Multi-Objective Electric Vehicle Scheduling Considering Customer and System Objectives
Electric vehicle (EV) scheduling is a multi-objective optimization problem with conflicting system and customer interests. They bear the potential to support the grid while providing incentives to the customers through energy transactions, demand response and grid support. Vehicle-to-grid operations provide the customer with attractive avenues for earning revenues but degrade the battery life. Efficient and economical solutions require a balance between customer incurred costs, battery degradation costs and system health. In this paper, the relationships between these objectives have been explored using a multi-objective optimization technique called augmented epsilon-constraint method (AUGMECON). The Pareto optimal solutions will provide day-ahead strategies for coordinating electric vehicles which can then be used for selecting mutually beneficial outcomes.
F. Maigha and M. Crow, "Multi-Objective Electric Vehicle Scheduling Considering Customer and System Objectives," Proceedings of 2017 IEEE Manchester PowerTech (2017, Manchester, UK), Institute of Electrical and Electronics Engineers (IEEE), Jun 2017.
The definitive version is available at https://doi.org/10.1109/PTC.2017.7981275
2017 IEEE Manchester PowerTech, Powertech 2017 (2017: Jun. 18-22, Manchester, UK)
Electrical and Computer Engineering
National Science Foundation (U.S.)
Keywords and Phrases
Charging (batteries); Electric batteries; Electric vehicles; Optimization; Pareto principle; Sales; Scheduling; Secondary batteries; Vehicles; Battery degradation; Demand response; Epsilon-constraint method; Multi-objective optimization problem; Multi-objective optimization techniques; Pareto optimal solutions; Vehicle scheduling; Vehicle to grids; Multiobjective optimization; Vehicle-to-grid
International Standard Book Number (ISBN)
International Standard Serial Number (ISSN)
Article - Conference proceedings
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