Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Estimation of power system inertia using particle swarm optimization
KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems. (PSOC)ORCID iD: 0000-0003-1993-7082
KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems. (PSOC)ORCID iD: 0000-0002-6431-9104
KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems. (PSOC)ORCID iD: 0000-0002-4210-8672
2017 (English)In: 2017 19th International Conference on Intelligent System Application to Power Systems, ISAP 2017, Institute of Electrical and Electronics Engineers (IEEE), 2017, article id 8071383Conference paper, Published paper (Refereed)
Abstract [en]

Power system inertia is being globally reduced, due to the substitution of conventional synchronous power plants by intermittent generation. This threatens the frequency stability of the system and makes the estimation of power system inertia necessary, so that proactive measures can be imposed. A disturbance-based method is proposed in this paper, which estimates the total inertia constant of the power system. The method applies particle swarm optimization (PSO) to minimize a cost function, which is defined based on the swing equation. To do that, data available at the generator buses are employed. The proposed method is applied on the Nordic57 test system under twenty different scenarios, which include generator and load disconnections. Furthermore, a comparison with two methods presented in the literature is performed and demonstrates the higher performance of the proposed method, in the sense of the mean and the variance of the errors.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2017. article id 8071383
Keywords [en]
Particle Swarm Optimization, Power System Dynamics, Power System Inertia, Renewable Energy Sources, Swing Equation
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:kth:diva-217790DOI: 10.1109/ISAP.2017.8071383Scopus ID: 2-s2.0-85039955585ISBN: 9781509040001 (print)OAI: oai:DiVA.org:kth-217790DiVA, id: diva2:1157531
Conference
19th International Conference on Intelligent System Applications to Power Systems, San Antonio, USA, 17-20 Sept. 2017
Note

QC 20171117

Available from: 2017-11-16 Created: 2017-11-16 Last updated: 2018-01-31Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Search in DiVA

By author/editor
Zografos, DimitriosGhandhari, MehrdadParidari, Kaveh
By organisation
Electric Power and Energy Systems
Electrical Engineering, Electronic Engineering, Information Engineering

Search outside of DiVA

GoogleGoogle Scholar

doi
isbn
urn-nbn

Altmetric score

doi
isbn
urn-nbn
Total: 60 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf