Use data to identify early signs of transformer failure
Transformers are some of the most expensive and critical components in a power grid. Often weighing in at more than 200 metric tons, these massive devices are situated at critical parts of the grid, transferring electricity between alternating-current circuits and increasing or decreasing the voltage as necessary.
Grid operators sometimes experience transformer failure. These events can lead to power outages for consumers and production losses for power companies. In the worst-case scenario, a malfunctioning transformer can catch fire and even explode. Repairing or replacing a malfunctioning transformer is both expensive and time-consuming.
Cognite has worked with Statnett, the Norwegian transmission system operator, to improve access to data and knowledge on how best to conduct maintenance on transformers. Today, Statnett is responsible for hundreds of transformers, and the company experiences about one malfunction a year. Statnett conducts regular maintenance of the transformers, and also invests in replacement components to ensure that power can quickly be restored in the case of an outage.
A health index score powered by data ingested into Cognite Data Fusion®
Statnett worked with Cognite to liberate information about transformers from its source systems, including temperature, load, dissolved gas analyses, technical specifications, and inspection logs, and ingest it into Cognite Data Fusion®.
With access to all the data relevant to transformers in a single location, the development team was able to calculate a health index for every transformer in the power grid. That health index was then visualized in a dashboard, giving Statnett's engineers the ability to monitor the entire fleet of transformers at a glance and see which components should be prioritized for maintenance.
Statnett is now able to make data-driven decisions about how to plan its transformer maintenance activities.
Each transformer failure costs society at least $5 million. Statnett has set a goal of reducing the chance of failures by 20-50% over the next five years, which in the short term will save the company $2 million a year.