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  <titleInfo>
    <title>Electrical load forecasting in Nepal</title>
    <subTitle>application of time series and simulation methods</subTitle>
  </titleInfo>
  <name type="personal">
    <namePart>Dhungel, Himesh</namePart>
    <role>
      <roleTerm authority="marcrelator" type="text">creator</roleTerm>
    </role>
  </name>
  <name type="personal">
    <namePart>Shrestha, Ram M.</namePart>
    <role>
      <roleTerm type="text">Chairperson</roleTerm>
    </role>
  </name>
  <name type="personal">
    <namePart>Lapillonne, Bruno</namePart>
    <role>
      <roleTerm type="text">Examination Committee</roleTerm>
    </role>
  </name>
  <name type="personal">
    <namePart>Nagarur, Nagendra N.</namePart>
    <role>
      <roleTerm type="text">Examination Committee</roleTerm>
    </role>
  </name>
  <name type="corporate">
    <namePart>The Government of Australia</namePart>
    <role>
      <roleTerm type="text">Scholarship Donor</roleTerm>
    </role>
  </name>
  <typeOfResource>text</typeOfResource>
  <originInfo>
    <place>
      <placeTerm type="code" authority="marccountry">th</placeTerm>
    </place>
    <place>
      <placeTerm type="text">Bangkok</placeTerm>
    </place>
    <publisher>Asian Institute of Technology</publisher>
    <dateIssued>1990</dateIssued>
    <issuance>monographic</issuance>
  </originInfo>
  <language>
    <languageTerm authority="iso639-2b" type="code">eng</languageTerm>
  </language>
  <physicalDescription>
    <extent>120 p.</extent>
  </physicalDescription>
  <abstract>This study deals with the problem of short term and long term peak load  forecasting in Nepal. The stochastic time series Autoregressive Integrated Moving  average (ARIMA) method has been used to forecast load in the hourly, daily, weekly  and the monthly time horizons. In the paper, the bivariate transfer function model  with temperature as an explanatory variable is used to forecast the hourly peak  demand of a small area. A comparison of the transfer function model and the ARIMA  model (to forecast hourly demand) found that transfer function model performed  better than the ARIMA model.  The long term simulation type of forecasting model called Model for Analysis  of the Energy Demand (MAED) is used to forecast the annual pealed load and the  system load curves. The analysis and simulation of t h e system load curves under  different hypothetical conditions suggested that load management strategies could  possibly implemented (in Nepal) to reduce the peak load in the intermediate term.  The case study was carried out for the integrated electric system of Nepal  Electricity Authority.</abstract>
  <note>A thesis submitted in partial fulfillment of the requirements of Master of Engineering, School of Engineering and Technology  </note>
  <note>Thesis (M.Eng.) - Asian Institute of Technology, 1990</note>
  <subject authority="lcsh">
    <topic>Electric power consumption</topic>
    <topic>Nepal</topic>
    <topic>Forecasting</topic>
  </subject>
  <relatedItem type="series">
    <titleInfo>
      <title>Thesis ; no. ET-90-14</title>
    </titleInfo>
    <name type="corporate">
      <namePart>Asian Institute of Technology.</namePart>
      <namePart/>
    </name>
  </relatedItem>
  <identifier type="uri">http://203.159.5.9/ait-thesis/detail.php?q=B18318</identifier>
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    <url displayLabel="Full-Text">http://203.159.5.9/ait-thesis/detail.php?q=B18318</url>
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    <recordCreationDate encoding="marc">280998</recordCreationDate>
    <recordChangeDate encoding="iso8601">20260818095451.0</recordChangeDate>
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