考虑碳交易量自适应决策的输电网两阶段鲁棒规划

doi:10.16183/j.cnki.jsjtu.2022.473

摘要/Abstract

摘要：

低碳化是新型电力系统未来发展趋势,在规划层面模拟水平年碳交易量对实现未来电网低碳经济运行具有重要作用.基于此,提出考虑碳交易量自适应决策的输电网鲁棒规划方法.首先,构建基于基准线法的碳配额交易成本计量方法,并考虑碳交易量约束,建立考虑风电和负荷不确定性的两阶段鲁棒规划模型.其次,利用松-紧解耦法将子问题按时间解耦为安全可行性检测子问题和低碳可行性检测子问题,并采用列和约束生成算法求解两阶段鲁棒规划模型,根据安全约束与碳配额交易量约束在各不确定场景下反馈的割信息,分析模型可行解空间与碳配额交易量阈值参数设置的映射关系,自适应决策碳交易量上下限.最后,以改进的IEEE-RTS 24节点系统进行算例仿真,分析低碳规划模型、碳配额交易量、碳价对规划结果的影响.结果表明所提模型实现了规划方案在经济性和低碳性方面的协同优化.

关键词: 鲁棒优化, 输电网, 碳交易, 碳配额, 时间解耦

Abstract:

Low carbon is the future development trend of new power system, and the simulation of horizontal annual carbon trading volume at the planning level plays an important role in realizing the low-carbon economic operation of future power grid. Based on this understanding, a robust planning method for transmission network considering adaptive decision-making of carbon trading volume is proposed. First, a measurement method of carbon quota trading cost based on the baseline method is constructed, and a two-stage robust programming model considering the uncertainty of wind power and load is established considering the constraint of carbon trading volume. Then, the relax-and-enforce decoupling method is used to decouple the sub-problem into security feasibility detection sub-problem and low carbon feasibility detection sub-problem according to time, and the two-stage robust programming model is solved by using the column and constraint generation algorithm. Based on the cut information feedback from the security constraint and the carbon quota trading volume constraint in each uncertain scenario, the mapping relationship between the feasible solution space of the model and the setting of the threshold parameter of carbon quota trading volume is analyzed, and the upper and lower limits of carbon trading volume are adaptively decided. Finally, the improved IEEE-RTS 24-node system is simulated to analyze the impacts of the low-carbon planning model, carbon quota trading volume, and carbon price on the planning results. The results show that the proposed model realizes the coordinated optimization of the planning scheme in terms of economy and low carbon.

Key words: robust optimization, transmission network, carbon trading, carbon quota, time decoupling

中图分类号:

TM715

蒋标, 刘佳, 曾平良, 唐早, 李亚楼. 考虑碳交易量自适应决策的输电网两阶段鲁棒规划[J]. 上海交通大学学报, 2024, 58(6): 826-835.

JIANG Biao, LIU Jia, ZENG Pingliang, TANG Zao, LI Yalou. Two-Stage Robust Planning for Transmission Network Considering Adaptive Decision of Carbon Trading Volume[J]. Journal of Shanghai Jiao Tong University, 2024, 58(6): 826-835.

图/表 9

图1

表1

图2

图3

图4

图5

图6

图7

图8

参考文献 26

[1]	习近平. 在第七十五届联合国大会一般性辩论上的讲话[EB/OL]. (2020-09-22)[2022-11-22]. https://baijiahao.baidu.com/s?id=1678546728556033497&wfr=spider&for=pc.
	XI Jinping. Speech at the general debate of the 75th session of United Nations General Assembly[EB/OL]. (2020-09-22)[2022-11-22]. https://baijiahao.baidu.com/s?id=1678546728556033497&wfr=spider&for=pc.
[2]	康重庆, 杜尔顺, 李姚旺, 等. 新型电力系统的“碳视角”: 科学问题与研究框架[J]. 电网技术, 2022, 46(3): 821-833.
	KANG Chongqing, DU Ershun, LI Yaowang, et al. Key scientific problems and research framework for carbon perspective research of new power systems[J]. Power System Technology, 2022, 46(3): 821-833.
[3]	DEHGHAN S, AMJADY N. Robust transmission and energy storage expansion planning in wind farm-integrated power systems considering transmission switching[J]. IEEE Transactions on Sustainable Energy, 2016, 7(2): 765-774.
[4]	樊金柱, 李华强, 刘万宇, 等. 考虑网源协同的输电网适应性扩展规划[J]. 电网技术, 2019, 43(9): 3360-3367.
	FAN Jinzhu, LI Huaqiang, LIU Wanyu, et al. Adaptability expansion planning of transmission grid considering grid-source coordination[J]. Power System Technology, 2019, 43(9): 3360-3367.
[5]	ZHANG X, CONEJO A J. Robust transmission expansion planning representing long-and short-term uncertainty[J]. IEEE Transactions on Power Systems, 2018, 33(2):1329-1338.
[6]	LIU J, TANG Z, ZENG P P, et al. Co-optimization of distribution system operation and transmission system planning: A decentralized stochastic solution[J]. Energy Reports, 2022, 8: 501-509.
[7]	ZHONG H W, ZHANG G L, TAN Z, et al. Hierarchical collaborative expansion planning for transmission and distribution networks considering transmission cost allocation[J]. Applied Energy, 2022, 307: 118147.
[8]	LIU J, TANG Z, ZENG P, et al. Distributed adaptive expansion approach for transmission and distribution networks incorporating source-contingency-load uncertainties[J]. International Journal of Electrical Power & Energy Systems, 2022, 136: 107711.
[9]	李玲芳, 陈占鹏, 胡炎, 等. 基于灵活性和经济性的可再生能源电力系统扩展规划[J]. 上海交通大学学报, 2021, 55(7): 791-801. doi: 10.16183/j.cnki.jsjtu.2020.024
	LI Lingfang, CHEN Zhanpeng, HU Yan, et al. Expansion planning of renewable energy power system considering flexibility and economy[J]. Journal of Shanghai Jiao Tong University, 2021, 55(7): 791-801.
[10]	WU Y W, LOU S H, LU S Y. A model for power system interconnection planning under low-carbon economy with CO₂ emission constraints[J]. IEEE Transactions on Sustainable Energy, 2011, 2(3): 205-214.
[11]	ZHONG J C, QI Y L, HAO X, et al. Power generation planning optimization model considering carbon emission[C]//2022 IEEE/IAS Industrial and Commercial Power System Asia. Shanghai, China: IEEE, 2022, 1050-1054.
[12]	WANG Z S, ZHAO T Q, XIA X, et al. Low carbon planning of power system based on stepped carbon tax considering thermal power support in the context of 3060[C]//2022 7th Asia Conference on Power and Electrical Engineering. Hangzhou, China: IEEE, 2022: 28-34.
[13]	HU Y, DING T, BIE Z H, et al. Integrated generation and transmission expansion planning with carbon capture operating constraints[C]//2016 IEEE Power and Energy Society General Meeting. Boston, USA: IEEE, 2016: 1-5.
[14]	周任军, 孙洪, 唐夏菲, 等. 双碳量约束下风电-碳捕集虚拟电厂低碳经济调度[J]. 中国电机工程学报, 2018, 38(6): 1675-1683.
	ZHOU Renjun, SUN Hong, TANG Xiafei, et al. Low-carbon economic dispatch based on virtual power plant made up of carbon capture unit and wind power under double carbon constraint[J]. Proceedings of the CSEE, 2018, 38(6): 1675-1683.
[15]	ZHANG R F, YAN K F, LI G Q, et al. Privacy-preserving decentralized power system economic dispatch considering carbon capture power plants and carbon emission trading scheme via over-relaxed ADMM[J]. International Journal of Electrical Power & Energy Systems, 2020, 121: 106094.
[16]	LU S Y, ZHOU B R, YAO W F, et al. Transmission network expansion planning towards a low-carbon economy with fuzzy modeling of wind generation[C]//2018 IEEE Power & Energy Society General Meeting. Portland, Oregon, USA: IEEE, 2018: 1-5.
[17]	吕齐, 李明轩, 魏韡, 等. 基于参数规划的含储能和风电电力系统低碳经济调度[J]. 电力自动化设备, 2023, 43(7): 12-18.
	LÜ Qi, LI Mingxuan, WEI Wei, et al. Low-carbon economic dispatch of power system with energy storage and wind power based on parametric program-ming[J]. Electric Power Automation Equipment, 2023, 43(7): 12-18.
[18]	刘哲远, 邢海军, 程浩忠, 等. 考虑碳排放流及需求响应的综合能源系统双层优化调度[J]. 高电压技术, 2023, 49(1): 169-178.
	LIU Zheyuan, XING Haijun, CHENG Haozhong, et al. Bi-level optimal scheduling of integrated energy system considering carbon emission flow and demand response[J]. High Voltage Engineering, 2023, 49(1): 169-178.
[19]	陈文溆乐, 向月, 彭光博, 等. “双碳”目标下电力系统供给侧形态发展系统动力学建模与分析[J]. 上海交通大学学报, 2021, 55(12): 1567-1576. doi: 10.16183/j.cnki.jsjtu.2021.294
	CHEN Wenxule, XIANG Yue, PENG Guangbo, et al. System dynamic modeling and analysis of power system supply side morphological development with dual carbon targets[J]. Journal of Shanghai Jiao Tong University, 2021, 55(12): 1567-1576.
[20]	YE H X, LI Z Y. Robust security-constrained unit commitment and dispatch with recourse cost requirement[J]. IEEE Transactions on Power Systems, 2016, 31(5): 3527-3536.
[21]	郭尊, 李庚银, 周明. 计及碳交易机制的电-气联合系统快速动态鲁棒优化运行[J]. 电网技术, 2020, 44(4): 1220-1228.
	GUO Zun, LI Gengyin, ZHOU Ming. Fast and dynamic robust optimization of integrated electricity-gas system operation with carbon tradin[J]. Power System Technology, 2020, 44(4): 1220-1228.
[22]	赵永斌, 丛建辉, 杨军, 等. 中国碳市场配额分配方法探索[J]. 资源科学, 2019, 41(5): 872-883. doi: 10.18402/resci.2019.05.05
	ZHAO Yongbin, CONG Jianhui, YANG Jun, et al. An innovative allowance allocation method in China’s unified national emissions trading scheme[J]. Resources Science, 2019, 41(5): 872-883. doi: 10.18402/resci.2019.05.05
[23]	中华人民共和国生态环境部. 2019—2020年全国碳排放权交易配额总量设定与分配实施方案(发电行业)[EB/OL]. (2020-12-30)[2022-11-22]. https://www.mee.gov.cn/xxgk2018/xxgk/xxgk03/202012/W020201230736907121045.pdf.
	Ministry of Ecology and Environment of the People’s Republic of China. Implementation plan for total quota setting and allocation of national carbon emission trading in 2019—2020 (power generation industry)[EB/OL]. (2020-12-30)[2022-11-22]. https://www.mee.gov.cn/xxgk2018/xxgk/xxgk03/202012/W020201230736907121045.pdf.
[24]	ZENG B, ZHAO L. Solving two-stage robust optimization problems using a column-and-constraint generation method[J]. Operations Research Letters, 2013, 41(5): 457-461.
[25]	GRIGG C, WONG P, ALBRECHT P, et al. The IEEE reliability test system-1996.A report prepared by the Reliability Test System Task Force of the Application of Probability Methods Subcommittee[J]. IEEE Transactions on Power Systems, 1999, 14(3): 1010-1020.
[26]	LIU J, CHENG H Z, ZENG P L, et al. Decentralized stochastic optimization based planning of integrated transmission and distribution networks with distributed generation penetration[J]. Applied Energy, 2018, 220: 800-813.

模型类别	线路规划方案	投资成本/ 万美元	机组运行成本 ×10^-6/美元	切负荷成本/ 万美元	碳交易成本/ 万美元	总成本 ×10^-6/美元
传统规划	1~2,1~5,6~10,7~8,14~16,21~22	1 391	360.55	166	2 366	399.78
低碳规划	1~5,6~10,7~8,14~16,21~22	1 359	363.44	216	1 717	396.36