Electric Vehicles in Smart Grids

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Electrical and Autonomous Vehicles".

Deadline for manuscript submissions: closed (30 April 2020) | Viewed by 41005

Special Issue Editors


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Guest Editor
Algoritmi Research Centre, Department of Industrial Electronics, University of Minho, 4800-058 Guimarães, Portugal
Interests: power electronics converters; electric mobility; renewable energy sources; digital control techniques; smart grids
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Department of Industrial Electronics, School of Engineering, University of Minho, 4800-058 Guimaraes, Portugal
Interests: power electronics; power quality; active power filters; renewable energy; energy efficiency; electric vehicles; energy storage systems; battery charging systems; smart grids; smart cities; smart homes; technologies for innovative railway systems
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

A symbiotic introduction of electric vehicles (EVs) in smart grids, accomplished by sophisticated operation modes and control strategies, will promote the opportunity for an active and collaborative participation by the different players in the energy market, including the end-user. In this sense, new advances in the development of innovative software and hardware technologies toward a dynamic integration of EVs (including all technologies) in smart grids is of paramount importance. Moreover, the impact in terms of power quality caused or suffered by the EV (e.g., charging system) and by the smart grid is also a relevant issue that should be considered. Consequently, the interactivity between EVs and smart grids will also facilitate the accomplishment of environmental targets, accommodate demand for electricity, as well as integrate renewables and energy storage systems in a collaborative and unified operation.

This Special Issue aims to establish a bridge between the present and future perspectives of EVs in smart grids, joining original contributions from different perspectives, including academic scientists and researchers, and professional communities.

Topics of interest include but are not limited to the following: 

  • Unified EV charging systems with renewable energy sources and energy storage systems;
  • Innovative operation modes for EVs considering on-grid and off-grid scenarios;
  • EV operation as a power conditioner for smart grids;
  • Advanced EV battery chargers considering on-board and off-board technologies;
  • Innovative EV battery chargers employing emerging technologies of power electronics;
  • EV integration in smart homes or microgrids as smart grid enablers;
  • EV charging systems in industrial, commercial, and residential scenarios;
  • EV integration as a contribution for energy control and decision, and demand response;
  • New contributions for EV propulsion systems;
  • EV wireless power transfer (WPT) systems in smart grids.

Dr. Vítor Duarte Fernandes Monteiro
Prof. João L. Afonso
Guest Editor

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Keywords

  • Electric vehicles
  • Smart grids
  • Smart homes
  • Power electronics
  • Renewable energy sources
  • Energy storage systems
  • Wireless power transfer
  • on-board and off-board technologies
  • EV charging systems

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Published Papers (6 papers)

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Research

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15 pages, 4187 KiB  
Article
Wireless Communication and Management System for E-Bike Dynamic Inductive Power Transfer Lanes
by Jose A. Afonso, Helder G. Duarte, Luiz A. Lisboa Cardoso, Vitor Monteiro and Joao L. Afonso
Electronics 2020, 9(9), 1485; https://doi.org/10.3390/electronics9091485 - 10 Sep 2020
Cited by 8 | Viewed by 5489
Abstract
This paper presents the design, implementation, and testing of a wireless communication system for automatic identification of e-bikes and management of their battery charging in the context of dynamic inductive wireless power transfer (DIWPT) lanes. The proposed system checks if an e-bike, uniquely [...] Read more.
This paper presents the design, implementation, and testing of a wireless communication system for automatic identification of e-bikes and management of their battery charging in the context of dynamic inductive wireless power transfer (DIWPT) lanes. The proposed system checks if an e-bike, uniquely identified by its RFID tag, is authorized to receive energy from the lane coils and acts accordingly. An authentication mechanism was developed based on the use of embedded Wi-Fi boards attached to the coils and communicating with a central HTTP server with a MySQL database. The developed management system also provides other features, such as the recording of the number of lane coils used by each e-bike for billing purposes. The results from experimental tests on a laboratory prototype were used to validate the developed functionalities and assess the quality of service provided by the proposed system. Full article
(This article belongs to the Special Issue Electric Vehicles in Smart Grids)
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15 pages, 2819 KiB  
Article
Machine Learning Based PEVs Load Extraction and Analysis
by Amin Mansour-Saatloo, Arash Moradzadeh, Behnam Mohammadi-Ivatloo, Ali Ahmadian and Ali Elkamel
Electronics 2020, 9(7), 1150; https://doi.org/10.3390/electronics9071150 - 16 Jul 2020
Cited by 27 | Viewed by 3263
Abstract
Transformation of the energy sector due to the appearance of plug-in electric vehicles (PEVs) has faced the researchers with challenges in recent years. The foremost challenge is uncertain behavior of a PEV that hinders operators determining a deterministic load profile. Load forecasting of [...] Read more.
Transformation of the energy sector due to the appearance of plug-in electric vehicles (PEVs) has faced the researchers with challenges in recent years. The foremost challenge is uncertain behavior of a PEV that hinders operators determining a deterministic load profile. Load forecasting of PEVs is so crucial in both operating and planning of the energy systems. PEV load demand mainly depends on traveling behavior of them. This paper tries to present an accurate model to forecast PEVs’ traveling behavior in order to extract the PEV load profile. The presented model is based on machine-learning techniques; namely, a generalized regression neural network (GRNN) that correlates between PEVs’ arrival/departure times and traveling behavior is considered in the model. The results show the ability of the GRNN to communicate between arrival/departure times of PEVs and the distance traveled by them with a correlation coefficient (R) of 99.49% for training and 98.99% for tests. Therefore, the trained and saved GRNN model is ready to forecast PEVs’ trip length based on training and testing with historical data. Finally, the results indicate the importance of implementing more accurate methods to predict PEVs to gain the significant advantages in the importance of electrical energy in vehicles in the years to come. Full article
(This article belongs to the Special Issue Electric Vehicles in Smart Grids)
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17 pages, 7189 KiB  
Article
Research on Stability Design of Differential Drive Fork-Type AGV Based on PID Control
by Tingting Wang, Ruoyan Dong, Rui Zhang and Dongchen Qin
Electronics 2020, 9(7), 1072; https://doi.org/10.3390/electronics9071072 - 30 Jun 2020
Cited by 7 | Viewed by 5378
Abstract
As one of the important components of intelligent warehousing logistics, Automated Guided Vehicles (AGVs) have greatly improved the efficiency of warehousing operations. AGVs are responsible for the delivery of goods in warehousing and logistics, and it is extremely important to maintain a stable [...] Read more.
As one of the important components of intelligent warehousing logistics, Automated Guided Vehicles (AGVs) have greatly improved the efficiency of warehousing operations. AGVs are responsible for the delivery of goods in warehousing and logistics, and it is extremely important to maintain a stable running state. In this paper, an AGV in-situ steering dynamic model is established according to the actual size, and the center deviation phenomenon during AGV steering is theoretically analyzed to obtain the parameters that affect the AGV’s in-situ steering stability. Secondly, the dynamic simulation method is used to analyze the law of the stability of the AGV in-situ steering parameters to verify the correctness of the theoretical derivation equation. According to the analysis results, the motion parameters related to AGV in-situ steering are analyzed, and a reasonable design scheme is given. Based on the optimized fork-type AGV, the AGV in-situ steering control strategy is studied, and the adaptive fuzzy PID control algorithm is used to construct the fork-type AGV steering control system. Then the software and hardware design of the AGV steering control system is carried out. The optimized fork-type AGV has been turned to work stably after commissioning, meeting the actual work requirements. Full article
(This article belongs to the Special Issue Electric Vehicles in Smart Grids)
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12 pages, 1488 KiB  
Article
The Vital Contribution of MagLev Vehicles for the Mobility in Smart Cities
by Richard M. Stephan and Amaro O. Pereira, Jr.
Electronics 2020, 9(6), 978; https://doi.org/10.3390/electronics9060978 - 11 Jun 2020
Cited by 13 | Viewed by 5197
Abstract
The role of transport in sustainable development was first recognized at the 1992 United Nations (UN) Earth Summit and reinforced in its outcome document—Agenda 21. It is also part of objective 11 of UN 2030 Agenda for Sustainable Development. The improvements in the [...] Read more.
The role of transport in sustainable development was first recognized at the 1992 United Nations (UN) Earth Summit and reinforced in its outcome document—Agenda 21. It is also part of objective 11 of UN 2030 Agenda for Sustainable Development. The improvements in the traditional methods of transportation lag behind the necessities. This paper shows that Magnetic Levitation (MagLev) can fulfill the demand and fits with smart grid concepts. Moreover, the levitation method based on the diamagnetic property of high-temperature superconductors in the proximity of rare-earth permanent magnets presents advantages in comparison with other levitation methods. This technological solution was tested with the operation of a real scale prototype inside the campus of the Federal University of Rio de Janeiro (UFRJ), operating since 2014. The paper presents a historical and technological overview of the steps necessary to turn this prototype into a commercial product. The development is framed within NASA’s Technological Readiness Levels (TRL). A new transportation paradigm is on the verge of becoming a reality. Full article
(This article belongs to the Special Issue Electric Vehicles in Smart Grids)
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18 pages, 1309 KiB  
Article
Operation of Battery Storage as a Temporary Equipment During Grid Reinforcement Caused by Electric Vehicles
by Lukas Held, Sebastian Baumann, Michael R. Suriyah, Thomas Leibfried, Levin Ratajczak, Selma Lossau and Martin Konermann
Electronics 2020, 9(6), 888; https://doi.org/10.3390/electronics9060888 - 27 May 2020
Cited by 3 | Viewed by 2143
Abstract
Electric vehicle charging stresses distribution grids significantly with high penetrations of electric vehicles. This will lead to grid reinforcement works in several distribution grids. Battery storage is a possible solution to bypass times of grid reinforcement due to electric vehicle charging. In this [...] Read more.
Electric vehicle charging stresses distribution grids significantly with high penetrations of electric vehicles. This will lead to grid reinforcement works in several distribution grids. Battery storage is a possible solution to bypass times of grid reinforcement due to electric vehicle charging. In this paper, different operation strategies for such a battery storage are tested at first in simulations. The main difference between the strategies is the necessary input data. Following the simulations, selected strategies are tested in reality in the project ”Netzlabor E-Mobility-Allee”. It is proved that battery storage is a functioning possibility to bypass times of grid reinforcement. Full article
(This article belongs to the Special Issue Electric Vehicles in Smart Grids)
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Review

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30 pages, 559 KiB  
Review
Electric Vehicles: A Data Science Perspective Review
by Dario Pevec, Jurica Babic and Vedran Podobnik
Electronics 2019, 8(10), 1190; https://doi.org/10.3390/electronics8101190 - 18 Oct 2019
Cited by 34 | Viewed by 18067
Abstract
Current trends are showing that the popularity of electric vehicles (EVs) has significantly increased over the last few years, causing changes not only in the transportation industry but generally in business and society. This paper covers one possible angle to the (r) evolution [...] Read more.
Current trends are showing that the popularity of electric vehicles (EVs) has significantly increased over the last few years, causing changes not only in the transportation industry but generally in business and society. This paper covers one possible angle to the (r) evolution instigated by EVs, i.e., it provides the data science perspective review of the interdisciplinary area at the intersection of green transportation, energy informatics, and economics. Namely, the review summarizes data-driven research in EVs by identifying two main research streams: (i) socio–economic, and (ii) socio–technical. The socio–economic stream includes research in: (i) acceptance of green transportation in countries and among different populations, (ii) current trends in the EV market, and (iii) forecasting future sales for the green transportation. The socio–technical stream includes research in: (i) electric vehicle battery price and capacity and (ii) charging station management. This kind of study is especially important now when the question is no longer whether the transition from internal-combustion engine vehicles to clean-fuel vehicles is going to happen but how fast it will happen and what are going to be implications for society, governmental policies, and industry. Based on the presented literature review, the paper also outlines the most significant open questions and challenges that are yet to be solved: (i) scarcity of trustworthy (open) data, and (ii) designing a generalized methodology for charging station deployment. Full article
(This article belongs to the Special Issue Electric Vehicles in Smart Grids)
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