A highly resolved modeling technique to simulate residential power demand

► Activity patterns for individuals are modeled using a heterogeneous Markov chain, calibrated with time-use data. ► The residential demand model allows reconstructing power consumption of a single or an aggregate group of households. ► A rigorous statistical validation framework has been developed to validate the proposed model. ► The residential demand model can serve as a tool to evaluate the effects of different technologies. ► The simulated residential demand loads show highly realistic patterns. This paper presents a model to simulate the electricity demand of a single household consisting of multiple individuals. The total consumption is divided into four main categories, namely cold appliances, heating, ventilation, and air conditioning, lighting, and energy consumed by household members’ activities. The first three components are modeled using engineering physically-based models, while the activity patterns of individuals are modeled using a heterogeneous Markov chain. Using data collected by the U.S. Bureau of Labor Statistics, a case study for an average American household is developed. The data are used to conduct an in-sample validation of the modeled activities and a rigorous statistical validation of the predicted electricity demand against metered data is provided. The results show highly realistic patterns that capture annual and diurnal variations, load fluctuations, and diversity between household configuration, location, and size.