Transformer Reliability and the Case for Condition-Based Maintenance
- Augusto Moser
- Apr 23
- 5 min read
Power transformers are critical components of electrical grids, ensuring stable energy transmission across vast networks. However, their failures can lead to significant economic and operational disruptions. The CIGRÉ Working Group A2.37's Transformer Reliability Survey provides a comprehensive analysis of transformer failures, offering insights into failure rates, causes, and locations. The survey underscores the importance of adopting condition-based maintenance (CBM) strategies, enabled by advanced sensor technologies, to enhance transformer reliability and optimize asset management.
Key Findings from the CIGRÉ A2.37 Transformer Reliability Survey
The survey, conducted by CIGRÉ Working Group A2.37, analyzed 964 major transformer failures from 1996 to 2010, covering a population of 167,459 transformer-years across 56 utilities in 21 countries. Transformers ranged from the 1950s to 2009 in manufacturing year, with voltage classes from 69 kV to above 700 kV. Below are the critical findings:
Failure Rates
Overall Failure Rates: The failure rates for substation transformers, generator step-up (GSU) transformers, and the combined group were all below 1%. Notably, GSU transformers in the 300–500 kV range exhibited a slightly higher failure rate of 1.32%.
Comparison with 1983 Survey: Compared to the 1983 CIGRÉ survey, which reported an average failure rate of 2%, the A2.37 survey indicates improved reliability, with failure rates dropping to 0.4% for post-1978 units (up to 20 years old) versus 0.8% for pre-1978 units.
Age-Dependent Failure Trends: Hazard curves for substation transformers showed no distinct "bathtub curve" (high early and late-life failures). Instead, failure rates remained low, with a slight increase from nearly 0% to about 1% after 30–40 years, suggesting that age alone does not justify replacement.
Failure Locations
Primary Contributors: Winding-related failures were the most significant, accounting for a substantial portion of major failures across all transformer types and manufacturing periods. Tap changer and bushing failures were also prominent, particularly in substation transformers.
GSU vs. Substation Transformers: GSU transformers had higher winding and lead exit failures, while substation transformers showed more tap changer issues, likely due to their frequent use. Bushing failure rates were similar across both applications.
Voltage Class Trends: Bushing and lead exit failures increased with higher voltage classes (up to 700 kV), while tap changer failures decreased. Winding is the major share for voltage classes lower than 100kV, with 89%.
Figure 1. Failure Locations
Failure Modes and Causes
Dominant Failure Modes: Dielectric failures (e.g., partial discharge, flashover) were the most common, followed by mechanical failures in substation transformers and thermal failures in GSUs due to higher loading.
Major Causes: Design and manufacturing issues, aging, and external short circuits were leading causes. However, 29% of failures had unknown causes, highlighting diagnostic challenges.
External Effects: While 76.5% of failures had no external effects, 7.1% resulted in fires and 5.9% in explosions, with bushing failures most likely to cause these severe consequences.
Voltage Class Trends: Dielectric was the highest share in voltage classes between 69kV and 100kV, with 70%.
Actions Taken
Repairs vs. Scrapping: Approximately two-thirds of failed transformers were repaired (on-site or in workshops), while one-third were scrapped. Winding failures typically led to scrapping, whereas tap changer and bushing failures were more likely repaired.
Figure 3. Actions Taken
The Case for Condition-Based Maintenance
The survey's findings reveal that transformer failures are not strongly correlated with age, challenging traditional time-based maintenance (TBM) strategies. Instead, unusual system events, such as external short circuits, often trigger failures, emphasizing the need for real-time monitoring and condition assessment. Condition-based maintenance (CBM), enabled by sensor technologies, offers a proactive approach to mitigate risks and extend transformer life.
Why Condition-Based Maintenance?
Low Hazard Rates: The absence of a pronounced bathtub curve suggests that TBM, which schedules maintenance based on fixed intervals, is inefficient for substation transformers. CBM focuses on actual transformer condition, reducing unnecessary interventions.
Early Detection of Issues: Sensors can detect early signs of dielectric, mechanical, or thermal issues, such as partial discharges or abnormal temperatures, allowing timely corrective actions to prevent major failures.
Severe Consequences of Failures: Bushing failures, which often lead to fires or explosions, underscore the need for continuous monitoring to catch anomalies before they escalate.
Economic Benefits: By optimizing maintenance schedules and preventing catastrophic failures, CBM reduces downtime and repair costs, which can be significant given the economic impact of transformer outages.
Role of Sensor Technologies
Since the 1990s, on-line monitoring systems have advanced significantly, enabling comprehensive assessment of transformer health. Key sensor-based techniques include:
Dissolved Gas Analysis (DGA): Detects gas concentrations in transformer oil, indicating insulation degradation or arcing.
Partial Discharge (PD) Monitoring: Identifies dielectric issues that could lead to flashovers or insulation failure.
Thermal Monitoring: Tracks temperature variations to prevent thermal mode failures, particularly in heavily loaded GSU transformers.
Bushing and Tap Changer Monitoring: Assesses the condition of critical components prone to failure, reducing the risk of severe external effects.
Frequency Response Analysis (FRA): Detects winding deformations, complementing on-line data with off-line diagnostics.
These sensors provide real-time data, enabling utilities and industries to correlate information across transformer components and make informed maintenance decisions. For instance, the survey notes cases where on-line gas sensors and bushing monitors prevented major failures by detecting issues early.
Implementation Considerations
Selective Monitoring: The survey suggests a "mix and match" approach, where monitoring is tailored to a transformer's importance and health. For example, cooler operation may be monitored from commissioning, while PD monitoring is prioritized when DGA indicates issues.
Data Integration: Comprehensive monitoring systems integrate data into a single database, allowing expert systems to deliver actionable health assessments.
Cost-Effectiveness: While monitoring all transformers is not financially viable, targeting high-risk units (e.g., older transformers or those in critical network positions) maximizes benefits.
Recommendations
The CIGRÉ A2.37 survey recommends that for maintenance strategies, utilities and industries should:
Shift to CBM: Replace TBM with CBM to align maintenance with actual transformer condition, leveraging sensor data for decision-making.
Invest in Sensors: Deploy on-line monitoring systems for critical transformers, focusing on DGA, PD, and bushing/tap changer diagnostics.
Enhance Diagnostics: Combine on-line monitoring with off-line techniques like FRA to address complex degradation mechanisms.
Train Personnel: Equip teams with skills to interpret sensor data and integrate it into asset management strategies.
Conclusion
The CIGRÉ A2.37 Transformer Reliability Survey highlights the improved reliability of modern transformers but also the persistent risks of winding, bushing, and tap changer failures. By demonstrating that failures are often event-driven rather than age-related, the survey advocates for condition-based maintenance as a superior alternative to traditional approaches. Sensor technologies, with their ability to provide real-time insights into transformer health, are pivotal in implementing CBM, reducing failure risks, and optimizing the lifespan of these critical assets. As utilities and industries face growing demands for reliable power, embracing CBM and advanced monitoring will be key to ensuring grid stability and economic efficiency.
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References
CIGRÉ Working Group A2.37's. Transformer Reliability Survey, 642. (2015)
