Time Alignment Method for Wide-area Measurement Data Based On Local Outlier Factor Algorithm

The timestamp shift exists in the data collection of wide-area measurement system. This paper presents an integrated time alignment method that includes the detection of data with timestamp shift and the corresponding alignment process. Firstly, the data with timestamp shift are detected by the Local Outlier Factor algorithm. Then, the outlier data with timestamp deviations are substituted into a polynomial function. By properly adjusting the degree and coefficients of the function, the fitting curve can closely approximate the trend of the normal data, thus achieving effective alignment of the time of the outliers. The effectiveness of this method is verified through experimental analysis with actual WAMS data.