Reliable Estimation for Health Index of Transformer Oil Based on Novel Combined Predictive Maintenance Techniques

Badawi, Mohamed; Ibrahim, Shimaa A.; Mansour, Diaa‐Eldin A.; Elfaraskoury, Adel A.; Ward, Sayed A.; Mahmoud, Karar; Lehtonen, Matti; Darwish, Mohamed M. F.

doi:10.1109/access.2022.3156102

Cited by 45 publications

(6 citation statements)

References 41 publications

(70 reference statements)

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“…CMD is applied to many power system components like generators, transformers, switchgear, transmission lines, cables etc. Up to now, researchers have put forward many developments and much progress in CMD of electrical power equipment and components by using different ways with different measured quantities [107–110]. Generally, CMD of electrical power components is carried out to achieve one or more of the following: Preventing failures and reducing maintenance costs: Any degradation or damage of certain equipment usually results in the eventual failure of such equipment.…”

Section: Iot and Digital Twin For Condition Monitoring And Diagnosismentioning

confidence: 99%

Applications of IoT and digital twin in electrical power systems: A comprehensive survey

Mansour

Numair

Zalhaf

et al. 2023

IET Generation Trans & Dist

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This paper reviews the applications of Internet of Things (IoT) and digital twin technology in electrical power systems. It begins by discussing the generalized IoT value chain, followed by the terminology of smart grid, with clarifying the role of IoT‐systems and the digital twin structure within the Smart Grid. A comparison between different short‐range and long‐range transports is presented. The paper then discusses the use of IoT and digital twin technology for effective energy management with applications in smart homes, smart buildings, smart grids, smart industries (Industry 4.0), smart transportation and smart cities. Additionally, the paper explores the use of IoT and digital twin technology for condition monitoring and diagnosis (CMD) in electrical power systems. Three different cases are presented for CMD, that is, CMD of power transformers, CMD of electrical grids and CMD of substations. IoT and digital twin applications are also highlighted in power electronic systems. Finally, the paper discusses the challenges and opportunities of applying IoT and digital twin technology to electrical power systems and provides recommendations for future research.

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Section: Iot and Digital Twin For Condition Monitoring And Diagnosismentioning

confidence: 99%

Applications of IoT and digital twin in electrical power systems: A comprehensive survey

Mansour

Numair

Zalhaf

et al. 2023

IET Generation Trans & Dist

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“…As one of the main equipment in the power system, the normal operation of the transformer is crucial for the reliability and stability of the power system . Dissolved gas analysis (DGA) in oil is an effective means to find early transformer faults and can determine the operating status of the transformer in advance, , which is of great significance in guiding the transformer overhaul work and preventing major accidents in the power grid. − Overheating of oil and paper inside the transformer, partial discharge of oil-paper insulation, moisture or bubbles in the oil, increased water content in the oil, and so forth will produce H 2 , CH 4 , NO 2 , C 2 H 2 , CH 4 , and other dissolved gases in the oil. − DGA can monitor the dissolved gas in the transformer oil in real time and online and send out an alarm signal when the concentration and rate of change of the dissolved gas in the oil exceeds a certain limit, so that effective measures can be taken in time to avoid transformer failure. , Therefore, the effective monitoring of dissolved gases in transformer oils is of great significance.…”

Section: Introductionmentioning

confidence: 99%

Adsorption Behavior of Dissolved Gas Molecules in Transformer Oil on Rh Modified GeSe Monolayer

Long,

Peng,

Guo

et al. 2024

ACS Omega

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Dissolved gas analysis in transformer oil is useful for detecting early transformer failures. The research on gas sensors for monitoring dissolved gas in transformer oil has attracted wide attention from academia and industry. In this study, Rh-doped GeSe monolayers were used as gas sensing materials based on the density functional theory (DFT). The potential of the Rh-GeSe monolayer as a gas sensor was evaluated by calculating the geometric structure, adsorption distance (d sub/gas ), binding energy (E b ), adsorption energy (E ads ), transfer charge (ΔQ), the density of states (DOS), band structure, electron localization function (ELF), charge difference density (CDD), and sensitivity (S) of Rh-GeSe monolayer with eight gas molecules (SO 2 , C 2 H 2 , NO 2 , H 2 , CH 4 , CO 2 , H 2 S, and CO). The results show that the Rh-GeSe monolayer has a prominent response to SO 2 , C 2 H 2 , and NO 2 gas molecules and has great potential to become an excellent gas sensor. This study provides a theoretical basis for the application of Rh-GeSe monolayer in the field of gas sensing and provides a new way for the development of other gas sensors.

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“…Any fault in the transformer causes a sudden interruption of the power supply, increases the reparation cost, and reduces the power system's reliability. Consequently, avoiding failures and maintaining the safe operation of transformers is crucial to ensure the overall system's reliability [1][2][3][4]. The health of a power transformer's insulation is critical to its long-term integrity and reliability.…”

Section: Introductionmentioning

confidence: 99%

Dissolved gas analysis and dissipation factor measurement of mineral oil‐based nanofluids under thermal and electrical faults

et al. 2023

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Mineral oil is the most frequent insulating liquid used in oil‐immersed transformers for electrical insulation and heat dissipation. However, oil‐based nanofluids are becoming more popular in scientific research as they have proved to have better dielectric and thermal characteristics. When applying these nanofluids into actual transformers, they would be exposed to thermal and electrical stresses. Thus, The aim of the authors is to investigate the generation pattern of dissolved gases in nanofluids under thermal and electrical faults and to assess the applicability of traditional Dissolved Gas Analysis (DGA) techniques if oil‐based nanofluids are used in transformers. Oil‐based nanofluid samples were prepared using a magnetic stirrer and an ultrasonic homogeniser and then subjected to simulated thermal and electrical faults in the laboratory using properly sealed test cells. Three types of metal oxides, Silicon dioxide, Titanium dioxide, and Aluminium oxide nanoparticles, have been used to prepare nanofluids with 0.02 g/L and 0.04 g/L concentrations. The gases released and dissolved into oil due to the simulated faults were analysed and compared to traditional mineral oil as a benchmark. The dielectric dissipation factor was obtained and analysed for all samples. According to the findings, the presence and concentration of nanoparticles were shown to influence the amount of gases produced. As a result, this research is crucial in guaranteeing that traditional DGA techniques can be employed in transformers that use oil‐based nanofluids.

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Reliable Estimation for Health Index of Transformer Oil Based on Novel Combined Predictive Maintenance Techniques

Abstract: Date of publication xxxx 00, 0000, date of current version xxxx 00, 0000.

Cited by 45 publications

References 41 publications

Applications of IoT and digital twin in electrical power systems: A comprehensive survey

Applications of IoT and digital twin in electrical power systems: A comprehensive survey

Adsorption Behavior of Dissolved Gas Molecules in Transformer Oil on Rh Modified GeSe Monolayer

Dissolved gas analysis and dissipation factor measurement of mineral oil‐based nanofluids under thermal and electrical faults

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