Data-driven flexibility requirements for current and future scenarios with high penetration of renewables

Karen Pardos Olsen, Yi Zong, Shi You, Henrik W. Bindner, Matti Juhani Koivisto, Juan Gea-Bermudez

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

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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 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.
Original languageEnglish
Title of host publicationProceedings of International Conference on Applied Energy 2019
Number of pages4
Publication date2019
Article numberPaper ID: 0341
Publication statusPublished - 2019
EventInternational Conference on Applied Energy 2019 - Mälardalens högskola, Västerås, Sweden
Duration: 12 Aug 201915 Aug 2019

Conference

ConferenceInternational Conference on Applied Energy 2019
LocationMälardalens högskola
Country/TerritorySweden
CityVästerås
Period12/08/201915/08/2019

Keywords

  • Energy  storage
  • Flexibility
  • Flexible  load
  • Power system planning
  • Renewable power
  • Timeseries  analysis

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