考虑机会约束的配电网光伏并网容量分布鲁棒优化方法

传统的经验性概率分布描述分布式光伏出力的不确定性难以准确获取概率分布参数.为此,提出一种基于Kullback-Leibler散度的分布鲁棒优化方法来评估配电网分布式光伏的最大并网容量.首先,通过Kullback-Leibler散度来量化实际概率分布与经验性概率分布之间距离,建立分布式光伏出力不确定性的模糊集.在考虑节点...

Distributionally robust optimization method of PV grid-connected capacity in a distributionnetwork considering chance constraints

The traditional empirical probability distribution is used to describe the uncertainty of distributed PV output but it is difficult to accurately obtain the probability distribution parameters. Therefore, this paper proposes a distributionally robust optimization method based on Kullback-Leibler divergence to evaluate the maximum grid-connected capacity of distributed PV in a distribution network. First, the distance between the actual probability distribution and the empirical probability distribution is quantified by Kullback-Leibler divergence, and the fuzzy set of distributed PV output uncertainty is established. Considering the nodal voltage and transmission capacity over limits chance constraints, a distributionally robust optimization model of distributed PV grid-connected capacity is established. This model is transformed into a mixed integer programming problem using value at risk and a sample average approximation method. The effectiveness and robustness of the method are demonstrated by simulation results on a modified IEEE-33 bus system.This work is supported by the Science and Technology Plan Projects of Hebei Province (No. 19212102D) and the Science and Technology Project of State Grid Hebei Electric Power Co., Ltd. (No. kj2020-049).