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Your Foresight Report

April 30, 2013 @ 6:00am (GMT)
Alloa,
Clackmannanshire, United Kingdom
Latitude: 56.114, Longitude: -3.792,
Radius: 10km

Step One: Identify Local Power Predictors

You can access and use data from any one of our Power Predictors within
10km of your chosen site. Take a look at the information from each unit by
clicking on the pins in the map or by examining the tabs below.

We found 0 Power Predictors
within your selected area. If you wish to exclude the data from any particular
site, you can deselect it below and it will no longer affect the rest of your
report.

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Power Predictors Selected

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years

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Click the tabs
above to see the measured data from each site.

Can't see all the data?Some of our Power Predictor units are different
to others and lack some information such as solar radiation or wind speed
distribution.

Above you can see all the monthly recorded data
for each Power Predictor site in your area. Use the information above to get
some idea of what the typical Power Predictor readings in your area are like.
Use the terrain view to examine and exclude any sites that are not similar to
your target site.

Step Two: Measured Data Summary

Power Predictor readings can be taken at a variety of mast heights. To
compare them, we've used the features of the surrounding terrain and the
current mast height for each site to work out what the wind speeds would be at
20m from the ground. To form one data set, we've weighted each site according
to the length of time it has been recording and produced the following readings.

Step Three: Get Modelled Data

The following wind and solar data is collected from our data partners 3Tier and indicates the
simulated conditions in the area around your site. This data will help us to
correlate the Power Predictor data from your selected area and predict what
the real world conditions will be like at your site.

The shaded areas in these graphs indicate a range
of expected values. The wider these shaded areas are, the greater the variance
in the readings is likely to be.

Step Four: Combine Data

For the final step, we try to fuse the measured and modelled wind and solar
data into a single reading. If you've got a lot of measured data recorded in
your area, the results for this section might look more like the graph from
Step Two. If you have not got a lot of recorded data nearby, this might closely
follow the data from the model in Step Three. The results in this section then
form our prediction of how a Power Predictor might report the wind and solar
conditions at your site.

Results

An annual mean wind speed of m/s at 20m mast height with a
standard deviation of m/s represents a wind
speed that could pay back the investment of a typical 10kW wind turbine in
with the current UK feed in tariff.

An annual solar average of W/m2 with a standard
deviation of W/m2 represents a
solar reading that could pay back the investment in a typical 3kWp
solar array in with the current UK feed
in tariff.

The above graph shows the level of
uncertainty in these results. Although our analysis predicts a payback period of
for a small wind turbine, this could be as
little as or as much as .

Similarly, for a solar
installation, we predict a payback period of but it
could be between and .

To find out precisely how much power you could generate and to reduce the
uncertainty before investing in renewable energy technologies, you can use a
site analysis tool, such as the Power Predictor. The Power Predictor measures
the real wind and solar data on your site and produces detailed customised
reports showing a full financial breakdown for a wide range of technologies. Find out
more here.

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