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Partial Discharge (PD) measurement is one of the best solutions for condition assessment of Gas Insulated Switchgears (GISs). For having Condition-based maintenance of GIS, online PD monitoring is of great importance. For this aim, Ultra High Frequency (UHF) PD sensors should be installed inside the GIS during the installation. However, in most installed GISs in industries, the internal UHF PD sensors are not installed. In this paper, a new method for online defect type recognition according to external UHF PD sensors and based on the time-frequency representation of PD signal is proposed. In this case, four artificial defect types named protrusion on the main conductor, protrusion on the enclosure, free moving metal particle, and metal particle on spacer are implanted inside the 132 kV L-Shaped structure of one phase in enclosure GIS. The signal energy at each level of the decomposed signal by Discrete Wavelet Transform (DWT) is applied for features of each defect type. The trends of signal energy variations at each frequency range of signal are applied for discriminating between each defect type. The Deep Feed Forward Network (DFFN) classifier is applied for PD pattern recognition. The results show the benefits and simplicity of the proposed method for PD signal classification, independent from the position of the PD sensor, especially in the case of online PD monitoring of GIS. [ABSTRACT FROM AUTHOR]

In recent years, the mining of cryptocurrencies such as Bitcoin has attracted much global attention due to the simplicity and high profitability of this business, especially in countries with low electricity rates. The process of cryptocurrency mining using cryptocurrency mining devices requires a significant amount of computing power. This industry, which is increasingly growing in energy and carbon emissions, can cause environmental concerns. Common ways to reduce this amount of energy consumption are to prohibit mining and charge these loads at a higher electricity rate; however, these solution methods are not feasible and applicable in many countries. This paper presents an energy efficiency program to persuade the customers to mine cryptocurrency using high‐efficient cryptocurrency mining devices (CMDs), including informative, regulation, and financial policy instruments. This energy efficiency approach suggests a standard, if implemented, would ban the application of inefficient CMDs, and would encourage the cryptocurrency miners to improve the profitability of their business with high‐efficient CMDs through a penalty‐reward strategy. The performance of this energy efficiency program is studied through an analysis of data gathered from different CMDs used in Iran. The effectiveness of this suggested program is proved through its sufficient incentives for miners using high‐efficient CMDs. [ABSTRACT FROM AUTHOR]

Change in customers' consumption patterns due to the introduction of new electricity consuming technologies into human consumption practices has impacted the existing optimal loading profile of the grid facilities. Although some MV/LV distribution transformers (DTs) are operating under a light load profile, this does not guarantee that they are in a healthy condition, since necessary maintenance procedures are required. On the other hand, many unplanned overloading conditions occur on the other DTs and causes accelerated failures which contributes to very high operational costs. This paper presents the outcome of a study on how the planned DTs relocation can save asset managers against their huge DTs replacement costs developed due to the highly overloaded DTs failures in a utility, and how it will improve the overall reliability of the DTs. A mixed-integer linear programming (MILP) solution is proposed to formulate the introduced economic relocation-based asset management (AM) framework while minimizing total cost (TC) of the network. The results show that incorporating relocation techniques into the AM formulation ends in reduction of the distribution network TC and a decrease in asset failure rates if compared with application of traditional techniques. [ABSTRACT FROM AUTHOR]

This article proposes a new three-stage stochastic framework for dealing with predictable two-phase natural disasters in distribution systems. This framework is a multiobjective optimization, in which the amount of curtailed energy, the number of switching actions, and the vulnerability of operational components are selected as the main criteria for decision-making process. The optimization problem is formulated in the form of a stochastic mixed-integer linear programming (MILP) problem. In this article, a windstorm event followed by flooding is analyzed as a two-phase natural disaster. In this regard, the uncertainties associated with gust-wind speed, floodwater depths, and load demands are taken into account by the proposed framework. The initial configurations of islands are formed just ahead of the storm event (first stage), and their borders are changed in the second stage, which is associated with the storm event and its aftermath. The final configurations of islands are determined by the third stage once the uncertainties of floodwater depths are revealed. In the proposed framework, the emergency generators (EGs) are assumed to be prone to flooding, and a novel approach is proposed for quantifying the flood-related failure probability of EGs. Likewise, overhead distribution structures are recognized as vulnerable components to storms. The proposed framework is implemented on a test system, and its effectiveness is investigated and verified through seven case studies. [ABSTRACT FROM AUTHOR]

Cryptocurrency mining device (CMD) is a plug-and-play device installed by any low-voltage customer to convert electrical energy to digital money. Recently, the significant increase in the price of digital currencies has persuaded residential customers in many countries to employ CMDs to obtain quick and easy profit. However, these rapidly evolving loads can cause a substantial increase in the coincident peak load of distribution networks. Therefore, it can threaten the safe and reliable operation of the network. A straightforward way to restrict the penetration rate of these home-based miners is to increase the electricity price such that this business becomes unprofitable; however, this solution affects the national regulations and is not practical in many countries. This paper proposes a practical electricity pricing strategy to manage the operation of cryptocurrency mining loads appropriately. This pricing strategy can change the miner’ threat to an opportunity to sell more electrical energy during the off-peak hours to these loads and to maximize the profit of the utility. The proposed strategy is studied using the load profile dataset obtained from the measurements of Tehran Electricity Distribution Company, and its effectiveness is demonstrated. [ABSTRACT FROM AUTHOR]

Partial Discharge (PD) measurement is one of the main methods for condition monitoring of Gas Insulated Switchgears (GIS). Internal Ultra High Frequency (UHF) sensors can be applied for capturing PD propagated electromagnetic signals within the GIS. PD sensor placement inside the GIS is one of the main challenges for designing an online PD measuring system. For this aim, the impacts of different GIS components on propagated PD electromagnetic waves should be studied. In this paper, different PD sensor position angles (with respect to PD sensor) are used to investigate their sensitivity to measuring PD electromagnetic waves. Two distinguishable parameters from the calculated PD electromagnetic waves, the first rated electric field and the signal's power over the two frequency ranges (0.3-2 GHz and 0.3-3 GHz) are used to analyze and quantify the calculation results. The impacts of different enclosure diameters, different types of spacers, and various disconnector contact gap distances (under different voltage levels) on this wave propagation are studied. Additionally, the two standard GIS busbar profiles, named L-shape and T-shape, are discussed in this paper. The results show that the attenuation degree of the measured PD EM waves is strongly influenced by the busbar dimensions and the configuration of its components. The GIS busbar designer can employ these results to select the proper PD sensors and their installation locations. [ABSTRACT FROM AUTHOR]

High-temperature superconducting (HTS) transformers with multi-segment windings have been proposed in earlier literatures for the hysteresis loss reduction and short circuit electromagnetic force mitigation. The optimum distributive ratios for these multi-segment windings have been determined in earlier literatures. Asymmetrical seven segment winding with its optimum distributive ratio (k = 1/12) results in minimization of short circuit electromagnetic forces under normal tap and any adjusted tap. However, insulation design and leakage inductance calculation for the multi-segment winding of an HTS transformer have not been addressed in past literatures. Insulation design is one of the most crucial aspects in the transformer design, especially for high voltage power transformers. The analysis and optimization of the electric field distribution over the winding's segments insulation in these HTS transformers provide the required dimensions for precise determination of the leakage inductances. In this paper, for the first time, winding insulation design and leakage inductance calculation of a 200 MVA, 230/20 kV HTS transformer with asymmetrical seven segment winding (and k of 1/12), are carried out. The analytical method besides a two-dimensional (2D) finite element method (FEM), through COMSOL Multiphysics software, is utilized for insulation design and calculation of leakage inductances of this transformer. [ABSTRACT FROM AUTHOR]

The short‐term expansion planning of the private utilities, as well as the emerging technologies such as photovoltaic panels (PVs), plug‐in hybrid electric vehicles (PHEVs), cryptocurrency mining, and storage elements spread, make the long‐term load estimation of distribution transformers (DTs) noticeably imprecise. In response, the number of overload and underload transformers is growing in recent years. The utilities normally analyse the loading of their DTs annually to determine the DTs, which should be replaced. It is a common practice for utilities to relocate these DTs to reduce the investment needed to purchase new transformers. Therefore, the utility needs a systematic algorithm to determine the optimal schedule to relocate/replace the DTs with minimum required time and cost. This paper introduces a two‐stage procedure to obtain the optimal schedule to replace DTs. In the proposed algorithm, the maximum permitted number of work‐hours per day for field workers is considered, which converts the problem to a daily‐task based optimisation problem. Also, an useful life investigation of the in‐service DTs is considered in the relocation problem. A real case study in Qom province, Iran, has been studied to prove the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

A better performance and consequently the widespread use of polymeric insulators in different parts of the power grid can increase their role in the grid reliability. The accumulation of contamination and housing‐erosion are the two most effective factors in undermining the performance of this type of insulators. Therefore, electric utilities need to identify contaminated insulators for washing and cracks in polymeric housing to replace them with healthy specimens. This paper discusses the impact of contamination layer and housing‐erosion of polymeric insulators on the partial discharges (PD) at the insulator surface, through RF‐PRPD (phase resolved partial discharge) patterns. The existence of different sources of PDs in a real environment (transmission line or station) makes it difficult to use the PRPD patterns to distinguish them from each other. Therefore, using a conical monopole antenna, the simultaneous PD signals and the related RF‐PRPD pattern of samples under test are captured. The grayscale image was obtained using the time‐frequency matrix of the PD signals transform, by wavelet. Then, features are extracted and selected from grayscale image. By clustering of the PD signals, the resulted RF‐PRPD sub‐patterns are well separated and provided the necessary means to distinguish among the status of different samples under test. [ABSTRACT FROM AUTHOR]

The integration of renewable energy (RE)‐based distributed generation (DG) with electric power distribution systems (DSs) in association with smart grid technology has numerous benefits, however, due to their intermittent nature, the utilisation of RE‐based DG may pose threats to the proper operation of conventional overcurrent (OC) protection schemes. The resulting threats, malfunctions, and non‐selective actions could occur by relays within the DS, and the development of efficient protection schemes is necessary. The objective of this study is to propose and simulate an adaptive OC protection scheme in DSs in the presence of doubly‐fed induction generator (DFIG) wind turbines based on wind speed forecast data with considerations for wind speed forecast uncertainty and a low‐voltage ride‐through requirement for wind turbines. In each time interval and possible operating mode, the output power of DFIG‐based wind turbines and relay setting parameters are determined offline. The results show that the proposed protection scheme prevents malfunctions and non‐selective operations of relays, and also provides faster fault isolations, as compared to the conventional OC protection scheme. [ABSTRACT FROM AUTHOR]

Presence of defects, conducting particles, nonconducting particles, and nitrogen gas bubbles in the insulation system of high-temperature superconducting (HTS) transformers, mainly inside the liquid nitrogen as its major insulation, can create local field enhancement and consequently partial discharges which eventually lead to the catastrophic failure of the transformer. In this paper, two-dimensional (2D) axisymmetric finite element method (FEM) modeling via COMSOL Multiphysics software has been utilized for the investigation of the impact of size and shape of conducting particles and nitrogen gas bubbles on partial discharge (PD) activities in liquid nitrogen. Conducting particles of various shapes and the nitrogen bubbles are studied for PD generation. The results have been analyzed and compared. This can be employed for HTS transformer efficiently and PD free insulation design to enhance its insulation life. [ABSTRACT FROM AUTHOR]

Utilization of superconducting equipment increases every day due to availability of the HTS tapes with reasonable prices, commercially. Since 1997, many high-temperature superconducting (HTS) transformers have been designed and fabricated. In this paper, all the different developments of HTS transformer windings since 1997 will be reviewed. Additionally, the advantages and disadvantages of the application of the two main winding types (the pancake and the layer) in the HTS transformer will be studied. [ABSTRACT FROM AUTHOR]

The appealing advantages of high-temperature superconducting (HTS) power transformers over conventional ones have attracted transformer manufacturing companies, power companies, research institutes, and universities worldwide to conduct research and development in this field. Unfortunately, HTS transformers are more vulnerable to mechanical stresses than conventional transformers. The results of the interaction between current carrying windings and leakage magnetic fluxes are the electromagnetic forces, which act on transformer windings. Under short circuit events, these forces are remarkable, and, therefore, catastrophic failure of transformer may arise. Flux-diverter applications have been reported in earlier literatures for increasing critical current or decreasing ac losses in HTS transformers. In this paper, a genetic algorithm based method is employed for the optimal design of flux diverter to minimize the axial short circuit force, in design stage of a sample 132/13.8 kV, 50 MVA three-phase core type HTS transformer. In this paper, the optimal dimensions, placement, and permeability of a flux diverter have been determined. It has been shown that utilizing this optimized flux diverter, the axial short circuit forces have been reduced significantly. Electromagnetic modeling and simulations, by the application of finite element method, have been employed for the verification of the analytical method results. A high degree of consistency has been observed between the analytical results and the simulation results. [ABSTRACT FROM AUTHOR]

High-temperature superconducting (HTS) transformers have remarkable appealing advantages over conventional ones. But higher brittleness of HTS windings with respect to copper windings makes HTS transformers more vulnerable in short circuit and inrush current situations. During tap changer operation, appreciable asymmetry and non-uniform distribution of ampere-turn along the windings causes high axial component of short circuit forces and makes the situation more severe. In this paper, multi-segment winding method is employed for reduction of axial short circuit forces. An analytical method is presented for calculation of axial component of short circuit forces under tap changer operation. Analytical method shows that with utilizing HLHLHLH asymmetrical multi-segment windings, during tap changer operation, the axial component of short circuit forces reduces significantly. The results of the analytical method are compared with the results of finite element method (FEM) model simulations, and the consistency is demonstrated. [ABSTRACT FROM AUTHOR]

Transformers are the key component in power system transmission and distribution networks. Condition-based maintenance will increase their expected life, and online monitoring is essential to ensure operation reliability. In this paper, a new approach to transformer online monitoring is provided based on partial discharge (PD) measurement. Simultaneous measurements of PD using IEC60270 and radio frequency (RF) techniques are employed to explore new features that can be used to distinguish between internal PDs and external interference, as well as among different internal PD sources. Stream clustering based on the density grid method with only a few features required is used to categorize active sources without requiring large storage of information. Active source identification is performed using feature extraction from micro-phase-resolved PD images with the histogram of oriented gradient method and a pre-trained network. Two experimental case studies are conducted to evaluate the effectiveness of the proposed method, one to demonstrate the distinction between internal and external sources and the other to demonstrate the distinction between different internal PD sources. It is shown that the proposed method for online monitoring of transformers using simultaneous measurement of PD with IEC60270 and RF techniques and stream clustering is very effective in distinguishing and identifying various PD sources without the requirement of large storage of data. [ABSTRACT FROM AUTHOR]

The general method for identifying the partial discharge type in a power transformer is based on their fingerprints in the form of phase‐resolved discharge patterns. In the case of multiple defects, traditional clustering methods can be applied for separation of active sources. However, such an approach is impractical for online real‐time monitoring due to the very large data size. In this paper a new method using stream clustering is introduced. The method separates the active sources by processing the signal once it is captured, then only a synopsis of the discharge data is stored. Two stream clustering algorithms: Density Grids and DenStream are employed. Through measurements obtained from laboratory experimental setups (corona, surface discharge, transformer defect model) performance of the proposed algorithms are evaluated. It is shown that stream clustering method is able to separate the constituent components involved in the stream of a multi‐source discharge signal without the need to store a large amount of information. The performance of the Density Grids method depends on a limited number of features that it can accommodate. In comparison, the DenStream method can capture more features which enable better separation of active sources at the expense of longer processing time. [ABSTRACT FROM AUTHOR]

The general method for identifying the partial discharge type in a power transformer is based on their fingerprints in the form of phase-resolved discharge patterns. In the case of multiple defects, traditional clustering methods can be applied for separation of active sources. However, such an approach is impractical for online real-time monitoring due to the very large data size. In this paper a new method using stream clustering is introduced. The method separates the active sources by processing the signal once it is captured, then only a synopsis of the discharge data is stored. Two stream clustering algorithms: Density Grids and DenStream are employed. Through measurements obtained from laboratory experimental setups (corona, surface discharge, transformer defect model) performance of the proposed algorithms are evaluated. It is shown that stream clustering method is able to separate the constituent components involved in the stream of a multi-source discharge signal without the need to store a large amount of information. The performance of the Density Grids method depends on a limited number of features that it can accommodate. In comparison, the DenStream method can capture more features which enable better separation of active sources at the expense of longer processing time. [ABSTRACT FROM AUTHOR]

Winding turn-to-turn fault (TTF) is one of the most reported reasons for transformer unplanned outage. If its occurrence is not detected at an early stage, it can develop into a costly phase-to-ground fault. In this paper, a novel algorithm based on the fault-related incremental currents is proposed to detect a low-level transformer TTF. This paper shows that the performance of the proposed method is independent of the transformer operating condition. Therefore, it is reliable even under the presence of power system transients such as the external faults. In addition, the proposed algorithm can be configured uniquely and easily. This feature prevents the algorithm from unnecessary trips. These trips can be considered as the general problem that most of the past presented methods face. The experimental tests used for verification of the algorithm show that, regardless of the transformer winding configuration and its pre-fault operating conditions, the proposed algorithm can accurately detect the TTF, which involves only 1% of the winding turns, in less than one cycle of power frequency. The reliable and secure performance of the proposed algorithm shows that it can be widely used in the advanced numerical relays. [ABSTRACT FROM AUTHOR]

Partial discharge (PD) measurement and identification have great importance to condition monitoring of power transformers. In this paper, a new method for recognition of single and multi-source of PD based on extraction of high level image features has been introduced. A database, involving 365 samples of phase-resolved PD (PRPD) data, is developed by measurement carried out on transformer artificial defect models (having different sizes of defect) under a specific applied voltage, to be used for proposed algorithm validation. In the first step, each set of PRPD data is converted into grayscale images to represent different PD defects. Two “image feature extraction” methods, the Local Binary Pattern (LBP), and the Histogram of Oriented Gradient (HOG), are employed to extract features from the obtained gray scale images. Different variants of Support Vector Machine (SVM) are adjusted for optimal classification of PD sources in this process. Impact of the employed parameters in the image processing such as image resolution, random noise, and phase shift, on identification accuracy is investigated and addressed. It is shown that by using HOG-SVM method 99.3% accuracy can be achieved. This is hardly affected by various external factors. Two case studies have been conducted on multi-source PD for evaluating the performance of the proposed algorithm. A void defect is implemented into the transformer model and the resultant recorded signal is used for the study. The DBSCAN algorithm is used as the mean of PD source clustering and sub-PRPD pattern development. It is shown that HOG-SVM method has superior performance in identifying active sources, under sub-PRPD pattern application. [ABSTRACT FROM AUTHOR]

High-temperature superconducting (HTS) transformers have a promising feature in reduction of total weight, total size, and the losses of large-scale distribution transformers. However, the lower leakage reactance of HTS transformers results in a higher short-circuit fault currents and electromagnetic forces. Therefore, optimization of short-circuit electromagnetic forces is one of the crucial aspects in the design of HTS transformers. In this paper, a novel analytical method is proposed for determination of optimum distributive ratios resulting in minimization of these forces for asymmetrical multi-segment windings of an HTS transformer. Employing these distributive ratios, radial and axial components of short-circuit electromagnetic forces in an HTS transformer are significantly reduced. Two- and three-dimensional (2D and 3D) finite element method (FEM) simulations are employed to verify the analytical method results. [ABSTRACT FROM AUTHOR]

A wind turbine transformer resonance can occur due to high frequency transients at its terminal i.e.; under its energization through a length of cable. Occurrence of resonance can be addressed by a sophisticated transformer design procedure. The goal is to obtain an optimum design capable of controlling the frequency response of the winding in such a way to avoid occurrence of any resonance under transient conditions. Three insulation clearances parameters which are employed for the wind turbine transformer winding design have been investigated in design of a (800 kVA, 690/20,000 V) wind turbine transformer to determine effect of their variation on its frequency response. It is shown that the best way to control the frequency response is to adjust the distance between LV and HV windings while maintaining other clearances as short as possible; realizing limitations enforced by other insulation constraints. Multiple-design algorithm is also investigated and found to be effective in control of the amplification factor under resonance frequency condition. Finally a 20 kV/690 V-400 kVA dry type wind turbine transformer is employed to verify the promising features of this design methodology, through comparison of the frequency responses of the real transformer against the model. [ABSTRACT FROM AUTHOR]

A wind turbine transformer resonance can occur due to high frequency transients at its terminal i.e.; under its energization through a length of cable. Occurrence of resonance can be addressed by a sophisticated transformer design procedure. The goal is to obtain an optimum design capable of controlling the frequency response of the winding in such a way to avoid occurrence of any resonance under transient conditions. Three insulation clearances parameters which are employed for the wind turbine transformer winding design have been investigated in design of a (800 kVA, 690/20,000 V) wind turbine transformer to determine effect of their variation on its frequency response. It is shown that the best way to control the frequency response is to adjust the distance between LV and HV windings while maintaining other clearances as short as possible; realizing limitations enforced by other insulation constraints. Multiple‐design algorithm is also investigated and found to be effective in control of the amplification factor under resonance frequency condition. Finally a 20 kV/690 V–400 kVA dry type wind turbine transformer is employed to verify the promising features of this design methodology, through comparison of the frequency responses of the real transformer against the model. [ABSTRACT FROM AUTHOR]

Summary: Partial discharge (PD) measurement is one of the best methods for condition monitoring of transformers. In this paper, we use 5 different types of defects as follows: scratch on winding insulation, bubble in oil, moisture in insulation paper, a very small free metal particle in the transformer tank, and a fixed sharp metal point on the transformer tank, for our PD‐related studies. Each type of defect is implemented into 1 of the 5 identical transformer models, which had been developed in the authors' recent work. The continuous wavelet transform is applied to each related measured time‐domain PD signals. This process results in an image, for each PD pulse in the time‐frequency domain. Using these images, a gray‐level covariance matrix is constructed. The texture features are extracted from the constructed gray‐level covariance matrix of each PD signal. Principal component analysis is applied on the recorded PD data to reduce its dimension, and then support vector machine is used to classify the computed first 6 principal components of those defects' PD signals. The accurate outcome of defects identification in this work verifies efficiency of the proposed method. [ABSTRACT FROM AUTHOR]

A novel high-voltage direct current (HVdc) power supply which has no transformer or voltage multiplier circuit is presented and analyzed in this paper. This is made possible upon the diodes storage delay phenomenon. This proposed power supply is compact, lightweight, and low cost. Its basic structure includes a diode with a proper reverse recovery specification that plays the role of a step-up transformer in the conventional HVdc supplies and a high-voltage capacitor which stabilizes the output voltage. This structure has remarkable advantages over the conventional transformer-based HVdc supplies, such as compactness, a low ripple output, and a low-cost power supply. Performance of the proposed method and its accuracy are investigated in this paper. The results are verified by implementation of a 1.2-kV prototype supply. [ABSTRACT FROM AUTHOR]

Current-transformer (CT) saturation causes severe distortion in the measured current waveform which may lead to maloperation of the protective devices. This paper proposes a low-cost, power-electronic device to prevent the CT from saturation. The proposed compensator is inserted in series with the relay in the CT secondary circuit and acts as a controlled voltage source (CVS). The proposed CVS generates a time-varying voltage to cancel the voltage developed across the CT burden; therefore, the CT magnetic flux remains almost constant and undistorted during the power system transients. It will be shown that this device can precisely compensate fault current, inrush current, and other probable transient currents despite its simplicity. The proposed device can be employed to compensate the already in-service CTs connected to nondigital and digital relays. Comprehensive computer simulations are carried out to validate the effectiveness of the proposed compensator. The performance of a sample compensator of this type is validated through special high-current laboratory experiments (carried out over several hundred amperes up to 1.6 kA), and the obtained results illustrate the capability of the proposed compensator to prevent CT saturation. [ABSTRACT FROM PUBLISHER]

In this study, a transformer model is proposed to simulate the behaviour of a real transformer, under presence of different types of defects which contribute to partial discharge (PD) generation, as closely as possible. Five different types of defects (scratch on winding insulation, bubble in oil, moisture in insulation paper, very small free metal particle in transformer tank and fixed sharp metal point on transformer tank) are implemented artificially into these transformer models to investigate the resultant PD current signal magnitude and characteristics. Time‐domain PD current waveforms are recorded on those transformer models which have one type of those defects. The resultant statistical PD current wave shapes and texture features are extracted from these captured PD current signals. The principal component analysis (PCA) is used to reduce the dimension of feature spaces which are required to develop the inputs for the classifier. The principal components obtained through PCA are applied to the support vector machine classifier, as an input. The classification results indicate that the extracted texture features (using grey‐level covariance matrix) preserve the best characteristics for separation of the related patterns of those five defect models, accurately. [ABSTRACT FROM AUTHOR]

To avoid saturation of a protective current transformer (CT) operating under an autoreclosing scheme, the CT size should be chosen much higher than a similar CT operating under a single-step fault clearing scheme. The main reason for this significant difference is that the residual flux (caused by the first stage of the fault) cannot be noticeably reduced during the deadtime interval of the reclosing process and, therefore, the occurrence of a subsequent fault can extremely saturate the CT. In this paper, a low-cost, low-power electronic device is developed and introduced to demagnetize the CT under the reclosing deadtime interval. It will be shown that by using this device, the required size of the CT is reduced by about 40%. To develop this device, an existing flux-based demagnetization technique is improved to operate faster and more efficient. The performance of this technique is independent of the CT characteristic parameters and provides promising results despite its simplicity. The proposed device can be employed to de-rate the new CTs to be installed in the system and/or to compensate the existing inservice CTs. Comprehensive computer simulations and laboratory experiments are employed to validate the reliability and effectiveness of the proposed compensation method. [ABSTRACT FROM PUBLISHER]

Due to the presence of excessive noise in the recorded partial discharge (PD) current signals, de-noising of these signals is a crucial task for performing any investigation on the subject. Meanwhile, to accelerate this de-noising process a single PD pulse can be extracted from the train of those recorded pulses, followed by its de-noising. In this paper a single PD pulse is extracted from the train of recorded PD pulses, using noisy recorded data cumulative energy. A de-noising technique based on adaptive neuro-fuzzy inference systems is proposed. To verify the validity of the proposed method, four different sources of PD signals are physically simulated. The proposed method is applied on laboratory recorded signals and is compared with a conventional method which is based on discrete wavelet transform (DWT) and linear adaptive filtering method. Furthermore, the proposed algorithm is used for extraction and de-noising of single PD activities of an on-site recorded data. This method introduces an efficient pulse distortion mitigation tool which requires no adjustment of any pre-set parameter-neither for different noise levels, nor for different kind of PD pulses. This is an important feature of the proposed technique. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Current-transformer (CT) saturation threatens accurate discrimination between internal fault current and magnetizing inrush current of a transformer and endangers the proper operation of a differential relay. Thus, compensation of CT saturation could substantially improve the performance and security of transformer differential relays. So far, almost all of the technical literature in this field has focused exclusively on fault current compensation. However, this paper proposes an efficient compensation algorithm to reconstruct the fault and inrush currents which are distorted by CT saturation. Some of the attractive features of the proposed method are its accuracy, fast response time, desired sample-by-sample output, no dependency on power system topology, immunity against noise and harmonics, and its simplicity. These features are extracted through the application of numerous test cases reflecting a wide range of variations in fault and inrush currents. The proposed algorithm proves to be fast, accurate, and reliable. [ABSTRACT FROM PUBLISHER]

Power transformers are considered to be one of the most essential and costly pieces of equipment in a power system. Identifying insulation faults in the shortest possible time prevents the occurrence of irreparable damage. Partial discharge (PD) is one of the most significant insulation faults. The first step in the study of PD is the precise modeling of transformer winding at high frequencies. In this paper, the finite element method is used to calculate the parameters for a detailed model of transformer winding. For this reason, a detailed model of transformer winding and the analytic formulations are first presented for the calculation of the parameters of the model. Using two-dimensional finite element methods, the 20-kV transformer winding is then simulated according to exact technical specifications and designed using Maxwell software. After that, the parameters for the detailed model presented in this paper are derived and calculated. Finally, the validity of the model in the frequency range is determined by applying a similar PD pulse on the real and simulated models. [ABSTRACT FROM AUTHOR]

To establish a circuit-breaker (CB) online monitoring system, the development of an effective diagnosis framework is essential. The purpose of this online monitoring system is to accurately assess its condition while under operation, and to foresee any risk of failure. Consequently, it would be possible to plan for the required maintenance on the CB sufficiently ahead of a failure occurrence. To fulfill this, a framework is proposed to precisely assess the SF6 CBs' condition using its control circuit signals' waveforms as easy-to-access, easy-to-measure, and noninvasive diagnosis parameters. The features found in these waveforms match the characteristics essential for diagnostic purposes, and could cover 50%–60% of CB failures. A data-mining process is employed to cluster the captured data against past-recorded data (in terms of faulty or healthy condition) of circuit breakers (CBs) diagnosis. To determine the probability distribution function of a CB condition cluster, a classifier is developed. In this model, the CB condition (based on its failure risk) is qualitatively classified into normal, alarm, and emergency states. In addition, to avoid any unnecessary maintenance activities during an alarm state, the condition of CBs in each state is quantified in terms of some probabilistic-based indices. The feasibility and applicability of the proposed methodology are verified using recorded data. [ABSTRACT FROM AUTHOR]

The online condition assessment of circuit breakers (CBs) has been increasingly requested by power utilities in recent years. Trip and close coil current (CC) signature is an effective and noninvasive parameter in CB online condition monitoring. This paper gives an insight into the impacts of the various failures on the coil current waveform, as well as on the CB operation time. The failures and their causes are categorized based on the outcome of these investigations. Finally, a new algorithm using trip/close CC is proposed to detect the mode and cause of CB incipient failures. In this study, the CC patterns are acquired by measurements carried out on (healthy and faulty) CBs of 72.5-kV and 24-kV rating voltages, having SF6 insulation medium, and are equipped with a spring-drive mechanism. [ABSTRACT FROM PUBLISHER]

SUMMARY Current and force calculations in different short-circuit conditions are required for short-circuit performance analysis of a multi-winding traction transformer which is one of the most important requirements in its design process. This paper extends the available low-frequency three-winding star equivalent circuits to develop a novel equivalent circuit for the four-winding traction transformers. The leakage inductances of the traction transformer are determined and employed to calculate the parameters of this developed star model. It is shown that the star equivalent circuit is a valid and appropriate model to simulate the steady-state and dynamic performance of the traction transformer under different short-circuit conditions. To analyze the short-circuit performance of the transformer, the short-circuit currents (simulated by the introduced model) are employed to compute the electromagnetic forces for a typical dry-type traction transformer. The analytical and numerical methods are used for short-circuit force calculations, and those results are compared against each other. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

A ternary dielectric is made of high density polyethylene (HDPE) and organoclay (OC) nanocomposites, through mixing granuls of ethylene vinyl acetate (EVA). The morphological properties of nanocomposites are examined using X-ray diffraction (XRD) spectra and transmission electron microscopy (TEM) which intercalate/exfoliate morphology of clay particles. It is shown that the electrical and mechanical properties of HDPE/EVA binary blend will be enhanced significantly when OC was treated with EVA compound. The insulation material which is developed in this work can be employed to insulate the adjacent core steel sheets of a high voltage transformer. [ABSTRACT FROM AUTHOR]

The proper and reliable operation of circuit breakers (CBs) directly affects the reliability and continuity of electricity services in a power systems. Condition-based maintenance (CBM) is the best economic CB maintenance strategy through its online monitoring (OLM) possibilities. Since there is a large number of CBs in a power system, to equip all CBs with OLM systems is not economically justifiable however. This paper, as the second part of a two-part paper, presents an effective optimization framework to find the optimal number of CBs to be monitored online as the kernel of CBM process. To prove its feasibility, the proposed approach is applied to the IEEE Roy Billinton Test System, which includes 32 CBs. The impacts of interest rate and load interruption cost variations as well as nonoptimum selection of CBs for monitoring on the results are also discussed in this paper. The results of numerical analyses of the case study presented in this paper demonstrate how the proposed method can be employed for maintenance management of power system CBs. [ABSTRACT FROM PUBLISHER]

Recognition of the circuit-breaker's (CB) vital role in reliable operation and protection of power systems (i.e., during energization, disconnecting loads, and clearing faults), helps to understand the requirement and importance of its maintenance management as well as maintenance scheduling. Condition-based maintenance (CBM), employing online monitoring (OLM) of CBs, has been long reported as the most practical maintenance policy on the power system CBs. There are a large number of CBs in a power system to be monitored; however, to address the financial limitations for OLM implementation (in utilities), a method will be proposed to find the most critical breakers for enforcing effectively the CBs CBM planning in this power system. This paper employs some qualitative and quantitative criteria to develop this method. While, the former criterion is deals with through assessing the condition of CBs through fuzzy sets theory. And the latter criterion is dealt with through the evaluation of CBs' influence on the overall system reliability (through introduced indices). This method is applied on a sample transmission substation with a breaker-and-a-half configuration. Numerical analysis of this simulation results demonstrates how this method can be employed to prioritize the CBs for OLM. [ABSTRACT FROM PUBLISHER]

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Distributed power generation and the ever-growing load demand have caused fault current levels to exceed the nominal rating of the power system devices, and fault current limiters are more needed. Superconducting fault current limiter (SFCL) forms an important category of current limiters. In this paper, a novel flux-based model for the inductive shield-type high-temperature SFCL is developed based on the Bean model. This model is employed to simulate the SFCL performance in a sample circuit. Utilizing the model, the signal characterization of the limited current is determined. A prototype laboratory scale SFCL has been fabricated with superconducting rings. Yttrium barium copper oxide powders have been used for superconducting ring production. The critical current density of fabricated rings has been measured with an innovative method based on application of a magnet device. The fabricated SFCL has been tested in a circuit by applying different types of faults. The related experimental results are recorded and compared with the model results. The results obtained based on the modeling shows full compatibility with the experimental results. [ABSTRACT FROM AUTHOR]