Bottom-up Markov Chain Monte Carlo approach for scenario based residential load modelling with publicly available data

In the residential sector, with the introduction of electric vehicles and photovoltaics, developments are taking place which have an impact on residential load curves. In order to assess the integration of these new types of technologies on both the generation and load side, as well as to develop mitigation strategies like demand side management, detailed information is required about the load curve of a household. To gain knowledge about this load curve a residential load model is developed based on publicly available data. The model utilises a Markov Chain Monte Carlo method to model the occupancy in a household based on time use surveys, which together with weather variables, neighbourhood charlectricity consumption ccupancy ousehold appliance arkov Chain oad curves acteristics and behavioural data are used to model the switching pattern of appliances. The modelling approach described in this paper is applied for the situation in the Netherlands. The resulting load curve probability distributions are validated with smart meter measurements for 100 Dutch households for a week. The validation shows that the model presented in this paper can be employed for further studies on demand side management approaches and integration issues of new appliances in distribution grids. © 2015 Elsevier B.V. All rights reserved.

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