To address the challenges of the inconsistency of functional units and the lag of static emission factors in the life cycle assessment (LCA) of power transformers

this paper proposes a systematic assessment framework integrating multi-dimensional evaluation metrics and dynamic scenarios. Four functional units containing the rated capacity

voltage level

and total lifecycle electricity transmission characterisitics are constructed

and a dynamic carbon accounting model is established based on China's energy transition path. Furthermore

the pedigree matrix is introduced to semi-quantitatively assess data quality

and Monte Carlo simulation is employed to verify the statistical stability of the results. The 10 typical transformers ranging from distribution to transmission levels are used as empirical objects

and the results show that

1）Methodological validity: functional units incorporating voltage and lifespan (e.g. kgCO2eq/MWh) objectively reflect the environmental benefits of high-efficiency

long-life models

correcting biases derived from single-capacity metrics. 2）Dynamic impact: under dynamic scenarios considering grid decarbonization

lifecycle emissions decrease by approximately 30%-50% compared to traditional static assessments. Although the proportion of operational emissions declines over time

it remains the dominant factor (>90%). 3）Scaling laws: a sub-linear scaling law between carbon emissions and rated capacity in the log-log space is revealed (R2>0.99)

validating the feasibility of rapid carbon footprint estimation based on capacity parameters. 4）Drivers and strategies: uncertainty analysis indicates heterogeneous material sensitivities across capacity levels

and variations in waste disposal methods can cause carbon emission fluctuations of up to 91 times. Consequently

a graded decarbonization strategy is proposed

focusing on copper and aluminium closed-loop recycling for small-capacity units

extreme energy efficiency design for large-capacity units

and standardized clean disposal of waste oil and steel for all series. This study provides a methodological support for the development of low-carbon evaluation standards and green design of power equipment.