计及需求响应的售电公司正偏差电量考核优化模型
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摘要
偏差电量考核是电力市场化进程中重要的环节之一,也是电力现货市场形成之前的过渡阶段。为了更为直观地表达偏差电量考核对于售电公司的影响,构建了基于偏差电量考核机制下的售电公司收益模型。同时,采取需求响应措施来减少偏差电量,在此基础上建立了以售电公司收益最大化为目标的可中断负荷合同及价差期权合同最优购买模型。以广东电力市场2017年交易数据为基础,对比分析了捆绑合同对售电公司收益的影响,并对月度市场出清价、用户统一价差和补偿费用进行了敏感性分析。结果表明,售电公司可以通过捆绑合同来降低考核费用,从而提高整体收益,同时也降低了用户的用电成本;月度市场出清价和中断负荷补偿费用的变动对偏差电量考核费用的影响最大,用户统一价差对售电公司用户成本影响最大。
Energy deviation penalty mechanism is an important part in the market-oriented electricity market and also a transitional stage before the formation of the electricity spot market. To express the impact of the deviation penalty on the sales revenue of retailers intuitively, a revenue-based corporate revenue model based on the penalty mechanism is constructed. Meanwhile, the demand response measures are adopted to reduce the amount of deviation electricity. An optimal purchase model of interruptible load contracts and spread options contracts is established with the goal of maximizing the sales revenue of retailers. Based on the transaction data of Guangdong power market in 2017, the impact of bundled contracts on the sale revenue of retailers is analyzed and the sensitivity analysis of monthly market price, user uniform price and compensation cost is carried out. The results show that retailers can reduce the appraisal cost by bundling contracts, then make the overall revenue increase and reduce the user's costs. In addition, the changes of monthly market price and compensation cost have the greatest impact on the deviation penalty, and the cost of retailers is most affected by user uniform price.
Energy deviation penalty mechanism is an important part in the market-oriented electricity market and also a transitional stage before the formation of the electricity spot market. To express the impact of the deviation penalty on the sales revenue of retailers intuitively, a revenue-based corporate revenue model based on the penalty mechanism is constructed. Meanwhile, the demand response measures are adopted to reduce the amount of deviation electricity. An optimal purchase model of interruptible load contracts and spread options contracts is established with the goal of maximizing the sales revenue of retailers. Based on the transaction data of Guangdong power market in 2017, the impact of bundled contracts on the sale revenue of retailers is analyzed and the sensitivity analysis of monthly market price, user uniform price and compensation cost is carried out. The results show that retailers can reduce the appraisal cost by bundling contracts, then make the overall revenue increase and reduce the user's costs. In addition, the changes of monthly market price and compensation cost have the greatest impact on the deviation penalty, and the cost of retailers is most affected by user uniform price.
引文
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[6] 赵博石,严宇,刘永辉,等.基于区域发电成本核准的跨区跨省电力交易偏差电量定价方法[J].电网技术,2016,40(11):3334-3341.ZHAO Boshi, YAN Yu, LIU Yonghui, et al. Pricing method of deviation electric quantity based on regional generation cost of cross-regional and cross-province electricity transaction[J]. Power System Technology, 2016, 40(11): 3334-3341.
[7] YU Xiaobao, TAN Zhongfu, ZHANG Yuxie, et al. The feedback mechanism of carbon emission reduction in power industry of delayed systems[J]. Mathematical Problems in Engineering, 2017(8): 1-14.
[8] 李春,卫志农,孙国强,等.考虑风力发电波动引起频率偏差的电力系统状态估计[J].电网技术,2015,39(5):1301-1306.LI Chun, WEI Zhinong, SUN Guoqiang, et al. State estimation of power system considering frequency deviation caused by fluctuation of wind power generation[J]. Power System Technology, 2015, 39(5): 1301-1306.
[9] HE Jianping, CAI Lin, CHENG Peng, et al. Optimal investment for retail company in electricity market[J]. IEEE Transactions on Industrial Informatics, 2015, 11(5): 1210-1219.
[10] KAZEMI M, MOHAMMADI I B, EHSAN M. Risk-constrained strategic bidding of GenCos considering demand response[J]. IEEE Transactions on Power Systems, 2014, 30(1): 376-384.
[11] 杨阳方,刘继春.计及电量互保策略的售电公司两阶段日前决策方法[J].电力系统自动化,2017,41(24):120-128.DOI:10.7500/AEPS20170612008.YANG Yangfang, LIU Jichun. Two-stage decision-making method of retailers considering power transfer strategy[J]. Automation of Electric Power Systems, 2017, 41(24): 120-128. DOI: 10.7500/AEPS20170612008.
[12] 郭曼兰,陈皓勇,张聪,等.偏差电量考核机制下售电公司的最优经营策略[J].电力系统自动化,2017,41(20):17-25.DOI:10.7500/AEPS20170330010.GUO Manlan, CHEN Haoyong, ZHANG Cong, et al. Optimal marketing strategy of retailers under energy deviation penalty[J]. Automation of Electric Power Systems, 2017, 41(20): 17-25. DOI: 10.7500/AEPS20170330010.
[13] 刘敦楠,汤洪海,杨沫,等.促进新能源消纳的电力交易偏差结算补偿机制[J].电力系统自动化,2017,41(24):105-111.DOI:10.7500/AEPS20170615020.LIU Dunnan, TANG Honghai, YANG Mo, et al. Settlement compensation mechanism of power trading deviation with promotion of renewable energy consumption[J]. Automation of Electric Power Systems, 2017, 41(24): 105-111. DOI: 10.7500/AEPS20170615020.
[14] 丁坚勇,张银芽,杨东俊,等.基于频率偏差的跨区电网交易偏差电量责任判定及定价方法[J].电力系统自动化,2017,41(16):105-110.DOI:10.7500/AEPS20161127001.DING Jianyong, ZHANG Yinya, YANG Dongjun, et al. Responsibility determination and pricing method of deviation electric quantity based on frequency deviation of cross-regional grids trading[J]. Automation of Electric Power Systems, 2017, 41(16): 105-110. DOI: 10.7500/AEPS20161127001.
[15] SAKURAMA K. Distributed flow network control with demand response via price adjustment[J]. Neurocomputing, 2017, 270: 34-42.
[16] IM K M. Automated demand response system in lighting for optimization of electricity cost[J]. Energy Efficiency, 2017, 10(6): 1329-1341.
[17] DUSPARIC I, TAYLOR A, MARINESCU A, et al. Residential demand response: experimental evaluation and comparison of self-organizing techniques[J]. Renewable & Sustainable Energy Reviews, 2017, 80: 1528-1536.
[18] ABDULAAL A, MOGHADDASS R, ASFOUR S. Two-stage discrete-continuous multi-objective load optimization: an industrial consumer utility approach to demand response[J]. Applied Energy, 2017, 206: 206-221.
[19] YU Xiaobao, TAN Zhongfu, CHEN Kangting, et al. Dynamic game analysis of coal electricity market involving multi-interests[J]. Mathematical Problems in Engineering, 2016(49): 1-9.
[20] ARAGON-BRICENO C, ROSS A B, CAMARGO-VALERO M A. Evaluation and comparison of product yields and bio-methane potential in sewage digestate following hydro thermal treatment[J]. Applied Energy, 2017, 208: 1357-1369.
[2] 罗琴,宋依群.售电市场环境下计及可中断负荷的营销策略[J].电力系统自动化,2015,39(17):134-139.LUO Qin, SONG Yiqun. Marketing strategy in competitive retail market considering interruptible load[J]. Automation of Electric Power Systems, 2015, 39(17): 134-139.
[3] 谭忠富,王冠,李鹏,等.市场环境下的售电商合作博弈研究[J].中国电力,2017,50(4):45-51.TAN Zhongfu, WANG Guan, LI Peng, et al. Research on cooperative game of electricity providers under the market environment[J]. Electric Power, 2017, 50(4): 45-51.
[4] 刘敦楠,孟雅儒.考虑非价格因素的售电公司竞争力分析[J].电力系统自动化,2017,41(23):53-60.DOI:10.7500/AEPS 20161017005.LIU Dunnan, MENG Yaru. Analysis on competitiveness of electricity retailers considering non-price factor[J]. Automation of Electric Power Systems, 2017, 41(23): 53-60. DOI: 10.7500/AEPS20161017005.
[5] 张晨,韩新阳,白翠粉,等.基于合作博弈的电力市场模式下售电商购电策略模型[J].中国电力,2017,50(6):177-184.ZHANG Chen, HAN Xinyang, BAI Cuifen, et al. Purchasing strategy model for power supplier based on the cooperative game theory in an open electricity market[J]. Electric Power, 2017, 50(6): 177-184.
[6] 赵博石,严宇,刘永辉,等.基于区域发电成本核准的跨区跨省电力交易偏差电量定价方法[J].电网技术,2016,40(11):3334-3341.ZHAO Boshi, YAN Yu, LIU Yonghui, et al. Pricing method of deviation electric quantity based on regional generation cost of cross-regional and cross-province electricity transaction[J]. Power System Technology, 2016, 40(11): 3334-3341.
[7] YU Xiaobao, TAN Zhongfu, ZHANG Yuxie, et al. The feedback mechanism of carbon emission reduction in power industry of delayed systems[J]. Mathematical Problems in Engineering, 2017(8): 1-14.
[8] 李春,卫志农,孙国强,等.考虑风力发电波动引起频率偏差的电力系统状态估计[J].电网技术,2015,39(5):1301-1306.LI Chun, WEI Zhinong, SUN Guoqiang, et al. State estimation of power system considering frequency deviation caused by fluctuation of wind power generation[J]. Power System Technology, 2015, 39(5): 1301-1306.
[9] HE Jianping, CAI Lin, CHENG Peng, et al. Optimal investment for retail company in electricity market[J]. IEEE Transactions on Industrial Informatics, 2015, 11(5): 1210-1219.
[10] KAZEMI M, MOHAMMADI I B, EHSAN M. Risk-constrained strategic bidding of GenCos considering demand response[J]. IEEE Transactions on Power Systems, 2014, 30(1): 376-384.
[11] 杨阳方,刘继春.计及电量互保策略的售电公司两阶段日前决策方法[J].电力系统自动化,2017,41(24):120-128.DOI:10.7500/AEPS20170612008.YANG Yangfang, LIU Jichun. Two-stage decision-making method of retailers considering power transfer strategy[J]. Automation of Electric Power Systems, 2017, 41(24): 120-128. DOI: 10.7500/AEPS20170612008.
[12] 郭曼兰,陈皓勇,张聪,等.偏差电量考核机制下售电公司的最优经营策略[J].电力系统自动化,2017,41(20):17-25.DOI:10.7500/AEPS20170330010.GUO Manlan, CHEN Haoyong, ZHANG Cong, et al. Optimal marketing strategy of retailers under energy deviation penalty[J]. Automation of Electric Power Systems, 2017, 41(20): 17-25. DOI: 10.7500/AEPS20170330010.
[13] 刘敦楠,汤洪海,杨沫,等.促进新能源消纳的电力交易偏差结算补偿机制[J].电力系统自动化,2017,41(24):105-111.DOI:10.7500/AEPS20170615020.LIU Dunnan, TANG Honghai, YANG Mo, et al. Settlement compensation mechanism of power trading deviation with promotion of renewable energy consumption[J]. Automation of Electric Power Systems, 2017, 41(24): 105-111. DOI: 10.7500/AEPS20170615020.
[14] 丁坚勇,张银芽,杨东俊,等.基于频率偏差的跨区电网交易偏差电量责任判定及定价方法[J].电力系统自动化,2017,41(16):105-110.DOI:10.7500/AEPS20161127001.DING Jianyong, ZHANG Yinya, YANG Dongjun, et al. Responsibility determination and pricing method of deviation electric quantity based on frequency deviation of cross-regional grids trading[J]. Automation of Electric Power Systems, 2017, 41(16): 105-110. DOI: 10.7500/AEPS20161127001.
[15] SAKURAMA K. Distributed flow network control with demand response via price adjustment[J]. Neurocomputing, 2017, 270: 34-42.
[16] IM K M. Automated demand response system in lighting for optimization of electricity cost[J]. Energy Efficiency, 2017, 10(6): 1329-1341.
[17] DUSPARIC I, TAYLOR A, MARINESCU A, et al. Residential demand response: experimental evaluation and comparison of self-organizing techniques[J]. Renewable & Sustainable Energy Reviews, 2017, 80: 1528-1536.
[18] ABDULAAL A, MOGHADDASS R, ASFOUR S. Two-stage discrete-continuous multi-objective load optimization: an industrial consumer utility approach to demand response[J]. Applied Energy, 2017, 206: 206-221.
[19] YU Xiaobao, TAN Zhongfu, CHEN Kangting, et al. Dynamic game analysis of coal electricity market involving multi-interests[J]. Mathematical Problems in Engineering, 2016(49): 1-9.
[20] ARAGON-BRICENO C, ROSS A B, CAMARGO-VALERO M A. Evaluation and comparison of product yields and bio-methane potential in sewage digestate following hydro thermal treatment[J]. Applied Energy, 2017, 208: 1357-1369.