Short-term Forecast Technology in Load of Electrified Railway based on Wavelet-extreme Learning Machine
Wentao Zhang, Wenhua Zhao, Xinhui Du · Journal of Networks · 2014
With the development of economy and the progress of science, the proportion of electrified railway load in the power gird has been keeping on increasing, which impacts the short-term forecasting in load a lot, therefore, it is very important to analyze short-term load of electrified railway forecasting. This paper analyzes the power gird load-forecasting considering the influence of the electrified railway load, and introduces wavelet mechanism for data processing based on the research of electrified railway load. The wavelet-extreme learning machine algorithm is proposed and used in the short-term forecast in load of electric railway on the platform of MATLAB. The application in the local electric power company indicates that the wavelet-extreme learning mechanism model has the features of accurate prediction, quick response, and strong practicability