The authors thank Gorm Bruun Andresen, associate professor at Aarhus University and Anna Scaglione, professor at Arizona State University, for valuable comments to improve this work. The authors thank Jakob Zimmermand at DTU CEE, for help with the extraction of data from Bornholm. Finally, the authors are grateful for the work done to maintain PowerLabDK and for the information received from helpful employees at BEOF, the DSO on Bornholm. This work is funded by the \Enhancing wind power integration through optimal use of cross-sectoral flexibility in an integrated multi-energy system (EPIMES)" project granted by the Danish Innovation Funding (No. 5185-00005A). This work beneted from support from the NSON-DK (Danish Energy Agency, EUDP, grant 64018-0032) and PSfuture (DTU Wind Energy, La Cour Fellowship) projects. This work is also supported by the "Converting WASTE to offer flexible GRID balancing Services with highly-integrated, efficient solid-oxide plants (Waste2Grids)" project granted by the EU H2020 (No. 826161).

The way towards a more sustainable future, involves increasing amounts of variable renewable energy (VRE), yet the inherent variability in VRE generation poses challenges on power system management. In this paper, a method is presented to quickly assess the fluctuating discrepancies between VRE production (wind and solar) and electricity consumption for system planning purposes. The method utilizes Fourier analysis to disentangle the energy storage and power flexibility requirements on different frequencies and is validated via application to different geographical areas and to current and future scenarios in both real and simulated hourly data. Novelties include a subdivision of the residual load in more temporal scales than usually adopted, a pie chart visualization to compare the strength of different oscillations and a ready-to-use Python module. We nd that energy storage requirements will increase significantly towards 2030 but less so towards 2050 for Denmark as a whole.