Application of AI techniques in monitoring and operation of power systems

被引：15

作者：

Gao, David Wenzhong ^{[1
,2
]}

Wang, Qiang ^{[3
]}

Zhang, Fang ^{[2
]}

Yang, Xiaojing ^{[3
]}

Huang, Zhigang ^{[3
]}

Ma, Shiqian ^{[4
]}

Li, Qiao ^{[1
]}

Gong, Xiaoyan ^{[5
]}

Wang, Fei-Yue ^{[5
]}

机构：

[1] Univ Denver, Denver, CO 80210 USA

[2] Tsinghua Univ, Dept Elect Engn, China State Key Lab Power Syst, Beijing 100084, Peoples R China

[3] State Grid Tianjin Elect Power Co, Tianjin 300010, Peoples R China

[4] State Grid Tianjin Elect Power Res Inst, Tianjin 300384, Peoples R China

[5] Chinese Acad Sci, CASIA, SKL, MCCS, Beijing 100190, Peoples R China

来源：

FRONTIERS IN ENERGY | 2019年 / 13卷 / 01期

关键词：

power system operation and monitoring; artificial intelligence (AI); deep learning; power flow analysis; NETWORKS;

D O I：

10.1007/s11708-018-0589-4

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：

In recent years, the artificial intelligence (AI) technology is becoming more and more popular in many areas due to its amazing performance. However, the application of AI techniques in power systems is still in its infancy. Therefore, in this paper, the application potentials of AI technologies in power systems will be discussed by mainly focusing on the power system operation and monitoring. For the power system operation, the problems, the demands, and the possible applications of AI techniques in control, optimization, and decision making problems are discussed. Subsequently, the fault detection and stability analysis problems in power system monitoring are studied. At the end of the paper, a case study to use the neural network (NN) for power flow analysis is provided as a simple example to demonstrate the viability of AI techniques in solving power system problems.

引用

页码：71 / 85

页数：15

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