The timetable of Trends in observed surface solar radiation and their causes in Brazil in the first 2 decades of the 21st century urban rail greatly affects its daily energy consumption.To improve the utilization of renewable energy between trains using timetabling has become an effective way to reduce energy consumption.Previous studies ignore or simplify the modelling of traction power supply network, which failed to accurately describe the flow of energy between trains through the power network.
This paper proposed an optimisation method of energy efficiency timetabling considering the power flow of traction power supply network.First, an urban rail transit DC traction network model Antibacterial activity of selenium nanoparticles/copper oxide (SeNPs/CuO) nanocomposite against some multi-drug resistant clinical pathogens is established, and the current-vector iterative method is used to characterize the energy consumption.Then, a train timetable optimisation model is proposed to minimize the total energy consumption of the traction network system by adjusting the dwell time and section running time.
The genetic algorithm is used to solve the optimisation problem.Finally, simulation result shows that the proposed method can accurately characterize the energy flow and effectively reduce the total energy consumption of the urban rail transit.