Modeling the effects of variable tariffs on domestic electric load profiles by use of occupant behavior submodels

Emerging infrastructure for residential meter communication and data processing carries the potential to control household electrical demand within local power system constraints. Deferral of load control can be incentivized through electricity tariff price structure, which can in turn reshape a daily load profile. This paper presents a stochastic bottom-up model designed to predict the change in domestic electricity profile invoked by consumer reaction to electricity unit price, with submodels comprising user behavior, price response, and dependency between behavior and electric demand. The developed models are used to analyze the demand side management potential of the most relevant energy consuming activities through a simulated German household demonstrating that in the given scenario 8% of the annual electricity demand is shifted, leading to a 35€ annual saving. However, a 7% higher than average peak load results from the structure of the tariff signal modeled herein. A discussion on selected aspects for tariff design for categories of typical household appliances is included