Online Detection of Low-Quality Synchrophasor Measurements: A Data-Driven Approach Academic Article uri icon

abstract

  • © 2016 IEEE. In this paper, an online data-driven approach is proposed for the detection of low-quality synchrophasor measurements. The proposed method leverages the spatio-temporal similarities among multiple-time-instant synchrophasor measurements and formulates the low-quality synchrophasor data as spatio-temporal outliers. A density-based local outlier detection technique is proposed to detect the spatio-temporal outliers. This data-driven approach involves no system modeling information. The detection algorithm can operate under both normal and fault-on system conditions, with fast computation speed suitable for online applications. Case studies on both synthetic and real-world synchrophasor data verify the effectiveness of the proposed approach.

author list (cited authors)

  • Wu, M., & Xie, L. e.

citation count

  • 32

publication date

  • November 2016