Getting started

This page is a quick guide to get you started with the Energibruksmodell (EBM) model. The model is designed to calculate energy use in the norwegian building stock. The model is developed by the Norwegian Water Resources and Energy Directorate (NVE).

Both the model and the datasets used by EBM can be downloaded from GitHub.

Requirements

EBM requires Python 3.11 or newer. Python is available from python.org.

Additional requirements like pandas, pandera and openpyxl will be installed along side EBM

Quick Start Guide

Please, open your preferred terminal application and follow the instructions below.

Installation

Install ebm using pip

python -m pip install ebm

What version of ebm are we running?

Once installed, you need to setup input files with all the parameters required to run EBM. But before we do that, let’s check if ebm is working properly. Open a terminal (powershell) and type:

ebm --version

The output should look something like this:

expected output

PS C:\Users\user> ebm --version
ebm 0.99.2
PS C:\Users\user>

The output shows what version of ebm you are running. Don’t worry if the version number you get is a bit off from the one in the example.

Note

These instructions are made for 1.1.0, but should work for later versions as well.

List available datasets

The following command lists all available input datasets:

ebm list-input

expected output

PS C:\Users\user\Documents> ebm list-input
Available datasets:
- <dataset name 1>: <description of dataset 1>

The output shows the names of the available datasets. If a dataset contains a README.md file with a Description section, the description will also be shown in the output.

Create an input directory

Before running the model you need to create a directory with the necessary input files. The recommended way of creating an input directory is to use create-input command.

create-input is a command at the same level as list-input:

ebm list-input
ebm create-input

The command can be used with or without arguments.

Create input from the default dataset

ebm create-input

This creates an input directory basesd on the default dataset.

Create input from a specific dataset

ebm create-input short_analysis_2025

This creates an input directory based on the short_analysis_2025 dataset.

Create input from a specific dataset with a custom directory name

ebm create-input short_analysis_2025 my-short_analysis_2025

This creates an input directory named my-short_analysis_2025 based on the short_analysis_2025 dataset.

expected output

PS C:\Users\user\Documents> ebm create-input short_analysis_2025 my-short_analysis_2025

0:00:00.55 - Using data from "input"
0:00:00.55- Copy input from C:\Users\user\pyc\Energibruksmodell\ebm\data\short_analysis_2025
0:00:00.55 - Creating directory my-short_analysis_2025
0:00:00.55 - Creating missing file  my-short_analysis_2025\building_code_parameters.csv
0:00:00.55 - Creating missing file  my-short_analysis_2025\s_curve.csv
0:00:00.55 - Creating missing file  my-short_analysis_2025\population_forecast.csv
0:00:00.56- Creating missing file  my-short_analysis_2025\new_buildings_residential.csv
0:00:00.56 - Creating missing file  my-short_analysis_2025\area_new_residential_buildings.csv
0:00:00.57 - Creating missing file  my-short_analysis_2025\area.csv
0:00:00.57 - Creating missing file  my-short_analysis_2025\energy_need_behaviour_factor.csv
0:00:00.57 - Creating missing file  my-short_analysis_2025\energy_need_original_condition.csv
0:00:00.57 - Creating missing file  my-short_analysis_2025\improvement_building_upgrade.csv
0:00:00.57 - Creating missing file  my-short_analysis_2025\energy_need_improvements.csv
0:00:00.57 - Creating missing file  my-short_analysis_2025\holiday_home_energy_consumption.csv
0:00:00.58 - Creating missing file  my-short_analysis_2025\holiday_home_stock.csv
0:00:00.58 - Creating missing file  my-short_analysis_2025\area_per_person.csv
0:00:00.58 - Creating missing file  my-short_analysis_2025\heating_system_initial_shares.csv
0:00:00.58 - Creating missing file  my-short_analysis_2025\heating_system_efficiencies.csv
0:00:00.58 - Creating missing file  my-short_analysis_2025\heating_system_forecast.csv
0:00:00.59 - Creating missing file  my-short_analysis_2025\README.md
0:00:00.60 - Finished creating input files in my-short_analysis_2025

The command creates a new directory named input, containing copies of all input files. By default, this directory is created in the current working directory. To specify a different location, use the --input=<directory name> option.

If the directory already exists, only missing files will be copied. Existing files will not be overwritten.

If the dataset contains a README.md file, it is copied to the created input directory. This ensures that information about the dataset is included together with the generated input files.

README.md descriptions

Dataset descriptions shown by the ebm list-input are read from the dataset’s README.md file.

The description should be placed under a description heading in the README.md file, for example:

# Beskrivelse
Short description of the dataset.

The text under this heading is read until the next heading and shown together with the dataset in ebm list-input.

List files in the input directory

You can use ls to get a list of all the files in the input directory:

ls input

expected output

PS C:\Users\user\Documents> ls my-short_analysis_2025

     Directory: C:\Users\user\Documents\my-short_analysis_2025

Mode                 LastWriteTime         Length Name
----                 -------------         ------ ----
-a----        30.09.2025     12:10           2475 area.csv
-a----        30.09.2025     12:10            114 area_new_residential_buildings.csv
-a----        30.09.2025     12:10            192 area_per_person.csv
-a----        30.09.2025     12:10            238 building_code_parameters.csv
-a----        30.09.2025     12:10            305 energy_need_behaviour_factor.csv
-a----        30.09.2025     12:10            462 energy_need_improvements.csv
-a----        30.09.2025     12:10          23191 energy_need_original_condition.csv
-a----        30.09.2025     12:10           1340 heating_system_efficiencies.csv
-a----        30.09.2025     12:10           1847 heating_system_forecast.csv
-a----        30.09.2025     12:10          67093 heating_system_initial_shares.csv
-a----        30.09.2025     12:10            446 holiday_home_energy_consumption.csv
-a----        30.09.2025     12:10            652 holiday_home_stock.csv
-a----        30.09.2025     12:10            475 improvement_building_upgrade.csv
-a----        30.09.2025     12:10           1807 new_buildings_residential.csv
-a----        30.09.2025     12:10            959 population_forecast.csv
-a----        30.09.2025     12:10           1854 s_curve.csv

If your shell does not have the ls command, you might have better luck with dir.

Run the model

You are now ready to run the model. Use the bare command EBM with no options:

ebm

expected output

PS C:\Users\user\Documents> python -m ebm
0:00:01.44 - Using data from "input"
0:00:04.58 - Wrote output\area.xlsx
0:00:04.97 - Wrote output\heating_system_share.xlsx
0:00:05.34 - Wrote output\heat_prod_hp.xlsx
0:00:09.32 - Wrote output\energy_use.xlsx
0:00:17.10 - Wrote output\energy_purpose.xlsx
0:00:18.39 - Wrote output\demolition_construction.xlsx

By default the scenario is read from input, and the results are written to the subdirectory output in the current working directory.

You can get a directory listing that shows all the result files created by issuing the command:

ls output

The resulting output should look something like:

expected output

    Directory: C:\Users\user\Documents\output


Mode                 LastWriteTime         Length Name
----                 -------------         ------ ----
-a----        18.09.2025     12:27          98844 area.xlsx
-a----        18.09.2025     12:27         119998 demolition_construction.xlsx
-a----        18.09.2025     12:27         647028 energy_purpose.xlsx
-a----        18.09.2025     12:27         526083 energy_use.xlsx
-a----        18.09.2025     12:27          32244 heating_system_share.xlsx
-a----        18.09.2025     12:27           7349 heat_prod_hp.xlsx
-a----        13.02.2025     11:18             50 README.md

The files can be opened using your favourite spreadsheet application. I.E. Microsoft Excel or LibreOffice Calc.

Tip

If you want to open the results automatically as they become available, you can use the --open option.

ebm --open

See also

Result files

An overview of the contents of all the output files.

Additional arguments

Shows all the commands available for EBM.

User case

gives a run-down on how you can change the input files to better suit your needs.

Last Updated on 2026-06-29.

Version: 1.1.0.