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Multi-timescale data-driven method identifying flexibility requirements for scenarios with high penetration of renewables

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  • Olsen, Karen Pardos
  • Zong, Yi
  • You, Shi
  • Bindner, Henrik
  • Koivisto, Matti
  • Gea-Bermúdez, Juan

Abstract

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 find that energy storage requirements will increase significantly towards 2030 but less so towards 2050 for Denmark as a whole.

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  • Olsen, Karen Pardos & Zong, Yi & You, Shi & Bindner, Henrik & Koivisto, Matti & Gea-Bermúdez, Juan, 2020. "Multi-timescale data-driven method identifying flexibility requirements for scenarios with high penetration of renewables," Applied Energy, Elsevier, vol. 264(C).
    • Handle: RePEc:eee:appene:v:264:y:2020:i:c:s0306261920302142
    DOI: 10.1016/j.apenergy.2020.114702
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    References listed on IDEAS

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    7. Zhao, Mingzhe & Wang, Yimin & Wang, Xuebin & Chang, Jianxia & Chen, Yunhua & Zhou, Yong & Guo, Aijun, 2022. "Flexibility evaluation of wind-PV-hydro multi-energy complementary base considering the compensation ability of cascade hydropower stations," Applied Energy, Elsevier, vol. 315(C).
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