Probabilistic Health Index-Based Apparent Age Estimation for Power Transformers

Li, Shuaibing; Wu, Guangning; Dong, Haiying; Yang, Lei; Zhen, Xiaofei

doi:10.1109/access.2020.2963963

Cited by 21 publications

(4 citation statements)

References 31 publications

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“…The apparent age concept could be implemented, which is the product from a combination of a transformer's service age and its health index condition. If the point is drawn into the regression line, that intersection between the regression line and the point then correspond with age abscissa, will indicate the apparent age of power transformer [35]. The apparent age can be older than the actual operating age based on its health index value, and vice versa.…”

Section: Correlation Between Age and Health Index Valuementioning

confidence: 99%

High voltage power transformer condition assessment considering the health index value and its decreasing rate

2021

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A health index method is a useful tool for the transformer assessment condition. This method has been used in several previous studies. However, most of them have not observed the health index decreasing rate as an aspect to improve the transformer condition assessment. A health index method with different approaches is proposed, considering the values and decreasing rate to assess the transformer condition. Inspection data from in‐service and out‐of‐service 150 kV power transformers provided by the Indonesian electric company are included. The correlation between operating age and Health Index value and Health Index decreasing rate was also observed. With increasing operation age, the Health Index value tends to decrease with a correlation coefficient R 2 of 0.631. Further analysis was conducted to power transformers with historical data of 3 years or more, which showed that the tendency of the Health Index value decreasing rate is higher with older transformers. This paper also illustrates the Health Index analysis of 35 out‐of‐service transformers, resulting in a more suitable Health Index value compared to the previous approach. This study proposes the transformer risk assessment based on its health index value and the decreasing rate.

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Section: Correlation Between Age and Health Index Valuementioning

confidence: 99%

High voltage power transformer condition assessment considering the health index value and its decreasing rate

2021

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“…The study in ref. [15] introduces a novel technique for assessing the apparent age of power transformers by means of a probabilistic HI. Unlike the conventional weighted-score-sum approach, the proposed method exploited a Bayesian belief network to fuse various transformer condition monitoring data for calculating the probabilistic HI.…”

Section: Introductionmentioning

confidence: 99%

A novel artificial neural network approach for residual life estimation of paper insulation in oil‐immersed power transformers

Nezami,

Equbal,

Ansari

et al. 2023

IET Electric Power Appl

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Avoiding financial losses requires preventing catastrophic oil‐filled power transformer breakdowns. Continuous online transformer monitoring is needed. The authors use paper insulation to evaluate transformer health for continuous online transformer monitoring. The study suggests a new artificial intelligence method for estimating paper insulation residual life in oil‐immersed power transformers. The four artificial intelligence models use backpropagation‐based neural networks to predict paper insulation lifespan. Four primary transformer insulating paper failure indices—degree of polymerisation, 2‐furfuraldehyde, carbon monoxide, and carbon dioxide—form the basis of these models. Each model, including the backpropagation‐based neural networks, estimates paper insulation life using one failure index, along with moisture and temperature data. Optimisation techniques enhance hidden layer neurons and epoch count for improved performance. Results are validated against literature‐based life models, establishing a precise input–output correlation. This method accurately predicts the remaining useable life of power transformer paper insulation, enabling utilities to take proactive measures for safe and efficient transformer operation.

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“…The authors of [14] used 19 diagnostic indicators and 4-years historical data from 1256 132 kV-transmission transformers and 3 single-phase 500 kV transformers in Malaysia to evaluate the tested transformers' condition. In [15,16], a method was proposed to assess the transformer states based on the health indices regression line, which is plotted from health index data analysis of power transformers' population. It is obvious that large power transformers are of more interest.…”

Section: Introductionmentioning

confidence: 99%

A Low-Cost Online Health Assessment System for Oil-Immersed Service Transformers Using Real-Time Grid Energy Monitoring

et al. 2022

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In this paper, we present a low-cost health assessment system for oil-immersed service transformers using a monitoring device to measure energy in real time. By assessing the important level of transformer components, three indicators, top oil temperature, vibration, and transformer load, were selected as main indicators to investigate the service transformer’s condition. An evaluation system using Fuzzy logic method is also presented in the paper to support monitor transformer health without adding the extra cost of installing expensive sensors. Different testing scenarios with different case studies were carried out on a simulated 50 kVA oil-immersed service transformer to express the feasibility and effectiveness of this low-cost, fast response health assessment system.

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Probabilistic Health Index-Based Apparent Age Estimation for Power Transformers

Cited by 21 publications

References 31 publications

High voltage power transformer condition assessment considering the health index value and its decreasing rate

High voltage power transformer condition assessment considering the health index value and its decreasing rate

A novel artificial neural network approach for residual life estimation of paper insulation in oil‐immersed power transformers

A Low-Cost Online Health Assessment System for Oil-Immersed Service Transformers Using Real-Time Grid Energy Monitoring

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