Load patterns often have a periodicity of a day, week and year, which can be taken advantage of when preprocessing load data before clustering. A typical load profile, which reflects the customer's load for a characteristic day, week or year, could be constructed to reduce the data to be processed during the clustering. Typical Daily Profiles (TDP) and Typical Weekly Profiles (TWP) are compared to see how the time resolution of data affects the clustering. Results show that the number of

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... s affects the Davies-Bouldin Index and the Dunn Index more than the temporal resolution of data as well as if TDPs or TWPs are clustered. Further, clustering based on customers' TWP instead of TDP makes it easier to find customers which have equipment turned on during Saturdays. This could be of importance when clustering is used to improve forecasting, distribution planning or tariff design.