IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i19p6806-d1247398.html
   My bibliography  Save this article

Multi-Time-Scale Rolling Optimal Scheduling of Virtual Power Plants in Energy and Flexible Ramping Product Markets

Author

Listed:
  • Xiaoqing Shi

    (Guangxi Key Laboratory of Power System Optimization and Energy Saving Technology, Guangxi University, Nanning 530004, China)

  • Xiaoqing Bai

    (Guangxi Key Laboratory of Power System Optimization and Energy Saving Technology, Guangxi University, Nanning 530004, China)

  • Puming Wang

    (Guangxi Key Laboratory of Power System Optimization and Energy Saving Technology, Guangxi University, Nanning 530004, China)

  • Qinghua Shang

    (Guangxi Key Laboratory of Power System Optimization and Energy Saving Technology, Guangxi University, Nanning 530004, China)

Abstract

Virtual power plants (VPPs) offer a feasible solution for integrating various types of distributed energy resources (DERs) into the power grid in the electricity market. This paper proposes a multi-time-scale rolling optimal scheduling for VPPs, enabling optimal self-scheduling plans across intra-week rolling scheduling, intra-day rolling dispatch, and real-time dispatch. The proposed method facilitates participation in energy and flexible ramping product (FRP) markets while considering the specific characteristics with complementary advantages for the aggregated renewable resources, gas turbines, energy storages, and flexible demands of each time scale. The flexible ramping products within the VPP framework are established, while the energy storage systems address fluctuations during dispatch periods. Case studies are conducted to verify the efficiency of the proposed method. The results show that the proposed method can obtain optimal self-scheduling plans within the multi-time framework and has better performance in economy and security operation in comparisons among cases.

Suggested Citation

  • Xiaoqing Shi & Xiaoqing Bai & Puming Wang & Qinghua Shang, 2023. "Multi-Time-Scale Rolling Optimal Scheduling of Virtual Power Plants in Energy and Flexible Ramping Product Markets," Energies, MDPI, vol. 16(19), pages 1-21, September.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:19:p:6806-:d:1247398
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/19/6806/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/16/19/6806/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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).
    2. Kasaei, Mohammad Javad & Gandomkar, Majid & Nikoukar, Javad, 2017. "Optimal management of renewable energy sources by virtual power plant," Renewable Energy, Elsevier, vol. 114(PB), pages 1180-1188.
    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. Shuo Yin & Yang He & Zhiheng Li & Senmao Li & Peng Wang & Ziyi Chen, 2024. "A Novel Multi-Timescale Optimal Scheduling Model for a Power–Gas Mutual Transformation Virtual Power Plant with Power-to-Gas Conversion and Comprehensive Demand Response," Energies, MDPI, vol. 17(15), pages 1-19, 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. Wafa Nafkha-Tayari & Seifeddine Ben Elghali & Ehsan Heydarian-Forushani & Mohamed Benbouzid, 2022. "Virtual Power Plants Optimization Issue: A Comprehensive Review on Methods, Solutions, and Prospects," Energies, MDPI, vol. 15(10), pages 1-20, May.
    2. Naval, Natalia & Yusta, Jose M., 2021. "Virtual power plant models and electricity markets - A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 149(C).
    3. Soha, Tamás & Munkácsy, Béla & Harmat, Ádám & Csontos, Csaba & Horváth, Gergely & Tamás, László & Csüllög, Gábor & Daróczi, Henriett & Sáfián, Fanni & Szabó, Mária, 2017. "GIS-based assessment of the opportunities for small-scale pumped hydro energy storage in middle-mountain areas focusing on artificial landscape features," Energy, Elsevier, vol. 141(C), pages 1363-1373.
    4. Tomasz Sikorski & Michal Jasiński & Edyta Ropuszyńska-Surma & Magdalena Węglarz & Dominika Kaczorowska & Paweł Kostyla & Zbigniew Leonowicz & Robert Lis & Jacek Rezmer & Wilhelm Rojewski & Marian Sobi, 2020. "A Case Study on Distributed Energy Resources and Energy-Storage Systems in a Virtual Power Plant Concept: Technical Aspects," Energies, MDPI, vol. 13(12), pages 1-30, June.
    5. 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.
    6. Rui Gao & Hongxia Guo & Ruihong Zhang & Tian Mao & Qianyao Xu & Baorong Zhou & Ping Yang, 2019. "A Two-Stage Dispatch Mechanism for Virtual Power Plant Utilizing the CVaR Theory in the Electricity Spot Market," Energies, MDPI, vol. 12(17), pages 1-18, September.
    7. 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).
    8. Fang, Fang & Yu, Songyuan & Liu, Mingxi, 2020. "An improved Shapley value-based profit allocation method for CHP-VPP," Energy, Elsevier, vol. 213(C).
    9. Lin, Wen-Ting & Chen, Guo & Zhou, Xiaojun, 2022. "Distributed carbon-aware energy trading of virtual power plant under denial of service attacks: A passivity-based neurodynamic approach," Energy, Elsevier, vol. 257(C).
    10. T. Kesavan & K. Lakshmi, 2022. "Optimization of a Renewable Energy Source-Based Virtual Power Plant for Electrical Energy Management in an Unbalanced Distribution Network," Sustainability, MDPI, vol. 14(18), pages 1-17, September.
    11. 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).
    12. 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.
    13. Iraj Faraji Davoudkhani & Farhad Zishan & Saeedeh Mansouri & Farzad Abdollahpour & Luis Fernando Grisales-Noreña & Oscar Danilo Montoya, 2023. "Allocation of Renewable Energy Resources in Distribution Systems While Considering the Uncertainty of Wind and Solar Resources via the Multi-Objective Salp Swarm Algorithm," Energies, MDPI, vol. 16(1), pages 1-17, January.
    14. Yang, Qing & Wang, Hao & Wang, Taotao & Zhang, Shengli & Wu, Xiaoxiao & Wang, Hui, 2021. "Blockchain-based decentralized energy management platform for residential distributed energy resources in a virtual power plant," Applied Energy, Elsevier, vol. 294(C).
    15. Fahad Alismail & Mohamed A. Abdulgalil & Muhammad Khalid, 2021. "Optimal Coordinated Planning of Energy Storage and Tie-Lines to Boost Flexibility with High Wind Power Integration," Sustainability, MDPI, vol. 13(5), pages 1-17, February.
    16. Iria, José & Scott, Paul & Attarha, Ahmad, 2020. "Network-constrained bidding optimization strategy for aggregators of prosumers," Energy, Elsevier, vol. 207(C).
    17. Mohammed, Nooriya A. & Al-Bazi, Ammar, 2021. "Management of renewable energy production and distribution planning using agent-based modelling," Renewable Energy, Elsevier, vol. 164(C), pages 509-520.
    18. 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).
    19. 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.
    20. Luo, Zhe & Hong, SeungHo & Ding, YueMin, 2019. "A data mining-driven incentive-based demand response scheme for a virtual power plant," Applied Energy, Elsevier, vol. 239(C), pages 549-559.

    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:19:p:6806-:d:1247398. 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.