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

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.

authors

• Xie, Le

published proceedings

• IEEE TRANSACTIONS ON POWER SYSTEMS

author list (cited authors)

• Wu, M., & Xie, L. e.

citation count

• 52

complete list of authors

• Wu, Meng||Xie, Le

publication date

• July 2017

publisher

• Institute of Electrical and Electronics Engineers (IEEE)  Publisher

published in

• IEEE TRANSACTIONS ON POWER SYSTEMS  Journal

keywords

• Data Mining
• Data Quality Improvement
• Outlier Detection
• Spatio-temporal Similarity
• Synchrophasor

Digital Object Identifier (DOI)

• 10.1109/TPWRS.2016.2633462

start page

• 2817

end page

• 2827

volume

• 32

issue

• 4

URL

• http://dx.doi.org/10.1109/tpwrs.2016.2633462