![]() ![]() “Regulators are providing multiple grants for building digital twins of power plants to increase safety and reduce the high costs of shutting systems down for tests,” Perez said. Separately, Deloitte plans to use NVIDIA Omniverse Enterprise to develop a physically accurate digital twin of a nuclear power plant for worker training scenarios. state is acting as a demo facility in an EPRI project that’s gathered broad interest. For example, a power plant in one southern U.S. Power Plants Get Digital Twinsīoth EPRI and Deloitte are helping create industrial digital twins to optimize operations and training at power plants. To keep shared data private, it can use NVIDIA FLARE software to train AI models. One is a database that already sports 150,000 images taken by drones of aging equipment on powerlines.ĮPRI also leads a startup incubator where utilities can collaborate with AI startups like Noteworthy AI, a member of NVIDIA Inception, to work on innovative projects. Separately, EPRI is curating 10 sets of anonymous data utilities can use to train AI models for their most critical jobs. “We want to automate 80 percent of the mundane tasks for operators, so they can do a better job focusing on the 20 percent of the most complex challenges,” said Renshaw.Ī 2021 report on how AI can address climate change cited as an important use case the L2RPN work which is expanding this year to include more complex models. ![]() Some are capable of controlling as many as five tasks at once to prevent an outage. Building AI Models, DatasetsĪt EPRI, Renshaw reports progress on several fronts.įor example, more than 300 organizations have joined its L2RPN challenge to build AI models with reinforcement learning. “Because it’s an open system, we could use our existing IT staff and, with NVIDIA’s support, do supercomputing-class work for our client,” Perez said. One effort combines data on the state of the electric grid with local weather conditions to identify - in time to dispatch a repair crew - distribution lines caked with ice and in danger of failing. To show utilities what’s possible, Deloitte runs jobs on NVIDIA DGX A100 systems in its Center for AI Computing. Past efforts on CPU-based systems took up to 36 hours, too long to be useful. city recently got traction with AI on NVIDIA GPUs, determining in less than 30 minutes the best truck routes for responding to a storm. are taking the first steps of creating a data engineering platform and an edge-computing practice, using sensor arrays and real-time analysis,” said Perez.įor example, a utility in a large U.S. “Some of the largest utilities in the U.S. ![]() Work is already underway at power plants and substations, on distribution lines and inside homes and businesses. Managing it requires advanced AI methods and high performance computing,” he said. “The future energy grid will be distributed and fueled by thousands of intermittent power sources including wind farms and various storage technologies. Rick Perez, a principal at Deloitte Consulting LLP with more than 16 years working with utilities and data analytics, agrees. “AI can support grid operators already stretched to their limits by automating repetitive or time-consuming tasks,” said Renshaw, who manages EPRI’s AI initiative. “AI will play a crucial role maintaining stability for an electric grid that’s becoming exponentially more complex with large numbers of low-capacity, variable generation sources like wind and solar coming online and two-way power flowing into and out of houses,” said Jeremy Renshaw, a senior program manager at the Electric Power Research Institute (EPRI), an independent, non-profit that collaborates with more than 450 companies in 45 countries on energy R&D. Given the changes ahead, experts say the grid must expand autonomous control systems that gather data at every node and use it to respond in real time. Yesterday’s hundred-year-old grid - a one-way system from a few big power plants to many users - must morph into a two-way, flexible, distributed network connected to homes and buildings that sport solar panels, batteries and electric vehicles. It called for a net-zero carbon grid by 2050, fueled by hundreds more gigawatts in renewable sources. “Extreme weather events of 2021 highlighted the risks climate change is introducing, and the importance of investing in more resilient electricity grids,” said a May 2021 report from the International Energy Agency, a group with members from more than 30 countries. Grid failures the past two summers sparked devastating wildfires amid California’s record drought. The winter 2021 megastorm in Texas left millions without power. Electric utilities are taking a course in machine learning to create smarter grids for tough challenges ahead. ![]()
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