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Analysis for Power Quality Monitoring

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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 (30 September 2019) | Viewed by 48022

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Special Issue Editors

Dr. Juan-José González de la Rosa

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Guest Editor

Department of Automation Engineering, Electronics, Architecture and Computer Networks, University of Cádiz, Cádiz, Spain
Interests: power quality; big data; smart instruments; computational intelligence for measurement systems; electronic instrumentation; higher-order statistics; non-destructive testing; statistical signal processing
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Manuel Pérez Donsión

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Guest Editor

Department of Computer Sciences, University of Vigo, Vigo, Pontevedra, Spain
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

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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

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Published Papers (12 papers)

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Editorial

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6 pages, 203 KiB

Open AccessEditorial

Special Issue “Analysis for Power Quality Monitoring”

by Juan-José González de-la-Rosa and Manuel Pérez-Donsión

Energies 2020, 13(3), 514; https://doi.org/10.3390/en13030514 - 21 Jan 2020

Cited by 9 | Viewed by 2226

Abstract

We are immersed in the so-called digital energy network, continuously introducing new technological advances for a better way of life. As a consequence, numerous emerging words are relevant to this point: Internet of Things (IoT), big data, smart cities, smart grid, industry 4.0, etc. To achieve this formidable goal, systems should work more efficiently, a fact that inevitably leads to power quality (PQ) assurance. Apart from its economic losses, a bad PQ implies serious risks for machines and, consequently, for people. Many researchers are endeavouring to develop new analysis techniques, instruments, measurement methods, and new indices and norms that match and fulfil the requirements regarding the current operation of the electrical network. This book, and its associated Special Issue, offer a compilation of some of the recent advances in this field. The chapters range from computing to technological implementation, going through event detection strategies and new indices and measurement methods that contribute significantly to the advance of PQ analysis and regulation. Experiments have been developed within the frameworks of research units and projects and deal with real data from industry practice and public buildings. Human beings have an unavoidable commitment to sustainability, which implies adapting PQ monitoring techniques to our dynamic world, defining a digital and smart concept of quality for electricity. Full article

(This article belongs to the Special Issue Analysis for Power Quality Monitoring)

Research

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25 pages, 3986 KiB

Open AccessArticle

Analysis of Dense-Mesh Distribution Network Operation Using Long-Term Monitoring Data

by Michal Ptacek, Vaclav Vycital, Petr Toman and Jan Vaculik

Energies 2019, 12(22), 4342; https://doi.org/10.3390/en12224342 - 14 Nov 2019

Cited by 5 | Viewed by 3559

Abstract

The technical and economic aspects and the possibility of the mesh network topology offering many radial configurations lead to the fact that large municipal networks are generally under radial operation. However, it is very important to analyze the operation and control of the mesh networks, especially in terms of their safety and durability and in the frame of the smart grid concept, respectively. The article deals with the analysis of the operation of the dense-mesh municipal distribution network of E.ON Distribuce a.s. based on the long-term data from power quality monitors. It also shows a brief view of the current lack of data usability from monitors installed in distribution networks in the context of smart grid. Full article

(This article belongs to the Special Issue Analysis for Power Quality Monitoring)

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14 pages, 2533 KiB

Open AccessArticle

PMU’s Behavior with Flicker-Generating Voltage Fluctuations: An Experimental Analysis

by Paolo Castello, Carlo Muscas, Paolo Attilio Pegoraro and Sara Sulis

Energies 2019, 12(17), 3355; https://doi.org/10.3390/en12173355 - 30 Aug 2019

Cited by 11 | Viewed by 2645

Abstract

Phasor measurement units (PMUs), which are the key components of a synchrophasor-based wide area monitoring system (WAMS), were historically conceived for transmission networks. The current trend to extend the benefits of the synchrophasor technology to distribution networks requires the PMU to also provide trustworthy information in the presence of signals that can occur in a typical distribution grid, including the presence of severe power quality (PQ) issues. In this framework, this paper experimentally investigates the performance of PMUs in the presence of one of the most important PQ phenomena, namely the presence of voltage fluctuations that generate the disturbance commonly known as flicker. The experimental tests are based on an ad-hoc high-accuracy measurement setup, where the devices under test are considered as “black boxes” to be characterized in the presence of the relevant signals. Two simple indices are introduced for the comparison among the different tested PMUs. The results of the investigation highlight possible critical situations in the interpretation of the measured values and provide a support for both the design of a new generation of PMUs and the possible development of an updated synchrophasor standard targeted to distribution systems. Full article

(This article belongs to the Special Issue Analysis for Power Quality Monitoring)

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21 pages, 3754 KiB

Open AccessArticle

Power Quality Disturbances Assessment during Unintentional Islanding Scenarios. A Contribution to Voltage Sag Studies

by Alexandre Serrano-Fontova, Pablo Casals Torrens and Ricard Bosch

Energies 2019, 12(16), 3198; https://doi.org/10.3390/en12163198 - 20 Aug 2019

Cited by 20 | Viewed by 3619

Abstract

This paper presents a novel voltage sag topology that occurs during an unintentional islanding operation (IO) within a distribution network (DN) due to large induction motors (IMs). When a fault occurs, following the circuit breaker (CB) fault clearing, transiently, the IMs act as generators due to their remanent kinetic energy until the CB reclosing takes place. This paper primarily contributes to voltage sag characterization. Therefore, this novel topology is presented, analytically modelled and further validated. It is worth mentioning that this voltage sag has been identified in a real DN in which events have been recorded for two years. The model validation of the proposed voltage sag is done via digital simulations with a model of the real DN implemented in Matlab considering a wide range of scenarios. Both simulations and field measurements confirm the voltage sag analytical expression presented in this paper as well as exhibiting the high accuracy achieved in the three-phase model adopted. Full article

(This article belongs to the Special Issue Analysis for Power Quality Monitoring)

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18 pages, 6470 KiB

Open AccessArticle

A Memory-Efficient True-RMS Estimator in a Limited-Resources Hardware

by Jose-Maria Flores-Arias, Manuel Ortiz-Lopez, Francisco J. Quiles Latorre, Francisco Jose Bellido-Outeiriño and Antonio Moreno-Muñoz

Energies 2019, 12(9), 1699; https://doi.org/10.3390/en12091699 - 5 May 2019

Cited by 8 | Viewed by 3944

Abstract

More and more human activities are increasingly dependent on the power quality energy they are supplied. In particular, those loads that have an electronic switching mode power supply (SMPS) and microcontrollers or microprocessors are very susceptible to de-energization of the AC line as voltage monitoring takes place on the DC end and may not have enough time to cope with a voltage event involving energy loss. There have been many proposals that analyze power quality or current consumption, even those using limited resources hardware or the classic formulas of discrete root mean square (RMS). In this proposal, an approximation to the problem by means of an RMS value estimator that uses as a base a microcontroller of basic range and low economic cost and algorithms of calculation of very low computational cost that elude complex arithmetic operation to controllers, such as powers or roots, is presented. The results of the experiments to which the proposal was subjected show its ability to provide an estimation of the RMS value of voltage with sufficient precision or an event alarm in less time than the options analyzed. The validation tests and functional comparison of the prototype which were carried out support its viability. Full article

(This article belongs to the Special Issue Analysis for Power Quality Monitoring)

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20 pages, 8961 KiB

Open AccessArticle

An Embedded Sensor Node for the Surveillance of Power Quality

by José-María Guerrero-Rodríguez, Clemente Cobos-Sánchez, Juan-José González-de-la-Rosa and Diego Sales-Lérida

Energies 2019, 12(8), 1561; https://doi.org/10.3390/en12081561 - 24 Apr 2019

Cited by 9 | Viewed by 4082

Abstract

The energy supply of office buildings and smart homes is a key issue in the global energy system. The growing use of microelectronics-based technology achieves new devices for a more comfortable life and wider use of electronic office equipment. On the one hand, these applications incorporate more and more sensitive electronic devices which are potentially affected by any external electrical transient. On the other hand, the existing electrical loads, which generally use electronic power systems (such as different types of battery chargers, ballasts, inverters, switching power supplies, etc.), generate different kinds of transients in their own electrical internal network. Moreover, improvements in the information of the state of the mains alternating current (AC) power line allows risk evaluation of any disturbance caused to permanently connected electronic equipment, such as computers, appliances, home security systems, phones, TVs, etc. For this reason, it is nowadays more important to introduce monitoring solutions into the electrical network to measure the level of power quality so that it can protect itself when necessary. This article describes a small and compact detector using a low-cost microcontroller and a very simple direct acquiring circuit. In addition; it analyzes different methods to implement various power quality (PQ) surveillance algorithms that can be implemented in this proposed minimum hardware platform. Hence; it is possible to achieve cheap and low-power monitoring devices that can become nodes of a wireless sensor network (WSN). The work shows that using a small computational effort; reasonable execution speed; and acceptable reliability; this solution can be used to detect a variety of large disturbance phenomena and spread the respective failure report through a 433 MHz or 2.4 GHz radio transmitter. Therefore, this work can easily be extended to the Internet of Things (IoT) paradigm. Simultaneously, a software application (PulsAC) has been developed to monitor the microcontroller’s real-time progress and detection capability. Moreover, this high-level code (C++ language), allows us to test and debug the different utilized algorithms that will be later run by the microcontroller unit. These tests have been performed with real signals introduced by a function generator and superimposed on the true AC sine wave Full article

(This article belongs to the Special Issue Analysis for Power Quality Monitoring)

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26 pages, 4932 KiB

Open AccessArticle

Power Quality Disturbance Monitoring and Classification Based on Improved PCA and Convolution Neural Network for Wind-Grid Distribution Systems

by Yue Shen, Muhammad Abubakar, Hui Liu and Fida Hussain

Energies 2019, 12(7), 1280; https://doi.org/10.3390/en12071280 - 3 Apr 2019

Cited by 93 | Viewed by 6312

Abstract

The excessive use of power semiconductor devices in a grid utility increases the malfunction of the control system, produces power quality disturbances (PQDs) and reduces the electrical component life. The present work proposes a novel algorithm based on Improved Principal Component Analysis (IPCA) and 1-Dimensional Convolution Neural Network (1-D-CNN) for detection and classification of PQDs. Firstly, IPCA is used to extract the statistical features of PQDs such as Root Mean Square, Skewness, Range, Kurtosis, Crest Factor, Form Factor. IPCA is decomposed into four levels. The principal component (PC) is obtained by IPCA, and it contains a maximum amount of original data as compare to PCA. 1-D-CNN is also used to extract features such as mean, energy, standard deviation, Shannon entropy, and log-energy entropy. The statistical analysis is employed for optimal feature selection. Secondly, these improved features of the PQDs are fed to the 1-D-CNN-based classifier to gain maximum classification accuracy. The proposed IPCA-1-D-CNN is utilized for classification of 12 types of synthetic and simulated single and multiple PQDs. The simulated PQDs are generated from a modified IEEE bus system with wind energy penetration in the balanced distribution system. Finally, the proposed IPCA-1-D-CNN algorithm has been tested with noise (50 dB to 20 dB) and noiseless environment. The obtained results are compared with SVM and other existing techniques. The comparative results show that the proposed method gives significantly higher classification accuracy. Full article

(This article belongs to the Special Issue Analysis for Power Quality Monitoring)

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15 pages, 3394 KiB

Open AccessArticle

Implementation of Processing Functions for Autonomous Power Quality Measurement Equipment: A Performance Evaluation of CPU and FPGA-Based Embedded System

by María-Ángeles Cifredo-Chacón, Fernando Perez-Peña, Ángel Quirós-Olozábal and Juan-José González-de-la-Rosa

Energies 2019, 12(5), 914; https://doi.org/10.3390/en12050914 - 9 Mar 2019

Cited by 7 | Viewed by 3160

Abstract

Motivated by the effects of deregulation over power quality and the subsequent need of new types of measurements, this paper assesses different implementations of an estimate for the spectral kurtosis, considered as a low-level harmonic detection. Performance of a processor-based system is compared with a field programmable gate array (FPGA)-based solution, in order to evaluate the accuracy of this processing function for implementation in autonomous measurement equipment. The fourth-order spectrum, with applications in different fields, needs advanced digital signal processing, making it necessary to compare implementation alternatives. In order to obtain reproducible results, the implementations have been developed using common design and programming tools. Several characteristics of the implementations are compared, showing that the increasing complexity and reduced cost of the current FPGA models make the implementation of complex mathematical functions feasible. We show that FPGAs improve the processing capability of the best processor using an operating frequency 33 times lower. This fact strongly supports its implementation in hand-held instruments. Full article

(This article belongs to the Special Issue Analysis for Power Quality Monitoring)

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13 pages, 2237 KiB

Open AccessArticle

Power Quality in DC Distribution Networks

by Julio Barros, Matilde de Apráiz and Ramón I. Diego

Energies 2019, 12(5), 848; https://doi.org/10.3390/en12050848 - 5 Mar 2019

Cited by 38 | Viewed by 6083

Abstract

This paper presents an overview of power quality in low-voltage DC distribution networks. We study which of the power quality disturbances in AC networks are also relevant in DC networks, as well as other disturbances specific to DC networks. The paper reviews the current status of international regulations in this topic and proposes different indices for the detection and characterization of the main types of power quality disturbances, presenting some results obtained in different laboratory tests in DC networks using different DC voltage shapes delivered by different DC power source types. Full article

(This article belongs to the Special Issue Analysis for Power Quality Monitoring)

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15 pages, 2022 KiB

Open AccessArticle

Application of Spectral Kurtosis to Characterize Amplitude Variability in Power Systems’ Harmonics

by Jose-María Sierra-Fernández, Sarah Rönnberg, Juan-José González de la Rosa, Math H. J. Bollen and José-Carlos Palomares-Salas

Energies 2019, 12(1), 194; https://doi.org/10.3390/en12010194 - 8 Jan 2019

Cited by 7 | Viewed by 3820

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 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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14 pages, 1374 KiB

Open AccessArticle

Reliability Monitoring Based on Higher-Order Statistics: A Scalable Proposal for the Smart Grid

by Olivia Florencias-Oliveros, Juan-José González-de-la-Rosa, Agustín Agüera-Pérez and José-Carlos Palomares-Salas

Energies 2019, 12(1), 55; https://doi.org/10.3390/en12010055 - 25 Dec 2018

Cited by 9 | Viewed by 2647

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 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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11 pages, 2339 KiB

Open AccessArticle

An Extended Kalman Filter Approach for Accurate Instantaneous Dynamic Phasor Estimation

by Matilde De Apráiz, Ramón I. Diego and Julio Barros

Energies 2018, 11(11), 2918; https://doi.org/10.3390/en11112918 - 26 Oct 2018

Cited by 12 | Viewed by 3636

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 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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