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A platform for research: civil engineering, architecture and urbanism
Data-driven flexibility requirements for current and future scenarios with high penetration of renewables
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 a discrete Fourier transform (DFT) analysis to disentangle the energy storage and power flexibility requirements on different frequencies and is applied here 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.
Data-driven flexibility requirements for current and future scenarios with high penetration of renewables
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 a discrete Fourier transform (DFT) analysis to disentangle the energy storage and power flexibility requirements on different frequencies and is applied here 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.
Data-driven flexibility requirements for current and future scenarios with high penetration of renewables
Olsen, Karen Pardos (author) / Zong, Yi (author) / You, Shi (author) / Bindner, Henrik W. (author) / Koivisto, Matti Juhani (author) / Gea-Bermudez, Juan (author)
2019-01-01
Olsen , K P , Zong , Y , You , S , Bindner , H W , Koivisto , M J & Gea-Bermudez , J 2019 , Data-driven flexibility requirements for current and future scenarios with high penetration of renewables . in Proceedings of International Conference on Applied Energy 2019 . , Paper ID: 0341 , International Conference on Applied Energy 2019 , Västerås , Sweden , 12/08/2019 .
Article (Journal)
Electronic Resource
English
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