v0.4.3 ✨

GLIMPSE is a graph-based desktop application to visualize and update GridLAB-D power grid models. The tool can be used to search and highlight power grid model objects. Additionally, it also update the model attributes and export the modified model future simulations. The application is developed using React.js, Electron.js, Node.js, and Python.

Build Instructions

Download Node and Nim

• Node.js
• Nim (Only if planning to export glm files updated with GLIMPSE tool)

In a directory of your choice clone the repository :

git clone http://github.com/pnnl/GLIMPSE

Then in GLIMPSE/glimpse:

npm install

After all node modules are installed run the following command to bundle the source code using webpack:

npm run webpack

After that in GLIMPSE/glimpse/local-server create a python environment:

python -m venv glimpse-server

Once the environment is created activate it using one of the following command for your system in the table below:

Platform	Shell	Command to activate virtual environment
POSIX	bash/zsh	$ source glimpse-server/bin/activate
-	fish	$ source glimpse-server/bin/activate.fish
-	csh/tcsh	$ source glimpse-server/bin/activate.csh
-	PowerShell	$ glimpse-server/bin/Activate.ps1
Windows	cmd.exe	C:\> glimpse-server\Scripts\activate.bat
-	PowerShell	PS C:\> glimpse-server\Scripts\Activate.ps1

You will know if the environment activation worked if there is a (glimpse-server) indicator at the start of your command line.

Next install the server's requirements:

pip install -r requirements.txt

Additional Instructions for MacOS with Apple Silicon

In glimpse/local-server/ clone the glm parser repository.

git clone https://github.com/NREL/glm.git

Then in glm/ you will then build the glm parser. For this you need to make sure that nim is installed and added to your computers PATH.

nim c -d:release --opt:size --cpu:arm64 --passC:"-flto -target arm64-apple-macos11" --passL:"-flto -target arm64-apple-macos11" --app:lib --out:lib/_glm.so src/glm.nim

Next run the following command to create the glm python library wheel

python setup.py bdist_wheel --plat-name=macosx_11_0_arm64

Once that is done, in glm/dist/ there is a .whl archive that you are able to install using pip to the local glimpse-server python environment

python -m pip install ./dist/glm-0.4.4-py2.py3-none-macosx_11_0_arm64.whl

Start GLIMPSE

In GLIMPSE/glimpse/ start the application with the following command:

npm run start

Supported Files

JSON

GLIMPSE supports two different JSON file structures:

1. GLIMPSE's data structure which is based on the glm2json parser used by GLIMPSE. Examples:
   • example 1
   • example 2
   • example 3
   • example 4
2. Networkx's node_link_data JSON dump function Example:
   • fishing example

GLM (GridLAB-D Model)

Examples:

We provide few examples of exploring standard IEEE bus models using GLIMPSE. From the home page, upload all the .glm files from GLIMPSE/glimpse/data/123-bus-model.

To re-upload files after visualization, click on the HOME button

Cite as

@inproceedings{sanchez2024glimpse,
  title={GLIMPSE of Future Power Grid Models},
  author={Sanchez, Armando Mendoza and Purohit, Sumit},
  booktitle={2024 IEEE 18th International Conference on Semantic Computing (ICSC)},
  pages={224--225},
  year={2024},
  organization={IEEE}
}