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Evolutionary Game-Based Regulatory Strategy Optimization for Information Transmission Prices in Integrated Energy Systems

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  • Kun Cui

    (School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan 430074, China
    Key Laboratory of Image Processing and Intelligent Control, Ministry of Education, Huazhong University of Science and Technology, Wuhan 430074, China)

  • Ming Chi

    (School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan 430074, China
    Key Laboratory of Image Processing and Intelligent Control, Ministry of Education, Huazhong University of Science and Technology, Wuhan 430074, China)

  • Yong Zhao

    (School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan 430074, China)

  • Zhiwei Liu

    (School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan 430074, China
    Key Laboratory of Image Processing and Intelligent Control, Ministry of Education, Huazhong University of Science and Technology, Wuhan 430074, China)

Abstract

The rapid evolution of Integrated Energy Systems (IESs) demands robust management of information transmission, which is critical for real-time monitoring, coordination, and operational efficiency. However, the increasing complexity and costs associated with information exchange necessitate effective pricing mechanisms to ensure economic sustainability and optimal resource allocation. This paper presents an evolutionary game-theoretic framework to analyze regulatory strategies governing information transmission within IES. In the context of market dynamics, both market regulators and communication network operators are considered as actors with bounded rationality, emphasizing their strategic interplay within the system. The main contributions include formulating a model that treats communication network operators as independent entities, enhancing the understanding of IES member diversity and interactivity. This study introduces evolutionary game dynamics, providing new insights into optimizing regulatory policies. This paper also innovates by considering asset utilization in defining effective assets, potentially curbing excessive investment by communication network operators and preventing information transmission prices from soaring. A case study is provided to reveal the dynamics and equilibrium states of the regulatory game, offering theoretical support for refining regulatory strategies in IESs.

Suggested Citation

  • Kun Cui & Ming Chi & Yong Zhao & Zhiwei Liu, 2025. "Evolutionary Game-Based Regulatory Strategy Optimization for Information Transmission Prices in Integrated Energy Systems," Energies, MDPI, vol. 18(6), pages 1-20, March.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:6:p:1452-:d:1613303
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    References listed on IDEAS

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