In the renewable energy industry, like many others, everyone’s talking about how recent innovations in generative artificial intelligence (AI) could be a key driver of change and progress. With its momentum showing no signs of slowing down, those who aren’t prepared to leverage this technology risk being left behind.
As we work to harness AI to accelerate the global energy transition, it’s important to start with an understanding of its capabilities and what is needed to reap its benefits.
Our first Ask an Expert video series, “AI Explained,” tackles just this. In the three-part series, Steve Voss, Power Factors’ VP of Advanced Analytics, gives us his definition of AI, explores how AI could benefit renewables, and explains the critical role of large datasets of trustworthy data.
Steve starts with the basics: defining what we mean when we talk about AI as well as the technologies and applications AI encompasses. AI can refer to different things depending on who you’re talking with. Some use it to talk about futuristic “science-fiction” artificial intelligences that match human intelligence. We’re not there yet.
For now, Steve’s definition of AI is more down to earth: AI is a versatile toolkit that includes machine learning (ML), good old-fashioned AI (GOFA), and generative AI. Essentially, AI is the combination of data, analysis, and automation to perform a given task or provide a given piece of information.
Watch part one of the AI Explained video series “Demystifying AI for Renewable Energy” for a more detailed breakdown of the types of AI.
Part 1: AI Explained: Demystifying AI for Renewable Energy
With all the hype around AI, it’s easy to think it’s the solution to every problem we face in renewables. But it’s helpful to remember what Will Troppe, our Director of Product, said in a recent blog post: “Recent advances in AI mean that it can do more than it could before — it can solve more problems in our industry and is the right tool for more jobs than before. But, like a hammer, AI is a tool. To a hammer, every problem looks like a nail. It is foolish and fatal to apply a tool incorrectly or where a different tool would be wiser.”
The key to using the AI toolkit effectively lies in making sure the necessary prerequisites are in place: things like working with vendors who have a proven track record of applying AI right, and who have access to large datasets of cleaned operational renewables data. It also looks like making sure the tool you’re using is a match for the task at hand.
Watch part two of the AI Explained video series, “Top Benefits and Risks of Renewables AI” to learn more from Steve about how AI is transforming renewables and the challenges we face as an industry when it comes to taking advantage of AI.
Part 2: AI Explained: Top Benefits and Risks of Renewables AI
When we at Power Factors talk about “AI for renewables done right” we’re talking about a few things.
First, it’s about our commitment to ensuring our customers can take advantage of the latest innovations in technology, now and into the future.
Second, it’s about our belief that a deep understanding of your data — both its quality and what the data you have access to can and can’t tell you — is essential groundwork when it comes to taking full advantage of AI.
Third, it’s about making sure our customers can see how the system arrived at its results, which builds trust and auditability into the analytics process.
Finally, our AI-powered insights and automations are informed by a real-world operational dataset from 260+ GW of managed assets. As Will Troppe said, “AI models are data-hungry; you’ll want to work with companies ready to feed them.”
Watch part three of the AI Explained video series, “AI for Renewables Done Right,” to learn more about how Power Factors’ approach to AI delivers tangible benefits to our customers and lays the foundation for a cleaner, brighter future fueled by sustainable energy.
Part 3: AI Explained: AI for Renewables Done Right
Interested in learning more about Power Factors’ approach to AI? Get a demo.