Abstract：As an important feature of the future power system，the penetration of a high proportion of

renewable energy sources significantly enhances the uncertainty of power system operation. The probabilistic load

flow calculation，compared with the conventional tidal current calculation，can fully consider the influence of

uncertainty factors，better reveal the characteristics of the system，and provide a computational basis for economic

operation，security and stability analysis，and reliability analysis in a stochastic environment. Considering the

stochastic characteristic of renewable energy and electricity/gas/heat load，and the correlation of the above random

factors，the method based on sparse polynomial chaos expansion was studied to model and calculate the random

variables，and ultimately obtain the probability distribution of the output state variable. Finally，multiple test cases

were calculated and analyzed，the effectiveness，rapidity，and practicality of the proposed methods were demonstrated by comparing with Monte Carlo and generalized polynomial chaos method，and the analysis of system voltage distribution levels was conducted for different scenarios of distributed energy resource penetration rates.

      Key words：probabilistic load flow calculation；sparse polynomial chaos expansion（SPCE）；renewable

energy；correlation