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Optimization for Charging and Discharging of Electric Vehicles
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Optimization for Charging and Discharging of Electric Vehicles

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

Deadline for manuscript submissions: closed (15 March 2023) | Viewed by 11891

Special Issue Editors

Dr. Shahid Hussain

E-Mail Website1 Website2 Website3
Guest Editor
Data Science Institute (DSI), Department of Electrical and Electronic Engineering, National University of Ireland, H91 TK33 Galway, Ireland
Interests: electric vehicles; smart parking lots; charging and discharging; optimization algorithm; smart grid; energy management; green hydrogen; fuel cell vehicles; fuzzy logic; neural network
Dr. Mousa Marzband

grade E-Mail Website
Guest Editor
Physics and Electrical Engineering, Department of Mathematics, Newcastle, United Northumbria University, London E1 7HT, UK
Interests: smart grids; scheduling; active distribution networks; power systems; energy economics; renewable energy integration
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Worldwide awareness of climate-related challenges and sustainable mobility necessitates controlling the emissions from gasoline-powered internal combustion engine vehicles. Electric vehicles (EV) are a promising technology that reduces carbon dioxide emissions and dependencies on fossil fuel and supports suitable mobility, thus resulting in large-scale electric mobility. However, the widespread adoption of electric vehicles (EVs) presents both challenges and opportunities in terms of charge/discharge load, cost, revenue, incentives, waiting time, and quality-of-service (QoS) satisfaction, as well as the power grid, utility companies, fleet operators, energy aggregators, and EV owners. Dealing with these challenges with renewable energy sources, energy storage systems, hybrid energy systems, green hydrogen, control techniques, energy management systems, and charging systems has necessitated the development of the optimal charge and discharge of electric vehicles according to the requirements and constraints of multiple shareholders within the scope of electric vehicle production. This Special Issue aims to look at the present and future of electric mobility and invites original contributions, including review papers, related (but not limited) to the following topics:·       

  • Charge and discharge optimization algorithms for G2V, V2G, V2H, V4G, and V2V.
  • Power flow, quality, reliability, and security analysis of smart grids.
  • Demand–response management for electric mobility.
  • Electromobility in the context of economic and environmental issues.
  • Advanced energy management solutions for integrating the charging and discharging of EVs in the private (building management system) and public (parking management system) spheres.
  • Analyzing the flexibility of existing charging options in the private, semi-public, and public spheres.
  • Assessing the load impact of different EV penetration and smart charging scenarios, taking the flexibility of the current load into account.
  • Charging station selection and load balancing.
  • Blockchain-based energy management solutions for EVs.
  • Green hydrogen and fuel cell vehicles.
  • Game theory approches to V2V, V2G, and G2V energy trading.
  • Machine learning and neural network models for electric load, charging cost, renewable generation, etc.
  • Renewable energy-based charging stations and charging EVs.
  • Communication network anlaysis for EVs.
  • Battery state-of-charge and state-of-health monitoring and control.

Dr. Shahid Hussain
Dr. Mousa Marzband
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

  • Charging and Discharging
  • Electric vehicles
  • Power grid
  • Charging stations

Published Papers (4 papers)

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Research

18 pages, 5263 KiB  
Article
Experimental Analysis and Simulation of Mixed Storage with Lithium-Ion Batteries and Supercapacitors for a PHEV
by Leone Martellucci, Mirko Dell’Aria and Roberto Capata
Energies 2023, 16(9), 3882; https://doi.org/10.3390/en16093882 - 4 May 2023
Cited by 2 | Viewed by 2344
Abstract
This work focuses on the simulation and testing of an innovative storage system for a PHEV vehicle, investigating the possibility of replacing the car’s original storage system with a mixed-storage system with lithium-ion batteries and supercapacitors connected in direct parallel without the use [...] Read more.
This work focuses on the simulation and testing of an innovative storage system for a PHEV vehicle, investigating the possibility of replacing the car’s original storage system with a mixed-storage system with lithium-ion batteries and supercapacitors connected in direct parallel without the use of an intermediate DC/DC converter. The aim is to evaluate the behavior of the supercapacitors’ branch compared with that of the Li-ion cells, both in the discharge/charge transients and over an entire WLTP cycle (Worldwide harmonized Light vehicles Test Procedure). The analysis started with the definition of the digital models of a lithium cell and a supercapacitor. The parameters of the models were tuned through experimental characterization of the two storage cells, Li-ion and supercapacitor. Subsequently, the overall models of the branch with the lithium cells and the branch with the supercapacitors were constructed and connected. The overall storage system was sized for application to a PHEV, and a reduced-scale storage system was realized and tested. Finally, the results obtained from the simulations were validated and compared with experimental tests. Full article
(This article belongs to the Special Issue Optimization for Charging and Discharging of Electric Vehicles)
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13 pages, 366 KiB  
Article
Privacy Protected Preservation of Electric Vehicles’ Data in Cloud Computing Using Secure Data Access Control
by Ahmed Abdu Alattab, Reyazur Rashid Irshad, Anwar Ali Yahya and Amin A. Al-Awady
Energies 2022, 15(21), 8085; https://doi.org/10.3390/en15218085 - 31 Oct 2022
Cited by 3 | Viewed by 1567
Abstract
Cloud computing provides a ubiquitous data storage and access mechanism for organizations, industries, and smart grids to facilitate their operations. However, the concern in cloud storage systems is to secure data access control toward authentication for sensitive data, such as the electric vehicles [...] Read more.
Cloud computing provides a ubiquitous data storage and access mechanism for organizations, industries, and smart grids to facilitate their operations. However, the concern in cloud storage systems is to secure data access control toward authentication for sensitive data, such as the electric vehicles (EVs) requesting information for attending a charging service. Consequently, denying an authentic user’s request will result in delaying the requested service, thereby leading to service inefficiency. The role-based access control (RBAC) plays a crucial role in securing and authenticating such time-sensitive data. The design mechanism of roles is based on skills, authority, and responsibilities for organizations. For EVs, the roles are based on the type of membership, such as permanent, occasional, or one-time. In this paper, we propose a new RBAC access control and privacy-preserving information access method toward the coarse-grained measure control and privacy protection in the cloud storage system for EVs. The data can be encrypted and decrypted based on the types of users who possess appropriate access permission toward authorized and unauthorized users according to their roles specified by role-based access control policies. The proposed approach has been simulated with various role-based scenarios, and the efficiency was evaluated against state-of-the-art role-based access-control techniques. Full article
(This article belongs to the Special Issue Optimization for Charging and Discharging of Electric Vehicles)
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18 pages, 1226 KiB  
Article
A Heuristic Charging Cost Optimization Algorithm for Residential Charging of Electric Vehicles
by Shahid Hussain, Subhasis Thakur, Saurabh Shukla, John G. Breslin, Qasim Jan, Faisal Khan, Ibrar Ahmad, Mousa Marzband and Michael G. Madden
Energies 2022, 15(4), 1304; https://doi.org/10.3390/en15041304 - 11 Feb 2022
Cited by 18 | Viewed by 2932
Abstract
The charging loads of electric vehicles (EVs) at residential premises are controlled through a tariff system based on fixed timing. The conventional tariff system presents the herding issue, such as with many connected EVs, all of them are directed to charge during the [...] Read more.
The charging loads of electric vehicles (EVs) at residential premises are controlled through a tariff system based on fixed timing. The conventional tariff system presents the herding issue, such as with many connected EVs, all of them are directed to charge during the same off-peak period, which results in overloading the power grid and high charging costs. Besides, the random nature of EV users restricts them from following fixed charging times. Consequently, the real-time pricing scenarios are natural and can support optimizing the charging load and cost for EV users. This paper aims to develop charging cost optimization algorithm (CCOA) for residential charging of EVs. The proposed CCOA coordinates the charging of EVs by heuristically learning the real-time price pattern and the EV’s information, such as the battery size, current state-of-charge, and arrival & departure times. In contrast to the holistic price, the CCOA determines a threshold price value for each arrival and departure sequence of EVs and accordingly coordinates the charging process with optimizing the cost at each scheduling period. The charging cost is captured at the end of each charging activity and the cumulative cost is calculated until the battery’s desired capacity. Various charging scenarios for individual and aggregated EVs with random arrival sequences of EVs against the real-time price pattern are simulated through MATLAB. The simulation results show that the proposed algorithm outperforms with a low charging cost while avoiding the overloading of the grid compared to the conventional uncoordinated, flat-rate, and time-of-use systems. Full article
(This article belongs to the Special Issue Optimization for Charging and Discharging of Electric Vehicles)
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13 pages, 2001 KiB  
Article
Self-Inductance Calculation of the Archimedean Spiral Coil
by Iftikhar Hussain and Dong-Kyun Woo
Energies 2022, 15(1), 253; https://doi.org/10.3390/en15010253 - 30 Dec 2021
Cited by 11 | Viewed by 3918
Abstract
In this paper, a new method to calculate the self-inductance of the Archimedean spiral coil is presented. The proposed method is derived by solving Neumann’s integral formula, and the numerical tool is used to calculate the inductance value. The calculation results are verified [...] Read more.
In this paper, a new method to calculate the self-inductance of the Archimedean spiral coil is presented. The proposed method is derived by solving Neumann’s integral formula, and the numerical tool is used to calculate the inductance value. The calculation results are verified with several conventional formulas derived from the Wheeler formula or its modified form and 3D finite element analyses. The comparison with simulation results shows that the conventional formula has an error of above 40% compared to the proposed method, which has below 7% when the wire diameter is reduced. To further check the validity, different sizes of the spiral coil are fabricated by changing the geometrical parameters such as the number of turns, turn spacing, inner radius, outer radius, and wire diameter. Litz wire is chosen for making the spiral coil, and bobbins are made using a 3D printer. Finally, the calculation results are compared with the experimental result. The error between them is less than 2%. The comparison with the conventional formulas, simulation, and measurement results shows the accuracy of the proposed method. This method can be used to calculate the self-inductance of wireless power coils, inductors and antenna design. Full article
(This article belongs to the Special Issue Optimization for Charging and Discharging of Electric Vehicles)
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