The cross impacts between transmission and distribution systems have drawn extensive attention, where multi-energy carriers become increasingly dominant in local market operations. Local energy hubs, integrated with multi-energy carriers, e.g., electricity, gas, heat, present great potentials to provide adequate power and reserve support for the transmission system, which could mitigate issues such as boundary mismatches in the upstream market. However, energy hubs are typically equipped with abundant distributed renewable resources. Such local uncertainties can adversely affect the well-being of the coordinated multi-energy market hierarchy. This paper presents a novel multi-period scheduling framework that considers the coordination between the transmission network and distribution energy hubs. Each agent performs local scheduling operations capturing independent uncertainties via a distributionally robust formulation. We then apply a tailored accelerated augmented Lagrangian algorithm embedded with the column-and-constraint method to decentralize the overall operation with agents' privacy preserved. The fast and convergent feature of the algorithm ensures its scalability and reliability in real-world applications of the energy hub design with transmission coordination. Numerical experiments confirm the efficacy of the proposed method.

中文翻译：

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输电市场和当地能源中心之间的分布式鲁棒分散调度


输配电系统的交叉影响受到广泛关注，多能源运营商在当地市场运营中日益占据主导地位。地方能源中心与电力、天然气、热力等多能源载体相结合，为输电系统提供充足的电力和储备支持，具有巨大的潜力，可以缓解上游市场边界错配等问题。然而，能源中心通常配备丰富的分布式可再生资源。这种地方性的不确定性可能会对协调的多能源市场体系的健康产生不利影响。本文提出了一种新颖的多周期调度框架，考虑了输电网络和配电能源中心之间的协调。每个代理执行本地调度操作，通过分布稳健的公式捕获独立的不确定性。然后，我们应用嵌入列和约束方法的定制加速增强拉格朗日算法来分散整体操作，同时保护代理的隐私。该算法的快速和收敛特性确保了其在具有传输协调的能源枢纽设计的实际应用中的可扩展性和可靠性。数值实验证实了该方法的有效性。