Cleantech Market Intelligence
AMI Data Brings New Possibilities for Energy Efficiency Measurement and Verification: Part 2
Coauthored by Emily Cross and Peter Steele-Mosey
Part 1 of this blog series covered operational improvements and provided background on the role of advanced metering infrastructure (AMI) data in energy efficiency program evaluation, measurement, and verification (EM&V). This blog continues the discussion with a focus on program impact evaluation. Navigant Research examines these topics in detail in its report, Utility Strategies for Smart Meter Innovation: Energy Efficiency Measurement and Verification.
Program Impact Evaluation
The use of AMI data for program evaluation has the potential to substantially reduce evaluation costs. A major cost associated with the evaluation of large customer (commercial and industrial) energy efficiency program evaluation is onsite verification and metering. For some programs, it is possible to reduce the number of site visits required or reduce the frequency of site visits. Another opportunity for faster program evaluation using AMI data is large-scale validation of coincident demand savings for energy efficiency programs. With AMI data, it is a straightforward matter to isolate demand impacts occurring during utility system peak performance hours.
Programs operating in utility services areas with full penetration of smart meters, deploying energy efficiency measures with consistent load reduction patterns, are excellent candidates for evaluation using hourly or subhourly AMI data. Energy efficiency impact analysis using utility data assumes enough of the program participant savings are above a minimum measurable threshold. That is, the signal-to-noise, savings-to-baseline ratio must be high enough to see the savings in the meter data for a substantial number of participants in the program. Otherwise, program savings estimates may be statistically non‑significant even if savings are being achieved.
A hybrid EM&V approach, using a combination of advanced, automated AMI data analytics and targeted in‑depth evaluation, provides the most value to utility clients and regulators. Automated impact analysis using AMI data (M&V 2.0) can serve as an initial screening of participants. It can quantify realized savings measured at each participant meter using high accuracy pre-post time-of-week/time-of-year and temperature normalized savings models. Participant projects screened out of the automated analysis can be identified and sampled for deeper analysis, providing targeted insights to utility clients and regulators for more complex projects.
Where automated screening methods provide sufficient program feedback without further investigation into the reasons for measured savings, evaluation costs could be reduced relative to traditional methods. Automated M&V2.0 screening provides a high level, statistically significant measure of program performance without the need for follow-up evaluation for programs with established performance. The evaluator using such methods must demonstrate there is no bias introduced by using only projects with measurable savings to characterize program performance.
For mass-market (residential and small commercial) programs, traditional evaluation often involves the application of survey findings to validate and update deemed savings values. In many cases, an empirical econometric approach can deliver an answer with just customer AMI data and program tracking data if the key question to be answered is simply: how many kilowatt-hours (kWh) and kilowatts (kW) is this program giving me? Such empirically-based savings could reduce program implementation and evaluation costs by streamlining or eliminating the ex ante customer application process, provided savings are measurable at the meter.