technology, 2016, 40(2): 602-607.
[5] BARINGO L, CONEJO A J.Strategic offering for a wind power producer[J]. IEEE transactions on power systems, 2013, 28(4): 4645-4654.
[6] 武昭原, 周明, 姚尚润, 等. 基于合作博弈论的风储联合参与现货市场优化运行策略[J]. 电网技术, 2019, 43(8): 2815-2824.
WU Z Y, ZHOU M, YAO S R, et al.Optimization operation strategy of wind-storage coalition in spot market based on cooperative game theory[J]. Power system technology, 2019, 43(8): 2815-2824.
[7] 何翔路, 娄素华, 吴耀武, 等. 双结算模式下风储一体化电站两阶段市场投标调度策略[J]. 电力系统自动化, 2022, 46(4): 47-55.
HE X L, LOU S H, WU Y W, et al.Two-stage market bidding and scheduling strategy of integrated wind power and energy storage station in dual-settlement mode[J]. Automation of electric power systems, 2022, 46(4): 47-55.
[8] WU Z Y, ZHOU M, LI G Y, et al.Interaction between balancing market design and market behaviour of wind power producers in China[J]. Renewable and sustainable energy reviews, 2020, 132: 110060.
[9] BARINGO L, CONEJO A J.Offering strategy of wind-power producer: a multi-stage risk-constrained approach[J]. IEEE transactions on power systems, 2015, 31(2): 1420-1429.
[10] DENG S J, OREN S S.Electricity derivatives and risk management[J]. Energy, 2006, 31(6/7): 940-953.
[11] PINEDA S, CONEJO A J.Using electricity options to hedge against financial risks of power producers[J]. Journal of modern power systems and clean energy, 2013, 1(2): 101-109.
[12] GHAFFARI R, VENKATESH B.Options based reserve procurement strategy for wind generators—using binomial trees[J]. IEEE transactions on power systems, 2013, 28(2): 1063-1072.
[13] AGUIAR N, GUPTA V, KHARGONEKAR P P.A real options market-based approach to increase penetration of renewables[J]. IEEE transactions on smart grid, 2020, 11(2): 1691-1701.
[14] MATEVOSYAN J, SODER L.Minimization of imbalance cost trading wind power on the short-term power market[J]. IEEE transactions on power systems, 2006, 21(3): 1396-1404.
[15] PARK H S, JUN C H.A simple and fast algorithm for K-medoids clustering[J]. Expert systems with applications, 2009, 36(2): 3336-3341.
[16] 王守相, 徐群, 张高磊, 等. 风电场风速不确定性建模及区间潮流分析[J]. 电力系统自动化, 2009, 33(21): 82-86.
WANG S X, XU Q, ZHANG G L, et al.Modeling of wind speed uncertainty and interval power flow analysis for wind farms[J]. Automation of electric power systems, 2009, 33(21): 82-86.
[17] 谷兴凯, 范高锋, 王晓蓉, 等. 风电功率预测技术综述[J]. 电网技术, 2007, 31(S2): 335-338.
GU X K, FAN G F, WANG X R, et al.Summarization of wind power prediction technology[J]. Power system technology, 2007, 31(S2): 335-338.
PDF(2670 KB)
