KEYWORDS: Data modeling, Power grids, Data acquisition, Power supplies, Detection and tracking algorithms, Neural networks, Model-based design, Databases, Chemical analysis, Analytical research
Station line loss is directly related to the operating efficiency of power grid enterprises. Traditional low-voltage station line loss management directly distinguishes abnormal line loss stations according to the index value, which is relatively extensive management. Based on the theory of station line loss, this paper proposes a method of station line loss anomaly analysis based on K-means clustering algorithm. Firstly, the LOF algorithm is used to eliminate the outliers in the platform area, and then the line losses in the platform area are clustered. Finally, the abnormal line loss platform area is identified by combining the value interval of the average line loss rate and the distance from the clustering center.
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