Pub Date : 2018-06-17DOI: 10.1109/EIC.2018.8480897
Peng Xue, Su Zhao, D. Xiao, Lili Zhu, Yizhou Wu
Low-pressure N2 has been considered as a potential alternative to SF6in area of gas insulation for its abundant resources, low price, environmental friendliness and good insulation performance. In this paper, flashover characteristics of insulator with N2 was tested. 50% flashover voltage under lightning impulse was measured. It is found that, with the increase of the gas pressure, flashover voltage increases approximately linearly. And polarity effect become stronger with the pressure rises. The flashover voltage first decreases and then rises with the increase of the surface roughness of the insulator. The experimental result indicated that adsorption and blocking actions of rough surface are the main factors for this phenomenon. And the effect of roughness on the flashover voltage under the positive lightning impulse is greater than it under the negative lightning impulse.
{"title":"Experimental Research on Flashover Characteristics of Insulator with N2","authors":"Peng Xue, Su Zhao, D. Xiao, Lili Zhu, Yizhou Wu","doi":"10.1109/EIC.2018.8480897","DOIUrl":"https://doi.org/10.1109/EIC.2018.8480897","url":null,"abstract":"Low-pressure N2 has been considered as a potential alternative to SF6in area of gas insulation for its abundant resources, low price, environmental friendliness and good insulation performance. In this paper, flashover characteristics of insulator with N2 was tested. 50% flashover voltage under lightning impulse was measured. It is found that, with the increase of the gas pressure, flashover voltage increases approximately linearly. And polarity effect become stronger with the pressure rises. The flashover voltage first decreases and then rises with the increase of the surface roughness of the insulator. The experimental result indicated that adsorption and blocking actions of rough surface are the main factors for this phenomenon. And the effect of roughness on the flashover voltage under the positive lightning impulse is greater than it under the negative lightning impulse.","PeriodicalId":184139,"journal":{"name":"2018 IEEE Electrical Insulation Conference (EIC)","volume":"273 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116550750","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-06-17DOI: 10.1109/EIC.2018.8481123
Zerye Ayalew, Kazuo Kobayashi, S. Matsumoto, Masamichi Kato
Transformer insulation oil is an important liquid for insulating and cooling of transformers. For many years' mineral oil has been used for as an insulating liquid in high voltage transformer. Mineral oil has good dielectric properties, however, due to environmental problem; recently many researchers have been looking for an alternative insulating liquid. Biodegradable and environmentally friendly ester oils have attracted more attention in recent years. This paper presents the experimental results of electrical arc stress on dissolved gases of transformer insulating oils (PFAE, MIDEL 7131 and mineral oil). The generated dissolved gases in the sample oils were examined by dissolved gas analysis (DGA) techniques. The test device used for testing is acrylic tube with a high voltage copper electrode at the top and a ground aluminum electrode at the bottom immersed in the oil. The experimental results from dissolved gas analysis (DGA) indicated that arc fault produce large amounts of hydrogen (H2) and acetylene (C2H2) with small quantities of methane (CH4), ethylene (C2H4) and ethane (C2H6) for both oils. Acetylene (C2H2) gas is the highest combustible gas generated by arc discharge in both mineral and ester oils. Therefore, there is a possibility that the diagnosis of a transformer filled with ester oil can be done using dissolved gas analysis (DGA) method.
{"title":"Dissolved Gas Analysis (DGA) of Arc Discharge Fault in Transformer Insulation Oils (Ester and Mineral Oils)","authors":"Zerye Ayalew, Kazuo Kobayashi, S. Matsumoto, Masamichi Kato","doi":"10.1109/EIC.2018.8481123","DOIUrl":"https://doi.org/10.1109/EIC.2018.8481123","url":null,"abstract":"Transformer insulation oil is an important liquid for insulating and cooling of transformers. For many years' mineral oil has been used for as an insulating liquid in high voltage transformer. Mineral oil has good dielectric properties, however, due to environmental problem; recently many researchers have been looking for an alternative insulating liquid. Biodegradable and environmentally friendly ester oils have attracted more attention in recent years. This paper presents the experimental results of electrical arc stress on dissolved gases of transformer insulating oils (PFAE, MIDEL 7131 and mineral oil). The generated dissolved gases in the sample oils were examined by dissolved gas analysis (DGA) techniques. The test device used for testing is acrylic tube with a high voltage copper electrode at the top and a ground aluminum electrode at the bottom immersed in the oil. The experimental results from dissolved gas analysis (DGA) indicated that arc fault produce large amounts of hydrogen (H2) and acetylene (C2H2) with small quantities of methane (CH4), ethylene (C2H4) and ethane (C2H6) for both oils. Acetylene (C2H2) gas is the highest combustible gas generated by arc discharge in both mineral and ester oils. Therefore, there is a possibility that the diagnosis of a transformer filled with ester oil can be done using dissolved gas analysis (DGA) method.","PeriodicalId":184139,"journal":{"name":"2018 IEEE Electrical Insulation Conference (EIC)","volume":"114 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123954964","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-06-01DOI: 10.1109/EIC.2018.8481052
G. Faria, Matheus Pereira, G. Lopes, J. Villibor, P. Tavares, I. Faria
This paper aims to evaluate the capacitance and the dielectric dissipation factor (DF) of brand new distribution transformers tested in the past two years at LAT-EFEI High Voltage Laboratory. Evaluation proposed consists to classify the capacitance between windings and between the windings and the ground, as well as the DF, according to the rated power, voltage class and number of phases. The DF analysis is based on IEEE Std. C57.152 limits and it aims to infer the insulation quality prior its operation on distribution networks. The parameters measurements were carried out on 170 distribution transformers made in Brazil, using a Schering bridge. The measurements showed a considerable number of samples with DF greater than the limit for a good insulation's condition.
{"title":"Evaluation of Capacitance and Dielectric Dissipation Factor of Distribution Transformers - Experimental Results","authors":"G. Faria, Matheus Pereira, G. Lopes, J. Villibor, P. Tavares, I. Faria","doi":"10.1109/EIC.2018.8481052","DOIUrl":"https://doi.org/10.1109/EIC.2018.8481052","url":null,"abstract":"This paper aims to evaluate the capacitance and the dielectric dissipation factor (DF) of brand new distribution transformers tested in the past two years at LAT-EFEI High Voltage Laboratory. Evaluation proposed consists to classify the capacitance between windings and between the windings and the ground, as well as the DF, according to the rated power, voltage class and number of phases. The DF analysis is based on IEEE Std. C57.152 limits and it aims to infer the insulation quality prior its operation on distribution networks. The parameters measurements were carried out on 170 distribution transformers made in Brazil, using a Schering bridge. The measurements showed a considerable number of samples with DF greater than the limit for a good insulation's condition.","PeriodicalId":184139,"journal":{"name":"2018 IEEE Electrical Insulation Conference (EIC)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115368677","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-06-01DOI: 10.1109/EIC.2018.8481128
G. Stone, H. Sedding, C. Chan, C. Wendel
Partial discharge (PD) testing has been used for over 60 years primarily as a method to detect aging of the stator winding insulation in motors and generators rated 6 kV and above. More recently it has also been used by some machine manufacturers as a means of assuring the quality of the insulation. The PD measuring systems in use work either in the low frequency regime (less than about 1 MHz) or in the very high frequency (30–300 MHz) range. By reference to several international standards, published work as well as some experiments described here, the advantages and disadvantages of the two approaches are reviewed. In most circumstances it is now clear that off-line PD tests should be done in the low frequency range. For on-line tests, either frequency range can be used, but with different advantages.
{"title":"Comparison of Low Frequency and High Frequency PD Measurements on Rotating Machine Stator Windings","authors":"G. Stone, H. Sedding, C. Chan, C. Wendel","doi":"10.1109/EIC.2018.8481128","DOIUrl":"https://doi.org/10.1109/EIC.2018.8481128","url":null,"abstract":"Partial discharge (PD) testing has been used for over 60 years primarily as a method to detect aging of the stator winding insulation in motors and generators rated 6 kV and above. More recently it has also been used by some machine manufacturers as a means of assuring the quality of the insulation. The PD measuring systems in use work either in the low frequency regime (less than about 1 MHz) or in the very high frequency (30–300 MHz) range. By reference to several international standards, published work as well as some experiments described here, the advantages and disadvantages of the two approaches are reviewed. In most circumstances it is now clear that off-line PD tests should be done in the low frequency range. For on-line tests, either frequency range can be used, but with different advantages.","PeriodicalId":184139,"journal":{"name":"2018 IEEE Electrical Insulation Conference (EIC)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121151051","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-06-01DOI: 10.1109/EIC.2018.8481132
Peng Zhang, B. Qi, Qipeng Chen, Zhihai Rong, Chengrong Li
As the transformation equipment of electrical energy, transformer is the key equipment in power system. When it comes to breakdown, there will be a great loss. Dissolved gas analysis (DGA) online testing is an important indicator of transformer health assessment which is widely used in insolation testing as it is sensitive to discharge defect. Nowadays, most of researches on DGA online testing analysis are aimed at the faults diagnosis. However, in some conditions, the fault may develop very rapidly. The operation and maintenance personnel don't have enough time to figure the problem out before the breakdown occur. This problem can be solved by forecasting the DGA on-line testing data effectively. With the reveal of deterioration trend, the serious failure will be avoided and the reliability of transformer will be improved. This paper proposes a short term trend forecast method based on online data optimization for dissolved gas in oil, which is a time series forecast. This method is made up of five parts: data optimization, related gases selection, the orders selection, model parameters estimation and model checking, multi-step forecast. With the field interference and DGA online testing device status error, the DGA online data's quality can't be assured. To improve the accuracy of forecast model, the transformer online testing data needs to be optimized in first step, including Pauta criterion removing for singular value and linear interpolation for missing data. The second step, select related gases, as different gases have strong relationship. The third step is to build forecaster model based on Auto-Regressive and Moving Average Model (ARMA), using Akaike information criterion (AIC) to select the model orders. The forth step, estimate the unknown parameters by least square method. After that, the model should be verified by residual error testing to make sure the effective information of the time series is fully extracted. The final step, use the forecast model to get the DGA forecast value by multi-step forecast. In this way, the short term deterioration trend can be reveal. About 323 normal transformers' one-year data and an overheat case's data are used to test the method, with research findings: 1) the forecast method has good short term forecasted accuracy, forecast error less than 10%. It reveals that the model can be used in the short-time dissolved gases forecast. However, if the value is too small as C2H4 or strong volatility as CO2, the ARMA forecast accuracy decreases sharply. 2) The longer time span, the larger forecast error will be, especially when it comes to the changes in condition. It's supposed that the model's response time influence the forecast error greatly. The further step is to reduce the method's response time.
{"title":"Short Term Trend Forecast of On-Line Monitoring Data of Dissolved Gas in Power Transformer","authors":"Peng Zhang, B. Qi, Qipeng Chen, Zhihai Rong, Chengrong Li","doi":"10.1109/EIC.2018.8481132","DOIUrl":"https://doi.org/10.1109/EIC.2018.8481132","url":null,"abstract":"As the transformation equipment of electrical energy, transformer is the key equipment in power system. When it comes to breakdown, there will be a great loss. Dissolved gas analysis (DGA) online testing is an important indicator of transformer health assessment which is widely used in insolation testing as it is sensitive to discharge defect. Nowadays, most of researches on DGA online testing analysis are aimed at the faults diagnosis. However, in some conditions, the fault may develop very rapidly. The operation and maintenance personnel don't have enough time to figure the problem out before the breakdown occur. This problem can be solved by forecasting the DGA on-line testing data effectively. With the reveal of deterioration trend, the serious failure will be avoided and the reliability of transformer will be improved. This paper proposes a short term trend forecast method based on online data optimization for dissolved gas in oil, which is a time series forecast. This method is made up of five parts: data optimization, related gases selection, the orders selection, model parameters estimation and model checking, multi-step forecast. With the field interference and DGA online testing device status error, the DGA online data's quality can't be assured. To improve the accuracy of forecast model, the transformer online testing data needs to be optimized in first step, including Pauta criterion removing for singular value and linear interpolation for missing data. The second step, select related gases, as different gases have strong relationship. The third step is to build forecaster model based on Auto-Regressive and Moving Average Model (ARMA), using Akaike information criterion (AIC) to select the model orders. The forth step, estimate the unknown parameters by least square method. After that, the model should be verified by residual error testing to make sure the effective information of the time series is fully extracted. The final step, use the forecast model to get the DGA forecast value by multi-step forecast. In this way, the short term deterioration trend can be reveal. About 323 normal transformers' one-year data and an overheat case's data are used to test the method, with research findings: 1) the forecast method has good short term forecasted accuracy, forecast error less than 10%. It reveals that the model can be used in the short-time dissolved gases forecast. However, if the value is too small as C2H4 or strong volatility as CO2, the ARMA forecast accuracy decreases sharply. 2) The longer time span, the larger forecast error will be, especially when it comes to the changes in condition. It's supposed that the model's response time influence the forecast error greatly. The further step is to reduce the method's response time.","PeriodicalId":184139,"journal":{"name":"2018 IEEE Electrical Insulation Conference (EIC)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121990934","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-06-01DOI: 10.1109/EIC.2018.8481034
Mrutyunjay Maharana, Niharika Baruah, A. Nanda, S. K. Nayak, N. Sahoo
This paper reveals the major experimental findings of a new batch of nanofluid (NF), which has all the dominating thermoelectrical properties being a novel transformer oil. Since liquid insulation of the power/distribution transformer carries nearly 80% of the entire insulation weight, so the efficiency of the insulating oil is very much important for the effective transformer efficiency. The investigation is being carried out taking titanium nanoparticle (NP) into consideration. An optimized concentration of 0.01wt% titanium NP is dispersed with mineral oil (MO). Two step method is implemented to prepare the NF, followed by addition of hydrophobic surfactant “Cetrimonium bromide [(C16H33)N(CH3)3]Br” (CTAB) which used to hinder sedimentation. Thermo electrical properties are studied for both MO and titanium NF and compared. It is observed that the addition of 0.01weight% NP to MO causes a significant enhancement in the dielectric strength of the NF. The resistivity increases and the dielectric losses (Tan delta) decreases, respectively for the NF. The kinematic viscosity of the NF is nearly unaffected and the thermal conductivity enhances significantly. The reason for the enhancement of breakdown voltage and thermal conductivity are analyzed numerically and validated experimentally.
{"title":"Thermoelectrically Enhanced Nanofluid is a Suitable Replacement for Transformer Oil","authors":"Mrutyunjay Maharana, Niharika Baruah, A. Nanda, S. K. Nayak, N. Sahoo","doi":"10.1109/EIC.2018.8481034","DOIUrl":"https://doi.org/10.1109/EIC.2018.8481034","url":null,"abstract":"This paper reveals the major experimental findings of a new batch of nanofluid (NF), which has all the dominating thermoelectrical properties being a novel transformer oil. Since liquid insulation of the power/distribution transformer carries nearly 80% of the entire insulation weight, so the efficiency of the insulating oil is very much important for the effective transformer efficiency. The investigation is being carried out taking titanium nanoparticle (NP) into consideration. An optimized concentration of 0.01wt% titanium NP is dispersed with mineral oil (MO). Two step method is implemented to prepare the NF, followed by addition of hydrophobic surfactant “Cetrimonium bromide [(C16H33)N(CH3)3]Br” (CTAB) which used to hinder sedimentation. Thermo electrical properties are studied for both MO and titanium NF and compared. It is observed that the addition of 0.01weight% NP to MO causes a significant enhancement in the dielectric strength of the NF. The resistivity increases and the dielectric losses (Tan delta) decreases, respectively for the NF. The kinematic viscosity of the NF is nearly unaffected and the thermal conductivity enhances significantly. The reason for the enhancement of breakdown voltage and thermal conductivity are analyzed numerically and validated experimentally.","PeriodicalId":184139,"journal":{"name":"2018 IEEE Electrical Insulation Conference (EIC)","volume":"106 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124634554","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper, a health status calculation method based on nonparametric kernel density estimation of dissolved gas in oil and association rules for transformer is proposed. Firstly, the online monitoring data of dissolved gas content which collected from multiple identical transformers are analyzed by nonparametric density estimation to obtain the health probability distribution function of various gases. Then, by mining the correlation between various gases and transformer fault conditions, an association rule method to calculate the weight coefficient of each gas is introduced. Finally, the weighted method is applied to calculate the health probability of transformer when the health probability and weight of each gas are obtained. The method introduced in this paper is validated by the state parameter data of transformer in a substation. The example shows that the health status of the transformer can be obtained in real time and this method is completely based on data driven, which is important to ensure the safety of grid.
{"title":"Nonparametric Kernel Density Estimation Model of Transformer Health Based on Dissolved Gases in Oil","authors":"Houying Li, Youyuan Wang, Xuanhong Liang, Yigang He, Yushun Zhao","doi":"10.1109/EIC.2018.8481032","DOIUrl":"https://doi.org/10.1109/EIC.2018.8481032","url":null,"abstract":"In this paper, a health status calculation method based on nonparametric kernel density estimation of dissolved gas in oil and association rules for transformer is proposed. Firstly, the online monitoring data of dissolved gas content which collected from multiple identical transformers are analyzed by nonparametric density estimation to obtain the health probability distribution function of various gases. Then, by mining the correlation between various gases and transformer fault conditions, an association rule method to calculate the weight coefficient of each gas is introduced. Finally, the weighted method is applied to calculate the health probability of transformer when the health probability and weight of each gas are obtained. The method introduced in this paper is validated by the state parameter data of transformer in a substation. The example shows that the health status of the transformer can be obtained in real time and this method is completely based on data driven, which is important to ensure the safety of grid.","PeriodicalId":184139,"journal":{"name":"2018 IEEE Electrical Insulation Conference (EIC)","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114356861","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-06-01DOI: 10.1109/EIC.2018.8481028
J. Timperley, Peter Longo, Daniel McKim, J. M. Vallejo
The traditional method to collect radio frequency spectrum data from 50 kHz to 100 MHz for Electromagnetic Interference analysis has been with a radio frequency current transformer. Experience has shown useful data can also be collected from the capacitor bus couplers schemes now in service. Several case studies are presented and comparison of the data collected is discussed.
{"title":"Electromagnetic Interference Data Collection from Bus Coupler Capacitors","authors":"J. Timperley, Peter Longo, Daniel McKim, J. M. Vallejo","doi":"10.1109/EIC.2018.8481028","DOIUrl":"https://doi.org/10.1109/EIC.2018.8481028","url":null,"abstract":"The traditional method to collect radio frequency spectrum data from 50 kHz to 100 MHz for Electromagnetic Interference analysis has been with a radio frequency current transformer. Experience has shown useful data can also be collected from the capacitor bus couplers schemes now in service. Several case studies are presented and comparison of the data collected is discussed.","PeriodicalId":184139,"journal":{"name":"2018 IEEE Electrical Insulation Conference (EIC)","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128061033","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-06-01DOI: 10.1109/eic.2018.8481054
Bharathi Balagam, Cynthia M. Chapple, T. Murray
Unsaturated polyester (UP) resins are used extensively in electrical impregnation applications. The major disadvantage of UP resins is that reactive diluents such as styrene, vinyl toluene and diallyphthalate must be used to maintain low viscosity for application. Approximately 30-75% of the reactive diluent is lost during the curing cycle as a volatile organic compound (VOC). The use of waterborne polyester resins is a competing technology. However even waterborne polyesters typically contain a co-solvent which contributes to VOC emissions. The presence of a co-solvent can also lead to low flashpoints and safety concerns. Epoxy resins on the other hand do not contain VOC's but are significantly more expensive than UP resins and are high viscosity for application on electrical devices. The current invention describes the utilization of UP Emulsion along with crosslinking agents for a high performance impregnation material. The emulsion particle size is less than one micron for long-term shelf life and has an application viscosity of only 300–600 cP at greater than 60% solids content. This UP emulsion product offers properties such as superior coating quality, high bond and dielectric strengths, and excellent corrosion / moisture resistance. The other advantages of emulsion products are that they are easy to use and cleanup, low VOC, no HAPS, no odor and low viscosity.
{"title":"UP Emulsion: A Novel Electrical Insulating Material","authors":"Bharathi Balagam, Cynthia M. Chapple, T. Murray","doi":"10.1109/eic.2018.8481054","DOIUrl":"https://doi.org/10.1109/eic.2018.8481054","url":null,"abstract":"Unsaturated polyester (UP) resins are used extensively in electrical impregnation applications. The major disadvantage of UP resins is that reactive diluents such as styrene, vinyl toluene and diallyphthalate must be used to maintain low viscosity for application. Approximately 30-75% of the reactive diluent is lost during the curing cycle as a volatile organic compound (VOC). The use of waterborne polyester resins is a competing technology. However even waterborne polyesters typically contain a co-solvent which contributes to VOC emissions. The presence of a co-solvent can also lead to low flashpoints and safety concerns. Epoxy resins on the other hand do not contain VOC's but are significantly more expensive than UP resins and are high viscosity for application on electrical devices. The current invention describes the utilization of UP Emulsion along with crosslinking agents for a high performance impregnation material. The emulsion particle size is less than one micron for long-term shelf life and has an application viscosity of only 300–600 cP at greater than 60% solids content. This UP emulsion product offers properties such as superior coating quality, high bond and dielectric strengths, and excellent corrosion / moisture resistance. The other advantages of emulsion products are that they are easy to use and cleanup, low VOC, no HAPS, no odor and low viscosity.","PeriodicalId":184139,"journal":{"name":"2018 IEEE Electrical Insulation Conference (EIC)","volume":"108 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127957715","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-06-01DOI: 10.1109/EIC.2018.8481041
W. Hong, M. Arshad
The insulation failure of multi-turn coils may cause significant damage to hydro generators including both the stator winding and core. A number of stator winding faults have been occurring on hydro generators in the last ten years as result of a turn-to-turn insulation failure. The insulation failure is complex in nature and is attributed to various design and operating factors, thus making the interpretation of the turn insulation condition extremely difficult. The purpose of this paper is to provide typical cases of failure and to share the experience in investigating these turn-to-turn faults, in order to increase knowledge about turn insulation failure. The requirements of insulation design and testing for new stator winding are specified, especially turn insulation. Surge protection to reduce the turn insulation degradation is also presented as the lesson learned from these cases. Some suggestions are also made that may enable utility owners to reduce the risk of multi-turn coil winding failures.
{"title":"Experience with Hydro-Generator Turn-to-Turn Insulation Fault, Investigation, and Recommendation for New Stator Winding Design and Protection","authors":"W. Hong, M. Arshad","doi":"10.1109/EIC.2018.8481041","DOIUrl":"https://doi.org/10.1109/EIC.2018.8481041","url":null,"abstract":"The insulation failure of multi-turn coils may cause significant damage to hydro generators including both the stator winding and core. A number of stator winding faults have been occurring on hydro generators in the last ten years as result of a turn-to-turn insulation failure. The insulation failure is complex in nature and is attributed to various design and operating factors, thus making the interpretation of the turn insulation condition extremely difficult. The purpose of this paper is to provide typical cases of failure and to share the experience in investigating these turn-to-turn faults, in order to increase knowledge about turn insulation failure. The requirements of insulation design and testing for new stator winding are specified, especially turn insulation. Surge protection to reduce the turn insulation degradation is also presented as the lesson learned from these cases. Some suggestions are also made that may enable utility owners to reduce the risk of multi-turn coil winding failures.","PeriodicalId":184139,"journal":{"name":"2018 IEEE Electrical Insulation Conference (EIC)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132473188","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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