https://github.com/WISDEM/WEIS
Wind Energy with Integrated Servo-controls Toolset
https://github.com/WISDEM/WEIS
Last synced: 4 days ago
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Wind Energy with Integrated Servo-controls Toolset
- Host: GitHub
- URL: https://github.com/WISDEM/WEIS
- Owner: WISDEM
- License: apache-2.0
- Created: 2020-08-21T16:54:28.000Z (over 4 years ago)
- Default Branch: main
- Last Pushed: 2025-05-03T01:13:33.000Z (8 days ago)
- Last Synced: 2025-05-03T17:44:02.743Z (7 days ago)
- Language: Roff
- Homepage: https://weis.readthedocs.io/en/latest/
- Size: 197 MB
- Stars: 61
- Watchers: 12
- Forks: 46
- Open Issues: 14
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
- open-sustainable-technology - WEIS - WEIS is a framework that combines multiple tools to enable design optimization of floating offshore wind turbines. (Renewable Energy / Wind Energy)
README
# WEIS
[](https://coveralls.io/github/WISDEM/WEIS?branch=develop)
[](https://github.com/WISDEM/WEIS/actions)
[](https://weis.readthedocs.io/en/develop/?badge=develop)
[](https://zenodo.org/badge/latestdoi/289320573)
WEIS, Wind Energy with Integrated Servo-control, performs multifidelity co-design of wind turbines. WEIS is a framework that combines multiple NREL-developed tools to enable design optimization of floating offshore wind turbines.
Author: [NREL WISDEM & OpenFAST & Control Teams](mailto:[email protected])
## Documentation
See local documentation in the `docs`-directory or access the online version at
## Packages
WEIS integrates in a unique workflow four models:
* [WISDEM](https://github.com/WISDEM/WISDEM) is a set of models for assessing overall wind plant cost of energy (COE).
* [OpenFAST](https://github.com/OpenFAST/openfast) is the community model for wind turbine simulation to be developed and used by research laboratories, academia, and industry.
* [TurbSim](https://www.nrel.gov/docs/fy09osti/46198.pdf) is a stochastic, full-field, turbulent-wind simulator.
* [ROSCO](https://github.com/NREL/ROSCO) provides an open, modular and fully adaptable baseline wind turbine controller to the scientific community.
In addition, three external libraries are added:
* [pCrunch](https://github.com/NREL/pCrunch) is a collection of tools to ease the process of parsing large amounts of OpenFAST output data and conduct loads analysis.
* [pyOptSparse](https://github.com/mdolab/pyoptsparse) is a framework for formulating and efficiently solving nonlinear constrained optimization problems.
The core WEIS modules are:
* _aeroelasticse_ is a wrapper to call [OpenFAST](https://github.com/OpenFAST/openfast)
* _control_ contains the routines calling [ROSCO](https://github.com/NREL/ROSCO) and the routines supporting distributed aerodynamic control devices, such trailing edge flaps
* _gluecode_ contains the scripts glueing together all models and libraries
* _multifidelity_ contains the codes to run multifidelity design optimizations
* _optimization_drivers_ contains various optimization drivers
* _schema_ contains the YAML files and corresponding schemas representing the input files to WEIS
## Installation
On laptop and personal computers, installation with [Anaconda](https://www.anaconda.com) is the recommended approach because of the ability to create self-contained environments suitable for testing and analysis. WEIS requires [Anaconda 64-bit](https://www.anaconda.com/distribution/). However, the `conda` command has begun to show its age and we now recommend the one-for-one replacement with the [Miniforge3 distribution](https://github.com/conda-forge/miniforge?tab=readme-ov-file#miniforge3), which is much more lightweight and more easily solves for the package dependencies. Sometimes, using `mamba` in place of `conda` with this distribution speeds up the installation process. WEIS is supported on Linux, MAC, Windows Sub-system for Linux (WSL), and native Windows.
The installation instructions below use the environment name, "weis-env," but any name is acceptable. For those working behind company firewalls, you may have to change the conda authentication with `conda config --set ssl_verify no`. Proxy servers can also be set with `conda config --set proxy_servers.http http://id:pw@address:port` and `conda config --set proxy_servers.https https://id:pw@address:port`.
0. If you are NOT installing WEIS on DOE's HPC system Kestrel, skip step 0 and run step 1 and 2 (skip step 3). If you are on Kestrel, follow steps 0, 1, and 3, and skip step 2. On Kestrel, start by purging existing modules and load conda
module purge
module load conda
1. In a terminal, setup and activate the Anaconda environment
conda config --add channels conda-forge
conda install git
git clone https://github.com/WISDEM/WEIS.git
cd WEIS
git checkout branch_name # (Only if you want to switch branches, say "develop")
conda env create --name weis-env -f environment.yml
conda activate weis-env # (if this does not work, try source activate weis-env)
2. If you are NOT on Kestrel, add in final packages and install the software
conda install -y petsc4py=3.22.2 mpi4py pyoptsparse # (Mac / Linux only, sometimes Windows users may need to install mpi4py)
pip install -e .
3. If you are on Kestrel, do:
module load comp-intel intel-mpi mkl
module unload gcc
pip install --no-deps -e . -v
**NOTE:** To use WEIS again after installation is complete, you will always need to activate the conda environment first with `conda activate weis-env` (or `source activate weis-env`). On Kestrel, make sure to reload the necessary modules
For Windows users, we recommend installing `git` and the `m264` packages in separate environments as some of the libraries appear to conflict such that WISDEM cannot be successfully built from source. The `git` package is best installed in the `base` environment.
## Developer guide
If you plan to contribute code to WEIS, please first consult the [developer guide](https://weis.readthedocs.io/en/latest/how_to_contribute_code.html).
## Feedback
For software issues please use .