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Master Thesis: Zeitreihen-Clustering von Industriekunden im Energiebereich
In the electricity segment of the energy industry, the consumption of industrial customers is recorded by means of load profile meters. The 15-minute time series measured are primarily used for billing the energy supplied. In addition, further information for the design of tariffs or forecasting can be taken from the measured time series. To get a deeper insight into the data, the data was clustered using the K-Means and Ward algorithm. With these algorithms, clusterings were possible that differed in terms of their consumption behavior in the observation periods of one year, month and day. The aim of the work was to group the customers according to their consumption profiles.
K-Means, energy industry, time series, Ward, clustering
K-Means, energy industry, time series, Ward, clustering
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).0 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Average influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average
