Receding horizon optimization for distributed control of electric vehicle charging stations

Anna Malkova, Jan Martin Zepter, Mattia Marinelli, Herbert Amezquita, Hugo Morais

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

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Abstract

With the continuous increase of electric vehicle (EV) adoption, deploying smart charging techniques offer a practical solution to mitigate the impact of grid overloading caused by simultaneous EV charging. At the same time, smart charging can help to stabilize the fluctuations in the production from local renewable energy sources (RES). This article introduces a receding horizon optimization model for the distributed control of EV chargers at charging stations, focusing on maximizing the profit of the charging station, while enhancing the utilization of local PV generation. The proposed model operates in 5-minute intervals, determining the power reference for the EV cluster at the charging station. Results demonstrate that the proposed model effectively lowers electricity cost for charging stations, while ensuring more than 90% energy delivery for charging EVs. Future research will be focused on integrating wind energy and refining the model in controlled lab tests for practical implementation and validation.
Original languageEnglish
Title of host publicationProceedings of 2024 IEEE PES Innovative Smart Grid Technologies Europe (ISGT EUROPE)
Number of pages5
PublisherIEEE
Publication date2025
ISBN (Electronic)979-8-3503-9042-1
DOIs
Publication statusPublished - 2025
EventIEEE PES Innovative Smart Grid Technologies Europe 2024 - Dubrovnik, Croatia
Duration: 14 Oct 202417 Oct 2024

Conference

ConferenceIEEE PES Innovative Smart Grid Technologies Europe 2024
Country/TerritoryCroatia
CityDubrovnik
Period14/10/202417/10/2024

Keywords

  • Electric vehicles
  • Receding horizon
  • Distributed control
  • EV charging station

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