Using Electric Vehicles for Grid Services: Capacity Available and Applications for Electric Utility Commercialization

As electric vehicle (EV) ownership increases, utilities face a high strain on electricity demand when vehicles charge at peak hours. EV grid services like managed charging (V1G) and bidirectional charging could enable electric vehicles' untapped energy storage capacity to improve grid resiliency. This thesis pertains to a detailed case study of EVs for grid services. Using Florida Power and Light residential charging data, the thesis lays out a method to estimate V1G and vehicle-to-grid (V2G) capacity and finds that EV grid services are most readily available in the early morning and evening. An aggregation algorithm designed for demand response is outlined to coordinate the discharge of vehicles during a dispatch event to meet an operator-defined target load reduction, and the resulting performance is highlighted. A V1G algorithm for residential chargers is proposed and highlighted as an opportunity to increase customer participation in offering their vehicle for grid services. A strategy is introduced to build off the concepts presented to create a simulation for utility planning for EV grid services. The thesis concludes with a road map of adoption for EV grid services and potential commercialization opportunities. Key risks and technical challenges are highlighted, and final recommendations for utilities are provided.

Name thesis:degree_name

Master

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Mechanical Engineering

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2022

Author dc:creator

• Castillo Jr., Gustavo

Advisors dc:contributor.advisor

• Freund, Daniel
• Annaswamy, Anuradha

Statement dc:rights

• In Copyright - Educational Use Permitted
• Copyright retained by author(s)

Licence dc:rights.uri

• https://rightsstatements.org/page/InC-EDU/1.0/

Handle dc:identifier.uri

https://hdl.handle.net/1721.1/146643

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/146643