The wind resource

According to the European Wind Energy Association (EWEA)[23], the UK has the best wind resource in Europe, an asset that has the potential to provide a considerable proportion of the UK energy market in years to come. Nevertheless, this does not mean that every wind project will produce satisfactory outputs. In order to design buildings that harness wind power it is not sufficient to understand how a wind turbine operates from a technical point of view. It is just as important to be able to estimate the wind resources at a specific site: the energy content of the wind should always be the basis for a wind power project.

For example, suppose that the wind speed at the design site is assumed to always be 5m.s71; the annual energy content of the wind can be calculated with equation

, and it would be:

/year

kWh/m

864

=

=

E

This is a simplistic approach that does not reflect the real life wind patterns, the wind speed and direction change continuously during the day, in different seasons and even between years.

In order to calculate the power density at a specific site it is necessary to calculate the average power density. This is done by averaging the cube of the recorded wind velocities. Yet the average wind speed can only partly describe the potential of a site, because the energy content of the wind does not depend linearly on the wind speed and it is thus necessary to know the different wind velocities that occur at the site and their duration, this is called the frequency distribution of wind speeds.

To obtain better estimates of the power density, the calculations of the energy content of the wind during one year using the frequency distribution are carried out using the cubes of the wind velocities, multiply these by the frequency and then adding these values. The result of this calculation is then substituted in the value of u in equation XIII. ( ) kWh/m2/year 1000 8760 v 0.625 = = × × E

Alternatively, a cube factor can be added when using equation to calculate the energy content during a year if the mean speed is known but not the frequency distribution. A cube factor value of 1.91 can be used for places in mid latitudes, the USA and most parts of Europe[18]. This factor depends on the frequency distribution of the wind and for places with trade or seasonal winds other values should be used. The most effective way to produce acceptable and detailed information about the energy content of the wind at the design site is to carry out a series of readings. This is carried out by installing wind measurement equipment that record wind speed and direction dataXIV, preferably at the hub height of the turbine intended for the site.

Nevertheless, wind speed and frequency distribution vary significantly during different years; this is why examining long term averages provide less variations in the data, which is better from a statistical point of view. It is often however, not

XIII

Note that equations 2.5 and 2.6 differ on the value of wind velocity, one being cube (u3) and the other one linear (v) respectively.

XIV

Wind velocities are measured using and anemometer and wind directions are registered by a wind vane.

practical to measure wind conditions over periods of five years or more in the specific site where the wind turbines would be sited.

This is why one approach is to take the nearest meteorological station that has long term average records as a reference site. The station must be representative for the regional wind profile at the design location. Usually, a correlation is valid only between sites having the same shape of wind speed distributionXV.

Alternatively, commercially available computer7based prediction toolsXVI can be used to give a slightly more refined indication of site wind speed, like the computer model of the UK wind energy resource developed by the DTI[24].

It is clear then that electricity production obtained from a wind potential with a given wind speed and wind turbine type, varies a lot with the wind speed distribution around the mean value. Wind speed distributions are commonly used to indicate the annual available wind energy. Therefore, it is essential to know the distribution of wind speeds on the project siteXVII.

For this study, wind data for Nottingham, UK. were obtained as a Test Reference Year (TRY) file[26]. The Test Reference Year consists of hourly data for twelve typical months, selected from approximately 207year data sets (typically 198372004), and

XV

The frequency distribution of the wind has proved to fit quite well to a probability distribution called the Weibull distribution and to the Rayleigh distribution, which is a special case of the former[25]. XVI

There are several different computer programs for wind power applications, based on the wind atlas method, like the Danish WAsP and EMD or the British WindFarm and WindFarmer[18]. Nevertheless, the developer of WaSP has expressed his concerns regarding the software being applied for physical and statistical estimates of wind speeds in the built environment; stating that given the complexity of the flow patterns, he would not expect good results[27].

XVII

As general indication, in the UK, it is possible to obtain an assessment of the average wind speed at a particular site, by using the UK wind speed database, available at www.bwea.com.

smoothed to provide a composite, but continuous, 17year sequence of data. These data show the probability of maximum gust velocity likely to occur at a height of 10m and lasting for 3 seconds.

In order to manage these data, the TRY file was exported to ECOTECT V.5.2 software to be later analysed with the Weather Tool of the same software.

Table 2.1 shows the frequency distribution for Nottingham, UK. It can be appreciated that the prevailing winds approach from South7West and West orientations (202.5° <θ <270°). Figure 2.5 illustrates the frequency distribution of wind speeds for those orientations (SW, SSW, WSW and W). The most frequent wind speeds are in the range of 3 to 5.5m.s71; 3.9% of the time the wind speed is 2.8m.s71 and the mean wind speed coming from those orientations is 4.4m.s71.

Using this frequency distribution of wind speeds, the energy content during a year for Nottingham, UK can be calculated with equation , resulting in a power density of 97.14 W.m72, or a total energy content of 851 kWh/m2/year.

How efficiently this power of the wind is utilized – i.e. converted to electricity – largely depends on the type of wind turbine to be used and its chosen siting location. Therefore, it is crucial to have a broad understanding of wind turbine basics.

Frequency distribution of wind speed for different orientations in Nottingham, UK.