Integrated Optimization of Energy Storage Allocation and Train Speed Control in Urban Rail Transit Systems

With the promotion of “double carbon” plan in China, the energy-saving problem of urban rail transit, as a major energy user of the government, has garnered significant attention. In urban rail train operations, the energy storage devices (ESDs) can temporarily store the regenerative energy from braking trains and feed it back to other accelerating trains. However, the ESDs comes with a high price tag and limited capacity. To minimize the overall energy consumption of urban rail lines with limited ESDs, this paper addresses the collaborative optimization of ESD allocation and train speed profiles, in order to coordinate the usage of energy among ESDs and accelerating/braking trains, such that the overall energy consumption, i.e., the consumed energy for train acceleration subtracting the used regenerated energy, can be minimized. Specifically, we construct a mixed-integer programming (MIP) model to collaboratively optimize the train running speed curve (with accelerating, coasting and braking) and ESD locations. A series of constraints are developed to limit the flow of energy among ESDs and the state transition of running trains. Finally, we verify the feasibility and effectiveness of our integrated approach using real-world data from Beijing Metro Yizhuang Line.