Comprehensive Optimization of Energy Consumption and Network Voltage Stability of Freight Multitrain Operation Based on amMOPSO Algorithm

The multitrain comprehensive optimization (MTCO) combined with the ac traction power supply system (TPSS) can achieve energy savings for traction substations. However, traditional energy-saving optimization methods can cause continuous voltage fluctuations in the power grid, which may endanger train security. To address this issue, this article proposes a comprehensive optimization method for energy saving and voltage stability in multiple trains. First, this article establishes the train-track-power (TTP) grid comprehensive optimization model for freight trains, which is composed of the train dynamics model, the traction drive model, and TPSS. Considering the dynamic complex power and network power loss, a multiobjective function for train energy saving and voltage offset is constructed. Due to the strong coupling and complexity of the nonlinear TTP model, it is difficult to optimize algorithm solution, and convergence accuracy is low, as well as the deficiencies in the distribution of nondominated solution set during iterations; an adaptive multistrategy multiobjective particle swarm optimization (amMOPSO) algorithm is proposed. Then, the effectiveness of the TTP model is validated through the measured data from the Shuohuang Railway in China. Finally, several classical and state-of-the-art algorithms are employed for experimental comparisons. Experimental results show that amMOPSO outperforms the other algorithms. The feasibility of the freight multitrain MTCO method is verified through three comparative experiments. The energy consumption of the trains is reduced by 53.97%, the total voltage offset is reduced by 66.96%, and the utilization efficiency of regenerative braking energy (RBE) is increased by 75.3% as demonstrated through the comprehensive optimization experiments involving three trains.