IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i14p5413-d1195334.html
   My bibliography  Save this article

A Joint Clearing Model of Energy-Frequency Modulation Based on Flexible Block Order

Author

Listed:
  • Qunli Wu

    (Department of Economics and Management, North China Electric Power University, Baoding 071003, China
    Beijing Key Laboratory of New Energy and Low-Carbon Development, North China Electric Power University, Baoding 071003, China)

  • Kaiyue Qu

    (Department of Economics and Management, North China Electric Power University, Baoding 071003, China)

Abstract

The large-scale integration of renewable energy into the grid has led to a gradual diversification of power generation trading units on the power-side, with varying operational characteristics, costs, and trading needs among diverse power generation trading units. Traditional power system clearing models face challenges. Block order is a bidding type that allows for multiple volume–price combinations. At the same time, the randomness and volatility of renewable energy poses challenges to the safe and stable operation of the system. Building a power system clearing model that meets the diverse and flexible needs of the power system has become an important consideration. Therefore, this paper considers the design of three flexible energy blocks: a sustaining block, flux block, and adjustment block to meet the differential needs of diverse trading units and establishes a flexible block order clearing model. Secondly, it establishes a joint clearing model of electrical energy and frequency modulation (FM) to ensure the stable and reliable operation of the system, and solves the model based on relevant constraints to determine the winning electrical energy price and FM price. The CPLEX and Yalmip algorithms are used to solve the model. Finally, a case study was conducted based on an improved IEEE 14-bus system. The results showed that the model proposed in this paper can satisfy the differential needs of diverse trading units, effectively improve the renewable energy consumption capacity, and reduce the prices of the energy market and frequency modulation market. Also, the standard deviation of the net load of the system is relatively low, which improves the reliability of the power system’s operation.

Suggested Citation

  • Qunli Wu & Kaiyue Qu, 2023. "A Joint Clearing Model of Energy-Frequency Modulation Based on Flexible Block Order," Energies, MDPI, vol. 16(14), pages 1-22, July.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:14:p:5413-:d:1195334
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/14/5413/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/16/14/5413/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Le, Hong Lam & Ilea, Valentin & Bovo, Cristian, 2019. "Integrated European intra-day electricity market: Rules, modeling and analysis," Applied Energy, Elsevier, vol. 238(C), pages 258-273.
    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. Tianlei Zang & Shijun Wang & Zian Wang & Chuangzhi Li & Yunfei Liu & Yujian Xiao & Buxiang Zhou, 2024. "Integrated Planning and Operation Dispatching of Source–Grid–Load–Storage in a New Power System: A Coupled Socio–Cyber–Physical Perspective," Energies, MDPI, vol. 17(12), pages 1-43, June.

    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. Reza Nadimi & Masahito Takahashi & Koji Tokimatsu & Mika Goto, 2024. "The Reliability and Profitability of Virtual Power Plant with Short-Term Power Market Trading and Non-Spinning Reserve Diesel Generator," Energies, MDPI, vol. 17(9), pages 1-19, April.
    2. Cao, K.H. & Qi, H.S. & Tsai, C.H. & Woo, C.K. & Zarnikau, J., 2021. "Energy trading efficiency in the US Midcontinent electricity markets," Applied Energy, Elsevier, vol. 302(C).
    3. Le Hong Lam & Valentin Ilea & Cristian Bovo, 2020. "New Clearing Model to Mitigate the Non-Convexity in European Day-ahead Electricity Market," Energies, MDPI, vol. 13(18), pages 1-28, September.
    4. Priyanka Shinde & Ioannis Boukas & David Radu & Miguel Manuel de Villena & Mikael Amelin, 2021. "Analyzing Trade in Continuous Intra-Day Electricity Market: An Agent-Based Modeling Approach," Energies, MDPI, vol. 14(13), pages 1-31, June.
    5. Lange, Sebastian & Sokolowski, Peter & Yu, Xinghuo, 2022. "An efficient, open-bid procurement auction for small-scale electricity markets," Applied Energy, Elsevier, vol. 314(C).
    6. Liu, Shuo & Yang, Zhifang & Xia, Qing & Lin, Wei & Shi, Lianjun & Zeng, Dan, 2020. "Power trading region considering long-term contract for interconnected power networks," Applied Energy, Elsevier, vol. 261(C).
    7. Ioannis Boukas & Damien Ernst & Thibaut Th'eate & Adrien Bolland & Alexandre Huynen & Martin Buchwald & Christelle Wynants & Bertrand Corn'elusse, 2020. "A Deep Reinforcement Learning Framework for Continuous Intraday Market Bidding," Papers 2004.05940, arXiv.org.
    8. Cristian Bovo & Valentin Ilea & Enrico Maria Carlini & Mauro Caprabianca & Federico Quaglia & Luca Luzi & Giuseppina Nuzzo, 2021. "Optimal Computation of Network Indicators for Electricity Market Bidding Zones Configuration Considering Explicit N-1 Security Constraints," Energies, MDPI, vol. 14(14), pages 1-31, July.
    9. Sikorska-Pastuszka, Magdalena & Papież, Monika, 2023. "Dynamic volatility connectedness in the European electricity market," Energy Economics, Elsevier, vol. 127(PA).
    10. Hakan Acaroğlu & Fausto Pedro García Márquez, 2021. "Comprehensive Review on Electricity Market Price and Load Forecasting Based on Wind Energy," Energies, MDPI, vol. 14(22), pages 1-23, November.
    11. Fusco, Andrea & Gioffrè, Domenico & Francesco Castelli, Alessandro & Bovo, Cristian & Martelli, Emanuele, 2023. "A multi-stage stochastic programming model for the unit commitment of conventional and virtual power plants bidding in the day-ahead and ancillary services markets," Applied Energy, Elsevier, vol. 336(C).
    12. Poplavskaya, Ksenia & Totschnig, Gerhard & Leimgruber, Fabian & Doorman, Gerard & Etienne, Gilles & de Vries, Laurens, 2020. "Integration of day-ahead market and redispatch to increase cross-border exchanges in the European electricity market," Applied Energy, Elsevier, vol. 278(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:16:y:2023:i:14:p:5413-:d:1195334. 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.