Real-Time Charging Scheduling and Optimization of Electric Buses in a Depot

Boud Verbrugge; Abdul Mannan Rauf; Haaris Rasool; Mohamed  Abdel-Monem; Thomas Geury; Mohamed El Baghdadi; Omar Hegazy

doi:10.3390/en15145023

Real-Time Charging Scheduling and Optimization of Electric Buses in a Depot

Boud Verbrugge, Abdul Mannan Rauf, Haaris Rasool, Mohamed Abdel-Monem, Thomas Geury, Mohamed El Baghdadi, Omar Hegazy

Research output: Contribution to journal › Article › peer-review

9 Citations (Scopus)

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Abstract

To improve the air quality in urban areas, diesel buses are getting replaced by battery electric buses (BEBs). This conversion introduces several challenges, such as the proper control of the charging process and a reduction in the operational costs, which can be addressed by introducing smart charging concepts for BEB fleets. Therefore, this paper proposes a real-time scheduling and optimization (RTSO) algorithm for the charging of multiple BEBs in a depot. The algorithm assigns a variable charging current to the different time slots the charging process of each BEB is divided to provide an optimal charging schedule that minimizes the charging cost, while satisfying the power limitations of the distribution network and maintaining the operation schedule of the BEBs. A genetic algorithm is used to solve the formulated cost function in real time. Several charging scenarios are tested in simulation, which show that a reduction in the charging cost up to 10% can be obtained under a dynamic electricity price scheme. Furthermore, the RTSO is implemented in a high-level charging management system, a new feature required to enable smart charging in practice, to test the developed algorithm with existing charging infrastructure. The experimental validation of the RTSO algorithm has proven the proper operation of the entire system.

Original language	English
Article number	5023
Pages (from-to)	1-18
Number of pages	18
Journal	Energies
Volume	15
Issue number	14
DOIs	https://doi.org/10.3390/en15145023
Publication status	Published - 9 Jul 2022

Bibliographical note

Funding Information:
This research was supported by the project HiEFFICIENT. This project has received funding from the ESCEL joint undertaking (JU) under grant agreement no. 101007281. The ESCEL JU receives support from the European Union’s Horizon 2020 research and innovation programme and Austria, Germany, Slovenia, Netherlands, Belgium, Slovakia, France, Italy and Turkey.

Publisher Copyright:
© 2022 by the authors.

Copyright:
Copyright 2022 Elsevier B.V., All rights reserved.

Keywords

electric buses
depot charging
charging scheduling
real-time optimization
cost analysis

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10.3390/en15145023Licence: CC BY

Real-time Scheduling and Optimization of Electric Buses in a DepotFinal published version, 3.58 MBLicence: CC BY

Cite this

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title = "Real-Time Charging Scheduling and Optimization of Electric Buses in a Depot",

abstract = "To improve the air quality in urban areas, diesel buses are getting replaced by battery electric buses (BEBs). This conversion introduces several challenges, such as the proper control of the charging process and a reduction in the operational costs, which can be addressed by introducing smart charging concepts for BEB fleets. Therefore, this paper proposes a real-time scheduling and optimization (RTSO) algorithm for the charging of multiple BEBs in a depot. The algorithm assigns a variable charging current to the different time slots the charging process of each BEB is divided to provide an optimal charging schedule that minimizes the charging cost, while satisfying the power limitations of the distribution network and maintaining the operation schedule of the BEBs. A genetic algorithm is used to solve the formulated cost function in real time. Several charging scenarios are tested in simulation, which show that a reduction in the charging cost up to 10% can be obtained under a dynamic electricity price scheme. Furthermore, the RTSO is implemented in a high-level charging management system, a new feature required to enable smart charging in practice, to test the developed algorithm with existing charging infrastructure. The experimental validation of the RTSO algorithm has proven the proper operation of the entire system.",

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note = "Funding Information: This research was supported by the project HiEFFICIENT. This project has received funding from the ESCEL joint undertaking (JU) under grant agreement no. 101007281. The ESCEL JU receives support from the European Union{\textquoteright}s Horizon 2020 research and innovation programme and Austria, Germany, Slovenia, Netherlands, Belgium, Slovakia, France, Italy and Turkey. Publisher Copyright: {\textcopyright} 2022 by the authors. Copyright: Copyright 2022 Elsevier B.V., All rights reserved.",

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AU - El Baghdadi, Mohamed

AU - Hegazy, Omar

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N2 - To improve the air quality in urban areas, diesel buses are getting replaced by battery electric buses (BEBs). This conversion introduces several challenges, such as the proper control of the charging process and a reduction in the operational costs, which can be addressed by introducing smart charging concepts for BEB fleets. Therefore, this paper proposes a real-time scheduling and optimization (RTSO) algorithm for the charging of multiple BEBs in a depot. The algorithm assigns a variable charging current to the different time slots the charging process of each BEB is divided to provide an optimal charging schedule that minimizes the charging cost, while satisfying the power limitations of the distribution network and maintaining the operation schedule of the BEBs. A genetic algorithm is used to solve the formulated cost function in real time. Several charging scenarios are tested in simulation, which show that a reduction in the charging cost up to 10% can be obtained under a dynamic electricity price scheme. Furthermore, the RTSO is implemented in a high-level charging management system, a new feature required to enable smart charging in practice, to test the developed algorithm with existing charging infrastructure. The experimental validation of the RTSO algorithm has proven the proper operation of the entire system.

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Real-Time Charging Scheduling and Optimization of Electric Buses in a Depot

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