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Railway is an important infrastructure of the state, national main artery and popular means of transport. With the gradually maturity of high-speed railway technology of China, the proportion of load of electric railway in the national power consumption load. As the electric railway load is characterized by high variation frequency, large fluctuation and poor periodicity, it causes a great influence on the forecast of local load. To solve this problem, this paper proposes a method of first treating the data by scale through wavelet analysis and then selecting partially similar day to forecast various loads in different frequencies with more load forecast models and improves wavelet svm forecast method to make the approximation under single scale in the past proceed in more scales and improve the partial approximation ability of this method. This method is used to forecast the ultrashort-term load of power system, the experiment result shows that the load forecast result precision of this method reaches above 97%, effectively improving the forecast prevision of load under the influence of interference factors.

Research on Forecast of Ultra-short-term Load under the Influence of Electric Railway