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dc.contributor.advisorIgnacio Pérez-Arriaga and Claudio Vergara.en_US
dc.contributor.authorEllman, Douglas (Douglas Austin)en_US
dc.contributor.otherMassachusetts Institute of Technology. Technology and Policy Program.en_US
dc.date.accessioned2015-09-17T17:42:01Z
dc.date.available2015-09-17T17:42:01Z
dc.date.copyright2015en_US
dc.date.issued2015en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/98551
dc.descriptionThesis: S.M. in Technology and Policy, Massachusetts Institute of Technology, Engineering Systems Division, 2015.en_US
dc.descriptionThis electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.en_US
dc.descriptionCataloged from student-submitted PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (pages 106-109).en_US
dc.description.abstractDespite efforts from governments and other organizations, hundreds of millions of people-primarily in Africa and South Asia-still have no electricity service. Electrification efforts have historically been focused on extension of the main electric grid, but technology developments have made off-grid power systems, such as microgrids and home systems, viable alternatives for some areas. Especially since rural electrification typically depends on limited subsidies, if universal electrification is to be achieved in a timely manner, smart planning is essential to ensure that resources are directed towards cost-efficient technical solutions. Since the areas requiring electrification are expansive, the technology choices are many, and experience with off-grid systems is limited, planners struggle to evaluate tradeoffs between technology choices and estimate project costs. This thesis demonstrates that computer models that can automatically produce cost-efficient designs to the individual customer level can provide significant value to the planning process. The development of such a model by the author and collaborators at MIT and Comillas University, called the Reference Electrification Model (REM), is described. REM uses a series of heuristics to process input data, identify areas better suited for on-grid or off-grid electrification, and produce technical designs for recommended grid-extension and off-grid projects. In addition to the current state of REM, the rationale for model design choices and recommendations for future developments are described. The process and results of a pilot application of REM to Vaishali District, in Bihar, India are also described. REM will only be useful if it is actually incorporated into planning processes. In this spirit, concepts for how models like REM can benefit the regulation of rural electrification are presented, with a focus on India.en_US
dc.description.statementofresponsibilityby Douglas Ellman.en_US
dc.format.extent109 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsM.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectEngineering Systems Division.en_US
dc.subjectTechnology and Policy Program.en_US
dc.titleThe reference electrification model : a computer model for planning rural electricity accessen_US
dc.title.alternativeComputer model for planning rural electricity accessen_US
dc.typeThesisen_US
dc.description.degreeS.M. in Technology and Policyen_US
dc.contributor.departmentMassachusetts Institute of Technology. Engineering Systems Division
dc.identifier.oclc920674644en_US


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