Cost-Constrained Dynamic Optimal Electric Vehicle Charging
Electric vehicles are an integral component of an environmentally sustainable and resilient infrastructure. Successful penetration of electric vehicles requires close coupling between the customers and load serving entities, adaptive energy markets, and technological advancements. In this paper, distribution line over-loading due to vehicle charging has been mitigated using both day-ahead (static) and real-time (dynamic) frameworks, using continuous and discrete charging rates. The proposed solution focuses on valley filling (system perspective) and charging cost reduction (customer perspective). The real-time solution was achieved using a moving horizon optimization technique. In addition to providing charging coordination, the impacts of two different pricing structures were analyzed to ascertain the customer's individual cost optima with respect to the system optima. The results presented strongly indicate that a global pricing structure will not be optimal for all consumers due to their diverse driving habits.
F. Maigha and M. Crow, "Cost-Constrained Dynamic Optimal Electric Vehicle Charging," IEEE Transactions on Sustainable Energy, vol. 8, no. 2, pp. 716 - 724, Institute of Electrical and Electronics Engineers (IEEE), Apr 2017.
The definitive version is available at https://doi.org/10.1109/TSTE.2016.2615865
Electrical and Computer Engineering
Keywords and Phrases
Cost reduction; Costs; Crashworthiness; Electric vehicles; Energy management; Sales; Vehicles; Constrained dynamics; Customer perspectives; Demand response; Electric vehicle charging; Integral components; Load serving entities; Moving horizon optimization; Technological advancement; Charging (batteries); Demand-response; Energy management; Moving horizon optimization
International Standard Serial Number (ISSN)
Article - Journal
© 2017 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
01 Apr 2017