Quick summary: Utilities are being challenged to change their approach to transmission and distribution investments, and intelligent technologies offer a solution.
As the U.S. grid infrastructure continues to age and the demands on it continue to evolve, utilities are under pressure to invest in upgrading and replacing their assets, particularly on the T&D side. According to the U.S. Department of Energy, 70 percent of transmission lines are over 25 years old, the average age for power transformers is 40, and 60 percent of circuit breakers are over 30 years old. Investments in T&D systems by major utilities has risen 54 percent over the last two decades to $51 billion annually, but more needs to be done.
Current approaches to T&D investment typically involves adhering to schedules that were set years in advance, determined by a patchwork of factors ranging from outage reports to the experience-based recommendations of engineering and maintenance personnel. But with significant disruptors changing the nature of both supply and demand in the United States, the old methods must give way to a more targeted, data-driven approach.
A changing ecosystem
Utilities that may have been reluctant to upgrade their approaches to T&D investment planning are facing a complex and rapidly changing ecosystem that is making “tried and true” methodologies obsolete.
Shifting demand patterns
Sales of electric vehicles (EVs) have seen slow, steady growth over the past decade but have skyrocketed in recent years, growing by 83 percent in 2021. To travel 100 miles, the average EV requires 30 kilowatt-hours—the equivalent of a day’s worth of energy use for the average U.S. home. Switching to EV fleets is also a growing trend among businesses, including such major players as Amazon, Walmart, Best Buy, and FedEx.
More EVs mean higher electricity demand—California predicts EVs will consume 5.4 percent of the state’s total electricity by 2030—and T&D infrastructures must be prepared to handle the load.
An evolving supply profile
Driven by environmental concerns, government incentive programs, and falling prices of wind, solar, and storage systems, the growing popularity of renewable distributed energy resources (DERs) has changed the face of power supply in the United States. In 2021 the residential solar market grew 30 percent over 2020, marking its fifth consecutive record year, and corporate solar deployment is 15 times larger today than it was a decade ago. In addition, a recent study shows a growing interest in DERs among commercial industrial sectors, spurred by the promise of avoiding voltage fluctuations that lead to downtimes and possible equipment damage.
As the decentralized power supply ecosystem of the future continues to take shape—including two-way electricity flows to and from end consumers—utilities must ensure they have the T&D infrastructure needed to support it.
Escalating climate change
In 2021 alone, the United States experienced a record-breaking winter storm in Texas, more than 8,000 wildfires in California, a major hurricane in Louisiana, and a historic heat wave along much of the West Coast—all of which caused disruptions in the power grid. Climate change–related weather events are on the rise, driving the need for an increasingly hardened T&D infrastructure that can keep the power flowing when environmental emergencies arise.
Increasing compliance requirements
Closely related to the climate change issue is the growing number and detailed nature of requirements from state public utilities commissions. In California, for example, utilities are required to submit Wildfire Mitigation Plans detailing how they are investing in measures to reduce the risk of catastrophic wildfires and proving that their initiatives have been effective.
Not only are utilities being held accountable for maintaining a safe and reliable T&D infrastructure, but they must also have a data ecosystem in place that can support their reporting requirements.
The path to data-driven investment planning
There is good news for utilities being compelled to change their approach to T&D investments. Edge technologies can automatically deliver the data they need, and AI and machine learning platforms can analyze this data—plus data from hundreds of other sources—to produce strategic insights in a fraction of the time it would take human workers.
A new generation of edge technologies
Advanced IoT technologies such as next-generation smart meters and equipment health-monitoring sensors stream vital data directly to utilities, delivering real-time insights on both the supply and demand sides. In addition, data from drone footage, lidar, geographic information systems (GIS) and other sources provide a more complete perspective of areas where T&D assets may need upgrades or replacement.
Machine learning for T&D infrastructure data
With terabytes of data streaming into their servers at top speed, utilities are then faced with the question of how to transform all this data into information that can drive a strategic T&D investment plan. Analytics platforms driven by AI and machine learning can not only spin massive amounts data into actionable insights, but also “learn” acceptable parameters—such as how much wear can appear on an asset before it’s at high risk for failure—and use the outcomes to become more skilled as time goes on.
Utilities can use the data from these platforms to identify areas where T&D assets are at highest risk for failure—and where those failures would have the greatest impact—to make the best use of their investment dollars in ensuring a safe, reliable grid.
Machine learning can also play a vital role in demand modeling, enabling utilities to predict and plan for surges in electricity usage, and in making decisions around public safety power shutoffs (PSPS) for areas of the infrastructure that are being threatened by extreme weather to proactively prevent ignition of wildfires.
Investing in the grid of the future
As utilities adapt to the challenges of the present environment—on both the supply and demand sides—it’s more important than ever to ensure the highest possible ROI on their T&D investments. By adapting a data-driven approach, they can ensure that areas at highest risk receive top priority in allocating investment dollars, and that healthy assets won’t divert resources away from where they are most vitally needed.
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Frederike Dubeau is a Manager in Logic20/20’s Advanced Analytics practice.
Chris Wu is a Manager in Logic20/20’s Advanced Analytics practice.