How Is Renewable Energy Stored? Batteries and AI | Intel Technology
- Hi, I'm Camille Morhardt, and today we have a prequel to our podcast. At the very end of the conversation I have with Jef Caers, he got sort of contemplative, and he said something that I think was really interesting. I just wanna let this play before we go into the interview. - Our field is starving for talent, and lots of talent goes into cybersecurity, or Facebook media, and then, when I give talks to engineer departments, then people are like, "Whoa, these are, like, really cool problems. I didn't know they existed," and I'm like, "Well, these are the problems that are gonna save the planet that you didn't know existed," because net zero, it has to save the planet. If it doesn't happen, we know what's gonna happen.
We see it happening today. If you live in California, it's 116 degrees in the Bay Area. That's never happened before. So, things are changing and net zero is the solution to that, but the plan to implement it isn't there either, and that's kind of where we need people to come and help us, because they have the talent. - [Announcer] Welcome to "What that Means with Camille," companion episodes to the InTechnology Podcast. In this series, Camille asks top technical experts to explain in plain English, commonly used terms in their field, then dives deeper, giving you insights into the hottest topics and arguments they face.
Get the definition directly from those who are defining it. Now, here is Camille Morhardt. - Hi, and welcome to this episode of "What That Means."
I have with me today, Jef Caers, who is a professor of Earth & Planetary Sciences at Stanford University's brand new Doerr School of Sustainability. He is gonna be talking with us about how we're using artificial intelligence to seek resources that we need to move into this new world of renewable resources. We'll get more into it. Welcome to the podcast, Jef.
- Glad to be here. - Okay, so I have to ask, Earth & Planetary Sciences, does this restrict you now from looking into resources on the Moon? - No, in our department, we're looking at the Moon, we're looking at Mars. Everything's very exciting, because studying other planets and planetoids is very interesting, also, understanding our own Earth and how it's formed. - Well, I forgot to mention, also, you're director of the Stanford Center for Earth Resources Forecasting.
So, what exactly does that mean? - We are a group of students and postdoc research staff, about 20 of us, and we're working on the general problem of exploitation of the Earth's resources, whether that's minerals, or water, or energy, and even subsurface storage, for example, like carbon, of course, CO2. It's gonna be very important in the future. - Okay, here's my first question.
Cobalt, what is it used for and what is the forecasted demand for cobalt? How is that increasing, and what is the known supply of cobalt in the world, and what are we gonna do about all those things? - That's a lot of questions in one, but it's a very good question to start with, I think. So, cobalt is used in the lithium ion batteries and, particularly, in the cathode, a particular element that is ideally suited for that in that combination. Right now, I'm not gonna go into the numbers, but suffice to say that we have a significant shortfalls of these, this one, if you think about dollars, $2 trillion from now to 2050, if we're thinking about changing over our vehicle fleet into electrical vehicles.
So, that's posing a significant challenge, particularly, on the supply side of course, and since cobalt is found only in few countries so far in large quantities, in fact, about 60% of the cobalt comes out of the Congo. That could potentially lead to conflict like we have had with oil and gas, and so, part of my research is to help increase that supply and increase that supply relatively fast, so that we can avoid all these problems that we've had with oil and gas, and, of course, that we don't wanna get with transitioning to renewable energies. - Probably, everybody gets it, but I just wanna make sure we're clear on why batteries are important as we move to renewables. Could you just talk a little bit about why they matter? - The problem with renewable energy, particularly, solar and wind, is their intermittency, and so, living out in California, yesterday was a big heat wave, so, electricity, man, goes up, and after four o'clock the sun goes down, and so, then everyone is supposed to turn off their air conditioning after four or five o'clock for that reason. So, this intermittency is something that we need to be able to deal with, and one of the ways to deal with it is storing the energy of these renewables into batteries, thereby being able to use that energy for our transportation, because even right now our electricity grid is not quite clean, it's still dirty. Natural gas is still being used, of course, particularly in California, and so, if you're charging your vehicle in California, that will be about 30% supply of renewables, but 70% is still non-renewable energy, and so, that's something that needs to change, and batteries are a key component for that for storing energy.
- Batteries for fixed usages like in buildings, and also for mobile usages like vehicles. - Yeah, so if we're talking about buildings, then, yeah, we will be installing batteries. For example, I'm going to get solar panels. In combination with that, I'm gonna have a battery in my garage. I have an electrical vehicle. The appliances that I have are all electric, and so, except for heating, I can live off the grid, so to speak, with only solar energy.
So, that is something that, more and more, is being encouraged, and, of course, the new bill that was just passed is also very much encouraged as also tax credits that are coming. It would certainly incentivize a person like me to go fully solar, and in San Francisco this is certainly possible. I think it's a great trend that we're going into. - I was shocked to learn that we're somewhere on the order of, like, 10 pounds of cobalt going into an electric vehicle.
- It's not just cobalt. I think that, often, the discussion goes on cobalt, because, of course, we hear about the Congo and the children mining the minerals, but there's also other metals that are very important, that is nickel. So, for example, nickel is a good second to cobalt in terms of a cathode material. Then we also need copper if we're going to build more wires, and chargers, and things like that, and, of course, we also need more lithium, and it seems to me that the real supply crunch, reading up on what the companies have to say about the mining companies, battery companies, and car companies is gonna hate us around 2030, 2035, because we know that a lot of countries and corporations have promised us, that by 2030 or 2035, we should be going EV, for example, in California, you'll not be able to buy an electrical vehicle in 2035. Most European countries will be fully EV by 2035, so that is not just a supply crunch on the cobalt side, but also, on the nickel, and the lithium, and the copper side, so it's not just about that one particular element.
- Okay, now we come to the, what are you gonna do about it? (laughing) - Yes. Well, there is a simple solution, and the simple solution is to find more. So, what we want to do is to speed up the discovery of minerals, of these particular minerals, and in over the last I would say 10 to 20 years, there's actually been a decline in the discovery of these minerals, and that has a lot to do with the fact that the easy minerals or easy deposits have been found, the ones that you can see on the surface. So, we're now looking underground with no or little surface exposure, so it becomes much harder to do, and so, we're also gonna have to do it faster, and so, that's where AI comes in, because a traditional way of mineral exploration is still very manual and expert driven, a geologists goes on the field, studies rocks, comes back, analyzes those rocks, makes models, and, usually, as one or two people, and, of course, if you're needing this supply over the long-term, that's not gonna work. So, we need to increase this discovery rate, which also is very important in mitigating conflicts or other things. - Interesting, because one of my best friend's fathers, when I was growing up, was a geologist for a major oil company, and flew all over the world, and made these predictions.
He was that, what you just described. - An exploration geologists. - Why is AI better? How is it going to work? - For one, it's not used today at all by major mining companies. So, I collaborate with startup company called Cobalt Metals, and that company is founded with the idea of using artificial intelligence to speed up discovery. So, there are a number of application areas that we have to talk about, I think, with regard to what this AI does.
One of the major problems with mineral exploration, as oil and gas exploration, is that you need to try a lot to find something, because if you're looking for an ore body, for example, in a subsurface, well, lots of things look like an ore body, they're mimicking like an ore body, and so, you're thinking you have something, but in reality there's nothing there. So, we call that the false positive problem, and so, right now the false positive rate is about... I mean, the discovery is about one in 200 times trying, so we need to speed that, we need to create that, and go down to maybe one in 50 times trying, and so, that means, number one, we have to look at more data faster, and also use decision signs, and artificial decision signs, intelligent decision signs in order to make better decisions. Rather than have an expert person making one decision at a time, now we need to leverage this massive amount of data that we have over the entire planet, and make better decisions related to that, how that data can be used in mineral exploration. So, that's kind of a broad overview of what is needed. - So, with the AI exploration techniques that we're using, are they going to come with incremental advances or are you expecting some kind of a breakthrough advance after gathering a bunch of data? - I think we're tuning these AI to the current experiments that are running, because we've just started programming this AI.
We're exploring in in Australia, in Zambia, in Greenland, and all these places, and I think once we kind of hit the way to do it, then it explodes, and you can use it everywhere else, because the way it's is set up is general. We don't hope it's incremental. We hope that it does explode out and discovers much more in a short amount of time. - Jef, are you optimistic? - I'm pretty optimistic, yeah. I've seen already the first results and the company has been achieving in two years what a normal mining company would achieve in 10 years. They haven't necessarily discovered deposits, but they have found what we call vectors towards deposits.
That means indications to where to go next, but it's still a slow process. You have to fly to northern part of Canada, Quebec, and you go in the summer, and there's helicopters involved, and there's fuel involved, and there's so much involved. It's not just sitting on your desk and programming in it. There's a lot of people stuff and moving stuff involved as well. - Yeah, you have to go validate the-- - Yeah, you have to go and drill. - What are you worried about in this conversion to AI? Are there any kind of major concerns? Do we have enough data to even feed into the model at this point? - So, that's one of the major questions.
We don't have enough data to feed into the models. So, our AI that we are developing is not an AI that uses data, but determines where and how to acquire data. So, this is an AI that can decide where in the world or what techniques should be used in order for that to do that, and that's not a single decision.
We call that a sequential decision, because it's not gonna be in one step. You're not gonna drill one borehole, and say, "Hey, it's great, or it's bad." No, it's gonna be multiple of these steps, and so, artificial intelligence is really great at solving problems like that, like self-driving car problems, these are similar problems, or chess playing problems. These are problems where you need to make sequential decision after decision in an uncertain world, an uncertain environment, and so, that's the kind of techniques that we use to do that. So, in a way, it's a very data sparse problem rather than what we are used to hearing about machine learning and deep learning as a very data dense problem. Now here's the opposite.
We need AI to decide what the data should be, and that is where the acceleration takes place, because right now it's just one person deciding that. - And how do you get there? - How do you get there? It's a lot of computer programs and a lot of computer modeling. So, what we're basically doing is we're kind of modeling the future. It's like we're saying, if I would be taking that data, what would that effect be? How would that, for example, reduce uncertainty, how much grade there is or how much volume of order there is? And so, predicting how data will affect our uncertainties is really key to addressing this false positive problem. If you don't understand uncertainty really well, then you're thinking there's something there, and so, you will go, and go out and collected data.
Well, it turns out, well, that's a waste of time. It's this data you shouldn't have collected, time you shouldn't have spent, and so, that's where we can improve. We save money and we make it faster. - I have so many questions, I don't really even know where to start.
I guess one of the questions is we need more of these resources, and surely, hopefully, there are more on the Earth. (Camille laughing) And we just have to find them, but I'm wondering about the other way to solve the problem, which could be design batteries differently or synthesize material as opposed to finding raw material. What's going on in those areas? - There's always future technology that's gonna be better and certainly for batteries, there are potential other ways of doing batteries. Lithium seems to be always within the area, but we have to also realize that the CO2 problem has to start to be addressed today. We can't wait for 10 years in the future to design a better battery. So, we are emitting CO2 in the atmosphere today at large quantities.
We're not leveraging enough solar and wind power, and so on, so we have to build that out right now, and the best technology right now is the lithium ion battery. There will probably be better batteries down the future, be it, if we're talking about solid state batteries and other types of batteries that require less of these materials, but at the same time, we are gonna use copper, we're gonna use nickel, and we are going to use lithium. Maybe we can mitigate somewhat the cobalt, but still, we have to do what we can today, and then work toward the future to hopefully design things that require less of these very sparsely distributed materials.
- I guess the only other approach I could think of offhand would be having some way to, you say the problem is intermittent, I guess, the only other thing would be to switch to ones that aren't intermittent like ocean tides. - Yeah. - Or to switch to an ability to shift power sources depending.
So, you have multiple inputs coming to one household, or something, and I'm gonna use solar, wind, or wave, or whatever there is. - Wave energy is very expensive. So, one of the great things about solar and wind is it's very cheap. In fact, solar is beating almost all other types of renewable energy.
The other that are less intermittent are hydro power, pump hydro, as well as geothermal. So, also work on the area of geothermal energy, and there, you're thinking about geothermal is almost constant and if we could drill deep enough to say 20 kilometers deep, which hasn't been done by the way, then we would've access to an infinite source of energy. - Did you say hasn't been done or has? - No, it hasn't been done. So, I think the deepest well goes to about three to four kilometers, but people are working on technologies for drilling, using laser based drilling rather than rotary bit drilling, and so, again, those are things that are probably gonna be here in 10 years, but in those 10 years, we're going to have made a lot of CO2, if we don't do anything, and that's why I think the current technology needs to be used right away.
Another option for the intermittency is, of course, hydrogen, is to use solar and wind to create hydrogen. Now hydrogen is created using, for example, electrolysis, and that requires platinum and palladium, so, where you need more metals. It's, like, not free. Hydrogen is still very expensive, and, again, will be something that will probably be in the future, maybe in a decade from now. It depends on how fast we develop that.
There's also issues in transportation with hydrogen, but it's definitely a fuel that's in the future, and I was thinking that we need to bet on all the horses here. I think if we start picking winners and losers, we may actually lose out on a winner, and so, I'm kind of betting on all the horses right now, and seeing what develops as the best option, and we are going to have to use energy in various forms. If you think about heating your house, that's not gonna work with batteries, that's not gonna work with hydrogen, so, there are already people thinking about geothermal? That means just using, if you have a pool in the backyard, or you have a groundwater system under your house, most people in Europe are starting to look into that, and the United States isn't as developed yet, but these are almost free forms of energy. - Talking about betting on the horses, are people in different parts of the world emphasizing different kinds of renewables? - Yeah, because it really depends on your geography. The United States is a very big, widely spread country. So, having one energy system for one area or for the whole country may not make a lot of sense.
Climatic, of course, it's also very important. Are you in a solar area in the west of the United States where solar is just so available? Wind is so available, so that's great for us, but if you live in Norway, that would be less so, but Norway has hydro, pumped hydro, so they have a lot of fjords, and things like that, so, also, we have to develop, I think, strategies that work for different areas of the world, and that would be different. - Do you think we'll be moving to more distributed grids or even, like, individual grids? - I'm not too familiar with the electricity grid. I do know from colleagues that our electricity grid is woefully inadequate at this point to deal with this renewable revolution, simply, because we're going to rely much, much more on electricity for our energy consumption, and so, that requires building a very different grid, a smarter grid, and things like that.
So, I'm not expert at that, but I know it's inadequate. - You mentioned some of your colleagues are looking at the Moon and Mars. - Yeah. - What are they looking for? Do they have a specific target in mind? - Well, yeah, so, of course, we are looking whether there was life. It's also an exploration problem, and I sometimes talk with my colleagues, and they say, "Hey, I hear you're working on mineral exploration using AI. What about Mars life exploration using AI, why not?" So, yes, for example, one of the projects...
I've had one student in my class once, that said, "Well, I have this rover on the Moon, and rovers can take three samples to discover water," and that would be interesting to know, if you've seen the series "For All Mankind," and it's very popular right now. It's also about finding water on the Moon and finding water on Mars, and so, knowing where to go, and where to take the samples, and what order to take the samples, and what data to use in order for you to better take the next move, take the next move, because, again, it's a problem where, probably, you have to drill a lot of times in order to find the water or evidence of life. So, again, I think AI is a natural solution there to improve the exploration endeavor. - In that case, you would be telling the AI that you want to find evidence of water-- - Right, exactly. - Not life,
because we've got a whole bunch of negatives on that data labeling-- - Yeah. - If we're looking for life. (laughing) - There's no data, there's no labels yet, so it's an unsupervised problem in a way is that, again, it's a problem of what data to collect, and there's a lot of data already, but it's remote sensing data. It's from circling around the Moon, and we take the temperature of the Moon, and, of course, you would look in a crater where there's a shadow, that's where you look for water, and so, but again, it's the same, like in mineral resources we have geophysical data, which is also data acquired by flying around the planet, but we don't have any subsurface data. When you do exploration, the problem is there's no labels, there's only unsupervised indirect information. - So, what else do we need to know? What else is important in your field that people are sort of arguing over, talking about, or worrying about? - I think what's very important is to start thinking about the human aspect and impact of what this mining revolution or renewable revolution is going to be.
Although people talk about green energy, most energy does require materials. Solar wind requires steel and all kind of other materials, copper, and so, those materials are going to be excavated in certain parts of the planet, and I think, right now, the process of how to include the communities that would live around these future mines, that process almost doesn't exist, and we're looking, specifically, in the continent of Greenland, because Greenland, the ice is melting, and it's exposing a lot of interesting outcrops for rare earth elements, and so, nickel, cobalt, copper, but, of course, people live there, and even though it's only 50,000 people, we can't just say, "Hey, move, and we'll come and dig up and destroy the whole continent." That's not what we want to do either. So, one of the things that I wanna work on, and that needs to be worked on is how you can start engaging the communities that live there into the development of any mines, or deciding, "Well, maybe this is not a good area to be mining," for these and these reasons.
So, right now those communities are often largely ignored, or what would happen is that mining companies would visit them, and they would have an info session, a 45 minute info session, and then walk away, and say, "Yeah, we did our work info session." So, that's something I wanna change too, is that one of my group, we're starting to develop with anthropologists, social anthropologists to develop ways of communicating, developing strategies for better including communities in the development process, and I think that has to start from mineral exploration, because once something is found, the pressure to mine is very hard, because, okay, it takes a lot of money to find it, and then, now we have this potential $10 billion profit lying in front of us, so there's a lot of pressure to do that. So, we wanna also look at, "Hey, if you're gonna explore in these and those areas like Greenland, what does that imply for the population?" If you would be starting mining over there, that may actually help exploration companies in thinking about how and where they would be exploring, because we don't wanna build our new economies on the back of native communities or other disadvantaged communities, and that's something that needs to be addressed as well, and that's something that, actually, in the school of sustainability is something that we wanna build more and more in that is this kind of environmental justice, these environmental issues, to put that in with the science as well. It's not just about the science and the AI, it's also about the human impact and how we do we understand that. - Thank you, Jef Caers, who is Professor of Earth & Planetary Sciences in Stanford University's new Doerr School of Sustainability. Thank you for talking with us today.
- It's been a pleasure to be here. - [Announcer] Never miss an episode of "What that means with Camille" by following us here on YouTube, or search for InTechnology wherever you get your podcasts. - [Announcer] The views and opinions expressed are those of the guests and author, and do not necessarily reflect the official policy or position of Intel Corporation. (upbeat music)