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The energy sector is currently undergoing a fundamental paradigm shift. A big challenge is to better match the output of an increasing share of intermittent generation from renewable energy sources to varying demand patterns of energy consumers. Large field projects are underway to evaluate technological readiness and economic effects of smart grid technology (eg?). Key components in these projects are demand side management systems (DSM), which are able to control household appliances (eg washing machines) and optimize their operation. An open question is how consumers equipped with this technology will react to different forms of time-based energy tariffs. We present a model that generates realistic energy load profiles for private households that are close to empirically measured profiles. We show that our model can be adjusted to fit synthetic load profiles commonly used to estimate household energy demand, and can be calibrated differently to reflect non-standard settings such as the specific consumption profile of about 100 participants in a smart grid field testing project called MeRegio (?). Based on the load profiles generated, our model simulates electricity consumption of households equipped with DSM technology who face time-based energy tariffs, by modeling household appliances and their shifting potential in combination with a simple demand shifting heuristic. The results of our simulation can guide the design of DSM systems in field test. The remainder of this paper is structured as follows: Section 2 reviews related work. In Section 3 we describe our residential energy demand response model. We evaluate the …