Hydro Leader July/August

Page 34

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Stuart Cohen of the National Renewable Energy Laboratory: Analyzing Pumped Hydro’s Role in a Stable Electricity Grid

An image from NREL’s interactive map of potential closed-loop pumped storage hydropower locations.

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he U.S. Department of Energy’s Water Power Technologies Office is funding the National Renewable Energy Laboratory (NREL) to create models for pumped hydro storage, an important tool for creating stability on the power grid. The models will enable researchers and policymakers to compare pumped hydro feasibility and cost with other energy storage technologies. Hydro Leader spoke with Stuart Cohen, a senior energy analyst at NREL, about his site and cost models, which will soon be plugged into the lab’s other energy models. Hydro Leader: Please tell us about your background and what you do at NREL.

Hydro Leader: Please tell us about NREL’s work on pumped storage hydropower. How do you view the importance of that technology?

34 | HYDRO LEADER | July/August 2022

Hydro Leader: One of the projects you’re leading involves site identification for closed-loop pumped storage. Is that something you were working on before the recent study by the Australian National University (ANU), or was it inspired by that study? Stuart Cohen: My original motivation for seeking funding to do this detailed pumped storage resource assessment comes from my work on the Hydropower Vision study. There was some discussion in that report of what pumped storage deployment could look like, but unfortunately, we had relatively poor data at the time for available pumped hydro resources; we just used Federal Energy Regulatory Commission applications to see where other people thought they could build sites and called that our resource base. As an analyst, I found that unsatisfying because there were a lot of inherent data inconsistencies and a lack of spatial coverage, so I started proposing a national resource assessment for pumped storage hydropower. This project was built off the algorithms ANU used to do the global pumped hydro energy resource assessment. The researchers at ANU ­­­­­­­ were helpful: They provided us with their code and helped us understand their algorithms and how to adapt them for the United States. We spent the last few years adapting those algorithms and doing a U.S.-focused pumped hydroleadermagazine.com

PHOTOS COURTESY OF NREL.

Stuart Cohen: I have been at NREL for about 10 years. My background is in mechanical engineering, but I focus on a broad range of energy systems analysis. My work is largely focused on optimization modeling of the electricity grid, primarily on the planning side, although I have also worked on operations modeling. Hydropower is one major focus, but I have also worked on things like the effects of climate change on the electricity system, energy economy interactions, and carbon policy analysis. I started working on hydropower right when I got here, running our Regional Energy Deployment System electric sector capacity expansion model for the U.S. Department of Energy Hydropower Vision study. I’ve been involved in hydropower-related projects to some extent ever since.

Stuart Cohen: At NREL, we’re in the business of doing objective analysis to understand a sustainable energy future, and so we consider all technologies and think about everything that’s on the table. We’re well known for our research on wind and solar, but hydropower and pumped storage hydropower can play a role, particularly in being a more flexible, dispatchable technology that can help integrate variable renewable energy. We do a lot of research on batteries, but we also recognize that pumped hydro is an established technology that has the potential to store energy for longer durations. We’re interested in exploring that; it’s another piece of the puzzle for a sustainable energy future. My work is focused on developing and integrating improved data on pumped storage hydropower resources and cost. I integrate those data into our energy models so that we can see how pumped storage competes with other technologies in our least-cost optimization analysis tools. We need to understand how it fits as we look into the future and think about how the grid could operate.


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