{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Overview" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "PyWake is an open-source wind farm simulation tool used for studying the interaction between turbines within a wind farm and its influence on the farm’s flow field and power production. Based in Python, PyWake is capable of accurately computing the physics behind wind farms as well as obtaining their AEP. It provides a unified interface to wind farm models of different fidelities, e.g., different engineering models and CFD-RANS (commercial plugin). Given its heavy vectorization and use of numerical libraries, PyWake is a very fast tool that can handle many variables at once." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## The PyWake Philosophy\n", "\n", "\"Empowering users\" underlines the formulation of PyWake. Its highly modular architecture (shown in the figure below) allows users to combine different AEP modelling blocks in all sorts of fashions - giving the flexibility to shape PyWake around the particularities of real-world problems more accurately. Yet with power also comes responsibility - the user needs to make an informed decision when combining the multitude of building blocks PyWake supplies. Essentially, everyone can build their *own* AEP model chain leveraging PyWake's flexibility, so there is not *one* PyWake solution either; users should thus ensure to report the particular PyWake building blocks they used to transparently communicate their results and methodology." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "