Eva Schmid

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.

Quantifying the long-term economic benefits of European electricity system integration

This paper analyses a set of model�?based decarbonization scenarios in order to quantify the long�?term economic benefits that arise from an increasing integration of the pan�?European electricity system. It thereby focuses on the interplay between transmission infrastructure and renewable generation capacity expansion. We confirm earlier findings that, on aggregate, pan�?European transmission capacity expansion constitutes a no�?regret option for integrating increasing shares of variable renewables in mitigation scenarios with positive social returns on investment. However, it turns out that the change in total discounted system costs that occurs as transmission capacity expansion increases is modest in magnitude, with a maximum of 3.5% for a case with no expansion compared to one with massive expansion. In technical terms this means that the optimum is rather flat and that taking into account regional and local benefits and distributional aspects, could alter the evaluation of the economic benefits considerably. A crucial finding in this context is that the configuration of pan�?European transmission infrastructure and the importance of specific country�?connections, i.e. a “Southern�? versus a “Northern�? solution, crucially hinges on the relative development of specific investment costs for solar and wind technologies over the next decades.

REMIND-D: A Hybrid Energy-Economy Model of Germany

This paper presents a detailed documentation of the hybrid energy-economy model REMIND-D. REMIND-D is a Ramsey-type growth model for Germany that integrates a detailed bottom-up energy system module, coupled by a hard link. The model provides a quantitative framework for analyzing long-term domestic CO2 emission reduction scenarios. Due to its hybrid nature, REMIND-D facilitates an integrated analysis of the interplay between technological mitigation options in the different sectors of the energy system as well as overall macroeconomic dynamics. REMIND-D is an intertemporal optimization model, featuring optimal annual mitigation effort and technology deployment as a model output. In order to provide transparency on model assumptions, this paper gives an overview of the model structure, the input data used to calibrate REMIND-D to the Federal Republic of Germany, as well as the techno-economic parameters of the technologies considered in the energy system module.