Review and prospect of P2P energy trading market mechanism and strategy optimization

Jiehui ZHENG, Zhiyan XU, Zhigang LI, Yuanzheng LI, Wenhu TANG, Zhaoxia JING

Electric Power ›› 2026, Vol. 59 ›› Issue (8) : 163-178.

Home Journals Electric Power
Electric Power

Abbreviation (ISO4): Electric Power      Chairperson: Changyu OUYANG

About  /  Aim & scope  /  Editorial board  /  Indexed  /  Contact  / 
Electric Power ›› 2026, Vol. 59 ›› Issue (8) : 163-178. DOI: 10.11930/j.issn.1004-9649.202606065
Original article

Review and prospect of P2P energy trading market mechanism and strategy optimization

Author information +
History +

Abstract

Peer-to-peer(P2P)energy trading can encourage prosumers to carry out local energy trading,and guide user- side resources including distributed energy resources(DERs), energy storage,electric vehicles(EVs)and flexible loads to participate in supply-demand balancing through market-based price signals,thereby boosting the local consumption rate of renewable energy.To accurately identify the core research priorities of P2P energy trading,this paper first elaborates its system architecture,operational logic and basic characteristics. Second,it reviews the existing market mechanisms and their applicable scenarios from the perspectives of market organization models,pricing,market clearing and settlement mechanisms.Third,it summarizes state-of-the-art research on strategy optimization approaches for P2P energy trading, covering mathematical optimization,game theory,distributed optimization,reinforcement learning and other methodologies. Finally,the paper outlines future development directions of P2P energy trading targeting critical challenges such as physical constraints of distribution networks,large-scale agent coor- dination,privacy protection,trusted trading and engineering demonstrations.The work is expected to provide references for market-oriented trading of user-side distributed resources and the operation of new distribution systems.

Key words

peer-to-peer energy trading / distributed energy resources / market mechanism / strategy optimization / engineering demonstration

Cite this article

Download Citations
Jiehui ZHENG , Zhiyan XU , Zhigang LI , et al . Review and prospect of P2P energy trading market mechanism and strategy optimization[J]. Electric Power. 2026, 59(8): 163-178 https://doi.org/10.11930/j.issn.1004-9649.202606065

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:发改能源〔2022〕206号[Z]. 2022.
[2]
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:发改体改〔2022〕118号[Z]. 2022.
[3]
晏鸣宇, 王玲玲, 滕飞, 等. 面向分布式能源的可交易能源市场研究综述与展望[J]. 电力系统自动化, 2023, 47(18):33-48.
YAN Mingyu, WANG Lingling, TENG Fei, et al. Review and prospect of transactive energy market for distributed energy resources[J]. Automation of Electric Power Systems, 2023, 47(18): 33-48.
[4]
冯昌森, 谢方锐, 胡嘉骅, 等. 配电系统中点对点电力交易市场设计与出清方法[J]. 电力系统自动化, 2022, 46(9):11-20.
FENG Changsen, XIE Fangrui, HU Jiahua, et al. Market design and clearing method for peer-to-peer power trading in distribution system[J]. Automation of Electric Power Systems, 2022, 46(9): 11-20.
[5]
ZHOU Y, WU J Z, LONG C, et al. State-of-the-art analysis and perspectives for peer-to-peer energy trading[J]. Engineering, 2020, 6(7):739-753.
[6]
王鲁浩, 张淑芳, 张凯, 等. 计及 P2P 电力交易不确定性的微网群区间联盟形成博弈[J]. 电力系统保护与控制, 2025, 53(18): 109-119.
WANG Luhao, ZHANG Shufang, ZHANG Kai, et al. Interval coalition formation game for microgrid clusters considering P2P power trading uncertainty[J]. Power System Protection and Control, 2025, 53(18):109-119.
[7]
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.
[8]
荆江平, 李晨, 孙勇, 等. 基于点对点交易与储能循环寿命约束的多微网综合能源系统能量共享优化[J]. 电力信息与通信技术, 2024, 22(9):8-17.
JING Jiangping, LI Chen, SUN Yong, et al. Optimization of energy sharing in multi-microgrid integrated energy systems based on peer-to-peer trading and energy storage cycle life constraints[J]. Electric Power Information and Communication Technology, 2024, 22(9):8-17.
[9]
MORSTYN T, FARRELL N, DARBY S J, et al. Using peer-to-peer energy-trading platforms to incentivize prosumers to form federated power plants[J]. Nature Energy, 2018, 3(2):94-101.
[10]
ZHANG C H, WU J Z, ZHOU Y, et al. Peer-to-peer energy trading in a microgrid[J]. Applied Energy, 2018, 220(C):1-12.
[11]
周玮, 党伟, 芝昕雨, 等. 基于灵活性资源调节和网络重构的P2P 交易的阻塞管理方法[J]. 电力系统保护与控制, 2024, 52(20):83-93.
ZHOU Wei, DANG Wei, ZHI Xinyu, et al. A congestion management approach for P2P transactions based on flexible resource regulation and network reconfiguration[J]. Power System Protection and Control, 2024, 52(20):83-93.
[12]
周任军, 彭鑫, 黄婧杰, 等. 考虑供需关系电价及其时段划分的点对点电能交易方法[J]. 电力科学与技术学报, 2025, 40(6):271-280.
ZHOU Renjun, PENG Xin, HUANG Jingjie, et al. Peer-to-peer electricity trading method considering supply-demand relationship tariffs and tariff time period division[J]. Journal of Electric Power Science and Technology, 2025, 40(6):271-280.
[13]
SORIN E, BOBO L, PINSON P. Consensus-based approach to peer-to-peer electricity markets with product differentiation[J]. IEEE Transactions on Power Systems, 2019, 34(2):994-1004.
[14]
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.
[15]
KIM H J, CHUNG Y S, KIM S J, et al. Pricing mechanisms for peer-to-peer energy trading:Towards an integrated understanding of energy and network service pricing mechanisms[J]. Renewable and Sustainable Energy Reviews, 2023, 183: 113435.
[16]
李刚, 赵琳颖, 关雪, 等. 基于博弈策略的能源区块链安全交易机制[J]. 电力建设, 2021, 42(12):127-135.
LI Gang, ZHAO Linying, GUAN Xue, et al. Security transaction mechanism of energy blockchain applying game strategy[J]. Electric Power Construction, 2021, 42(12):127-135.
[17]
PAUDEL A, CHAUDHARI K, LONG C, et al. Peer-to-peer energy trading in a prosumer-based community microgrid:a game-theoretic model[J]. IEEE Transactions on Industrial Electronics, 2019, 66(8): 6087-6097.
[18]
WEI C, SHEN Z Z, XIAO D L, et al. An optimal scheduling strategy for peer-to-peer trading in interconnected microgrids based on RO and Nash bargaining[J]. Applied Energy, 2021, 295: 117024.
[19]
KHORASANY M, MISHRA Y, LEDWICH G. A decentralized bilateral energy trading system for peer-to-peer electricity markets[J]. IEEE Transactions on Industrial Electronics, 2020, 67(6):4646-4657.
[20]
YE Y J, TANG Y, WANG H Y, et al. A scalable privacy-preserving multi-agent deep reinforcement learning approach for large-scale peer-to-peer transactive energy trading[J]. IEEE Transactions on Smart Grid, 2021, 12(6):5185-5200.
[21]
ZHENG J H, LIANG Z T, LI Y Z, et al. Multi-agent reinforcement learning with privacy preservation for continuous double auction-based P2P energy trading[J]. IEEE Transactions on Industrial Informatics, 2024, 20(4):6582-6590.
[22]
QIU D W, WANG J H, DONG Z H, et al. Mean-field multi-agent reinforcement learning for peer-to-peer multi-energy trading[J]. IEEE Transactions on Power Systems, 2023, 38(5):4853-4866.
[23]
GUERRERO J, CHAPMAN A C, VERBIČ G. Decentralized P2P energy trading under network constraints in a low-voltage network[J]. IEEE Transactions on Smart Grid, 2019, 10(5):5163-5173.
[24]
PAUDEL A, SAMPATH L P M I, YANG J W, et al. Peer-to-peer energy trading in smart grid considering power losses and network fees[J]. IEEE Transactions on Smart Grid, 2020, 11(6):4727-4737.
[25]
YAN M Y, SHAHIDEHPOUR M, PAASO A, et al. Distribution network-constrained optimization of peer-to-peer transactive energy trading among multi-microgrids[J]. IEEE Transactions on Smart Grid, 2021, 12(2):1033-1047.
[26]
WANG B B, XU L, WANG J L. A privacy-preserving trading strategy for blockchain-based P2P electricity transactions[J]. Applied Energy, 2023, 335( C).
[27]
WANG S, TAHA A F, WANG J H, et al. Energy crowdsourcing and peer-to-peer energy trading in blockchain-enabled smart grids[J]. IEEE Transactions on Systems,Man,and Cybernetics:Systems, 2019, 49(8):1612-1623.
[28]
SOUSA T, SOARES T, PINSON P, et al. Peer-to-peer and community-based markets:a comprehensive review[J]. Renewable and Sustainable Energy Reviews, 2019, 104:367-378.
[29]
MEHDINEJAD M, SHAYANFAR H, MOHAMMADI-IVATLOO B. Peer-to-peer decentralized energy trading framework for retailers and prosumers[J]. Applied Energy, 2022, 308: 118310.
[30]
HUANG C Y, ZHANG M Z, WANG C M, et al. An interactive two-stage retail electricity market for microgrids with peer-to-peer flexibility trading[J]. Applied Energy, 2022, 320: 119085.
[31]
单俊嘉, 董子明, 胡俊杰, 等. 基于区块链技术的产消者 P2P 电能智能交易合约[J]. 电网技术, 2021, 45(10):3830-3839.
SHAN Junjia, DONG Ziming, HU Junjie, et al. P2P smart power trading contract based on blockchain technology[J]. Power System Technology, 2021, 45(10):3830-3839.
[32]
刘峰伟, 陈佳佳, 赵艳雷, 等. 端对端交易模式下基于移动储能共享的配电系统韧性提升[J]. 电力系统自动化, 2022, 46(16):151-159.
LIU Fengwei, CHEN Jiajia, ZHAO Yanlei, et al. Resilience enhancement for distribution system based on mobile energy storage sharing in peer-to-peer transaction mode[J]. Automation of Electric Power Systems, 2022, 46(16):151-159.
[33]
于娣, 胡健, 张晓杰, 等. 电力 P2P 交易中的双轮竞价博亦模型[J]. 电力建设, 2023, 44(7):21-32.
YU Di, HU Jian, ZHANG Xiaojie, et al. Double-round bidding game model for P2P electricity transactions[J]. Electric Power Construction, 2023, 44(7):21-32.
[34]
何帅, 刘念, 张泽坤, 等. 基于集合竞价拍卖的大规模多微网能量共享方法[J]. 电力建设, 2023, 44(8):128-141.
HE Shuai, LIU Nian, ZHANG Zekun, et al. Call auction mechanism-based energy sharing method for many multiple microgrids[J]. Electric Power Construction, 2023, 44(8):128-141.
[35]
伍宇铜, 刘洋, 许立雄, 等. 储能辅助下基于多重博亦的社区光伏用户电能交易模型[J]. 电力建设, 2024, 45(7):167-178.
WU Yutong, LIU Yang, XU Lixiong, et al. Energy trading model for community photovoltaic users based on multi-game theory with energy storage support[J]. Electric Power Construction, 2024, 45(7): 167-178.
[36]
JIA Y B, WAN C, YU P, et al. Security constrained P2P energy trading in distribution network:an integrated transaction and operation model[J]. IEEE Transactions on Smart Grid, 2022, 13(6): 4773-4786.
[37]
张虹, 闫贺, 申鑫, 等. 面向能源社区能量管理的配网产消者分布式优化调度[J]. 中国电机工程学报, 2022, 42(12):4449-4459.
ZHANG Hong, YAN He, SHEN Xin, et al. Distributed optimal scheduling for prosumer in distribution network for energy community energy management[J]. Proceedings of the CSEE, 2022, 42(12):4449-4459.
[38]
皇甫霄文, 李科, 许长清, 等. 计及多微网灵活性的端对端分散式交易策略[J]. 中国电力, 2025, 58(9):194-204, 218.
HUANGFU Xiaowen, LI Ke, XU Changqing, et al. Decentralized peer-to-peer trading strategy considering flexibility of multiple microgrids[J]. Electric Power, 2025, 58(9):194-204, 218.
[39]
赵鹏杰, 吴俊勇, 林凯骏, 等. 基于一致性算法的多微电网点对点分布式能量交易策略[J]. 电网技术, 2023, 47(1):205-216.
ZHAO Pengjie, WU Junyong, LIN Kaijun, et al. Peer to peer distributed transactive energy strategy for multi-microgrid based on consistency algorithm[J]. Power System Technology, 2023, 47(1): 205-216.
[40]
张书涵, 艾芊, 李晓露, 等. 适用于多虚拟电厂交易的改进拜占庭容错算法共识机制[J]. 中国电力, 2024, 57(1):71-81, 157.
ZHANG Shuhan, AI Qian, LI Xiaolu, et al. Improved PBFT consensus mechanism for multi-virtual power plant transactions[J]. Electric Power, 2024, 57(1):71-81, 157.
[41]
RUAN H B, GAO H J, GOOI H B, et al. Active distribution network operation management integrated with P2P trading[J]. Applied Energy, 2022, 323: 119632.
[42]
XU S, ZHAO Y, LI Y Z, et al. An iterative uniform-price auction mechanism for peer-to-peer energy trading in a community microgrid[J]. Applied Energy, 2021, 298: 117088.
[43]
HUTTY T D, BROWN S. P2P trading of heat and power via a continuous double auction[J]. Applied Energy, 2024, 369: 123556.
[44]
LIU Y B, ZUO K Y, LIU X A, et al. Dynamic pricing for decentralized energy trading in micro-grids[J]. Applied Energy, 2018, 228:689-699.
[45]
LEE W P, HAN D J, WON D. Grid-oriented coordination strategy of prosumers using game-theoretic peer-to-peer trading framework in energy community[J]. Applied Energy, 2022, 326: 119980.
[46]
KHODOOMI M, SAHEBI H. Robust optimization and pricing of peer-to-peer energy trading considering battery storage[J]. Computers &Industrial Engineering, 2023, 179: 109210.
[47]
TARASHANDEH N, KARIMI A. Peer-to-peer energy trading under distribution network constraints with preserving independent nature of agents[J]. Applied Energy, 2024, 355: 122240.
[48]
HOQUE M M, KHORASANY M, AZIM M I, et al. A framework for prosumer-centric peer-to-peer energy trading using network-secure export-import limits[J]. Applied Energy, 2024, 361: 122906.
[49]
ZARE A, MEHDINEJAD M, ABEDI M. Designing a decentralized peer-to-peer energy market for an active distribution network considering loss and transaction fee allocation,and fairness[J]. Applied Energy, 2024, 358: 122527.
[50]
ESMAT A, DE VOS M, GHIASSI-FARROKHFAL Y, et al. A novel decentralized platform for peer-to-peer energy trading market with blockchain technology[J]. Applied Energy, 2021, 282( PA).
[51]
ZHENG B S, WEI W, CHEN Y, et al. A peer-to-peer energy trading market embedded with residential shared energy storage units[J]. Applied Energy, 2022, 308: 118400.
[52]
LIU J, YANG H X, ZHOU Y K. Peer-to-peer trading optimizations on net-zero energy communities with energy storage of hydrogen and battery vehicles[J]. Applied Energy, 2021, 302: 117578.
[53]
SAMPATH L P M I, PAUDEL A, NGUYEN H D, et al. Peer-to-peer energy trading enabled optimal decentralized operation of smart distribution grids[J]. IEEE Transactions on Smart Grid, 2022, 13(1): 654-666.
[54]
DUKOVSKA I, SLOOTWEG J G H, PATERAKIS N G. Introducing user preferences for peer-to-peer electricity trading through stochastic multi-objective optimization[J]. Applied Energy, 2023, 338( C).
[55]
ZHANG X H, GE S Y, LIU H, et al. Distributionally robust optimization for peer-to-peer energy trading considering data-driven ambiguity sets[J]. Applied Energy, 2023, 331: 120436.
[56]
SUN Z X, LI Z G, XUE Y X, et al. Price-function-free energy pricing in bilevel peer-to-peer energy markets considering network security[J]. Applied Energy, 2025, 391: 125864.
[57]
LI J K, GE S Y, LIU H, et al. Domestic P2P energy market design considering network reconfiguration and usage fees:bi-level nonlinear programming and exact clearing algorithm[J]. Applied Energy, 2024, 368: 123039.
[58]
GAO H J, ZHANG F, XIANG Y M, et al. Bounded rationality based multi-VPP trading in local energy markets:a dynamic game approach with different trading targets[J]. CSEE Journal of Power and Energy Systems, 2023, 9(1):221-234.
[59]
TUSHAR W, SAHA T K, YUEN C, et al. A coalition formation game framework for peer-to-peer energy trading[J]. Applied Energy, 2020, 261: 114436.
[60]
XIA Y X, XU Q S, HUANG Y, et al. Preserving privacy in nested peer-to-peer energy trading in networked microgrids considering incomplete rationality[J]. IEEE Transactions on Smart Grid, 2023, 14(1):606-622.
[61]
YU X J, PAN D, ZHOU Y K. A Stackelberg game-based peer-to- peer energy trading market with energy management and pricing mechanism:a case study in Guangzhou[J]. Solar Energy, 2024, 270:112388.
[62]
LIU J H, LONG Q F, LIU R P, et al. Online distributed optimization for spatio-temporally constrained real-time peer-to-peer energy trading[J]. Applied Energy, 2023, 331: 120216.
[63]
AMINLOU A, MOHAMMADI-IVATLOO B, ZARE K, et al. Activating demand side flexibility market in a fully decentralized P2P transactive energy trading framework using ADMM algorithm[J]. Sustainable Cities and Society, 2024, 100: 105021.
[64]
CHANG X Y, XU Y L, GUO Q L, et al. A Byzantine-resilient distributed peer-to-peer energy management approach[J]. IEEE Transactions on Smart Grid, 2023, 14(1):623-634.
[65]
CHEN T Y, BU S R, LIU X, et al. Peer-to-peer energy trading and energy conversion in interconnected multi-energy microgrids using multi-agent deep reinforcement learning[J]. IEEE Transactions on Smart Grid, 2022, 13(1):715-727.
[66]
QIU D W, WANG J H, WANG J K, et al. Multi-agent reinforcement learning for automated peer-to-peer energy trading in double-side auction market[C]// Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence.Montreal,Canada.International Joint Conferences on Artificial Intelligence Organization, 2021: 2913-2920.
[67]
QIU D W, YE Y J, PAPADASKALOPOULOS D, et al. Scalable coordinated management of peer-to-peer energy trading:a multi- cluster deep reinforcement learning approach[J]. Applied Energy, 2021, 292: 116940.
[68]
SAMENDE C, CAO J, FAN Z. Multi-agent deep deterministic policy gradient algorithm for peer-to-peer energy trading considering distribution network constraints[J]. Applied Energy, 2022, 317: 119123.
[69]
PEREIRA H, GOMES L, VALE Z. Peer-to-peer energy trading optimization in energy communities using multi-agent deep reinforcement learning[J]. Energy Informatics, 2022, 5(4): 44.
[70]
CUI Y, XU Y, WANG Y J, et al. Peer-to-peer energy trading with energy trading consistency in interconnected multi-energy microgrids:a multi-agent deep reinforcement learning approach[J]. International Journal of Electrical Power&Energy Systems, 2024, 156: 109753.
[71]
FENG C, LIU A L. Peer-to-peer energy trading of solar and energy storage:a networked multiagent reinforcement learning approach[J]. Applied Energy, 2025, 383: 125283.
[72]
QIU D W, XUE J X, ZHANG T Q, et al. Federated reinforcement learning for smart building joint peer-to-peer energy and carbon allowance trading[J]. Applied Energy, 2023, 333: 120526.
[73]
International Renewable Energy Agency. Peer-to-peer electricity trading:Innovation Landscape Brief[R/OL].Abu Dhabi: International Renewable Energy Agency,2020[2026-05-13].
[74]
Housing Evolutions by Housing Europe. Quartierstrom-P2P Prosumer Energy Village[EB/OL].[2026-06-10].
[75]
Synergy. Community Battery Storage Trials[EB/OL].[2026-06-10].
[76]
Piclo. The Independent Marketplace for Energy Flexibility[EB/OL]. [2026-06-10].
[77]
Sonnen. Aus Wildpoldsried hinaus in die Welt[EB/OL].(2024-03)[2026-06-10].
[78]
Quartierstrom. Field test successfully completed[EB/OL]. 2020-02-07[2026-05-13].
[79]
Synergy. RENeW Nexus Plan peer-to-peer energy trading trial[EB/ OL].[2026-05-13].
[80]
Sonnen. All about sonnenVPP: our virtual power plant[EB/OL]. [2026-05-13].

Funding

National Natural Science Foundation of China(No.52477097),and Guangdong Basic and Applied Basic Research Foundation(2024A1515240034)

Accesses

Citation

Detail

Sections
Recommended

/