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Special Issue "Analysis for Power Quality Monitoring"

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "Electrical Power and Energy System".

Deadline for manuscript submissions: 30 September 2019

Special Issue Editors

Guest Editor
Prof. Dr. Juan-José González de la Rosa

Research Group PAIDI-TIC-168: Computational Instrumentation and Industrial Electronics. Department of Automation Engineering, Electronics, Architecture and Computer Networks, University of Cádiz, Spain
Website | E-Mail
Phone: +34-956-028069
Interests: Power quality; smart instruments; electronic instrumentation; higher-order statistics; non-destructive testing
Guest Editor
Prof. Manuel Pérez Donsión

Department of Computer Sciences, University of Vigo
Website | E-Mail
Interests: power quality; renewable energy resources; energy management systems

Special Issue Information

Dear Colleagues,

The Guest Editor is inviting submissions for this Special Issue of Energies on the subject area of “Analysis for Power Quality Monitoring".

Power Quality (PQ) analysis is evolving continuously mainly due to the incessant growth and development of the smart grid, and the incipient Industry 4.0 which demands quick and accurate tracking of supply dynamics. At first instance, we found structural issues, with numerous distributed energy resources and loads, whose highly fluctuating demands alter the ideal power delivery conditions. Then we had to consider the huge amount of data (big data), generated by the measurement equipment deployed during the monitoring campaigns. Data are usually difficult to interpret and manage for different reasons, for example, complex structures and communication protocols that hinder accessibility to storage units, and the limited options of monitoring equipment, based on regulations that do not reflect the current operation.

A bad PQ can have serious consequences from an economic, human or technological point of view. Indeed, more and more works demand customer-oriented PQ assessment and measurement equipment; an issue that leads inexorably to the concept of temporal and spatial scalability. Differences in load sensitivity demand certain contractual conditions, introducing thresholds that allow claiming against eventual contractual breaches. Certainly, domestic easy-to-handle instruments should incorporate elements of indication and visualization that do not require too much technical knowledge. Also, companies demand ad hoc PQ assessment. Industry research benchmarking reports would allow performance comparison of PQ metrics; hence, quantifying losses and the proposal of compensation strategies are key factors. The benefits on human safety and equipment life are also obvious.

All in all, this Special Issue aims to gather research papers and reviews dealing with the latest advances in PQ analysis, comprising ad hoc signal processing techniques, artificial intelligence and soft computing, big data analytics and cloud computing for the smart grid, development of new PQ indices, monitoring with newly PQ graphical representations, and their practical implementation in measurement equipment. As a novelty, this issue also pays special attention to the human, technological and financial consequences of a bad PQ, welcoming economic and techno–economic works focussing on losses and the financial effects of PQ mitigation plans. Topics of interest for publication include, but are not limited to:

  • Power quality and reliability,
  • Statistical signal processing applied to PQ,
  • Intelligent methods for PQ analysis,
  • PQ indices and thresholds,
  • Customized PQ for utilities, customers and specific areas,
  • Big data in the smart grid: compression and temporal scalability,
  • Modelling and forecasting of PQ time-series,
  • PQ monitoring systems: architectures and communications,
  • New tendencies in smart instruments for PQ,
  • Sensors networks for PQ monitoring,
  • Graphical visualization of PQ,
  • PQ losses assessment and mitigation,
  • Economic impact of bad PQ losses,
  • PQ maintenance strategies in networks,
  • Industry research benchmark reports on PQ metrics,
  • Prospective introduction of new PQ monitoring norms and standards.

Prof. Dr. Juan-José González de la Rosa
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 papers will be 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 1800 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

  • power quality (PQ) and reliability monitoring systems
  • statistical signal processing
  • intelligent methods for PQ analysis
  • PQ indices and thresholds
  • customized PQ for utilities and customers
  • big data in the smart grid: temporal and space compression and scalability
  • graphical PQ
  • PQ mitigation
  • PQ losses assessment
  • economic impact of bad PQ losses
  • PQ maintenance strategies in networks
  • new tendencies in smart instruments for PQ
  • PQ norms

Published Papers (3 papers)

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Research

Open AccessArticle Application of Spectral Kurtosis to Characterize Amplitude Variability in Power Systems’ Harmonics
Energies 2019, 12(1), 194; https://doi.org/10.3390/en12010194
Received: 30 November 2018 / Revised: 31 December 2018 / Accepted: 2 January 2019 / Published: 8 January 2019
PDF Full-text (2022 KB) | HTML Full-text | XML Full-text
Abstract
The highly-changing concept of Power Quality (PQ) needs to be continuously reformulated due to the new schemas of the power grid or Smart Grid (SG). In general, the spectral content is characterized by their averaged or extreme values. However, new PQ events may [...] Read more.
The highly-changing concept of Power Quality (PQ) needs to be continuously reformulated due to the new schemas of the power grid or Smart Grid (SG). In general, the spectral content is characterized by their averaged or extreme values. However, new PQ events may consist of large variations in amplitude that occur in a short time or small variations in amplitude that take place continuously. Thus, the former second-order techniques are not suitable to monitor the dynamics of the power spectrum. In this work, a strategy based on Spectral Kurtosis (SK) is introduced to detect frequency components with a constant amplitude trend, which accounts for amplitude values’ dispersion related to the mean value of that spectral component. SK has been proven to measure frequency components that follow a constant amplitude trend. Two practical real-life cases have been considered: electric current time-series from an arc furnace and the power grid voltage supply. Both cases confirm that the more concentrated the amplitude values are around the mean value, the lower the SK values are. All this confirms SK as an effective tool for evaluating frequency components with a constant amplitude trend, being able to provide information beyond maximum variation around the mean value and giving a progressive index of value dispersion around the mean amplitude value, for each frequency component. Full article
(This article belongs to the Special Issue Analysis for Power Quality Monitoring)
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Open AccessArticle Reliability Monitoring Based on Higher-Order Statistics: A Scalable Proposal for the Smart Grid
Energies 2019, 12(1), 55; https://doi.org/10.3390/en12010055
Received: 18 November 2018 / Revised: 14 December 2018 / Accepted: 20 December 2018 / Published: 25 December 2018
PDF Full-text (1374 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
The increasing development of the smart grid demands reliable monitoring of the power quality at different levels, introducing more and more measurement points. In this framework, the advanced metering infrastructure must deal with this large amount of data, storage capabilities, improving visualization, and [...] Read more.
The increasing development of the smart grid demands reliable monitoring of the power quality at different levels, introducing more and more measurement points. In this framework, the advanced metering infrastructure must deal with this large amount of data, storage capabilities, improving visualization, and introducing customer-oriented interfaces. This work proposes a method that optimizes the smart grid data, monitoring the real voltage supplied based on higher order statistics. The method proposes monitoring the network from a scalable point of view and offers a two-fold perspective based on the duality utility-prosumer as a function of the measurement time. A global PQ index and 2D graphs are introduced in order to compress the time domain information and quantify the deviations of the waveform shape by means of three parameters. Time-scalability allows two extra features: long-term supply reliability and power quality in the short term. As a case study, the work illustrates a real-life monitoring in a building connection point, offering 2D diagrams, which show time and space compression capabilities, as well. Full article
(This article belongs to the Special Issue Analysis for Power Quality Monitoring)
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Open AccessArticle An Extended Kalman Filter Approach for Accurate Instantaneous Dynamic Phasor Estimation
Energies 2018, 11(11), 2918; https://doi.org/10.3390/en11112918
Received: 4 October 2018 / Revised: 18 October 2018 / Accepted: 23 October 2018 / Published: 26 October 2018
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Abstract
This paper proposes the application of a non-linear Extended Kalman Filter (EKF) for accurate instantaneous dynamic phasor estimation. An EKF-based algorithm is proposed to better adapt to the dynamic measurement requirements and to provide real-time tracking of the fundamental harmonic components and power [...] Read more.
This paper proposes the application of a non-linear Extended Kalman Filter (EKF) for accurate instantaneous dynamic phasor estimation. An EKF-based algorithm is proposed to better adapt to the dynamic measurement requirements and to provide real-time tracking of the fundamental harmonic components and power system frequencies. This method is evaluated using dynamic compliance tests defined in the IEEE C37.118.1-2011 synchrophasor measurement standard, providing promising results in phasor and frequency estimation, compliant with the accuracy required in the case of off-nominal frequency, amplitude and phase angle modulations, frequency ramps, and step changes in magnitude and phase angle. An important additional feature of the method is its capability for real-time detection of transient disturbances in voltage or current waveforms using the residual of the filter, which enables flagging of the estimation for suitable processing. Full article
(This article belongs to the Special Issue Analysis for Power Quality Monitoring)
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