Fast Clearing Method for Inter-Provincial Medium- and Long-Term Power Transactions Considering Low Carbon Value and Uncertainty Characteristics of Green Power

LIU Chang, LIU Hongli, CHEN Hongfei, WEI Yang, LIU Xueyuan, CHEN Lipin, XU Ke, YU Juan

Electric Power Construction ›› 2026, Vol. 47 ›› Issue (1) : 166-177.

PDF(1712 KB)
PDF(1712 KB)
Electric Power Construction ›› 2026, Vol. 47 ›› Issue (1) : 166-177. DOI: 10.12204/j.issn.1000-7229.2026.01.013
Power Economics

Fast Clearing Method for Inter-Provincial Medium- and Long-Term Power Transactions Considering Low Carbon Value and Uncertainty Characteristics of Green Power

Author information +
History +

Abstract

[Objective] Building and improving the mid-long-term electricity market between provinces is one of the fundamental links in promoting the development of green electricity and implementing the “dual carbon” goals. However,the randomness of green power output affects the physical feasibility of medium- and long-term clearing schemes for inter-provincial electricity transactions,and the participation of large-scale green power increases the burden of solving the clearing model. This paper proposes a fast-clearing method for mid- to long-term inter-provincial electricity transactions that considers the low-carbon value and stochastic characteristics of green electricity to improve the feasibility of clearing schemes and the efficiency of clearing calculations. [Methods] This paper constructs an inter-provincial electricity mid- to long-term transaction-clearing model that considers the low-carbon value and stochastic characteristics of green electricity. The objective function includes the cost of carbon emissions from power generation and the non-executable electricity penalty established based on the distribution characteristics of green electricity output,enabling clean and low-carbon green electricity to gain an advantage in market competition and improve the enforceability of green electricity-winning bids. Subsequently,an acceleration strategy based on fixed transaction variables is proposed. Based on the calculation results of the period decoupling model,transaction variables with a high probability of not closing are fixed,thereby constructing a smaller-scale clearing model and improving the efficiency of the clearing calculation. [Conclusions] Simulation examples based on actual transaction data from China show that the proposed model can balance the feasibility of the green electricity winning bid quantity and winning bid electricity. In addition,the proposed acceleration strategy can improve the computational efficiency by an average of 1.91 times while ensuring feasibility and accuracy (with an average relative error of only 0.4% compared with the optimal solution in multiple examples). [Conclusions] This translation accurately reflects the technical meaning and structure of the original Chinese sentence while being fluent and appropriate for an academic context.

Key words

inter-provincial medium and long-term power transactions / randomness of green power / non executable electricity / clearing acceleration

Cite this article

Download Citations
LIU Chang , LIU Hongli , CHEN Hongfei , et al . Fast Clearing Method for Inter-Provincial Medium- and Long-Term Power Transactions Considering Low Carbon Value and Uncertainty Characteristics of Green Power[J]. Electric Power Construction. 2026, 47(1): 166-177 https://doi.org/10.12204/j.issn.1000-7229.2026.01.013

References

[1]
国家发展改革委国家能源局关于完善能源绿色低碳转型体制机制和政策措施的意见[EB/OL]. (2022-02-11) [2024-06-25]. https://www.yidaiyilu.gov.cn/p/221685.html.
[2]
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.
[3]
周明, 严宇, 丁琪, 等. 国外典型电力市场交易结算机制及对中国的启示[J]. 电力系统自动化, 2017, 41(20): 1-8, 150.
ZHOU Ming, YAN Yu, DING Qi, et al. Transaction and settlement mechanism for foreign representative power markets and its enlightenment for Chinese power market[J]. Automation of Electric Power Systems, 2017, 41(20): 1-8, 150.
[4]
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(暂行)》的通知[EB/OL]. (2017-01-12) [2024-06-25]. https://www.gov.cn/xinwen/2017-01/12/content_5159156.htm.
[5]
程海花, 杨辰星, 刘硕, 等. 基于路径组合计及ATC的省间中长期交易优化出清和系统研发[J]. 电网技术, 2022, 46(12): 4762-4774.
CHENG Haihua, YANG Chenxing, LIU Shuo, et al. Optimization clearing and system development of inter-provincial medium and long term trade considering ATC base on path combination[J]. Power System Technology, 2022, 46(12): 4762-4774.
[6]
刘丽, 叶钰童, 王宝, 等. 面向省间电力现货市场的购电博弈竞价模型[J]. 浙江电力, 2024, 43(7): 111-119.
LIU Li, YE Yutong, WANG Bao, et al. A game bidding model for electricity purchasing tailored to inter-provincial electricity spot market[J]. Zhejiang Electric Power, 2024, 43(7): 111-119.
[7]
陆雯, 王舒颦, 章丽娜, 等. 考虑现货市场价格不确定性的市场化用户中长期合同电量曲线分解策略[J]. 浙江电力, 2024, 43(7): 120-128.
LU Wen, WANG Shupin, ZHANG Lina, et al. A curve decomposition strategy for medium-to-long term contract energy of market-based customers considering price uncertainty in spot market[J]. Zhejiang Electric Power, 2024, 43(7): 120-128.
[8]
杨玉强, 徐程炜, 邓晖. 碳市场与电力市场协同运行关键问题研究[J]. 浙江电力, 2023, 42(5): 66-75.
YANG Yuqiang, XU Chengwei, DENG Hui. A study of key issues in the coordinated operation between carbon market and electricity market[J]. Zhejiang Electric Power, 2023, 42(5): 66-75.
[9]
项中明, 曾凯乐, 杨承河, 等. 考虑受端电网保供风险的省间现货购电策略[J]. 浙江电力, 2024, 43(12): 15-27.
XIANG Zhongming, ZENG Kaile, YANG Chenghe, et al. An electricity purchasing strategy for interprovincial spot market considering the risk of power supply security in the receiving-end grid[J]. Zhejiang Electric Power, 2024, 43(12): 15-27.
[10]
陈景文, 单茜, 刘耀先, 等. 面向电力市场的用户侧电力电量预测综述[J]. 电网与清洁能源, 2024, 40(2): 10-20.
CHEN Jingwen, SHAN Xi, LIU Yaoxian, et al. A review of user-side power and energy forecasting for electricity market[J]. Power System and Clean Energy, 2024, 40(2): 10-20.
[11]
宋永华, 包铭磊, 丁一, 等. 新电改下我国电力现货市场建设关键要点综述及相关建议[J]. 中国电机工程学报, 2020, 40(10): 3172-3187.
SONG Yonghua, BAO Minglei, DING Yi, et al. Review of Chinese electricity spot market key issues and its suggestions under the new round of Chinese power system reform[J]. Proceedings of the CSEE, 2020, 40(10): 3172-3187.
[12]
樊宇琦, 丁涛, 孙瑜歌, 等. 国内外促进可再生能源消纳的电力现货市场发展综述与思考[J]. 中国电机工程学报, 2021, 41(5): 1729-1752.
FAN Yuqi, DING Tao, SUN Yuge, et al. Review and cogitation for worldwide spot market development to promote renewable energy accommodation[J]. Proceedings of the CSEE, 2021, 41(5): 1729-1752.
[13]
舒征宇, 朱凯翔, 王灿, 等. 考虑碳交易的虚拟电厂日前电力市场竞价策略[J]. 电力工程技术, 2024, 43(5): 58-68, 149.
SHU Zhengyu, ZHU Kaixiang, WANG Can, et al. Virtual power plants participating in day-ahead electricity market bidding strategy considering carbon trading[J]. Electric Power Engineering Technology, 2024, 43(5): 58-68, 149.
[14]
赵晋泉, 吴天娇, 林孙奔, 等. 两种第三方主体参与的现货市场出清模式比较[J]. 电力工程技术, 2023, 42(6): 241-248.
ZHAO Jinquan, WU Tianjiao, LIN Sunben, et al. Comparison of two market clearing modes for day-ahead power market incorporating third-party entity[J]. Electric Power Engineering Technology, 2023, 42(6): 241-248.
[15]
周竞, 耿建, 唐律, 等. 可调节负荷资源参与电力辅助服务市场规则分析与思考[J]. 电力自动化设备, 2022, 42(7): 120-127.
ZHOU Jing, GENG Jian, TANG , et al. Rule analysis and cogitation for adjustable load resources participating in ancillary service market[J]. Electric Power Automation Equipment, 2022, 42(7): 120-127.
[16]
WU Z, ZENG P L, ZHANG X P, et al. A solution to the chance-constrained two-stage stochastic program for unit commitment with wind energy integration[J]. IEEE Transactions on Power Systems, 2016, 31(6): 4185-4196.
[17]
李志伟, 赵书强, 刘金山. 基于相关机会目标规划的电力系统优化调度研究[J]. 中国电机工程学报, 2019, 39(10): 2803-2816.
LI Zhiwei, ZHAO Shuqiang, LIU Jinshan. Optimal scheduling of power system based on dependent-chance goal programming[J]. Proceedings of the CSEE, 2019, 39(10): 2803-2816.
[18]
季峰, 蔡兴国, 岳彩国. 含风电场电力系统的模糊鲁棒优化调度[J]. 中国电机工程学报, 2014, 34(28): 4791-4798.
JI Feng, CAI Xingguo, YUE Caiguo. Fuzzy robust dispatch for power systems with wind farms[J]. Proceedings of the CSEE, 2014, 34(28): 4791-4798.
[19]
AL-AWAMI A T, AMLEH N A, MUQBEL A M. Optimal demand response bidding and pricing mechanism with fuzzy optimization: application for a virtual power plant[J]. IEEE Transactions on Industry Applications, 2017, 53(5): 5051-5061.
[20]
CATALAO J P S, POUSINHO H M I, MENDES V M F. Optimal offering strategies for wind power producers considering uncertainty and risk[J]. IEEE Systems Journal, 2012, 6(2): 270-277.
[21]
ZHAO C Y, GUAN Y P. Unified stochastic and robust unit commitment[J]. IEEE Transactions on Power Systems, 2013, 28(3): 3353-3361.
[22]
陈建华, 吴文传, 张伯明, 等. 安全性与经济性协调的鲁棒区间风电调度方法[J]. 中国电机工程学报, 2014, 34(7): 1033-1040.
CHEN Jianhua, WU Wenchuan, ZHANG Boming, et al. A robust interval wind power dispatch method considering the tradeoff between security and economy[J]. Proceedings of the CSEE, 2014, 34(7): 1033-1040.
[23]
滕越, 赵骞, 袁铁江, 等. 绿电-氢能-多域应用耦合网络关键技术现状及展望[J]. 发电技术, 2023, 44(3): 318-330.
Abstract
氢能作为一种绿色、零碳的二次能源,是能源转型发展的重要载体之一,已成为能源互联的重要媒介。可再生能源电解水制氢是未来制氢的主要途径,将促进能源结构调整与转型。然而我国氢能技术研发和产业应用尚处于初始阶段,氢能制备、储运、转换和应用产业链的各环节存在大量问题有待解决。分析了绿电制氢技术、氢气储运技术、氢能应用技术的发展现状,研究了绿电-氢能-多域应用典型场景和网络耦合集成关键技术,可为氢能制、储、用技术的结合和多域应用网络发展提供参考思路。
TENG Yue, ZHAO Qian, YUAN Tiejiang, et al. Key technology status and outlook for green electricity-hydrogen energy-multi-domain applications coupled network[J]. Power Generation Technology, 2023, 44(3): 318-330.

As a green and zero-carbon secondary energy, hydrogen is one of the key carriers for the development of energy transition and has become an important medium for energy interconnection. Hydrogen production by electrolytic decomposition of water is the main way to produce hydrogen in the future, which will promote the adjustment and transformation of energy structure. However, the development and industrial application of hydrogen energy technology in China is still at the initial stage. In addition, there are a lot of problems to be solved in the aspects of hydrogen energy production, storage and transportation, conversion and application industry chain. This paper analyzed the development status of green power hydrogen production technology, hydrogen storage and transportation technology, hydrogen application technology, and studied the typical scenarios of green electricity-hydrogen energy-multi-domain application and the key technologies of network coupling and integration. This work provides indicative ideas for the combination of hydrogen energy production, storage and application technology, and the development of application network in various areas.

[24]
赵懿雯, 温家兴, 陈斐, 等. 可再生能源配额制下电力市场发电主体决策优化模型[J]. 电网与清洁能源, 2024, 40(1): 150-155, 162.
ZHAO Yiwen, WEN Jiaxing, CHEN Fei, et al. Optimization model of power generation subject decision-making in electricity market under renewable energy quota system[J]. Power System and Clean Energy, 2024, 40(1): 150-155, 162.
[25]
张恒基, 王海宁, 袁明珠, 等. 中国电力中长期市场交易机制分析与建议[J]. 电力系统自动化, 2024, 48(11): 11-23.
ZHANG Hengji, WANG Haining, YUAN Mingzhu, et al. Analysis and suggestions on trading mechanism of China’s medium-and long-term electricity market[J]. Automation of Electric Power Systems, 2024, 48(11): 11-23.
[26]
许彦平, 黄越辉, 李湃, 等. 计及优先级及电力平衡的新能源中长期交易电量分解方法[J]. 电力系统自动化, 2021, 45(17): 117-125.
XU Yanping, HUANG Yuehui, LI Pai, et al. Decomposition method for medium-and long-term trading electricity of renewable energy considering priority and power balance[J]. Automation of Electric Power Systems, 2021, 45(17): 117-125.
[27]
刘凌杰, 林济铿. 考虑风电不确定性的短期合同电量协同分解优化模型及算法[J]. 中国电力, 2023, 56(12): 227-237.
LIU Lingjie, LIN Jikeng. Model and algorithm of cooperative optimization decomposition for short-term contract electricity considering wind power uncertainty[J]. Electric Power, 2023, 56(12): 227-237.
[28]
MOLZAHN D K. Identifying redundant flow limits on parallel lines[J]. IEEE Transactions on Power Systems, 2018, 33(3): 3210-3212.
[29]
NIKOLOPOULOU E I, MANOUSSAKIS G E, ANDROULAKIS G S. Locating binding constraints in LP problems[J]. American Journal of Operations Research, 2019, 9(2): 59-78.
[30]
付聪, 王砚平, 刘俊磊, 等. 基于辅助优化问题的安全约束机组组合约束削减方法[J]. 电力系统保护与控制, 2021, 49(21): 9-17.
FU Cong, WANG Yanping, LIU Junlei, et al. Constraint reduction method for security-constrained unit commitment based on an auxiliary optimization problem[J]. Power System Protection and Control, 2021, 49(21): 9-17.
[31]
朱正春, 杨知方, 余娟, 等. 面向小样本场景的数据驱动安全约束经济调度快速计算方法[J]. 中国电机工程学报, 2022, 42(12): 4430-4440.
ZHU Zhengchun, YANG Zhifang, YU Juan, et al. A data-driven fast calculation method for security-constrained economic dispatch with small sample requirements[J]. Proceedings of the CSEE, 2022, 42(12): 4430-4440.
[32]
MEUS J, PONCELET K, DELARUE E. Applicability of a clustered unit commitment model in power system modeling[J]. IEEE Transactions on Power Systems, 2018, 33(2): 2195-2204.
[33]
李林威, 林伟, 杨知方, 等. 考虑多时段耦合特性的联络线功率可行域确定方法[J]. 电力系统保护与控制, 2020, 48(23): 64-72.
LI Linwei, LIN Wei, YANG Zhifang, et al. Characterizing a Tie-line transfer capacity region considering time coupling in day-ahead multi-period dispatch[J]. Power System Protection and Control, 2020, 48(23): 64-72.
[34]
TEJADA-ARANGO D A, WOGRIN S, CENTENO E. Representation of storage operations in network-constrained optimization models for medium- and long-term operation[J]. IEEE Transactions on Power Systems, 2018, 33(1): 386-396.
[35]
汪洋, 夏清, 康重庆. 机组组合算法中起作用整数变量的辨识方法[J]. 中国电机工程学报, 2010, 30(13): 46-52.
WANG Yang, XIA Qing, KANG Chongqing. Identification of the active integer variables in security constrained unit commitment[J]. Proceedings of the CSEE, 2010, 30(13): 46-52.
[36]
OUYANG Z, SHAHIDEHPOUR S M. An intelligent dynamic programming for unit commitment application[J]. IEEE Transactions on Power Systems, 1991, 6(3): 1203-1209.
[37]
WANG Y, XIA Q, CHENG Y, et al. Unit commitment based on identification method for valid optimization space[J]. International Journal of Power and Energy Systems, 2010, 30(4): 274.
[38]
陈泓霏, 向明旭, 杨知方, 等. 大规模省间电力中长期交易出清的伴随模型引导加速方法[J]. 中国电机工程学报, 2024, 45(13): 4992-5004.
CHEN Hongfei, XIANG Mingxu, YANG Zhifang, et al. Adjoint model-guided acceleration method for clearing large-scale inter-provincial long-term electricity transactions[J]. Proceedings of the CSEE, 2024, 45(13): 4992-5004.
[39]
赵书强, 胡利宁, 田捷夫, 等. 基于中长期风电光伏预测的多能源电力系统合约电量分解模型[J]. 电力自动化设备, 2019, 39(11): 13-19.
ZHAO Shuqiang, HU Lining, TIAN Jiefu, et al. Contract power decomposition model of multi-energy power system based on mid-long term wind power and photovoltaic electricity forecasting[J]. Electric Power Automation Equipment, 2019, 39(11): 13-19.
[40]
生态环境部、国家统计局关于发布2021年电力二氧化碳排放因子的公告[EB/OL]. (2024-04-13) [2024-06-25]. https://m.thepaper.cn/baijiahao_27019338.
[41]
第一财经研究院. 中国碳市场年报2022年&2023年[R]. 上海: 第一财经研究院, 2024.

Funding

Science and Technology Project of State Grid Sichuan Electric Power Company(52199722002N)
National Natural Science Foundation of China(52307082)
PDF(1712 KB)

Accesses

Citation

Detail

Sections
Recommended

/