A met mast draws one hourly wind-speed sample at a time from a Weibull distribution — the standard statistical model for wind resource assessment — with shape k (gustiness/variability) and scale c (the mean speed at the 10 m reference height). Each sample is scaled up to hub height with the wind-shear power law, then pushed through the turbine's power curve to get an instantaneous output. The teal bars are the live histogram of every sample drawn so far; the white curve is the theoretical Weibull density they should converge to.
v_hub = v10 · (H / 10)^α
P(v) = 0 v < v_cut-in
P(v) = P_rated · (v³−v_ci³)/(v_r³−v_ci³) v_cut-in ≤ v < v_rated
P(v) = P_rated v_rated ≤ v < v_cut-out
P(v) = 0 v ≥ v_cut-out
- Shape k / mean speed c — describe the site's wind climate; low k means gustier, more variable wind, high k means a steadier breeze at roughly the same mean.
- Hub height and terrain roughness α — taller towers and smoother terrain (open water, low α) reach faster, steadier wind; forests and towns (high α) shear the wind down near the ground.
- Rated power — the turbine's nameplate output once wind passes the rated speed (fixed at 12 m/s here); cut-in is 3 m/s, cut-out is 25 m/s.
- Capacity factor — projected annual energy divided by what the turbine would deliver running at rated power every hour of the year; real onshore sites typically land between 25–45%.
Real-world relevance: this is exactly how developers screen an onshore wind site before committing — a year or more of anemometer data gets fitted to a Weibull curve, scaled to the proposed hub height, and run through the candidate turbine's power curve to estimate annual energy production and capacity factor before a single turbine is built.