WindLab Pro — Wind Farm Optimizer

Farm geometry

Rows

Columns

Turbines N

Cell spacing dx (m)

Cell spacing dy (m)

Farm dimensions will appear here.

Turbine + wind

Rotor radius R (m)

Hub height Z (m)

Free wind U0 (m/s)

Flow direction θ (deg)

Roughness Z0 (m)

Wake map grid

Flow-to convention: θ = 0° reproduces the MATLAB benchmark (+Y, top → bottom); θ = 90° means +X. This is not the meteorological wind-from convention.

Wake model

Single-wake model

Wake superposition

Wake expansion k

k from roughness

Gaussian virtual origin x0/D

Rotor sampling

Wake coefficient will appear here.

Power curve

Power curve mode

Legacy ideal: 500 kW × N

Cut-in (m/s)

Rated speed (m/s)

Cut-out (m/s)

Rated power (kW)

Cubic coefficient

Custom power curve table: wind speed (m/s), power (kW)

For custom mode, rows are linearly interpolated. Include the cut-out drop if desired.

Thrust coefficient CT

CT mode

Uniform fallback CT

CT(U) table or cell,CT map

CT(U) uses wind-speed interpolation. Cell-specific mode expects rows like 17,0.82; unspecified cells use the uniform fallback CT. Values are clipped to 0 ≤ CT < 1.

Optimization

Base seed

Max iterations

Algorithms

Population / swarm size

MC samples / iter

SA steps / iter

ACO archive / ants

Objective is Cost/P. For fixed N, this is equivalent to maximizing power. Random-key encoding selects the top N cells.

Ready. Select wake model, CT model and power-curve mode, then run.

Best power

—

Best objective

—

Cost / Power

Wake loss

—

relative to ideal

Best algorithm

—

Selected turbine cells

Convergence

Best-so-far farm power versus iteration.

Optimized layout

Black X markers show selected grid-cell centers.

Velocity field U/U0

Selected wake model and superposition, visualized at hub height.

Wake deficit 1 − U/U0

High values indicate stronger velocity deficit.

Power curve preview

Parametric or custom turbine power curve used by the optimizer.

CT curve preview

Uniform CT, CT(U), or cell-map fallback used by wake sources.

Optimizer summary

Power, objective, wake loss and selected cells for every optimizer.

Turbine-level results for selected layout

Effective rotor-equivalent wind speed, power, CT source value and upstream wakes.

Scientific note. Jensen/Park is a top-hat engineering wake model; Bastankhah Gaussian is a far-wake momentum-conserving Gaussian model. Both are steady engineering models, not LES/CFD. For journal-grade AEP, add wind rose integration, turbulence-intensity dependent wake expansion, terrain/ABL correction, and validation against SCADA, wind-tunnel, LES, or field data.