.. _quick_overview:

Quick Overview
==============

This quick overview walks you through a complete wind resource assessment
workflow in PyWAsP. By the end, you'll have calculated the annual energy
production (AEP) for wind turbines at a real site.

.. note::

    Make sure you have PyWAsP :doc:`installed <installation>` and your license
    configured (``pywasp configure``) before starting.

Import Libraries
----------------

.. jupyter-execute::

    import pywasp as pw
    import windkit as wk

Get Tutorial Data
-----------------

Download tutorial data for the Serra Santa Luzia site in Portugal:

.. jupyter-execute::

    path = wk.get_tutorial_data("serra_santa_luzia")

The tutorial data folder contains:

- ``bwc.omwc`` - Observed wind climate (WAsP format)
- ``SerraSantaLuzia.map`` - Elevation and roughness (WAsP map format)
- ``turbines.csv`` - Turbine positions
- ``Bonus1MW.wtg`` - Turbine power curve (WAsP format)

Create a Topography Map
-----------------------

Read elevation and roughness from the WAsP map file:

.. jupyter-execute::

    elev = wk.read_elevation_map(path / "SerraSantaLuzia.map")
    rgh = wk.read_roughness_map(path / "SerraSantaLuzia.map")
    topo_map = pw.wasp.TopographyMap(elev, rgh)

Generalize the Wind Climate
---------------------------

Load the observed wind climate, reproject to match the map CRS, and remove terrain effects:

.. jupyter-execute::

    bwc = wk.read_bwc(path / "bwc.omwc", crs="EPSG:4326")
    bwc = wk.spatial.reproject(bwc, "EPSG:32629")
    gwc = pw.wasp.generalize(bwc, topo_map)
    gwc

Predict Wind Climate at Turbines
--------------------------------

Load turbine positions and downscale the wind climate:

.. jupyter-execute::

    turbines = wk.read_wind_turbines(path / "turbines.csv", crs="EPSG:32629")
    wwc = pw.wasp.downscale(gwc, topo_map, output_locs=turbines)
    wwc

Calculate AEP
-------------

Load the turbine model and calculate gross annual energy production:

.. jupyter-execute::

    wtg = wk.read_wtg(path / "Bonus1MW.wtg")
    aep = pw.gross_aep(wwc, wtg)
    aep

.. jupyter-execute::

    total_aep = float(aep["gross_aep"].sum())
    print(f"Total gross AEP: {total_aep:.2f} GWh")

----

Next Steps
----------

.. grid:: 1 2 2 2
    :gutter: 4

    .. grid-item-card:: Calculate Net AEP
        :link: ../user_guide/calculate_aep
        :link-type: doc

        Add wake effects, losses, and uncertainty.

    .. grid-item-card:: Tutorials
        :link: ../tutorials/tutorials
        :link-type: doc

        Work through detailed examples.

    .. grid-item-card:: Wind Climates
        :link: ../user_guide/wind_climates
        :link-type: doc

        Understand wind climate types.

    .. grid-item-card:: WAsP Flow Model
        :link: ../user_guide/wasp_flow_model
        :link-type: doc

        Deep dive into terrain effects.