The spread of “electricity-hungry data centers and clean-technology factories” throughout the United States is “leaving utilities and regulators grasping for credible plans to expand the nation’s creaking power grid,” according to a recent article in the Washington Post. According to the report, the surge in industrial power requirements due to such factors as innovation in artificial intelligence (AI) and the corresponding construction of large computing infrastructure, is prompting some officials to “look beyond the grid” to ease the “grid bottleneck” and meet electricity demands.

Standard Power, a provider of infrastructure as a service to advanced data processing companies, has chosen NuScale Power as the technology provider for its plans to develop two small modular reactor–powered facilities in Ohio and Pennsylvania to run nearby data centers, the Portland, Ore.-based SMR developer announced on October 3.

Advanced reactors are promising energy systems that can enable the world to transition to a more sustainable energy matrix. These concepts are potentially more fuel efficient and safer, compared with previous generations of nuclear reactors. Many designs, like high-­temperature gas reactors (HTGRs) and molten salt fast reactors (MSFRs), target high outlet temperatures, allowing for their operation in processes where high heating is required, such as for hydrogen production and desalination.

Jamie Coble

The nuclear power industry has the opportunity for significant advancements in the coming years, driven by the digital integration of instrumentation and controls (I&C), machine learning (ML), artificial intelligence (AI), and optimized operations and maintenance (O&M) technologies. These developments are the enabling technologies that can ensure the efficiency, safety, and reliability of our future fleet of nuclear power plants, propelling the industry toward a more sustainable and intelligent future.

I&C plays a vital role in monitoring and controlling various aspects of nuclear power plants. Traditional I&C systems have relied on hardwired control circuits, but modern advancements are shifting towards digital I&C systems, also known as digital control systems (DCS). These systems offer enhanced flexibility, scalability, and reliability. They utilize advanced sensors, data acquisition systems, and distributed control algorithms to enable real-time monitoring, fault detection, and control optimization.

Imagine if your employees had a Virtual Assistant that could create condition reports, work requests, or plan work orders simply by asking for it. Or better yet, what if the Virtual Assistant could create work packages and plan your employees’ day automatically without even having to ask? How much more productive would we be if we all had a Virtual Assistant to help perform our work and capture and share our activities as they occurred?

X-energy, the Rockville, Md.–based small modular reactor developer, has announced its plan to open the first Xe-100 reactor fleet management, monitoring, and training facility—the Plant Support Center–East (PCSE)—in the fourth quarter of this year.

Artificial intelligence (AI) and machine learning (ML) are helping scientists, engineers, regulators, and plant decision makers in their research and development of clean energy production to achieve a net-zero carbon footprint. While this science is new in terms of actual applications, it is fostering innovation in a variety of domains, from material discovery and qualification to advanced reactor design to supporting efficiencies in current power plants and transforming the usability of nuclear power plant control rooms.

The Department of Energy’s Naval Reactors Division is seeking applicants for its Rickover Fellowship Program in Nuclear Engineering for 2022-2023. The deadline for application submissions is January 31.

Application forms are available at the South Carolina Universities Research and Education Foundation (SCUREF) website. Applicants should submit all materials electronically through this site.

As predictive analytical tools, artificial intelligence (AI) and machine learning (ML) show promise in improving nuclear reactor safety while offering economic savings. To get a better understanding of current usage and future trends in AI and ML in the commercial nuclear power industry, the Nuclear Regulatory Commission is seeking comments from the public, the nuclear industry, and other stakeholders, as well as other interested individuals and organizations.

This year’s Utility Working Conference, held on August 11, had a dynamic opening plenary and a packed roster of informative sessions. Following are recaps of some of the 12:00 p.m. (EDT) sessions that took place.

You can read about the UWC's opening plenary here.

Look for more meeting recaps later today.

The Department of Energy announced on March 4 that it will provide $30 million for new research on fusion energy. The funding will provide $17 million for research focused specifically on artificial intelligence (AI) and machine learning (ML) approaches for the prediction of key plasma phenomena, management of facility operations, and accelerated discovery through data science, among other topics. An additional $13 million under a separate funding opportunity will be devoted to fundamental fusion theory research, including computer modeling and simulation, focused on factors affecting the behavior of hot plasmas confined by magnetic fields in fusion reactors.