IDEAS home Printed from https://ideas.repec.org/a/nat/natene/v7y2022i1d10.1038_s41560-021-00950-2.html
   My bibliography  Save this article

Integration of prosumer peer-to-peer trading decisions into energy community modelling

Author

Listed:
  • Alejandro Pena-Bello

    (Energy Efficiency Group, Institute for Environmental Sciences and Forel Institute, University of Geneva)

  • David Parra

    (Energy Efficiency Group, Institute for Environmental Sciences and Forel Institute, University of Geneva)

  • Mario Herberz

    (University of Geneva)

  • Verena Tiefenbeck

    (School of Business, Economics and Society, Friedrich-Alexander University Erlangen-Nürnberg (FAU))

  • Martin K. Patel

    (Energy Efficiency Group, Institute for Environmental Sciences and Forel Institute, University of Geneva)

  • Ulf J. J. Hahnel

    (University of Geneva)

Abstract

Peer-to-peer (P2P) exchange of renewable energy is an attractive option to empower citizens to actively participate in the energy transition. Whereas previous research has assessed P2P communities primarily from a techno-economic perspective, little is yet known about prosumer preferences for solar power trading. Importantly, impacts of community members’ trading decisions on key performance indicators, such as individual electricity bills, community autarky and grid stress, remain unknown. Here, we assess P2P trading decisions of German homeowners on the basis of an online experimental study, and simulate how various decision-making strategies impact the performance of P2P communities. The findings suggest that community autarky is slightly higher when prosumers are enabled to trade energy compared to when they merely aim to maximize their self-consumption. Our analysis, moreover, shows that P2P energy trading based on human decision-making may lead to financial benefits for prosumers and traditional consumers, and reduced stress for the grid.

Suggested Citation

  • 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.
    • Handle: RePEc:nat:natene:v:7:y:2022:i:1:d:10.1038_s41560-021-00950-2
    DOI: 10.1038/s41560-021-00950-2
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41560-021-00950-2
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1038/s41560-021-00950-2?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.

    Citations

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


    Cited by:

    1. Idiano D’Adamo & Claudio Sassanelli, 2022. "Biomethane Community: A Research Agenda towards Sustainability," Sustainability, MDPI, vol. 14(8), pages 1-22, April.
    2. Dukovska, Irena & Slootweg, J.G. (Han) & Paterakis, Nikolaos G., 2023. "Introducing user preferences for peer-to-peer electricity trading through stochastic multi-objective optimization," Applied Energy, Elsevier, vol. 338(C).
    3. Xia, Yuanxing & Xu, Qingshan & Li, Fangxing, 2023. "Grid-friendly pricing mechanism for peer-to-peer energy sharing market diffusion in communities," Applied Energy, Elsevier, vol. 334(C).
    4. Xia, Yuanxing & Xu, Qingshan & Fang, Jicheng & Tang, Rongchuan & Du, Pengwei, 2024. "Bipartite graph-based community-to-community matching in local energy market considering socially networked prosumers," Applied Energy, Elsevier, vol. 353(PB).
    5. 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.
    6. 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.
    7. 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.
    8. Wang, Juan & Zheng, Junjun & Yu, Liukai & Goh, Mark & Tang, Yunying & Huang, Yongchao, 2023. "Distributed Reputation-Distance iterative auction system for Peer-To-Peer power trading," Applied Energy, Elsevier, vol. 345(C).
    9. D'Adamo, Idiano & Mammetti, Marco & Ottaviani, Dario & Ozturk, Ilhan, 2023. "Photovoltaic systems and sustainable communities: New social models for ecological transition. The impact of incentive policies in profitability analyses," Renewable Energy, Elsevier, vol. 202(C), pages 1291-1304.
    10. Kılkış, Şiir & Ulpiani, Giulia & Vetters, Nadja, 2024. "Visions for climate neutrality and opportunities for co-learning in European cities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 195(C).
    11. Jing, Rui & Hua, Weiqi & Lin, Jian & Lin, Jianyi & Zhao, Yingru & Zhou, Yue & Wu, Jianzhong, 2022. "Cost-efficient decarbonization of local energy systems by whole-system based design optimization," Applied Energy, Elsevier, vol. 326(C).
    12. Yehui Li & Dalin Qin & H. Vincent Poor & Yi Wang, 2024. "Introducing edge intelligence to smart meters via federated split learning," Nature Communications, Nature, vol. 15(1), pages 1-14, December.
    13. Keiner, Dominik & Thoma, Christian & Bogdanov, Dmitrii & Breyer, Christian, 2023. "Seasonal hydrogen storage for residential on- and off-grid solar photovoltaics prosumer applications: Revolutionary solution or niche market for the energy transition until 2050?," Applied Energy, Elsevier, vol. 340(C).
    14. May, Ross & Huang, Pei, 2023. "A multi-agent reinforcement learning approach for investigating and optimising peer-to-peer prosumer energy markets," Applied Energy, Elsevier, vol. 334(C).
    15. Daishi Sagawa & Kenji Tanaka & Fumiaki Ishida & Hideya Saito & Naoya Takenaga & Kosuke Saegusa, 2023. "P2P Electricity Trading Considering User Preferences for Renewable Energy and Demand-Side Shifts," Energies, MDPI, vol. 16(8), pages 1-25, April.
    16. Kanakadhurga, Dharmaraj & Prabaharan, Natarajan, 2022. "Peer-to-Peer trading with Demand Response using proposed smart bidding strategy," Applied Energy, Elsevier, vol. 327(C).
    17. Hahnel, Ulf J.J. & Fell, Michael J., 2022. "Pricing decisions in peer-to-peer and prosumer-centred electricity markets: Experimental analysis in Germany and the United Kingdom," Renewable and Sustainable Energy Reviews, Elsevier, vol. 162(C).

    More about this item

    Statistics

    Access and download statistics

    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:nat:natene:v:7:y:2022:i:1:d:10.1038_s41560-021-00950-2. 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.

    We have no bibliographic references for this item. You can help adding them by using 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.nature.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.