The Research of Train Energy-Efficient Operation Strategy Based on Multi-Objective Optimization

Abstract

Abstract-In order to reducing the energy consumption of the train running between the stations, ensuring punctuality and the comfort of the passengers, this paper studies the train energyefficient operation strategy. After taking account of the slope and the speed limit of the line, the model of multi-objective optimization train energy-efficient is established based on train energy consumption, running time and passenger comfort. The improved multi-objective genetic algorithm (MOGA) is used to optimize the target speed sequence to obtain the operation strategy of the train. Different from previous multi-objective optimization, the energy-efficient driving optimization method is realized by considering automatic train operation's (ATO) double-level control structure, slope equivalent strategy, and Pareto optimization in this paper. Based on the actual line data and vehicle parameters of Yizhuang line in Beijing subway, the optimization method is verified by simulation. The simulation results show that, after using the improved multi-objective genetic algorithm, the energy consumption and running time of the train in Yizhuang train station are obviously decreased, and after the train comfort is measured, the rate of change in acceleration or deceleration meet the requirements of passenger experience needs. It can be seen that the proposed algorithm can effectively reduce the energy consumption of the train, ensure the accuracy of the running time and improve the comfort of the passengers.

An auxiliary optimization method for electric heating renovation based on using a clustering algorithm

“…The method is tested on a standard IEEE system and the performance of the technology is verified on a real Indian power grid network [3]. • Yang et al verified the effectiveness of the distributed electric heating cluster hybrid control strategy by simulating and analyzing the wind power output consumption, start/stop of electric heating equipment, and indoor temperature changes under the distributed electric heating cluster hybrid control strategy [4]. • Zhang used the enthalpy method model to establish a simplified mathematical model for the phase change thermal storage electric heating module.…”