IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i21p8274-d964173.html
   My bibliography  Save this article

Price-Guided Peer-To-Peer Trading Scheme and Its Effects on Transaction Costs and Network Losses

Author

Listed:
  • SungJoong Kim

    (Electric Power Network and Economics Laboratory, Department of Electrical and Computer Engineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 08826, Korea)

  • YongTae Yoon

    (Electric Power Network and Economics Laboratory, Department of Electrical and Computer Engineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 08826, Korea)

  • YoungGyu Jin

    (Power System Economics Laboratory, Department of Electrical Engineering, Jeju National University, 102 Jejudaehak-ro, Jeju 62343, Korea)

Abstract

Distributed energy resources (DERs), such as small-scale renewable energy generators, storage systems, and controllable loads, have been attracting great attention. Accordingly, interest in peer-to-peer (P2P) energy trading between prosumers with DERs is growing. The prosumers may perform the P2P electricity trading within the loss-guided framework, where network losses are primarily considered during the peer matching process. However, the loss-guided framework has limitations in that prosumer welfare is neglected in favor of prioritizing the network losses caused by the P2P transactions. Thus, in this study, a price-based framework for P2P electricity trading is suggested, where the prosumer welfare is considered by including not only network loss costs but also energy costs in the matching procedure. The effects of the suggested price-based framework on network efficiency, prosumer welfare, and social welfare are examined by comparing simulation results with the loss-guided framework and the random transactions. Further, how those three properties are affected by the change in loss price is analyzed and a guideline for the suitable choice of the loss price is suggested.

Suggested Citation

  • SungJoong Kim & YongTae Yoon & YoungGyu Jin, 2022. "Price-Guided Peer-To-Peer Trading Scheme and Its Effects on Transaction Costs and Network Losses," Energies, MDPI, vol. 15(21), pages 1-19, November.
  • Handle: RePEc:gam:jeners:v:15:y:2022:i:21:p:8274-:d:964173
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/21/8274/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/15/21/8274/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jiayi, Huang & Chuanwen, Jiang & Rong, Xu, 2008. "A review on distributed energy resources and MicroGrid," Renewable and Sustainable Energy Reviews, Elsevier, vol. 12(9), pages 2472-2483, December.
    2. Yael Parag & Benjamin K. Sovacool, 2016. "Electricity market design for the prosumer era," Nature Energy, Nature, vol. 1(4), pages 1-6, April.
    3. Alarcon-Rodriguez, Arturo & Ault, Graham & Galloway, Stuart, 2010. "Multi-objective planning of distributed energy resources: A review of the state-of-the-art," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(5), pages 1353-1366, June.
    4. SungJoong Kim & YeonOuk Chu & HyunJoong Kim & HyungTae Kim & HeeSeung Moon & JinHo Sung & YongTae Yoon & YoungGyu Jin, 2022. "Analyzing Various Aspects of Network Losses in Peer-to-Peer Electricity Trading," Energies, MDPI, vol. 15(3), pages 1-23, January.
    5. Akorede, Mudathir Funsho & Hizam, Hashim & Pouresmaeil, Edris, 2010. "Distributed energy resources and benefits to the environment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(2), pages 724-734, February.
    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. Mallikarjun, Sreekanth & Lewis, Herbert F., 2014. "Energy technology allocation for distributed energy resources: A strategic technology-policy framework," Energy, Elsevier, vol. 72(C), pages 783-799.
    2. Fridgen, Gilbert & Halbrügge, Stephanie & Olenberger, Christian & Weibelzahl, Martin, 2020. "The insurance effect of renewable distributed energy resources against uncertain electricity price developments," Energy Economics, Elsevier, vol. 91(C).
    3. Di Somma, M. & Graditi, G. & Heydarian-Forushani, E. & Shafie-khah, M. & Siano, P., 2018. "Stochastic optimal scheduling of distributed energy resources with renewables considering economic and environmental aspects," Renewable Energy, Elsevier, vol. 116(PA), pages 272-287.
    4. Botelho, D.F. & de Oliveira, L.W. & Dias, B.H. & Soares, T.A. & Moraes, C.A., 2022. "Prosumer integration into the Brazilian energy sector: An overview of innovative business models and regulatory challenges," Energy Policy, Elsevier, vol. 161(C).
    5. Sward, Jeffrey A. & Siff, Jackson & Gu, Jiajun & Zhang, K. Max, 2019. "Strategic planning for utility-scale solar photovoltaic development – Historical peak events revisited," Applied Energy, Elsevier, vol. 250(C), pages 1292-1301.
    6. Mavromatidis, Georgios & Orehounig, Kristina & Carmeliet, Jan, 2018. "A review of uncertainty characterisation approaches for the optimal design of distributed energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 88(C), pages 258-277.
    7. Kalkbrenner, Bernhard J. & Yonezawa, Koichi & Roosen, Jutta, 2017. "Consumer preferences for electricity tariffs: Does proximity matter?," Energy Policy, Elsevier, vol. 107(C), pages 413-424.
    8. Kang, Jing & Wang, Shengwei, 2018. "Robust optimal design of distributed energy systems based on life-cycle performance analysis using a probabilistic approach considering uncertainties of design inputs and equipment degradations," Applied Energy, Elsevier, vol. 231(C), pages 615-627.
    9. Di Somma, M. & Yan, B. & Bianco, N. & Graditi, G. & Luh, P.B. & Mongibello, L. & Naso, V., 2017. "Multi-objective design optimization of distributed energy systems through cost and exergy assessments," Applied Energy, Elsevier, vol. 204(C), pages 1299-1316.
    10. Yanine, Franco F. & Sauma, Enzo E., 2013. "Review of grid-tie micro-generation systems without energy storage: Towards a new approach to sustainable hybrid energy systems linked to energy efficiency," Renewable and Sustainable Energy Reviews, Elsevier, vol. 26(C), pages 60-95.
    11. Wolsink, Maarten, 2020. "Distributed energy systems as common goods: Socio-political acceptance of renewables in intelligent microgrids," Renewable and Sustainable Energy Reviews, Elsevier, vol. 127(C).
    12. Hirsch, Adam & Parag, Yael & Guerrero, Josep, 2018. "Microgrids: A review of technologies, key drivers, and outstanding issues," Renewable and Sustainable Energy Reviews, Elsevier, vol. 90(C), pages 402-411.
    13. Paliwal, Priyanka & Patidar, N.P. & Nema, R.K., 2014. "Planning of grid integrated distributed generators: A review of technology, objectives and techniques," Renewable and Sustainable Energy Reviews, Elsevier, vol. 40(C), pages 557-570.
    14. Maarten Wolsink, 2020. "Framing in Renewable Energy Policies: A Glossary," Energies, MDPI, vol. 13(11), pages 1-31, June.
    15. Adil, Ali M. & Ko, Yekang, 2016. "Socio-technical evolution of Decentralized Energy Systems: A critical review and implications for urban planning and policy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 1025-1037.
    16. Tan, Wen-Shan & Hassan, Mohammad Yusri & Majid, Md Shah & Abdul Rahman, Hasimah, 2013. "Optimal distributed renewable generation planning: A review of different approaches," Renewable and Sustainable Energy Reviews, Elsevier, vol. 18(C), pages 626-645.
    17. Georgarakis, Elena & Bauwens, Thomas & Pronk, Anne-Marie & AlSkaif, Tarek, 2021. "Keep it green, simple and socially fair: A choice experiment on prosumers’ preferences for peer-to-peer electricity trading in the Netherlands," Energy Policy, Elsevier, vol. 159(C).
    18. Gao, Jiajia & Kang, Jing & Zhang, Chong & Gang, Wenjie, 2018. "Energy performance and operation characteristics of distributed energy systems with district cooling systems in subtropical areas under different control strategies," Energy, Elsevier, vol. 153(C), pages 849-860.
    19. Woon-Gyu Lee & Thai-Thanh Nguyen & Hak-Man Kim, 2022. "Multiagent-Based Distributed Coordination of Inverter-Based Resources for Optimal Operation of Microgrids Considering Communication Failures," Energies, MDPI, vol. 15(10), pages 1-19, May.
    20. Moghaddam, Amjad Anvari & Seifi, Alireza & Niknam, Taher, 2012. "Multi-operation management of a typical micro-grids using Particle Swarm Optimization: A comparative study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(2), pages 1268-1281.

    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:gam:jeners:v:15:y:2022:i:21:p:8274-:d:964173. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.