This letter proposes a new approach for online detection of low-quality synchrophasor data under both normal and event conditions. The proposed approach utilizes the features of synchrophasor data in time and frequency domains to distinguish multiple regional PMU signals and detect low-quality synchrophasor data. The proposed approach does not require any offline study and it is more effective to detect low-quality data with apparently indistinguishable profiles. Case studies from recorded synchrophasor measurements verify the effectiveness of the proposed approach.
@article{arxiv.2011.12365,
title = {Online Detection of Low-Quality Synchrophasor Data Considering Frequency Similarity},
author = {Wenyun Ju and Horacio Silva-Saravia and Neeraj Nayak and Wenxuan Yao and Yichen Zhang and Qingxin Shi and Fan Ye},
journal= {arXiv preprint arXiv:2011.12365},
year = {2020}
}