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https://github.com/WISDEM/WEIS

Wind Energy with Integrated Servo-controls Toolset
https://github.com/WISDEM/WEIS

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Wind Energy with Integrated Servo-controls Toolset

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README 

        
# WEIS



[![Coverage Status](https://coveralls.io/repos/github/WISDEM/WEIS/badge.svg?branch=develop)](https://coveralls.io/github/WISDEM/WEIS?branch=develop)

[![Actions Status](https://github.com/WISDEM/WEIS/workflows/CI_WEIS/badge.svg?branch=develop)](https://github.com/WISDEM/WEIS/actions)

[![Documentation Status](https://readthedocs.org/projects/weis/badge/?version=develop)](https://weis.readthedocs.io/en/develop/?badge=develop)

[![DOI](https://zenodo.org/badge/289320573.svg)](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 currently supported on Linux, MAC and Windows Sub-system for Linux (WSL). Installing WEIS on native Windows is not yet supported, but planned in 2024.



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.  On the DOE HPC system eagle, make sure to start from a clean setup and type



        module purge

        module load conda        



1.  Setup and activate the Anaconda environment from a prompt (WSL terminal on Windows or Terminal.app on Mac)



        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. Add in final packages and install the software



        conda install -y petsc4py mpi4py pyoptsparse     # (Mac / Linux only)

        pip install -e .



3. Instructions specific for DOE HPC system Eagle.  Before executing the setup script, 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 Eagle, 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 .