TITLE:
Online Capacitor Voltage Transformer Measurement Error State Evaluation Method Based on In-Phase Relationship and Abnormal Point Detection
AUTHORS:
Yongqi Liu, Wei Shi, Jiusong Hu, Yantao Zhao, Pang Wang
KEYWORDS:
Capacitor Voltage Transformer, Measurement Error, Online Monitoring, Principal Component Analysis, Local Outlier Factor
JOURNAL NAME:
Smart Grid and Renewable Energy,
Vol.15 No.1,
January
26,
2024
ABSTRACT: The
assessment of the measurement error status of online Capacitor Voltage
Transformers (CVT) within the power grid is of profound significance to the
equitable trade of electric energy and the secure operation of the power grid.
This paper advances an online CVT error state evaluation method, anchored in
the in-phase relationship and outlier detection. Initially, this method
leverages the in-phase relationship to obviate the influence of primary side
fluctuations in the grid on assessment accuracy. Subsequently, Principal Component Analysis (PCA) is employed to meticulously
disentangle the error change information inherent in the CVT from the
measured values and to compute statistics that delineate the error state.
Finally, the Local Outlier Factor (LOF) is deployed to discern outliers in the
statistics, with thresholds serving to appraise the CVT error state. Experimental
results incontrovertibly demonstrate the efficacy of this method, showcasing
its prowess in effecting online tracking of CVT error changes and conducting
error state assessments. The discernible enhancements in reliability, accuracy,
and sensitivity are manifest, with the assessment accuracy reaching an
exemplary 0.01%.