A Novel Data-Driven Robust Method Applied to OPF with Uncertain Wind Power

被引：0
|
作者：
Su, Xiangyang [1 ]
Bai, Xiaoqing [1 ]
Zheng, Yi [1 ]
Song, Zhewei [1 ]
Cao, Yiqi [1 ]
Zhang, Jun [1 ]
机构：
[1] Guangxi Univ, Key Lab Guangxi Elect Power Syst Optimizat & Ener, Nanning, Peoples R China
来源：
2018 2ND IEEE CONFERENCE ON ENERGY INTERNET AND ENERGY SYSTEM INTEGRATION (EI2) | 2018年
关键词：
data-driven method; optimal power flow (OPF); robust optimization; uncertainty; wind power;
D O I：
暂无
中图分类号：
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号：
0807 ; 0820 ;
摘要：
With the arrival of the big data era, the wind power accommodation has an alternative solution. Meanwhile, the traditional stochastic optimization or robust optimization methods may result in uneconomic or conservative decisions in dealing with the uncertainty problems. Based on this, it is proposed to apply robust optimization of data driven to optimal power flow under the participation of wind power, and the model is improved on the basis of integrated 1-norm and infinity norm. The final example analysis also proves the validity and practicability of the model.
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页数：5
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