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
Part of the WETO Stack
WISDEM is primarily developed with the support of the U.S. Department of Energy and is part of the WETO Software Stack. For more information and other integrated modeling software, see:
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
- MoorPy is 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. However, the conda command has begun to show its age and we now recommend the one-for-one replacement with the Miniforge3 distribution, which is much more lightweight and more easily solves for the WISDEM package dependencies.
Installation as a "library"
-
Create a conda environment with your preferred name (
wisdem-envin the following example) and favorite, approved Python version:conda create -n wisdem-env python=3.13 -y -
Activate the environment:
conda activate wisdem-env -
Install WISDEM via a
condaorpip. We highly recommend via conda.conda install wisdemor
pip install wisdem
To use WISDEM's modules as a library for incorporation into other scripts or tools, WISDEM is available via conda install wisdem or pip install wisdem, assuming that you have already setup your python environment. Note that on Windows platforms, we suggest using conda exclusively.
Installation for direct use or development
These instructions are for interaction with WISDEM directly, the use of its examples, and the direct inspection of its source code.
The installation instructions below use the environment name, "wisdem-env," but any name is acceptable. Below are a series of considerations:
- 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:portandconda config --set proxy_servers.https https://id:pw@address:port. - To setup an environment based on a different Github branch of WISDEM, simply substitute the branch name for
masterin the setup line.
Note For Windows users, we recommend installing
gitand them2w64packages in separate environments as some of the libraries appear to conflict such that WISDEM cannot be successfully built from source. Thegitpackage is best installed in thebaseenvironment.
Direct use
We still highly recommend users use conda install wisdem into an environment, but if there is a reason that is not
desired, please use the following instructions.
Setup and activate the Anaconda environment from a prompt (Anaconda3 Power Shell on Windows or Terminal.app on Mac)
-
Install
gitif you don't already have it:conda install git -
Clone the repository and enter it:
git clone https://github.com/NLRWindSystems/WISDEM.git cd WISDEM
-
Checkout the desired branch, if necessary:
git checkout <branch> -
Create and activate your
wisdem-envenvironment, substituting "wisdem-env" with a different desired name.conda env create --name wisdem-env -f environment.yml conda activate wisdem-env
-
Install WISDEM.
pip install --no-deps . -v
Development
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 / editable mode using the instructions here. If you really just want to use WISDEM as a library and lean on the documentation, you can always do conda install wisdem and be done. Note the differences between Windows and Mac/Linux build systems.
Please follow steps 1-3 in the Direct Use section above, replacing steps 4 & 5 with the following to ensure the development dependencies for building, testing, and documentation are also installed:
-
Create and activate your
wisdem-envenvironment, substituting "wisdem-env" with a different desired name.conda env create --name wisdem-env -f environment_dev.yml conda activate wisdem-env
-
Install WISDEM. Please note the
-e(editable) flag used to ensure your code changes are registered dynamically every time you save modifications.pip install --no-deps -e . -v
Run Unit Tests
Each package has its own set of unit tests, and the project runs the examples as integration tests. These can be run in batch with the following command:
pytest
Users can add either the --unit or --integration flags if they would like to skip running
the examples or just run the examples. Otherwise, all tests will be run.
Feedback
For software issues please use https://github.com/NLRWindSystems/WISDEM/issues. For functionality and theory related questions and comments please use the NWTC forum for Systems Engineering Software Questions.
Metadata
Release files for wisdem 4.2.8
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| wisdem-4.2.8.tar.gz | 5.6 MB | Details |
Built distributions (wheels)
Total release size: 264.6 MB
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