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A Cloud- and Game Model-Based Approach to Project Evaluations of Sustainable Power Supply Investments

Author

Listed:
  • Kuoyi Lin

    (College of Business, Guilin University of Electronic Technology, Guilin 541004, China)

  • Bin Li

    (College of Business, Guilin University of Electronic Technology, Guilin 541004, China)

Abstract

In light of electrical energy’s increasing role in economic systems worldwide, prioritizing investments in sustainable power supplies has become paramount. This study proposes a model based on cloud theory and game theory to evaluate sustainable power supply investment projects. It establishes a foundation for assessing the merits of power supply investments, which are crucial for continuous electricity provision and economic advancement. By integrating an enhanced analytic hierarchy process and the entropy method, the study develops a dual-weighted evaluative index system. This hybrid approach addresses ambiguities and enhances the weight determination accuracy, which, when applied to the Liaojiawan Transformer Substation, verifies the project’s high benefit level, corroborated by empirical data. This innovative methodology offers a strategic framework for future power supply investments.

Suggested Citation

  • Kuoyi Lin & Bin Li, 2024. "A Cloud- and Game Model-Based Approach to Project Evaluations of Sustainable Power Supply Investments," Sustainability, MDPI, vol. 16(10), pages 1-16, May.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:10:p:4040-:d:1392854
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    References listed on IDEAS

    as
    1. Song, Xiaoling & Zhang, Huqing & Fan, Lurong & Zhang, Zhe & Peña-Mora, Feniosky, 2023. "Planning shared energy storage systems for the spatio-temporal coordination of multi-site renewable energy sources on the power generation side," Energy, Elsevier, vol. 282(C).
    2. Xiaoning Cao & Hongguang Bo & Yongkui Liu & Xiaobing Liu, 2023. "Effects of different resource-sharing strategies in cloud manufacturing: a Stackelberg game-based approach," International Journal of Production Research, Taylor & Francis Journals, vol. 61(2), pages 520-540, January.
    3. Qingsheng Zhu & Kai Gao & Jia-Bao Liu, 2023. "Cloud model for new energy vehicle supply chain management based on growth expectation," Journal of Combinatorial Optimization, Springer, vol. 45(5), pages 1-23, July.
    4. Li, Qi & Xiao, Xukang & Pu, Yuchen & Luo, Shuyu & Liu, Hong & Chen, Weirong, 2023. "Hierarchical optimal scheduling method for regional integrated energy systems considering electricity-hydrogen shared energy," Applied Energy, Elsevier, vol. 349(C).
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