Wind annual energy production (AEP) and capacity factor calculator
Enter the site's mean wind speed, the hub height and the turbine details to see gross and net annual energy production, the capacity factor and the full-load hours. It is a quick estimate for pre-feasibility; the calculation runs in your browser.
Wind resource
Air density
Turbine
The generic power curve is approximate: a v³ curve with Cp up to 0.45, rounded off towards rated power and clipped at rated power. A real turbine's curve can differ markedly; if possible, enter the manufacturer's curve as a table.
Losses
- Net annual energy (AEP)
- 5,767 MWh/year
- Capacity factor (net)
- 32.9%
- Gross annual energy
- 6,653 MWh/year
- Capacity factor (gross)
- 38%
- Full-load hours (net)
- 2,883 hours/year
- Mean speed at hub
- 6.94 m/s
- Weibull A at hub
- 7.83 m/s
- Weibull k
- 2
- Air density
- 1.225 kg/m³
- Cp in generic curve
- 0.45
- Total loss factor
- 0.867
- Speed distribution (hours/year)
- Power curve (kW)
Sensitivity
| Sensitivity | Net AEP | Capacity factor | Change |
|---|---|---|---|
| Base | 5,767 | 32.9% | — |
| Hub speed −5 % | 5,269 | 30.1% | -8.6% |
| Hub speed +5 % | 6,245 | 35.6% | +8.3% |
| Weibull k −0.2 | 5,732 | 32.7% | -0.6% |
| Weibull k +0.2 | 5,771 | 32.9% | +0.1% |
A = v̄ / Γ(1 + 1/k) · F(v) = 1 − exp(−(v/A)^k) · AEP = Σ P(v) · ΔF · 8760 · CF = AEP / (Prated · 8760) · v_hub = v_meas · (h_hub/h_meas)^α
The values you enter are processed in your browser and are not sent anywhere.
This result is a pre-feasibility estimate. A bankable energy estimate requires at least 1 year of on-site measurements, long-term correction (MCP), terrain and flow modelling, wake loss and uncertainty analysis. The defaults are examples, not real project data.
Would you like to go from measurement data to annual energy and anomaly analysis for a wind site? Let's look at your data together.
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How to use it
A
Enter the mean wind speed and measurement height, the turbine's hub height and the Weibull k (start with 2 if you do not know it).
B
Enter the turbine's rated power, rotor diameter and speed limits, or paste the manufacturer's power curve as a speed;kW table; adjust the losses for your site.
C
Read the net AEP, capacity factor and full-load hours; see in the charts which speeds the energy comes from and in the sensitivity table how mean speed and k matter.
02
How is annual energy calculated?
Wind speed varies through the year, and this distribution is usually described by a Weibull distribution: the scale parameter A sets the magnitude of the speed and the shape parameter k its spread. When the mean speed is known, A = v̄ / Γ(1 + 1/k); k = 2 is the Rayleigh distribution.
Measurements are usually not taken at hub height, so the speed is scaled with height: in the power law v_hub = v_meas · (h_hub/h_meas)^α (α ≈ 0.14 is a common value over open terrain), or in the logarithmic profile with the ratio ln(h/z₀) using the roughness length z₀. Air density falls with altitude and temperature; at lower density the same wind yields less power.
The tool divides the speed axis into 0.25 m/s bins; for each it takes the hours per year from the Weibull distribution and the power at that speed from the power curve, multiplies and sums. This is gross energy; availability, wake, electrical and other losses are applied as factors to get the net AEP.
03
What do capacity factor and full-load hours tell you?
The capacity factor is the annual net energy divided by what the turbine would produce if it ran at rated power all year: CF = AEP / (rated power × 8760). Full-load hours give the same information in hours: AEP / rated power. Both are practical ways to compare sites and turbines.
The capacity factor depends not only on the wind but also on the turbine's specific power: a turbine with a large rotor for its rated power (low specific power) gives a higher capacity factor in the same wind. Comparing two different turbines on capacity factor alone can therefore mislead; look at MWh/year and investment cost together.
04
What does this calculation not show?
This is a pre-feasibility tool. A single year of measurements may not represent the long-term climate; a bankable estimate needs at least one year of on-site measurements transferred to the long term with reference data (MCP). Terrain effects, turbines shading each other (wake), icing, curtailment and measurement uncertainty must also be modelled separately.
The wind case study on our site tests a short-term production forecasting and anomaly detection method on open data (ENGIE La Haute Borne). This tool covers the other end of the job, a quick view of the expected annual energy when deciding whether to build; the two complement each other.
FAQ
- Are the values I enter sent anywhere?
- No. The calculation runs entirely in code inside your browser; the values are neither transmitted to a server nor stored.
- Are the default values a real project?
- No. The defaults (6.5 m/s, a generic 2 MW / 90 m turbine, the losses) are examples chosen to show how the tool works. Enter the values for your own site and turbine.
- What should I enter if I do not know the Weibull k?
- 2 (Rayleigh) is a reasonable start. If you can derive k from your measurement data, use that; the sensitivity table shows how much a ±0.2 change in k affects the result.
- What happens when the power curve is "generic"?
- A v³ curve with Cp up to 0.45 is rounded off towards rated speed and clipped at rated power. It is approximate; pasting the manufacturer's power curve as a speed;kW table gives much more accurate results.
- How does air density affect the result?
- The power in the wind is proportional to density. At high altitude or in a hot climate, density falls below 1.225 kg/m³ and energy drops. The tool computes density from altitude and temperature with the standard atmosphere, or lets you enter it.
- Can I base a bank or investment decision on the result?
- No. It is a pre-feasibility estimate. A financing or investment decision needs at least 1 year of on-site measurements, long-term correction and an independent energy yield assessment.
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We combine measurement, SCADA and production data for annual energy, performance deviation and anomaly analysis. Let's talk about your data in a free discovery call.