generation_layouts

Return every individual that was fitness-evaluated in a given
generation (<code>allCoords</code>). Duplicate layouts (same cell IDs) are flagged.

The genetic algorithm is designed to optimize wind farms of any shape. Each layout is encoded as n unique grid-cell identifiers. It requires a predefined amount of turbines, a unified rotor radius and an average wind speed value for each incoming wind direction. A terrain effect model can be included that downloads an 'SRTM' elevation model and loads a Corine Land Cover raster to approximate surface roughness.

Sebastian Gatscha

windfarmGA

Genetic Algorithm for Wind Farm Layout Optimization

generation_layouts function

<dl><dt>result</dt>
<dd>The output of <code>genetic_algorithm</code></dd>
<dt>generation</dt>
<dd>Generation index (1 = first). Default is the last
generation in <code>result</code>.</dd></dl>

Arguments

Layouts evaluated in one generation — generation_layouts

<dl>

<dt>result</dt>
<dd>The output of <code>genetic_algorithm</code></dd>


<dt>generation</dt>
<dd>Generation index (1 = first). Default is the last
generation in <code>result</code>.</dd>

</dl>

generation_layouts: Layouts evaluated in one generation

Description

Usage

Value

Arguments

See Also

Examples