Evolutionary Game-Theoretic Approach to Enhancing User-Grid Cooperation in Peak Shaving: Integrating Whole-Process Democracy (Deliberative Governance) in Renewable Energy Systems

Kun Wang, Lefeng Cheng () and Ruikun Wang ()
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Kun Wang: Institute for Human Rights, Guangzhou University, Guangzhou 510006, China
Lefeng Cheng: School of Mechanical and Electrical Engineering, Guangzhou University, Guangzhou 510006, China
Ruikun Wang: School of Mechanical and Electrical Engineering, Guangzhou University, Guangzhou 510006, China

Mathematics, 2025, vol. 13, issue 15, 1-79

Abstract: The integration of renewable energy into power grids is imperative for reducing carbon emissions and mitigating reliance on depleting fossil fuels. In this paper, we develop symmetric and asymmetric evolutionary game-theoretic models to analyze how user–grid cooperation in peak shaving can be enhanced by incorporating whole-process democracy (deliberative governance) into decision-making. Our framework captures excess returns, cooperation-driven profits, energy pricing, participation costs, and benefit-sharing coefficients to identify equilibrium conditions under varied subsidy, cost, and market scenarios. Furthermore, this study integrates the theory, path, and mechanism of deliberative procedures under the perspective of whole-process democracy, exploring how inclusive and participatory decision-making processes can enhance cooperation in renewable energy systems. We simulate seven scenarios that systematically adjust subsidy rates, cost–benefit structures, dynamic pricing, and renewable-versus-conventional competitiveness, revealing that robust cooperation emerges only under well-aligned incentives, equitable profit sharing, and targeted financial policies. These scenarios systematically vary these key parameters to assess the robustness of cooperative equilibria under diverse economic and policy conditions. Our findings indicate that policy efficacy hinges on deliberative stakeholder engagement, fair profit allocation, and adaptive subsidy mechanisms. These results furnish actionable guidelines for regulators and grid operators to foster sustainable, low-carbon energy systems and inform future research on demand response and multi-source integration.

Keywords: evolutionary game theory; whole-process democracy (deliberative governance); low-carbon economy; renewable energy integration; user–grid collaboration; peak regulation strategy; policy incentives; dynamic equilibrium modeling (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2025
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