The Measurecorrelatepredict technique

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The MCP approach is based on taking a series of measurements of wind speed at the wind farm site and correlating them with simultaneous wind speed measurements made at a meteorological station. The averaging period of the site-measured data is chosen to be the same as that of the meteorological station data. In its simplest implementation, linear regression is used to establish a relationship between the measured site wind speed and the long-term meteorological wind speed data of the form:

Coefficients are calculated for the 12 30° directional sectors and the correction for the site applied to the long-term data record of the meteorological station. This allows the long-term wind speed record held by the meteorological station to be used to estimate what the wind speed at the wind-farm site would have been over the last, say, 20 years. It is then assumed that the site long-term wind speed is represented by this estimate which is used as a prediction of the wind speed during the life of the project. Thus, MCP requires the installation of a mast at the wind farm site on which are mounted anemometers (usually cup anemometers) and a wind vane. If possible one anemometer is mounted at the hub height of the proposed wind turbines with others lower to allow wind shear to be measured. Measurements are made over at least a 6 month period (although clearly the more data obtained the more confidence there will be in the result) and correlated with the measurements made concurrently at the meteorological station.

There are a number of difficulties of using MCP (Landberg and Mortensen, 1993) including:

• with modern wind turbines, high site meteorological masts are necessary and these may themselves require planning permission;

• there may not be a suitable meteorological station nearby (within say 50-100 km) or with a similar exposure and wind climate;

• the data obtained from the meteorological station may not always be of good quality and may include gaps so that it may be time consuming to ensure that it is properly correlated with the site data;

• it is based on the assumption that the previous long-term record provides a good estimate of the wind resource over the lifetime of the wind farm.

Conventional MCP techniques assume that the wind direction distribution at the site is the same as that of the meteorological station. Recent investigations (Addison et al., 2000) suggest that this assumption is source of significant error and a correlation technique based on artificial neural networks is proposed. Using this approach an improvement in predictive accuracy of 5-12 percent was obtained although it should be emphasized that these advanced techniques are not common industrial practice.

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Renewable Energy 101

Renewable Energy 101

Renewable energy is energy that is generated from sunlight, rain, tides, geothermal heat and wind. These sources are naturally and constantly replenished, which is why they are deemed as renewable. The usage of renewable energy sources is very important when considering the sustainability of the existing energy usage of the world. While there is currently an abundance of non-renewable energy sources, such as nuclear fuels, these energy sources are depleting. In addition to being a non-renewable supply, the non-renewable energy sources release emissions into the air, which has an adverse effect on the environment.

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