Skip to main content

Windfarm operations and maintenance cost-benefit analysis tool

Project description

https://badge.fury.io/py/wombat.svg https://mybinder.org/badge_logo.svg https://img.shields.io/badge/License-Apache%202.0-blue.svg pre-commit https://img.shields.io/badge/code%20style-black-000000.svg https://img.shields.io/badge/%20imports-isort-%231674b1?style=flat&labelColor=ef8336

This library provides a tool to simulate the operation and maintenance phase (O&M) of distributed, land-based, and offshore windfarms using a discrete event simultaion framework.

WOMBAT is written around the SimPy framework for discrete event simulation framework. Additionally, this is supported using a flexible and modular object-oriented code base, which enables the modeling of arbitrarily large (or small) windfarms with as many or as few failure and maintenance tasks that can be encoded.

Please note that this is still heavily under development, so you may find some functionality to be incomplete at the current moment, but rest assured the functionality is expanding. With that said, it would be greatly appreciated for issues or PRs to be submitted for any improvements at all, from fixing typos (guaranteed to be a few) to features to testing (coming FY22!).

WOMBAT in Action

There a few Jupyter notebooks to get users up and running with WOMBAT in the examples/ folder, but here are a few highlights:

Setup

Requirements

  • Python 3.7+, see the next section for more.

Environment Setup

Download the latest version of Miniconda for the appropriate OS. Follow the remaining steps for the appropriate OS version.

Using conda, create a new virtual environment:

conda create -n <environment_name> python=3.8 --no-default-packages
conda activate <environment_name>
conda install -c anaconda pip

# to deactivate
conda deactivate

Installation

Pip

pip install wombat

From Source

Install it directly into an activated virtual environment:

git clone https://github.com/WISDEM/WOMBAT.git
cd wombat
python setup.py install

or if you will be contributing:

git clone https://github.com/WISDEM/WOMBAT.git
cd wombat
pip install -e '.[dev]'

Required for automatic code formatting!

pre-commit install

or for documentation:

git clone https://github.com/WISDEM/WOMBAT.git
cd wombat
pip install -e '.[docs]'

Build the site

NOTE: You may want to change the “execute_notebook” parameter in the conf.py file to “off” unless you’re updating the coded examples or they will be run every time you build the site.

cd docs/
make html

View the results: docs/_build/html/index.html

or both at once:

git clone https://github.com/WISDEM/WOMBAT.git
cd wombat
pip install -e '.[all]'

Usage

After installation, the package can imported:

python
import wombat
wombat.__version__

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

wombat-0.4.1.tar.gz (63.9 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

wombat-0.4.1-py3-none-any.whl (69.9 kB view details)

Uploaded Python 3

File details

Details for the file wombat-0.4.1.tar.gz.

File metadata

  • Download URL: wombat-0.4.1.tar.gz
  • Upload date:
  • Size: 63.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.8.0 pkginfo/1.8.2 readme-renderer/33.0 requests/2.27.1 requests-toolbelt/0.9.1 urllib3/1.26.8 tqdm/4.63.0 importlib-metadata/4.11.2 keyring/23.5.0 rfc3986/2.0.0 colorama/0.4.4 CPython/3.10.2

File hashes

Hashes for wombat-0.4.1.tar.gz
Algorithm Hash digest
SHA256 8689cfe95c2e13a4d4cf5d203632bd2fb38987d85d6d71d63394a1e4905740ab
MD5 fd7dbf5bbf997972282eb3be7b838dee
BLAKE2b-256 45719c6a071da277f38e70b7c97b83a6ec83b3e73ceb476b6c82e17a66e12660

See more details on using hashes here.

File details

Details for the file wombat-0.4.1-py3-none-any.whl.

File metadata

  • Download URL: wombat-0.4.1-py3-none-any.whl
  • Upload date:
  • Size: 69.9 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.8.0 pkginfo/1.8.2 readme-renderer/33.0 requests/2.27.1 requests-toolbelt/0.9.1 urllib3/1.26.8 tqdm/4.63.0 importlib-metadata/4.11.2 keyring/23.5.0 rfc3986/2.0.0 colorama/0.4.4 CPython/3.10.2

File hashes

Hashes for wombat-0.4.1-py3-none-any.whl
Algorithm Hash digest
SHA256 25f9808721565c9f28ec2b1a68ba376c339dadb51de025f1e44622bec0a6d81a
MD5 89715c4c98d153b0a7e7f0619e5b649c
BLAKE2b-256 6e034cefe8a05e3e0b6e77cdf86c7644016837520ecd5c6cafc6e589ab124fcf

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page