New approach to power transformer asset management and life assessment using fuzzy logic techniques

Hossam-Eldin, Ahmed A.; Refaey, Mostafa; Ramadan, Haitham

doi:10.1109/mepcon.2017.8301287

Cited by 9 publications

(2 citation statements)

References 6 publications

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“…Hossam, et al [88] Fuzzy logic (FL) technique AM for power transformer Here, the standard fuzzy logic technique has been used to perform the lifetime assessment of the power transformer.…”

Section: Moderate Accuracymentioning

confidence: 99%

A review of asset management using artificial intelligence‐based machine learning models: Applications for the electric power and energy system

Rajora,

Sanz‐Bobi,

Tjernberg

et al. 2024

IET Generation Trans & Dist

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Power system protection and asset management present persistent technical challenges, particularly in the context of the smart grid and renewable energy sectors. This paper aims to address these challenges by providing a comprehensive assessment of machine learning applications for effective asset management in power systems. The study focuses on the increasing demand for energy production while maintaining environmental sustainability and efficiency. By harnessing the power of modern technologies such as artificial intelligence (AI), machine learning (ML), and deep learning (DL), this research explores how ML techniques can be leveraged as powerful tools for the power industry. By showcasing practical applications and success stories, this paper demonstrates the growing acceptance of machine learning as a significant technology for current and future business needs in the power sector. Additionally, the study examines the barriers and difficulties of large‐scale ML deployment in practical settings while exploring potential opportunities for these tactics. Through this overview, insights into the transformative potential of ML in shaping the future of power system asset management are provided.

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“…Hossam, et al [88] Fuzzy logic (FL) technique AM for power transformer Here, the standard fuzzy logic technique has been used to perform the lifetime assessment of the power transformer.…”

Section: Moderate Accuracymentioning

confidence: 99%

A review of asset management using artificial intelligence‐based machine learning models: Applications for the electric power and energy system

Rajora,

Sanz‐Bobi,

Tjernberg

et al. 2024

IET Generation Trans & Dist

View full text Add to dashboard Cite

show abstract

“…In turn, FL based transformer asset management considering DGA, temperature, etc. is elaborated in [9]. Based on oil insulation test and FL model decision, a prediction is carried out for the remaining operational life of the transformer in [10].…”

Section: Introductionmentioning

confidence: 99%

Real-Time Monitoring & Adaptive Protection of Power Transformer to Enhance Smart Grid Reliability

Raichura

Chothani

Patel

2019

Electrical, Control and Communication Engineering

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Power transformer is one of the most important pieces of equipment in the grid to reliably and efficiently transmit power to the consumers. Asset management and protection are the best concepts for prolongation of transformer lifespan as well as for the increase of grid reliability. This article presents electrical and non-electrical parameter-based power transformer monitoring and protection. Various data such as core flux, age of asset, heat generation, current harmonics and temperature are monitored in real time and processed accordingly to enhance the working capability of the transformer. The proposed scheme is successfully tested on 15 kVA laboratory transformer using Arm CORTEX-M4 processor. A Fitness Function (Ff) is estimated from the collected data to examine the working condition of the transformer. Moreover, voltage, current and power-based inrush detection as well as Adaptive Power Differential Protection (APDP) are applied to protect the transformer against fault. The hardware implementation and result validation prove the effectiveness of the proposed scheme in enhancing reliability of the distribution grid.

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Real-Time Monitoring and Adaptive Protection of Power Transformer

Patel¹,

Chothani

2020

Power Systems

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New approach to power transformer asset management and life assessment using fuzzy logic techniques

Cited by 9 publications

References 6 publications

A review of asset management using artificial intelligence‐based machine learning models: Applications for the electric power and energy system

A review of asset management using artificial intelligence‐based machine learning models: Applications for the electric power and energy system

Real-Time Monitoring & Adaptive Protection of Power Transformer to Enhance Smart Grid Reliability

Real-Time Monitoring and Adaptive Protection of Power Transformer

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