Abstract The rapid growth of gas-fired units and the development of power-to-gas (PtG) technology have strengthened the interdependency of power system and natural gas system and provided a new way for the absorption of renewable energy. This paper proposes a distributionally robust optimization (DRO) scheduling model for the electricity-gas coupled integrated energy system considering wind power uncertainty and PtG technology. Combining the advantages of stochastic programming and robust optimization, the proposed DRO model describes the uncertainty by an ambiguity set constructed based on the confidence bands of its probability density function, and aims to minimize the expectation of the re-dispatch cost under the worst-case distribution. Moreover, a novel affine adjustable strategy with the allocation ratio pairs is developed to enhance the flexibility of reserve configuration. Benefiting from the special structure of the ambiguity set, the proposed model with uncertainties can be reformulated as a mixed integer linear program problem to solve. Case studies are implemented on three coupled systems with different scales, and simulation results demonstrate that DRO with proposed affinely adjustable strategy can obtain the scheduling solution with lower conservatism and higher economical performance compared to the adjustable robust optimization and DRO with the single adjustment strategy.

中文翻译：

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考虑概率密度函数置信区间的电力天然气综合能源系统分布鲁棒优化调度

摘要 燃气机组的快速增长和电转气（PtG）技术的发展，加强了电力系统与天然气系统的相互依存关系，为可再生能源的消纳提供了新途径。本文提出了一种考虑风电不确定性和 PtG 技术的电-气耦合综合能源系统的分布式鲁棒优化（DRO）调度模型。结合随机规划和鲁棒优化的优点，所提出的 DRO 模型通过基于其概率密度函数的置信区间构建的模糊集来描述不确定性，旨在最小化最坏情况下重新调度成本的期望分配。而且，开发了一种具有分配比率对的新型仿射可调策略，以增强储备配置的灵活性。受益于模糊集的特殊结构，所提出的具有不确定性的模型可以重新表述为混合整数线性规划问题来解决。在三个不同规模的耦合系统上进行了案例研究，仿真结果表明，与可调鲁棒优化和采用单一调整策略的 DRO 相比，采用仿射可调策略的 DRO 可以获得具有更低保守性和更高经济性的调度解。