Multi-Timescale Optimal Scheduling of Rural Integrated Energy System with Electric Heating Considering Tiered Carbon Trading and Carbon Capture

Abstract

: To support the transition to clean heating in northern rural areas, this study addresses the coordinated scheduling of uncertain renewable generation, electric-heating demand, and low-carbon resources. A rural integrated energy system (IES) scheduling model is developed by coupling power-to-gas (P2G) with carbon capture and storage (CCS). A tiered carbon trading mechanism internalizes emission costs, while CCS-P2G coupling enables CO 2 utilization and synthetic methane production. A two-stage strategy combining day-ahead robust optimization with intra-day rolling adjustment is then proposed. The day-ahead layer establishes a cost-minimizing robust baseline under a budgeted wind/Wind and photovoltaic (PV) uncertainty set. The intra-day model predictive control (MPC) layer updates wind, PV, and load forecasts every 15 min and implements only the first control action of each rolling horizon. Case-study results indicate that the proposed framework coordinates electric heating, energy conversion, storage, and carbon-management resources while supporting economical and low-carbon operation of rural energy systems.