Carpe Diem : A Novel Approach to Select Representative Days for Long-Term Power System Models with High Shares of Renewable Energy Sources

In order to explore scenarios on the future of power systems, a variety of numerical models have been developed. As the share of variable renewable energy sources, particularly wind and solar, is projected to significantly increase, accounting for their temporal and spatial variability becomes ever more important in developing sound long-term scenarios. Computational restrictions prevent many long-term power system models being developed with an hourly resolution; instead they use time slices that aggregate periods with similar load and renewable electricity generation levels. There is to date no reproducible and validated method to derive and select time slices for power system models with multiple fluctuating time series. In this paper, we present a novel and effective method that is easily applied to input data for all kinds of power system models. We utilize this procedure in the long-term power system model LIMES-EU and show that a small number of representative days developed in this way are sufficient to reflect the characteristic fluctuations of the input data. Alongside a validation of the method, we discuss the conditions under which seasonal differentiation, and the use of representative weeks instead of days, is necessary