
<ns0:uwmetadata xmlns:ns0="http://phaidra.univie.ac.at/XML/metadata/V1.0" xmlns:ns1="http://phaidra.univie.ac.at/XML/metadata/lom/V1.0" xmlns:ns10="http://phaidra.univie.ac.at/XML/metadata/provenience/V1.0" xmlns:ns11="http://phaidra.univie.ac.at/XML/metadata/provenience/V1.0/entity" xmlns:ns12="http://phaidra.univie.ac.at/XML/metadata/digitalbook/V1.0" xmlns:ns13="http://phaidra.univie.ac.at/XML/metadata/etheses/V1.0" xmlns:ns2="http://phaidra.univie.ac.at/XML/metadata/extended/V1.0" xmlns:ns3="http://phaidra.univie.ac.at/XML/metadata/lom/V1.0/entity" xmlns:ns4="http://phaidra.univie.ac.at/XML/metadata/lom/V1.0/requirement" xmlns:ns5="http://phaidra.univie.ac.at/XML/metadata/lom/V1.0/educational" xmlns:ns6="http://phaidra.univie.ac.at/XML/metadata/lom/V1.0/annotation" xmlns:ns7="http://phaidra.univie.ac.at/XML/metadata/lom/V1.0/classification" xmlns:ns8="http://phaidra.univie.ac.at/XML/metadata/lom/V1.0/organization" xmlns:ns9="http://phaidra.univie.ac.at/XML/metadata/histkult/V1.0">
  <ns1:general>
    <ns1:identifier>o:5420</ns1:identifier>
    <ns1:title language="en">Electricity Usage Efficiency and Electricity Demand Modeling in the Case of Germany and the UK</ns1:title>
    <ns1:language>en</ns1:language>
    <ns1:description language="en">Abstract: In this article, monthly and yearly electricity consumption predictions for the German
power market were calculated using the multiple variable regression model. This model accounts for
several factors that are often neglected when forecasting electricity demand in practice, in particular
the role of the higher efficiency of electricity usage from year to year. The analysis performed in
this paper helps to explain why no growth in power consumption has been observed in Germany
during the last decade. It shows that the electricity efficiency usage dataset is a relevant input for the
model, which mitigates the combined impact of other factors on the final electricity consumption.
The electricity demand forecasting model presented in this article was built in the year 2013 with
forecasts for the future years’ electricity demand in Germany provided until 2020. These forecasts
and related findings are also evaluated in this article.</ns1:description>
    <ns1:keyword language="en">Keywords: electricity consumption; demand forecasting; regression models; electricity usage efficiency</ns1:keyword>
    <ns2:identifiers>
      <ns2:resource>1552099</ns2:resource>
      <ns2:identifier>10.3390/app10072291</ns2:identifier>
    </ns2:identifiers>
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  <ns1:lifecycle>
    <ns1:upload_date>2024-09-26T08:43:10.668Z</ns1:upload_date>
    <ns1:status>44</ns1:status>
    <ns2:peer_reviewed>yes</ns2:peer_reviewed>
    <ns1:contribute seq="0">
      <ns1:role>46</ns1:role>
      <ns1:entity seq="0">
        <ns3:firstname>Branislav </ns3:firstname>
        <ns3:lastname>Dudic </ns3:lastname>
        <ns3:institution>Fakultet za ekonomiju i inženjerski menadžment u Novom Sadu</ns3:institution>
        <ns3:orcid>0000-0002-4647-6026</ns3:orcid>
      </ns1:entity>
      <ns1:entity seq="1">
        <ns3:firstname> Jan </ns3:firstname>
        <ns3:lastname>Smolen</ns3:lastname>
        <ns3:type>person</ns3:type>
      </ns1:entity>
      <ns1:entity seq="2">
        <ns3:firstname>Pavel</ns3:firstname>
        <ns3:lastname> Kovac</ns3:lastname>
        <ns3:type>person</ns3:type>
      </ns1:entity>
      <ns1:entity seq="3">
        <ns3:firstname>Borislav </ns3:firstname>
        <ns3:lastname>Savkovic </ns3:lastname>
        <ns3:type>person</ns3:type>
      </ns1:entity>
      <ns1:entity seq="4">
        <ns3:firstname>Zdenka</ns3:firstname>
        <ns3:lastname>Dudic</ns3:lastname>
        <ns3:type>person</ns3:type>
      </ns1:entity>
      <ns1:date>2020</ns1:date>
    </ns1:contribute>
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  <ns1:technical>
    <ns1:format>application/pdf</ns1:format>
    <ns1:size>2352228</ns1:size>
    <ns1:location>https://unilib.phaidrabg.rs/o:5420</ns1:location>
  </ns1:technical>
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    <ns1:cost>no</ns1:cost>
    <ns1:copyright>yes</ns1:copyright>
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    <ns1:purpose>70</ns1:purpose>
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  <ns1:organization>
    <ns8:hoschtyp>1552253</ns8:hoschtyp>
    <ns8:approbation_period>2020-03-23</ns8:approbation_period>
  </ns1:organization>
  <ns12:digitalbook>
    <ns12:name_magazine language="en">Applied Sciences</ns12:name_magazine>
    <ns12:volume>10</ns12:volume>
    <ns12:booklet>7</ns12:booklet>
    <ns12:from_page>2291</ns12:from_page>
    <ns12:to_page>2291</ns12:to_page>
    <ns12:releaseyear>2020-03-27</ns12:releaseyear>
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