Journal article Open Access

Adaptive clustering-based hierarchical layout optimisation for large-scale integrated energy systems

Guo, Hui; Shi, Tianling; Wang, Fei; Zhang, Lijun; Lin, Zhengyu


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  <identifier identifierType="URL">https://zenodo.org/record/4610207</identifier>
  <creators>
    <creator>
      <creatorName>Guo, Hui</creatorName>
      <givenName>Hui</givenName>
      <familyName>Guo</familyName>
      <affiliation>Shanghai University</affiliation>
    </creator>
    <creator>
      <creatorName>Shi, Tianling</creatorName>
      <givenName>Tianling</givenName>
      <familyName>Shi</familyName>
      <affiliation>Shanghai University</affiliation>
    </creator>
    <creator>
      <creatorName>Wang, Fei</creatorName>
      <givenName>Fei</givenName>
      <familyName>Wang</familyName>
      <affiliation>Shanghai University</affiliation>
    </creator>
    <creator>
      <creatorName>Zhang, Lijun</creatorName>
      <givenName>Lijun</givenName>
      <familyName>Zhang</familyName>
      <affiliation>Shanghai University</affiliation>
    </creator>
    <creator>
      <creatorName>Lin, Zhengyu</creatorName>
      <givenName>Zhengyu</givenName>
      <familyName>Lin</familyName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0001-7733-2431</nameIdentifier>
      <affiliation>Loughborough University</affiliation>
    </creator>
  </creators>
  <titles>
    <title>Adaptive clustering-based hierarchical layout optimisation for large-scale integrated energy systems</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2021</publicationYear>
  <subjects>
    <subject>power distribution reliability</subject>
    <subject>optimisation</subject>
    <subject>distributed power generation</subject>
  </subjects>
  <dates>
    <date dateType="Issued">2021-02-16</date>
  </dates>
  <language>en</language>
  <resourceType resourceTypeGeneral="Text">Journal article</resourceType>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/4610207</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsIdenticalTo">10.1049/iet-rpg.2020.0105</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="URL" relationType="IsPartOf">https://zenodo.org/communities/rdc2mt</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;Different energy systems are generally planned and operated independently, which result in the low energy&amp;nbsp;utilisation, weak self-healing ability, and low system reliability. Therefore, an adaptive clustering-based hierarchical layout&amp;nbsp;optimisation method is proposed for a large-scale integrated energy system, considering energy balance, transmission&amp;nbsp;losses and construction costs. First, an adaptive clustering partition method based on energy balance and load moments is&amp;nbsp;proposed to determine the optimal location of energy hubs and to allocate each distributed generation and load to&amp;nbsp;different energy hubs, forming multiple regional integrated energy systems adaptively. Then, the proposed hierarchical&amp;nbsp;layout optimisation model is formulated as to find the modified minimum spanning tree of regional integrated energy&amp;nbsp;system and multi-regional integrated energy systems respectively, to construct an economical and reliable interconnection&amp;nbsp;network. Finally, the effectiveness of the optimisation model and strategy is verified by simulations.&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/H2020/734796/">734796</awardNumber>
      <awardTitle>Research, Demonstration, and Commercialisation of DC Microgrid Technologies</awardTitle>
    </fundingReference>
  </fundingReferences>
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