Demand Controlled Filtration

1
Demand Controlled Filtration

• David Faulkner, MS, PE
• Indoor Environment Department
• Lawrence Berkeley National Lab

2
Demand Controlled Filtration

• What it is, what it is not
• Background
• Previous work
• Energy savings potential

3
What it is, what it is not

• Controls particle concentration, via the
  recirculation fans, not controlling ventilation
  (amount of outside air)
• As particle counts increase, then recirculation
  fans increase speed

4
Previous Study

• Class 100 cleanroom
• Area of 300 ft2
• Intermittent use
• Energy reduction of 60-80
• Reference Faulkner, D., W.J. Fisk, and J.T
  Walton, Energy Savings in Cleanrooms from
  Demand-Controlled Filtration, Journal of the
  Institute of Environmental Sciences 39 (6)
  21-27, 1996. LBNL-38869.

5
Current Study

• Industrial Cleanroom in San Francisco Bay Area
• 4 separate regions with different cleanliness
  ratings
• Experiments performed in Class 10,000 room
• 16 FFU
• Floor Area 606 ft2

6
Other Industrial Settings

• Southern CA industrial facility is saving energy
  by night-time setback
• Large Southern CA manufacturer is in the process
  of implementing DCF
• Large university in the East recently retrofitted
  cleanroom facilities and is ready to implement DCF

7
Case study recirculation setback

• Setback based solely on time clock, 800 PM-600
  AM
• No reported process problems or concerns from
  process engineers
• 60 70 power reduction on turndown

8
Facility Existing Procedures

• All fans controlled by PC running proprietary
  software
• Software capable of scheduling fan speeds
• Fans controlled from 100 during day to 50 at
  night and weekends??
• 100 from 600 am to 1000 pm

9
(No Transcript)
10
(No Transcript)
11
(No Transcript)
12
(No Transcript)
13
Study Phases

• Background measurements
• DCF
• Occupancy sensor

14
DCF

• Used a MetOne particle counter
• Continued night and weekend setback

15
Occupancy Sensors

• Stopped weekend and night setback
• 6 wireless occupancy sensors
• 30 minute delay after last occupancy detection

16
(No Transcript)
17
(No Transcript)
18
(No Transcript)
19
(No Transcript)
20
(No Transcript)
21
(No Transcript)
22
The Savings
23
Conclusions

• Facility was already saving (?) 28 by night and
  weekend setback as compared to 24/7
• Additional savings possible of 40 with DCF
• Smaller but still significant savings of 37 with
  Occupancy Sensors

24
Acknowledgements

• Paul Rogensack and Tony Wong
• Larry Chu and Peter Rumsey
• Dennis DiBartolomeo, Duo Wang, and Bill Tschudi
• Industry contacts
• Pacific Energy Center

25
Future Work Questions

• Is increase recirculation fan speed optimum?
• Simple interface for control

26
DAVID FAULKNER

• D_Faulkner_at_lbl.gov
• 510.486.7326