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.