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WEVJ
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Electric Vehicles Integration in Smart Grids
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Electric Vehicles Integration in Smart Grids

A special issue of World Electric Vehicle Journal (ISSN 2032-6653).

Deadline for manuscript submissions: closed (20 May 2022) | Viewed by 14375

Special Issue Editors

Dr. Fanlin Meng

E-Mail Website
Guest Editor
Department of Mathematical Sciences, University of Essex, Colchester, UK
Interests: smart energy and mobility; energy market; smart buildings; artificial intelligence; game theory
Dr. Xinan Yang

E-Mail Website
Guest Editor
Department of Mathematical Sciences, University of Essex, Colchester CO4 3SQ, UK
Interests: dyanmic programming; revenue management; vehicle routing; meta-heuristics; stochastic optimzation
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The energy sector (e.g., transport and electricity & heat) accounts for more than 70% of total emissions globally, which contextualises ongoing efforts on the development of clean and modern energy technologies (e.g., smart grids and renewable energy), and the increasing integration of electric vehicles (EVs). The co-development and integration of EVs and renewable energy in smart grids will bring significant benefits to multiple sectors (e.g., transport and electricity), however, at the same time will create unprecedented challenges to reliable and efficient system operations. For instance, with the uptake of EVs and public charging infrastructures, the electricity demand will increase significantly, which inevitably accelerates the already increasing growth of renewable energy to meet the demand and thus poses new challenges on the existing energy system planning and operations. On the other hand, the renewable energy and EVs integration in smart grids considering their sizing and location selection will affect the transport planning and operations and create interesting and important charging/discharging and driving behaviors.

The above coupled hybrid cyber-physical system involving different sectors exhibits complex interactive behaviors among different parties, which presents a series of challenging and open research questions to be answered. Therefore, this Special Issue is devoted to the latest developments in the integration of electric vehicles in smart grids. Prospective authors are invited to submit original contributions that include but are not limited to the following topics of interest:

  • EVs operations optimization in smart grids
  • EVs for demand response in smart grids at local and/or national level
  • Optimization and/or machine learning for EVs charging/discharging analysis
  • Optimization and/or machine learning for EVs driving behaviour analysis
  • Optimization and/or machine learning for EVs charging station sizing and location selection
  • Optimization and/or machine learning for EVs integration in smart grids at local and/or national level
  • Game-theoretic modelling for large-scale EVs integration in smart grids at local and/or national level
  • Optimization and/or machine learning for the impact of EVs on the transport and logistics operations
  • Game-theoretic modelling for the impact of EVs on the transport and logistics operations
  • Optimization and/or machine learning for the impact of EVs on system operations of multiple energy sectors
  • Game-theoretic modelling for the impact of EVs on system operations of multiple energy sectors
  • Participation of EVs aggregators in local and wholesale electricity markets
  • Demand management and pricing in EVs participated electricity network
  • Innovations and evolutions in car rental/sharing industry brought by EVs
  • Integrated delivery/mobility network with EVs and other electric-driven autonomous (e.g., E-bikes, E-scooter, Drones, Robots, etc.)
  • Innovative charging strategies for EVs (e.g., using drones) and their management

Technical surveys and review papers are highly encouraged for submission and possible publication in this Special Issue “Electric Vehicles Integration in Smart Grids” of the World Electric Vehicle Journal.

Dr. Fanlin Meng
Dr. Xinan Yang
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. World Electric Vehicle Journal is an international peer-reviewed open access monthly 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 1400 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

  • Electric Vehicles
  • Smart Grids
  • Transport
  • Smart Energy and Mobility
  • Energy Management
  • Demand Management
  • Electricity Market
  • Optimization
  • Machine Learning
  • Game Theory
  • Artificial Intelligence

Published Papers (5 papers)

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Research

26 pages, 1216 KiB  
Article
Why Do Pricing Rules Matter? Electricity Market Design with Electric Vehicle Participants
by Felipe Maldonado and Andrea Saumweber
World Electr. Veh. J. 2022, 13(8), 143; https://doi.org/10.3390/wevj13080143 - 2 Aug 2022
Cited by 1 | Viewed by 2836
Abstract
The energy transition, a process in which fossil fuels are being replaced by cleaner sources of energy, comes with many challenges. The intrinsic uncertainty associated with renewable energy sources has led to a search for complementary technologies to tackle those issues. In recent [...] Read more.
The energy transition, a process in which fossil fuels are being replaced by cleaner sources of energy, comes with many challenges. The intrinsic uncertainty associated with renewable energy sources has led to a search for complementary technologies to tackle those issues. In recent years, the use of electric vehicles (EVs) has been studied as an alternative for storage, leading to a much more complex market structure. Small participants are now willing to provide energy, helping to keep the desired balance of supply and demand. In this paper, we analyse the electricity spot market, providing a model where EVs decide to participate depending on the underlying conditions. We study pricing rules adapted from versions currently in use in electricity markets, and focus on two of them for our experimental settings: integer programming (IP) and extended locational marginal (ELM) pricing. We particularly pay attention to the properties those prices might satisfy, and numerically test them under some scenarios representing different levels of participation of EVs and an active demand side. Our results suggest that IP pricing generally derives larger individual uplift payments and further produces public prices that are not well aligned with the final payments of market participants, leading to distortions in the market. Full article
(This article belongs to the Special Issue Electric Vehicles Integration in Smart Grids)
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18 pages, 1262 KiB  
Article
EVB-Supportive Energy Management for Residential Systems with Renewable Energy Supply
by Xinan Yang, Thanet Chitsuphaphan, Hongsheng Dai and Fanlin Meng
World Electr. Veh. J. 2022, 13(7), 122; https://doi.org/10.3390/wevj13070122 - 4 Jul 2022
Viewed by 2096
Abstract
This study examines the potential role that an Electric Vehicle Battery (EVB) can play in Home Energy Management System (HEMS) based on a future development on the performance and costs of batteries. The value of EVB in an HEMS with different home connection [...] Read more.
This study examines the potential role that an Electric Vehicle Battery (EVB) can play in Home Energy Management System (HEMS) based on a future development on the performance and costs of batteries. The value of EVB in an HEMS with different home connection settings and energy consumption/storage/generation capacities are investigated to advise the optimal future HEMS setups. Solar PV are considered as the residential renewal energy supply, which is the main resource of uncertainty of the system. A novel forecasting model is deployed which incorporates geographical information, solar radiation forecast and weather-related conditions into an exponential-based method to simulate day-ahead solar PV output. Optimal flows of energy and usage of storage (batteries) are then captured by a Stochastic Programming (SP) model and solved by CPLEX. Managerial insights and optimal designs of the HEMS are drawn based on the results obtained. Full article
(This article belongs to the Special Issue Electric Vehicles Integration in Smart Grids)
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24 pages, 2990 KiB  
Article
Collaborative Optimization of the Battery Capacity and Sailing Speed Considering Multiple Operation Factors for a Battery-Powered Ship
by Yan Zhang, Lin Sun, Fan Ma, You Wu, Wentao Jiang and Lijun Fu
World Electr. Veh. J. 2022, 13(2), 40; https://doi.org/10.3390/wevj13020040 - 16 Feb 2022
Cited by 7 | Viewed by 3001
Abstract
In the context of harsh emission control and ecological environment protection, the shipping industry is transforming and upgrading towards greening, decarburization, and electrification. Battery-powered all-electric inland ships have been attracting increasingly attention. However, its initial investment cost is much more expensive than a [...] Read more.
In the context of harsh emission control and ecological environment protection, the shipping industry is transforming and upgrading towards greening, decarburization, and electrification. Battery-powered all-electric inland ships have been attracting increasingly attention. However, its initial investment cost is much more expensive than a traditional diesel-driven mechanical ship because lithium-ion batteries are currently expensive. Hence, a suitable battery size and efficient energy management strategy for ship sailing are very important for a battery-powered ship. In this paper, a novel joint optimization method of the sailing speed and battery capacity, which considers the interaction between battery size and sailing speed as well as multiple operation factors, such as freight demand and battery life, and port electricity price, is proposed to fully exploit the battery-powered ships’ application potential. Moreover, a joint optimization model of the sailing speed and battery energy consumption model considers the battery-powered ship’s characteristics and waterway characteristics. Next, a solution algorithm for the proposed joint optimization model is established to achieve joint decision-making regarding the sailing speed and battery size. Finally, case studies are conducted to demonstrate the flexibility and effectiveness of the proposed method. The results show that the proposed method can obtain the optimal sailing speed and the corresponding battery capacity synchronously when the actual transportation scenario is fixed. Moreover, the battery initial investment cost can be effectively reduced with the prosed method. Full article
(This article belongs to the Special Issue Electric Vehicles Integration in Smart Grids)
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16 pages, 3539 KiB  
Article
Optimal Design of a Short Primary Double-Sided Linear Induction Motor for Urban Rail Transit
by Hanming Wang, Jinghong Zhao, Yiyong Xiong, Hao Xu and Sinian Yan
World Electr. Veh. J. 2022, 13(2), 30; https://doi.org/10.3390/wevj13020030 - 31 Jan 2022
Viewed by 2458
Abstract
Linear induction motors (LIMs) have been widely used in rail transit. However, Due to the breaking of the primary core and the large air gap, the efficiency and power factor of LIMs are seriously damaged, causing a large amount of energy waste. To [...] Read more.
Linear induction motors (LIMs) have been widely used in rail transit. However, Due to the breaking of the primary core and the large air gap, the efficiency and power factor of LIMs are seriously damaged, causing a large amount of energy waste. To improve the efficiency and power factor of LIMs for urban rail transit, we present a new optimization method for the design of a short primary double-sided linear induction motor (SP-DLIM) with a rated speed of 45 km/h and small thrust. The method is based on a steady state equivalent circuit model and the differential evolutionary algorithm (DEA). Moreover, the design constraints and the objective functions are proposed for the optimization problem. Finally, the optimized SP-DLIM is simulated by 2D transient finite element method (FEM). The 2-D transient FEM results verify the accuracy of the optimization method proposed in this paper. Full article
(This article belongs to the Special Issue Electric Vehicles Integration in Smart Grids)
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22 pages, 7287 KiB  
Article
Integrating Electric Vehicles into Power System Operation Production Cost Models
by Jose David Alvarez Guerrero, Bikash Bhattarai, Rajendra Shrestha, Thomas L. Acker and Rafael Castro
World Electr. Veh. J. 2021, 12(4), 263; https://doi.org/10.3390/wevj12040263 - 15 Dec 2021
Cited by 9 | Viewed by 2597
Abstract
The electrification of the transportation sector will increase the demand for electric power, potentially impacting the peak load and power system operations. A change such as this will be multifaceted. A power system production cost model (PCM) is a useful tool with which [...] Read more.
The electrification of the transportation sector will increase the demand for electric power, potentially impacting the peak load and power system operations. A change such as this will be multifaceted. A power system production cost model (PCM) is a useful tool with which to analyze one of these facets, the operation of the power system. A PCM is a computer simulation that mimics power system operation, i.e., unit commitment, economic dispatch, reserves, etc. To understand how electric vehicles (EVs) will affect power system operation, it is necessary to create models that describe how EVs interact with power system operations that are suitable for use in a PCM. In this work, EV charging data from the EV Project, reported by the Idaho National Laboratory, were used to create scalable, statistical models of EV charging load profiles suitable for incorporation into a PCM. Models of EV loads were created for uncoordinated and coordinated charging. Uncoordinated charging load represents the load resulting from EV owners that charge at times of their choosing. To create an uncoordinated charging load profile, the parameters of importance are the number of vehicles, charger type, battery capacity, availability for charging, and battery beginning and ending states of charge. Coordinated charging is where EVs are charged via an “aggregator” that interacts with a power system operator to schedule EV charging at times that either minimize system operating costs, decrease EV charging costs, or both, while meeting the daily EV charging requirements subject to the EV owners’ charging constraints. Beta distributions were found to be the most appropriate distribution for statistically modeling the initial and final state of charge (SoC) of vehicles in an EV fleet. A Monte Carlo technique was implemented by sampling the charging parameters of importance to create an uncoordinated charging load time series. Coordinated charging was modeled as a controllable load within the PCM to represent the influence of the EV fleet on the system’s electricity price. The charging models were integrated as EV loads in a simple 5-bus system to demonstrate their usefulness. Polaris Systems Optimization’s PCM power system optimizer (PSO) was employed to show the effect of the EVs on one day of operation in the 5-bus power system, yielding interesting and valid results and showing the effectiveness of the charging models. Full article
(This article belongs to the Special Issue Electric Vehicles Integration in Smart Grids)
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