Show simple item record

dc.contributor.advisorGeorgia Perakis, James Kirtley and Konstantin Turitsyn.en_US
dc.contributor.authorYuan, Sandy (Sandy Roan-Jane)en_US
dc.contributor.otherLeaders for Global Operations Program.en_US
dc.date.accessioned2017-09-15T15:38:07Z
dc.date.available2017-09-15T15:38:07Z
dc.date.issued2017en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/111527
dc.descriptionThesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, in conjunction with the Leaders for Global Operations Program at MIT, 2017.en_US
dc.descriptionThesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, in conjunction with the Leaders for Global Operations Program at MIT, 2017.en_US
dc.description"June 2017." Cataloged from PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (pages 61-62).en_US
dc.description.abstractA need exists for systematic evaluation methods of battery storage sizing as an electric utility asset investment. Atlantic Electric, like many US utilities, has begun to consider battery energy storage systems for multiple applications, and will likely continue to evaluate potential investments in energy storage in the future. This thesis develops and evaluates three sizing methodologies for battery energy storage systems for a reliability application at an electric distribution substation. The methods are applied to three substation locations using real historical load data to understand the required supplemental capacity provided by on-site battery storage energy systems in situations of peak demand coinciding with N-1 contingency. The study also includes analysis of business processes for asset planning and recommendations. The results of the analysis indicate that deterministic conservative sizing methods, when compared to a probabilistic historical risk-based method, yield battery size that is significantly larger. The most conservative battery size, which would cover the most extreme capacity needs, is approximately twice the size of the risk-based battery size, which would cover approximately 80% of capacity need events. Going forward, the methodologies from this thesis can be developed further for evaluating battery storage systems for reliability applications among diverse conditions and use cases. Furthermore, integrating multiple use cases and potential value streams for battery storage systems in utility operations will involve cross-functional and comprehensive processes for evaluation in the future.en_US
dc.description.statementofresponsibilityby Sandy Yuan.en_US
dc.format.extent62 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsMIT 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.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectSloan School of Management.en_US
dc.subjectMechanical Engineering.en_US
dc.subjectLeaders for Global Operations Program.en_US
dc.titleBattery storage system sizing evaluation for utility distribution asset investment deferralen_US
dc.typeThesisen_US
dc.description.degreeM.B.A.en_US
dc.description.degreeS.M.en_US
dc.contributor.departmentLeaders for Global Operations Program at MITen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Mechanical Engineering
dc.contributor.departmentSloan School of Management
dc.identifier.oclc1003324384en_US


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record