Receding horizon optimization for distributed control of electric vehicle charging stations

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.

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Publication Details

Published
2024-10-14
DOI
https://doi.org/10.1109/isgteurope62998.2024.10863250
Citations
1
Primary Topic
Electric Vehicles and Infrastructure
Type
article
Field-Weighted Citation Impact
0.21

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article

Receding horizon optimization for distributed control of electric vehicle charging stations

Jan Martin Zepter, Herbert Amezquita, Mattia Marinelli, Hugo Morais et al.
1 citations
Electric Vehicles and Infrastructure
0.21
article

Receding horizon optimization for distributed control of electric vehicle charging stations

Jan Martin Zepter, Herbert Amezquita, Mattia Marinelli, Hugo Morais, А. В. Малкова
article en
1 citations

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.

Instituto de Engenharia de Sistemas e Computadores Investigação e Desenvolvimento (PT), University of Lisbon (PT), Technical University of Denmark (DK)
HORIZON EUROPE Framework Programme
Affordable and clean energy
Openalex Percentile: Top 44%
Electric Vehicles and Infrastructure
0.21
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