Low-Carbon Economic Dispatch of Integrated Energy System Considering Expanding Carbon Emission Flows

To address the issues of low coordination in low-carbon operation between Carbon Capture and Storage (CCS) devices and Power to Gas (P2G) devices in integrated energy systems (IES), as well as the inaccurate characterization of carbon emissions from energy storage devices, this paper proposes an extended carbon emission flow model that integrates the collaborative operation mode of CCS-P2G and the low-carbon characteristics of energy storage. The model establishes a coupling relationship between CCS and P2G on the energy supply side to achieve low-carbon economic operation of P2G. On the energy storage side, the concept of "electricity-carbon ratio (ECR)" is introduced to characterize the carbon emission characteristics of energy storage devices, exploring the potential for coordinated low-carbon dispatch on both the energy supply and energy storage sides. Based on this, a low-carbon economic dispatch model for integrated energy systems is constructed, considering multiple uncertainties such as wind power, electricity prices, and electric-heat-gas loads. To achieve fast and efficient solving of the model, a parallel multi-dimensional approximate dynamic programming algorithm is adopted, which significantly improves solving efficiency by constructing a multi-layer parallel loop nested framework without losing solving accuracy. The effectiveness of the proposed model and algorithm is validated using an improved E14-H6-G6 system, consisting of a 14-node power grid, a 6-node heating network, and a 6-node gas network. The CCS-P2G (Carbon Capture, Storage, and Power-to-Gas) collaborative operation mode discussed in this article significantly enhances the economic and low-carbon performance of the Integrated Energy System (IES) by fully reutilizing CO2. Compared to unmodified coal-fired power units, the total cost is reduced by 137,900 yuan, thereby validating the effectiveness of the CCS-P2G collaborative operation mode in low-carbon scheduling.