Optimal Battery Energy Storage System Sizing for Demand Charge Management in EV Fast Charging Stations

Conference paper (2021)

Authors

George Koolman Student
M. Stecca DC systems, Energy conversion & Storage - EEMCS
P. Bauer DC systems, Energy conversion & Storage - EEMCS
Research Group
DC systems, Energy conversion & Storage (EEMCS) (TU Delft)
Copyright: © 2021 George Koolman, M. Stecca, P. Bauer
DOI: https://doi.org/10.1109/ITEC51675.2021.9490138
Genetic algorithms NSGA-II Electrical vehicles Battery energy storage systems Demand charge management Fast charging stations Multi-objective optimizations
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Published Date

2021

Language

English

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Faculty

Electrical Engineering, Mathematics and Computer Science

Department

Electrical Sustainable Energy

Research Group

DC systems, Energy conversion & Storage

Abstract

The high pulsating demand of fast charging stations (FCS) may cause monthly demand charges to account for a significant fraction of a station's electric bill. To reduce these costs, demand charge management can be applied to suppress peak power demands at FCSs, also using battery energy storage systems (BESS). This paper proposes a multi-objective approach for the optimal BESS and grid-tie sizing in FCS designs using genetic algorithms. With demand data from a FCS in the Netherlands, numerical studies are conducted in the Mosaik and Pymoo environments to assess the effectiveness of the proposed formulation.