Insulating Oil Test Research Articles

Practical Maintenance Model of Power Transformer in Thai Transmission System by Using FMECA

Failure Modes Effects and Criticality Analysis of the maintenance model of risk management for power transformers in Thai transmission system is proposed and measured by severity, occurrence, and detection in order to establish a risk priority number or criticality. The severity involves two criteria: susceptibility and efficiency. The susceptibility-severity concerns four sub-criteria: service life of transformer components, system stability, social aspect, and public image, while the efficiency-severity focuses on the percentage of component condition index determined by the electrical and insulating oil tests, and visual inspection. The weight and score technique is also applied. The occurrence specifies the frequency of component failure, while the detection refers to the capability to detect failures. Furthermore, the scores of severity, occurrence, and detection are compared to their limitation with five levels: one for low and five for high risks. Subsequently, the criticality to plan and prioritize the maintenance model is established into two approaches: susceptibility-criticality and efficiency-criticality. The maintenance action is categorized into four models: low for acceptable, medium for tolerable, high and very high degrees for unacceptable risks. In the analysis, 78 transformers rating 115 kV and 33 transformers rating 230 kV in Thailand are studied. Available major failures on winding, on load tap changer and bushing are investigated. The results show that all the windings are first prioritized with refurbishment or replacement action due to unacceptable risk with frequent failure and very low detectability. Consequently, the effective maintenance model can be achieved with higher system reliability and reduced failure risk.

Fuzzy logic approach for transformer remnant life prediction and asset management decision

The quality of insulation system within power transformer reflects the overall health condition of the asset. A timely and reliable maintenance decision along with the remaining operational life estimation of the asset can be identified through the measurements of some parameters reflecting the degradation rate of the transformer dielectric insulation. However, the process is not always straightforward due to the complexity of the insulation structure and degradation process. This paper proposes a new fuzzy logic approach to provide a proper asset management decision and predict the remaining operational life of a power transformer based on some insulating oil tests. The developed fuzzy logic model is validated through field data collected for various transformers of preknown health condition and life span. Results show that the proposed model is reliable and can be facilitated to provide a timely asset management decision with less reliance on expert personnel.

Risk assessment based on condition and importance criteria for power transformer in Thailand transmission network

This paper proposes an innovative risk‐assessment strategy based on condition and importance criteria for power transformer maintenance in a transmission network. The condition assessment is performed by the analysis of different diagnosis methods such as electrical test, insulating oil test, and visual inspection. The importance assessment is evaluated from various aspects such as load criticality, impact on system stability, possibility of failure, failure consequence, damage to property, as well as social impact and environmental concerns. Weighting and scoring techniques are applied to determine the actual condition and importance of the power transformer with regard to condition and importance aspects. By combining the condition and importance assessment, the overall risk to the power transformer is assessed and differentiated into nine categories in the risk matrix from the lowest to the highest risk. Additionally, by applying distance ‘d’ technique, the risk‐based assessment matrix for the power transformer can be identified into five zones: healthy, good, moderate, bad, and risky. These five zones are also represented by color indicators as green, blue, yellow, orange, and red, which are further interpreted to five steps of maintenance tasks. The transformer with longer distance ‘d’ is subjected to higher risk and should be maintained first. By this method, a total of 19 power transformers were analyzed and are presented as examples for risk‐based maintenance. Then, risks of a total 598 power transformers are shown in the risk matrix. A computerized web application program is developed for practical implementation in a utility in Thailand. Finally, the systematic risk assessment and maintenance task of the power transformer fleet in Thailand are effectively managed. Thereby, the total maintenance cost of power transformer can be reduced. © 2014 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

Risk-based maintenance for asset management of power transformer: practical experience in Thailand

SUMMARY Nowadays, the requirement on diminishing operating and maintenance costs is highly concerned for utilities in competitive electricity market. Power transformer is first focused due to its acquisition costs and failure consequences (FCs). Traditional preventive maintenance for power transformer is generally applied. However, it is very costly and does not take into account actual transformer condition. Hence, risk-based maintenance is introduced in this paper to facilitate the maintenance works of power transformers. The conditions of power transformers are evaluated from electrical test, insulating oil test and visual inspection by using the ranking and weighting techniques. In addition, the Analytic Hierarchy Process (AHP) is proposed to determine the important weighting factor of each transformer component. The three main criteria of the AHP are maintenance difficulty, FC and failure history. Moreover, the Weibull distribution techniques are applied to analyze failure causes. The computerized web-application program is developed and implemented for practical use in a utility in Thailand. The power transformers installed in 115 kV and 230 kV transmission systems in Thailand are assessed due to availability and quality of data. From statistical analysis of failure records, the conditions of power transformer can be divided into three different zones as risk, moderate and healthy zone. The defective components in risk zone with higher proportion of failure should be carefully focused. The components and overall condition of the transformers are perceived from the analysis of test results. Subsequently, the risk-based maintenance is properly planned according to the actual condition. Therefore, maintenance of power transformer fleet can be effectively managed resulting in higher availability and reliability, lower risk of failure and lower cost of maintenance. Copyright © 2013 John Wiley & Sons, Ltd.