IDEAS home Printed from https://ideas.repec.org/a/spr/orspec/v45y2023i1d10.1007_s00291-022-00697-6.html
   My bibliography  Save this article

A classification scheme for local energy trading

Author

Listed:
  • Jens Hönen

    (University of Twente)

  • Johann L. Hurink

    (University of Twente)

  • Bert Zwart

    (Eindhoven University of Technology
    Centrum Wiskunde & Informatica (CWI))

Abstract

The current trend towards more renewable and sustainable energy generation leads to an increased interest in new energy management systems and the concept of a smart grid. One important aspect of this is local energy trading, which is an extension of existing electricity markets by including prosumers, who are consumers also producing electricity. Prosumers having a surplus of energy may directly trade this surplus with other prosumers, who are currently in demand. In this paper, we present an overview of the literature in the area of local energy trading. In order to provide structure to the broad range of publications, we identify key characteristics, define the various settings, and cluster the considered literature along these characteristics. We identify three main research lines, each with a distinct setting and research question. We analyze and compare the settings, the used techniques, and the results and findings within each cluster and derive connections between the clusters. In addition, we identify important aspects, which up to now have to a large extent been neglected in the considered literature and highlight interesting research directions, and open problems for future work.

Suggested Citation

  • 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.
  • Handle: RePEc:spr:orspec:v:45:y:2023:i:1:d:10.1007_s00291-022-00697-6
    DOI: 10.1007/s00291-022-00697-6
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s00291-022-00697-6
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s00291-022-00697-6?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. Ströhle, Philipp & Flath, Christoph M., 2016. "Local matching of flexible load in smart grids," European Journal of Operational Research, Elsevier, vol. 253(3), pages 811-824.
    2. 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.
    3. 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.
    4. Jonathan F. Bard, 1988. "Short-Term Scheduling of Thermal-Electric Generators Using Lagrangian Relaxation," Operations Research, INFORMS, vol. 36(5), pages 756-766, October.
    5. Hélène Le Cadre, 2019. "On the efficiency of local electricity markets under decentralized and centralized designs: a multi-leader Stackelberg game analysis," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 27(4), pages 953-984, December.
    6. Hong, Tao & Pinson, Pierre & Fan, Shu & Zareipour, Hamidreza & Troccoli, Alberto & Hyndman, Rob J., 2016. "Probabilistic energy forecasting: Global Energy Forecasting Competition 2014 and beyond," International Journal of Forecasting, Elsevier, vol. 32(3), pages 896-913.
    7. McAfee, R. Preston, 1992. "A dominant strategy double auction," Journal of Economic Theory, Elsevier, vol. 56(2), pages 434-450, April.
    8. Chen, Kaixuan & Lin, Jin & Song, Yonghua, 2019. "Trading strategy optimization for a prosumer in continuous double auction-based peer-to-peer market: A prediction-integration model," Applied Energy, Elsevier, vol. 242(C), pages 1121-1133.
    9. 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.
    10. Johnson, Raymond B. & Oren, Shmuel S. & Svoboda, Alva J., 1997. "Equity and efficiency of unit commitment in competitive electricity markets," Utilities Policy, Elsevier, vol. 6(1), pages 9-19, March.
    11. Bushnell, J. & Oren, S., 1997. "Transmission pricing in California's proposed electricity market," Utilities Policy, Elsevier, vol. 6(3), pages 237-244, September.
    12. Devine, Mel T. & Bertsch, Valentin, 2018. "Examining the benefits of load shedding strategies using a rolling-horizon stochastic mixed complementarity equilibrium model," European Journal of Operational Research, Elsevier, vol. 267(2), pages 643-658.
    13. Li, Longxi, 2021. "Coordination between smart distribution networks and multi-microgrids considering demand side management: A trilevel framework," Omega, Elsevier, vol. 102(C).
    14. Hahn, Heiko & Meyer-Nieberg, Silja & Pickl, Stefan, 2009. "Electric load forecasting methods: Tools for decision making," European Journal of Operational Research, Elsevier, vol. 199(3), pages 902-907, December.
    15. Ventosa, Mariano & Baillo, Alvaro & Ramos, Andres & Rivier, Michel, 2005. "Electricity market modeling trends," Energy Policy, Elsevier, vol. 33(7), pages 897-913, May.
    16. Mitridati, Lesia & Kazempour, Jalal & Pinson, Pierre, 2021. "Design and game-Theoretic analysis of community-Based market mechanisms in heat and electricity systems," Omega, Elsevier, vol. 99(C).
    17. Zugno, Marco & Morales, Juan Miguel & Pinson, Pierre & Madsen, Henrik, 2013. "A bilevel model for electricity retailers' participation in a demand response market environment," Energy Economics, Elsevier, vol. 36(C), pages 182-197.
    18. Lloyd S. Shapley, 1967. "On balanced sets and cores," Naval Research Logistics Quarterly, John Wiley & Sons, vol. 14(4), pages 453-460.
    19. René Aïd & Roxana Dumitrescu & Peter Tankov, 2021. "The entry and exit game in the electricity markets: A mean-field game approach," Post-Print hal-03215763, HAL.
    20. Aussel, Didier & Brotcorne, Luce & Lepaul, Sébastien & von Niederhäusern, Léonard, 2020. "A trilevel model for best response in energy demand-side management," European Journal of Operational Research, Elsevier, vol. 281(2), pages 299-315.
    21. Alejandro Pena-Bello & David Parra & Mario Herberz & Verena Tiefenbeck & Martin K. Patel & Ulf J. J. Hahnel, 2022. "Integration of prosumer peer-to-peer trading decisions into energy community modelling," Nature Energy, Nature, vol. 7(1), pages 74-82, January.
    22. Ren'e Aid & Pierre Gruet & Huy^en Pham, 2015. "An optimal trading problem in intraday electricity markets," Papers 1501.04575, arXiv.org.
    23. E. J. Anderson & A. B. Philpott, 2002. "Optimal Offer Construction in Electricity Markets," Mathematics of Operations Research, INFORMS, vol. 27(1), pages 82-100, February.
    24. Dan Bienstock & Mauro Escobar & Claudio Gentile & Leo Liberti, 2020. "Mathematical programming formulations for the alternating current optimal power flow problem," 4OR, Springer, vol. 18(3), pages 249-292, September.
    25. Hélène Le Cadre & Enrique Rivero Puente & Hanspeter Höschle, 2019. "Consensus Reaching With Heterogeneous User Preferences," Working Papers hal-01874798, HAL.
    26. René Aïd & Pierre Gruet & Huyên Pham, 2015. "An optimal trading problem in intraday electricity markets," Working Papers hal-01104829, HAL.
    27. Askeland, Magnus & Backe, Stian & Bjarghov, Sigurd & Korpås, Magnus, 2021. "Helping end-users help each other: Coordinating development and operation of distributed resources through local power markets and grid tariffs," Energy Economics, Elsevier, vol. 94(C).
    28. Rene Carmona & Michael Coulon & Daniel Schwarz, 2012. "Electricity price modeling and asset valuation: a multi-fuel structural approach," Papers 1205.2299, arXiv.org.
    Full references (including those not matched with items on IDEAS)

    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. 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. Roman Le Goff Latimier & H. Ben Ahmed, 2023. "Peer to peer electricity markets," Post-Print hal-04268639, HAL.
    3. Möst, Dominik & Keles, Dogan, 2010. "A survey of stochastic modelling approaches for liberalised electricity markets," European Journal of Operational Research, Elsevier, vol. 207(2), pages 543-556, December.
    4. Luo, Jian & Hong, Tao & Gao, Zheming & Fang, Shu-Cherng, 2023. "A robust support vector regression model for electric load forecasting," International Journal of Forecasting, Elsevier, vol. 39(2), pages 1005-1020.
    5. Nieta, Agustín A. Sánchez de la & Ilieva, Iliana & Gibescu, Madeleine & Bremdal, Bernt & Simonsen, Stig & Gramme, Eivind, 2021. "Optimal midterm peak shaving cost in an electricity management system using behind customers’ smart meter configuration," Applied Energy, Elsevier, vol. 283(C).
    6. Abate, Arega Getaneh & Riccardi, Rossana & Ruiz, Carlos, 2022. "Contract design in electricity markets with high penetration of renewables: A two-stage approach," Omega, Elsevier, vol. 111(C).
    7. Rafal Weron & Florian Ziel, 2018. "Electricity price forecasting," HSC Research Reports HSC/18/08, Hugo Steinhaus Center, Wroclaw University of Technology.
    8. 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).
    9. Herenčić, Lin & Kirac, Mislav & Keko, Hrvoje & Kuzle, Igor & Rajšl, Ivan, 2022. "Automated energy sharing in MV and LV distribution grids within an energy community: A case for Croatian city of Križevci with a hybrid renewable system," Renewable Energy, Elsevier, vol. 191(C), pages 176-194.
    10. Weron, Rafał, 2014. "Electricity price forecasting: A review of the state-of-the-art with a look into the future," International Journal of Forecasting, Elsevier, vol. 30(4), pages 1030-1081.
    11. Moutinho, Victor & Moreira, António C. & Mota, Jorge, 2014. "Do regulatory mechanisms promote competition and mitigate market power? Evidence from Spanish electricity market," Energy Policy, Elsevier, vol. 68(C), pages 403-412.
    12. Dagoumas, Athanasios S. & Polemis, Michael L., 2017. "An integrated model for assessing electricity retailer’s profitability with demand response," Applied Energy, Elsevier, vol. 198(C), pages 49-64.
    13. Kristie Kaminski Küster & Daniel Gebbran & Alexandre Rasi Aoki & Germano Lambert-Torres & Daniel Navarro-Gevers & Patrício Rodolfo Impinisi & Cleverson Luiz da Silva Pinto, 2023. "Adoption of Local Peer-to-Peer Energy Markets: Technical and Economical Perspectives for Utilities," Energies, MDPI, vol. 16(5), pages 1-24, March.
    14. 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).
    15. Soares, Inês & Alves, Maria João & Henggeler Antunes, Carlos, 2021. "A deterministic bounding procedure for the global optimization of a bi-level mixed-integer problem," European Journal of Operational Research, Elsevier, vol. 291(1), pages 52-66.
    16. Carlos Henggeler Antunes & Maria João Alves & Billur Ecer, 2020. "Bilevel optimization to deal with demand response in power grids: models, methods and challenges," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 28(3), pages 814-842, October.
    17. 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).
    18. Florian Ziel & Rick Steinert, 2015. "Electricity Price Forecasting using Sale and Purchase Curves: The X-Model," Papers 1509.00372, arXiv.org, revised Aug 2016.
    19. Grimm, Veronika & Orlinskaya, Galina & Schewe, Lars & Schmidt, Martin & Zöttl, Gregor, 2021. "Optimal design of retailer-prosumer electricity tariffs using bilevel optimization," Omega, Elsevier, vol. 102(C).
    20. 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).

    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:spr:orspec:v:45:y:2023:i:1:d:10.1007_s00291-022-00697-6. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.