Systems and methods for implementing online and offline applications are described. Such systems and methods may in some cases provide the same programming interface, regardless of whether the application is online or offline. Such systems and methods may also or instead in some cases provide additional or other possible capabilities, including installation without elevated privileges, simplified data synchronization, sharing of applications and application data, access to data from other applications, and richer client functionality than may be provided by an application such as a web browser.

Online and offline applications

As the population of transformers in service increases and their operating time extends, much attention has been focused on their availability and reliability. However, insufficient research work concentrates on how to evaluate transformer's aging condition, although huge progress has been made on the techniques of fault diagnosis and condition assessment of transformer in past decades. This paper presents the concept of Aging Index (AI), which is a practical tool that combines the results of routine inspections, and site and laboratory testing to estimate the aging condition of oil-immersed transformers. Further, frequency domain spectroscopy (FDS) as a novel non-destructive testing technique to estimate remained life expectancy is included in aging evaluation system. Moreover, a software system based on transformer's electrical and thermal parameters is developed correspondingly, by using a multi-parameters analytic approach. This system would dedicate to decision-making and replacement planning and has good application prospects.

/pdf/aging-assessment-of-power-transformer-using-multi-parameters-3ti19vc708.pdf

Aging Assessment of Power Transformer Using Multi-parameters

This paper describes an optical fiber sensor and temperature sensor-based instrumentation system to measure the moisture content in transformer oil. The sensor system consists of (i) Diode Laser Source, (ii) a bare and bent multimode fiber as sensor probe, (iii) an LDR as detector, (iv) LM35-based temperature sensor, and (v) microcontroller system having a trained ANN for processing and calibration. The bare and bent optical fiber sensor and the temperature sensor LM35 are used to provide the measures of refractive index (RI) and temperature of a transformer oil sample. An ATmega32-microcontroller-based system with trained ANN algorithm has been developed to determine the moisture content of the transformer oil sample by sampling the readings of the bare bent optical fiber sensor and the temperature sensor.

/pdf/monitoring-of-moisture-in-transformer-oil-using-optical-u5oopvsg1a.pdf

Monitoring of Moisture in Transformer Oil Using Optical Fiber as Sensor

https://ietresearch.onlinelibrary.wiley.com/doi/pdf/10.1049/hve2.12074

High voltage power transformer condition assessment considering the health index value and its decreasing rate

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.

/pdf/study-on-correlation-among-oil-dielectric-characteristics-3ik7pdd8wh.pdf

Study on Correlation Among Oil Dielectric Characteristics, Dissolved Gases, and Operating Life of 150 kV Power Transformer

It is a well known fact that the moisture content of a power transformer insulation system is a key parameter for the estimation of its aging condition and operation reliability. Therefore detection of the moisture content is a very essential task within power transformer diagnostics. While conventional methods for estimation of the water content of the insulation system require a transformer shutdown for several hours, the proposed method calculates the profiles of water concentration in the cellulosic part of the insulation system, as well as the concentration of water in transformer oil from operational parameters. An advanced model for the moisture diffusion in paper estimates the temperature dependent moisture distributions in the paper for non-uniform temperature distributions along the transformer winding. The model covers temperature dependent diffusion coefficients and acts as a non-linear control loop for the water concentration in transformer oil. Moreover the water concentration at the oil-paper interface, which is a measure for the risk of surface discharges, is computed. The identification procedure for the models is based on nameplate data and dielectric response measurements. Sensors for temperatures and relative water concentration of oil provide the possibility to integrate the models into a framework of model-based diagnosis using structured residuals. The models have been verified with a laboratory setup consisting of a power transformer, equipped with sensors for temperature, load current and oil humidity.

An advanced model-based diagnosis system for online detection of the moisture content of power transformer insulations

It is a well known fact that the moisture content of a power transformer insulation system is a key parameter for the estimation of its aging condition and operation reliability. Therefore, detection of the moisture content is a very essential task within power transformer diagnostics. While conventional methods for estimation of the water content of the insulation system require a transformer shutdown of several hours, the proposed method calculates the profiles of water concentration in the cellulosic part of the insulation system, as well as the concentration of water in transformer oil from operational parameters. An one-dimensional model for the moisture diffusion in paper estimates the temperature dependent moisture distributions in the paper. It includes temperature dependent diffusion coefficients and acts as a non-linear control loop for the water concentration in transformer oil. Beside experimental work, two-dimensional finite element (FE) calculations of the temperature dependent water concentration distribution in the transformer insulation system have been performed for model verification. The calculations are based on an opensource Whitney-Element solver. The computed results show the validity of the diffusion model and give important guidelines for the required complexity of thermal models.

Verification of a model-based diagnosis system for on-line detection of the moisture content of power transformer insulations using finite element calculations

W. Hribernik

Papers

An advanced model-based diagnosis system for online detection of the moisture content of power transformer insulations

Verification of a model-based diagnosis system for on-line detection of the moisture content of power transformer insulations using finite element calculations