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.. PyWake documentation master file, created by
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Welcome to PyWake
===========================================

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.. image:: logo.svg

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:align: center
PyWake is an open-sourced and Python-based wind farm simulation tool developed at DTU capable of computing flow fields, power production of individual turbines as well as the Annual Energy Production (AEP) of a wind farm. The software solution provides an interface to both a selection different engineering models as well as CDF RANS (PyWakeEllipSys). It is highly efficient in calculating how the wake propagates within a wind farm and can quantify the interaction between turbines.

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What can PyWake do?
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

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The main objective of PyWake is to calculate the wake interaction in a wind farm in a computationally inexpensive way for a range of steady state conditions. It is very useful for computing the power production of a wind farm while considering the wake losses for a specific wind farm layout configuration. Some of the main capabilities of PyWake that have been in constant development in the last few years include:

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* The possibility to use different engineering wake models for the simulation, such as the NOJ and Bastankhah wake deficit models.
* The option of choosing between different sites and their wind resource, with the additional option of user-defined sites.
* The ability to have user-defined wind turbines or import turbine files from WAsP.
* The capability of working with chunkification and parallelization.
* The advantage of visualizing flow maps for the wind farm layout in study.

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For installation instructions, please see the :ref:`Installation Guide <installation>`.

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https://gitlab.windenergy.dtu.dk/TOPFARM/PyWake
License:
MIT_
.. _MIT: https://gitlab.windenergy.dtu.dk/TOPFARM/PyWake/blob/master/LICENSE
Getting Started
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
PyWake is equipped with many capabilities that can range from basic to complex. For new users, the :ref:`Overview </notebooks/Overview.ipynb>` section contains a basic description of PyWake’s architecture and the elements behind it. Plus, the :ref:`Quickstart </notebooks/Quickstart.ipynb>` section shows how to set up and perform some basic operations in PyWake.
Explanations of PyWake's core objects can be found in the following tutorials:
* :ref:`Site </notebooks/Site.ipynb>`: this tutorial walks through the set up of pre-defined sites in PyWake as well as the possibility for user-defined sites.
* :ref:`Wind Turbine </notebooks/WindTurbines.ipynb>`: this example demonstrates how to set up a wind turbine object and also to create user-defined turbines with specific power and CT curves.
* :ref:`Engineering Wind Farm Models </notebooks/EngineeringWindFarmModels.ipynb>`: here there is a detailed explanation of all the wake deficit models available in PyWake as well as other engineering models such as wake superposition, deflection, etc.
The :ref:`Wind farm simulation </notebooks/RunWindFarmSimulation.ipynb>` example shows how to execute PyWake and extract relevant information about the wind farm studied. In addition, PyWake's capablities to calculate gradients are demonstrated in the :ref:`Gradients, parallelization and precision </notebooks/gradients_parallellization.ipynb>` example, and an optimization with TOPFARM is available in the :ref:`Optimization </notebooks/Optimization.ipynb>` tutorial.
Lastly, the remaining notebooks illustrate some relevant examples and exercises to see the different properties that PyWake has to offer.

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.. toctree::

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installation

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notebooks/ChangeLog

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.. toctree::

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notebooks/Site
notebooks/WindTurbines
notebooks/EngineeringWindFarmModels
notebooks/RunWindFarmSimulation
notebooks/gradients_parallellization
.. toctree::
notebooks/literature_verification/TurbOPark

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.. toctree::
:maxdepth: 2

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validation
.. toctree::

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api/WindTurbines
api/Site
api/WindFarmModel
api/EngineeringWindFarmModels
api/PredefinedEngineeringWindFarmModels
api/SimulationResult
api/FlowMap