Abstract

The impact and randomness of the impact load, especially the high-speed rail load, has many negative impacts on the grid, and it is mainly studied from the perspective of ultra-short-term prediction. Firstly, the load characteristics of high-speed railway load in a certain area were analyzed by dispatching and control cloud platform, and Monte Carlo method was proposed to solve the problem that the randomness of high-speed railway load was difficult to predict. Then, an ultra-short-term load forecasting model for high-speed rail is established based on actual factors, and the probability of the prediction is estimated by the uncertainty analysis. A practical regional grid calculation example in the database for dispatching and controlling cloud verifies the correctness and effectiveness of the proposed method. This study provides a quantitative theoretical basis for the analysis and scheduling of high-speed railways for short-term high-speed railway load forecasting during actual power grid operation.

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