Dual-Objective Optimization of Maximum Rail Potential and Total Energy Consumption in Multitrain Subway Systems

Abstract

The dc traction power system is commonly adopted in multitrain subway systems. During the operation of multiple trains, different power distribution of the system directly affects the energy consumption and power supply safety. It is urgent for multitrain subway systems to optimize the operation parameters to ensure energy-saving and safety. In this article, nondominated sorting genetic algorithm II (NSGA-II) based on kernel density estimation (KDE) is proposed for collaborative optimization of total energy consumption and the maximum rail potential in the system. First, a simulation model for the dynamic operation of multiple trains with a parallel multiconductor traction network is established to realize the dynamic flow calculation with train–network coupling. Second, a dual-objective optimization model of the maximum rail potential and the total energy consumption is formulated to realize the energy-saving and power supply safety of the system. Finally, the NSGA-II algorithm based on KDE is proposed to handle the dual-objective optimization model. According to the dynamic simulations of Guangzhou Metro Line 2, the optimization method is verified. Results show that the total energy consumption is reduced by 22.2%, and the maximum rail potential is dropped by 40.3%, which effectively realizes the energy-saving and power supply safety.