Multiobjective Optimization of Traction Substation Converter Characteristic and Train Timetable in Subway Systems

Abstract

Currently, power supply accidents and excessive energy consumption occur frequently in DC traction power systems of multitrain subway lines. Rail potential (RP) exceeds the standard limit frequently, energy consumption and fluctuation of the traction current are high, which are directly affected by the traction substation converter characteristic and train timetable. In this paper, multi-objective optimization of traction substation converter characteristic and train timetable is conducted to realize the safe and economic operation of subway systems. Firstly, a power flow calculation platform with multitrain running dynamically is established to work out the operating parameters of the system. Then, a multi-objective optimization model consisting of maximum RP, energy consumption and maximum traction current is designed. For the coordination of multiple goals to be optimized, an enhanced Non-Dominated Sorting Genetic Algorithm-III (NSGA-III) is proposed to obtain an optimal traction substation converter characteristic and train timetable. Finally, the multi-objective optimization is conducted with the data of Guangzhou Metro Line 2. Results indicate that three optimized objectives are dropped by 43.8%, 33.4% and 40.3% respectively based on the proposed optimization method, which will greatly enhance the energy conservation and power supply safety of subway systems.