IoT-Based Smart Transformer Monitoring System with Raspberry Pi

Ravindran, Vijay; Ponraj, Ram Prakash; Krishnakumar, C.; Ragunathan, Satheesh; Ramkumar, V; Swaminathan, Karthik

doi:10.1109/i-pact52855.2021.9696779

Cited by 39 publications

(7 citation statements)

References 23 publications

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“…119 By monitoring the system, you can increase stability and dependability. 120 (vii) This method prevents excessive current and temperature. A structural comparison of the existing power grid transformer and the next-generation power grid transformer is shown in Table 7.…”

Section: Road To Next-generation Power Grid Transformermentioning

confidence: 99%

See 1 more Smart Citation

Towards next generation power grid transformer for renewables: Technology review

Agarwala,

Tahsin,

Ali

et al. 2024

Engineering Reports

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This paper develops a technical framework for the next‐generation power grid transformer (NGPGT) for grid renewables. This framework is structured to overcome the environmental challenges produced by the explosive use of nonrenewable base energy generation sources. The use of these sources cannot meet the required electricity for the world's growing community due to their availability, cost, and lack of flexibility. However, modern energy systems focus on the use of renewable energy sources, where the grid transformer's interaction plays an essential role in their generation, transmission, and distribution. The lack of centralization, local monitoring, interoperability, authenticity, and precise bi‐directional flow may limit the application of current framework power grid transformers in grid renewables. In this paper, a new technical framework, called NGPGT, is developed by introducing some extended features for addressing the challenges shown in current‐generation transformers. This is structured by enabling some advanced technical features with the existing framework, which includes automatic condition monitoring, intelligent inverters, edge computing, automatic controlling, and intelligent management. This paper also illustrates the benefits and scope of the NGPGT compared to the existing transformer by assembling essential requirements and obligatory components. Additionally, this paper highlights a few difficulties of implementing NGPGT in terms of operational, communication, energy management, and economic points of view, which may enable further research scopes for the researchers.

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Section: Road To Next-generation Power Grid Transformermentioning

confidence: 99%

“…(v) The usage of Wi‐Fi results in improved fault monitoring accuracy and reaction times. (vi) By monitoring the system, you can increase stability and dependability 120 . (vii) This method prevents excessive current and temperature.…”

Section: Road To Next‐generation Power Grid Transformermentioning

confidence: 99%

Towards next generation power grid transformer for renewables: Technology review

Agarwala,

Tahsin,

Ali

et al. 2024

Engineering Reports

View full text Add to dashboard Cite

show abstract

“…v) The usage of wifi results in improved fault monitoring accuracy and reaction times. vi) By monitoring the system, you can increase stability and dependability [108]. vii) This method prevents excessive current and temperature.…”

Section: Road To Next-generation Power Grid Transformermentioning

confidence: 99%

Towards Next Generation Power Grid Transformer for Renewables:Technology Review

Agarwala,

Tahsin,

Ali

et al. 2023

Preprint

View full text Add to dashboard Cite

This paper develops a technical framework for the next-generation power grid transformer (NGPGT) for grid renewables. This framework is structured to overcome the environmen-tal challenges produced due to the explosive use of non-renewable base energy generation sources. The use of these sources cannot meet the required electricity for the world’s growing community due to their availability, cost, and lack of flexibility. However, modern energy systems focus on the use of renewable energy sources where the grid transformer’s interaction acts the essential role in their generation, transmission, and distribution. The lack of central-ization, local monitoring, interoperability, authenticity, and precise bi-directional flow may limit the application of current framework power grid transformers in grid renewables. In this paper, a new technical framework, called NGPGT, is developed by introducing some ex-tended features for addressing the challenges shown in the current-generation transformers. This is structured by enabling some advanced technical features with the existing frame-work which includes automatic condition monitoring, intelligent inverters, edge computing, automatic controlling, and intelligent management. This paper also illustrates the benefits and scopes of the NGPGT compared to the existing transformer by assembling essential re-quirements and obligatory components. Additionally, this paper highlights a few difficulties of implementing NGPGT in terms of operational, communication, energy management, and economic point of view which may enable further research scopes for the researchers.

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“…Thingspeak is an open-source IoT platform [ 90 ] compatible with MATLAB (for AI capabilities), microcontrollers and DAQs. It has been utilised for real-time room condition monitoring systems, water monitoring systems and analytics, air quality monitoring systems, traffic control systems, and transformer subsystems [ 90 , 91 , 92 , 93 , 94 , 95 , 96 ]. When used with MATLAB (for example), the channel ID and API key are inputted to enable sensor data to be read with the help of the ESP8266 WIFI module and Arduino microcontroller.…”

Section: Iot and Online Ageing Detectionmentioning

confidence: 99%

Towards Online Ageing Detection in Transformer Oil: A Review

Elele

Nekahi

Ali

et al. 2022

Sensors

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Transformers play an essential role in power networks, ensuring that generated power gets to consumers at the safest voltage level. However, they are prone to insulation failure from ageing, which has fatal and economic consequences if left undetected or unattended. Traditional detection methods are based on scheduled maintenance practices that often involve taking samples from in situ transformers and analysing them in laboratories using several techniques. This conventional method exposes the engineer performing the test to hazards, requires specialised training, and does not guarantee reliable results because samples can be contaminated during collection and transportation. This paper reviews the transformer oil types and some traditional ageing detection methods, including breakdown voltage (BDV), spectroscopy, dissolved gas analysis, total acid number, interfacial tension, and corresponding regulating standards. In addition, a review of sensors, technologies to improve the reliability of online ageing detection, and related online transformer ageing systems is covered in this work. A non-destructive online ageing detection method for in situ transformer oil is a better alternative to the traditional offline detection method. Moreover, when combined with the Internet of Things (IoT) and artificial intelligence, a prescriptive maintenance solution emerges, offering more advantages and robustness than offline preventive maintenance approaches.

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IoT-Based Smart Transformer Monitoring System with Raspberry Pi

Cited by 39 publications

References 23 publications

Towards next generation power grid transformer for renewables: Technology review

Towards next generation power grid transformer for renewables: Technology review

Towards Next Generation Power Grid Transformer for Renewables:Technology Review

Towards Online Ageing Detection in Transformer Oil: A Review

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