Publisher of Humanities, Social Science & STEM Books
Wind Farm Vector

How to Select a Location for a Wind Farm

Posted on: September 30, 2019

By: Vaughn Nelson, Kenneth Starcher

Electricity from a wind farm is now amongst the cheapest forms of renewable energy and less expensive than that produced by new coal and nuclear power plants. As installations have increased, capacity has grown at an average rate of 28% per year from 1995 to 2012, and 14% per year from 2013 to 2017.

The numbers for wind power to date and for the future are astounding. Capacity is expected to reach 600 GW in 2019 and grow to around 1,000 GW by 2030 to meet the goals for wind power set by China, Europe, and the United States.

wind turbine

Siting a Wind Turbine

The crucial factor in siting a wind farm (also called wind park or wind plant) is the annual energy production and how the value of the energy produced compares to other sources of energy. Using long-term is data therefore critical. Data should be collected at a potential site for 2–3 years, after which other questions arise:

  • What is the long-term annual variability?
  • How well can we predict the renewable energy production?

wind power

Data on Wind Power

To determine whether historical data from a site is adequate to describe long-term wind resources at another site, a rigorous analysis should be done. The annual hourly linear correlation coefficient should be at least 0.90 between the reference site and off-site data. Wind shear must also be factored in if the heights are different at the two locations. If the two sites do not exhibit similar wind speed and direction trends and lack similar topographic exposures, they will probably not have sufficient correlation value.

These wind power stations should continue to collect data even after a wind farm is installed. The data improves siting of a wind farm and also provides reference sites for delineating wind resources for single or distributed wind turbine in the region.

renewable energy

Renewable Energy Production

The number of met stations and duration of data collection to predict the energy production for a wind farm vary depending on the terrain and the availability of long-term base data in the vicinity. In general, numerical models of wind flow will predict wind speeds to within 5% for relatively flat terrain and 10% for complex terrain, which means an error in energy of 15–30%. A wind measurement program is therefore imperative before a wind farm is installed. However, if a number of wind farms are already in the region, one year of data collection may suffice.

For complex terrain, one met station per three to five wind turbines may be needed. For more homogeneous terrain, a primary tall met station and one to four smaller met stations may suffice.

The money spent on micrositing (siting of wind turbines over an area the size of a wind farm, about 5–20 km2) is a small fraction of project cost, but the value of the information gained is critical for estimating energy production accurately. Many problems with low energy production are the results of poor siting.

wind farm

Siting a Wind Farm

Wind power is now amongst the cheapest forms of renewable energy. Learn more about the critical factors in siting a small wind turbine to a large wind farm including examples from recent case studies.

Get Started

wind speed

Digital Maps on Wind Speed

Digital maps are useful for siting a wind farm as they give a general overview of wind resource, provide confidence in the data, and provide information about land use and transmission lines, and other features can easily be displayed on the same maps.

  • Wind Site Assessment Dashboard (formerly Windnavigator), a web platform based on Google Maps, is an interactive tool that includes wind resource maps and world data. The map provides wind speed data at custom height of 10–140m and a pointer to locate the minimum and maximum mean annual wind speed.
  • Vaisala provides a similar interactive wind resource map (map, satellite, hybrid, and terrain views) and data for much of the world, which features wind speed data for 20, 50, and 80m and with Wind GIS Data Layers, resolution is at 90m.

Remember that wind speed maps provide useful indicators of wind energy, and wind power maps are the next step.

geographic information systems

Geographic Information Systems (GIS)

A Geographic Information System is a computer system capable of holding and using spatially oriented data. Geographic Information Systems typically link different data sets or display a base set over which overlays of other data sets are placed. Information is linked as it relates to the same geographical area. GIS mapping is an analysis tool, not simply a computer system for making maps.

Geographic Information Systems allows a user to associate information with a feature on a map and create relationships that can determine the feasibilities of various locations, for example, a hierarchical system for locating anemometer stations for wind prospecting.

wind forecasting

Wind Forecasting

Numerical models for predicting winds are becoming more accurate and useful, especially for areas of the world where surface wind data are scarce or unreliable. When using them, it is important to keep in mind that a small difference in wind speed can make a large difference in renewable energy production. In the final analysis, surface wind data is still required for wind farms.

  • MesoMap: This system was developed specifically for near-surface wind forecasting. It uses historical atmospheric data spanning 20 years and a fine grid (typically 1–5 km).  The model provides descriptive statistics utilizing wind speed histograms, Weibull frequency parameters, turbulence and maximum gusts, maps of wind energy potential within specific geographical regions, and even the annual energy production data for a wind turbine of any height for selected sites in a region.
  • WAsP: The Wind Atlas Analysis and Application Program software was developed by Denmark’s Risoe National Laboratory to predict wind climate and power production from a wind turbine. The predictions are based on wind data measured at stations in the region. The program includes a complex terrain flow model.

wind farms

Micrositing of Wind Farms

Wind maps, data compiled by meteorological towers, models, and other criteria are used to select wind farm locations. Further considerations for a wind farm developer are the type of terrain (complex to flat plain), wind shear, wind direction, and spacing of wind turbines based on predominant wind direction and availability, land cost, and requirements such as roads, turbine foundations, and substations. In complex terrain, such as mountains and ridges, micrositing is particularly important.

Satellite and aerial images are used in micrositing and are available from various sources; some are free. Zoom Earth has the option of switching among sources, such as Google Maps, Microsoft VE, and others. Although micrositing techniques of wind farm developers are proprietary, satellite images show the layout of wind farms, and can provide good information about siting from the images and topographic maps.

Economic and institutional issues also affect micrositing. An example is the Waubra wind farm project in Australia, which involves environmental, cultural, heritage, and environmental management issues. Since installation, many residents have expressed opposition, claiming health effects caused by wind farms.

offshore wind

Offshore Wind

Ocean wind observations provide complementary sources of information for siting of a offshore wind farm. The advantages of ocean wind maps are:

  • Some satellite wind maps are public domain
  • All offer global coverage allowing observation of large areas without large numbers of meteorological towers
  • All are accessible in archives spanning several years
  • Accuracy is sufficient for wind resource screening
  • They quantify spatial variations
  • They are available at resolutions of 400m, 1.6m, and 0.25 degree
  • Software has been developed for their use

The major problems with ocean winds are:

  • Data are for 10m height and values of wind shear are not known
  • Standard deviations are around 1.2 to 1.5m/s on mean wind speed
  • Data are not available or not as reliable within 25 km of shore


Geographic Information Systems provides very flexible and powerful tools for terrain analysis relevant to wind energy prospecting. They can help reclassify existing wind maps and identify areas showing potential as possible wind farm sites. In addition, Geographic Information Systems can be used to quantify wind power potential and, in conjunction with numerical models, estimate annual energy production.

After a location is selected, Geographic Information Systems and topographical maps can be used for micrositing. Wind turbines should be located within a wind plant area to maximize annual energy production.

This article was cited from Wind Energy: Renewable Energy and the Environment, 3rd Edition, by Vaughn Nelson and Kenneth Starcher.