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Jose Ignacio Pérez-Arriaga. Barbar, Marc(Marc F.) Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science. Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science 2019-11-04T20:22:31Z 2019-11-04T20:22:31Z 2019 2019 https://hdl.handle.net/1721.1/122752 1124855462 Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2019 Cataloged from PDF version of thesis. Includes bibliographical references (pages 101-102). The recent spike in the frequency of hurricanes in Central America has severely damaged the conventional electrical grid. Notably, the government of Puerto Rico laid out a plan to reinvent its energy sector to improve its level of resiliency against natural disasters. Better planning and preparation can minimize the damage that needs to be repaired on time. For instance, when necessary facilities, such as hospitals, lose access to electricity, the ability to manage a displaced population after a hurricane is diminished. Computational planning tools allow policymakers and planners to take reliability metrics, resource constraints, interactions between off-grid and traditional grid-extension projects into account when designing contingency plans for the electric grid. The goal of this thesis is to explore the role of a hybrid decentralized structure of the electrical grid to improve the level of reliability through extraordinary circumstances. In this thesis, I develop algorithms that are shown via several case studies. Given the proper input data, these algorithms can provide insight into the technical feasibility of where to deploy microgrids given the existing infrastructure. This research emphasizes the need for granular spatial data at the distribution level to make better planning decisions. by Marc Barbar. S.M. S.M. Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science 102 pages eng Massachusetts Institute of Technology MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission. http://dspace.mit.edu/handle/1721.1/7582 Electrical Engineering and Computer Science. Resiliency and reliability planning of the electric grid in natural disaster affected areas Thesis application/pdf 2019-11-04T20:22:30Z Publication Master EECS unknown unknown <Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="299c43d0-fd4c-4332-942c-9684f1fd732f"> <Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type> <Language>eng</Language> <Title>Resiliency and reliability planning of the electric grid in natural disaster affected areas</Title> <PublishedIn> <Publication> </Publication> </PublishedIn> <PublicationDate>2019</PublicationDate> <Authors> <Author> <DisplayName>Barbar, Marc(Marc F.)</DisplayName> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> </Authors> <Editors> </Editors> <Publishers> <Publisher> <DisplayName>Massachusetts Institute of Technology</DisplayName> <OrgUnit /> </Publisher> </Publishers> <License>http://dspace.mit.edu/handle/1721.1/7582</License> <Keyword>Electrical Engineering and Computer Science.</Keyword> <Abstract>The recent spike in the frequency of hurricanes in Central America has severely damaged the conventional electrical grid. Notably, the government of Puerto Rico laid out a plan to reinvent its energy sector to improve its level of resiliency against natural disasters. Better planning and preparation can minimize the damage that needs to be repaired on time. For instance, when necessary facilities, such as hospitals, lose access to electricity, the ability to manage a displaced population after a hurricane is diminished. Computational planning tools allow policymakers and planners to take reliability metrics, resource constraints, interactions between off-grid and traditional grid-extension projects into account when designing contingency plans for the electric grid. The goal of this thesis is to explore the role of a hybrid decentralized structure of the electrical grid to improve the level of reliability through extraordinary circumstances. In this thesis, I develop algorithms that are shown via several case studies. Given the proper input data, these algorithms can provide insight into the technical feasibility of where to deploy microgrids given the existing infrastructure. This research emphasizes the need for granular spatial data at the distribution level to make better planning decisions.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication>