A GSDF‐Based Renewable Energy Carbon Emission Reduction Calculation Method Considering Network Losses

Accurately quantifying the carbon emission reduction (CER) of renewable energy (RE) is crucial for the coupled electricity‐carbon market. However, traditional methods based on regional average emission factors ignore topological constraints and transmission losses causing systematic biases in evaluating RE's environmental value. To address this, this paper proposes a high‐precision physics‐based CER accounting framework integrating topological sensitivity mapping with bidirectional network loss allocation. First, an improved generation shift distribution factor (GSDF)‐based marginal emission factor model is established to overcome geographical blindness and precisely identify specific high‐carbon marginal units displaced by RE. Second, upstream and downstream power flow tracing algorithms are utilised to bidirectionally allocate network losses, equitably attributing carbon emissions embedded in dissipated energy. Third, a virtual lossless network is reconstructed and RE is treated as a negative virtual load, through which the precise displacement pathways from marginal units to RE nodes are rigorously mapped. Case studies on a regional power grid in Zhejiang, China, demonstrate that the proposed framework successfully corrects systematic underestimations providing a highly credible pricing benchmark for green certificates and carbon assets.