National Grid sees machine learning as the brains behind the utility business of the future – TechCrunch

If a corporate venture capital firm’s portfolio can be taken as an indication for the strategic priorities of their parent companies, then National Grid There are high expectations for automation as the future of the utility industry.

With a population of 20 million people, one of the nation’s largest privately held utilities, a heavy emphasis on automation and machine learning is significant. And a sign where the industry can go.

Since its launch, National Grid’s venture company, National Grid Partners, Has invested in 16 startups that reflect machine learning at the core of their pitch. More recently, the company supported AI Dash, which uses machine learning algorithms to analyze satellite images and predicts vegetation encroachments on national grid power lines to avoid outages.

A more recent investment, Aperio uses data from sensors monitoring critical infrastructure to account for degradation or loss of data quality from a cyber attack.

In fact, the firm, which invested $ 175 million in investments, has paid approximately $ 135 million to companies leveraging machine learning for its services.

“AI will be critical for the energy industry to achieve aggressive deconverification and decentralization goals,” said Lesa Lambert, chief technology and innovation officer at National Grid and founder and president of National Grid Partners.

Lambert said the National Grid started the year off slowly due to the COVID-19 epidemic, but its investment momentum picked up and the company is on track to hit its investment targets for the year.

Lambert said modernization is important for an industry that still runs mostly on spreadsheets and collective knowledge that is locked into an aging employee base with no contingency plans in the event of retirement. This is the situation that is forcing National Grid and other utilities to automate their businesses.

“Most companies in the utility sector are now trying to automate for efficiency reasons and cost reasons. Today, most companies have everything written in a manual; As an industry, we basically run our networks with spreadsheets and the skills and experience of the people running the network. If we retire those people then we have got serious issues. self drive [and] Digitizing is top of mind for all utilities that we have talked about in the Next Grid Alliance.

To date, many automation tasks that have been done around basic automation of business processes. But there are new capabilities on the horizon that will advance automation of various activities up the value chain, Lambert said.

“ML is the next level – delivering to the customer, predictable maintenance of your property. For example, Unifor: you’re learning from every interaction you have with your customer, which is included in the algorithm and the next time you meet the customer So, you’re going to do better. So this is the next generation, “Lambert said.” Once everything goes digital, you’re learning from those engagements – whether it’s a property or a human being entangled Have been. “

Lambert is another source of demand for new machine learning technology that is in need of utilities to rapidly decarbonate. Shifting away from fossil fuels will require completely new ways of operating and managing the power grid. One where humans are less likely.

Lambert said, “In the next five years, utilities have to get automation and analytics, if they are going to give any chance in a net-zero world – you need to run those assets differently.” “There are no windmills and solar panels [part of] Traditional Distribution Network. A lot of traditional engineers probably don’t think of the need to do something new, because they are building engineering technology that was relevant decades ago when building assets – while all these renewable assets are built in the era of OT / IT . “