Community Wind Handbook/Assess Your Wind Resource
Assess Your Wind Resource
The wind resource at the selected site needs to be characterized and understood at a level of detail and confidence appropriate to the project's development stage. Preliminary resource assessment can be conducted early in the development process to validate the investment of time and money for an onsite measurement campaign. While an onsite measurement campaign may be started relatively early in the development process, it is referred to as late-stage resource assessment in this handbook.
As an initial step, state and regional wind maps or other forms of modeled wind data can be used to estimate the resource in your region. WINDExchange offers a variety of wind maps, including 80-meter high-resolution maps. They are a starting point for large community wind project resource assessments due to their high level and coarse resolution.
There are pros and cons associated with state and regional wind maps as they may be accurate for locations with relatively simple terrain (e.g., no trees or other obstructions) and areas with ample validation data, but they can be less accurate for areas with complex terrain and little data. Although state and regional wind maps are useful, they are not accurate enough to replace onsite measurements (see below for more on this topic).
Large-scale computer weather forecasting is an additional form of modeled wind data that can be used as part of a resource assessment. These models are based on historical data and are designed to predict wind conditions at a specific site. Forecasts of a site’s wind resource can be less expensive than conducting onsite data collection for a year or more, but measured, on-site wind data assessments are generally considered to be the most reliable way to evaluate a site's wind resource.
Site-specific data collection confirms the modeled data provided by wind maps and publicly available wind data from nearby locations. Note that publicly available data could have been collected at heights different from your planned turbine’s hub height.
If your preliminary site assessment indicates a strong wind resource, you have considered the preliminary siting characteristics (including land ownership profile and interest), and you want to move forward with a large community wind project, the next step is to conduct a thorough resource assessment. Understanding the wind resource of your site is critical because it will determine whether it is worth your time and effort to move forward with the project.
Because the investment for a large community wind project is substantial and most likely will involve some form of outside funding (e.g., bank loan, investors), it is critical to ensure that your resource assessment is thorough and uses industry best practices. Measured wind data assessments can be conducted using one of three methods: installing anemometers on meteorological towers (“met” towers), using Sonic Detection and Ranging (SODAR), or using Light Detection and Ranging (LIDAR).
One method of assessing wind resources involves installing anemometers on “met” (meteorological) towers. The number of met towers depends on the complexity of the terrain and the size of the wind project. Most community wind projects involve only one or two turbines, so one met tower should suffice.
The ideal approach to equipping this type of monitoring system is to install anemometers at various heights corresponding to the entire swept area of the rotor at hub height, one at the lowest height the tip of the blade reaches and another at the highest point that the tip reaches. However, due to the high tip heights of utility-scale turbines, it is often impractical to install a met tower this high.
Towers between 50 and 60 meters can be equipped with as many as three anemometers (though two can be used in a minimal equipment scenario) to measure the wind resource for your community wind project. Taller towers (80 meters) can be equipped with as many as four anemometers if a developer determines it is necessary.
Your met tower should also be equipped with a calibrated wind vane located on a boom at the same height as the main anemometer and a data logger housed in a waterproof case and located at the base of the tower. Additional equipment can include a temperature and pressure gauge located at a lower height than the anemometer and supplemental wind vanes and anemometers to ensure accuracy.
Costs associated with the purchase, installation, and 2-year operation of a 50-meter to 60-meter tower plus equipment is between $50,000 and $70,000. The costs increase substantially if you select an 80-meter tower, to $170,000 to $190,000.
SODAR and LIDAR
As the cost of remote sensing devices decreases and the technology's accuracy and reliability improve, SODAR and LIDAR could be used as alternatives to traditional met towers. These two methods are capable of measuring wind characteristics above anemometer tower heights. 
Validate the Wind Resource Assessment Data
Data from the wind resource assessment will need to be validated during the resource measurement campaign. Validation can be conducted monthly, quarterly, or annually and should ensure that the data are complete and reasonable, as well as to detect invalid or potentially suspect values within the data collection.
Wind resource assessment data validation and analysis can be conducted with software from data logger vendors or through commercial software. A manual review is also recommended. For more information on data validation, see Section 9 of NYSERDA’s Wind Resource Assessment Handbook. It is important to speak with the project financer to see what information will be required to prove the potential of your wind resource.
At a minimum, the collected data include wind speed and wind direction, almost always at multiple heights. Temperature data are useful and are usually collected as well. Less frequently collected but still of use are barometric pressure and rain data. The industry standard is to sample the data at least every 2 seconds (0.5 Hz) and to record 10-minute average, standard deviation, high reading, and low reading. Common statistics that can be derived from analysis include mean wind speed, wind shear, turbulence intensity, mean air density, speed frequency distribution, diurnal average wind speed, wind rose, and daily and seasonal speed distributions.
Studies have shown that under- or over-estimating the mean wind speed, turbulence intensity, or vertical wind shear at a given site can have a serious impact on turbine loads, resulting in increased maintenance costs and reduced lifetime for each turbine.
A variety of factors can influence the uncertainty of a wind resource assessment, so it is vital to account for individual sources of error to gauge the total uncertainty of a project. The uncertainties of a project’s wind resource, power curve, and energy losses must be combined to determine the overall annual energy production uncertainty. This is essential in estimating the risk associated with a large community wind project.
Many uncertainties can arise when measured wind resource data are extrapolated to estimate the long-term wind resource at a site. Even though wind resource measurements are typically conducted over a year or more, the data from those particular years may not characterize the actual long-term resource at the site. Generally, the long-term resource of a site is represented by a 20-year period. To reduce the uncertainties associated with extrapolating measured data, long-term data from a nearby site are used in a process called measure-correlate-predict (MCP) to estimate the long-term wind resource for a project.
Long-term data are integral in determining whether measured wind data are representative of a low-, medium-, or high-wind year, allowing for adjustments to a project’s long-term production estimate. Long-term data can sometimes be found from nearby airports or weather stations.
Understand Bankability and the Wind Resource
Bankability, the idea that a given project is worthy of investment, is a concern that can be addressed by conducting a resource assessment that meets or exceeds lender standards. Most financial institutions require onsite data collection for a minimum of 1 to 2 years prior to committing financial resources to a project.
- "National Renewable Energy Laboratory. A Framework for Project Development in the Renewable Energy Sector"
- "New York State Energy Research Development Authority. Wind Resource Assessment Handbook"
- "Windustry. Community Wind Toolbox, Chapter 4: Wind Resource Assessment"
- "Energy Trust of Oregon. Community Wind: An Oregon Guidebook"
- "Germanischer Lloyd Renewables Consulting & Engineering. The Impact of Site Conditions on the Turbine Suitability"
- "Renewable Energy Research Laboratory, University of Massachusetts, Amherst. Uncertainty Analysis in Wind Resource Assessment and Wind Energy Production Estimation"