Doctoral Dissertations
Abstract
"Electric vehicles provide a two pronged solution to the problems faced by the electricity and transportation sectors. They provide a green, highly efficient alternative to the internal combustion engine vehicles, thus reducing our dependence on fossil fuels. Secondly, they bear the potential of supporting the grid as energy storage devices while incentivizing the customers through their participation in energy markets. Despite these advantages, widespread adoption of electric vehicles faces socio-technical and economic bottleneck. This dissertation seeks to provide solutions that balance system and customer objectives under present technological capabilities. The research uses electric vehicles as controllable loads and resources. The idea is to provide the customers with required tools to make an informed decision while considering the system conditions.
First, a genetic algorithm based optimal charging strategy to reduce the impact of aggregated electric vehicle load has been presented. A Monte Carlo based solution strategy studies change in the solution under different objective functions. This day-ahead scheduling is then extended to real-time coordination using a moving-horizon approach. Further, battery degradation costs have been explored with vehicle-to-grid implementations, thus accounting for customer net-revenue and vehicle utility for grid support. A Pareto front, thus obtained, provides the nexus between customer and system desired operating points. Finally, we propose a transactive business model for a smart airport parking facility. This model identifies various revenue streams and satisfaction indices that benefit the parking lot owner and the customer, thus adding value to the electric vehicle"--Abstract, page iv.
Advisor(s)
Crow, Mariesa
Committee Member(s)
Ferdowsi, Mehdi
Kimball, Jonathan W.
Joo, Jhi-Young
Long, Suzanna, 1961-
Department(s)
Electrical and Computer Engineering
Degree Name
Ph. D. in Electrical Engineering
Publisher
Missouri University of Science and Technology
Publication Date
Summer 2017
Journal article titles appearing in thesis/dissertation
- Economic scheduling of residential plug-in (hybrid) electric vehicle (PHEV) charging
- Cost-constrained dynamic optimal electric vehicle charging
- Electric vehicle scheduling considering co-optimized customer and system objectives
- A transactive operating model for smart airport parking lots
Pagination
xiii, 114 pages
Note about bibliography
Includes bibliographic references.
Rights
© 2017 Maigha, All rights reserved.
Document Type
Dissertation - Open Access
File Type
text
Language
English
Thesis Number
T 11176
Electronic OCLC #
1003043355
Recommended Citation
Maigha, "Optimal electric vehicle scheduling : A co-optimized system and customer perspective" (2017). Doctoral Dissertations. 2586.
https://scholarsmine.mst.edu/doctoral_dissertations/2586