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How Cognite Data Fusion helps grid operators prevent transformer failure

Improved monitoring means increased safety and fewer costly repairs.

Cognite worked with a major grid operator to improve monitoring and maintenance of electrical transformers.

The solution will save the grid operator an estimated $2 million a year.

In Short

Cognite and the grid operator used liberated, contextualized data in Cognite Data Fusion to calculate a health index for the company's transformers, enabling easy monitoring of the devices and data-driven prioritization of maintenance work.

$2 million in estimated annual savings
Data-driven maintenance planning
Reduced risk of transformer failure

Challenge

Transformers are some of the most expensive and critical components in a power grid. Often weighing it 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 a major grid operator to improve how it conducts maintenance of transformers. Today, the grid operator is responsible for hundreds of transformers, and it experiences about one malfunction a year. The grid operator conducts regular maintenance of the transformers, and it also invests in replacement components to ensure that power can quickly be restored in the case of an outage.

The grid operator expressed an interest in further improving both those processes. How could data help the grid operator identify early signs of transformer failure, and how could it optimize its spending on replacement parts?

Solution

Cognite worked with the grid operator to liberate information about transformers from the company’s source systems, including temperature, load, dissolved gas analyses, technical specifications, and inspection logs, and ingest it into Cognite Data Fusion (CDF).

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 the grid operator’s engineers the ability to monitor the entire fleet of transformers at a glance and see which components should be prioritized for maintenance.

Impact

The health index helps the grid operator make data-driven decisions about how to plan its transformer maintenance activities. Each transformer failure costs the grid operator at least $5 million. The grid operator 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 about $2 million a year.

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