Calibrating the csv-file

After extracting the GIS-data to a csv-file, it is time to calibrate the CSV-file. This has two main purposes:

  1. To ensure the population in the settlements match the official statistics

  2. To identify which settlements are likely electrified already.

The calibration is done using a Jupyter Notebook found among the main OnSSET codes

To launch the Jupyter Notebook, open Anaconda Prompt and run:

cd PATH
conda activate onsset_env
jupyter notebook

Replace PATH with the location where you downloaded and extracted the main OnSSET code.

First, open the 1. OnSSET_Calibration notebook:

_images/open_calibration_notebook.png

This notebook calibrates the CSV file created in the previous exercise.

Run all cells from top to bottom.

Step 1 – GIS Data Selection

Select the file created in the previous exercise:

_images/calibration_gis_data_collection.png

Step 2 – Start Year

Enter the start year of your analysis. This is typically the latest year that you have data from, e.g. 2025.

Step 3 – Enter Baseline Country Data

Update the demographic and electrification parameters for your country or region of interest:

_images/demographic_parameters.png

Step 4 – Calibration of Start-Year Values

Run the first cell in Step 4.

This step:

  • Calibrates the population

  • Generates additional information based on the GIS data

If successful, a preview table of the GIS data will appear.

_images/csv_imported.png

Electrification Identification

Based on the input data in the previous steps, in the next cell the code now creates some additional layers that are useful for the electrification analysis. This can be an iterative process which requires calibration from the user. One of the most important steps in the electrification analysis is the identification of the currently electrified settlements. Based on their location, the model then decides how easy it is to extend the grid to neighboring cells, or rather choose an off-grid technology. The model calibrates which settlements are likely to be electrified in the start year, to match the national statistical values defined above. A settlement is considered to be electrified if it meets all of the following conditions:

  • Has more night-time lights than the defined threshold (this is set to 0 by default).

  • Is closer to the existing grid network than the distance limit.

  • Has more population than the threshold.

In the next cells, adjust the input thresholds and run all the cells to calibrate the population to match the official statistics and identify which settlements are likely electrified already. You should see a map of electrified settlements in blue at the end of this section.

_images/electrified_settlements_map.png

Example output showing electrified settlements.

Note

In case you get an error at any point, commonly this is because you have not clicked Run on all cells after updating the input values, or the input values are not in the correct format (e.g. using a comma instead of a dot for decimals)

Step 5 – Exporting the Calibrated File

In the final cell, a pop-up window will ask where to save the calibrated file.

After saving the file, you are ready to run a scenario.