21, rue d Artois, F-75008 PARIS A2-116 CIGRE 2016 http : //www.cigre.org Dynamic Behaviour of Fault Gases and Online Gas Sensors S. TENBOHLEN 1, I. HÖHLEIN 2, M. LUKAS 3, A. MÜLLER 4, K. SCHRÖDER 5, U. SUNDERMANN 6 1 University of Stuttgart, 2 Siemens AG, 3 Vattenfall Europe Generation AG, 4 TÜV SÜD ET, 5 EMH GmbH, 6 Amprion Germany SUMMARY To ensure safe and secure operation of transformers a number of diagnosis techniques are known. Especially, the established dissolved gas analysis (DGA) can provide relevant information about internal transformer faults. Natural aging, thermal and electrical failures generate typical fault gases, which dissolve in the insulating oil. By analysing these fault gas profiles evidence about kind and severity of the fault can be estimated. A feasible gas based diagnosis requires the consideration of both, gas generation and gas losses. Gases escaping through the conservator tank may lead to misleading concentration levels and underrated gas generation rates. Therefore, the influence of gas losses on DGA based diagnoses should be considered. In this contribution a model of transformers gas losses dependent on oil temperature and the boundary surface area in the conservator is presented. A system of two differential equations is used for modelling the gas transport. At a higher oil exchange rate, the losses rise. The calculation shows that for free breathing transformers the fault gas loss is mainly influenced by the exchange of oil between main tank and conservator. Online instruments for gas-in-oil analysis may be based on other than gas chromatographic techniques, nevertheless bringing high accuracy and precision. A laboratory comparison between classical DGA and online DGA-monitors based on infrared technology or membrane extraction with consequent conductivity measurement of hydrogen and carbon monoxide has been performed and evaluated. The real time swift response to concentration changes, as well as the good correlation between laboratory and monitoring values make commercial instruments monitoring based on IR technology very promising for field applications. Several use cases show the possibilities but also limits of online condition monitoring with gas sensors. With the example of a large generator step-up transformer it is shown how the careful analysis of the dynamic the fault gas development offers the possibility to keep a faulty transformer longer in service. This enabled the utility to keep the power station as long in operation as needed for providing a backup transformer. KEYWORDS Power Transformer, Gas in Oil Analysis, Online Monitoring, IR spectroscopy, Gas Diffusion, Oil Flow Rate, Gas Loss Factor stefan.tenbohlen@ieh.uni-stuttgart.de
1 INTRODUCTION Regarding the availability of electrical energy networks power transformers play a dominant role for asset managers. To ensure safe and secure operation of transformers a number of diagnosis techniques are known. Especially, the established dissolved gas analysis (DGA) can provide relevant information about internal transformer faults. Natural aging, thermal and electrical failures generate typical fault gases, which dissolve in the insulating oil. By analysing these fault gas profiles evaluation on kind and severity of the fault can be estimated. Online Monitoring is a powerful tool, enabling the control of fault gas development continuously and thus guaranteeing an optimal energy transmission. The existing DGA standards are based on relatively complicated procedures, which can be well controlled under laboratory conditions. The field application, however, requires robustness and high long time precision for reliable trend development, which is the main focus of online monitoring. For an accurate diagnosis not only gas generation but also gas losses should be taken into account especially for free breathing transformers. Gases escaping through the conservator tank may lead to misleading concentration levels and underrated gas generation rates. Therefore, the influence of gas losses on DGA based diagnoses should be considered. Furthermore the dynamic behaviour and accuracy of online gas sensors hast to be taken into account. Several use cases show the possibilities but also limits of online condition monitoring using gas sensors. 2 DYNAMICS BETWEEN OIL AND GAS PHASE 2.1 Oil Flow Rate between Tank and Conservator A feasible gas based diagnosis requires the consideration of both, gas generation and gas losses. Gases escaping through the conservator tank may lead to misleading concentration levels and underrated gas generation rates especially for free breathing transformers [1, 2]. But also the other way round is possible: gases from the ambient air, mainly nitrogen and oxygen, are slowly dissolving in the conservator tank oil and are afterwards mixed with the main tank oil, too. An adequate model can help to assume the actual fault gas generation rate of a transformer. Thus, the severity of an upcoming fault could be determined more accurately for free breathing transformers. The loss of dissolved fault gases mainly depends on the conservator tank design. The oil is in direct contact to ambient air at free breathing conservator tanks. Fault gases can evaporate into the atmosphere and air gases can dissolve in the transformer oil. Free breathing conservator tanks for power transformers are common in several European and other countries [3]. Gas exchange does not occur at hermetically sealed transformers, transformers with a gas blanket or transformers with a membrane installed in the conservator tank. The exchange of dissolved gases through the conservator tank is called breathing. The oil transports dissolved fault gases from the main into the conservator tank. There, the different fault gas concentrations between oil and air are equalized by diffusion, which results in a loss of fault gases and an increase of ambient air gases. Breathing depends on the exchange rate between main tank and conservator [2]. The exchange rate depends on several factors: the entire oil volume of the transformer, the loading behaviour of the transformer, the ambient temperature, the design of the conservator tank and its connection to the main tank. The oil flow is driven by two effects. The temperature dependent oil density forces a volume change of the oil and hence a flow from the main tank into the conservator tank at rising temperatures because oil expands with app. 0.076 % K -1. Additionally, a convection effect occurs (natural circulation), which is caused by the temperature gradient between main tank top oil temperature and the oil temperature in the conservator tank which approximately equals ambient temperature. The flow rate for 26 different power transformers is calculated from thermal monitoring data in order to evaluate the effects of breathing [4]. The calculation only considers the oil flow due to volume change. The transformers nominal power varies between 31.5 and 850 MVA including generator step-up units, grid couplers and wind park transformers. Therefore, the loading and the cooling types are diverse. The resulting flow rates cover a wide range from 4 to 36 l/day per 1000 l oil volume for grid coupling and wind park transformers, both with volatile load factors. Generation step-up units 2
provide a flow rate of 1.8 6.2 l/day per 1000 l oil volume, with stable load factors. ODWF units provide even lower flow rates because of a temperature controlled cooling system. 2.2 Laboratory Experiments for Evaporation via the Conservator The exchange of gases at the boundary surface between oil and ambient air in the conservator tank is simulated in a laboratory setup. Barrels are used as substitutes for a conservator tank. These barrels have a total volume of about 217 l. To vary the surface area between oil and ambient air inside, one experiment is carried out with an upright standing barrel with a boundary surface of about 0.26 m² and one with a horizontal barrel and a boundary surface of about 0.48 m². The oil volume is kept constant at 100(± 5) l. Thus, there is a gas volume with about 117 l over the oil, which is open to the atmosphere. All experiments use mineral oil. Before each experiment, the oil is degassed, dried, and filtered at 60 C with a vacuum oil treatment system. After degassing a fault gas mix is dissolved in the oil using a porous PTFE plastic. A. Influence of surface area The influence of the boundary surface between oil and ambient air on the loss of fault gases is examined by the two surface areas 0.26 m² and 0.48 m². The experiments are performed at room temperature. Throughout the experiment the oil is not moved. Fig. 1 (left) 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(-l t). The gas loss factor l has the unit 1/h and depends on the boundary surface area. The decrease of hydrogen concentration is faster for the larger surface area. Besides hydrogen, also other fault gases are analysed with the same experimental setup. Fig. 1 (right) shows the gas loss factors l of all gases for both surface areas. With a linear increasing surface area the gas loss factor also increases linearly. Thus, more gases evaporate. Hydrogen evaporates at the fastest rate, followed by CO and CH 4. H 6 evaporates the slowest. concentration (ppm) 500 400 300 200 100 surface area 0.48 m² surface area 0.26 m² loss factor l (1/h) 8 x 10-3 6 4 2 CO CH 4 H 4 H 6 0 0 200 400 600 800 1000 1200 time (hours) 0 0 0.2 0.4 0.6 surface area (m²) Figure 1: left: Concentration trend of hydrogen for different boundary surface areas right: Gas loss factor over surface area for different fault gases B. Temperature dependency In this series of experiments, the influence of temperature is investigated. Four temperatures are considered: 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 m²). Fig. 2 (left) shows the fitted gas loss factors l for all gases at different temperatures. The gas loss factors over temperature show an exponential increase. An exemplary exponential gradient over temperature is plotted for CO. Again, has a higher gas loss factor and is more volatile than the other presented gases. 3
loss factor l (1/h) 0.06 0.05 0.04 0.03 0.02 0.01 CO CH 4 H 4 H 6 concentration (ppm) 200 150 100 50 main tank, 20 l/h conservator, 20 l/h main tank, 40 l/h conservator, 40 l/h 0 0 20 40 60 temperature ( C) 0 0 50 100 150 time (days) Figure 2: left: Gas loss factors of different fault gases over temperature. Dashed line: exemplary exponential gradient for CO. right: Concentration trend for in main tank (straight line) and conservator (dashed line) at different oil exchange rates The large deviation between the gas loss factor at 22 C and 35 C may be explained by the experimental procedure. No heating of the test barrel is necessary at room temperature (22 C). At higher temperatures (35-65 C) a ring-shaped barrel heater is used. Due to the radial heat input a convection effect occurs in the oil. This leads to an increased mixing of the oil and thus to a higher gas loss factor. 2.3 Calculation of Fault Gas Losses The conducted experiments show the possibility to calculate the gas losses of a free breathing conservator tank by taking the oil temperature and the boundary surface area into account. Changes of the gas concentration in the main tank influence the concentration in the conservator tank and vice versa. Therefore, the derivative of each concentration is affected by the concentrations of both, main and conservator tank. A system of two differential equations is used for modelling the gas transport (1). (1) K(t) and A(t) are the time-dependent gas concentrations of the main tank oil K and of the conservator tank oil A; m, n, p and q are constants which depend on the volume, the gas loss factor and the oil exchange rate. The exemplary transformer has an oil volume of 42000 l for the simulation. The free breathing conservator tank of this transformer has an oil filled volume of 1700 l. The main tank contains a concentration of 200 ppm dissolved hydrogen as starting condition. At the beginning, there is no dissolved hydrogen in the conservator tank. The exchange between the main and conservator tank is assumed constant at 20 l/h (40 l/h) corresponding to the results shown in chapter 2.1. Every hour, 20 l oil flow into the conservator and back into the main tank. Temperatures are also considered constant. The gas loss factor in the conservator tank is set to l H2 = 0.1, which corresponds to a surface area of 1.5 m² and an average temperature of 15 C. The l H2 value is extrapolated from the values measured in the experiment presented above. Fig. 2 (right) shows the concentration trend for hydrogen with the previously made assumptions. The oil concentration of hydrogen in the main tank decreases exponentially. The concentration in the 4
conservator first increases and then decreases exponentially. At a starting concentration for of 200 ppm the loss corresponds to 0.086 ppm/h or 2.06 ppm/d for an oil exchange of 20 l/h. At higher oil exchange rates also the losses rise. The comparison between the calculations for 20 l/h and 40 l/h shows, that the fault gas loss is strongly influenced by the exchange of oil between main and conservator tank. For an improved model further laboratory tests as well as the evaluation of existing measurements from real transformers have to be performed. 3 INVESTIGATION OF ACCURACY AND DYNAMIC RESPONSE OF ONLINE GAS SENSORS The requirements on gas-in-oil monitoring on-site are not less demanding compared to these in the laboratory. The DGA under laboratory conditions has been described in numerous standards and is based on gas chromatography, allowing a very low detection limit. Laboratory methods, however, require intensive maintenance, e.g. change of parts as well as gas supply and trained personnel. On-site gas monitors have higher challenges in the sense of robustness and long term stability [5]. To meet these requirements other techniques than gas chromatography are becoming more competitive. In the case of the single gas (or warn type) monitors the conductivity sensor technology for detecting gases like hydrogen or carbon monoxide has found wide application. Single gas sensors with membrane gas extraction technology can be robust but they have typically limited accuracy. In addition their oil transport system based on alternating temperature inlet change requires averaging and filtering of raw values due to the variation of those values from conductivity sensors with the temperature inlet change. Figure 3 shows the reaction of raw values ( sensor output in µs) and filtered/averaged values ( display value in ppm) on a stepwise increase of gas in oil content for a hydrogen and carbon monoxide (warn type) sensor. It is based on a conductivity sensor with membrane extraction and a transport system based on alternating temperature inlet change (sensor oil temperature in C). Due to the alternating sensor oil temperature the displayed value has to be filtered which results in an output delay of app. one hour. Figure 3: Dependency of raw values ( sensor output in µs) and filtered/averaged values ( display value in ppm) on alternating temperature inlet change (Sensor oil temp.) For the determination of hydrocarbon gases as well as carbon oxides one or multi fold type channel IR based on-site monitors are already state of art. Infrared technology is robust. In combination with hydrogen detection by means of e.g. conductivity detectors, it allows a simultaneous high resolution and fast response determination of the fault gases responsible for major faults. An important part of the system is the gas extraction out of the oil. Wide spread systems are membrane or head space extraction. The reliability of the sensor is depending on its ability to sample and analyse representative oil out of the bulk. Important is the transport of the oil out of the tank to the analysing system this could be pump enabled or by alternating temperature inlet change. Manufacturers of on-line monitors indicate accuracy and stability of measurement which, however, are always connected to certain testing setups and very difficult to be validated by users. The calculation 5
of detection limit, repeatability and reproducibility according statistic procedures e.g. DIN 32645 are applicable for laboratory methods, but not for on-line measuring equipment. Of importance for the user is the comparability of the values to laboratory methods, as well as the quick response to changing gas concentrations. In this study a comparison of the absolute values of a commercial IRbased on-line monitor with laboratory gas-in-oil values has been performed. The examined gas-in-oil monitor is able to determine simultaneously carbon monoxide, acetylene and ethylene by means of IR spectroscopy and hydrogen by means of a microelectronic sensor. The concentration in the oil has been reached by the introducing of a gas mixture of hydrocarbons, carbon monoxide, carbon dioxide, atmospheric gases and hydrogen in the system and circulating the oil at ambient temperature and 40 C. The concentration has been continuously monitored by taking samples and analysing these with laboratory DGA for comparison. Since the starting concentration of the hydrocarbons was relatively high, a partial degassing during circulation has been performed in order to follow the rate of concentration change. The test has been done on a testing device, consisting of degassing unit used simultaneously as a conservator, tank with possibility of heating, circulating unit, connected with the tank and conservator where the monitoring devices are attached, and vacuum and circulating pumps. The comparison between the monitor readings and laboratory gas-in-oil analysis of the corresponding fault gases is presented on Figure 4 to Figure 6. Figure 4: Comparison of low range monitored hydrogen values with laboratory gas-in-oil values Figure 5: Comparison of low range monitored carbon monoxide values with laboratory gas-in-oil values Figure 6: Comparison of monitored ethylene values with laboratory gas-in-oil values Figure 7: Development of hydrogen and acetylen after an electrical failure 6
Generally the monitoring values of hydrogen, carbon monoxide and hydrocarbons even in a low level are in a good agreement with the laboratory values and within the 20 % uncertainty (Figure 4, Figure 5). The values of ethylene seem to be consequently higher in comparison to these measured by means of GC (Figure 6). Since the gas mixture contained propylene, it seems probable that the ethylene monitoring value is a sum value of the unsaturated hydrocarbons, which however does not interfere with common evaluation criteria. The tested monitoring device is vacuum proof. The applied vacuum caused a decrease in the gas-in-oil values as expected. This decrease was well seen as trend not only in the laboratory gas-in-oil values, but also in the monitoring level. Figure 7 shows a significant and fast increase of both hydrogen and acetylene values from a multigas sensor for hydrogen, carbon monoxide, acetylene and ethylene mounted on a 100 MVA 220/23,8 kv transformer after an electrical failure. The high values for both hydrogen and acetylene have been confirmed by both portable offline DGA as well as laboratory DGA analysis. The transformer has been taken off service and it has been inspected by the manufacturer. After switching off the transformer the gas production stopped. This real time swift response to concentration changes, as well as the good correlation between laboratory and monitoring values make commercial instruments monitoring based on IR technology very promising for field applications. However multigas sensors based on other extraction principles then membrane extraction (e.g. head space or vacuum extraction) present other challenges due to the need of moving parts to realize the oil transport and gas extraction (pump, compressor, flow meter, oil and gas vales and oil level sensors). Potential solutions and future research work could therefore be the combination of new membrane extraction technologies in combination with IR gas sensing principle. 4 USE CASES FROM ONSITE MEASUREMENTS 4.1 Gassing Behaviour due to Broken Potential Connection Figure 8 shows, as an example for early fault recognition, a developing hydrogen content measured by single gas monitor mounted at a 400 kv single phase GSU transformer (267 MVA). After detection of the increased hydrogen level a conventional DGA was performed that validated the hydrogen level and showed an additional amount of acetylene. With respect to the DGA a PD measurement was performed that showed a PD-level of several nano coulombs, the PD location pointed to a failure location at the connection of the HV bushing. The final inspection of the bushing and the lead connection showed a broken potential connection of the HV screening electrode. As a conclusion gas monitors are useful to detect faults like PD or hot spots, where the fault development is coupled with gas generation. Figure 8: Hydrogen level of a 400 kv single phase GSU transformer with broken potential connection 7
4.2 Gassing Behaviour after Inter Turn Failure On the other hand gas sensors can t detect faults where no gas is produced or where the fault development is spontaneous. Figure 9 shows the reading of a single gas monitor mounted at a 400 kv three phase GSU transformer (750MVA) before and after a serious fault. Before the fault the measured gas concentration was constant and in good correlation to the conventional DGA. After the tripping of the Buchholz relay a steep increase of the gas content appeared. The inspection of the active part of the transformer showed an inter turn failure within the HV winding of one phase. It is typical for inter turn failures that the gas generation starts not till the discharge occurs. Gas monitors are also helpful to ensure the integrity of a transformer when operating out of normal service conditions. Figure 9: Gas concentration of a 400 kv GSU transformer before and after an inter turn failure 4.3 Gassing Behaviour under Overload Condition Figure 10 shows the reading of a single gas monitor mounted at a 750 MVA GSU transformer with overload capability of 1000 MVA. Due to a failure of a transformer in parallel the unit had to operate at a load of 1000 MVA during a period of some months. When starting the overload operation a steep increase of the measured gas concentration was detected. Conventional DGA showed that the increase was caused by the increase of CO concentration with respect to the higher temperatures. After a few days the gas concentration stayed constant and remained stable until the overload operation was finished. After some months of normal operation the gas concentration decreased to the level the transformer had before the overload operation started. Figure 10: Gas concentration of a 750 MVA GSU transformer with overload capability of 1000 MVA before and after overload operation 8
4.4 Extension of Operating Time by DGA Monitoring A 600 MVA / 380 kv generator step-up unit monitored by an IR-based multi gas analyser showed in the beginning of July a strong and continuous increase of dissolved combustible gases (Figure 11). 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 analysed in the laboratory daily. This offered the possibility to check the deviation between monitoring and laboratory results. The dissolved gas was extracted by headspace and vacuum technology. Hydrocarbons showed very good agreement between monitoring and laboratory values (Figure 11a). The highest deviations occurred with hydrogen, which could be attributed to its high diffusivity. But although the oil samples analysed in the laboratory revealed slightly different absolute gas values, the failure cause and trend corresponded fairly well with the monitoring results. Most notably hydrogen, methane, ethane and ethylene were generated in high amounts. The Duval triangle indicated a thermal fault with temperatures above 700 C. The concentration of CO and CO 2 stayed almost constant, which indicated no involvement of paper in the fault. Because the amount of acetylene increased during the first 50 days quiet slowly just by app. 15 ppm melting of the core laminations was also excluded as failure cause. a) b) Figure 11: Gas concentration of a 600 MVA / 380 kv GSU transformer In the beginning of August the total amount of dissolved combustible gases (app. 5000 ppm) and respective generation rate exceeded the values given as Condition 4 according to IEEE Std C57.104, which suggests to remove the transformer from service under these circumstances [6]. Despite of the high dissolved combustible gas amounts (see Figure 11b) 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. If the rise of acetylene had exceeded 5ppm/day in an interval of two days or an abrupt rise of 5 ppm/h occurred, the transformer would have been switched off immediately. Due to the continuous monitoring of the different fault gases this strategy of supervised extension of operation was possible in order to prevent switching off the power station with its high financial impact. The reduction of load factor showed a stagnation of the gas generation. Based on the DGA results as potential failure causes problems with current leads (e.g. increased resistance of selector contacts or crimped connections) or circulating currents were taken into account. Unfortunately the repetitive changing of tap positions didn t change the gassing behaviour. After a further increase of the gassing rate the loading of the transformer was reduced by 50 %. Due to this load reduction the gas production stopped immediately, which at least could be interpreted as a temporary intermission of the failure. Also the following load increase showed no resumption of the failure. 9
On 10 th of September the transformer was switched off as scheduled and exchanged by a spare unit provided at that moment. A visual inspection of the tank revealed that due to mechanical problems the tank got in contact with the magnetic core sheets, which resulted in circulating currents via the normal core grounding system. This circulating current is induced by the load dependent stray flux and can reach levels of some hundred amperes. At the contact point of tank and core a hot spot with oil carbon was visible indicating the decomposition of the oil. Additionally the copper cable for the normal grounding of the core outside on top of the tank was melted which led to the intermission of the failure. 5 CONCLUSION A feasible gas based diagnosis requires the consideration of both, gas generation and gas losses. A model for free breathing transformers gas losses dependent on oil temperature and the boundary surface area in the conservator is presented. A system of two differential equations is used for modelling the gas transport. At a higher oil exchange rate between tank and conservator the losses rise. The calculation shows that for free breathing transformers the fault gas loss is mainly influenced by the exchange of oil between main tank and conservator. A laboratory comparison between classical DGA and online DGA-monitors based on infrared technology or membrane extraction with successive conductivity measurement of hydrogen and carbon monoxide has been performed and evaluated. The real time swift response to concentration changes, as well as the good correlation between laboratory and monitoring values make commercial instruments monitoring based on IR technology very promising for field applications. Several use cases show the possibilities but also limits of online condition monitoring with gas sensors for the identification of developing faults. With the example of a large generator step-up transformer it is shown how the careful attention of the dynamic fault gas development offers the possibility to keep a faulty transformer longer in service. This enables the utility to keep the power station longer in operation in order to provide a spare transformer. 6 BIBLIOGRAPHY [1] R. Anderson, U-R. Roderick, V. Jaakkola, N. Östman, The transfer of fault gases in transformers and its effect upon the interpretation of gas analysis data, Cigré Report 12-02, 1976 [2] E. Bräsel, O. Bräsel, U. Sasum, Gashaushalt bei Transformatoren der offenen Bauart Neue Erkenntnisse, ew, Jg. 109, Heft 14-15, pp. 56-59, 2010 [3] Cigré Brochure 296, Recent Developments in DGA Interpretation, June 2006 [4] A. Müller, S. Tenbohlen, Analysis of Fault Gas Losses through the Conservator Tank of Free- Breathing Power Transformers, 18 th Int. Symp. on High Voltage Engineering, Seoul, South Korea, 2013 [5] Cigré Brochure 409, Report on Gas Monitors for Oil-Filled Electrical Equipment, February 2010 [6] IEEE Std. C57.104, IEEE Guide for the Interpretation of Gases Generated in Oil-Immersed Transformers, 2008 10