IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v13y2020i18p4963-d417195.html
   My bibliography  Save this article

Iterative Auction for P2P Renewable Energy Trading with Dynamic Energy Storage Management

Author

Listed:
  • Chen Zhang

    (School of Energy and Power Engineering, Huazhong University of Science and Technology, Wuhan 430074, China)

  • Yong Wang

    (Department of Systems Science and Industrial Engineering, Binghamton University, Binghamton, NY 13902, USA)

  • Tao Yang

    (School of Energy and Power Engineering, Huazhong University of Science and Technology, Wuhan 430074, China)

Abstract

In this paper, a peer-to-peer (P2P) renewable energy trading mechanism for microgrids when energy suppliers are equipped with storage devices is studied. A dynamic energy storage management strategy based on the local trading price is proposed and each supplier decides the amount of energy to be sold and stored in real time. An iterative auction algorithm is presented to obtain the market equilibrium and optimal energy allocation schedule. The economic analysis of introducing energy storage devices in this trading market is further studied. Numerical examples of two 7 × 24-h energy trading scenarios with 20 consumers and 20 solar energy producers are used to illustrate the feasibility of this proposed trading mechanism, with sensitivity analysis of different parameters on social welfare. A comparison of the hourly optimal local trading price of these two markets is demonstrated to explain the dynamic process. It is found that in those days with high solar radiation, compared with the market with no storage device, the total cost for buyers in the market when storage devices are used shows a decline of 1.52% and the total profit for sellers shows an increase of 1.27%, which leads to a substantial relative improvement of 118.94% in the overall social welfare. Moreover, a brief economic analysis shows that the advantage of using energy storage in this example is guaranteed after five years of operation. Longer operation time does not mean more benefits considering the deterioration of battery packs and increase of operation and maintenance costs, and the profit reaches its maximum value at the 15th year.

Suggested Citation

  • Chen Zhang & Yong Wang & Tao Yang, 2020. "Iterative Auction for P2P Renewable Energy Trading with Dynamic Energy Storage Management," Energies, MDPI, vol. 13(18), pages 1-20, September.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:18:p:4963-:d:417195
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/13/18/4963/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/13/18/4963/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Wei, F. & Jing, Z.X. & Wu, Peter Z. & Wu, Q.H., 2017. "A Stackelberg game approach for multiple energies trading in integrated energy systems," Applied Energy, Elsevier, vol. 200(C), pages 315-329.
    2. Jian Wang & Qianggang Wang & Niancheng Zhou & Yuan Chi, 2017. "A Novel Electricity Transaction Mode of Microgrids Based on Blockchain and Continuous Double Auction," Energies, MDPI, vol. 10(12), pages 1-22, November.
    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. Luis Gomes & Hugo Morais & Calvin Gonçalves & Eduardo Gomes & Lucas Pereira & Zita Vale, 2022. "Impact of Forecasting Models Errors in a Peer-to-Peer Energy Sharing Market," Energies, MDPI, vol. 15(10), pages 1-18, May.
    2. 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. Jin, Xiaolong & Wu, Qiuwei & Jia, Hongjie, 2020. "Local flexibility markets: Literature review on concepts, models and clearing methods," Applied Energy, Elsevier, vol. 261(C).
    2. Yiqi Dong & Zuoji Dong, 2023. "Bibliometric Analysis of Game Theory on Energy and Natural Resource," Sustainability, MDPI, vol. 15(2), pages 1-19, January.
    3. Wang, Lixiao & Jing, Z.X. & Zheng, J.H. & Wu, Q.H. & Wei, Feng, 2018. "Decentralized optimization of coordinated electrical and thermal generations in hierarchical integrated energy systems considering competitive individuals," Energy, Elsevier, vol. 158(C), pages 607-622.
    4. Ning Wang & Weisheng Xu & Weihui Shao & Zhiyu Xu, 2019. "A Q-Cube Framework of Reinforcement Learning Algorithm for Continuous Double Auction among Microgrids," Energies, MDPI, vol. 12(15), pages 1-26, July.
    5. Miguel Carpintero-Rentería & David Santos-Martín & Josep M. Guerrero, 2019. "Microgrids Literature Review through a Layers Structure," Energies, MDPI, vol. 12(22), pages 1-22, November.
    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. Wang, Lu & Gu, Wei & Wu, Zhi & Qiu, Haifeng & Pan, Guangsheng, 2020. "Non-cooperative game-based multilateral contract transactions in power-heating integrated systems," Applied Energy, Elsevier, vol. 268(C).
    8. Hong-Chao Gao & Joon-Ho Choi & Sang-Yun Yun & Seon-Ju Ahn, 2020. "A New Power Sharing Scheme of Multiple Microgrids and an Iterative Pairing-Based Scheduling Method," Energies, MDPI, vol. 13(7), pages 1-20, April.
    9. Hou, Langbo & Tong, Xi & Chen, Heng & Fan, Lanxin & Liu, Tao & Liu, Wenyi & Liu, Tong, 2024. "Optimized scheduling of smart community energy systems considering demand response and shared energy storage," Energy, Elsevier, vol. 295(C).
    10. Wang, Shouxiang & Wang, Shaomin & Zhao, Qianyu & Dong, Shuai & Li, Hao, 2023. "Optimal dispatch of integrated energy station considering carbon capture and hydrogen demand," Energy, Elsevier, vol. 269(C).
    11. Wang, Can & Yan, Chao & Li, Gengfeng & Liu, Shiyu & Bie, Zhaohong, 2020. "Risk assessment of integrated electricity and heat system with independent energy operators based on Stackelberg game," Energy, Elsevier, vol. 198(C).
    12. Lu, Qing & Lü, Shuaikang & Leng, Yajun, 2019. "A Nash-Stackelberg game approach in regional energy market considering users’ integrated demand response," Energy, Elsevier, vol. 175(C), pages 456-470.
    13. Wang, L.X. & Zheng, J.H. & Li, M.S. & Lin, X. & Jing, Z.X. & Wu, P.Z. & Wu, Q.H. & Zhou, X.X., 2019. "Multi-time scale dynamic analysis of integrated energy systems: An individual-based model," Applied Energy, Elsevier, vol. 237(C), pages 848-861.
    14. Peter O’Donovan & Dominic T. J. O’Sullivan, 2019. "A Systematic Analysis of Real-World Energy Blockchain Initiatives," Future Internet, MDPI, vol. 11(8), pages 1-14, August.
    15. Frederik Plewnia, 2019. "The Energy System and the Sharing Economy: Interfaces and Overlaps and What to Learn from Them," Energies, MDPI, vol. 12(3), pages 1-17, January.
    16. 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).
    17. Gourisetti, Sri Nikhil Gupta & Sebastian-Cardenas, D. Jonathan & Bhattarai, Bishnu & Wang, Peng & Widergren, Steve & Borkum, Mark & Randall, Alysha, 2021. "Blockchain smart contract reference framework and program logic architecture for transactive energy systems," Applied Energy, Elsevier, vol. 304(C).
    18. Anees, Amir & Dillon, Tharam & Chen, Yi-Ping Phoebe, 2019. "A novel decision strategy for a bilateral energy contract," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    19. Wenting Zhao & Jun Lv & Xilong Yao & Juanjuan Zhao & Zhixin Jin & Yan Qiang & Zheng Che & Chunwu Wei, 2019. "Consortium Blockchain-Based Microgrid Market Transaction Research," Energies, MDPI, vol. 12(20), pages 1-22, October.
    20. Meifang Wei & Youyue Deng & Min Long & Yahui Wang & Yong Li, 2022. "Transaction Model Based on Stackelberg Game Method for Balancing Supply and Demand Sides of Multi-Energy Microgrid," Energies, MDPI, vol. 15(4), pages 1-20, February.

    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:13:y:2020:i:18:p:4963-:d:417195. 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.