Online Dissolved Gas Analysis Research Articles

Testing and approval standard development of online dissolved gas analysis monitors for oil‐filled transformers—Part I hydrogen monitors

Testing and approval standard development of online dissolved gas analysis monitors for oil‐filled transformers—Part I hydrogen monitors

Analysis of Microphone Coupling and Zero-Point Calibration Model for Non-Resonant Photoacoustic Spectroscopy

Dissolved Gas Analysis (DGA) of transformer insulation oil is an effective method for monitoring transformer operating conditions and diagnosing faults. Photoacoustic spectroscopy (PAS) is widely employed for online dissolved gas analysis in transformer oil. The positioning of the pressure equalization hole within the sound field significantly impacts the microphone’s sensitivity when coupled with the photoacoustic cell in non-resonant photoacoustic spectroscopy. The static temperature and humidity characteristics inside the photoacoustic cell also have a notable influence on the microphone’s output signal. Consequently, an analysis is performed to explore the relationship between the sensitivity of the photoacoustic spectrometer and temperature/humidity, leading to the optimization of the system configuration based on the microphone parameters. Moreover, the photoacoustic zero-point signal is influenced by the temperature and humidity levels within the photoacoustic cell. To address this problem, air mixtures at different humilities are measured, resulting in the establishment of a zero-point model for the background signal in Photoacoustic Spectroscopy (PAS). Subsequently, the experimental detection of acetylene under various humidity mixtures is conducted, successfully extracting effective signals for the measurement of 5 ppm acetylene gas. These results serve as evidence showcasing the efficacy of both the proposed structural optimization and zero-point model put forth in this study.

A Methodology for the Calculation of Typical Gas Concentration Values and Sampling Intervals in the Power Transformers of a Distribution System Operator

Predictive maintenance strategies in power transformers aim to assess the risk through the calculation and monitoring of the health index of the power transformers. The parameter most used in predictive maintenance and to calculate the health index of power transformers is the dissolved gas analysis (DGA). The current tendency is the use of online DGA monitoring equipment while continuing to perform analyses in the laboratory. Although the DGA is well known, there is a lack of published experimental data beyond that in the guides. This study used the nearest-rank method for obtaining the typical gas concentration values and the typical rates of gas increase from a transformer population to establish the optimal sampling interval and alarm thresholds of the continuous monitoring devices for each power transformer. The percentiles calculated by the nearest-rank method were within the ranges of the percentiles obtained using the R software, so this simple method was validated for this study. The results obtained show that the calculated concentration limits are within the range of or very close to those proposed in IEEE C57.104-2019 and IEC 60599:2015. The sampling intervals calculated for each transformer were not correct in all cases since the trend of the historical DGA samples modified the severity of the calculated intervals.

Teflon AF2400 Hollow Fiber Membrane Contactor for Dissolved Gas-in-Oil Extraction: Mass Transfer Characteristics

Ceramic-supported Teflon AF2400 hollow fiber membrane contactors for dissolved gas-in-oil extraction has gained importance in online dissolved gas analysis (DGA) monitoring. An improved understandi...

전력용 변압기의 상태를 고려한 온라인 가스분석 진단장치 설치시기에 관한 연구

The DGA(Dissolved Gas Analysis) can diagnose the transformer state through the characteristic gas generated by the fault. Also, DGA can be used as an essential inspection because it can be measured even in operation. If the result of DGA is bad, the inspection cycle can be shortened and an on-line DGA equipment can be installed and operated for real-time inspection as needed. However, the lifetime of the on-line DGA equipment is shorter than the transformer, resulting in economic losses when installing simultaneously with the transformer. This paper analyzes the transformer lifetime and the lifetime of the on-line DGA equipment. Also, considering the number of alarms and the additional inspection cost according to the result of DGA, the appropriate installation time of the on-line DGA equipment is suggested.

Validity Evaluation of Transformer DGA Online Monitoring Data in Grid Edge Systems

Dissolved gas analysis (DGA) is an important method of predicting transformer faults, and the accuracy of DGA measurements is of great significance to the evaluation of the transformer state in grid edge systems. In actual situations, it is difficult to regularly calibrate online DGA monitoring devices in a uniform way. Therefore, this paper proposes a method based on B-EMD and DBN to evaluate the validity of online DGA monitoring data and optimize the corresponding calibration plan. An analysis of actual DGA signals shows that the method proposed in this paper can effectively diagnose faults and improve the reliability of DGA online monitoring devices.

Transformer Fleet Optimal Maintenance with Risk Considerations

This paper aims at proposing an optimization model for high voltage transformers’ maintenance scheduling to minimize operational cost and risk. The focus of the paper is on the transformer fleet management, and not on a single transformer maintenance procedure or the evaluation of a single transformer failure risk. The proposed methodology takes as inputs the importance (e.g., based on the expected energy not supplied) and failure risk of each transformer (e.g., based on on-line Dissolved Gas Analysis), and the maintenance cost for each transformer. It also considers the main practical constraints in field interventions. As output, the proposed methodology provides the best timing for the maintenance of each transformer from the fleet of interest. The problem has been modeled as mixed-integer linear programming. Eleven months of real data from the Brazilian transmission system are used for setting up the recent history of outages. The following year data are employed to test the effectiveness of the optimization model. The output of the proposed fleet maintenance scheduling tool is the optimum viable intervention calendar for a power transformer fleet within a 52-week horizon. This proposal represents an innovative and robust solution, which can support the operational planning experts’ decision-making process.

Dissolved Gas Analysis Equipment for Online Monitoring of Transformer Oil: A Review.

Power transformers are the most important assets of electric power substations. The reliability in the operation of electric power transmission and distribution is due to the correct operation and maintenance of power transformers. The parameters that are most used to assess the health status of power transformers are dissolved gas analysis (DGA), oil quality analysis (OQA) and content of furfuraldehydes (FFA) in oil. The parameter that currently allows for simple online monitoring in an energized transformer is the DGA. Although most of the DGA continues to be done in the laboratory, the trend is online DGA monitoring, since it allows for detection or diagnosis of the faults throughout the life of the power transformers. This study presents a review of the main DGA monitors, single- or multi-gas, their most important specifications, accuracy, repeatability and measurement range, the types of installation, valve or closed loop, and number of analogue inputs and outputs. This review shows the differences between the main existing DGA monitors and aims to help in the selection of the most suitable DGA monitoring approach according to the needs of each case.

Doping effects of ZnO quantum dots on the sensitive and selective detection of acetylene for dissolved-gas analysis applications of transformer oil

We report on the doping effect on the sensing properties of ZnO quantum dots (QDs) for the detection of acetylene. We found that In-doped ZnO (IZO) QDs exhibited a better sensing performance to 10 ppm acetylene than undoped ZnO (ZO) QDs and Al-doped ZnO (AZO) QDs. The higher sensing response of IZO QDs can be attributed to a greater number of reactive sites for detecting acetylene, which is likely to originate from the increased number of oxygen vacancies, and the larger optical band gap and surface area of IZO. This is due to a higher valence dopant and a smaller particle size. The sensing properties of IZO QDs to 10 ppm acetylene was also found to be superior to previously reported acetylene sensors that are based on semiconducting metal oxides. Furthermore, we demonstrated that 10 ppm of acetylene can be selectively detected in air within ∼100 s using a recently developed miniaturized gas chromatography (GC) integrated with the IZO QDs sensor. In addition, we found that the device can detect the major fault gases of hydrogen and acetylene separately within ∼100 s. Our study demonstrates that the device can be utilized in the GC-based on-line dissolved gas analysis to detect small amounts of acetylene gas in transformer oil.

Multi-gas detection in power transformer oil based on tunable diode laser absorption spectrum

Online dissolved gas analysis (DGA) is an effective technique to obtain the health status information of insulation oil in power transformers. The typical hydrocarbon gases (methane, ethyne, ethene, ethane) decomposed from insulation oil, are the key indicators to diagnose the fault type and severity. To realize contactless and field measurement, a multi-gas detection system based on tunable diode laser absorption spectrum (TDLAS) is proposed in this paper. Critical technique problems on the light source, long path gas cell, and the topology for multi-gas detection are investigated. Individual central wavelengths of hydrocarbon gases are set at as 1653.72 nm for methane, 1530.37 nm for ethyne, 1620.04 nm for ethene and 1679.06 nm for ethane in the near infrared band. A 10.13 m long multi-pass gas cell is developed with the advantage of anti-vibration design. To share the optical absorption path, an optical switch is adopted to merge the multi-gas detection system. The high sensitivity of the TDLAS multi-gas detection system was demonstrated in the laboratory calibrations, with ethyne detection reaching sub-parts per million level, and the other hydrocarbon gases achieving ppm level. Furthermore, the comparison detection in the real 220 kV power transformer gave evidence to the effective monitoring of DGA, proving it an alternative approach to online detection of multiple gases in power transformer oil.

On-Line Analysis of Oil-Dissolved Gas in Power Transformers Using Fourier Transform Infrared Spectrometry

To address the problem of on-line dissolved gas analysis (DGA) of a power transformer, a Fourier transform infrared (FT-IR) spectrometer was used to develop an analysis instrument. Carbon monoxide (CO), carbon dioxide (CO2), methane (CH4), ethane (C2H6), ethylene (C2H4) and acetylene (C2H2) were the analytes for the FT-IR spectrometer while propane (C3H8), propylene (C3H6), propyne (C3H4), n-butane (n-C4H10) and iso-butane (iso-C4H10) were the interferents, which might exist in the dissolved gas but are not currently used as analytes for detecting an internal fault. The instrument parameters and analysis approach are first introduced. Specifically, an absorption spectra reading approach by switching two cone-type gas cells into separate light-paths was presented for reducing the effects of gas in the gaps between gas cells and spectrometers, scanning the background spectrum without clearing the sample cell, and increasing the dynamics. Then, the instrument was tested with a standard gas mixture that was extracted from insulation oil in a power transformer. The testing results show that the detection limit of every analyte component is lower than 0.1 μL/L, and the detection limits of all analytes meet the detection requirements of oil-dissolved gas analysis, which means that the FT-IR spectrometer may be an ideal instrument due to its benefits, such as being maintenance-free and having a high stability.

Tracing Acetylene Dissolved in Transformer Oil by Tunable Diode Laser Absorption Spectrum

Dissolved gas analysis (DGA) is widely used in monitoring and diagnosing of power transformer, since the insulation material in the power transformer decomposes gases under abnormal operation condition. Among the gases, acetylene, as a symbol of low energy spark discharge and high energy electrical faults (arc discharge) of power transformer, is an important monitoring parameter. The current gas detection method used by the online DGA equipment suffers from problems such as cross sensitivity, electromagnetic compatibility and reliability. In this paper, an optical gas detection system based on TDLAS technology is proposed to detect acetylene dissolved in transformer oil. We selected a 1530.370 nm laser in the near infrared wavelength range to correspond to the absorption peak of acetylene, while using the wavelength modulation strategy and Herriott cell to improve the detection precision. Results show that the limit of detection reaches 0.49 ppm. The detection system responds quickly to changes of gas concentration and is easily to maintenance while has no electromagnetic interference, cross-sensitivity, or carrier gas. In addition, a complete detection process of the system takes only 8 minutes, implying a practical prospect of online monitoring technology.

A new method to detect dissolved gases in transformer oil using NIR-IR spectroscopy

Dissolved gas analysis (DGA) is widely accepted as an effective technique to detect incipient faults within power transformers. Gases such as hydrogen, methane, acetylene, ethylene and ethane are generated as a result of insulation oil decomposition, while carbon monoxide and carbon dioxide are generated as a result of insulation paper decomposition. Laboratory-based gas chromatography (GC) in accordance to ASTM D3612 standard is globally accepted as a reliable technique to quantify dissolved gases in transformer oil samples. However, this technique incurs running cost and requires an expert to conduct the test. Furthermore, due to the complexity of the equipment, measurement is only performed in a laboratory environment and takes long time to get the results since the extraction of the oil sample from the transformer. To overcome these issues, various online DGA techniques have been developed and currently used by industry. However, these techniques are still considered in development stage with some limitations that have to be addressed to fully accept its results. This paper proposes a new method to estimate the concentration of various dissolved gases in transformer oil using near infrared-to-infrared (NIR-IR) spectroscopy that can be conducted instantly onsite with relatively inexpensive equipment. The proposed measuring technique does not call for expert person to conduct the measurements and has the potential to be implemented online. Results show a good correlation between oil spectral response and the concentration of each dissolved gas in the oil at particular wavelength range. Fuzzy logic model approach is employed to model this correlation and estimate the concentration of each dissolved gas.

Tracing methane dissolved in transformer oil by tunable diode laser absorption spectrum

Dissolved gas analysis (DGA)in power transformers is related to the degradation of insulation materials and dissolved methane (CH 4 )is a symbol gas of low energy electrical or thermal faults in power transformer oil. Conventional online DGA equipment suffers from problems such as cross sensitivity, electromagnetic compatibility and reliability. Based on tunable diode laser absorption spectroscopy (TDLAS) technique, a novel optical method is proposed to detect dissolved methane in transformer oil. Oil samples with fault gases are prepared and dissolved methane detection has been carried out in the laboratory. 1653.72 nm is selected as the central wavelength of tunable diode laser, moreover, a multipass gas cell and wavelength modulation strategy is utilized to trace methane dissolved in oil. Results show that the resolution of detection reaches 0.28 µL/L, and accuracy is less than 2 µL/L at low concentration. In addition, the detection cycle is so time-saving, less than 5 minutes. The proposed measurement method shows tremendous advantages, such as immediate response to concentration changes, no cross interference, no carrier gases, which is proved to be a promising maintain-free technique instead of conventional DGA equipment.

Estimation of dissolved gas concentrations in transformer oil from membranes

In China, online dissolved gas analysis systems with fluorinated ethylene-propylene membranes have been installed in many transformers for measurement of dissolved gases, and this article proposes a method of quickly estimating the gas concentrations well before the permeation equilibrium is reached.