【摘要】 面对铁路运行气候环境恶劣、电网薄弱的问题，具备自牵引能力的双源动力动车组受到高度关注。然而，现有车载储能系统配置研究无法满足长大坡道自牵引过分相与应急自走行等特殊需求，为此，结合极端气候环境和活跃的地理地质条件下车载储能多场景应用需求，提出动车组多场景应用运行策略及适配的储能系统优化配置方法。首先，提出自牵引过分相运行策略及应急自走行节能运行策略，建立过分相自牵引与应急自走行最小能耗计算模型，分析储能容量对负荷削峰率、制动能量利用率、自牵引过分相能力以及应急自走行能力等多场景参数的交互影响机制；其次，以过分相能耗、应急自走行能耗、体积/质量为约束条件，以制动能量回收率、牵引功率波动率、车载储能系统全寿命运营周期经济效益为优化目标，构建多场景储能系统配置的多目标、多约束优化模型；最后，以某典型路段为例进行算例分析，结果表明，优化配置方案能满足动车组应急自走行与过分相自牵引供电能力，20 a投资收益率327.6%,制动能量回收率56.68%,减小波动率30.54%,减少总能耗16.84%。更多还原

【Abstract】 The dual-source power EMU with self-traction capability have attracted significant attention, as railway operation faces the problems of harsh environment and weak external power grid. However, the existing research on the configuration of the on-board energy storage systems cannot meet the particular needs of self-traction neutral section passing and emergency self-running on long and steep grades. To this end, an optimal configuration model of the energy storage system for EMU multi-scenario adaptation was established, combined with the extreme climate environment and active geographical and geological conditions. Firstly, a self-traction neutral section passing operation strategy and emergency self-running energy-saving operation strategy were proposed, and a calculation model of minimum energy consumption for self-traction neutral section passing and emergency self-running was established to study the interactive influence mechanism of energy storage capacity on multi-scenario parameters such as load peak shaving rate, braking energy utilization rate, self-traction neutral section passing capability, and emergency self-running capability. Secondly, an optimal configuration model of the multi-scenario energy storage system was constructed, with the energy consumption of excessive phase power supply, emergency self-propelled energy consumption, and volume weight as constraints, and the economic benefits of the EMU braking energy recovery rate, the traction power fluctuation rate, and the full-life operation cycle of the vehicle-mounted energy storage system as optimization goals. Finally, based on some typical sections of line, the optimization simulation calculation was carried out. The simulation results show that the optimally configured on-board energy storage system can meet the train’s emergency self-running and excessive phase self-traction power supply capabilities, with a 20-year investment return rate of 327.6%, a braking energy recovery rate of 56.68%, a reduction in volatility of 30.54%, and a reduction in total energy consumption of 16.84%.更多还原