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  <doc>
    <id>336</id>
    <completedYear/>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>article</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2020-10-06</completedDate>
    <publishedDate>2020-10-06</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Producer’s Best Response in Pay-as-clear Day-ahead Electricity Market with Uncertain Demand</title>
    <abstract language="eng">We deal with several sources of uncertainty in electricity markets. The independent system operator (ISO) maximizes the social welfare using chance constraints to hedge against discrepancies between the estimated and real electricity&#13;
demand. We find an explicit solution of the ISO problem, and use it to tackle the&#13;
problem of a producer. In our model, production as well as income of a producer&#13;
are determined based on the estimated electricity demand predicted by the ISO, that&#13;
is unknown to producers. Thus, each producer is hedging against the uncertainty of&#13;
prediction of the demand using the value-at-risk approach. To illustrate our results, a&#13;
numerical study of a producer’s best response given a historical distribution of both&#13;
estimated and real electricity demand is provided.</abstract>
    <enrichment key="SubmissionStatus">under review</enrichment>
    <enrichment key="review.accepted_by">2</enrichment>
    <licence>Creative Commons - CC BY-NC-ND - Namensnennung - Nicht kommerziell - Keine Bearbeitungen 4.0 International</licence>
    <author>Martin Branda</author>
    <author>René Henrion</author>
    <author>Miroslav Pistek</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>electricity market</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>multi-leader-common-follower game</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>stochastic demand</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>day-ahead bidding</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>chance constraints</value>
    </subject>
    <collection role="institutes" number="">Weierstraß-Institut für Angewandte Analysis und Stochastik</collection>
    <collection role="subprojects" number="">B04</collection>
    <file>https://opus4.kobv.de/opus4-trr154/files/336/BHP_2020.pdf</file>
  </doc>
</export-example>
