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Electronics
Special Issues
Electrification of Smart Cities
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Electrification of Smart Cities

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Computer Science & Engineering".

Deadline for manuscript submissions: closed (31 December 2021) | Viewed by 13822

Printed Edition Available!
A printed edition of this Special Issue is available here.

Special Issue Editors

Dr. Chun Sing Lai

E-Mail Website
Guest Editor
Brunel Interdisciplinary Power Systems Research Centre, Department of Electronic and Electrical Engineering, Brunel University London, Kingston Lane, London UB8 3PH, UK
Interests: smart energy management; smart grids; smart battery management systems; power system optimization; energy system modeling; data analytics; electric vehicle systems; hybrid powertrains optimization; energy economics for renewable energy and storage systems
Special Issues, Collections and Topics in MDPI journals
Dr. Kim-Fung Tsang

E-Mail Website
Guest Editor
Department of Electrical Engineering, City University of Hong Kong, Hong Kong, China
Interests: Internet of Things standards; sensors; wireless protocols; network optimization; emerging networks of Internet of Things; artificial intelligence for smart applications; blockchain and cyber security for Internet of Things
Special Issues, Collections and Topics in MDPI journals
Prof. Yinhai Wang

E-Mail Website
Guest Editor
Faculty of Civil & Environmental Engineering, University of Washington, Washington, DC, USA
Interests: infrastructure and smart cities; transportation engineering; traffic detection systems
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Electrification plays a key role in decarbonizing energy consumption for various sectors, including transportation, heating, and cooling. There are several essential infrastructures for a smart city, including smart grids and transportation networks. These infrastructures are the complementary solutions to successfully developing novel services, with enhanced energy efficiency and energy security.

This Special Issue seeks high-quality papers that address issues related to cutting-edge smart city technologies in the electrification process. Topics of interest for this Special Issue include, but are not limited to:

  • Electrification of building environments and transportation systems;
  • Role and impact of smart grids for smart cities;
  • ICT and IoT infrastructures with big data for smart cities electrification;
  • Market, services, and business models for smart cities electrification;
  • Standards and implementation for smart cities electrification;
  • Advanced smart grid technology integration in smart cities, such as energy storage, demand-side management, and distributed energy resources.

Dr. Chun Sing Lai
Dr. Kim-Fung Tsang
Prof. Yinhai Wang
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. Electronics 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 2400 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

  • Electrification of building environments and transportation systems
  • Role and impact of smart grids for smart cities
  • ICT and IoT infrastructures with big data for smart cities electrification
  • Market, services and business models for smart cities electrification
  • Standards and implementation for smart cities electrification
  • Advanced smart grid technology integration in smart city such as energy storage, demand side management, and distributed energy resources

Published Papers (6 papers)

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Editorial

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3 pages, 153 KiB  
Editorial
Electrification of Smart Cities
by Chun Sing Lai, Kim Fung Tsang and Yinhai Wang
Electronics 2022, 11(8), 1235; https://doi.org/10.3390/electronics11081235 - 14 Apr 2022
Cited by 2 | Viewed by 1048
Abstract
Electrification plays a key role in decarbonizing energy consumption for various sectors, including transportation, heating, and cooling [...] Full article
(This article belongs to the Special Issue Electrification of Smart Cities)

Research

Jump to: Editorial

21 pages, 1576 KiB  
Article
An Efficient Detour Computation Scheme for Electric Vehicles to Support Smart Cities’ Electrification
by Cole Mansfield, Jack Hodgkiss, Soufiene Djahel and Avishek Nag
Electronics 2022, 11(5), 803; https://doi.org/10.3390/electronics11050803 - 04 Mar 2022
Cited by 2 | Viewed by 2245
Abstract
Achieving carbon-neutral transportation is the ultimate goal of the ongoing joint efforts of governments, policy-makers, and the transportation research community. Electrification of smart cities is a very important step towards the above objective; therefore, accelerating the adoption and widening the use of Electric [...] Read more.
Achieving carbon-neutral transportation is the ultimate goal of the ongoing joint efforts of governments, policy-makers, and the transportation research community. Electrification of smart cities is a very important step towards the above objective; therefore, accelerating the adoption and widening the use of Electric Vehicles (EVs) are required. However, to achieve the full potential of EVs, ground-breaking detour computation and charging station selection schemes are needed. To this end, this paper developed a new scheme that finds the most suitable detour/route for an EV whenever an unexpected event occurs on the road. This scheme is based on A* and uses an original, Simple-Additive-Weighting (SAW)-based, charging station selection method. The performance evaluation carried out using the open-source traffic simulation platform SUMO under a grid map, as well as a real road network map highlighted that our scheme ensured more than 99% of EVs will reach their destination within a reasonable time even if a battery recharge is needed. This is a significant improvement compared to the baseline scheme that uses the A* only. Full article
(This article belongs to the Special Issue Electrification of Smart Cities)
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19 pages, 3304 KiB  
Article
Identifying the Lack of Energy-Conscious Behaviour in Clinical and Non-Clinical Settings: An NHS Case Study
by Ahmad Taha, Tim Hopthrow, Ruiheng Wu, Neil Adams, Jessica Brown, Ahmed Zoha, Qammer H. Abbasi, Muhammad Ali Imran and Jan Krabicka
Electronics 2021, 10(20), 2468; https://doi.org/10.3390/electronics10202468 - 11 Oct 2021
Cited by 4 | Viewed by 2042
Abstract
The race against climate change has been a great challenge for years, and the UK government has taken serious steps towards achieving the net-zero carbon target by 2050. Technology is leading the way and innovation is believed to be a key solution. Nevertheless, [...] Read more.
The race against climate change has been a great challenge for years, and the UK government has taken serious steps towards achieving the net-zero carbon target by 2050. Technology is leading the way and innovation is believed to be a key solution. Nevertheless, tackling the issue, by attempting to limit the waste in energy, due to negative energy usage behaviour, has proven to be a successful approach that is capable of complementing other technology-based initiatives. The first step towards this is to promote energy-conscious behaviour and pinpoint where savings can be made. Thereby, this paper contributes to the existing literature, by presenting a new methodology to identify potential energy waste and negative energy usage behaviour in an NHS hospital. The paper presents an analysis of electricity consumption vs occupancy during minimal consumption periods (i.e, bank holidays and weekends) and it presents a log of equipment left switched on outside of working hours, in order to highlight the level of energy-conscious behaviour. The results revealed that the proposed technique is not only able to identify negative energy usage behaviour amongst the hospital staff but helps identify areas where immediate energy savings can be made, with potential savings of more than 30,000 pounds, if action is taken. Full article
(This article belongs to the Special Issue Electrification of Smart Cities)
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19 pages, 11745 KiB  
Article
Video Super-Resolution Based on Generative Adversarial Network and Edge Enhancement
by Jialu Wang, Guowei Teng and Ping An
Electronics 2021, 10(4), 459; https://doi.org/10.3390/electronics10040459 - 13 Feb 2021
Cited by 8 | Viewed by 2378
Abstract
With the help of deep neural networks, video super-resolution (VSR) has made a huge breakthrough. However, these deep learning-based methods are rarely used in specific situations. In addition, training sets may not be suitable because many methods only assume that under ideal circumstances, [...] Read more.
With the help of deep neural networks, video super-resolution (VSR) has made a huge breakthrough. However, these deep learning-based methods are rarely used in specific situations. In addition, training sets may not be suitable because many methods only assume that under ideal circumstances, low-resolution (LR) datasets are downgraded from high-resolution (HR) datasets in a fixed manner. In this paper, we proposed a model based on Generative Adversarial Network (GAN) and edge enhancement to perform super-resolution (SR) reconstruction for LR and blur videos, such as closed-circuit television (CCTV). The adversarial loss allows discriminators to be trained to distinguish between SR frames and ground truth (GT) frames, which is helpful to produce realistic and highly detailed results. The edge enhancement function uses the Laplacian edge module to perform edge enhancement on the intermediate result, which helps further improve the final results. In addition, we add the perceptual loss to the loss function to obtain a higher visual experience. At the same time, we also tried training network on different datasets. A large number of experiments show that our method has advantages in the Vid4 dataset and other LR videos. Full article
(This article belongs to the Special Issue Electrification of Smart Cities)
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17 pages, 4586 KiB  
Article
An Improved Multi-Exposure Image Fusion Method for Intelligent Transportation System
by Mingyu Gao, Junfan Wang, Yi Chen, Chenjie Du, Chao Chen and Yu Zeng
Electronics 2021, 10(4), 383; https://doi.org/10.3390/electronics10040383 - 04 Feb 2021
Cited by 7 | Viewed by 1540
Abstract
In this paper, an improved multi-exposure image fusion method for intelligent transportation systems (ITS) is proposed. Further, a new multi-exposure image dataset for traffic signs, TrafficSign, is presented to verify the method. In the intelligent transportation system, as a type of important [...] Read more.
In this paper, an improved multi-exposure image fusion method for intelligent transportation systems (ITS) is proposed. Further, a new multi-exposure image dataset for traffic signs, TrafficSign, is presented to verify the method. In the intelligent transportation system, as a type of important road information, traffic signs are fused by this method to obtain a fused image with moderate brightness and intact information. By estimating the degree of retention of different features in the source image, the fusion results have adaptive characteristics similar to that of the source image. Considering the weather factor and environmental noise, the source image is preprocessed by bilateral filtering and dehazing algorithm. Further, this paper uses adaptive optimization to improve the quality of the output image of the fusion model. The qualitative and quantitative experiments on the new dataset show that the multi-exposure image fusion algorithm proposed in this paper is effective and practical in the ITS. Full article
(This article belongs to the Special Issue Electrification of Smart Cities)
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20 pages, 1420 KiB  
Article
A Novel Power Market Mechanism Based on Blockchain for Electric Vehicle Charging Stations
by Zhaoxiong Huang, Zhenhao Li, Chun Sing Lai, Zhuoli Zhao, Xiaomei Wu, Xuecong Li, Ning Tong and Loi Lei Lai
Electronics 2021, 10(3), 307; https://doi.org/10.3390/electronics10030307 - 27 Jan 2021
Cited by 25 | Viewed by 3267
Abstract
This work presents a novel blockchain-based energy trading mechanism for electric vehicles consisting of day-ahead and real-time markets. In the day-ahead market, electric vehicle users submit their bidding price to participate in the double auction mechanism. Subsequently, the smart match mechanism will be [...] Read more.
This work presents a novel blockchain-based energy trading mechanism for electric vehicles consisting of day-ahead and real-time markets. In the day-ahead market, electric vehicle users submit their bidding price to participate in the double auction mechanism. Subsequently, the smart match mechanism will be conducted by the charging system operator, to meet both personal interests and social benefits. After clearing the trading result, the charging system operator uploads the trading contract made in the day-ahead market to the blockchain. In the real-time market, the charging system operator checks the trading status and submits the updated trading results to the blockchain. This mechanism encourages participants in the double auction to pursue higher interests, in addition to rationally utilize the energy unmatched in the auction and to achieve the improvement of social welfare. Case studies are used to demonstrate the effectiveness of the proposed model. For buyers and sellers who successfully participate in the day-ahead market, the total profit increase for buyer and seller are 22.79% and 53.54%, respectively, as compared to without energy trading. With consideration of social welfare in the smart match mechanism, the peak load reduces from 182 to 146.5 kW, which is a 19.5% improvement. Full article
(This article belongs to the Special Issue Electrification of Smart Cities)
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