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Storage and Demand Response inclusion in the network extension planning process

Raúl RODRÍGUEZ-SÁNCHEZ; Santiago GARCÍA-LÁZARO; Gianluigi MIGLIAVACCA; Dario SIFACE


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  <identifier identifierType="DOI">10.5281/zenodo.7064973</identifier>
  <creators>
    <creator>
      <creatorName>Raúl RODRÍGUEZ-SÁNCHEZ</creatorName>
      <affiliation>TECNALIA R&amp;I (BRTA)</affiliation>
    </creator>
    <creator>
      <creatorName>Santiago GARCÍA-LÁZARO</creatorName>
      <affiliation>TECNALIA R&amp;I (BRTA)</affiliation>
    </creator>
    <creator>
      <creatorName>Gianluigi MIGLIAVACCA</creatorName>
      <affiliation>RSE</affiliation>
    </creator>
    <creator>
      <creatorName>Dario SIFACE</creatorName>
      <affiliation>RSE</affiliation>
    </creator>
  </creators>
  <titles>
    <title>Storage and Demand Response inclusion in the network extension planning process</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2022</publicationYear>
  <subjects>
    <subject>Storage - Demand Response – Electricity Network - Planning - Flexibility</subject>
  </subjects>
  <dates>
    <date dateType="Issued">2022-09-02</date>
  </dates>
  <resourceType resourceTypeGeneral="JournalArticle"/>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/7064973</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.5281/zenodo.7064972</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 increasing participation of variable wind and solar energy production plants in the power system requires flexibility from other resources, such as fast reacting generation assets, storage and demand response. Storage, other than pumped-storage hydropower, and demand response have not been considered in traditional network planning procedures, but they are expected to play a bigger role in the operation of power systems in the future. In the frame of the EU FlexPlan R&amp;amp;D project (https://flexplan-project.eu/) an innovative network planning methodology is proposed, where flexibility resources are presented as candidates for network planning, competing with conventional network assets. The candidate pre-selection is carried out by a specific software tool developed to interact automatically with the main planning tool. The consideration of relatively small size flexibility resources in the planning process, along with other aspects such as the environmental impact, the reliability, various scenarios and the interaction between distribution and transmission network operation, makes challenging the formulation and solution of the optimization function. Therefore, a pre-section of network extension candidates contributes to reduce the dimension of the mathematical problem. The flexibility resources analysis is performed by the candidate pre-processor through the following steps: &amp;bull; Network lines and transformers potentially affected by congestion are identified after performing an optimal power flow (OPF) simulation in the non-expanded network. The network model is evaluated under several generation and load scenarios. A ranking of congested branches is proposed based on hourly Lagrange multipliers&amp;rsquo; (LM) values. 11029 Session 2022 C1 Power System Development and Economics PS2 &amp;ndash; Energy sector integration and tackling the complexity of multi-faceted network projects Information available from your National Committee and in the emails sent to your att. 2 &amp;bull; The flexibility resources analysis tool (pre-processor) proposes a list of network expansion candidates for identified congested assets, including storage (Li-ion, NaS and flow batteries, hydrogen, CAES and LAES), demand response (DR), and lines/cables/transformers. This selection is performed based on congestion characteristics and on possible location-related constraints. Cost and size details are provided related to the technology of each selected candidate. &amp;bull; Eventually, the proposed candidates for grid congestion support are provided to the planning tool as input, which, in turn, assesses the best planning option for the power system in the time frame of the study. Before proposing the candidate technologies, locational constraints and bus characteristics are checked. The network information provided for relevant nodes is used to discard, or not, some of the candidate technologies: urban substations, restricted areas, or the inexistence of loads, for example, already make some of them unfeasible. The characteristics of the congestion, such as the number of congestion hours in one year or the number of consecutive congestion hours are also an input for the selection of candidate technologies. A set of rules is predefined at the pre-processor to perform the assessment. Once the most suitable technologies have been selected, the pre-processor estimates and provides a size and cost for each of them.&lt;/p&gt;</description>
  </descriptions>
  <fundingReferences>
    <fundingReference>
      <funderName>European Commission</funderName>
      <funderIdentifier funderIdentifierType="Crossref Funder ID">10.13039/100010661</funderIdentifier>
      <awardNumber awardURI="info:eu-repo/grantAgreement/EC/Horizon 2020 Framework Programme - Research and Innovation action/863819/">863819</awardNumber>
      <awardTitle>Advanced methodology and tools taking advantage of storage and FLEXibility in transmission and distribution grid PLANning</awardTitle>
    </fundingReference>
  </fundingReferences>
</resource>
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