Data-driven Research Method For Power System Stability Detection

被引:0
作者
Jia Tianxia [1 ]
Gu Zhuoyuan [1 ]
Sun Huadong [1 ]
Gao Pengfei [1 ]
Yi Jun [1 ]
Xu Shiyun [1 ]
Zhao Bing [1 ]
机构
[1] China Elect Power Res Inst, Beijing 100192, Peoples R China
来源
2018 INTERNATIONAL CONFERENCE ON POWER SYSTEM TECHNOLOGY (POWERCON) | 2018年
基金
中国国家自然科学基金;
关键词
power system; cognitive method; wide area measurement system(WAMS); data-driven; PREDICTION;
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
Energy security is vital to the national welfare and the livelihood of the masses. As the most important link in the energy transfer chain, the security of power system operation is of great significance. For a long time, how to improve the knowledge of power system--one of the most complicated artificial system--has always been the goal and motivation of electronic engineers. This paper firstly summarizes the cognitive method of general physical system and power system, teases out their inner link and mapping relationship. With the population of WAMS in power grid, a new idea about taking advantages of WAMS data for stability detection , data-driven research method is purposed. This paper reviews on the classification, development and status quo of all kinds of data-driven methods. In view of the ambiguity in the internal of data-driven methods, this paper summarizes all kinds of technique routes and a clear frame of data-driven method is sorted out.
引用
收藏
页码:3061 / 3069
页数:9
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