Package: wisdem
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 usingOpenMDAO, 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 officialNREL systems engineering for wind energy website.Author:NREL WISDEM TeamDocumentationSee local documentation in thedocs-directory or access the online version athttps://wisdem.readthedocs.io/en/master/PackagesWISDEM® is a family of modules.  The core modules are:CommonSEincludes several libraries shared among modulesFloatingSEworks with the floating platformsDrivetrainSEsizes the drivetrain and generator systems (formerly DriveSE and GeneratorSE)TowerSEis a tool for tower (and monopile) designRotorSEis a tool for rotor designNREL CSMis the regression-based turbine mass, cost, and performance modelORBITis the process-based balance of systems cost model for offshore plantsLandBOSSEis the process-based balance of systems cost model for land-based plantsPlant_FinanceSEruns the financial analysis of a wind plantThe core modules draw upon some utility packages, which are typically compiled code with python wrappers:Airfoil Preppyis a tool to handle airfoil polar dataCCBladeis the BEM module of WISDEMpyFrame3DDbrings libraries to handle various coordinate transformationsMoorPyis a quasi-static mooring line modelpyOptSparseprovides some additional optimization algorithms to OpenMDAOInstallationInstallation withAnacondais the recommended approach because of the ability to create self-contained environments suitable for testing and analysis.  WISDEM® requiresAnaconda 64-bit.  However, thecondacommand has begun to show its age and we now recommend the one-for-one replacement with theMiniforge3 distribution, which is much more lightweight and more easily solves for the WISDEM package dependencies.Installation as a "library"To use WISDEM's modules as a library for incorporation into other scripts or tools, WISDEM is available viaconda install wisdemorpip install wisdem, assuming that you have already setup your python environment.  Note that on Windows platforms, we suggest usingcondaexclusively.Installation for direct useThese 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.  For those working behind company firewalls, you may have to change the conda authentication withconda config --set ssl_verify no.  Proxy servers can also be set withconda 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 formasterin the setup line.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 env create --name wisdem-env -f https://raw.githubusercontent.com/WISDEM/WISDEM/master/environment.yml python=3.10
conda activate wisdem-envIn order to directly use the examples in the repository and peek at the code when necessary, we recommend all users install WISDEM indeveloper / editablemode using the instructions here.  If you really just want to use WISDEM as a library and lean on the documentation, you can always doconda install wisdemand be done.  Note the differences between Windows and Mac/Linux build systems. For Linux, we recommend using the native compilers (for example, gcc and gfortran in the default GNU suite).conda install -y petsc4py mpi4py                 # (Mac / Linux only)
conda install -y gfortran                        # (Mac only without Homebrew or Macports compilers)
conda install -y m2w64-toolchain libpython       # (Windows only)
git clone https://github.com/WISDEM/WISDEM.git
cd WISDEM
python setup.py develop				 # Currently more reliable than: pip install -eNOTE:To use WISDEM again after installation is complete, you will always need to activate the conda environment first withconda activate wisdem-envRun Unit TestsEach package has its own set of unit tests.  These can be run in batch with thetest_all.pyscript located in the top leveltest-directory.FeedbackFor software issues please usehttps://github.com/WISDEM/WISDEM/issues.  For functionality and theory related questions and comments please use the NWTC forum forSystems Engineering Software Questions.