WEBVTT - AI Data Centers: Making Waves in the Energy Demand Sea 0:00:00.360 --> 0:00:02.719 This is Tom Rowland's Reese and you're listening to Switched 0:00:02.759 --> 0:00:07.240 on the BNF podcast. Today we're discussing BNF's new Energy Outlook, 0:00:07.280 --> 0:00:10.160 our annual flagship report that represents our long term energy 0:00:10.160 --> 0:00:13.000 and climate scenarios for the transition to a low carbon economy. 0:00:13.280 --> 0:00:16.360 AI data centers have dominated conversations in the clean energy 0:00:16.360 --> 0:00:19.360 sector of late, with forecasts varying wildly over just how 0:00:19.400 --> 0:00:22.120 much extra load there set to place on already strained 0:00:22.160 --> 0:00:24.960 power grids. As with every hot button topic, comes the 0:00:25.040 --> 0:00:28.120 risk of hype versus reality. While data center energy demand 0:00:28.160 --> 0:00:31.440 is unquestionably growing at speed, it currently represents just one 0:00:31.480 --> 0:00:34.120 point four percent of global power demand and only around 0:00:34.159 --> 0:00:37.600 two percent of that figure is actually consumed by AI facilities. 0:00:37.960 --> 0:00:40.600 The demand itself is also uneven, with some regions like 0:00:40.640 --> 0:00:43.440 the US needing significantly large amounts of power than others. 0:00:43.520 --> 0:00:45.040 And when it comes to meeting the needs of these 0:00:45.120 --> 0:00:48.120 energy intensive facilities, can the development of clean power sources 0:00:48.159 --> 0:00:50.559 even be done at the scale and pace required. To 0:00:50.640 --> 0:00:53.080 learn more about the forecast for data center energy demand, 0:00:53.120 --> 0:00:55.680 I'm joined by b and EF's head of Energy Systems Modeling, 0:00:55.720 --> 0:00:58.440 Ian Berrman to discuss findings from the twenty twenty five 0:00:58.640 --> 0:01:01.360 edition of our new Energy Outlook. BNF plans can find 0:01:01.360 --> 0:01:04.000 the full report at BNF go on the Bloomberg terminal 0:01:04.080 --> 0:01:06.160 or on BNF dot com, and if you're not yet 0:01:06.160 --> 0:01:08.399 a client, you can also download the executive summary at 0:01:08.440 --> 0:01:10.840 BNEF dot com. All right, let's get to talking about 0:01:10.840 --> 0:01:20.959 the impact of data centers on this year's NEO with Ian. 0:01:23.000 --> 0:01:24.600 Ian. Welcome to the podcast. 0:01:24.840 --> 0:01:26.839 Thanks Tom. So Ian has. 0:01:26.760 --> 0:01:27.880 Been on this podcast before. 0:01:27.959 --> 0:01:31.280 We had a freewheeling discussion around the power system as 0:01:31.280 --> 0:01:35.520 a whole. He had this crazy metaphor involving multiple people 0:01:35.720 --> 0:01:38.280 on like a bike, I mean, as in millions of 0:01:38.280 --> 0:01:40.520 people all on the same bike like this is not 0:01:40.560 --> 0:01:44.200 a very relatable metaphor. But okay, I got more messages 0:01:44.240 --> 0:01:47.800 on LinkedIn saying what a great episode after that particular 0:01:47.840 --> 0:01:50.680 one than I've ever had before, So I'm sure this's 0:01:50.680 --> 0:01:52.000 gonna be a fascinating discussion. 0:01:52.360 --> 0:01:53.440 I'm going to talk about NEO. 0:01:53.960 --> 0:01:57.680 So Ian tell us about NEO, which is obviously something 0:01:57.720 --> 0:01:59.800 as well that we hype a lot at BNEF, but 0:02:00.160 --> 0:02:01.920 so spell out what any means for those of us 0:02:02.000 --> 0:02:03.080 that are not familiar with it. 0:02:03.720 --> 0:02:07.440 NEO is the New Energy Outlook and it's benef's flagship publication. 0:02:07.800 --> 0:02:11.840 It's our house view on the future of the energy transition. 0:02:12.440 --> 0:02:15.280 We've been publishing it for many, many years now, since 0:02:15.320 --> 0:02:17.920 before I started, so seven or eight years ago, and 0:02:18.120 --> 0:02:21.040 in some ways it's the culmination of everything we do 0:02:21.080 --> 0:02:23.760 because we are looking at the entire energy transition. We're 0:02:23.800 --> 0:02:26.160 bringing in work from all our colleagues and all the 0:02:26.240 --> 0:02:29.800 various different sectors that touch on that into one comprehensive 0:02:29.960 --> 0:02:32.280 and coordinated house view on the. 0:02:32.200 --> 0:02:33.519 Future of energy and the transition. 0:02:33.919 --> 0:02:36.840 Awesome, and so I kind of have this view of 0:02:36.880 --> 0:02:40.200 it as this it's like an orchestra and we're pulling 0:02:40.240 --> 0:02:43.720 together everything that BNFS done in this coordinated way. And 0:02:43.800 --> 0:02:46.040 so where do you sit in this? AREI the composer, 0:02:46.160 --> 0:02:48.799 the conductor? Are you the star violinist? 0:02:50.040 --> 0:02:50.480 How do you read? 0:02:50.600 --> 0:02:52.080 Why is it that I'm talking to you on this 0:02:52.120 --> 0:02:54.720 podcast and not someone else? That's a good question. I'm 0:02:55.000 --> 0:02:56.840 I'm trying to figure out where to go with this analogy. Now, 0:02:57.360 --> 0:03:00.000 I'm definitely not the conductor that would be my boss. 0:03:00.400 --> 0:03:02.440 Do I make the instruments? Possibly? 0:03:02.720 --> 0:03:03.959 Possibly I write the music. 0:03:04.280 --> 0:03:07.079 Maybe that's that's the way so I sometimes will play 0:03:07.120 --> 0:03:09.959 along in an instrument when when and where I'm needed. 0:03:10.040 --> 0:03:12.240 But the Energy Systems modeling team, which I head up, 0:03:12.240 --> 0:03:14.720 our role is to work on the models which go 0:03:14.760 --> 0:03:17.120 into producing this. So I guess, I guess we make 0:03:17.160 --> 0:03:18.959 the instruments that other people play well. 0:03:19.240 --> 0:03:21.280 I feel like I mean, Firstly, obviously the people who 0:03:21.320 --> 0:03:24.240 make the instruments are fundamental to the orchestra, even if 0:03:24.240 --> 0:03:26.600 they don't get the limelight. So maybe I'm glad we're 0:03:26.600 --> 0:03:29.080 having you on this podcast so you can get your flowers. Finally, 0:03:29.240 --> 0:03:31.160 I feel like you might be being a little modest 0:03:31.280 --> 0:03:35.040 because the music that we create with NEO, I think 0:03:35.320 --> 0:03:38.440 very few people understand it in its completeness more than 0:03:38.480 --> 0:03:40.080 you do, which is which is why we have you 0:03:40.120 --> 0:03:43.760 on today. So Neo, it's this outlook to twenty fifty, 0:03:43.800 --> 0:03:45.240 a comprehensive look at everything. 0:03:45.560 --> 0:03:46.800 And obviously, if we're going to. 0:03:46.840 --> 0:03:50.040 Do that every year and just update our view on 0:03:50.080 --> 0:03:53.360 a twenty five year twenty five year plus forecast, it's 0:03:53.440 --> 0:03:55.960 not you know, you question why we're doing it, because 0:03:56.120 --> 0:03:58.000 not that much can Chette have changed or how we 0:03:58.000 --> 0:04:00.800 see twenty fifty between one year and the next. So 0:04:00.920 --> 0:04:03.800 we always do new things to kind of keep it fresh, 0:04:03.840 --> 0:04:06.120 keep it interesting, have some other insight to say. 0:04:06.240 --> 0:04:08.800 So this year, what would you say the focus was? 0:04:09.200 --> 0:04:11.440 So this year, which is probably not going to surprise 0:04:11.480 --> 0:04:14.720 anyone that's listening, the hot topic has been data centers 0:04:14.760 --> 0:04:18.320 and AI, so we went away. We developed our own 0:04:18.320 --> 0:04:22.599 in house short and long term forecasts for electricity demand 0:04:22.600 --> 0:04:25.200 from data centers and AI. That's a big feature in 0:04:25.240 --> 0:04:29.080 the report. We refreshed our entire base case, which we 0:04:29.120 --> 0:04:32.520 call the economic Transition scenario, which is not exactly a 0:04:32.520 --> 0:04:35.560 business as usual scenario. And it's probably worth unpacking that 0:04:35.760 --> 0:04:39.080 very briefly because I think economic Transition scenario really reflects 0:04:39.120 --> 0:04:42.560 what makes I think NEO unique and BNF's approach to 0:04:42.640 --> 0:04:45.560 producing this type of global analysis unique, And what makes 0:04:45.560 --> 0:04:48.080 the Economic Transition scenario unique is that we're taking an 0:04:48.080 --> 0:04:51.240 economics led approach, and we're doing this informed where we 0:04:51.320 --> 0:04:54.800 can by bottom up modeling, so very detailed and granular modeling. 0:04:54.880 --> 0:04:57.240 And when we say we're putting economics in front, that 0:04:57.279 --> 0:05:00.040 means we're trying to strip out policy, particularly if that 0:05:00.040 --> 0:05:03.360 that's aspirational, any sort of targets which are non binding, 0:05:03.400 --> 0:05:05.920 et cetera. And we're really trying to hone in on 0:05:06.000 --> 0:05:09.320 the technology and economics story, and that this leaves us 0:05:09.320 --> 0:05:12.000 with a story where economics are in the driving seat 0:05:12.080 --> 0:05:13.520 and technology is a story. 0:05:13.800 --> 0:05:16.279 Right, it's almost I mean, this is a fair way 0:05:16.320 --> 0:05:19.960 to describe it. What we're painting there is a picture 0:05:20.000 --> 0:05:23.320 of a world that follows what we would consider to 0:05:23.360 --> 0:05:28.600 be an economically rational ideal without the interference of inconvenient 0:05:28.720 --> 0:05:33.479 human beings who are either pushing for more low carbon 0:05:33.520 --> 0:05:38.720 technologies to reflect the challenges or the crisis should say 0:05:38.720 --> 0:05:43.279 of climate change or other ideologies, or one could even 0:05:43.320 --> 0:05:46.080 say global dysfunctions that can get in a way of 0:05:46.160 --> 0:05:47.760 maybe that pure economic vision. 0:05:48.120 --> 0:05:48.800 Yeah, exactly. 0:05:48.839 --> 0:05:54.000 And policy can push to carbonization faster or slower than 0:05:54.080 --> 0:05:57.240 what the economics would tell you is least cost. And 0:05:57.279 --> 0:05:59.680 as soon as you try and produce like a four 0:05:59.760 --> 0:06:03.040 car if you will, and you're making judgment calls on 0:06:03.120 --> 0:06:06.600 what policies are announced, when, how long they last for, etc. 0:06:07.200 --> 0:06:10.680 You're really putting your analysis on shaky ground. So by 0:06:10.800 --> 0:06:13.640 focusing on that economic store, it's always useful to know 0:06:13.680 --> 0:06:15.599 what the least cost system is, even if you don't 0:06:15.640 --> 0:06:17.080 know what politics are going to be. And I don't 0:06:17.120 --> 0:06:18.839 think many of us know what politics are going to 0:06:18.880 --> 0:06:19.960 be at the moment. 0:06:20.279 --> 0:06:24.560 We do forecast some sort of human I say, brilliant 0:06:25.279 --> 0:06:27.240 if I might, in terms of we look, we do 0:06:27.279 --> 0:06:30.360 take into account cost declines of technology and the sort 0:06:30.360 --> 0:06:35.200 of technological progress we expect to have happen. But we yeah, 0:06:35.240 --> 0:06:39.119 we don't forecast the politics. We don't forecast either people 0:06:39.160 --> 0:06:41.960 being able to miraculously get on the same page. And 0:06:42.000 --> 0:06:45.359 we don't forecast in which particular way people are dividing 0:06:45.400 --> 0:06:48.280 among themselves and tearing each other apart, which is obviously 0:06:48.279 --> 0:06:50.600 impossible to forecast. So it's kind of like a north 0:06:50.680 --> 0:06:51.920 star in a certain sense. 0:06:52.279 --> 0:06:54.080 North starts a good way to put it, and may 0:06:54.080 --> 0:06:55.760 I also don't want to give people the impression that 0:06:55.760 --> 0:06:58.400 it's sort of too cold and rational and is not 0:06:58.560 --> 0:07:01.200 based on the real world necessarily. And I think that 0:07:01.320 --> 0:07:03.520 there's two main reasons why that's not the cases. First, 0:07:03.760 --> 0:07:05.680 I mean, from our sector teams, we do have a 0:07:05.760 --> 0:07:08.200 very good handle on what we think will happen in 0:07:08.320 --> 0:07:11.320 the next at least at least five years for most sectors. 0:07:11.600 --> 0:07:14.360 We've got huge project databases that BNF is very very 0:07:14.360 --> 0:07:17.520 famous for renewable assets and other types of asset classes, 0:07:17.560 --> 0:07:20.119 so we know what's coming and that feeds into the model, 0:07:20.120 --> 0:07:22.480 and it's sort of there's a transition away from what 0:07:22.720 --> 0:07:24.880 is known and fixed in the short term for the 0:07:24.880 --> 0:07:26.880 next few years, and then what the model proposes to 0:07:26.920 --> 0:07:29.520 do after that, and that's sort of a gradual transition 0:07:29.600 --> 0:07:30.800 and handover in the results. 0:07:30.920 --> 0:07:31.880 And then also, not. 0:07:32.080 --> 0:07:36.440 All sectors that we model are as rational, as for example, 0:07:36.480 --> 0:07:39.520 the power system, and so I mean consumer behaviors in 0:07:39.920 --> 0:07:42.520 important part of how we model our ev uptakes. So 0:07:42.640 --> 0:07:45.480 that's just one example of where it's not like completely 0:07:45.520 --> 0:07:50.520 without taking humans into consideration. But the focus is the economics. Ultimately, 0:07:50.560 --> 0:07:52.040 that's the story we're trying to tell. 0:07:52.240 --> 0:07:56.000 And my impression that that's complex enough as it is. 0:07:56.360 --> 0:07:59.440 I think that you said something interesting before the podcast. 0:07:59.640 --> 0:08:02.840 That is the number one kind of piece of feedback 0:08:02.880 --> 0:08:05.240 you get from clients about this is that they don't 0:08:05.280 --> 0:08:07.440 like a particular kind of charts. Tell me what kind 0:08:07.440 --> 0:08:08.280 of chart don't they like? 0:08:08.400 --> 0:08:10.840 Yeah, So I've been involved in here for a while now, 0:08:10.880 --> 0:08:14.200 and I mean, sometimes, well maybe this is feels like 0:08:14.240 --> 0:08:16.520 a couple of years ago now, but sometimes there's not 0:08:16.640 --> 0:08:19.760 big disturbances in markets, and things tend to tick along, 0:08:19.800 --> 0:08:21.680 and I feel like people sort of get used to 0:08:21.800 --> 0:08:24.320 charts and they can go up, they can go down, 0:08:24.360 --> 0:08:26.320 but they tend to be sort of like quite constant. 0:08:26.360 --> 0:08:28.960 They show a direction, they show a direction, which direction 0:08:29.120 --> 0:08:32.160 plays itself out in a way that you're like, okay, cool, 0:08:32.280 --> 0:08:33.160 so that's the trend. 0:08:33.520 --> 0:08:34.200 And yeah. 0:08:34.520 --> 0:08:36.400 I mean one of the charts that I've got the 0:08:36.520 --> 0:08:38.640 most questions about, or the general type of charts, is 0:08:38.679 --> 0:08:40.640 where that doesn't happen, where you'll have something that goes 0:08:40.720 --> 0:08:43.520 up and then it goes down and people immediately latch 0:08:43.559 --> 0:08:45.240 onto that and they're like, what's happening here? And I mean, 0:08:45.280 --> 0:08:47.160 I think that's part of what makes us a unique 0:08:47.160 --> 0:08:48.880 cause we try to do that bottom up modeling, and 0:08:48.920 --> 0:08:50.760 I think when you do that, you can see these 0:08:50.800 --> 0:08:54.240 sort of weird changes of directions occasionally in your results. 0:08:54.240 --> 0:08:56.360 I think if you're doing a trend based analysis more 0:08:56.360 --> 0:08:58.040 top down, you wouldn't see that at all. 0:08:58.040 --> 0:08:58.960 You would miss that. 0:09:00.040 --> 0:09:02.520 I'm always amazed by client's ability to hone in and 0:09:02.600 --> 0:09:05.839 identify those charts that change tackicy. It has come at 0:09:05.880 --> 0:09:07.160 me with questions. 0:09:06.880 --> 0:09:09.560 If you're been a f client, presumably by the fact 0:09:09.600 --> 0:09:11.920 that you even find our content useful. You do not 0:09:12.080 --> 0:09:16.199 fear change, but you might still fear change of change. 0:09:16.679 --> 0:09:19.280 And that's what those charts are, is like the change. 0:09:19.320 --> 0:09:22.400 We've got some change, and then the change changes, and 0:09:22.720 --> 0:09:23.800 that's a little bit weird. 0:09:24.080 --> 0:09:26.240 Yeah, I mean, it's probably usual to talk about a 0:09:26.240 --> 0:09:28.079 little bit. I mean, the main culport of this has 0:09:28.120 --> 0:09:31.240 been when you zoom out, our results are basically saying, 0:09:31.240 --> 0:09:34.200 if you look at US gas demand, we see a 0:09:34.280 --> 0:09:37.719 decline until twenty thirty and then growth again, and sort 0:09:37.760 --> 0:09:42.000 of people immediately what's behind that, And it's not a 0:09:42.040 --> 0:09:44.960 super complex idea to unpack. Essentially, what we have today 0:09:45.160 --> 0:09:48.880 are many parts of the US where we're still building renewables, 0:09:48.880 --> 0:09:51.600 and renewables are still in the money, and that expansion 0:09:51.640 --> 0:09:55.640 of renewables continues, and so there's some displacement of natural 0:09:55.679 --> 0:09:58.480 gas demand in the power system towards twenty thirty. But 0:09:58.520 --> 0:10:01.720 then around twenty thirty at least when we've modeled this 0:10:01.760 --> 0:10:03.160 to the last year or two, I mean, the whole 0:10:03.200 --> 0:10:05.720 system is moving so equally. Reinpoints the wrong sort of 0:10:06.040 --> 0:10:08.880 terminology here, but we sort of reach a penetration level 0:10:08.920 --> 0:10:11.840 of renewables where the system struggles to move past that 0:10:12.000 --> 0:10:15.080 and so post twenty thirty, what happens. We still build renewables, 0:10:15.280 --> 0:10:17.800 but what you see is the whole system is getting bigger, 0:10:17.880 --> 0:10:20.920 and renewables role in that system grows more or less 0:10:20.920 --> 0:10:23.640 in proportion with that system wide growth, which means the 0:10:23.679 --> 0:10:26.040 other parts of the system also grow in proportion there 0:10:26.040 --> 0:10:29.560 and you see a return to gas demand growth after 0:10:29.600 --> 0:10:30.280 twenty thirty. 0:10:30.480 --> 0:10:32.200 I would go so far as to say that this 0:10:32.360 --> 0:10:34.640 is part of the real value add I mean the 0:10:34.679 --> 0:10:36.400 fact that you have these and clients hone in on 0:10:36.440 --> 0:10:38.280 them and ask questions. And maybe it's not because they 0:10:38.280 --> 0:10:40.720 fear the change that's happened to change. It might just 0:10:40.760 --> 0:10:43.640 be that they've actually identified this is where the value 0:10:43.679 --> 0:10:46.720 really is. Is Some of these things kind of reminds 0:10:46.760 --> 0:10:49.800 me back in my early days as an analyst. My team, 0:10:50.200 --> 0:10:53.760 as an April Full we wrote a pretend research note 0:10:53.800 --> 0:10:55.840 and sent it to the editors. 0:10:56.360 --> 0:10:57.840 I mean, this is how nerdy we were. 0:10:58.000 --> 0:11:01.280 And in it we had a forecast, we had the methodology, 0:11:01.280 --> 0:11:04.960 and we had developed a methodology called the IACAGR, which 0:11:05.000 --> 0:11:09.000 stands for Indiscriminate application of a compound annual growth rate. 0:11:09.360 --> 0:11:13.360 So obviously just making fun of like how you can 0:11:13.440 --> 0:11:15.680 make something look with the sort of like the laziest 0:11:15.720 --> 0:11:18.240 possible methodology, and I think this just really emphasizes that 0:11:18.280 --> 0:11:21.320 you definitely haven't done the indiscriminate application of a compound 0:11:21.320 --> 0:11:24.400 annual growth rate. There's a lot of complexity behind what 0:11:24.440 --> 0:11:27.160 you've done, and so even with some of the policy 0:11:27.400 --> 0:11:30.240 interventions going one way or other stripped out, there's still 0:11:30.280 --> 0:11:33.840 a lot of the zigzagging that happens within this as 0:11:33.880 --> 0:11:36.800 some of these different dynamics play out. So speaking of 0:11:37.000 --> 0:11:39.480 different dynamics that up playing out, let's get on to 0:11:39.640 --> 0:11:43.960 one of the big additions of this report, which was 0:11:44.160 --> 0:11:49.800 bringing in an analysis of the impact that data centers, 0:11:49.800 --> 0:11:53.679 principally driven by power demand for AI, how they could 0:11:53.920 --> 0:11:57.640 impact the energy transition. So for full context, we did 0:11:57.640 --> 0:12:02.000 a podcast with our colleagues Natalie Lamandebrata and Helen co 0:12:02.080 --> 0:12:04.959 and they were talking about specifically maybe the nearer term 0:12:05.040 --> 0:12:07.040 view and particularly to the US, although I think a 0:12:07.040 --> 0:12:10.040 lot of those themes apply more broadly, and so that 0:12:10.160 --> 0:12:12.559 was part of obviously your analysis, but you also looked 0:12:12.559 --> 0:12:15.199 in the longer term as well. You extended this out 0:12:15.240 --> 0:12:17.760 to twenty fifty and obviously the team as well took 0:12:17.800 --> 0:12:20.400 this global. So, yeah, what were some of the things 0:12:20.520 --> 0:12:23.199 that you found doing this analysis? 0:12:23.800 --> 0:12:26.440 So, I mean, first off, I'm definitely standing on the 0:12:26.520 --> 0:12:28.360 shoulders of giants when it comes to the work that 0:12:28.440 --> 0:12:30.360 Natalie and Helen have done here. This is a couple 0:12:30.400 --> 0:12:33.400 of couple of interesting dynamics here is one, because of 0:12:33.520 --> 0:12:37.640 latency concerns, that forward looking view of where where is 0:12:37.720 --> 0:12:41.240 data center demand coming from? It's a lot more globally 0:12:41.280 --> 0:12:44.640 distributed than you might otherwise imagine. I mean that's not 0:12:44.679 --> 0:12:47.160 to downplay the role that the US plays, Like the 0:12:47.240 --> 0:12:50.319 US is still huge, say China's massive. 0:12:50.120 --> 0:12:53.680 Approaching fifty percent of data centers today are in the US. 0:12:53.840 --> 0:12:56.280 I think, well, yeah, no, that's that's more or less 0:12:56.280 --> 0:12:58.720 on the money. And yeah, and so we see like 0:12:58.760 --> 0:13:02.040 a large geographic spread, at least towards the longer term. 0:13:02.040 --> 0:13:03.480 And there's sort of a dynamic here where I mean, 0:13:03.520 --> 0:13:06.080 the US is definitely sort of leading the pack here, 0:13:06.120 --> 0:13:08.640 but other economies who might be a bit later that 0:13:08.720 --> 0:13:13.040 party will eventually catch up in their demand for general 0:13:13.120 --> 0:13:15.600 data and AI specific use cases will grow. 0:13:15.400 --> 0:13:16.160 Over time too. 0:13:16.640 --> 0:13:19.000 There's also I mean there's a seg here as well, 0:13:19.040 --> 0:13:23.120 because that story of renewed gas demand growth in the 0:13:23.200 --> 0:13:27.280 US post twenty thirty is partly responsible from data centers 0:13:27.320 --> 0:13:30.320 as well. There's definitely a long term growth there data 0:13:30.360 --> 0:13:33.839 centers and interestingly electric vehicle demand as well. So that 0:13:34.240 --> 0:13:36.600 was another sort of high level result that popped out 0:13:36.600 --> 0:13:40.840 which was quite interesting, is that evs in most places 0:13:41.080 --> 0:13:44.640 by twenty thirty is still much more significant demand than 0:13:44.840 --> 0:13:47.400 data centers may potentially not much more significant. Other places 0:13:47.400 --> 0:13:48.920 are a bit closer, and I mean US is one 0:13:48.920 --> 0:13:51.199 of the few exceptions where we think that data center 0:13:51.240 --> 0:13:54.400 demand will outpace demand from EV's in the short term, 0:13:54.400 --> 0:13:56.800 but eventually I think EV's will catch up by about 0:13:56.840 --> 0:13:57.439 twenty thirty. 0:13:57.720 --> 0:13:59.439 So where else would we see that trend. 0:13:59.800 --> 0:14:00.560 That's a good question. 0:14:00.600 --> 0:14:03.240 I think we're probably if you looked at markets where 0:14:03.440 --> 0:14:06.560 EV growth is a bit behind the curve, where you 0:14:06.559 --> 0:14:08.880 still have strong demand from data centers. So I think 0:14:09.040 --> 0:14:10.920 I haven't seen these charts, but my guesses would be 0:14:10.960 --> 0:14:14.640 potentially places like Australia or Malaysia where there's a reasonable 0:14:14.640 --> 0:14:17.240 amount of data centers going in but they're not necessarily 0:14:17.280 --> 0:14:18.760 particularly strong EVA markets. 0:14:20.160 --> 0:14:21.000 It's really interesting. 0:14:21.000 --> 0:14:25.000 I mean, actually we just recorded a podcast with Colin Mcherrika, 0:14:25.040 --> 0:14:27.880 who heads up our advanced Transport analysis, and we were 0:14:27.880 --> 0:14:31.440 talking about EVO, which is the transport counterpart to NEO, 0:14:31.520 --> 0:14:33.240 So that's the electric vehicle out look, and we had 0:14:33.240 --> 0:14:35.200 a long discussion about how the US is going to 0:14:35.240 --> 0:14:37.680 be moving slower than other markets on electric vehicles. But 0:14:37.880 --> 0:14:39.960 you know, it's interesting there's this pattern that some of 0:14:39.960 --> 0:14:42.040 those markets they might be getting some data centers, so 0:14:42.080 --> 0:14:44.920 there's going to be demand growth either way. I remember 0:14:45.160 --> 0:14:50.200 a really interesting point that you made in a meeting 0:14:50.440 --> 0:14:53.200 when we were just talking about our data center analysis, 0:14:53.280 --> 0:14:56.000 because you know, there's this question that is sort of 0:14:56.040 --> 0:14:58.760 everyone wants the answer to all this data center demand, 0:14:58.760 --> 0:15:01.240 all this electric vehicle to Is it going to mean 0:15:01.240 --> 0:15:03.240 more renewables and more gas? Is it going to mean 0:15:03.280 --> 0:15:06.600 more emissions? And I remember you explaining this really nuanced point, 0:15:06.680 --> 0:15:10.000 which is that you can create a model that has 0:15:10.400 --> 0:15:13.160 all of those extra things layered in and you can 0:15:13.200 --> 0:15:16.200 see the difference to the power generation mix. But it's 0:15:16.280 --> 0:15:19.600 not necessarily correct to just say that the difference to 0:15:19.640 --> 0:15:22.680 the mix is what is attributing that to those data 0:15:22.720 --> 0:15:25.880 centers or electric vehicles? Can you just explain that? Am 0:15:25.920 --> 0:15:26.960 I remembering this right? 0:15:27.080 --> 0:15:27.800 You are? 0:15:27.840 --> 0:15:29.560 And I mean there's a there's a chart in NEO 0:15:29.600 --> 0:15:32.480 which I think illustrates this point quite well. So we 0:15:32.520 --> 0:15:35.640 with our economic transition scenario, we modeled in an additional 0:15:35.680 --> 0:15:38.840 scenario sort of behind the scenes, where we stripped out 0:15:38.960 --> 0:15:42.080 demand from data centers, and so we solved these two 0:15:42.360 --> 0:15:45.000 nearly identical scenarios. The only difference is that missing data 0:15:45.000 --> 0:15:47.080 center demand. And you can then look at those two 0:15:47.120 --> 0:15:49.760 sets of results and compare them and start to infer 0:15:50.040 --> 0:15:52.400 what the effects are of that data center demand. And 0:15:52.840 --> 0:15:54.480 this goes into a chart which we have in the 0:15:54.520 --> 0:15:56.840 report where you see that potentially out to twenty thirty, 0:15:56.840 --> 0:16:00.960 about two thirds of the additional demand and for data 0:16:01.000 --> 0:16:03.680 centers is met by fossil fuels. And you can't stop 0:16:03.680 --> 0:16:05.760 there though, because that's not the actual message. That's what 0:16:05.800 --> 0:16:07.880 the chart shows. But you sort of have to unpack 0:16:08.040 --> 0:16:10.440 what that sensitivity means, and I think it goes back 0:16:10.440 --> 0:16:13.600 to this concept of additionality. So, first off, we're not 0:16:13.640 --> 0:16:15.920 saying that two thirds of the electrons that are going 0:16:15.960 --> 0:16:17.800 to go into data centers are going to come from 0:16:17.920 --> 0:16:19.240 fossil fueled plants at all. 0:16:19.280 --> 0:16:20.200 That's not what we're saying. 0:16:20.320 --> 0:16:22.040 I think we're probably saying the opposite I think we're 0:16:22.080 --> 0:16:25.200 looking at the sort of corporate ppa activity and there's 0:16:25.240 --> 0:16:27.680 like huge demand there. So like these data centers at 0:16:27.760 --> 0:16:30.000 least normally are going to be powered more often than 0:16:30.000 --> 0:16:33.680 not by renewables, and that's not just a US trend. 0:16:33.640 --> 0:16:36.000 And those I mean, the interesting thing about it as 0:16:36.040 --> 0:16:38.440 a market, and this is very different from electric vehicles, 0:16:38.520 --> 0:16:41.360 is it's so concentrated with a small number of very 0:16:41.480 --> 0:16:45.560 huge organizations that have considerable power in the market. Yeah, 0:16:45.600 --> 0:16:49.080 and a lot of those organizations are investing heavily in 0:16:49.720 --> 0:16:51.240 renewables supply, so. 0:16:51.760 --> 0:16:54.920 And nuclear and other things as well. And I mean 0:16:54.920 --> 0:16:57.640 we also hear stories of them building on site gas 0:16:57.680 --> 0:16:59.880 generation as well. So there's a lot of things happening. 0:16:59.880 --> 0:17:02.120 But I think this concept of coming back to this 0:17:02.160 --> 0:17:04.960 concept of additionality. So we're not saying that two thirds 0:17:04.960 --> 0:17:06.760 of the power that goes into these things is coming 0:17:06.760 --> 0:17:10.560 from fossil fuels. What our analysis shows is that when 0:17:10.640 --> 0:17:13.959 you add this additional demand to the system, can we 0:17:14.119 --> 0:17:17.280 meaningfully increase the rate at which we build renewables in 0:17:17.320 --> 0:17:20.600 the next five to ten years And our analysis tends 0:17:20.640 --> 0:17:22.960 to indicate that we can't. And so this is the 0:17:23.000 --> 0:17:26.400 important idea of additionality it we're going to build these 0:17:26.440 --> 0:17:29.960 data centers and nominally they're going to be powered by renewables, 0:17:29.960 --> 0:17:32.959 But that doesn't mean extra renewables built in the world. 0:17:33.119 --> 0:17:35.760 It probably just means renewables that were already going to 0:17:35.800 --> 0:17:38.800 be built somewhere else now being built and attributed to 0:17:38.920 --> 0:17:40.959 data centers. Does that means the rest of the system 0:17:41.080 --> 0:17:43.040 becomes a little bit more more fossil heavy. And I 0:17:43.080 --> 0:17:45.919 think that's the way to understand the chart. That concept 0:17:45.960 --> 0:17:48.960 of additionality is that we're not building many more renewables 0:17:49.000 --> 0:17:51.120 because of this additional demand, and the reason being we're 0:17:51.119 --> 0:17:53.520 sort of near or at the limits of what we 0:17:53.560 --> 0:17:56.680 think renewable supply chains can manage in the next five 0:17:56.720 --> 0:17:58.480 to ten years and what the grid could manage in 0:17:58.520 --> 0:17:59.720 the next five to ten years. 0:18:00.040 --> 0:18:02.840 I mean, it's really interesting because I think where we 0:18:02.880 --> 0:18:07.080 get to here is on that boundary between our economically 0:18:07.160 --> 0:18:11.800 rational model and something that reflects the what happens in 0:18:11.840 --> 0:18:14.800 the fog of war. And I could make the argument 0:18:14.920 --> 0:18:16.919 that when you say all those renewables would have been 0:18:16.920 --> 0:18:19.480 built anyway, but now they're going to be built with 0:18:19.520 --> 0:18:21.560 a PPA for a data center, you could make the 0:18:21.640 --> 0:18:24.160 argument actually they weren't going to get built anyway, even 0:18:24.200 --> 0:18:26.800 though it was the economically rational thing from a system 0:18:26.840 --> 0:18:29.679 point of view, because might just be the market design 0:18:29.760 --> 0:18:31.879 didn't favor that. So I and we also have to 0:18:31.960 --> 0:18:34.720 keep that in mind, is that sometimes these things can 0:18:34.840 --> 0:18:38.560 act as of forcing mechanism to make maybe the outcome 0:18:38.560 --> 0:18:42.080 that should have happened anyway on an economic basis happen. 0:18:42.280 --> 0:18:44.439