IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v10y2017i1p144-d88583.html
   My bibliography  Save this article

Bidding Strategy for Aggregators of Electric Vehicles in Day-Ahead Electricity Markets

Author

Listed:
  • Yunpeng Guo

    (School of Electrical and Electronic Engineering, North China Electric Power University, Beijing 102206, China)

  • Weijia Liu

    (School of Electrical Engineering, Zhejiang University, Hangzhou 310027, China)

  • Fushuan Wen

    (Department of Electrical and Electronic Engineering, Universiti Teknologi Brunei, Bandar Seri Begawan BE1410, Brunei)

  • Abdus Salam

    (Department of Electrical and Electronic Engineering, Universiti Teknologi Brunei, Bandar Seri Begawan BE1410, Brunei)

  • Jianwei Mao

    (Division of Electric Vehicle Service, State Grid Zhejiang Electric Power Company, Hangzhou 310007, China)

  • Liang Li

    (Division of Electric Vehicle Service, State Grid Zhejiang Electric Power Company, Hangzhou 310007, China)

Abstract

To make full use of the flexible charging and discharging capabilities of the growing number of electric vehicles (EVs), a bidding strategy for EV aggregators to participate in a day-ahead electricity energy market is proposed in this work. The proposed bidding strategy is able to reduce the operating cost of the EV aggregators and to handle the uncertainties of day-ahead market prices properly at the same time. Agreements between the EV owners and the aggregators are discussed, and a hierarchical market structure is proposed. While assuming the aggregators as economic rational entities, the bidding strategy is established based on the market prices, extra battery charging/discharging costs and the expected profits. The bidding clearing system will display the current/temporal market clearance results of the day-ahead market before the final clearance, and hence the market participants can revise their bids and mitigate the risks, to some extent, of forecasted market price forecast errors. Numerical results with a modified IEEE 30-bus system have demonstrated the feasibility and effectiveness of the proposed strategy.

Suggested Citation

  • Yunpeng Guo & Weijia Liu & Fushuan Wen & Abdus Salam & Jianwei Mao & Liang Li, 2017. "Bidding Strategy for Aggregators of Electric Vehicles in Day-Ahead Electricity Markets," Energies, MDPI, vol. 10(1), pages 1-20, January.
    • Handle: RePEc:gam:jeners:v:10:y:2017:i:1:p:144-:d:88583
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/10/1/144/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/10/1/144/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ramos Muñoz, Edgar & Razeghi, Ghazal & Zhang, Li & Jabbari, Faryar, 2016. "Electric vehicle charging algorithms for coordination of the grid and distribution transformer levels," Energy, Elsevier, vol. 113(C), pages 930-942.
    2. Andersson, S.-L. & Elofsson, A.K. & Galus, M.D. & Göransson, L. & Karlsson, S. & Johnsson, F. & Andersson, G., 2010. "Plug-in hybrid electric vehicles as regulating power providers: Case studies of Sweden and Germany," Energy Policy, Elsevier, vol. 38(6), pages 2751-2762, June.
    3. Shafie-khah, Miadreza & Parsa Moghaddam, Mohsen & Sheikh-El-Eslami, Mohamad Kazem & Rahmani-Andebili, Mehdi, 2012. "Modeling of interactions between market regulations and behavior of plug-in electric vehicle aggregators in a virtual power market environment," Energy, Elsevier, vol. 40(1), pages 139-150.
    4. Pudjianto, Danny & Djapic, Predrag & Aunedi, Marko & Gan, Chin Kim & Strbac, Goran & Huang, Sikai & Infield, David, 2013. "Smart control for minimizing distribution network reinforcement cost due to electrification," Energy Policy, Elsevier, vol. 52(C), pages 76-84.
    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. Isaias Gomes & Rui Melicio & Victor Mendes, 2020. "Comparison between Inflexible and Flexible Charging of Electric Vehicles—A Study from the Perspective of an Aggregator," Energies, MDPI, vol. 13(20), pages 1-13, October.
    2. Stergios Statharas & Yannis Moysoglou & Pelopidas Siskos & Pantelis Capros, 2021. "Simulating the Evolution of Business Models for Electricity Recharging Infrastructure Development by 2030: A Case Study for Greece," Energies, MDPI, vol. 14(9), pages 1-24, April.
    3. Dapeng Chen & Zhaoxia Jing & Huijuan Tan, 2019. "Optimal Bidding/Offering Strategy for EV Aggregators under a Novel Business Model," Energies, MDPI, vol. 12(7), pages 1-19, April.
    4. Riccardo Iacobucci & Benjamin McLellan & Tetsuo Tezuka, 2018. "The Synergies of Shared Autonomous Electric Vehicles with Renewable Energy in a Virtual Power Plant and Microgrid," Energies, MDPI, vol. 11(8), pages 1-20, August.
    5. Wu, Hongbin & Wang, Jingjie & Lu, Junhua & Ding, Ming & Wang, Lei & Hu, Bin & Sun, Ming & Qi, Xianjun, 2022. "Bilevel load-agent-based distributed coordination decision strategy for aggregators," Energy, Elsevier, vol. 240(C).
    6. Tepe, Benedikt & Figgener, Jan & Englberger, Stefan & Sauer, Dirk Uwe & Jossen, Andreas & Hesse, Holger, 2022. "Optimal pool composition of commercial electric vehicles in V2G fleet operation of various electricity markets," Applied Energy, Elsevier, vol. 308(C).
    7. Fei Zeng & Zhinong Wei & Guoqiang Sun & Mingshen Wang & Haiteng Han, 2023. "Frequency Regulation of Electric Vehicle Aggregator Considering User Requirements with Limited Data Collection," Energies, MDPI, vol. 16(2), pages 1-21, January.
    8. Bomiao Liang & Weijia Liu & Fushuan Wen & Md. Abdus Salam, 2017. "Well-Being Analysis of Power Systems Considering Increasing Deployment of Gas Turbines," Energies, MDPI, vol. 10(7), pages 1-18, July.
    9. Yusuf A. Sha’aban & Augustine Ikpehai & Bamidele Adebisi & Khaled M. Rabie, 2017. "Bi-Directional Coordination of Plug-In Electric Vehicles with Economic Model Predictive Control," Energies, MDPI, vol. 10(10), pages 1-20, September.
    10. Feng Qi & Fushuan Wen & Xunyuan Liu & Md. Abdus Salam, 2017. "A Residential Energy Hub Model with a Concentrating Solar Power Plant and Electric Vehicles," Energies, MDPI, vol. 10(8), pages 1-17, August.
    11. Qing Deng & Changsen Feng & Fushuan Wen & Chung-Li Tseng & Lei Wang & Bo Zou & Xizhu Zhang, 2019. "Evaluation of Accommodation Capability for Electric Vehicles of a Distribution System Considering Coordinated Charging Strategies," Energies, MDPI, vol. 12(16), pages 1-20, August.

    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. Shi You & Junjie Hu & Charalampos Ziras, 2016. "An Overview of Modeling Approaches Applied to Aggregation-Based Fleet Management and Integration of Plug-in Electric Vehicles †," Energies, MDPI, vol. 9(11), pages 1-18, November.
    2. Shafie-khah, M. & Heydarian-Forushani, E. & Golshan, M.E.H. & Siano, P. & Moghaddam, M.P. & Sheikh-El-Eslami, M.K. & Catalão, J.P.S., 2016. "Optimal trading of plug-in electric vehicle aggregation agents in a market environment for sustainability," Applied Energy, Elsevier, vol. 162(C), pages 601-612.
    3. Zheng, Yanchong & Niu, Songyan & Shang, Yitong & Shao, Ziyun & Jian, Linni, 2019. "Integrating plug-in electric vehicles into power grids: A comprehensive review on power interaction mode, scheduling methodology and mathematical foundation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 112(C), pages 424-439.
    4. Juul, Nina, 2012. "Battery prices and capacity sensitivity: Electric drive vehicles," Energy, Elsevier, vol. 47(1), pages 403-410.
    5. Liu, Yingqi, 2017. "Demand response and energy efficiency in the capacity resource procurement: Case studies of forward capacity markets in ISO New England, PJM and Great Britain," Energy Policy, Elsevier, vol. 100(C), pages 271-282.
    6. Hall, Stephen & Roelich, Katy, 2016. "Business model innovation in electricity supply markets: The role of complex value in the United Kingdom," Energy Policy, Elsevier, vol. 92(C), pages 286-298.
    7. Chitchai Srithapon & Prasanta Ghosh & Apirat Siritaratiwat & Rongrit Chatthaworn, 2020. "Optimization of Electric Vehicle Charging Scheduling in Urban Village Networks Considering Energy Arbitrage and Distribution Cost," Energies, MDPI, vol. 13(2), pages 1-20, January.
    8. Shi, Ruifeng & Li, Shaopeng & Zhang, Penghui & Lee, Kwang Y., 2020. "Integration of renewable energy sources and electric vehicles in V2G network with adjustable robust optimization," Renewable Energy, Elsevier, vol. 153(C), pages 1067-1080.
    9. Galus, Matthias D. & Zima, Marek & Andersson, Göran, 2010. "On integration of plug-in hybrid electric vehicles into existing power system structures," Energy Policy, Elsevier, vol. 38(11), pages 6736-6745, November.
    10. Ioannis Karakitsios & Dimitrios Lagos & Aris Dimeas & Nikos Hatziargyriou, 2023. "How Can EVs Support High RES Penetration in Islands," Energies, MDPI, vol. 16(1), pages 1-17, January.
    11. Robu, Valentin & Chalkiadakis, Georgios & Kota, Ramachandra & Rogers, Alex & Jennings, Nicholas R., 2016. "Rewarding cooperative virtual power plant formation using scoring rules," Energy, Elsevier, vol. 117(P1), pages 19-28.
    12. Gerald Broneske & David Wozabal, 2017. "How Do Contract Parameters Influence the Economics of Vehicle-to-Grid?," Manufacturing & Service Operations Management, INFORMS, vol. 19(1), pages 150-164, February.
    13. Schill, Wolf-Peter, 2011. "Electric Vehicles in Imperfect Electricity Markets: The case of Germany," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 39(10), pages 6178-6189.
    14. Sovacool, Benjamin K. & Kester, Johannes & Noel, Lance & Zarazua de Rubens, Gerardo, 2020. "Actors, business models, and innovation activity systems for vehicle-to-grid (V2G) technology: A comprehensive review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 131(C).
    15. Müller, Mathias & Blume, Yannic & Reinhard, Janis, 2022. "Impact of behind-the-meter optimised bidirectional electric vehicles on the distribution grid load," Energy, Elsevier, vol. 255(C).
    16. Rahman, Syed & Khan, Irfan Ahmed & Khan, Ashraf Ali & Mallik, Ayan & Nadeem, Muhammad Faisal, 2022. "Comprehensive review & impact analysis of integrating projected electric vehicle charging load to the existing low voltage distribution system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 153(C).
    17. Li, Francis G.N. & Trutnevyte, Evelina & Strachan, Neil, 2015. "A review of socio-technical energy transition (STET) models," Technological Forecasting and Social Change, Elsevier, vol. 100(C), pages 290-305.
    18. Nosratabadi, Seyyed Mostafa & Hooshmand, Rahmat-Allah & Gholipour, Eskandar, 2016. "Stochastic profit-based scheduling of industrial virtual power plant using the best demand response strategy," Applied Energy, Elsevier, vol. 164(C), pages 590-606.
    19. Ito, Masakazu & Takano, Akihisa & Shinji, Takao & Yagi, Takahiro & Hayashi, Yasuhiro, 2017. "Electricity adjustment for capacity market auction by a district heating and cooling system," Applied Energy, Elsevier, vol. 206(C), pages 623-633.
    20. Zhang, Xian & Chan, Ka Wing & Wang, Huaizhi & Zhou, Bin & Wang, Guibin & Qiu, Jing, 2020. "Multiple group search optimization based on decomposition for multi-objective dispatch with electric vehicle and wind power uncertainties," Applied Energy, Elsevier, vol. 262(C).

    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:10:y:2017:i:1:p:144-:d:88583. 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.