Power transformer asset management and remnant life

2018 ◽  
pp. 259-293
Author(s):  
Norazhar Abu Bakar
Keyword(s):  
Asset Management ◽  
Power Transformer

An approach to power transformer asset management using health index

2009 ◽  
Vol 25 (2) ◽  
pp. 20-34 ◽  
Author(s):  
A. Jahromi ◽  
R. Piercy ◽  
S. Cress ◽  
J. Service ◽  
Wang Fan
Keyword(s):  
Asset Management ◽  
Power Transformer ◽  
Health Index

Methanol: A Novel Approach to Power Transformer Asset Management

2012 ◽  
Vol 27 (2) ◽  
pp. 514-520 ◽  
Author(s):  
Jocelyn Jalbert ◽  
Roland Gilbert ◽  
Yves Denos ◽  
Pierre Gervais
Keyword(s):  
Asset Management ◽  
Power Transformer ◽  
Novel Approach

scholarly journals Fault Diagnosis and Asset Management of Power Transformer Using Adaptive Boost Machine Learning Algorithm

2021 ◽  
Vol 1055 (1) ◽  
pp. 012133
Author(s):  
Sujatha Balaraman ◽  
R. Madavan ◽  
S. Vedhanayaki ◽  
S. Saroja ◽  
M. Srinivasan ◽  
...  
Keyword(s):  
Machine Learning ◽  
Fault Diagnosis ◽  
Asset Management ◽  
Learning Algorithm ◽  
Power Transformer ◽  
Machine Learning Algorithm

scholarly journals Multiparameter-Based Fuzzy Logic Health Index Assessment for Oil-Immersed Power Transformers

2019 ◽  
Vol 2019 ◽  
pp. 1-12
Author(s):  
Edwell Tafara Mharakurwa ◽  
Rutendo Goboza
Keyword(s):  
Fuzzy Logic ◽  
Asset Management ◽  
Power Transformer ◽  
Carbon Oxide ◽  
Degree Of Polymerization ◽  
Health Index ◽  
Estimation Model ◽  
Inference System ◽  
Index Model ◽  
Power Utilities

The health index scheme can be the most fundamental tool that unifies all transformer condition status information into a singular outcome, thereby enhancing the power transformer asset management and life longevity strategies. This study aims at establishing a multiple parameter-dependent transformer health index estimation model cascaded with a fuzzy logic inference system. This strategy is centered on the effect of dynamic loading regime, varying hotspot temperatures and multiple attesting results of the insulation system. Furthermore, a nonintrusive degree of polymerization (DP) model based on furans and carbon oxide ratios as DP pointers is also factored in developing the health index model. The general outcome of the health index depends on entirely considered elements, but not on any isolated attribute. Data obtained from in-service transformers were used to validate the proposed model. The outcome of the model mirrors the practical condition of the evaluated transformers. Therefore, the proposed health index model can be a vital tool to asset managers and power utilities.

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