The Electric Grid’s Growing Adoption of AI

There is a coming decades-long transformation in electricity infrastructure, and it’s not renewable energy. Yes, that’s happening too, but we’re talking about the software systems and artificial intelligence that will control, maintain, and optimize an increasingly complex electrical grid. Productivity tools will allow power companies to shift skilled labor away from mundane tasks. Faster and better inspections will allow companies to maintain higher run times and mitigate tail risk. Localized assets like the standby generator in your home and smart thermostats will work in tandem with advanced modeling to reduce blackouts during times of peak demand and reduced supply. And behind it all will be numerous artificial intelligence platforms. 

Indeed, the adoption of AI has already started. In October, the Electric Power Research Institute (EPRI) told a House subcommittee that it has been involved in over 70 AI projects in applications ranging from predictive maintenance to grid management and streamlining workflows.(1) EPRI believes AI will increasingly contribute to the safety and reliability of energy generation, transportation, and consumption. However, it is also concerned with new challenges, including cybersecurity/privacy risk and even AI’s own massive electricity consumption.

It’s no secret that the challenges facing America’s electric infrastructure are significant: Demand is increasing (EVs, HVAC demands, smart devices, etc.), infrastructure is aging, and inflation is driving costs higher. Furthermore, as renewable generation gains market share, these issues only become magnified (reliability concerns, transmission line upgrades, etc). 

While utilities are notoriously slow to adopt anything new, early indications are that power companies are actually beginning to embrace AI. It seems that infrastructure challenges are so great that AI technology may be the only viable solution. 

This is such a significant topic that it was featured in a Barron’s Magazine cover story in January of 2024.(2)

Specific to the scale of the buildout required, some of the figures cited were jaw dropping:

 

“All told, publicly traded electric utilities [in the US] have spent some $134 billion a year on average maintaining their $2 trillion asset base, with few dollars going to drive the modest growth. Such complacency won’t cut it in the years ahead… Over the next 30 years, some $9 trillion, or about $300 billion a year on average, should be spent adding generating, transmission, and distribution assets while upgrading in-home technology such as smart metering, connected thermostats, and smart, connected circuit breakers.”

Early detection of maintenance issues through predictive analytics and AI can prevent minor damages from escalating into larger safety hazards. For instance, detecting damaged or faulty components in power lines early can prevent the occurrence of devastating events such as wildfires, protecting both the environment and public safety,” says Chaudhry. This is particularly applicable to California, where local regulation makes utilities fully liable for wildfire costs, keeping “a lid on valuations for utilities based in the state,” according to Barron’s.

Starting a software company to service this sector is not for the faint of heart. Large and often political, bureaucratic, and monopolistic utilities have little interest in doing business with fledgling startups – especially on enterprise level solutions. To gain traction, you must convince them you can protect their data and you are a sustainable organization with capital and the right people in place. Your leadership team, your board, and your capital providers all matter.

Market leadership is especially important in this context. The more you are perceived as being at the forefront of your field, the sooner you are able to be taken seriously by skeptical utility customers. The faster you land those customers, the more established you become into their systems and the faster you can build scale. But the sales cycles are long and complicated. For example, Buzz’s sales process touches IT, asset management / maintenance, security (cyber and physical), regulatory, drone survey teams, and even lineman. To navigate this dynamic, founders need thoughtful advisors and the right kind of long term capital… and sufficient amounts of both.

Early detection of maintenance issues through predictive analytics and AI can prevent minor damages from escalating into larger safety hazards. For instance, detecting damaged or faulty components in power lines early can prevent the occurrence of devastating events such as wildfires, protecting both the environment and public safety,” says Chaudhry. This is particularly applicable to California, where local regulation makes utilities fully liable for wildfire costs, keeping “a lid on valuations for utilities based in the state,” according to Barron’s.

Starting a software company to service this sector is not for the faint of heart. Large and often political, bureaucratic, and monopolistic utilities have little interest in doing business with fledgling startups – especially on enterprise level solutions. To gain traction, you must convince them you can protect their data and you are a sustainable organization with capital and the right people in place. Your leadership team, your board, and your capital providers all matter.

Market leadership is especially important in this context. The more you are perceived as being at the forefront of your field, the sooner you are able to be taken seriously by skeptical utility customers. The faster you land those customers, the more established you become into their systems and the faster you can build scale. But the sales cycles are long and complicated. For example, Buzz’s sales process touches IT, asset management / maintenance, security (cyber and physical), regulatory, drone survey teams, and even lineman. To navigate this dynamic, founders need thoughtful advisors and the right kind of long term capital… and sufficient amounts of both.

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The Electric Grid’s Growing Adoption of AI

Productivity tools will allow power companies to shift skilled labor away from mundane tasks. Faster and better inspections will allow companies to maintain higher run times and mitigate tail risk. Localized assets like the standby generator in your home and smart thermostats will work in tandem with advanced modeling to reduce blackouts during times of peak demand and reduced supply. And behind it all will be numerous artificial intelligence platforms.

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