following, to analyze it. A specific objective is identified, which can provide valuable knowledge for decision taking to the different agents: to evaluate trends in temporal patterns of energy consumption from end users in the electricity distribution network, grouping the users by their temporal electric signature, or the way the energy is used and its amount variation in time. case, 24 dimensions of dynamic data objects. The development presented in this thesis takes as an initial stage the concepts presented by the different authors in their developments of specific-purpose algorithms for raw time series or sequence data, and presents, as a further step, a development which is able to use different similarity measures to obtain temporal patterns from n dimensional data objects.Following, this development is presented and tested on a dataset of energy consumption load profiles from a sample of domestic users in Spain.