Conference paper Open Access

Optimal Direct Load Control of Renewable Powered Small Cells: Performance Evaluation and Bounds

Piovesan, Nicola; Miozzo, Marco; Dini, Paolo

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      <creatorName>Piovesan, Nicola</creatorName>
      <affiliation>Centre Tecnològic de Telecomunicacions de Catalunya (CTTC)</affiliation>
      <creatorName>Miozzo, Marco</creatorName>
      <affiliation>Centre Tecnològic de Telecomunicacions de Catalunya (CTTC)</affiliation>
      <creatorName>Dini, Paolo</creatorName>
      <affiliation>Centre Tecnològic de Telecomunicacions de Catalunya (CTTC)</affiliation>
    <title>Optimal Direct Load Control of Renewable Powered Small Cells: Performance Evaluation and Bounds</title>
    <subject>Mobile Networks</subject>
    <subject>Energy Sustainability</subject>
    <subject>Optimal Control</subject>
    <subject>Demand Response</subject>
    <subject>Dynamic Programming</subject>
    <subject>Direct Load Control</subject>
    <date dateType="Issued">2018-04-15</date>
  <resourceType resourceTypeGeneral="Text">Conference paper</resourceType>
    <alternateIdentifier alternateIdentifierType="url"></alternateIdentifier>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsIdenticalTo">10.1109/WCNC.2018.8377448</relatedIdentifier>
    <rights rightsURI="">Creative Commons Attribution 4.0 International</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
    <description descriptionType="Abstract">&lt;p&gt;In this paper, we propose an optimal direct load control of renewable powered small base stations based on Dynamic Programming. The optimization is represented using Graph Theory and the problem is stated as a Shortest Path problem. The proposed optimal algorithm is able to adapt to the varying conditions of renewable energy sources and traffic demands. We analyze the optimal ON/OFF policies considering different energy and traffic scenarios. Then, we evaluate network performance in terms of system drop rate and grid energy consumption. The obtained results are compared with a greedy approach. This study allows to elaborate on the behavior and performance bounds of the system and gives a guidance for approximated policy search methods.&lt;/p&gt;</description>
    <description descriptionType="Other">© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.</description>
      <funderName>European Commission</funderName>
      <funderIdentifier funderIdentifierType="Crossref Funder ID">10.13039/501100000780</funderIdentifier>
      <awardNumber awardURI="info:eu-repo/grantAgreement/EC/H2020/675891/">675891</awardNumber>
      <awardTitle>Sustainable CellulAr networks harVEstiNG ambient Energy</awardTitle>
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