The global shift from nonrenewable to clean renewable energy sources is an all-hands mission. Reaching net-zero carbon emissions requires focus and support comparable to landing a spaceship on the moon. In fact, the U.S. Department of Energy (DOE) calls this 21st century mission Energy Earthshots™. But unlike the singular goal of a moon landing, Earthshots™ involve a multi-pronged approach to harness the renewable power of hydrogen, the Earth’s heat, and wind and to store that energy, making industry more efficient and eliminating net carbon emissions.
To support DOE’s Energy Earthshots™, Pacific Northwest National Laboratory (PNNL) will lead two separate Energy Earthshot Research Centers (EERCs). These centers build upon PNNL’s established expertise in performing the basic science underpinning (1) geothermal energy and (2) floating offshore wind energy. PNNL scientists will also support a third center focused on carbon dioxide sequestration.
Chemist Kevin Rosso leads the Center for Understanding Subsurface Signals and Permeability (CUSSP) to advance enhanced geothermal systems with the goal of making them a widely accessible and reliable source of renewable energy. CUSSP aims to predict and control how water flows through hot rock formations in the subsurface through complex simulations and accurate field measurements.
Earth scientist Larry Berg heads the effort to make floating offshore wind a long-term viable energy source through the center titled Addressing Challenges in Energy: Floating Wind in a Changing Climate (ACE-FWICC). ACE-FWICC will advance the design and control of floating offshore wind turbines and their integration into the grid by incorporating knowledge of weather and ocean conditions.
Both PNNL-led efforts include team members at other national laboratories and universities, bringing together the diverse expertise necessary to make meaningful progress toward deploying both enhanced geothermal and offshore wind energy.
PNNL is a partner in a third center focused on carbon dioxide removal, the Terraforming Soil EERC: Accelerating Soil-Based Carbon Drawdown through Advanced Genomics and Geochemistry, led by Lawrence Livermore National Laboratory. The EERC program provides each center with $19 million of funding over a period of four years.
“We at PNNL are proud to support and advance the Office of Science’s important scientific mission and the ambitious goals of the Energy Earthshots™,” said Steven Ashby, PNNL Director. “These new centers will draw on PNNL’s deep fundamental science expertise to drive the applied solutions required for our nation’s clean energy future.”
Understanding what’s under the surface
Geothermal energy operates under a simple principle: Water heated in the Earth’s subsurface can be used to generate electricity. Historically, humans have taken advantage of natural sources of geothermal energy such as hot springs. But meeting future energy needs will take more than these scattered resources.
Enhanced geothermal systems involve creating geothermal energy at newly built sites. This requires drilling wells to pump cool water deep into the Earth and then extracting the heated water from the subsurface. To enable fluid flow, a network of fractures is created beneath the surface to connect the injection and production wells. The water flows through the small cracks, picking up heat along the way. However, the extreme conditions deep underground mean that the fracture network can change over time in complex ways that are difficult to predict.
The new Earthshot Center aims to take the guess work out of predicting how a geothermal site will change over time. The PNNL-led team is taking a new approach to understanding how water flows in these subsurface fractures.
“Our approach will use sensing measurements from an active field site to find clear links between the detected signals and different physical and chemical processes that control fluid flow,” said Rosso. “This would allow us to learn and ultimately predict what’s happening both now and in the future, based on data from a realistic test site.”
PNNL expertise in geochemistry, geophysics, and subsurface modeling will all contribute to the team’s research effort. For example, PNNL-developed software called PFLOTRAN models the complexities of changing subsurface flows. Previous work led to a first-of-its-kind capacity to integrate geophysical data into PFLOTRAN. The project’s focus on enhanced geothermal systems will mean expanding PFLOTRAN’s ability to predict subsurface processes to include geochemistry coupled to geomechanics, and the corresponding sensing signals governed by those processes.
Making geothermal power practical with models
The long-term stability and feasibility of enhanced geothermal systems relies on knowing how the fracture network will behave over time. At the high temperatures and pressures found deep underground, chemical processes are active and rapid. Minerals can dissolve in the water and redeposit elsewhere, changing the shape of the fracture network and affecting the flow patterns.
As the flow patterns change, so does the overall output of the geothermal system. Tracking the active chemistry is challenging, because making measurements inside the fracture network is impractical. Therefore, researchers rely on subsurface remote sensing and sampling at the input and output wells. PNNL researchers are experts in using sensing techniques to identify the physical processes that occur deep underground.
“It’s analogous to satellite imaging in that we’re sensing processes that are occurring far from the sensors,” said Tim Johnson, a PNNL computational scientist and member of the CUSSP leadership team. “We put geophysical sensors in deep boreholes so we can ‘see’ what’s happening between them.”
By combining geophysical, geochemical, and geomechanical data, the research team aims to produce a rich picture of the evolving fracture network at an enhanced geothermal research site. The data will help identify how a site will evolve over time, enabling optimization and reducing the cost of clean geothermal energy production. The team plans to use machine learning approaches to help parse the data and identify the most important factors.
From the Earth to the sea
In ACE-FWICC, PNNL researchers are leveraging their deep knowledge of atmospheric and oceanic phenomena, artificial intelligence and machine learning, and the electric grid to overcome hurdles to deploying floating offshore wind. Floating offshore wind turbines represent an exciting way to capture significant amounts of energy because they can be placed over deep areas of the ocean where anchored wind platforms are impractical.
At this point, deploying floating offshore wind faces several major challenges. These challenges include identifying locations for wind farms, understanding how meteorological and ocean conditions will affect the turbines, and effectively integrating the energy into the grid. The new offshore wind Earthshot center pulls from expertise across all these areas to create a team that combines basic and applied sciences.
“PNNL has spent decades building deep knowledge about the atmosphere/ocean system, controlling wind turbines to optimize power production and turbine lifetime, efficient and reliable operation of the electrical grid, and artificial intelligence and machine learning,” said Berg. “ACE-FWICC allows us to partner across atmospheric and ocean science, wind plant control, and grid integration to help make floating offshore wind cost effective.”
Installing floating offshore wind turbines requires a significant investment, so making sure that they are placed in areas that will remain appropriately windy for decades to come is essential for their long-term viability. The team will model meteorological and oceanic conditions in a changing climate, identifying their effects on the strength and availability of wind.
These model results will feed into predictions of power produced by such turbines and to estimate their lifetimes by calculating wear and tear. Data on power to be generated by these turbines will be used in grid models to help enable their smooth integration to the larger power grid.
A powerful force for offshore wind
This type of interconnected modeling effort is in the earliest stages for floating offshore wind. Traditional modeling approaches take each section of a wind energy ecosystem and simulate it separately. This can result in models that either cannot communicate or produce data that is hard to use in other, related models. Developing a new, deeply collaborative framework can lead to more effective modeling.
The center will bring together the disparate parts of the floating offshore wind prediction ecosystem using artificial intelligence and machine learning to create faster and more accurate models. Through these models, researchers will be able to determine where to construct floating offshore wind turbines and how to effectively integrate them into the future grid.
The team includes researchers from a wide range of backgrounds, career levels, and institutions. “When we were building our team, we thought very intentionally about how to bring different perspectives to the project,” said Alicia Mahon, an advisor to ACE-FWICC and the program manager for wind energy at PNNL. “The group we have is diverse and talented, exactly what this problem needs.”