Explore the weather-normalized changes in energy use, driven by factors that you do and do not totally control, and run accurate measurement and verification reports.
Measurement and Verification reports, drift charts, variance by source tables, and long-term trend graphs are available for Meter data. Buildings and Groups can see streamlined variance analysis tables comparing the most recently available period to the same period one year prior.
What is weather-normalized change in energy use?
Weather normalization isolates the changes in a building’s energy use that can be attributed to changes in the weather from the changes in energy use attributed to other causes.
In most buildings, weather has an impact on how much energy is used. Imagine if September 2016 had above average temperature while September 2017 was below average. It would seem these two months are each an apple and an orange. But by filtering out weather effects–by correcting for observed differences in the temperature–you can isolate the other changes and focus on what’s actually happening inside the building.
Customizable drift charts
Comparing the change in energy use from one month to another is as simple as selecting one Analysis Period and one Baseline Period. Of course, the Baseline Period must come before the Analysis Period on the calendar.
The resulting drift chart automatically updates to the date ranges selected. Move your cursor anywhere inside the chart area to see each interval reading’s Analysis Period demand and corresponding Baseline Period demand.
- Day of the week: Across the four weeks of the month, Snapmeter averages together all Monday load curves, all of the Tuesday load curves, and so on. This allows the drift chart to be summarized within one calendar week.
- Analysis period demand: This line is an average load curve for each day of the week during the four calendar weeks of the Analysis Period month.
- Decrease from baseline: This light blue shaded area shows when the Analysis Period demand is lower than the Baseline Period demand. Nice work!
- Increase from baseline: This light yellow shaded area shows when the Analysis Period demand is higher than the Baseline Period demand.
Variance by source table for details
The foundation of a Measurement and Verification report is the Variance by source table. This is where you can see the results of Snapmeter’s calculations isolating out the causes of changes in how your meter uses energy:
–Baseload use: Snapmeter looks carefully at all of your meter’s data to split up the load curve into its component parts, including baseload use (and it automatically updates as new data becomes available). This is the portion of the meter’s energy use that occurs during those times when the meter is not considered to be fully operating. The % change is relative to the Baseline Period’s baseload use, not the total change.
–Temperature response: This calculation relies on the combination of two quantifiable facts: weather conditions and your building’s response to changes in the weather. This is the estimate of the net effect of weather conditions on the meter’s energy use. The % change is relative to the Baseline Period’s weather-driven use, not the total change.
–Operational use: The variance between the Analysis Period and the Baseline Period is composed of three things; baseload, weather, and operations factors. Borrowing a page from Einstein’s cosmological constant–since we can calculate the first two components, we can estimate the remaining portion of the variance to be driven by operations! The % change is relative to the Baseline Period’s operational use, not the total change.
–Total: Keep in mind, the total change reported here is for the calendar period selected, and therefore unlikely to tie exactly to a specific utility billing period. While the kWh / 4 weeks figures for baseload, weather-driven, and operational use do add up on this line, the % change is relative to the Baseline Period’s total change amount.
Isolate drivers in the long-term trend graph
While a Measurement and Verification report isolates the change between two selected months, the long-term trend graph lets you explore your meter’s entire interval data history, with each interval reading split into its component parts of baseload, weather-driven, and operational use.
Click on or off each of the variance components in the chart’s legend to isolate one or more lines on the graph. Changes in baseload use are particularly easy to spot when it is clicked on by itself.
Total kW may equal zero when there are power outages or gaps in the meter’s underlying interval data. Weather-driven use is a measure of the incremental, additional energy used by the meter that can be attributed to changes in temperature–it is, therefore, a non-negative number. Since operational use is the remaining value–after baseload and weather-driven use is already calculated–it can, from time to time, show a negative kW reading.