A time-of-use-based residential electricity demand model for smart grid applications

In a smart grid viewpoint, modeling residential energy demand profiles could be useful in various analyzes: the impacts of different technologies and policies can be indeed assessed and, by inserting these models in wider integrated frameworks, possible future scenarios can be evaluated. This paper presents a time-of-use-based bottom-up model of residential electricity consumption. This high-resolution model takes into account the presence of multiple individuals in a household, their behavior and the related use of appliances, and considers also air conditioning, lighting, and cold appliances power consumption, basing on building features and owned devices. The activity patterns of each households member are generated according to a Markov-chain approach, calibrated and validated by means of Time-Use Survey data. Every other part of the model is based on actual data from different surveys and studies. The generated electricity demand profiles are consequently validated against metered data. The validation shows that the model is able to represent correctly the power demand trends over the day, diurnal variations and load fluctuations.