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Campus Summer Energy Study

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Matt Schumann. Brett Kersh. Amalia Villarruel. Ryan O'Hagan. Some Background. We know: ... Electricity use drives power demand and greenhouse gas emissions ... – PowerPoint PPT presentation

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Title: Campus Summer Energy Study


1
Campus Summer Energy Study
  • Preliminary findings and recommendations

2
Student Team
  • Brianne Haner
  • LaShonda Windham
  • Ria Mehta
  • Nickita Mehta
  • Nicole Grabowski
  • Emily Pochubay

Corrine Thomas Matt Schumann Brett Kersh Amalia
Villarruel Ryan OHagan
3
Some Background
  • We know
  • Summer uses as much if not more energy per month
    than during the school year
  • Electricity use drives power demand and
    greenhouse gas emissions
  • Electricity demand is rising faster than steam
  • We know a lot about power plant operations and
    usage per month for buildings as a whole
  • but we dont know much about sub-building usage
    and demand behavior

4
Trajectory
Stabilization target
5
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6
Summer Study
  • Question 1
  • What is the effect on decreased electrical energy
    demand by modification of the HVAC schedule?
  • Question 2
  • What is the effect on decreased electrical energy
    demand through modification of end-user behavior?

7
Summer study sites
  • Focus on 6 buildings
  • Administration
  • Food Science
  • Food Safety and Toxicology
  • Bessey
  • Geography
  • Wells
  • Buildings selected based on type
    office/admin/academic laboratory classroom

8
Experimental Design
  • Measure two elements of energy usage
  • HVAC operations
  • Plug load from individual appliances,
    instruments, computers, lights, etc
  • Measure during two, four week periods
  • Baseline period business as usual, no
    conservation efforts in place
  • Commitment period conservation measures put in
    place

9
Measurements
  • Inventory tabulation of all plug load items in
    all buildings
  • Room by room inspection
  • Make and model of all units thousands
  • Produces estimate of plug load capacity
  • Monitoring tabulation and observation of what is
    running in all buildings
  • Room by room survey, one per week day time, once
    per 4 weeks night time
  • Occupancy, large equipment, lights, computers
  • Produces estimation of on-time

10
Plug Load vs. HVAC
  • Calculation aim
  • Total Energy HVAC Plug Load
  • Total Energy (HVACon-time) (PLon time)
  • KWh (KWH hH) (KWP hP)
  • For HVAC, central control
  • Obtain back plate rating for VAC, Amps, Watts for
    equipment on central control
  • Use run time numbers
  • For HVAC, not central control
  • Estimate run time
  • For Plug Load
  • Obtain power rating (actual or thru the web) for
    VAC, Amps, Watts from Inventory database
  • Estimate on-time from Monitoring surveillance
    database

11
Conservation Measures
  • A stewardship outreach and education effort
  • Provided a packet of savings behaviors and things
    that could be done
  • Web site with Tips of the Month
  • Communication with building teams

12
Sneak preview of results
13
Climate effects are minimal
14
Some scenario peeks
  • Lights in Administration
  • Plug Load inventory 3076
  • Plug Load monitoring 8 hours per day
  • Lights watts on time usage
  • 3076 32 watts 40 hr / week 3937 KWh
  • Light usage 8.3 of total usage
  • Lights off one hour each day
  • 3076 32 watts 35 hr / week 3445 KWh
  • This is a 3 reduction in building energy usage
  • Change in technology 32 to 28 W lamps
  • 3076 28 watts 40 hr /week 3445 KWh
  • This is a 3 reduction in energy usage

15
Recommendations
  • Energy and GHG reductions will come as a series
    of wedges at all scales, power plant, building
    design, usage
  • For the latter focus on
  • Reducing HVAC usage (by one hour) 3
  • Reducing lighting office and labs by one hour
    (3)
  • Turn off computers at night
  • Closing fume hoods and ovens in science buildings
  • Improve the monitoring capabilities
  • Installing protocols and certification program
    for units
  • Building design and LEED certification for new
    buildings
  • Use procurement process for energy data collection

16
Next Steps
  • Begin focus on meeting CCX targets
  • Understand day-night base load components
  • Understand effects of scheduling
  • Begin tabulation of off sets

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