Multi-Objective Optimization for Bidirectional Electric Vehicle Charging Stations

Journal Article (2025)
Author(s)

I. Bara (TU Delft - DC systems, Energy conversion & Storage)

G.R. Mouli (TU Delft - DC systems, Energy conversion & Storage)

P. Bauer (TU Delft - DC systems, Energy conversion & Storage)

Research Group
DC systems, Energy conversion & Storage
DOI related publication
https://doi.org/10.1109/OAJPE.2025.3614816
More Info
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Publication Year
2025
Language
English
Research Group
DC systems, Energy conversion & Storage
Volume number
12
Pages (from-to)
652-663
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Abstract

The increasing number of electric vehicles (EVs) means both a challenge and an opportunity for the electric grid. Different charging algorithms have been proposed in the literature to tackle these specific challenges and make use of the potential services that EVs can provide. However, to properly investigate the conflicting objectives, a multi-objective approach is paramount. These algorithms provide a family of solutions instead of just one, so the decision-maker can see the connection and trade-offs between the objectives. This paper proposes a highly customisable multi-objective framework based on an expanded version of the augmented $\varepsilon $ -constraint 2 method. Together with a mixed integer linear programming (MILP) formulation, it is used to solve a charging station scheduling problem. An energy management system (EMS) executes the calculated schedules to show the effect on the individual EVs. Numerical simulations based on market and EV data from the Netherlands demonstrate the adaptability and effectiveness of the proposed algorithm.