How Much Power Does a Wind Turbine Produce? Realistic Annual Yields for Small Wind Turbines

"So how much power does the wind turbine actually produce?" - that's the question that comes up first in almost every consultation. The honest answer is: it depends on three things that have nothing to do with the rated power on the spec sheet. This article puts all the cards on the table - with numbers, formulas, and a complete worked example.

Direct Answer: Realistic Annual Yields by Power Class

The table below shows typical annual yields for small wind turbines across several power classes at three mean wind speeds. All figures assume an overall annual efficiency of around 20%. This annual average captures the power coefficient, drivetrain and inverter losses, and the turbine's operating limits (cut-in wind speed, power limiting above rated wind, shutdown in storm conditions). The peak efficiency of a well-designed turbine is considerably higher - but averaged over a full year, roughly 20% is what remains. The figures apply to horizontal-axis turbines on a free-standing mast. Vertical-axis turbines with aerodynamically optimized geometry can achieve comparable results at turbulent sites - rotor swept area remains the decisive parameter.

The Physics: Why the Cube Law Dominates Everything

The power contained in the wind is given by:

P = 0.5 × ρ × A × v³ × cp

• ρ = air density (≈ 1.225 kg/m³ at sea level)
• A = rotor swept area in m²
• v = wind speed in m/s
• cp = power coefficient (theoretical maximum per Betz's law: 0.593, or 59.3%). Real-world turbines at their design point: horizontal-axis (HAWT) 0.40-0.45, H-Darrieus vertical-axis 0.25-0.35, Savonius rotors 0.15-0.20.

The decisive term is v³. If wind speed doubles from 3 to 6 m/s, the available wind power increases eightfold (2³ = 8). A site with 6 m/s therefore delivers not twice but eight times as much wind power as a site with 3 m/s - with the same turbine.

It's worth emphasizing that this rule is exact: the energy ratio between two sites is always precisely the ratio of their wind speeds cubed. 8 m/s versus 6 m/s gives 8³/6³ = 512/216 = 2.37× - no more. Anyone quoting a higher factor is doing the math wrong.

This leads to another important consequence: Rotor swept area, not rated power, is the true performance metric. Swept area grows with the square of the rotor diameter. A turbine with a 5 m rotor diameter has a swept area of just under 20 m² and therefore harvests four times as much wind energy as a turbine with a 2.5 m diameter - regardless of what the nameplate says.

Why Rated Power Is Misleading

Small wind turbines only reach their rated power at relatively high wind speeds, typically around 10 m/s or above. A turbine with a 3 kW rating will therefore only deliver that output on very windy days - at a typical inland site with a mean annual wind speed of 4-5 m/s, it runs well below rated power most of the time.

The right tool for a meaningful comparison is the power curve: it shows how many watts the turbine actually delivers at each wind speed between cut-in (typically 2-3 m/s) and rated wind speed (typically 10-14 m/s). Two turbines with the same 5 kW rated power can deliver annual yields of 3,400 kWh and 4,900 kWh respectively at a site with a mean wind speed of 4 m/s - the difference comes down to rotor diameter. Both figures assume a rotor considerably larger than the 5 m used in the table above; at a 4 m/s site, yields of that magnitude are only achievable with a correspondingly large swept area.

When comparing quotes, always ask: What is the certified annual yield at 4 m/s and at 5 m/s? And: What is the rotor diameter?

Wind Speed Distribution: Why the Mean Alone Isn't Enough

When someone says the wind at their site averages 5 m/s, that tells you surprisingly little. What matters is how often each wind speed actually occurs - the so-called frequency distribution.

Wind speed distributions are typically described using the two-parameter Weibull distribution, characterized by the shape parameter k and the scale factor A. The shape parameter k indicates how steady the wind is:

• k = 1.5-1.8: highly variable winds, typical of inland sites - many calm periods but occasional strong-wind episodes
• k = 2: the Rayleigh distribution, commonly used as the standard assumption across Europe
• k = 3: steady winds such as trade winds - rare in Central Europe

Why does this matter in practice? Because strong storms are rare, while moderate to fresh winds occur relatively often - which produces an asymmetric distribution of wind speeds.

The most important mathematical consequence: because power scales with v³, the mean wind power is always greater than the power at mean wind speed. For the Rayleigh distribution (k = 2), the exact relationship is:

Mean of v³ = 1.91 × (Mean of v)³

This factor of 1.91 is called the energy pattern factor. Leaving it out means underestimating annual yield by nearly half. At k = 1.5 the factor is around 2.4; at k = 3 it is around 1.4.

Two sites with an identical mean wind speed of 5 m/s but different k values will therefore deliver different annual yields. A reliable yield forecast requires not just the mean wind speed, but the full Weibull parameterization of the site.

Hub Height and Wind Shear: The Most Powerful Economic Lever

Wind is slowed near the ground by friction and obstacles. This phenomenon is known as vertical wind shear - wind speed changes continuously with height between the ground and the undisturbed air layers several kilometers above.

For practical purposes, the logarithmic wind profile is a good approximation over flat terrain:

v(z) = v_ref × ln(z / z₀) / ln(z_ref / z₀)

The strength of wind shear depends on the roughness length z₀ of the terrain:

The rougher the terrain, the more the ground slows the wind at low heights - and the more every additional meter of hub height is worth. Wind energy generation in inland areas with high roughness lengths therefore requires very tall hub heights.

Concrete example: A turbine is sited in farmland with hedges (z₀ ≈ 0.1 m). The mean wind speed at a reference height of 10 m is 4.5 m/s. Plugging into the logarithmic profile:

• Hub height 12 m: 4.5 × ln(12 / 0.1) / ln(10 / 0.1) = 4.5 × ln(120) / ln(100) = 4.5 × 4.788 / 4.605 = approx. 4.68 m/s
• Hub height 18 m: 4.5 × ln(18 / 0.1) / ln(10 / 0.1) = 4.5 × ln(180) / ln(100) = 4.5 × 5.193 / 4.605 = approx. 5.07 m/s

Six extra meters of mast height increase wind speed by roughly 8.5%. Since energy scales with v³, that translates to a yield gain of 1.085³ = 1.28, or about 28%. No other single investment in the turbine itself comes close to that kind of leverage.

For context: the effect is larger in rougher terrain and smaller in open terrain. At z₀ = 0.03 m (open field), the same jump from 12 to 18 m yields only about 21% more - the ground slows the wind less there, so there is less to recover.

Obstacles and Turbulence: Clearances That Matter

Buildings, trees, and terrain edges don't just create a wind shadow behind them - they also generate turbulence that stresses the rotor and reduces yield. Buildings, trees, and other obstacles in residential areas, towns, and settlements create turbulence and reduce wind speed, significantly impairing turbine performance.

Rules of thumb for clearance relative to the prevailing wind direction:

• Minimum clearance upwind of an obstacle: The turbine should be positioned at least twice the obstacle height in front of it - three times is better.
• Minimum clearance downwind of an obstacle: Maintain at least ten times the obstacle height of separation before the wind can be considered undisturbed again.
• Rooftop mounting: Rooftop installations of small wind turbines are often unsuccessful - not least because of poor wind conditions. A ground-based installation on a mast should always be preferred where possible.

Where to Get Wind Data

Step 1 - Initial orientation with wind atlases:

• DWD wind maps: Germany's national meteorological service (DWD) offers free wind maps available for download as PDF files, based on long-term measurement series from 170 weather stations. Useful for a first estimate, but the resolution is coarse and the data refer to 10 m height.
• Global Wind Atlas: Since 2015, the Global Wind Atlas has provided a worldwide, freely accessible source of regional wind statistics derived from reanalysis data via downscaling. Developed by DTU Wind Energy and the World Bank, freely accessible at globalwindatlas.info.
• State-level wind atlases: Bavaria, Baden-Württemberg, North Rhine-Westphalia, and other German states have published their own wind atlases, some at high spatial resolution.

Step 2 - Site-specific wind measurement:

Wind atlases have a spatial resolution of 1-3 km and cannot capture local effects such as hilltops, valleys, or clusters of buildings. Wind data from official databases describe the wind profile at greater heights from 50 m upward and are not sufficient to produce meaningful yield forecasts for small wind turbine operation.

For investments of roughly $20,000-$30,000 or more, a dedicated measurement campaign is economically justified. For a reliable and credible site assessment, a professional wind measurement campaign of at least 3 months - and preferably 6 or 12 months - is recommended in order to capture seasonal variation. Depending on the provider and measurement duration, the cost of renting and evaluating a professional measurement mast runs roughly between $3,000 and $10,000 - a manageable sum relative to the investment certainty it provides.

Complete Worked Example: From Wind Data to Dollar Yield

Assumptions (all stated explicitly):

Step 1 - Wind power at mean wind speed:

P(v_m) = 0.5 × 1.225 kg/m³ × 19.6 m² × (5.5 m/s)³ = approx. 2,000 W

This is explicitly not the mean wind power - it is only the power available at exactly 5.5 m/s.

Step 2 - Correction to actual mean wind power:

Because power scales with v³, the energy pattern factor must be applied:

P_mean = 2,000 W × 1.91 = approx. 3,820 W

Step 3 - Electrical output and annual yield:

P_el = 3,820 W × 0.20 = approx. 765 W

E_annual = 765 W × 8,760 h = approx. 6,700 kWh/year

Cross-check: 6,700 kWh divided by 5 kW rated power gives roughly 1,340 full-load hours, corresponding to a capacity factor of 15%. That is a plausible figure for a 5 kW turbine at a mean annual wind speed of 5.5 m/s - and it is consistent with the table at the start of this article, which shows approximately 5,000 kWh at 5 m/s and approximately 8,700 kWh at 6 m/s for the same turbine.

Step 4 - Self-consumption and financial benefit:

• Self-consumption: 6,700 kWh × 70% = 4,690 kWh -> savings: 4,690 × $0.30 = $1,407/year
• Grid export: 6,700 kWh × 30% = 2,010 kWh -> feed-in revenue: 2,010 × $0.074 = $149/year
• Total annual benefit: approx. $1,556/year

This figure deserves an honest assessment: even in this comparatively favorable scenario - a good site, a high self-consumption share, a high electricity price - an annual benefit of roughly $1,550 must be weighed against the full investment in turbine, mast, foundation, grid connection, and permitting. The payback period therefore extends well beyond ten years. At lower wind speeds or a lower self-consumption share, it can easily exceed the turbine's service life.

The key factors for the economic viability of a small wind turbine are mean wind speed at hub height, a high-yield wind generator, and a high self-consumption share. Anyone who cannot consume the wind-generated electricity on-site should scrutinize the investment carefully: operating a small wind turbine profitably on feed-in revenue alone is not feasible.

Interactive Yield Calculator

Common Mistakes in Yield Forecasts - and How to Spot Unreliable Quotes

Mistake 1: Confusing rated power with yield

For small wind turbines, rated power is not a sufficient basis for comparison, since turbines with the same rated power can deliver very different annual yields. Rotor swept area is the decisive factor. Comparing only the kilowatt figure is buying a pig in a poke.

Mistake 2: Estimating wind speed by gut feeling

Be cautious about "felt wind" at your own property - it can be deceptive. Gusts you notice are not a mean annual wind speed. Reliable numbers require measured data.

Mistake 3: Uncritically accepting atlas wind speeds

Wind atlases can overestimate local yields. Feeding atlas figures directly into a yield forecast without site-specific corrections risks a significantly over-optimistic projection.

Mistake 4: Treating rooftop installation as a solution

Many prospective buyers think in terms of solar panels and prefer a rooftop installation. For wind energy, however, this positioning is frequently disadvantageous - building structures generate turbulence that impairs rotor performance.

Mistake 5: Applying the energy pattern factor twice - or not at all

A common calculation error is to multiply the power at mean wind speed by 8,760 hours and then apply a capacity factor on top of that. This double-counts a deduction that should only be made once. Conversely, omitting the factor of 1.91 leads to an underestimate of nearly half. The correct approach is: mean wind power (with energy pattern factor) × annual efficiency × 8,760 h.

How to spot unreliable quotes:

• Annual yields are quoted without stating the underlying wind speed assumption
• The stated wind speed for an inland site at 10 m height is 6 m/s or above - in most regions, that is the exception, not the rule
• An energy ratio is quoted that does not correspond to the cube of the speed ratio (8 m/s versus 6 m/s is 2.37× - not 3× and not 3.4×)
• No power curve or independently verified yield data is provided
• Full certification to the international standard IEC 61400 can cost over $200,000 per turbine - many small wind turbine manufacturers cannot afford this, which results in a market with limited transparency. Ask which tests and certifications are available.

Conclusion: What Really Matters

The question "How much power does a wind turbine produce?" has no universal answer - but it does have a clear methodology. Anyone who understands the three decisive levers - wind speed at hub height, rotor swept area, and self-consumption share - can calculate realistic yields and evaluate quotes critically.

A sound investment decision requires site-specific wind data, the power curve of the specific turbine, and an honest assessment of self-consumption potential. Everything else is speculation.

Further reading: Small wind turbine costs overview · Running a wind turbine at home · Vertical wind turbines: technology and applications · Off-grid wind turbines: buyer's guide · Garden wind turbines: a reality check

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