1. 1 Integrating Measurement & Verification in Existing Building Commissioning Projects IPMVP Options B and C David Jump, Ph.D., P.E. Principal Quantum Energy Services & Technologies, Inc. (QuEST) www.quest-world.com

2. 2 Presentation Overview This presentation will discuss: Need for M&V in EBCx projects CCC’s Verification of Savings Guideline M&V Methodology & Approach Overlap with EBCx projects Procedure Case Studies

3. 3 Benefits of EBCx Indoor air quality Thermal comfort Equipment reliability Equipment Maintenance More… Most quantifiable benefit: Energy Savings

4. 4 Need for M&V in EBCx EBCx Energy Savings Typically ~5% of whole building energy use Cannot “see” at main meters Based on data collected before improvements made Called “ex-ante” savings estimates No standard calculation methodologies for ex-ante savings

5. 5 Ex-Ante Savings Calculations Savings = 24,379 – 7,603 = 16,776 kWh annually (?)

6. 6 Data Requirements In example: Trends of fan power and weather required Sources:  Building automation system  Independent loggers  Local weather stations Data preparation requirements: Merge data sets Prepare analysis ‘bins’ Analysis Model systems Make assumptions QA on result (“reasonableness”) Savings calculation effort takes time, focus, & resources away from commissioning the building!

7. 7 Need for M&V in EBCx Need confidence that savings are real Typ. project cost: $20k to $100k Owners Need assurance of return on investment Utility programs Need to justify expense of ratepayer moneys

8. 8 “Confidence” Expressed as “Uncertainty” Less uncertainty = more confidence Ex-ante savings: No way to determine savings uncertainty e.g 16,776 kWh  ??? Uncertainty may only be determined by: Calculations using measurements of energy use before and after ECM installed e.g. 16,776  839 kWh (10%)

9. 9 Methodology Overview This methodology is based on: Continuously monitored building data Regression-based energy modeling Applied to: Whole building Building subsystems Written for integration in EBCx projects Large overlap between M&V and EBCx processes

10. 10 Guideline - Contents Introduction General Description of M&V Process M&V Approach Required Resources Analysis Methods Measurement and Verification Process Appendices A: Empirical Models B: Uncertainty Analysis C: Example M&V Plan D: Example Projects How to design a good M&V Plan

11. 11 Measurement & Verification - Graphical Concept Adjusted Baseline Measured energy use

12. 12 M&V - Basic Equation Energy Savings = Baseline Energy – Post-Installation Period Energy ± Adjustments Adjustments are: Routine Adjustments Non-Routine Adjustments

13. 13 Routine Adjustments Normal and expected variations in energy use due to operating conditions, normal productions, etc. Equation becomes: Energy Savings = Adjusted Baseline Energy – Post-Installation Period Energy ± Non-Routine Adjustments

14. 14 Non-Routine Adjustments Energy use (or lack of) due to non- routine events, occupancy or equipment changes, etc. Examples: Tenant moving in or out of a space Chiller failure and replacement Major renovation project Etc.

15. 15 Focus of this Guideline Whole Building (IPMVP Option C) Short-term interval data from Utility or energy information systems (EIS) Meters connected to EMCS and trended Individual building systems (IPMVP Option B) EMCS trends Other energy information system data Temporary or permanently installed meters 2 different approaches, 1 method

16. 16 Scope of Cx Activity Identify purpose/goals of Cx activity Describe roles of involved parties Identify systems included in Cx process Planning Phase Establish bldg. requirements Review available info./ visit site / interview operators Develop EBCx Plan Document operation conditions Investigation Phase Identify current building needs Facility performance analysis Diagnostic monitoring System testing Create list of findings Implementation Phase Prioritize recommendations Install/Implement recommendations Commission Recommendations Document improved performance Turnover Phase Update building documentation Develop final report Update Systems Manual Plan ongoing commissioning Provide Training Persistence Phase Monitor and track energy use Monitor and track non-energy metrics Trend key system parameters Document changes Implement persistence strategies M&V Process EBCx Process (Guideline p.2 )

17. 17 M&V Approach Option C - Whole Building Option B: Retrofit Isolation (HVAC Systems) Select measurement boundary (Guideline p.9)

18. 18 Retrofit Isolation Defining Systems - by ‘Services’ provided Chilled water system:  Chiller, CHW pumps, etc. Air handling system:  Supply fan, return fan, exhaust fan Hot water system:  Boiler, HW pumps (Guideline p.14)

19. 19 Data Sources Whole-Building Meters Electric – 15 minute interval data Monthly Gas & Electric data Utility websites, e.g. PG&E’s Interact Resource http://www.pge.com/mybusiness/ener gysavingsrebates/demandresponse/to ols/ e,g, PG&E’s Business Tools http://www.pge.com/mybusiness/ myaccount/analysis/ Interval Gas Data (Pulse Counter) Bolt-on pulse meter Face plate replacement

20. 20 Data Sources BTU meters Water flow meters Portable ultrasonic Insertion-paddlewheel

21. 21 Data Sources Weather PG&E’s Interact website provides cleaned weather data on hourly basis Other Sources: www.gard.com/weather/index.htm www.weatherunderground.com Take particular note of http://www.eere.energy.gov/buildings/energyplus/cfm/ weather_data.cfm  which gives sources for weather data in a variety of formats, including real-time data.

22. 22 Data Sources For Option B Retrofit Isolation Approach e.g. HVAC Systems

23. 23 Data Sources HVAC Systems Cooling Tower Fans Chillers CDW & CHW Pumps AHU Fans Constant load Variable load Equipment Power “Spot” measurements Power logging instruments Convert feedback status signals to power/energy Proxy variables

24. 24 Proxy Variables Generates energy variables (kWh, kW, therms, etc.) from: Feedback status signals trended in EMCS Constant load / constant speed equipment  on/off status, etc. Variable load / variable speed equipment  VFD speed, amps, etc. Independently measured or logged data kWh, kW Hot and chilled water flow, etc. (Guideline p.21)

25. 25 Proxy Variables Example of constant and variable load feedback signals on EMCS

26. 26 Proxy Variables For ON/OFF status points Make “spot” measurements of kW Multiple measurements and take average kW = kW measured * STATUS For variable speed/load signals Short term logging of equipment kW Corresponding trended load data from EMCS Develop relationship between kW and load

27. 27 Proxy Variables VFD Speed for kW

28. 28 Required Resources - Data Gather physical information, within the measurement boundary, for the baseline period: Energy data (kWh, kW, therms, etc.) Assure sensors are calibrated Independent variables: Ambient temperature, occupied hours, etc. Static Factors: Equipment inventory, building characteristics Occupancy, operational schedules Operating procedures, set points Should be in EBCx documentation

29. 29 Amount of Data Interval Data (Whole Building and Systems): Issue needs more research (ASHRAE research topic) General guidance: Enough to cover a “cycle” of operation (IPMVP requires data through one cycle)  Constant load equipment: spot measurement  Variable load equipment: through range of its operation  Chilled water system: entire cooling season  Building – one year, or half year from coldest to warmest months Enough to capture 80 or 90% of range of data Data collected in season when ECMs have most impact (Guideline p.34)

30. 30 Preparing Data Different sources Whole building electric – short term interval data Local airport or NOAA weather file Energy information system Energy management and control system Different types COV, analog, digital, “categorical”, etc. Different time intervals 5-min (e.g. EMCS trend) 15 min (utility whole-building kWh) Hourly (NOAA weather) (Guideline p.25)

31. 31 Preparing Data Methods require all data to be on common time interval Called “analysis time interval” Guideline recommends: Hourly Daily

32. 32 Useful Data Preparation Software Tools Universal Translator Merges and aligns multiple data sets to same time stamp Interpolates between points, etc. Much more! Free from www.utonline.org Energy Charting and Metrics (ECAM) Tool Sets up categorical variables for weekdays, weekends, etc. Much more! Excel add-in Free from www.cacx.org

33. 33 Important! In almost all cases, after the ECM has been installed, you cannot go back and re-create the baseline. It no longer exists! It is very important to properly define and document all baseline conditions before the ECM is implemented.

34. 34 Short Term Interval Methods Empirical energy use models E = F (x i ) Statistical regressions Models are built directly from data Can determine best model type and fit Can calculate model uncertainty (Guideline p.29)

35. 35 Energy Modeling 1-parameter model Ambient Temp C Energy use 2-parameter model Energy use B1 C Ambient Temp 3-parameter model (heating) Energy use C B2 B1 Ambient Temp Energy use B1 B2 C Ambient Temp 3-parameter model (cooling) Energy use B3 C B2 B1 Ambient Temp 4-parameter model (heating)4-parameter model (cooling) Energy use B3 C Ambient Temp B2 B1 5-parameter model Energy use C B1 B2 B3B4 Ambient Temp

36. 36 Modeling Examples

37. 37 Developing Models General Procedure Plot data Select model type (1-P, 2-P, 3-P Cooling, etc.) Select change point Perform regressions (averages where needed) Calculate CV & NMBE Adjust change point Perform new regressions Calculate CV & NMBE, compare with run #1 Iterate to lowest CV & NMBE Can develop in spreadsheets using macros

38. 38 Assess Baseline Model Develop different energy use models Select model that best fits data (low NMBE, CV) Run uncertainty assessment Determines if model can determine savings within reasonable uncertainty May need to select alternate approach Finalize approach Decide how long to measure in post-installation period (Reporting Period) Document in M&V Plan

39. 39 Uncertainty Assessment Purpose: To determine if model will be able to distinguish savings from the model’s uncertainty Reference: ASHRAE Guideline 14 Annex B Appendix B in Verifying Savings in EBCx Guideline Procedure: Gather data Develop model Estimate expected savings Calculate fractional savings uncertainty Compare with savings estimate (Guideline p.61)

40. 40 Uncertainty Assessment ASHRAE G14, Annex B, Eqn. B-15 Uncertainty in Fractional Savings,  E save,m /E save,m For “weather models with correlated residuals” Each point has a relationship with the previous point Potential when time unit is short (e.g. daily or hourly)

41. 41 Useful Software QuEST Change-Point Model Spreadsheets www.quest-world.com Excel-based Energy Explorer Automatically determines best fit of change-point models to data, makes charts, calculates savings, uncertainty, etc. Source: Prof. Kelly Kissock, University of Dayton ASHRAE Inverse Modeling Toolkit (RP1050) Purchase with Research Project 1050 DOS-based, source and executable files Includes test data sets

42. 42 Spreadsheet Demonstration Linear and change-point models

43. 43 Post Installation Model Similar to baseline model Developed from post-installation data Two Uses: 1. Annualizing Energy Savings 2. Savings Persistence/Performance Tracking Example in Case Study

44. 44 Annualizing Savings Use when less than one year of data Baseline or Post-Installation Use baseline and post-installation models with independent variables TMY weather data Other variables Difference is annual savings

45. 45 Case Studies UC Berkeley Soda Hall Computer Science Building 109,000 ft 2 UC Davis Shields Library 400,070 ft 2 Undergraduate library

46. 46 Soda Hall UC Berkeley’s Computer Science Department (24/7 operation) 109,000 ft 2 Central Plant (2 - 215 ton chillers & associated equipment) Steam to hot water heating 3 Main VAV AHUs, AHU1 serves building core, AHUs 3 and 4 serve the perimeter, with hot water reheat

47. 47 Soda Hall EBCx Findings

48. 48 M&V Approach for Soda Hall Resources: Whole-building electric and steam meters present EMS that trends all points at 1 min (COV) intervals 8-month history of data RCx measures in AHU and Chilled Water Systems Electric and steam savings Very high EUI – unsure if can discern savings at whole building level M&V Approach: Option B – applied at systems level (electric only) Option C – whole building level (electric and steam)

49. 49 Baseline Model: Soda Hall Total Building ElectricBuilding Steam Peak Period ElectricHVAC System Electric

50. 50 Soda Hall M&V: HVAC Systems

51. 51 Soda Hall: Estimated vs. Verified Savings

52. 52 Shields Library UC Davis Undergraduate Library 400,072 ft 2 Chilled Water and Steam provided by campus central plant 2 CHW service entrances, variable volume 2 HW service entrances 11 AHU, 3 VAV, 8 CAV 5 electric meters

53. 53 Shields Library RCx Findings Savings: no estimates prior to measure implementation

54. 54 M&V Approach for Shields Library Assessment: Whole-building meters present: 5 electric meters 2 CHW meters (installed as part of project) 3 HW meters (installed as part of project) EMS that trends all points at 5 min intervals RCx measures in AHU, CHW and HW pumps Electric, chilled water, and hot water savings M&V Approach: Option C – whole building level

55. 55 Shields Library: M&V Models ElectricChilled Water Steam

56. 56 Shields Library: 480V Electric Meter Savings

57. 57 Shields Library: Chilled Water Savings

58. 58 Shields Library: Hot Water Savings

59. 59 Costs Including all costs, project remains cost-effective: Soda Hall: 1.7 year payback Tan Hall: 0.7 year payback Shields Library: 1.0 year payback Added costs of metering hardware and software did not overburden project’s costs In private sector – metering costs lower Existing electric meters Sophisticated BAS systems MBCx approach should be viable Evaluated project realization rates: 105% electric, 106% gas

60. 60 Questions?

61. 61 Future Work QuEST M&V Tool for Universal Translator Additional M&V Guidelines from CCC Option A Option B – component based Option D – simulations Non-IPMVP adherent methods ASHRAE TRFP