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Energies
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Monitoring and Automation of Complex Power Systems
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Monitoring and Automation of Complex Power Systems

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "F: Electrical Engineering".

Deadline for manuscript submissions: closed (20 August 2021) | Viewed by 16748

Special Issue Editors

Dr. Marco Pau

E-Mail Website
Guest Editor
Department of Grid Planning and Grid Operation, Fraunhofer IEE, 34121 Kassel, Germany
Interests: design of measurement systems for monitoring and management of active distribution systems; development of solutions for distribution grid automation; power system state estimation; distribution networks; power system measurement; power grids; mathematical analysis; demand-side management; smart meters; distributed power generation; fault location; measurement uncertainty; power engineering computing; AC–DC power converters; Internet of Things; Kalman filters
Special Issues, Collections and Topics in MDPI journals
Dr. Paolo Attilio Pegoraro

E-Mail Website
Guest Editor
Department of Electrical and Electronic Engineering, University of Cagliari, 09123 Cagliari, Italy
Interests: new measurement techniques; measurement uncertainty and propagation analysis; measurements for modern power networks; synchronized instruments; distributed measurement systems; power system state estimation; compressive sensing methods
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Electric power systems are evolving into increasingly complex systems, which require advanced monitoring and automation to achieve the desired targets of efficiency, security, and reliability. The automation chain integrates a set of different components, such as sensors and measurements, communication infrastructure, information technologies, energy management systems, and advanced control algorithms, which are all critical for the design of the overall automation solution. The system architecture that is used also has a key impact on the achievable reliability and scalability.

During the last several years, phasor measurement units and synchronized measurement systems have been being deployed to track the dynamic conditions of the grid and to enable new control applications. Modern ICT technologies are being integrated into innovative approaches to extend the functionalities of traditional automation schemes. Future energy management systems will rely more and more on the use of cloud-based technologies and Internet of Things concepts, while the roll-out of 5G communication will unlock new possibilities for highly distributed applications, thanks to low latency, network slicing, and edge cloud availability.

The aim of this Special Issue is to collect research articles presenting innovative views and solutions for the monitoring and automation of transmission and distribution grids. Topics of interest include both the analysis of specific components of the automation chain and higher-level perspectives on platforms and system architectures. Contributions discussing issues, solutions, and practical experience from field deployments or pilot demonstrations are also more than welcome.

Dr. Marco Pau
Prof. Dr. Paolo Attilio Pegoraro
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. Energies 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

  • Grid monitoring
  • Phasor measurement units
  • Self-healing systems
  • Advanced control methods
  • Distribution system automation
  • Energy management systems
  • Advanced metering infrastructure
  • Cloud-based architectures
  • IoT platform
  • ICT for energy
  • 5G and edge cloud
  • Substation automation

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Published Papers (6 papers)

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Editorial

Jump to: Research

3 pages, 152 KiB  
Editorial
Monitoring and Automation of Complex Power Systems
by Marco Pau and Paolo Attilio Pegoraro
Energies 2022, 15(8), 2949; https://doi.org/10.3390/en15082949 - 18 Apr 2022
Viewed by 1561
Abstract
This Special Issue aims at collecting new research contributions and perspectives on the topic of the monitoring and automation of modern power systems [...] Full article
(This article belongs to the Special Issue Monitoring and Automation of Complex Power Systems)

Research

Jump to: Editorial

19 pages, 2395 KiB  
Article
Multi-Objective Electrical Power System Design Optimization Using a Modified Bat Algorithm
by Khaled Guerraiche, Latifa Dekhici, Eric Chatelet and Abdelkader Zeblah
Energies 2021, 14(13), 3956; https://doi.org/10.3390/en14133956 - 1 Jul 2021
Cited by 12 | Viewed by 2370
Abstract
The design of energy systems is very important in order to reduce operating costs and guarantee the reliability of a system. This paper proposes a new algorithm to solve the design problem of optimal multi-objective redundancy of series-parallel power systems. The chosen algorithm [...] Read more.
The design of energy systems is very important in order to reduce operating costs and guarantee the reliability of a system. This paper proposes a new algorithm to solve the design problem of optimal multi-objective redundancy of series-parallel power systems. The chosen algorithm is based on the hybridization of two metaheuristics, which are the bat algorithm (BA) and the generalized evolutionary walk algorithm (GEWA), also called BAG (bat algorithm with generalized flight). The approach is combined with the Ushakov method, the universal moment generating function (UMGF), to evaluate the reliability of the multi-state series-parallel system. The multi-objective design aims to minimize the design cost, and to maximize the reliability and the performance of the electric power generation system from solar and gas generators by taking into account the reliability indices. Power subsystem devices are labeled according to their reliabilities, costs and performances. Reliability hangs on an operational system, and implies likewise satisfying customer demand, so it depends on the amassed batch curve. Two different design allocation problems, commonly found in power systems planning, are solved to show the performance of the algorithm. The first is a bi-objective formulation that corresponds to the minimization of system investment cost and maximization of system availability. In the second, the multi-objective formulation seeks to maximize system availability, minimize system investment cost, and maximize the capacity of the system. Full article
(This article belongs to the Special Issue Monitoring and Automation of Complex Power Systems)
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13 pages, 4312 KiB  
Article
Multi-Area Distribution System State Estimation Using Decentralized Physics-Aware Neural Networks
by Minh-Quan Tran, Ahmed S. Zamzam, Phuong H. Nguyen and Guus Pemen
Energies 2021, 14(11), 3025; https://doi.org/10.3390/en14113025 - 24 May 2021
Cited by 17 | Viewed by 2817
Abstract
The development of active distribution grids requires more accurate and lower computational cost state estimation. In this paper, the authors investigate a decentralized learning-based distribution system state estimation (DSSE) approach for large distribution grids. The proposed approach decomposes the feeder-level DSSE into subarea-level [...] Read more.
The development of active distribution grids requires more accurate and lower computational cost state estimation. In this paper, the authors investigate a decentralized learning-based distribution system state estimation (DSSE) approach for large distribution grids. The proposed approach decomposes the feeder-level DSSE into subarea-level estimation problems that can be solved independently. The proposed method is decentralized pruned physics-aware neural network (D-P2N2). The physical grid topology is used to parsimoniously design the connections between different hidden layers of the D-P2N2. Monte Carlo simulations based on one-year of load consumption data collected from smart meters for a three-phase distribution system power flow are developed to generate the measurement and voltage state data. The IEEE 123-node system is selected as the test network to benchmark the proposed algorithm against the classic weighted least squares and state-of-the-art learning-based DSSE approaches. Numerical results show that the D-P2N2 outperforms the state-of-the-art methods in terms of estimation accuracy and computational efficiency. Full article
(This article belongs to the Special Issue Monitoring and Automation of Complex Power Systems)
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23 pages, 2794 KiB  
Article
Characterization Procedure for Stand-Alone Merging Units Based on Hardware-in-the-Loop Technology
by Alessandro Mingotti, Federica Costa, Lorenzo Peretto and Roberto Tinarelli
Energies 2021, 14(7), 1993; https://doi.org/10.3390/en14071993 - 4 Apr 2021
Cited by 1 | Viewed by 3204
Abstract
The digitalization of a medium voltage network requires huge efforts from distributed system operators and electric utilities. The main reason is attributed to the costs associated with the replacement or introduction of new intelligent electronic devices capable of collecting and digitalizing current and [...] Read more.
The digitalization of a medium voltage network requires huge efforts from distributed system operators and electric utilities. The main reason is attributed to the costs associated with the replacement or introduction of new intelligent electronic devices capable of collecting and digitalizing current and voltage measurements. To this purpose, this paper introduces a new idea of a stand-alone merging unit (SAMU), which features real-time and hardware-in-the-loop technology, completed with accurate voltage and current sensors. Furthermore, the characterization procedure that allows an evaluation of the metrological performance of a complex device, such as a SAMU, is fully described. From the results, it is highlighted that (i) the developed SAMU is capable of performing highly accurate voltage, current, and power measurements; (ii) the characterization procedure is simple and exploitable for all kinds of SAMUs and other synchronized measurement devices. Full article
(This article belongs to the Special Issue Monitoring and Automation of Complex Power Systems)
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16 pages, 2939 KiB  
Article
Extended SINDICOMP: Characterizing MV Voltage Transformers with Sine Waves
by Gabriella Crotti, Giovanni D’Avanzo, Domenico Giordano, Palma Sara Letizia and Mario Luiso
Energies 2021, 14(6), 1715; https://doi.org/10.3390/en14061715 - 19 Mar 2021
Cited by 18 | Viewed by 2630
Abstract
The paper presents a method for the frequency characterization of voltage transformers (VTs) for medium voltage (MV) grids which involves only sine waves. It is called extended SINDICOMP, since it is an extended version of the previously developed technique SINDICOMP. It requires, in [...] Read more.
The paper presents a method for the frequency characterization of voltage transformers (VTs) for medium voltage (MV) grids which involves only sine waves. It is called extended SINDICOMP, since it is an extended version of the previously developed technique SINDICOMP. It requires, in the first step, an evaluation and a compensation of the non-linearity introduced by the VT when it is supplied with a 50 Hz sinusoidal input at rated value. Then, the VT is characterized with a low voltage sinusoidal frequency sweep from the second harmonic frequency up to the first resonance frequency. Some rules to build the approximated frequency response, starting from these two sets of data, are given in the paper. The proposed approach is applied to three commercial MV VTs. Significant improvement of the VT performance is obtained, compared to the use of a frequency response obtained from the low voltage characterization. Full article
(This article belongs to the Special Issue Monitoring and Automation of Complex Power Systems)
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25 pages, 1165 KiB  
Article
A Distribution System State Estimator Based on an Extended Kalman Filter Enhanced with a Prior Evaluation of Power Injections at Unmonitored Buses
by David Macii, Daniele Fontanelli and Grazia Barchi
Energies 2020, 13(22), 6054; https://doi.org/10.3390/en13226054 - 19 Nov 2020
Cited by 12 | Viewed by 2852
Abstract
In the context of smart grids, Distribution Systems State Estimation (DSSE) is notoriously problematic because of the scarcity of available measurement points and the lack of real-time information on loads. The scarcity of measurement data influences on the effectiveness and applicability of dynamic [...] Read more.
In the context of smart grids, Distribution Systems State Estimation (DSSE) is notoriously problematic because of the scarcity of available measurement points and the lack of real-time information on loads. The scarcity of measurement data influences on the effectiveness and applicability of dynamic estimators like the Kalman filters. However, if an Extended Kalman Filter (EKF) resulting from the linearization of the power flow equations is complemented by an ancillary prior least-squares estimation of the weekly active and reactive power injection variations at all buses, significant performance improvements can be achieved. Extensive simulation results obtained assuming to deploy an increasing number of next-generation smart meters and Phasor Measurement Units (PMUs) show that not only the proposed approach is generally more accurate and precise than the classic Weighted Least Squares (WLS) estimator (chosen as a benchmark algorithm), but it is also less sensitive to both the number and the metrological features of the PMUs. Thus, low-uncertainty state estimates can be obtained even though fewer and cheaper measurement devices are used. Full article
(This article belongs to the Special Issue Monitoring and Automation of Complex Power Systems)
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