Partitioning of an Electrical Distribution Systems Using K-Means and DBSCAN Clustering Algorithms
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Abstract
This paper proposes the methodology to perform the partitioning of a distribution network using data clustering algorithms such as K-means and DBSCAN. The data is obtained by generating variations in the network parameters and simulating the voltage profile using OpenDSS software. The proposed methodology is implemented on standard IEEE test distribution networks of 34 and 123-node test feeders. The obtained results are compared with methods obtained from the literature.
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