In the dynamic and rapidly evolving renewable energy industry, wind farms stand out as the biggest drivers of clean energy. The efficiency, reliability, and longevity of these installations hinge on effective asset management, a task that has been revolutionised by advancements in online monitoring technologies. This blog delves into the substantial benefits of integrating online monitoring systems for asset managers and how these cutting-edge technologies can optimise performance, reduce downtime, and enhance the overall lifespan of wind farm transformer assets.
Online transformer monitoring for wind farms involves continuously collecting and analysing data to ensure optimal performance and detects potential issues in real-time. Utilising advanced sensors and machine learning, this technology monitors parameters like temperature, voltage, and load conditions. For wind farms, it offers early fault detection, reduces unexpected breakdowns and repairs, and enhances reliability and efficiency. This proactive maintenance approach maximises energy output and extends the lifespan of this critical piece of equipment.
Life extension
In some situations, transformers with known defects must continue operating for prolonged periods due to the unavailability of replacement or spare transformers. In these cases, online monitoring is crucial for ensuring that defects do not worsen. By monitoring key parameters such as temperature, voltage, and load, online monitoring helps manage transformer operating conditions effectively, thereby extending the service life of the equipment and preventing further deterioration.
Asset health scoring
For conducting risk assessment and maintenance planning, many transformer Asset Managers utilise health scores or indices. These indices are typically used as a relative ranking in order to identify which critical transformers should be prioritised for maintenance, allocation of spares, or planned replacement. Traditionally, these health indices would be based on the transformer age, its operational history, along with offline diagnostic test data and information from visual inspections.
Online monitoring can provide valuable insight into the asset condition since the assets are exposed to stresses from operating conditions which are not present during offline testing. Online monitoring data is not commonly considered in asset health scores or condition indices, and the exclusion of online monitoring data in many cases can be due to uncertainty with how to interpret and assess some online data, e.g. partial discharge data. In other instances, it may be due to uncertainty with integrating the online data for transformer fleet assessment.
In a CIGRÉ publication by Camlin Energy an analytical method for computing transformer health indices using both online monitoring data and/or offline test data for power transformers is described. The method evaluates a condition index score based on offline diagnostic test data and online monitoring data. This approach to integrate online monitoring data into condition health scores for power transformer asset management provides multiple benefits.
One benefit is that that the condition for a fleet of assets can be monitored in a consistent way utilising a centralised database or data historian that is populated by online monitoring data continuously and translated into a condition score or index for all monitored assets.
Visual inspection data and/or offline test data can also be integrated and automatically populated into the calculation of a hybridised condition index which factors online with offline data. For fleet asset management, this type of system would provide the up-to-date current data for maintenance planning, and life cycle management planning for transformer replacements or spares.
Life cycle management – aging estimation
What is thermal aging?
With transformer online monitoring data, it is possible to track the thermal aging that the transformer insulation endures. This thermal aging is what is usually used to define the transformers end of life, which is directly related to the transformer paper condition.
Impact of thermal aging
When power transformers age to end of life, the transformer paper insulation becomes embrittled. When becomes so brittle that movements in the transformer winding caused from network disturbances can cause the paper materials to rip or tear, ultimately leading to a transformer winding fault.
Value of online monitoring
Online monitoring data for aging estimation can inform when the transformer should be replaced and may inform the early/ projected sourcing of replacement transformers preventing the risk of transformers failing in service after surpassing their serviceable lifetime based on the paper condition.
In conclusion, integrating online transformer monitoring on your wind assets significantly enhances efficiency, reliability, and lifespan of transformers. Continuous, real-time data enables proactive defect management, informed maintenance planning, and extended operational life. By combining online monitoring with traditional diagnostics, asset health assessments become more precise, ensuring effective resource allocation and timely replacements.
Tracking thermal aging through online monitoring helps anticipate end-of-life for transformer insulation, preventing failures. Overall, adopting these systems is imperative for optimising performance, reducing downtime, and ensuring a reliable energy supply in the renewable energy sector.
