Keywords
Smart Grid
clustering algorithm
forecasting
power system
How to Cite
Abstract
A comparative analysis of clustering methods was performed to identify gaps and anomalous values in the data. Data from the northwestern region of the United States were used for evaluation. According to the analysis results, it was found that the use of the DBSCAN method leads to a much smaller number of false positives. An algorithm for two-stage data validation using clustering and time series decomposition methods is proposed. Ref.9, fig. 3, tables 3.
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Copyright (c) 2021 P.V. Shymaniuk, V.O. Miroshnyk