The Application of Multi-objective PSO Algorithm in Energy-efficient optimization of Metro Systems

In order to reduce the energy consumption of urban rail transit, a hierarchical energy-saving optimization method is proposed. The upper layer properly allocates travel time of every interstation in whole line, and the lower layer optimizes the train target speed curve in different interstation. In the lower optimization scheme, the multi-objective target speed curve optimization mathematical model is established. Then by using multi-objective particle swarm optimization algorithm (MOPSO), both a set of optimal energy-saving speed curves and their corresponding energy consumptions were obtained. Least squares method was used to curve fitting data and mathematical model of the relationship between energy consumption and travel time for interstation is established. In the upper level optimization scheme, interstation travel time distribution optimization model was established, whose target is minimizing the whole line energy consumption. the travel time allocation of every interstation was optimized by gradient descent method. Finally, based on the real data of Yizhuang Line, Beijing Subway, the proposed optimization model was simulated and verified. As the simulation results show, in lower layer optimization the operation energy efficiency is greatly improved. In upper layer, interstation travel time distribution optimization, 10.7% energy consumption is reduced.