Caution
This software is experimental and subject to change.
- Visually animate and play through each timestep.
- Dynamically filter both generators and transmission lines.
- Web apis to upload new PCM scenarios as part of your modeling pipeline.
The animation engine loops through rows in the timeseries data and maps them to transmission or generator geometries.
Follow the instructions here for uploading new scenarios to GridSight.
To set up you will need python3 and node installed locally.
Run docker-compose build and docker-compose up
Install the gridsight client into your virtual environment.
pip install . or pip install git+https://www.github.com/NREL/GridSight
To upload the demonstration data run python upload_test_data.py
After uploading data, log in at http://localhost:3000 or http://127.0.0.1:3000
The login credentials are determined by environment variables found in the docker compose file.
User: test
Password: test123
After logging in, select the Demo project and Demo scenario. (Assuming you have uploaded the test data described above)
You can adjust the layer styles to scale up the generation and transmission radius/width.
- Generalization of animated layers to allow any type of geometry+timeseries
- Allow Custom Color maps.
- Multi-Scenario animation and comparison.
- Drilldown capabilities into individual generators/lines and geographic areas (aggregate generation or transmission).
This software was developed as part of the National Transmission Planning study.
NREL software record: SWR-24-16
Geometry data was sourced from the Texas2k Series24 datasets. Timeseries data is completely fictional. https://electricgrids.engr.tamu.edu/activsg2000-dynamics-cases-2024/