Graph-Based Electricity Carbon Sensitivity Analysis for Distribution Substations

With the intensification of global climate change, achieving carbon peak and carbon neutrality has become a key objective for many nations. As one of the major sources of carbon emissions, the power system’s carbon emission characteristics are closely tied to power flow within the grid. This paper proposed a graph-based algorithm for analyzing the electricity carbon sensitivity of generating units in a distribution network, aiming to identify the impact of various generating units on the carbon emissions of the target substation based on the network’s topology and power flow estimation results. First, the paper constructed a graph model of the distribution network, defining its topological connections and employing graph computation to obtain power flow estimations. Then, a graph parallel supply path search algorithm and a recursive supply percentage calculation for a distribution substation were developed. Finally, an electricity carbon sensitivity analysis method was proposed by integrating the carbon emissions of different types of units to achieve the rapid carbon flow trace. Using a provincial distribution network in Southwest China as a case study, the proposed method was validated for its rationality and feasibility. Results showed that the algorithm efficiently and accurately calculated the carbon sensitivity of units, which contributed to the optimization of carbon emissions in the power grid and promoted the adoption of clean energy.