Sampling for M&V: Reference Guide
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Note that parameters like efficiency, kW/ton, and R or U value are not directly (or easily)
measurable quantities. Each requires multiple (and sometimes difficult) measurements, adding to
the complexity, cost, and uncertainty of the measurement process. It is better to focus on directly
measurable quantities like power (kW) rather than trying to rigorously quantify equipment
performance.
If the population is reasonably homogeneous, random samples can be selected from the population.
If either the usage or performance characteristics vary widely, the population should be divided
into groups containing items of similar characteristics. However, too many groups with small
numbers in each will be difficult to evaluate as well. The grouping should be a balance between
resolution and number of groups. In general, no more than a dozen groups should be necessary.
Table 3-1: Performance and Usage Characteristics for Typical Technologies and Applications
Technology or Application Performance Characteristics Usage Characteristics
Lighting Fixtures Power (watts) Space type, operating hours
Motors hp, RPM, rated efficiency
Constant speed and load, variable speed
and load, operating hours
Rooftop Units Capacity (tons), EER / SEER Operating hours, local climate
Office Equipment Function, power (Watts) Operating hours, cycles
Power (Watts / kBTUh), gallons Inlet and outlet temperatures, gallons/day
Envelope Improvements R value, U value, SHGC
Indoor temperature, outdoor temperature
(climate), window orientation
Homes Size, type (SF, MF, condo),
number of bedrooms, overall R
and U values
Number of occupants, age of occupants /
hours home, local climate, vintage, type of
heating equipment
Small Commercial Buildings Size, function, internal
equipment
Schedule, number of occupants, local
climate
If the population has been divided into groups, consider whether to use simple random sampling
for each group or stratified sampling. Simple random sampling is easy to implement and the results
from one group have no influence on another group. Stratified random sampling allocates
resources more effectively, providing lower overall measurement costs. However, the calculation
process is more complex and results from one group may affect the overall uncertainty of the entire
process.
The acceptable level of confidence and precision needs to be established before the research has
begun. BPA recommends measured sampling with 10% precision at 90% confidence level but
allows some flexibility in the target precision in certain cases. Where individual measurements are
expensive, or the populations have large variances (high CV), reducing the acceptable precision
results in smaller sample sizes. (The evaluator should avoid revising downward the anticipated CV
to reduce the required sample size.) Consider the savings expected from the project or program,
the cost of each measurement, and the overall evaluation budget. Choosing an acceptable precision
level may be an iterative process as the estimated measurement and evaluation cost is compared
to the available budget or project/program savings. Absent a defined budget, initial M&V costs
should be no more than 10% of the project budget; and annual M&V costs should be no more than