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Sensing and Measurement for Advanced Power Grids
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Sensing and Measurement for Advanced Power Grids

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

Deadline for manuscript submissions: closed (31 January 2023) | Viewed by 12697

Special Issue Editors

Prof. Dr. Carmine Landi

E-Mail Website
Guest Editor
Department of Engineering, University of Campania “Luigi Vanvitelli”, 81031 Aversa (CE), Italy
Interests: measurement; instrumentation; power quality; real-time measurement; current and voltage transducers; digital signal processing; storage systems; smart metering
Special Issues, Collections and Topics in MDPI journals
Dr. Mario Luiso

E-Mail Website
Guest Editor
Department of Engineering, University of Campania “Luigi Vanvitelli”, 81031 Aversa, Italy
Interests: measurements; instrumentation; power quality; voltage and current instrument transformers; smart sensors for power grids; phasor measurement units (PMU)
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

As is well known, the driver for the implementation of future grids is the optimal integration of distributed generation, as well as distributed energy storage systems and demand-side management systems. These three technologies, usually grouped under the name of distributed energy resources (DER), constitute the base of advanced power grids. Advanced power grids can be seen as electrical power grids with fully integrated distributed energy resources (DER) that apply information, advanced networking, real-time monitoring, and control technologies to lower costs, save energy, and improve security, interoperability, and reliability.

Considering that most DER power, provided by wind power farm and large-scale photovoltaic generation systems, is intermittent and unpredictable, their impact on the power grid state and stability and on the quality of the transferred power requires being managed through large-scale, active, and real-time control systems, capable of operating under highly dynamic conditions. This necessitates considerable changes to sensing, timing, intelligence, modeling, and communication requirements in advanced grids. Therefore, the technology area of sensing and measurement is an essential component of advanced power grid systems.

Advanced sensing and measurement technologies must be able to acquire and transform data into information and enhance multiple aspects of power system management. These technologies will evaluate equipment health and the integrity of the grid. They will also help to relieve congestion and reduce emissions by enabling consumer choice and demand response and by supporting new control strategies.

Within this framework, Guest Editors are inviting experts to contribute to this Special Issue by submitting papers dealing with, but not limited to, the following research areas and their applications in sensing and measurement for advanced power grids:

  • Advanced current/voltage sensors for measurements and protection purposes, including low power instrument transformers (LPIT) with analog or digital output, and their characterization in actual operating conditions;
  • Power/energy measurement algorithms/methods and evaluation of uncertainty of the whole measurement chain (transducer, analog-to-digital conversion, digital signal processing) using digital instrumentation;
  • Power quality and synchrophasor measurements for grids with high penetration of power electronics;
  • Real-time grid state monitoring by using merging units or stand-alone merging units.

Prof. Dr. Carmine Landi
Dr. Mario Luiso
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.

Keywords

  • Electrical and electronic measurements 
  • Voltage and current instrument transformers and sensors 
  • Phasor measurement unit (PMU) 
  • Power system modeling 
  • Energy efficiency 
  • Power quality 
  • Energy storage 
  • Renewable energies 
  • Electronic power conversion 
  • Energy storage, renewable energies, and e-mobility

Published Papers (5 papers)

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Research

17 pages, 4166 KiB  
Article
FPGA-Based Smart Sensor to Detect Current Transformer Saturation during Inrush Current Measurement
by G. de J. Martínez-Figueroa, Felipe Córcoles-López and Santiago Bogarra
Sensors 2023, 23(2), 744; https://doi.org/10.3390/s23020744 - 09 Jan 2023
Cited by 1 | Viewed by 2435
Abstract
Current transformer saturation affects measurement accuracy and, consequently, protection reliability. One important concern in the case of overcurrent protections is the discrimination between faults and inrush current in power transformers. This paper presents an FPGA-based smart sensor to detect current transformer saturation, especially [...] Read more.
Current transformer saturation affects measurement accuracy and, consequently, protection reliability. One important concern in the case of overcurrent protections is the discrimination between faults and inrush current in power transformers. This paper presents an FPGA-based smart sensor to detect current transformer saturation, especially during inrush current conditions. Several methods have been proposed in the literature, but some are unsuitable for inrush currents due to their particular waveform. The proposed algorithm implemented on the smart sensor uses two time-domain features of the measured secondary current: the second-order difference function and the third-order statistic central moment. The proposed smart sensor presents high effectiveness and immunity against noise with accurate results in different conditions: different residual flux, resistive burdens, sampling frequency, and noise levels. The points at which saturation starts are detected with an accuracy of approximately 100%. Regarding the end of saturation, the proposed method detects the right ending points with a maximum error of a sample. The smart sensor has been tested on experimental online and real-time conditions (including an anti-aliasing filter) with accurate results. Unlike most existing methods, the proposed smart sensor operates efficiently during inrush conditions. The smart sensor presents high-speed processing despite its simplicity and low computational cost. Full article
(This article belongs to the Special Issue Sensing and Measurement for Advanced Power Grids)
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20 pages, 33877 KiB  
Article
How Instrument Transformers Influence Power Quality Measurements: A Proposal of Accuracy Verification Tests
by Gabriella Crotti, Yeying Chen, Huseyin Çayci, Giovanni D’Avanzo, Carmine Landi, Palma Sara Letizia, Mario Luiso, Enrico Mohns, Fabio Muñoz, Renata Styblikova and Helko van den Brom
Sensors 2022, 22(15), 5847; https://doi.org/10.3390/s22155847 - 04 Aug 2022
Cited by 12 | Viewed by 2397
Abstract
The integration of renewable energy sources on a large scale in the electrical energy distribution systems, as well as the widespread of non-linear loads, has led to a significant increase in power quality (PQ) disturbances. For this reason, PQ monitoring is also becoming [...] Read more.
The integration of renewable energy sources on a large scale in the electrical energy distribution systems, as well as the widespread of non-linear loads, has led to a significant increase in power quality (PQ) disturbances. For this reason, PQ monitoring is also becoming a key task in medium voltage (MV) grids. The measurement of PQ at MV levels can only be performed using instrument transformers (ITs) to scale down the level of voltage and current to levels suitable for the input stage of PQ instruments. However, no international standards currently require the verification of the errors introduced by ITs in the measurement of PQ phenomena. Moreover, this issue is only partially addressed in the scientific literature, where papers dealing with specific and limited aspects of the problem can be found. For this reason, this paper aims to comprehensively assess the issue, proposing IT accuracy verification tests for different PQ parameters. First, a set of PQ phenomena relevant for IT testing is chosen, as well as the associated ranges of variation, based on a review of the enforced standards and the scientific literature. For each selected PQ phenomenon, possible performance indices and test waveforms are proposed. Finally, the proposed procedure is validated by applying it to the characterization of two different types of commercial voltage transformers. Full article
(This article belongs to the Special Issue Sensing and Measurement for Advanced Power Grids)
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23 pages, 1851 KiB  
Article
GrAb: A Deep Learning-Based Data-Driven Analytics Scheme for Energy Theft Detection
by Sudeep Tanwar, Aparna Kumari, Darshan Vekaria, Maria Simona Raboaca, Fayez Alqahtani, Amr Tolba, Bogdan-Constantin Neagu and Ravi Sharma
Sensors 2022, 22(11), 4048; https://doi.org/10.3390/s22114048 - 26 May 2022
Cited by 10 | Viewed by 2232
Abstract
Integrating information and communication technology (ICT) and energy grid infrastructures introduces smart grids (SG) to simplify energy generation, transmission, and distribution. The ICT is embedded in selected parts of the grid network, which partially deploys SG and raises various issues such as energy [...] Read more.
Integrating information and communication technology (ICT) and energy grid infrastructures introduces smart grids (SG) to simplify energy generation, transmission, and distribution. The ICT is embedded in selected parts of the grid network, which partially deploys SG and raises various issues such as energy losses, either technical or non-technical (i.e., energy theft). Therefore, energy theft detection plays a crucial role in reducing the energy generation burden on the SG and meeting the consumer demand for energy. Motivated by these facts, in this paper, we propose a deep learning (DL)-based energy theft detection scheme, referred to as GrAb, which uses a data-driven analytics approach. GrAb uses a DL-based long short-term memory (LSTM) model to predict the energy consumption using smart meter data. Then, a threshold calculator is used to calculate the energy consumption. Both the predicted energy consumption and the threshold value are passed to the support vector machine (SVM)-based classifier to categorize the energy losses into technical, non-technical (energy theft), and normal consumption. The proposed data-driven theft detection scheme identifies various forms of energy theft (e.g., smart meter data manipulation or clandestine connections). Experimental results show that the proposed scheme (GrAb) identifies energy theft more accurately compared to the state-of-the-art approaches. Full article
(This article belongs to the Special Issue Sensing and Measurement for Advanced Power Grids)
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29 pages, 9374 KiB  
Article
The Vulnerability of the Power Grid Structure: A System Analysis Based on Complex Network Theory
by Banghua Xie, Xiaoge Tian, Liulin Kong and Weiming Chen
Sensors 2021, 21(21), 7097; https://doi.org/10.3390/s21217097 - 26 Oct 2021
Cited by 9 | Viewed by 2488
Abstract
The safety and reliability of the power grid are related to national power security, economic development and people’s daily life. The occurrence of extreme weather changes the external environment greatly. Including generators and transmission lines, many power grid units cannot resist such a [...] Read more.
The safety and reliability of the power grid are related to national power security, economic development and people’s daily life. The occurrence of extreme weather changes the external environment greatly. Including generators and transmission lines, many power grid units cannot resist such a huge attack and get damaged easily, which forces units to quit from the power grid running system for a while. Furthermore, if the number of influenced units is high enough, the whole power system will be destroyed by cascading failure caused by extreme weather. Aiming at dealing with the cascading failure emergencies, this paper is trying to improve the traditional power structural vulnerability model so that it can be used to discuss extreme weather and propose a theoretical topological model to help scholars measure the damage caused by extreme cases. Based on previous research in this field, this paper utilizes complex network knowledge to build the power grid topology model. Then, considering extreme cases and the three attack modes simulation process, this paper makes use of the characteristic parameters of the power grid topology model and designs an algorithm, according to the realistic situation of the propagation mechanism of cascading failure of the power grid model as well as extreme weather research. Finally, taking IEEE-30 and IEEE-118 node bus system as examples, which shows that the structural vulnerability method proposed in this paper can properly address the mechanism of unbalanced load of cascading failure of power grid units under extreme conditions and can provide theoretical reference for preventing and reducing the impact of extreme cases on power grid which improves the reliability of the power grid. Full article
(This article belongs to the Special Issue Sensing and Measurement for Advanced Power Grids)
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12 pages, 2249 KiB  
Communication
An Approach to Steady-State Power Transformer Modeling Considering Direct Current Resistance Test Measurements
by Henrique Pires Corrêa and Flávio Henrique Teles Vieira
Sensors 2021, 21(18), 6284; https://doi.org/10.3390/s21186284 - 19 Sep 2021
Cited by 4 | Viewed by 1910
Abstract
Measurements obtained in transformer tests are routinely used for computing associated steady-state model parameters, which can then be used for load flow simulation and other modeling applications. The short circuit and open circuit tests are most commonly performed with this purpose, allowing estimation [...] Read more.
Measurements obtained in transformer tests are routinely used for computing associated steady-state model parameters, which can then be used for load flow simulation and other modeling applications. The short circuit and open circuit tests are most commonly performed with this purpose, allowing estimation of series and parallel branch transformer parameters. In this study, an extended model is proposed which does not employ the usually assumed cantilever circuit approximation and explicitly accounts for transformer connection resistance. An estimation of the proposed model parameters is enabled by usage of additional measurements yielded by the direct current (DC) resistance test. The proposed approach is validated by means of an experiment carried out on a real distribution power transformer, whose results demonstrate that the proposed model and parameter computation approach effectively decompose total transformer resistance into winding and contact components. Furthermore, the numerical results show that contact resistance is not negligible especially for low voltage windings, which reinforces the usefulness of the proposed model in providing detailed modeling of transformer resistances. Full article
(This article belongs to the Special Issue Sensing and Measurement for Advanced Power Grids)
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