轨道交通供电系统中列车运行与路侧储能系统的两阶段协调能量管理
Two-stage Coordinated Energy Management of Train Operation and Wayside Energy Storage System for Rail Power Supply Systems
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中文总结 AI 辅助
针对电气化铁路供电系统，提出两阶段协调能量管理方法，联合优化列车运行与储能调度，通过日前计划和日内滚动优化，降低电网峰值功率35.7%和系统总成本28.8%。
中文摘要 AI 辅助
铁路供电系统（RPSS）日益电气化加剧了铁路电力系统接口处的运行和经济挑战。储能系统（ESS）能够提供快速灵活的支持，以缓解短期功率尖峰并改善能量管理。然而，在时变牵引需求和网络限制下，电气化铁路运行与储能系统调度之间的紧密耦合使得实现协调运行面临挑战。本文提出了一种针对电气化铁路供电系统的两阶段协调能量管理方法，该方法在明确考虑牵引潮流约束的同时，联合优化铁路系统运行、列车轨迹和储能系统调度。首先，日前运行阶段确定列车运行曲线和储能系统设定决策，以建立基线运行计划。然后，基于自适应权重经济模型预测控制（AWC-MPC）的日内滚动优化阶段，在更新的牵引需求和可再生能源出力预测下更新储能系统调度。利用瑞典实际铁路案例，以最小化购电成本和储能系统成本并降低电网峰值功率，展示了其实际适用性，实现了35.7%的电网峰值功率需求和28.8%的系统总成本降低。
英文摘要
The increasing electrification of railway power supply system (RPSS) intensify the operational and economic challenges at the railway power system interface. Energy storage systems (ESSs) can provide fast and flexible support to mitigate short term power spikes and to improve the energy management. However, achieving coordinated operation is challenged by the tight coupling among electrical railway operation and ESS dispatch under time-varying traction demand and network limits. This paper proposes a two-stage coordinated energy management method for electrified RPSSs that jointly optimizes railway system operation, train trajectories and ESS dispatch while explicitly accounting for traction power flow constraints. First, a day-ahead operation stage determines the train operating profiles and the ESS setting decisions to establish the baseline operating plan. Then, an intra-day rolling optimization stage based on adaptive weight economic-model predictive control (AWC-MPC) updates ESS dispatch under refreshed forecasts of traction demand and renewable output. A real Swedish railway case is utilized to minimize the energy purchase cost and the ESS cost while reducing peak grid power, demonstrating its practical applicability with 35.7% peak grid power demand and 28.8% total system cost reduction.
