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Friday, 14 February 2014

Wind - Going off at a tangent

When I first became interested in the contribution wind and solar energy could make to a sustainable energy economy, a good starting point seemed to get an understanding of the energy available for conversion into heat or electricity.  There is a lot of good wind data available in the public domain, so I started plotting out out wind speed distribution diagrams like to one below for a randomly selected group of worldwide locations.

As is the way with these things, one question leads to several more.  The first concerned the sample.  Most "good" data is collected not amuse spreadsheet addicts, but to assist the safe passage of ships and aeroplanes which tend to operate from open, uncluttered spaces and often produce neat and tidy datasets which can be modelled with the Rayleigh or Weibull distribution (the Rayleigh distribution is a special case of the Weibull distribution in which the shape factor is constant at 2.0).  Even without attracting attention to oneself by cycling around with a wind speed meter, it became clear that the wind speed distribution in places like backyards and some other parts of the urban and rural landscape where more complex.


Terrain is a factor in determining the amount of wind energy available at a given location.  The average wind speed and distribution will be different at the floor of a valley from that at the ridges either side.  These comments are drawn from work in progress from which as yet no definite conclusion as been drawn, thus they should be treated with caution.  In general, offshore wind polewards of the tropics has a higher average speed than onshore and approximates to a Weibull distribution with a shape factor of 2.0.  Onshore at a similar latitude, the average wind speed is lower than offshore and its distribution more skewed to the left, in terms of the Weibull distribution, the shape factor is often in the range 1.3 to 1.8, the higher values being associated with flat, open areas.

In an attempt to explore the effects of terrain on the distribution of wind speed, I plotted small contour maps using data from the SRTM mission, like the one shown below which is centred on a windmill close to where I live..


I've had to put this work to one side for a few months, but not being the most disciplined of researchers, I wondered if the software used for the contour plots could be used to give an insight into the location of windmills.  In reality, this was going off at a tangent, but the logic was that windmills are found in places for which there is no readily available source of wind speed data, thus studying their location would be an interesting way of looking at terrain and wind, this work has also been moved to one side, but I am looking forward to returning to it.


Wikipedia has some excellent lists of windmills from around the United Kingdom, and in may cases does the tedious task of converting National Grid coordinates to lat/lng relative to the WGS84 datum which are compatible with the SRTM data.

Windmills are part of the English landscape, especially in the eastern counties, but I was surprised at the number of them, maybe 2,000 (a guess) with the majority being built and operated in the 19th Century.  At the beginning of the 20th century, the windmills were displaced by factories powered by steam, oil  or electricity.  For there to be so many windmills in operation, there must have been a substantial industry dedicated to their construction and maintenance together with a knowledge of the relationship between terrain an wind energy, I would be curious to know if there was a reference work on this?

In a week in which the UK has been lashed by some of the most violent storms in living memory, it should be remembered that the wind machinery has to survive under considerably harsher conditions than it normally operates.  In storm conditions, wind turbines shut down in an attempt to minimize the risk of damage.



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