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March 3, 20260 citationsOpen Access

Multidimensional Impact Assessment of Social Welfare Incorporating Dynamic Cross Subsidy and Tiered Carbon Trading

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YCYa-Juan CaoNanjing Institute of TechnologyBQBin-Yang QiuChina Three Gorges UniversityQWQiu-Jie WangChina Three Gorges University

Key Points

  • Evaluate the socioeconomic impacts of a dynamic cross subsidy and tiered carbon trading model in energy policy.
  • Developed an optimal dispatch model for a multi-microgrid system.
  • Established a unified operational framework combining electricity tariff cross subsidy and tiered carbon trading.
  • Designed a dynamic subsidy rate linked to renewable energy output.
  • Conducted a comparative simulation across scenarios: no subsidy, traditional cross subsidy, and dynamic cross subsidy.
  • Reduced system carbon emissions by 17.05% compared to the non-subsidy baseline.
  • Significantly optimized total costs under the proposed dynamic subsidy model.

Abstract

In the context of advancing two pivotal national commitments, namely the “Dual Carbon” goals and the common prosperity strategy, energy policy formulation must move beyond purely economic or environmental considerations and adopt integrated social welfare assessments. This study develops an optimal dispatch model for a multi-microgrid system that incorporates dynamic cross subsidy and tiered carbon trading. From the perspective of welfare economics, the socioeconomic impacts of the proposed model are then systematically evaluated. First, a unified operational framework is established, combining dynamic electricity tariff cross subsidy with a tiered carbon trading mechanism. Next, a quantitative model for electricity tariff cross subsidy is proposed, and a dynamic subsidy rate linked to renewable energy output is designed to guide electricity consumption behavior. Finally, a comparative simulation is conducted across three scenarios: no subsidy, traditional cross subsidy, and the proposed dynamic cross subsidy. The results demonstrate that the proposed dynamic mechanism reduces system carbon emissions by 17.05% compared to the non-subsidy baseline while significantly optimizing total costs.

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Cite This Study

Cao et al. (2026) studied this question.

synapsesocial.com/papers/69a67f06f353c071a6f0ac2ahttps://doi.org/10.3390/en19051225
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