Special Issue "Bidirectional Energy Transfer Technologies for Vehicle-to-Grid and Other Vehicle-to-X Applications, and Solutions to Issues Caused by High Electric Vehicle Penetration Rates"

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

Deadline for manuscript submissions: 31 July 2020.

Special Issue Editors

Prof. Udaya K Madawala
Website
Guest Editor
University of Auckland, Auckland, New Zealand
Interests: wireless (inductive) power transfer; power electronics; renewable energy; V2G systems
Dr. Craig Baguley
Website
Co-Guest Editor
Auckland University of Technology, Auckland, New Zealand
Interests: power electronics; magnetic component design and application; power systems in the pacificislands; renewable energy
Dr. Shantha Gamini Jayasinghe
Website
Co-Guest Editor
Australian Maritime College, University of Tasmania
Interests: power electronics; electric ship propulsion; renewable energy systems

Special Issue Information

Dear Colleagues,

The penetration rate of electric vehicles (EVs) into the transport sector of future societies will be high. This will result some excellent outcomes, but will also bring one of the greatest challenges to the electric power industry that it has ever faced. Multiple solutions must be developed to address a range of issues at various levels. One potential solution of high promise is vehicle-to-grid (V2G) technology.

Conventionally, energy is transferred from grid to vehicle and stored in EV batteries for later use for EV motor drive. However, and instead, this energy could be retrieved and used to provide electricity to a house (V2H), building (V2B), neighbourhood, or back to the grid (V2G). Through V2G, a range of power system services can be provided, including support for intermittent renewable energy power sources, frequency and voltage stabilization, and peak shaving. In addition, for power systems that are heavily dependent on fossil fuelled generation, carefully planned V2G implementation can generate revenue for utility companies while saving money for consumers through energy time shifting.

We propose a Special Issue on leading edge power electronic and power system issues related to high EV penetration rates, as well as the bi-directional transfer of energy between EVs and other systems (this encompasses not only V2G but all V2X system types). We welcome and encourage submissions in this area. Topics of interest include but are not limited to the following:

  • Power electronic V2G, and other V2X, interface technology challenges and solutions;
  • V2G, and other V2X, electricity network planning and integration requirements;
  • Charge/discharge scheduling and optimization, and issues related to high EV penetration rates;
  • Energy-related opportunities and challenges V2G and other V2X will present to EV owners, property owners, and utilities.

Prof. Udaya K Madawala
Dr. Craig Baguley
Dr. Shantha Gamini Jayasinghe
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 papers will be 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 1800 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

  • Plug-in electric vehicle
  • Vehicle-to-grid, V2G
  • V2X
  • Bi-directional energy transfer
  • Battery charger
  • Charge scheduling, discharge scheduling
  • Distribution networks.

Published Papers (4 papers)

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Open AccessArticle
Multi-Agent Reinforcement Learning Approach for Residential Microgrid Energy Scheduling
Energies 2020, 13(1), 123; https://doi.org/10.3390/en13010123 - 25 Dec 2019
Abstract
Residential microgrid is widely considered as a new paradigm of the home energy management system. The complexity of Microgrid Energy Scheduling (MES) is increasing with the integration of Electric Vehicles (EVs) and Renewable Generations (RGs). Moreover, it is challenging to determine optimal scheduling [...] Read more.
Residential microgrid is widely considered as a new paradigm of the home energy management system. The complexity of Microgrid Energy Scheduling (MES) is increasing with the integration of Electric Vehicles (EVs) and Renewable Generations (RGs). Moreover, it is challenging to determine optimal scheduling strategies to guarantee the efficiency of the microgrid market and to balance all market participants’ benefits. In this paper, a Multi-Agent Reinforcement Learning (MARL) approach for residential MES is proposed to promote the autonomy and fairness of microgrid market operation. First, a multi-agent based residential microgrid model including Vehicle-to-Grid (V2G) and RGs is constructed and an auction-based microgrid market is built. Then, distinguish from Single-Agent Reinforcement Learning (SARL), MARL can achieve distributed autonomous learning for each agent and realize the equilibrium of all agents’ benefits, therefore, we formulate an equilibrium-based MARL framework according to each participant’ market orientation. Finally, to guarantee the fairness and privacy of the MARL process, we proposed an improved optimal Equilibrium Selection-MARL (ES-MARL) algorithm based on two mechanisms, private negotiation and maximum average reward. Simulation results demonstrate the overall performance and efficiency of proposed MARL are superior to that of SARL. Besides, it is verified that the improved ES-MARL can get higher average profit to balance all agents. Full article
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Open AccessArticle
Investigating the Impact of E-Mobility on the Electrical Power Grid Using a Simplified Grid Modelling Approach
Energies 2020, 13(1), 39; https://doi.org/10.3390/en13010039 - 19 Dec 2019
Abstract
To achieve climate goals, it is necessary to decarbonise the transport sector, which requires an immediate changeover to alternative power sources (e.g., battery powered vehicles). This change will lead to an increase in the demand for electrical energy, which will cause additional stress [...] Read more.
To achieve climate goals, it is necessary to decarbonise the transport sector, which requires an immediate changeover to alternative power sources (e.g., battery powered vehicles). This change will lead to an increase in the demand for electrical energy, which will cause additional stress on power grids. It is therefore necessary to evaluate energy and power requirements of a future society using e-mobility. Therefore, we present a new approach to investigate the influence of increasing e-mobility on a distribution grid level. This includes the development of a power grid model based on a cellular approach, reducing computation efforts, and allowing time and spatially resolved grid stress analysis based on different load and renewable energy source scenarios. The results show that by using the simplified grid model at least seven times, more scenarios can be calculated in the same time. In addition, we demonstrate the capability of this novel approach by analysing the influence of different penetrations of e-mobility on the grid load using a case study, which is calculated using synthetic charging load profiles based on a real-life mobility data. The results from this case study show an increase on line utilisations with increasing e-mobility and the influence of producers at the same connection point as e-mobility. Full article
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Open AccessFeature PaperArticle
Evaluation of Optimization-Based EV Charging Scheduling with Load Limit in a Realistic Scenario
Energies 2019, 12(24), 4730; https://doi.org/10.3390/en12244730 - 11 Dec 2019
Cited by 2
Abstract
In the literature, optimization-based approaches are frequently proposed for the control of electric vehicle charging. However, they are usually evaluated under simplifying assumptions and are not compared to more simple approaches. The present work compares optimization-based approaches with rule-based ones in a simple [...] Read more.
In the literature, optimization-based approaches are frequently proposed for the control of electric vehicle charging. However, they are usually evaluated under simplifying assumptions and are not compared to more simple approaches. The present work compares optimization-based approaches with rule-based ones in a simple but realistic scenario, in which a certain limit for the total load has to be satisfied. The scenario is based on the situation at an office building in Germany. In simulation experiments, different control approaches are evaluated not only in terms of pure performance but also from an economic perspective. The results indicate that, although the optimization-based approaches outperform the rule-based approaches, they are not always the right choice from an economic point of view. Full article
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Review

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Open AccessReview
An Insight into Practical Solutions for Electric Vehicle Charging in Smart Grid
Energies 2020, 13(7), 1545; https://doi.org/10.3390/en13071545 - 26 Mar 2020
Abstract
The electrification of transportation has been developed to support energy efficiency and CO2 reduction. As a result, electric vehicles (EVs) have become more popular in the current transport system to create more efficient energy. In recent years, this increase in EVs as [...] Read more.
The electrification of transportation has been developed to support energy efficiency and CO2 reduction. As a result, electric vehicles (EVs) have become more popular in the current transport system to create more efficient energy. In recent years, this increase in EVs as well as renewable energy resources (RERs) has led to a major issue for power system networks. This paper studies electrical vehicles (EVs) and their applications in the smart grid and provides practical solutions for EV charging strategies in a smart power system to overcome the issues associated with large-scale EV penetrations. The research first reviews the EV battery infrastructure and charging strategies and introduces the main impacts of uncontrolled charging on the power grid. Then, it provides a practical overview of the existing and future solutions to manage the large-scale integration of EVs into the network. The simulation results for two controlled strategies of maximum sensitivity selection (MSS) and genetic algorithm (GA) optimization are presented and reviewed. A comparative analysis was performed to prove the application and validity of the solution approaches. This also helps researchers with the application of the optimization approaches on EV charging strategies. These two algorithms were implemented on a modified IEEE 23 kV medium voltage distribution system with switched shunt capacitors (SSCs) and a low voltage residential network, including EVs and nonlinear EV battery chargers. Full article
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