Sustainable Energy Powered with AI

When it’s software-defined, the electric grid becomes more resilient, affordable, and decarbonized through renewable energy and integration of distributed energy resources (DERs). From digital twins of power plants to AI-driven grid operations to next-generation smart meters capable of real-time control, the power grid of tomorrow will accelerate our energy transition to a more sustainable future.

Autonomous Operations

Autonomous Operations

With NVIDIA Modulus and NVIDIA Omniverse, power plants can automate manually intensive inspections to improve predictive maintenance, reduce unplanned downtimes, and protect worker health and safety.

Global Decarbonization

Global Decarbonization

To reach ambitious net-zero emissions goals by 2050, renewable energy resources such as wind, solar, and electric are growing in adoption. AI can dynamically manage these new resources on the grid.

Grid Decentralization

Grid Decentralization

As more electric vehicles and residential solar panels come online, traditional energy grids will quickly become overloaded and unreliable. Smart grids, built on software and powered by edge AI, can automate management.

Enhancing Energy Efficiency at Every Stage

The Software-Defined Smart Grid

Managing distributed energy resources, such as electric vehicles, solar panels, and wind farms, presents challenges for traditional grids. Edge AI helps dynamically manage energy resources, predict demand, and allocate supply to enhance grid resiliency. Advances in smart meters—powered by a software-defined smart grid chip based on the NVIDIA® Jetson edge AI platform–deliver greater value to utilities and their customers, while unlocking new opportunities for clean energy companies and third-party market developers.

Software-Defined Smart Grid
Power Line Predictive Maintenance

Grid Predictive Maintenance

In the U.S, utilities own 185 million poles and spend tens of millions of dollars each year tracking the status of transformers, fuses, and other attached devices for potential faults. This manually intensive process can take up to a decade, yet the condition of each device is critical to delivering power safely to homes and businesses. By deploying the NVIDIA Jetson edge AI platform on service trucks, utilities can automate data collection and analysis, including the identification of vegetation growing too closely to power lines. And with NVIDIA Omniverse, enterprises can simulate wildfires using a digital twin to better predict and respond to fires in real time.

Real-Time Power Grid Management

Managing loads within large regional grids is complex. With the emergence of microgrids and nanogrids—small-scale local backup power systems that operate autonomously and integrate distributed energy resources—real-time load balancing and price adjustments are exponentially more complex. With NVIDIA GPUs, utilities can accelerate simulations of power networks at scale, achieve optimal power flow, and rapidly identify grid anomalies. Daily workloads such as outage scheduling and contingency analysis can also be accelerated.

Real-Time Grid Management
Power Plant Digital Twins

Industrial Digital Twins

Global energy enterprises are looking to build industrial digital twins to reduce the unplanned downtime of equipment for maintenance and repairs. The solution uses NVIDIA Modulus, a framework for developing physics-machine learning neural network models, and NVIDIA Omniverse, a physically accurate virtual world simulation and collaboration platform for 3D workflows. By analyzing real-time data to reduce the frequency of planned shutdowns, utilities can maintain worker safety, improve site efficiency, and save billions of dollars per year.

Building AI in the Utilities Ecosystem

Noteworthy AI
National Renewable Energy Laboratory

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