WEIS

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

Version

This software is a version 0.0.1.

Documentation

See local documentation in the docs-directory or access the online version at https://weis.readthedocs.io/en/latest/

Packages

WEIS integrates in a unique workflow four models:

• WISDEM is a set of models for assessing overall wind plant cost of energy (COE).
• OpenFAST is the community model for wind turbine simulation to be developed and used by research laboratories, academia, and industry.
• TurbSim is a stochastic, full-field, turbulent-wind simulator.
• ROSCO provides an open, modular and fully adaptable baseline wind turbine controller to the scientific community.

In addition, three external libraries are added:

• ROSCO_Toolbox is a toolbox designed to ease controller implementation for the wind turbine researcher and tune the ROSCO controller.
• pCrunch is a collection of tools to ease the process of parsing large amounts of OpenFAST output data and conduct loads analysis.
• 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
• control contains the routines calling the ROSCO_Toolbox 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 is the recommended approach because of the ability to create self-contained environments suitable for testing and analysis. WEIS requires Anaconda 64-bit.

The installation instructions below use the environment name, "weis-env," but any name is acceptable.

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 (Anaconda3 Power Shell on Windows or Terminal.app on Mac)

   conda config --add channels conda-forge
   conda create -y --name weis-env python=3.8       # (you can install an environment at a predefined path by switching "--name weis-env" with "--prefix path/weis-env")
   conda activate weis-env                          # (if this does not work, try source activate weis-env)
   

2. Use conda to install the build dependencies. Note the differences between Windows and Mac/Linux build systems. Skip to point #3 if you are on the DOE HPC system Eagle

   conda install -y cmake cython control dill git jsonschema make matplotlib-base numpy openmdao openpyxl pandas pip pyoptsparse pytest python-benedict pyyaml ruamel_yaml scipy setuptools simpy slycot smt sortedcontainers swig
   conda install -y petsc4py mpi4py                 # (Mac / Linux only)   
   conda install -y compilers                       # (Mac only)   
   conda install -y m2w64-toolchain libpython       # (Windows only)
   pip install marmot-agents jsonmerge fatpack
   git clone https://github.com/WISDEM/WEIS.git
   cd WEIS
   git checkout branch_name # (Only if you want to switch git branch, say develop)
   python setup.py develop
   

3. Instructions specific for DOE HPC system Eagle

    conda install -y cmake cython control dill git jsonschema make matplotlib-base numpy openmdao openpyxl pandas pip pyoptsparse pytest python-benedict pyyaml ruamel_yaml scipy setuptools simpy slycot smt sortedcontainers swig
    conda install -y petsc4py mpi4py
    pip install marmot-agents jsonmerge fatpack
    git clone https://github.com/WISDEM/WEIS.git
    cd WEIS
    git checkout branch_name # (Only if you want to switch git branch, say develop)
    module load comp-intel intel-mpi mkl
    module unload gcc
    python setup.py develop
   

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

Developer guide

If you plan to contribute code to WEIS, please first consult the developer guide.

Feedback

For software issues please use https://github.com/WISDEM/WEIS/issues.