Review on Carbon Emission Accounting in New Energy Power Systems

With the continuous advancement of the “dual carbon” goals, carbon emission accounting in the power system has become a critical foundation supporting the low-carbon transition of the energy sector. The new power system, predominantly based on renewable energy, differs significantly from traditional thermal power systems in terms of operational characteristics, power source structure, and dispatch mechanisms. It exhibits new features such as strong spatiotemporal heterogeneity in carbon emissions, high proportions of indirect and lifecycle emissions, and blurred carbon responsibility boundaries among multiple entities, posing severe challenges to existing accounting methods. This paper systematically reviews the carbon emission accounting framework for the new power system, including direct emissions during operation, indirect emissions resulting from peak-shaving thermal power and external energy dependencies, as well as lifecycle emissions encompassing equipment manufacturing, operation, and decommissioning. The principles for defining system boundaries are also discussed. Based on this, a comprehensive overview of current mainstream carbon accounting methods is provided. On the supply side, Life cycle assessment (LCA) can systematically quantify the carbon footprint across the entire chain but faces challenges in data acquisition; Input-output (IO) analysis is suitable for macro-level policy formulation but struggles to reflect technological differences. On the demand side, the regional average method is simple to calculate but overlooks nodal-level spatiotemporal dynamics; Carbon emission flow (CEF) tracking enables precise allocation of carbon responsibilities in cross-regional transactions but involves high computational complexity; while machine learning-based methods offer minute-level prediction capabilities, but they rely on extensive data and exhibit weak interpretability. By comparing the differences among various methods in terms of accuracy, real-time capability, data requirements, and applicable scenarios, this paper highlights the existing limitations of the current system in dynamic response capability, spatial resolution, comprehensive coverage of all segments, and fair allocation of responsibilities among multiple entities. Finally, it proposes that future efforts should focus on constructing a dynamic carbon accounting model that integrates source-grid-load-storage coordination, developing real-time prediction technologies that combine physical mechanisms with artificial intelligence, and accelerating the establishment of a unified, transparent, and lifecycle-encompassing carbon emission accounting standard system, thereby providing scientific support for the low-carbon transition of the new power system.