【目的】针对雪灾、暴雨等极端事件可能导致高速公路服务区微网光伏发电骤减、与大电网联络线中断等突发事件，为保障服务区微网供能稳定，提出一种考虑应急电源车的高速公路服务区微网两阶段优化调度方法。【方法】日前阶段，考虑服务区综合能源微网中可调度储能容量的灵活性资源能力，以微网运行成本最低为优化目标，建立微网日前经济调度模型，得到储能资源荷电状态下限，作为日内优化调度阶段的参数；日内阶段，基于模型预测控制理论，建立日内滚动优化调度模型。日内滚动优化考虑应急电源车参与服务区微网调度，并对服务区的多种用能负荷按照重要程度进行分级处理。以应急电源车运行费用最低和切负荷惩罚最低为目标函数，得到最终日内优化调度结果。【结果】通过构建极端场景下光伏出力骤降及并网中断的仿真算例，将文章所提研究方法与无储能荷电状态优化约束方案和不考虑应急电源车调度方案进行对比分析。仿真结果表明：所提方法有效降低了电/热/冷负荷削减量，同时系统运行成本也有所减少。【结论】算例分析验证了所提服务区微网两阶段优化调度方法在极端场景下的有效性，通过储能系统与应急电源车的协同调度机制，不仅增强了服务区微网抵御外部冲击的能力，还实现了供能稳定性提升与运行成本优化的双重目标，保障了服务区微网重要负荷的稳定供能。

[Objective] Given the sudden drop in photovoltaic power generation in highway service-area microgrids and the interruption of interconnection lines with the large power grid caused by extreme events such as snowstorms and heavy rains， a two-stage optimization scheduling method for highway service-area microgrids， considering emergency power-supply vehicles， is proposed to ensure the stable energy supply of microgrids in service areas. [Methods] In the day-ahead stage， the flexibility of the dispatchable energy storage capacity in the integrated energy microgrid in the service area is considered. The optimization goal is to minimize the operation cost of the microgrid. A day-ahead economic scheduling model of the microgrid is established， and the lower limit of the charge state of the energy storage resource is obtained as a parameter of the intraday optimization scheduling stage. In this stage， based on model predictive control theory， an intraday rolling optimization scheduling model is established. Intraday rolling optimization considers the participation of emergency power-supply vehicles in the scheduling of service-area microgrids， and the various energy loads in the service area are graded according to their importance. The lowest operating cost of the emergency power-supply vehicle and lowest load-shedding penalty are taken as objective functions to obtain the final intraday optimization scheduling. [Results] By constructing simulation examples of photovoltaic output drop and grid interruption under extreme scenarios， the proposed method is compared and analyzed with the state of charge （SOC） optimization constraint scheme without energy storage and the scheduling scheme without considering an emergency power-supply vehicle. The simulation results indicate that the proposed method significantly reduces the curtailment of electrical， thermal， and cooling loads while concurrently achieving a reduction in system operational costs. [Conclusions] Case analysis verifies the effectiveness of the proposed two-stage optimization scheduling method for the service-area microgrid in extreme scenarios. The coordinated scheduling mechanism of the energy storage system and the emergency power-supply vehicle not only enhances the external shock resistance of the service-area microgrid but also achieves the dual goals of improving energy-supply stability and optimizing operating costs， ensuring a stable energy supply for important loads in the service-area microgrid.