Wind Farm Capacity Factor Calculator
Calculate the capacity factor of a wind turbine or wind farm, the fraction of its theoretical maximum output that was actually delivered over a period. It is the single most important metric for comparing real-world wind project performance.
Last updated: May 2026
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About this calculator
Capacity factor is defined as actual energy produced divided by the energy the same equipment would produce running at rated power for every hour of the year, expressed as a percentage. The formula is CF = (E_actual / (P_rated * 8760)) * 100 percent, where E_actual is the measured energy in MWh, P_rated is the nameplate capacity in MW, and 8760 is hours per year (use 8784 in a leap year). A capacity factor of 35 percent means the wind farm delivered 35 percent of what it could have produced if running flat-out continuously, equivalently, it ran at average power equal to 35 percent of nameplate. Modern onshore wind farms typically achieve 30 to 45 percent depending on site quality and turbine design; offshore farms reach 40 to 55 percent; older sub-MW turbines often sat at 20 to 25 percent. The metric absorbs every loss in the system: poor wind years, low cut-in winds, curtailment by the grid, mechanical downtime, blade soiling, array wake losses, and electrical losses through cables and substations. Edge cases: a CF above 100 percent indicates either an input error or that you are measuring over a period shorter than a full year where wind happened to be unusually strong and the formula should use that period's hours, not 8760. CF below 15 percent indicates a marginal site or a poorly matched turbine. CF is not the same as availability (the fraction of time the turbine was technically able to run) or efficiency (Cp); a turbine can be 100 percent available and still produce a 25 percent capacity factor if the wind is weak.
How to use
Example 1: A single 1.5 MW turbine produced 2,500 MWh last year. Compute capacity factor: 2,500 / (1.5 * 8,760) = 2,500 / 13,140 = 0.1902 = 19.0 percent. This is below the 25 percent rule-of-thumb for viability, so either the site is marginal, the year was poor for wind, or the turbine had significant downtime. Investigate before drawing conclusions; one year is short. Example 2: A 200 MW offshore wind farm produced 880 GWh in a calendar year. Compute: 880,000 MWh / (200 * 8,760) = 880,000 / 1,752,000 = 0.5023 = 50.2 percent. That is excellent and typical of a high-quality offshore site in the North Sea or U.S. East Coast. Verify by working backwards: 200 MW * 50 percent * 8,760 h = 876,000 MWh, matching within rounding. If your number is suspicious, compare with industry benchmarks: U.S. onshore averaged 35 percent in 2023, the U.S. offshore early projects 45 to 55 percent, mature European offshore 50 to 55 percent.
Frequently asked questions
What is the difference between capacity factor and turbine efficiency?
Capacity factor and turbine efficiency measure entirely different things and should never be confused. Turbine efficiency (the coefficient of performance, Cp) is the fraction of the kinetic energy in the wind passing through the rotor that the turbine converts into electricity at any given instant; it is a property of the machine, capped at the Betz limit of 0.593. A modern utility turbine has Cp about 0.45 at its operating sweet spot. Capacity factor is the fraction of the rated nameplate capacity actually produced over a long period; it is a property of the site, the wind year, downtime, curtailment, and the match between the turbine and the local wind distribution. A turbine can be 45 percent efficient (high Cp) yet produce only a 25 percent capacity factor if the site has weak average winds. Conversely, a turbine with modest Cp can deliver a 50 percent capacity factor if the site is windy and the rated power is matched to the wind regime.
What is a 'good' capacity factor for a wind project?
It depends heavily on the type of project and the era. Modern onshore wind in good U.S. or European sites achieves 35 to 45 percent; very best sites in the U.S. Great Plains or coastal Brazil approach 50 percent; the average across the U.S. fleet was 35 percent in 2023, up from about 26 percent in 2010 because newer machines have larger rotors and taller towers. Offshore wind typically delivers 40 to 55 percent, with frontier projects in the North Sea hitting 55 to 60 percent. Distributed and small wind frequently runs 15 to 25 percent because rotors are small, towers are short, and siting is constrained. As a rule of thumb, anything below 25 percent for a modern utility project is marginal economically, 30 to 35 percent is the typical break-even point with current power prices, and above 40 percent is excellent. Older 1990s turbines achieving 20 to 25 percent were considered fine; the bar has risen with machine improvements.
Why might capacity factor differ between two identical turbines on adjacent sites?
Even neighboring turbines can see very different capacity factors because wind resource is highly variable across short distances and because of wake effects in wind farms. Local terrain such as a hill, a forest, or a row of buildings can reduce mean wind speed by 10 to 20 percent over distances of only a few hundred meters. Because energy scales as the cube of wind speed, that small terrain effect becomes a 30 to 50 percent swing in energy. Inside a wind farm, turbines downstream of others sit in the wake of those upstream and see slower, more turbulent wind; depending on layout and spacing, wake losses can cost 5 to 15 percent of annual energy across a project, and individual machines in the worst positions can lose 20 to 25 percent. Other reasons for differences include differing tower heights, different commissioning dates (one of the turbines might have been down for a maintenance event), grid curtailment that hits only some machines, or icing or soiling that varies across the site. Even electrical hookup order along the collection cable can produce small but persistent differences in measured net output between identical machines.
When should I NOT use capacity factor as the headline metric?
Do not use capacity factor when comparing projects of different technologies (wind vs. solar vs. baseload). A 35 percent wind capacity factor and a 25 percent solar capacity factor are not directly comparable because they describe different generation profiles: wind is variable across hours-to-days, solar across diurnal patterns. Do not use capacity factor in isolation to judge project economics: a high-CF project with a high installed cost or low power price can be less profitable than a lower-CF project with cheaper construction and a premium PPA. Do not use it to assess grid value or capacity credit; those depend on when the power arrives, not on the annual total. Do not draw conclusions from a single calendar quarter; wind has strong seasonality, and a winter quarter will show a different CF than a summer quarter. Always report alongside the period covered, the rated capacity used, and ideally a multi-year average.
What are the most common mistakes when calculating capacity factor?
The two biggest mistakes are (1) using the wrong period length and (2) using the wrong rated capacity. If you are computing capacity factor for a month, use 720 or 744 hours, not 8,760. If your wind farm was commissioned in May and you are computing the calendar year, prorate by the actual operating hours since commissioning. The second mistake is to use installed capacity that does not reflect what was actually in service: if the farm has been derated for grid constraints, or two turbines were down for the whole period, the 'rated capacity' should reflect the available fleet, not the nameplate. A third subtle error is to use gross energy production (before transformer and line losses to the grid connection point) when investors and benchmarks expect net production at the meter, or vice versa. Document carefully which definition you used. Always confirm whether your reported figure is gross or net, single-year or multi-year, and based on actual or nameplate capacity.