Excepciones o exclusiones de los límites generales

To reiterate, no logging equipment was operational, so extrapolated LSBU wind speeds for 2013 and 2014 are relied upon to estimate the potential Strata energy output and compare to the manufacturers claims. Following the same methodology conducted at LSBU to compare measured and Weibull predicted outputs with a theoretical Strata case study should give an interesting juxtaposition of two different turbine installations in the same urban environment. Methodology and process is as outlined in section 4.4.

Table 60 displays the data collected over the test periods and Table 61 shows the predicted energy yield using this data.

Data Available Data

Collected Missing Missing %

2013 52560 51202 1358 3

2014 52560 51451 1109 2

Norwin 18kW

Norwin

18kW Theoretical Ave

at 6.2 m/s at 6.2 m/s Max Yield Rayleigh Weibull Wind V

kWh kWh kWh kWh kWh m/s Lower Upper 2013 45000 100000 14313 13868 12734 5.2 2014 45000 100000 12463 11689 11521 5 2013 % Efficiency Lower 95 92 85 2014 % Efficiency Lower 83 78 77 2013 % Efficiency Upper 43 42 38 2014 % Efficiency Upper 37 35 35

Table 61: Displays predicted energy yield for the Strata site compared to manufacturers marketing figures, turbine efficiency and average wind speed for 2013 and 2014. The manufacturers estimate covered a range of 45 - 100 MWh per year, therefore predicted yield is evaluated against both extremes.

Figure 133 to Figure 136 presents the Strata site's predicted energy output and wind speed

distribution curves. As can be seen, the Rayleigh predictions are shown to be higher than the Weibull due, in part, to the Rayleigh's higher wind speed peak compared to the lower wind speed

concentration of the Weibull, which peters out where manufacturers power coefficients start to rise (around 6 m/s).

It is clear from Figure 134 and Figure 136 that the Rayleigh curves crest over-estimates the concentration of wind speeds whilst the Weibull curve slightly under estimates these same speeds when compared to collected data. As the Weibull curve best fits the distribution curve of collected wind speed data it would be more realistic to take the Weibull prediction as a good estimation of annual energy yield at the Strata site.

Figure 134: Displays measured, Weibull and Rayleigh predicted wind speed distributions for the Strata in 2013.

Figure 135: Displays Energy yield predictions for 2014 at the Strata site.

Table 61 shows that the manufacturers lower end predictions were not too far off from the more suitable Weibull predictions; a 15 - 23 % difference is calculated19. This difference becomes wider when compared to the upper end estimations; a 62 - 65 % difference is calculated

The manufacturer predictions of 45 to 100 MWh p.a. is based on an average wind speed for London of 6.21 m/s. This was derived from NOABL archived average wind speeds recorded at Heathrow's average wind of 4.7 m/s at a 10 m height, which is extrapolated to 140m height, roughness class 3 to give 6.21 m/s (Norwin, 2008). This is higher than the authors estimate of 5.2 and 5 m/s and for 2013 and 2014 which are attributed to a couple of things:

1. The roughness class 3 used by the manufacturer gives a roughness length of 0.4, more suitable for villages, small towns, agricultural land, rough and uneven terrain. A roughness class of 4 (roughness length 1.6) was used in the authors calculations to allow for the dense urban topography within the Elephant and Castle area. This point, on its own, should have far elevated the authors calculations above the manufacturers expectations if it were not for point 2.

2. Heathrow is a rural, open plane with less disturbed wind flow and higher wind speeds. Heathrow's average wind speed is 4.7 m/s which extrapolates to 6 m/s at 49 m height whereas the average recorded wind speed at 49 m at the LSBU site was 3.5 m/s.

The manufacturer is not UK based therefore it is understandable why the NOABL database was relied upon, but does highlight the need for site specific wind speed data for accurate estimations of energy generation as the manufacturer estimates appear over optimistic.

It should be noted that in the manufacturer 'Turbine Design Study' (Norwin, 2008) the following points are noted:

1. There may be a 'blockage effect of the wind due to the presence of the building'. This could diminish wind speeds at the turbines.

2. '25% of the time the wind direction is in the acceptable interval where the turbines are allowed to operate'. Due to the lack of yaw mechanism the turbines cannot furl into the wind. They are fixed facing winds from the south20 therefore using wind roses from the NOABL database it is calculated that a prevailing wind from the south would occur ~25 % of the time.

3. 'The reduction of power output due to skew winds when the wind direction is more from the side elaborates to an average of 10% loss'. The venturi and building shape has been taken into consideration as having potential to block the wind and reduction wind speeds at the turbine.

4. 'It is assumed that the turbine is running both day and night'. This was added in case noise levels became too obtrusive for residents at night, therefore meaning the turbines would only be operational during the day. As estimated from noise measurements made at the Strata

19 _{It is important to note that manufacturer estimations of 45-100 MWh is for all three turbines. Investigations} thus far have been on just one so figures have been adjusted accordingly.

20

site and evaluated in section 5.2.2, this would most likely not be an issue and therefore the turbines could run 24 hours a day.

Figure 137 confirms the manufacturers concerns as measured wind direction data in the area results in the displayed wind rose, which clearly depicts a predominantly south-westerly prevailing wind. The difference is building response to wind direction is displayed in Figure 138 and Figure 139, confirming the manufacturers estimations of a reduced wind flow at the turbines influenced by the venturi and building shape when wind is not directly from the south. The extrapolated LSBU data was therefore scaled accordingly to simulate this effect. These results and points will be further discussed in chapter 6.1.2.

Figure 137: Displays a Strata wind rose depicting the predominantly south-westerly prevailing wind resource.

Chapter 6

Wind Energy Economics & London Guidance Compliance