Dynamic tracking of life cycle carbon emissions in power grids based on a flow network model.

ABSTRACT: This study introduces a flow network model to dynamically track carbon emissions in power grids, addressing limitations of traditional methods by transforming grids into directed graphs with virtual sink nodes for transmission losses. Using Markov chain-based probabilistic flow analysis, the model allocates emissions from generators to loads and power lines, incorporating life cycle emissions and eliminating matrix inversion. Validated via a 24-hour simulation on the IEEE 30-bus system, results demonstrate significant fluctuations in emission factors driven by renewable generation variability. Loads near renewables achieve near-zero emission factors during peak green generation, while loads remote from renewable sources exhibit weaker responses. The grid-level emission factor, inversely co

SUBMITTER: Wang C 

PROVIDER: S-EPMC12290027 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature