Multi-stage Interventions to Promote Persistent Plug-load Energy Savings in Office Buildings

Transcription

1 Multi-stage Interventions to Promote Persistent Plug-load Energy Savings in Office Buildings Shuoqi Wang, Ph.D. Dept. of Civil & Environmental Engineering, University of Washington, Seattle WA Amy A. Kim, Ph.D. Dept. of Civil & Environmental Engineering, University of Washington, Seattle WA Emma M. Johnson Civic Services, City of Bellevue, Bellevue, WA

2 2 Advanced Power Strips 80x Tier 2 APS deployed to staff; 20x to common areas Web-based software for users Program supported by DEFG/Enmetric Source:

3 3 Multi-Stage Experiment Design Information only how to log in to software. 60% logged in, but no savings Time based rules users received instructions and background on issue. 13% scheduled devices Admin rule monitors were scheduled off at night. 3 users opted out Team competition three teams with a champion. 28%-38% energy reduction per team Personalized energy reports showing comparison with peers. 16% overall energy reduction

4 4 Baseline Info only Rules Team Competition Baseline Personalized energy reports

5 City of Bellevue Employee Responses (n=29) 5

6 6 Project Challenges Installation time-consuming and interruptive. Attrition, labeling changes, & password management.

7 7 Savings Estimate- Energy 403 WH/Day/Cubicle

8 8 Cost Estimates- Labor Plan, direct or coordinate the study Conduct existing office equipment inventory Install plug load monitoring equipment Communicate with participating occupants Perform equipment and network maintenance Hours 1.5 hrs / quarter 33.5 hrs / project 16 hrs / project 4 hrs / month 3 hrs / quarter

9 9 Cost Estimate - Hardware Cost of APS from Different Brands Average = $53.93

10 10 Applied Energy 191 (2017) Corresponding Author: Amy Kim Co-Authors: Shuoqi Wang; Emma M Johnson Understanding the Deterministic and Probabilistic Business Cases for Occupant Based Plug Load Management Strategies in Commercial Buildings

11 11 Define cost and benefit categories Hardware Cost Labor Cost Energy Savings Analyze data from empirical studies Deterministic Calculate descriptive statistics of cost and benefit Calculate deterministic ROI using NPV, IRR, payback period Assign appropriate distributions to each parameter Generating parameter values using Monte Carlo simulation Calculate probabilistic ROI using NPV, IRR, payback period

12 12 Deterministic With the added labor cost, cash saved each year is not enough to cover the recurring cost, and initial investment will not be recovered

13 13 Deterministic When recurring labor cost is not considered, initial investment could be recovered in 6 to 10 years depending on utility price. Ten-Year NPV = $ Ten-Year IRR = 16.87% Payback period = 6 years Ten-Year NPV = $2.52 Ten-Year IRR = 6.10% Payback period = 10 years

14 14 Probabilistic Hardware and Labor National Washington State Min. Median Mean Max. Min. Median Mean Max. Count -118,800-10,680-6, ,300 10,472 kwh/yr for 100 cubicles is mean result from study -69,020-12,600-10, ,700 Need 33,630 kwh/yr to result in a positive NPV NPV [$]

15 15 Probabilistic Washington State Hardware only - limit energy savings below 60%

16 16 Results For the deterministic approach, the interventions are successful in reducing utility costs when labor cost is excluded. For the probabilistic approach, the interventions fail to recapture the additional cost of equipment acquisition, implementation, and operational expenses.

17 Shuoqi Wang Amy Kim Emma Johnson