IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v240y2025ics0960148124022614.html
   My bibliography  Save this article

A tripartite stochastic evolutionary game for trading strategies under renewable portfolio standards in China’s electric power industry

Author

Listed:
  • Teng, Minmin
  • Lv, Kunfeng
  • Han, Chuanfeng
  • Liu, Pihui

Abstract

China must adopt effective policies for implementing tradable green certificates (TGC) under renewable portfolio standards (RPS). Current research overlooks the strategic interactions among TGC trading entities and the role of market mechanisms in promoting green certificates. This paper develops a tripartite stochastic evolutionary game involving thermal power plants, green power plants, and the grid to analyze how key parameters—such as price levels, regulatory penalties, and interference intensity (the degree of external disruptions)—affect the strategies of these players under stochastic interference. The results are as follows: The results are as follows: (1) At an interference intensity of 0.8, if the excess consumption price of renewable energy is lower than the average prices of wind and photovoltaic TGC, RPS and TGC policies have the greatest impact. (2) In the coupled market for new energy consumption and green power certificates, parity TGC implementation significantly reduces green power plants' willingness to trade. (3) At an interference intensity of 0.5, with a unit penalty three times the average prices of wind and photovoltaic TGC and a quota completion reward of 0.4, the incentive for thermal power plants and the grid to trade TGC is maximized. This research optimizes TGC implementation policies, promotes renewable energy development.

Suggested Citation

  • Teng, Minmin & Lv, Kunfeng & Han, Chuanfeng & Liu, Pihui, 2025. "A tripartite stochastic evolutionary game for trading strategies under renewable portfolio standards in China’s electric power industry," Renewable Energy, Elsevier, vol. 240(C).
  • Handle: RePEc:eee:renene:v:240:y:2025:i:c:s0960148124022614
    DOI: 10.1016/j.renene.2024.122193
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148124022614
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.renene.2024.122193?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    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:eee:renene:v:240:y:2025:i:c:s0960148124022614. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/renewable-energy .

    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.