Utility weather data normalization

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In the Utility Bill Analytics module, you can perform regression analysis on utility consumption to normalize the data for different weather conditions. You can then view and compare an account's actual consumption with its expected normalized profile to identify potential operational inefficiencies and cost saving opportunities. Accounts can be ranked by actual against expected, weather normalized consumption variance to obtain a holistic view of the best and worst performers.

Regression analysis dashboard

Access the regression analysis dashboard from an account's Analyze menu. Use the regression analysis tool to perform baseline regression analysis of consumption against heating and cooling loads or against other performance metrics that are predictive of consumption. The regression analysis tool helps you to identify the correlation between consumption and the predictive variables that can be used to predict consumption.

To use the dashboard, at least 12 months of historical data must be available, and the location must be linked to an appropriate weather station for Heating Degree Days (HDD) and Cooling Degree Days (CDD) values to be calculated.

For more information about the regression analysis tool, prerequisites, and creating a regression model, see the related link.

Bulk regression analysis

The Bulk Regression Modeler - Accounts report enables you to perform bulk regression analysis on weather metrics for a selected range of accounts, based on a few predefined parameters. The regression analysis in the report works the same way as the account regression analysis dashboard, with the advantage of running the analysis in bulk.

Ranking actual against normalized Excel reporting template

The Ranking Actual vs Normalized Excel reporting template (ERT) provides a comprehensive view of actual consumption and its normalized profile values. Accounts and meters are ranked based on their variances to normalized values. Site-level comparison is also available, by examining the aggregated values of all accounts and meters within the site and comparing them with other sites.

Prerequisite: To use the ERT, you must perform regression analysis on applicable accounts or meters, either through the regression analysis tool, or by modelling externally. In either case, the derived regression coefficients must be saved into IBM® ESG Suite as account attributes:
  • Slope for HDD
  • Slope for CDD
  • Base load for working day
  • Base load for holiday

To access the Ranking Actual vs Normalized ERT, click Verify > Ranking Actual vs Normalized.

Complete the fields in the Run report form and submit. The generated report contains three tabs:
  • Ranking by accounts and meters
  • Monthly break down, which also includes HDD, CDD and slope coefficients, and so on, that are used in generating the normalized values
  • Ranking by sites
Note the following key report features:
  • By default the ranking is based on the variance percentage.
  • The DataSheet tab contains the raw data extract that breaks down into monthly blocks for each account.
  • If the account does not have any normalization coefficients that are saved in the system, then the normalized values are displayed with value 0 in the report.
You can also access the Ranking Actual vs Normalized ERT at the group and location levels:
  • At the group level, click Consumption > Ranking Actual vs Normalized
  • At the location level, click Analyze > Ranking Actual vs Normalized

Actual against normalized dashboard

Use the Actual vs Normalized dashboard to compare actual and normalized values visually in dashboard charts. The dashboard also calculates savings and waste in relation to the normalized values to enable you to determine the account's energy performance in the selected period.

Prerequisite: Similar to the Ranking Actual vs Normalized ERT, you must perform regression analysis on applicable accounts or meters, either through the regression analysis tool, or by modelling externally. In either case, the derived regression coefficients must be saved into Envizi ESG Suite as account attributes.

The net accumulated saving and net accumulated waste bars in the chart show an overall performance of the account or meter over the selected period.