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ID-O Energy Dashboard Engaging Occupants to Save Energy
1/15/2014 1
«dashboard-controllers» that enable building occupants to control energy-using components and systems with expert feedback for saving energy and increased occupant comfort
Azizan Aziz*
Vivian Loftness*, Bertrand Lasternas*,
Ray Yun*, Leah Mo*, Ruchie Kothari*, Jie Zhao*
Peter Scupelli [Design], Anthony Rowe [ECE]
*Center for Building Performance and Diagnostics Carnegie Mellon University
EEBHUB Year 3: Energy Dashboards for Plug Loads Lighting, Thermal, Ventilation for Future Years
Plug Load Best Practices Guide Managing Your Office Equipment Plug Load : NBI/Pier 2012
1/15/2014 2
FEATURES (1st generation Dashboard) feedback
control*
control*
recommendation
whoops, on overnight
my desktop!
FEEDBACK ………………….. selecting the format that communicates to you
I left this much on during vacation?
FEEDBACK ………………….. looking a monthly consumption
FEEDBACK ………………….. checking out the competition
I use double the average?
RECOMMENDATION … generated by expert analysis of use
wow look what I saved
CONTROL ……………………. on-line, item by item or as a group
Preliminary Study
For a preliminary study, we provided our system to one government research lab (n=8), one university office suite (n=7), one university graduate research lab (n=6). We investigated the impact on Energy Dashaboard on energy savings.
Government research lab (8)
University graduate lab (6)
University office suite (7)
1st generation dashboard (2012)
The Energy Dashboard with monitoring, advice, comparisons and controls yielded 10% energy savings overall. (Government lab: 5% increase! With reductions in the University office suite: 30%, University lab: 31.5%)
168 kWh 155 kWh
89 kWh 82 kWh
76 kWh
63 kWh
0 kWh
50 kWh
100 kWh
150 kWh
200 kWh
250 kWh
300 kWh
350 kWh
2 Weeks Before Intervention 2 Weeks After Intervention
(kWh) Energy Savings (Overall)
Weekend
Night
Day
10 %
Saving
Preliminary Findings
In the University Office Suite, occupants turned off their electronics more often at night and on weekends after the dashboard intervention.
42,225 Wh 35,734 Wh
8,731 Wh
1,837 Wh
6,653 Wh
3,033 Wh
2 Weeks Before Intervention 2 Weeks After Intervention
University Office Suite
Weekend
Night
Day
30 % Saving
60
50
40
30
20
10
0
(kWh)
54%
79%
Best Preliminary Findings
13
2nd Generation Dashboard
Area Chart …………. Week view with hourly intervals Most useful and engaging
Behavior Effectiveness Percent effectiveness for your behavior towards energy savings per device
CONTROL ……………………. on-line, item by item or as a group
Calendar Scheduled control
Field Study
Eighty employees were divided into four groups. The first group is the control group, the three differently designed interface were assigned to the rest of the groups.
Large office building (80)
Feedback only (n=20)
Feedback + Control (n=20)
Feedback + Control + Automation (n=20)
Preliminary Findings
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Group A (Nothing)
Before Energy Dashboard After
Preliminary Findings
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kWh
Group B (Feedback only)
Before Energy Dashboard After
Preliminary Findings
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Group C (Feedback + Control)
Before Energy Dashboard After
Preliminary Findings
0
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Group D (Feedback + Control + Calendar)
Before Energy Dashboard After
0
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Before After
Group A (Nothing)
Weekend
Night
Day
4.9 % Reduction
Preliminary Findings
(kWh)
0
1
2
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6
7
Before After
Group B (Feedback only)
Weekend
Night
Day
14% Reduction
17%
11%
Preliminary Findings
14%
(kWh)
0
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Before After
Group C (Feedback + Control)
Weekend
Night
Day
23% Reduction
29%
11%
Preliminary Findings
44%
(kWh)
0
1
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Before After
Group D (Feedback + Control + Automation)
Weekend
Night
Day
42% Reduction
60%
19%
Preliminary Findings
75%
(kWh)
28
http://online.wsj.com/article/SB10001424127887324886704579052883651889864.html
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JOURNAL REPORTS September 22, 2013, 5:17 p.m. ET
Journal Report
Insights from The Experts
Read more at WSJ.com/Energy
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TKtk
The dashboard used in the Carnegie Mellonstudy charts individual energy use by deviceover time.
By LISA WARD
Energy dashboards—tools that show consumers how much power they are using, and how to use
less—are becoming more common in households.
Can the same technology help reduce energy use in
office buildings?
That's the question two separate pilot projects are
hoping to answer. Researchers from Carnegie Mellon
University and the National Renewable Energy
Laboratory are giving so-called energy dashboards to
dozens of office workers to show them, via charts and
graphics, how much energy they are using at any
particular moment.
Based on what they see, and the dashboard's feedback, workers can then make smart decisions
about how to cut back on their energy usage.
If more workers took responsibility for their own
power usage, the savings could be huge. Commercial
buildings account for 36% of all energy used in the
U.S., according to Department of Energy. Experts
believe a significant portion of that is waste; many
buildings run close to full power on nights and
weekends.
So far, the indications are promising. The Carnegie
Mellon team found that two out of three sites in an
initial small-scale study saved about 30% of energy
compared with a baseline. The third site, a government
research lab, showed no real savings because the lab's
policy is to keep its computers running at all times.
The amount of energy employees personally have control over may grow even more in the
future. Plug loads—the energy used by anything plugged into an electric socket—represent about
10% to 30% of consumption in an average office building, says Nicholas Holt, a director at the
Dow Jones Reprints: This copy is for your personal, non-commercial use only. To order presentation-ready copies for distribution to your colleagues, clients orcustomers, use the Order Reprints tool at the bottom of any article or visit www.djreprints.com
Energy Dashboards Enter the Office CubicleStudies Give Workers Tools to Monitor and Reduce Their Individual Energy Use
now we need to tackle the bigger energy users: heating, cooling, lighting, ventilation... for energy conservation and increased occupant comfort
WHAT’S NEXT?
1/15/2014 30
Page 9
Challenges
• Focus on how OB physically and quantitatively affect on building performance
IEA Annex 66: Definition and Simulation of Occupant Behavior in Buildings
Back-up slides
1/15/2014 32
Diagnostic : Energy Saving Parameters had deficient settings, energy saver was working for the monitor but not the for CPU. The user believed her computer was in sleep mode as her monitor was in sleep mode. Recommendation : Optimization of the CPU Energy Management Settings .
Savings : 70 % Energy Savings
Individual Actions
1/15/2014 33
1/15/2014 34
Diagnostic : This old computer was used as a server and needed to stay active all the time. This obsolete computer was using too much energy. Recommendation : Change the computer with Top 10 Energy saving computer http://www.energystar.gov/index.cfm?fuseaction=find_a_product.
Savings : 60 % Energy Savings
Individual Actions
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