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Frontiers in Energy

ISSN 2095-1701

ISSN 2095-1698(Online)

CN 11-6017/TK

Postal Subscription Code 80-972

2018 Impact Factor: 1.701

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Front. Energy    2023, Vol. 17 Issue (2) : 189-197    https://doi.org/10.1007/s11708-023-0873-9
PERSPECTIVE
P2P energy trading via public power networks: Practical challenges, emerging solutions, and the way forward
Yue ZHOU, Jianzhong WU(), Wei GAN
School of Engineering, Cardiff University, Cardiff CF24 3AA, Wales, UK
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Abstract

Peer-to-peer (P2P) energy trading is an emerging energy supply paradigm where customers with distributed energy resources (DERs) are allowed to directly trade and share electricity with each other. P2P energy trading can facilitate local power and energy balance, thus being a potential way to manage the rapidly increasing number of DERs in net zero transition. It is of great importance to explore P2P energy trading via public power networks, to which most DERs are connected. Despite the extensive research on P2P energy trading, there has been little large-scale commercial deployment in practice across the world. In this paper, the practical challenges of conducting P2P energy trading via public power networks are identified and presented, based on the analysis of a practical Local Virtual Private Networks (LVPNs) case in North Wales, UK. The ongoing efforts and emerging solutions to tackling the challenges are then summarized and critically reviewed. Finally, the way forward for facilitating P2P energy trading via public power networks is proposed.
Keywords distribution network      local virtual private network      network charges      peer-to-peer (P2P) energy trading      practical implementation.     
Corresponding Author(s): Jianzhong WU   
Online First Date: 17 May 2023    Issue Date: 29 May 2023
 Cite this article:   
Yue ZHOU,Jianzhong WU,Wei GAN. P2P energy trading via public power networks: Practical challenges, emerging solutions, and the way forward[J]. Front. Energy, 2023, 17(2): 189-197.
 URL:  
https://academic.hep.com.cn/fie/EN/10.1007/s11708-023-0873-9
https://academic.hep.com.cn/fie/EN/Y2023/V17/I2/189
Fig.1  Existing and potential sites of solar PV power plants of this case in North Wales.
Fig.2  Indicative electricity import and export prices in the county.
Category Method Function Advantage Disadvantage
Technology-oriented solutions Sensitivity analysis-based network permission [25] Tackle both voltage issues and line congestion Respect network operational constraints and reduce peak network demand for P2P energy trading Not able to address the problems brought by existing network charging regulations
Network constrained P2P energy trading [26]
Line flow constraints-embedded bilateral trading [27] Tackle line congestion
Market capacity-based congestion management [28]
Local information-based voltage management [29] Tackle voltage issues
Grid influenced peer-to-peer energy trading [30] Reduce peak network demand
Network-charing solutions Graph-based network loss allocation [31,32] Reflect and signal the network losses Provide the incentive for reducing network losses in P2P energy trading Network losses only account for a very small percentage of electricity bills
Current/power tracing-based network loss allocation [33,34]
Least-cost energy path optimisation [35]
Loss allocation with diminished cross-subsidisation [36]
Locational marginal pricing mechanisms [37–40] Reflect and signal all the major operational network issues including congestion and losses Provide accurate incentive for reducing network losses and congestion at the same time Require high-resolution real-time data exchange and do not reflect the network replacement and reinforcement costs
Exogenous network charging methods [41,42] Reflect and signal all the long-term and short-term network costs Simple, good scalability, able to reflect a wide range of costs, and not requiring high network digitalisation level Oversimplified so being difficult to provide highly reflective and accurate incentive
Tab.1  Summary and comparison of existing solutions on P2P energy trading through public power networks
1 C Zhang, J Wu, Y Zhou. et al.. Peer-to-peer energy trading in a microgrid. Applied Energy, 2018, 220: 1–12
https://doi.org/10.1016/j.apenergy.2018.03.010
2 Y Zhou, J Wu, C Long. Evaluation of peer-to-peer energy sharing mechanisms based on a multiagent simulation framework. Applied Energy, 2018, 222: 993–1022
https://doi.org/10.1016/j.apenergy.2018.02.089
3 T Morstyn, N Farrell, S J Darby. et al.. Using peer-to-peer energy-trading platforms to incentivize prosumers to form federated power plants. Nature Energy, 2018, 3(2): 94–101
https://doi.org/10.1038/s41560-017-0075-y
4 Y Zhou, J Wu, C Long. et al.. State-of-the-art analysis and perspectives for peer-to-peer energy trading. Engineering (Beijing), 2020, 6(7): 739–753
https://doi.org/10.1016/j.eng.2020.06.002
5 L F Cheng, Y Chen, G Y Liu. 2PnS-EG: A general two-population n-strategy evolutionary game for strategic long-term bidding in a deregulated market under different market clearing mechanisms. International Journal of Electrical Power & Energy Systems, 2022, 142(Part A): 108182
https://doi.org/10.1016/j.ijepes.2022.108182
6 Y Chen, W Wei, F Liu. et al.. Energy trading and market equilibrium in integrated heat-power distribution systems. IEEE Transactions on Smart Grid, 2019, 10(4): 4080–4094
https://doi.org/10.1109/TSG.2018.2849227
7 L F Cheng, T Yu. A new generation of AI: A review and perspective on machine learning technologies applied to smart energy and electric power systems. International Journal of Energy Research, 2019, 43(6): 1928–1973
https://doi.org/10.1002/er.4333
8 L F Cheng, T Yu. Smart dispatching for energy internet with complex cyber-physical-social systems: A parallel dispatch perspective. International Journal of Energy Research, 2019, 43(8): 3080–3133
https://doi.org/10.1002/er.4384
9 J YanC Yuen T K Saha, et al.. Call for papers for: Special issue on ‘energy sharing in the peer-to-peer network – moving towards real implementation. Applied Energy, 2021-01-02, available at the Elsevier website
10 Ofgem. Breakdown of an electricity bill. 2021-01-07, available at the website of Ofgem
11 A PaceJ LordT Edwards, et al.. A review of the embedded benefits accruing to distribution connected generation in GB. 2022-09-08, available at the website of theade
12 Ofgem. “Ofgem’s future insights series: Local energy in a transforming energy system. 2021-04-11, available at the website of Ofgem
13 Ofgem. Current arrangements. Access and forward-looking charges significant code review—Summer 2019 working paper. 2021-01-07, available at the website of Ofgem
14 A PaceJ LordT Edwards, et al.. A review of the embedded benefits accruing to distribution connected generation in GB. 2021-01-07, available at the website of theade
15 Scottish & Southern Electricity Networks. How are DUoS charges calculated?—Overview. 2021-01-07, available at the website of Scottish & Southern Electricity Networks
16 Ofgem. Links with procurement of flexibility – discussion note. Access and forward-looking charges significant code review – Summer 2019 working paper. 2021-01-17, available at the website of Ofgem
17 R Nepal, J Foster. Electricity networks privatization in Australia: An overview of the debate. Economic Analysis and Policy, 2015, 48: 12–24
https://doi.org/10.1016/j.eap.2015.10.001
18 M Castaneda, M Jimenez, S Zapata. et al.. Myths and facts of the utility death spiral. Energy Policy, 2017, 110: 105–116
https://doi.org/10.1016/j.enpol.2017.07.063
19 Ofgem. Illustrative examples note. Access and forward-looking charges significant code review – Summer 2019 working paper. 2021-01-21, available at the website of Ofgem
20 Ofgem. Electricity network access and forward-looking charging review: Open letter on our shortlisted policy options. 2021-01-24, available at the website of Ofgem
21 Ofgem. Options for reform of access rights for distribution and transmission—Discussion note. 2021-01-24, available at the website of Ofgem
22 Ofgem. Access and forward-looking charges significant code review: Consultation on updates to minded to positions and response to June 2021 Consultation feedback. 2022-09-08, available at the website of Ofgem
23 Networks Association (ENA) Energy. Open networks. 2022-09-08, available at the website of ENA
24 W Tushar, T K Saha, C Yuen. et al.. Peer-to-peer trading in electricity networks: An overview. IEEE Transactions on Smart Grid, 2020, 11(4): 3185–3200
https://doi.org/10.1109/TSG.2020.2969657
25 J Guerrero, A C Chapman, G Verbič. Decentralized P2P energy trading under network constraints in a low-voltage network. IEEE Transactions on Smart Grid, 2019, 10(5): 5163–5173
https://doi.org/10.1109/TSG.2018.2878445
26 W Tushar, T K Saha, C Yuen. et al.. Grid influenced peer-to-peer energy trading. IEEE Transactions on Smart Grid, 2020, 11(2): 1407–1418
https://doi.org/10.1109/TSG.2019.2937981
27 M Khorasany, Y Mishra, G Ledwich. A decentralized bilateral energy trading system for peer-to-peer electricity markets. IEEE Transactions on Industrial Electronics, 2020, 67(6): 4646–4657
https://doi.org/10.1109/TIE.2019.2931229
28 H Liu, J Li, S Ge. et al.. Distributed day-ahead peer-to-peer trading for multi-microgrid systems in active distribution networks. IEEE Access: Practical Innovations, Open Solutions, 2020, 8: 66961–66976
https://doi.org/10.1109/ACCESS.2020.2983645
29 A Paudel, M Khorasany, H B Gooi. Decentralized local energy trading in microgrids with voltage management. IEEE Transactions on Industrial Informatics, 2021, 17(2): 1111–1121
https://doi.org/10.1109/TII.2020.2980160
30 M Yan, M Shahidehpour, A Paaso. et al.. Distribution network-constrained optimization of peer-to-peer transactive energy trading among multi-microgrids. IEEE Transactions on Smart Grid, 2021, 12(2): 1033–1047
https://doi.org/10.1109/TSG.2020.3032889
31 A I Nikolaidis, C A Charalambous, P Mancarella. A graph-based loss allocation framework for transactive energy markets in unbalanced radial distribution networks. IEEE Transactions on Power Systems, 2019, 34(5): 4109–4118
https://doi.org/10.1109/TPWRS.2018.2832164
32 I Bhand, S Debbarma. Transaction-tracing based loss allocation in distribution networks under TE system. IEEE Systems Journal, 2021, 15(4): 5664–5673
https://doi.org/10.1109/JSYST.2020.3038037
33 H K Nunna, A Sesetti, A K Rathore. et al.. Multiagent-based energy trading platform for energy storage systems in Distribution systems with interconnected microgrids. IEEE Transactions on Industry Applications, 2020, 56(3): 3207–3217
https://doi.org/10.1109/TIA.2020.2979782
34 E Vega-Fuentes, J Yang, C Lou. et al.. Transaction-oriented dynamic power flow tracing for distribution networks—Definition and implementation in GIS environment. IEEE Transactions on Smart Grid, 2021, 12(2): 1303–1313
https://doi.org/10.1109/TSG.2020.3033625
35 O Jogunola, W Wang, B Adebisi. Prosumers matching and least-cost energy path optimization for peer-to-peer energy trading. IEEE Access: Practical Innovations, Open Solutions, 2020, 8: 95266–95277
https://doi.org/10.1109/ACCESS.2020.2996309
36 A Azizi, F Aminifar, M Moeini-Aghtaie. et al.. Transactive energy market mechanism with loss implication. IEEE Transactions on Smart Grid, 2021, 12(2): 1215–1223
https://doi.org/10.1109/TSG.2020.3028825
37 S Wang, A F Taha, J Wang. et al.. Energy crowdsourcing and peer-to-peer energy trading in blockchain-enabled smart grids. IEEE Transactions on Systems, Man, and Cybernetics, 2019, 49(8): 1612–1623
https://doi.org/10.1109/TSMC.2019.2916565
38 T Morstyn, A Teytelboym, C Hepburn. et al.. Integrating P2P energy trading with probabilistic distribution locational marginal pricing. IEEE Transactions on Smart Grid, 2020, 11(4): 3095–3106
https://doi.org/10.1109/TSG.2019.2963238
39 K Zhang, S Troitzsch, S Hanif. et al.. Coordinated market design for peer-to-peer energy trade and ancillary services in distribution grids. IEEE Transactions on Smart Grid, 2020, 11(4): 2929–2941
https://doi.org/10.1109/TSG.2020.2966216
40 J Kim, Y A Dvorkin. P2P-dominant distribution system architecture. IEEE Transactions on Power Systems, 2020, 35(4): 2716–2725
https://doi.org/10.1109/TPWRS.2019.2961330
41 A Paudel, L P M I Sampath, J Yang. et al.. Peer-to-peer energy trading in smart grid considering power losses and network fees. IEEE Transactions on Smart Grid, 2020, 11(6): 4727–4737
https://doi.org/10.1109/TSG.2020.2997956
42 T Baroche, P Pinson, R L Latimier. et al.. Exogenous cost allocation in peer-to-peer electricity markets. IEEE Transactions on Power Systems, 2019, 34(4): 2553–2564
https://doi.org/10.1109/TPWRS.2019.2896654
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