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20 pages, 2419 KiB

Open AccessArticle

Prediction Model for Dissolved Gas Concentration in Transformer Oil Based on Modified Grey Wolf Optimizer and LSSVM with Grey Relational Analysis and Empirical Mode Decomposition

by Bing Zeng, Jiang Guo, Fangqing Zhang, Wenqiang Zhu, Zhihuai Xiao, Sixu Huang and Peng Fan

Energies 2020, 13(2), 422; https://doi.org/10.3390/en13020422 - 15 Jan 2020

Cited by 24 | Viewed by 3103

Abstract

Oil-immersed transformer is one of the most important components in the power system. The dissolved gas concentration prediction in oil is vital for early incipient fault detection of transformer. In this paper, a model for predicting the dissolved gas concentration in power transformer [...] Read more.

Oil-immersed transformer is one of the most important components in the power system. The dissolved gas concentration prediction in oil is vital for early incipient fault detection of transformer. In this paper, a model for predicting the dissolved gas concentration in power transformer based on the modified grey wolf optimizer and least squares support vector machine (MGWO-LSSVM) with grey relational analysis (GRA) and empirical mode decomposition (EMD) is proposed, in which the influence of transformer load, oil temperature and ambient temperature on gas concentration is taken into consideration. Firstly, GRA is used to analyze the correlation between dissolved gas concentration and transformer load, oil temperature and ambient temperature, and the optimal feature set affecting gas concentration is extracted and selected as the input of the prediction model. Then, EMD is used to decompose the non-stationary series data of dissolved gas concentration into stationary subsequences with different scales. Finally, the MGWO-LSSVM is used to predict each subsequence, and the prediction values of all subsequences are combined to get the final result. DGA samples from two transformers are used to verify the proposed method, which shows high prediction accuracy, stronger generalization ability and robustness by comparing with LSSVM, particle swarm optimization (PSO)-LSSVM, GWO-LSSVM, MGWO-LSSVM, EMD-PSO-LSSVM, EMD-GWO-LSSVM, EMD-MGWO-LSSVM, GRA-EMD-PSO-LSSVM and GRA-EMD-GWO-LSSVM. Full article

(This article belongs to the Special Issue Power Transformer Condition Assessment)

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25 pages, 13275 KiB

Open AccessFeature PaperArticle

A Comprehensive Analysis of Windings Electrical and Mechanical Faults Using a High-Frequency Model

by Mehran Tahir and Stefan Tenbohlen

Energies 2020, 13(1), 105; https://doi.org/10.3390/en13010105 - 24 Dec 2019

Cited by 17 | Viewed by 6029

Abstract

The measurement procedures for frequency response analysis (FRA) of power transformers are well documented in IEC and IEEE standards. However, the interpretation of FRA results is still far from reaching an accepted methodology and is limited to the analysis of the experts. The [...] Read more.

The measurement procedures for frequency response analysis (FRA) of power transformers are well documented in IEC and IEEE standards. However, the interpretation of FRA results is still far from reaching an accepted methodology and is limited to the analysis of the experts. The dilemma is that there are limited case studies available to understand the effect of different faults. Additionally, due to the destructive nature, it is not possible to apply the real mechanical deformations in the transformer windings to obtain the data. To solve these issues, in this contribution, the physical geometry of a three-phase transformer is simulated using 3D finite integration analysis to emulate the real transformer operation. The novelty of this model is that FRA traces are directly obtained from the 3D model of windings without estimating and solving lumped parameter circuit models. At first, the method is validated with a simple experimental setup. Afterwards, different mechanical and electrical faults are simulated, and their effects on FRA are discussed objectively. A key contribution of this paper is the winding assessment factor it introduces based on the standard deviation of difference (SDD) to detect and classify different electrical and mechanical faults. The results reveal that the proposed model provides the ability of precise and accurate fault simulation. By using SDD, different deviation patterns can be characterized for different faults, which makes fault classification possible. Thus, it provides a way forward towards the establishment of the standard algorithm for a reliable and automatic assessment of transformer FRA results. Full article

(This article belongs to the Special Issue Power Transformer Condition Assessment)

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15 pages, 2462 KiB

Open AccessFeature PaperArticle

Frequency Response Quality Index for Assessing the Mechanical Condition of Transformer Windings

by Eugeniusz Kornatowski and Szymon Banaszak

Energies 2020, 13(1), 29; https://doi.org/10.3390/en13010029 - 19 Dec 2019

Cited by 9 | Viewed by 2430

Abstract

Frequency response analysis (FRA) is a popular method for assessing a transformer’s mechanical condition. The paper proposes a new method for interpreting the frequency response measurement results. The currently used numerical indices only give one value, which may be misleading in the analysis, [...] Read more.

Frequency response analysis (FRA) is a popular method for assessing a transformer’s mechanical condition. The paper proposes a new method for interpreting the frequency response measurement results. The currently used numerical indices only give one value, which may be misleading in the analysis, while the proposed frequency response quality index (FRQI) tool analyses three separate features in the whole frequency range. The applied numerical calculations technique allows for estimations of not only the values of the average quality indices, but also locally for given frequency ranges of the analysed spectrum. It allows for determination of the problems that can be found in the active part of a transformer. The presented results come from three transformers, representing cases of typical faults. Two of them are from industry, while one was used for deformational tests in laboratory conditions. The proposed FRQI method showed its usefulness in FRA test results analysis and may be introduced into the automated assessment of such data. Each of the component parameters is sensitive to other types of differences observed between the compared frequency response curves, and may be used as a good quality detection tool. Full article

(This article belongs to the Special Issue Power Transformer Condition Assessment)

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17 pages, 6232 KiB

Open AccessArticle

Quantitative Analysis of the Sensitivity of UHF Sensor Positions on a 420 kV Power Transformer Based on Electromagnetic Simulation

by Chandra Prakash Beura, Michael Beltle, Stefan Tenbohlen and Martin Siegel

Energies 2020, 13(1), 3; https://doi.org/10.3390/en13010003 - 18 Dec 2019

Cited by 27 | Viewed by 3865

Abstract

With an increasing interest in ultra-high frequency (UHF) partial discharge (PD) measurements for the continuous monitoring of power transformers, it is necessary to know where to place the UHF sensors on the tank wall. Placing a sensor in an area with many obstructions [...] Read more.

With an increasing interest in ultra-high frequency (UHF) partial discharge (PD) measurements for the continuous monitoring of power transformers, it is necessary to know where to place the UHF sensors on the tank wall. Placing a sensor in an area with many obstructions may lead to a decrease in sensitivity to the UHF signals. In this contribution, a previously validated simulation model of a three-phase 300 MVA, 420 kV power transformer is used to perform a sensitivity analysis to determine the most sensitive sensor positions on the tank wall when PD activity occurs inside the windings. A matrix of UHF sensors located on the transformer tank is used to perform the sensitivity analysis. Some of the windings are designed as layer windings, thus preventing the UHF signals from traveling through them and creating a realistic situation with very indirect propagation from source to sensor. Based on these findings, sensor configurations optimized for UHF signal sensitivity, which is also required for PD source localization, are recommended for localization purposes. Additionally, the propagation and attenuation of the UHF signals inside the windings and the tank are discussed in both oil and air. Full article

(This article belongs to the Special Issue Power Transformer Condition Assessment)

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18 pages, 1410 KiB

Open AccessArticle

A Transformer Fault Diagnosis Model Based On Hybrid Grey Wolf Optimizer and LS-SVM

by Bing Zeng, Jiang Guo, Wenqiang Zhu, Zhihuai Xiao, Fang Yuan and Sixu Huang

Energies 2019, 12(21), 4170; https://doi.org/10.3390/en12214170 - 01 Nov 2019

Cited by 44 | Viewed by 3693

Abstract

Dissolved gas analysis (DGA) is a widely used method for transformer internal fault diagnosis. However, the traditional DGA technology, including Key Gas method, Dornenburg ratio method, Rogers ratio method, International Electrotechnical Commission (IEC) three-ratio method, and Duval triangle method, etc., suffers from shortcomings [...] Read more.

Dissolved gas analysis (DGA) is a widely used method for transformer internal fault diagnosis. However, the traditional DGA technology, including Key Gas method, Dornenburg ratio method, Rogers ratio method, International Electrotechnical Commission (IEC) three-ratio method, and Duval triangle method, etc., suffers from shortcomings such as coding deficiencies, excessive coding boundaries and critical value criterion defects, which affect the reliability of fault analysis. Grey wolf optimizer (GWO) is a novel swarm intelligence optimization algorithm proposed in 2014 and it is easy for the original GWO to fall into the local optimum. This paper presents a new meta-heuristic method by hybridizing GWO with differential evolution (DE) to avoid the local optimum, improve the diversity of the population and meanwhile make an appropriate compromise between exploration and exploitation. A fault diagnosis model of hybrid grey wolf optimized least square support vector machine (HGWO-LSSVM) is proposed and applied to transformer fault diagnosis with the optimal hybrid DGA feature set selected as the input of the model. The kernel principal component analysis (KPCA) is used for feature extraction, which can decrease the training time of the model. The proposed method shows high accuracy of fault diagnosis by comparing with traditional DGA methods, least square support vector machine (LSSVM), GWO-LSSVM, particle swarm optimization (PSO)-LSSVM and genetic algorithm (GA)-LSSVM. It also shows good fitness and fast convergence rate. Accuracies calculated in this paper, however, are significantly affected by the misidentifications of faults that have been made in the DGA data collected from the literature. Full article

(This article belongs to the Special Issue Power Transformer Condition Assessment)

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22 pages, 4139 KiB

Open AccessArticle

A Novel Fault Diagnosis Method for Power Transformer Based on Dissolved Gas Analysis Using Hypersphere Multiclass Support Vector Machine and Improved D–S Evidence Theory

by Haikun Shang, Junyan Xu, Zitao Zheng, Bing Qi and Liwei Zhang

Energies 2019, 12(20), 4017; https://doi.org/10.3390/en12204017 - 22 Oct 2019

Cited by 25 | Viewed by 3240

Abstract

Power transformers are important equipment in power systems and their reliability directly concerns the safety of power networks. Dissolved gas analysis (DGA) has shown great potential for detecting the incipient fault of oil-filled power transformers. In order to solve the misdiagnosis problems of [...] Read more.

Power transformers are important equipment in power systems and their reliability directly concerns the safety of power networks. Dissolved gas analysis (DGA) has shown great potential for detecting the incipient fault of oil-filled power transformers. In order to solve the misdiagnosis problems of traditional fault diagnosis approaches, a novel fault diagnosis method based on hypersphere multiclass support vector machine (HMSVM) and Dempster–Shafer (D–S) Evidence Theory (DET) is proposed. Firstly, proper gas dissolved in oil is selected as the fault characteristic of power transformers. Secondly, HMSVM is employed to diagnose transformer fault with selected characteristics. Then, particle swarm optimization (PSO) is utilized for parameter optimization. Finally, DET is introduced to fuse three different fault diagnosis methods together, including HMSVM, hybrid immune algorithm (HIA), and kernel extreme learning machine (KELM). To avoid the high conflict between different evidences, in this paper, a weight coefficient is introduced for the correction of fusion results. Results indicate that the fault diagnosis based on HMSVM has the highest probability to identify transformer faults among three artificial intelligent approaches. In addition, the improved D–S evidence theory (IDET) combines the advantages of each diagnosis method and promotes fault diagnosis accuracy. Full article

(This article belongs to the Special Issue Power Transformer Condition Assessment)

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17 pages, 7075 KiB

Open AccessArticle

Modeling of the Winding Hot-Spot Temperature in Power Transformers: Case Study of the Low-Loaded Fleet

by Michał Kunicki, Sebastian Borucki, Andrzej Cichoń and Jerzy Frymus

Energies 2019, 12(18), 3561; https://doi.org/10.3390/en12183561 - 17 Sep 2019

Cited by 13 | Viewed by 3051

Abstract

A proposal of the dynamic thermal rating (DTR) applied and optimized for low-loaded power transformers equipped with on-line hot-spot (HS) measuring systems is presented in the paper. The proposed method concerns the particular population of mid-voltage (MV) to high-voltage (HV) transformers, a case [...] Read more.

A proposal of the dynamic thermal rating (DTR) applied and optimized for low-loaded power transformers equipped with on-line hot-spot (HS) measuring systems is presented in the paper. The proposed method concerns the particular population of mid-voltage (MV) to high-voltage (HV) transformers, a case study of the population of over 1500 units with low average load is analyzed. Three representative real-life working units are selected for the method evaluation and verification. Temperatures used for analysis were measured continuously within two years with 1 h steps. Data from 2016 are used to train selected models based on various machine learning (ML) algorithms. Data from 2017 are used to verify the trained models and to validate the method. Accuracy analysis of all applied ML algorithms is discussed and compared to the conventional thermal model. As a result, the best accuracy of the prediction of HS temperatures is yielded by a generalized linear model (GLM) with mean prediction error below 0.71% for winding HS. The proposed method may be implemented as a part of the technical assessment decision support systems and freely adopted for other electrical power apparatus after relevant data are provided for the learning process and as predictors for trained models. Full article

(This article belongs to the Special Issue Power Transformer Condition Assessment)

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17 pages, 6366 KiB

Open AccessEditor’s ChoiceArticle

Calibration Proposal for UHF Partial Discharge Measurements at Power Transformers

by Martin Siegel, Sebastian Coenen, Michael Beltle, Stefan Tenbohlen, Marc Weber, Pascal Fehlmann, Stefan M. Hoek, Ulrich Kempf, Robert Schwarz, Thomas Linn and Jitka Fuhr

Energies 2019, 12(16), 3058; https://doi.org/10.3390/en12163058 - 08 Aug 2019

Cited by 27 | Viewed by 6035

Abstract

The continuous, non-intermitted service of electrical grids relies on the reliability of their assets, e.g., power transformers. Local insulation defects can result in serve failures such as breakdowns with severe subsequent costs. The prevention of such events is crucial. Hence, partial discharge (PD) [...] Read more.

The continuous, non-intermitted service of electrical grids relies on the reliability of their assets, e.g., power transformers. Local insulation defects can result in serve failures such as breakdowns with severe subsequent costs. The prevention of such events is crucial. Hence, partial discharge (PD) activity at power transformers is evaluated directly in the factory before shipment. Additionally, PD activity can be monitored during service using the ultra-high frequency (UHF) method. In this contribution, a calibration procedure is proposed for the UHF method. The calibration process is required to ensure both, reproducibility and comparability of UHF measurements: Only a calibrated UHF measurement procedure can be introduced supplementary to IEC 60270 in acceptance tests of power transformers. The proposed calibration method considers two factors: The influence of the UHF-antenna’s sensitivity and the PD recorder characteristics including accessories such as cable damping, pre-amplifier, etc. The former is addressed by a characterization of UHF sensors using the standard antenna factor (AF) in a gigahertz transverse electromagnetic (GTEM) cell. The PD recorder’s influence is corrected by using a defined, invariable test signal as reference for all recording devices. A practical evaluation of the proposed calibration procedure is performed in a laboratory setup using different UHF recording devices and UHF sensors using artificial PD signals and real voltage-driven PD sources. Full article

(This article belongs to the Special Issue Power Transformer Condition Assessment)

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14 pages, 5753 KiB

Open AccessArticle

Frequency Response Modeling of Transformer Windings Utilizing the Equivalent Parameters of a Laminated Core

by Konstanty Marek Gawrylczyk and Katarzyna Trela

Energies 2019, 12(12), 2371; https://doi.org/10.3390/en12122371 - 20 Jun 2019

Cited by 11 | Viewed by 4547

Abstract

The aim of the article is to present the method for modeling transformer winding inductance, taking into account the complex magnetic permeability and equivalent electric conductivity of the magnetic core. In the first stage of the research, a physical model of a 24-turn [...] Read more.

The aim of the article is to present the method for modeling transformer winding inductance, taking into account the complex magnetic permeability and equivalent electric conductivity of the magnetic core. In the first stage of the research, a physical model of a 24-turn coil wound on the distribution transformer core was prepared. The Frequency Response Analysis (FRA) measurements of the coil were taken; then, the inductance of the coil as a function of frequency was calculated from the received frequency response curves. In the second stage, two-dimensional (2D) and three-dimensional (3D) computer models of the coil based on the finite element method (FEM) were established. In order to obtain the equivalent inductance characteristics of the winding modeled in 2D and 3D in a wide frequency range, the equality of the reluctance of the limbs and yokes in both models was assured. In the next stage of the research, utilization of the equivalent properties for the laminated magnetic material simulations was proposed. This outcome can be used to calculate the frequency response of the winding of the power transformer. The other obtained result is the method for modeling the resonance slope, which is visible on the inductance curve received from the FRA measurement. Full article

(This article belongs to the Special Issue Power Transformer Condition Assessment)

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18 pages, 4171 KiB

Open AccessArticle

Comparative Analysis of the Results of Diagnostic Measurements with an Internal Inspection of Oil-Filled Power Transformers

by Tomasz Piotrowski, Pawel Rozga and Ryszard Kozak

Energies 2019, 12(11), 2155; https://doi.org/10.3390/en12112155 - 05 Jun 2019

Cited by 17 | Viewed by 3324

Abstract

This article presents a description of four independent case studies concerning situations when power transformers were directed to internal inspection. This inspection was the result of a specific case of a routine diagnostic procedure that was carried out and, where the transformer was [...] Read more.

This article presents a description of four independent case studies concerning situations when power transformers were directed to internal inspection. This inspection was the result of a specific case of a routine diagnostic procedure that was carried out and, where the transformer was switched off by a Buchholz gas relay. The case studies described were selected such that they represented situations when availability of historical data on the previous measurements was limited and a quick diagnosis had to be made on the basis of the results from the last measurement. In all of the cases presented here, the analysis of the gases dissolved in oil had played an important role in the detection of the defects that turned out to be dangerous for further exploitation of the transformers considered. The first signal about a possible developing defect was elicited solely from the measurements of the oil samples taken from the transformer in service. However, more detailed recognition and initial localization of the defect was possible after additional supplementary measurements (winding resistance, sweep frequency response analysis, etc.), which required the transformer to be switched off. The conducted sequence of actions, based on the developed diagnostic procedure, indicated the possibility of effective and early withdrawal of the transformer from operation, before it underwent a serious failure. Full article

(This article belongs to the Special Issue Power Transformer Condition Assessment)

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21 pages, 6381 KiB

Open AccessArticle

A General Transformer Evaluation Method for Common-Mode Noise Behavior

by Kaining Fu, Wei Chen and Subin Lin

Energies 2019, 12(10), 1984; https://doi.org/10.3390/en12101984 - 23 May 2019

Cited by 5 | Viewed by 7996

Abstract

In isolated power converters, the transformer is a key part of voltage transformation and isolation. Since common-mode (CM) noise is rather difficult to suppress compared with different-mode (DM) noise, more and more scholars are paying attention to the characteristics of CM noise, especially [...] Read more.

In isolated power converters, the transformer is a key part of voltage transformation and isolation. Since common-mode (CM) noise is rather difficult to suppress compared with different-mode (DM) noise, more and more scholars are paying attention to the characteristics of CM noise, especially in high-frequency CM noise behaviors. CM noise can be further divided into conducted CM noise and radiated CM noise, and the main focus of this paper is on conducted CM noise. The CM coupling capacitance of the transformer is one of the main contributors of CM noise, which has been verified in many previous studies. Hence, eliminating the CM noise in a transformer coupling path can significantly lower the whole CM noise level of the converter. Professional conducted electromagnetic interference (EMI) testing instruments are quite expensive. In this paper, a general transformer evaluation technique for CM noise behavior is proposed. Only a signal generator and oscilloscope can achieve transformer CM noise behavior evaluation. PCB planar flyback transformers are designed, and a series of noise spectrums and voltage waveforms can verify the effectiveness of the proposed transformer evaluation method. The flyback adapter porotype can pass the EMI standard limited line EN55022 class B by the proposed evaluation method. Full article

(This article belongs to the Special Issue Power Transformer Condition Assessment)

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16 pages, 4825 KiB

Open AccessArticle

The Influence of Pressure on the Discharge along Oil-Paper Interface under AC Stress

by Guangcai Hu, Guangning Wu, Rui Yu, Peng Zhou, Bo Gao, Yan Yang and Kai Liu

Energies 2019, 12(10), 1846; https://doi.org/10.3390/en12101846 - 15 May 2019

Cited by 9 | Viewed by 2491

Abstract

This study explores the influence of hydrostatic pressure on the discharge along the oil-paper interface under AC voltage, especially for the normal operating condition and breakdown. In this paper, an experimental platform was set up to record the partial discharge (PD) parameters of [...] Read more.

This study explores the influence of hydrostatic pressure on the discharge along the oil-paper interface under AC voltage, especially for the normal operating condition and breakdown. In this paper, an experimental platform was set up to record the partial discharge (PD) parameters of the test sample under different hydrostatic pressures, while the applied AC voltage was increased to final flashover voltage step by step. Experimental results showed that higher hydrostatic pressure had different effects on PD under different voltages. Higher pressure decreased the PD energy and increased the flashover voltage. Furthermore, under higher hydrostatic pressure, discharge traces (white mark) were found on the surface of the samples after intense discharging on the oil-paper interfaces, indicating that the hydrostatic pressure can affect the gas generation and dissipation process underneath the surface of the pressboards. Finally, the mechanism of how hydrostatic pressure influences the PD, flashover voltage, and white mark was interpreted based on the bubble theory. The results derived in this paper can be helpful for an optimal design and reasonable operation of oil-paper insulation systems, especially for power transformers. Full article

(This article belongs to the Special Issue Power Transformer Condition Assessment)

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13 pages, 5241 KiB

Open AccessArticle

Effect of Oil Regeneration on Improving Paper Conditions in a Distribution Transformer

by Qiang Liu, Ramamoorthi Venkatasubramanian, Shanika Matharage and Zhongdong Wang

Energies 2019, 12(9), 1665; https://doi.org/10.3390/en12091665 - 01 May 2019

Cited by 11 | Viewed by 5861

Abstract

Managing a large fleet of ageing assets has become a technical challenge faced by many electricity utilities in developed countries. Asset managers are increasingly interested in techniques that can help extend the useful lifetime of a transformer. Oil regeneration is one of such [...] Read more.

Managing a large fleet of ageing assets has become a technical challenge faced by many electricity utilities in developed countries. Asset managers are increasingly interested in techniques that can help extend the useful lifetime of a transformer. Oil regeneration is one of such techniques. In this paper, oil regeneration experiments were performed on a 6.4/0.4 kV retired distribution transformer to investigate the effect of oil regeneration on improving paper conditions. Oil regeneration was conducted in two stages, with the first stage aimed at ‘cleaning the oil’ and the second stage targeted at ‘cleaning the paper’. Oil samples were collected at regular intervals throughout the process and paper samples were obtained from the transformer before and after each oil regeneration stage. It was found that oil regeneration restores oil parameters, including moisture and acidity, similar to those of new oils at the end of stage 1. Analysis of paper samples indicated a reduction in paper moisture at the end of stage 2 by nearly 40%, while low molecular weight acids (LMA) in paper exhibited a reduction by around 30% on average. It is found that the extended oil regeneration period, i.e., stage 2, is necessary to improve the paper condition and hence to reduce the paper ageing rate. Full article

(This article belongs to the Special Issue Power Transformer Condition Assessment)

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13 pages, 2815 KiB

Open AccessArticle

Regeneration of Transformer Insulating Fluids Using Membrane Separation Technology

by Leila Safiddine, Hadj-Ziane Zafour, Ungarala Mohan Rao and Issouf Fofana

Energies 2019, 12(3), 368; https://doi.org/10.3390/en12030368 - 24 Jan 2019

Cited by 25 | Viewed by 3957

Abstract

Oxidation of oil/paper insulation initiates premature aging and introduces carboxylic acids with eventual increase in oil acidity, which hampers the properties of the oil. In this paper, a membrane separation technology-based purification process for aged insulation oil has been evaluated and reported. The [...] Read more.

Oxidation of oil/paper insulation initiates premature aging and introduces carboxylic acids with eventual increase in oil acidity, which hampers the properties of the oil. In this paper, a membrane separation technology-based purification process for aged insulation oil has been evaluated and reported. The intent of the present study is to eliminate carboxylic acids, dissolved decay contents and other colloidal contamination present in aged oil and enhance the useful life of oil. The potential of the membrane treatment process has been demonstrated using Ultraviolet Visible Infrared Spectroscopy and Fourier Transform Infrared Spectroscopy diagnostic measurements for oil and membrane. Additionally, membrane retention properties like membrane flux, retention coefficient, sorption time and membrane mass have been analyzed to understand the treatment process. To further evaluate the performance of the membrane and effectiveness of the treatment process, acidity, dielectric dissipation factor, relative permittivity, and resistivity measurements of the oil before and after filtration have been also reported. The proposed membrane purification method has been tested for Algerian utility in-service oil samples. It is inferred that, membrane filtration method is a simple and effective method for treatment of aged oils and aids in extending the remnant life of the oil. The procedure is economically attractive because of increasing prices for transformer liquids, cost effective and environmentally sounds. Full article

(This article belongs to the Special Issue Power Transformer Condition Assessment)

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27 pages, 11676 KiB

Open AccessArticle

Active Dielectric Window: A New Concept of Combined Acoustic Emission and Electromagnetic Partial Discharge Detector for Power Transformers

by Wojciech Sikorski

Energies 2019, 12(1), 115; https://doi.org/10.3390/en12010115 - 29 Dec 2018

Cited by 25 | Viewed by 5679

Abstract

The detection and location of partial discharge (PD) is of great significance in evaluating the insulation condition of power transformers. This paper presents an active dielectric window (ADW), which is a new concept of combined acoustic emission (AE) and electromagnetic PD detector intended [...] Read more.

The detection and location of partial discharge (PD) is of great significance in evaluating the insulation condition of power transformers. This paper presents an active dielectric window (ADW), which is a new concept of combined acoustic emission (AE) and electromagnetic PD detector intended for assembly in a transformer’s inspection hatch. The novelty of this design lies in the fact that all structural components of an ultrasonic transducer, i.e., the matching and backing layer, an active piezoelectric element with electrodes, and electrical leads, were built into a dielectric window. Due to the fact that its construction was optimized for work in mineral oil, it is characterized by much higher sensitivity of PD detection than a general-purpose AE sensor mounted outside a transformer tank. Laboratory tests showed that the amplitude of the AE pulses generated by creeping discharges, which were registered by the ADW, was around five times higher on average than the pulses registered by a commonly used contact transducer. A possibility of simultaneous detection of acoustic and electromagnetic pulses (with an integrated ultra-high frequency (UHF) antenna) is an important advantage of the ADW. It allows for an increase in the reliability of PD detection, the accuracy of defect location, and the effectiveness of disturbance identification. This paper describes in detail the applied methods of designing and modeling the ADW components, the manufacturing process of the prototype construction, and the results of preliminary laboratory tests, in which the detector’s sensitivity as well as the efficiency of the PD source location were evaluated. Full article

(This article belongs to the Special Issue Power Transformer Condition Assessment)

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Review

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30 pages, 5282 KiB

Open AccessReview

Methanol Marker for the Detection of Insulating Paper Degradation in Transformer Insulating Oil

by Jocelyn Jalbert, Esperanza M. Rodriguez-Celis, Oscar H. Arroyo-Fernández, Steve Duchesne and Brigitte Morin

Energies 2019, 12(20), 3969; https://doi.org/10.3390/en12203969 - 18 Oct 2019

Cited by 24 | Viewed by 4239

Abstract

This manuscript presents a comprehensive literature review with the aim to provide readers a reference document with up-to-date information on the field of methanol use as a chemical marker. It has been a little more than a decade since methanol was first introduced [...] Read more.

This manuscript presents a comprehensive literature review with the aim to provide readers a reference document with up-to-date information on the field of methanol use as a chemical marker. It has been a little more than a decade since methanol was first introduced as a marker for assessing solid insulation condition in power transformers. It all started when methanol was identified in the laboratory during thermal ageing tests carried out with oil-immersed insulating papers and was subsequently also identified in transformer field samples. The first publication on the subject was released in 2007 by our research group. This review covers the methanol fundamentals such as the analytical methods for its determination in transformer oil, which is generally performed by headspace gas chromatography with mass spectrometry or flame ionization as a detector. Current standardization efforts for its determination include ASTM working group 30948 and IEC TC10. Kinetic studies have confirmed the relationship between methanol generation, the number of broken 1,4-β-glycosidic bonds of cellulose and changes in mechanical properties. Laboratory tests have confirmed its stability at different accelerated ageing temperatures. Several utilities have identified methanol during field measurements, case studies on power and some distribution transformers are presented, as well as transformer postmortem investigations. These field-testing results demonstrate its utility in monitoring cellulosic insulation degradation. Recently, a model of methanol interpretation has become available that allows for evaluation of the average degree of polymerization of core type transformer cellulose winding. Methanol has a role as an indicator of cellulosic solid insulation ageing in transformer mineral oil, and it is expected that in the future it will be in routine use by utilities. Full article

(This article belongs to the Special Issue Power Transformer Condition Assessment)

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