191 - How Siemens Grid Software is Accelerating Energy Transition with AI-Driven Solutions

Discover how Siemens is driving the future of energy grids in this insightful conversation with Sabine Erlinghagen, CEO of Siemens Grid Software. In this episode of the "Insider’s Guide to Energy" podcast, Sabine shares how Siemens is using advanced software solutions to address grid capacity challenges, streamline interconnections, and ensure a smooth energy transition. Leveraging AI and data-driven insights, Siemens is revolutionizing how utilities plan, operate, and manage distributed energy resources. 

Sabine explains how Siemens' Grid Scale X platform is transforming grid operations by increasing visibility, improving flexibility, and enabling more efficient use of existing grid infrastructure. With real-time data and AI-powered disaggregation, Siemens software helps utilities connect up to 30% more renewable energy while mitigating risks of overload and ensuring faster response times in the case of outages. Whether in Europe, North America, or Norway’s EV-dense grids, Siemens is leading the charge for smarter, more efficient energy networks. 

Listen in to explore the critical role of digitalization and AI in grid management, from planning to operations. Learn how Siemens’ solutions not only extend asset life but also reduce costs for utilities facing the pressures of growing energy demand and electrification. If you’re an energy leader looking to stay ahead in the rapidly evolving energy landscape, this episode is a must-listen.

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Transcript

00:00:01 Sabine Erlinghagen

Grids are becoming the bottleneck of the energy transition unless we use the full power of software, we won't be able to keep up with the.

00:00:09 Sabine Erlinghagen

Change.

00:00:13 Chris Sass

Your trusted source for information on the energy transition. This insider's guide to energy podcast.

00:00:25 Chris Sass

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00:01:28 Chris Sass

Welcome to another edition of the Insiders Guide to Energy. I'm your host Chris Sass with me is my co-host Jeff McCauley. And today we have with us Sabina, early Hagen, the CEO of Siemens Grid software. Sabina, welcome to the podcast.

00:01:41 Sabine Erlinghagen

Welcome. Thanks for having me.

00:01:44 Chris Sass

I'm excited to have you here. I'm always a sucker for software, and when it comes to making the grid better, we all know there's a layer of software that needs to be developed and it sounds like your organization.

00:01:54 Chris Sass

'S working on.

00:01:54 Chris Sass

It why don't we start by what is Siemens grid software?

00:02:01 Sabine Erlinghagen

Tunes Grid software is all about helping grid operators plan, operate and maintain their grids in a better way and using the full potential of software. And that's specifically important given all the challenges that we see with the energy transition. Certainly the need for grid capacity both in the transmission.

00:02:20 Sabine Erlinghagen

Grid as well as the in the distribution grid, but then more importantly, even the distributed energy resources and this complexity that comes with it for both grid planning, grid operations and maintenance.

00:02:35 Jeff McAulay

Let's start on the grid planning and operations side. Sabina, you are very well aware. One of the biggest challenges in the renewable energy world today is really about interconnection. How can software help speed up the interconnection process?

00:02:53 Sabine Erlinghagen

The interesting thing about interconnections is that you need to give an answer of yes or no whether something can still come onto the grid, and most of those decisions are actually based on no data or on statistics and theoretical load curves and assumption.

00:03:10 Sabine Erlinghagen

So I think the first thing that you can do is provide transparency and understand how much can your grid still take on and that must be a data-driven decision. And our software grid scale X can help you do that by understanding how loaded a transformer is already is already like how much of A risk.

00:03:31 Sabine Erlinghagen

You have of overloading that and if you then still connect, what can you do in terms of flexibility management to allow it to come on under certain conditions and then act?

00:03:44 Sabine Erlinghagen

So I think it's a terrible news to know that 2000 gigawatts worth of interconnection requests are actually queuing at the moment and we have very poor data to do those decisions. And typically because we are risk averse.

00:04:04 Sabine Erlinghagen

We say no, even if we could still say.

00:04:07 Sabine Erlinghagen

Yes.

00:04:08 Chris Sass

So are you planning an infrastructure where we can over subscribe because you understand the impact of the oversubscription and then you can control the demand? Is that what the vision is here to buy some time?

00:04:20 Sabine Erlinghagen

I think that's a very good way of putting it. Yes, I think the n -, 1 principle is something that was born out of a lack of better data or better knowledge or better manageability of the.

00:04:34 Sabine Erlinghagen

To load and if at the moment we put so much buffer in it that uh.

00:04:41 Sabine Erlinghagen

We can't afford that in the future and I think software has done in other industries with airplanes. I mean, you run airplanes no longer on for engines just to be safe, you don't have factories creating a lot of waste and having a spare production line next to it. Software has solved all of those problems. Why shouldn't it be?

00:05:02 Sabine Erlinghagen

Possible to solve that for the grid?

00:05:05 Chris Sass

Do we need every device to register with your your system in order to be understood? Or can you define this from the way the traffic patterns are and knowing what I'm planning on connecting to?

00:05:17 Sabine Erlinghagen

You hit the nail on the head. The software actually disaggregates the information from the meters and knows.

00:05:26 Sabine Erlinghagen

With high enough certainty, what's behind the meter and what are the patterns that you conduct?

00:05:32 Sabine Erlinghagen

From it and you, it learns how much of that load, be it from an EV vehicle. If it comes from solar panel or so, how much of that load is flexible and how much you can act upon with which means and based on that data and that probabilistic learning, you actually then are safe to act.

00:05:53 Sabine Erlinghagen

On it and it's as you said, it's not a putting out more sensors game and wait until you've rolled out masses of sensors.

00:06:01 Sabine Erlinghagen

But it's a game of disaggregation. It's a game of AI and and the like, understanding the patterns and then acting upon them.

00:06:17 Jeff McAulay

This makes sense. So so Bina, basically what you're describing is we have a grid that in many cases is overbuilt.

00:06:24 Jeff McAulay

And we have to rely on that safety factor because we don't have visibility and we don't have flexibility. But when you add that flexibility and visibility with software, it enables you to run more efficiently, more confidently within tighter control parameters. What does that get your utility customers? What are the outputs?

00:06:45 Jeff McAulay

So we talked about maybe a faster interconnection process. What are the other benefits that your customers might see?

00:06:52 Sabine Erlinghagen

I mean, certainly we see that you can actually add 20 to 30% more to the grid than you would do with previous methods. Secondly, if something is happening, you know how to counter react and you have different layers of counter reacting. And if it comes to the worst case of a low voltage.

00:07:14 Sabine Erlinghagen

Or distribution power outage. Then you can react on those much, much faster and restore restore it much better.

00:07:21 Sabine Erlinghagen

And in the end it brings down cost because you can utilize your assets in the field better and you can make sure that the lifetime of those assets are longer because if you overheat the transformer too many times and especially for too long of a period without knowing, then you run those things to an early failure.

00:07:41 Sabine Erlinghagen

And that's a big problem because if you look up the lead times or supply chain times for the distribution Transformers these days, you won't you won't want inadvertently to run down too many Transformers run out of stock and then wait for two years to repair.

00:07:57 Sabine Erlinghagen

Your home, so you better know in advance you better understand the risk and you control it with dedicated actions.

00:08:06 Jeff McAulay

Can we talk about some case studies, what geographies, countries or do you have specific types of use cases of distributed energy resources that you want to call to mind that illustrate what you're talking?

00:08:20 Sabine Erlinghagen

So with grid scale X we launched both for Europe as well as As for the US, the cases are slightly different as the audiences will be aware we have the unbalanced grids and we have balanced grids and in in Europe you have the low voltage.

00:08:40 Sabine Erlinghagen

Which are different topologies.

00:08:42 Sabine Erlinghagen

And so the use cases are slightly different, but the software platform in essence is the same. So let's take the example of Norway, for example. Norway is known for its high density of electric vehicles, so they are kind of living in the future that we will all live in already.

00:09:03 Sabine Erlinghagen

And there's a huge problem with grid capacity.

00:09:06 Sabine Erlinghagen

They say they need to double their grid capacity in seven years, so if you think about it, you build a grid for 100 years and then you need to double it in seven. So it's pretty clear that with the conventional approach of digging up the roads, getting the permits and whatnot, this won't be possible. So we are partnering with.

00:09:27 Sabine Erlinghagen

Yeah. Which is the local utility. Uh for Oslo. And the bigger region and with grid scale acts, we're helping them.

00:09:35 Sabine Erlinghagen

Understand what's going on in their low voltage network. Enabling those conditional connection requests and and and and provide better customer service and get that those.

00:09:52 Sabine Erlinghagen

Connection requests processed really fast.

00:09:54 Jeff McAulay

Wow. Doubling of grid capacity in the seven years does sound very challenging. What's driving that, primarily, is it Ed adoption, renewable energy, low growth through electrification? What are the primary drivers say?

00:10:10 Sabine Erlinghagen

I would guess all of the above. I mean, the EVA's are already pretty high, so they've kind of gotten used to it and and learned to live with it. But there was actually even to the US press, there was an interesting incident, there was an ammunition factory who wanted to expand their capacity and.

00:10:30 Sabine Erlinghagen

Get more power from the grid and at the same time there was a TikTok data center going online and since TikTok was faster, the ammunition factory had to wait for the connection request and that made it I think even to the Washington Post.

00:10:45 Chris Sass

And that's an American use case. You're saying that happened?

00:10:47 Sabine Erlinghagen

No, there was Oslo and it made it to the Washington Post because it's it's it's about the Ukraine war and the ammunition factory kind of wanting to produce more for Ukraine. So those are kind of I think it's it's it's a very like, sweet Norway has become very attractive for for industry.

00:10:49 Chris Sass

It was an awesome got it, got it.

00:11:08 Sabine Erlinghagen

For data Centers for like all kinds of industry which is energy intensive and they they they just are prosperous and that leads to higher electrification levels.

00:11:20 Sabine Erlinghagen

And hence you have the grid capacity demand.

00:11:24 Chris Sass

What? What is the the the North American story happening? You launched multiple contents. We all know power runs differently and the infrastructure set up differently. How is North America using the software or planning to use your?

00:11:39 Chris Sass

Software.

00:11:40

M.

00:11:41 Sabine Erlinghagen

I mean, first of all, what? Uh, I mean North America has done a great job in rolling out smart meters and has also done a great job in kind of building data lakes and trying digitalization strategies. But what we're missing is making sense out of the data and for metadata management.

00:12:01 Sabine Erlinghagen

Or meters making more out of the data than just in inverted commas. The billing process so.

00:12:08 Sabine Erlinghagen

Metering is still meter meter to cache and we've embarked on all those very heavy lifting digitalization processes and with grid scale X. The approach is to do that more lightweight and to.

00:12:28 Sabine Erlinghagen

Have the data understand or be interpreted in the context of the grid topology.

00:12:34 Sabine Erlinghagen

And what that does is, and I think Peter Kelly in one of your previous podcasts, said it like, yes, you have meta data, you have that that's around for some time, but people can't interpret it and can't do anything with it because they don't know what it means for the assets, for the distribution Transformers.

00:12:55 Sabine Erlinghagen

And and what's the financial impact of not consuming energy of connecting more?

00:13:03 Sabine Erlinghagen

Or replacing ahead of time or later so we can't quantify that yet. And our software helped to do that. We created a a pretty sleek thing called the Grid Impact score which on one view on every level of topology of your grid.

00:13:23 Sabine Erlinghagen

Tells you how loaded your grid is and where you run a risk of of overload and where you still can add more capacity and that's.

00:13:34 Sabine Erlinghagen

That's like solving a pretty big problem, which people haven't even started to try to solve because it's so heavy lifting.

00:13:43 Jeff McAulay

I mean, you mentioned visibility into the problem, but you've also hinted at taking action. So what kind of actions can utility grid operators take with this new visa?

00:13:57 Sabine Erlinghagen

Yeah. I mean, if I have a high great impact score, it means like I have more frequent or higher overload situations. So I can in my asset management department, I can actually change the cadence of how much I like. When do I replace an asset.

00:14:17 Sabine Erlinghagen

And and secondly, which is the even smarter solution is then align that with your demand response programs and actually incentivize people to use less on certain times and then really in real time react on on the situations that you see on the grid and you can target.

00:14:38 Sabine Erlinghagen

Your programs to those areas where you really get an overload situation and you can make more precise connection approvals and admit more to the same existing grid.

00:14:53 Chris Sass

Now Siemens traditionally, have you been known as a software provider for or more of a hardware manufacturer in this space?

00:15:02 Sabine Erlinghagen

The in grits, we've been around with software for a long, long time, so 70% of the world's electrons flow through.

00:15:15 Sabine Erlinghagen

Grids that are planned with our software, so most of the US plans with our PSE software suite. So that goes back a very long time. If you think about Siemens overall, obviously we have also a very significant hardware footprint, but when it comes to grids.

00:15:34 Sabine Erlinghagen

We are really in software for a very long time and we've come the same traditional way than than most others. So we started in having very sophisticated methods for managing transmission.

00:15:48 Sabine Erlinghagen

Lines both in the Control Center space as well as in the in the planning space and and the attention these days has shifted clearly to to distribution and what we figured is you can't just take the paradigm from transmission down to distribution, but you really gotta rethink that and.

00:16:08 Sabine Erlinghagen

Rethink it from the bottom.

00:16:09 Sabine Erlinghagen

And since we traditionally also have a very long history in media data management, that was a quite natural step for us to flip it on its head and say, what can we do with the data that we have already and how can we overlay planning and operations functions in one modern software.

00:16:30 Sabine Erlinghagen

Platform. So we took quite a radical innovation approach to that one and not just continued what we've been doing for the last 20-30 years.

00:16:39 Chris Sass

And how did the market receive this, this this kind of change in the paradigm and utilities tend to be slow movers. How is it being received?

00:16:48

Right.

00:16:50 Sabine Erlinghagen

I think everybody acknowledges that we need to take a new approach. I mean, there are so many projects, call them germs or whatever, that have not gotten the results that were expected. They take ages and they cost a fortune. And then.

00:17:09 Sabine Erlinghagen

They don't realize the return that you had anticipated for, so our approach from the get go was to do something that is fast, that creates value fast.

00:17:21 Sabine Erlinghagen

And within weeks, you generate the first value out of our cloud based software and you can start gain transparency and gain that actionability that I talked about. So there was quite like ad tech there. It was quite well noted that we took a pretty radically different.

00:17:40 Sabine Erlinghagen

Approach to the conventional ones. And as you said, I mean it's it takes time to adopt because nothing is fast in our industry.

00:17:53 Chris Sass

Have you seen a dramatic decrease in interconnects from time frames for the folks that have tried your software as have you actually seen it ripple out to to real world shortening of interconnect time frames?

00:18:05 Sabine Erlinghagen

And certainly people dare to connect more and I think have better data and reconfirmation to to do that. So that's that's clearly there. And I think the.

00:18:20 Sabine Erlinghagen

The the first acknowledgment that we see is that it's it's really heavy lifting for them to get their data clean and with a very nice approach of making that heavy lifting an easier one to start with. So already in that process of getting your data straight, you learn a lot and.

00:18:40 Sabine Erlinghagen

You, you you know that you're not making an error in the end when you admit.

00:18:47 Sabine Erlinghagen

Something to the grid.

00:18:50 Jeff McAulay

Sabina, you're talking about the the arc of history and Siemens has been active for a long time. You've had a long history with Siemens. Also have a stint at Enernoc now and LX before returning to lead the the software group at Siemens. What have you seen in the arc?

00:19:09 Jeff McAulay

Of your career to date and can you give us a hint around about what's might be around the corner?

00:19:16 Sabine Erlinghagen

The the beauty of what I've seen with Enernoc, which by all means was still a startup or at least a small company when compared to Siemens, is that you can build things very fast and you, uh, can innovate and revolutionize the market very fast. So I had the chance for enough to to be in Switzerland.

00:19:35 Sabine Erlinghagen

And really, pioneering the the demand response paradigm in Switzerland at the time. So that's like 10 years ago by now time flies. But I I mean it's I think that knowledge of.

00:19:56 Sabine Erlinghagen

Like knowing the having the power of a big company, but the attitude of a small company is what can drive a big change, because the at the moment when I talk to utilities via Tsos or DSOs, we are all still underestimating the pace of change, somebody said.

00:20:16 Sabine Erlinghagen

Once that the utility industry is 1 where everything happens in the next three or five years, so whenever you ask, it's the next three or five years. And that was a decade long truth or several decades.

00:20:31 Sabine Erlinghagen

Now it's actually happening much faster than anybody thought. So when you think about connection requests, I went to Estonia and they told me they have 10 folded their connection requests in two years.

00:20:49 Sabine Erlinghagen

Or when you talk to some executives at at TDs, also in in Europe that you asked them.

00:20:55 Sabine Erlinghagen

Like how many?

00:20:56 Sabine Erlinghagen

More connection requests. Could you process with the way you're doing it today and they you are like 2 * 3 * 4 times.

00:21:04 Sabine Erlinghagen

They say no, no, no.

00:21:04

No.

00:21:05 Sabine Erlinghagen

And then say, you know that DR's will go up 7X until 2030, so the all of a sudden we have a momentum and things are getting faster than expected and that was not the case for a very very very long time. So.

00:21:24 Sabine Erlinghagen

You have been an alarmist if you have said like, oh, this is coming, this is coming and now it's coming faster than you would ever.

00:21:33 Sabine Erlinghagen

Fact, and I think that is something where you've got to be ready and you gotta act because those exponential curves, they're they're tricky, right? They go after a while. They have so much momentum that it's impossible to keep up unless you've prepared for it.

00:21:53 Sabine Erlinghagen

And that's what we've done the last 3-4 years we've seen that coming and we've invested massively in making things easier and faster. If you think about how utility is procured.

00:22:09 Sabine Erlinghagen

Day. I mean, you have an RFP, you make a selection process. So this easy little procurement process takes two or three years from the initial idea of you want something to to then actually making the the award and the procurement decision and then you start implementing something like a derm.

00:22:30 Sabine Erlinghagen

System or an Adm?

00:22:31 Sabine Erlinghagen

Mess and that takes you another five years, so 678 years into you want to do something, you realize the first value to know that you've missed, like 8 years of innovation in between. So this is something that can't go on. It's impossible because we will always be like.

00:22:51 Sabine Erlinghagen

Half a decade or a decade too late, with anything we do, so the I think the industry needs to learn.

00:23:00

To.

00:23:01 Sabine Erlinghagen

Get value faster, change faster transform faster with the risk of.

00:23:09 Sabine Erlinghagen

Like incremental or not the risk, but with an approach of incremental value and incremental step. It has worked in any other industry in the world. It's just because of the regulation and the paradigms that we have in our industry that this hasn't happened yet and given the dynamics that we see and and the pressure.

00:23:30 Sabine Erlinghagen

That will rise from like, be it the effects of climate change or the try to the attempts.

00:23:36 Sabine Erlinghagen

Avoid it. It's something inevitable, and that's like our ambition to be that partner who can evolve and act faster than anybody else.

00:23:51 Chris Sass

You have two.

00:23:52 Chris Sass

Parts to the solution. You have a planning phase and I think you covered that fairly well the the the problem statement of what planning takes today. And then you have an operational component of this.

00:24:02 Chris Sass

For folks just getting engaged with their platform, what's driving the immediate need? Is it the planning that they're they're hoping to get ahead or is operation saying, hey, we need a better tool?

00:24:14 Sabine Erlinghagen

It's a very interesting question and I think it's very much dependent on like the internal setup of or of the utility or what what? Where's the bigger problem. And so like circumstances can decide what is the bigger problem. In the end, our conviction is you need to tackle.

00:24:34 Sabine Erlinghagen

Both simultaneously, because if you.

00:24:38 Sabine Erlinghagen

Don't plan with the same data that and the same assumptions. Then you can act upon in your operations. Then you get a problem because the whole thing about flexibility, the probabilistic view on on flexibility can't be acted upon. So you've planned with this is just enough capacity.

00:25:00 Sabine Erlinghagen

And then you see in your operations that you have a problem. So unless you get that lined up.

00:25:07 Sabine Erlinghagen

You won't succeed in that world. Where do we start? I mean, we we started from both sides to be honest. And the interesting part is then working with our utility partners to bring those departments together because it's, hey, this is my tool. I've brought it in for operations and then.

00:25:27 Sabine Erlinghagen

This is not for planning. This is not for operation, so you have very interesting internal transformation processes that you're witnessing and that we we can help facilitate by saying, hey.

00:25:39 Sabine Erlinghagen

This is the same underlying platform. It just once gives you the grid impact score and here you get an outage management process, but it's the same software. You just click on a different view and you get more real time perspective as opposed to a longer term perspective and especially where you have.

00:26:01 Sabine Erlinghagen

CIOs coming in or C level who who has has a pretty bold vision on digitalization, this resonates a lot.

00:26:14 Jeff McAulay

Yes. So you've touched on a few different categories of software, whether that's germs, distributed energy, resource management, ATMs, better data management system, MEMS. Are these creating false silos? You haven't really talked about individual separate categories. You've talked more about and.

00:26:33 Jeff McAulay

Overarching platform that can do multiple different things. Do we need to breakdown?

00:26:37 Jeff McAulay

Some of those silos.

00:26:39 Jeff McAulay

Or do you think those are still important separate individual procurements?

00:26:45 Sabine Erlinghagen

The answer is yes. I mean in the sense of do we need to bring down the silos so we can leave it there? Absolutely. Unless we have a digitalization strategy that goes across, it's it's not right. Obviously there are different processes that each of those departments supports.

00:27:06 Sabine Erlinghagen

But if you think about planning operations, it's just the time frame that is different, like the one is longer term than it's getting to medium term, but you also simulate and plan in operations. You just do it daily or every like 15 minutes. It's just a matter of time perspective so.

00:27:26 Sabine Erlinghagen

That's why I don't make that much of a difference. But of course the buying behaviors and the departments are still cut in that way.

00:27:38 Chris Sass

All right, we we've talked quite a bit. We're coming up to time here, but I do have one more question, which is how much is the current AI revolution enabling your platform or could we have done what you're doing a few years ago is is, is, is, is AI really fundamental for what you're?

00:27:55 Chris Sass

Talking about.

00:27:57 Sabine Erlinghagen

I mean, AI is older than ChatGPT, so we are using AI for a while, especially to if you take media data. I was talking about that. So does it need to be real time or is it good enough to estimate the?

00:28:15 Sabine Erlinghagen

The periods in between or the the time lag that that you have given a trained model and so forth. So that's there's certainly algorithms that we use for for a longer time. Also the disaggregation we were talking about that like not needing sensors but understanding what's behind the meter and overlaying that to grid.

00:28:35 Sabine Erlinghagen

Topology or making the building the grid topology and making that easier?

00:28:42 Sabine Erlinghagen

Based on suggestions is all things that are powered by AI these days already. So if you consider AI being older than ChatGPT, then the answer is yes.

00:28:57 Chris Sass

No. I consider language models newer technology, but the the chipsets, there's been a a huge amount of money and effort going into AI, right? So machine learning, neural networks have all been around a long time. I mean, I did those in Graduate School long ago.

00:29:11 Chris Sass

However, there has been a big push and a lot of resources going into it, so the the one thing that I always think about with utility is scales. I spent a number of years working in telecom and doing things at scale is hard and and utilities are scale when you start talking about meters and and and the numbers, that's.

00:29:30 Chris Sass

OK, so I was just curious if the technology, if there's some technology event in the last couple of years that has really enabled you to offer something that maybe you couldn't have.

00:29:37 Chris Sass

Offered in the past, that's all I was asking.

00:29:39 Sabine Erlinghagen

I mean certainly cloud technology and the data processing that you see there is something that is fundamental and to to work with unstructured data to is is something that is today much easier done than than previously think the.

00:29:59 Sabine Erlinghagen

More than a technology challenge, it's a mindset challenge on how you approach these things and the way we've done that is by mixing people quite a bit. I mean, we have years and years and years of domain know how Ingrid planning and grid operations, we run a lot of grids both on the.

00:30:21 Sabine Erlinghagen

Transmission as well as in the distribution sites around the world.

00:30:25 Sabine Erlinghagen

That how do you challenge that and how do you get to a vision of autonomous grid management in the end, where AI where uh, software takes over some of the decision making, makes recommendations and and automates a lot of the complexity and takes away the burden from the planner or the operator?

00:30:46 Sabine Erlinghagen

And if that to achieve that you need paradigms to to change and that we achieve by mixing people from different disciplines.

00:30:59 Sabine Erlinghagen

And having them challenged other and giving them the freedom to think without legacy and and then you use the technology that is there. But I don't think that for grids you need to invent a specific technology. You just need to make use of everything that is there with the right mindset.

00:31:18 Sabine Erlinghagen

And with the right.

00:31:20 Sabine Erlinghagen

It.

00:31:21 Sabine Erlinghagen

Vision of the future and my take away is that the complexity that we are seeing, running and planning grids is something that a human being can't manage with the tools that we have today because the data and the volumes will just explode and the decisions that any individual would need to take.

00:31:43 Sabine Erlinghagen

Are just way, way, way too many. So you need to go to semi autonomous and then autonomous grids to be able to manage grids safely in the future.

00:31:55 Jeff McAulay

Wonderful. So you know this has been a great conversation. We covered a lot of ground from planning to operations to demand response in in multiple different countries and great environments. Thank you so much. I really appreciate the discussion today.

00:32:11 Sabine Erlinghagen

Thank you.

00:32:13 Chris Sass

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