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Robinson Meyer:
[1:26] Hi, I’m Robinson Meyer, the founding executive editor of Heatmap News. It is Wednesday, April 1. The electricity system is more important than ever, and the prices we pay for power are starting to reflect that. Last year, the increase in power prices outpaced overall inflation across the economy. The power grid was a huge issue in statewide elections, especially in New Jersey and Georgia. And in some parts of the country, especially the mid-Atlantic’s grid, PJM, we saw data centers begin to drive up overall electricity rates. We know the pressure in the system is building, although I think power prices are unlikely to exceed inflation again this year, thanks to the Iran war. Last year, utilities asked for more than $28 billion in rate hikes, and many of those hikes were approved by state regulators and are now essentially baked into the system and are going to be paid by customers this year or next year. But what’s funny about the power system, at least in the U.S., is that while I can kind of cite that statistic abstractly, it’s very hard to get a real-time look at the prices that people are actually paying for electricity. While we have retrospective studies in some states, it can be hard to know in real time why power costs are rising in some places and not others. Is it more competition for power? Basically, is there an electricity shortage? Is it that infrastructure costs are going up? Is it a big storm with extreme weather?
Robinson Meyer:
[2:42] That’s a problem for policymakers, and it’s provided an opening for Trump officials like Energy Secretary Chris Wright to claim that the simple presence of wind and solar on the grid drives up power rates. So I’m excited to announce in this very podcast that Heatmap has a new solution to this problem. With our partners at the Massachusetts Institute of Technology, we released today the Electricity Price Hub. It’s a public-facing electricity data platform that provides monthly utility level estimates of residential electricity rates and bills across the United States. So for the first time ever, you can go in there right now. It’s very user friendly. It’s on heatmap.news. And of course, it’s in the show notes, like go do it right now. And you can see how your state, your zip code, or your utility service areas, average power prices and bills have changed over the past six years. And you can see what part of the power system drove those changes? Was it generation? Was it transmission? Was it distribution? I don’t think there’s any other tool like this on the internet right now.
Robinson Meyer:
[3:45] I’m so excited that we were able to publish it at Heatmap. And today on Shift Key, I’m excited to dive into it. So joining us today on this episode of Shift Key are our partners in producing the Electricity Price Hub. I’m joined by Brian Deese. He’s an Institute Innovation Fellow at the Center for Energy and Environmental Policy Research at MIT. He’s also, of course, the former director of the White House Economic Council under President Joe Biden.
Robinson Meyer:
[4:06] Also joining me is Lauren Sidner. She’s a senior advisor at the Center for Energy and Environmental Policy at MIT. She’s also a former senior advisor to U.S. Special Presidential Envoy for Climate, John Kerry, also during the Biden administration. It’s all coming up on Shift Key. Brian and Lauren, welcome to Shift Key.
Brian Deese:
Excited to be here.
Lauren Sidner:
[4:29] Really good to be here. Thanks, Rob.
Robinson Meyer:
[4:31] As listeners will have heard, we announced a very exciting new tool on our website
Robinson Meyer:
[4:35] today, the Electricity Price Hub, and we’re going to talk about it in a second. But I want to start by talking about why this tool is important and what the state of the data was before this tool, what the state of our knowledge of the electricity system was before this tool. Because the electricity system, obviously, incredibly important to the U.S. economy, and yet it was something that it was very hard to understand in real time. So like prior to today, Brian, what was the state of our real time knowledge about the electricity grid and electricity prices? And how did that influence our ability to govern it?
Brian Deese:
[5:15] It may come as a surprise to people who have just seen all of the public reporting and news on this topic, that the state of our knowledge was really poor. It was a bit like the basketball player who was short, slow, and couldn’t shoot. So if you wanted to find data on electricity prices, one, almost all the data operated with a delay. You could find data three months, six months, 12 months delay. Two, the data is
Brian Deese:
[5:47] very aggregated at the state level or the national level, didn’t tell you much about what you were experiencing. And three, it was top level, what the electricity rate you’re paying, but it didn’t really tell you what you might actually be paying out of pocket. It didn’t tell you why, and it didn’t tell you what was driving those prices. So if you really wanted to ask the question of like, what am I paying in electricity today based on where I actually am and why am I paying that? It’s really hard to answer any of those things. And that was what motivated us. Was there a way to solve all of those problems together?
Robinson Meyer:
[6:25] And I remember as a reporter having these moments where we could say, okay, electricity inflation, according to CPI or according to PCE is running hot compared to overall economic inflation right now. But like, why was it so hard to get data on these topics? And what kind of delays are we talking about here? Is this like a month or two months? Because there’s already kind of this pass through time in the electricity grid, where like, if fuel costs go up today, it will take a long time for utilities to get those fuel costs approved by regulator and then pass them through to customers. Is that like the kind of delay we’re talking about? Or is this something more fundamental in the data.
Brian Deese:
[7:10] The principal reason why it’s tricky is a reflection of the electricity system we have in the U.S., which is we don’t have one system. We don’t even have a couple of systems. We have dozens and dozens of systems in the U.S. That are producing, transmitting, distributing, and utilizing power. And the structure of when that data is released, in what form it’s released, is a reflection of this patchwork of dozens and dozens and dozens of different jurisdictions around the U.S. And so to your point, there is data at the national level, CPI, CPI is inflation, within inflation data at the national level every month, how much is electricity price inflation going up compared to overall inflation? But that operates at the national level. If it’s disaggregated, you can find data that is operating with roughly a year delay. But even then, you have to be relatively committed to the proposition of going and looking at the data in each of these jurisdictions. And so you can get data for what’s happening in one utility jurisdiction in one state and one utility jurisdiction in another state. But you look and you say, well, but are those comparable? Because they’re presented in different ways. And it really is just a reflection of that patchwork electricity system we have in the United States.
Robinson Meyer:
[8:32] And that also, I would imagine, poses a big problem for policymakers because you can look at national level data, which I think is survey data, basically asking the same set of people who we survey kind of all the inflation data from, how much are you spending on electricity? And they’ll tell you. But then if you want to backtrack that to how much are...
Robinson Meyer:
[8:50] New Jerseyans spending on electricity? Or what do rising electricity costs in this state or this utility mean you should then do as a policy? Or why are they rising? Or what subcomponents are causing electricity prices to go up? Is this a data center thing? Is this a renewables thing? Like all of that, none of that is captured by data that before today was like close at hand or easy to access. Is that right?
Lauren Sidner:
[9:18] Yeah, that’s exactly right. It’s the kind of number of sources that Brian talked about. It’s the difference from one source to the next, just in terms of how the information is presented, whether it’s available in the first place. Oftentimes, you’ll have to pair information from one source with some estimates from federal reporting to be able to even interpret the information you get. The kind of main or kind of best-in-class federal data on this can give you a pretty good sense from one utility to the next, what the average rates look like, but it doesn’t tell you any of the kind of things that go into that rate. And so you can’t start to understand the kind of different drivers behind that. And then to your point earlier about what are New Jerseyans paying, there’s even within a state, there’s a huge range in terms of what’s happening. And so I guess it speaks to the real need for location, time, specific data. And that is just challenging given the number of places we’re talking about.
Robinson Meyer:
[10:14] What is the tool and how is this tool different?
Brian Deese:
[10:17] In basic terms, this tool will provide reliable, comparable data on a monthly basis on both electricity rates, what it costs for electricity and electricity bills, what people are paying at essentially the zip code level in states across the country. So for the first time, like we have with jobs or like we have with other sorts of data, every month, we will release data that is consistent, comparable, and reliable across those metrics. And it allows us to overcome those sort of the three problems of the basketball player, right? Which is, it’ll come out every month. It’ll come out at a level of granularity that allows you to say,
Brian Deese:
[10:59] Boy, I live in southern New Jersey, and it feels like I pay a lot more than my sister that lives in northern New Jersey. Is that the case? It’ll allow you to overcome that. And importantly, it’ll allow you to look into the rate data and say, what are the components of that rate. So if my rate is 100, how much of that is connected to generation? How much of that is transmission, distribution? It will break those things down. So our goal here is to provide that in a way that helps to make clearer what has been really hard to figure out.
Robinson Meyer:
[11:31] To kind of compare it to what used to exist, you would get these studies that would come out on a lag that would be able to disaggregate why rates had gone up in, say, California. And California, because it has the country’s most expensive electricity, or it’s consistently in the top five states, tends to get these very good research on the composition of its electricity rates. And you could look at California and be like, oh, they’re spending more on their distribution system. They’re spending more on this. That’s why rates are going up. I think this is the first time where you don’t have to wait for a study.
Robinson Meyer:
[12:05] You can look at states, you can look at zip codes, you can look at congressional districts, and you can say, oh, well, in the southeast, for instance, when rates are going up, or in even more specifically in this utility in Tampa, when rates have gone up, it’s because the distribution system is getting more expensive because of extreme weather. But when you look at parts of the mid-Atlantic, like central New Jersey or something, It’s because generation is getting more expensive because of data centers. This is like the first time we can actually, in a live way, compare why electricity prices are behaving the way they are across zip codes, utility service areas, states, like various kinds of jurisdictions across the country. It’s really cool.
Brian Deese:
[12:49] And I would say on that, Rob, that importantly, this tool is intended to empower all of the analysis that you just described. It is not actually a prescriptive tool that on its own, as of today, comes to all of those conclusions, but it provides the data in a consistent, repeatable way so that folks can do that type of analysis much more easily and across the country, not just in areas where there’s been enough focus or enough attention that people have really decided to research on its own.
Brian Deese:
[13:20] The other thing I should say about this is our goal is for this to be completely transparent, the methods and data architecture out there for people to explore, and completely open source in the sense that what’s one of the cool things about this partnership with you all and with Heatmap is that the goal is to put this data out into the open in a consistent, repeatable way so that we don’t have to operate with a lag for people to answer the question like that. So you can look and you can say, what are the components of transmission distribution? I want to be very clear. That doesn’t answer the policy question. It doesn’t. It doesn’t. What it does is it enables a more sort of intelligent exploration, research, debate dynamic around the policy question. That’s really the goal.
Robinson Meyer:
[14:01] So interesting, because in the current moment of the closure of the Strait of Hormuz, we basically have up to the minute data on gasoline prices because of this company, GasBuddy, and because of AAA that does daily compilations, we know, like...
Robinson Meyer:
[14:17] If gas prices, you know, of course, we know the macro environment is that there’s basically no oil transiting out of the Strait of Hormuz. But even on a subnational level, we can say, okay, well, Michigan is in the middle of a price cycle, which means kind of prices are happened to be going up at the moment. And also it’s experiencing supply constraints this way. We know up to the hour, basically, within states and localities, what people are paying for gasoline. While if you wanted like comparable data for the electricity system was like, you could maybe find out what people were paying in a state or possibly a region of the country three to 24 months ago.
Brian Deese:
[15:00] Gas prices are the most transparent price in our entire economy. Almost everybody lives within earshot of that price being literally displayed, where they drive, where they walk. It is the most transparent price. Electricity prices are among the least transparent because they’re so hard to find for all the reasons we just described. And even if you find them, most people, their lived experience is not what is the electricity price that I’m paying? It’s what’s my bill. Which is another part of this tool that I think is important, which is we are doing consistent data both on the rate and also the average bill paid. The bill is obviously a function of the rate and then how much energy you are consuming. And that’s important too, I think, to start to get closer to being more transparent is that for people and what they experience, the experience of what’s driving both the rate and the bills. They both matter.
Robinson Meyer:
[15:57] So let’s talk about how it came together. Like maybe Lauren, can you describe for us like how was data collected for this? If we’ve never had a resource like this before, where did the data come from and how is it compiled to form the numbers that we’re reporting in the database today?
Lauren Sidner:
[16:14] Yeah. So for our own unique new data collection, we sourced information on utility rates from two key sources, both official reporting. The first category was data reported by state regulators or other state agencies on a regular basis. So we have a set of states where we collect rate data directly from those entities for all of the utilities that they regulate. For the remainder of states, we, for those kind of larger utilities in each state, we collect the rate data directly from utility rate books. And what we collect is any rates associated with standard residential rate plan, along with any other charges that apply to the typical residential customer. We then take that and pair it with information primarily from the EIA on the average usage by residential customers in a specific place in a specific month to calculate a single average rate and then a single average bill for each month. And obviously, as rates go up, bills go up, but that relationship isn’t always exactly what you would expect. We just out of curiosity and for a fun exercise mapped every utility in our data set onto a set of quadrants that it was sort of the national average rate, the national average bill. And there are a surprising number of utilities that fall above the national average rate and below the national average bill or below the national average rate and above the national average bill. So those things don’t always line up because a lot of what ends up influencing bill is not just the number you start with, but also, you know, typical household size, climate conditions, the kind of basic efficiency of the typical household in a place. So a lot goes into that number. And so that’s why we thought it was important to keep both numbers in mind in the dataset and to get a more complete picture.
Robinson Meyer:
[17:58] That’s so cool. You know, when we are able to say, okay, well, generation is X% of the bill or X number of dollars in the bill and transmission is X number of dollars in the bill or distribution. Is that coming out of the Public Utility Commission data and the state level data? Is that coming from what the utilities describe in their rate books? How are we able to get that level of granularity about the data?
Lauren Sidner:
[18:22] Yeah. So like I mentioned, we collect the rates for any charge that would apply to the typical customer. We then go through each of those charges and identify any kind of function-specific charges. And we base that on the kind of definitional language included in the utility tariff document. Oftentimes those documents will include a formula that explains how a charge is computed. And so use that language to understand how best to classify a given charge. And so we categorize those that can kind of neatly be sorted into one of our categories. It’s not always the case. There are going to be charges that cover multiple of the categories or straddle multiple of the category. So then for those, we go into the actual regulatory filings. The most frequent example of this is base rate charges. And there we pull the relevant utility regulatory filings that describe the kind of total revenue requirement, what they need to earn to cover all of their costs and the return on capital, and specifically look at what has been allocated to the residential customers and how those costs have been functionalized in those filings, the functional breakdown of the total amount in their filings.
Robinson Meyer:
[19:30] I’ve been a climate reporter for a long time, but kind of I had an interregnum during COVID where I helped run and put together and report on a volunteer project to collect COVID data from states. What I learned from that project is that every number in a database took incredible amounts of work to get, and actually a lot of discussions about where you should categorize something and where the cutoff is and what’s on the cusp. Like every number in a database has a.
Robinson Meyer:
[20:04] Often put together by human hands, not in a synthetic way, but there are so many decisions that go into making something that you can then cite as data that people don’t even realize when they think about it. Let me ask one more question, and then I want to get into the kind of what the stories here are. Sometimes we’re talking about electricity prices, and we’re talking about electricity bills. And I think what people will see when they play with a tool online is that there are some states that have very expensive electricity prices and then actually moderately sized bills. And there’s some states that have pretty good electricity prices, but then very expensive bills. And we can get into that story more and I want to, but if you were to take a look at your power bill, there’s a lot of charges on there that are not called your electricity rates, but nonetheless, are part of the price you pay for electricity. And I think you guys have dealt with this in a really interesting way. So can you just describe like, when you report an electricity price, is that just the electricity residential rate that’s been described by the utility? Or basically, what else goes into the number you describe as an electricity price?
Lauren Sidner:
[21:17] In every case, we are trying to capture the entirety of the typical residential customer’s bill. And so we capture what you just described as sort of the standard residential rate charges. And we add to that all the additional riders and adjustments that the average customer would also see. We don’t include any kind of voluntary charges or opt-in type of charges, but we do capture the kind of full extent of what would show up on a bill. And it’s worth noting too, that there’s a ton of variation in how that information is presented in the bill to the customer, how user-friendly that information presentation is in the end, and how readily customers are able to kind of understand the different pieces of the bill based on that.
Robinson Meyer:
[23:25] Let’s get into stories. One of the key distinctions that people will see the second they open the tool is that we distinguish between rates and bills. Why is it important to think about the rates and bills story separately? And what did you learn from looking at electricity rates and looking at electricity bills?
Brian Deese:
[23:46] The single most important thing is understanding when you have an issue where people are paying a lot for electricity, understanding what component of that is rate, what component of that is bill. In some ways it’s like the first question in answering the why, the like what’s going on, right? There’s an interesting story going on in Alabama, where if you look at Alabama and you look at rates are not particularly high and rates are not rising particularly fast. But Alabama, the typical residential customer in Alabama, uses a lot of electricity.
Brian Deese:
[24:24] Principally because you have to do a lot of cooling and because you’ve got less efficient buildings, houses in the state. And so as a result, the typical household in Alabama is paying in bill a lot compared to other parts of the country. And what’s interesting about that is in 2026 in Alabama, for the first time in at least a decade, if not more, there are now competitive Public Utility Commission elections going on. And in the context of that competitive election, there is now an active political debate around should Alabama Power in particular be required to change the way that it does its regulatory and rate setting?
Brian Deese:
[25:08] Fundamentally, that story is a story about the bills that people pay, right? And you could slow the growth in the electricity rate in Alabama and not actually get at the core thing that’s bugging people or that is an economic drag on people, which is that they’re paying high electricity bills just because of that. And the inverse of that is also true. There are parts of the country where the rates are increasing very quickly, but people’s bills are actually lower than others because they live in places where either you’re spending less on heating and cooling and/or where they live in more efficient homes or they work in more efficient buildings. So you really need to, I think, as we get going from the data to the why and what’s going on in any given place, understanding the rate and bill distinction is like, I think it’s like the first step. It’s the first step in most of these places is you want to ask what component of this is being driven by rates, what components are being driven by bills, and then you go to the next step of what’s behind either or both of those.
Robinson Meyer:
[26:09] In some ways, bill is what matters the most in terms of how people actually think through their electricity system. What’s an example of a place where rates might be increasing really quickly, but bills aren’t surging in the same way?
Lauren Sidner:
[26:23] Wisconsin, Michigan, Arizona all have rates that are above the national average, but bills that are below the national average.
Robinson Meyer:
[26:31] Huh. This stuck out to me looking at New York State too, honestly, is that if you look at Con Ed, which is the main utility for Manhattan and parts of Queens and parts of Brooklyn, you say, oh, the rates are really bad. But if you look at the bills, it’s like, oh, well, people have tiny apartments. They’re just not buying that much electricity every month.
Brian Deese:
[26:48] Bills matter in an absolute sense, but rates do matter in a relative sense, because people’s lived experience is also not just about it’s why inflation has the unsettling economic effect that it has, which is that as prices go up, even if they’re off a lower base — your point about Manhattan is a good one, which is it’s a good example of sort of high rates, low bills. But if the rate of increase of the bill is going up, then it also means that people are going to feel this more.
Robinson Meyer:
[27:17] And it’s complicated because from a utility revenue perspective, the bill is also what matters. And if you think about from a systems perspective, and the utility is trying to recoup the costs of running its system and then make a profit, the volumetric rate is a technical mechanism it uses to like allot the costs of running its system. But actually, the size of the revenue that it receives from each household matters far more in terms of its ability to turn a profit, to cover its cost, to invest further in the system. Like that is the number that matters in terms of actual upkeep for the system. Although I still find it requires a bit of a brain reformatting to remember that’s actually how the entire power grid works.
Brian Deese:
[27:57] It’s why it has been so difficult for us to figure out how to credit efficiency within our system. Because in an overly crude way, if the bill matters, then the utility actually wants to avoid incremental efficiency, which is not true in practice, but the mechanism to actually credit efficiency, whether that efficiency is actually at the household level or is efficiency of the system, efficiency of the grid, capacity and storage. All of those things run into this basic challenge, which is if you make the system more efficient, the utility often doesn’t get paid for it.
Robinson Meyer:
[28:36] This is one of the classic problems that I think we’re now struggling with in terms of governing utilities. I mean, when you looked at individual states or individual political jurisdictions, were there any that stood out where you were like, man, you can really see in this state the difficulty of utility governance or the difficulty of incentivizing utilities or customers to be more efficient in their energy use?
Lauren Sidner:
[28:59] A good number of states have adopted mechanisms that try to do away with the sort of internal disincentive to support efficiency. So very frequently, you’ll see charges that allow utilities to recover the costs of efficiency programs. But you will also, in maybe a more limited number of examples, see charges that allow utilities to recover the revenue that they lose because of those programs or because of distributed energy or other policy-related aims that may be in place. I believe Arizona has that kind of recovery mechanism, but it’s not uncommon. And then occasionally in states like California, you’ll see charges that will give a benefit to a customer for using less power. So it’ll be a tiered charge where if the customer kind of stays within the lower tier, they can actually get sort of a bill credit or something along those lines. So they sometimes even build it into the rate design in addition to just making sure the utility is made whole for supporting that kind of investment.
Robinson Meyer:
[29:58] You both now have come kind of up to the coalface of electricity pricing mechanics and seen at the data level, you know, how the generation system, the distribution system, the transmission system come together to form an electricity price, which then is assessed through bills. What did collecting this data, interacting with this data, change your mind about?
Brian Deese:
[30:23] For me, it increased the urgency around actually challenging and reforming these incentive models to try to get to the most efficient and best outcome for the rate payer. And in fact, the underlying complexity through rates and bills and the components thereof reinforces the challenge that oftentimes in this process, the end ratepayer, the end consumer, and their end experience gets kind of lost in that complicated process. And so for me, it reinforced that we’re not going to shift from a local and utility jurisdiction to a state to a regional to a federal, we’re not going to shift in, it’s neither feasible or advisable to have a single national electricity system, I don’t believe. But yet we need to be more aggressive and more creative about testing, challenging, and then scaling reforms to these systems to actually get to that outcome. I think that was the thing for me that was the most. And it goes back to when I was in government and we were thinking about the scope of national authority, which typically runs through FERC. FERC is the federal regulator charged with oversight. That there has been a real dispositional reticence to having FERC play a more assertive role because of this idea that states and individual utility jurisdictions are really where the action is at. This process challenged that thinking from my perspective. And I think that to really challenge and get that kind of constructive reform, you need to have a more full-throated national role, not to take over at a national level, but to exert that national authority, not just as a nudge, but as a hard nudge in the direction of a sort of more pro-consumer outcome to the grid.
Robinson Meyer:
[32:12] Lauren, what did just coming up against this data change your mind about?
Lauren Sidner:
[32:16] Yeah, going in, I kind of recognized the patchwork fragmented nature that Brian described earlier. But it was just really stark to me that there’s huge, huge variability in the kind of information environment from one state to the next, how easy it is to find kind of critical bits of information, how kind of user friendly regulatory filing systems are, how easy it is for people to understand just the basic makeup of their bills. I mean, there’s just a really wide, wide range across different states. And even in the absolute kind of best case of that, the utility still has this huge information advantage. And there’s a giant gap between that sort of best case and a lot of states. And so when you try and think about kind of identifying the right solutions that are specific to a given player or tailored to the challenges that exist in a given place, I think starting from fixing utility incentives to operate in a way that, like Brian said, is more consumer friendly is going to be really critical.
Robinson Meyer:
[33:14] What states stuck out to you as being the smartest or the most pro-consumer in how they represented and shared this information?
Lauren Sidner:
[33:20] I’m not sure I can name a single state. There were good practices that stood out from one state to the next. Finding basic information in regulatory filings was really surprisingly quite easy in South Carolina. So the South Carolina Commission provided helpful kind of summaries of the outcomes of different regulatory proceedings and what it would mean for consumers’ bills, for example. There were states that stood out because of the way they present the information in a bill. There were states that stood out because they compile and report in a standard way all of the kind of rates and bills for the utilities that they regulate. So I think there was no one best practice, but there were examples of things that were quite helpful from one state to the next.
Robinson Meyer:
[34:03] Looking at the results, what has been striking to me is, I mean, first of all, you look at the price data and you go, wow. Looking at the Continental 48, right? California sticks out. And I think the Northeast sticks out when you look at prices. And I think that’s a story that has become better understood over the past six or eight months. I would say that if you’re looking at inflation and electricity rates, where the price levels are the worst is New England, which has kind of its own islanded energy issues and has, as we’ve talked about in previous episodes, challenges with winter peaks and fuel availability, and California, which is kind of famously its own, has its own regulatory apparatus. But when you look at bills, the story becomes really different. And suddenly the Southeast and parts of the interior, which seem to have quite cheap power on a kilowatt hour basis, look like they’re really failing. And Tennessee, for instance, Alabama, that these places actually charge a lot of money on a monthly basis for power because of maybe an old building stock, because people have to buy a lot of power because of their cooling needs, because of maybe bills there are increasingly volatile. And like what stuck out to me is the success stories here. I have no other information to back up, but just like doing a facile reading of the data is like, it’s the Southwest.
Robinson Meyer:
[35:25] It’s Texas, Arizona, and New Mexico that both have pretty cheap power rates and also pretty cheap electricity bills, despite extremely high cooling needs. At this point, I’m not surprised by a lot with ERCOT, but I think the Southwest was really impressive in that regard.
Brian Deese:
[35:43] So, Rob, I was going to say, I think that this, for me, reinforced that we just have a lot to learn from Texas. And that’s not in any way a sort of whole scale or simplistic endorsement of ERCOT, right, with all its complexity. But you are getting lower prices, lower bills, and more cheaper and efficient sources of generation and distribution onto that grid. And those things are related. I guess on reflection with the data, it is not a total surprise that the system that enables the quickest and most efficient deployment of cheap and efficient power onto the grid is also the place that can navigate that dynamic of relatively lower prices and relatively lower bills. Nothing in this space is simple. So that doesn’t mean that we can just take that Texas model and stamp it out in every jurisdiction. But I also think it means we —
Robinson Meyer:
[36:35] For one thing, the Permian only exists in a couple of states, which really helps as does the huge wind alleys and solar alleys. But there’s so much more that we could be —
Brian Deese:
[36:45] Geography matters, temperature matters, density matters. But I think it causes me to say we need to challenge … There are so many settled, accepted views in this space that need to be challenged. The idea that we couldn’t do any of those things in PJM or in the Northeast because of those fundamental differences, I think needs to be challenged. It needs to be challenged more aggressively at the federal level, and needs to be challenged more aggressively at the state level. And I think we’re starting to see that happen.
Robinson Meyer:
[37:17] Let’s talk about PJM for a second and the Mid-Atlantic, because I think that has really dominated the electricity discourse recently. It does seem to be the part of the country where you can point most directly and say, power is getting more expensive in PJM. And that is at least in large part because of data centers. When you were able to look under the hood in PJM, what did you see? Like, what nuance are we missing by telling this data center PJM story? And are there some places in PJM that are maybe handling new demand or new capacity better than other places and able to keep bills from going up as much as maybe some large swaths of the grid are?
Brian Deese:
[37:57] Well, let me jump in first and then, Lauren, you should jump in on PJM too, because I think it is such an interesting story. For me, the PJM learning was the value of actually going under the hood and being able to solve the second problem of the, I guess, the basketball player who was slow, of actually being able to go down at the intra-regional level, right? Because PJM as a jurisdiction, you’re seeing exactly the price dynamics that you described. Within that, if you look at individual utilities, you see the largest skew, the largest distribution of outcomes, right? So you see the skew from literally a 30% increase in rates to a 5% decrease in rates. And then you look at how much of that is generation related, right? Charges associated with generation, and you see as high as a 40% increase and a 10% decrease, right? And so within those jurisdictions, within PJM as a whole, there is a lot to learn, again, about what’s going on in those particularly spiky jurisdictions and those that are managing that.
Robinson Meyer:
[39:03] Let’s get specific. So which jurisdictions are maybe handling this better?
Lauren Sidner:
[39:07] There are a variety of factors at play in the kind of range that Brian just described. And so it’s less that there’s specific parts of the region that are handling it better than others, because I think types of things that come into play are, there are some of the utilities that don’t participate in the capacity auction. And so they haven’t been as affected as others by the kind of very recent trends. There are some that own their own generation capacity and own their own generation assets, so maybe sort of buffered from some of those impacts. But then there are also kind of pockets or regions within the broader region that have very particular capacity constraints because there isn’t a lot of generation capacity with, you know, local generation capacity. Or there are kind of grid bottlenecks that are keeping cheaper sources of energy from flowing into those particular places. So it’s a kind of aggregation of all those things that are adding to this patchwork. And so we kind of have this settled wisdom of interconnection bottlenecks or slow interconnection timelines and grid constraints are driving this sort of region-wide trend. But in reality, the picture looks pretty different from one part of the region to another.
Robinson Meyer:
[40:16] Another story we’ve been telling about the power grid is that extreme weather is starting to make prices worse and starting to make bills go up. And that’s absolutely famously the story in California where the huge amount of adaptation to wildfires they’ve had to do, the huge amount of rebuilding after wildfires that they’ve had to do of the distribution grid and the transmission grid as well has really driven up rates, of course, as has the insurance costs. Is that just a California story or are there other places around the country where you look and say, wow, extreme weather, whether or not it represents climate change or not, is helping to drive up power prices in this maybe surprising place that people haven’t thought about yet?
Lauren Sidner:
[40:58] I think you’re right to point out California. It is definitely an extreme example here. We’ve seen the distribution part of the bill for parts of the state as much as or more than double in five years. And that’s in large part driven by the different types of costs that are coming because of wildfires, whether it’s repairs or preparing for wildfires or whether it’s liability resulting from those disasters. But it’s really not just California. And I think we’re going to, it’s that this trend is just going to continue. One of the biggest transmission and distribution utilities in Texas is just concluding a rate case. And by their own kind of description, they requested an increase in annual revenue of something like over $800 million. And they, by their own description, say that the largest kind of portion of that increase is attributable to storm damage over the last three years. And then across the country, but particularly in places like the Southeast and Florida, we’re seeing utilities have these additional charges that show up on people’s bills. And those charges have just kind of shot up over time. So Tampa Electric, for example, it has storm protection charge. It added a temporary storm-related surcharge to deal with some of the costs that have added up over the past few years. And the trend in those over the last five years has been really stark. It’s more than doubled over that period. And that is not unique to Tampa Electric either. And so I think throughout the country, this is going to be adding to distribution and other grid costs going forward.
Robinson Meyer:
[42:20] What other states linger in your thinking or other zip codes or utilities where you’re like, wow, you just encountered it and it really revealed something to you about the power grid?
Lauren Sidner:
[42:31] Maybe I’d point to Virginia, where we collected data on the two largest investor-owned utilities in the state. And a big part of the story there to me is that more and more of the bill is flowing through these other charges. And there’s just an enormous number of charges that go into residential customer bills in Virginia, which speaks to this question of utility incentives that we’ve touched on a couple times. But, you know, if utilities are able to just immediately pass costs through to customers, regardless of how they kind of line up with or relate to kind of projected or budgeted costs, there’s not a whole lot of built-in incentive for the utility to manage that. So that stood out, not just because it took forever to collect the data there, but …
Brian Deese:
[43:15] Another place that stood out to me was New Jersey, where obviously the politics of electricity prices have been front and center, including because of the gubernatorial election last year. And what’s interesting about New Jersey is not only a rising rate environment, but pockets of extraordinary volatility. So if you look at Atlantic City or Rockland Electric in that part of New Jersey, you see 200% plus swings in electricity prices intra-year, within the year, right? And that’s increasing significantly. This is just speculative, but I think that volatility, and this is for study, for other people to study based on the data, but I think that volatility is in part connected to the more extreme weather patterns that you’re seeing in this space. And I also think it connects to the lived experience in the politics of this issue, that it’s both about prices, but also volatility that leave people with the sense that something is different about the way that they are having to pay for the electricity that they tend to rely on than has been in the past.
Robinson Meyer:
[44:22] In some ways, the worst case scenario here is that electricity, which I think is already. Depending on where you live, the biggest or the second largest energy expense for most American households, becomes more like gasoline, but with even less price transparency than gasoline. Like gas can get really expensive. It has enormous volatility, but people tend to know what it costs. That’s one reason it’s so politically salient. If electricity becomes just as volatile and people fear the experience of opening their bills and not being able to predict their monthly expenses around electricity in the same way that they might struggle to predict it with gasoline or they might have to change other spending habits to accommodate higher gas prices, then that is bad for the economy. It’s bad for electrification. It’s really bad for decarbonization because if our whole goal here is to get people to shift from liquid fuels and oil and gas to heat pumps and especially electric vehicles. If they have the sense that electricity prices are as volatile as gas prices, that is really, really bad for the whole project.
Brian Deese:
[45:35] Yeah, like one of my goals and hopes in this whole project is that we can make electricity prices just more transparent and understandable. And it is complicated, but just because it is complicated doesn’t mean it has to be non-transparent. And so one of my hopes in this course here is to say, we’re now going to produce this data and make it more publicly available and try to bring a clearer sense that even if the underlying drivers as to why we are getting to the prices or the bills that people are paying are not straightforward, the prices and the bills that people should be paying should be, and they should be transparent. And there’s no reason why states, jurisdictions, utilities can’t get better at doing the things that would make it easier for us to hopefully, you know, ultimately, we can put the energy price hub out of business by just making all this data really freely available, I think, for some period of time until the system adapts to that. But look, that’s one of the goals is let’s just make this transparent. That alone is not going to bring electricity prices down, but it’s a step in the process.
Robinson Meyer:
[46:35] One of the things I’m most excited about is being able to continue to follow this data on a monthly basis and see emerging trends in the system and have you back on Shift Key to talk about them and to analyze them. And until then, we’ll have to leave it there. But thank you so much for joining us, Brian and Lauren. And people should check out. We’ll put it all over the show notes. It will be impossible to miss if you follow any heat map or shift key distribution channel. But the Electricity Price Hub, you should go check it out. You should go play around with it. Type in your zip code, type in your congressional district, type in your enemy’s zip code and congressional district, click around. There’s so much there to learn and see and explore. And I think we’re only just getting started in understanding all the data that you’ve made available through this tool.
Brian Deese:
[47:18] And give us feedback too, because this tool will get better the more that we publish it and the more that we have feedback as well. So thank you, Rob.
Robinson Meyer:
[47:24] Well, hey, thank you for joining us today on Shift Key. Thank you, Brian. Thank you, Lauren.
Lauren Sidner:
[47:27] Thanks, Rob.
Robinson Meyer:
[47:33] That will do it for today’s episode of Shift Key. I implore you, though, go play around with the Electricity Price Hub. You can find it on heatmap.news. You can find it in the show notes. I am sure the most interesting things to learn from this tool have not yet been learned. We haven’t found them yet at Heatmap or at MIT. So go look at your state. Go look at your zip code. Go look at the utility that you hate the most. Go look at the utility that you work for. Like, this is your moment. Go play around because it is such a rich data set and there’s so much information in it. I am just sure that one of our readers is going to find something so interesting that’s going to help all of us understand the electricity system better and better formulate policy. If you do find something let us know we’re at shiftkey@heatmap.news or editors@heatmap.news you can also find me of course on Twitter, BlueSky, or LinkedIn. Always feel free to reach out. Until next time, Shift Key is a production of Heatmap News. Our editors are Jillian Goodman and Nico Lauricella. Multimedia editing and audio engineering is by Jacob Lambert and Nick Woodbury. Our music is by Adam Kromelow. Thanks so much for listening. See you next week.
