Revolutionizing the Grid
As a Director with Clarum Advisors, Molly Podolefsky leverages her experience in economics, decarbonization, corporate sustainability, corporate finance, and the power and utilities sector to help innovative, clean tech companies. Prior to Clarum, Molly spent a decade at Guidehouse working with utility clients managing EE and DSM EM&V portfolios, supporting regulatory compliance and conducting research focused on IoT, smart and connected devices, load flexibility and demand response. Dr. Podolefsky earned her PhD in Economics from the University of Colorado at Boulder, with a focus on energy and environmental economics.
AI has people on edge for many reasons, from its potential use as a disinformation tool to its competition with human workers. At the same time, AI is placing a tremendous strain on the electric grid through the rapid expansion of hyperscale data centers.
By focusing only on the negatives, however, we risk missing an equally important story — the emerging narrative around AI’s potential to revolutionize grid operation, allowing us to safely and reliably get more out of systems and infrastructure already in place.
AI has the potential to revolutionize the functioning of the U.S. power system by improving the speed, scale, and efficiency of buying, selling, and moving electricity around the grid, thereby helping address the capacity, transmission, and decarbonization issues it has created. AI also has the potential to contribute solutions to energy system problems it did not cause, from anticipating power outages and preventing blackouts to identifying system faults and protecting against wildfires and cyber attacks.
Addressing Demand Shortages
Over the past decade, AI has shown tremendous potential for reducing demand by improving the way companies use energy and leveraging flexibility to create capacity. As early as 2016, Google pioneered the use of AI to intelligently cool its data centers, thereby reducing energy demand.
Through its DeepMind AI platform, the company was able to significantly reduce the energy used for cooling. More recently, Google has begun leveraging AI platforms to shift workloads between data centers, creating flexible loads that can be treated as a Virtual Power Plant and shared with grid operators in response to energy crises.
AI-powered Virtual Power Plants unlock vast reservoirs of flexible capacity outside the realm of hyperscaler data centers. Leveraging predictive analytics and real-time data processing, AI-driven Virtual Power Plants can intelligently orchestrate and dispatch solar power, battery storage, EV charging systems, vehicle-to-grid assets, smart thermostats, smart buildings, commercial HVAC, and flexible industrial loads, thereby avoiding the buildout of new generation capacity.
Relieving Transmission and Distribution Constraints
At the same time AI is burdening transmission and distribution systems with increased load, system operators are leveraging AI to build the power grid of the future. Grid modernization through AI enables power system operators to manage and synthesize vast amounts of data from disparate sources, use that data to rapidly generate accurate forecasts of supply and demand, and dynamically optimize system responses.
AI enables grid operators to optimize transmission flows in real time, minimizing cost. The National Renewable Energy Laboratory has begun testing a power grid control room AI assistant, eGridGPT, to enhance the effectiveness of human grid operators by analyzing procedures, simulating scenarios, and optimizing decision-making processes.
Other AI-driven innovations aim to expand the capacity of transmission and distribution lines themselves, allowing greater volumes of energy to be transferred using existing infrastructure.
LineVision, a grid modernization provider, deploys AI-powered dynamic line rating hardware and software systems enabling utilities and grid operators to increase capacity on existing transmission lines by up to forty percent.
Facilitating Decarbonization
While hyperscaler growth has extended the lives of coal-fired power plants and increased investments in natural gas generation, AI is also powering decarbonization. AI enables real-time dynamic pricing models, which allow for more efficient integration of intermittent renewables on the grid, and data center companies have begun leveraging AI to decarbonize their own operations.
Smart buildings and home energy management systems increasingly allow energy consumers to minimize carbon emissions. AI tools also have the potential to speed labor-intensive review and permitting processes, bringing renewables online faster.
The U.S. Department of Energy is investing in AI-powered software aiding the federal review process for National Environmental Policy Act compliance. The Department of Energy is also investing in AI to tackle the backlog of renewables projects in interconnection queues, which will speed the interconnection review, approval, and commissioning process.
Improving Grid Reliability and Resilience
AI confers benefits on the energy system extending beyond mitigation of negative impacts on generation capacity, T&D systems, and the pace of decarbonization. Over the next decade, AI holds the potential to significantly increase grid reliability and resilience.
U.S. grid infrastructure is aging, and the key to reliability and resilience will be proactive detection of faults and failures. Argonne National Lab is developing AI-enabled grid asset health monitoring software designed to predict failure before it occurs, reducing the potential for power failures and minimizing downtime.
While digital twin technology has been in use for over a decade, we are witnessing massive improvements in digital twin performance as AI enables integration and learning based on ever larger datasets, facilitating detection of patterns and anomalies to predict failure earlier and with greater accuracy.
Reducing Power Outages and Wildfires
AI-enabled software systems will play an increasingly important role in detecting faults in the energy system that could lead to power outages and wildfires. Harnessing the power of AI to identify telltale signs of equipment faults and failure earlier, utilities and grid operators will be better equipped to ensure the reliability and safety of power systems.
AI-powered utility pole and transformer sensors deployed by Ubicquia can assist with fault and damage detection, wildfire prevention, and storm response. Utilities such as Portland General Electric are beginning to leverage AI-powered camera systems to improve wildfire ignition response times.
After extreme weather events and natural disasters, utilities are increasingly relying on AI to restore power faster and more efficiently. AI helps companies assess damage to assets, prioritize repairs, optimize repair routes, and dispatch crews efficiently to restore power, significantly reducing the amount of time customers spend without power.
Hardening the Grid Against Cyber Attacks
A final frontier for AI to improve energy system resilience in the next decade will be hardening U.S. grid infrastructure against cyber attacks. Attacks targeting U.S. grid infrastructure have increased significantly in recent years. Fortress, a cybersecurity company specializing in solutions for energy utilities recently released a report detailing “highly exploitable” vulnerabilities in software products and code used by U.S. utilities.
Using generative AI, cybersecurity software providers can synthesize vast and varied datasets, create more sophisticated defenses, and leverage complex simulations to detect vulnerabilities. Cybersecurity companies serving utilities and grid operators leverage AI to help detect and mitigate vulnerabilities and cyberthreats, increasing the resilience of the grid.
While AI-induced load growth seems likely to continue, from our vantage point, the larger and more impactful story will be AI’s role in revolutionizing the grid. Between now and the end of this decade, many of today’s nascent AI-powered grid technologies will mature, transforming the grid in ways we cannot yet imagine. While load growth will continue to pose challenges for the energy sector, we should not underestimate AI’s potential to transform the energy economy for the better.
