Conference paper Open Access

MODEL PREDICTIVE CONTROLBASED ENERGY MANAGEMENT OPTIMIZATION FOR A EUROPEAN MICROGRID IMPLEMENTATION

Gonca GÜRSES-TRAN; Dominik MILDT; Michael HIRST; Marco CUPELLI; Antonello MONTI


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  <identifier identifierType="DOI">10.5281/zenodo.3567858</identifier>
  <creators>
    <creator>
      <creatorName>Gonca GÜRSES-TRAN</creatorName>
      <affiliation>RWTH Aachen University</affiliation>
    </creator>
    <creator>
      <creatorName>Dominik MILDT</creatorName>
      <affiliation>RWTH Aachen University</affiliation>
    </creator>
    <creator>
      <creatorName>Michael HIRST</creatorName>
      <affiliation>E.ON -UK</affiliation>
    </creator>
    <creator>
      <creatorName>Marco CUPELLI</creatorName>
      <affiliation>RWTH Aachen University</affiliation>
    </creator>
    <creator>
      <creatorName>Antonello MONTI</creatorName>
      <affiliation>RWTH Aachen University</affiliation>
    </creator>
  </creators>
  <titles>
    <title>MODEL PREDICTIVE CONTROLBASED ENERGY MANAGEMENT OPTIMIZATION FOR A EUROPEAN MICROGRID IMPLEMENTATION</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2019</publicationYear>
  <subjects>
    <subject>Microgrid control, model predictive control, rule-based control</subject>
  </subjects>
  <dates>
    <date dateType="Issued">2019-06-03</date>
  </dates>
  <language>en</language>
  <resourceType resourceTypeGeneral="ConferencePaper"/>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/3567858</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.5281/zenodo.3567857</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;This paper presents a case study oftwo approaches for optimal microgrid control. The simulations are based on a real test site located in Sweden. One of the two presented models replicates the actual implemented rule based control(RBC)that is currently realized on the test site. The second model applies a model predictive control (MPC) scheme assuming the same system and boundary conditions. The performance is assessedin terms of maximizing the islanding time, signifying the timethe microgrid(MG)can disconnect from the remaining distribution grid.&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/H2020/731289/">731289</awardNumber>
      <awardTitle>Interactions between automated energy systems and Flexibilities brought by energy market players</awardTitle>
    </fundingReference>
  </fundingReferences>
</resource>
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