针对调压站天然气压力能在传输过程中利用率低、流量无法准确预测以及集中充电站的换电池协调优化调度问题，本文提出了一种面向源-荷双重不确定性的调压站微电网分布鲁棒优化调度策略。首先，构建了压差发电-集中充电站-电网耦合的微电网分布鲁棒协同优化调度模型，并采用线性加权法对微电网运行成本最低和联络线功率波动最小两个目标进行综合优化。其次，引入基于综合范数约束的多离散场景概率模糊集，刻画了压力能发电、光伏和负荷的不确定性边界；构建了日前决策与日内最恶劣场景修正的min + maxmin两阶段分布鲁棒优化模型，并采用列与约束生成算法进行求解。最后，基于秋林集气总站16个月实际运行数据进行算例分析。结果表明，所提方法相比鲁棒优化、随机优化，在保证系统高可靠性的同时，显著提升了压力能全额消纳水平与微电网的整体经济效益。

To address the low utilization rate and inaccurate flow prediction of natural gas pressure energy during transmission, as well as the coordinated optimal dispatch problem of battery swapping in centralized charging stations, this paper proposes a distributionally robust optimal dispatch strategy for pressure regulation station microgrids considering dual source-load uncertainties. First, a distributionally robust collaborative optimal dispatch model is developed for a microgrid that integrates pressure differential power generation, a centralized charging station, and the main grid. The linear weighting method is then employed to comprehensively optimize the two objectives: minimizing the microgrid's operating cost and minimizing tie-line power fluctuation. Second, a multi-discrete-scenario probability ambiguity set based on comprehensive norm constraints is introduced to accurately characterize the uncertainty boundaries of pressure energy generation, photovoltaic (PV) output, and load. A two-stage min + maxmin distributionally robust optimization (DRO) model, featuring day-ahead decision-making and intra-day worst-case scenario correction, is formulated and solved using the column-and-constraint generation (C&CG) algorithm. Finally, a case study is conducted based on 16 months of actual operating data from the Qiulin gas gathering station. The results demonstrate that, compared with traditional robust optimization and stochastic optimization, the proposed method significantly enhances the full accommodation level of pressure energy and the overall economic benefits of the microgrid while ensuring high system reliability.