Tomas Babarskis - Academia.edu (original) (raw)
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Mehran University of Engineering and Technology
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Papers by Tomas Babarskis
Accurate information about the actual behavior of electricity users is essential to the electrici... more Accurate information about the actual behavior of electricity users is essential to the electricity suppliers in order to ensure efficient decisions in planning pricing, e.g., designing tariffs and load planning. Load profiles of customers is a straightforward source for such data, however it should be analyzed to extract relevant information. Most of the existing techniques are tested with small data sets or over short periods, which does not allow to investigate seasonality influence. We present a new methodology for the grouping of electricity customers based on the similarities of their (hourly) consumption patterns. Approach is based on the periodicity analysis and well-known clustering technique – K-means, which is applied for identification for separate users load profiles and clustering of load profiles. Values of model parameter are selected using adequacy measures. Finally, the results obtained by this methodology with a data set of 3753 electricity customers are presented...
Accurate information about the actual behavior of electricity users is essential to the electrici... more Accurate information about the actual behavior of electricity users is essential to the electricity suppliers in order to ensure efficient decisions in planning pricing, e.g., designing tariffs and load planning. Load profiles of customers is a straightforward source for such data, however it should be analyzed to extract relevant information. Most of the existing techniques are tested with small data sets or over short periods, which does not allow to investigate seasonality influence. We present a new methodology for the grouping of electricity customers based on the similarities of their (hourly) consumption patterns. Approach is based on the periodicity analysis and well-known clustering technique – K-means, which is applied for identification for separate users load profiles and clustering of load profiles. Values of model parameter are selected using adequacy measures. Finally, the results obtained by this methodology with a data set of 3753 electricity customers are presented...