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Application of Digital Signal Processing Methods to Electric Power Systems

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

Deadline for manuscript submissions: closed (29 October 2021) | Viewed by 11170

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Special Issue Editor

Dr. Marco Faifer

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Guest Editor

Dipartimento di Elettronica, Informazione e Bioingegneria (DEIB), Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133 Milan, Italy
Interests: measurements; digital signal processing; voltage and current transducers; electric device characterization; diagnostic of electric device; PV systems characterization

Special Issue Information

Dear Colleagues,

It is my pleasure to invite submissions to a Special Issue of the journal Energies on the topic of “Application of Digital Signal Processing Methods to Electric Power Systems”.

The modern power system is evolving toward a more and more complex system. Its control and proper management requires the application of efficient techniques at any layers of the network, from the single component of the network to the management processes. In particular, the application of digital signal processing techniques yields an improvement in the performance of devices and systems based on standard hardware through the addition of computational capability. The enhancement can be both in terms of improvement of the basic functionality of the device/system and of additional functions aimed at improving the overall performance of power systems. In order to achieve these goals, proper modeling of the devices/systems should be attained, thus allowing to develop optimized algorithms tailored to the specific application.

With this Special Issue, we would like to encourage original contributions regarding recent developments and ideas in application of digital signal processing in power systems. Potential topics include but are not limited to transducer enhancement, protection device enhancement, power quality, monitoring, diagnostics, reliability, maintenance, microgrids, and smart development.

Prof. Dr. Marco Faifer
Guest Editor

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

Digital signal processing
Instrument transformers
Diagnostic
Reliability
Monitoring systems
Power quality (PQ)
Smart grid
Microgrids
Power system

Published Papers (4 papers)

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Research

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16 pages, 2806 KiB

Open AccessArticle

Design of a Stationary Energy Recovery System in Rail Transport

by Giuliano Cipolletta, Antonio Delle Femine, Daniele Gallo, Mario Luiso and Carmine Landi

Energies 2021, 14(9), 2560; https://0-doi-org.brum.beds.ac.uk/10.3390/en14092560 - 29 Apr 2021

Cited by 18 | Viewed by 2339

Abstract

Although rail is one of the most sustainable transport systems, there is still room to reduce its energy demand. In particular, during the braking of DC powered trains, a significant amount of energy is wasted. The recent developments in energy storage system technologies, combined with the widely used technique of regenerative braking, can considerably increase energy saving. This paper explores this theme, quantifying the amount of braking energy that can be potentially recovered in a real case study, starting from the experimental data measured on-board train. A simplified numerical model of the recovery process has been implemented. Adopting it, the energy that can be saved, with one or two energy storage systems, has been quantified for each possible position along the track. The procedure allows to determine the optimal position. Further findings about the impact of voltage level on the efficiency of the recovery process have been reported. The optimal level of voltage has been determined, also considering the additional losses in the catenary, both during the traction and braking phase of the train. Moreover, it allows dimensioning of stationary storage systems considering two different energy management strategies and their impact on the peak of stored energy. The proposed approach will be presented with reference to the concrete case of a specific route on the Italian rail network, analyzing a train in normal commuter service and the obtained results will be discussed. In the best situation, about the 73% of the braking energy can be recovered. Full article

(This article belongs to the Special Issue Application of Digital Signal Processing Methods to Electric Power Systems)

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17 pages, 3389 KiB

Open AccessArticle

A Novel Algorithm for Fast DC Electric Arc Detection

by Michał Dołęgowski and Mirosław Szmajda

Energies 2021, 14(2), 288; https://0-doi-org.brum.beds.ac.uk/10.3390/en14020288 - 7 Jan 2021

Cited by 7 | Viewed by 2858

Abstract

Electric arcing is a common problem in DC power systems. To overcome this problem, the electric arc detection algorithm has been developed as a faster alternative to existing algorithms. The following issues are addressed in this paper: The calculation of the proposed algorithm of incremental decomposition of the signal over time; the computational complexity of Fast Fourier Transform (FFT) and the incremental decomposition; the test bench used to measure electric arcs at given parameters; the analysis of measurements using FFT; and the analysis of measurements using incremental decomposition. The parameters are the DC voltage, electric load, and width of the gap between electrodes. The results showed that the proposed algorithm allows for a faster calculation—about seven times faster than FFT—and cheaper implementation in electric arc detection devices than FFT. Full article

(This article belongs to the Special Issue Application of Digital Signal Processing Methods to Electric Power Systems)

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15 pages, 734 KiB

Open AccessFeature PaperArticle

Phasor Estimation for Grid Power Monitoring: Least Square vs. Linear Kalman Filter

by Yassine Amirat, Zakarya Oubrahim, Hafiz Ahmed, Mohamed Benbouzid and Tianzhen Wang

Energies 2020, 13(10), 2456; https://0-doi-org.brum.beds.ac.uk/10.3390/en13102456 - 13 May 2020

Cited by 21 | Viewed by 2780

Abstract

This paper deals with a comparative study of two phasor estimators based on the least square (LS) and the linear Kalman filter (KF) methods, while assuming that the fundamental frequency is unknown. To solve this issue, the maximum likelihood technique is used with an iterative Newton–Raphson-based algorithm that allows minimizing the likelihood function. Both least square (LSE) and Kalman filter estimators (KFE) are evaluated using simulated and real power system events data. The obtained results clearly show that the LS-based technique yields the highest statistical performance and has a lower computation complexity. Full article

(This article belongs to the Special Issue Application of Digital Signal Processing Methods to Electric Power Systems)

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Other

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16 pages, 7525 KiB

Open AccessBrief Report

Low Frequency Injection as a Method of Low-Level DC Microgrid Communication

by Matthew Davidson and Andrea Benigni

Energies 2020, 13(10), 2452; https://0-doi-org.brum.beds.ac.uk/10.3390/en13102452 - 13 May 2020

Viewed by 1977

Abstract

This paper provides a simple low-level unidirectional global communication method for DC microgrids, and requires no hardware modifications to the microgrid and interfacing power electronic converters. The underlying premise to this communication method is injecting low-frequency low-voltage sinusoidal components into the DC microgrid power lines. This method deviates from the common bit-level communication scheme by relating parameters and commands with certain frequency components. Communication structures are included as a basis for communication protocols, and a detection method is proposed for detecting the injected frequencies. The injection method, communication structure, and detection method are implemented on a live-scale DC microgrid. Full article

(This article belongs to the Special Issue Application of Digital Signal Processing Methods to Electric Power Systems)

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