This document summarizes a residential energy study conducted in San Marcos, CA. The study found that electricity consumption has a strong positive correlation with temperature, with peak consumption occurring in the summer. It was also found that some households are high energy users who increase their usage more in response to rising temperatures. The conclusions are that climate change may exacerbate energy demand in the future and that San Marcos should promote energy efficiency and renewable energy generation to reduce emissions.

1. B Y : K A Y L A C A R P E N T E R
Residential Energy Study in Relation to
Weather Conditions for San Marcos, CA

2. Energy Consumption & CO2 Emissions in the U.S
 Climate change is caused
by the emission of green
house gases such as CO2
 Sea level rise
 Wild fires
 Increased frequency
and intensity of heat
waves and drought
 Fossil fuel electricity
generation accounts for
38% of CO2 emissions
13%
19%
27%
39%
Sources of electricity
Renewable
Nuclear
Natural Gas
Coal
6.8%4.2%
1.0%
0.5%
0.4% 0.3%
Hydro
Wind
Biomass wood
Biomass waste
Geothermal
Solar

3. Energy Consumption & CO2 Emissions in CA
 California emits 345
million metric tons of
energy related CO2 per
year
29.7
Commercial
Electric Power
Residential
Industrial
Transportation
20%
80%
Renewables Other
 Ranked 2nd overall for
energy related CO2
emissions

4. Energy Consumption & CO2 Emissions in the U.S
 There’s a federal and state goal of reducing energy use
 The federal goal of reducing carbon emissions by 17%
below 2005 levels by the year 2020
 The California goal (AB 32 ) of reducing emissions to
1990 levels by 2020
 Jerry Brown executive order
 Options for reductions:
 At a community level  life style adjustments
 At a governmental level increase renewable energy

5. Other Studies:
 A Residential energy study in Seville, Spain found:
 The sensitivity of electricity load to daily air temperature
have increased along time
 Maximum electricity demand when maximum and
minimum temperatures occur (Valor et al. 2001)
 Now I will look at San Marcos

6. Hypotheses:
 Objective 1: Characterize energy use and CO2 emissions
in San Marcos
 Objective 2: Characterize seasonal and daily energy use
 temperature and relative humidity will positively
correlate with electricity consumption
 peak consumption will occur over the summer season
 Objective 3: Characterize the energy use behavior of high
versus low users

7. San Marcos
0
10
20
30
40
50
60
70
80
0
0.5
1
1.5
2
2.5
3
3.5
1 2 3 4 5 6 7 8 9 10 11 12
Temperature(°F)
Rainfall(in)
Long-term Averages at Vista,
CA (1981-2010)
Avg Rainfall (in) Avg Temp (°F)

8. San Marcos, CA
 Became an incorporated city in 1963
 Population in 2010 was approximately 90,000
 Pop density approximately ~ 3,400 people/mile2
 Median household income~ $64,415

9. Methods
 Hourly meter data from
SDGE in kilo-watt hours
 1 kWh will power a 100
watt light bulb for 10
hours
1 kWh = watching TV
for 10 hours
 Hourly temperature &
relative humidity data
from the University of
Utah
 Data organization
 Analyses :
 Descriptive statistics
 Correlation

10. Hypotheses:
 Objective 1: Characterize energy use and CO2 emissions
in San Marcos
 Objective 2: Characterize seasonal and daily energy use
 temperature and relative humidity will positively
correlate with electricity consumption
 peak consumption will occur over the summer season
 Objective 3: Characterize the energy use behavior of high
versus low users

11. Results: San Marcos and National average of
electricity usage and carbon emissions per household
12069
7753
0
2000
4000
6000
8000
10000
12000
14000
National San Marcos
kWh
Average kWh
kWh/home
7.27
5.35
0
1
2
3
4
5
6
7
8
National San Marcos
Average metric tons CO2
Metric tons CO2/home
Metrictons

12. Hypotheses:
 Objective 1: Characterize energy use and CO2 emissions
in San Marcos
 Objective 2: Characterize seasonal and daily energy use
 temperature and relative humidity will positively
correlate with electricity consumption
 peak consumption will occur over the summer season
 Objective 3: Characterize the energy use behavior of high
versus low users

13. Results: Seasonal Correlation
 Seasonal correlation between energy use and weather
conditions (N=2160)
Temperature Relative Humidity
Winter .025 .085
Spring .250** -.116**
Summer .492** -.275**
Fall .384** .007
* Significant at 0.05. ** Significant at 0.01

14. Hourly Electricity Consumption by Season
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
kWh
Time
Winter
Spring
Summer
Fall
All Seasons

15. Peak Hour
Usage
Summer at 9
pm: r = .729**
Winter at 7 pm:
r= -.190
30
40
50
60
70
80
1 1.5 2 2.5 3
Winter
summer
kWh
Temperature(°F)

16. Energy Consumption in the Summer at 9 pm
• Average household
uses ~1.4 kWh
• Bottom 5% of
households used
<.5 kWh
• Top 5% used >2.67
kWh

17. Hypotheses:
 Objective 1: Characterize energy use and CO2 emissions
in San Marcos
 Objective 2: Characterize seasonal and daily energy use
 temperature and relative humidity will positively
correlate with electricity consumption
 peak consumption will occur over the summer season
 Objective 3: Characterize the energy use behavior of high
versus low users

18. Identifying high and low users
0
0.5
1
1.5
2
2.5
Group 1
Group 1: households with a
significant positive
correlation between usage
and temperature
Group 0: remaining
households
T value: 7.04
Significance: .000
Standard error of the
difference: .066
Group 0
kWh
N = 374 N = 189

19. Discussion
 Comparison to Seville, Spain:
 Temperature has a strong positive correlation to energy
demand
 Both San Marcos and Seville use the most energy at the
highest temperature
 Due to the similar mild climate:
 Results are applicable to San Diego

20. Discussion
 In Mediterranean, there is a projected 2°C increase from
2031-2060
 Reduced energy use in winter, increased over summer
 Peak demand occurs over the dry season which is
expected to become drier
 Potential for energy shortages
 Conditions for solar and wind power may improve
(Giannakopoulos et al. 2009)

21. Discussion
 The frequency of extreme heat events in California is
projected to increase rapidly
 An increase up to 4x for previously temperate cities
 At current ability, electrical deficits up to 17% can occur
(Miller et al. 2007)
 Because there is a definitive relationship between
temperature and electricity demand in San Marcos:
 Deficits can occur on peak demand days

22. Conclusion:
 Temperature and electricity demand are strongly correlated
 Climate change will worsen this demand
 To comply with emission reduction goals and to avoid
potential future energy deficits, San Marcos should:
 Adjust comfort level at peak hour demand over summer
 Increase solar and wind power generation

23. Acknowledgements
 National Science Foundation
 San Diego Gas & Electric
 Dr. Yin
 Dr. Searcy

24. References
Valor, Enric, Vicente Meneu, and Vicente Caselles. "Daily air temperature and electricity load in Spain." Journal of applied
Meteorology 40.8 (2001): 1413-1421.
Miller, Norman L., et al. "Climate, extreme heat, and electricity demand in California." Journal of Applied Meteorology and
Climatology 47.6 (2008): 1834-1844.
Giannakopoulos, Christos, et al. "Climatic changes and associated impacts in the Mediterranean resulting from a 2 C global
warming." Global and Planetary Change 68.3 (2009): 209-224.
"U.S. Energy Information Administration - EIA - Independent Statistics and Analysis." Lower Electricity-related CO2
Emissions Reflect Lower Carbon Intensity and Electricity Use. Web. 21 Apr. 2015.
<http://www.eia.gov/todayinenergy/detail.cfm?id=18511#>.
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<http://energyalmanac.ca.gov/electricity/total_system_power.html>.
"U.S. Energy Information Administration - EIA - Independent Statistics and Analysis." Residential Energy Consumption
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"U.S. Energy Information Administration - EIA - Independent Statistics and Analysis." State-Level Energy-Related Carbon
Dioxide Emissions, 2000-2009. Web. 21 Apr. 2015. <http://www.eia.gov/environment/emissions/state/analysis/>.