<?xml version='1.0' encoding='UTF-8'?><?xml-stylesheet href='static/style.xsl' type='text/xsl'?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-04-07T11:46:01Z</responseDate><request verb="GetRecord" identifier="oai:ebiltegia.mondragon.edu:20.500.11984/5959" metadataPrefix="rdf">https://ebiltegia.mondragon.edu/oai/request</request><GetRecord><record><header><identifier>oai:ebiltegia.mondragon.edu:20.500.11984/5959</identifier><datestamp>2024-03-04T11:39:19Z</datestamp><setSpec>com_20.500.11984_1143</setSpec><setSpec>col_20.500.11984_1148</setSpec></header><metadata><rdf:RDF xmlns:rdf="http://www.openarchives.org/OAI/2.0/rdf/" xmlns:ow="http://www.ontoweb.org/ontology/1#" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:ds="http://dspace.org/ds/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:doc="http://www.lyncode.com/xoai" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/rdf/ http://www.openarchives.org/OAI/2.0/rdf.xsd">
   <ow:Publication rdf:about="oai:ebiltegia.mondragon.edu:20.500.11984/5959">
      <dc:title>Design and validation of a predictive energy management strategy for self-consumption in tertiary buildings</dc:title>
      <dc:creator>Oca, Laura</dc:creator>
      <dc:contributor>Feijoo Arostegui, Ane</dc:contributor>
      <dc:contributor>Goitia Zabaleta, Nerea</dc:contributor>
      <dc:contributor>Milo, Aitor</dc:contributor>
      <dc:contributor>Gaztañaga, Haizea</dc:contributor>
      <dc:subject>photovoltaic (PV)</dc:subject>
      <dc:subject>Buildings</dc:subject>
      <dc:subject>Measurement uncertainty</dc:subject>
      <dc:subject>Control systems</dc:subject>
      <dc:subject>Real-time systems</dc:subject>
      <dc:subject>Battery charge measurement</dc:subject>
      <dc:description>This work presents a predictive energy management strategy for self-consumption in tertiary buildings. The self-consumption is composed of a photovoltaic generation and a battery. The energy management strategy is composed of a forecast module, high-level strategy and real-time adaptative control. Due to the daily forecast, significant data was available 24 hours in advance, allowing the energy management strategy to take advantage. The high-level strategy defines the battery’s operation mode for each hour of the day. The real-time adaptative control corrects the possible errors with instant measurements and generates real-time battery commands and its operation mode. With this approach, a reduction of 16.17 % of the electric bill was obtained by comparing it to a scenario without a battery and its correspondent strategy. The development was integrated and validated in a test bench, obtaining a 60.43 % grid independence increase.</dc:description>
      <dc:date>2023-01-16T12:14:18Z</dc:date>
      <dc:date>2023-01-16T12:14:18Z</dc:date>
      <dc:date>2022</dc:date>
      <dc:type>http://purl.org/coar/resource_type/c_c94f</dc:type>
      <dc:identifier>978-1-6654-0896-7</dc:identifier>
      <dc:identifier>2165-4093</dc:identifier>
      <dc:identifier>https://katalogoa.mondragon.edu/janium-bin/janium_login_opac.pl?find&amp;ficha_no=170383</dc:identifier>
      <dc:identifier>https://hdl.handle.net/20.500.11984/5959</dc:identifier>
      <dc:language>eng</dc:language>
      <dc:rights>© 2022 IEEE</dc:rights>
      <dc:publisher>IEEE</dc:publisher>
   </ow:Publication>
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