Power Quality Monitoring Research Articles

A Novel Power Quality Monitor Placement in Transmission Systems Method Using Binary Teaching Learning-Based Optimization Algorithm Considering Monitoring Redundancy

This paper deals with optimal employment of power quality monitors (PQMs) in transmission networkson the basis of the idea of monitor reach area. The proposed model uses binary string, representing the installation modeof PQMs (Yes or No) in each bus of the network. In the current article, the binary version ofthe teaching learning-based optimization algorithm (BTLBO) is used. It has the ability to enhance the search potential and provides a rapid and secure convergence rate in the optimization process. The concept of redundancy is considered in this study. Theoverall cost function is formulated to optimize the two indices. The first one is the index of monitoring overlap, and the second one is the index of sag severity. Amongthe solutions whoseobjective function experiments the minimum value, the evaluating the redundancyindexgives the final optimal answer. With an excellent redundancy, the buses of the system faced with faults are monitored more times, on average. In the current research, DIGSILENT software is employed in short circuit analysis, whereas the BTLBO manages the optimization process. In the proposed algorithm, the IEEE 30 Bus transmission network is consideredas a case study, and results are compared to similar investigations to clarify the impressiveness of the proposed algorithm.

A New Classification Scheme Based on Extended Kalman Filter and Support Vector Machine

In the field of power quality monitoring, due to the extensive quantity of measurements data, it is preferred that the detection, identification and classification of Power Quality Disturbances (PQD) can be performed automatically. This paper proposes a new efficient classification scheme based on two powerful techniques, the Extended Kalman Filter (EKF) and the Support Vector Machine (SVM). The feature extraction step plays the most important role, where, the EKF has a good advantage in reducing time computation by dispensing with the segmentation step. Moreover, only three suitable features are extracted from the parameters estimated based on the EKF, thus conserve memory space and time do without need for feature selection step. After the normalization of the extracted features, in the second step, the SVM classifier is applied to classify these disturbances into their specific categories. Simulation results are examined under different Gaussian white noises to prove the efficiency of the proposed classification diagram. Moreover, performance comparisons with other methods proposed in the literature are conducted, to show the effectiveness of the proposed scheme in term of, consumption of memory space, computation time, implementation complexity, and classification accuracy.

Design and Implementation of Single-phase Power Quality Monitor Based on IM1281B

In order to better analyze the influence of electrical equipment on power grid fluctuations, a detection system is designed for power quality monitoring. The system uses 51 single-chip microcomputer as the control core, combined with IM1281B single-phase mutual inductance energy metering module, to collect real-time voltage RMS, current RMS, power factor, apparent power, active power and other electrical parameters of electrical equipment connected to the grid. The standard Modbus-RTU is used for communication between IM1281B and the single-chip microcomputer, which realizes the real-time acquisition and processing of multiple electrical parameters of the electrical equipment connected to the power grid. The experimental results show that, the single-phase power quality monitor designed based on IM1281B is simple in structure, and relatively complete in collecting electrical parameters, which can meet the needs of power quality analysis.

Recovery of Power Quality Terminal’s Harmonic Data with the Interference of Bad Data

Power quality monitoring equipment is inevitably faced with the problem of data loss and is vulnerable to the interference of noise or bad data. We propose a harmonic data recovery method that is based on graph clustering and non-negative matrix factorization (NMF) under multiple constraints. Compared with the existing harmonic data recovery methods, the proposed method can effectively recover lost data and it has a strong anti-interference ability, especially for the recovery of harmonic data with interference. In the recovery of data loss, noisy interference tests and bad data interference tests, the presented recovery algorithm has high accuracy within 60% for continuous missing data. In an environment with SNR = 50, this method has high recover reliability and accuracy within 15% for situations involving bad data interference.

IoT Cloud-Based Power Quality Extended Functionality for Grid-Interactive Appliance Controllers

Due to the myriad of loads that are collected into commercial grid-interactive efficient buildings (GEBs) focused on the industry 4.0 paradigm, it is important to ensure their proper electrical operation. The power quality (PQ) here requires a granular monitoring approach, reaching a point where each device connected to the microgrid can diagnose whether its power supply is optimal. Otherwise, it can participate cooperatively in decision-making to avoid anomalies or faults in the microgrid. In this work, we present cloud-based extended functionality to make smart appliances responsive to the grid, either autonomously or managed under the open automated demand response standard. Further to acting as a switch, the main strength lies in its PQ monitoring via the FIWARE Internet of Things (IoT) platform with data-driven analytics capabilities. It identifies and even predicts a broad spectrum of electrical disturbances, far exceeding the capabilities of previous solutions such as the grid-friendly appliance controller, so it is possible to customize a battery of alarms at will (e.g., according to IEEE 1547 standard). Moreover, although it can act autonomously, its main mission will be to act in a coordinated manner, either cooperatively or under the supervision of the GEB Energy Management System. Finally, different case studies are presented to show their capabilities. With the integration of these distributed submetering systems, under standards IoT wireless communication protocols, a further step will be taken in the advent of the digital utility paradigm.

Harmonic Source Location and Identification in Radial Distribution Feeders: An Approach Based on Particle Swarm Optimization Algorithm

The location and identification of harmonic sources in radial distribution feeders are essential tasks since they improve the power quality monitoring and assist in mitigating issues resulting from harmonic distortions. Thus, this article presents an approach based on particle swarm optimization algorithm with adaptive and individual inertia, which was used to locate and estimate the parameters (harmonic magnitudes, real and reactive power) of the harmonic source with the highest contribution. The proposed approach needs only 20 cycles in steady state, considering the harmonic source pre- and postconnection as input data. In addition, this approach uses few meters to reduce the cost of investment. As a result, it was possible to locate the harmonic source, in the IEEE 34-bus test feeder, with absolute errors less than 1.78 km, using only 3 m. Moreover, the harmonic source identification algorithm reached mean percentage relative errors of less than 3.7%.

Different Power Quality Issues of the Energy Power System with Their Analysis and Mitigation Techniques

The power systems have the utilization of the power electronics devices for electric power supply becomes a very common trend. These power electronics devices work like as a nonlinear loads and produce the distortion in the system which introduces unwanted harmonics for reduction of the PQ supply system. The power quality of the system becomes very important issue due to the utilization of the power electronics devices and their application of day to day life. Power suppliers faced a number of problems for transferring the power supply from generating station to the end users and load demand centers with minimum investment or high reliability of the system. Different power quality monitoring techniques describe with their applicable solution of the issues. Custom power devices are utilized for achieving the better power quality through the mitigation techniques like UPS, TVSS for the system. Due to the different advantages of the power quality S-TATCOM can be utilize for renewable energy system. Spinning reserve is the traditional method for improving the power quality of the system. Flow chart of the power quality of the system provide the information of the about the problem identification and evaluation of the problem of power quality in first stage. It can be divided into five parts of the problem evaluation like voltage sag, transients, flicker, voltage regulation and harmonics distortion. Standards of the power quality with their different issues in the energy system for monitoring techniques have been discussed with use of particular custom power devices.

Multi-Objective Optimization Aiming to Minimize the Number of Power Quality Monitors and Multiple Fault Estimations in Unbalanced Power Distribution Systems

Utilities are already concerned about power quality monitoring. Several papers proposed strategies to choose the best locations to install power quality monitors, minimizing the investment cost while guaranteeing observability of power quality disturbances, mostly voltage sags. Although several papers studied this problem in power transmission systems, many problems remain unsolved for power distribution systems, such as power quality monitors allocation in unbalanced distribution systems, the impact of distributed generation in allocation methods, and allocation of power quality monitor for fault location. This paper makes contributions in all these three points. It proposes a multi-objective binary integer linear programming model for unbalanced systems, which is still suitable for power transmission systems. Furthermore, we analyze the connection/disconnection of a distributed generator, and our tests showed no need to change allocation regardless of the generator connection status. Finally, the allocation method reduced the multiple estimation problem; therefore, meter-based fault location methods could improve their performance with our allocation.

Impact of DC Transient Disturbances on Harmonic Performance of Voltage Transformers for AC Railway Applications.

This paper analyzes the impact of typical DC transient events occurring in railway grids on the frequency performance of instrument transformers (ITs) installed onboard trains and in AC substations for power quality (PQ) applications. PQ monitoring in railway systems is an issue of great interest because it plays a key role in the improvement of energy efficiency. The measurement chain for the PQ measurements, at 15 kV at 16.7 Hz and 25 kV at 50/60 Hz, commonly includes ITs to scale the voltage to levels fitting the input of the measurement units. Nevertheless, the behavior of ITs in the presence of PQ phenomena represents an open issue from a normative point of view, even for those installed in conventional AC power supply systems. In this context, the paper presents a possible definition of DC transient disturbances test waveforms, a measurement procedure, and a setup to assess the impact of these disturbances on the harmonic performances of ITs for railway systems. Preliminary experimental tests carried out on two commercial ITs under wide ranges of variation for the amplitude and the time duration of DC disturbances show that, in some cases, the error introduced in harmonic measurements can exceed 100%.

Recursive versus nonrecursive Richardson algorithms: systematic overview, unified frameworks and application to electric grid power quality monitoring

Sufficiently accurate, fast and computationally efficient solution of the system of linear equations is required in many estimation problems. Richardson iteration is one of the main solvers for linear equations, which provides optimization possibilities for time critical and accuracy critical applications. Convergence rate improvement and reduction of the computational complexity of the Richardson iteration are the most important problems in the area. The introduction of Newton–Schulz iterations is the efficient way for convergence rate improvement and the paper starts with systematic overview of the high-order Newton–Schulz matrix inversion algorithms. In addition, the unified framework for recursive computationally efficient convergence accelerators and error models for a number of combinations of Richardson and Newton–Schulz iterations is developed. A new nonrecursive parameter estimation concept is introduced and compared in this paper with recursive estimation. Recursive and nonrecursive Richardson algorithms together with the standard LU decomposition method were applied to the electric grid power quality monitoring problem. The algorithms were tested for the detection of the sag and swell signatures in the voltage and current signals on real data in three-phase power system. Nonrecursive Richardson algorithms which save close to half of the computational time compared to LU decomposition method were recommended for power quality monitoring applications.

Classification of complex power quality disturbances based on modified empirical wavelet transform and light gradient boosting machine

Accurate detection and classification of power quality (PQ) disturbances is an essential prerequisite for PQ mitigation. To address this issue, a new PQ assessment framework based on modified empirical wavelet transform (MEWT) and light gradient boosting machine (LightGBM) is proposed here. First, the frequency estimation mechanism and band segmentation rule of empirical wavelet transform (EWT) is modified, which makes EWT suitable for analysing complex PQ signals. Second, based on the PQ disturbance analysis results of MEWT, 8 characteristic curves are defined and statistical features are extracted in both the time and frequency domain. Third, binary relevance-based LightGBM (BR-LightGBM) is designed for the multilabel classification of massive PQ events. Considering the impact of input features and model structure, feature selection and hyper parameter optimization are conducted for achieving better classification performance. Finally, extensive experiments based on synthetic data and two groups of measured data show the effectiveness of the proposed method on 48 types of complex PQ disturbances. Compared with other algorithms for multiple PQ signals, the proposed method is fast for computation and performs better in classification accuracy and robustness, which is a prospective alternative for the PQ monitoring system.

Problem of Total Harmonic Distortion Measurement Performed by Smart Energy Meters

Abstract Currently, electricity is treated as commodity that should be delivered from a distributor to a consumer with a certain quality. The power quality is defined by the set of measures with specific limit values. One of the basic measures is the Total Harmonic Distortion (THD), which allows to assess the level of the voltage distortion. The measurement of THD ratio should be carried out in accordance with the normative specification. It is assumed that this requirement is met by class A power quality analyzers. Currently, measures are taken to monitor power quality in a large number of measurement points with the use of smart energy meters that are part of the Advanced Metering Infrastructure (AMI). The paper presents the problem of THD ratio measurement by AMI meters if voltage fluctuations occur. In such situation, inconsistency in measurement results of AMI meters and class A power quality analyzers occurs. The problem is presented on the basis of laboratory study results in which disturbances in power grid are recreated.

Review on detection and classification of underlying causes of power quality disturbances using signal processing and soft computing technique

The new age power system is highly subjected to PQ disturbances that require proper attention and address. The research in this field is mainly categorized into different parts such as mathematical modeling, basic PQ principles, standards, impact and solutions, sources, and analysis. There are several underlying causes behind the occurrence of the PQ disturbance. Therefore, it is important to address the exact underlying cause for proper mitigation of the PQ disturbance. There are several methods available in the literature, which concentrated on to detection and classification of power quality events rather than the root cause of the PQ events. An effective method for root cause identification of PQ events is the need of the day. This article covers a broad review of signal processing and soft computing techniques used for the detection & recognition of the underlying cause of it. This will help the researcher, engineers, designers working in the field of detection, recognition, and monitoring of power quality. The comparative study of existing methods used in the literature is tabulated. The major concerns and obstacles in categorizing the recognition of power quality disturbances are thoroughly examined and discussed. The potential for new researchers in the field of power quality disturbance detection and recognition of underlying causes is further explored in this review.

Power Grid Resource Integration of Enterprise Middle Station based on Analytic Hierarchy Process

With the transformation from smart grid to power Internet of Things, new power businesses such as power grid automation and power quality monitoring are constantly emerging. The load environment of power grid is changeable. In order to meet the needs of multi-service, the integrated access scheme for power grid resources in power enterprises is gradually diversified, which brings challenges to the unified management and control of power grid communication network. In this paper, SDN technology is used to improve the operation and maintenance management and control of power communication network, which aims at the integration scheme of power grid resources in power enterprises. Based on the controller cluster technology, combined with the new power business requirements, this paper designs a software-defined network centralized control architecture of the new business of power communication network. The architecture realizes the operation and maintenance management of network resources under the centralized control architecture of typical enterprise scenarios, such as power grid enterprises. The convergence speed is improved by 27%. The minimum value of iterative convergence is 31% better than that of other methods. The system requirement is reduced by 13.5%, which is helpful to improve the efficiency of node dynamic allocation and ensure the need of large-capacity data transmission of smart grid. The research in this paper can realize the two-way interaction, real-time expansion and unified deployment of power business in the future, and promote the intensive and lean development of power communication network.

A Comprehensive Overview on Modified Versions of Stockwell Transform For Power Quality Monitoring

The increasing trends toward the accurate identification of power quality disturbances (PQD) via power quality (PQ) monitoring require an appropriate digital signal processing (DSP) technique and a robust classifier. To this end, Stockwell transform (ST), one of the most efficient feature extraction DSP tools, and its several variants play an utmost role in PQ assessment framework. Its time-varying spectral characteristics generally extract the local instantaneous frequency spectrum from the global temporary behavior of PQD signal. However, the Standard ST suffers from thepoor time-frequency resolution because of its frequency-dependent Gaussian window (GW). While the analysis of the statistically time-varying signals requires a suitable balance between time and frequency resolution. To this end, this paper provides a comprehensive literature review on several modified versions of Standard ST for the first time to reduce the computational complexity of the algorithm as well as maximize the energy concentration of the time-frequency plane. A comparative analysis of all the modified STs has been presented in tabular form to provide the key characteristics of each technique. Additionally, a case study has been presented to substantiate the highest accuracy of the proposed algorithm over the other ST variants. Apart from the PQD classification, miscellaneous applications of Standard ST and its modified variants have been indicated. This review paper may provide a valuable resource to the researchers for further improvement of the time-frequency resolution of ST not only in classifying PQD but also for its other wide applications.

Productive uses of electricity at the energy-health nexus: Financial, technical and social insights from a containerized power system in Rwanda

We present a case study of successful uptake of a productive use of electricity (PUE) co-located at an off-grid clinic powered by OffGridBox in Rwanda. We develop a techno-economic analysis of the standardized, modular, and redeployable power supply technology, characterizing cost components, revenue considerations, and key challenges. We present a technical characterization of system utilization based on remote monitoring of electricity consumption, power reliability, and power quality at a PUE intervention site, estimating system reliability at 81% over the study period. Lastly, we characterize socio-economic costs and benefits from the productive user's perspective drawing on mixed-method interviews. We find that relatively low amounts of electricity consumption (10–30 kWh per month) command a high revealed willingness to pay (∼$3 per kWh) for the solar-powered displacement of diesel-based welding, significantly improving the unit economics of the deployed system. This analysis and data provides a resource model for the standardization of mini-grid hardware, performance and cost frameworks, and metrics to assess off-grid, under-grid and ultimately grid interactive distributed generation systems. These models are urgently needed to meet the UN Sustainable Development Goal SDG 7 commitment to achieve universal energy access by 2030.

Site Characterization Index for Continuous Power Quality Monitoring Based on Higher-order Statistics

The high penetration of distributed generation (DG) has set up a challenge for energy management and consequently for the monitoring and assessment of power quality (PQ). Besides, there are new types of disturbances owing to the uncontrolled connections of non-linear loads. The stochastic behaviour triggers the need for new holistic indicators which also deal with big data of PQ in terms of compression and scalability so as to extract the useful information regarding different network states and the prevailing PQ disturbances for future risk assessment and energy management systems. Permanent and continuous monitoring would guarantee the report to claim for damages and to assess the risk of PQ distortions. In this context, we propose a measurement method that postulates the use of two-dimensional (2D) diagrams based on higher-order statistics (HOSs) and a previous voltage quality index that assesses the voltage supply waveform in a continous monitoring campaign. Being suitable for both PQ and reliability applications, the results conclude that the inclusion of HOS measurements in the industrial metrological reports helps characterize the deviations of the voltage supply waveform, extracting the individual customers' pattern fingerprint, and compressing the data from both time and spatial aspects. The method allows a continuous and robust performance needed in the SG framework. Consequently, the method can be used by an average consumer as a probabilistic method to assess the risk of PQ deviations in site characterization.

Using Grey Target Theory for Power Quality Evaluation Based on Power Quality Monitoring Data

Smart grid puts forward higher requirements for power quality. Power quality evaluation can provide a decision-making basis for quality improvement. Based on power quality monitoring data, a grey target method is proposed for power quality evaluation. The grey target is composed of power quality evaluation standard and power quality monitoring data to be evaluated. Combining with the characteristics of each power quality evaluation index, the target center of the whole grey target system is found. Then, the power quality monitoring data to be evaluated and the power quality standard mode are compared and analyzed to construct the power quality grey correlation difference information space. Finally, the target center coefficient and target degree of power quality are calculated to realize the comprehensive evaluation of power quality, and the evaluation grade of power quality monitoring data to be evaluated is obtained. Compared with the evaluation results of the existing literature, the effectiveness of the proposed method is verified, which shows that grey target theory is reasonable in the comprehensive evaluation of power quality.

Analysis of Power Quality Monitoring and Reactive Power Compensation Technology

Analysis of Power Quality Monitoring and Reactive Power Compensation Technology

Newly Implemented Real-Time PQ Monitoring for Transmission 4.0 Substations

The growth of penetration of large blocks of inverter based renewable energy in transmission power systems may lower the power quality of these systems, especially with rising of harmonic and interharmonic distortion and voltage fluctuation. Poor Power Quality (PQ) can negatively affect the protection system and may cause premature aging of electrical equipment connected to the power system. Thus, real-time and continuous PQ monitoring can be of great value for operation, maintenance and expansion of the system. This paper presents a recently implemented real-time PQ monitoring system based on the concept of Digitally Enabled Substation Architecture or Substation 4.0 (SB4.0). The proposed PQ monitoring system receives voltage and current signal samples from a Merging Unit (MU) and calculates the various power quality parameters. Since the system uses the SB4.0 concept the power quality monitoring is a software application implemented in an industrial computer. Also, the system provides a Data Recording application, running as additional software task that provide oscillography triggered by instantaneous Total Harmonic Distortion (iTHD). This paper presents the architecture of the developed and implemented system as well as the field results gathered from a transmission system in the north of Brazil.