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

George Koolman, Marco Stecca, Pavol Bauer

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

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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.
Original languageEnglish
Title of host publication2021 IEEE Transportation Electrification Conference & Expo (ITEC)
Subtitle of host publicationProceedings
PublisherIEEE
Pages588-594
Number of pages7
ISBN (Electronic)978-1-7281-7583-6
ISBN (Print)978-1-7281-7584-3
DOIs
Publication statusPublished - 2021
Event2021 IEEE Transportation Electrification Conference & Expo (ITEC) - Virtual at Chicago, United States
Duration: 21 Jun 202125 Jun 2021

Conference

Conference2021 IEEE Transportation Electrification Conference & Expo (ITEC)
CountryUnited States
CityVirtual at Chicago
Period21/06/2125/06/21

Bibliographical note

Accepted author manuscript

Keywords

  • Battery energy storage systems
  • Demand charge management
  • Electrical vehicles
  • Fast charging stations
  • Genetic algorithms
  • Multi-objective optimizations
  • NSGA-II

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