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  <titleInfo>
    <title>Implications of using electricity in passenger transport and cooking for the energy system development in Bhutan</title>
  </titleInfo>
  <name type="personal">
    <namePart>Yangka, Dorji</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>Kumar, Sivanappan</namePart>
    <role>
      <roleTerm type="text">Examination Committee</roleTerm>
    </role>
  </name>
  <name type="personal">
    <namePart>Mithulananthan, N.</namePart>
    <role>
      <roleTerm type="text">Examination committee</roleTerm>
    </role>
  </name>
  <name type="corporate">
    <namePart>Austrian Development Agency</namePart>
    <role>
      <roleTerm type="text">Scholarship donor</roleTerm>
    </role>
  </name>
  <typeOfResource>text</typeOfResource>
  <genre authority="marc">series</genre>
  <genre authority="marc">technical report</genre>
  <originInfo>
    <place>
      <placeTerm type="code" authority="marccountry">th</placeTerm>
    </place>
    <place>
      <placeTerm type="text">Pathum Thani, Thailand</placeTerm>
    </place>
    <publisher>Asian Institute of Technology</publisher>
    <dateIssued>2008</dateIssued>
    <issuance>continuing</issuance>
  </originInfo>
  <language>
    <languageTerm authority="iso639-2b" type="code">eng</languageTerm>
  </language>
  <physicalDescription>
    <extent>99 p. : ill. + 1 online resource</extent>
  </physicalDescription>
  <abstract>Energy  models  are  widely  accepted  as  a  decision  support  tool.  In  this  study  a  long  term energy system model for Bhutan was developed under the MARKAL model framework.  This  study  basically  highlights  the  future  energy  pathways  under  the  least  cost  energy system configuration and under three non base case scenarios. Under the least cost energy system, it is expected that the dependency on the imported fossil fuel will increase with its share  in  the  primary  energy  supply  rising  from  27% in  2005  to  43%  in  2040.  In  the planning  period,  biomass  is  expected  to  reach  its  maximum  sustainable  yield.  Electricity demand  is  expected  to  grow  at  an  annual  average  rate  of  8.3%.  Implications  of  three simple  alternative  scenarios  were  analyzed.  In  the electric  cooking  scenario  significant reduction  in  biomass  and  kerosene  demand  is  expected  which  subsequently  leads  to reduction in CO2, SO2 and NOx emission levels. In the extreme electric cooking case, total primary energy supply reduces by 14% but the total system cost increases by 1.3%. In the partial  electrification  of  the  transport  system,  when  the  capital  cost  of  battery  electric vehicles  were  reduced  by  25%,  then  electric  vehicles  take  over  the  ICE  vehicles  and subsequently reduces the diesel import by 15% over the base case. However this transition requires  132  MW  of  additional  electricity  demand  by  2040.  The  effect  of  the  combined scenario of electric cooking and electrification of transport system was done. As expected the  impacts  were  greater  compared  to  when  each  policy  were  deployed  separately. Inference  from  the  model  result  under  base  case  and  non  base  cases  shows  that  at  the existing  {u2018}arranged  price{u2019}  the  model  prefers  to  import  electricity  than  to  invest  in  hydro power plants in meeting the increasing electricity demand during the planning period. This  study  can  be  taken as  the  stepping  stone  for  highlighting  the  likely  energy  issues  in the  future.  To  assess  all  possible  future  scenarios  is  beyond  the  scope  of  this  work. Nevertheless this study may be treated as a baseline for detail analysis of other numerous alternative  energy  pathways  and  assess  their  corresponding  impacts  and  subsequent decision  that  may  be  taken.  With  better  and  more  realistic  assumptions  and  refined  data, and involving team work could further improve the model. Energy policy implications can be  studied  at  the  national  level,  sector  level  as  well  as  at  the  end  use  demand  level.  A consistent and constant updating may be very much necessary.</abstract>
  <note>A thesis submitted in partial fulfillment of the requirements for the degree of Master of Engineering in Energy Economics and Planning</note>
  <note>Thesis (M.Eng.) - Asian Institute of Technology, 2008</note>
  <subject authority="lcsh">
    <topic>Energy development</topic>
    <geographic>Bhutan</geographic>
  </subject>
  <subject authority="lcsh">
    <topic>Electricity in transportation</topic>
    <geographic>Bhutan</geographic>
  </subject>
  <relatedItem type="series">
    <titleInfo>
      <title>Thesis ; no. ET-08-27</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=B02195</identifier>
  <location>
    <url displayLabel="Full-Text">http://203.159.5.9/ait-thesis/detail.php?q=B02195</url>
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  <recordInfo>
    <recordCreationDate encoding="marc">100218</recordCreationDate>
    <recordChangeDate encoding="iso8601">20260818134534.0</recordChangeDate>
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