Transformer Monitoring System Research Articles

An Experimental Setup for Monitoring Distribution Transformer Health

The Distribution transformers are the most expensive and important component which are used for transmission and distribution of electrical energy. It is imperative that the transformers function correctly without any faults, and should any faults occur, the same should be detected and corrected as soon as possible to prevent the failure of the power system to supply power. Health monitoring systems of distribution transformers are used to diagnose the distribution transformer and to deduce its working condition under the occurrence of incipient faults. This paper presents a model of a health monitoring system for distribution transformers in a laboratory environment. The proposed model ensures that faults do not disrupt the regular supply of power.

Research on Intelligent Monitoring Technology of Substation and Distribution Station Driven by Big Data

The power transformation and distribution station is the power supply foundation to ensure the normal operation of all kinds of large factories and large communities. The realization of the overall solution of intelligent monitoring system for transformer and distribution station based on big data helps to ensure the safe operation of power transformation and distribution station and ensure the quality and stability of regional power supply. The intelligent monitoring system of power transformation and distribution station based on big data is composed of automatic monitoring system of power transformation and distribution and intelligent monitoring system of Internet of things of power transformation and distribution station. Through the research and application of partial discharge monitoring, SF6 leakage detection, wireless sensor and other technologies, big data analysis technology is used to analyze the monitoring data, so as to realize remote monitoring and intelligent monitoring and diagnosis of power transformation and distribution station.

A Monitoring Method for Average Winding and Hot-Spot Temperatures of Single-Phase, Oil-Immersed Transformers

Transformers are the most expensive element of a power system, and so transformer monitoring systems are becoming more important as loads increase. Under heavy loading conditions, the hot-spot temperature of a transformer is the most critical parameter to determine the limit of loading. Therefore, to make an accurate estimation of hot-spot temperature and maintain the reliability of a power system, dynamic thermal models or methods must be employed. Due to the complexity of thermal phenomena, the methods presented so far needs to be improved to reduce computational errors. This is particularly the case for variable loading conditions and power utilities are still in need of good techniques. This paper describes two methods to determine temperature in single-phase, oil-immersed transformers. The first method calculates average windings temperature (AWT) using the voltage and current from primary and secondary windings. The second method, which uses data from the first method, determines the hot-spot temperature of the transformer. The methods have been investigated by experiments on a 30 kVA single-phase transformer and verified the results using COMSOL ™ software. Our methods have proven more accurate than the IEEE Annex G method.

The study of health and quality of operation of the transformer equipment electrical systems

Detection of defects at an early stage of their occurrence, especially for power transformers that have worked out the standard term, is an acute problem. This article discusses the possibility of using the system of monitoring, control and diagnosis of transformer equipment (SMUID) electrical systems in conjunction with the automated control system of electrical equipment (ASU ETO) and automated information-measuring system of commercial electricity metering (AIIS KUE) with the use of QR-code, as well as using TeamViewer for the operational elimination of accidents and identify abnormal operation of transformer equipment. Transformer monitoring system is designed for monitoring isolation, recording and analysis of partial discharges, monitoring of technical condition ensuring maximum fault-free service life of transformers. In addition, the introduction of automated diagnostics and electrical equipment is a necessary condition for the introduction of SmartGrid technology in industrial electric networks, contributes to the reduction of capital investments in the renewal of the equipment fleet. The methods currently used do not detect dangerous insulation degradation, are not sensitive to its aging, and in some cases mistakenly assess the isolation condition. The work analyses the operability and quality of the systems under consideration, shows the hierarchical structure of SMUID. By applying the proposed idea with the QR-code, it is possible to speed up the process of searching for information about the current technical state of electrical equipment.

Transportation Monitoring of Geo-Location, Speed, Vibration, and Shock Acceleration for 110-kV Vehicular Mobile Transformers

As a kind of transformer installed on vehicles, the vehicular mobile transformer needs to realize frequent transportation quickly and safely. However, there are few studies on the on-line monitoring of vehicular mobile transformers. In this article, a transportation condition monitoring system for vehicular mobile transformers is introduced and developed. The transportation process of a 110-kV/40-MVA vehicular mobile transformer is monitored from Jiangsu Province to Guangdong Province, which is recognized as the first time that the transformer is monitored for more than 12 h and more than 1000-km transportation. The geo-location, driving speed, vibration, and shock acceleration in six different road sections are obtained in real-time. The results show that the vibration and shock acceleration has a strong positive correlation with the driving speed. The amplitude of the $y$ -axis acceleration is generally the lowest among three-axis accelerations, and the three-axis vibration and shock acceleration has the same trend of increase and decrease. During the whole transportation process, the driving speed of the 110-kV/40-MVA vehicular mobile transformer varies from 0 to 76 km/h, and the vibration and shock acceleration amplitudes obtained by the monitoring system do not exceed 1 g, which has great significance to the safe operation of power grid and can provide the strong evidence of online monitoring data to set transportation guidelines for vehicular mobile transformers.

Overvoltages and Transients Identification In On-line Bushing Monitoring

Overvoltages and transients are sometimes recognized as the cause of bushings’ rapid failure. This fact is confirmed by the studies published at the 2018 CIGRE session. They can also initiate dangerous resonance phenomena in transformer windings. The identification of very fast overvoltages characterized by high dynamics of voltage changes, so-called "transients", is difficult due to the limited frequency response of station voltage transformers. However, the bushing monitoring systems, based on the so-called "voltage method" can be used for this purpose successfully. There are several running bushing monitoring systems based on this method in Poland. The transients’ events are registered together with their oscillographs in Transformer Monitoring Systems (TMS). The overvoltage statistics are also performed to support service procedures.The TMS are integrated with station systems, which greatly increases the possibility of overvoltages phenomena analyzing.

On-Line Partial Discharge Monitoring System for Power Transformers Based on the Simultaneous Detection of High Frequency, Ultra-High Frequency, and Acoustic Emission Signals

The article presents a novel on-line partial discharge (PD) monitoring system for power transformers, whose functioning is based on the simultaneous use of three unconventional methods of PD detection: high-frequency (HF), ultra-high frequency (UHF), and acoustic emission (AE). It is the first monitoring system equipped in an active dielectric window (ADW), which is a combined ultrasonic and electromagnetic PD sensor. The article discusses in detail the process of designing and building individual modules of hardware and software layers of the system, wherein the most attention was paid to the PD sensors, i.e., meandered planar inverted-F antenna (MPIFA), high-frequency current transformer (HFCT), and active dielectric window with ultrasonic transducer, which were optimized for detection of PDs occurring in oil-paper insulation. The prototype of the hybrid monitoring system was first checked on a 330 MVA large power transformer during the induced voltage test with partial discharge measurement (IVPD). Next, it was installed on a 31.5 MVA substation power transformer and integrated according to the standard IEC 61850 with SCADA (Supervisory Control and Data Acquisition) system registering voltage, active power, and oil temperature of the monitored unit. The obtained results showed high sensitivity of the manufactured PD sensors as well as the advantages of the simultaneous use of three techniques of PD detection and the possibility of discharge parameter correlation with other power transformer parameters.

Power Transformer Monitoring System

Monitoring and diagnosis of power as well as distribution transformer is the most important process for extending the life of transformer. A transformer monitoring system is already developed by Siemens which is based on SCADA system. But that system can’t be used in small scale industry because most of the industry lacks in automation. This paper presents the details of a monitoring system which is a standalone device equipped on every transformer individually and this device is able to detect phase failure, unbalanced voltage, and earth fault. Apart from these, the device can also monitor the oil level and oil temperature. The main aim of research is to develop this product and make available on economic rates.

Use of sensor networking technology to build a power transformer monitoring system

The paper discusses the technology of designing a monitoring system for power transformers and power supply devices, based on the use of sensor networks, describes the creation of a Bayesian network to predict the probability of failure. Conditions for achieving the maximum diagnostic efficiency with the required accuracy are formulated. A diagnostic system is proposed that allows assessing the influence of each parameter on the accuracy of predicting failures. Using the method of expert assessments, the possibility to calculate the probabilities of failures with a lack of information is shown.

Study of on-line monitoring and fault diagnosis system for a naval transformer

Study of on-line monitoring and fault diagnosis system for a naval transformer

An Internet of Things (IoT) based Monitoring System for Oil-immersed Transformers

While the electricity power industry in the world continues to grow, it also becomes more traceable and smart with the developing technology. Naturally, the integration of these technologies into the electrical power systems brings with an additional cost. Most of the time producers and consumers struggle under the pressure of these additional costs and try new products that will reduce the cost. In this sense, competitive products in the market must be advantageous in terms of cost. In this study, an original IoT based transformer monitoring system has been developed by using open source software, modular and low cost components as an alternative to studies in literature. Arduino Mega 2560 microcontroller has been used as the main component in the system. The system can acquire data from a wide variety of sensors using internal and external transducers. And this data can be saved to the cloud system synchronously with the memory card on the monitoring system. The developed monitoring system has been utilized free and reliable platforms such as the ThingSpeak web interface and PushingBox Notification application. The all test process of the developed monitoring system has been carried out in the laboratory environment.

Adjustment of Model Parameters to Estimate Distribution Transformers Remaining Lifespan

Currently, the electrical system in Argentina is working at its maximum capacity, decreasing the margin between the installed power and demanded consumption, and drastically reducing the service life of transformer substations due to overload (since the margin for summer peaks is small). The advent of the Smart Grids allows electricity distribution companies to apply data analysis techniques to manage resources more efficiently at different levels (avoiding damages, better contingency management, maintenance planning, etc.). The Smart Grids in Argentina progresses slowly due to the high costs involved. In this context, the estimation of the lifespan reduction of distribution transformers is a key tool to efficiently manage human and material resources, maximizing the lifetime of this equipment. Despite the current state of the smart grids, the electricity distribution companies can implement it using the available data. Thermal models provide guidelines for lifespan estimation, but the adjustment to particular conditions, brands, or material quality is done by adjusting parameters. In this work we propose a method to adjust the parameters of a thermal model using Genetic Algorithms, comparing the estimation values of top-oil temperature with measurements from 315 kVA distribution transformers, located in the province of Tucumán, Argentina. The results show that, despite limited data availability, the adjusted model is suitable to implement a transformer monitoring system.

Power transformer monitoring systems for better asset management

The technology of sensors and other control equipment installed on power transformers has improved rapidly in last few years, with the number of new solutions and measuring methods also continuously growing. Monitoring systems contain a large variety of different measurements and calculated data related to measured values and standards. Monitoring systems on power transformers are not only a new feature for users, they can also be a good tool for manufacturers during the transformer's lifetime. Transformer manufacturers are able to monitor their products through such systems using data and events recorded on the transformer. Users are able to detect events or developing faults on the transformer that could disturb its operation. This leads to more efficient asset management. ICT equipment that is the core of such systems offers almost unlimited possibilities for processing and storing the recorded data. Also, a visualisation of such a system can be presented to the user using an innovative graphic interface. One of the most important requirements during the design phase of a described monitoring system was also the implementation of a dissolved gas sensor with multiple gas measuring capabilities. Measuring of multiple dissolved gases in transformer oil is important for better monitoring and understanding of transformer condition and better prediction of possible failures during the operation.

Online condition monitoring system for substation and service transformers

Deregulation in power industry accelerates competition among various power companies. These companies are trying to gain maximum profit with minimum maintenance cost. This could be achieved by developing a condition-based monitoring product for the assessment of health of substation and service transformers. This study presents online condition monitoring system (OCMS) for transformers which is useful to replace reactive and preventive maintenance of transformers by predictive maintenance. Proposed OCMS is cost effective, online and accurate tool and it has several features like proposing corrective actions for the benefit of power utilities. Proposed system results are evaluated by comparing with the results obtained from utility model. Proposed OCMS applies only to transformers without abnormal faults such as detected by dissolved gas analysis. It is therefore very different from the other health index algorithms present in the market for condition monitoring of transformers, including in case of abnormal faults.

Transformer Fleet Monitoring

Transformer monitoring systems are increasing in number and having a clear overview of the whole fleet of monitored transformers is becoming crucial in an effort to provide the end user with an easy way to monitor its transformer assets and react accordingly to the monitored situations. This paper will introduce a Fleet monitoring solution that provides the architecture and tools to accomplish the set tasks of connecting and accessing information of all the monitoring systems from their dedicated locations.Standard transformer monitoring system configuration is made of a local unit on the transformer for collecting and processing raw data from the sensors and transferring the data to another unit, usually a server located in the substation which stores it in the database. The server unit is also responsible for the presentation of data to the end user and communication with supervisory control systems. This configuration is well capable of achieving its purpose of monitoring the transformer state and operation. The challenge is in accessing the monitored data.Traditional approach for accessing the data was to access the servers locally in the substations. Responding to the monitored conditions was done by connecting critical alarm signals from the monitoring system to the substation control system and in case of an alarm indication the operator from the substation was required to access the monitoring system for further details and inform personnel responsible for the maintenance of transformer units. The transformer maintenance personnel were then required to check the monitored data either by connecting remotely to the monitoring system, which in most cases is not possible due to security and technical restrictions, or to travel to the remote location to investigate the issue. This approach was both very time consuming and costly. There is also a consideration that the modern substations are becoming unmanned or have just a basic crew which may consist of personnel not qualified or trained for the required tasks.The challenge was to enable a centralized access to the distributed monitoring systems across multiple substations. An architecture, both hardware and software, was developed, that accomplishes this task. The architecture is highly modular so that the components of the system can be distributed and integrated into an overall system which is fully customizable to the end user requirements. During development one of the main considerations was to make the integration of already existing systems as seamless as possible. The result is a Fleet monitoring solution that centralizes access to the information from all connected monitoring systems while at the same time does not interfere with the work of dedicated monitoring systems at remote locations. This way the data can be presented directly to the right personnel. This paper will also discuss further goals and directions of development for transformer fleet monitoring.

Distribution transformer monitoring for smart grid using FPGA: a case study implementation in Indian conditions

In this paper, a pilot implementation of a distribution transformer monitoring system (DTMS) using field programmable gate array (FPGA) based technology has been explained in the context of smart grid developments in India. The field implementation consists of a network of sensors, energy meters and communication over wireless network. ZigBee technology has been used between end nodes and data concentrator for local area network (LAN); whereas, general packet radio services (GPRS) has been used for communication between data concentrator and utility control centre. The system is installed at a group of DTs to test its field performance. This approach effectively monitors the operating state of a network of transformers and dispatches the critical information to maintenance personal. The system has the scalability to interface the range of sensors and energy meters, and communicate over different protocols. The main advantage of the system is the significant cost savings and its reliability.

Характеристика систем непрерывного контроля технического состояния печных трансформаторов

The paper describes briefly transformers of the ladle furnaces (LF) of the electric steel making shop (ESMS) at OJSC Magnitogorsk Iron and Steel Works. It notes a lack of regulations and experience of development and implementation of the system for control of furnace transformer condition at domestic iron and steel works. The paper provides analysis of the known systems enabling condition monitoring for transformers of this class. Their disadvantages are mentioned, too. Main attention is paid to estimation of the TDMS system developed by OJSC Dimrus together with Magnitogorsk State Technical University and OJSC Magnitogorsk Iron and Steel Works. The modular configuration is under consideration. System units and sensors installed at ESMS transformers are listed. The study provides a list of main functions and technological parameters controlled by the system. It describes the MINITRANS device designed for gas and oil moisture control and installed at transformer of LF No. 3 and the unit of built-in sensors used within the transformer monitoring system of LF No. 1. Interface of the TDMS system is considered; main views of the application are also provided. The paper suggests the threshold values of main diagnostic parameters reflecting transformer technical condition. Technical and economical benefits resulted from the system introduction should be noted.

Study on the Detection of Transformer Oil Temperature

Based on the influence of the ambient temperature, wind speed and other factors on the transformer monitoring system, the hot spot temperature model of the transformer outer wall is established by using thermoelectric analogy theory and lumped parameter model. Through the analysis of experimental data, mathematical model of influence of ambient temperature and wind speed on temperature of transformer is built, and the correction values on the temperature of the transformer are obtained under the different ambient temperature and wind speed. The correction values make the transformer hot-spot temperature more objective and more authentic, which has significant influence on the running of the transformer safely and efficiently.

Analysis of Partial Discharge Signal Characteristics of Nano-Mineral Oil for Transformer Condition Monitoring Applications

Transformer is an expensive and key component in an electric power transmission network. Most of the failure of transformer occurs due to degradation of insulation oil, which further leads to major economical losses and power shutdown. Advancements in nanotechnology has given horizons for the development of nanofluids for transformer insulation applications. Understanding the enhancements in dielectric properties of nanofiller added mineral oil is a hot research area. In recent times, partial discharge (PD) detection and analysis is a well recognized insulation condition monitoring technique for transformers. However, reports on PD signal characteristics of nano filler added mineral oil is scanty. This paper attempts to investigate the PD characteristics of SiO2 nanofiller added mineral oil at different %wt concentrations of nanofiller material. Major PD source normally experienced in transformers i.e. corona discharge due to non-uniform electric field was simulated in the laboratory using needle-plane electrode configuration and the corresponding PD signals were measured using wide band PD detection system. Important PD characteristics such as inception voltage, stable PD formation voltage, PD amplitude with respect to increase in voltage stress and PD signal frequency spectrum were evaluated. Results clearly show that addition of SiO2 nanofiller material in the base mineral oil enhances PD performance of mineral oil and these results will be useful for electrical utilities for developing effective condition monitoring system for transformers.

Electrodynamic energy harvester for electrical transformer’s temperature monitoring system

The development of an electrodynamic energy harvester (EDEH) for operating a wireless temperature monitoring system for electrical transformer is reported in this work. Analytical modeling, fabrication and characterization of EDEH prototype are performed. The developed EDEH consists of a mild steel core, a wound copper coil and Teflon housing. COMSOL Multiphysics software is used to optimize the design of the harvester. The split-cylindrical design of the developed EDEH permitted the harvester to be wrapped around the output power cable of the electrical transformer without shutting-off the power or disconnecting the power cable. From the electrical transformer, at current levels of 27, 72 and 155 A in the main power line, the energy harvester produced maximum RMS load voltages of 0.356, 1.09 and 2.58 V respectively, when connected to 100 Ω load resistance. However, at matching impedance of 24 Ω (resistance of the coil), the EDEH produced the maximum power levels of 2.99, 19.66 and 112.03 mW for a cable currents of 27, 72 and 155 A respectively. The simulation results of the devised analytical model of the harvester are in good agreement with the experimental results. Moreover, at a cable current of 93 A, when the harvester is connected to the rectifying circuit, the optimum impedance shifted to 185 Ω and the maximum power of 19 mW is generated at that load. The reduction in power generation is attributed to the power consumption of the rectifying circuit. When the rectified DC voltage is used to charge a 3.8 V, Nickel–Cadmium (Ni–Cd) rechargeable battery, it took 3 h to completely charge the battery from 1 to 3.85 V. With the charged battery a wireless temperature sensor node is successfully operated for monitoring the temperature of the electrical transformer.