What Correlates With Energy Consumption?

Well, after yesterday’s comparison of Texas and California, which are at the opposite ends of the spectrum regarding energy consumption per person per year, I thought I’d take it a bit further.

Here is a ranked list of 49 of the 50 states (missing Hawaii and Washington D.C. at the moment): Energy per capita with other factors, US 2009

The average for the entire U.S. was 308 mbtus (million British Thermal Units) per person per year for 2009. That compares favorably with Canada (427 mbtus  per capita) but not so well with Germany (250 mbtus).

However, there is more variation found within the United States than between the U.S. and other developed countries. New York has per capita energy consumption of 196 mbtus. Wyoming has consumption of 956 mbtus, higher than Kuwait, Qatar…

Because Germany is a well-developed, high infrastructure country that even has autobahns without speed limits, I think they could serve as a goal for U.S. energy efficiency enthusiasts such as myself. So it’s nice to begin this with the observation that nine U.S. states (Maryland, Florida, New Hampshire, Connecticut, Arizona, California, Massachusetts, Rhode Island and New York) all have already achieved this target.

And there are really only 13 states with per capita energy consumption above 400 mbtus (Wyoming, Alaska, Louisiana, North Dakota, Iowa, Texas, South Dakota, Kentucky, Nebraska, Montana, Indiana, Alabama and Oklahoma).

There are some other points of interest:

  • The median household income for the 13 worst states is $46,816. The median household income for the 9 best performing states is $58,016. Those who say that rising incomes lower energy consumption may have a point, although it could be that wealthier people prefer Connecticut to North Dakota…
  • The average population density per square mile for the 13 worst states is 58.3. The average population density per square mile for the 9 top performers is 488. Urbanization is the environment’s best friend.
  • The average insolation (a measurement of how much sunlight an area receives) for the 13 worst states is 3.97. The average insolation for the 9 best performing states is 4.21.
  • The average residential electricity rates in the 13 worst states in 2010 was 9.85 cents per kilowatt hour. The average residential electricity rates in the 9 best performing states in 2010 was 15.29 cents per kilowatt hour. Incentive to conserve…

Have a look at the data and let me know what else you find that’s interesting.

State Population density (2011) Energy consumption per capita Detached Housing Median Income Ave. Insolation
 Wyoming 5.851 956 145,260 52,664 4.25
 Alaska 1.264 907 152,688 66,953 2.09
 Louisiana 105 750 1,184,167 42,492 4.76
 North Dakota 9.916 661 179,821 47,827 3.68
 Iowa 54.81 472 911,987 48,044 3.77
 Texas 98.07 456 5,171,892 48,259 4.83
 South Dakota 10.86 444 217,681 45,043 3.87
 Kentucky 110 435 1,156,003 40,072 3.9
 Nebraska 23.97 423 519,763 47,357 3.98
 Montana 6.858 422 276,433 42,322 3.96
 Indiana 181.7 409 1,802,259 45,424 3.87
 Alabama 94.65 405 1,300,272 40,489 4.34
 Oklahoma 55.22 404 1,080,624 41,664 4.36
 West Virginia 77.06 393 583,695 37,435 3.73
 Mississippi 63.5 386 791,569 36,646 3.59
 Kansas 35.09 385 818,954 47,817 4.11
 Arkansas 56.43 365 809,373 37,823 4.46
 South Carolina 155.4 347 1,078,678 42,442 4.15
 Minnesota 67.14 344 1,399,993 55,616 3.68
 Tennessee 155.4 340 1,642,085 41,725 4.04
 New Mexico 17.16 334 475,829 43,028 4.97
 Idaho 19.15 330 369,924 44,926 4.24
 Maine 43.04 327 439,459 45,734 3.82
 Ohio 281.9 315 3,221,505 45,395 3.83
 Wisconsin 105.2 309 1,531,612 49,993 3.69
88.08 inhabitants per square mile (34.01 /km2) 308
 Washington 102.6 305 1,527,867 56,548 3.53
 Missouri 87.26 304 1,679,585 45,229 4.09
 Virginia 204.5 303 1,810,353 59,330 3.9
 Georgia 169.5 301 2,107,317 47,590 4.37
 Illinois 231.5 296 2,831,011 53,966 3.72
 Colorado 49.33 290 1,122,331 55,430 4.55
 Pennsylvania 284.3 290 2,935,248 49,520 3.84
 Delaware 464.3 288 191,688 56,860 3.84
 Oregon 40.33 279 911,595 48,457 3.82
 New Jersey 1,189 275 1,794,967 68,342 3.63
 North Carolina 198.2 272 2,267,890 43,674 4.2
 Michigan 173.9 271 2,988,818 45,255 3.58
 Utah 34.3 271 520,101 55,117 4.53
 Nevada 24.8 268 432,437 53,341 5.3
 Vermont 67.73 254 193,229 51,618 3.43
 Maryland 596.3 251 1,097,673 69,272 3.98
 Florida 353.4 232 3,816,527 44,736 5.26
 New Hampshire 147 229 341,299 60,567 3.58
 Connecticut 739.1 224 816,706 67,034 3.59
 Arizona 57.05 221 1,244,172 48,745 5.38
 California 241.7 217 6,883,493 58,931 5.4
 Massachusetts 840.2 216 1,374,479 64,081 3.58
 Rhode Island 1,006 207 241,202 54,119 3.64
 New York 412.3 196 3,198,486 54,659 3.53

13 responses to “What Correlates With Energy Consumption?

  1. The “2010 Residential Electricity Rates” column, that was in my email table on this post, didn’t make it to the table above.

    The folks in LA pay a lot less then the average price noted as they didn’t do anything in regards to the 20%RE mandate vs the three large ISO’s.

    “California’s 46 publicly owned utilities manage about a quarter of the state’s power. Of them, the Los Angeles Department of Water and Power (LADWP), the state’s (and the nation’s) largest public utility with about nine percent to 12 percent of California’s generation, has been thought the bad boy for making lots of promises about developing renewables and then going back to fossil fuels.”



  2. Hi Kakatoa

    I couldn’t make it fit into the table and have it display on this blog’s format. Residential rates are in the Excel sheet at the top of the post.

  3. Tom,

    Thanks I should of checked your link to the table first……. Speaking of tables I am a PG&E customer (with a PV system installed in 2006) and I recently obtained a copy of PG&E’s “PG&E Rate Design Window 2012” documents. http://docs.cpuc.ca.gov/published/proceedings/A1202020.htm

    The documents are loaded with details by different climate zones.
    The number of households in each zone are noted below.

    Table 2A-6
    Baseline territory customers # of households
    non care (times 10^3)) % in cat % of total
    Zone P 53.1 1.95 1.405
    Q 0.931 0.03 0.025
    R 226.9 8.32 6.006
    S 443 16.24 11.725
    T 691.8 25.36 18.311
    V 25.4 0.93 0.672
    W 114.4 4.19 3.028
    X 1153.3 42.27 30.526
    Y 17.5 0.64 0.463
    Z 1.9 0.07 0.050
    toatl 2728.231 100.00

    P 22 2.10 0.582
    Q 0.07 0.01 0.002
    R 188.1 17.92 4.979
    S 212 20.19 5.611
    T 218 20.76 5.770
    V 15 1.43 0.397
    W 100.5 9.57 2.660
    X 289.4 27.57 7.660
    Y 4.8 0.46 0.127
    Z 0.01 0.00 0.000
    1049.88 100.00 100
    Grand total 3778.111
    Care % 27.79
    % Non-Care 72.21

    Sorry about the table’s lack of formatting….

  4. Cool–thanks for this! What prompts your interest in all this stuff?

    • T-

      Curiosity mostly. Like most folks I focus my energy on things I am interested in. As you noted there is a lot of stuff. Awhile back I became interested in Systems Theory and the concept of “The Problem of Problems and Problem-Solving” as discussed by Checkland http://en.wikipedia.org/wiki/Peter_Checkland . I have always been interested in the role of feedback in processes. My corporate experience was focused on reducing variation- the SD in processes. Hence I keep the components of variation in mind when looking at average data. I keep getting drawn back to “The Tragedy of the Commons” by Garret Hardin and his concerns about feedback- as noted in his “How To Legislate Temperance” part of the original paper.

      Most of my interest has been on how to make things work from an engineering perspective. In regards to PV (your Average Isolation column) it’s amazing how many things can impact the actual output of PV. A few years back I came across Andy Black’s work which was really helpful to me when specifying my PV system and rate schedule. Like Andy I have a bit of a concern on what the actual output will be from of the PV systems we are putting in place. Andy explains the issues better then I can http://www.ongrid.net/papers/PaybackOnSolarSERG.pdf .

  5. Duncan MacKenzie

    I’ve been having some difficulty getting links for you. This one isn’t per capita, but does have consumption split out by residential, commercial, industrial, and transportation.

    Back to CA and TX: The total energy used for residential and commerical is similar. CA uses a bit more for transportation, but TX has 3 times the industrial energy consumption.

    Last night I found a link from the CA department of energy about the regression factors that drive residential consumption fixes.
    Number of households per structure was important, number of people per structure was very important, cooling degree days was much more important than heating degree days, it was late and I don’t remember the rest of the parameters.

    One thing I haven’t seen discussed in any government statistics is the impact of building codes. I’m confident a significant reason for CA’s advantage is the building codes require developers to spend more upfront on energy efficiency.

    I don’t know a source that would give an indication of average age of homes in each state, but that might correlate also.

  6. Kakatoa, thanks for the link to Andy Black. Duncan, thanks for your link, too. I suspect you might be right about age of structure. As for households per structure, I’m just not accustomed to thinking of California as a multi-family structure state. And I live in San Francisco, all apartment buildings… I guess it’s because I grew up in the ‘burbs…

    • Tom,

      Andy is a great guy and just down highway 280/85 from you. I can confirm his estimate of dirty panels effecting PV output. The trees in my area are in full pollination. I have a weekly cleaning protocol which normally keep my efficiency up. This last week the pollen has been super heavy so I had to clean them twice. I was losing 10% of my output with just 3 days of pollen load on the panels. I have only had about a dozen zero output days with my PV system. Almost all of the zero output days were due to the snow load on my panels being over 1″.

      Opps. I forgot a rather large detail when it comes down to our states (CA) need for electrical power- moving and treating water to get it to the end users (in a potable form) and treating sewage. The PG&E residential energy usage data does account for this (unless you have a well like I do). It’s hard to believe I forgot about the biggest user of electrical energy in my county (El Dorado). I am sure I would of recalled this if I obtained my water from my local water purveyor http://www.eid.org/ . as they have been in the news a bunch lately- they have had to raise their rates for both water and sewage services primarily to cover the capital they spent to move to tertiary sewage treatment.

      Somewhere on my PC I have a reference that indicates that 20% of the entire states electrical usage is to purvey water and treat sewage

      • Dang spell check- the sentence above “The PG&E residential energy usage data does account for this (unless you have a well like I do).” does should be doesn’t!!!!

  7. Tom,
    Do you have links for the source(s) of info in your linked spreadsheet?

  8. Interesting paper in regards to folks behavior in Mexico-
    “Cash for Coolers”
    Lucas Davis, Alan Fuchs, and Paul Gertler
    “This paper examines a large-scale appliance replacement program in Mexico that since 2009 has helped 1.5 million households replace their old refrigerators and air-conditioners with energy-efficient models. Using household-level electric billing records from the population of Mexican residential customers we find that refrigerator replacement reduces electricity consumption by an average of 11 kilowatt hours per month, about a 7% decrease. We find that air-conditioning replacement, in contrast, increases electricity consumption by an average of 6 kilowatt hours per month, with larger increases during the summer. To put these results in context we present a simple conceptual framework in which energy-efficient durable goods cost less to operate, so households use them more. This ends up being important for air-conditioners, but not important for refrigerators.”

    Download this paper in Adobe Acrobat format: http://ei.haas.berkeley.edu/pdf/working_papers/WP230.pdf

  9. You should control for climate. Colder regions need more fuel for heating, see Canada…, Very hot regions need more energy for AC.

  10. Pingback: Internal Variability In U.S. Energy Consumption | 3000 Quads

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