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Applied Sciences
Special Issues
Smart Grid and Smart Cities Activities
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Smart Grid and Smart Cities Activities

A special issue of Applied Sciences (ISSN 2076-3417).

Deadline for manuscript submissions: closed (15 June 2018) | Viewed by 9142

Special Issue Editors

Prof. Dr. Jong-Bae Park

E-Mail Website
Guest Editor
Electrical Engineering Department, Konkuk University, Seoul, Korea
Interests: smart grid; electric power system operations and planning
Dr. Sung-Yong Son

E-Mail Website
Guest Editor
Department of Electrical Engineering, College of IT Convergence, Global Campus, Gachon University, Seongnam-si 13120, Republic of Korea
Interests: smart grid; smart home; smart city; energy service
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Both smart grids and smart cities are considered as essential infrastructure in the future energy environment. Smart grids and smart cities are the complementary solutions to effectively implement new services, such as energy efficiency, security, metering, etc.

This Special Issue on smart grid and smart city activities seeks high-quality papers that address issues related to cutting-edge smart grid and smart city technologies. Topics of interest include but are not limited to the following areas:

  • Role and contribution of smart grid in smart city
  • Role and contribution of smart city to smart grid
  • Synergy of smart grid and smart city
  • Sharing big data between smart grid and smart city
  • IoT infrastructure for smart grid and smart city
  • Market and services for smart grid and smart city
  • Implementation of smart grid and smart city
  • Other advanced smart grid technology integration in smart city such as energy efficiency, electric vehicle, distributed energy resources, etc.

Prof. Dr. Jong-Bae Park
Dr. Sung-Yong Son
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. Applied Sciences 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

  • Smart grid
  • smart city
  • architecture
  • market and service
  • information
  • IoT
  • big data

Published Papers (2 papers)

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Research

19 pages, 3216 KiB  
Article
A Solar–Thermal-Assisted Adiabatic Compressed Air Energy Storage System and Its Efficiency Analysis
by Xiaotao Chen, Tong Zhang, Xiaodai Xue, Laijun Chen, Qingsong Li and Shengwei Mei
Appl. Sci. 2018, 8(8), 1390; https://0-doi-org.brum.beds.ac.uk/10.3390/app8081390 - 17 Aug 2018
Cited by 13 | Viewed by 4996
Abstract
Adiabatic compressed air energy storage (A-CAES) is an effective balancing technique for the integration of renewables and peak-shaving due to the large capacity, high efficiency, and low carbon use. Increasing the inlet air temperature of turbine and reducing the compressor power consumption are [...] Read more.
Adiabatic compressed air energy storage (A-CAES) is an effective balancing technique for the integration of renewables and peak-shaving due to the large capacity, high efficiency, and low carbon use. Increasing the inlet air temperature of turbine and reducing the compressor power consumption are essential to improving the efficiency of A-CAES. This paper proposes a novel solar–thermal-assisted A-CAES system (ST-CAES), which features a higher inhale temperature of the turbine to improve the system efficiency. Solar–thermal energy, as an external thermal source, can alleviate the inadequate temperature of the thermal energy storage (TES), which is constrained by the temperature of the exhaust air of the compressor. Energy and exergy analyses were performed to identify ST-CAES performance, and the influence of key parameters on efficiency were studied. Furthermore, exergy efficiency and the destruction ratio of each component of ST-CAES were investigated. The results demonstrate that electricity storage efficiency, round-trip efficiency, and exergy efficiency can reach 70.2%, 61%, and 50%, respectively. Therefore, the proposed system has promising prospects in cities with abundant solar resources owing to its high efficiency and the ability to jointly supply multiple energy needs. Full article
(This article belongs to the Special Issue Smart Grid and Smart Cities Activities)
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18 pages, 3854 KiB  
Article
Power System Voltage Correction Scheme Based on Adaptive Horizon Model Predictive Control
by Yan Zhang, Meng Liu, Wen Zhang, Wenchuan Sun, Xingwang Hu and Gang Kong
Appl. Sci. 2018, 8(4), 641; https://0-doi-org.brum.beds.ac.uk/10.3390/app8040641 - 20 Apr 2018
Cited by 2 | Viewed by 3672
Abstract
Model predictive control (MPC) is commonly used to compensate for modeling inaccuracies and measurement noise in voltage control problems. The length of the prediction horizon and control horizon of a MPC-based method has significant impact on the control performances. In existing relevant works, [...] Read more.
Model predictive control (MPC) is commonly used to compensate for modeling inaccuracies and measurement noise in voltage control problems. The length of the prediction horizon and control horizon of a MPC-based method has significant impact on the control performances. In existing relevant works, those horizon parameters are determined off-line based on experience or enumeration, and keeps constant during the entire receding-horizon optimization process. This paper presents a system voltage correction scheme based on adaptive horizon model predictive control (AH-MPC). The reactive power compensation and voltage regulation devices are coordinated to maintain the system voltages within a desired range. An evaluation index is proposed to determine the horizon parameters, which reflects the maximum voltage regulation ability with the current parameter configuration. Within each sampling interval, the horizon parameters are updated according to the evaluation index and real-time measurements periodically, which comprehensively considers the system uncertainties and voltage recovery speed, and the computational effort is remarkably reduced. The validation and effectiveness of the proposed method is verified by the simulation analysis on the test system. Full article
(This article belongs to the Special Issue Smart Grid and Smart Cities Activities)
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