The Method of High Speed Railway Load Ultra-Short-Term Forecast Based on Dispatching and Control Cloud Platform

• Published in: 2018 IEEE International Conference on Information and Automation (ICIA) pp. 722 - 727
• Main Authors: Ge, Weichun, Wang, Shunjiang, Zhang, Zhen, Yang, Kaifan, Liu, Qianwei, Su, Anlong
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.08.2018
• Subjects: Dispatching; Dispatching and control cloud; High-speed railway load; Load modeling; Monte Carlo; Monte Carlo methods; Power Systems; Predictive models; Rail transportation; Traction power supplies; Ultra-short-term forecast
• DOI: 10.1109/ICInfA.2018.8812405

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.