View in EDS

The evolutionary game equilibrium theory on power market bidding involving renewable energy companies.

Saved in:
Bibliographic Details
Title: The evolutionary game equilibrium theory on power market bidding involving renewable energy companies.
Authors: Cheng, Lefeng1 (AUTHOR), Peng, Pan1 (AUTHOR), Lu, Wentian1 (AUTHOR) luwentian@gzhu.edu.cn, Sun, Jian2 (AUTHOR), Wu, Fan2 (AUTHOR), Shi, Mingming2 (AUTHOR), Yuan, Xiaodong2 (AUTHOR), Chen, Yang1 (AUTHOR) zdchenyang@163.com
Source: International Journal of Electrical Power & Energy Systems. Jun2025, Vol. 167, pN.PAG-N.PAG. 1p.
Subjects: Independent system operators, Renewable energy transition (Government policy), Energy industries, Electricity markets, Bidding strategies
Abstract: • Summarizes key power generation market (PGM) transaction models and bidding mechanisms. • Analyzes spontaneous evolutionarily stable equilibrium (ESE) formation mechanisms in PGM. • Investigates strategic generator bidding under the market clearing price (MCP) mechanism. • Proposes a comprehensive game-theoretic model for renewable energy coordination. • Demonstrates MCP guides PGM to low-price ESE via payoff adjustments. In the electricity bidding market, power generation companies and distribution-oriented grid enterprises face increasingly complex and dynamic decision-making challenges that cannot be fully captured by static or one-shot approaches. To address these challenges, this study proposes a novel evolutionary game-theoretic framework featuring a "mixed-strategy distortion" mechanism, which introduces adaptive periodic adjustments in bidding ranges. This extension to classical evolutionary models reveals how cyclical constraints and strategic disruptions influence the emergence of cooperative equilibria and market dynamics. The study develops a theoretical framework for analyzing long-term stable equilibria in asymmetric evolutionary games involving distinct groups of power generators, underpinned by a renewable energy grid-connected benefit coordination model. Theoretical analyses are validated through dynamic simulations that examine the interplay of key parameters, including generation costs, local market demands, bidding ranges, and production capacities. The results demonstrate how variations in these factors influence the evolution of bidding strategies, providing insights into the stability of competitive equilibria in electricity markets. Furthermore, the findings highlight that rational adjustments to bidding intervals can mitigate distortions, reduce electricity prices, and promote dynamic market stability. By advancing the understanding of adaptive bidding strategies in competitive electricity markets, this research offers actionable insights for policy development, market regulation, and strategic decision-making for power generation enterprises and grid operators. These contributions provide a foundation for the design of more efficient market mechanisms, promoting both economic efficiency and sustainable energy transitions. [ABSTRACT FROM AUTHOR]
Copyright of International Journal of Electrical Power & Energy Systems is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
FullText Text:
  Availability: 0
Header DbId: egs
DbLabel: Engineering Source
An: 184434713
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: The evolutionary game equilibrium theory on power market bidding involving renewable energy companies.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Cheng%2C+Lefeng%22">Cheng, Lefeng</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Peng%2C+Pan%22">Peng, Pan</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Lu%2C+Wentian%22">Lu, Wentian</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> luwentian@gzhu.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Sun%2C+Jian%22">Sun, Jian</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Wu%2C+Fan%22">Wu, Fan</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Shi%2C+Mingming%22">Shi, Mingming</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Yuan%2C+Xiaodong%22">Yuan, Xiaodong</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Chen%2C+Yang%22">Chen, Yang</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> zdchenyang@163.com</i>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Electrical+Power+%26+Energy+Systems%22">International Journal of Electrical Power & Energy Systems</searchLink>. Jun2025, Vol. 167, pN.PAG-N.PAG. 1p.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Independent+system+operators%22">Independent system operators</searchLink><br /><searchLink fieldCode="DE" term="%22Renewable+energy+transition+%28Government+policy%29%22">Renewable energy transition (Government policy)</searchLink><br /><searchLink fieldCode="DE" term="%22Energy+industries%22">Energy industries</searchLink><br /><searchLink fieldCode="DE" term="%22Electricity+markets%22">Electricity markets</searchLink><br /><searchLink fieldCode="DE" term="%22Bidding+strategies%22">Bidding strategies</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: • Summarizes key power generation market (PGM) transaction models and bidding mechanisms. • Analyzes spontaneous evolutionarily stable equilibrium (ESE) formation mechanisms in PGM. • Investigates strategic generator bidding under the market clearing price (MCP) mechanism. • Proposes a comprehensive game-theoretic model for renewable energy coordination. • Demonstrates MCP guides PGM to low-price ESE via payoff adjustments. In the electricity bidding market, power generation companies and distribution-oriented grid enterprises face increasingly complex and dynamic decision-making challenges that cannot be fully captured by static or one-shot approaches. To address these challenges, this study proposes a novel evolutionary game-theoretic framework featuring a "mixed-strategy distortion" mechanism, which introduces adaptive periodic adjustments in bidding ranges. This extension to classical evolutionary models reveals how cyclical constraints and strategic disruptions influence the emergence of cooperative equilibria and market dynamics. The study develops a theoretical framework for analyzing long-term stable equilibria in asymmetric evolutionary games involving distinct groups of power generators, underpinned by a renewable energy grid-connected benefit coordination model. Theoretical analyses are validated through dynamic simulations that examine the interplay of key parameters, including generation costs, local market demands, bidding ranges, and production capacities. The results demonstrate how variations in these factors influence the evolution of bidding strategies, providing insights into the stability of competitive equilibria in electricity markets. Furthermore, the findings highlight that rational adjustments to bidding intervals can mitigate distortions, reduce electricity prices, and promote dynamic market stability. By advancing the understanding of adaptive bidding strategies in competitive electricity markets, this research offers actionable insights for policy development, market regulation, and strategic decision-making for power generation enterprises and grid operators. These contributions provide a foundation for the design of more efficient market mechanisms, promoting both economic efficiency and sustainable energy transitions. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of International Journal of Electrical Power & Energy Systems is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=184434713
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1016/j.ijepes.2025.110588
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 1
        StartPage: N.PAG
    Subjects:
      – SubjectFull: Independent system operators
        Type: general
      – SubjectFull: Renewable energy transition (Government policy)
        Type: general
      – SubjectFull: Energy industries
        Type: general
      – SubjectFull: Electricity markets
        Type: general
      – SubjectFull: Bidding strategies
        Type: general
    Titles:
      – TitleFull: The evolutionary game equilibrium theory on power market bidding involving renewable energy companies.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Cheng, Lefeng
      – PersonEntity:
          Name:
            NameFull: Peng, Pan
      – PersonEntity:
          Name:
            NameFull: Lu, Wentian
      – PersonEntity:
          Name:
            NameFull: Sun, Jian
      – PersonEntity:
          Name:
            NameFull: Wu, Fan
      – PersonEntity:
          Name:
            NameFull: Shi, Mingming
      – PersonEntity:
          Name:
            NameFull: Yuan, Xiaodong
      – PersonEntity:
          Name:
            NameFull: Chen, Yang
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 06
              Text: Jun2025
              Type: published
              Y: 2025
          Identifiers:
            – Type: issn-print
              Value: 01420615
          Numbering:
            – Type: volume
              Value: 167
          Titles:
            – TitleFull: International Journal of Electrical Power & Energy Systems
              Type: main
ResultId 1