IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v12y2019i22p4318-d286368.html
   My bibliography  Save this article

Distributed Peer-to-Peer Electricity Trading Considering Network Loss in a Distribution System

Author

Listed:
  • Jin Zhang

    (School of Electrical Engineering and Automation, Anhui University, Hefei 230601, China)

  • Cungang Hu

    (School of Electrical Engineering and Automation, Anhui University, Hefei 230601, China
    Collaborative Innovation Center of Industrial Energy-saving and Power Quality Control, Anhui University, Hefei 230601, China)

  • Changbao Zheng

    (School of Electrical Engineering and Automation, Anhui University, Hefei 230601, China
    Collaborative Innovation Center of Industrial Energy-saving and Power Quality Control, Anhui University, Hefei 230601, China)

  • Tao Rui

    (Collaborative Innovation Center of Industrial Energy-saving and Power Quality Control, Anhui University, Hefei 230601, China
    School of Internet, Anhui University, Hefei 230601, China)

  • Weixiang Shen

    (Faculty of Science, Engineering and Technology, Swinburne University of Technology, Melbourne, VIC 3122, Australia)

  • Bo Wang

    (State Grid Anhui Dispatching and Control Center, No.9 Huangshan Road, Hefei 230069, China)

Abstract

In this paper, a distributed peer-to-peer (P2P) electricity trading model was proposed to study economic interactions between load aggregators (LAs) and microgrid operators (MGOs) considering network losses in a distribution system. In this model, the economic interactions among market participants were formulated as a Nash bargaining game, where LAs and MGOs can bargain with each other on the trading volume of electricity and payment. To achieve the Nash bargaining solution, the game was divided into two sub-problems: social welfare maximization and payment bargaining. Then, the alternating direction method of multipliers was used to solve the two sub-problems with limited information exchange. Finally, we tested the proposed model on a 12 × 12 km 2 distribution system, and the results verify its effectiveness.

Suggested Citation

  • Jin Zhang & Cungang Hu & Changbao Zheng & Tao Rui & Weixiang Shen & Bo Wang, 2019. "Distributed Peer-to-Peer Electricity Trading Considering Network Loss in a Distribution System," Energies, MDPI, vol. 12(22), pages 1-18, November.
  • Handle: RePEc:gam:jeners:v:12:y:2019:i:22:p:4318-:d:286368
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/12/22/4318/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/12/22/4318/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Nash, John, 1950. "The Bargaining Problem," Econometrica, Econometric Society, vol. 18(2), pages 155-162, April.
    2. Zhou, Yue & Wu, Jianzhong & Long, Chao, 2018. "Evaluation of peer-to-peer energy sharing mechanisms based on a multiagent simulation framework," Applied Energy, Elsevier, vol. 222(C), pages 993-1022.
    3. Zhang, Ni & Yan, Yu & Su, Wencong, 2015. "A game-theoretic economic operation of residential distribution system with high participation of distributed electricity prosumers," Applied Energy, Elsevier, vol. 154(C), pages 471-479.
    4. Fan, Songli & Ai, Qian & Piao, Longjian, 2018. "Bargaining-based cooperative energy trading for distribution company and demand response," Applied Energy, Elsevier, vol. 226(C), pages 469-482.
    5. Zhang, Chenghua & Wu, Jianzhong & Zhou, Yue & Cheng, Meng & Long, Chao, 2018. "Peer-to-Peer energy trading in a Microgrid," Applied Energy, Elsevier, vol. 220(C), pages 1-12.
    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. Azim, M. Imran & Tushar, Wayes & Saha, Tapan K. & Yuen, Chau & Smith, David, 2022. "Peer-to-peer kilowatt and negawatt trading: A review of challenges and recent advances in distribution networks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 169(C).
    2. 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).
    3. Koo-Hyung Chung & Don Hur, 2020. "Towards the Design of P2P Energy Trading Scheme Based on Optimal Energy Scheduling for Prosumers," Energies, MDPI, vol. 13(19), pages 1-15, October.
    4. 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).
    5. Arnob Das & Susmita Datta Peu & Md. Abdul Mannan Akanda & Abu Reza Md. Towfiqul Islam, 2023. "Peer-to-Peer Energy Trading Pricing Mechanisms: Towards a Comprehensive Analysis of Energy and Network Service Pricing (NSP) Mechanisms to Get Sustainable Enviro-Economical Energy Sector," Energies, MDPI, vol. 16(5), pages 1-27, February.

    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. Gjorgievski, Vladimir Z. & Cundeva, Snezana & Markovska, Natasa & Georghiou, George E., 2022. "Virtual net-billing: A fair energy sharing method for collective self-consumption," Energy, Elsevier, vol. 254(PB).
    2. Wang, Jianxiao & Zhong, Haiwang & Wu, Chenye & Du, Ershun & Xia, Qing & Kang, Chongqing, 2019. "Incentivizing distributed energy resource aggregation in energy and capacity markets: An energy sharing scheme and mechanism design," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    3. Lyu, Cheng & Jia, Youwei & Xu, Zhao, 2021. "Fully decentralized peer-to-peer energy sharing framework for smart buildings with local battery system and aggregated electric vehicles," Applied Energy, Elsevier, vol. 299(C).
    4. Lefeng, Shi & Shengnan, Lv & Chunxiu, Liu & Yue, Zhou & Cipcigan, Liana & Acker, Thomas L., 2020. "A framework for electric vehicle power supply chain development," Utilities Policy, Elsevier, vol. 64(C).
    5. Wang, Zibo & Yu, Xiaodan & Mu, Yunfei & Jia, Hongjie, 2020. "A distributed Peer-to-Peer energy transaction method for diversified prosumers in Urban Community Microgrid System," Applied Energy, Elsevier, vol. 260(C).
    6. Bhatti, Bilal Ahmad & Broadwater, Robert, 2019. "Energy trading in the distribution system using a non-model based game theoretic approach," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    7. Chen, Yang & Park, Byungkwon & Kou, Xiao & Hu, Mengqi & Dong, Jin & Li, Fangxing & Amasyali, Kadir & Olama, Mohammed, 2020. "A comparison study on trading behavior and profit distribution in local energy transaction games," Applied Energy, Elsevier, vol. 280(C).
    8. Davarzani, Sima & Pisica, Ioana & Taylor, Gareth A. & Munisami, Kevin J., 2021. "Residential Demand Response Strategies and Applications in Active Distribution Network Management," Renewable and Sustainable Energy Reviews, Elsevier, vol. 138(C).
    9. Soto, Esteban A. & Bosman, Lisa B. & Wollega, Ebisa & Leon-Salas, Walter D., 2021. "Peer-to-peer energy trading: A review of the literature," Applied Energy, Elsevier, vol. 283(C).
    10. Abdullah M. Alabdullatif & Enrico H. Gerding & Alvaro Perez-Diaz, 2020. "Market Design and Trading Strategies for Community Energy Markets with Storage and Renewable Supply," Energies, MDPI, vol. 13(4), pages 1-31, February.
    11. Esmat, Ayman & de Vos, Martijn & Ghiassi-Farrokhfal, Yashar & Palensky, Peter & Epema, Dick, 2021. "A novel decentralized platform for peer-to-peer energy trading market with blockchain technology," Applied Energy, Elsevier, vol. 282(PA).
    12. 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).
    13. Rodrigues, Daniel L. & Ye, Xianming & Xia, Xiaohua & Zhu, Bing, 2020. "Battery energy storage sizing optimisation for different ownership structures in a peer-to-peer energy sharing community," Applied Energy, Elsevier, vol. 262(C).
    14. Filipe Bandeiras & Álvaro Gomes & Mário Gomes & Paulo Coelho, 2023. "Exploring Energy Trading Markets in Smart Grid and Microgrid Systems and Their Implications for Sustainability in Smart Cities," Energies, MDPI, vol. 16(2), pages 1-41, January.
    15. El-Baz, Wessam & Tzscheutschler, Peter & Wagner, Ulrich, 2019. "Integration of energy markets in microgrids: A double-sided auction with device-oriented bidding strategies," Applied Energy, Elsevier, vol. 241(C), pages 625-639.
    16. Castellini, Marta & Di Corato, Luca & Moretto, Michele & Vergalli, Sergio, 2021. "Energy exchange among heterogeneous prosumers under price uncertainty," Energy Economics, Elsevier, vol. 104(C).
    17. Soto, Esteban A. & Bosman, Lisa B. & Wollega, Ebisa & Leon-Salas, Walter D., 2022. "Comparison of net-metering with peer-to-peer models using the grid and electric vehicles for the electricity exchange," Applied Energy, Elsevier, vol. 310(C).
    18. Qiu, Dawei & Ye, Yujian & Papadaskalopoulos, Dimitrios & Strbac, Goran, 2021. "Scalable coordinated management of peer-to-peer energy trading: A multi-cluster deep reinforcement learning approach," Applied Energy, Elsevier, vol. 292(C).
    19. Lüth, Alexandra & Zepter, Jan Martin & Crespo del Granado, Pedro & Egging, Ruud, 2018. "Local electricity market designs for peer-to-peer trading: The role of battery flexibility," Applied Energy, Elsevier, vol. 229(C), pages 1233-1243.
    20. Meena, Nand K. & Yang, Jin & Zacharis, Evan, 2019. "Optimisation framework for the design and operation of open-market urban and remote community microgrids," Applied Energy, Elsevier, vol. 252(C), pages 1-1.

    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:12:y:2019:i:22:p:4318-:d:286368. 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.