M&V 2.0 - Background and Applications Building Performance Session 2: Elements of Building and Data Management Tools M&V 2.0 - Background and Applications David Jump, Ph.D., P.E. Quantum Energy Services & Technologies, Inc. August 3, 2015

Agenda M&V 2.0 - Defined Tools Example Application Guidelines

Whole Building M&V Option C - Whole Building Option B: Retrofit Isolation (HVAC Systems)

Technology Advancements Advanced Metering Systems Capture time-granular data (5-15 minute, daily) Time-of-use meters in large buildings Smart Meters Small and medium sized commercial Residential Building sub meters / EMS trends Advanced Modeling Capability Advanced Regressions Change-point models Nearest Neighbor Neural Networks, etc. More influencing parameters: weather, time of day, solar effects

M&V 2.0 Definition M&V 2.0 uses short time interval data and advanced analytics to determine actual savings in a building or building subsystem Intervals: 5, 15 minute, hourly, daily, etc. Applicable at any building sub system level when data available M&V 1.0: monthly billing data, degree-days, ordinary least squares, or other simple regression analysis

Illustration – Monthly vs. Interval Data M&V 1.0 - Monthly M&V 2.0 - Interval

Comparison M&V 2.0 – Interval Data M&V 1.0 –Monthly Data Linear regressions 12 months/data points per year High uncertainty with moderate savings Ex: 10% savings, 10% CV, 95% confidence 77% Uncertainty Monitoring duration req. 12-month baseline & post Advanced analytics 8760 hourly points per year 6-fold lower uncertainty with moderate savings Ex: 10% savings, 10% CV, 95% confidence, high autocorrelation 12% Uncertainty Monitoring duration – can be much shorter 3 & 6 month baseline 3 & 6 month post Applicable to subsystem interval data

Timeline Representation

Predictability Good buildings: Predictable operation Bad buildings Requires intervention Ugly buildings Cannot predict future use The Good The Bad The Ugly

Whole Building M&V 2.0 Advantages Comprehensive: accounts for all ECM savings, including interactive effects Simple: few data streams required Shorter monitoring requirements: Baseline model development and savings estimations based on months, not years Higher quality: Estimates savings uncertainty Persistence: Fast feedback on building performance Scalable: one methodology for all buildings Lower administration costs: standardization and automation reduces time required for both savings analysis and technical review, tools help too! Tool Availability: public domain and embedded in EMIS

Unable to determine savings above code and standard requirements Disadvantages Unable to determine savings above code and standard requirements Intervention required for non-routine loads Added loads Temporary outages Unexpected behavior Unpredictable buildings Prescreening may be required

M&V 2.0 Tools Public Domain EMIS - Proprietary Universal Translator M&V Analysis Module Energy Charting and Metrics Tool Inverse Model Toolkit (RP 1050)

Tool/Model Testing and Validation DOE Building Technologies Office supporting work to accelerate the adoption of analytics tools and interval data for M&V Leverage automation and increasingly available data to reduce time and cost of M&V, while maintaining or improving accuracy Develop transparent statistical test procedures to quantify accuracy of models used in automated tools Apply test procedures to demonstrate accuracy for 10 proprietary and published models w/ data from 500+ buildings Demonstrate automated approaches in partnership with utilities, implementers, tool vendors Tool, Model B Tool, Model A http://eis.lbl.gov/auto-mv.html

Energy Charting and Metrics (ECAM) Excel add-in Free: https://afe.org/certification/ECAMplus

ASHRAE Inverse Model Toolkit UI Versions: E-model, Energy Explorer

Universal Translator M&V Tool Sponsored by California Energy Commission PIER Funds Goals: Enable users to develop accurate baseline models with short-time interval energy data Enable quantification of savings and uncertainty Reduce the overall time to conduct M&V analysis Facilitate project review through transparency and standardization

What is the UT M&V Tool? Analysis Module in PG&E’s Universal Translator version 3 (UT3) Free software for desktop use www.utonline.org UT3 + M&V Module provides: Data preparation functions (merge, time re-sampling, etc.) Advanced regression modeling Model fit and sufficiency checks Savings quantification Uncertainty analysis Users: Service providers Technical reviewers Others

User Interface

Discussion Wide application: University buildings, laboratories, large commercial offices, medical offices, etc. Allows intervention for non-routine loads Added loads Temporary outages Unexpected behavior Can be used as: quality assurance of savings estimates, or the savings settlement methodology Low learning curve, typical time for analysis is hours, not days

M&V Tool Limitations Time and one independent variable Future version to include additional variables Reporting features can be improved Uncertainty Algorithm Currently requires 12 months baseline & 6 months post-installation data Unpredictable buildings Prescreening may be required

Applications Quality Assurance Parallel analysis to traditional deemed or engineering calculations Ca. UC/CSU/CCC MBCx programs Programs where codes and standards do not apply RCx Controls Behavioral Savings settlement method for Comprehensive EE Programs RCx, Retrofit, Behavioral, DR Continuous Improvement Set a baseline and track progress Pay for Performance Pay based on through the meter savings With or without ex-ante savings estimates

Case Study: Pay-for-Performance Seattle City Light Program Participating Building 582,000 ft2, 34 story office bldg, 30% occupied Electric heating and cooling systems M&V Tool used to set baseline & track savings Measures implemented over time Isolation dampers – don’t condition unoccupied zones Replace a 550 ton chiller and convert to VAV CHW loop VFDs on 2 100 hp supply, 60 hp exhaust fans 1st year savings: 16% Uncertainty: 2% @ 68% CI => 16% ± 1% (ASHRAE G14) Compares with M&V tool cross-validation method

Pay-For-Performance 1 2 3

Application Protocols and Guidelines I Bonneville Power Administration Conduit: https://conduitnw.org/ Engineering Calculations with Verification Sampling Reference Guide & Tool Regression Reference Guide Equipment or End-Use Metering Option A or B Energy Modeling (Option B or C) Energy Use Indexing (Option C) Existing Building Commissioning Application Guide End-Use Metering (absent baseline) Application Guide

Application Protocols and Guidelines I Bonneville Power Administration Conduit: https://conduitnw.org/ Engineering Calculations with Verification Sampling Reference Guide & Tool Regression Reference Guide Equipment or End-Use Metering Option A or B Energy Modeling (Option B or C) Energy Use Indexing (Option C) Existing Building Commissioning Application Guide End-Use Metering (absent baseline) Application Guide

Thank You! Questions? David Jump, Ph.D., P.E. Quantum Energy Services & Technologies, Inc. Berkeley, CA djump@quest-world.com