International 6SigmaDC User Conference CFD Modeling for Lab Energy Savings DCSTG Lab Temperature Setpoint Increase

Transcription

1 International 6SigmaDC User Conference CFD Modeling for Lab Energy Savings DCSTG Lab Temperature Setpoint Increase Chris Noland Vipha Kanakakorn 3/4/2010

2 Goal & Limitations Goal: To confirm energy savings based on industry understandings related to raising Lab Return Air Temperature Setpoint (RATS) and water temperature setpoints in a replicable way throughout Cisco community Temperature Limit: Cisco Equipment Non Cisco Equipment Human Comfort Humidity SJC7 Lab D CRAH Setpoint 104 F 95 F F F

3 Challenges Raising lab temperature safely Identify potential hot spots Take measures to prevent equipment overheating Maintain temperature safety margin Identify optimal air and chilled water temperatures Optimizing air flow in the lab Minimize short-circuiting air by-passing air mixing of hot and cold air Floor Grill Rearrangement Blanking Panel Containment Time Budget Constraints; Future Plans

4 SJC7 Lab D The Building: Commissioned in1999 mixed-use building Building total 2.5 MW The Lab Working lab for MDS product line 6,800 sqft 2 Raised Floor 7 30-ton CRAHs IT Load 2.3 kw/rack average 368 racks total 735 kw Implemented Best Practices: Redundant power supplies off Power Savings Program Virtualization Blanking Panels Floor Grill Rearrangement Picture courtesy of Future Facilities

5 SJC7 Lab D (cont d) Cisco Lab Environment Lab D is functioning QA Lab for MDS product line No UPS No Redundancy Frequent equipment moves, mostly additions Cisco labs occupy more sq.ft. than datacenters, 1.2 M sq ft total Cisco labs consume more energy than datacenters Overheat plot Damper Open Area Plot

6 SJC7 Lab D (cont d) Monitoring: M&O team monitors and controls 200+ Temp Sensors at different heights in front & back of racks Temp Sensors at CRAHs return & supply Temp Sensor at make up air grills Outside Air Temperature (OAT) 3 Chillers Cooling Plant measured as black box PM8 & CT Coils additional metering

7 Steps Evaluate the CFD Tool Build & Calibrate baseline model Outline what-if scenarios Floor Grills Blanking Panel Different Temperatures Turn one CRAH off Turn Lights off Simulate the scenarios Identify optimal solutions from modeling Implement selected solutions Quantify Savings

8 Evaluation of 6 Sigma Compare sensor temperature reading to simulated temperature and positive correlation is confirmed

9 Evaluation of 6 Sigma (cont d) Compare simulated and actual temperatures at the CRAH units

10 Evaluation of 6 Sigma (cont d) Compare simulated and measured volumetric airflows and 10-15% error was found Simulated Measured Model was then calibrated according to the actual measurement of airflow as well as power consumption Pictures and information courtesy of Future Facilities

11 Simulation Scenarios I Baseline to ensure model integrity II Blanking Panels Installation Nov 25, 2008 to reduce mixing of hot and cold air III Floor Grill Rearrangement a. Dec 4, 2008 to resolve some hot spots b. Jan 8, 2009 to reduce overcooled areas

12 Simulation Results I BASELINE II BLANKING PANELS III FLOOR GRILLS a III FLOOR GRILLS b

13 More Simulation Scenarios IV Increase CRAH setpoint Baseline setpoint 71.6F Increments of 2 F until we saw red: 73.6F, 75.6 F, 77.6F, 78.6F, 80.6F, 82.6 F, V What if lights are turned off VI What if one CRAH unit is turned off VII Blanking Panel Scenarios ACU Supply and Return Plot

14 Simulation Results: IV CRAH Setpoint Increase Status Quo: 71.6F 73.6F 75.6F As CRAH Setpoint increases, simulation shows there is room to further increase the setpoint without the equipment overheating.

15 Simulation Results: IV CRAH Setpoint Increase (cont d) 77.6F 79.6F 81.6F With Return Air Temperature at 81.6 F, equipment begin to overheat.

16 Simulation Results: V Lights On & Off Lights On Lights Off Lighting has minimal effect on temperature profile Still a good practice

17 Simulation Results: VI One CRAH off All CRAH s On One CRAH Off At 77.6 F setpoint, turning one CRAH off results in some equipment overheating

18 Simulation Results: VII Blanking Panel Scenarios No Blanking Front Blanking Lid on Top Lid on Top and Front Blanking

19 Selected Implementations based on Simulation Results Install Blanking Panels Rearrange Floor Grills Increase CRAH Setpoint to F Turn lights off when not in use Under floor plot

20 Implementation: Raising Setpoints Raised RATS in Labs, from 70 to 74,76,78 & 80 Setpoint Temperature (F) Date Lab D CRAH Lab C CRAH Lab A&B CRAH Supply Chilled Water Baseline /24/ /25/ /26/ /3/ /10/ /12/ /8/ /29/09 48 Two weeks later raised chilled water setpoint from 44 to 46 and then to 48

21 Savings Results Pairing Similar Days Model Prediction Model Pairing Model Incremental Changes Day of week Date Last Change Average OAT (F) Ave. IT Load (kw) Ave. Cooling Load (kw) Savings kwh/year Cooling Savings Parameters affecting energy consumption: Outside Air Temperature (OAT) IT Load Day of the Week (DOW) Time of the Day (TOD) Previous days OAT and IT Load 1 Sun 2/22/09 Baseline 58 1, Sun 3/1/09 Lab D 78 F 59 1, , % Sat 3/7/09 Lab D 80 F 50 1, Sat 3/14/09 Lab C+ 80 F 51 1, Mon 3/9/09 Lab D 80 F 48 1, Mon 3/23/09 Lab C+ 80 F 49 1, Sun 3/29/09 Chilled water 44 F 55 1, Sun 4/26/09 Chilled water 46 F 54 1, Tue 4/7/09 Chilled water 44 F 56 1, Tue 4/28/09 Chilled water 46 F 55 1, Pairing Model Baseline to Final Day of week Date Last Change Average OAT (F) Ave.IT Load (kw) Ave. Cooling Load (kw) 123, % 49, % 483, % 541, % Savings kwh/year Cooling Savings Setpoint Temperature (F) Date Lab D CRAH Lab C CRAH Lab A&B CRAH Supply Chilled Water Baseline /24/ /25/ /26/ /3/ /10/ /12/ Sun 2/22/09 Baseline 58 1, Sun 5/24/09 Chilled water 48 F 57 1, , % 4/8/ /29/09 48

22 Prediction Model Parameters: OAT, IT load, DOW, TOD, and OAT/IT Load from previous 5 days Baseline, CHW 44 F: data is used to create model 03/16/09-04/06/09 After Temp Change, CHW 48 F: 05/08/09-10/07/09 Data is plugged in to model to predict energy consumption Prediction model curve represents the energy used had we not changed the setpoint Savings is the delta between Prediction model & Actual measurements Savings 2,006,000 kwh annually or 21% of cooling cost.

23 Lessons Learned Room Prep Raised RATs Raised CHW OAT and IT load can affect cooling load beyond current day and they change constantly needed to incorporate into model More measurement points needed for longer periods of time More testing cold aisle containment stay tuned It s better to learn in simulations than to try it on actual room. Things to incorporate in future simulations: Containment More Separation of Hot and Cold Air VFD Close floor tile dampers to match the load of room

24 Conclusion Raising air and water temp saves 13-21% of cooling cost Payback period for SJC7 proof of concept is 6-12 months Based on this work, Cisco Facilities has increased lab temperature in San Jose and other campuses where appropriate for an estimated savings $2M+ per year These efforts are a part of Cisco s larger strategy to reduce its carbon footprint by 25% by 2012 Future Facilities was valuable and proving to the facilities team that it is safe to raise temperature in the lab Current lab design is awesome because it lasts over 20 years

25 A Special Thank You to our Partners CISCO WPR Special Thanks to Akhil Docca & Future Facilities Support Team Chris Noland Vipha Kanakakorn