IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v282y2020i2p753-771.html
   My bibliography  Save this article

Peer-to-peer electricity market analysis: From variational to Generalized Nash Equilibrium

Author

Listed:
  • Le Cadre, Hélène
  • Jacquot, Paulin
  • Wan, Cheng
  • Alasseur, Clémence

Abstract

We consider a network of prosumers involved in peer-to-peer energy exchanges, with differentiation price preferences on the trades with their neighbors, and we analyze two market designs: (i) a centralized market, used as a benchmark, where a global market operator optimizes the flows (trades) between the nodes, local demand and flexibility activation to maximize the system overall social welfare; (ii) a distributed peer-to-peer market design where prosumers in local energy communities optimize selfishly their trades, demand, and flexibility activation. We first characterize the solution of the peer-to-peer market as a Variational Equilibrium and prove that the set of Variational Equilibria coincides with the set of social welfare optimal solutions of market design (i). We give several results that help understanding the structure of the trades at an equilibrium or at the optimum. We characterize the impact of preferences on the network line congestion and renewable energy surplus under both designs. We provide a reduced example for which we give the set of all possible generalized equilibria, which enables to give an approximation of the price of anarchy. We provide a more realistic example which relies on the IEEE 14-bus network, for which we can simulate the trades under different preference prices. Our analysis shows in particular that the preferences have a large impact on the structure of the trades, but that one equilibrium (variational) is optimal. Finally, the learning mechanism needed to reach an equilibrium state in the peer-to-peer market design is discussed together with privacy issues.

Suggested Citation

  • Le Cadre, Hélène & Jacquot, Paulin & Wan, Cheng & Alasseur, Clémence, 2020. "Peer-to-peer electricity market analysis: From variational to Generalized Nash Equilibrium," European Journal of Operational Research, Elsevier, vol. 282(2), pages 753-771.
  • Handle: RePEc:eee:ejores:v:282:y:2020:i:2:p:753-771
    DOI: 10.1016/j.ejor.2019.09.035
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377221719307921
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ejor.2019.09.035?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Le Cadre, Hélène & Pagnoncelli, Bernardo & Homem-de-Mello, Tito & Beaude, Olivier, 2019. "Designing coalition-based fair and stable pricing mechanisms under private information on consumers’ reservation prices," European Journal of Operational Research, Elsevier, vol. 272(1), pages 270-291.
    2. Liran Einav & Chiara Farronato & Jonathan Levin, 2016. "Peer-to-Peer Markets," Annual Review of Economics, Annual Reviews, vol. 8(1), pages 615-635, October.
    3. Masao Fukushima, 2011. "Restricted generalized Nash equilibria and controlled penalty algorithm," Computational Management Science, Springer, vol. 8(3), pages 201-218, August.
    4. Matthew Rabin, 2000. "Risk Aversion and Expected-Utility Theory: A Calibration Theorem," Econometrica, Econometric Society, vol. 68(5), pages 1281-1292, September.
    5. Madani, Mehdi & Van Vyve, Mathieu, 2018. "Revisiting minimum profit conditions in uniform price day-ahead electricity auctions," European Journal of Operational Research, Elsevier, vol. 266(3), pages 1072-1085.
    6. Harker, Patrick T., 1991. "Generalized Nash games and quasi-variational inequalities," European Journal of Operational Research, Elsevier, vol. 54(1), pages 81-94, September.
    7. Hélène Le Cadre, 2018. "On the Efficiency of Local Electricity Markets Under Decentralized and Centralized Designs: A Multi-leader Stackelberg Game Analysis," Working Papers hal-01619885, HAL.
    8. Koichi Nabetani & Paul Tseng & Masao Fukushima, 2011. "Parametrized variational inequality approaches to generalized Nash equilibrium problems with shared constraints," Computational Optimization and Applications, Springer, vol. 48(3), pages 423-452, April.
    9. Fouquet, Doerte & Johansson, Thomas B., 2008. "European renewable energy policy at crossroads--Focus on electricity support mechanisms," Energy Policy, Elsevier, vol. 36(11), pages 4079-4092, November.
    10. Le Cadre, Hélène & Mezghani, Ilyès & Papavasiliou, Anthony, 2019. "A game-theoretic analysis of transmission-distribution system operator coordination," European Journal of Operational Research, Elsevier, vol. 274(1), pages 317-339.
    11. Sousa, Tiago & Soares, Tiago & Pinson, Pierre & Moret, Fabio & Baroche, Thomas & Sorin, Etienne, 2019. "Peer-to-peer and community-based markets: A comprehensive review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 104(C), pages 367-378.
    12. Sherali, Hanif D. & Soyster, Allen L. & Murphy, Frederic H. & Sen, Suvrajeet, 1982. "Linear programming based analysis of marginal cost pricing in electric utility capacity expansion," European Journal of Operational Research, Elsevier, vol. 11(4), pages 349-360, December.
    13. Olamide Jogunola & Augustine Ikpehai & Kelvin Anoh & Bamidele Adebisi & Mohammad Hammoudeh & Haris Gacanin & Georgina Harris, 2017. "Comparative Analysis of P2P Architectures for Energy Trading and Sharing," Energies, MDPI, vol. 11(1), pages 1-20, December.
    14. Giorgia Oggioni & Yves Smeers & Elisabetta Allevi & Siegfried Schaible, 2012. "A Generalized Nash Equilibrium Model of Market Coupling in the European Power System," Networks and Spatial Economics, Springer, vol. 12(4), pages 503-560, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Dynge, Marthe Fogstad & Berg, Kjersti & Bjarghov, Sigurd & Cali, Ümit, 2023. "Local electricity market pricing mechanisms’ impact on welfare distribution, privacy and transparency," Applied Energy, Elsevier, vol. 341(C).
    2. Hildebrandt, Benjamin & Hurink, Johann & Manitz, Michael, 2024. "Local energy management: A base model for the optimization of virtual economic units," Energy Economics, Elsevier, vol. 129(C).
    3. Zhou, Yuekuan & Lund, Peter D., 2023. "Peer-to-peer energy sharing and trading of renewable energy in smart communities ─ trading pricing models, decision-making and agent-based collaboration," Renewable Energy, Elsevier, vol. 207(C), pages 177-193.
    4. Jens Hönen & Johann L. Hurink & Bert Zwart, 2023. "A classification scheme for local energy trading," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 45(1), pages 85-118, March.
    5. Braouezec, Yann & Kiani, Keyvan, 2023. "Economic foundations of generalized games with shared constraint: Do binding agreements lead to less Nash equilibria?," European Journal of Operational Research, Elsevier, vol. 308(1), pages 467-479.
    6. Yann BRAOUEZEC & Keyvan KIANI, 2021. "Economic foundations of generalized games with shared constraint: Do binding agreements lead to less Nash equilibria?," Working Papers 2021-ACF-06, IESEG School of Management.
    7. Xia, Yuanxing & Xu, Qingshan & Chen, Lu & Du, Pengwei, 2022. "The flexible roles of distributed energy storages in peer-to-peer transactive energy market: A state-of-the-art review," Applied Energy, Elsevier, vol. 327(C).
    8. Zacharie De Grève & Jérémie Bottieau & David Vangulick & Aurélien Wautier & Pierre-David Dapoz & Adriano Arrigo & Jean-François Toubeau & François Vallée, 2020. "Machine Learning Techniques for Improving Self-Consumption in Renewable Energy Communities," Energies, MDPI, vol. 13(18), pages 1-17, September.
    9. Erol, Özge & Başaran Filik, Ümmühan, 2022. "A Stackelberg game approach for energy sharing management of a microgrid providing flexibility to entities," Applied Energy, Elsevier, vol. 316(C).
    10. Tsaousoglou, Georgios & Ellinas, Petros & Varvarigos, Emmanouel, 2023. "Operating peer-to-peer electricity markets under uncertainty via learning-based, distributed optimal control," Applied Energy, Elsevier, vol. 343(C).
    11. Spiliopoulos, Nikolas & Sarantakos, Ilias & Nikkhah, Saman & Gkizas, George & Giaouris, Damian & Taylor, Phil & Rajarathnam, Uma & Wade, Neal, 2022. "Peer-to-peer energy trading for improving economic and resilient operation of microgrids," Renewable Energy, Elsevier, vol. 199(C), pages 517-535.
    12. Rahman Khorramfar & Osman Y. Özaltın & Karl G. Kempf & Reha Uzsoy, 2022. "Managing Product Transitions: A Bilevel Programming Approach," INFORMS Journal on Computing, INFORMS, vol. 34(5), pages 2828-2844, September.
    13. Liu, Junhong & Long, Qinfei & Liu, Rong-Peng & Liu, Wenjie & Hou, Yunhe, 2023. "Online distributed optimization for spatio-temporally constrained real-time peer-to-peer energy trading," Applied Energy, Elsevier, vol. 331(C).
    14. João Mello & Cristina de Lorenzo & Fco. Alberto Campos & José Villar, 2023. "Pricing and Simulating Energy Transactions in Energy Communities," Energies, MDPI, vol. 16(4), pages 1-22, February.
    15. Wicak Ananduta & Sergio Grammatico, 2022. "Equilibrium Seeking and Optimal Selection Algorithms in Peer-to-Peer Energy Markets," Games, MDPI, vol. 13(5), pages 1-13, October.
    16. Schwidtal, J.M. & Piccini, P. & Troncia, M. & Chitchyan, R. & Montakhabi, M. & Francis, C. & Gorbatcheva, A. & Capper, T. & Mustafa, M.A. & Andoni, M. & Robu, V. & Bahloul, M. & Scott, I.J. & Mbavarir, 2023. "Emerging business models in local energy markets: A systematic review of peer-to-peer, community self-consumption, and transactive energy models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 179(C).
    17. Moret, Fabio & Pinson, Pierre & Papakonstantinou, Athanasios, 2020. "Heterogeneous risk preferences in community-based electricity markets," European Journal of Operational Research, Elsevier, vol. 287(1), pages 36-48.
    18. Xiang, Liu, 2022. "A large-scale equilibrium model of energy emergency production: Embedding social choice rules into Nash Q-learning automatically achieving consensus of urgent recovery behaviors," Energy, Elsevier, vol. 259(C).
    19. Tsaousoglou, Georgios & Giraldo, Juan S. & Paterakis, Nikolaos G., 2022. "Market Mechanisms for Local Electricity Markets: A review of models, solution concepts and algorithmic techniques," Renewable and Sustainable Energy Reviews, Elsevier, vol. 156(C).
    20. Capper, Timothy & Gorbatcheva, Anna & Mustafa, Mustafa A. & Bahloul, Mohamed & Schwidtal, Jan Marc & Chitchyan, Ruzanna & Andoni, Merlinda & Robu, Valentin & Montakhabi, Mehdi & Scott, Ian J. & Franci, 2022. "Peer-to-peer, community self-consumption, and transactive energy: A systematic literature review of local energy market models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 162(C).
    21. Shama Naz Islam, 2024. "A Review of Peer-to-Peer Energy Trading Markets: Enabling Models and Technologies," Energies, MDPI, vol. 17(7), pages 1-18, April.
    22. Faia, Ricardo & Lezama, Fernando & Soares, João & Pinto, Tiago & Vale, Zita, 2024. "Local electricity markets: A review on benefits, barriers, current trends and future perspectives," Renewable and Sustainable Energy Reviews, Elsevier, vol. 190(PA).
    23. Bogdan-Constantin Neagu & Ovidiu Ivanov & Gheorghe Grigoras & Mihai Gavrilas, 2020. "A New Vision on the Prosumers Energy Surplus Trading Considering Smart Peer-to-Peer Contracts," Mathematics, MDPI, vol. 8(2), pages 1-27, February.
    24. Roman Le Goff Latimier & H. Ben Ahmed, 2023. "Peer to peer electricity markets," Post-Print hal-04268639, HAL.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Le Cadre, Hélène & Mezghani, Ilyès & Papavasiliou, Anthony, 2019. "A game-theoretic analysis of transmission-distribution system operator coordination," European Journal of Operational Research, Elsevier, vol. 274(1), pages 317-339.
    2. Jiawang Nie & Xindong Tang & Lingling Xu, 2021. "The Gauss–Seidel method for generalized Nash equilibrium problems of polynomials," Computational Optimization and Applications, Springer, vol. 78(2), pages 529-557, March.
    3. Han, Deren & Zhang, Hongchao & Qian, Gang & Xu, Lingling, 2012. "An improved two-step method for solving generalized Nash equilibrium problems," European Journal of Operational Research, Elsevier, vol. 216(3), pages 613-623.
    4. Le Cadre, Hélène & Bedo, Jean-Sébastien, 2020. "Consensus reaching with heterogeneous user preferences, private input and privacy-preservation output," Operations Research Perspectives, Elsevier, vol. 7(C).
    5. Giorgia Oggioni and Yves Smeers, 2012. "Degrees of Coordination in Market Coupling and Counter-Trading," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3).
    6. Sreekumaran, Harikrishnan & Hota, Ashish R. & Liu, Andrew L. & Uhan, Nelson A. & Sundaram, Shreyas, 2021. "Equilibrium strategies for multiple interdictors on a common network," European Journal of Operational Research, Elsevier, vol. 288(2), pages 523-538.
    7. Tom Brijs & Daniel Huppmann & Sauleh Siddiqui & Ronnie Belmans, 2016. "Auction-Based Allocation of Shared Electricity Storage Resources through Physical Storage Rights," Discussion Papers of DIW Berlin 1566, DIW Berlin, German Institute for Economic Research.
    8. Friedrich Kunz & Alexander Zerrahn, 2013. "The Benefit of Coordinating Congestion Management in Germany," Discussion Papers of DIW Berlin 1298, DIW Berlin, German Institute for Economic Research.
    9. Letícia Becher & Damián Fernández & Alberto Ramos, 2023. "A trust-region LP-Newton method for constrained nonsmooth equations under Hölder metric subregularity," Computational Optimization and Applications, Springer, vol. 86(2), pages 711-743, November.
    10. Alexey Izmailov & Mikhail Solodov, 2014. "On error bounds and Newton-type methods for generalized Nash equilibrium problems," Computational Optimization and Applications, Springer, vol. 59(1), pages 201-218, October.
    11. J. Contreras & J. B. Krawczyk & J. Zuccollo, 2016. "Economics of collective monitoring: a study of environmentally constrained electricity generators," Computational Management Science, Springer, vol. 13(3), pages 349-369, July.
    12. Migot, Tangi & Cojocaru, Monica-G., 2020. "A parametrized variational inequality approach to track the solution set of a generalized nash equilibrium problem," European Journal of Operational Research, Elsevier, vol. 283(3), pages 1136-1147.
    13. Huppmann, Daniel & Egging, Ruud, 2014. "Market power, fuel substitution and infrastructure – A large-scale equilibrium model of global energy markets," Energy, Elsevier, vol. 75(C), pages 483-500.
    14. Vladimir Shikhman, 2022. "On local uniqueness of normalized Nash equilibria," Papers 2205.13878, arXiv.org.
    15. Shariat Torbaghan, Shahab & Madani, Mehdi & Sels, Peter & Virag, Ana & Le Cadre, Hélène & Kessels, Kris & Mou, Yuting, 2021. "Designing day-ahead multi-carrier markets for flexibility: Models and clearing algorithms," Applied Energy, Elsevier, vol. 285(C).
    16. Le Cadre, Hélène & Mou, Yuting & Höschle, Hanspeter, 2022. "Parametrized Inexact-ADMM based coordination games: A normalized Nash equilibrium approach," European Journal of Operational Research, Elsevier, vol. 296(2), pages 696-716.
    17. Anna Schwele & Christos Ordoudis & Pierre Pinson & Jalal Kazempour, 2021. "Coordination of power and natural gas markets via financial instruments," Computational Management Science, Springer, vol. 18(4), pages 505-538, October.
    18. Cortade, Thomas & Poudou, Jean-Christophe, 2022. "Peer-to-peer energy platforms: Incentives for prosuming," Energy Economics, Elsevier, vol. 109(C).
    19. Kunz, Friedrich & Zerrahn, Alexander, 2015. "Benefits of coordinating congestion management in electricity transmission networks: Theory and application to Germany," Utilities Policy, Elsevier, vol. 37(C), pages 34-45.
    20. Adewole, Ayooluwa & Shipworth, Michelle & Lemaire, Xavier & Sanderson, Danielle, 2023. "Peer-to-Peer energy trading, independence aspirations and financial benefits among Nigerian households," Energy Policy, Elsevier, vol. 174(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ejores:v:282:y:2020:i:2:p:753-771. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eor .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.