Calendarization overview

Calendarization more accurately allocates utility bill use and cost to the appropriate calendar month by prorating the cost and use by day (dividing the data into day-size chunks and allocating to the appropriate month). Calendarization is required because most utility bills start and end dates don't correspond to the exact calendar month or may vary in length.

Using billing period data may not accurately reflect consumption and cost in the correct calendar month.

The weather regression calculations used by calendarization and normalization do not exclude statistical outliers. Cost Avoidance DOES exclude statistical outliers.

Why calendarize data?

  • More helpful to Energy Managers to see use and cost in the month it occurred.
  • Provides better month-to-month and year-to-year comparisons.
  • More representative of actual monthly energy use when used in fiscal reporting, budgeting, accruals, and energy performance evaluation.

Calendarization is a better way to report data unless you need to:

  • Discuss actual bills with the vendor.
  • Reconcile actual bills with accounting functions.
  • Use actual bills to charge tenants or departments for their portion of the utility bill.

User-defined calendarization

You can configure user-defined calendarization periods in the Accounts module menu.

calendarization diagram

How does calendarization happen?

  • Not weather-sensitive meter, the data is prorated.
  • Weather-sensitive meter incorporates degree day data to allocate use and cost.

Option 1 Simple average daily use and cost allocation

When a meter is not weather sensitive, the bill is simply prorated into each month based on the number of billing period days. A bill from 9/12 to 10/14  has 32 days (the first day counts, the last day doesn't because the next bill begins on 10/14). 19 days are in September, so 19/32 of the use and cost are allocated to September and 13/32 to October.

Option 2 Weather (degree day) allocation

When a meter is weather sensitive, a more sophisticated method is used to prorate the weather-sensitive portion of the energy bill based on the number of degree days in the appropriate billing period in each month, and to prorate the remaining, not weather-sensitive portion based on the number of days. See Use vs Weather for more details.

Calendarization does not appreciably affect annual totals because the process merely moves use and cost data to the most appropriate calendar month for reporting and analysis purposes. The annual use and cost totals should be almost identical to the billing period data.

Use vs Weather

screenshot
Use vs Weather summarizes the weather sensitivity of the meter for each season and year. Expand each row to see more details.

Determining weather sensitivity for calendarization is a similar but a separate process from determining the baseline (weather sensitivity) in Cost Avoidance.

Cost Avoidance excludes statistical outliers.

Calendarization settings are global; weather sensitivity is configured on each meter with the Cost Avoidance module.

Calendarization

  • Uses the weather assigned to the building.
  • The weather regression relies on the previous year's weather data.
  • Average use per day is based on the balance point temperature from the normalization year.
example of setting balance point temperature

Defining statistical outliers

Statistical outliers are handled differently in the calendarization and normalization process than they are in Cost Avoidance.

In Cost Avoidance statistical outliers (those periodic use data points which fall more than two standard deviations away from the regression line defining a use/weather correlation for a meter) are handled as exceptions and are excluded from the weather adjustment process. This produces a better use vs. weather correlation using the remaining (non-excluded) bills.

In calendarization and normalization, the outliers are handled differently. These processes are less sophisticated and less calculation-intensive than Cost Avoidance. Outliers are included. If an outlier causes the regression to fail, it invalidates weather adjustments for that meter, that season, that year. If an outlier exists and the regression remains valid, the weather factors are applied to outlier bills and non-outlier bills.