Research on multi‐train energy saving optimization based on cooperative multi‐objective particle swarm optimization algorithm. (14th September 2020) - Zhang, Yong; Zuo, Tingting; Zhu, Muhan; Huang, Cheng; Li, Jun; Xu, Zhiliang
Summary: An energy saving optimization method of multi‐train collaboration is studied. According to the different scenarios of two and three trains, the corresponding overlapping time calculation model was established respectively. Minimizing the total energy consumption, a multi‐train collaborative energy consumption optimization model is established. The cooperative multi‐objective PSO algorithm was used to solve the model from the aspects of optimizing stop time and departure interval as well as the train speed curve. Finally, the energy optimization of the whole line of multi‐train during the morning rush hour were carried out by the actual data of Guangzhou metro line 7. The results show that the optimization model can greatly improve the utilization efficiency of regenerative energy and save energy consumption of the whole line by 11.74%. Abstract : The methods of regenerative braking energy utilization based on stop time, departure interval adjustment and speed curve adjustment are studied in this paper. Establish multrain‐train energy‐saving optimization model and carry out simulations based on the data of Guangzhou Metro Line 7. The simulation result shows that the optimized train greatly improves the utilization efficiency of regenerative braking energy and reduces the net traction energy consumption.