AC cooling US

Average area cooled per capita per building type

Table 1

* Assuming that the area cooled grows like the population
†Converted from sq ft to square meter

A number in parentheses represents the row in question

$\displaystyle ‡\frac{\left((0) + 1\right) \times \left((1) + 1\right) \times \left((10) + (11)\right) \times \left((2) + 1\right) \times \left((3) + 1\right) \times \left((4) + 1\right)}{(5)}$

$\displaystyle §\frac{\left((0) + 1\right) \times \left((1) + 1\right) \times \left((12) + (13)\right) \times \left((2) + 1\right) \times \left((3) + 1\right) \times \left((4) + 1\right)}{(5)}$

¶Rounded to the nearest houndredth

References

[1]: Population of the United States (2020 and historical) 
 https://www.worldometers.info/world-population/us-population/
[2]: Table HC10.1 Total square footage of U.S. homes, 2015 
 https://www.eia.gov/consumption/residential/data/2015/hc/php/hc10.1.php

Average AC intensity per building type

Table 2

*Converted from sq ft to square meter

A number in parentheses represents the row in question

$\displaystyle †\frac{(1)}{(5)}$

$\displaystyle ‡\frac{(2)}{(6)}$

$\displaystyle §\frac{(3)}{(10)}$

$\displaystyle ¶\frac{(4)}{(8)}$

$\displaystyle **\frac{(9) \times (13)}{(13) + (14)} + \frac{(10) \times (14)}{(13) + (14)}$

$\displaystyle ††\frac{(11) \times (15)}{(15) + (16)} + \frac{(12) \times (16)}{(15) + (16)}$

‡‡Rounded to the nearest houndredth

References

[1]: Table HC10.9 Average square footage of U.S. homes, 2015 
 https://www.eia.gov/consumption/residential/data/2015/hc/php/hc10.9.php
[2]: See Table 1

Efficiency improvement factors

There are several ways to decrease the cooling demand, i.e. the energy intensity to cool a building:

• Retrofitting of buildings to keep the cool inside and prevent heat from outside to enter the building
• Adopting newer ACs with improved technology
• Through behavior change, mainly increasing the temperature and by making use of smart thermostats

Retrofitting of buildings

The need for cooling and thus the energy consumed can be reduced significantly by improving the energy efficiency of the building. The earlier in the lifecycle of a building energy efficiency with regards to cooling is considered, the easier and cheaper it is to achieve energy efficiency, this should ideally start at the planning stage. But it is also possible to retrofit existing buildings with measures to inprove the energy efficiency and the need for cooling. Typical measures include:

• Trees that provide shade
• Green or cool roofs
• Compensate lack of thermal mass with insulation
• Light outside colours
• Energy efficient doors, windows and roofs
• Reduced air flows
• Air sealing
• Solar protection (low-emissivity window films or shading through shutters, overhangs or awnings)
• Storing cold

While some measures such as improving wall insulation can lead to quantifyable results through the improved U-value, others such as implementing shading result in a less predictable outcome. The effects of “cool surfaces” (roofs and walls) for example largely depend on the climate and weather circumstances where the measure is taken. The efficiency improvement factor from retrofitting a building to reduce the cooling need will therefore be an estimate. We recommend adapting it to the local circumstances. Our estimates are based on the following sources:

• IEA: The Future of Cooling, https://iea.blob.core.windows.net/assets/0bb45525-277f-4c9c-8d0c-9c0cb5e7d525/The_Future_of_Cooling.pdf
• Department of Energy: Cool Roofs, https://www.energy.gov/energysaver/cool-roofs
• Department of Energy: Attic insulation, https://www.energy.gov/energysaver/cool-roofs
• Heat Island Group: Berkeley Lab, https://heatisland.lbl.gov/coolscience/insulation
• Energy Star: Methodology for Estimated Energy Savings from Cost-Effective Air Sealing and Insulating, https://www.energystar.gov/campaign/seal_insulate/methodology

Table 3

* Assumption, based on multiple sources.

Improved AC technology

Although the energy efficiency of AC equipment has been rising in recent years, there are still large variations across and within markets. The energy efficiency of Air Conditioners differs by a factor of 3 between the least and most energy efficient ones on the market today according to the report The Future of Cooling by the International Energy Agency.

Inverter technology is an energy efficient technology for ACs, where the motor speed is adjusted instead of the unit switching on and off to maintain the set temperature. The following article contains a comparison between standard ACs and inverter ACs: https://www.researchgate.net/publication/336234751_Comparison_of_Energy_Consumption_between_a_Standard_Air_Conditioner_and_an_Inverter-type_Air_Conditioner_Operating_in_an_Office_Building.

Whilest inverter ACs are common among new sales across Europe and Japan, they have not yet been adopted at the same rate in the U.S. According to the following article by the International Energy Agency, ACs sold in Europe and Japan are typically 25% more efficient than the ones sold in the United States. https://www.iea.org/news/air-conditioning-use-emerges-as-one-of-the-key-drivers-of-global-electricity-demand-growth. This is the number we are suggesting as the efficiency improvement that can be achieved by adopting an AC with improved technology.

Table 4

References

[1]: Air conditioning use emerges as one of the key drivers of global electricity-demand growth, 2018 
 https://www.iea.org/news/air-conditioning-use-emerges-as-one-of-the-key-drivers-of-global-electricity-demand-growth

More efficient use of ACs

The U.S. Energy Information Administration published statistics from 2020 about the use of ACs. These statistics contain among others the age of the AC units, the temperature they are set at, the use of thermostat etc. The statistics are available at: https://www.eia.gov/consumption/residential/data/2020/hc/pdf/HC%207.1.pdf. Other sources have explored the energy savings (the decrease in energy intensity to cool a certain area) through behaviour change and the energy impacts that such changes have. The suggested behavior changes are to raise the temperature generally and to make use of the thermostat to vary the temperature over time to align it with the cooling needs (e.g. cooler when someone is at home, less cool when not).

The Department of Energy suggests in its energy saving tips found on https://www.energy.gov/energysaver/programmable-thermostats that by raising the temperature between 7F and 10F (3.9C to 5.6C) for 8 hours of the day, up to 10% of the energy can be saved.

According to the Hindu Business Line, the Indian Bureau of Energy Efficiency (BEE) has estimated the energy savings of a temperature increase of 4C (7.2F) would result in energy savings of 24%. That is 6% per 1C (1.8F), https://www.thehindubusinessline.com/news/bee-raising-ac-setting-by-1-can-save-6-power/article24272825.ece. The two sources come to a similar conclusion regarding energy savings from increased temperature. These findings combined with the statistics of current behavior show that there is a significant potential for energy saving through behavior change alone, requiring little or no upfront investment.

When calculating the estimated savings factor, we have compared a baseline scenario based on the weighted average behavior listed in https://www.eia.gov/consumption/residential/data/2020/hc/pdf/HC%207.1.pdf with the optimal scenario suggested in mainly https://www.energy.gov/energysaver/programmable-thermostats. To perform these calculations, we have made the following assumptions and simplifications:

• We have taken the numbers for all homes and not distinguished between single-family, multi-family or mobile homes.
• We have assumed that the time is split equally between when someone is home daytime, no one is home daytime and night time, i.e. 8h each.
• To calculate the average temperature, we have assumed the middle of each range, as well as 68F for “below 70” and 82F for “above 79”.
• For the purpose of calculating the savings factor of behavior change, we have disregarded the type and the age of the AC equipment. Calculations are detailed below.

Baseline behavior

Table 5

*Converted from degree Fahrenheit to degree Celsius

A number in parentheses represents the row in question

$\displaystyle †Weighted average temperature of (0), (1), (2), (3), (4), (5) using the middle of the respective intervals$

$\displaystyle ‡Weighted average temperature of (6), (7), (8), (9), (10), (11) using the middle of the respective intervals$

$\displaystyle §Weighted average temperature of (12), (13), (14), (15), (16), (17) using the middle of the respective intervals$

$\displaystyle ¶\text{Average of } (18), (19), (20)$

References

[1]: Table HC7.1 Air conditioning in U.S. homes, by housing unit type, 2020 
 https://www.eia.gov/consumption/residential/data/2020/hc/pdf/HC%207.1.pdf

Energy saving temperatures suggested by the Department of Energy

Table 6

*Converted from degree Fahrenheit to degree Celsius

A number in parentheses represents the row in question

$\displaystyle †\text{Average of } (0), (1), (2)$

$\displaystyle ‡(3) - (8)$

$\displaystyle §(7) - (9)$

$\displaystyle ¶\text{Product of } (11), (12)$

**Rounded to the nearest tenth

References

[1]: Department of Energy: Energy saver - Programmable thermostats 
 https://www.energy.gov/energysaver/programmable-thermostats
[2]: See Table 5