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PowerFactory-Python based assessment of frequency and transient stability in power systems dominated by power electronic interfaced generation

Jose Rueda; Peter Palensky; Jorge Mola-Jimenez; Arcadio Perilla; Da Wang; Mart van der Meijden


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  <identifier identifierType="URL">https://zenodo.org/record/2573889</identifier>
  <creators>
    <creator>
      <creatorName>Jose Rueda</creatorName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0001-7288-0228</nameIdentifier>
      <affiliation>Delft University of Technology</affiliation>
    </creator>
    <creator>
      <creatorName>Peter Palensky</creatorName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0003-3183-4705</nameIdentifier>
      <affiliation>Delft University of Technology</affiliation>
    </creator>
    <creator>
      <creatorName>Jorge Mola-Jimenez</creatorName>
      <affiliation>Delft University of Technology</affiliation>
    </creator>
    <creator>
      <creatorName>Arcadio Perilla</creatorName>
      <affiliation>Delft University of Technology</affiliation>
    </creator>
    <creator>
      <creatorName>Da Wang</creatorName>
      <affiliation>Delft University of Technology</affiliation>
    </creator>
    <creator>
      <creatorName>Mart van der Meijden</creatorName>
      <affiliation>Delft University of Technology</affiliation>
    </creator>
  </creators>
  <titles>
    <title>PowerFactory-Python based assessment of frequency and transient stability in power systems dominated by power electronic interfaced generation</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2019</publicationYear>
  <subjects>
    <subject>Frequency stability, key performance indicators, power electronics interfaced generation, power system dynamics, transient stability, wind power</subject>
  </subjects>
  <dates>
    <date dateType="Issued">2019-02-20</date>
  </dates>
  <resourceType resourceTypeGeneral="ConferencePaper"/>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/2573889</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsIdenticalTo">10.1109/MSCPES.2018.8405403</relatedIdentifier>
  </relatedIdentifiers>
  <rightsList>
    <rights rightsURI="https://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;The deployment of variable renewable energy based power plants is increasing all over the world, however, unlike&lt;br&gt;
conventional power plants these are mostly connected to the grid via power electronic interfaces. High penetration of power&lt;br&gt;
electronic interfaced generation (PEIG) has an important impact&amp;nbsp;on the inertia of the system, which is of major concern for&lt;br&gt;
frequency and large disturbance rotor angle (transient) stability. Therefore, it is desirable to study the effectiveness of widely&lt;br&gt;
used approaches to assess the stability of a system with high penetration of PEIG. This paper concerns with the modelling and&lt;br&gt;
control aspects of a power system for the evaluation of the most widely used metrics (indicators) to assess the dynamics of the&lt;br&gt;
power system related to frequency and rotor angle stability. The functionalities of Python are used to automate the generation of&lt;br&gt;
operational scenarios, the execution of time domain simulations, and the extraction of signal records to compute the aforesaid&lt;br&gt;
indicators. The paper also provides a discussion about possible improvements in the application of these indicators in monitoring&lt;br&gt;
tasks.&lt;/p&gt;</description>
  </descriptions>
  <fundingReferences>
    <fundingReference>
      <funderName>European Commission</funderName>
      <funderIdentifier funderIdentifierType="Crossref Funder ID">10.13039/501100000780</funderIdentifier>
      <awardNumber awardURI="info:eu-repo/grantAgreement/EC/H2020/691800/">691800</awardNumber>
      <awardTitle>Massive InteGRATion of power Electronic devices</awardTitle>
    </fundingReference>
  </fundingReferences>
</resource>
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