User-side resource allocation and equalization method for carbon emission reduction

To address the challenges of low resource allocation efficiency and insufficient carbon reduction benefits in user-side resource aggregation under China's "dual carbon" goals, this paper proposes a carbon reduction-oriented aggregation regulation and demand response strategy for distribution grids. A collaborative framework integrating "grid-transformer area-user" interactions is established, incorporating cross-regional green power trading and dynamic carbon emission allocation. A cooperative game model with Conditional Value-at-Risk (CVaR) is developed to quantify carbon emission reductions from green power transfers, while an improved Shapley value method optimizes benefit distribution among stakeholders. The model addresses uncertainties in user-side resource output through Monte Carlo sampling and employs a particle swarm optimization algorithm to solve the game equilibrium, balancing regulation costs and carbon reduction objectives. Simulation results based on an IEEE 33-node distribution network demonstrate that the proposed strategy reduces peak-valley load differences by 44.5%, increases transformer area profit growth rates by 9.7%, and enhances carbon reduction benefits by 33.50% and 12.28% compared to benchmark methods. The framework effectively supports flexible demand response, improves renewable energy integration, and aligns with China's carbon neutrality targets.