WISDEM®

The Wind-Plant Integrated System Design and Engineering Model (WISDEM®) is a set of models for assessing overall wind plant cost of energy (COE). The models use wind turbine and plant cost and energy production as well as financial models to estimate COE and other wind plant system attributes. WISDEM® is accessed through Python, is built using OpenMDAO, and uses several sub-models that are also implemented within OpenMDAO. These sub-models can be used independently but they are required to use the overall WISDEM® turbine design capability. Please install all of the pre-requisites prior to installing WISDEM® by following the directions below. For additional information about the NWTC effort in systems engineering that supports WISDEM® development, please visit the official NREL systems engineering for wind energy website.

Author: NREL WISDEM Team

Documentation

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

Packages

WISDEM® is a family of modules. The core modules are:

CommonSE includes several libraries shared among modules
FloatingSE works with the floating platforms
DrivetrainSE sizes the drivetrain and generator systems (formerly DriveSE and GeneratorSE)
TowerSE is a tool for tower (and monopile) design
RotorSE is a tool for rotor design
NREL CSM is the regression-based turbine mass, cost, and performance model
ORBIT is the process-based balance of systems cost model for offshore plants
LandBOSSE is the process-based balance of systems cost model for land-based plants
Plant_FinanceSE runs the financial analysis of a wind plant

The core modules draw upon some utility packages, which are typically compiled code with python wrappers:

Airfoil Preppy is a tool to handle airfoil polar data
CCBlade is the BEM module of WISDEM
pyFrame3DD brings libraries to handle various coordinate transformations
pyMAP provides a python interface to MAP++, a quasi-static mooring line model
pyOptSparse provides some additional optimization algorithms to OpenMDAO

Installation

Installation with Anaconda is the recommended approach because of the ability to create self-contained environments suitable for testing and analysis. WISDEM® requires Anaconda 64-bit.

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

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 wisdem-env python=3.7
conda activate wisdem-env
```
In order to directly use the examples in the repository and peek at the code when necessary, we recommend all users install WISDEM in developer mode. This is done by first installing WISDEM as a conda package to easily satisfy all dependencies, but then removing the WISDEM conda package and reinstalling from the Github source code. Note the differences between Windows and Mac/Linux build systems:
```
conda install -y wisdem git jupyter
conda remove --force wisdem
conda install compilers     # (Mac / Linux only)
conda install m2w64-toolchain libpython       # (Windows only)
pip install simpy marmot-agents
git clone https://github.com/WISDEM/WISDEM.git
cd WISDEM
git checkout develop
python setup.py develop
```
OPTIONAL: Install pyOptSparse, a package that provides a handful of additional optimization solvers and has OpenMDAO support:
```
 git clone https://github.com/evan-gaertner/pyoptsparse.git
 cd pyoptsparse
 python setup.py install
 cd ..
```

NOTE: To use WISDEM again after installation is complete, you will always need to activate the conda environment first with conda activate wisdem-env

Run Unit Tests

Each package has its own set of unit tests. These can be run in batch with the test_all.py script located in the top level test-directory.

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