Integrating Measurement & Verification in Existing Building Commissioning Projects IPMVP Options B and C

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

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

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

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. 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. “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. 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. How to design a good M&V Plan 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

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

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

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. 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. 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. (Guideline p.2) EBCx Process M&V Process 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

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

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

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

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

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. Proxy Variables (Guideline p.21) • 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.

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

26. Proxy Variables • For ON/OFF status points • Make “spot” measurements of kW • Multiple measurements and take average • kW = kWmeasured * 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. Proxy Variables • VFD Speed for kW

28. Should be in EBCx documentation 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

29. Amount of Data (Guideline p.34) • 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

30. Preparing Data (Guideline p.25) • 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)

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

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

35. Energy use B1 Energy use C C Ambient Temp 1-parameter model 2-parameter model Ambient Temp B1 B1 Energy use Energy use C C B2 B2 Ambient Temp Ambient Temp 3-parameter model (heating) 3-parameter model (cooling) B1 B1 Energy use Energy use Energy use B2 C B2 B2 C C B1 B3 B3 B4 B3 Ambient Temp Ambient Temp Ambient Temp 4-parameter model (heating) 4-parameter model (cooling) 5-parameter model Energy Modeling

36. Modeling Examples

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. 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. Uncertainty Assessment (Guideline p.61) • 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

40. Uncertainty Assessment • ASHRAE G14, Annex B, Eqn. B-15 • Uncertainty in Fractional Savings, Esave,m/Esave,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. 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. Spreadsheet Demonstration • Linear and change-point models

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

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. Case Studies • UC Berkeley • Soda Hall • Computer Science Building • 109,000 ft2 • UC Davis • Shields Library • 400,070 ft2 • Undergraduate library

46. Soda Hall • UC Berkeley’s Computer Science Department (24/7 operation) • 109,000 ft2 • 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. Soda Hall EBCx Findings

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. Baseline Model: Soda Hall • Total Building Electric Building Steam • Peak Period Electric HVAC System Electric

50. Soda Hall M&V: HVAC Systems