基于风险决策的风火发电权交易研究
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摘要
风电与高排放火电之间进行发电权交易是用市场化手段促进风电消纳、火电减排以及维护国家能源安全的一种有效手段。然而,风电出力波动性以及目前的风、火电成本差严重阻碍了2者之间开展发电权交易。对此现状,首先搭建了风电和清洁火电同台竞争的多买方市场;其次,将风电出力波动的平滑成本、火电的碳排放成本分别定义为风、火电的外部环境成本,纳入到2者的发电成本中,并建立了与外部环境成本呈递减关系的受让方激励。在此基础上,针对外部环境成本随机变化导致的交易风险,借鉴金融市场的风险管控理论和委托代理原则,以发电权交易风险最小为目标,构建了风火发电权交易模型。最后,算例结果验证了所提模型的可行性与有效性。
Power generation right trading between wind power and high emissions thermal power is an effective market-oriented means for promoting large-scale wind power integration, reducing thermal power emission and protecting nation's energy security. But the trading is blocked by wind power volatility and large cost difference between the two powers. Considering these situations, competitive market composed of wind power and clean thermal power is constructed. Then, cost of smoothing wind power outputfluctuation and emissions-reduction cost of thermal power are defined as external environmental costs(EEC) introduced into power generation costs. Incentive functions of wind power and clean thermal powerare designed as EEC decreasing functions. On these bases, for market risks caused by EEC random variability, according to conditional value at risk(CVa R) and principal agent theory, model of power generation right trading between wind and thermal powersisconstructed. Feasibility and effectiveness of the proposed model are verified with simulation results.1
Power generation right trading between wind power and high emissions thermal power is an effective market-oriented means for promoting large-scale wind power integration, reducing thermal power emission and protecting nation's energy security. But the trading is blocked by wind power volatility and large cost difference between the two powers. Considering these situations, competitive market composed of wind power and clean thermal power is constructed. Then, cost of smoothing wind power outputfluctuation and emissions-reduction cost of thermal power are defined as external environmental costs(EEC) introduced into power generation costs. Incentive functions of wind power and clean thermal powerare designed as EEC decreasing functions. On these bases, for market risks caused by EEC random variability, according to conditional value at risk(CVa R) and principal agent theory, model of power generation right trading between wind and thermal powersisconstructed. Feasibility and effectiveness of the proposed model are verified with simulation results.1
引文
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[16]周明,聂艳丽.电力市场下长期购电方案及风险评估[J].中国电机工程学报,2006,26(6):116-122.Zhou Ming,Nie Yanli.Long-term electricity purchasing scheme and risk assessment in power markets[J].Proceedings of the CSEE,2006,26(6):116-122(in Chinese).
[17]王绵斌,谭忠富,曹福成,等.输配分开环境下供电公司购电风险的优化控制模型[J].电工技术学报,2007,22(9):184-190.Wang Mianbin,Tan Zhongfu,Cao Fucheng,et al.Optimal control model of purchase electricity risk for power-supplying company under transmission and distribution separation[J].Transactions of China Electrotechnical Society,2007,22(9):184-190(in Chinese).
[18]张兴平,陈玲,武润莲.加权CVa R下的发电商多时段投标组合模型[J].中国电机工程学报,2008,28(16):79-83.Zhang Xingping,Chen Ling,Wu Runlian.Analysis of multi-period combined bidding of power suppliers based on weighted CVa R[J].Proceedings of the CSEE,2008,28(16):79-83(in Chinese).
[19]陈国富.委托·代理与激励设计[M].天津:南开大学出版社,2003,7-17.
[20]Anderson F,Mausser H,Rosen D,et al.Credit risk optimization with conditional value-at-risk criterion[J].Mathematical Programming,2000(89):273-291.
[2]Al-Awami A T,El-Sharkawi Mohamed A.Coordinated trading of wind and thermal energy[J].IEEE Transactions on Sustainable Energy,2011,2(3):277-287.
[3]Akhtar G M A,Al-Awami A T.Emission-aware energy trading by coordinating thermal&wind power generation[C]//Proceeding of International Conference on Power Engineering,Energy and Electrical Drives.Istanbul:IEEE,2013:1023-1027.
[4]Li Xingyu,Zhao Dongmei.An optimal dynamic generation scheduling for a wind-thermal power system[J].Energy and Power Engineering,2013(5):1016-1021.
[5]于大洋,黄海丽,雷鸣,等.电动汽车充电与风电协同调度的碳减排效益分析[J].电力系统自动化,2012,36(10):10-18.Yu Dayang,Huang Haili,Lei Ming,et al.CO2 reduction benefit by coordinated dispatch of electric vehicle charging and wind power[J].Automation of Electric Power Systems,2012,36(10):10-18(in Chinese).
[6]姜书鹏,乔颖,徐飞,等.风储联合发电系统优化配置模型及敏感性分析[J].电力系统自动化,2013,37(20):16-21.Jiang Shupeng,Qiao Ying,Xu Fei,et al.Capacity optimization and sensitivity analysis of cogeneration system of wind power and energy storage[J].Automation of Electric Power Systems,2013,37(20):16-21(in Chinese).
[7]熊猛,高峰,张海峰,等.基于混合储能系统的风电场调度策略[J].电网技术,2014,38(5):1242-1249.Xiong Meng,Gao Feng,Zhang Haifeng.Hybrid energy storage based generation scheduling of wind farms[J].Power System Technology,2014,38(5):1242-1249(in Chinese).
[8]García-González J,Ruiz de la Muela R M,Santos L M,et al.Stochastic joint optimization of wind generation and pumped-storage units in an electricity market[J].IEEE Transactions on Power Systems,2008,23(2):460-468.
[9]于佳,任建文,周明.基于机会约束规划的风-蓄联合动态经济调度[J].电网技术,2013,37(8):116-122.Yu Jia,Ren Jianwen,Zhou Ming.A chance-constrained programming based dynamic economic dispatch of wind farm and pumped-storage power station[J].Power System Technology,2013,37(8):116-122(in Chinese).
[10]盛四清,孙晓霞.利用风蓄联合削峰的电力系统经济调度[J].电网技术,2014,38(9):2484-2489.Sheng Siqing,Sun Xiaoxia.An economic dispatching strategy of peak loading shifting by wind farm and pumped storage plant[J].Power System Technology,2014,38(9):2484-2489(in Chinese).
[11]Vlachogiannis J G.Probabilistic constrained load flow considering integration of wind power generation and electric vehicles[J].IEEE Transactions on Power Systems,2009,24(4):1808-1817.
[12]Saber A Y,Venayagamoorthy G K.Efficient utilization of renewable energy sources by gridable vehicles in cyber-physical energy systems[J].IEEE Systems Journal,2010,4(3):285-294.
[13]Zhao Junhua,Wen Fushuan,Dong Zhaoyang,et al.Optimal dispatch of electric vehicles and wind power using enhanced particle swarm optimization[J].IEEE Transactions on Industrial Informatics,2012,8(4):889-899.
[14]董振.基于风险理论的新能源消纳分析模型及实证研究[D].北京:华北电力大学,2013.
[15]Dahlgren R,Liu C C,Lawarree J.Risk assessment in energy trading[J].IEEE Transactions on Sustainable Energy,2003,18(5):503-511.
[16]周明,聂艳丽.电力市场下长期购电方案及风险评估[J].中国电机工程学报,2006,26(6):116-122.Zhou Ming,Nie Yanli.Long-term electricity purchasing scheme and risk assessment in power markets[J].Proceedings of the CSEE,2006,26(6):116-122(in Chinese).
[17]王绵斌,谭忠富,曹福成,等.输配分开环境下供电公司购电风险的优化控制模型[J].电工技术学报,2007,22(9):184-190.Wang Mianbin,Tan Zhongfu,Cao Fucheng,et al.Optimal control model of purchase electricity risk for power-supplying company under transmission and distribution separation[J].Transactions of China Electrotechnical Society,2007,22(9):184-190(in Chinese).
[18]张兴平,陈玲,武润莲.加权CVa R下的发电商多时段投标组合模型[J].中国电机工程学报,2008,28(16):79-83.Zhang Xingping,Chen Ling,Wu Runlian.Analysis of multi-period combined bidding of power suppliers based on weighted CVa R[J].Proceedings of the CSEE,2008,28(16):79-83(in Chinese).
[19]陈国富.委托·代理与激励设计[M].天津:南开大学出版社,2003,7-17.
[20]Anderson F,Mausser H,Rosen D,et al.Credit risk optimization with conditional value-at-risk criterion[J].Mathematical Programming,2000(89):273-291.