Measurement & Verification

Measurement & Verification
IBPSA - USA 1

The Path to Improved Performance includes M&V activities
On-going Commissioning Energy Management Comparison Against Predicted Performance M&V is part of a performance feedback loop that benefits: Facility Managers Designers Energy Modelers The Path to Improved Performance Once a building is occupied, there are several activities that can be undertaken to ensure the building is operating as it was intended. These include: on-going commissioning, energy management, and evaluating actual performance against predicted performance, which is a key part of the M&V process. Once built, the building should be commissioned to test for proper equipment functioning and interoperability. This can occur on a on-going basis. More frequently “on-going” commissioning also makes use of BAS monitored data to check current performance against historic performance and support the identification of irregularities or malfunctions (referred to as “monitoring-based” commissioning). Energy management activities may be conducted by the building operator, facilities manager, or included as part of specialized software for managing large building portfolios. Metrics are compiled and checked against benchmarks and historical data. This can provide a high-level view of building performance and give some indication of performance problems should they arise. The third activity involves comparing actual against predicted performance determined through building simulation analysis. This can provide a powerful additional view that supports identifying areas that are underperforming or not performing per their design intent. It also provides valuable feedback to the energy modeler and design team members. 2

Predicted vs. Actual “ … a quarter of the new buildings that have been certified do not save as much energy as their designs predicted ..” “If you’re not reducing carbon, you’re not doing your job.” Scott Horst, Senior Vice President, USGBC New York Times, August 31, 2009, Some Buildings Not Living Up to Green Label. The New Buildings Institute was commissioned by the USGBC to evaluate the energy performance of LEED projects. One comparison that was made was between measured results and predicted and baseline performance. This graph, which is based on that data, is published in the report. The graph shows that many of the predictions of savings are lower or higher than “measured.” Does anyone find this graph misleading? If so, why? There may be good reasons for the variations shown in this graph. No corrections have been made to account for differences in weather. The model as not been updated to account for actual operating conditions, schedules, plug loads or installed equipment. There are many explanations for discrepancy. So while the USGBC may have gotten some bad press about the effectiveness of LEED (as indicated by the NY Times article quote), the sentiment of the importance of achieved performance is critical. Being able to demonstrate that savings that were anticipated are achieved is important for making the business case for energy efficiency. It also brings greater credibility to energy modeling. From NBI/USGBC, “Energy Performance of LEED for New Construction Buildings”, March 2008. 3

M&V Resources Document Description Links IPMVP Volume I
Basic concepts and methods, measurement, uncertainty, examples IPMVP Volume III – New Construction Baseline definition, overview of methods FEMP M&V Guidelines, version 2.2 ESCO focus, owner support; application document, calibration methodology, sample selection FEMP M&V Guidelines, version 3.0 ASHRAE Guideline 14 – 2002 IPMVP concepts +, calibration criteria, instrumentation, data management, regression techniques, examples To verify energy savings, the concept of measurement and verification (M&V) should be applied. The concept of M&V was first developed in the early 1990s as the idea of ESCOs and funding energy conservation projects with energy cost savings arose. The International Performance Measurement and Verification Protocol (IPMVP) was developed that outlined an industry accepted procedure for quantifying savings that the ESCO business (and utility DSM programs) could be based on. Some good sources of information about M&V concepts can be found in the sources listed on the slide. These documents can be downloaded directly from the internet except for ASHRAE Guideline , which must be ordered from ASHRAE and costs $80/$64 (non-members/members). The FEMP M&V Guidelines v 2.2 has a couple of chapters devoted to M&V Option D. It is one of the few fully developed methodology descriptions that I am aware of. In version 3.0, it was dropped in an effort to make the document shorter. The first link listed for FEMP is for version 3.0, the second is for version 2.2. 4

M&V – Option D Activities
Savings Commissioning As-Designed Model Calibrated Model Metering Performance Data Much of the emphasis of M&V is often and somewhat mistakenly placed on the energy savings calculation. But many important IPMVP concepts need to be applied in going from installation to savings calculation. First of all the building needs to be operating per its design intent so commissioning activities must take place. It has been recoginzed the commissioning itself can result in 5 to 15% annual energy savings. Metering of the building systems supports informs, commissioning and trouble shooting activies and supports energy management. The data are also used refine energy modeling assumptions and create the as-designed model. By calibrating the energy model against actual performance data, additional insights can be gained. This information can benefit the facilities manager, energy modeler, and design team. The calibrated model can then be used to calculate verified energy savings relative to a baseline. For some projects, energy savings are a critical element (e.g. energy savings performance contracts). For LEED projects, the energy savings are less critical since they are determined relative to a somewhat arbitrary baseline that was never designed or costed. Thus for LEED projects, the process to get to the savings value may have greater value. 5

LEED M&V LEED NC EAc5 Measurement and Verification Intent Requirements
Provide for ongoing accountability of energy consumption over time Requirements M&V Plan – Option B, D savings method 2, Vol. III 1 Year M&V Period Process for corrective action Reference Guide M&V rigor and value IPMVP Volume III overview M&V activities timeline LEED NC has made M&V of interest for New Construction projects. The application of M&V to New Construction has been limited in the past for ESCOs because of the difficulty/arbitrariness of establishing a baseline. With the popularity of the USGBC LEED certification program, M&V is getting more attention- specifically IPMVP Option D. It is unfortunate though that the documentation describing this methodology has not kept up with the newer applications. But hopefully efforts by the IPMVP to update documents in the next year will help to address these needs. 6

M&V – Option D Procedures
Develop M&V Plan Ensure sufficient metering Gather and check data Calibrate Calculate verified savings The steps for carrying out M&V to support Option D are outlined in the table. One might also follow steps three and four when developing the as-built model for an existing building. This steps are described in detail in the following slides. The modeler may be less involved in step 2 than the others. If you are working on the M&V Plan and need to address metering requirements, it is important to be familiar with the details of the system design, controls, and sequence of operations as well as the electrical one-line diagrams and other drawings that indicated meter placements and type. If you are involved but are not familiar with these, try to coordinate with other members of the design team who are or the commissioning agent. 7

Develop M&V Plan LEED NC Considerations
M&V Plan – General Considerations √ Responsible party for implementing the M&V Plan Activities addressing ongoing accountability M&V option B or D Baseline definition One-year M&V period Calibration of predicted performance analysis Use of weather data coinciding with M&V period Energy savings calculation Metering requirements See for more detailed M&V Plan content outline and example LEED EAc5 M&V Plan An M&V Plan is written to outline the M&V objectives, baseline definition, metering requirements for data collection, and savings calculations. The model “calibration” encompasses the “performance reconciliation” process. For any of the IPMVP Options, the “Baseline” needs to be specified that energy savings are to be calculated relative to. Once the IPMVP Option has been specified, the savings calculation procedure is set. For example, Option B calculates savings at an EEM level based on component or system-level actual performance data compared to baseline performance data. For Option D, energy savings are calculated from actual whole-building energy use data and simulated baseline data. 8

Develop M&V Plan balance risk of savings with value of savings
In writing and carrying out the plan, one should be aware of a fundamental M&V concept that focuses on “balancing risk with value” . What this means is that you shouldn’t put more time and effort into gaining certainty of energy savings than needed. If a EEM involves a relatively fixed load with a constant schedule – it most likely will perform as assumed (but performance should be spot-checked). But if you have a highly variable load with a lot of potential energy savings associated with it, has higher risk. This EEM should be monitored sufficiently to ensure all savings are achieved. Another fundamental M&V concept is “uncertainty”. The uncertainty has to do with the accuracy of the measured results. It is based on the parameter being measured and the measuring device. The level of acceptable accuracy depends on meter accuracy and the magnitude of savings one is trying to measure. More details on uncertainty analysis can be found in the M&V reference documents. 9

Ensure Sufficient Metering
Review CD documents and coordinate with Cx agent to ensure systems in place to monitor building energy performance May not be monitoring energy usage directly Monitor to ensure building is operating per its design intent Prioritize what to monitor by considering Owner’s needs At risk “savings” Confirmation of modeling assumptions The need for metering to support monitoring-based commissioning to ensure the building is operating as intended should evaluated and the necessary monitoring points included as part of the M&V Plan. While LEED NC EAc5 would like you to make direct comparisons of electric end use data, this may not always be feasible. Instead, you may measure parameters that are an indication of energy use. In evaluating meters, keep in mind the value of the data that will be collected. Can it identify control issues that commonly arise? Will it help to confirm assumptions made in the original analysis, such as HVAC system operating schedules, lighting schedules, or plug loads? 10

Ensure Sufficient Metering
System Measure / Verification Component Verify Measure / Condition Monitoring Points Hot Water Variable-flow loop; hot water pumps equipped with VFDs. - variable-flow operation, to maintain pressure differential set point between supply and return heating water piping mains - interlocked with boiler operation; two minute delay on boiler disable - VFD speed - pump status - differential pressure between supply and return - water flow rate - heating water supply and return temperatures Chillers Equipped with VFDs. Reset chilled water supply temperature to maintain air handler discharge air temperature. - chiller efficiency (NPLV = 0.50) - chiller VFD operation - chilled water supply temperature reset from 48ºF to maintain air handler discharge air temperature - chiller power - chiller efficiency (calculated point) or/ - CHWS/RT - CHW flow This is an example of some metering points that might be included in an M&V Plan. Additional insights can be gained as to how to combine metering to support commissioning efforts as well as savings calculations can be had by looking at the sample LEED M&V Plan available through the link listed in the slide. The number of monitoring points required for an M&V process may be higher than would be normally installed, though most provide some value for operations and maintenance. These additional point might include things like chiller kW or electrical submeters on circuits like lighting. In cases where a permanent measurement point does not seem practical, then allowance for short term measurement should be provided. A good strategy is to keep circuits for different loads separate, such as lighting, plugs loads and HVAC. See for example LEED EAc5 M&V Plan with monitoring points 11

Gather and Check Data after building is commissioned
Building Description Data Climatic data Utility Data As-built documents Sequence of operations Specs Submittals Once the building is commissioned and operating per its design intent, building characteristics, climatic, and performance data can be collected to start the M&V process. The building data will be used to refine modeling assumptions to reflect actual conditions. Utility billing data should also be gathered and reviewed for gross billing errors. This can be accomplished through plotting and visual inspection or degree-day correlations. Review the rate schedule and make sure it is consistent with the values used in the model. Check the utility bill for irregularities. Use the rate schedule to give you indications of schedule and base load information. Calculate metrics to use in making high level performance comparisons. The collected and monitored data should be checked for gross errors by comparing against benchmark energy use data. Documents you may try to gather include as-built construction drawings, sequence of operations and TAB reports. You can use these documents to start to refine the original assumptions used in the model. 12

Gather and Check Data after building is commissioned
Survey and Audit Data Occupant feedback Operator interview Survey / audit forms TAB reports Monitored data Additional clarify about the actual installed systems and their operation can be gathered by conducted an on-site survey or audit. During the on-site visit, you’ll want to collect equipment name plate data and discuss the building with the facility manager or building operator. There are many sources for audit data collection sheets that you can make use of. You can also gain some insights into comfort conditions, which can affect performance, by talking to the occupants. Back at the office you can look up manufacturer's data for the installed equipment. During the calibration process, you’ll update the proposed design energy model using the collected data to develop the as-built energy model. 13

Gather and Check Data Creating Custom Weather Files
Parameters DOE-2 EnergyPlus Dry Bulb √ Wet Bulb Dew Point Humidity DP RH Atmospheric Pressure Horizontal infrared Total horizontal radiation Direct normal radiation Diffuse normal radiation Wind direction Wind speed Present weather codes Clouds Snow Depth Flag See simulation program documentation for more details on data requirements and processing tools There are certain scenarios when custom weather files are necessary. 1) TMY or TRY weather files do not exist for your location 2) A calibrated model is needed for utility data from a specific year When are actual weather data files necessary for calibration? Building loads are dependent on ambient conditions (envelope driven, high outdoor air ventilation rates such as labs and hospitals) Actual weather data varies from typical year In creating a custom weather file, you’ll want to find out what weather data parameters your building simulation program requires. This table outlines the key variables required by DOE-2/eQUEST and Energy Plus. Most simulation programs have some sort of a weather processor tool that will help with some aspects of creating the weather once you have gathered the actual weather data. Typically, this might be to convert it from text format to a format used by the program. Refer to your program documentation for more information. 14

Example Process: Create a custom weather file for 2007 for Atlanta, GA Download the TMY .CSV file for Atlanta, GA (available from EnergyPlus site) Request hourly data for 2007 from the EnergyPlus request site a_about.cfm Fill any data gaps in CSV files that you receive via Convert data to correct units for TMY version (if required) Here we go through an example process for scenario B: Create a custom weather file for 2007 for Atlanta, GA. Download the TMY .CSV file for Atlanta, GA (available from EnergyPlus site) Request hourly data for 2007 from the EnergyPlus request site Fill any data gaps in CSV files that you receive via Convert data to correct units for TMY version (if required) 15

Create a custom weather file for 2007 for Atlanta, GA Convert Dry Bulb and Dew Point Temperature to % Relative Humidity using the relation: Tdb = dry bulb temperature, Tdp = dew point temperature, RH = Relative Humidity Copy the 2007 hourly data (including the calculated RH) to the appropriate columns in the TMY .CSV file. Try to find hourly solar data…hopefully your site is included here: Copy the 2007 solar radiation values to the appropriate columns in the TMY file Convert the altered .CSV file to the type of weather file required for a given energy modeling tool using various weather file converter tools Convert Dry Bulb and Dew Point Temperature to % Relative Humidity using the relation: Tdb = dry bulb temperature, Tdp = dew point temperature, RH = Relative Humidity (if the source provides wetbulb temperature instead of dewpoint, then a different conversion is necessary. The ASHRAE Handbook Fundamentals is once source of information) Copy the 2007 hourly data (including the calculated RH) to the appropriate columns in the TMY .CSV file. Try to find hourly solar data…hopefully your site is included here: Now you have solar radiation data, but not illuminance – if you need to model daylight, then you must correlate the solar data to illuminance 16

Calibration Bound the Problem
Strong parameters Range of probable values Identify Values and Ranges Electric kWH Electric kW Gas Visually compare As-built info Operating schedules Plug loads Controls Revise Modeling Assumptions Bound calibration problem by using walk-through audit data and real information garnered about the building. Use metrics, modeling and design experience to identify the parameters of highest uncertainty/impact and their probable range of possible values. Identify and classify known and unknown model parameters Audit checklist should minimize unknown data Despite the best efforts some data will be missing or unknown Estimate Values for Unknown Parameters and Create Feasible Ranges Equipment maintenance contracts and depreciation schedules ASHRAE Handbook of Fundamentals: guidelines for equipment and lighting loads Equipment efficiencies: Reference local building codes and equipment ages Manufacturers data sheets from equipment model numbers With all the pieces now in place, you are ready to calibrate. Initially, you can do a visual check by plotting the actual versus simulated gas and electric data. If all looks good, you won’t need to go much deeper than the utility level but generally you will. Drill down as needed. Use the utility billing data to check on large end uses that be extrapolated from seasonal variation. It is always ideal to be able to directly compare actual total end use data against modeled end use data but you will usually have to use representative data sets or secondary parameters to get an indication of actual use. Focus on those components or systems that you think are questionable due to their variability or operator insights. For parameters that you are uncertain about, check their impact on performance within the range of their uncertainty to better understand the value of investigating them in more detail. 17

Calibration Guide the Investigation
Run Building Simulation Perform sensitivity analysis Identify plausible solutions Refine solution through reconciliation with actual data With all the pieces now in place, you are ready to calibrate. Initially, you can do a visual check by plotting the actual versus simulated gas and electric data. If all looks good, you won’t need to go much deeper than the utility level but generally you will. Drill down as needed. Use the utility billing data to check on large end uses that be extrapolated from seasonal variation. It is always ideal to be able to directly compare actual total end use data against modeled end use data but you will usually have to use representative data sets or secondary parameters to get an indication of actual use. Focus on those components or systems that you think are questionable due to their variability or operator insights. For parameters that you are uncertain about, check their impact on performance within the range of their uncertainty to better understand the value of investigating them in more detail. 18

Calibration Reconciliation with Utility Data
Rough calibration of components DHW from gas in summer Cooling from electric in summer Heating from gas in winter Swing season for schedules, plugs 19

Calibration Reconciliation with Hourly Data
Having tools to help facilatate data visualization can be very helpful during the calibration process. These charts are from a tool called Visualize-IT listed on the EERE tools directory and available from RLW Analytics – since purchased by KEMA. The Texas A&M also has affortable visualization tools. Both tools make use of carpet charts – shown at the bottom of the slide. Each graph shows 8760 data values. They are plotted by time of day and day of year. This type of presentation makes it easy to see ranges of values by time-of-day over the year. This is helpful for identifying patterns and outliers. In Visualize-IT, you can select a single day in the carpet chart and see the actual load shape as shown in the upper right. 20

Calibration Art versus Science
“… a detailed simulation program involving numerous input parameters is a highly under-determined problem (i.e. , the presence of too many parameters is likely to result in any solution being non-unique. “ Reddy T.A. and Itzhak Maor, “Procedures for Reconciling Computer-Calculated Results with Measured Energy Data, ” ASHRAE Research Project 1051-RP “.. It seems like most of the world’s conventional wisdom is to treat the building simulation like it is some kind of academic exercise and as though it really doesn’t make any difference whether the model of a building accurately reflects reality, just as long as it looks good.” Waltz, James, Computerized Building Simulation Handbook, Fairmont Press, Liburn, GA. There seems to be two schools of thought regarding calibration. One is presented in an ASHRAE research project (see citing) whose objective was to demonstrate that model calibration can completed be based on a scientific /statistical/ mathematical process with the user requiring limited knowledge about the building. The research project also presents an exhaustive literature review that summarizes many key considerations for performing calibrations. The other perspective is that from an experienced practitioner with a background in facilities management and energy auditing. He believes that calibration can be a better-defined problem if the analyst approaches the model by trying to model the actual building by relying on audit data and one’s experiences in distinguishing between certain and uncertain model inputs. Perhaps the approach that is best for you is somewhere in the middle. But what both authors do agree upon is that there is more than one solution. Reddy suggests averaging the savings from the handful of solutions with the best goodness-of-fit. Waltz suggests using ones experience and real-building data to narrow it down. 21

Calibration How Good is Good Enough?
Check if Calibration Criteria are Met Mean ERRmonth (+/- 15%) =100 * (M-S) / M Mean ERRyear (+/- 10%) = ∑ ERRmonth / 12 CV(RMSEyear ) (+/- 10%) =(∑ [(M-S)2 / 12])0.5 From FEMP M&V Guidelines v. 2.2 The mean bias error may be influenced by offsetting errors As pointed out by Bloomfield (Bloomfield, D.P., “An overview of validation methods for energy and environmental software”, ASHRAE Transactions, 105(2), SE , 9 pages), all computer programs make approximations. Hence any comparisons between measured and predicted performance should, therefore, be seen not in terms of whether the program agrees with the measurements, but whether the program is good enough for its intended purposes. The issue then is how does one determine “good enough.” The FEMP M&V Guidelines v. 2.2 does provide calibration criteria that helps distinguish when the results are “good enough”. The values for comparisons with monthly data are listed in the slide. ASHRAE Guideline also provides ranges of value that have been found to be mostly acceptable. You should include the calibration criteria you are going to follow in your M&V Plan. The FEMP M&V Guidelines v 2.2 has a couple of chapters devoted to M&V Option D. It is one of the few fully developed methodology descriptions that I am aware of. In version 3.0, it was dropped in an effort to make the document shorter. As part of the method, the calculations for the calibration criteria are presented. Two sets are included – one based on monthly data, another based on hourly data. The three key calculations are the monthly mean error, the yearly mean error, and the coefficient of variation of the root-mean-square error. The mean biased error is calculated slightly differently for hourly data (the sum of the hourly bias over the sum of the measured hourly data). For hourly data, the FEMP Guidelines specify MBE +/- 7%, CV(RMSE) +/- 15%. The IPMVP documents do not specify target values for calibration criteria. The ASHRAE Guideline gives ranges of values typically found to be acceptable. 22

Calculate Energy Savings
Make baseline model adjustments (schedules, setpoints, variable dependent on operation, conditions beyond the control of ESCO) Calculate Savings Savings = Adjusted Baseline Energy – Actual Energy (Option D, Method 2) Modeled Actual Energy (Option D, Method 1) The general equation for calculating savings is very basic. But to calculate the “adjusted” baseline requires a bit of effort. Adjustments are made to the baseline building model to account for differences that exist between the original modeling assumptions and the actual conditions that relate to behavior and not performance. These updates correspond to changes you made to schedules, plug loads, setpoints, etc. when you started to develop the as-built model from the as-designed model. For ESCO projects, it is easy to understand why this adjustment happens. The ESCO is responsible for the performance aspects of the installation. They are not responsible for parameters that can impact performance that are out of their control. These variables need to be identified, assumptions updated, and applied in the energy model. For LEED projects, the savings are determined relative to the ASHRAE Baseline. This is helpful for understanding how the built building performs when compared against a building built in accordance with standard building practice. But the real benefit results from going through all the steps to get to the savings calculations. Through the reconciliation process, a lot of potential performance problems can be identified and rectified. 23

IBPSA - USA M&V Case Study California Office Building 24

High-rise Office M&V Example LEED NC 2.1 M&V Implementation
New Construction Size: Approx 400,000 ft2 Principal Use: Office, Cafe, Parking Garage, Fitness Center, Data Center Energy Costs: $2.35/ft2-year Source Energy Use: 209 kBtu/ft2 year Site Energy Use: 69 kBtu/ft2 year Awards: LEED NC 2.1 Gold Efficiency Features: Under-floor air distribution Chiller efficiency, 0.51 kW/ton Variable-speed chiller Low lighting power, <0.7W/ft2 Daylighting controls Efficient glazing, SHGC 0.24 This is an example of the M&V process for new construction, in this case a high-rise office building. At the request of the owner, the name and location are not included. This work was performed when the building had been occupied for about one year. The intent here is to talk a little bit about the LEED M&V process, but to focus mostly on the simulation model calibration process; and hopefully to gain a few insights into how get our models to more closely predict actual building performance. The cost for this M&V project was close to cost of the original modeling effort, and included data collection as well as calibration and reporting. This slide shows a brief summary of building features. The design phase simulation analysis predicted 19% energy cost savings, using Title as the yardstick. 25

High-rise Office M&V Example LEED NC 2.1 M&V Implementation
Project used IPMVP Option D, Method 1 Current LEED requires Method 2 There were a few goals for the project. One was to meet LEED requirements and implement the M&V plan that had been developed for LEED EAc5 compliance. In that context the goal was to check whether verified savings match predicted savings. But that’s kind of an academic exercise, so the secondary, and probably more important goals were to identify opportunities for improvement while performing this analysis. We were hoping to provide some real value through this process. For this project we used Option D, Method 1. That means that we compared two simulation results: the calibrated simulation of the Design Case and the simulation of the Budget Case, both using typical weather. Method 1 was ok under LEED 2.1, and it was the method chosen in the M&V plan. If we had used Method 2, which is required in the current LEED program, then we would use actual utility data for the Design Case, replacing the results in the lower left box in this diagram. And the budget case would be run with actual weather data. So methods 1 and 2 differ in how the final savings are calculated. But much of the process is similar, especially the model calibration. Also this project was in California, so the baseline was Title 24 rather than Standard 90.1. 26

High-rise Office M&V Example Predicted vs. Actual
Step #1 Compare design model to utility bills  Not very close (details on following slides) The first step was gathering utility data and comparing the design-phase energy model results. 27

Electricity Not a good match. You can see that actual electricity use was about double what was predicted by the model. 28

Peak Electric Demand Electric demand was not quite as bad, but still much higher than predicted. 29

Natural Gas And natural gas was actually the opposite; in most months actual gas consumption was less than predicted. If these monthly utility data were all we had to go on, then we could make some educated guesses to calibrate the model. Fortunately in this case, we did have some additional data sources. 30

From EMS Step #2 Dig deeper… Data sources in this case Building automation system (BAS) Separate Energy monitoring system (EMS) Short-term monitoring Chiller kW From BAS The building has a pretty extensive BAS with lots of trend points. Extracting the data was harder than it should be, and data quality wasn’t perfect, but there were several useful points such as the chilled water load plotted in the lower right chart. Even more exciting was an energy monitoring system that had just been installed, which included electricity submeters on many loads. Unfortunately it wasn’t working completely at the time of this project, but we could squeeze some data out of it, such as the hourly total-building electric demand shown in the upper right. In both these graphs the hourly simulation output is plotted for comparison. These hourly reports are extremely valuable for calibration. The kW chart starts to shed some light on why our model results are so far off from actual results… Finally, some data loggers were used to gather a few weeks of kW data from the chillers because those data were not available from either of the other two sources. 31

High-rise Office M&V Example Model Calibration
Step #3 Calibrate Model Verify system performance - chillers & air handlers We saw on the previous slide that night usage was probably the main calibration issue, but we wanted to verify the performance of some of the main systems first. Accuracy of some of the data is uncertain because it comes from the BAS, and calibration was not verified as part of this project. But it is still a helpful exercise to make sure the model is reasonably close. On the left, actual fan efficiency in terms of W/cfm appears better than the model, but also appears that actual supply air flow is higher than in the model. As it turned out in this case the hourly kW matched pretty well. I didn’t bother adjusting the model, considering I wasn’t sure of the accuracy of the cfm data. In an ideal world I would have adjusted the model’s W/cfm and also try to get the airflow to match a bit better. On the right, chiller seemed to be a pretty good match, with the model being perhaps a little optimistic at low loads. But here also I didn’t see a need to make model adjustments. 32

Step #3 (continued) Verify system performance – computer room air conditioners As it turns out, a big load not included in the original model was a data center and it’s associated CRACs. Fortunately there were submeters on CRACs that could be used to verify their demand. This chart covers about one-half day and shows the constant fan and cycling compressors for two different size CRAC units. Also fortunate in this case was that the building engineers had kept a written log of kW reading from the power supply that feed the servers, and from that we learned there was about 100 kW of constant plug load that was not in the original model. That started to explain some of the missing nighttime load. 33

Step #3 (continued) Make adjustments Data center & CRACs Parking garage nighttime lighting Telecom/electrical room loads Off-hour plug loads Exterior lighting Outdoor air ventilation rate After adding the data center, and chasing down some additional loads, the kW and CHW profiles match up much better. In this case we used visual calibration because we did not have full set of hourly data and were missing large time periods. So we picked a few weeks that looked typical, and compared those to the model. We didn’t expect a perfect match because the simulation was not using actual weather data. 34

Step #3 (continued) Monthly calibrated model results Elec kWh Gas Min ERRmonth -1% 64% Max ERRmonth -7% 13% ERRyear -4% 16% CV(RMSEmonth) 6% 51% Meet Criteria? Yes No Criteria: Mean ERRmonth +/- 15 Mean ERRyear /- 10% CV(RMSEmonth ) +/- 10% At the end, the electricity results met calibration criteria listed earlier, but the gas consumption was still pretty far off. Given more time it’s possible that we could have improved the match, but we didn’t see a lot of value in doing so. That’s always a bit of a tricky issue in calibration exercises. When do we stop pursuing calibration accuracy. There are always more inputs to tweak or there is more trend data to evaluate. It’s certainly good to try to meet the criteria listed here, but it’s more important to focus on the value of the work. 35

High-rise Office M&V Example Calculate Savings
Step #4 Adjust budget model Add data center, other loads… Match schedule adjustments Match OA ventilation rate Step #5 Calculate verified savings Step #6 Think about results… Once you have a “verified design case”, the next step is to make corresponding adjustments to the budget model for things like plug loads, schedule adjustments, etc. Then calculate the verified savings. Remember, that step 5 will depend on the IPMVP method that you are using. For this project, verified savings were 17% vs predicted savings of 19%. The absolute savings was actually a little higher, but since the total usage is also higher, the percentage is lower. The lower right chart shows a slightly different picture when only regulated end uses are included. Since this was LEED 2.1, original LEED savings calculations included only regulated uses. In that context, the verified savings are a bit higher than the original prediction, which is a more satisfying result for the owner. Finally, think about what we learned… For new construction, M&V can be somewhat of an academic exercise. So what if savings versus a made-up baseline are 17% instead of 19%? Often the verified results are different than the predicted results due to a feature (or flaw) in the energy modeling process, and not necessarily a problem with building construction and operation. It can be a great education for the modeler, but how about the building owner? In this project, most of the difference between predicted and actual performance was due to things that were left out of the original model. And fixing the model doesn’t really help provide the building owner with very useful information. On the other hand, this process did highlight the fact that there is a big after-hours load in this building that is probably an opportunity for savings. And a few other opportunities were identified in viewing trends and interviewing building staff. It could be that another approach to evaluating the building, such as an energy audit or retro-commissioning project would have been a more direct path to a similar finding, but this is an example of an insight that might not otherwise pop up. 36

IBPSA - USA M&V Case Study Bethke Elementary School 37

Bethke Elementary Case Study Design through Occupancy
Owner: Poudre School District Location: Timnath, CO Principal Use: 10-month school with classrooms, gym, media center, office School Capacity: 525 Completion Date: Aug 2008 Cost: $151/sq ft Size: 63,000 sq ft Energy Costs: $0.58/ft2 year Energy Use: 47 kBtu/ft2 year Awards: LEED for Schools Gold, 3 of 4 Green Globes, Energy Star Label of 99 Bethke Elementary School, built in 2008, is located near Fort Collins, CO and is part of the Poudre School District. The project, which deserves recognition on its own merits, is compelling because of its context and story. Bethke is the 7th and last facility built through bond money released to PSD in Originally only 6 buildings were planned to be built with the bond money. But due to good planning and management of their construction projects, PSD was able to get Bethke designed and built as well. The seven schools built by PSD since 2000 all have earned Energy Star label ratings ranging from 94 to 99. 38

Bethke Elementary Design Approach – Use of Prototypes
PSD takes a prototype design approach to reduce the costs and time associated with building new schools. With each consecutive building, they would try to improve the design based on lessons learned. Four schools have been built from the elementary prototype design. With the prototype approach, each of the elementary schools have the same orientation and floor plan with improvements made to envelop, glazing, solar control, daylighting controls, and mechanical systems over time. The prototype elementary was designed for high performance from the beginning. Set on an east-west orientation, classrooms face true north or true south and are housed in a two-story portion of the building, thus reducing the building envelope size and roof area. More active parts of the building are on the south side (media center, kindergarten, art, and music) where solar control around the winter solstice can be challenging but is less critical for these space types (see Figure 1). The perimeter daylighting design includes sidelighting from vision and daylight glazing. Daylighting into core spaces occurs through toplighting with SolatubesTM. 39

Bethke Elementary M&V – EAc5 M&V Plan
Savings Calculations Operation Verification 3 Cooling tower (CT -1) VFD. Occupied / Unoccupied mode. - cooling tower fan operation interlocked with cooling water pump operation. - VFD will modulate fan speed to maintain chilled water supply at 60°F (adj.) 4 Cooling water circulation loop (P -4) Pump interlocked with chilled water pump. - pump operation interlocked with chilled water distribution pump operation. Architectural Energy Corporation provided, daylighting, energy modeling, and commissioning services for the project. The also developed the M&V Plan. The top graphic shows the approach for calculating savings. It actual depicts IPMVP Option D Method 1. Currently only Option 2 is accepted by the USGBC. The M&V Plan includes the technical approach for reconciling performance and calculating savings. The major sections of the report are: the Building Energy Budget Case and Design Case, Determination of Energy “Savings”, Weather Data, Short-term Monitoring, Visual Inspections. The M&V Plan also includes: Building System Description, Verification Components, Monitoring Points List, Data Analysis Procedures, Quality Assurance, Schedule, Monitoring Equipment Specifications and BAS Control Points. 40

Bethke Elementary M&V – Implementation
PSD Approach Commission building Compare actual against anticipated Compare actual against other prototypes OK While the M&V Plan was prepared for the project, it was not implemented as envisioned. Instead, PSD carried out their own version of M&V. Because they did have other buildings just like this building in the area, it was a reasonable approach but less complete than if the M&V Plan had been carried out. 41

Bethke Elementary M&V – Implementation
Option D Approach Collect performance data* Update proposed-design energy model Adjust baseline model for independent variables such as occupancy, schedules, .. Calculate energy savings * Assumes building is operating as intended Risk versus value? As an modeler, I wanted to find out how well our predicted savings compared against actual performance. I also wanted to do a cursory check of the building performance. With this project, the risk versus value proposition became apparent. The graphical check of the data indicted that gas performance might be off or that the modeling assumptions might be off. But electrical appeared to be in the ball park. The total actual energy costs for the building are typically ~ $36,000/year. Gas costs are ~ $12,000/year. During the first year of operation, Bethke’s gas use were about the same as Rice’s. The buildings are the same except that Bethke was 55% occupied and and had energy recovery worth about ~$1,100/year. So all the information makes me believe there could be a fraction of that $1,100 savings at risk . So perhaps PSD’s approach is sufficient given the risk and value of this proposition. 42

Bethke Elementary M&V – Calibration
From the modeling perspective though, our characterization of the Bethke’s gas use can be improved. Some studies were done to investigate the sensitivity of gas use on some modeling assumptions. We have found that in many of the buildings we model that gas use is underestimated due to over optimistic control operation. These and a few others were explored. They include: Original eQUEST – as-designed building gas use modeled in 1998 New eQUEST – latest version of eQUEST 2010 Boiler correction – increase boiler efficiency to represent condensing boilers Reduced occupants – reduced heat gain by occupants by 50% (less occupancy, small children) Partial DCV – changed DCV control type from DCV Return Sensor to Fraction of Design Flow Less Supply Air - Lower maximum reset temperature set for cooling. Reduced from 65 to 63 F. Increase U Values – Derated R-values by ~ 20% for wall ,roof, and windows. Fort Collins TMY3 – Updated weather file from Boulder TMY2 to Fort Collins TMY3. 43

Original model Original Elec Gas Total Cost kBtu/ft2 year $ Modeled 15.7 12.0 27.7 34,590 FY 2009 Actual 13.1 26.0 39.1 36,387 Error 20% -54% -29% -5% Improved Gas Modeling Assumptions Changes improved comparison. Gas use annual difference decreased from -54% to -13%. Improved Gas Elec Gas Total Cost kBtu/ft2 year $ Modeled 17.2 24.9 42.1 42,900 FY 2009 Actual 13.1 28.6 41.7 36,387 Error 32% -13% 1% 18% 44

Checking calibration criteria (monthly data)* Mean ERRmonth +/- 15% * (M-S) / M Mean ERRyear /- 10% ∑ ERRmonth / 12 CV(RMSEyear ) +/- 10% (∑ [(M-S)2 / 12])0.5 * From FEMP M&V Guidelines v. 2.2 and ASHRAE Guideline Example calculations for gas Changes in gas do not result in calibration criteria to be met. In addition, incorporating all the changes results in the electric falling outside the recommended calibration criteria ranges. Need to change only some of gas parameters and recheck or investigate electric. Data also highlight the meaninglessness of the monthly error for a utility like gas that goes to near zero in the summer. A small difference in value during one of these months results in a big error that impacts meeting criteria. 45

Measurement & Verification

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