2009 IEEE Bucharest PowerTech 2009
DOI: 10.1109/ptc.2009.5282017
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Clustering techniques for energy losses evaluation in distribution networks

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Cited by 9 publications
(3 citation statements)
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“…The probabilities must also add up to 1 in probabilistic (crisp) clustering, which calculates the likelihood that each point belongs to each cluster. Moreover, clustering can be based on a variety of models [11].…”
Section: Clustering and Classification Framework 21 Clustering Conceptmentioning
confidence: 99%
“…The probabilities must also add up to 1 in probabilistic (crisp) clustering, which calculates the likelihood that each point belongs to each cluster. Moreover, clustering can be based on a variety of models [11].…”
Section: Clustering and Classification Framework 21 Clustering Conceptmentioning
confidence: 99%
“…al [33] utilize GIS data and clustering of urban areas for optimizing the design and operation of district energy systems, identifying zones 'where consumers, resources and technologies are integrated'. Cartina et al [34] apply clustering to electrical networks to identify feeder characteristics. Further cases in building stock management are discussed in the next subsection.…”
Section: Hierarchical and Partitioning Clusteringmentioning
confidence: 99%
“…• Identification of the weakest areas in distribution network and improving them; • Reduction of the length of the distribution networks by relocation of distribution substation/installations of additional transformers; • Identification overloads feeders, and reallocates the loads. In an extensive distribution network, with uncertainty in the data it is impossible to carry out an exhaustive analysis [1], thus, the use of statistical methods that are designed to discover the complex relationships between the available data would be so effective. One of these methods is Cluster analysis that as an unsupervised process divides a set of objects into homogeneous groups.…”
Section: Introductionmentioning
confidence: 99%