Post tagged with "home electricity consumption"

Outlier

Will the Super Bowl save the planet? How America’s most watched TV event reduces home energy usage

  • By Barry Fischer
  • January 27, 2013

The 2012 Super Bowl was the most watched television broadcast in US history. An estimated 111.3 million viewers tuned in – more than a third of the country’s population.

That’s a lot of TVs aglow at one time.  The amount of electricity collectively consumed by TVs during the big game is reckoned by General Electric to exceed 11 million kilowatt-hours – equivalent to the power generated by ten medium-sized coal-fired power plants over the course of the event.

But here’s the real kicker: all those TVs illuminated during the Super Bowl are actually a force for dramatically lower overall energy consumption.

Turning back the clock to February 5th 2012, we analyzed electricity consumption data across 145,000 households on last year’s Super Bowl Sunday. And our analysis revealed a remarkably consistent pattern: when the game kicks off, electricity usage plummets.

Decrease in US home electricity use is 3x the amount of energy consumed by the TVs watching it

Let’s examine the game-day details and explore how a major televised sporting event can affect home energy use…

When Super Bowl XLVI kicked off, home electricity usage dropped off

First, let’s take a look at game-day energy usage in the western part of the country, for which we analyzed data from 91,000 anonymous households.

The chart below shows how average residential electricity consumption on 2012’s Super Bowl Sunday (broken up into 15-minute intervals) differed from a typical midwinter Sunday. From morning through midafternoon, Super Bowl Sunday was a fairly normal energy day in the West.  Between 10am and 3:30pm, electricity usage was slightly above typical – possibly as party hosts were doing preparatory tasks like washing dishes, and soon-to-be party guests were firing up their ovens to bake jalapeño poppers. 

But then something special happened around 3:30pm PST: the Giants and Patriots ran onto the field at Indianapolis’ Lucas Oil Stadium. Immediately, electricity consumption began to tumble downwards. As the game’s suspense escalated, usage levels descended –dropping to around 7% below what is normal for a Sunday afternoon/evening.

During the halftime show, the game’s viewership surged to 114 million people (even higher than the 111.3 million that the game averaged), who were treated to performances by Madonna, the dance duo LMFAO, and the English singer M.I.A.

But something else also seemed to be M.I.A. during halftime: home electricity usage. It faded to a full 7.7% below typical levels.

And so while in the hours before the game, home electricity usage had been just slightly above (+2.4%) what is typical, things changed radically after kickoff. Over the course of the game, consumption decisively decreased to 5% below normal.

And usage remained well below average (-3.7%), even after the game was over.

Why do homes use significantly less electricity during the Super Bowl?

We think there are a couple key reasons for the sharp reduction in usage:

1) Many households are not using appliances other than their TV during the game. On a typical Sunday in the early evening, many people would have been at home using multiple different kinds of electricity-consuming appliances (e.g. laundry machine, kitchen appliances, vacuum cleaner, TV) around the house—as suggested below by the relatively high evening usage that normally takes place on a Sunday.

But the Super Bowl changes this pattern: it concentrates activity around the TV. With so many people glued to the couch during the game, fewer households are using electricity for cooking, cleaning, or anything else other than watching the tube. Abstaining from other forms of energy usage naturally causes game-time electricity consumption to decline below typical levels.

And what explains the persistence of below-average consumption levels even after the conclusion of the game? One factor (another is described below) may simply be sustained fixation on the TV, which continues to divert people away from their typical Sunday night uses of electricity.  For example, after the game ended in 2012, tens of millions Americans didn’t leave the couch: 37.6 million viewers stayed huddled around the TV to watch the season premiere of the musical reality-TV show “The Voice.”

2) Many people watch the game at houses of friends and family. For many fans, watching football is a community event — meaning that people leave their homes to watch the game with other fans. In 2011, an extensive poll by Nielsen found that 45% of Super Bowl viewers planned to watch the game with friends or relatives.

A mass movement toward collective TV-watching at friends’ houses (or at a bar) on a Sunday night will result in significantly lower-than-average electricity use. Just as carpooling reduces transportation energy use, gathering together to watch televised sports—let’s call it “TV-Pooling”—decreases home electricity use. Twenty people watching one large TV at a friend’s house requires much less energy than 20 people watching 20 TVs in their individual homes.

And because for West coast audiences the Super Bowl concludes fairly early (around 7pm), the communality of the game-watching is likely to segue into additional away-from-home social revelry that persists longer into the night…as is suggested by the sustained lower-than-average usage through the very end of Super Bowl Sunday.

The numbers and analysis above correspond specifically to the Western region, but what about elsewhere? To test whether the Super Bowl’s energy-saving effect truly represents a broader nationwide phenomenon, let’s check to see if the pattern we’ve identified also materializes on the other side of the country.

Chips and (Electricity Usage) Dips: across the country, home energy consumption declines during the Super Bowl

Now we know what to look for, as we shift our attention to 54,000 anonymous households located in the eastern part of the country…

When last year’s Super Bowl kicked off (at 6:30pm EST), did the region’s average home electricity usage substantially decrease like it did in the West?

Indeed it did: game-time consumption in the East dropped to as much as 5% below typical levels.

Up until game-time, usage in the Eastern region was slightly below normal — likely due to the relatively warm weather that day, which may have given people an incentive to spend more time outside.  But then the Giants and Patriots took the field in Indianapolis, and poof: electricity consumption decreased significantly. Each 15-minute interval of usage during the heart of the game was more anomalously low than any other interval that day.

Consolidating the 15-minute usage intervals into wider time periods, we see that home electricity usage during the game was, in total, nearly 4% lower than we would expect on a typical midwinter Sunday evening – and represented the day’s most significant deviation from normal.

The pronounced decline in game-time electricity usage in the East is, similar to what we saw in the West, most likely a consequence of two related behavioral phenomena: exclusive focus on the TV and communal game-watching.

Importantly, these two subconscious energy-saving actions take place during a time that is normally characterized by peak residential consumption — i.e. when people are typically at home doing their Sunday evening routine (cooking, washing, etc.).  It’s for this reason that the Super Bowl produces a prominent energy-conservation effect: relative to a run-of-the-mill midwinter Sunday evening, the Super Bowl catalyzes an extensive cutback in household energy use.

And why did eastern residential electricity consumption spike to above-average levels after the game, given that the entire rest of the day had been below average? Quite simply, the Super Bowl ends on the late side in the Eastern time zone. That means that immediately after the game, many people (at least those planning to report to work the next day) were probably returning home en masse from parties.  One can imagine that as they walked in their doors, they collectively flipped on the lights and other appliances. This, in turn, translated into an unusually above-average period of energy usage relative to a typical Sunday’s late night, when most people would have been winding down and going to bed.

Better together: TV-Pooling is good for the planet, the pocketbook, and civic life

We were struck by how the Super Bowl – which has for the last 3 years been the most watched television event in US history – appears to reduce home energy usage.

Mass TV watching traditionally conjures up images of enormous, electricity-gobbling 42-inch plasma screens.  But as it turns out, all these TVs are a force, at least over the course of a few hours, for decreased electricity consumption.

And we were especially intrigued by the energy-efficiency implications of a key factor behind the decrease: TV-Pooling.

Communal TV viewing may at first seem like a trivial concept, but its effect on a country’s residential energy consumption could be significant. Super Bowl XLVI demonstrated that when around one-third of Americans collectively watch a single 3.5-hour sporting event, the corresponding reduction in the nation’s daily energy bill can be upwards of $3.1 million. That’s a lot of guacamole. Replicate this phenomenon a couple times each month, and you’re potentially talking about some serious energy and cash savings.

In addition, TV-Pooling may do more than conserve energy: it may help strengthen our social bonds. In his influential book Bowling Alone, Harvard Professor Robert Putnam chronicles how Americans have become increasingly disconnected from their friends and neighbors in recent decades, replacing communal engagements with individualized entertainment. In Putnam’s analysis, television is among the culprits – and perhaps appropriately so. But, there is something different about how we watch major broadcasts like the Super Bowl.

Events like the Super Bowl are not just popular, they are social. And, as such, they may help, just a little, to unite neighbors, friends, and family – and help save the planet.

Special thanks to Ashley Sudney, Efrat Levush, Steven Blumenfeld, Nathan Srinivas, Emily Bailey, Elena Washington, Yoni Ben-Meshulam, David Moore, Katie DeWitt, Andrew Sharp, Nate Kaufman, Jordan Jakubovitz, Carly Baker, and Arkadi Gerney.

Follow @OpowerOutlier on Twitter

Methodology:

The aggregated data used for this analysis stems from two large regional samples (nwest = 91,355 households; neast = 53,574 households). Time-of-use consumption data in both cases are defined at an AMI granularity of 15 minute intervals.

Baseline electricity usage levels (used to evaluate the deviation in home electricity usage on Super Bowl Sunday, relative to a typical day) correspond to energy usage levels observed on other Sundays in January 2012 and February 2012 that exhibited similar regional weather to February 5, 2012.  Similarity in weather is based on comparable daily mean temperature and negligible-to-zero precipitation.  Each regional analysis is demarcated by a geographic area with maximum radius of 25 miles.  To reinforce the analytical comparability of daily weather conditions and the underlying electricity usage requirements associated with them, the analysis is explicitly restricted to homes that utilize gas heating systems. Meteorological data is sourced from Weather Underground.

Each 15-minute game-time usage interval exhibits a standard deviation of no more than 0.40 kWh. Accordingly, the computed interval differences from baseline usage are statistically significant at the 99% level, within an confidence interval of  +/- 0.005 kWh (equivalent to the amount of electricity consumed by a single 20-watt efficient light bulb during the interval considered).

Note that, in the western region case, the above-average usage levels observed during the pregame period are more than offset by the strongly below-average usage levels that register when the game starts. This suggests that Super Bowl Sunday does not simply reduce usage during a certain segment of day; it also, as a result of the exceptional game-time contraction in consumption, is an overall net reducer of daily residential energy use. This outcome holds true across both regional analyses.

Calculations:

TV power demand in terms of number of power plants: General Electric estimates that all TVs beaming the Super Bowl in the US collectively use 11,309,607 kWh over a 5 hour period, implying an instantaneous power demand of 2,262 MW.  Net capacity of an average coal-fired power plant in the US is 228 MW. Aggregate demand of 2,262 MW over the course of the event thus corresponds to approximately 10 average coal-fired power plants. This is a conservative assumption, as it does not reflect transmission and distribution losses, which are generally considered to be around 7%.

Game-time usage reduction > 3x the energy consumed by TVs watching it: Based on GE’s 5-hour TV energy consumption estimate of 11,309,607 kWh. Proportionality to our game-time-specific analysis suggests that all TVs watching the big game for 3.5 hours = (3.5/5) * 11,309,607 kWh = 7,916,725 kWh.  The larger of our two regional time-of-use evaluations suggest that average residential electricity usage falls to 5.0% below typical levels during the game. A given US household consumes an average of 11,496 kWh per year (i.e. 8,760 hours), and so for a 3.5 hour period is proportionally assumed to consume 11,496 kWh * (3.5/8,760) = 4.59 kWh.  Average per-household usage reduction during Super Bowl = 4.59 kWh * 5% game-time reduction = 0.23 kWh. Across 114.76 million households in the US, the specific game-time reduction nationwide sums to 26,355,811 kWh. This is approximately 3.3 times as much electricity as the 7,916,725 kWh consumed by TVs during the game. This is a conservative estimate, insofar as the Super Bowl takes place on a Sunday afternoon/evening, which is a relatively high-usage time of the week for the residential sector.

Game-time monetary savings almost equal to cost of a 30-second commercial: Specific game-time reduction sums to 26,355,811 kWh (see above). At a national average residential cost of electricity of $0.1187/kWh, the game-time energy cost savings is $3.13 million. 30-second spots during Super Bowl XLVI fetched $3.5 million.

Data Privacy: All data analyzed here are anonymous and treated in strict adherence to Opower’s Data Principles.

Author’s note: The analysis and commentary presented above solely reflect the views of the author(s) and do not reflect the views of Opower’s utility partners.

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America’s most energy-efficient tradition? Home energy usage falls by 5-10% on Thanksgiving

  • By Barry Fischer
  • November 20, 2012

There’s a lot to look forward to during the Thanksgiving holiday: a day off from work, traveling to see friends and relatives, cooking and eating great food.

Something else to look forward to? The striking fact that residential energy usage on Thanksgiving will be 5-10% lower than on a comparable day.

Turning back the clock to November 2011, we conducted a statistical analysis of how 146,000 households in the Northwest consumed electricity and natural gas on Thanksgiving last year.  We discovered the holiday is an exemplar of residential energy efficiency.

The key driver of Thanksgiving’s reduced energy footprint appears to be its distinctively communal nature: quite simply, eating turkey together saves a lot of energy.

Let’s take a closer look at the data and carve out some insights.

Energy usage on Thanksgiving: not your typical Thursday

Thanksgiving is an unusual Thursday.

While many Americans spend part of the holiday traveling (an estimated 43.6 million of us this year), many others are cozying up at home and cooking up a storm in anticipation for those travelers’ arrival.

The chart below shows how these factors distinguish Thanksgiving’s energy profile (curve with diagonal lines) from a typical weekday (yellow curve).  Each curve in the graph indicates the proportion of homes consuming a certain level of electricity on a given day.  For this comparison – and the rest of analysis to follow — we looked at days with similar weather and temperatures:

What story does this picture tell? The important takeaways lie in the white diagonal-line regions on the left side and right side of the graph, where the two curves do not overlap. They reveal that Thanksgiving energy usage is distinct from a typical weekday in a couple of key ways:

1)   On Thanksgiving, a larger-than-usual proportion of homes use very little energy (consistent with the larger-than-usual number of people who leave their homes to travel out of town)

2)   At the other end of the spectrum, a larger-than-usual proportion of homes use a lot of energy on Thanksgiving (consistent with the large number of people staying home to host a feast).

It turns out that these two effects tend to balance out: average household energy usage on Thanksgiving is actually very similar to that of a typical weekday.

But before we examine that, let’s take a quick look at how the holiday’s energy usage stacks up against an arguably more comparable day – namely, the weekly holiday that we call Sunday.

Does Thanksgiving’s energy profile resemble a weekend day?

The short answer is no. Thanksgiving is different.

It’s true that Thanksgiving and other autumnal Sundays are both characterized by keeping cozy in a heated home, watching football, and having a family meal.

But we all know that Thanksgiving is a much more communal day. And on that special day, tens of millions of families power down their own homes before heading to convene with their loved ones.

So, when we compare Thanksgiving Day (diagonal-lines curve) to a typical November Sunday (blue curve), we observe that on Thanksgiving, a dramatically higher proportion of homes use very little electricity.

And although the homes of Thanksgiving hosts are likely to exhibit heavy energy usage on the holiday (e.g. making sure the home is warm enough for guests; multi-hour turkey roasting; big-screen TVs beaming with football games all day), the prevalence of powered-down homes exerts an even stronger effect.

The net result: relative to a typical weekend day, Thanksgiving’s residential energy consumption is deliciously low…

Residential energy usage is 5-10% below normal on Thanksgiving

In gathering together on Thanksgiving, groups of Americans effectively centralize their energy usage into a single home – an approach that appears to be highly efficient.

Year round, many of us reduce our gasoline consumption by car-pooling. On Thanksgiving, a similar thing takes place: we significantly reduce our community’s residential electricity and natural gas usage by turkey-pooling.

The pair of bar graphs below show that, relative to a weather-comparable weekend day, average electricity usage on Thanksgiving decreases by more than 5%, and natural gas usage (mainly used by these homes for cooking and water heating) goes down by approximately 10%.  Somewhat surprisingly, given the day’s focus on cooking and ultra-cozy heated homes, Thanksgiving’s energy usage profile is actually quite similar to that of a typical weekday.

Combining the holiday’s implicit electricity and gas savings into a common unit of energy measurement – the British thermal unit (Btu) – we conservatively calculate that the average American home’s energy usage falls by about 12,000 Btu on Thanksgiving (see Methodology).

If we aggregate that average per-home savings across all 113.6 million American households, the reduction in the country’s residential energy consumption on Thanksgiving Day is sizeable.  A 5% national decrease in home energy usage on a single day is equivalent to…

  • The total caloric energy contained in 26 million roasted turkeys
  • Energy bill savings that could buy 6.3 million individual Thanksgiving dinners (there are 6.8 million US households that currently face severe food insecurity)
  • Nearly 7 months of aggregate residential energy consumption in Plymouth, Massachusetts (pop. 57,000) – where the first Thanksgiving reportedly took place in 1621

And while it’s true that the holiday’s energy-intensive travel patterns (i.e. using gasoline and jet fuel) may counteract much of the in-home energy savings from turkey-pooling, the underlying finding of our analysis stands: Thanksgiving, as a quintessential community event, demonstrates how congregating and dining under one roof isn’t just social and fun – it also saves a significant amount of energy.

Who knew that energy efficiency could be so delicious.

Happy Thanksgiving!

Special Thanks(giving) to Ashley Sudney, Abhishek Chandrasekhar, Yoni Ben-Meshulam, Arhan Gunel, Nathan Srinivas, and David Moore.

Follow @OpowerOutlier on Twitter

Methodology: Analysis based on anonymized sample of 146,481 northwestern households with data on daily electric consumption (full sample) and natural gas (n=21,021). All homes considered are electrically-heated homes located in the same region, so face similar energy needs and weather conditions.

The daily energy usage analysis, as depicted in the probability density functions and bar graphs, reflects comparisons across weather-similar days in late autumn 2011. The baseline November weekday is defined as a composite of three November weekdays whose mean temperatures closely resembled (within +/- 1 degree) Thanksgiving Day (45°F).  Similarly, the baseline November weekend day is a composite of two November weekend days and one early-December weekend day – all of which had no or minimal difference in mean temperature relative to Thanksgiving Day. All days considered experienced minimal or zero precipitation. Meteorological data sourced from Weather Underground.

Per-household reduction in energy usage on Thanksgiving Day is projected to be approximately 12,000 Btu: Average annual US per-home energy usage is 89.6 million Btu (i.e. 245,479 Btu/day); a conservatively estimated daily usage reduction of 5% corresponds to 245,579 Btu * 0.05 = 12,274 Btu. Total national decrease in residential usage is this figure multiplied across the country’s 113.6 households, yielding 1.39 x 10^12 Btu.

26 million roasted turkeys: Estimate based on US Department of Agriculture Nutrient Laboratory Data, which indicate that a 16-pound, or 7.25 kg Turkey (whole, meat and skin, cooked, roasted) contains 13,869 kilocalories. This imbedded energy content can be converted vis-a-vis the above national Btu savings, using an equivalency factor of 1 Btu = 0.252 kCal.

6.3 million turkey dinners: Average yearly US per-household residential energy cost is $2,024, suggesting a daily average of $5.55. A 5% daily savings equals $0.28/household, and $31.5 million nationally – which could fetch 6.3 million turkey dinners at an average cost of $5/dinner.

Plymouth, MA: A town of 56,794, with per-person home energy usage of 44.8 million Btu/year (based on the Massachusetts state average). Given the above calculations, a 5% national savings on a single day corresponds to 6.6 months of town-wide residential consumption.

Data Privacy: All data analyzed here are anonymous and treated in strict adherence to Opower’s Data Principles.

Author’s note: The analysis and commentary presented above solely reflect the views of the author(s) and do not reflect the views of Opower’s utility partners.

 

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Outlier

Politics and power: Americans who vote more use 7-10% less electricity

  • By Barry Fischer
  • October 31, 2012

Three out of four voters in this year’s election view energy as a “very important” issue in their evaluation of candidates.  As voters examine the candidates’ positions on energy, we decided to turn the tables — and instead shine the light on the energy profile of the voters themselves…

We wondered if any statistical relationship might exist between voting patterns and energy usage. So we cracked open Opower’s energy data warehouse (spanning 50 million US households), and linked it up with historical election data from the last seven years.

Our analysis uncovered a striking pattern that held resolutely across geographic regions: Americans who vote more also use less electricity.

Let’s dig into the data streams to assess what the voting-energy relationship looks like, and what may be driving it.

Higher voting frequency is associated with lower household electricity usage

Our analysis zeroed in on 137,000 households, whose electricity consumption data we were able to match with publicly available records indicating how many elections the utility account holder has voted in since 2004.

We sourced voting records and energy usage data from two states that exhibit distinct electoral identities – a western state and an eastern state. Then we matched up the voting/energy data streams in a way that fully protects the personally identifiable information of the households.

Between 2004 and 2010, voters in each state had the opportunity to participate in an average of about 10 elections (spanning primary, general, local, and special elections). As you can see below, people who voted in a greater number of those elections also consistently use less electricity.

Note that the data above represents only utility customers who lived in their respective households over the full 2004-10 period, so all of them faced a similar number of opportunities to cast votes. (And if you’re wondering why the eastern state exhibits higher average electricity usage in general — it’s simply because a larger fraction of households there use electricity as a heating source.)

The inverse relationship between voting frequency and home electricity usage becomes even more apparent when we categorize people as “rare voters,” “sometimes voters,” or “frequent voters.”

So what’s the explanation for frequent voters’ persistently lower household electricity usage?

Could it be that the frequent voters’ homes are simply smaller and therefore use less electricity? No: our property-level data indicates that homes in all three voting-frequency groups are similarly clustered around an average size of 1900-2000 square feet.

Or could it be that frequent voters are for some reason more likely to use gas furnaces or other non-electric heating systems, so naturally would consume less electricity per year? It’s not that either: we found that rare voters and frequent voters are equally as likely to own homes with electric heating.

Indeed, we found that the sizable difference in electricity consumption across types of voters is related not so much to the physical characteristics of their homes, as it is to the characteristics of the voters themselves.

We’ve identified two major factors at play. Let’s explore them in turn…

Older Americans: their voter turnout is high, their home electricity consumption is low

Year after year, the most frequent voters in America are the country’s older citizens, as we can see clearly from voter turnout in the 2008 Presidential election (which had the highest overall turnout since 1968), and the 2010 midterm election.

As people get older, they vote more frequently – likely because, as explained in a recent article by Money magazine, older Americans have an acutely personal stake in policy issues (e.g. Social Security and Medicare) and have more time to register to vote, evaluate candidates, and turn out to the polls.

This age/voting relationship is similarly evident in our own analysis. On average, the “frequent” voters in our two-state dataset had an average age of 60 – noticeably higher than the people voting “sometimes” (average age 55) or “infrequently” (average age 52).

(If these average ages seem high in general, it’s because our dataset is intentionally restricted to householders who lived in the same voting jurisdiction and residence from 2004 to 2010 – a tenure length that is more characteristic of higher age groups.)

And while growing older is associated with voting more often, it’s also associated with using less electricity.

The chart above exclusively displays electricity consumption (i.e. it excludes fuels like natural gas and heating oil that can also be important components of home energy usage). But the pattern is consistent with Department of Energy data indicating that older households also exhibit lower total energy consumption than their younger neighbors. For example, homes whose head of household is aged 65-74 consume 13% less total energy per year than homes whose householder is aged 45-54.

A few key reasons that older households have lower energy consumption:

  • Empty nest: The kids have already moved out, so there are fewer electricity users roaming around the house.
  • Fixed income: Older households are more likely to live on a fixed-income, so may be more attentive to minimizing energy bills.
  • Fewer gadgets: Although older Americans do watch more TV than any other age group, they also spend considerably less time using other consumer electronics like computers and power-hungry gaming consoles.

As a variable, voter age drives most of the electricity consumption difference between frequent- and infrequent-voting households. And yet, our analysis shows that variation in age alone is not sufficient to fully explain why frequent voters use less electricity.  We identified another statistically significant dynamic that appears to transcend age…and implies a fascinatingly direct relationship between political participation and energy-efficient behavior.

Two sides of the same coin: civic engagement and energy efficient behavior

Our analysis of the relationship between voting frequency and electricity usage suggests that, beyond age, there is something special about politically engaged Americans that also leads them to consume less energy.

Consider, for example, two American householders — let’s call them Sam and Pat  – who are virtually identical: same age, same neighborhood, same income level, same home square footage, same kind of heating system, and same number of children.

There is, however, one key behavioral difference between Sam and Pat: Sam voted in ten elections during the 2004-10 time period, while Pat voted in none.

When we compare the yearly household electricity consumption of Sam and Pat, a stark difference appears: Sam, the frequent voter, on average consumes 659 fewer kilowatt-hours per year (~$80 lower annual electricity bill) than Pat.

This pattern is precisely the one that emerged from our analysis across 137,000 American homes. Using a straightforward statistical technique called linear regression (see Methodology), we were able to isolate the statistical relationship between voting frequency and household electricity usage, and arrived at a striking conclusion:

Holding all other factors fixed, each ballot that a voter cast between 2004-2010 is associated with an incremental 66 kilowatt-hour (~$8) reduction in the voter’s average annual household electricity usage.

This remarkable result prompted us to ask:

What is it about frequent voters in particular that puts downward pressure on their household electricity consumption?

We can propose a few hypotheses:

  • Patriotism? People who regularly cast ballots may do so in part from a sense of patriotism or national pride – which, in a nation that increasingly prizes the notion of energy security, can also motivate a commitment to energy efficiency.
  • More informed? It’s possible that frequent voters may simply be more informed or engaged when it comes to popular public issues like energy, and so are more attuned to adopting energy efficiency in their own lives.
  • Perceived importance of individual actions? Enthusiasm for voting and a passion for energy efficiency may originate from a common underlying belief – specifically, a belief in the power of individual actions (e.g. a single vote or one person’s habit of turning off the lights when leaving a room) to influence large-scale outcomes (e.g. election results or global environmental sustainability).

The causal reason for the inverse relationship between voting frequency and electricity usage isn’t clear-cut — and we’re curious to read your thoughts and hypotheses in the comments below. But the statistical phenomenon we’ve identified does make one thing clear…

No matter who you’re voting for on November 6th, your vote itself is a good sign for the future of energy efficiency in America.  Put simply, a more engaged citizenry is also a more energy-efficient one.

Special thanks to Ashley Sudney, Arjun Dasgupta, Tyler Curtis, Nathan Srinivas, Rachel Zuraw, David Moore, Will Pierce, Efrat Levush, Jillian Cairns, and Peter Kjeldgaard.

Follow @OpowerOutlier on Twitter

Methodology: Publicly-sourced voter data was matched with household electricity consumption data across 137,415 homes, corresponding to customer utility accounts that remained continuously active from January 2004 to August 2010. Electricity consumption data is based on monthly usage reads from January 2008 onwards.

The aggregation of householders into voting intensity categories (i.e. “infrequent”, “sometimes,” and “frequent”) reflects the fact that there is not a meaningful behavioral distinction between, say, a person who voted 3 times and a person who voted 4 times during the 2004-10 time period; but there is a fundamental difference between voting 3 times and voting 9 times. The underlying findings of our analysis are not sensitive to marginal changes in the definitional boundaries of the aggregated groups.

Specific average consumption levels for each voting intensity category, from infrequent to frequent, are as follows: Eastern State (11,911 kWh; 11,774 kWh; 11,051 kWh), Western State (10,313 kWh; 10,131 kWh; 9,332 kWh). Confidence intervals (at the 95% significance level) span approximately +/- 50 kWh for the Eastern state, +/- 140 kWh for the Western state.

Multivariate linear regression analyses were run for each regional dataset (neast = 121,847; nwest = 15,298), regressing annual household electricity usage against a number of key household characteristics, householder traits, and a variable representing the number of total votes that a householder cast during the 2004-10 timeframe. In both sets of model results, the regression coefficients for householder age and total votes cast were strongly negative and statistically significant at the 99% confidence level. The regressions exhibited F-statistics that substantially exceed the critical values required to reject null hypotheses: (15, 91991) = 1740; (15, 10357) = 226. Both regressions as a whole were significant at the 99% level (p < 0.001).

Data Privacy: All data analyzed here are anonymous and treated in strict adherence to Opower’s Data Principles.

Author’s note: The analysis and commentary presented above solely reflect the views of the author(s) and do not reflect the views of Opower’s utility partners.

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