On a road trip 15 years ago, Clayton Barrows passed by the National Renewable Energy Laboratory (NREL) and thought out loud about pursuing a meaningful career in power systems modeling at the lab. Today he is the group manager of Grid Operations Planning in NREL’s Grid Planning and Analysis Center.
Earlier this year, he celebrated two career milestones: his 10-year anniversary at the laboratory and the official debut of Sienna, an open-source ecosystem for the comprehensive simulation and optimization of modern energy systems.
Here he reflects on how his research interests have enabled him to play a role in transforming energy and how NREL modeling and analysis innovations like Sienna support climate resilience in Puerto Rico and beyond.
First, congratulations on celebrating 10 years at NREL! What led you to Colorado and specifically to NREL?
I grew up in Wyoming, so Denver is close to home. When I was just starting my Ph.D. at Penn State, my wife and I happened to drive through Denver on a break from grad school. I pointed to NREL and said, “If I could get a job there, that would be a good reason to have embarked on this Ph.D.”
As I was nearing the end of my Ph.D., I presented at a conference, and Paul Denholm was in that session. I had read several of his papers and followed his work, some of which I built on during my Ph.D. So I approached him and [asked about] job opportunities. A week later, I had an interview, and a week after that, I had an offer.
What do you like about NREL? And outside of work, how do you make the most of living in Colorado?
I like that we are doing cutting-edge science and solving very relevant problems. And I really like the culture. I like the fact that we have a very open and transparent research culture and a very accepting and dynamic workforce.
Outside of work, I enjoy mountain biking and skiing with my wife and two boys, who are 5 and 7. Living close to the lab allows us to minimize our driving and enjoy the Colorado climate by getting around on bikes for most of our day-to-day activities.
How do you talk to your kids about what you do and why you do it?
I point at the power lines and say, “That’s what I think about—how to put electricity on power lines and get the energy they provide to the people who need it, and do it without burning coal.”
How does that connect to your decision to focus on power systems modeling?
Wyoming is an economy built on energy, and I grew up in Laramie, which isn’t an energy-centered economy. But the funds that made Laramie and the university prosperous all come from energy extraction, so it was very clear to me what role the energy industry plays in people’s lives.
I also saw the bad parts of the energy industry—the destruction associated with it and the sole reliance on it in the state economy. And as an electrical engineering student, I ended up focusing on power systems even though it wasn’t a popular major in electrical engineering at the time.
That was quite fortuitous, because as climate change became more and more of a hot topic, ways to address it started to center around power systems and electrification and renewable energy production.
Are you able to see how your work at the U.S. Department of Energy’s (DOE’s) NREL has an impact in the real world?
I like to keep a balance of more basic method development work and applied work in my project portfolio. I find the applied work gives me opportunities to interact with people who are on the ground operating systems and dealing with real issues in this energy transition. That enables us to identify the most relevant features and capabilities to work on, and then we can go back and develop those methods in ways that solve real problems.
I’ve recently been working on the Puerto Rico Grid Resilience and Transitions to 100% Renewable Energy Study (PR100), where there’s a lot of interaction with the stakeholders and the utility. And it’s very clear where the results of our analysis are going to lead. The smaller-scale applied work that has more direct, tangible outcomes can be especially valuable because you can really dig into the details that matter.
I get a lot of value from the applied work, and a lot of the reason I’m doing it is so I can make sure I’m building methods and tools that can help other people do more applied work.
On the method development side, what is one of the biggest challenges you’ve had an opportunity to address?
I’ve been fortunate enough to get support from NREL, and to some extent DOE, to develop a set of open-source tools [previously Scalable Integrated Infrastructure Planning], now named Sienna, that has a lot of new methods, capabilities, and modeling tools. And one of the biggest challenges has been building the tools so they can be used by other people. And then getting other people to use them.
We’ve started to see an enormous uptick in usage in the last year or so, but that was really, really hard for a long time. A lot of that is because people are very comfortable with what they use day to day. There’s a really strong sentiment, even among researchers, that if you’re not using tool X or a specific calculation, you’re not using the best option.
Model validation is extremely challenging in our industry. A lot of the data is proprietary. A lot of the results are proprietary. So it’s not like there’s something that’s easy to check it against. You don’t have real-world experiments you can play with easily.
Trying to change the minds of colleagues and others in the industry—to demonstrate that not only can an open-source tool make those calculations, but it sometimes can do it more efficiently, or show that tool X itself has a bug in it—has been an uphill battle.
And it’s really rewarding when they come back and say, “Hey, actually, you’re right—that was really useful.”
What changes or shifts have enabled you to overcome those hurdles?
A lot of what we have built with Sienna has been driven by a few of us insisting we need to be able to understand exactly what we are doing with every simulation we run and then be able to reproduce it when we have new data or find bugs in the approach or the data.
Enabling that more programmatic workflow and more transparent approach to the modeling and analysis we do has been a hard-fought battle. There’s been a gradual recognition of the need to do our analysis in a more controlled and reproducible fashion. And we’ve made a lot of progress.
As you reflect on your decade here, what accomplishment are you most excited about?
Sienna, hands down. I’m very excited to see people using the tools we’ve built, to know the capabilities are second to none, and to get feedback that it’s working well and provides value.
I want to build tools people will use, first and foremost, and seeing other people use them is validating. It’s not just colleagues; it’s people outside the lab and around the world, and that’s really rewarding. I’m really proud of the team for coming together and producing some really amazing things.
How is Sienna a game changer in terms of NREL’s ability to support disaster preparedness or grid resilience?
With grid resilience analysis, one of the challenges is that in conditions where you need a resilient energy system, the system isn’t really working. And most of the power systems analysis and modeling capabilities in existence are there to model how well a system works or help make a system work well. They’re basically designed to model a working system.
In this context, Sienna’s value is that, with its flexibility and customizability, we can go in and adjust the methods we’re using to represent different things. Whether it’s scheduling, stability, power flow, or whatever the topic of analysis, we can adjust to use routines that are better suited to represent a degraded or nonoperational system.
And then we can move forward with decision support analysis to learn how to improve it.
How can Sienna help solve even bigger, more complex resilience problems better and faster as the climate crisis intensifies?
There’s a real need to create more climate data for energy systems analysis. And we need to be able to use that data in the tools that support that analysis.
With Sienna, we can easily scale and evaluate tons of scenarios using cloud or high-performance computing resources without worrying about license access or having to go make changes in a cumbersome software environment. You can write scripts and deploy simulations at scale quickly and efficiently. And then there are lots of opportunities with stochastic optimization and understanding the uncertainty with new formulations.
How have modeling and analysis innovations like Sienna increased NREL’s impact?
One way Sienna has increased NREL’s impact is by improving the transparency of our modeling approach. We’re able to better understand the details of the simulations we’re running. And we can create new representations of battery operations or other technologies with more confidence and then provide that transparent approach to external stakeholders along with the tools to reproduce it on their own systems.
When you think about NREL’s work over the past decade, what makes you most hopeful?
The thing that makes me most hopeful is that time and time again our results from our forward-looking studies have ultimately come to pass and been quite accurate. I’m hopeful because we’re good at what we do.
Learn more about how Sienna and other NREL modeling tools and approaches support the transition to resilient energy systems. Additionally, learn more about Sienna in our overview video.
By Karen Petersen
Originally published on NREL website.
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