IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v17y2024i8p1921-d1377643.html
   My bibliography  Save this article

Research on Market Evaluation Model of Reserve Auxiliary Service Based on Two-Stage Optimization of New Power System

Author

Listed:
  • Boyang Qu

    (School of Electrical Engineering, Shenyang University of Technology, Shenyang 110870, China)

  • Lisi Fu

    (The College of Information and Electrical Engineering, Shenyang Agricultural University, Shenyang 110866, China)

Abstract

Large-scale fluctuating and intermittent new energy power generation in a new power system is gradually connected to the grid. In view of the impact of the uncertainty of wind power on the spinning reserve capacity of thermal power units in the new power system’s day-ahead dispatching and reserve auxiliary service market, the original dispatching mode and intensity can no longer meet the system demand. To address this problem, the establishment of a wind power grid-connected new power system’s standby auxiliary service market reward and punishment assessment mechanism is undertaken to fundamentally reduce the demand for auxiliary services of the new power system pressure. In the first part of this paper, a two-stage optimal scheduling strategy is proposed for the first day of the year that takes into account the operational risk and standby economics. First, a data-driven method is used to generate the forecast value of the wind power interval before the day, and a unit start–stop optimization model (the first-stage optimization model) is established by taking into account the CvaR (conditional value at risk) theory to optimize the risk loss of wind abandonment and loss of load and the fuel cost of each unit, and an optimization algorithm is used to carry out the three scenarios and the corresponding four scenarios to optimize the configuration of the start–stop state and power output of each unit. The optimization algorithm is used to optimize the starting and stopping status and output of each unit for three circumstances and four corresponding scenarios. Then, in the second stage, a standby auxiliary service market incentive and penalty assessment model is established to effectively coordinate the sharing of rotating standby capacity and cost among thermal power units through the incentive and penalty mechanism so as to make a reasonable and efficient allocation of wind power output, curtailable load, and synchronized standby capacity. The new power system with improved IEEE30 nodes is simulated and verified, and it is found that the two-stage optimization model obtains a scheduling strategy that takes into account the system operating cost, standby economy, and reliability, and at the same time, through the standby auxiliary service market incentive and penalty assessment mechanism, the extra cost caused by standby cost mismatch can be avoided. This evaluation model provides a reference for the safe, efficient, flexible, and nimble operation of the new power system, improves the economic efficiency and improves the auxiliary service market mechanism.

Suggested Citation

  • Boyang Qu & Lisi Fu, 2024. "Research on Market Evaluation Model of Reserve Auxiliary Service Based on Two-Stage Optimization of New Power System," Energies, MDPI, vol. 17(8), pages 1-25, April.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:8:p:1921-:d:1377643
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/17/8/1921/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/17/8/1921/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Harbord, David & Pagnozzi, Marco, 2014. "Britain's electricity capacity auctions: lessons from Colombia and New England," MPRA Paper 56224, University Library of Munich, Germany.
    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. Holmberg, P. & Tangerås, T., 2021. "Strategic Reserves versus Market-wide Capacity Mechanisms," Cambridge Working Papers in Economics 2132, Faculty of Economics, University of Cambridge.
    2. Sebastian Schäfer & Lisa Schulten, 2015. "Efficient Promotion of Renewable Energy with Reverse Auctions," MAGKS Papers on Economics 201520, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    3. Lange, Sebastian & Sokolowski, Peter & Yu, Xinghuo, 2022. "An efficient, open-bid procurement auction for small-scale electricity markets," Applied Energy, Elsevier, vol. 314(C).
    4. Nicolas Stevens & Yves Smeers & Anthony Papavasiliou, 2024. "Indivisibilities in investment and the role of a capacity market," Journal of Regulatory Economics, Springer, vol. 66(2), pages 238-272, December.
    5. Liu, Shuangquan & Yang, Qiang & Cai, Huaxiang & Yan, Minghui & Zhang, Maolin & Wu, Dianning & Xie, Mengfei, 2019. "Market reform of Yunnan electricity in southwestern China: Practice, challenges and implications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 113(C), pages 1-1.
    6. Saldarriaga-C., Carlos A. & Salazar, Harold, 2016. "Security of the Colombian energy supply: The need for liquefied natural gas regasification terminals for power and natural gas sectors," Energy, Elsevier, vol. 100(C), pages 349-362.
    7. Sebastian Schäfer & Lisa Altvater, 2021. "A Capacity Market for the Transition towards Renewable-Based Electricity Generation with Enhanced Political Feasibility," Energies, MDPI, vol. 14(18), pages 1-24, September.
    8. Sebastian Schäfer & Lisa Schulten, 2014. "A Capacity Market to Improve the Transition towards Sustainable Electricity Generation," MAGKS Papers on Economics 201439, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    9. Yiakoumi, Despina & Rouaix, Agathe & Phimister, Euan, 2022. "Evaluating capacity auction design for electricity: An experimental analysis," Energy Economics, Elsevier, vol. 115(C).
    10. Peter Cramton, 2017. "Electricity market design," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 33(4), pages 589-612.

    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:17:y:2024:i:8:p:1921-:d:1377643. 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.