Computational efficient Integration of Flexibility Options in Large Scale Energy System Models

Abstract

The integration of variable renewable energy sources (RES) with increased share in power supply systems leads to new challenges in power system models. In this context, flexibility options have a high potential to balance fluctuating renewable energy feed-in in a cost efficient and low emission way [8, 9]. However, the combination of model parameters like simulation time, space, sectors with increasing level of detail call for advances in model reduction techniques [6]. Hence, a trade-off between the increasing complexity introduced by introducing flexibility options and the required computational effort has to be found. In Section 1, the extension of storage units in the energy system as one of these flexibility options is investigated with the eGo model [4]. Furthermore, the model can take into account several other possibilities of flexibility options such as demand side management or power-to-X, which can be modelled as functional storage. The latter will gain in importance when the heat and transport sector are decarbonized by the use of sector coupling [1]. Section 2 presents an approach of the technoeconomic assessment of flexibility options from an operator's point of view, based on a large-scale energy system model.