Research on the Optimal Scheduling Model of Virtual Power Plant Considering GCT-CET Interaction Mechanism and CVaR

Under the dual-carbon policy, virtual power plants (VPPs) optimize multi-energy coordination and renewable integration. This study develops a risk-aware scheduling model integrating green certificate-ladder carbon trading (GCT-CET) and Conditional Value-at-Risk (CVaR) theory to balance economy and sustainability. The framework enhances renewable utilization through GCT mechanisms, employs incentive-based demand response (IDR) for load shifting, and quantifies operational risks via CVaR. An improved quantum particle swarm algorithm minimizes daily costs. The multi-scenario comparison shows that the mechanism can effectively improve the new energy consumption and reduce carbon emissions through source-load collaborative optimization, which confirms its collaborative optimization ability in improving the low carbon and economy of the system.