178 - Optimizing Storm Preparedness and Climate Resilience with Steven Quiring of Storm Impact
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Broadcasting from Washington, DC, This is insider's guide to energy.
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Welcome to insiders guide to energy. I'm your host Chris Sass with me as my co-host Jeff McCauley. And this week we're talking to Steven Quiring's, chief scientist at storm impact. Stephen, welcome to the podcast.
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Thanks so much, Chris, great to be.
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Here.
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We're excited to have you here. We've been looking at forward to this episode for quite some time. I think it was quite a while ago when you and I first had our conversation and we are in the height of storm activity and things going on. So with a company named Storm Impact and we're talking about energy, what is it you do?
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Storm Impact is focused on helping utilities be storm ready and climate resilient. And So what we mean by that is that we want to help utilities optimally prepare.
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Before storms occur so that they can optimize their response by having the right number of crews in the right location so that they can quickly and efficiently restore the power. And this is for things like tornadoes and thunderstorms and winter storms and hurricanes. And then we also talked about things on a longer.
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Time scale and and so this idea of being climate smart. So a climate smart utility is one that's going to be investing in infrastructure hardening in a way that.
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Optimizes the resilience of their grid and reduces the likelihood and the duration of outages as we see changes in future frequency and severity of things like hurricanes and tornadoes.
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Well, you mentioned hurricanes and as Chris highlighted in the beginning here, we're just launching into this year's hurricane season and I'm not sure about our listeners, but I've been seeing reports of record high temperatures in the Atlantic.
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And everybody always says that that generates to more and more powerful storms. So what can we expect going into this year's hurricane season?
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It's a great question. And as we sit here, just approaching the start of the hurricane season, it looks to be an extremely active hurricane season and there's a couple of ingredients that go into driving that, Jeff.
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The first is, as you mentioned, sea surface temperatures, so the warmer the ocean, the more energy there is to for latent heat. The evaporation of of water and that energy is what powers hurricanes, and so all else being equal, a warmer ocean. And and we're seeing near record temperatures.
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In the main development region in the tropical Atlantic, and so that is.
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Leading to an enhanced probability of more and stronger hurricanes this season, the 2nd is related to wind shear and so wind shear is a change in direction or speed with height and when we have conditions like El Nino that tends to result in more wind shear.
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And so that decreases the probability of hurricanes we're exiting an El Nino phase and entering a La Nina phase, which results in more favorable conditions in terms of shear. And so both sea surface temperatures and shear are favorable.
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Therefore, all of the major seasonal forecasting predictions like the National Oceanic and Atmospheric Administration and Colorado State University, the European Center and many others are all forecasting above normal numbers of hurricanes and above normal numbers of major hurricanes.
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For this upcoming season.
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So the for utilities that are listening to this, what can actually be done about that? I mean you you mentioned the near term and the long term, so now we're on the we're on the order of weeks and months.
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What is it that a utility can even do to brace for that kind of impact? Or again, it's not really known. This is probabilistic. So what's the preparation that can be done weeks and months ahead of time?
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Excellent. Yeah. Utilities at this point should be looking to make preparations. And while they can't redirect a hurricane or move their service territory very easily, they can do things on the storm preparation and storm response side that allow them to.
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More efficiently, restore power after a storm occurs.
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So the areas that we help utilities is in determining what their resource needs are, how many crews will be required to efficiently restore power after hurricane occurs. So our software can be used to do what if scenarios kind of a planning or tabletop exercise.
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Where we can take a hypothetical storm, pass it over a particular track. So what would Hurricane Katrina look like on Sandy's track and then predict what the impacts will be in terms of damage and customers interrupted for a given?
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Utility that gives them a sense of what the worst case could be and allows them to identify how many the material needs and the the crew needs a second area in addition to those kind of tabletop and long term planning exercises.
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Is actually putting tools in their hands that they can use in the days leading up to a storm.
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So our hurricane outage prediction model gives utilities up to seven days of lead time. And of course, there's lots of uncertainty at those longer lead times. But as we approach a storm, we provide predictions not just from the National Hurricane Center, but from all of the models might have heard of the spaghetti plot or seen all of those tracks.
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That show up on a map and see. So we run each one of those storms, which has a different track and intensity, which allows us to come up with an ensemble.
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Of predictions for each event, and so they can say, well, what's the probability we're going to have more than 100,000 customers out or more than 500 damaged poles. They can look at the best case they can look at the worst case and we have within our tool the ability for them to actually make modifications.
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To the track and intensity a a slider where they can say, well, what if this makes landfall as a Category 4 instead of a category three? Or what if it slows down? Or what if it shifts 60 miles to the West? What would that look?
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Like and so this data-driven machine learning model approach puts tools in their hands to make better decisions so that when they're having to request crews through mutual aid, they can do that knowing what the likely impacts are in their service.
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Territory.
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Great with with a hurricane, I would think that you already have scales, right? You you would already know ahead of time what your resources are. So is this more effective than for immediate use? This the storms a day or two out or is this planning using models? You know you're out saying here's a Class 3 storm. Here's a Class 4 storm.
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Here's the kind of budget we need and the kind of resources and mutual.
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Aid agreements we need.
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To have in place. Yeah, it can be used for both often.
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The the most difficult decisions to make are the ones in the 72 hours before an event, and the reason that that's challenging is there's still substantial uncertainty in the track and intensity of the storm.
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And it's at that time window where if they want cruise, let's say if we're talking about a Gulf Coast utility and they're bringing in crews from upstate new.
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Work. You've got to get those trucks rolling days before the storm makes landfall. If you want them to be in place so that they can efficiently respond after the storm moves through. So it's too late to wait for the storm to make landfall before pulling the trigger on how many contract crews you're going to be.
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Again, and so our goal is to help them minimize the uncertainty around those those decisions. And if you make the wrong decision, these are pretty costly in terms of their budgets, because if you're bringing in lots of people, putting them up at the Hampton Inn, feeding them a steak dinner.
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Paying them double overtime and then the storm shifts and misses your service territory. They're they're just going to head home and you've spent that money and you can't recoup it.
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On the other hand, if you get caught short, then obviously there's both the prolonged outages that your customers will experience and the associated health and safety challenges that go along with that, but also the reputational cost to utilities and the scrutiny that they receive.
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From utility commissions, when they're called to respond to their performance on the storm restore.
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You mentioned this program called Mutual aid.
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That sounds like a very well named program, so I can guess at what it is, but it's not something I'm actually familiar with, so this is an agreement between utilities to support each other during outages. Is there is there more to it than that?
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Yeah. So the the mutual aid approach is something that utilities have developed over a long period of time. And there are regional collaborations amongst utilities where they share resources and where they cooperate in this.
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Free store.
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Firm and in the storm recovery. And so it is designed to streamline the process by which utilities can request the resources that they need that they can onboard those crews into their system. So get them into.
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The payroll system and into the dispatch system so that they can effectively manage and deploy those resources. And this is all done.
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Well in advance. So these agreements are in place well before the storms occur and it it provides an organized way for utilities to request the resources they need from areas that are outside of the expected impact.
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Zone from a particular hurricane or winter storm.
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I think that's pretty interesting you you got the mutual aid set up now, how personalized are these plans? I mean, how, how the impact would vary, right? Two different utilities have very different infrastructure, different, you know, different tools at their disposal.
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Help me understand how this gets unique to an individual utility and how granular this gets.
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Right. So there is various scales at which information and these predictions are made the.
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Ultimately this needs to get down to a particular service center and a particular dispatch area where a crew is sent to to a trouble spot to fix a broken pole.
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But before a storm, you're not going to know exactly which polls are going to be broken. And so we are aggregating those in terms of outage management areas or service center areas or districts and providing them with aggregated totals to say we expect.
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200 poles and 100 Transformers are going to need to be replaced in this particular district, and here's the uncertainty. Bands around those conditioned on the particulars of the storm event and then they can roll those up to an operating company.
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Total or to a utility total. So some of the utilities that we work with are in different States and so they may have impacts that are both in Texas and Oklahoma for example, or in Ohio and Indiana. And so obviously they can't dispatch crews.
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From Ohio to Indiana, if both those states, both those operating companies, are going to be affected, but they could bring in crews from other parts of the company's other service territories that are further afield. So there's the the internal part.
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As well as the external part. So the external part says OK, we don't have enough people within our company to do this restoration. Now we need to ask our friends through mutual aid and this could be other utilities in the United States or for big restorations or especially in the Northern tier of the US.
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Utilities from Canada also send crews to the US to help with restoration, and so each utility is doing this estimation on their own, so no one is going to tell their their neighbor their.
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Our competitor or a fellow utility, here's how many crews we think you need. Each utility needs to make that that determination internally and then these are grouped into a regional estimate and then the the mutual aid can happen from there.
00:14:06 Speaker 4
Thank you for explaining this, I actually saw.
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Ah, some of the impact of that, it was I was driving up to see the eclipse, and it was after, I think a pretty big windstorm in New Hampshire and literally every parking lot I drove by was full of bucket trucks. And it was every it was just like, what is going on and it it, it literally looked exactly like that, like every single bucket truck.
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From, you know, 100 mile radius had converged on this area for storm damage repair, but so great to hear that that's a program AP program that's out there. And it seems like that's essential for storm recovery.
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But we're seeing now more different types of storms in multiple places. So is this a system that can really carry us through the next generation of of storm damage and are there any new techniques? I feel like we're all used to hearing the the typical refrain of vegetation management.
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OK, great. We can go out and trim the trees. Everybody then always asks about, well, what about undergrounding? Ohh, and it's too.
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Intensive. So where does this go? We're in the current moment of the current systems of just send all the bucket trucks clean up the storm damage. Don't really change any long term behavior, but you said you're also helping utilities look ahead. What are those initiatives that can be put into place to make the entire system more resilient?
00:15:29 Speaker 2
Great question. And yeah, we, we work on these two different time scales, one which is very short in the days to hours before a storm occurs and one which is much much longer looking ahead decades to say what is the grid of the future look like.
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And how can we use climate information to more intelligently design and build and potentially to improve the the organization, the structure of the grid today? So for us that is.
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Something that we use some of the same data-driven machine learning models that are trained on the historical performance of the grid, but then we're looking at hotspots.
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Where there are challenges with reliability, perhaps every time there's a thunderstorm, this particular circuit is taken down. And so how do we we can use that information and provide it to utilities to say you have a limited budget for doing.
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Hardening and for enhancing the grid. So where is the best place to spend that? Where are you? Where are you going to get the biggest ROI?
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Investment and the type of investment really varies depending on the utility and depending on the types of storms that they're susceptible to. And so this could be something as simple as you know, hardening, replacing wood poles with.
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Steel or?
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Concrete or that there are those more expensive options that you mentioned related to undergrounding and those utilities are using strategically in certain areas and they're getting the technologies getting better to more efficiently and cost effectively do that undergrounding. But in general that's not going to be kind of the.
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The magical solution for these long term climate resilience question.
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And so I actually think that other strategies like microgrids and distributed generation and the smarter automated switching system that can self heal the grid when there are outages or damage that occur are going to be the.
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The more optimal solutions in the future.
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And so our expertise is on assessing where and how much risk from future climate change there might be to the grid. And this is, you know, is it in coastal locations where there's going to be more surge and and high winds from storms, is it in low lying areas where there'll be increases?
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Then in.
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Flooding is it in exposed areas where we have higher gusts associated with durations or winter storms and so we provide them with the information on the climate risk and how that's going to change in the future, how the probability of damage and outages will change, and then we let them.
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Risks.
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Assess, you know, given their budget, given their operational constraints, what's the best solution? How can they most effectively utilize?
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Their resources to enhance the resilience.
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Let's make this more tangible. Who are the they? Or maybe you can give us a use case where someone's using your technology and how they use it.
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Sure. So on the short term storm preparation part, we're working with Gulf Coast utilities in Alabama and in Texas and we're working with East Coast Utilities.
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And New Jersey and other coastal states. And so we have a large number of customers that we're serving on the pre storm preparation side that are every day. They're meteorology teams. Their storm response teams are monitoring conditions and it's been a very active.
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In 2024, and that has definitely driven interest in our solutions as well because utilities are doing storm response all the time.
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Time in terms of the longer term climate risk part, there is a lot of interest out West where utilities are thinking about wildfires and the risk that infrastructure, electrical infrastructure causes. And so they want to reduce their liability.
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They want to increase the resilience of the grid in those locations and so that requires them to think about big investments.
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In reducing that, that wildfire risk and deploying this to say, well, where are those places where they're going to see because of storm conditions, the the highest likelihood of ignitions occurring.
00:20:38 Speaker 3
Talking a lot about whether you talked about meteorologists, where is this data coming from? How are you doing a better job than their current meteorologists of helping them make predictions?
00:20:48 Speaker 2
Sure. So we don't necessarily pretend or state that we're going to do a better job than their meteorologists. Their meteorologists have a great deal of experience and they also have the benefit of knowing their grid and their infrastructure and working every day with the people on the ground.
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Who are doing the restoration, so we tend to partner with their meteorologists and Co develop solutions that build on the existing products and services that that are they provide.
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And so our advantage is that we are combining the weather and climate information with a whole host of other data sets that they don't have access to and to do it in a way that is automated and that is objective and that improves over time.
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And so the the secret sauce is in pulling together the information from hundreds of different features, things like soil conditions, soil moisture, vegetation type, the height of vegetation, health of vegetation, the age and health of system.
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Assets.
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The historical performance of the grid in those locations and multiple weather forecasts all within a family of machine learning models that are trained and validated using the historical performance on their system. And we can do that.
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More quickly and more cost effectively and more accurately than their in-house teams because it's something that we do all the time.
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So where we need their help is when we show them the results and we say, hey, it did really well with these storms. And Ohh yeah, missed the the forecast. It underestimated a bit or it overestimated a bit for this forecast. Why did that take place and they'll be like Oh well, you know that's a part of our grid that was just recently built out.
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Or hey, we had vegetation crews go through there just last month or ohh it was just one single. You know, there was actually a squirrel that took out a substation. So that wasn't a weather related outage at all.
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Well, and so that is where the partnership comes in. And so we work very closely with meteorologists, with the storm bosses to improve and validate the models. And because we're running it in the cloud, that is a much more efficient and cost effective solution.
00:23:26 Speaker 4
Steven, are there other non utility stakeholders that might have interest in the same data and analysis? For example insurance companies or there's, I've heard multi year wait lists for Transformers so they're suppliers who want to know.
00:23:43 Speaker 4
More in advance how to be ready to supply the materials for the restoration? Are there individuals? I'm getting notices now. You go on like Redfin or Zillow about the the weather risk. Is there an outage risk product for individuals when thinking about buying a home? Are there other solar or generator companies?
00:24:04 Speaker 4
Who want to target customers based on outage duration? I could think of a long list there. I know you're, you know, still an early stage company, but are there other stakeholders who are starting to show interest in the work that you're doing?
00:24:16 Speaker 2
Yeah, great question. And you're right, the Skype the limit in terms of the potential customers and consumers of this information and people that can benefit from it, so.
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To answer your question, there's a number of stakeholders that we've worked with, Emergency Management agencies who are interested in understanding where power outages may occur. Because there are people who have medical devices that are electricity dependent and so.
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When thinking about.
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Whether to.
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Evacuate and relocate those people to a safer location, understanding the probability of power outages is really important. We've worked with the FAA. They're very interested in understanding power outages and the likelihood that that would disrupt some of their operations.
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There are FEMA and DHS use cases related to power outages as well. So in the federal landscape there, there's a lot of interest at the state and federal levels for this information on.
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The commercial side, if you think about a Walmart or Home Depot, there are sales that are driven by power outages. So if you are going to have a prolonged power outage, you may acquire a generator in advance or you may after the storm.
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Purse.
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Need to buy a generator to keep all the steak in your freezer from going bad. Or if you're going to be preparing your residence to sustain and through a storm, you may be buying a lot of plywood or other supplies and so understanding the.
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Impacts before these events occur allow.
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Those vendors to have the right amount of materials in the right place at the right time and so that they can know they capitalize, but they can serve effectively serve their customers and meet the needs in the marketplace. On the insurance side, catastrophe.
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Models are are really important and so understanding the number of claims and the total insured losses from these types of storms.
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Many insurance companies want to get adjusters out in the field to help their customers more quickly file claims and keep customer satisfaction up. And so those things are opportunities as well as we're working on developing an individual.
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So like you mentioned, a homeowner or an individual person may want to have access to an app that says the probability of there being an outage at your place in the next 24 hours is.
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And this would allow you to make decisions about should you book a hotel room at the Holiday Inn, should you, you know, move some of the expensive stuff in your freezer to someone else's house should you have a party at your house on a particular day? Or maybe go somewhere else instead.
00:27:35 Speaker 4
Steven, your list included some categories that I didn't anticipate, which are government agencies. You mentioned FAA and FEMA and storm impact has actually received federal grants before. Can you tell us about the grants that you've received and how you secured those?
00:27:53 Speaker 2
Yeah. We have funding from.
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Through an SBIR program, the the NASA Ignite phase one and two grants or funding that we receive that are allowing us to leverage NASA Earth observations to optimize vegetation management for utilities. So to use satellites.
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To monitor vegetation growth and vegetation health in and around utility right of.
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Ways and to help them determine when and how often to trim particular circuits. Most utilities have a a standard trim cycle of three or four years, so they just come through and trim the same circuit on a on a fixed time scale. But of course based on weather conditions based on vegetation.
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Health based on insects and diseases and all those kind.
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Of things, there are cases where you might need to trim a circuit every two years and then another circuit may only need to be trimmed every six years, and so they can take the same budget and allocate it much more efficiently and reduce outage risk and improve electrical reliability by leveraging this.
00:29:06 Speaker 2
And there are other sources of that information, like Lidar.
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But Lidar is really expensive to fly and process, and so our partnership with NASA allows us to leverage NASA satellites as well as commercial satellites to provide that information over large areas. Because these service territories are are massive, and to do that in a very cost effective way.
00:29:32 Speaker 3
We talked about the solution and we've talked a bit about the stakeholders about the personal journey. You're you're at university, you're in Ohio. How how did you get into this?
00:29:42 Speaker 2
Great question Chris. I am not a business person by training. I did not ever anticipate starting a tech company.
00:29:51 Speaker 2
But I did it because of the opportunities that were presented as part of my research. I started at Texas A&M University and when I in my first year there sat next to an engineer who was working with an electrical utility and that engineer.
00:30:10 Speaker 2
Had questions about hurricane data and climate information, and we got talking and that very first conversation led to us developing a hurricane outage prediction model for Alabama power.
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And then over the years, we expanded and improved and automated this. I moved to Ohio State in 2016 and that opened up the opportunity for me to work with AEP, which is headquartered here in Columbus. OH, and also to be introduced to FirstEnergy.
00:30:44 Speaker 2
Which is in Akron. OH. And so that opened up so many of our existing utility customers were contracts to the university and then Ohio State is very.
00:31:00 Speaker 2
Much encouraging faculty to take the next step and to commercialize technology that is relevant and that there's a market for and they were very supportive in this journey. And so Mike, Co founders for storm impact are a research scientist who was in my lab at Ohio State.
00:31:21 Speaker 2
And an undergraduate student.
00:31:23 Speaker 2
Who? Who? Well, a person at the time who was an undergraduate student, he wasn't even in it. In my classes, his roommate was in one of my classes and I was saying, hey, I'm trying to build this dashboard. We want to do some coding. Does anyone know anyone who might be good at this? And then I got this e-mail out of the blue from Scott Hall and.
00:31:43 Speaker 2
It turns out this guy is an absolutely brilliant coder and he recently just finished.
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Is PhD in Planetary Sciences and so he is a we. We have a very bright team and dedicated team and that's been part of the the success of the company is the the great people that I get to work with.
00:32:07 Speaker 3
It's an amazing conversation. I just kind of one last question to we're running line on time here.
00:32:13 Speaker 3
What kind of impact economically do you have for the utilities? So how how big is savings or what kind of impact is being able to stage their equipment or have better forecasting make on the bottom line?
00:32:25 Speaker 2
Great question. It all comes down to helping them demonstrate a return on investment. And so if you think about a major storm response, a major storm response could cost a utility millions of dollars. And so from a hurricane for a.
00:32:45 Speaker 2
A large utility we're talking about.
00:32:49 Speaker 2
Many millions of dollars. And so if we can optimize that restoration and help them get the power back on a few days earlier and with the right number of crews, we can save them a few $1,000,000 per storm. And so the total savings per company depends on how many.
00:33:08 Speaker 2
Storms, they get. So I don't want to say that I'm cheering for utilities to experience a lot of outages, but the more major storms that they experience, the more times they rely on our model and the better off they'll be. If we add up those savings from from each one of the the storms that occur.
00:33:29 Speaker 3
Awesome, I appreciate this conversation. I want to thank you for coming on the podcast today. Steven, it's been a pleasure talking to.
00:33:34 Speaker 3
You thank you so much.
00:33:36 Speaker 2
Thanks for having me.
00:33:38 Speaker 3
For our audience, we hope you've enjoyed this content. If you did take a second right now and like and subscribe to our content, we'd love bring you the content. The likes help us get guests and we will see you again next time on the insiders guide to energy. Bye for now.
