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Journal articles on the topic 'Transformer monitoring'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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1

Bansod, Pooja M., and Dinesh V. Rojatkar. "Transformer Parameter Monitoring and Controlling." International Journal of Trend in Scientific Research and Development Volume-1, Issue-6 (October 31, 2017): 812–14. http://dx.doi.org/10.31142/ijtsrd4632.

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2

Jaković, Tihomir, Ivan Murat, Filip Klarić, and Samir Keitoue. "Transformer Fleet Monitoring." Procedia Engineering 202 (2017): 20–28. http://dx.doi.org/10.1016/j.proeng.2017.09.691.

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3

Wu, H. "All eyes on transformers [super grid transformer remote monitoring]." Power Engineer 18, no. 5 (2004): 32. http://dx.doi.org/10.1049/pe:20040506.

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4

Angeline, P. M. Sneha. "Performance Monitoring of Transformer Parameters." IJIREEICE 3, no. 8 (August 15, 2015): 49–51. http://dx.doi.org/10.17148/ijireeice.2015.3811.

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5

Kovacevic, Dragan, Slobodan Skundric, and Jelena Lukic. "Monitoring and diagnostics of power transformer insulation." Thermal Science 10, no. 4 (2006): 43–54. http://dx.doi.org/10.2298/tsci0604043k.

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Liberalization of the energy market drives utilities to a more cost-effective power system. Power transformers are the most complex, important, and critical components of the transition and distribution power systems. Insulation system is the key component of life extension, better availability and higher reliability of a transformer. In order to achieve both decreasing operational cost and reliable service condition-based maintenance is needed. Monitoring and diagnostics methods and techniques, for insulation condition assessment of power transformers, are described. Date base and knowledge rules diagnostics management system, in internet oriented environment, is outlined. .

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6

Ottele, Andy, and Rahmat Shoureshi. "Neural Network-Based Adaptive Monitoring System for Power Transformer." Journal of Dynamic Systems, Measurement, and Control 123, no. 3 (February 11, 1999): 512–17. http://dx.doi.org/10.1115/1.1387248.

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Power transformers are major elements of the electric power transmission and distribution infrastructure. Transformer failure has severe economical impacts from the utility industry and customers. This paper presents analysis, design, development, and experimental evaluation of a robust failure diagnostic technique. Hopfield neural networks are used to identify variations in physical parameters of the system in a systematic way, and adapt the transformer model based on the state of the system. In addition, the Hopfield network is used to design an observer which provides accurate estimates of the internal states of the transformer that can not be accessed or measured during operation. Analytical and experimental results of this adaptive observer for power transformer diagnostics are presented.

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7

Liu, Li Peng, Yong Li Zhu, and Guo Qiang Wang. "Transformer Winding on-Line Monitoring and Diagnosis Using Current Source Method." Applied Mechanics and Materials 291-294 (February 2013): 2272–77. http://dx.doi.org/10.4028/www.scientific.net/amm.291-294.2272.

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Transformer winding deformation is a main type of transformer fault. The Frequency Response Analysis is a effective method to detect transformer winding deformation. Based on the traditional Frequency Response Method, the current source method is a new way to detect winding deformation. This method adopts the current source as sweep frequency source and uses the current frequency response curve to judge winding deformation. The simulation shows that the current source method is feasible. For some special transformers, this method can realize transformer winding on-line monitoring and diagnosis.

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8

Zhang, Wei Cong, Zheng Wu Dai, Wen Xiang Zhang, and Ji Zhang. "Research on Transformer Monitoring System Based on Vibrational Spectroscopy." Advanced Materials Research 765-767 (September 2013): 2238–41. http://dx.doi.org/10.4028/www.scientific.net/amr.765-767.2238.

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Power transformers vibration principle was analyzed, using vibration spectroscopy, design and development of a power transformer online monitoring system, through the transformer vibration monitoring, to indirectly infer the DC magnetic bias circumstances, Realized condition monitoring of Substation. This paper describes the system works, the constituent modules and the corresponding indicator characteristics, proposed monitoring algorithm optimization, Given the interface of real-time monitoring data, historical data, system was running good, stable and reliable.

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9

Liu, Wei Jia, Xin Wang, Yi Hui Zheng, Li Xue Li, and Qing Shan Xu. "The Assessment of the Overload Capacity of Transformer Based on the Temperature Reverse Extrapolation Method." Advanced Materials Research 860-863 (December 2013): 2153–56. http://dx.doi.org/10.4028/www.scientific.net/amr.860-863.2153.

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The assessment of the overload capacity of transformer has a certain practical significance. In this paper, a temperature reverse extrapolation method is proposed to assess the overload capacity of transformer. Firstly, the top oil temperature is monitored by the online monitoring system. Secondly, the temperature distribution model and the calculation methods of hot spot temperature in the PTP7 (Power Transformers. Part 7: Loading guide for oil-immersed power transformers) guide are analyzed. Then, a new method called temperature reverse extrapolation which can calculate the overload factor of transformer is composed. And based on the overload factor, two meaningful data about overload capacity are obtained. Finally, an assessment system of transformer overload capacity based on the online monitoring is developed.

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10

Ahmed, Aneel, Atif Saeed, and Mohammad Shan. "Real Time Condition Monitoring of Transformer." International Journal of Electronics and Electrical Engineering 6, no. 4 (2018): 71–75. http://dx.doi.org/10.18178/ijeee.6.4.71-75.

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11

Bengtsson, C. "Status and trends in transformer monitoring." IEEE Transactions on Power Delivery 11, no. 3 (July 1996): 1379–84. http://dx.doi.org/10.1109/61.517495.

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12

Disios, Konstantinos, Irodotos Mantas, Antonios Melanitis, Eleftherios Amoiralis, and Marina Tsili. "Electric Machine Design through Investigation of Thermal Performance by Installing Thermocouple Sensors." Materials Science Forum 856 (May 2016): 349–55. http://dx.doi.org/10.4028/www.scientific.net/msf.856.349.

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The aim of this paper is to explore new approaches of monitoring, diagnosis, condition evaluation, and possibility of extending the life of transformers. Research, emphasizing to experimental work, is conducted on a 1.5 KVA single-phase transformer to measure the internal temperature of the primary and secondary winding, using reliable instruments. Special consideration is given to the convenience in the acquisition and management of experimental data, so that the proposed monitoring system can be exploited for all kinds of thermal tests and various loading conditions. The transformer under study is designed and constructed from scratch, according to particular technical specifications. Having completed the transformer construction with the temperature sensors linked in each coil, our aim is to apply various types of loads and record the temperature variation inside the transformer. A process of acquisition and processing of data related to various parameters of transformers is developed so as to predict the behavior and prevent the failure of a transformer.

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13

Sun, Wen Xing, Zhao Hui Li, and Shi Jie Cheng. "A Highly Reliable Online Monitoring and Real-Time Alarm System for the Insulation Condition of Power Transformers." Advanced Materials Research 971-973 (June 2014): 1045–50. http://dx.doi.org/10.4028/www.scientific.net/amr.971-973.1045.

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Many successful applications for the online monitoring of the insulation condition for electric power transformers have been reported over last thirty years. However, false or unsolved alarms have been quite frequently generated by those condition monitoring systems. Failures and some occasionally catastrophic accidents involving transformers have still occurred. A highly reliable insulation condition online monitoring and real-time alarm system has been developed, to help resolve these problems. An electric power transformer has strongly linked mechanical, electrical, magnetic, chemical and thermal characteristics, and is also directly linked to circuit breakers and generators. Team Intelligence (TI) was employed to integrate all the monitoring modules of the various different aspects of the transformer into one unique system. This system could also be integrate with the condition monitoring systems of various linked facilities, such as the monitoring systems of the turbine and the generator in a Optimal Maintenance Information System for Hydropower Plant (HOMIS). Highly reliable monitoring and real-time alarms of transformer insulation condition could be achieved, due to highly coordinated and rapid response features. This system has been deployed in several hydropower plants. The industrial application examples are demonstrated.

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14

Ravi, Dayyala. "Condition Monitoring of High Voltage Transformer using Dissolved Gas Analysis Methods." International Journal for Research in Applied Science and Engineering Technology 9, no. VI (June 20, 2021): 1759–70. http://dx.doi.org/10.22214/ijraset.2021.35374.

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Power transformer plays a significant role in the entire power transmission network; thus, transformer protection requires more attention for fault free electric supply. when the mineral oil and insulation inside the transformer is subjected to high thermal and electrical stresses, gases are created by the decay of mineral oil and cellulose. Different gases create different faults, Identification of faults inside the power transformer before they occur reduces its failure rate during its service period. For Knowing the fault condition of power transformer, Dissolved Gas Analysis (DGA) is proven to be as accurate method based on combination of concentration of gases like CO, CO2, H2, C2H6, C2H4, C2H2 etc., Dissolved gas analysis is the most important test in determining the fault condition of a transformer and it is the first indicator of a problem and can identify deteriorating insulation and oil, overheating hot spots, partial discharge and arcing. For developing this DGA Techniques, the MATLAB GUIDE interface can be used for making easy interaction between the user and software developed. This software is designed using some conditional statements and logical functions to get the type of faults in transformers based on the concentration of gases in transformer oil. The faults in transformer using dissolved gases analysis are detected using methods such as key gas, Roger’s methods, IEC ratio, Doernenburg ratio, Duval triangle and the Combined DGA methods. In this paper, these four methods of dissolved gas analysis (DGA) are presented and explained briefly.

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15

Zhang, Zhan, and Cai Xia Gao. "Hardware Design of Online Monitoring System for Power Transformer Malfunction." Applied Mechanics and Materials 143-144 (December 2011): 618–21. http://dx.doi.org/10.4028/www.scientific.net/amm.143-144.618.

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Power transformers are vital equipments in the grid and their reliability can affect the security of the grid directly. So it is always necessary to monitor the power transformers online. The study designed a multi-parameter online monitoring system for power transformer malfunction utilizing DSP and computer technology. The paper mainly introduced the design and component selection of online monitoring circuit for partial discharge, dielectric loss, gas component in oil and iron core's grounding current. The result showed that this system can diagnose most the malfunctions in power transformers with satisfactory property.

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16

Hermawan, Ahmad, Rachmat Sutjipto, Shafira Irmadhani Hidayat, and Florentina Berlian Suryaningtyas. "Studi Pengaruh Pembebanan sebagai Dasar Scheduling Maintenance untuk Meminimalisir Susut Umur Transformator 1 GI Blimbing." ELPOSYS: Jurnal Sistem Kelistrikan 7, no. 3 (November 4, 2020): 33–38. http://dx.doi.org/10.33795/elposys.v7i3.16.

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Transformer 1’s load in Blimbing Substation has increased significantly each year. In 2016 until 2018 the load on Transformer 1 was 33.81%, 43.53%, and 71.75%. The amount of this transformer’s load will affect the hot spot temparature. Hot spot temperature is also affected by environmental temperature. In this study, load curve method was used then followed by calculate the loss life of transformer. From the calculation, known that the higher of hot spot temperature, the higher impact to loss life of transformer too. In 2018, the highest loading data was on November and it was obtained loss life of transformers by 0.649% per month, so it is estimated that this Transformer 1 at Blimbing Substation has a lifespan of 30 years 9 months. According to IEC 60076-7 normal life of transformers with loading under nominal is 20.55 years or 180000 hours. To minimize loss life of transformer or in other words extend the life time of transformer can be done by scheduling maintenance. Scheduling maintenance is the activity which monitoring the main transmission material on scheduled and provided a treatment based on the monitoring results. It can be concluded that the lifespan of Transformer 1 at Blimbing Substation can exceed the specified standard. The one of factors that affect this, is scheduling maintenance.

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17

Levin, Vladimir M., and Ammar A. Yahya. "Adaptive management of technical condition of power transformers." International Journal of Electrical and Computer Engineering (IJECE) 10, no. 4 (August 1, 2020): 3862. http://dx.doi.org/10.11591/ijece.v10i4.pp3862-3868.

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Ensuring reliable operation of power transformers as part of electric power facilities is assigned to the maintenance and repair system, whose important components are diagnostics and monitoring of the technical condition. Monitoring allows you to answer the question of whether the transformer abnormalities and how to do they manifest, while diagnostics allow determining the nature, the severity of the problem, determine the cause and possible consequences. The article presents the results of the authors ' research on creating an algorithm for adaptive control of the technical condition of power transformers using diagnostic and monitoring data. The developed algorithm implements the decision-making procedure for ensuring the reliable operation of oil-filled transformer equipment as part of the substations of electric power facilities. The decision-making procedure is based on the method of statistical Bayesian identification the states of a transformer based on the results of dissolved gas analysis (DGA) in oil. The method is characterized by high reliability of recognizing defects in the transformer and the ability to adapt the probabilities of the obtained solutions to the newly received diagnostic information. These results illustrate the effectiveness of the developed approach and the possibility of its application in the operation of oil-filled transformer equipment.

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18

G. Deakin, Anthony, Duncan H. Smith, Joseph W. Spencer, Darren Jones, and Nigel Johnson. "Chromatic acoustic condition monitoring of transformers." Sensor Review 34, no. 3 (June 10, 2014): 291–96. http://dx.doi.org/10.1108/sr-04-2013-663.

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Purpose – The purpose of this paper is to present an approach for continuous acoustic condition monitoring of transformers based on chromatic principles for abstracting information on individual acoustic events as well as secondary trends in the behaviour of the events. Design/methodology/approach – The potential benefits of condition monitoring of high-value transformer equipment are explored, and an approach based on chromatic information abstraction is illustrated and discussed. Findings – Tracking of large numbers of complex and variable individual acoustic events over time using a chromatic approach appears to offer a means for remote operators to evaluate mechanical transformer tap changer condition in a traceable manner. Originality/value – The condition monitoring is retrofittable and non-intrusive, and the approach may be applied generically for combining condition indicators for overall health-checking. A complex system behaviour may be operationally simplified without discarding the complexity.

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19

Wang, Zhenzhuo, and Amit Sharma. "Research on transformer vibration monitoring and diagnosis based on Internet of things." Journal of Intelligent Systems 30, no. 1 (January 1, 2021): 677–88. http://dx.doi.org/10.1515/jisys-2020-0111.

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Abstract A recent advent has been seen in the usage of Internet of things (IoT) for autonomous devices for exchange of data. A large number of transformers are required to distribute the power over a wide area. To ensure the normal operation of transformer, live detection and fault diagnosis methods of power transformers are studied. This article presents an IoT-based approach for condition monitoring and controlling a large number of distribution transformers utilized in a power distribution network. In this article, the vibration analysis method is used to carry out the research. The results show that the accuracy of the improved diagnosis algorithm is 99.01, 100, and 100% for normal, aging, and fault transformers. The system designed in this article can effectively monitor the healthy operation of power transformers in remote and real-time. The safety, stability, and reliability of transformer operation are improved.

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20

Behjat, Vahid, Reza Emadifar, Mehrdad Pourhossein, U. Mohan Rao, Issouf Fofana, and Reza Najjar. "Improved Monitoring and Diagnosis of Transformer Solid Insulation Using Pertinent Chemical Indicators." Energies 14, no. 13 (July 2, 2021): 3977. http://dx.doi.org/10.3390/en14133977.

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Transformers are generally considered to be the costliest assets in a power network. The lifetime of a transformer is mainly attributable to the condition of its solid insulation, which in turn is measured and described according to the degree of polymerization (DP) of the cellulose. Since the determination of the DP index is complex and time-consuming and requires the transformer to be taken out of service, utilities prefer indirect and non-invasive methods of determining the DP based on the byproduct of cellulose aging. This paper analyzes solid insulation degradation by measuring the furan concentration, recently introduced methanol, and dissolved gases like carbon oxides and hydrogen, in the insulating oil. A group of service-aged distribution transformers were selected for practical investigation based on oil samples and different kinds of tests. Based on the maintenance and planning strategy of the power utility and a weighted combination of measured chemical indicators, a neural network was also developed to categorize the state of the transformer in certain classes. The method proved to be able to improve the diagnostic capability of chemical indicators, thus providing power utilities with more reliable maintenance tools and avoiding catastrophic failure of transformers.

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21

Wang, Hong Jie, Jian Gang Bi, Yuan Yang, and Ning Yang. "The Develop of Intelligent Electronic Device Platform for Transformer Multi-Condition Monitoring." Applied Mechanics and Materials 543-547 (March 2014): 1050–56. http://dx.doi.org/10.4028/www.scientific.net/amm.543-547.1050.

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The intelligent electronic device used for transformer multi condition monitoring platform was designed based on IEC61850 communication protocol. Based on the analysis of condition monitoring parameter, the overall program and module function were elaborated, the function and design method of signal conditioning module, data acquisition and transformer system, threshold setting were discussed in detail. The intelligent electronic device platform can realize comprehensive monitoring of multi state parameters of transformers. The monitored data will be uploaded automatically in case of the monitoring parameters overrunning. The platform is of a high degree of intelligence, good reliability, flexibility, versatility, and scalability.

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22

Yang, Yunze, Chang Wang, Shujuan Li, Li Min, and Yuanyuan Yang. "Research review of transformer vibration monitoring technique." E3S Web of Conferences 252 (2021): 01062. http://dx.doi.org/10.1051/e3sconf/202125201062.

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Transformer vibration monitoring technique has been known to be safe, stable and resistant to interference. Based on the theories of transformer vibration and its origins, this study focuses on the equivalent mathematical model of transformer vibration, signal characteristics, as well as monitoring system for transformer vibration, to summarize research findings over recent years. A series of intelligent technologies have been adopted to reach certain diagnoses and monitoring outcomes; however, their applications are to some extent limited by the experience of users and other variants. The stability and reliability of techniques for monitoring transformer vibration need further improving.

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23

Jiang, Shu Bo. "Fault Monitoring of Transformer Based on FTIR." Advanced Materials Research 383-390 (November 2011): 5094–99. http://dx.doi.org/10.4028/www.scientific.net/amr.383-390.5094.

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Transformer is important power transmission equipment, and its working condition directly affects the safety level. Using the Fourier transformer infrared spectrometer for the qualitative analysis of the fault gases, using the theory of BP neural network for the quantitative analysis of the characteristics of the fault gases, can determine the operational status of transformer. This method monitors the function of the transformer effectively, judges the potential failure or hidden dangers accurately.

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24

Gao, Qiang, Feng Yuan, Zhan Nan Guo, Qi Liu, Dan Tian Zhong, Mao Jun Wang, Ping Li, et al. "Transformer Bushing Online Monitoring Method Based on the Method of Relative Angle Difference." Applied Mechanics and Materials 668-669 (October 2014): 961–64. http://dx.doi.org/10.4028/www.scientific.net/amm.668-669.961.

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Transformer is the main equipment of power system, its operation reliability is directly related to power system security and reliability of power supply. In order to guarantee the safe operation of power system, must strengthen the monitoring of the main transformer.With the development and popularization of intelligent station, the detection of transformers insulation is faced with the new problem that PT signal is not convenient to get and even unable to get. This paper proposes the relative method which is used to calculate and monitor dielectric loss of transformer bushing and designs the on-line monitoring device, through the data acquiring form the on-line monitoring instrument which are installed in the transformer of substation shows that this method has high precision, strong anti-interference ability.

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25

Ab Ghani, Siti Soleha, and Nor Asiah Muhamad. "Review on Dissolved Fault Gases in Monitoring Bio-Oil Filled Transformer." Applied Mechanics and Materials 818 (January 2016): 69–73. http://dx.doi.org/10.4028/www.scientific.net/amm.818.69.

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The combination of solid insulation (usually cellulose paper) and liquid insulation (usually mineral oil) yield good dielectric properties at fair cost. However, arising concerns on environmental effect of mineral oil when leakage and its risk of fire has force researches for alternative fluids. One of the suitable options for replacement of mineral oil is biodegradable oil that is plant-based, high biodegradability, non-toxicity and high fire point. Some refining and modification to crude vegetable oils resulting to suitable transformer dielectric fluid such as BIOTEMP®, ENVIROTEMP® FR3 and PFAE (palm fatty acid ester). Application of these oils in small scale distribution transformers give positive feedback so far, hence, led to development of biodegradable oil-based large power transformer. Monitoring of the oil for power transformer is important to ensure its reliability and avoid unnecessary cost of failure. Dissolved Gas Analysis (DGA) is one of the methods for oil monitoring of transformer. This method analyzes oil condition to detect incipient faults so that relevant actions can be made before actual failures occur. This paper will review the hydrocarbon gases or known as faults gases for monitoring and faults diagnosis for mineral and biodegradable oil-filled transformer. Past works about DGA on biodegradable oil such as sunflower, soybean, and corn oil are analyzed. Any different on gases production of oil through different tests will be discuss further in this paper.

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26

Zebua, Osea, Endah Komalasari, Syaiful Alam, and Aldiansyah Aldiansyah. "Rancang Bangun Alat Monitoring Ketidakseimbangan Beban Transformator Distribusi Berbasis Internet of Things." Electrician 15, no. 2 (May 6, 2021): 146–52. http://dx.doi.org/10.23960/elc.v15n2.2203.

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Intisari — Kerusakan transformator distribusi sering disebabkan oleh ketidakseimbangan beban, sehingga monitoring ketidakseimbangan beban transfornator distribusi perlu dilakukan. Letak dan lokasi transformator distribusi yang jauh dan tersebar mengharuskan monitoring harus dilakukan dari jarak jauh. Teknologi internet of things (IoT) dan komunikasi tanpa kabel mendukung monitoring dari jarak jauh. Makalah ini menyajikan perancangan dan pembuatan alat monitoring ketidakseimbangan beban transformator distribusi menggunakan teknologi IoT. Mikrokontroler Arduino digunakan untuk memproses data tegangan dan arus dari sensor, menghitung indikator ketidakseimbangan beban dan mengirim data hasil proses ke jaringan internet menggunakan Ethernet shield dan router yang diperlengkapi dengan modem. Thingspeak digunakan sebagai platform IoT. Hasil pengujian menunjukkan bahwa peralatan monitoring mampu bekerja dengan baik sehingga kondisi ketidakseimbangan beban transformator distribusi dapat dimonitor secara online dari jarak jauh menggunakan perangkat yang terhubung ke jaringan internet. Kata kunci — Monitoring, Ketidakseimbangan Beban, Transformator Distribusi, Internet of things. Abstract — Damage to the distribution transformer is often caused by unbalanced load, so it is necessary to monitor the unbalanced load condition of the distribution transformer. The remote and dispersed location of distribution transformers requires remote monitoring. Internet of things (IoT) technology and wireless communication support remote monitoring. This paper presents the design and manufacture of distribution transformer unbalanced load monitoring tools using IoT technology. The Arduino microcontroller is used to process voltage and current data from sensors, calculate unbalanced load indicators and send process data to the internet network using an Ethernet shield and a router equipped with a modem. Thingspeak is used as an IoT platform. The test results show that the monitoring equipment can work properly so that the distribution transformer unbalanced load conditions can be monitored online remotely using a device connected to the internet network. Keywords— Monitoring, Unbalanced Load, Distribution Transformer, Internet of Things.

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27

LUO, Mingfeng, and Dongyin LAI. "Distribution transformer monitoring and reactive power compensation." European Journal of Electrical Engineering 20, no. 3 (June 27, 2018): 309–24. http://dx.doi.org/10.3166/ejee.20.309-324.

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28

Bethalsha, C. "Real-Time Transformer Health Monitoring using IOT." International Journal for Research in Applied Science and Engineering Technology 8, no. 9 (September 30, 2020): 521–26. http://dx.doi.org/10.22214/ijraset.2020.31512.

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29

Fofana, Issouf, and Yazid Hadjadj. "Power Transformer Diagnostics, Monitoring and Design Features." Energies 11, no. 12 (November 22, 2018): 3248. http://dx.doi.org/10.3390/en11123248.

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30

Acakpovi, Amevi. "Transformer Wireless Monitoring System Using Arduino/XBEE." American Journal of Electrical Power and Energy Systems 8, no. 1 (2019): 1. http://dx.doi.org/10.11648/j.epes.20190801.11.

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31

Van Bolhuis, J. P., E. Gulski, and J. J. Smit. "Monitoring and Diagnostic of Transformer Solid Insulation." IEEE Power Engineering Review 22, no. 3 (March 2002): 62. http://dx.doi.org/10.1109/mper.2002.4312084.

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32

Tissier, Jean François, and Jérôme Cornet. "New soft sensors for distribution transformer monitoring." CIRED - Open Access Proceedings Journal 2017, no. 1 (October 1, 2017): 363–67. http://dx.doi.org/10.1049/oap-cired.2017.0840.

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33

van Bolhuis, J. P., E. Gulski, and J. J. Smit. "Monitoring and diagnostic of transformer solid insulation." IEEE Transactions on Power Delivery 17, no. 2 (April 2002): 528–36. http://dx.doi.org/10.1109/61.997930.

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34

Markova, L. V., N. K. Myshkin, and V. M. Makarenko. "Fluorescence Method for Quick Transformer Oil Monitoring." Chemistry and Technology of Fuels and Oils 52, no. 2 (May 2016): 194–202. http://dx.doi.org/10.1007/s10553-016-0690-5.

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35

Musthofa, Musthofa. "Sistem Monitoring Online Real Time Beban Unbalance dan Overload Trafo Distribusi di PT PLN (Persero)." Energi & Kelistrikan 12, no. 2 (December 22, 2020): 156–64. http://dx.doi.org/10.33322/energi.v12i2.1163.

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Public and government demands for PLN to serve all people to enjoy electricity with a target of 100% Electrification Ratio. To fulfill the Electrification Ratio, of course, it is necessary to increase the capacity of the distribution transformer with the addition of an insert transformer and a new transformer. So that the increasing number of connections to customers' homes or buildings will result in overload or unbalance loading of the distribution transformer. The problem is the number of transformers 3,938 units at PLN UP3 Padang with limited load measuring officers only 70 teams, there is still a transformer failure of 0.41% in 2019. This is because the load measurement is done directly (manually on site) so it requires large human resources and costs. Under these conditions, a realtime online load measurement system is needed. This study uses the Root Couse Problem Solving (RCPS) methodology and system and equipment design by creating a transformer load monitoring system both unbalance and overload online Real Time. With this System and Equipment, the substation load in realtime with a speed of 2 seconds, the condition of the transformer is known. Telemetering function by sending load data so that the risk of damage to the transformer can be reduced because this tool is an early warning against unbalanced loads, single phase outages and so on. So that PLN can maintain life time and recovery time in maintaining the quality of its service.

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36

Sihite, Josep Franklin, and Takehisa Kohda. "Power Transformers Condition Assessment of GI Simangkuk Switchyard Sumatra Interconnection in Indonesia." Advanced Materials Research 452-453 (January 2012): 975–79. http://dx.doi.org/10.4028/www.scientific.net/amr.452-453.975.

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The electricity needs of Indonesia grow an average 10% each year. Therefore, PLN (Perusahaan Listrik Negara) as the only power utility business in Indonesia, has a master plan to develop new power plant, switchyard and transmission system. One of the new developed systems is GI Simangkuk switchyard of Sumatra interconnection system. This switchyard is prepared to improve reliability of Sumatra interconnection system. This site utilizes power transformers of 275 kV. Power transformer is one of the main equipments in power systems. When a failure occurs in a power transformer, the whole system will be failed and the electricity could not be delivered to customer. Each utility has to assure their reliability in order to maintain electrical power system stability by assessing transformer condition. There is an increasing need for better diagnostic and monitoring tools to assess the condition of transformers. Modern power transformers are equipped with software and computer system control. The reliability of this computer systems are needed to evaluate for assurance of system safety. This paper describes the need of assessment and maintenance of power transformers such as outages effect of failures, high cost of maintenance and replacement, increase of world demand, aging effect and used of old transformer, and computer protection system failure. Monitoring and diagnostic methods of transformers assessment have been developing in recently years. They can be separated into traditional and non-traditional methods that have been used in many years and are still in research stage. In this paper we propose a new approach in order to assess power transformer condition by using fault tree analysis.

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Liang, Li, Ning Wang, Xiao Chang Ma, and Zhen Liu. "Design of On-Line Monitoring System for Transformer Oil Chromatogram and its Data Analysis." Advanced Materials Research 462 (February 2012): 281–86. http://dx.doi.org/10.4028/www.scientific.net/amr.462.281.

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On-line monitoring system of transformer oil chromatogram works in laboratory. Using the basic principles of gas chromatography (GC) of the broad spectrum, the system provides online-testing of dissolving gases from oil with a single gas chromatographic column and sensors with high sensitivity. The single-chip is used to collect the data and control transformers. The main controlling computer realizes the function of analyzing and managing the collected data, by which transformer fault can be judged.

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Liu, Ming Jun, Jian Zhang Zou, Qiu Kuan Zhou, Yang Lin Li, and Nian Ping Yan. "On-Line Condition Monitoring for Power Transformers Based on UHF PD Measurements." Advanced Materials Research 614-615 (December 2012): 1158–62. http://dx.doi.org/10.4028/www.scientific.net/amr.614-615.1158.

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An on-line monitoring system based on ultra high frequency (UHF) partial discharge (PD) measurements was developed for power transformers. The UHF PD signals were coupled by a UHF sensor and preprocessed by peak envelope detection technique. The system has high sensitivity, strong ability of interference suppression and well real-time capability according to the simulated experiment in lab and field test of a power transformer. Experimental results showed that the forepart PD faults could be discovered by the analysis of UHF PD signals. The on-line monitoring system has already been applied on a power transformer for years.

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Bustamante, Sergio, Mario Manana, Alberto Arroyo, Raquel Martinez, and Alberto Laso. "A Methodology for the Calculation of Typical Gas Concentration Values and Sampling Intervals in the Power Transformers of a Distribution System Operator." Energies 13, no. 22 (November 12, 2020): 5891. http://dx.doi.org/10.3390/en13225891.

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Predictive maintenance strategies in power transformers aim to assess the risk through the calculation and monitoring of the health index of the power transformers. The parameter most used in predictive maintenance and to calculate the health index of power transformers is the dissolved gas analysis (DGA). The current tendency is the use of online DGA monitoring equipment while continuing to perform analyses in the laboratory. Although the DGA is well known, there is a lack of published experimental data beyond that in the guides. This study used the nearest-rank method for obtaining the typical gas concentration values and the typical rates of gas increase from a transformer population to establish the optimal sampling interval and alarm thresholds of the continuous monitoring devices for each power transformer. The percentiles calculated by the nearest-rank method were within the ranges of the percentiles obtained using the R software, so this simple method was validated for this study. The results obtained show that the calculated concentration limits are within the range of or very close to those proposed in IEEE C57.104-2019 and IEC 60599:2015. The sampling intervals calculated for each transformer were not correct in all cases since the trend of the historical DGA samples modified the severity of the calculated intervals.

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Qu, Bo, Jian Bo Nie, Min Xuan Shen, and Kun Wang. "Design and Development of Transformer Data Monitoring System Based on J2EE." Advanced Materials Research 945-949 (June 2014): 2703–8. http://dx.doi.org/10.4028/www.scientific.net/amr.945-949.2703.

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The principle of the distribution transformer monitoring terminal and distribution transformer monitoring system is the base of the article. This paper establishes the implement programs of the distribution transformer monitoring system to strengthen the management of distribution transformer. This system provides many functions: real-time monitoring, graphs and reports display of historical data statistics of distribution transformer. This system uses formal J2EE framework, combining with eXtremeComponents (reporting system development tool) to develop customized reports.

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Sharma, R. Rajesh. "Design of Distribution Transformer Health Management System using IoT Sensors." September 2021 3, no. 3 (September 16, 2021): 192–204. http://dx.doi.org/10.36548/jscp.2021.3.005.

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Transformers are one of the primary device required for an AC (Alternating Current) distribution system which works on the principle of mutual induction without any rotating parts. There are two types of transformers are utilized in the distribution systems namely step up transformer and step down transformer. The step up transformers are need to be placed at some regular distances for reducing the line losses happening over the electrical transmission systems. Similarly the step down transformers are placed near to the destinations for regulating the electricity power for the commercial usage. Certain regular check-ups are must for a distribution transformer for increasing its operational life time. The proposed work is designed to regularize such health check-ups using IoT sensors for making a centralized remote monitoring system.

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Lu, Yong Jun, and Yi Bo Lu. "Research and Implement of Measuring the Errors of Transformers with Actual-Burden Using Programmable Digital Synthesizing Three-Phase Power Supply." Applied Mechanics and Materials 128-129 (October 2011): 970–74. http://dx.doi.org/10.4028/www.scientific.net/amm.128-129.970.

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Monitoring the actual state of transformer is imperative for measuring the errors of transformer with its actual burden load. The simplified three phases testing method is the practical and effective in monitoring the transformer state. And a programmable three-phase power supply is its core. The three-phase programmable power supply using DDS synthesizer can change the phase angle through changing triggering time of frequency update and adjusts amplitude through multiplier. It can generate three-phase signal voltage whose amplitude and phase angle can be adjusted by program. So it is suitable for the instrument for measuring the errors of transformer with its actual burden load. By using the instrument an environment of actual burden load is simulated completely. So the measuring of transformers with actual burden load is made precisely. The measuring principle and hardware and software design of the instrument are discussed in the paper.

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Shi, Lin, Long Hua Mu, Xu Feng Xu, and Xiao Ming Liu. "Scheme for on-Line Monitoring System of Converter Transformer." Advanced Materials Research 614-615 (December 2012): 1729–33. http://dx.doi.org/10.4028/www.scientific.net/amr.614-615.1729.

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To achieve a smart converter station, an on-line monitoring system for converter transformer is needed. Furthermore, it is the requirement for transition of maintenance strategy from ‘time-based maintenance’ to ‘condition-based maintenance’. This paper proposes a configuring of converter transformer on-line monitoring system based on the principle and application of on-line monitoring system for transformer, and the characteristics and operating environment of converter transformer. Architecture of converter transformer on-line monitoring system is also proposed on the basis of the 3-layer & 2-net structure applied in new smart substations and reconstruction. The designed scheme is suitable for transformation or new of smart converter transformer on-line monitoring system, which with good reference significance and application value.

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Wu, Min, and Hai Pu. "Study on Online Monitoring System of Power Transformer." Advanced Materials Research 1030-1032 (September 2014): 1484–87. http://dx.doi.org/10.4028/www.scientific.net/amr.1030-1032.1484.

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This paper puts forward an on-line monitoring system of power transformer which could online collect multiple physical parameters of power transformer at the same time without using electricity sensor. In this case, the sensor will not affected by the strong electric field, magnetic field and electromagnetic wave. The system analysis the running state of power transformer according to physical parameters accurately, as current technology can only measure single physical parameters, it can solve this problem that the measurement results lack of association. Moreover, the system improves the reliability of power transformer operation and security of online measurement, ensuring the safe operation of power system.

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Liu, Guang Ya, Lu Kang, and Wei Na Peng. "On-Line Monitoring System for Transformer Partial Discharge." Applied Mechanics and Materials 303-306 (February 2013): 464–67. http://dx.doi.org/10.4028/www.scientific.net/amm.303-306.464.

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On-line insulation monitoring of transformer and the fault diagnosis are effective means to avoid sudden accidents happening on the transformer, which are necessary to perform the condition based maintenance (CBM) of transformer. Partial discharge is often accompanied by the external signals of sound, light and electricity as well as some detectable physical phenomena such as characteristic gas and dielectric loss. The partial discharge defects inside the transformer can be found by detecting the external signals. The principle of electro-acoustic monitoring, its monitoring systems and the related judgment technologies are expounded, on the basis of which an outline design of the monitoring system is presented.

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Tong, Liu. "Research on Intelligent Online Monitoring and Evaluation of Power Transformer." Open Electrical & Electronic Engineering Journal 9, no. 1 (October 9, 2015): 483–89. http://dx.doi.org/10.2174/1874129001509010483.

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Transformer is the power equipment of power system core. Intelligent monitoring and operation of transformer can not only monitor the full range of the transformer, the realization of state evaluation, it should be required repair, maintenance required good, but also on the latent fault early diagnosis and prediction. Research on transformer intelligent monitoring and operating technology of safe operation of power system and the substation has great significant and impoertance. According to the theory and method of transformer intelligent, combined with intelligent transformer on-line monitoring technology has been achieved, mainly explores the intelligent cooling and adjustable transformer pressure control technology.

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Hernandez, Maria Del Pilar Colin, and Ashraf Labib. "Selecting a condition monitoring system for enhancing effectiveness of power transformer maintenance." Journal of Quality in Maintenance Engineering 23, no. 4 (October 9, 2017): 400–414. http://dx.doi.org/10.1108/jqme-07-2015-0027.

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Purpose The purpose of this paper is to propose a model for assisting in the decision-making process for acquiring a condition monitoring (CM) system for an oil-immersed power transformer in order to improve its maintainability. Design/methodology/approach The proposed model is based on the analytic hierarchy process. The assessment was performed by pairwise comparisons, and a sensitivity analysis (what-if analysis) was used to identify the implications of changing the criteria weights. In order to select the criteria and alternatives, a search was conducted for the power transformer failure modes, monitored parameters and CM technologies. Findings The proposed model provides a structured solution for a complex problem: deciding the best combination of technologies for CM of power transformers. Research limitations/implications Because the pairwise comparisons were done only by the author, the results may need to be improved with the assessment of more experts. Also, it was done for a specific type of transformer; it might be necessary to customise the alternatives for other cases. Finally, as a future consideration, more levels can be added to the hierarchy to improve the accuracy of the model. Practical implications The power transformer is an asset where the most appropriate maintenance strategy for it is condition-based maintenance. In order to improve its maintainability, it is recommendable to improve its testability and diagnosability. For achieving this goal, the maintenance personnel have to decide the best combination of technologies for CM. The methodology developed can assist the decision makers to select the most appropriate cost-benefit strategy. Originality/value The paper presents a structured and generic method of selecting the most appropriate CM system for power transformers.

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Liu, Yong, Liang Ding, Shi Long Tang, Min Yi Guo, and Zhan Long Zhang. "Real-Time Online Monitoring of Transformer Losses and the Warning Devices." Advanced Materials Research 562-564 (August 2012): 1809–14. http://dx.doi.org/10.4028/www.scientific.net/amr.562-564.1809.

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Developing a transformer loss monitoring and warning online equipment, introduces the theory, composition and application of the system. The whole system consists of monitoring terminal and the monitoring center. Monitoring terminal obtains transformer loss by acquiring transformer secondary current signal. When transformer loss is high, the staff takes order to reduce the loss and improves energy efficiency according to the data.

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Yuan, Lu Lu, Zhu Yuan, and Wei Wei Zhang. "The Necessity of Intelligent Transformer On-Line Monitoring Configuration Analysis." Applied Mechanics and Materials 427-429 (September 2013): 1297–300. http://dx.doi.org/10.4028/www.scientific.net/amm.427-429.1297.

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Intelligent transformer as an important part of intelligent substation, can be flexible and controllable and can real-time monitoring, protection, control transformer normally. online monitoring is the guarantee of realization of intelligent transformer, Partial discharge on-line monitoring optical fiber temperature measurement, casing medium on-line monitoring, winding on-line monitoring are the most important three aspects. The commonly used methods of Partial discharge on-line monitoring, a pulse current method, UFH method, gas chromatography, and ultrasound. The analysis of necessity of the main transformer partial discharge on-line monitoring configuration, and the fiber winding temperature online monitoring configuration.

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Ding, Qiao Lin, Jian Chen, and Li Qing Liu. "The Research of Spectral-Line Monitoring of Transformer Vibration." Applied Mechanics and Materials 128-129 (October 2011): 1489–92. http://dx.doi.org/10.4028/www.scientific.net/amm.128-129.1489.

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This paper presents the using vibration spectrum of transformer operational status with online monitoring methods, analyzes and discusses the transformer vibration spectrum about the producing mechanism and extraction scheme . At the same time, it also discusses the feasibility and necessity of using vibration spectrum methods to monitor the transformer fault .Some vibration spectrum methods ,relating to the transformer research contents and key technical breakthrough direction, are summarized in detail. Finally, it put forward a new immune from organization antibody network model and antibody generating algorithm that is used for vibration spectrum power transformer fault diagnosis.

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