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Prediction of Frequency Nadir by Employing a Neural Network Approach
KTH, School of Electrical Engineering and Computer Science (EECS), Electric Power and Energy Systems. (PSOC)ORCID iD: 0000-0003-1993-7082
KTH, School of Electrical Engineering and Computer Science (EECS), Electric Power and Energy Systems.ORCID iD: 0000-0003-4736-4760
KTH, School of Electrical Engineering and Computer Science (EECS), Electric Power and Energy Systems.
2018 (English)In: 2018 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe), Institute of Electrical and Electronics Engineers (IEEE), 2018Conference paper, Published paper (Refereed)
Abstract [en]

The increased integration rate of inverter-interfaced devices is affecting the frequency response of the modern power systems. This leads to an increase of the variability of the power generation and to a reduction of the total system's inertia. This evolution of the system necessitates the prediction of frequency metrics, so that the frequency stability of the system can be guaranteed and that necessary mitigation measures can be taken. This paper proposes a method to predict the frequency nadir by using a Neural Network (NN) approach. As the approach uses measurements during a first short time period after the event, it more accurately predicts the frequency nadir compared to using static values. Several inputs for the NN are examined and when the appropriate ones are selected, a highly accurate prediction is accomplished.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2018.
Series
IEEE PES Innovative Smart Grid Technologies Conference Europe, ISSN 2165-4816
Keywords [en]
Frequency Response, Neural Network, Power System Dynamics, Power System Inertia, Renewable Energy Sources
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Electrical Engineering
Identifiers
URN: urn:nbn:se:kth:diva-241141DOI: 10.1109/ISGTEurope.2018.8571581ISI: 000458690200066Scopus ID: 2-s2.0-85060251220ISBN: 978-1-5386-4505-5 (print)OAI: oai:DiVA.org:kth-241141DiVA, id: diva2:1278322
Conference
2018 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe), 21-25 Oct. 2018, Sarajevo, Bosnia-Herzegovina
Note

QC 20190117

Available from: 2019-01-14 Created: 2019-01-14 Last updated: 2019-05-10Bibliographically approved

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Rabuzin, Tin

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
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More styles
Language
  • de-DE
  • en-GB
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  • nn-NB
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  • Other locale
More languages
Output format
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