Affordable Site Assessments for Small-Scale Wind Power Projects

Wind power is a gamble if the project site is not assessed properly prior to the installation of wind turbines; two identical units can have very different outputs depending on their locations. A very important factor that defines if the project makes sense from the financial standpoint is capacity factor – the percentage of maximum possible output the project will yield.

• A year has 8,760 hours, and if a 2-megawatt wind turbine could operate at full power all year long, it would produce 17,520 MWh of energy. Of course, this does not happen in real life because wind speed is variable and sometimes drops off to zero.
• At a capacity factor of 30%, this project would produce 5,256 MWh/year.
• On the other hand, at a capacity factor of 20%, the output is 3,504 MWh/year.
• Finally, a capacity factor of 10% would mean producing only 1,752 MWh/year.

If this project was developed by an industrial energy consumer who saves 80 £/MWh, for a total installed cost of £2.2 million, the financial attractiveness would vary significantly depending on the capacity factor.

Table 01. How capacity factor influences the financial performance of wind power.

This is just an example, but it clearly explains how the capacity factor can make or break a wind power project. Capacity factor can only be calculated precisely with a site assessment.

Since wind conditions have a considerable impact on wind power projects, utility-scale developers carry out extensive measurements before proceeding with any installation. On-site anemometry is normally carried out for periods of up to three years, but given the stakes in a project of this magnitude, these assessments are a small price to pay. However, the same cannot be said for a small-scale project, where carrying out a site assessment like those of utility-scale projects has a prohibitive cost. Hence, a different approach is needed.

Reducing the Cost of a Wind Power Site Assessment

There are three main ways to reduce the cost of site assessments for small-scale wind power:

• Ruling out unfavorable sites based on historic weather data, whenever possible.
• Reducing the timeframe of wind speed measurements.
• Using affordable measurement equipment, such as WindLogger stations.

With this approach, the project assessment cost can be reduced significantly compared to that of a utility-scale wind farm.

Pre-Screening Project Sites

Wind site assessments based only on historic wind data (no measurements on-site) do not provide enough accuracy for concluding that a site is suitable for wind power. However, historic wind data can still be useful: Prospective sites that are obviously unfavorable can be ruled out without measurements, saving time and reducing costs.

Pre-screening reduces the number of field measurements required to determine optimal sites for wind power. Perhaps some unsuitable sites will remain undetected until the measurement phase, but the pool of potential locations becomes smaller and cheaper to assess.

Wind Measurements for Remaining Sites

Once the pool of possible project sites has been reduced, the remaining sites can be assessed with direct measurements. There is still a chance of wasting time by carrying out measurements at sites that appeared promising at first but were unfavorable, although the total number of sites will have already been filtered down by this point.

Although site measurements for utility scale projects typically last from one to three years, the University of Leeds carried out a study in 2014, where they could successfully predict wind turbine performance in small-scale sites with only three months of logged data.

In general, the two main factors to assess in any prospective site for wind power are the following:

• The wind speed distribution, which describes the frequency of several wind speed values over a specified timeframe. These measurements can then be used to calculate the expected power output of a wind turbine.
• The wind rose, which describes the dominant directions in which the wind blows.

When these data are combined with power curves provided by the manufacturer, it is possible to estimate wind turbine output with accuracy. This then serves as a basis for financial projections, based on which the project owner can decide to install the turbine. Wind speed is the single most important metric to assess, since it has a cubic relationship with output power – just a 10% increase in wind speed boosts the theoretical output power by 33%.

WindLogger builds upon the experience of Logic Energy, a provider of weather and energy monitoring solutions a track record of more than a decade. Our technology comes with GSM/GPRS capabilities to communicate from any potential project site, and is factory configured to offer a plug-and-play solution with data backup at out cloud servers.

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