Julia interface for ANDES, a power system tool for symbolic modeling and numerical simulation
Author cuihantao
7 Stars
Updated Last
1 Year Ago
Started In
April 2020


The Julia API for ANDES.

Build Status


Andes.jl is the Julia API for ANDES, a power system simulation tool for symbolic modeling and numerical simulation.

Andes.jl provides APIs through PyCall and Conda for calling ANDES from Julia.


Install Andes.jl with

using Pkg

Customize Python Environment

If you have installed andes in an existing Python environment and do not want to reinstall it from conda, you can configure it in Pycall.

You can manually set the Python path with the following commands in Julia:

ENV["PYTHON"] = "... path of the python executable ..."
# ENV["PYTHON"] = "C:\\Python37-x64\\python.exe"        # example for Windows
# ENV["PYTHON"] = "/usr/bin/python3.7"                  # example for *nix
# ENV["PYTHON"] = "/home/name/miniconda3/envs/andes"    # example for conda"PyCall")

Check out the documentation of PyCall.jl for more details.


Andes.jl exposes all Python APIs under Use the package with

using Andes
[ Info: Precompiling andes [93a26e3f-343a-4ab9-b467-a68c67574964]

All subsequent usages can be made to in the same way as in Python.

For example, to run power flow for kundur_full.xlsx (assume exists in the current directory), run

julia> system ="kundur_full.xlsx")
Parsing input file <kundur_full.xlsx>
Input file kundur_full.xlsx parsed in 0.0768 second.
-> Power flow calculation with Newton Raphson method:
Power flow initialized.
0: |F(x)| = 14.9283
1: |F(x)| = 3.60859
2: |F(x)| = 0.170093
3: |F(x)| = 0.00203827
4: |F(x)| = 3.76414e-07
Converged in 5 iterations in 0.0063 second.
Report saved to <kundur_full_out.txt> in 0.0007 second.
-> Single process finished in 0.1666 second.
PyObject <andes.system.System object at 0x1522910b8>

Visit ANDES Documentation for tutorial and API details


Contributions to Andes.jl are welcome. Please see for code contribution guidelines.


Andes.jl (the ANDES Julia interface only) is released under MIT license.

Andes.jl has been developed as part of the Large Scale Testbed (LTB) project at the Center for Ultra-Wide-Area Resilient Electric Energy Transmission Networks (CURENT), a National Science Foundation Engineering Research Center that is jointly supported by NSF (National Science Foundation) and the DoE (Department of Energy) of the United States.

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