The uncertainties from renewable energy sources (RESs) will not only introduce significant influences to active power dispatch, but also bring great challenges to the analysis of optimal reactive power dispatch (ORPD). To address the influence of high penetration of RES integrated into active distribution networks, a distributionally robust chance constraint (DRCC)-based ORPD model considering discrete reactive power compensators is proposed in this paper. The proposed ORPD model combines a second-order cone programming (SOCP)-based model at the nominal operation mode and a linear power flow (LPF) model to reflect the system response under certainties. Then, a distributionally robust optimization (WDRO) method with Wasserstein distance is utilized to solve the proposed DRCC-based ORPD model. The WDRO method is data-driven due to the reason that the ambiguity set is constructed by the available historical data without any assumption on the specific probability distribution of the uncertainties. And the more data is available, the smaller the ambiguity would be. Numerical results on IEEE 30-bus and 123-bus systems and comparisons with the other three-benchmark approaches demonstrate the accuracy and effectiveness of the proposed model and method.

中文翻译：

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有源配电网中具有Wasserstein距离的分布鲁棒最优无功功率分配

可再生能源（RESs）的不确定性不仅会对有功功率分配产生重大影响，而且对最优无功功率分配（ORPD）的分析也将带来巨大挑战。为了解决集成到有源配电网中的RES的高穿透性的影响，提出了一种基于离散鲁棒机会约束（DRCC）的ORPD模型，该模型考虑了离散无功功率补偿器。提出的ORPD模型将标称工作模式下基于二阶锥规划（SOCP）的模型与线性潮流（LPF）模型相结合，以反映确定性下的系统响应。然后，利用具有Wasserstein距离的分布鲁棒优化（WDRO）方法来求解所提出的基于DRCC的ORPD模型。WDRO方法是数据驱动的，原因是不确定性集是由可用的历史数据构成的，而没有对不确定性的特定概率分布进行任何假设。而且可用数据越多，歧义就越小。在IEEE 30总线和123总线系统上的数值结果以及与其他三基准方法的比较证明了所提出模型和方法的准确性和有效性。