Budget model configuration

Model Configuration trains regression models that power budget predictions in EnerG. In the building view, expand Budget in the left sidebar and open Model Configuration. Link trained models to budgets in Budget planning through the Model field in Basic Setup. For how budget models produce predicted values, see Budgets and capital planning. For portfolio rollups, see Portfolio budget and planning. For variance against an active plan, see Building budget overview.

Models need enough historical usage and weather data in the reference period. Confirm meter completeness on Building meters before you train.

Open Model Configuration

Select a building

From Portfolio Home, open a building in the building view.

Open Model Configuration

In the left sidebar, expand Budget, then click Model Configuration.

Manage configurations

The Model Configuration page lists prediction models for the building. Click + Create Configuration to start the five-step wizard. Click a Name to open the summary drawer, or use Actions to edit or delete a row.

Model Configuration page for One Financial Plaza showing table with Name Test Budget 2026 Budget 2025 Budget 2024 Budget Reference Period and Prediction Period date ranges Meters count 2 and edit delete actions plus Create Configuration button — Model Configuration list with reference and prediction periods

Column	What it shows
Name	Model label. Click to review training results
Reference Period	Historical window used to train the model
Prediction Period	Future window the model targets
Meters	Count of meters included
Actions	Edit or delete the configuration

Review the summary drawer

Click a configuration Name to open Summary without entering the wizard.

Summary drawer showing Reference Period January 2025 through December 2025 Prediction Period January 2026 through December 2026 Variables Weather Normalization tag and District Steam Model and Electric Model Succeeded badges with Close Delete and Edit Configuration buttons — Model Configuration Summary drawer with trained models

Field	What it shows
Reference Period	Training baseline dates
Prediction Period	Target forecast dates
Variables	Independent drivers, such as Weather Normalization
Trained Models	Per-service-type status, such as Succeeded for Electric Model and District Steam Model

Click Edit Configuration to change settings or Delete to remove the model.

Create a model configuration

Click + Create Configuration to open the wizard. Progress appears in the left sidebar across five steps: Basic Setup, Historical Usage, Historical Weather, Variables, and Summary.

Step 1: Basic setup

Define the model name, prediction period, and meters by service type.

Model Configuration wizard step 1 of 5 Basic Setup with Model Name Budget Period Start January 2026 End December 2026 Electric meter MTR-100214-E01 and District Steam meter MTR-100214-S01 selected in tables — Model Configuration wizard step 1 Basic Setup with meter selection

Field	Purpose
Model Name	Label in lists and in Budget planning Model dropdown
Description	Optional notes
Period Start / Period End	Prediction period for the model
Service Types	Select meters per commodity. Tables show Meter, Tariff Name, Deregulated, and Utility Provider Name

Click Next to continue.

Step 2: Historical usage

Choose a reference year and review usage or cost trends that inform the model.

Control	Purpose
Reference Year Info	Historical window for training, such as January 2025 – December 2025
Budget Historical Usage Trends	Line chart by service type across the reference year
Usage / Cost	Toggle the chart and table between consumption and spend

Scroll below the chart for a monthly table.

Historical Usage table with Usage selected showing Month District Steam in MBtu and Electric in kWh for each month of 2025 — Historical Usage monthly table in Usage view

Confirm seasonal patterns before you click Next.

Step 3: Historical weather

Review temperature and degree-day patterns for the reference period.

YOY comparison

YOY Comparison plots monthly temperature for the reference year.

Degree days analysis

Degree Days Analysis shows HDD (heating degree days) and CDD (cooling degree days) by month. Use this view when Weather Normalization is a model variable. See Weather normalization for base-temperature and tolerance settings.

Step 4: Variables

Select independent variables for the linear regression model.

Section	Purpose
Normalization Baseline	Baseline Period and Historical Period for weather-adjusted models
Select Independent Variables	Add drivers such as Weather Normalization, Occupancy Percentage, or Building Square Foot
+ Building Square Foot	Adds floor area from Building information when available

Use the pencil icon to edit a variable or the trash icon to remove one.

Step 5: Summary

Submit the configuration to train models for each service type. EnerG trains one model per service type you selected in Basic Setup.

Training runs in the background. An info banner notes that validation takes time. Refresh the wizard or reopen Summary from the configuration list when training completes.

Model Configuration wizard step 5 Summary showing Trained Models District Steam Model and Electric Model each with Successful badge and Previous Delete Finish buttons — Model Configuration Summary with successful trained models

Section	What it shows
Trained Models	One row per commodity, such as District Steam Model and Electric Model
Successful	Training completed and passed validation for that service type

Click Finish to save the configuration. Use Delete only when you want to discard the draft before finishing. Failed models show an error state instead of Successful; widen the reference period or adjust Variables before you retry.

Do not delete a configuration that an Active budget in Budget planning still references.

Use models in Budget planning

When you create a budget in Budget planning, choose Smart Generation or Reference Year and select the trained Model from the dropdown in Basic Setup. EnerG applies predicted values from the configuration you completed here.

Next steps

Budget planning

Build Draft, Active, or Completed budgets using trained models.

Building budget overview

Compare actual spend to your active budget.

Building information

Confirm occupancy, area, and envelope inputs that affect variables.

Building meters

Verify billing completeness before you set reference periods.

Get Started

Concepts

Portfolio view

Building view

Reference

Open Model Configuration