Tremendous wind energy resources exist in India and abroad. For example, it is estimated that the wind resources in the Pacific Northwest of the United States could theoretically provide the entire world’s power supply. Other places around the world also have significant also.

Wind Power is now considered as one of the best of the Alternative Energy strategies. The cost per unit is now becoming competitive with traditional coal fueled sources of energy, although it cannot yet match the present low cost of natural gas (LPG). Further innovations in wind energy power generation technology, along with the rising cost of fossil fuels is driving wind energy production costs

Near the tropics, ascending moist air rises and moves towards the poles. As it moves away from the equator, it cools and loses moisture (causing rain in the process).

As the air descends, it heats up and retains more moisture, causing the cycle to sustain itself.

This process repeats over different latitude ranges, as well as at the poles. The addition of the earth’s rotation causes the following overall wind pattern to occur.

## Windspeed vs. Time

Average wind speed is the most important element of wind power design. However, wind speed varies dramatically over time. It is constantly changing direction and speed, even on a second to second basis. For this reason, data logging over an extended duration of time is essential to smooth out the irregularities in speed and direction. This gives a more accurate profile of the wind at a particular site.

## Wind Speed vs. Height Estimations

The wind speed varies greatly with height and the surface characteristics. Many atmospheric measurements are taken at the standardized height of 10 meters. This is just above the tops of the trees in many places.

There are two general methods of estimating wind speed versus height.

__Method 1:__

v(h2)/ v(h1) = (h2/h1)^ (1/7)

where h1 and h2 are two different heights (h2 > h1).

This is the simpler formula, which is mostly valid for smooth terrain, such as near water. There are some particular cases in which this formula is not valid, such as valleys in which wind are accelerated.

__Method 2:__

There is a more complicated but also more accurate wind speed estimation formula, which is based on the natural logarithm.

v2/v1 = (ln(h2/z0))/(ln(h1/z0)),

where z0 is the roughness factor, which has the following coefficients according to the type of surface the wind is flowing over:

· Class 0 – Water – 0.0002 (meter)

· Class 1 – Open land – 0.03 (meter)

· Class 2 – Farmland – 0.10 (meter)

· Class 3 – Urban and obstructed rural – 0.4 (meter)

It should be noted that the lengths shown above do not correspond to the lengths of physical objects.

Combining the facts that wind power increases with the cube of the wind speed (covered in the Wind Turbine Virtual Lab) and the present result, that the wind speed increases substantially with height, yields the result that the power output of a turbine increases dramatically when the turbine height above ground increases. Again, this depends on the location and wind speed profile both in time and height.

This is the reason that the modern turbines are placed so high above the ground, in which the turbine hub height is as much as 70 meters.

An additional benefit is that large wind speed spikes can significantly contribute to the average power output. However, the turbine design must be optimized to handle these spikes.

## Practical Wind Speed Assessment Tips

Wind speed knowledge is important for turbine design, efficiency, and optimization. Because of the large importance of knowing the wind speed profile for selecting the turbine to be installed, it is suggested that measurements be taken at different heights for 1 year. The various heights frequently monitored are the wind turbine hub height, and the hub height plus and minus the blade length.

Optimum wind power placement is above flat terrain with the smoothest possible surface before the turbine (from the wind’s perspective). Near Ocean bodies are typically the best.

## Site Assessment

The first step in assessing a site for suitability for wind power production is to analyze the available wind resources. Wind energy varies greatly with location and height. A wind sensor, called an anemometer, measures the velocity and direction of the wind stream being monitored.

While wind resource data is available in various online databases, these databases only cover macro solar data, for example data gleaned from orbiting satellites, or data from specific monitoring points, such as from installed metrological weather stations, which do not always provide information relevant to the particular site that is being assessed. For example, buildings, trees, height, nearby water bodies and many other factors may affect the locally available wind power.

This Virtual Lab experiment is designed to teach the process of actual, applied wind energy site assessment using modern data acquisition systems and the relevant data post-processing techniques. At the end of this experiment, the student will have the necessary skills to analyze wind data for a real-world assessment of a site for wind energy production.

## Kinetic Energy and Wind Energy Density of an Airstream

The Kinetic Energy of a stream of wind is given by:

KE = ½ mv2 = ½ ρ (AΔx) v2,

where ρ is the air density, A is the cross section area of the stream, and Δx is in the direction of wind movement (mass = density * volume = density * area * delta length = ρAΔx).

Then the Wind Energy Density, Pw, is given by the derivative of KE with respect to time, divided by the Area

Pw = dKE/dt * (1/A) = ½ ρ A (Δx/dt) v2 *(1/A)

Pw = ½ ρ (dx/dt) v2 = ½ ρ v v2 = ½ ρ v3

**P**_{w }= ½ **ρ v**^{3} (watts/meter^{2})

Also, it’s important to note that the density of the air changes with temperature

**ρ = P/(RT,) (kg/m3)**

where P = Pressure, R = the Gas Constant, and T = Temperature**. **The air density, ρ, is frequently assumed to be constant at sea level and equal to 1.2929 kg/m^{3}.

## The Practical Aspects of Wind Energy Density

As shown above, the Wind Energy Density is proportional to the cube of the wind speed. Therefore, a 3-fold increase in wind speed corresponds to a 27-fold increase in Wind Energy Density. This means the wind speed peaks contribute more to the average wind energy density than the dips in wind speed take away from it.

Similar phenomena as with cars – doubling the speed requires increasing the HP by a factor of 8.

This is why racing cars may have so much more power (800 hp +), 4 to 8 times as much as a normal car, but only go 2 or 3 timesfaster. (Other factors affecting the equation are reduced mass, altered aerodynamics, and the need for high acceleration capability).

The previous equation, Pw = ½ ρ v3 (watts/meter2), means that the available power generating capacity of the wind increases greatly as wind speed increases.

A more useful measurement is the average wind energy received over a given unit area over a given time frame. Average wind energy values are very important to gather, as wind energy measurements change dramatically over the short term, but are reliable when averaged over the relevant longer time frame. A proper assessment of the energy collected is essential to determining the type and size of wind turbine to be installed. The installation of an improperly selected wind turbine is not only expensive, but it may not rotate under the given wind conditions and will not generate energy.

To determine the power an installed wind turbine will produce, it is necessary to multiply the wind energy density times the swept area of the rotor times a theoretical maximum limit of energy extraxtion called the Betz limit. The Betz limit is 0.59 and is dimensionless. For a proof of the Betz limit, please see the Webliography in the References tab.

Pi = ½ A ρ v3 (Watts)

where A is the swept area of the wind turbine; A = 3.14r2 , where r is the length of the radius of the turbine rotor.

Due to other losses, as explained in other Wind Energy Virtual Labs, the maximum power produced by a turbine is normally much less than this theoretical limit.