Mentor Program: Communication, Control and Optimization for Extreme Fast Charging Stations

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Systems & Control Engineering".

Deadline for manuscript submissions: closed (25 October 2023) | Viewed by 3565

Special Issue Editors


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Guest Editor
Division of Energy, Matter and Systems, University of Missouri Kansas City, Kansas City, MO 64110, USA
Interests: distribution system planning and operation; electric vehicle grid integration; metaheuristic optimization techniques; microgrid control and management; cybersecurity issues; convex relaxations; machine learning applications
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Guest Editor
1. Department of Engineering Technology, University of Houston, Houston, TX 77004, USA
2. Department of Electrical and Computer Engineering, University of Houston, Houston, TX 77004, USA
Interests: distributed energy resources; electric vehicle charging; microgrid stability; power quality issues; power converters for distributed energy sources; wireless power transfer
Special Issues, Collections and Topics in MDPI journals
Division of Energy, Matter and Systems, University of Missouri Kansas City, Kansas City, MO 64110, USA
Interests: electric utility smart grid communications; sensor networks for home energy savings; scheduling and service prioritization for wireless systems; ultra-reliable low latency cellular communication

Special Issue Information

Dear Colleagues,

The push towards the goal of net-zero emissions coupled with the rise in fuel costs has led to the rapid proliferation of electric vehicles. Although EV ownership has been increasing significantly, the transportation market is still dominated by internal-combustion-engine-based vehicles. One of the major impediments to the adoption of EVs is the range anxiety issue among customers, which stems from the lack of fast-charging infrastructure. The industry and academia have been doing notable work in this area lately. However, significant gaps remain in terms of research and development of megawatt-level charging stations. This Special Issue aims to bring together a collection of research articles on the architecture, control, and management of extreme fast-charging facilities. Within the scope of the extreme fast-charging infrastructure, the topics of interest include, but are not limited to, the following:

  • Optimal planning of fast-charging infrastructure;
  • Novel power converter topologies for fast charging stations;
  • Techno-economic analysis for charging station infrastructure;
  • Vehicle-to-grid (V2G) and vehicle-to-building applications;
  • Grid impacts of megawatt-level charging infrastructure;
  • Intelligent charging techniques to mitigate the adverse impacts of EV charging;
  • Energy management within the charging stations;
  • Communication for charging station infrastructure;
  • Cybersecurity issues for EV grid integration.

Dr. Preetham Goli
Prof. Dr. Wajiha Shireen
Dr. Cory Beard
Guest Editors

This program intends to provide an opportunity for early career scientists to enhance their editing, networking, and organizational skills and to work closely with our journal to gain more editorial experience. Early career scientists who have novel ideas for new Special Issues of Electronics (ISSN: 2079-9292) will act as Guest Editors under the mentorship of an experienced scientist; this mentor could be a member of the Electronics Editorial Board or may be from other well-established research institutes or laboratories, etc.

Certificates and awards:

When the Special Issue is closed, the Editorial Office will provide official certificates for all of the mentors. The young scholars involved in the program will be prioritized as candidates for Electronics Young Investigator Awards in the future.

If you are interested in this opportunity, please send your Special Issue proposal to the Electronics Editorial Office ( or ), and we will discuss the process (mentor collaboration, Special Issue topic feasibility analysis, etc.) in further detail.

Manuscript Submission Information

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Keywords

  • electric vehicle (EV) grid integration
  • power converter topologies
  • communication for EV charging
  • cybersecurity for EV grid integration
  • placement and sizing of fast EV charging infrastructure
  • vehicle-to-grid and vehicle-to-building
  • smart charging techniques
  • controller design for charging stations
  • techno-economic analysis

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Published Papers (2 papers)

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Research

18 pages, 10557 KiB  
Article
Simulation of an Ultrafast Charging Station Operating in Steady State
by Alexandra Blanch-Fortuna, David Zambrano-Prada, Martín Gállego-Casals and Luis Martinez-Salamero
Electronics 2023, 12(23), 4811; https://doi.org/10.3390/electronics12234811 - 28 Nov 2023
Cited by 3 | Viewed by 1439
Abstract
This report presents the analysis, study, and simulation of an ultrafast charging station (UFCS) for electric vehicles (EVs) operating in steady state. The electrical architecture of the charging station uses an ac bus plus two dc buses and it is supported by a [...] Read more.
This report presents the analysis, study, and simulation of an ultrafast charging station (UFCS) for electric vehicles (EVs) operating in steady state. The electrical architecture of the charging station uses an ac bus plus two dc buses and it is supported by a storage system based on batteries and super-capacitors. The power demand of the EVs is established taking into account the electric characteristics of their batteries and the availability of the station charging points. The analysis introduces a supervisory control based on a state machine description for different operating modes, which eventually facilitates fault detection in the electrical architecture. In addition, the study proposes different methods to handle the required energy for the charging demand and a procedure for the correct sizing of both the energy storage system and the input transformer. In laboratory experiments in a reduced-scale storage system, a SCADA supervision with CAN communication has proved successful in gathering data corresponding to modes of charge and discharge in batteries and super-capacitors, and subsequently displaying them on a computer screen. Full article
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16 pages, 3103 KiB  
Article
A Novel Levy-Enhanced Opposition-Based Gradient-Based Optimizer (LE-OB-GBO) for Charging Station Placement
by Sanket Raval, Thangadurai Natarajan and Sanchari Deb
Electronics 2023, 12(7), 1522; https://doi.org/10.3390/electronics12071522 - 23 Mar 2023
Cited by 5 | Viewed by 1306
Abstract
Transportation modes are shifting toward electric vehicles from conventional internal combustion engines to reduce pollution and dependency on conventional fuels. This reduces the fuel cost, while charging stations must be distributed across the locations to minimize range anxiety. Installing charging stations randomly across [...] Read more.
Transportation modes are shifting toward electric vehicles from conventional internal combustion engines to reduce pollution and dependency on conventional fuels. This reduces the fuel cost, while charging stations must be distributed across the locations to minimize range anxiety. Installing charging stations randomly across the distribution system can lead to violation of active power loss, voltage deviation, and reliability parameters of the power system. The problem of the optimal location of charging stations is a nonlinear optimization problem that includes the parameters of the distribution system and road network with their respective constraints. This work proposes a new metaheuristic optimization algorithm, a levy-enhanced opposition-based gradient-based optimizer (LE-OB-GBO), to solve the charging station placement problem. It has a balance between exploration and exploitation and fast convergence rate. The performance of the proposed algorithm was evaluated by solving CEC 2017 benchmark functions and charging station problem. The performance of the proposed algorithm was also compared with that of other state-of-the-art optimization algorithms and was found to outperform 17 out of 29 CEC 2017 functions. Statistical analysis of the charging station placement problem indicates the lowest mean values of 1.4912, 1.4783, and 1.5217 for LE-OB-GBO for considered cases 1 to 3, respectively, thus proving the efficacy of the proposed algorithm. Full article
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