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Bidding Agents for PV and Electric Vehicle-Owning Users in the Electricity P2P Trading Market

Author

Listed:
  • Daishi Sagawa

    (School of Engineering, The University of Tokyo, Tokyo 113-8656, Japan)

  • Kenji Tanaka

    (School of Engineering, The University of Tokyo, Tokyo 113-8656, Japan)

  • Fumiaki Ishida

    (The Kansai Electric Power Co., Inc., Osaka 530-8270, Japan)

  • Hideya Saito

    (The Kansai Electric Power Co., Inc., Osaka 530-8270, Japan)

  • Naoya Takenaga

    (Nihon Unisys, Ltd., Tokyo 135-8560, Japan)

  • Seigo Nakamura

    (Nihon Unisys, Ltd., Tokyo 135-8560, Japan)

  • Nobuaki Aoki

    (Nihon Unisys, Ltd., Tokyo 135-8560, Japan)

  • Misuzu Nameki

    (Nihon Unisys, Ltd., Tokyo 135-8560, Japan)

  • Kosuke Saegusa

    (Nihon Unisys, Ltd., Tokyo 135-8560, Japan)

Abstract

As the world strives to decarbonize, the effective use of renewable energy has become an important issue, and P2P power trading is expected to unlock the value of renewable energy and encourage its adoption by enabling power trading based on user needs and user assets. In this study, we constructed a bidding agent that optimizes bids based on electricity demand and generation forecasts, user preferences for renewable energy (renewable energy-oriented or economically oriented), and owned assets in a P2P electricity trading market, and automatically performs electricity trading. The agent algorithm was used to evaluate the differences in trading content between different asset holdings and preferences by performing power sharing in a real scale environment. The demonstration experiments show that: EV-owning and economy-oriented users can trade more favorably in the market with a lower average execution price than non-EV-owning users; forecasting enables economy-enhancing moves to store nighttime electricity in batteries in advance in anticipation of future power generation and market prices; EV-owning and renewable energy-oriented users can trade more favorably in the market with other users. EV-owning and renewable energy-oriented users can achieve higher RE ratios at a cost of about +1 yen/kWh compared to other users. By actually issuing charging and discharging commands to the EV and controlling the charging and discharging, the agent can control the actual use of electricity according to the user’s preferences.

Suggested Citation

  • Daishi Sagawa & Kenji Tanaka & Fumiaki Ishida & Hideya Saito & Naoya Takenaga & Seigo Nakamura & Nobuaki Aoki & Misuzu Nameki & Kosuke Saegusa, 2021. "Bidding Agents for PV and Electric Vehicle-Owning Users in the Electricity P2P Trading Market," Energies, MDPI, vol. 14(24), pages 1-17, December.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:24:p:8309-:d:698913
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    References listed on IDEAS

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    1. Zorić, Jelena & Hrovatin, Nevenka, 2012. "Household willingness to pay for green electricity in Slovenia," Energy Policy, Elsevier, vol. 47(C), pages 180-187.
    2. Iria, José & Soares, Filipe & Matos, Manuel, 2019. "Optimal bidding strategy for an aggregator of prosumers in energy and secondary reserve markets," Applied Energy, Elsevier, vol. 238(C), pages 1361-1372.
    3. Longo, Alberto & Markandya, Anil & Petrucci, Marta, 2008. "The internalization of externalities in the production of electricity: Willingness to pay for the attributes of a policy for renewable energy," Ecological Economics, Elsevier, vol. 67(1), pages 140-152, August.
    4. Dagher, Leila & Harajli, Hassan, 2015. "Willingness to pay for green power in an unreliable electricity sector: Part 1. The case of the Lebanese residential sector," Renewable and Sustainable Energy Reviews, Elsevier, vol. 50(C), pages 1634-1642.
    5. Iria, José & Soares, Filipe & Matos, Manuel, 2018. "Optimal supply and demand bidding strategy for an aggregator of small prosumers," Applied Energy, Elsevier, vol. 213(C), pages 658-669.
    6. Kobashi, Takuro & Yoshida, Takahiro & Yamagata, Yoshiki & Naito, Katsuhiko & Pfenninger, Stefan & Say, Kelvin & Takeda, Yasuhiro & Ahl, Amanda & Yarime, Masaru & Hara, Keishiro, 2020. "On the potential of “Photovoltaics + Electric vehicles” for deep decarbonization of Kyoto’s power systems: Techno-economic-social considerations," Applied Energy, Elsevier, vol. 275(C).
    7. Sousa, Tiago & Soares, Tiago & Pinson, Pierre & Moret, Fabio & Baroche, Thomas & Sorin, Etienne, 2019. "Peer-to-peer and community-based markets: A comprehensive review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 104(C), pages 367-378.
    8. Tabi, Andrea & Hille, Stefanie Lena & Wüstenhagen, Rolf, 2014. "What makes people seal the green power deal? — Customer segmentation based on choice experiment in Germany," Ecological Economics, Elsevier, vol. 107(C), pages 206-215.
    9. Englberger, Stefan & Abo Gamra, Kareem & Tepe, Benedikt & Schreiber, Michael & Jossen, Andreas & Hesse, Holger, 2021. "Electric vehicle multi-use: Optimizing multiple value streams using mobile storage systems in a vehicle-to-grid context," Applied Energy, Elsevier, vol. 304(C).
    10. Mengelkamp, Esther & Gärttner, Johannes & Rock, Kerstin & Kessler, Scott & Orsini, Lawrence & Weinhardt, Christof, 2018. "Designing microgrid energy markets," Applied Energy, Elsevier, vol. 210(C), pages 870-880.
    11. Juhar Abdella & Khaled Shuaib, 2018. "Peer to Peer Distributed Energy Trading in Smart Grids: A Survey," Energies, MDPI, vol. 11(6), pages 1-22, June.
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    Cited by:

    1. 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.
    2. Mika Goto & Hiroshi Kitamura & Daishi Sagawa & Taichi Obara & Kenji Tanaka, 2023. "Simulation Analysis of Electricity Demand and Supply in Japanese Communities Focusing on Solar PV, Battery Storage, and Electricity Trading," Energies, MDPI, vol. 16(13), pages 1-24, July.
    3. Shinji Kuno & Kenji Tanaka & Yuji Yamada, 2022. "Effectiveness and Feasibility of Market Makers for P2P Electricity Trading," Energies, MDPI, vol. 15(12), pages 1-24, June.

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    Keywords

    P2P energy trading; bidding agent; electric vehicle;
    All these keywords.

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