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Papers by karunika diwyacitta
Springer proceedings in physics, 2023
Springer proceedings in physics, 2022
2022 International Conference on Radar, Antenna, Microwave, Electronics, and Telecommunications (ICRAMET)
2022 6th International Conference on Information Technology, Information Systems and Electrical Engineering (ICITISEE)
2017 International Conference on Electrical Engineering and Computer Science (ICECOS), 2017
This Transformer experiences aging everyday as it gets older. The aging of transformer can be det... more This Transformer experiences aging everyday as it gets older. The aging of transformer can be detected by assessing the condition of its oil insulation. Every transformer has its own aging rate which is influenced by many factors. This paper discusses about effects of lifetime and loading factor on DGA using regression linear method. 219 sample data including DGA and transformer age were collected from operating transformers in PT. PLN (persero). Specifically, the age of transformer ranges from 0 to 30 years and the rated voltage are 150/20kV and 150/70kV. The result shows that CO, CO2, CO+CO2 and TDCG have strong correlations with transformer age. The strongest correlation is between CO and transformer age with correlation coefficient 0.715. Trend analysis of CO and CO2 are carried out from transformer with various loading factors while the capacity and rated voltage are remained the same. The capacity of transformers discussed is 60MVA with rated voltage 150/20kV and 150/70kV. Loa...
2017 International Conference on High Voltage Engineering and Power Systems (ICHVEPS), 2017
Aging of transformer occurs as the transformer operates. Dielectric characteristics testing of oi... more Aging of transformer occurs as the transformer operates. Dielectric characteristics testing of oil insulation in transformers is needed to estimate the condition of transformers due to aging. Insulating materials in long-term operations will degrade gradually and cause the change of its properties. In this paper, a database of result for dielectric characteristics was analyzed statistically using linear regression method. Specifically the database consists of 219 dielectric characteristics and transformer age in the range of 0–30 years old with rated voltage 150/20kV and 150.70kV. Correlation analysis between dielectric characteristics and transformer age was discussed. Color, IFT (interfacial tension) and acidity were correlated to transformer age with correlation coefficient 0.502, 0.463 and 0.348 respectively. The secondary database consists of trend acidity and color in several years was carried out from operating transformers with the same capacity and rated voltage but various...
2017 International Conference on High Voltage Engineering and Power Systems (ICHVEPS), 2017
Dissolved Gases and Oil Characteristics are widely available data for detecting faults and evalua... more Dissolved Gases and Oil Characteristics are widely available data for detecting faults and evaluating condition of oil-impregnated power transformers. This paper presents the statistical insights of the effect of transformer paper deterioration to oil insulation. The oil characteristics, dissolved gases, and 2FAL data of 108 Indonesian transformers are collected. 2FAL is used as paper condition parameter and then directly linked to the degree of polymerization estimated (DPest). The correlation analysis is done using simple linear regression to find several most correlated parameters to transformer paper deterioration. The result is CO and CO2 is the most correlated dissolved gases to transformer paper condition. CO and CO2 have long been recognized as one of the cellulose degradation products. The oil characteristics data shows high correlation of interfacial tension (IFT), acidity, and color to the transformer paper aging condition. Finally, the result is compared to the standard.
This paper presents the possibility of using Adaptive Neuro Fuzzy Inference System for Power Tran... more This paper presents the possibility of using Adaptive Neuro Fuzzy Inference System for Power Transformer Paper Condition Assessment. The dielectric characteristics, dissolved gasses, and furan of 108 running transformers is collected. The 2-furaldehyde (2FAL) data is transformed to Degree of Polymerization (DP), and then statistically analysed to get independent variables as the predictor for the transformer paper condition assessment. CO and CO2 are well known as one of the product of cellulose degradation, while interfacial tension, acidity, and color from the oil are statistically correlated with furan. ANFIS (Adaptive Neuro-Fuzzy Inference System) and Multiple Regression (MR) model is built based on the previous statistical analysis, and then the result is evaluated and compared, resulting in better accuracy of ANFIS model. Three different evaluation criteria MAE (Mean Absolute Error), MAPE (Mean Absolute Percentage Error), and RMSE (Root Mean Square Error) calculated from ANFIS prediction are lower than those from MR model, with the MAPE of ANFIS model is 15.38%.
International Journal on Electrical Engineering and Informatics
Power transformer undergo aging overtime that degrades its insulation system. Oil-immersed paper ... more Power transformer undergo aging overtime that degrades its insulation system. Oil-immersed paper insulation degradation in transformer can be assessed through the change in oil characteristics and the dissolved gases. Data related to these parameters are abundant, but study on correlation among these parameters and the operating time of power transformer is still limited. This paper presents statistical insights into aging of transformer insulation system through oil characteristics, dissolved gases and the operating time of transformer. As much as 219 in service 150 kV transformers population testing data were included in this study. The data was analyzed using linear regression correlation analysis to Figureure out the dependency of each parameters. Statistical correlation between each properties of oil insulation, dissolved gases and operating time were carried out. There are some oil properties that have correlation with operating time, which are color scale, IFT and acidity. Moreover, color scale, IFT and acidity shows dependency among them. IFT tends to gradually decrease while acidity increases as operating time trend rises. On the other hand, operating time are also highly correlated with CO and CO2, which are commonly known as the main product of paper insulation degradation in transformers. Correlation among prior correlated parameters found that CO is strongly correlated with color and IFT. Subsequently, a high correlation coefficient of parameter to operating time could be interpreted that the ageing process happens during the life of a transformer changes certain parameters which these changes should be noticed for better decision making whether the transformer still feasible to be used in the system with certain maintenance or should be replaced.
Power transformer undergo aging overtime that degrades its insulation system. Oil-immersed paper ... more Power transformer undergo aging overtime that degrades its insulation system. Oil-immersed paper insulation degradation in transformer can be assessed through the change in oil characteristics and the dissolved gases. Data related to these parameters are abundant, but study on correlation among these parameters and the operating time of power transformer is still limited. This paper presents statistical insights into aging of transformer insulation system through oil characteristics, dissolved gases and the operating time of transformer. As much as 219 in service 150 kV transformers population testing data were included in this study. The data was analyzed using linear regression correlation analysis to Figureure out the dependency of each parameters. Statistical correlation between each properties of oil insulation, dissolved gases and operating time were carried out. There are some oil properties that have correlation with operating time, which are color scale, IFT and acidity. Moreover, color scale, IFT and acidity shows dependency among them. IFT tends to gradually decrease while acidity increases as operating time trend rises. On the other hand, operating time are also highly correlated with CO and CO2, which are commonly known as the main product of paper insulation degradation in transformers. Correlation among prior correlated parameters found that CO is strongly correlated with color and IFT. Subsequently, a high correlation coefficient of parameter to operating time could be interpreted that the ageing process happens during the life of a transformer changes certain parameters which these changes should be noticed for better decision making whether the transformer still feasible to be used in the system with certain maintenance or should be replaced.
Energies
This article presents an algorithm for modelling an Adaptive Neuro Fuzzy Inference System (ANFIS)... more This article presents an algorithm for modelling an Adaptive Neuro Fuzzy Inference System (ANFIS) for power transformer paper conditions in order to estimate the transformer's expected life. The dielectric characteristics, dissolved gasses, and furfural of 108 running transformers were collected, which were divided into 76 training datasets and another 32 testing datasets. The degree of polymerization (DP) of the transformer paper was predicted using the ANFIS model based on using the dielectric characteristics and dissolved gases as input. These inputs were analyzed, and the best combination was selected, whereas CO + CO 2 , acidity, interfacial tension, and color were correlated with the paper's deterioration condition and were chosen as the input variables. The best combination of input variables and membership function was selected to build the optimal ANFIS model, which was then compared and evaluated. The proposed ANFIS model has 89.07% training accuracy and 85.75% testing accuracy and was applied to a transformer paper insulation assessment and an estimation of the expected life of four Indonesian transformers for which furfural data is unavailable. This proposed algorithm can be used as a furfural alternative for the general assessment of transformer paper conditions and the estimation of expected life and provides a helpful assistance for experts in transformer condition assessment.
Springer proceedings in physics, 2023
Springer proceedings in physics, 2022
2022 International Conference on Radar, Antenna, Microwave, Electronics, and Telecommunications (ICRAMET)
2022 6th International Conference on Information Technology, Information Systems and Electrical Engineering (ICITISEE)
2017 International Conference on Electrical Engineering and Computer Science (ICECOS), 2017
This Transformer experiences aging everyday as it gets older. The aging of transformer can be det... more This Transformer experiences aging everyday as it gets older. The aging of transformer can be detected by assessing the condition of its oil insulation. Every transformer has its own aging rate which is influenced by many factors. This paper discusses about effects of lifetime and loading factor on DGA using regression linear method. 219 sample data including DGA and transformer age were collected from operating transformers in PT. PLN (persero). Specifically, the age of transformer ranges from 0 to 30 years and the rated voltage are 150/20kV and 150/70kV. The result shows that CO, CO2, CO+CO2 and TDCG have strong correlations with transformer age. The strongest correlation is between CO and transformer age with correlation coefficient 0.715. Trend analysis of CO and CO2 are carried out from transformer with various loading factors while the capacity and rated voltage are remained the same. The capacity of transformers discussed is 60MVA with rated voltage 150/20kV and 150/70kV. Loa...
2017 International Conference on High Voltage Engineering and Power Systems (ICHVEPS), 2017
Aging of transformer occurs as the transformer operates. Dielectric characteristics testing of oi... more Aging of transformer occurs as the transformer operates. Dielectric characteristics testing of oil insulation in transformers is needed to estimate the condition of transformers due to aging. Insulating materials in long-term operations will degrade gradually and cause the change of its properties. In this paper, a database of result for dielectric characteristics was analyzed statistically using linear regression method. Specifically the database consists of 219 dielectric characteristics and transformer age in the range of 0–30 years old with rated voltage 150/20kV and 150.70kV. Correlation analysis between dielectric characteristics and transformer age was discussed. Color, IFT (interfacial tension) and acidity were correlated to transformer age with correlation coefficient 0.502, 0.463 and 0.348 respectively. The secondary database consists of trend acidity and color in several years was carried out from operating transformers with the same capacity and rated voltage but various...
2017 International Conference on High Voltage Engineering and Power Systems (ICHVEPS), 2017
Dissolved Gases and Oil Characteristics are widely available data for detecting faults and evalua... more Dissolved Gases and Oil Characteristics are widely available data for detecting faults and evaluating condition of oil-impregnated power transformers. This paper presents the statistical insights of the effect of transformer paper deterioration to oil insulation. The oil characteristics, dissolved gases, and 2FAL data of 108 Indonesian transformers are collected. 2FAL is used as paper condition parameter and then directly linked to the degree of polymerization estimated (DPest). The correlation analysis is done using simple linear regression to find several most correlated parameters to transformer paper deterioration. The result is CO and CO2 is the most correlated dissolved gases to transformer paper condition. CO and CO2 have long been recognized as one of the cellulose degradation products. The oil characteristics data shows high correlation of interfacial tension (IFT), acidity, and color to the transformer paper aging condition. Finally, the result is compared to the standard.
This paper presents the possibility of using Adaptive Neuro Fuzzy Inference System for Power Tran... more This paper presents the possibility of using Adaptive Neuro Fuzzy Inference System for Power Transformer Paper Condition Assessment. The dielectric characteristics, dissolved gasses, and furan of 108 running transformers is collected. The 2-furaldehyde (2FAL) data is transformed to Degree of Polymerization (DP), and then statistically analysed to get independent variables as the predictor for the transformer paper condition assessment. CO and CO2 are well known as one of the product of cellulose degradation, while interfacial tension, acidity, and color from the oil are statistically correlated with furan. ANFIS (Adaptive Neuro-Fuzzy Inference System) and Multiple Regression (MR) model is built based on the previous statistical analysis, and then the result is evaluated and compared, resulting in better accuracy of ANFIS model. Three different evaluation criteria MAE (Mean Absolute Error), MAPE (Mean Absolute Percentage Error), and RMSE (Root Mean Square Error) calculated from ANFIS prediction are lower than those from MR model, with the MAPE of ANFIS model is 15.38%.
International Journal on Electrical Engineering and Informatics
Power transformer undergo aging overtime that degrades its insulation system. Oil-immersed paper ... more Power transformer undergo aging overtime that degrades its insulation system. Oil-immersed paper insulation degradation in transformer can be assessed through the change in oil characteristics and the dissolved gases. Data related to these parameters are abundant, but study on correlation among these parameters and the operating time of power transformer is still limited. This paper presents statistical insights into aging of transformer insulation system through oil characteristics, dissolved gases and the operating time of transformer. As much as 219 in service 150 kV transformers population testing data were included in this study. The data was analyzed using linear regression correlation analysis to Figureure out the dependency of each parameters. Statistical correlation between each properties of oil insulation, dissolved gases and operating time were carried out. There are some oil properties that have correlation with operating time, which are color scale, IFT and acidity. Moreover, color scale, IFT and acidity shows dependency among them. IFT tends to gradually decrease while acidity increases as operating time trend rises. On the other hand, operating time are also highly correlated with CO and CO2, which are commonly known as the main product of paper insulation degradation in transformers. Correlation among prior correlated parameters found that CO is strongly correlated with color and IFT. Subsequently, a high correlation coefficient of parameter to operating time could be interpreted that the ageing process happens during the life of a transformer changes certain parameters which these changes should be noticed for better decision making whether the transformer still feasible to be used in the system with certain maintenance or should be replaced.
Power transformer undergo aging overtime that degrades its insulation system. Oil-immersed paper ... more Power transformer undergo aging overtime that degrades its insulation system. Oil-immersed paper insulation degradation in transformer can be assessed through the change in oil characteristics and the dissolved gases. Data related to these parameters are abundant, but study on correlation among these parameters and the operating time of power transformer is still limited. This paper presents statistical insights into aging of transformer insulation system through oil characteristics, dissolved gases and the operating time of transformer. As much as 219 in service 150 kV transformers population testing data were included in this study. The data was analyzed using linear regression correlation analysis to Figureure out the dependency of each parameters. Statistical correlation between each properties of oil insulation, dissolved gases and operating time were carried out. There are some oil properties that have correlation with operating time, which are color scale, IFT and acidity. Moreover, color scale, IFT and acidity shows dependency among them. IFT tends to gradually decrease while acidity increases as operating time trend rises. On the other hand, operating time are also highly correlated with CO and CO2, which are commonly known as the main product of paper insulation degradation in transformers. Correlation among prior correlated parameters found that CO is strongly correlated with color and IFT. Subsequently, a high correlation coefficient of parameter to operating time could be interpreted that the ageing process happens during the life of a transformer changes certain parameters which these changes should be noticed for better decision making whether the transformer still feasible to be used in the system with certain maintenance or should be replaced.
Energies
This article presents an algorithm for modelling an Adaptive Neuro Fuzzy Inference System (ANFIS)... more This article presents an algorithm for modelling an Adaptive Neuro Fuzzy Inference System (ANFIS) for power transformer paper conditions in order to estimate the transformer's expected life. The dielectric characteristics, dissolved gasses, and furfural of 108 running transformers were collected, which were divided into 76 training datasets and another 32 testing datasets. The degree of polymerization (DP) of the transformer paper was predicted using the ANFIS model based on using the dielectric characteristics and dissolved gases as input. These inputs were analyzed, and the best combination was selected, whereas CO + CO 2 , acidity, interfacial tension, and color were correlated with the paper's deterioration condition and were chosen as the input variables. The best combination of input variables and membership function was selected to build the optimal ANFIS model, which was then compared and evaluated. The proposed ANFIS model has 89.07% training accuracy and 85.75% testing accuracy and was applied to a transformer paper insulation assessment and an estimation of the expected life of four Indonesian transformers for which furfural data is unavailable. This proposed algorithm can be used as a furfural alternative for the general assessment of transformer paper conditions and the estimation of expected life and provides a helpful assistance for experts in transformer condition assessment.