A low-carbon scheduling model for virtual power plants based on a cyber-physical-social system

In the process of promoting the low-carbon transformation of power systems， integrating cyber， physical， and social factors is crucial for effectively managing carbon assets on the user side and implementing low-carbon scheduling in virtual power plants （VPPs）. To this end， this paper proposes a low-carbon scheduling model for VPPs based on a cyber-physical-social system （CPSS）. First， a low-carbon scheduling framework for VPPs is established under the CPSS. Then， considering the coupling characteristics of dynamic carbon emission factors and users’ response behavior over time， a user-side carbon asset development evaluation system based on carbon asset price coefficients is built to obtain an optimized user sequence for low-carbon demand response. Finally， an optimization model is proposed with the objective of minimizing carbon emissions from VPPs， and orderly scheduling is performed based on the optimized sequence. Case analysis on the IEEE 33-node system demonstrates that the proposed low-carbon scheduling method maximizes adherence to users’ electricity consumption patterns while fully exploiting user-side carbon assets， thereby achieving low-carbon scheduling for VPPs.