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Hantao Cui edited this page Feb 23, 2020 · 1 revision

ANDES can be installed in Python 3.7+.

Environment

Setting Up Miniconda

We recommend the Miniconda distribution that includes the conda package manager and Python. Downloaded and install the latest Miniconda (x64, with Python 3) from https://conda.io/miniconda.html.

Step 1: Open the Anaconda Prompt and create an environment for ANDES (optional)

conda create --name andes python=3.7

Activate the new environment. On Microsoft Windows, do

activate andes

On Linux or macOS, do

conda activate andes

You can skip this step to install ANDES to the base environment, though it is not recommended.

Step 2: Add the conda-forge channel and set it as default

conda config --add channels conda-forge
conda config --set channel_priority flexible

Existing Python Environment (Advanced)

This is for advanced user only. Please skip it if you have set up a Conda envirnonment. Instead of using Conda, if you prefer an existing Python environment, you can install ANDES with `pip`:

python3 -m pip install andes

If you see a Permission denied error, you will need to install the packages locally with --user

Install ANDES

ANDES can be installed in the user mode and the development mode.

User Mode

If you want to use ANDES without modifying the source code, you can install it in the user mode.

In the Anaconda environment, run

conda install andes

Developer Mode (Recommended)

If you want to hack into the code and, for example, develop new models or routines, please install it in the development mode (recommended). The development mode has the same usage as the user mode. In addition, changes to the source code will be reflected immediately without having to re-install the package.

Step 1: Get ANDES source code

Download the ANDES source code from https://github.com/cuihantao/andes and extract all files to the path of your choice. You can also git clone the source code (recommended).

git clone https://github.com/cuihantao/andes

Step 2: Install dependencies

In the Anaconda environment, use cd to change directory to the ANDES root folder.

Install dependencies with

conda install --file requirements.txt

Install development dependencies if you want to build documentation with

conda install --file requirements-dev.txt

Step 3: Install ANDES in the development mode using

python3 -m pip install -e .

Pip will take care of the rest.

Optional Packages

Install cvxoptklu to use KLU for speed up. cvxoptklu is a standalone KLU direct solver for linear equations. KLU is generally ~20% faster than UMFPACK. cvxoptklu requires a C compiler, and the openblas and SuiteSparse libraries.

python3 -m install cvxoptklu

Trouble-Shooting

There is a known issue of CVXOPT with versions earlier than 1.2.2 in Windows for handling complex numbers. For stock cases, if you see obviously incorrect power flow results or experienced a crash running time-domain simulation, please install the latest CVXOPT (=>1.2.2) and double check with conda list or pip list.