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<export-example>
  <doc>
    <id>32775</id>
    <completedYear/>
    <publishedYear>2023</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>340</pageFirst>
    <pageLast>363</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>bookpart</type>
    <publisherName>Edward Elgar Publishing</publisherName>
    <publisherPlace>Cheltenham, UK ; Northampton, Massachusetts, USA</publisherPlace>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2024-02-02</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">A mixed-integer linear programming approach for an optimal-economic design of renewable district heating systems: a case study for a German grid</title>
    <parentTitle language="eng">Handbook on the economics of renewable energy</parentTitle>
    <identifier type="isbn">978-1-80037-901-5</identifier>
    <identifier type="doi">10.4337/9781800379022.00024</identifier>
    <enrichment key="BTU">an der BTU erstellt / created at BTU</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="Fprofil">1 Energiewende und Dekarbonisierung / Energy Transition and Decarbonisation</enrichment>
    <enrichment key="Fprofil">3 Globaler Wandel und Transformationsprozesse / Global Change and Transformation Processes</enrichment>
    <author>
      <firstName>Maximilian</firstName>
      <lastName>Sporleder</lastName>
    </author>
    <editor>
      <firstName>Pablo del</firstName>
      <lastName>Río</lastName>
    </editor>
    <submitter>
      <firstName>Manuela</firstName>
      <lastName>Krüger</lastName>
    </submitter>
    <author>
      <firstName>Michael</firstName>
      <lastName>Rath</lastName>
    </author>
    <editor>
      <firstName>Mario</firstName>
      <lastName>Ragwitz</lastName>
    </editor>
    <author>
      <firstName>Markus</firstName>
      <lastName>Jansen</lastName>
    </author>
    <author>
      <firstName>Robin</firstName>
      <lastName>Mann</lastName>
    </author>
    <collection role="institutes" number="3221">FG Integrierte Energieinfrastrukturen</collection>
  </doc>
  <doc>
    <id>32440</id>
    <completedYear/>
    <publishedYear>2023</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>2241</pageFirst>
    <pageLast>2252</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject_ref</type>
    <publisherName>ECOS</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2024-01-12</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Utilizing Historical Operating Data to increase  Accuracy for Optimal Seasonal Storage  Integration and Planning</title>
    <abstract language="eng">Policies reasoned by global climate change and increasing commodity prices due to the international energy crisis force district heating providers to transform their assets. Pit thermal energy storage combined with solar energy can improve this transformation process. Optimal energy planning of district heating systems is often achieved by applying a linear programming model due to its fast computing. Unfortunately, depicting those systems in linear programming requires complexity reduction. We introduce a method capable of designing and operating the system with the complexity increase of considering the top and bottom temperatures of the pit thermal energy storage in linear programming. Firstly, we extract and clean data from existing sites and simulations of seasonal storages. Secondly, we develop a polynomial regression model based on the extracted data to predict the top and bottom temperatures. Lastly, we develop a mixed-integer linear programming model using the predictions and compare it to existing sites. The model uses solar thermal energy, a pit thermal energy storage, and other units to meet the demand of a district heating system. The polynomial regression results show an accuracy of up to 92 % with only a few features to base the prediction. The optimization model can design the storage and depict the correlation between decreasing specific costs and thermal losses due to an increasing volume. The control strategy of the heat pump requires further improvement.</abstract>
    <parentTitle language="eng">36th International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems (ECOS 2023), Las Palmas De Gran Canaria, Spain</parentTitle>
    <identifier type="doi">10.52202/069564-0202</identifier>
    <enrichment key="BTU">an der BTU erstellt / created at BTU</enrichment>
    <enrichment key="BTUfunderNamenotEU">BMBF</enrichment>
    <enrichment key="Publikationsweg">Open Access</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="Fprofil">1 Energiewende und Dekarbonisierung / Energy Transition and Decarbonisation</enrichment>
    <enrichment key="Fprofil">3 Globaler Wandel und Transformationsprozesse / Global Change and Transformation Processes</enrichment>
    <author>
      <firstName>Maximilian</firstName>
      <lastName>Sporleder</lastName>
    </author>
    <submitter>
      <firstName>Manuela</firstName>
      <lastName>Krüger</lastName>
    </submitter>
    <author>
      <firstName>Michael</firstName>
      <lastName>Rath</lastName>
    </author>
    <author>
      <firstName>Yuwei</firstName>
      <lastName>Xu</lastName>
    </author>
    <author>
      <firstName>Mathias van</firstName>
      <lastName>Beek</lastName>
    </author>
    <author>
      <firstName>Mario</firstName>
      <lastName>Ragwitz</lastName>
    </author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>MILP</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Seasonal Storage</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Optimization</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>District Heating</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Design</value>
    </subject>
    <collection role="institutes" number="3221">FG Integrierte Energieinfrastrukturen</collection>
  </doc>
</export-example>
