Differential Electricity Pricing and Load Management Strategies for Virtual Power Plant Considering the Synergistic Effect of Green Certificate Trading and Carbon Trading

Under the carbon neutrality goals, this paper addresses the critical challenge of enhancing operational flexibility and low‐carbon performance in northern China’s heating regions, where the power generation determined by heat for combined heat and power (CHP) unit restricts renewable energy consumption. To tackle this, a novel virtual power plant (VPP) framework is proposed by incorporating electric heat pump (EHP), carbon capture system, and shared energy storage. A leader‐follower game model is also built between the VPP and multiple industrial users. The upper‐level model optimizes VPP profit by designing differential electricity pricing strategies considering the synergistic effect of green certificate trading (GCT) and carbon emission trading (CET), solved using a self‐adaptive immune genetic algorithm (SIGA). The lower‐level model minimizes user costs through production process‐based load management, solved via a dual ascent and alternating direction multiplier method. Example analysis from Tianjin, China, demonstrates that the proposed strategy increases VPP profit by over 110% compared to a baseline scenario, reduces carbon emissions by 13.9%, enhances the capacity of renewable energy utilization, and lowers total user costs by 4.56%. These results verify that the synergistic GCT‐CET mechanism, combined with flexible equipment configuration and differentiated pricing, effectively coordinates low‐carbon transition, economic efficiency, and renewable energy consumption. It can provide a viable pathway for VPP operation in northern heating regions.