In view of the problems of low accuracy in detecting abnormal parameters,inaccurate search and positioning and slow response in power plant equipment monitoring,based on cluster analysis algorithm,a abnormality search method for monitoring parameters of power plant equipment is proposed.The correlation was analyzed,determine the global index exclusion of abnormal correlation values.Results of the field test and commissioning test on the battery energy storage system and a 20 kV line in a me-dium voltage network power plant show that the cluster analysis algorithm can accurately extract the abnormal parameter informa-tion.When the coefficient is 0.756,the data shows low concentration and the abnormal data distribution is far from the standard line.And the smaller the short-term flicker indicator is,the more concentrated the data is.It can be concluded that the anomaly search method for power plant equipment monitoring parameters,based on cluster analysis greatly improves the reliability of data transmission in power systems,realizes the reliable data interaction,and verifies the rationality and technical advantages of the al-gorithm design.
power plant equipmentparameter identificationanomaly searchsoftware controlintelligent identification
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