IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v12y2024i9p1408-d1388615.html
   My bibliography  Save this article

An Effective Method of Equivalent Load-Based Time of Use Electricity Pricing to Promote Renewable Energy Consumption

Author

Listed:
  • Xiaoqing Zeng

    (School of Economics and Management, Changsha University of Science and Technology, Changsha 410075, China)

  • Zilin He

    (College of Information Engineering, Inner Mongolia University of Technology, Hohhot 010051, China)

  • Yali Wang

    (School of Economics and Management, Changsha University of Science and Technology, Changsha 410075, China)

  • Yongfei Wu

    (School of Economics and Management, Changsha University of Science and Technology, Changsha 410075, China)

  • Ao Liu

    (School of Economics and Management, Changsha University of Science and Technology, Changsha 410075, China)

Abstract

The variability and intermittency inherent in renewable energy sources poses significant challenges to balancing power supply and demand, often leading to wind and solar energy curtailment. To address these challenges, this paper focuses on enhancing Time of Use (TOU) electricity pricing strategies. We propose a novel method based on equivalent load, which leverages typical power grid load and incorporates a responsibility weight for renewable energy consumption. The responsibility weight acts as an equivalent coefficient that accurately reflects renewable energy output, which facilitates the division of time periods and the development of a demand response model. Subsequently, we formulate an optimized TOU electricity pricing model to increase the utilization rate of renewable energy and reduce the peak–valley load difference of the power grid. To solve the TOU pricing optimization model, we employ the Social Network Search (SNS) algorithm, a metaheuristic algorithm simulating users’ social network interactions to gain popularity. By incorporating the users’ mood when expressing opinions, this algorithm efficiently identifies optimal pricing solutions. Our results demonstrate that the equivalent load-based method not only encourages renewable energy consumption but also reduces power generation costs, stabilizes the power grid load, and benefits power generators, suppliers, and consumers without increasing end users’ electricity charges.

Suggested Citation

  • Xiaoqing Zeng & Zilin He & Yali Wang & Yongfei Wu & Ao Liu, 2024. "An Effective Method of Equivalent Load-Based Time of Use Electricity Pricing to Promote Renewable Energy Consumption," Mathematics, MDPI, vol. 12(9), pages 1-27, May.
  • Handle: RePEc:gam:jmathe:v:12:y:2024:i:9:p:1408-:d:1388615
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/12/9/1408/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2227-7390/12/9/1408/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Huilan Jiang & Bingqi Liu & Yawei Wang & Shuangqi Zheng, 2014. "Multiobjective TOU Pricing Optimization Based on NSGA2," Journal of Applied Mathematics, Hindawi, vol. 2014, pages 1-8, July.
    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. Wu, Xiaodan & Li, Juan & Chu, Chao-Hsien, 2019. "Modeling multi-stage healthcare systems with service interactions under blocking for bed allocation," European Journal of Operational Research, Elsevier, vol. 278(3), pages 927-941.
    2. Wanlei Xue & Xin Zhao & Yan Li & Ying Mu & Haisheng Tan & Yixin Jia & Xuejie Wang & Huiru Zhao & Yihang Zhao, 2023. "Research on the Optimal Design of Seasonal Time-of-Use Tariff Based on the Price Elasticity of Electricity Demand," Energies, MDPI, vol. 16(4), pages 1-17, February.
    3. Esmeralda Mukoni & Karen S. Garner, 2022. "Multi-Objective Non-Dominated Sorting Genetic Algorithm Optimization for Optimal Hybrid (Wind and Grid)-Hydrogen Energy System Modelling," Energies, MDPI, vol. 15(19), pages 1-18, September.

    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:jmathe:v:12:y:2024:i:9:p:1408-:d:1388615. 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.