Managing transformer health and performance with utility analytics
The broader challenge for utilities managers and executives is how to manage their way through an aging set of assets with reduced manpower
Editor’s note: This is a guest post written by Randy Schrieber, Marketing & Sales Manager, ABB Power Equipment Services
In a recent web publication on utility analytics, Mike Smith at intelligentutility.com said:
“… a second area where the predictive characteristics of analytics are being applied is in managing assets across transmission and distribution infrastructure, which is costly to maintain. While most utilities have been using some type of enterprise asset management (EAM) system for years to help manage these maintenance and operations tasks, the roll-out of the smart grid is providing new opportunities for improvement as the infrastructure becomes smarter. We are starting to see examples at utilities where leveraging newly available data into predictive, condition-based decision making can save millions of dollars each year. The typically expensive management of transformer assets is emerging as a favorite application.”
The industry is looking at a smarter grid to support improved analytics and an asset health management process that addresses performance of aging assets. Power transformers are a key asset and fortunately, transformers are quite predictable. Given info on transformer history and symptoms, their health risks become clear. A power transformer in a key application may be monitored heavily, and its health frequently assessed to avoid an unexpected outage.
But that typically is the exception, as monitoring system costs can be substantial and the effort to assess multiple modes of failure can be time consuming. Adding to that challenge is that test data, loading and maintenance histories are usually in scattered locations, and different types and vintages of transformers have their own strengths and weaknesses.
The broader challenge for utilities managers and executives is how to manage their way through an aging set of assets with reduced manpower, constrained O&M budgets and capital budgets that are inadequate to replace these assets for many, many years.
It is possible to optimize a path forward. Given knowledge of the health risks, the impact to customers of a failure, the expected maintenance costs and the replacement costs, a capital plan can be established to minimize the downside risk from the assets still in service.
Aggregating the data to support this and the analytics to properly determine the risks are key. But these are existing capabilities that can all be integrated to provide a solution. It will take years for utilities to work their way through an aging infrastructure, but it is a challenge that can be managed.
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