On the importance of accurate demand representation in large scale energy system models: hourly profiles and socioeconomic dynamics

policymaking processes; however, they do not come without their limitations, as the current changes and trends in power systems have shown. On the one hand, energy system models require certainty concerning their input parameters or at least clearly defined statistical properties, and they are affected by the curse of dimensionality when more detailed representations are required, as is the case when representing variable renewable energy sources. In this work, we highlight how the uncertainty about the input parameters, particularly demand, leads to significant changes in the results obtained from the models; we use an inhouse bi-hourly model of the Austrian power system and show how even a slight reduction in demand, because of an energy saving policy from example, or a shift in the patterns of consumption, due to increased adoption of electric vehicles, lead to different investment and operational decisions.