floris.optimization.layout_optimization.layout_optimization_scipy

Classes

LayoutOptimizationScipy(fmodel, boundaries)

This class provides an interface for optimizing the layout of wind turbines using the Scipy optimization library.

class floris.optimization.layout_optimization.layout_optimization_scipy.LayoutOptimizationScipy(fmodel, boundaries, bnds=None, min_dist=None, solver='SLSQP', optOptions=None, enable_geometric_yaw=False, use_value=False)

This class provides an interface for optimizing the layout of wind turbines using the Scipy optimization library. The optimization objective is to maximize annual energy production (AEP) or annual value production (AVP).

Args:

fmodel (FlorisModel): A FlorisModel object. boundaries (iterable(float, float)): Pairs of x- and y-coordinates

that represent the boundary's vertices (m).

bnds (iterable, optional): Bounds for the optimization

variables (pairs of min/max values for each variable (m)). If none are specified, they are set to 0 and 1. Defaults to None.

min_dist (float, optional): The minimum distance to be maintained

between turbines during the optimization (m). If not specified, initializes to 2 rotor diameters. Defaults to None.

solver (str, optional): Sets the solver used by Scipy. Defaults to 'SLSQP'. optOptions (dict, optional): Dictionary for setting the

optimization options. Defaults to None.

enable_geometric_yaw (bool, optional): If True, enables geometric yaw

optimization. Defaults to False.

use_value (bool, optional): If True, the layout optimization objective

is to maximize annual value production using the value array in the FLORIS model's WindData object. If False, the optimization objective is to maximize AEP. Defaults to False.

optimize()

This method finds the optimized layout of wind turbines for power production given the provided frequencies of occurrence of wind conditions (wind speed, direction).

Returns:

opt_locs (iterable): A list of the optimized locations of each turbine (m).