The Local Reference Electrification Model : comprehensive decision-making tool for the design of rural microgrids

Current estimates indicate that an alarming 1 billion existing people still lack access to electricity around the world. Technological advancements have pushed off-grid solutions into the limelight as possible alternatives to the traditional method of electrification via extension of the centralized grid. When grid reliability is poor, the community is remote, or when the arrival of the grid is undetermined, off-grid systems may be suitable substitutes for traditional grid extension efforts. Nonetheless, severe resource constraints, the scale of planning, and the choice between electrification modes create a complicated environment under which planners in the developing world must devise electrification plans and relevant policies. This thesis demonstrates how computational tools can provide value to rural electrification planning. The Reference Electrification Model (REM) assists planners by identifying optimal regions for grid extension projects and off-grid solutions, along with technical design and associated financial metrics. In particular, this thesis focuses on the discussion of the Local Reference Electrification Model (LREM), an adaption of REM to localized electrification design. LREM is a comprehensive, decision-making tool that produces detailed generation and network designs for a singular microgrid system. It contributes to the electrification effort by providing the quantitative basis with which to explore financial, technical, and performance implications of various factors in microgrid design. In doing so, LREM improves the microgrid designs relied upon by REM in its regional planning decisions. This research emphasizes the ability for computational tools such as REM and LREM to assist in developing viable policies and regulations, as well as feasible designs and plans to accelerate electricity access globally.

Department dc:contributor.department

Massachusetts Institute of Technology. Engineering Systems Division

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2016

Author dc:creator

• Li, Vivian, S.M. Massachusetts Institute of Technology

Advisor dc:contributor.advisor

• Jose Ignacio Pérez-Arriaga and Claudio Vergara.

• Institute for Data, Systems, and Society.
• Engineering Systems Division.
• Technology and Policy Program.

Statement dc:rights

• M.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.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/104828

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/104828