scholarly journals A Markovian model for power transformer maintenance

Author(s):  
Zhenglin Liang ◽  
Ajith Parlikad
2017 ◽  
Vol 23 (4) ◽  
pp. 400-414 ◽  
Author(s):  
Maria Del Pilar Colin Hernandez ◽  
Ashraf Labib

Purpose The purpose of this paper is to propose a model for assisting in the decision-making process for acquiring a condition monitoring (CM) system for an oil-immersed power transformer in order to improve its maintainability. Design/methodology/approach The proposed model is based on the analytic hierarchy process. The assessment was performed by pairwise comparisons, and a sensitivity analysis (what-if analysis) was used to identify the implications of changing the criteria weights. In order to select the criteria and alternatives, a search was conducted for the power transformer failure modes, monitored parameters and CM technologies. Findings The proposed model provides a structured solution for a complex problem: deciding the best combination of technologies for CM of power transformers. Research limitations/implications Because the pairwise comparisons were done only by the author, the results may need to be improved with the assessment of more experts. Also, it was done for a specific type of transformer; it might be necessary to customise the alternatives for other cases. Finally, as a future consideration, more levels can be added to the hierarchy to improve the accuracy of the model. Practical implications The power transformer is an asset where the most appropriate maintenance strategy for it is condition-based maintenance. In order to improve its maintainability, it is recommendable to improve its testability and diagnosability. For achieving this goal, the maintenance personnel have to decide the best combination of technologies for CM. The methodology developed can assist the decision makers to select the most appropriate cost-benefit strategy. Originality/value The paper presents a structured and generic method of selecting the most appropriate CM system for power transformers.


2019 ◽  
Vol 2019 ◽  
pp. 1-10 ◽  
Author(s):  
Edwell T. Mharakurwa ◽  
G. N. Nyakoe ◽  
A. O. Akumu

Decision making on transformer insulation condition based on the evaluated incipient faults and aging stresses has been the norm for many asset managers. Despite being the extensively applied methodology in power transformer incipient fault detection, solely dissolved gas analysis (DGA) techniques cannot quantify the detected fault severity. Fault severity is the core property in transformer maintenance rankings. This paper presents a fuzzy logic methodology in determining transformer faults and severity through use of energy of fault formation of the evolved gasses during transformer faulting event. Additionally, the energy of fault formation is a temperature-dependent factor for all the associated evolved gases. Instead of using the energy-weighted DGA, the calculated total energy of related incipient fault is used for severity determination. Severity of faults detected by fuzzy logic-based key gas method is evaluated through the use of collected data from several in-service and faulty transformers. DGA results of oil samples drawn from transformers of different specifications and age are used to validate the model. Model results show that correctly detecting fault type and its severity determination based on total energy released during faults can enhance decision-making in prioritizing maintenance of faulty transformers.


2013 ◽  
Vol 732-733 ◽  
pp. 930-935
Author(s):  
Hai Feng Liang ◽  
De Shan Lin

As one of the important hinge equipments in the electric power system, the operating reliability of power transformer has deep influences on security and stability of power system. In order to guide transformer maintenance and assess the risk of the electric power system, it is of important significance to know the state of the running insulation of transformer in time and accurately. Based on the analysis of transformer state parameters, the method determining the evaluation index weight has been studied; methods of entropy value objective weight and improved analytic hierarchy process subjective weight have been combined to calculate the weighting coefficients of evaluation indexes. Its correctness has been verified by analyzing examples of transformer operation.


2016 ◽  
Vol 13 (2) ◽  
pp. 285-299
Author(s):  
Olga Ristic ◽  
Bratislav Iricanin ◽  
Vladica Mijailovic

The paper presents the dynamic model of maintenance costs of the power transformer functional components. Reliability is modeled combining the exponential and Weibull's distribution. The simulation was performed with the aim of corrective maintenance and installation of the continuous monitoring system of the most critical components. Simulation Dynamic System (SDS) method and VENSIM PLE software was used to simulate the cost. In this way, significant savings in maintenance costs will be achieved with a small initial investment.


2014 ◽  
Vol 1070-1072 ◽  
pp. 1127-1132
Author(s):  
Si Yu Wang

Both the cost-effective operation of power systems and reliable operation are inextricably linked with the transformer life assessment. This paper analyzes the composition of the transformer life, life assessment factors and existing assessment methods. Based on factors of the current life assessment and problems of assessment methods, the paper analyzed the importance significance of uncertainty in the transformer life assessment and proposed the transformer remaining life assessment model, and methods based the random fuzzy theory. Assessment results can provide the basis for the transformer maintenance and help safe and economic operation of power systems.


1945 ◽  
Vol 16 (61) ◽  
pp. 14
Author(s):  
A.E. Shearer

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