Vector taps machine learning to transform transformer maintenance

Energy company teams up with VIA

Energy company Vector has teamed up with US-based artificial intelligence and blockchain start-up VIA to develop a system that will use machine learning to predict faults in the transformers, and other components, in electricity distribution networks.

According to its website, VIA was founded in 2016 to solve asset management and operational issues alongside key players in the energy industry.

It has developed a blockchain-based application, called Trusted Analytics Chain (TAC) that it says is the bridge that securely connects power company data, distributed across many locations, to potential AI solutions.

Vector said that, with VIA, it will develop a database for transformer data, the Global Data Asset Collaborative (GDAC) "to help electricity distribution companies take a more proactive approach to transformer management by using machine learning to predict faults before they happen."

VIA CEO, Colin Gounden, said the database would become the world’s largest machine learning-ready transformer dataset.

"Our goal is to reduce the risk of grid transformer failures worldwide," Gounden added. "To make this goal a reality, GDAC members will use the VIA developed Trusted Analytics Chain blockchain-based … to provide access to company data in a secure way.

"This feature makes it easy for companies to collaborate and benefit from the collective data and expertise."

Initially, the GDAC project will focus on 216 of Vector’s largest transformers in its major Auckland sub-stations. Vector said it had the potential to extend the system to more than 20,000 smaller transformers and other network assets.

"With secure access to bigger and smarter datasets, transformer maintenance works can be targeted with greater precision, which drives operational efficiencies and improves the overall service experience for customers," Vector said.

Vector CEO Simon Mackenzie said proactive maintenance was becoming increasingly important as new technologies like distributed energy resources and battery storage become an integral part of electricity networks.

"We have a responsibility to make this transition as efficiently as we can and without burdening customers with excessive infrastructure costs," he added. "Improving our data and analytics capability will play a central role in that."

Vector said GDAC founding members (none other than it and VIA have been named) would recruit new utilities, equipment manufacturers, and recommend data sources like weather to contribute to the collaborative.

"The new members will contribute both data and expertise to help create more robust transformer analyses and expand initiatives outside of transformer failure to other kinds of transformer analyses," it said.

VIA also plans to create new GDAC initiatives for other pieces of equipment.

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