| 引用本文: | 于腾凯,董靓媛,杜晓东,柳永超.考虑机会约束的配电网光伏并网容量分布鲁棒优化方法[J].电力系统保护与控制,2021,49(10):43-50.[点击复制] |
| YU Tengkai,DONG Liangyuan,,DU Xiaodong,LIU Yongchao.Distributionally robust optimization method of PV grid-connected capacity in a distributionnetwork considering chance constraints[J].Power System Protection and Control,2021,49(10):43-50[点击复制] |
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| 摘要: |
| 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。在考虑节点电压和传输容量越限机会约束的情况下，建立了分布式光伏并网容量分布鲁棒优化模型。通过采用风险价值和样本平均近似方法将分布鲁棒优化模型转化为一个混合整数规划问题求解。在改进的IEEE-33节点系统的仿真结果表明了所提出分布鲁棒优化方法的有效性和鲁棒性。 |
| 关键词: 光伏并网容量 配电网 机会约束 Kullback-Leibler散度 分布鲁棒优化 |
| DOI：DOI: 10.19783/j.cnki.pspc.200909 |
| 投稿时间：2020-07-29修订日期：2020-12-30 |
| 基金项目:河北省重点研发计划项目资助(19212102D)；国网河北省电力有限公司科技项目资助(kj2020-049) |
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| Distributionally robust optimization method of PV grid-connected capacity in a distributionnetwork considering chance constraints |
| YU Tengkai1,DONG Liangyuan1,,DU Xiaodong1,LIU Yongchao2 |
| (1. State Grid Hebei Electric Power Research Institute, Shijiazhuang 050021, China;
2. Shanghai Keliang Information Engineering Company, Shanghai 200233, China) |
| Abstract: |
| 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). |
| Key words: PV grid-connected capacity distribution network chance constraints Kullback-Leibler divergence distributionally robust optimization |
