Optimal scheduling of campus-level virtual power plant considering carbon capture under supply-demand interactive carbon trading

To promote the optimal resource allocation and low-carbon transition of virtual power plant (VPP), this paper adopts a supply-demand interactive carbon trading mechanism. Taking the maximum comprehensive benefit of park-level VPP and the minimum energy consumption cost of users as dual optimization objectives, a day-ahead and intraday combined optimal scheduling model for low-carbon economic operation is proposed, which takes power-to-gas (P2G) and carbon capture and storage (CCS) technologies into account. To improve economic efficiency and operational flexibility, time-of-use energy prices are adopted, and an integrated electric-thermal demand response mechanism is established. Meanwhile, supply-demand interactive carbon trading and CCS are incorporated into VPP operation to enhance low-carbon performance. Based on source-load uncertainty forecasting and energy flow regulation, typical VPP operation modes are constructed for verification and analysis. Case results show that the comprehensive benefits of the park-level VPP optimized by the proposed model are increased by 15.67%, 22.25%, 20.17% and 7.41% respectively compared with the control groups. The proposed model can effectively reduce the peak-valley load difference, system carbon emissions, scheduling errors and users' energy costs, and maximize the comprehensive benefits of the park VPP. Furthermore, it significantly improves the economic efficiency, low-carbon performance and operational flexibility of VPP operation.