Multi-Objective Electric Vehicle Scheduling Considering Customer and System Objectives

Abstract

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.

Meeting Name

2017 IEEE Manchester PowerTech, Powertech 2017 (2017: Jun. 18-22, Manchester, UK)

Department(s)

Electrical and Computer Engineering

Sponsor(s)

National Science Foundation (U.S.)

Comments

The authors gratefully acknowledge the financial support of the National Science Foundation under the project ECCS1068996

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)

978-1-5090-4238-8

International Standard Serial Number (ISSN)

2472-8152

Document Type

Article - Conference proceedings

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2017 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.

Publication Date

01 Jun 2017

Share

 
COinS