Impact of Low Data Quality on Disturbance Triangulation Application Using High-Density PMU Measurements

被引:19
作者
Deng, Xianda [1 ]
Bian, Desong [2 ]
Shi, Di [2 ]
Yao, Wenxuan [1 ,3 ]
Wu, Ling [1 ]
Liu, Yilu [1 ,3 ]
机构
[1] Univ Tennessee, Dept Elect Engn & Comp Sci, Knoxville, TN 37996 USA
[2] Global Energy Interconnect Res Inst North Amer, San Jose, CA 95134 USA
[3] Oak Ridge Natl Lab, POB 2009, Oak Ridge, TN 37830 USA
关键词
Disturbance triangulation; low data quality; PMU measurement; TDOA; MULTIPLE EVENT DETECTION; POWER; FRAMEWORK;
D O I
10.1109/ACCESS.2019.2932035
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
High-density PMUs can be implemented to estimate the location of a large power system disturbances based on the theory of Time Difference of Arrival (TDOA). Unfortunately, real-world measurements suffer from low data quality issues frequently caused by various uncontrollable and unpredictable factors. In this paper, four types of practical low data quality issues from onsite PMUs are first identified from the industry perspective. Then, the impacts of each low-quality data issue on disturbance triangulation are explored using real-time measurement cases from Jiangsu power grid with a high-density PMU network. This paper provides valuable guidance for utility operators and academic researchers to use actual PMU data for power grid applications.
引用
收藏
页码:105054 / 105061
页数:8
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