计及联络线容量备用预留的跨省区能量-备用联合优化出清方法

doi:10.19595/j.cnki.1000-6753.tces.250399

Abstract
Figure/Table
References
Related Citation (15)

Download: PDF (2312 KB) HTML (1 KB)
Export: BibTeX | EndNote (RIS)

Abstract The development of inter-provincial electricity markets enables optimal inter-provincial allocation of electricity resources and promotes complementary resource utilization across provinces. Currently, China's inter-provincial electricity markets mainly focus on energy trading. However, with the rapid growth of cross-regional renewable energy accommodation demands, inter-provincial reserve trading has attracted increasing attention. The critical challenge lies in addressing transmission line capacity reservation under uncertain dispatch scenarios. This paper proposes an energy-reserve co-optimization clearing method incorporating tie-line capacity reservation for inter-provincial markets. By constructing reserve transaction pairs, the paper explicitly quantifies the correlation between reserve transactions and transmission capacity, establish linearized constraint models, achieving coordinated optimization of inter-provincial energy and reserves while ensuring deliverability of cleared reserves.
First, the paper mathematically characterizes intra-regional and inter-provincial reserve trading, highlighting their differences. Then, we analyze limitations of existing transmission capacity reservation methods M1 and M2 in handling inter-provincial reserve transactions. To address the deficiency in explicitly characterizing the relationship between reserve transaction and transmission capacity, the paper proposes a reserve transaction pair-based framework that maps responsibility relationships between reserve supply and demand nodes. By constructing transfer distribution factor matrices for reserve dispatch, the paper quantifies the incremental impact of reserve transactions on transmission power flows. Two dispatch modes - “M3, arbitrary dispatch” and “M4, rational dispatch” - are designed, corresponding respectively to strict security boundaries and economically optimal boundaries for capacity reservation. The linearized transmission constraints are then embedded into unit commitment and economic dispatch co-optimization model.
Simulation results demonstrate that: Among methods M1~M4, M1 is unable to recognize the spatial value of reserve resources, relying solely on marginal costs, making it difficult to ensure the deliverability of reserve. While M2 establishes a preliminary linkage between reserve transactions and transmission capacity, it fails to explicitly characterize this relationship, leaving network security vulnerable during intermediate reserve dispatch states. The proposed M3 and M4 methods quantify the correlation between reserve transaction and transmission capacity, fully reflecting spatial value differences of reserves, enabling reasonable capacity allocation and ensuring cleared reserve deliverability. Specifically, M3 adopts “arbitrary dispatch” mode corresponding to security boundaries, while M4 employs “rational dispatch” mode for economic boundaries.
The following conclusions can be drawn from the simulation analysis: (1) Compared with existing methods, the proposed approaches better evaluate spatial value of reserve resources and ensures deliverability in inter-provincial markets. (2) Establishing the correlation between reserve transaction and transmission capacity enables rational transmission capacity allocation. (3) The proposed method preserves linearized constraints, ensure model's computational efficiency.

Key words： Electricity market inter-provincial transactions co-optimization transmission capacity reservation deliverability of reserve

Received: 12 March 2025

PACS:

TM732

	Service

	E-mail this article
	Add to my bookshelf
	Add to citation manager
	E-mail Alert
	RSS
	Articles by authors
	Yang Fuwang
	Yang Zhifang

Cite this article:

Yang Fuwang,Yang Zhifang. Inter-Provincial Energy-Reserve Co-Optimization Clearing Method Considering Tie-Line Capacity Reservation for Reserve[J]. Transactions of China Electrotechnical Society, 2026, 41(5): 1450-1465.

URL:

https://dgjsxb.ces-transaction.com/EN/10.19595/j.cnki.1000-6753.tces.250399 OR https://dgjsxb.ces-transaction.com/EN/Y2026/V41/I5/1450

[1] 张智刚, 康重庆. 碳中和目标下构建新型电力系统的挑战与展望[J]. 中国电机工程学报, 2022, 42(8): 2806-2819.
Zhang Zhigang, Kang Chongqing.Challenges and prospects for constructing the new-type power system towards a carbon neutrality future[J]. Proceedings of the CSEE, 2022, 42(8): 2806-2819.
[2] 中电联发布2024-2025年度全国电力供需形势分析预测报告[EB/OL]. (2025-01-24)[2025-03-06]. https://cec.org.cn/detail/index.html?3-341403.
[3] 张振宇, 王文倬, 王智伟, 等. 跨区直流外送模式对新能源消纳的影响分析及应用[J]. 电力系统自动化, 2019, 43(11): 174-180.
Zhang Zhenyu, Wang Wenzhuo, Wang Zhiwei, et al.Impact analysis and application of cross-region HVDC delivery mode in renewable energy accommodation[J]. Automation of Electric Power Systems, 2019, 43(11): 174-180.
[4] 《全国统一电力市场发展规划蓝皮书》编写组. 全国统一电力市场发展规划蓝皮书[M]. 北京: 中国电力出版社, 2024.
[5] 国家发展改革委, 国家能源局. 关于加快建设全国统一电力市场体系的指导意见[EB/OL]. (2022-01-18) [2025-03-05]. https://www.gov.cn/zhengce/zhengceku/2022-01/30/content_5671296.htm.
[6] 国家发展改革委, 国家能源局. 关于印发《电力中长期交易基本规则》的通知[EB/OL]. (2020-06-10) [2025-03-05]. https://www.gov.cn/gongbao/content/2020/content_5532632.htm.
[7] 王轶辰. 省间现货市场正式运行——我国电力体制改革再上新台阶[N]. 经济日报, 2024-10-17(3).
[8] 舒康安, 张昌, 艾小猛, 等. 基于分段电价的跨区风电消纳[J]. 电工技术学报, 2017, 32(增刊1): 39-49.
Shu Kang'an, Zhang Chang, Ai Xiaomeng, et al.Wind power accommodation based on block price[J]. Transactions of China Electrotechnical Society, 2017, 32(S1): 39-49.
[9] 王怡, 杨知方, 余娟, 等. 从优化视角剖析电力市场的定价问题[J]. 电工技术学报, 2023, 38(17): 4729-4745.
Wang Yi, Yang Zhifang, Yu Juan, et al.Analyzing pricing problem in electricity market from an optimization perspective[J]. Transactions of China Electrotechnical Society, 2023, 38(17): 4729-4745.
[10] 冯艺萱, 边晓燕, 陈雯, 等. 新型电力系统灵活性资源成本回收机制分析及挑战[J]. 电工技术学报, 2025, 40(21): 7013-7028.
Feng Yixuan, Bian Xiaoyan, Chen Wen, et al.Analysis and challenges of new power system flexibility resource cost recovery mechanisms[J]. Transactions of China Electrotechnical Society, 2025, 40(21): 7013-7028.
[11] 林雪杉, 张汀荟, 王蓓蓓. 高渗透率分布式发电并网下公共配电网市场化收费的思考[J]. 电工技术学报, 2023, 38(19): 5256-5273.
Lin Xueshan, Zhang Tinghui, Wang Beibei.Review of distribution network tariff design with high-penetration of distributed generation[J]. Transactions of China Electrotechnical Society, 2023, 38(19): 5256-5273.
[12] NWPP Reserve Sharing Program. Northwest power pool reserve sharing program documentation[R/OL]. (2025-07-11)[2025-07-30].https://www.westernpowerpool.org/private-media/documents/NWPP_RSG_Program_Doc_-_RSGC_Approved_effective_7.1.2025.pdf.
[13] European Network of Transmission System Operators for Electricity. MARI activation optimization function public description[R/OL]. (2022-04-21)[2025-03-05]. https://eepublicdownloads.blob.core.windows.net/public-cdn-container/clean-documents/Network%20codes%20documents/NC%20EB/2022/MARI_AOF_PublicDocumentation.pdf.
[14] 李竹, 庞博, 李国栋, 等. 欧洲统一电力市场建设及对中国电力市场模式的启示[J]. 电力系统自动化, 2017, 41(24): 2-9.
Li Zhu, Pang Bo, Li Guodong, et al.Development of unified European electricity market and its implications for China[J]. Automation of Electric Power Systems, 2017, 41(24): 2-9.
[15] Gomez T, Herrero I, Rodilla P, et al.European union electricity markets: current practice and future view[J]. IEEE Power and Energy Magazine, 2019, 17(1): 20-31.
[16] 国家能源局综合司. 电力辅助服务市场基本规则(征求意见稿)[EB/OL]. (2024-10-08)[2025-03-05]. https://zfxxgk.nea.gov.cn/2024-10/08/c_1212404033.htm.
[17] Domínguez R, Oggioni G, Smeers Y.Reserve procurement and flexibility services in power systems with high renewable capacity: effects of integration on different market designs[J]. International Journal of Electrical Power & Energy Systems, 2019, 113: 1014-1034.
[18] Van den Bergh K, Delarue E. Energy and reserve markets: interdependency in electricity systems with a high share of renewables[J]. Electric Power Systems Research, 2020, 189: 106537.
[19] Gebrekiros Y, Doorman G, Jaehnert S, et al.Reserve procurement and transmission capacity reservation in the Northern European power market[J]. International Journal of Electrical Power & Energy Systems, 2015, 67: 546-559.
[20] Van den Bergh K, Bruninx K, Delarue E. Cross-border reserve markets: network constraints in cross-border reserve procurement[J]. Energy Policy, 2018, 113: 193-205.
[21] Chen Yonghong, Gribik P, Gardner J.Incorporating post zonal reserve deployment transmission constraints into energy and ancillary service co-optimization[J]. IEEE Transactions on Power Systems, 2014, 29(2): 537-549.
[22] Wang Fengyu, Hedman K W.Dynamic reserve zones for day-ahead unit commitment with renewable resources[J]. IEEE Transactions on Power Systems, 2015, 30(2): 612-620.
[23] Lyon J D, Wang Fengyu, Hedman K W, et al.Market implications and pricing of dynamic reserve policies for systems with renewables[J]. IEEE Transactions on Power Systems, 2015, 30(3): 1593-1602.
[24] 马子明, 钟海旺, 李竹, 等. 美国电力市场信息披露体系及其对中国的启示[J]. 电力系统自动化, 2017, 41(24): 49-57.
Ma Ziming, Zhong Haiwang, Li Zhu, et al.Information disclosure system in American electricity market and its enlightenment for China[J]. Automation of Electric Power Systems, 2017, 41(24): 49-57.
[25] CAISO. Intertie constraint and branch group information full network model reference document [R/OL]. (2024-07-01)[2025-03-05]. https://www.caiso.com/documents/intertie-constraint-and-branch-group-information-full-network-model-reference-document-07-2024.pdf.
[26] CAISO. Business practice manual for managing full network model[R/OL]. (2024-09-12)[2025-03-05]. https://bpmcm.caiso.com/BPM%20Document%20Library/Managing%20Full%20Network%20Model/Managing%20Full%20Network%20Model%20BPM%20Version%2026_redline.pdf.
[27] Knörr J, Bichler M, Dobos T. Zonal vs. Nodal pricing: an analysis of different pricing rules in the German day-ahead market[J/OL]. ArXiv, 2024: 2403.09265. https://doi.org/10.48550/arXiv.2403.09265.
[28] 陈启鑫, 张维静, 滕飞, 等. 欧洲跨国电力市场的输电机制与耦合方式[J]. 全球能源互联网, 2020, 3(5): 423-429.
Chen Qixin, Zhang Weijing, Teng Fei, et al.Transmission mechanisms and coupling approaches in European transnational electricity markets[J]. Journal of Global Energy Interconnection, 2020, 3(5): 423-429.
[29] 陈熠, 王晗, 严正, 等. 全国统一电力市场演进过程下省间-省内市场出清及定价模型[J]. 电工技术学报, 2024, 39(7): 2116-2131.
Chen Yi, Wang Han, Yan Zheng, et al.Inter-and intra-provincial electricity market clearing and pricing model under the evolution of national unified electricity market[J]. Transactions of China Electrotechnical Society, 2024, 39(7): 2116-2131.
[30] 蔡帜, 丁强, 崔晖, 等. 区域电网的分省备用容量留取方案(二): 优化模型[J]. 中国电机工程学报, 2023, 43(3): 1037-1048.
Cai Zhi, Ding Qiang, Cui Hui, et al.Configuration scheme of provincial reserve capacity in regional power grid (part Ⅱ): optimization model[J]. Proceedings of the CSEE, 2023, 43(3): 1037-1048.
[31] 刘硕, 张梦晗, 夏清, 等. 基于备用辅助服务需求申报的现货市场机制设计[J]. 电力系统自动化, 2022, 46(22): 72-82.
Liu Shuo, Zhang Menghan, Xia Qing, et al.Design of spot market mechanism based on demand bidding of reserve ancillary service[J]. Automation of Electric Power Systems, 2022, 46(22): 72-82.