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Developments in Electric Vehicle Charging Station Infrastructure

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "E: Electric Vehicles".

Deadline for manuscript submissions: closed (25 February 2022) | Viewed by 5581

Special Issue Editors

Department of Electrical Engineering, University of Cape Town, Cape Town 7701, South Africa
Interests: renewable energy systems; distributed generation; power system protection; microgrids; smart grids; EV storage systems; EV charging station infrastructure
Special Issues, Collections and Topics in MDPI journals
Department of Electrical Engineering, Tshwane University of Technology (TUT), Pretoria, South Africa
Interests: renewable energy; active distribution networks; automotive vehicle energy storage systems; microgrids; smart grids; energy efficiency; IoT and energy management systems; EV charging systems

Special Issue Information

Dear Colleagues,

The Guest Editors are inviting submissions to a Special Issue of Energies on the subject area of “Developments in Electric Vehicle Charging Station (EVCS) Infrastructure and Present Scenarios”. Electric vehicles (EV) are becoming important agents of reducing carbon footprints and environmental pollution across the globe. However, electric vehicles have been suffering from two major bottlenecks, namely poor range and limited attractiveness. Nevertheless, the current bottleneck for the take-up of EV adoption is the lack of sufficient feasible charging facilities. EV penetration leads to huge energy demand on distribution networks and also needs different modes of access to charging points such as the home, workplace, and/or public charging. Thus, take-up of electric vehicles and customer preference for these vehicles are highly dependent on proper infrastructure development for electric vehicle charging stations.

Key issues that need extensive exploration and research for charging station infrastructure development are as outlined below:

  • Global and country-specific technical challenges for developing EVCS infrastructure;
  • Impact of EVCS integration on distribution network operation, load characteristics, and consumption pattern at distribution level;
  • Management of EVCS energy demand to ensure adherence to power quality guidelines with minimum losses and total harmonic distortion;
  • Application of intelligent methods, IoT, and smart technology to manage the operation of EVCS;
  • Impact of EVCS integration on protection systems and asset management and upgrades in an existing power grid;
  • Planning of EVCS deployment taking into account the stochastic nature of traffic network in a region;
  • Technological innovation and upgrades for EVCS infrastructure to keep up with the technological advancements in an EV, e.g., EV battery and automobile mechanism or with growth of the EV customer base in developing and developed countries.

Extensive research is being carried out for charging station technology development, placement, real-time energy management, and fault diagnostics so that they operate smoothly to meet the needs of existing traffic networks and usage. Research is also taking place to explore the impact of charging station integration into national grids on power grid operation and protection, power quality, energy consumption profile, and grid assets. The application of renewable energy systems and energy storage, artificial intelligence (AI), big data analysis and data-driven management strategies, smart metering and communication technologies, and the Internet of Things (IoT) are also suitable topics on which power and energy researchers are finding ever-increasing interest for a deeper exploration of proper applications to EV charging station infrastructure development, placement, and management.

This Special Issue will deal with cutting-edge developments in electric vehicle charging station infrastructure to alleviate current challenges. Topics of interest for this publication include but are not limited to:

  • Challenges and opportunities for EVCS development and deployment;
  • Applications of AI-based intelligent systems in EVCS developments;
  • EVCS impacts on electric distribution and transmission systems;
  • Renewable energy system applications in EVCS developments;
  • Hybrid renewable energy power plants for EVCS;
  • Automotive energy storage and supply systems;
  • Smart grid for vehicle-to-grid infrastructure;
  • EV adoption and big energy demand;
  • Smart metering and communication;
  • IoT in EVCS energy management;
  • Power electronics and controls;
  • Power quality and protection;
  • Energy management systems;
  • Demand side management;
  • Energy storage systems;
  • EVCS load modeling;
  • Charger penetration;
  • Wireless charging;
  • EVCS placements;
  • DC fast charging;
  • Voltage stability;
  • Cyber security;
  • Data analytics;
  • AC charging.

Dr. Sunetra Chowdhury
Prof. Dr. SP Daniel Chowdhury
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • EV adoption
  • EV penetration
  • AC charging
  • DC charging
  • Wireless charging
  • Fast charging
  • Placement
  • Cybersecurity
  • Big demand
  • V2G
  • Smart grid
  • Smart metering
  • Voltage stability
  • Power quality
  • Renewable energy
  • Deployment
  • Development
  • Charger penetration
  • Cyber security
  • Demand-side management
  • Load modeling
  • Hybrid power
  • Backup power
  • Automotive storage
  • Driving range

Published Papers (2 papers)

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Research

18 pages, 5113 KiB  
Article
Prediction of Charging Demand of Electric City Buses of Helsinki, Finland by Random Forest
Energies 2022, 15(10), 3679; https://doi.org/10.3390/en15103679 - 17 May 2022
Cited by 7 | Viewed by 1578
Abstract
Climate change, global warming, pollution, and energy crisis are the major growing concerns of this era, which have initiated the electrification of transport. The electrification of roadway transport has the potential to drastically reduce pollution and the growing demand for energy and to [...] Read more.
Climate change, global warming, pollution, and energy crisis are the major growing concerns of this era, which have initiated the electrification of transport. The electrification of roadway transport has the potential to drastically reduce pollution and the growing demand for energy and to increase the load demand of the power grid, thereby giving a rise to technological and commercial challenges. Thus, charging load prediction is a crucial and demanding issue for maintaining the security and stability of power systems. During recent years, random forest has gained a lot of popularity as a powerful machine learning technique for classification as well as regression analysis. This work develops a random forest (RF)-based approach for predicting charging demand. The proposed method is validated for the prediction of public e-bus charging demand in the city of Helsinki, Finland. The simulation results demonstrate the effectiveness of our scheme. Full article
(This article belongs to the Special Issue Developments in Electric Vehicle Charging Station Infrastructure)
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26 pages, 1527 KiB  
Article
Minimum-Cost Fast-Charging Infrastructure Planning for Electric Vehicles along the Austrian High-Level Road Network
Energies 2022, 15(6), 2147; https://doi.org/10.3390/en15062147 - 15 Mar 2022
Cited by 9 | Viewed by 2557
Abstract
Given the ongoing transformation of the transport sector toward electrification, expansion of the current charging infrastructure is essential to meet future charging demands. The lack of fast-charging infrastructure along highways and motorways is a particular obstacle for long-distance travel with battery electric vehicles [...] Read more.
Given the ongoing transformation of the transport sector toward electrification, expansion of the current charging infrastructure is essential to meet future charging demands. The lack of fast-charging infrastructure along highways and motorways is a particular obstacle for long-distance travel with battery electric vehicles (BEVs). In this context, we propose a charging infrastructure allocation model that allocates and sizes fast-charging stations along high-level road networks while minimizing the costs for infrastructure investment. The modeling framework is applied to the Austrian highway and motorway network, and the needed expansion of the current fast-charging infrastructure in place is modeled under different future scenarios for 2030. Within these, the share of BEVs in the car fleet, developments in BEV technology and road traffic load changing in the face of future modal shift effects are altered. In particular, we analyze the change in the requirements for fast-charging infrastructure in response to enhanced driving range and growing BEV fleets. The results indicate that improvements in the driving range of BEVs will have limited impact and hardly affect future costs of the expansion of the fast-charging infrastructure. On the contrary, the improvements in the charging power of BEVs have the potential to reduce future infrastructure costs. Full article
(This article belongs to the Special Issue Developments in Electric Vehicle Charging Station Infrastructure)
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