Physical and Market Structure of Peer-to-Peer Trading Networks: Comparison
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A peer-to-peer (P2P) network is a distributed self-organising network that does not need to have central nodes, and each node can act as either a server or a client at any given time. In recent years, tThe evolution of DERs and the principles of peer-to-peer networks have given rise to interest in the concept of P2P energy trading networks. In a P2P energy trading network, there are no intermediate energy suppliers. People are encouraged to share their energy surplus directly with their local communities. The energy surplus will be sold at an export price, and the additional electricity demand can be encouraged by a cheaper-than-normal retail price.

  • community energy
  • energy sharing
  • barrier analysis
  • tragedy of commons
  • free rider effect

1. P2P Networks

Over recent decades, network management has progressed steadily. Several distribution methods, such as centralised, decentralised and fully distributed, have been investigated or implemented in response to the increased need for additional features such as scalability, security and flexibility in network management solutions. A peer-to-peer (P2P) network is a distributed self-organising network that does not need to have central nodes, and each node can act as either a server or a client at any given time [1]. Analogies to P2P networking have been shown in the history of evolution, when living beings benefit from the efficiency of collaboration with neighbours, or even internal parasites, for survival or performance improvement (symbiosis) [2]. Modern P2P, or the so-called “sharing economy” concept, goes back to the late 1990s, with the emergence of the internet and the consequent digital revolution [3]. The first large P2P scheme (which allowed users to share music files with each other) [4] was developed by Napster in 1999 and was quickly followed by the Gnutella protocol [5], resulting in a massive surge in internet traffic [6]. Both methods of sharing faced significant legal problems, from challenges by old industries and traditional modes of selling or commodification. P2P differs from traditional networks as every peer in the network has multiple roles, such as being a provider of data, collector of data, and maintainer of software. The fundamental objective of P2P technology is to share resources directly between ‘peers’. By combining the resources of many autonomous nodes, P2P systems can provide a low-cost platform for distributed computing. Because of the properties and special mechanisms that are used in the network, a P2P network is more robust [7] than traditional networks. P2P traffic on the internet has now surpassed HTTP traffic and is utilised in a number of sectors. There have been several P2P applications in telecommunication [8], energy trading [9], financial services [10], and file sharing [11[11][12],12], among other areas. Because of its high sharing efficiency and, thus, high resource utilisation performance, it has become even more popular in recent years [13] and has diffused into our daily lives. Another emerging P2P framework arises in the context of renewable energy sharing or trading.

2. Energy Network Decentralisation and P2P Energy Trading Emergence

Climate change is increasingly recognised as a civilisational threat arising from pollution and the destructive extraction of food and resources, which requires immediate global action. Traditional energy sources such as coal, oil, and natural gas are key sources of pollution [15][14]. Hence, using renewable resources such as wind and solar energy is often taken as a path to a better future. In recent years, distributed energy resources (DERs) have expanded rapidly because of their greater energy efficiency, lesser environmental impact, and wider range of energy sources [16,17][15][16]. DERs are typically composed of wind turbines and solar panels, which, in combination with an energy storage system, enable users to generate, store, and access energy onsite without reliance on centralised power plants. Renewable energy is not necessarily a DER as it can be centralised in large-scale wind and solar farms, but it has that potential, as solar, in particular, is cheap, environmentally friendly, modular, and hence easy to install locally in increments.
The rise in DERs is altering energy distribution networks and changing ways of producing and consuming, as well as changing the roles of energy consumers [18][17]. The connection and integration of various DERs to the energy grid have resulted in the emergence of new roles for grid and DER owners. Traditionally, the only role of end users in the electricity grid has been as a consumer. Transmission and distribution networks have been used to transport energy from large power plants to customers, involving only one-way transmission. With the development of DERs, end users can produce energy by themselves and transmit it back into the distribution network. Hence, the role of the end users has changed into becoming ‘prosumers’, and there can be a two-way information exchange and two-way energy flow between prosumers and other market agents [19][18]. There are other systems, such as virtual power plants (VPPs), which may look like P2P trading but are not. For instance, AGL, a large electricity company with more than 3.95 million customers in Australia [20][19], has released a VPP program based on its studies of DERs [21][20]. These VPP systems are intended to orchestrate the operation of the members’ home energy system to benefit multiple stakeholders, including the homeowners (through reduced energy bills), the retail company (reduced peak purchase from the pool market), and the network and society (reducing peak demand). Unlike P2P trading, there is no interaction between members in the VPPs and system control is carried out either by a third-party company known as a distributed network service provider (DNSP) or the retailer (e.g., AGL in this example).
One immediate consequence of widespread DER uptake is underutilisation of the asset through curtailment of the surplus energy of the user (when the electricity generation is higher than the current load requirement and the remaining capacity of the installed storage systems). This curtailment is a problem for centralised systems as well, but costs can be absorbed by the supplying company. Individual prosumers are more likely to resent not being paid when they could be, in theory, and are likely to seek a solution for the unrealised income. This resource underutilisation problem is similar to that of unused rooms in a house (which the concept of Airbnb came to utilise) or underused cars in the family (from which Uber emerged) [22][21]. Hence, right from the early stages of DER uptake in some countries over the last decade, the need for sharing economy business solutions has been raised and investigated (e.g., as with Continental Power Exchange CPEX) [23][22]. In summary, the evolution of DERs and the principles of peer-to-peer networks have given rise to interest in the concept of P2P energy trading networks.

3. The Physical and Market Structure of P2P Trading Networks

In general, P2P energy trading involves both new technology and commercial energy transferring models on the demand side of power networks, allowing prosumers to freely select their energy trading parameters, such as the trading price per unit or amount of energy sharing, so as to enhance their overall energy performance, engagement with others, and economic benefits [24][23]. In a P2P energy trading network, there are no intermediate energy suppliers. People are encouraged to share their energy surplus directly with their local communities. The energy surplus will be sold at an export price, and the additional electricity demand can be encouraged by a cheaper-than-normal retail price [25][24]. P2P energy appears to have various advantages, including a decrease in power outages, an improvement in power system efficiency, an enhancement of local energy supplies, possible local application of those supplies, some independence from utility providers and a choice of multiple energy sources to go with user preferences [9,26][9][25]. In addition, P2P energy trading can also meet community requirements, such as reducing power bills [27][26], encouraging clean energy, and distributing surplus energy to those in need in a way decided by the community [28][27]. However, there is a possible problem for traditional energy suppliers as they can lose control over the markets and pricing, hence lose profit and start to work against the sharing system. Figure 1 illustrates the differences between a traditional centralised energy network and the emerging decentralised network with prosumers building demand-side P2P energy sharing networks.
Figure 1.
Demand-side electricity trade: (
A
) Traditional system, (
B
) P2P-enabled energy network.
Soto et al. [25][24] provided a general overview of P2P energy trading. They mention that the change of roles from consumer to prosumer enables prosumers to gain benefits. Azim et al. [29][28] have demonstrated that both small sellers and buyers can gain economic benefits in a typical day. Based on their simulation results, the authors demonstrate that “the more prosumers participate in P2P trading, the more they can gain financial benefits”.
Tushar et al. [30,31][29][30] provided a detailed background discussion of P2P energy trading. They divided the P2P energy system into two elements: the virtual layer and the physical layer. The virtual layer offers participants a safe computerised link through which they may select the settings for their energy trading. The physical layer is the physical network that enables electricity to be moved from sellers to buyers. According to Tushar et al. [30][29], the key components in the virtual layer are information systems, market operations, pricing mechanisms, and energy management systems. In the physical layer, the key components are grid connection, metering, and communication infrastructure. In what we might call the social and political layers, regulations are another influential element, affecting the ease of action such as connection, payment and change.
The information system is the core of the virtual layer as it supports bidirectional communication between peers and helps them decide the energy parameters they will use, and it enables each market participant’s usage to be monitored in real time [32][31]. The ‘smart contract’ (self-executing programs that have the capability to observe and modify the ledger based on rules defined by the user) is an example of such an information system. Han et al. [33][32] designed a smart contract model as a partial blockchain platform. The results show that their blockchain model implemented the whole trading process successfully as the smart contract strictly executes the trading and payment regulations, so the safety and fairness of electricity trading are greatly improved.
Market operations refer to the bidding strategies and market clearing methodologies that match real-time buying and selling orders. Muhsen et al. [34][33] reviewed different types of current bidding strategies as well as market clearing approaches from various business perspectives. Pricing mechanisms (also known as ‘pricing schemes’) can also help balance the demand and supply of energy [30][29]. A study by Lee et al. [35][34] has provided a theoretical analysis of pricing where the authors suggest a strategy for community microgrids in which individual prosumers with solar and storage can engage in a P2P system to trade with other residents (if the social and political layers including regulations allow them) and create dynamic power prices. An energy management system (EMS) is supposed to secure the energy supply of prosumers. Akter et al. [36][35] provided a hierarchical transactive energy management system for a residential microgrid. Using their generalised cost-benefit analysis framework, the authors concluded that prosumers and those residents without renewable energy sources and energy storage systems could benefit through their proposed energy management scheme. According to Khalilpour and Vassallo’s study [22][21], cooperation-based pricing mechanisms in P2P markets improved the resilience of the network and provided the fairest financial incentives to all members.
Grid connection, metering, and communication infrastructure are the main elements in physical layers. The terms ‘grid-connected’ and ‘grid-disconnected’ (or ‘off-grid’) define the relationship of the user’s premises with a circumferent electricity grid, if available. Other features in relation to grid connection are the flow directions of energy, which can be referred to as ‘one-directional’ or ‘bidirectional’. One-directional connections allow either energy export or energy import, while bidirectional connections allow both. Azim et al. [37][36] conducted a thorough analysis of the physical layer to investigate how P2P trading may affect network energy losses. Since there may not always be a direct transfer of electricity from the same prosumer to the target customers, the study states that energy trading in the physical layers can be transferred in watts and negawatts (the amount of energy saved by lowering electricity demand or consumption for a certain period) [38][37].

References

  1. Buragohain, C.; Agrawal, D.; Suri, S. A game theoretic framework for incentives in P2P systems. In Proceedings of the Third International Conference on Peer-to-Peer Computing (P2P2003) 0121562, Linköping, Sweden, 1–3 September 2003; pp. 48–56.
  2. Chapelle, G.; Servigne, P. Mutual Aid: The Other Law of the Jungle; John Wiley & Sons: Hoboken, NJ, USA, 2021.
  3. Raymond, E.S. The Cathedral & the Bazaar: Musings on Linux and Open Source by an Accidental Revolutionary; O’Reilly Media Inc: Sebastopol, CA, USA, 2001.
  4. Washbourne, L. A survey of P2P network security. arXiv 2015, arXiv:1504.01358.
  5. Howe, A. Napster and Gnutella: A Comparison of Two Popular Peer-to-Peer Protocols; Universidade de Victoria: Victoria, BC, Canada, 2000; Available online: http://members.tripod.com/ahowe_ca/pdf/napstergnutella.pdf (accessed on 19 November 2022).
  6. Strahilevitz, L.J. Charismatic code, social norms, and the emergence of cooperation on the file-swapping networks. Va. Law Rev. 2003, 89, 505–596.
  7. Palomar, E.; Estevez-Tapiador, J.M.; Hernandez-Castro, J.C.; Ribagorda, A. Security in P2P networks: Survey and research directions. In Emerging Directions in Embedded and Ubiquitous Computing; LNCS; Springer: Berlin/Heidelberg, Germany, 2006; Volume 4097, pp. 183–192.
  8. Kellerer, W.; Kunzmann, G.; Schollmeier, R.; Zöls, S. Structured peer-to-peer systems for telecommunications and mobile environments. AEU-Int. J. Electron. Commun. 2006, 60, 25–29.
  9. Abdella, J.; Shuaib, K. Peer to peer distributed energy trading in smart grids: A survey. Energies 2018, 11, 1560.
  10. Moenninghoff, S.C.; Wieandt, A. The Future of Peer-to-Peer Finance. Schmalenbachs Z. Für Betriebswirtschaftliche Forsch. 2013, 65, 466–488.
  11. Golle, P.; Leyton-Brown, K.; Mironov, I.; Lillibridge, M. Incentives for sharing in peer-to-peer networks. In Proceedings of the 3rd ACM Conference on Electronic Commerce, Tampa, FL, USA, 14–17 October 2001; Volume 2232, pp. 75–87.
  12. Marshall, J.P.; Rimini, F. Paradoxes of Property: Piracy and Sharing in Information Capitalism The Incoherence of Property. In A Reader on International Media Piracy; Amsterdam University Press: Amsterdam, The Netherlands, 2015; pp. 1–27.
  13. Asvanund, A.; Clay, K.; Krishnan, R.; Smith, M.D. An empirical analysis of network externalities in peer-to-peer music-sharing networks. Inf. Syst. Res. 2004, 15, 155–174.
  14. Azad, A.K.; Khan, M.M.K.; Ahasan, T.; Ahmed, S.F. Energy Scenario: Production, Consumption and Prospect of Renewable Energy in Australia. J. Power Energy Eng. 2014, 2, 19–25.
  15. Bilan, Y.; Rabe, M.; Widera, K. Distributed Energy Resources: Operational Benefits. Energies 2022, 15, 8864.
  16. Schwartz, L.; Wei, M.; Morrow, W.; Deason, J.; Schiller, S.R.; Leventis, G.; Smith, S.; Leow, W.L.; Levin, T.; Plotkin, S.; et al. Electricity End Uses, Energy Efficiency, and Distributed Energy Resources Baseline; Lawrence Berkeley National Laboratory: Berkeley, CA, USA, 2017; Volume 77.
  17. Muqeet, H.A.; Ahmad, A.; Sajjad, I.A.; Liaqat, R.; Raza, A.; Iqbal, M.M. Benefits of Distributed Energy and Storage System in Prosumer Based Electricity Market. In Proceedings of the IEEE International Conference on Environment and Electrical Engineering and 2019 IEEE Industrial and Commercial Power Systems Europe (EEEIC/I&CPS Europe), Genova, Italy, 11–14 June 2019; pp. 3–8.
  18. Qi, M.; Yang, H.; Wang, D.; Luo, Y.; Zhang, S.; Liao, S. Prosumers Peer-to-Peer Transaction Decision Considering Network Constraints. In Proceedings of the 2019 IEEE 3rd Conference on Energy Internet and Energy System Integration (EI2), Changsha, China, 8–10 November 2019; pp. 643–647.
  19. AGL Energy Limited. annual report 2020. 2020. Available online: https://www.agl.com.au/content/dam/digital/agl/documents/about-agl/investors/2020/2097212_annualreport.pdf (accessed on 28 November 2022).
  20. ARENA. AGL Virtual Power Plant—Australian Renewable Energy Agency (ARENA). Available online: https://arena.gov.au/projects/agl-virtual-power-plant/ (accessed on 28 November 2022).
  21. Khalilpour, K.R.; Vassallo, A. Cooperative Community Energy Networks BT—Community Energy Networks with Storage: Modeling Frameworks for Distributed Generation; Khalilpour, K.R., Vassallo, A., Eds.; Springer: Singapore, 2016; pp. 151–182.
  22. Tuch, D.; Weier, B.; John, S. Apparatus and Method for Trading Electric Energy. U.S. Patent 6115698A, 5 September 2000. Available online: https://patents.google.com/patent/US6115698A/en (accessed on 28 November 2022).
  23. Tushar, W.; Chai, B.; Yuen, C.; Smith, D.B.; Wood, K.L.; Yang, Z.; Poor, H.V. Three-Party Energy Management with Distributed Energy Resources in Smart Grid. IEEE Trans. Ind. Electron. 2015, 62, 2487–2498.
  24. Soto, E.A.; Bosman, L.B.; Wollega, E.; Leon-salas, W.D. Peer-to-peer energy trading: A review of the literature. Appl. Energy 2021, 283, 116268.
  25. Zhou, Y.; Wu, J.; Song, G.; Long, C. Framework design and optimal bidding strategy for ancillary service provision from a peer-to-peer energy trading community. Appl. Energy 2020, 278, 115671.
  26. Australian Renewable Energy Agency. Peer-to-Peer Distributed Ledger Technology Assessment. In Virtual Peer-to-Peer Energy Trading Using Distributed Ledger Technology: Comprehensive Project Assessment Report; Australian Renewable Energy Agency: Sydney, Australia, 2017.
  27. Klein, L.P.; Krivoglazova, A.; Matos, L.; Landeck, J.; De Azevedo, M. A novel peer-to-peer energy sharing business model for the Portuguese energy market. Energies 2019, 13, 125.
  28. Azim, M.I.; Pourmousavi, S.A.; Tushar, W.; Saha, T.K. Feasibility Study of Financial P2P Energy Trading in a Grid-tied Power Network. In Proceedings of the 2019 IEEE Power & Energy Society General Meeting (PESGM), Atlanta, GA, USA, 4–8 August 2019; Volume 2019, pp. 1157–1161.
  29. Tushar, W.; Saha, T.K.; Yuen, C.; Smith, D.; Poor, H.V. Peer-to-Peer Trading in Electricity Networks: An Overview. IEEE Trans. Smart Grid 2020, 11, 3185–3200.
  30. Tushar, W.; Yuen, C.; Saha, T.K.; Morstyn, T.; Chapman, A.C.; Jan, E.; Alam, M.; Hanif, S.; Poor, H.V. Peer-to-peer energy systems for connected communities: A review of recent advances and emerging challenges. Appl. Energy 2021, 282, 116131.
  31. Wörner, A.; Ableitner, L.; Meeuw, A.; Wortmann, F.; Tiefenbeck, V. Peer-to-peer energy trading in the real world: Market design and evaluation of the user value proposition. In Proceedings of the 40th International Conference on Information Systems (ICIS 2019), Munich, Germany, 15–18 December 2019.
  32. Han, D.; Zhang, C.; Ping, J.; Yan, Z. Smart contract architecture for decentralized energy trading and management based on blockchains. Energy 2020, 199, 117417.
  33. Muhsen, H.; Allahham, A.; Al-halhouli, A.; Al-mahmodi, M. Business Model of Peer-to-Peer Energy Trading: A Review of Literature. Sustainability 2022, 14, 1616.
  34. Lee, J.T.; Henriquez-Auba, R.; Poolla, B.K.; Callaway, D.S. Pricing and Energy Trading in Peer-to-Peer Zero Marginal-Cost Microgrids. IEEE Trans. Smart Grid 2022, 13, 702–714.
  35. Akter, M.N.; Mahmud, M.A.; Oo, A.M.T. A hierarchical transactive energy management system for energy sharing in residential microgrids. Energies 2017, 10, 2098.
  36. Azim, M.I.; Tushar, W.; Saha, T.K. Investigating the impact of P2P trading on power losses in grid-connected networks with prosumers. Appl. Energy 2020, 263, 114687.
  37. Lovins, A.B. Saving Gigabucks with Negawatts. 1985. Available online: https://www.osti.gov/biblio/5787710 (accessed on 29 November 2022).
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