电能量和旋转备用市场下电-热综合能源系统低碳优化运行

doi:10.16183/j.cnki.jsjtu.2021.297

上海交通大学学报 ›› 2021, Vol. 55 ›› Issue (12): 1650-1662.doi: 10.16183/j.cnki.jsjtu.2021.297

所属专题：《上海交通大学学报》2021年“电气工程”专题；《上海交通大学学报》2021年12期专题汇总专辑

电能量和旋转备用市场下电-热综合能源系统低碳优化运行

江婷¹, 邓晖²^,³, 陆承宇²^,³, 王旭¹(), 蒋传文¹, 龚开¹

1.上海交通大学电力传输与功率变换控制教育部重点实验室,上海 200240
2.国网浙江省电力有限公司电力科学研究院,杭州 310014
3.国网浙江省电力有限公司电力市场仿真实验室,杭州 310014

收稿日期:2021-08-12 出版日期:2021-12-28 发布日期:2021-12-30
通讯作者: 王旭 E-mail:wangxu1989@sjtu.edu.cn
作者简介:江婷(1998-),女,湖北省黄石市人,硕士生,主要从事电力市场和电力系统优化运行研究.
基金资助:
国网浙江省电力有限公司科技资助项目(5211DS200089)

Low-Carbon Optimal Operation of an Integrated Electricity-Heat Energy System in Electric Energy and Spinning Reserve Market

JIANG Ting¹, DENG Hui²^,³, LU Chengyu²^,³, WANG Xu¹(), JIANG Chuanwen¹, GONG Kai¹

1. Key Laboratory of Control of Power Transmission and Conversion of the Ministry of Education, Shanghai Jiao Tong University, Shanghai 200240, China
2. Electric Power Research Institute, State Grid Zhejiang Electric Power Supply Co., Ltd., Hangzhou 310014, China
3. State Grid Zhejiang Electricity Market Simulation Laboratory, State Grid Zhejiang Electric Power Supply Co., Ltd., Hangzhou 310014, China

Received:2021-08-12 Online:2021-12-28 Published:2021-12-30
Contact: WANG Xu E-mail:wangxu1989@sjtu.edu.cn

摘要/Abstract

摘要：

建立电-热综合能源系统,同时参与电能量市场和旋转备用市场的日前优化决策模型,并将阶梯式碳交易引入该模型中.模型采用条件风险价值方法对新能源和电负荷不确定性风险进行管理,以电-热综合能源系统运营方案成本和碳排放成本最低为目标函数,制定运行计划和安排备用资源.算例分析表明,该模型通过发挥综合能源系统多能互补优势和合理安排备用资源应对不确定性因素引发的风险,提高了能源供应的可靠性、经济性和低碳性.

关键词: 电能量市场, 旋转备用市场, 储能, 风险规避, 低碳优化运行

Abstract:

A day-ahead optimal decision-making model is established for an integrated electricity-heat energy system to participate in both the electric energy market and the spinning reserve market, and the step-by-step carbon trading is introduced into the proposed model. The conditional value at risk method is used to manage the uncertainty risk of renewable energy and electrical load. With the objective to minimize the operation scheme cost and carbon emission cost, an operation plan is developed and the reserve resources are arranged for the integrated electricity-heat energy system. The results of a case study show that the proposed model improves the reliability, economy, and low-carbon level by taking the complementary advantages of the integrated energy system and reasonably arranging reserve resources to deal with the risks caused by uncertain factors.

Key words: electric energy market, spinning reserve market, energy storage, risk aversion, low-carbon optimal operation

中图分类号:

TM732

江婷, 邓晖, 陆承宇, 王旭, 蒋传文, 龚开. 电能量和旋转备用市场下电-热综合能源系统低碳优化运行[J]. 上海交通大学学报, 2021, 55(12): 1650-1662.

JIANG Ting, DENG Hui, LU Chengyu, WANG Xu, JIANG Chuanwen, GONG Kai. Low-Carbon Optimal Operation of an Integrated Electricity-Heat Energy System in Electric Energy and Spinning Reserve Market[J]. Journal of Shanghai Jiao Tong University, 2021, 55(12): 1650-1662.

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参考文献 25

[1]	青岛全搜索电子报. 推进能源消费供给技术体制革命[EB/OL].(2019-10-23) [2020-05-01]. http://wb.qdqss.cn/html/qdrb/20191023/qdrb410269.html.
	Qingdao Full Search Electronic Newspaper. Promoting the technological system revolution of energy consumption and supply[EB/OL]. (2019-10-23) [2020-05-01]. http://wb.qdqss.cn/html/qdrb/20191023/qdrb410269.html.
[2]	人民网. 全球碳排放权交易市场建设不断加快(国际视点)[EB/OL].(2021-04-23) [2020-05-01]. http://sh.people.com.cn/n2/2021/0423/c138654-34690929.html.
	People’s Daily Online. The construction of global carbon emission trading market is accelerating (International perspective)[EB/OL].(2021-04-23) [2020-05-01]. http://sh.people.com.cn/n2/2021/0423/c138654-34690929.html.
[3]	中国政府网. 习近平:中国承诺实现从碳达峰到碳中和的时间, 远远短于发达国家所用时间[EB/OL].(2021-04-22) [2020-05-01]. http://www.gov.cn/xinwen/2021-04/22/content_5601515.htm.
	Chinese Government Website. President Xi Jinping: China has committed to move from carbon peak to carbon neutrality in a much shorter time span than what might take many developed countries[EB/OL].(2021-04-22) [2020-05-01]. http://www.gov.cn/xinwen/2021-04/22/content_5601515.htm.
[4]	肖云鹏, 王锡凡, 王秀丽, 等. 多能源市场耦合交易研究综述及展望[J]. 全球能源互联网, 2020, 3(5):487-496.
	XIAO Yunpeng, WANG Xifan, WANG Xiuli, et al. Review and prospects of coupled transactions in multi-carrier energy systems[J]. Journal of Global Energy Interconnection, 2020, 3(5):487-496.
[5]	崔杨, 曾鹏, 仲悟之, 等. 考虑阶梯式碳交易的电-气-热综合能源系统低碳经济调度[J]. 电力自动化设备, 2021, 41(3):10-17.
	CUI Yang, ZENG Peng, ZHONG Wuzhi, et al. Low-carbon economic dispatch of electricity-gas-heat integrated energy system based on ladder-type carbon trading[J]. Electric Power Automation Equipment, 2021, 41(3):10-17.
[6]	王文学, 胡伟, 孙国强, 等. 电-热互联综合能源系统区间潮流计算方法[J]. 电网技术, 2019, 43(1):83-95.
	WANG Wenxue, HU Wei, SUN Guoqiang, et al. Interval energy flow calculation method of integrated electro-thermal system[J]. Power System Technology, 2019, 43(1):83-95.
[7]	CHEN H H, ZHANG T, ZHANG R F, et al. Interval optimal scheduling of integrated electricity and district heating systems considering dynamic characteristics of heating network[J]. IET Energy Systems Integration, 2020, 2(3):179-186. doi: 10.1049/iet-esi.2019.0046 URL
[8]	郑豪丰, 杨国华, 潘欢, 等. 考虑区域供热系统及不确定性因素的综合能源系统日前调度[J]. 电力系统及其自动化学报, 2020, 32(8):83-90.
	ZHENG Haofeng, YANG Guohua, PAN Huan, et al. Day-ahead scheduling of integrated energy system considering districted heating system and uncertain factors[J]. Proceedings of the CSU-EPSA, 2020, 32(8):83-90.
[9]	郑超铭, 黄博南, 王子心, 等. 计及网络传输损耗的电热综合能源系统多目标优化调度[J]. 电网技术, 2020, 44(1):141-154.
	ZHENG Chaoming, HUANG Bonan, WANG Zixin, et al. Multi-objective optimization dispatch for integrated electro-heating systems including network transmission losses[J]. Power System Technology, 2020, 44(1):141-154.
[10]	ZHANG N, HU Z G, DAI D H, et al. Unit commitment model in smart grid environment considering carbon emissions trading[J]. IEEE Transactions on Smart Grid, 2016, 7(1):420-427. doi: 10.1109/TSG.2015.2401337 URL
[11]	张晓辉, 董兴华. 含风电场多目标低碳电力系统动态经济调度研究[J]. 电网技术, 2013, 37(1):24-31.
	ZHANG Xiaohui, DONG Xinghua. Research on multi-objective scheduling for low-carbon power system with wind farms[J]. Power System Technology, 2013, 37(1):24-31.
[12]	张晓辉, 闫柯柯, 卢志刚, 等. 基于场景概率的含风电系统多目标低碳经济调度[J]. 电网技术, 2014, 38(7):1835-1841.
	ZHANG Xiaohui, YAN Keke, LU Zhigang, et al. Scenario probability based multi-objective optimized low-carbon economic dispatching for power grid integrated with wind farms[J]. Power System Technology, 2014, 38(7):1835-1841.
[13]	胡静哲, 王旭, 蒋传文, 等. 计及综合能源服务商参与的电力系统低碳经济调度[J]. 电网技术, 2020, 44(2):514-522.
	HU Jingzhe, WANG Xu, JIANG Chuanwen, et al. Low-carbon economic dispatch of power system considering participation of integrated energy service providers[J]. Power System Technology, 2020, 44(2):514-522.
[14]	黄伟, 葛良军, 华亮亮, 等. 参与双重市场的区域综合能源系统日前优化调度[J]. 电力系统自动化, 2019, 43(12):68-75.
	HUANG Wei, GE Liangjun, HUA Liangliang, et al. Day-ahead optimal scheduling of regional integrated energy system participating in dual market[J]. Automation of Electric Power Systems, 2019, 43(12):68-75.
[15]	张晓辉, 闫柯柯, 卢志刚, 等. 基于碳交易的含风电系统低碳经济调度[J]. 电网技术, 2013, 37(10):2697-2704.
	ZHANG Xiaohui, YAN Keke, LU Zhigang, et al. Carbon trading based low-carbon economic dispatching for power grid integrated with wind power system[J]. Power System Technology, 2013, 37(10):2697-2704.
[16]	卫志农, 张思德, 孙国强, 等. 基于碳交易机制的电—气互联综合能源系统低碳经济运行[J]. 电力系统自动化, 2016, 40(15):9-16.
	WEI Zhinong, ZHANG Side, SUN Guoqiang, et al. Carbon trading based low-carbon economic operation for integrated electricity and natural gas energy system[J]. Automation of Electric Power Systems, 2016, 40(15):9-16.
[17]	秦婷, 刘怀东, 王锦桥, 等. 基于碳交易的电—热—气综合能源系统低碳经济调度[J]. 电力系统自动化, 2018, 42(14):8-13.
	QIN Ting, LIU Huaidong, WANG Jinqiao, et al. Carbon trading based low-carbon economic dispatch for integrated electricity-heat-gas energy system[J]. Automation of Electric Power Systems, 2018, 42(14):8-13.
[18]	孙国强, 周亦洲, 卫志农, 等. 能量和旋转备用市场下虚拟电厂热电联合调度鲁棒优化模型[J]. 中国电机工程学报, 2017, 37(11):3118-3128.
	SUN Guoqiang, ZHOU Yizhou, WEI Zhinong, et al. Thermal and electrical scheduling of a virtual power plant for participating in energy and spinning reserve markets based on robust optimization[J]. Proceedings of the CSEE, 2017, 37(11):3118-3128.
[19]	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 Zhaoyuan, ZHOU Ming, YAO Shangrun, 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.
[20]	邓婷婷. 考虑源荷双端灵活性的电力系统优化调度研究[D]. 武汉: 华中科技大学, 2019.
	DENG Tingting. Optimal dispatch of power system considering the flexibility of demand side and power generation side[D]. Wuhan: Huazhong University of Science and Technology, 2019.
[21]	PARVANIA M, FOTUHI-FIRUZABAD M. Demand response scheduling by stochastic SCUC[J]. IEEE Transactions on Smart Grid, 2010, 1(1):89-98. doi: 10.1109/TSG.2010.2046430 URL
[22]	李鹏, 吴迪凡, 李雨薇, 等. 基于综合需求响应和主从博弈的多微网综合能源系统优化调度策略[J]. 中国电机工程学报, 2021, 41(4):1307-1321.
	LI Peng, WU Difan, LI Yuwei, et al. Optimal dispatch of multi-microgrids integrated energy system based on integrated demand response and stackelberg game[J]. Proceedings of the CSEE, 2021, 41(4):1307-1321.
[23]	张津珲, 王旭, 蒋传文, 等. 新型城镇下含热电联产机组的配电网两阶段鲁棒优化调度[J]. 电力系统自动化, 2019, 43(23):155-163.
	ZHANG Jinhui, WANG Xu, JIANG Chuanwen, et al. Two-stage robust optimization scheduling of distribution network with combined heat and power units in new-type towns[J]. Automation of Electric Power Systems, 2019, 43(23):155-163.
[24]	SHI L, LUO Y, TU G Y. Bidding strategy of microgrid with consideration of uncertainty for participating in power market[J]. International Journal of Electrical Power & Energy Systems, 2014, 59:1-13. doi: 10.1016/j.ijepes.2014.01.033 URL
[25]	冉晓洪, 周任军, 李湘华, 等. 计及等排性能系数的冷热电多联供环境经济调度[J]. 电力自动化设备, 2013, 33(9):94-99.
	RAN Xiaohong, ZHOU Renjun, LI Xianghua, et al. Environmental economic dispatch considering equal emission performance coefficient for CCHP[J]. Electric Power Automation Equipment, 2013, 33(9):94-99.

模型编号	电能量市场收益/欧元	旋转备用市场收益/ 欧元	MT和 FC成本/ 欧元	CHP机组成本/ 欧元	锅炉成本/ 欧元	储能成本/ 欧元	DR成本/ 欧元	碳交易成本/欧元	碳排放量/t	CVaR/ 欧元	总收益/ 欧元
1	-4242.77	120983.34	5734.82	2697.99	1947.66	1004.55	976.41	909.56	918.33	—	99230.48
2	-5951.53	120947.99	4301.35	2706.44	1746.37	991.92	976.52	188.71	857.61	—	99712.72
3	-4935.42	120713.24	6000.63	2650.66	2040.06	991.98	944.67	930.4	923.61	42748.05	124511.26
4	-6546.11	121121.77	5184.85	2631.99	1945.57	1077.63	954.65	202.21	881.69	39123.7	127679.36

电能量和旋转备用市场下电-热综合能源系统低碳优化运行

Low-Carbon Optimal Operation of an Integrated Electricity-Heat Energy System in Electric Energy and Spinning Reserve Market

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