基于多元GARCH-VaR的水电站短期发电风险调度
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摘要
发电风险调度是电力市场下水电企业风险规避及管理的一种方式。基于VaR风险测量理论,在水电站短期优化调度中考虑电价风险,提出了更易理解、更具有可操作性的风险收入指标,并将GARCH-VaR电价风险测量模型与水电站短期优化调度模型有机耦合,建立了多元的GARCH-VaR发电风险调度模型。通过实例分析得到两种极端风险调度下的出力组合方案,同时还可以根据不同的风险水平和收入期望设置风险收入限额,得到同一风险下的最优组合解,为水电站参与市场竞争、短期发电风险管控提供了决策依据。
Power generation risk dispatching is a feasible way for risk aversion and management of hydropower enterprises in electricity market.Based on VaR risk measurement theory,considering the electricity price risk in short-term optimal scheduling of hydropower station,this paper put forward more understandable and more operational risk income index.And then the GARCH-VaR price risk measurement model was integrated into short-term optimal scheduling model of hydropower station.Power generation risk dispatching model of multiple GARCH-VaR was established.By the case analysis,this paper obtained the output combination scheme under two kinds of extreme risk operations.The optimal solution under the same risk could be obtained by setting the risk income limit according to the different levels of risk and expected income,which provide decision basis for hydropower station to participate in the market competition and shortterm generation risk management.
Power generation risk dispatching is a feasible way for risk aversion and management of hydropower enterprises in electricity market.Based on VaR risk measurement theory,considering the electricity price risk in short-term optimal scheduling of hydropower station,this paper put forward more understandable and more operational risk income index.And then the GARCH-VaR price risk measurement model was integrated into short-term optimal scheduling model of hydropower station.Power generation risk dispatching model of multiple GARCH-VaR was established.By the case analysis,this paper obtained the output combination scheme under two kinds of extreme risk operations.The optimal solution under the same risk could be obtained by setting the risk income limit according to the different levels of risk and expected income,which provide decision basis for hydropower station to participate in the market competition and shortterm generation risk management.
引文
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[10]涂启玉,张茂林.小波神经网络预测电价的新改进[J].电力系统及其自动化学报,2011,23(2):157-160.
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[2]王壬,尚金成,冯旸,等.基于CvaR风险计量指标的发电商投标组合策略及模型[J].电力系统自动化,2005,29(14):5-9.
[3]李继清,张玉山,王丽萍,等.市场环境下水电站发电风险调度问题研究[J].水力发电学报,2005,24(5):1-6,109.
[4]徐刚,马光文.计及电价风险的水电站短期优化调度[J].中国农村水利水电,2006,25(1):91-92,95.
[5]马建军,伍永刚.能量市场和AGC市场中水电优化调度及风险评估[J].水电自动化与大坝监测,2006,30(4):1-4.
[6]K Fong Chan.Using Extreme Value Theory to Measure Value-at-risk for Daily Electricity Spot Prices[J].International Journal of Forecasting,2006,22(2):283-300.
[7]Gong X S,Luo X,Wu J J.Electricity Auction Market Risk Analysis Based on EGARCH-EVT-CVaR Model[C]//Proceedings of IEEE International Conference on Industrial Technology,Gippsland,Victoria,Australia,10-13,2009:1-5.
[8]金菊良,杨晓华,金保明,等.预测日径流过程的双线性模型[J].水电能源科学,2000,18(2):11-13,23.
[9]刘刚,马光文,陈仕军.基于电价波动率的现货电价风险度量研究[J].水电能源科学,2015,33(10):195-198.
[10]涂启玉,张茂林.小波神经网络预测电价的新改进[J].电力系统及其自动化学报,2011,23(2):157-160.
[11]王东生,曹磊.混沌、分形及其应用[M].北京:中国科学技术大学出版社,1995.