电力市场下水电厂短期优化运行研究
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摘要
当前国外比较成熟的电力市场一般包括长期合约市场和短期市场等多级市场,短期市场往往又包括能量市场和辅助服务市场等,传统意义上的水电优化调度问题在电力市场下演变成多个市场中的联合优化调度问题。AGC市场是辅助服务市场中最重要的组成部分,水电机组由于启停灵活,非常适宜参加AGC调节,本文重点研究了水电厂在日前市场中的能量市场和AGC市场间的联合优化调度问题,并取得了一些有价值的研究成果。
本文首先介绍了当前国内外电力市场发展现状,给出水电将要面临的市场环境,然后分析了水电参与电力市场面临的市场风险,介绍了当前金融领域使用较多的几种风险衡量方法,并评述了它们各自的优缺点,这些是本文后续制定联合调度计划的基础。
联合调度计划的制定是本文的重点,针对均值-方差模型的不足,文中使用VaR(Value at Risk)风险测度指标和期望收益联合构成不同的效用函数来描述不同发电商的市场行为,基于预测电价建立了水电厂在能量市场和AGC市场间的短期联合优化调度模型。在调度模型中,将由中长期调度计划中得到的用水量约束作为软约束,更好的修正了中长期调度计划的不足。针对效用函数中对发电商不同风险偏好比较难考虑的问题,应用蒙特卡罗模拟法对制定出的联合发电计划进行了电价和径流的联合风险评估,评估结果作为反馈信息反过来帮助发电商选择合适的风险因子,直到制定出的调度计划满足发电商的心理预期,从而完善调度计划。
最后,以三峡电厂为背景,结合新英格兰电力市场历史电价数据给出了算例。
The current mature electricity markets overseas generally include long-term contract market and short-term market, which composing multistage markets. The short-term market is often composed of energy market and ancillary service market and so on. The optimization dispatch problem for hydropower plants turns into the coordinative dispatch problem in the multi-markets in the electricity market. The AGC market is the most important part of the ancillary service market. Because of excellent performance at start and stop as well as adjustment for hydro unit, it is extremely suitable for participates in the AGC adjustment. This paper studies the combination optimization dispatch problem for hydropower plants in the day-ahead energy market and AGC market and obtains some valuable research results.
This paper first introduces the current worldwide electricity markets, pointing out the market environment for hydropower plants. Then the market risk faced by hydropower plants and the methods of risk assessment, which are widely used in current financial domain, have been analyzed. These are the foundations of making coordinative schedule in the following parts of this paper.
Solving the coordinate dispatch problem is the most important part of this paper. As the doubt of using variance for risk assessment, it takes the value at risk (VaR) as the risk measurement index. The VaR and expected revenue constitute different utility functions to describe market behavior of different power producer. A model for short-term coordinative dispatch in energy and AGC markets is established for hydropower plants, which is based on the forecasted MCPs for energy market and AGC market. In the model, the constrain of water using, which is obtained by the medium or long-term dispatch plan, is considered as a weak constrain, which is proven to be effective to revise the longer plan. In consideration of the difficulty of choosing appropriate risk factor in utility function for different power producer, Monte-Carlo Method is used for combined risk assessment of power price and inflow. The result can help power producer choose more appropriate risk factor (weight factor), thereby improving the generate schedule.
A case study is given in the end of this paper, which is based on the Three Gorges plant and the historic price data of New England in American.
本文首先介绍了当前国内外电力市场发展现状,给出水电将要面临的市场环境,然后分析了水电参与电力市场面临的市场风险,介绍了当前金融领域使用较多的几种风险衡量方法,并评述了它们各自的优缺点,这些是本文后续制定联合调度计划的基础。
联合调度计划的制定是本文的重点,针对均值-方差模型的不足,文中使用VaR(Value at Risk)风险测度指标和期望收益联合构成不同的效用函数来描述不同发电商的市场行为,基于预测电价建立了水电厂在能量市场和AGC市场间的短期联合优化调度模型。在调度模型中,将由中长期调度计划中得到的用水量约束作为软约束,更好的修正了中长期调度计划的不足。针对效用函数中对发电商不同风险偏好比较难考虑的问题,应用蒙特卡罗模拟法对制定出的联合发电计划进行了电价和径流的联合风险评估,评估结果作为反馈信息反过来帮助发电商选择合适的风险因子,直到制定出的调度计划满足发电商的心理预期,从而完善调度计划。
最后,以三峡电厂为背景,结合新英格兰电力市场历史电价数据给出了算例。
The current mature electricity markets overseas generally include long-term contract market and short-term market, which composing multistage markets. The short-term market is often composed of energy market and ancillary service market and so on. The optimization dispatch problem for hydropower plants turns into the coordinative dispatch problem in the multi-markets in the electricity market. The AGC market is the most important part of the ancillary service market. Because of excellent performance at start and stop as well as adjustment for hydro unit, it is extremely suitable for participates in the AGC adjustment. This paper studies the combination optimization dispatch problem for hydropower plants in the day-ahead energy market and AGC market and obtains some valuable research results.
This paper first introduces the current worldwide electricity markets, pointing out the market environment for hydropower plants. Then the market risk faced by hydropower plants and the methods of risk assessment, which are widely used in current financial domain, have been analyzed. These are the foundations of making coordinative schedule in the following parts of this paper.
Solving the coordinate dispatch problem is the most important part of this paper. As the doubt of using variance for risk assessment, it takes the value at risk (VaR) as the risk measurement index. The VaR and expected revenue constitute different utility functions to describe market behavior of different power producer. A model for short-term coordinative dispatch in energy and AGC markets is established for hydropower plants, which is based on the forecasted MCPs for energy market and AGC market. In the model, the constrain of water using, which is obtained by the medium or long-term dispatch plan, is considered as a weak constrain, which is proven to be effective to revise the longer plan. In consideration of the difficulty of choosing appropriate risk factor in utility function for different power producer, Monte-Carlo Method is used for combined risk assessment of power price and inflow. The result can help power producer choose more appropriate risk factor (weight factor), thereby improving the generate schedule.
A case study is given in the end of this paper, which is based on the Three Gorges plant and the historic price data of New England in American.
引文
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[2] 张勇传. 水电站经济运行原理. 第二版. 北京: 中国水力水电出版社, 1998
[3] 罗予如. 梯级水电厂群短期经济运行的探讨. 水力发电, 2000 年第 2 期: 57~58
[4] Litle J. D. C. The use of storage water in a hydroelectric system, Oper.Res.3, 1995
[5] 王金文, 袁晓辉等. 随机动态规划在三峡梯级长期发电优化调度中的应用,电力自动化设备, 2002, 22(8): 54~56
[6] 梁年生, 姜铁兵. 水电站群补偿调节模型(HCOM)极其求解, 水电能源科学, 1995, 13(1): 43~51
[7] 董子敖. 水库群调度与规划的优化理论与应用, 济南: 山东科学技术出版社, 1989. 86~88
[8] 吴爱华, 陶东兵等. 基于随机动态规划方法的水电站优化调度的研究与应用. 广东水利水电, 2003 年第 1 期: 23~28
[9] 张勇传, 熊斯毅, 黄益芬. 水电站水库群优化调度方法研究. 水力发电学报, 1987 年第 3 期
[10] 田峰巍, 解建仓. 梯级水电站群最优运行的递阶控制算法. 西安理工大学学报, 1998, 14(2): 118~122
[11] 李伟, 纪昌明. 梯级水电站群短期经济运行研究:关联预估与微增率逐次逼近相结合法. 水电能源科学, 2000, 18(1): 13~15
[12] Yeh. William. W-G. Reservoir Management and Operations Models: A State-of-the-art Review. Water Resources Research, 1985, 21(2): 1797~1818
[13] 张铭. 水电站水库调度图及短期优化调度研究: [硕士学位论文]. 武汉: 武汉大学图书馆, 2004
[14] 伍永刚, 张勇传, 王定一. 水火电混合系统经济调度的双链态遗传算法. 华中理工大学学报, 1997, 25(7): 94~96
[15] 马光文, 王黎. 遗传算法在水电站优化调度中的应用. 水科学进展, 1997, 8(3): 275~280
[16] 伍永刚, 王定一. 二倍体遗传算法求解梯级水电站日优化调度问题. 水电能源科学, 1999, 17(3): 31~34
[17] 宋朝红. 基于混合遗传算法的水库群优化调度研究. 武汉大学学报, 2003, 36(4): 28~31
[18] 赵学顺, 黄民翔, 韩祯祥. 电力市场中风险规避问题的研究(一):不同电力市场阶段风险规避模型. 电力系统自动化, 2001, 25(7): 14~20
[19] Shahidehpour S M, Yamin H Y. Risk and Profit in Self-Scheduling for GenCos. IEEE Trans on Power Systems, 2004, 19(4): 2104~2106
[20] Conejo A J, Nogales F J, Arroyo J M et al. Risk-constrained self-scheduling of a thermal power producer. IEEE Trans on Power Systems, 2004, 19(3): 1569~1574
[21] Antonio J. Conejo, José Manuel Arroyo, Javier Contreras, et al. Self-Scheduling of a Hydro Producer in a Pool-Based Electricity Market. IEEE Trans on Power Systems, 2002, 17(4): 1265~1272
[22] J. M. Arroyo, A. J. Conejo, Optimal Response of a Thermal Unit to an Electricity Spot Market. IEEE Trans on Power Systems, 2000, 15(3): 1098~1104
[23] Sebastián de la Torre, José M. Arroyo, Antonio J. Conejo, et al. Price Maker Self-Scheduling in a Pool-Based Electricity Market: A Mixed-Integer LP Approach. IEEE Trans on Power Systems, 2002, 17(4): 1037~1042
[24] 吴世勇, 马光文, 过夏明. 基于边际电价预测的水电厂日优化运行. 水电自动化与大坝监测, 2004, 28(2): 10~12
[25] 刘治理, 马光文, 岳耀峰. 电力市场下的梯级水电厂短期预发电计划研究. 继电器, 2006, 34(4): 46~48
[26] Pettigrew, J. Trading in Ancillary Services. IEE Seminar on Electricity Trading (Ref. No 2000/038), 2000: 3/1~3/6
[27] 任震, 黄福全, 黄雯莹, 等. 电力市场中的发电厂投标组合策略. 电力系统自动化, 2002, 26(2): 14~17
[28] 刘亚安, 薛禹胜, 管晓宏. Price-taker 在两个电力市场中的交易决策(二):发电商的策略. 电力系统自动化, 2004, 28(17): 12~15
[29] 曾次玲, 张步涵, 谢培元, 等. 基于风险管理在开放的能量市场和备用市场间优化分配发电容量. 电网技术, 2004, 28(13): 70~74
[30] Dahlgren R, Liu C C, Lawarree J. Risk assessment in energy trading. IEEE Trans on Power Systems, 2003, 18(2): 503~511
[31] 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. 电力系统自动化, 2005, 29(14): 5~9
[32] Arroyo J M, Conejo A J. Optimal Response of a Power Generator to Energy, AGC, and Reserve Pool-Based Markets. IEEE Trans on Power Systems, 2002, 17(2): 404~410
[33] 于尔铿, 谢开, 韩放, 等. 电力市场概述. 电网技术, 1995, 19(3): 58~62
[34] 邢连中. 英国电力改革发展及电力市场运作. 华东电力, 1999 年第 5 期: 55~58
[35] 鲁海燕, 宋永华. 英国电力工业概述. 现代电力, 2005, 22(2): 91~94
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