A Probabilistic Modelling Approach for Residential Load Profiles

In this paper, a model is presented that generates electricity load profiles for individual German households. It is assumed that the electricity consumption is mainly determined by the behavior of the residents and their appliances. Activity patterns for the residents living in the household are simulated by using a first-order Markov-chain, which has been calibrated by time use data from a German survey obtained in 2012/2013. The model is then validated by using the original sample to check whether daily routines are realistically reflected in the model. Furthermore, the electricity load profiles are validated by comparing the outcome of the model with real measured load profiles, synthetic load profiles but also statistical characteristics, which have been obtained through national surveys. Validation shows that the approach is suitable to simulate electricity demand that captures annual consumption, diurnal variation but also differences between individual households. The developed load profile generator can be used to analyze the impacts of the emersion and expansion of new technologies on residential load patterns and respective distribution network loads