IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i7p3054-d1108870.html
   My bibliography  Save this article

A Robust Participation in the Load Following Ancillary Service and Energy Markets for a Virtual Power Plant in Western Australia

Author

Listed:
  • Behnaz Behi

    (School of Engineering and Energy, Murdoch University, Murdoch, WA 6150, Australia)

  • Philip Jennings

    (School of Engineering and Energy, Murdoch University, Murdoch, WA 6150, Australia)

  • Ali Arefi

    (School of Engineering and Energy, Murdoch University, Murdoch, WA 6150, Australia)

  • Ali Azizivahed

    (School of Electrical and Data Engineering, University of Technology Sydney, Broadway, NSW 2007, Australia)

  • Almantas Pivrikas

    (School of Engineering and Energy, Murdoch University, Murdoch, WA 6150, Australia)

  • S. M. Muyeen

    (Department of Electrical Engineering, Qatar University, Doha P.O. Box 2713, Qatar)

  • Arian Gorjy

    (Innogreen Technologies Pty Ltd., Perth, WA 6000, Australia)

Abstract

Virtual power plants (VPPs) are an effective platform for attracting private investment and customer engagement to speed up the integration of green renewable resources. In this paper, a robust bidding strategy to participate in both energy and ancillary service markets in the wholesale electricity market is proposed for a realistic VPP in Western Australia. The strategy is accurate and fast, so the VPP can bid in a very short time period. To engage customers in the demand management schemes of the VPP, the gamified approach is utilized to make the exercise enjoyable while not compromising their comfort levels. The modelling of revenue, expenses, and profit for the load-following ancillary service (LFAS) is provided, and the effective bidding strategy is developed. The simulation results show a significant improvement in the financial indicators of the VPP when participating in both the LFAS and energy markets. The payback period can be improved by 3 years to the payback period of 6 years and the internal rate of return (IRR) by 7.5% to the IRR of 18% by participating in both markets. The accuracy and speed of the proposed bidding strategy method is evident when compared with a mathematical method.

Suggested Citation

  • Behnaz Behi & Philip Jennings & Ali Arefi & Ali Azizivahed & Almantas Pivrikas & S. M. Muyeen & Arian Gorjy, 2023. "A Robust Participation in the Load Following Ancillary Service and Energy Markets for a Virtual Power Plant in Western Australia," Energies, MDPI, vol. 16(7), pages 1-20, March.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:7:p:3054-:d:1108870
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/7/3054/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/16/7/3054/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Behnaz Behi & Ali Baniasadi & Ali Arefi & Arian Gorjy & Philip Jennings & Almantas Pivrikas, 2020. "Cost–Benefit Analysis of a Virtual Power Plant Including Solar PV, Flow Battery, Heat Pump, and Demand Management: A Western Australian Case Study," Energies, MDPI, vol. 13(10), pages 1-24, May.
    2. Moghaddam, Saeed Zolfaghari & Akbari, Tohid, 2018. "Network-constrained optimal bidding strategy of a plug-in electric vehicle aggregator: A stochastic/robust game theoretic approach," Energy, Elsevier, vol. 151(C), pages 478-489.
    3. Behnaz Behi & Ali Arefi & Philip Jennings & Arian Gorjy & Almantas Pivrikas, 2021. "Advanced Monitoring and Control System for Virtual Power Plants for Enabling Customer Engagement and Market Participation," Energies, MDPI, vol. 14(4), pages 1-19, February.
    4. Wang, Han & Riaz, Shariq & Mancarella, Pierluigi, 2020. "Integrated techno-economic modeling, flexibility analysis, and business case assessment of an urban virtual power plant with multi-market co-optimization," Applied Energy, Elsevier, vol. 259(C).
    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. Iria, José & Scott, Paul & Attarha, Ahmad, 2020. "Network-constrained bidding optimization strategy for aggregators of prosumers," Energy, Elsevier, vol. 207(C).
    2. Khalil Gholami & Behnaz Behi & Ali Arefi & Philip Jennings, 2022. "Grid-Forming Virtual Power Plants: Concepts, Technologies and Advantages," Energies, MDPI, vol. 15(23), pages 1-26, November.
    3. Bianca Goia & Tudor Cioara & Ionut Anghel, 2022. "Virtual Power Plant Optimization in Smart Grids: A Narrative Review," Future Internet, MDPI, vol. 14(5), pages 1-22, April.
    4. Xiao, Xiangsheng & Wang, Jianxiao & Lin, Rui & Hill, David J. & Kang, Chongqing, 2020. "Large-scale aggregation of prosumers toward strategic bidding in joint energy and regulation markets," Applied Energy, Elsevier, vol. 271(C).
    5. Olga Bogdanova & Karīna Viskuba & Laila Zemīte, 2023. "A Review of Barriers and Enables in Demand Response Performance Chain," Energies, MDPI, vol. 16(18), pages 1-33, September.
    6. Wang, Qi & Huang, Chunyi & Wang, Chengmin & Li, Kangping & Xie, Ning, 2024. "Joint optimization of bidding and pricing strategy for electric vehicle aggregator considering multi-agent interactions," Applied Energy, Elsevier, vol. 360(C).
    7. Behnaz Behi & Ali Baniasadi & Ali Arefi & Arian Gorjy & Philip Jennings & Almantas Pivrikas, 2020. "Cost–Benefit Analysis of a Virtual Power Plant Including Solar PV, Flow Battery, Heat Pump, and Demand Management: A Western Australian Case Study," Energies, MDPI, vol. 13(10), pages 1-24, May.
    8. Cui, Xueyuan & Liu, Shu & Ruan, Guangchun & Wang, Yi, 2024. "Data-driven aggregation of thermal dynamics within building virtual power plants," Applied Energy, Elsevier, vol. 353(PB).
    9. Hu, Junfeng & Yan, Qingyou & Kahrl, Fredrich & Liu, Xu & Wang, Peng & Lin, Jiang, 2021. "Evaluating the ancillary services market for large-scale renewable energy integration in China's northeastern power grid," Utilities Policy, Elsevier, vol. 69(C).
    10. Tomasz Popławski & Sebastian Dudzik & Piotr Szeląg & Janusz Baran, 2021. "A Case Study of a Virtual Power Plant (VPP) as a Data Acquisition Tool for PV Energy Forecasting," Energies, MDPI, vol. 14(19), pages 1-24, September.
    11. Thomas Adisorn & Lena Tholen & Johannes Thema & Hauke Luetkehaus & Sibylle Braungardt & Katja Huenecke & Katja Schumacher, 2020. "Towards a More Realistic Cost–Benefit Analysis—Attempting to Integrate Transaction Costs and Energy Efficiency Services," Energies, MDPI, vol. 14(1), pages 1-15, December.
    12. Lechl, Michael & Fürmann, Tim & de Meer, Hermann & Weidlich, Anke, 2023. "A review of models for energy system flexibility requirements and potentials using the new FLEXBLOX taxonomy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 184(C).
    13. Lin Cheng & Yuling Li & Shiyou Yang, 2024. "Distributed Cooperative Optimal Operation of Multiple Virtual Power Plants Based on Multi-Stage Robust Optimization," Sustainability, MDPI, vol. 16(13), pages 1-24, June.
    14. Michał Jasiński & Tomasz Sikorski & Dominika Kaczorowska & Jacek Rezmer & Vishnu Suresh & Zbigniew Leonowicz & Paweł Kostyła & Jarosław Szymańda & Przemysław Janik & Jacek Bieńkowski & Przemysław Prus, 2021. "A Case Study on Data Mining Application in a Virtual Power Plant: Cluster Analysis of Power Quality Measurements," Energies, MDPI, vol. 14(4), pages 1-14, February.
    15. Máximo A. Domínguez-Garabitos & Víctor S. Ocaña-Guevara & Félix Santos-García & Adriana Arango-Manrique & Miguel Aybar-Mejía, 2022. "A Methodological Proposal for Implementing Demand-Shifting Strategies in the Wholesale Electricity Market," Energies, MDPI, vol. 15(4), pages 1-28, February.
    16. Behnaz Behi & Ali Arefi & Philip Jennings & Arian Gorjy & Almantas Pivrikas, 2021. "Advanced Monitoring and Control System for Virtual Power Plants for Enabling Customer Engagement and Market Participation," Energies, MDPI, vol. 14(4), pages 1-19, February.
    17. Kumar, T. Bharath & Singh, Anoop, 2021. "Ancillary services in the Indian power sector – A look at recent developments and prospects," Energy Policy, Elsevier, vol. 149(C).
    18. Xukun Zhang & Fancheng Meng & Linquan Sun & Zhaowu Zhu & Desheng Chen & Lina Wang, 2022. "Influence of Several Phosphate-Containing Additives on the Stability and Electrochemical Behavior of Positive Electrolytes for Vanadium Redox Flow Battery," Energies, MDPI, vol. 15(21), pages 1-14, October.
    19. Guntram Pressmair & Christof Amann & Klemens Leutgöb, 2021. "Business Models for Demand Response: Exploring the Economic Limits for Small- and Medium-Sized Prosumers," Energies, MDPI, vol. 14(21), pages 1-28, October.
    20. Yuqing Wang & Min Zhang & Jindi Ao & Zhaozhen Wang & Houqi Dong & Ming Zeng, 2022. "Profit Allocation Strategy of Virtual Power Plant Based on Multi-Objective Optimization in Electricity Market," Sustainability, MDPI, vol. 14(10), pages 1-22, May.

    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:16:y:2023:i:7:p:3054-:d:1108870. 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.