Residential M&V Panel: Real Time M&V Where are we, where could we go, what would it take?

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Residential M&V Panel: Real Time M&V Where are we, where could we go, what would it take? Miriam L Goldberg & Michelle Marean ACEEE Intelligent Efficiency Conference Boston Dec 8, 2015 1 SAFER, SMARTER, GREENER

Background Changing EM&V Paradigm - Landscape of New Tools & Data Analytics, A Review of Key Trends and New Industry Developments, and Their Implications on Current and Future EM&V Practices, prepared by DNV GL DRAFT REPORT FOR STAKEHOLDER REVIEW 11-10-15 Purpose: Help stakeholders understand emerging trends, technologies, and techniques that can be leveraged to enhance EM&V Thanks to: Julie Michals, NEEP Outside reviewers 2

What s New? Advanced Data Analytics Improved Data Collection Tools & Increases in Data Availability Software: Cloud-based Platforms & programs for rapid high-volume processing Potential to analyze higher volume & higher frequency data collection Hardware: Smart meters, smart T-Stats, NILM New ways to collect data Potential to increase amount and types of data collected 3

Advanced Data Collection and Analysis Tools New Tool/Method Advanced Data Analytics Auto M&V Software Auto M&V Software as a Service (SaaS) AMI Smart Devices Home Energy Management System Key New Features Predictive Analytics Machine learning Machine learning Cloud platform High volume auto processing Service delivery via Auto M&V Large scale high-volume interval data 2-way communication 2-way communication Monitoring, feedback, & controls, 2-way communication End-Use Metering Non-Intrusive Load Monitoring 4

Key EE Delivery Applications of Advanced Data Collection and Analytic Tools Energy Audits Customer Engagement Tracking and Benchmarking Virtual Energy Assessments Measurement and Verification Customer Segmentation and Targeting Program Planning and Optimization 5

What Are E M and V? Evaluation, Measurement, and Verification Assessment of the effects of a program and the effectiveness of program processes Measurement and Verification Verification Determination of energy savings from particular sites or measures, based on a combination of measured parameters and calculations Confirmation that an EE measure has been installed 6

Evaluation Approaches (SEE Action, CPP EM&V Guidance) Evaluation, Measurement, and Verification Measurement and Verification Deemed Savings Large-Scale Consumption Data Analysis Verificatio n 7

Where Do New Tools Fit into Evaluation? Evaluation, Measurement, and Verification Measurement and Verification End-Use Metering AMI Data Deemed Savings Large-Scale Consumption Data Analysis Verificatio n High Volume Whole-Facility Consumption Data Analysis 8

Consumption Data Analysis 9

Find the Baseline Consumption Data Analysis Consumption Pre-Program Actual Pre-program at post-program operating condition Post-Program if Standard Efficiency Without Program Post-Program Actual Installation Time 10

Find the Baseline Consumption Data Analysis Consumption Pre-Program Actual Pre-program at post-program operating condition Post-Program if Standard Efficiency Post-Program Actual Installation Without Program Natural Replacement Time Time Pre-Installation, even weather-adjusted, is the right baseline for evaluation only in limited circumstances Have to consider other changes, natural replacement, program influence, (new construction) Comparison group can sometimes work for large, homogeneous population 11

How Can New Tools Shorten the Evaluation Timeline? What Would Be Gained and Lost? Planning & Scoping Stakeholder engagement Data cleaning & Sampling Data Analysis Site data analysis Site reporting 2-3 months 4-9 months 2-4 months 1-2 months 9 18 months overall Recruiting & Data Collection 3-6 months of metering Recruitment, installation & retrieval Reporting Stakeholder engagement Reporting & review of results 12

Streamlining the Process Planning Period Establish methods, instruments, protocols Eliminate most of planning period by pre-specifying Review 1 & mo confirm Program Period Recruitment and Data Collection Sampling and Recruitment Data Collection Analysis & Reporting Analysis Reporting Begin data collection & analysis immediately with pre-agreed protocols Begin reporting immediately Final report a couple months after program close 13

Streamlining the Process What Would We Lose? Planning Period Establish methods, instruments, protocols Eliminate most of planning period by pre-specifying Ability to tailor to particular evolving program & learn from recent evaluation experience Review 1 & mo confirm Ability to conduct custom analysis where needed, explore anomalies Program Period Recruitment and Data Collection Sampling and Recruitment Data Collection Analysis & Reporting Analysis Reporting Post-install year, final P Begin data collection & analysis immediately with pre-agreed protocols Begin reporting immediately Final report a couple months after program close Solid consumption analysis takes 12 mos post 14

Potential Uses of Advanced Data Collection and Automated Analytics for Evaluation Early, ongoing feedback is valuable even if it s not the final evaluation word Where programs are already gathering and analyzing data via new tools, evaluation ideally will take advantage of those data and analyses Extends long-standing evaluation practice Requires understanding program data handling & analysis, potential biases Requires tool performance assessment Still need evaluation review and potentially adjustment eg for data attrition bias Accuracy of baseline estimation tools can be tested empirically, up to a point Often no observable no-program or without the measure condition Transparency of nonroutine adjustments is a challenge Pre-agreed standard protocols can streamline evaluation Automated ongoing data analysis is one example Limits depth of exploration and customization possible Establishing meaningful baselines for gross and net savings is not easily automated for many situations 15

Where Do New Tools Fit into Evaluation? Evaluation, Measurement, and Verification Measurement and Verification Deemed Savings Large-Scale Consumption Data Analysis Verificatio n? Automated Consumption Data Analysis with prespecified data screening & adjustment protocols 16