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Enhancing power generation, transmission, and distribution for grid modernization and lower costs.
Building a software-defined smart grid enhances resiliency during extreme weather events, improves electricity affordability and reliability through real-time optimal power flow, integrates distributed energy resources such as solar, wind, electric vehicles (EVs) and home batteries, and accelerates decarbonization initiatives. With AI, utilities can modernize legacy grid infrastructure, scale renewable energy, and deliver lower cost power to homes and businesses.
In a keynote at the Edison Electric Institute’s annual meeting, NVIDIA Founder and CEO Jensen Huang spoke about ways the industrial revolution of generative AI is transforming the future for utilities and their customers.
Learn how Utilidata, Hubbell, and NVIDIA are bringing distributed AI to the grid edge, giving utilities real-time visibility into grid operations and distributed energy resources.
Managing Distributed Energy Resources
Managing distributed energy resources, such as solar panels, wind farms, electric vehicles (EVs), and home batteries presents challenges for traditional grids. Edge AI helps dynamically manage these 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.
Automating Grid Asset Inspection
Most drone inspections still require a human to manually inspect the video for defects. Training a computer vision model to automate inspection is difficult without a large pool of labeled data for every possible defect. By using synthetic data generation in Omniverse, utilities can automatically create thousands of labeled, photorealistic examples of diverse defects. These synthetic images can then train an inspection model for real-time drone inspection.
Optimizing Power Flow and Outage Scheduling
The emergence of microgrids and nanogrids—small-scale local backup power systems that operate autonomously and integrate distributed energy resources—has made real-time load balancing and price adjustments exponentially more complex. High-performance computing (HPC) lets utilities quickly model networks at scale and achieve optimal power flow for outage scheduling and contingency analysis. AI-enhanced intelligent video analytics and cybersecurity secure grid infrastructure from unauthorized access.
Analyzing Infrastructure to Automate Repairs
In the U.S. alone, utilities own 185 million poles and spend tens of millions of dollars each year tracking the status of crossarms, transformers, fuses, and other grid assets for 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 field service trucks, utilities can automate data collection and analysis, accurately monitor real-time grid health, and identify needed repairs and vegetation management.
Personalizing Customer Interactions
Customer service, a key metric for utilities, relies on 24/7 service availability. Higher-than-normal demand volatility due to unexpected outages can cause surges in call volume from affected customers. However, AI and data analytics enhance the overall customer experience and help control operating expenses. In call centers, utilities can use AI as virtual assistants to support agents. Data analytics can be utilized to present the customer support agent with a 360-degree view of the customer, including past usage, peer comparison, and rate guidance, which reduces call times and customer frustration.
Improving Truck Rolls During Extreme Weather
During power outages due to heavy wind, rain, or other weather events, utilities are expected to quickly and efficiently deploy fleets of field service trucks to restore power to residents and businesses. Utilities are exploring using AI to optimize vehicle route planning in real time, reduce travel times, cut fuel costs, and improve response times.
Learn how AI is improving power generation, reducing energy costs, and advancing scientific breakthroughs.
Exelon, the largest regulated electric utility in the U.S., is using NVIDIA Omniverse to automatically create thousands of grid asset defect examples for real-time drone inspection models—enhancing grid reliability and resiliency.
Minerva CQ, a member of the NVIDIA Inception program, is making customer service calls in energy quicker and more efficient for agents and customers. Learn how the startup uses NVIDIA Riva for real-time dialogue suggestions, sentiment analysis, and optimal journey flows.
Image courtesy of Open Climate Fix.
Open Climate Fix, a member of NVIDIA Inception, built transformer-based AI models trained on terabytes of satellite data to improve solar energy generation predictions by 3x. Learn how the nonprofit is helping decarbonize the UK's electric grid.
By using synthetic data generation in NVIDIA Omniverse, our goal was to automatically create thousands of labeled photorealistic examples of various defects in grid assets. We are in the process of using real images and these synthetic images to train inspection models.
— Justo Ankush Agarwal, Director of Advanced Analytics, Exelon
In Oregon, we are experiencing the impacts of climate change first-hand and recognize the urgent need for innovation at the grid edge as we transition to a clean energy future. Investing in new technologies for the grid is a key strategy for PGE to achieve its climate goals and provide customers with clean, affordable, and resilient energy.
— Ananth Sundaram, Senior Manager of Integrated Grid, Portland General Electric (PGE)
With the increase in distributed energy resources–especially batteries, solar, and electric vehicles–those technologies can pose a management problem or opportunity to utilities. We’re working with NVIDIA to move that central computation out to the edge of the grid, so we can manage those resources in real time and integrate them into real-time power flow dynamics from the substation to the end of the line.
— Marissa Hummon, Chief Technology Officer, Utilidata
Southern California Edison and NVIDIA launched the Intelligent Grid Collaboration to enhance electric grid planning and management using AI—including load interconnections, asset inspection, vegetation maintenance, and incident response.
Utilidata
Consumers Energy is partnering with AI technology company Utilidata to deploy custom NVIDIA modules, with plans to add AI-powered modules to 18,000 electric meters used by Michigan EV owners for real-time data analytics and predictions.
EPRI announced DCFlex, an initiative to leverage data centers as a flexible resource on the electric grid to address peak loads and enhance reliability. NVIDIA is a founding member, along with innovative utilities and technology companies.
PG&E
PG&E is deploying Atomic Canyon’s Neutron Enterprise generative AI solution, built and running on NVIDIA’s full-stack AI platform, at PG&E’s Diablo Canyon Power Plant to transform enterprise search and retrieval—enabling cost savings and improved operational efficiency.
Schneider Electric announced a collaboration with NVIDIA on new reference designs to optimize data center infrastructure for performance, scalability, and energy efficiency—paving the way for groundbreaking advancements in AI and digital twins.
Learn about the AI and HPC hardware, software, and networking solutions for utilities.
NVIDIA Jetson brings accelerated AI performance to the edge in a power-efficient and compact form factor. Together with the NVIDIA JetPack™ SDK and NVIDIA Isaac™ software for Robotics Operating System, these Jetson modules, including the new NVIDIA Jetson Orin Nano™, support a full range of edge AI and robotics applications.
With NVIDIA AI Enterprise, energy companies can speed up development of use case applications, such as reservoir simulation, seismic processing, demand forecasting, predictive maintenance, and power grid management. Learn how to get access to NVIDIA AI with free curated labs to start testing.
NVIDIA DGX™ Cloud is an end-to-end, scalable AI platform for developers, offering scalable capacity built on the latest NVIDIA architecture and co-engineered with the world’s leading cloud service providers (CSPs).
NVIDIA Fleet Command™ is a managed platform for container orchestration that streamlines the provisioning and deployment of systems and AI applications at the edge. It simplifies the management of distributed computing environments with the scale and resiliency of the cloud.
NVIDIA® cuOpt™ optimizes operations by enabling better, faster decisions with accelerated computing. cuOpt helps teams solve complex routing problems with multiple constraints and delivers new capabilities such as dynamic rerouting, horizontal load-balancing, and robotic simulations, with subsecond solver response times.
NVIDIA Riva is a GPU-accelerated speech AI SDK for building and deploying fully customizable, real-time AI pipelines that deliver world-class accuracy in all clouds, on premises, at the edge, and on embedded devices.
NVIDIA Morpheus is a framework that lets cybersecurity developers create optimized AI pipelines for filtering, processing, and classifying large volumes of real-time data. Bringing a new level of security to the data center, cloud, and edge, Morpheus uses AI to identify and act on threats and anomalies previously impossible to identify.
NVIDIA Metropolis is an application framework, set of developer tools, and partner ecosystem bringing together visual data and AI to improve operational efficiency and safety across healthcare, logistics, manufacturing, retail, and more. It helps make sense of data created by trillions of sensors for some of the world’s most valuable physical transactions.
With NVIDIA Omniverse Enterprise, developers build advanced, generative AI-enabled 3D tools and applications for industrial digitalization, speeding up product development, delivering more immersive customer experiences, and unlocking breakthrough operational efficiencies. Omniverse combined with NVIDIA Modulus, a framework for developing physics-informed machine learning (physics-ML) models, enables digital twins for wind farms, power plants, electric grids, and, someday, Earth itself.
Videos
Webinars
Use Jupyter iPython Notebooks on a Jetson Nano Developer Kit to build a deep learning classification project with computer vision models. This easy-to-use, powerful computer runs multiple neural networks in parallel.
Gain an understanding of the various building blocks of NVIDIA Modulus, the basics of physics-informed deep learning, and how the framework integrates with the overall Omniverse platform.
Find out how to model mixed-fleet vehicle-routing problems for delivery or intralogistics and apply multiple routing constraints like capacity, time windows, mixed priority, or skills with simple APIs.
Explore NVIDIA Inception, the free program designed to help startups evolve faster through access to cutting-edge technology and NVIDIA experts, connections with venture capitalists, and co-marketing support to raise visibility.
Connect with millions of like-minded developers in the NVIDIA Developer Program to do your life’s work, and gain access to free containers, pretrained models, SDKs, technical documentation, and peer and domain expert help.
Expand and support your portfolio with NVIDIA’s Venture Capital (VC) Alliance, an initiative between NVIDIA and investors around the world who are focused on startups building cutting-edge technology with AI, data science, and HPC.
NVIDIA solutions for the power and utilities industry go beyond products. Our partners are here to assist your organization at every level to build and execute transformative AI strategies, products, and services.
Chat with NVIDIA energy experts to help solve your business challenges.
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