Modeling Dynamic Carbon Emissions in Power System Based on Nodal Carbon Intensity Clustering

Abstract

Power system is the main force in the battlefield of carbon peaking and carbon neutrality. A fresh look at the power system from a carbon perspective will provide a better reference for the low-carbon transition, and how to better portray the carbon emission pattern of the power system at all times becomes the key to related research. Based on the carbon emission flow (CEF) theory of the power system and the idea of macro dynamic carbon emission factors, this paper proposes the concept of the real-time zoned carbon emission factor. User nodes with similar carbon intensities are divided into the same region through a density-based clustering method, and the dynamic carbon emission factor of this region will be shared with all users inside. The algorithm is assessed through a dynamic simulation study on the IEEE 30-bus system and the results confirm the effectiveness of the proposed solution. By this means, carbon emissions in the power system can be presented in a real-time zoned format, which is useful for the demand-side response as well as power system planning and green power dispatch.