Distributionally Robust Optimization Method for Grid-connected Microgrid Considering Extreme Scenarios

被引：0
|
作者：
Cao J. [1 ,4 ]
Zeng J. [1 ,2 ]
Liu J. [3 ]
Xue F. [4 ]
机构：
[1] School of Electric Power, South China University of Technology, Guangzhou
[2] Guangdong Key Laboratory of Clean Energy Technology (South China University of Technology), Guangzhou
[3] School of Automation Science and Engineering, South China University of Technology, Guangzhou
[4] Dongguan Power Supply Bureau of Guangdong Power Grid Corporation, Dongguan
来源：
Dianli Xitong Zidonghua/Automation of Electric Power Systems | 2022年 / 46卷 / 07期
基金：
中国国家自然科学基金;
关键词：
Distributionally robust optimization; Extreme scenario; Fuzzy set of probability distribution; Improved analytical target cascading; Microgrid;
D O I：
10.7500/AEPS20210706005
中图分类号：
学科分类号：
摘要：
Uncertainties of loads and distributed generators are the difficulties in the microgrid operation optimization. This paper proposes a day-ahead distributionally robust optimization method for grid-connected microgrid considering extreme scenarios to ensure the robustness and efficiency of microgrid energy management. Firstly, considering the uncertainty of sources and loads, a fuzzy set of probability distribution based on Wasserstein distance is constructed, and the fuzzy set is modified by the extreme scenario method to improve the robustness of the fuzzy set. Secondly, considering that the microgrid and the distribution network are different stakeholders in the grid-connected mode, the day-ahead operation optimization models of the microgrid and the distribution network are established, respectively, and the improved analytical target cascading is used to carry out decoupling and iterative solution. Finally, the effectiveness of the proposed method is verified by the simulation comparison. © 2022 Automation of Electric Power Systems Press.
引用
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页码：50 / 59
页数：9
相关论文
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