Abstract
Power quality monitoring equipment is inevitably faced with the problem of data loss and is vulnerable to the interference of noise or bad data. We propose a harmonic data recovery method that is based on graph clustering and non-negative matrix factorization (NMF) under multiple constraints. Compared with the existing harmonic data recovery methods, the proposed method can effectively recover lost data and it has a strong anti-interference ability, especially for the recovery of harmonic data with interference. In the recovery of data loss, noisy interference tests and bad data interference tests, the presented recovery algorithm has high accuracy within 60% for continuous missing data. In an environment with SNR = 50, this method has high recover reliability and accuracy within 15% for situations involving bad data interference.
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