A statistical forecasting method based on the measured data is proposed to evaluate the influence of a new electrified railway on the power quality of power grid. Through analysis of statistical distribution characteristics of a large number of traction load test data, parameters such as the charged effective coefficient, maximum value, variance, and skewness coefficient are selected to describe the main characteristics of the traction load in probability distribution. Using the fuzzy C-means clustering algorithm, 42 groups of measured data are divided into 10 types. Based on the characteristic values of traction load provided by railway design departments, the probability model of the new electrified railway can be derived from the above 10 types, and its probability distribution function (PDF) is accordingly obtained. Finally, the feeder currents in traction substation of the new electrified railway are predicted by Monte Carlo sampling method. The validity of the method is verified by the fitting curves of PDF using the predicted data and the mean square error of PDF is less than 0.1.
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