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Communication and Data Management for Smart Grids
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Communication and Data Management for Smart Grids

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Communications".

Deadline for manuscript submissions: closed (6 July 2021) | Viewed by 8599

Special Issue Editors

Dr. Rasmus Olsen

E-Mail Website
Guest Editor
Aalborg Universitety, Aalborg, Denmark
Interests: communication networks; data analytics, smart grids, ICT infrastructure, security
Dr. Hans-Peter Schwefel

E-Mail Website
Guest Editor
Aalborg Universitety, Aalborg, Denmark
Interests: communication; data analysis; smart grids
Dr. Christian Wietfeld

E-Mail Website
Guest Editor
TU Dortmund University, Dortmund, Germany
Interests: smart grid; electric vehicle communications; cognitive networking; heterogeneous networks; mobile radio networks; multi-scale, stochastic simulation and analytical modeling
Dr. Jiakun Fang

E-Mail Website
Guest Editor
School of Electrical and Electronic Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
Interests: robust optimization; energy system integration; power-to-hydrogen
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Energy distribution grids are complex, requiring not only advanced monitoring functionality that is reliable and capable of handling large amounts of data, but also flexible services to enable an efficient and reliable operation of the grid. While today’s methodologies and approaches have been shaped by requirements from 10–20 years ago, near-future requirements that allow high penetration of renewable energy resources lead to a demand for change in the existing infrastructure that supports the operation of grids, as well as changing load patterns due to, for example, electric vehicles. Smart solutions need to ensure data is collected, distributed, and managed for reliable grid services and need to scale well to large amounts of heterogeneous grid-related data sources. Such solutions are key to the success of future smart energy distribution grids.

In this Special Issue, we encourage submissions that design and assess communication and data management solutions and related data analytics and control applications that contribute to the dependable smart energy distribution grid for the future.

Topics of interest may include, but are not limited to, the following::

  • Advanced modeling methods for integrated distributed energy networks.
  • Artificial intelligence and smart decision tools for distributed energy systems.
  • Data-driven algorithms and their application in the distributed energy systems.
  • Emerging and enabling facilities in the distributed energy systems.

Dr. Rasmus Olsen
Dr. Hans-Peter Schwefel
Dr. Christian Wietfeld
Dr. Jiakun Fang
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. Sensors 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.

Published Papers (4 papers)

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Research

19 pages, 4791 KiB  
Article
Optimal Performance and Modeling of Wireless Technology Enabling Smart Electric Metering Systems Including Microgrids
by Carlos Suárez and Esteban Inga
Sensors 2021, 21(21), 7208; https://doi.org/10.3390/s21217208 - 29 Oct 2021
Cited by 1 | Viewed by 1213
Abstract
This work is focused on the performance analysis and optimal routing of wireless technology for intelligent energy metering, considering the inclusion of micro grids. For the study, a geo-referenced scenario has been taken into account, which will form the structure of a graph [...] Read more.
This work is focused on the performance analysis and optimal routing of wireless technology for intelligent energy metering, considering the inclusion of micro grids. For the study, a geo-referenced scenario has been taken into account, which will form the structure of a graph to be solved using heuristic-based algorithms. In the first instance, the candidate site of the world geography to perform the case study is established, followed by deploying infrastructure devices and determining variables and parameters. Then, the model configuration is programmed, taking into account that a set of nodes and vertices is established for proper routing, resulting in a preliminary wireless network topology. Finally, from a set of restrictions, a determination of users connected to the concentrator and optimal routing is performed. This procedure is treated as a coverage set problem. Consequently, to establish the network parameters, two restrictions are specifically considered, capacity and range; thus, can be determined the best technology to adapt to the location. Finally, a verification of the resulting network topologies and the performance of the infrastructure is done by simulating the wireless network. With the model created, scenarios are tested, and it is verified that the optimization model demonstrates its effectiveness. Full article
(This article belongs to the Special Issue Communication and Data Management for Smart Grids)
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16 pages, 625 KiB  
Article
Resilient Adaptive Event-Triggered Load Frequency Control of Network-Based Power Systems against Deception Attacks
by Xiao Zhang, Fan Yang and Xiang Sun
Sensors 2021, 21(21), 7047; https://doi.org/10.3390/s21217047 - 24 Oct 2021
Cited by 3 | Viewed by 1590
Abstract
This paper investigates the problem of networked load frequency control (LFC) of power systems (PSs) against deception attacks. To lighten the load of the communication network, a new adaptive event-triggered scheme (ETS) is developed on the premise of maintaining a certain control performance [...] Read more.
This paper investigates the problem of networked load frequency control (LFC) of power systems (PSs) against deception attacks. To lighten the load of the communication network, a new adaptive event-triggered scheme (ETS) is developed on the premise of maintaining a certain control performance of LFC systems. Compared with the existing ETSs, the proposed adaptive ETS can adjust the number of triggering packets, along with the state changes in the presence of deception attacks, which can reduce the average data-releasing rate. In addition, sufficient conditions can be derived, providing a trade-off between the limited network communication resources and the desired control performance of PSs. Finally, an application case is presented for the PSs to demonstrate the advantages of the proposed approach. Full article
(This article belongs to the Special Issue Communication and Data Management for Smart Grids)
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22 pages, 2340 KiB  
Article
Experimental Validation and Deployment of Observability Applications for Monitoring of Low-Voltage Distribution Grids
by Karthikeyan Nainar, Catalin Iosif Ciontea, Kamal Shahid, Florin Iov, Rasmus Løvenstein Olsen, Christine Schäler and Hans-Peter Christian Schwefel
Sensors 2021, 21(17), 5770; https://doi.org/10.3390/s21175770 - 27 Aug 2021
Cited by 7 | Viewed by 2196
Abstract
Future distribution grids will be subjected to fluctuations in voltages and power flows due to the presence of renewable sources with intermittent power generation. The advanced smart metering infrastructure (AMI) enables the distribution system operators (DSOs) to measure and analyze electrical quantities such [...] Read more.
Future distribution grids will be subjected to fluctuations in voltages and power flows due to the presence of renewable sources with intermittent power generation. The advanced smart metering infrastructure (AMI) enables the distribution system operators (DSOs) to measure and analyze electrical quantities such as voltages, currents and power at each customer connection point. Various smart grid applications can make use of the AMI data either in offline or close to real-time mode to assess the grid voltage conditions and estimate losses in the lines/cables. The outputs of these applications can enable DSOs to take corrective action and make a proper plan for grid upgrades. In this paper, the process of development and deployment of applications for improving the observability of distributions grids is described, which consists of the novel deployment framework that encompasses the proposition of data collection, communication to the servers, data storage, and data visualization. This paper discussed the development of two observability applications for grid monitoring and loss calculation, their validation in a laboratory setup, and their field deployment. A representative distribution grid in Denmark is chosen for the study using an OPAL-RT real-time simulator. The results of the experimental studies show that the proposed applications have high accuracy in estimating grid voltage magnitudes and active energy losses. Further, the field deployment of the applications prove that DSOs can gain insightful information about their grids and use them for planning purposes. Full article
(This article belongs to the Special Issue Communication and Data Management for Smart Grids)
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21 pages, 6518 KiB  
Article
Coordination of Macro Base Stations for 5G Network with User Clustering
by Kun Li, Xiaomeng Ai, Jiakun Fang, Bo Zhou, Lingling Le and Jinyu Wen
Sensors 2021, 21(16), 5501; https://doi.org/10.3390/s21165501 - 16 Aug 2021
Cited by 2 | Viewed by 2299
Abstract
With the increasing amounts of terminal equipment with higher requirements of communication quality in the emerging fifth generation mobile communication network (5G), the energy consumption of 5G base stations (BSs) is increasing significantly, which not only raises the operating expenses of telecom operators [...] Read more.
With the increasing amounts of terminal equipment with higher requirements of communication quality in the emerging fifth generation mobile communication network (5G), the energy consumption of 5G base stations (BSs) is increasing significantly, which not only raises the operating expenses of telecom operators but also imposes a burden on the environment. To solve this problem, a two-step energy management method that coordinates 5G macro BSs for 5G networks with user clustering is proposed. The coordination among the communication equipment and the standard equipment in 5G macro BSs is developed to reduce both the energy consumption and the electricity costs. A novel user clustering method is proposed together with Benders decomposition to accelerate the solving process. Simulation results show that the proposed method is computationally efficient and can ensure near-optimal performance, effectively reducing the energy consumption and electricity costs compared with the conventional dispatching scheme. Full article
(This article belongs to the Special Issue Communication and Data Management for Smart Grids)
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