DOE eyes AI, machine learning to accelerate long-duration energy storage research

At-a-Glance:

A proposed federal research program to accelerate research into the durability and performance of long-duration energy storage is a critical step to meeting the Biden administration’s decarbonization goals, speakers said Thursday at a Department of Energy (DOE) panel. DOE officials said long-duration energy storage technology must be commercially ready, at scale, by 2030, in order to increase the share of renewables on the grid and meet the administration’s 100% clean electricity by 2035 goal. To learn more, read, DOE eyes AI, machine learning to accelerate long-duration energy storage research.”

Key Takeaways:

  • In July, DOE announced a moonshot goal to reduce the cost of utility-scale, long-duration storage by 90% within a decade, backed by federal research, large-scale demonstrations and domestic manufacturing incentives
  • Deputy Energy Secretary David Turk said bringing long-duration storage to the grid wouldn’t just make it possible to rely on more renewable energy, but also “increase resilience and lower energy burdens” for vulnerable communities.
  • Although there have been technical breakthroughs on long-duration technologies — notably Form Energy’s July announcement of a 100-hour iron-air battery — experts have cautioned about the limited window to test batteries in the real world.
    • ROVI, the proposed initiative from DOE’s national labs, seeks to close that information gap by using machine learning and artificial intelligence to model performance of different long-duration storage technologies, including predicting how the technology will lose performance or hold up physically over time.

Path to 100% Perspective:

Artificial Intelligence (AI) and Machine Learning (ML) will be key elements for the design of future energy systems, supporting the growth of smart grids and improving the efficiency of power generation, along with the interaction among electricity customers and utilities. Centralized power systems enable equal access to clean power at the lowest cost, reducing economic inequality. Regardless of whether the path forward is more or less centralized, AI brings value to all parties. The more AI is used in the dispatch of power plants, the more it will be needed in the design and creation process for new power plants or aggregations of power generation equipment. AI and equipment expertise are needed to enhance the safety, reliability, and efficiency of power equipment and systems. AI and machine learning will play increasingly important roles in future power generation, especially as more communities and organizations come to rely on smart grids and renewable fuels for their electricity needs.

Photo by Michael Dziedzic on Unsplash

How Green Energy Will Transform the Ranks of the World’s Biggest Electric Generators

At-a-Glance:

The world’s energy sector has embarked on a transitional journey to a clean, green, low-carbon future powered by windmills and solar panels. It’s going to be a long trip. According to the International Energy Agency, we still derive an incredible 80% of our primary energy from fossil fuels—with oil contributing 32%, coal 27% and natural gas 23%. To learn more, read How Green Energy Will Transform the Ranks of the World’s Biggest Electric Generators.” Reading this article may require a subscription from the news outlet.

Key Takeaways:

  • Electric industry analyst Hugh Wynne of research shop SSR says carbon dioxide will be regulated in one way or another, via a carbon tax, cap-and-trade or emissions allowances.
  • Analysts believe companies with stubbornly high emissions are going to have to pay to pollute — while those with low emissions will enjoy a profitability advantage.
  • Wynne found the “dirtiest” utilities are those with coal-fired fleets in China, Russia and India.
  • Meanwhile, some of the more progressively minded utility companies are keen to take advantage of new tools evolving out of advances in machine learning and artificial intelligence.
  • Forbes Global 2000 companies Southern Company, Exelon, and Dominion Energy are all customers of a startup called Urbint, which was founded by Forbes 30 Under 30 alum Corey Capasso and has raised more than $40 million in funding for its A.I.-driven infrastructure safety platform.

Path to 100% Perspective:

Artificial intelligence (AI) is a very broad field. Forecasts for price and power are generated by AI and represent the expected trajectory or probability distribution of that value. In the end, as a power trader, it is important to remember the historical data is not a picture of the future, but rather a statistical distribution that can be leveraged to inform the most probable outcome of the unknown future. AI is more capable at leveraging statistics than people will ever be. The benefit of using AI is more effective utilization of the existing infrastructure. There is quite a bit of under-utilized infrastructure in the power generation industry. However, with the use of greater intelligence on the edges of the network coupled with great intelligence at the points of central dispatch, under-utilized infrastructure can be maximized for a more reliable power system.

The POWER Interview: The Importance of AI and Machine Learning

At-a-Glance:

Artificial intelligence (AI) and machine learning (ML) are becoming synonymous with the operation of power generation facilities. The increased digitization of power plants, from equipment to software, involves both thermal generation and renewable energy installations. To learn more, read “The POWER Interview: The Importance of AI and Machine Learning.”

Key Takeaways:

  • AI and ML will be key elements for the design of future energy systems, supporting the growth of smart grids and improving the efficiency of power generation, along with the interaction among electricity customers and utilities.
  • Centralized power systems enable equal access to clean power at the lowest cost, reducing economic inequality. Regardless of whether the path forward is more or less centralized, AI brings value to all parties.
  • “AI is very important to smart grids,” Wärtsilä General Manager of Data Science, Energy Storage & Optimization, Luke Witmer said. “AI is extremely important to the integration of smart charging of electric vehicles, and leveraging those mobile batteries for grid services when they are plugged into the grid.”
  • The more AI is used in the dispatch of power plants, the more it will be needed in the design and creation process for new power plants or aggregations of power generation equipment.

Path to 100% Perspective:

Wärtsilä uses AI and equipment expertise to enhance the safety, reliability, and efficiency of power equipment and systems. AI and machine learning will play increasingly important roles in future power generation, especially as more communities and organizations come to rely on smart grids and renewable fuels for their electricity needs.

 

Photo by Michael Dziedzic on Unsplash