Measurement data‐driven investigation of the actual power grid resilience with increasing renewable energy feed‐in

• Published in: Energy science & engineering 2022-01, Vol.10 (1), p.145-154
• Main Authors: Schädler, Yannik, Sorg, Michael, Fischer, Andreas
• Format: Article
• Language: English
• Subjects: Algorithms; Alternative energy sources; Carbon dioxide; Electric power grids; Electricity distribution; Emissions; Energy sources; Intervals; Investigations; Monte Carlo simulation; network sufficiency; optimization; Renewable energy; Renewable resources; Simulation; Solar energy; Spatial resolution; Temporal resolution; transformation of energy system; transport needs; Uncertainty; wind energy
• ISSN: 2050-0505; 2050-0505
• DOI: 10.1002/ese3.1015

The transformation of the energy system towards a sustainable reduction of CO2 emissions and the consequently rising contribution of fluctuating energy sources to the German energy system leads to new challenges. In particular, the sufficiency of the present powerline system is of interest. To evaluate the German network sufficiency, a data‐based modelling is used to measure the number of intervals with insufficient transport capabilities as well as the yearly sum of infeasible power transports. In order to do so, the actual residual loads are calculated from the power data in the database “GEOWISOL” and the data on the German power grid are obtained from the project “SciGrid.” The temporal resolution of power data is 15 min, and the spatial resolution refers to the 2‐digit ZIP code regions. The present transmission network is shown to be insufficient in a linearly increasing number of intervals for scenarios with increasing renewable power production. The uncertainties of the results presented are also investigated by means of a Monte Carlo simulation with the known uncertainties of the power data. The simulation results in a relative uncertainty for the number of intervals with insufficient transport capabilities of the network of roughly 1%. Thus, it can be used in the future either to investigate network expansion plans or to validate network expansion studies with simulated data or synthetic networks. The growing power input of renewable energy sources leads to challenges for the power grid. In this article, the powergrid is modelled on a database of measured data, first the method is presented, the quality of the investigation is quantified, and an example is given.