Load-current demand forecasting in substations of urban railway lines

Abstract

Load-current forecasting is important in the operation and energy management of urban railway lines. It helps control strategies to manage and distribute energy optimally, thereby saving energy and reducing voltage fluctuations. This paper presents a method to predict the traction
current at the busbar of a substation using the supervised machine learning algorithm..