WAVES

Wind Asset Value Estimation System is a tool for estimating the lifecycle costs of offshore wind projects using NREL's flagship techno economic models.
https://github.com/NatLabRockies/WAVES

Category: Renewable Energy
Sub Category: Wind Energy

Keywords

discrete-event-simulation lcoe offshore-wind python simulation wind-energy wind-energy-analytics

Last synced: about 24 hours ago
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Offshore Wind Farm Lifecycle Estimation

README.md

WAVES: Wind Asset Value Estimation System

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Overview

Runs analyses for offshore wind projects by utilizing ORBIT (CapEx), WOMBAT (OpEx), and FLORIS (AEP)
to estimate the lifecycle costs using NREL's flagship technoeconomic models.

Please visit our documentation site for API documentation, a
reference guide, and examples.

Requirements

Python 3.10+

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 and replace "waves" with a different environment
name, if preferred:

conda create -n waves python=3.14
conda activate waves
conda install -c anaconda pip
conda config --set pip_interop_enabled true

# to deactivate
conda deactivate

Installation

Requires Python 3.10+.

For basic usage, users can install WAVES directly from PyPI, or from source for more advanced usage.

Pip

pip install waves

From Source

A source installation is great for users that want to work with the provided example, and
potentially modify the code at a later point in time.

git clone https://github.com/NREL/WAVES.git
cd WAVES
pip install .

If working with the example, or running with Jupyter Notebooks, be sure to install the examples
dependencies like the following:

pip install ".[examples]"

Tinkering

Use the -e for an editable installation, in case you plan on editing any underlying code.

pip install -e .

Usage

After installation, the package can imported:

python
import waves
waves.__version__

CLI

waves library-path configuration1.yaml configuration2.yaml

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Last synced: 27 days ago

Total issues: 1
Total pull requests: 38
Average time to close issues: over 1 year
Average time to close pull requests: 18 days
Total issue authors: 1
Total pull request authors: 4
Average comments per issue: 1.0
Average comments per pull request: 0.79
Merged pull request: 31
Bot issues: 0
Bot pull requests: 0

Past year issues: 0
Past year pull requests: 14
Past year average time to close issues: N/A
Past year average time to close pull requests: 20 days
Past year issue authors: 0
Past year pull request authors: 3
Past year average comments per issue: 0
Past year average comments per pull request: 0.57
Past year merged pull request: 13
Past year bot issues: 0
Past year bot pull requests: 0

More stats: https://issues.ecosyste.ms/repositories/lookup?url=https://github.com/NatLabRockies/WAVES

Top Issue Authors

  • RHammond2 (1)

Top Pull Request Authors

  • RHammond2 (21)
  • dmulash (8)
  • nRiccobo (5)
  • crookp (4)

Top Issue Labels

  • enhancement (1)

Top Pull Request Labels

  • enhancement (13)
  • bug (9)
  • documentation (8)

Dependencies

.github/workflows/python-publish-test.yml actions
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  • actions/setup-python v4 composite
  • pypa/gh-action-pypi-publish release/v1 composite
.github/workflows/python-publish.yml actions
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  • actions/setup-python v4 composite
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  • peaceiris/actions-gh-pages v3.6.1 composite
pyproject.toml pypi
  • attrs *
  • floris ==3.6
  • matplotlib >=3.6
  • numpy-financial >=1.0.0
  • orbit-nrel >=1.0.8
  • pyyaml *
  • tqdm *
  • typer >=0.12.3
  • wombat >=0.9.3

Score: -Infinity