新型电力系统与综合能源

基于碳排放流模型的分布式产消者点对点电-碳交易机制

  • 詹博淳 ,
  • 冯昌森 ,
  • 王晓晖 ,
  • 张恒 ,
  • 马军伟 ,
  • 文福拴
展开
  • 1.浙江大学 电气工程学院,杭州 310027
    2.浙江工业大学 信息工程学院,杭州 310023
    3.国网经济技术研究院有限公司,北京 102200
    4.国网山西省电力有限公司信息通信公司,太原 030001
詹博淳(1999—),硕士生,从事电力市场、区块链技术在电力系统中的应用研究.
文福拴,教授,博士生导师,电话(Tel.):0571-87951542;E-mail:wenfs@hotmail.com.

收稿日期: 2023-04-17

  修回日期: 2023-07-13

  录用日期: 2023-07-14

  网络出版日期: 2023-07-27

基金资助

国家自然科学基金资助项目(U1910216);国家电网有限公司科技项目资助(SGSXXT00JFJS2250157)

A P2P Electricity-Carbon Trading Mechanism for Distributed Prosumers Based on Carbon Emission Flow Model

  • ZHAN Bochun ,
  • FENG Changsen ,
  • WANG Xiaohui ,
  • ZHANG Heng ,
  • MA Junwei ,
  • WEN Fushuan
Expand
  • 1. College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China
    2. College of Information Engineering, Zhejiang University of Technology, Hangzhou 310023, China
    3. State Grid Economic and Technical Research Institute Co., Ltd., Beijing 102200, China
    4. Information and Telecommunication Company, State Grid Shanxi Electric Power Co., Ltd., Taiyuan 030001, China

Received date: 2023-04-17

  Revised date: 2023-07-13

  Accepted date: 2023-07-14

  Online published: 2023-07-27

摘要

针对配电系统层面设计分布式交易机制时,需要考虑产消者间的双边碳交易.提出一种考虑电能交易碳足迹的点对点(P2P)电-碳交易机制.首先,分析储能装置的碳排放特性,建立考虑储能装置的碳排放流模型.其次,建立基于碳排放流模型的产消者P2P电-碳交易模型,基于 Benders 分解法将原问题分解为网络约束主问题和产消者优化调度松弛子问题,采用分布式求解方法确定产消者最优P2P电-碳交易量,以保护产消者隐私.然后,建立基于纳什议价模型的产消者P2P电-碳交易结算模型,依据产消者在电-碳交易中的贡献度分配合作收益.最后,以改进的IEEE 33节点配电系统为例对所提交易模型进行验证,仿真结果表明所提机制可在保证配电网络安全运行的前提下,有效促进需求侧碳减排,并公平地分配产消者合作收益.

本文引用格式

詹博淳 , 冯昌森 , 王晓晖 , 张恒 , 马军伟 , 文福拴 . 基于碳排放流模型的分布式产消者点对点电-碳交易机制[J]. 上海交通大学学报, 2024 , 58(12) : 1846 -1856 . DOI: 10.16183/j.cnki.jsjtu.2023.139

Abstract

It is necessary to consider the carbon emission trading between prosumers when designing a distributed transaction mechanism in a distribution system. In this paper, a peer-to-peer (P2P) electricity-carbon transaction mechanism considering the carbon footprint of electricity trading is established. First, the carbon emission characteristic of energy storage system is analyzed, and a carbon emission flow model considering energy storage system is established. Next, a P2P electricity-carbon transaction model based on the carbon emission flow model is established. Based on the improved Benders decomposition method, the original problem is decomposed into the main problem considering network constraints and the subproblem of optimal scheduling for prosumers. Through distributed solutions, the optimal P2P electricity-carbon trading amount of prosumers is solved to protect the privacy of prosumers. Then, a P2P electricity-carbon trading settlement model based on the Nash bargaining model is established, and the cooperation benefit is distributed according to the contribution of prosumers in the electricity-carbon transaction. Finally, the effectiveness of the proposed model is validated by case studies on the improved IEEE 33-bus distribution system. The proposed model can not only ensure the secure operation of the distribution system, but also promote the reduction of demand-side carbon emission and fairly distribute the benefit among cooperative prosumers.

参考文献

[1] 中华人民共和国国家能源局. 能源碳达峰碳中和标准化提升行动计划[EB/OL]. (2022-10-09)[2023-04-05]. http://www.nea.gov.cn/2022-10/09/c_1310668927.htm.
  National Energy Administration of the People’s Republic of China. Action plan for energy carbon peaking and carbon neutrality standardization improvement[EB/OL]. (2022-10-09)[2023-04-05]. http://www.nea.gov.cn/2022-10/09/c_1310668927.htm.
[2] 秦博宇, 周星月, 丁涛, 等. 全球碳市场发展现状综述及中国碳市场建设展望[J]. 电力系统自动化, 2022, 46(21): 186-199.
  QIN Boyu, ZHOU Xingyue, DING Tao, et al. Review on development of global carbon market and prospect of China’s carbon market construction[J]. Automation of Electric Power Systems, 2022, 46(21): 186-199.
[3] CAO Z W, ZHOU X, HU H, et al. Toward a systematic survey for carbon neutral data centers[J]. IEEE Communications Surveys & Tutorials, 2022, 24(2): 895-936.
[4] 王健, 周念成, 王强钢, 等. 基于区块链和连续双向拍卖机制的微电网直接交易模式及策略[J]. 中国电机工程学报, 2018, 38(17): 5072-5084.
  WANG Jian, ZHOU Niancheng, WANG Qianggang, et al. Electricity direct transaction mode and strategy in microgrid based on blockchain and continuous double auction mechanism[J]. Proceedings of the CSEE, 2018, 38(17): 5072-5084.
[5] 高红均, 张凡, 刘俊勇, 等. 考虑多产消者差异化特征的社区微网系统P2P交易机制设计[J]. 中国电机工程学报, 2022, 42(4): 1455-1470.
  GAO Hongjun, ZHANG Fan, LIU Junyong, et al. Design of P2P transaction mechanism considering differentiation characteristics of multiple prosumers in community microgrid system[J]. Proceedings of the CSEE, 2022, 42(4): 1455-1470.
[6] 刘连光, 潘明明, 田世明, 等. 考虑源网荷多元主体的售电竞争非合作博弈方法[J]. 中国电机工程学报, 2017, 37(6): 1618-1626.
  LIU Lianguang, PAN Mingming, TIAN Shiming, et al. A non-cooperative game analysis of an competitive electricity retail considering multiple subjects of source-grid-load[J]. Proceedings of the CSEE, 2017, 37(6): 1618-1626.
[7] CUI S C, WANG Y W, SHI Y, et al. A new and fair peer-to-peer energy sharing framework for energy buildings[J]. IEEE Transactions on Smart Grid, 2020, 11(5): 3817-3826.
[8] MORSTYN T, TEYTELBOYM A, MCCULLOCH M D. Bilateral contract networks for peer-to-peer energy trading[J]. IEEE Transactions on Smart Grid, 2019, 10(2): 2026-2035.
[9] KIM J, DVORKIN Y. A P2P-dominant distribution system architecture[J]. IEEE Transactions on Power Systems, 2020, 35(4): 2716-2725.
[10] WANG B X, DUAN M S. Consignment auctions of emissions trading systems: An agent-based approach based on China’s practice[J]. Energy Economics, 2022, 112: 106187.
[11] YANG Y X, XU X. Production and carbon emission abatement decisions under different carbon policies: Supply chain network equilibrium models with consumers’ low-carbon awareness[J]. International Transactions in Operational Research, 2024, 31(4): 2734-2764.
[12] FENG F, DU X, SI Q, et al. Hybrid game optimization of microgrid cluster (MC) based on service provider (SP) and tiered carbon price[J]. Energies, 2022, 15(14): 5291.
[13] KANG C Q, ZHOU T R, CHEN Q X, et al. Carbon emission flow from generation to demand: A network-based model[J]. IEEE Transactions on Smart Grid, 2015, 6(5): 2386-2394.
[14] YAN Z Y, ZHOU T, ZHANG H, et al. Real-time carbon flow algorithm of electrical power systems based on network power decomposition[C]// 2021 IEEE Conference on Telecommunications, Optics and Computer Science. Shenyang, China: IEEE, 2021: 467-470.
[15] CHENG Y H, ZHANG N, WANG Y, et al. Modeling carbon emission flow in multiple energy systems[J]. IEEE Transactions on Smart Grid, 2019, 10(4): 3562-3574.
[16] WANG Y Q, QIU J, TAO Y C, et al. Carbon-oriented operational planning in coupled electricity and emission trading markets[J]. IEEE Transactions on Power Systems, 2020, 35(4): 3145-3157.
[17] POURAKBARI-KASMAEI M, LEHTONEN M, CONTRERAS J, et al. Carbon footprint management: A pathway toward smart emission abatement[J]. IEEE Transactions on Industrial Informatics, 2020, 16(2): 935-948.
[18] NAN J P, FENG J R, DENG X, et al. Hierarchical low-carbon economic dispatch with source-load bilateral carbon-trading based on aumann-shapley method[J]. Energies, 2022, 15(15): 5359.
[19] 赵伟, 熊正勇, 潘艳, 等. 计及碳排放流的电力系统低碳规划[J]. 电力系统自动化, 2023, 47(9): 23-33.
  ZHAO Wei, XIONG Zhengyong, PAN Yan, et al. Low-carbon planning of power system considering carbon emission flow[J]. Automation of Electric Power Systems, 2023, 47(9): 23-33.
[20] 张笑演, 王橹裕, 黄蕾, 等. 考虑扩展碳排放流和碳交易议价模型的园区综合能源优化调度[J]. 电力系统自动化, 2023, 47(9): 34-46.
  ZHANG Xiaoyan, WANG Luyu, HUANG Lei, et al. Optimal dispatching of park-level integrated energy system considering augmented carbon emission flow and carbon trading bargain model[J]. Automation of Electric Power Systems, 2023, 47(9): 34-46.
[21] RAHMANIANI R, AHMED S, CRAINIC T G, et al. The benders dual decomposition method[J]. Operations Research, 2020, 68(3): 878-895.
[22] ZOU J K, AHMED S, SUN X A. Stochastic dual dynamic integer programming[J]. Mathematical Programming, 2019, 175(1): 461-502.
[23] IRIA J, COELHO A, SOARES F. Network-secure bidding strategy for aggregators under uncertainty[J]. Sustainable Energy, Grids & Networks, 2022, 30: 100666.
[24] LU S, GU W, ZHANG C, et al. Hydraulic-thermal cooperative optimization of integrated energy systems: A convex optimization approach[J]. IEEE Transactions on Smart Grid, 2020, 11(6): 4818-4832.
[25] LI G G, LI Q Q, YANG X, et al. General Nash bargaining based direct P2P energy trading among prosumers under multiple uncertainties[J]. International Journal of Electrical Power & Energy Systems, 2022, 143: 108403.
[26] SI F Y, HAN Y H, XU Q Q, et al. Cloud-edge-based we-market: Autonomous bidding and peer-to-peer energy sharing among prosumers[J]. Journal of Modern Power Systems & Clean Energy, 2023, 11(4): 1282-1293.
文章导航

/