BENCHMARKING DATA ANALYSIS: FACT SHEET
Benchmarking Analysis Process FLOW CHART FOR PARSING AND ANALYSIS OF BENCHMARKING DATA: For benchmarking programs using Energy Star Portfolio Manager as the energy benchmarking tool, the two most important energy efficiency metrics to be evaluated are a property’s Energy Use Intensity (EUI) and Energy Star score. In general, the EUI is an indicator of the absolute amount of energy a property consumes, while the Energy Star score is a measure of how efficiently the energy was consumed relative to a theoretical peer group. Having both of these metrics defined for a property offers one of the best ways to understanding how the property, overall, uses energy. Unfortunately, Energy Star Portfolio Manager will generate Energy Star scores for only 21property types out of a total of about 84 different types. This means that for many benchmarking programs, much of the collected benchmarking data will come from properties ineligible to receive an Energy Star score and will have an EUI but no score. The figure below shows a flow chart of the various data parsing steps and associated levels of benchmarking analysis that can be applied to benchmarking datasets. One important outcome from following the flow chart will be a subset of properties having the most reliable
EUIs and Energy Star scores. Step 1: After generating a “raw” benchmarking dataset using Energy Star Portfolio Manager, data should be cleansed of suspect and erroneous data. Flagged data should be removed from the dataset and used to provide feedback to building owners/ operators who have supplied suspect or missing data. Step 2: Identify and parse properties eligible and ineligible to receive an Energy Star Portfolio Manager score. All properties at this point should have, at a minimum, an Energy Use Intensity (EUI) metric. Step 3: Parse properties eligible to receive an Energy Star score into properties that actually received a score and those that didn’t. At this point, data quality analyses should be performed on the subset of eligible properties that didn’t receive a score. The information developed from these analyses can be used to provide feedback to the building owners/ operators who supplied suspect or missing data. The subset of eligible properties that didn’t receive an Energy Star score can be combined with the parsed set of properties ineligible properties (see Step 2) for further benchmarking analysis. Step 4: Parse properties that received an Energy Star score into properties that used default data and those that didn’t. Although all properties at this point will have both an EUI and Energy Star score, the subset of properties that didn’t use default data will have the most reliable information about the energy efficiency of level of the property. Step 5: Perform analyses on all properties, parsed by specific property type, that have both an EUI and Energy Star score to understand basic energy performance metrics and associated energy costs.
Figure: Flow Chart for Parsing and Analyzing Benchmarking Data