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With the increasing age of the primary equipment of the electrical grids there exists also
an increasing need to know its internal condition. For this purpose, off- and online diagnostic methods
and systems for power transformers have been developed in recent years. Online monitoring is
used continuously during operation and offers possibilities to...
Contexts in source publication
Context 1
... failure data of the full population were analyzed as a function of the primary location (component) in the transformer where the failure was initiated. Figure 1 shows the failure location analysis for substation transformers with voltages 100 kV and above, respectively. Energies 2016, 9, 347 3 of 25 ...
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... failure data of the full population were analyzed as a function of the primary location (component) in the transformer where the failure was initiated. Figure 1 shows the failure location analysis for substation transformers with voltages 100 kV and above, respectively. [4]. ...
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... this case, the transformer was equipped with three oil valves and therefore three identical UHF Sensors were installed. Figure 10 shows the positions of the UHF PD sensors (UHF 1-UHF 3) and the acoustic PD sensors (A1-A6). At nominal voltage, UHF signals from internal PD sources were detectable with all three UHF sensors. ...
Context 4
... this case, the transformer was equipped with three oil valves and therefore three identical UHF Sensors were installed. Figure 10 shows the positions of the UHF PD sensors (UHF 1-UHF 3) and the acoustic PD sensors (A1-A6). Energies 2016, 9, 347 9 of 25 Figure 9 shows a bar graph for each pattern. ...
Context 5
... this case, the transformer was equipped with three oil valves and therefore three identical UHF Sensors were installed. Figure 10 shows the positions of the UHF PD sensors (UHF 1-UHF 3) and the acoustic PD sensors (A1-A6). At nominal voltage, UHF signals from internal PD sources were detectable with all three UHF sensors. ...
Context 6
... illustrated in Figure 10, the position of the located PD source is in the vicinity of the tap changer. Inaccuracy is thereby within the range of approx. ...
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... interpretation of particular differences between two transfer function curves is the missing link between failure identification, measurement and assessment of the transformer. Figure 11 shows the frequency ranges with their corresponding winding parts being sensitive towards mechanical changes as identified by CIGRE WG A2.26 [20]. For smaller power transformers, the frequency ranges of interest tend to be shifted towards higher frequency. ...
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... time of flights of the acoustic signals can be computed accurately with the help of the Hinkley criterion [9], which is based on the signal energy of the measured signal [15]. As illustrated in Figure 10, the position of the located PD source is in the vicinity of the tap changer. Inaccuracy is thereby within the range of approx. ...
Context 9
... interpretation of particular differences between two transfer function curves is the missing link between failure identification, measurement and assessment of the transformer. Figure 11 shows the frequency ranges with their corresponding winding parts being sensitive towards mechanical changes as identified by CIGRE WG A2.26 [20]. For smaller power transformers, the frequency ranges of interest tend to be shifted towards higher frequency. ...
Context 10
... two most commonly used test types for transfer function measurement of power transformers are the so-called end-to-end transfer function measurement TFEE(f) and the capacitive inter-winding (CI) measurement TFCI(f) [20]. Figure 12 shows the associated connection diagrams. The obtained transfer function of a measured phase then is: ...
Context 11
... two most commonly used test types for transfer function measurement of power transformers are the so-called end-to-end transfer function measurement TF EE (f ) and the capacitive inter-winding (CI) measurement TF CI (f ) [20]. Figure 12 shows the associated connection diagrams. The obtained transfer function of a measured phase then is: ...
Context 12
... order to explain misinterpretation, a case study is presented here. Figure 13 shows two traces of the middle phase of a 30 kVA/10 kV transformer measured at two different temperatures. The measurements were carried out on the same day and in a healthy condition. ...
Context 13
... order to explain misinterpretation, a case study is presented here. Figure 13 shows two traces of the middle phase of a 30 kVA/10 kV transformer measured at two different temperatures. The measurements were carried out on the same day and in a healthy condition. ...
Context 14
... order to explain misinterpretation, a case study is presented here. Figure 13 shows two traces of the middle phase of a 30 kVA/10 kV transformer measured at two different temperatures. The measurements were carried out on the same day and in a healthy condition. ...
Context 15
... of the numerical indices are based on only the magnitude response of the transfer function. However, the transfer function has a magnitude and a phase value in each frequency sample, i.e. a vector in the complex plane for each frequency sample, Figure 14. The index, Euclidean distance (ED) [24], calculates the magnitude differences of each frequency and, then, computes the root sum squared of them over the frequency range, Figure 14a. ...
Context 16
... the transfer function has a magnitude and a phase value in each frequency sample, i.e. a vector in the complex plane for each frequency sample, Figure 14. The index, Euclidean distance (ED) [24], calculates the magnitude differences of each frequency and, then, computes the root sum squared of them over the frequency range, Figure 14a. A new index, complex distance (CD), can be defined to include the phase information; it calculates the distance between two samples in the complex plane, Figure 14b,c shows the amounts of both indices for different steps of axial displacements in a winding. ...
Context 17
... index, Euclidean distance (ED) [24], calculates the magnitude differences of each frequency and, then, computes the root sum squared of them over the frequency range, Figure 14a. A new index, complex distance (CD), can be defined to include the phase information; it calculates the distance between two samples in the complex plane, Figure 14b,c shows the amounts of both indices for different steps of axial displacements in a winding. As can be seen, including the phase response does not impair the linearity of the index, but increases the sensitivity of the index to the mechanical change significantly, i.e., it makes the detection of the mismatches between two FRA traces simpler. ...
Context 18
... of the numerical indices are based on only the magnitude response of the transfer function. However, the transfer function has a magnitude and a phase value in each frequency sample, i.e. a vector in the complex plane for each frequency sample, Figure 14. The index, Euclidean distance (ED) [24], calculates the magnitude differences of each frequency and, then, computes the root sum squared of them over the frequency range, Figure 14a. ...
Context 19
... the transfer function has a magnitude and a phase value in each frequency sample, i.e. a vector in the complex plane for each frequency sample, Figure 14. The index, Euclidean distance (ED) [24], calculates the magnitude differences of each frequency and, then, computes the root sum squared of them over the frequency range, Figure 14a. A new index, complex distance (CD), can be defined to include the phase information; it calculates the distance between two samples in the complex plane, Figure 14b,c shows the amounts of both indices for different steps of axial displacements in a winding. ...
Context 20
... index, Euclidean distance (ED) [24], calculates the magnitude differences of each frequency and, then, computes the root sum squared of them over the frequency range, Figure 14a. A new index, complex distance (CD), can be defined to include the phase information; it calculates the distance between two samples in the complex plane, Figure 14b,c shows the amounts of both indices for different steps of axial displacements in a winding. As can be seen, including the phase response does not impair the linearity of the index, but increases the sensitivity of the index to the mechanical change significantly, i.e., it makes the detection of the mismatches between two FRA traces simpler. ...
Context 21
... the experiment the oil is not moved. Figure 16a shows the concentration profile of hydrogen for the two different boundary surfaces. The curves are exponential partial regressions to the corresponding measured values, with C(t) = C 0 exp(´λt). ...
Context 22
... hydrogen, also other fault gases are analyzed with the same experimental setup. Figure 16b shows the gas loss factors λ of all gases for both surface areas. With a linear increasing surface area the gas loss factor also increases linearly. ...
Context 23
... the experiment the oil is not moved. Figure 16a shows the concentration profile of hydrogen for the two different boundary surfaces. The curves are exponential partial regressions to the corresponding measured values, with C(t) = C0 exp(−λt). ...
Context 24
... hydrogen, also other fault gases are analyzed with the same experimental setup. Figure 16b shows the gas loss factors λ of all gases for both surface areas. With a linear increasing surface area the gas loss factor also increases linearly. ...
Context 25
... tests are performed using the same oil volume (100 L) and with a constant surface area between oil and ambient air (0.26 m 2 ). Figure 17a shows the fitted gas loss factors λ for all gases at different temperatures. The gas loss factors over temperature show an exponential increase. ...
Context 26
... the evaporation is also dependent on the influence of temperature, four different temperatures are investigated: room temperature (about 22 ˝ C), 35 ˝ C, 50 ˝ C and 65 ˝ C. All tests are performed using the same oil volume (100 L) and with a constant surface area between oil and ambient air (0.26 m 2 ). Figure 17a shows the fitted gas loss factors λ for all gases at different temperatures. The gas loss factors over temperature show an exponential increase. ...
Context 27
... λH2 value is extrapolated from the values measured in the experiment presented above. Figure 17b shows the concentration trend for hydrogen with the previously made assumptions. The oil concentration of hydrogen in the main tank decreases exponentially. ...
Context 28
... gas loss factor in the conservator tank is set to λ H2 = 0.1, which corresponds to a surface area of 1.5 m 2 and an average temperature of 15 ˝ C. The λ H2 value is extrapolated from the values measured in the experiment presented above. Figure 17b shows the concentration trend for hydrogen with the previously made assumptions. The oil concentration of hydrogen in the main tank decreases exponentially. ...
Context 29
... 600 MVA/380 kV generator step-up unit monitored by an IR-based multi gas analyzer showed in the beginning of July a strong and continuous increase of dissolved combustible gases (Figure 18). Because of the high TDCG rate (total dissolved combustible gases) of more than 100 ppm/day, in parallel to the DGA monitoring system oil samples were analyzed in the laboratory daily. ...
Context 30
... dissolved gas was extracted by headspace and vacuum technology. Hydrocarbons showed very good agreement between monitoring and laboratory values (Figure 18a). The highest deviations occurred with hydrogen, which could be attributed to its high diffusivity. ...
Context 31
... the beginning of August, the total amount of dissolved combustible gases (approximately 5000 ppm) and respective generation rate exceeded the values given as "Condition 4" according to IEEE Std C57.104 [42], which suggests to remove the transformer from service under these circumstances. Despite of the high dissolved combustible gas amounts (Figure 18b) no undissolved gases could be detected in the Buchholz relay. Additionally, the very low level of acetylene led to the decision to keep the transformer in service until a spare transformer would be in place. ...
Context 32
... 600 MVA/380 kV generator step-up unit monitored by an IR-based multi gas analyzer showed in the beginning of July a strong and continuous increase of dissolved combustible gases (Figure 18). Because of the high TDCG rate (total dissolved combustible gases) of more than 100 ppm/day, in parallel to the DGA monitoring system oil samples were analyzed in the laboratory daily. ...
Context 33
... dissolved gas was extracted by headspace and vacuum technology. Hydrocarbons showed very good agreement between monitoring and laboratory values (Figure 18a). The highest deviations occurred with hydrogen, which could be attributed to its high diffusivity. ...
Context 34
... the beginning of August, the total amount of dissolved combustible gases (approximately 5000 ppm) and respective generation rate exceeded the values given as "Condition 4" according to IEEE Std C57.104 [42], which suggests to remove the transformer from service under these circumstances. Despite of the high dissolved combustible gas amounts (Figure 18b) no undissolved gases could be detected in the Buchholz relay. Additionally, the very low level of acetylene led to the decision to keep the transformer in service until a spare transformer would be in place. ...
Context 35
... means that even a perfectly serviced transformer will become wet with increasing age. There are studies which show that the ageing accelerates with higher moisture content and at the same time water is produced due to ageing (Figure 19) [48]. One can conclude that lifetime estimations of cellulosic insulating systems do not only depend on operating temperature but also on moisture content of solid insulation. ...
Context 36
... advanced thermal model is used to calculate the top-oil temperature which is based on IEC 60076-7 model [53]. The thermal-electrical analogy of the model is shown in Figure 21. The thermal ...
Context 37
... advanced thermal model is used to calculate the top-oil temperature which is based on IEC 60076-7 model [53]. The thermal-electrical analogy of the model is shown in Figure 21. The thermal resistances of this model are temperature dependent values and affected by the bottom-oil temperature and the temperature of the oil in the cooler [54]. ...
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Citations
... As the most efficient and economical electric transmission method, ultra-high voltage (UHV) transmission has the advantages of long-distance transmission, large capacity, and low energy loss [1]. There are more than 40 types of power equipment operating on the UHV transmission lines to complete the power transmission and conversion tasks, such as power transformers, reactors, UHV gas-insulated switches, and cables [2]. In the practical electrical engineering site, the above power equipment generally operates under extremely severe conditions, such as a high-voltage field, high-temperature field, and strong mechanical stress [3]. ...
... The moisture generated by the aging reaction can be divided into two forms: (1) The breakage of the cellulose chain in the insulating paper generates some moisture. (2) The oxidation of the hydrocarbon compounds in the insulating oil generates some moisture. Due to the porous structure of the insulating paper, 99% of the moisture exists in the insulating paper, and only 1% of the moisture diffuses into the insulating oil. ...
... Based on the RVM curve of the oil-paper insulation with different aging degrees, Zhou Lijun et al. [20] Energies 2024, 17, 2089 19 of 35 have obtained the following conclusions: (1) The maximum value of the recovery voltage curve increases with the increase in the charging voltage and is significantly affected by the charging time. (2) The central time constant is not easily changed by the external testing conditions (3) The initial slope of the RVM curve is positively correlated with the ratio between the charging time and discharging time, and it is less affected by the charging voltage. However, the above feature parameters are extracted based on the shape of the RVM curve, which has no practical physical meaning. ...
Oil–paper insulation is the critical insulation element in the modern power system. Under a harsh operating environment, oil–paper insulation will deteriorate gradually, resulting in electrical accidents. Thus, it is important to evaluate and monitor the insulation state of oil–paper insulation. Firstly, this paper introduces the geometric structure and physical components of oil–paper insulation and shows the main reasons and forms of oil–paper insulation’s degradation. Then, this paper reviews the existing condition assessment techniques for oil–paper insulation, such as the dissolved gas ratio analysis, aging kinetic model, cellulose–water adsorption isotherm, oil–paper moisture balance curve, and dielectric response technique. Additionally, the advantages and limitations of the above condition assessment techniques are discussed. In particular, this paper highlights the dielectric response technique and introduces its evaluation principle in detail: (1) collecting the dielectric response data, (2) extracting the feature parameters from the collected dielectric response data, and (3) establishing the condition assessment models based on the extracted feature parameters and the machine learning techniques. Finally, two full potential studies are proposed, which research hotspots’ oil–paper insulation and the electrical–chemical joint evaluation technique. In summary, this paper concludes the principles, advantages and limitation of the existing condition assessment techniques for oil–paper insulation, and we put forward two potential research avenues.
... The most common cause of power equipment failure is weak insulation [4]. PD in air cavities embedded in solid insulation can lead to dielectric breakdown and therefore indicate the onset of aging in high-voltage equipment (HV) [5][6][7]. ...
Partial discharge (PD) in cavities can lead to a breakdown in solid insulation and, therefore, indicate the onset of aging in electrical equipment. It is necessary to investigate the activity of single- and double-cavity PD under aging conditions, which is the focus of this study. The results obtained can be useful in monitoring the condition of insulation systems. The factors (pressure, effective work function, and charge decay time constant) that influence PD behaviour under different test conditions were permutated in a PD model. The simulation results agree with measurements obtained for the same applied voltage. The model can generate PD pulse distribution shapes similar to the measured PD of single and double cavities. Both turtle-like and rabbit-ear-like phase-resolved PD (PRPD) patterns were observed during the aging process of the samples in both double and single cavities. This study concludes that the identification of the PD pattern achieved in this work for closely coupled cavities is a step towards characterizing multiple defects phenomena through PD evolution patterns.
... Early detection and resolution of problems through diagnostics can extend the service life of oil-based power transformers for power supply companies [6,[8][9][10]. In the energy sector, oil-based power transformers are important components of electric power systems [1,[11][12][13]. They play a fundamental role in the transmission, conversion and distribution of electricity [1,[14][15][16]. ...
In the electric power industry, oil-type power transformers are considered the main device that ensures reliable transmission of electric power, and their technical capabilities are analyzed. Factors affecting long-term reliable operation of oil-fired power transformers are investigated. In this paper, a simulation model is developed to assess the condition of oil power transformers during rapid diagnosis. A mathematical model has also been developed that allows calculating the absorption coefficients and the general technical condition of oil power transformers depending on the value of the input variables of oil power transformers operating in city power networks. The authors developed a Simulink model for rapid assessment of the technical condition of the oil power transformer. A block diagram is created that allows to determine the value of the technical condition of the oil power transformer according to the vibroacoustic parameters.
... One of the most expensive devices, playing a crucial role, is a power transformer. Its significance in power systems, along with the constantly increasing average age of the transformer population, has led to the development of many diagnostic methods, including modern advanced tests, measurements, and analyses [1,2]. One major aspect of a transformer's technical state is its mechanical condition, characterized by good clamping and the absence of deformations in the windings and the core. ...
... The second one is based on the definition of cross-correlation; therefore, it will only indicate the similarity between the shapes of the compared curves, and is not sensitive to the magnitude of the amplitude. The QI criterion (1) proposed in this work takes into account the similarity of shapes, S, average values, M, and the dynamics of changes, G, in the analyzed data sets (M and G refer to the amplitude). All the most important similarity attributes of the two curves (data sets) are included in one quality indicator. ...
The paper describes the application of the numerical tool quality index for an objective evaluation of complementary frequency response analysis (FRA) and vibroacoustic method (VM) test methods. These diagnostic methods are used in the industrial practice of transformer diagnostics for the assessment of the mechanical condition of windings and a core. The quality index is based on a numerical comparison of the curve obtained from measurements and the reference curve in a frequency domain. The quality index is based on estimators for the covariance, variance, and expected values. First, both methods of analysis were applied to a group of transformers of similar construction, leading conclusions on quality index values being quickly drawn. Next, it was applied to another transformer’s FRA and VM measurement results. The results showed problems with its mechanical condition, thus confirming that the proposed methods can be used in the practical assessment of transformers with these two diagnostic methods. The assessment of transformer’s active-part mechanical condition with complementary FRA and VM methods can be performed much more easily with the proposed quality indices.
... Moreover, geomagnetically induced currents and other DC components of the core cause additional noise sources [4]. The combination of the aforementioned factors creates a complex sound field that is further influenced by the age of the transformer, its loading, and potential anomalies [5]. In this paper, a novel approach is developed to use the sound emission patterns of a transformer to represent and monitor the transformer condition during operation. ...
We present a novel approach for measuring and representing acoustic emissions of transformers. The representation of location-based acoustic emissions enables improved monitoring of transformers, e.g., to detect and predict anomalies and failure events. Here, we introduce 3D acoustic heatmaps to visualize the sound emission patterns of a transformer. We use a combined sensing approach consisting of a 3D point cloud, a microphone array, and beamforming algorithms to generate the distributed representation of acoustic emissions over the entire surface of the transformer. In a further step, we intend to apply machine learning methods to the generated data to enable early fault prevention and predictive maintenance.
... Various studies have been conducted to monitor the cooling system conditions of transformers. Offline and online methods are typically used to assess the condition of the cooling system of transformers [10]. ...
... Peak燗mplitude RMS Crest factor= (10) The impulse factor is used to characterize the impulsiveness or transient nature of a signal. It provides information about sudden changes or impulses within a signal and could be expressed as follows: ...
Cooling fans are one of the critical components of air-forced (AF) dry-type transformers for regulating internal temperatures. Therefore, effective malfunction detection is crucial to maintain the transformer temperature within an acceptable range and prevent overheating. Regular maintenance occurs periodically and issues with cooling fans may arise between maintenance periods, leading to prolonged operation under malfunctioning conditions and potential failures. In addition, utilities typically have online information about whether a fan works or not without providing information about cooling fan malfunctioning circumstances. To address these challenges, this study proposes learning-based online monitoring techniques to detect malfunctions in AF transformer cooling fans. Random forests (RFs) and convolutional neural networks (CNNs) are developed to classify the audio signals from cooling fans into normal and malfunctioning classes. Unlike RFs, which require separate feature extraction, CNNs are trained based on spectrogram images derived from audio signals. Thus, various time-frequency techniques are utilized for feature extraction in RFs. Besides, multiple data augmentation techniques are employed to enhance the dataset size and diversity. Algorithmic performance is optimized through hyperparameter tuning and classifier threshold adjustment. Simulations reveal that CNNs outperform RFs, whereas the latter provides superior interpretability of acoustic features compared to the former.
... Because transformer oil has the characteristics of low viscosity, good insulation, and good heat transfer performance, it can protect transformer cores and windings well. However, with increasing transformer use time, failure will occur more frequently [1]. To solve the problems of low efficiency and high cost of manually inspecting internal faults of transformers, scholars have designed internal fault detection robots for oil-immersed transformers, which are based on vision [2][3][4]. ...
Aiming at the problem that the robot is difficult to locate in the oil-immersed transformer, a visual positioning of the robot is proposed for internal inspection. First, in order to solve the problem of blur, distortion, and low contrast of the image obtained by the camera in the deteriorated and discolored transformer oil, an image enhancement algorithm based on multiscale fusion is developed to provide a reliable data source for robot localization. Then, the FAST key points are extracted and the BRIEF descriptors are calculated from the enhanced images, and the pose transformation of the robot between image frames is calculated by using polar constraint and EPnP method. A pose optimization model of the robot is designed to improve the positioning accuracy. Finally, to verify the effectiveness of the proposed methods, function tests are carried out by using the real continuous image sequence acquired by the robot in Mitsubishi transformer. The experimental results show that the trajectory of the robot in the transformer can be accurately drawn, the position data of the robot can be efficiently obtained, and autonomous positioning of the robot in the transformer can be well achieved.
... The structural characteristics of the transformer parts can be altered by the presence of excessive heat. Reduced age will occur from deviations from the permitted limit of roughly 6°C [2]. ...
Distribution transformer is one of the important equipment in the distribution of electricity to consumers. The electricity demand increases every year, so that the transformer works optimally, it must also be considered regarding the loading. According to IEC 354 if the transformer is loaded stable 80% with conditions around 20℃ and the winding temperature is 98℃, but if the ambient temperature is more than 20℃ then the age of the transformer will decrease. With an average loading of 71.75%, based on the calculation that the predicted useful age of the 160 KVA distribution transformer in 2027 will have an age loss index of 1.1 p.u, so it is estimated that the remaining age of the distribution transformer is 12 years and 7 months. Analysis using a statistical approach assisted by SPSS software was also carried out to see how much influence the loading has on the age loss of the transformer.
... Power transformers are no doubt one of the key elements of the entire power system, so their technical condition, especially faults, may directly affect the reliability of the system. Condition assessment of transformers is based on various measurement data, usually aimed at assessment of the insulation system and mechanical condition [5][6][7][8], as well as the influence of physical factors like temperature [9][10][11], load, and even weather [12]. Knowing the technical condition of a particular unit is only the first step in the maintenance and risk management chain regarding the entire fleet. ...
This paper presents an alternative approach to the Transformer Assessment Index (TAI) by proposing a relatively simple rating method called the Exploitation Perspective Index (EPI). The method provides two numerical indicators: the first reflects the overall technical condition of the particular unit, and the second shows the condition of the unit in the context of the entire fleet. The objective of the EPI method is to support the decision-making process regarding the technical condition assessment of each of the transformers in the target population, considering not only technical but also economic aspects of transformer maintenance. Application of the method is described step by step, including input data, parametrization of the weights, and interpretation of the output results it provides. The proposed method is evaluated by two representative use cases and compared with two other methods. As a result, EPI confirms its applicability, and it has already been successfully implemented by the electric power industry. EPI can be potentially freely adopted for any transformer fleet, as well as for the specific situation of the utility, by adjusting the relevant parameters.
... The external faults commonly manifest as a result of external short circuits within the power system, over-flux phenomena, or overloading. Various fault location areas exist for transformers situated within substations (operating at voltages greater than 100 kV), as documented in reference [16]. The pre-eminent realm where faults manifest is within the winding, exhibiting a likelihood of occurrence at 37.69%. ...
The detection of partial discharge (PD) activities in high-voltage equipment can be conducted according to several mechanisms of signal detection, including electromagnetic wave signal detection, acoustic signal detection, chemical reactions, electrical signal detection, and optical emission detection. Recently, multiple methods of detection and localization of partial discharge activities, which occurred in power transformers and gas-insulated switchgear (GIS), have been proposed to monitor the health condition of high-voltage equipment, especially when the awareness regarding preventive maintenance has been emphasized at the industrial level and among electrical providers. In aligning the needs of the industrial sector and the improvement of PD-detection methods, this manuscript focuses on reviewing the current practice methods for the detection and localization of PD signals in high-voltage equipment, comparing their efficacy, and summarizing the future direction of research work-related methods of PD detection. The comparative reviews are discussed in terms of the mechanism of PD signal detection, indication parameters, calibration techniques, and the advantages and limitations of each method of PD measurement in detail.
