In this paper, we propose the use of energy load profiles to learn human activities. An energy load profile determines the energy consumption of an appliance during a specific interval of time. We propose the use of clustering techniques to group the different profiles according to their temporal consumption. Both Hard and Soft clustering techniques are evaluated. We have tested the method with data from REMODECE (Residential Monitoring to Decrease Energy Use and Carbon Emissions in Europe) 1 database.