Battery storage system sizing evaluation for utility distribution asset investment deferral

A 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.

Department dc:contributor.department

Leaders for Global Operations Program at MIT

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2017

Author dc:creator

• Yuan, Sandy (Sandy Roan-Jane)

Advisor dc:contributor.advisor

• Georgia Perakis, James Kirtley and Konstantin Turitsyn.

• Sloan School of Management.
• Mechanical Engineering.
• Leaders for Global Operations Program.

Statement dc:rights

• 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.

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/1721.1/111527

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/111527