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Debunking Trump’s Claim of “War on Beautiful, Clean Coal” Using Graphs

In President Trump’s first State of the Union Address last week, a wide range of topics in the Administration’s agenda were covered extensively while energy was largely pushed to the side. Trump did include two sentences on his self-described push for “American Energy Dominance,” and these two sentences sent wonks in the energy industry into a frenzy on social media:

“We have ended the war on American energy. And we have ended the war on beautiful, clean coal.”

My Twitter feed lit up with various energy journalists and market watchers who noted the impressiveness that just 18 words over two sentences could contain so many misleading, or outright false, claims.

Source

As one of those energy reporters who immediately took to Twitter with my frustration, I thought I would follow up on these statements last week with arguments why the claims of ‘clean coal’ and the supposed ‘war’ on it do not reflect the reality the Trump Administration would have you believe, and I’ll do so with just a handful of graphs.



What is ‘clean coal’?

As a pure fuel, coal is indisputably the ‘dirtiest’ energy source in common use in the power sector, accounting for about 100 kilograms (kg) of carbon dioxide (CO2) per million British thermal unit (MMBtu) of energy output. This output is notably larger than other major energy sources, including natural gas (about 50 kg/MMBtu), petroleum products like propane and gasoline (about 60 to 70 kg/MMBtu), and carbon neutral fuels like nuclear, hydroelectric, wind, and solar. In the face of the scientific consensus on CO2’s contributions to climate change, many have noted that one of the best actions that can be taken in the energy industry is to shift away from coal to fuels that emit less CO2— which has definitively given coal a dirty reputation.

The premise of ‘clean coal’ is largely a PR push (literally invented by an advertising agency in 2008)– an ingenious marketing term, but one that does not have much in the way of legs. When you hear politicians talking about ‘clean coal,’ it is usually referring to one or more of the following suite of technologies:

  • Washing coal before it’s burned to remove soil and rock and thus reduce ash and weight of the coal;
  • Using wet scrubbers on the gas generated from burning coal to remove the sulfur dioxide from being released;
  • Various carbon capture and storage (CCS) technologies for new or existing coal plants that intervene in the coal burning process (either pre-combustion or post-combustion) to capture up to 90% of the CO2 produced from its burning and then sending it miles underground for permanent storage instead of releasing it into the atmosphere; or
  • Anything done to the coal-fired power plant to increase the efficiency of the entire process of generating electricity (e.g., the 700 Megawatt supercritical coal plant in West Virginia that is so efficient it reportedly releases 20% less CO2 than older coal plants) and reduce the overall emissions.

Source

When most in the energy industry discuss ‘clean coal’ technology, they are typically referring to CCS. However it should be noted that Trump did not mention CCS by name in this (or any) speech. Some analysts have noted that the White House’s attempts to cut CCS funding and send the Secretaries of the Department of Energy (DOE) and Environmental Protection Agency (EPA) to supercritical coal plants are not-so-subtle hints that the Trump Administration’s preferred type of ‘clean coal’ is improving the efficiency of coal-fired generation. Even Bob Murray, the influential coal magnate, has written to the President to indicate his contempt for CCS, calling it a ‘pseudonym for no coal,‘ echoing the concerns of many proponents of coal that CCS is being pushed as the only ‘clean coal’ option so that if/when it fails (due to economic impracticalities) it would be the death knell of coal-fired generation altogether.

So regardless of which ‘clean coal’ technology the Trump Administration supports, issues remain. With regard to wet scrubbers, coal washing, and general plant efficiency improvements, the reductions in CO2 emissions are not nearly enough to compete with cleaner fuels. Even if all coal plants could be made 20% more efficient (and less reduce CO2 emissions by about 20%) like the West Virginia supercritical plant, which would be a massive undertaking, it would still result in coal generation being among the dirtiest energy in the country.

With regard to CCS, not only is the cost one of the biggest issues (which will be looked at in more detail later), but it does not remove all the pollutants from burning coal. Even with the most effective CCS capturing 90% of CO2 emissions, that leaves 10% of CO2 making its way into the atmosphere along with the other notable pollutants in coal gas (including mercury, nitrogen oxide, and other poisonous contaminants). When compared with the carbon neutral energy sources increasingly gaining ground in the United States, coal plants with CCS still hardly seem clean.

Again, the Energy Information Administration’s (EIA) listing of carbon dioxide emissions coefficients shows the CO2 emissions associated with different fuel types when burned as fuel. As previously noted, coal is the far-away leader on CO2 emissions coefficients as a pure fuel. In DOE analysis of future-built generation (an analysis that focuses on the costs and values of different types of power plants to be built in the future, which will come up again in more detail later), the only type of coal generation even considered is coal with either 30% or 90% carbon sequestration, with 90% being the technological ceiling and 30% being the minimum example of new coal-fired generation that would still be compliant with the Clean Air Act. The below graph, our first in demonstrating the issues with claims of a ‘war on beautiful, clean coal,’ plots the CO2 coefficients of major fuel sources in the U.S. power sector, including coal using no CCS, 30% CCS, or 90% CCS. Existing power plants do not have the same requirements under the Clean Air Act, so they might still be producing CO2 at the far right of the ‘coal’ bar (indeed, last year almost 70% of U.S. coal was delivered to power plants that are at least 38 years old meaning they are likely far from the most efficient coal plants out there). Coal plants that are touted as ‘clean’ because of their up to 20% increases in efficiency would still find themselves in the same (or greater) range of emissions as 30% CCS coal plants, while 90% CCS coal plants appear to the be the only ones that can compete with other fuels environmentally (though it comes at a potentially prohibitive cost, which will show up in a later graph).

Note that the data for these CO2 emission coefficients come from this EIA listing. The lines for 30%/90% CCS are not just drawn 30%/90% lower, but rather account for the presence of CCS requiring more energy and thus cause a dip in efficiency– this graph uses the rough efficiency drop assumed for CCS plants in this International Energy Agency report

These numbers paint a scary picture of coal and are the source of what causes many energy prognosticators to scoff at the utterance of ‘beautiful, clean coal,’ though it is important to be clear that these numbers don’t tell the whole story. While nuclear and renewable energy sources do not emit any fuel-related CO2, they are not completely carbon neutral over their lifetimes, as the building, operation, and maintenance of nuclear and renewable generation plants (as with any utility-scale generation source) all have their own non-zero effect on the environment. However, since fuel makes up the vast majority of carbon output in the electricity generation sector, any discussion of clean vs. dirty energy must return to these numbers.

Further, the separation of dispatchable vs. non-dispatchable technologies (i.e., energy sources whose output can be varied to follow demand vs. those that are tied to the availability of an intermittent resource) shown in the above graph is important. Until batteries and other energy-storage technologies reach a point technologically and economically to assist renewable (non-dispatchable) energy sources fill in the times when the energy resource is unavailable, dispatchable technologies will always be necessary to plug the gaps. So regardless of what drawbacks might exist for each of the dispatchable technologies, CO2 emissions and overall costs included, at least some dispatchable energy  will still be critical in the coming decades.

Who is orchestrating the ‘war on coal’?

Even with the knowledge that coal will never truly be ‘clean,’ the question then becomes why haven’t the advancements in coal energy that is cleaner and more efficient than traditional coal-fired plants become more prominent in the face of climate and environmental concerns? The common talking point from the Trump Administration is that there is a biased war on coal being orchestrated, and the actions of President Trump to roll back regulation is the only way to fight back against this unjust onslaught that the coal industry is facing. But again, from where is this onslaught coming?

The answer to this question is actually pretty easy– it’s not regulation that is causing coal to lose its place as the king of the U.S. power sector, it’s competition from more affordable energy sources (that also happen to be cleaner). The two charts below demonstrate this pointedly, with the left graph showing the fuel makeup of the U.S. electric power sector since 1990 along with the relative carbon intensity of the major CO2-emitting fuel sources, while the right graph shows what’s happened to the price of each each major fuel type over the past decade. The carbon intensity shown on the left graph is even more indicative than the first graph above in detailing the actual degree to which each fuel is ‘clean’ as it factors in the efficiency of plants using the fuel and indicates the direct CO2 emissions relative to electricity delivered to customers.

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Note that the costs are taken from this EIA chart, with coal taken from fossil steam, natural gas taken from gas turbine and small scale, and wind/solar taken as the gas turbine and small scale price after removing the cost of fuel. Electric power generation and carbon emission data taken from this EIA source

Just from analysing these two graphs, a number of key observations and conclusions can be made about the electric power sector and coal’s evolving place in it:

  • In 1990, coal accounted for almost 1.6 million Gigawatt-hours (GWh) of power generation, representing 52% of the sector. By 2016, that figure dropped to 1.2 million GWh or 30% of U.S. power generation.
  • Over that same time period, natural gas went from less than 400,000 GWh (12%) to almost 1.4 million GWh (34%); nuclear went from less than 600,000 GWh (19%) to over 800 GWh (20%), and combined wind and solar went from 3,000 GWh (0.1%) to over 260,000 GWh (6%).
  • While the coal sector’s carbon intensity hovered around 1.0 kg of CO2 per kilowatt-hour (kWh) of electricity produced from 1990 to 2016 (even as CCS and other ‘clean coal’ technologies began to break into the market), natural gas dropped from 0.6 kg CO2/kWh to less than 0.5 kg CO2/kWh, while nuclear, wind, and solar do not have any emissions associated with their generation (again noting that there are some emissions associated with the operation and maintenance of these technologies, but they are neglible compared with fossil fuel-related emissions). The drop in natural gas carbon intensity combined with coal losing ground to natural gas, nuclear, and renewable energy led the electric power sector’s overall average carbon intensity to drop from over 0.6 kg CO2/kWh to less than 0.5 kg CO2/kWh.
  • While the narrative some would prefer to push is that coal is getting replaced because of a regulatory ‘war on coal,’ the real answer comes from the right graph where the cost to generated a kWh of electricity for coal increased notably from 2006 to 2016. Meanwhile, natural gas (which started the decade more expensive than coal) experienced a drastic drop in price to become cheaper than coal (thanks to advances in natural gas production technologies) while the low cost of nuclear fuel and ‘free’ cost of wind and solar allowed these energy sources to start and remain well below the total cost of coal generation. This natural, free-market competition from other energy sources, thanks to increasingly widespread availability and ever decreasing prices, is what put pressure on coal and ultimately led to natural gas dethroning coal as the predominant energy source in the U.S. power sector.

What these two graphs show is that the energy market is naturally evolving, there is no conspiratorial ‘war’ on coal. The technologies behind solar and wind are improving, getting cheaper, and becoming more prolific for economic, environmental, and accessibility reasons. Nuclear power is holding strong in its corner of the electricity market. Natural gas, more than any other, is getting cheaper and much more prominent to the U.S. power sector (while having the benefit of about half the CO2 emissions of coal), which is what has made it the natural ‘enemy’ of coal of the past decade or two. All that’s to say, the only ‘war on coal’ that’s been widespread in recent memory is a capitalistic, free-market war that will naturally play out when new energy sources are available at cheaper prices and contribute significantly less to climate change.

Will Trump policies reverse the course of coal in the United States?

Going back to the statement from Trump’s State of the Union Address, he claimed that his Administration had ended the war on clean coal. As stated previously, there was never an outward war on coal that was hindering the fuel. Even still, the main policy change from the Trump Administration with regard to coal was to repeal the Clean Power Plan (CPP) that aimed to cut carbon emissions from power generation.  However, many analysts predicted that would not change the current trends, as repealing the CPP does nothing to reverse the pricing pattern of the fuels. Indeed, this week EIA released its Annual Energy Outlook for 2018 and confirmed the tough future that coal generation has compared with natural gas and renewables– both with and without the CPP. While the CPP reduces the projections of coal generation, it doesn’t move the needle all that much and natural gas and renewables are still shown to surpass coal.

Source

So the major policy decision of the Trump Administration with respect to coal generation doesn’t appear to reverse the course of coal’s future. Again, this conclusion isn’t terribly surprising considering the economics of coal compared with other fuels. EIA projects the Levelized Cost of Electricity (LCOE) for different type of new power generation (assumed to be added in 2022) which serves to show the relative costs to install new power generation. In the same analysis, EIA projects Levelized Avoided Cost of New Generation (LACE), which can be thought of as the ‘value’ of the new generation to the grid (for more detailed description in the calculations and uses of these measures, read through the full report). When the LACE is equal or greater than the LCOE, that is in indication of a financially viable type of power to build (evaluated over the lifetime of the plant). So by looking at the relative costs (LCOE) of each power type and whether or not they are exceeded by their values (LACE), we can get a clear picture of what fuel types are going to be built in the coming years (and to continue the focus on whether coal or other fuels are ‘clean,’ let’s put the economics graph side-by-side with the CO2 emissions coefficients):

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Note that the source of the data on the left graph is the EIA Levelized Cost of Electricity analysis, with the ends of the boxes representing the minimum and maximum values and the line in the middle representing the average– the difference in possible values comes from variations in power plants, such as geographic differences in availability and cost of fuel. Also note that, counter-intuitively, EIA’s assumed costs for 30% CCS are actually greater than for 90% CCS because the 30% CCS coal plants would ‘still be considered a high emitter relative to other new sources and thus may continue to face potential financial risk if carbon emissions controls are further strengthened. Again, the data for the right graph takes CO2 emission coefficients from this EIA listing by fuel type

Looking at these graphs, we can see that the cost of new coal generation (regardless of CCS level) not only exceeds the value it would bring to the grid, but also largely exceeds the cost of natural gas, nuclear, geothermal, biomass, onshore wind, solar photovoltaic (PV), and hydroelectric power (all of which emit less CO2 than coal). Thus even in the scenario where 90% of carbon is captured by CCS (which allows it to be ‘cleaner’ than natural gas and biomass), it still comes at a significant cost premium compared with most of the other fuel types. These are the facts that are putting the hurt on the coal industry, not any policy-based ‘war on coal.’ Even the existing tax credits that are given to renewable energy generation are minor when looking at the big picture, as the below graph (which repeats the above graph but removes the renewable tax credits from the equation) shows. Even if these tax credits are allowed to expire, the renewable technology would still outperform coal both economically and environmentally.

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The last graphical rebuttal to President Trump’s statement on energy and coal during the State of the Union that I’ll cite comes from Tyler Norris, a DOE adviser under President Obama:

Source

As pointed out by Norris and other energy journalists chiming in during the State of the Union address, if the goal were to expand ‘clean coal,’ then the Trump Administration’s budget is doing the opposite by taking money away from DOE programs that support the research and development of the technology. In fact, at the end of last week a leaked White House budget proposal indicated even further slashes to the DOE budget that would further hamper the ability of the government to give a leg up to the development of ‘clean coal’ technology. Any war on energy is coming from the Trump Administration, and any battle that coal is fighting is coming from the free market of cheaper and cleaner fuels.

Sources and additional reading

20 Years of Carbon Capture and Storage: International Energy Agency

Annual Energy Outlook 2018: Energy Information Administration

Average Power Plant Operating Expenses for Major U.S. Investor-Owned Electric Utilities, 2006 through 2016: Energy Information Administration

Carbon Dioxide Emissions Coefficients: Energy Information Administration

Did Trump End the War on Clean Coal? Fact-Checking the President’s State of the Union Claim: Newsweek

How Does Clean Coal Work? Popular Mechanics

How much carbon dioxide is produced per kilowatthour when generating electricity with fossil fuels? Energy Information Administration

Is There Really Such a Thing as Clean Coal? Big Think

Levelized Cost and Levelized Avoided Cost of New Generation Resources in the Annual Energy Outlook 2017: Energy Information Administration

Trump touts end of ‘war on beautiful, clean coal’ in State of the Union: Utility Dive

Trump’s Deceptive Energy Policy: New York Times

What is clean coal technology: How Stuff Works

About the author: Matt Chester is an energy analyst in Washington DC, studied engineering and science & technology policy at the University of Virginia, and operates this blog and website to share news, insights, and advice in the fields of energy policy, energy technology, and more. For more quick hits in addition to posts on this blog, follow him on Twitter @ChesterEnergy.  

Super Bowl Sunday and Electricity Demand: What Happens in Cities with Super Bowl Teams and Host Cities?

The Super Bowl is upon us once again, along with all the fun sideshows that go with it. There are few events in American culture that bring as many people collectively around a single event quite like the Super Bowl, with even non-football fans gorging on fatty foods, enjoying the commercials, and relishing in the excuse to attend parties on a Sunday evening. The grip that Super Bowl Sunday has on our group consciousness allows for some interesting analysis of data (how much food do we collectively eat?) and myths (despite what I heard on the schoolyard growing up, the simultaneous flushing of toilets during halftime has not actually caused damage to sewer systems).

Thinking of the ‘everyone flushing the toilet at the same time’ myth got me to wondering about how electricity demand as a whole is affected by the Super Bowl, particularly in the regions whose teams made the big game (and presumably cause even more of the population to tune it) and the region hosting the Super Bowl. Indeed, grid operators like ISO New England recognize that ‘even when the game is thousands of miles away, the Super Bowl can have a big impact on regional electricity demand with spikes and dips throughout the game,’ requiring them to monitor the demand closely throughout the day.

So just as I started this football season analyzing the sustainability-ranking of each team, I’ll end it by analyzing the championship game in energy terms. Going into this analysis, I expected that a city/region having their team in the Super Bowl, or hosting the festivities, would lead to a definitive increase in power demand– but keep reading to see why I was surprised to find that assumption was misguided.



Graphical Results

We’ll jump right into the graphical results of this analysis– if you’re interested in reading the methodology, head down to the Methodology section now. The methodology section will also answer where the data came from and why for Super Bowls from 2015 and earlier there isn’t data available for each of the three relevant cities (two participant teams and the host city).

Super Bowl 51

Starting with the most recent Super Bowl and working backwards, first up is Super Bowl 51. This game saw the New England Patriots defeat the Atlanta Falcons in Houston, Texas, in the largest comeback in Super Bowl history. Below is the graph of electricity use in the power regions that are home to Boston, Atlanta, and Houston compared with a typical Sunday of comparable weather (note that all times displayed in this and other graphs are in Eastern Standard Time even when the region in question is in a different timezone):

For this specific Super Bowl, the electricity demand in all three regions is mostly lower than a normal Sunday for the whole day, though the demand of the Atlanta fans drops even lower than normal come game time and we see the New England electricity demand increase compared with normal as the games continues. As will be discussed later, this difference in how the two cities reacted over the course of the game likely reflects the attitudes and activities each fan-base had to what was looking like a blowout victory for Atlanta.

Super Bowl 50

Super Bowl 50 featured the Denver Broncos defeating the Carolina Panthers in Santa Clara, California. Comparing the electricity use this Super Bowl Sunday with a typical winter Sunday in the power regions that contain Denver, Charlotte, and Santa Clara gives the following visual:

In what we’ll find is a more typical effect of Super Bowl Sunday, the electricity use in both Denver and Santa Clara saw an increase from normal use early in the day, only to fall below average during the time when the game was on. Panthers fans, however, set an unparalleled increase in power demand compared with a normal Sunday all day, but especially high during the afternoon lead up to the game and notably dropping during the game.

Super Bowl 49

Working backwards, Super Bowl 49 is the first instance where we find that data is not available for all three regions (see Methodology section for an explanation). In this game, which found the New England Patriots defeating the Seattle Seahawks in Glendale, AZ on a game-ending interception in the end zone, we only have data from the New England power region to consider:

In looking at the New England electricity demand, we find a peak compared with normal early in the day and a general increase compared with normal over the course of the game.

Super Bowl 48

For Super Bowl 48, where the Seattle Seahawks dominated the Denver Broncos all game in East Rutherford, NJ, the only available data was for the power system that is home to East Rutherford.

Here we again find a peak in electricity demand compared with normal early in the day, which dissipates and eventually leads to lower electricity used during the actual playing of the Super Bowl compared with a normal day.

Super Bowl 47

Last but not least is Super Bowl 47, featuring the Baltimore Ravens defeating the San Francisco 49ers in New Orleans, LA. I was particularly looking forward to gathering the data from this one (and was disappointed to find only the Baltimore area data available) because this is the game that infamously featured a power outage in the stadium that delayed the game by over half an hour. I was hoping specifically for the New Orleans data to see what the electricity demand looked like before and after the blackout, but it was not meant to be.

However we can see from the Baltimore data a peak in electricity use compared with normal early in the day and a distinct drop off as the game is set to begin and throughout the course of the game. Because the data provided is hourly, it’s not clear if there was any effect during the half hour delay in the Super Bowl, but it looks like people in Baltimore continued whatever it was they were doing during the power outage in New Orleans, rather than decide to use the break in action to start up the dishwasher or the clothes dryer.

Conclusions

General trends

Interestingly, we don’t find one iron-clad trend that weaves its way through the entire data set analyzed, though there are some patterns.

  • For regions with teams in the Super Bowl, four out of six (Baltimore in 2013, New England in 2015, Denver in 2016, and Carolina in 2016) of them show an increase in electricity use during the lead up to the game, while four out of six (Baltimore in 2013, Denver in 2016, New England in 2017, Atlanta in 2017)  of them show a decrease in electricity use during the game.
  • For the regions hosting the Super Bowl, a similar trend is found. Two out of three host regions (East Rutherford in 2014 and Santa Clara in 2016) showed an increased electricity demand in the hours preceding the game, while all three host regions showed a general decrease in electricity demand during the game.

While these data are not complete or detailed enough to make definitive conclusions (in addition to the lack of more years of historical data, the issue of controlling for the weather is difficult to do since some of the wider regions will have more varied temperatures throughout the region and make it more difficult to ensure the weather is not causing electricity fluctuations as a whole), they do generally follow the results of U.S.-wide studies. A study by Outlier found, through working with utilities during Super Bowl 46, the following:

More specifically, versus a typical Sunday afternoon/evening in the winter, home power usage was 5 percent lower during the Super Bowl, with big consequences for overall energy use:

Source

Going further, ISO New England’s minute-by-minute graphical analysis during Super Bowls 49 and 50 show the types of effects the big moments like the start, halftime, and end of the game have on the total demand load (and also serve to solidify that the effects are more pronounced when a region’s local team is in the game!)

Source

 

Explanation of the trends

The conclusion of less electricity usage over the course of the Super Bowl may sound surprising at first, given that it’s an event centered around an electronic device in the TV, but when you break it down it really makes sense. While it’s true that Americans gather around the television, they are often doing so collectively– going to parties or bars. So while the Super Bowl is often uncontested as the most watched television program of the year, that does not necessarily lead to an increase in the number of television sets being powered as people congregate around TVs together. These effects are going to be even more drastic if a local team is in the game (drawing in the more casual viewer) or if the game is being played locally (meaning more people will be in or near the stadium to enjoy the festivities).

Further, just because people are turning on their TVs does not indicate that household energy use is going up. That is because TVs require less than 400 Watts (W), and sometimes as few as 20 W, compared with most energy-sucking appliances like the vacuum (650 W), washing machine (2,500 W), or water heater (4,000 W). During the Super Bowl when the TVs are on, households are significantly less likely to be using these more electricity-consumptive appliances (not to mention many households would regularly have their TVs on during these hours anyway) and thus overall electricity demand noticeably drops.

That combination of people gathering together as opposed to being in separate households and using TVs instead of other appliances satisfyingly explains the drop in power use during the game. We could also conjecture that power use goes up before the game as people are getting the energy intensive chores (washing clothes, vacuuming, washing dishes, etc.) done earlier in the day before heading out to their Super Bowl gathering. They might also be preparing food to enjoy during the big game using their ovens/microwaves/stove tops in these early afternoon hours when they would not normally be in the kitchen.

Exceptions to the trends

Though the previously discussed trends were found in a majority of the cases analyzed in this article, there were a couple that bucked the trend. Specifically, analyzing the electricity use on Super Bowl Sunday compared with a comparable Sunday found that:

  • In 2017, both New England and Atlanta, as well as host city Houston, had lower than normal electricity demand in the hours before the game;
  • In 2016, the Carolina region saw large peak in electricity use compared with normal in the afternoon leading up to the game; and
  • In 2015, New England had increased electricity demand the morning of the Super Bowl as well as during the game.

There are a number of potential reasons that these specific instances did not meet the trends found in other places. The main one could be that while the average temperature used to find a comparable Sunday was close to the temperature on Super Bowl Sunday, there could have been wildly varying temperatures in different parts of the region or in different times of the day that prompted heating or cooling systems to be ramped up. Without the availability hourly temperature data and/or the analysis of temperature data of many cities within a region, it is impossible to know for sure. Further, grid operators also monitor aspects of weather like dew point, precipitation, cloud cover, and wind to predict electricity demand– which would be significantly more difficult for me to control for here. So for aberrations outside of the expected trends, these type of weather effects are the most likely culprit.

Another interesting explanation to look for is how captivating a particular game might have been. In its analysis of Super Bowl energy numbers, MISO notes that the more captivated and the more glued to their seats watchers are during the game, the more the demand will remain steady and low. As soon as people start to get up and do other things in the house (either because its halftime or a game is uninteresting), they notice a real uptick in electricity demand. This effect could perhaps explain why electricity use started to go closer to normal levels in New England in 2017 when the Patriots were building a seemingly insurmountable deficit, and it could also explain why electricity demand started to increase compared with normal in Carolina in 2016 about midway through the game (while never down by more than 10 until the closing minutes, more casual Panthers fans might have been frustrated with their team’s lackluster offense and inability to score more than 7 points through the third quarter and tuned out to partake in more energy-intensive activities).

Methodology

Availability of data

The availability of a region’s electricity demand depends on the entities who deliver energy and how far back in time you are looking. At the suggestion of the Federal Energy Regulatory Commission (FERC), a number of regional transmission organizations (RTOs) and independent system operators (ISOs) have been established in the United States to coordinate, control, and monitor complex and sometimes multi-state grid systems. One of the results of the use of these systems is they often make hourly electricity demand data publicly available going back a number of years, which allows for us to look back on some of the regions of the participants/hosts of the Super Bowl. The cities/years where those data are available are shown in the table below.

For regions that are not a part of RTOs or ISOs, unfortunately the electric companies rarely make public the same type of data. However a proxy we can utilize the Energy Information Administration’s (EIA) Electric System Operating Data tool. While it only goes back to the summer of 2015, it does provide the same type of hourly electricity demand data for regions and utilities outside of RTOs/ISOs. So where needed, this data is used as well as indicated in the below table.

When going back to Super Bowl 49 and earlier, some data become unavailable and those cities are not included in the analysis, shown below as ‘not available.’

 

For links to each of the electricity data sources listed in the above table, go to the ‘Sources and additional reading‘ section.

Finding a reasonable day for comparison

To determine the changes in electricity demand that are attributed to each region for Super Bowl analyzed, a reasonable day for comparison was found in each region using the following criteria:

  • As pointed out in the previous post analyzing electricity usage during a federal government shutdown, nothing will affect a region’s power demand more than the weather. If all buildings and homes are turning up either the air conditioning or the heat, that will have a greater effect on electricity usage than anything else– even an event as large as the Super Bowl. With the goal of comparing electricity demand on Super Bowl Sunday with other days and controlling for other factors, the methodology used was to assure that the comparison day chosen had an average temperature as close as possible to the average temperature on the day of the Super Bowl in that region. As a rough proxy, the average temperature on the day of the Super Bowl in the major city associated with each team/region was found on Weather Underground, and the goal was to find a comparison day with an average temperature within a few degrees Fahrenheit;
  • There are also distinct patterns to electricity demand depending on the day of the week, so the comparable day chosen was always made to be a Sunday; and
  •  Lastly, the comparable day chosen was kept to be within one to three weeks of the Super Bowl (either before or after), while avoiding any Sunday that had a playoff football game for the region’s home team, to assure any other externalities are kept as constant as possible.

With that criteria in mind, the following were the days used for comparison to Super Bowl Sunday in each region:

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Graphical comparisons

Once the hourly data for each Super Bowl Sunday and chosen comparable dates were pulled, the hour-by-hour comparison is calculated using a simple percentage change from the regular non-Super Sunday. These percentages are what are ultimately graphed on an hourly basis, with the up to three regions (depending on how many available) on the same graph to see if there are any trends based on the cities. Similar comparison was not included for overall U.S. electricity trends because the large and varied geography of the United States makes controlling for the effects of weather on electricity demand much more complicated and difficult (however, as noted earlier, a study that looked at thousands of households during the 2012 Super Bowl found that an on overall basis, electricity demand increases on Super Bowl Sunday in the hours before the game and decreases once the game begins).

Sources and additional reading

5 Facts About Energy During the Big Game: MISO

Baltimore Gas & Electric: PJM RTO

California ISO: Pacific Gas & Electric electricity demand

Carolinas region electricity demand (EIA)

Energy Reliability Council of Texas (RTO) Coastal Region Electricity Data

How a Patriots Super Bowl affects the region’s power grid: ISO Newswire

How the Super Bowl saves energy: ABB

New England ISO Electricity Data

Northwestern region electricity demand (EIA)

Public Service Company of Colorado (EIA)

Public Service Electric & Gas Company: PJM RTO

Regional Transmission Organizations (RTO)/Independent System Operators (ISO): FERC

Southeastern region electricity demand (EIA)

Why people use less energy on Super Bowl Sunday: Washington Post

 

About the author: Matt Chester is an energy analyst in Washington DC, studied engineering and science & technology policy at the University of Virginia, and operates this blog and website to share news, insights, and advice in the fields of energy policy, energy technology, and more. For more quick hits in addition to posts on this blog, follow him on Twitter @ChesterEnergy.