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Wind gust statistics and turbulence studies during storms at a wind generator site in Central Otago, New Zealand
Renewable Energy, Vol.5, Part I, pp. 730-732, 1994 El~viet Science Ltd Print~l in Great Bdtain 0960-1481/94 $7.00+0.00
Pergamon
WIND GUST STATISTICS AND TURBULENCE STUDIES DURING STORMS AT A WIND GENERATOR SITE IN CENTRAL OTAGO, NEW ZEALAND K.R. DAWBER, G.D. NEILSON and D.R.A. FRASER Physics Department, University of Otago, P.O. Box 56, Dunedin, New Zealand.
ABSTRACT Wind gust data and turbulence statistics were collected during storms which passed over the Rocklands Atmospheric Tower (Dawber, 1990) located near the Old Dunstan Road in the Lammermoor Range area of Central Otago, and transmitted via a UHF data link to a computer in the Physics Department Laboratories some 50 km away. Wind gust profiles at 10 m and 30 m elevations, wind shear statistics on a 0.2 s basis, the statistical distributions of the gusts of various magnitudes during storms, the 10 minute mean wind speed distributions and the turbulent intensities were evaluated and analysed. KEYWORDS Wind energy; wind turbulence; gusts at a New Zealand site. SITE DESCRIPTION AND METHODOLOGY The site and a description of the equipment was given in a paper presented at the second World Renewable Energy Congress (Dawber and Neilson, 1992). In summary, the basic equipment consisted of Gill-type propeller anemometers mounted horizontally in pairs at 10 m and 30 m above ground level on a freestanding tower at Rocklands, located as shown in Fig. 1. Data from the Rocklands Tower was transmitted in real time to the University of Otago Physics Department Laboratories via a two stage UHF radio link where selected events could be archived on the hard disk of a micro-computer. While the site is not a particularly windy one, its annual mean wind speed being about 6 ms -1, it was subject to strong wind flows from both the NW and the SW directions during storms. These storms correlate closely with domestic electricity usage in the area, making it an attractive potential wind farm site. In this study, therefore, archiving and analysis was limited to these storm periods. The project was partly funded by ECNZ, New Zealand's main electricity generating utility, who were particularly interested in extreme gust reports such as were discussed in the paper referred to above. FURTHER EXTREME EVENT ANAYLSIS Extreme events were defined as gusts where the acceleration or deceleration of the wind averaged more than the "trigger level" over a running average of one second. Measurements were initially taken each 0.1 s but for most of the present series of results, wind speeds were recorded each 0.2 s. The usual trigger level was set at 2.5 ms -1 so an "extreme event" was recorded if the wind changed by more than 2.5 ms -1 in any one second. However, for more gentle wind flow periods, the trigger level was set to 1.0 ms -1. A comparison of the statistics for extreme events for a 12 hour SW storm of 20 ms -1 mean wind speed with those from a similar period of 10 ms -t mean wind speed is shown in Fig. 2. This method of analysis can
730
731 also be extended to show the statistics of less violent speed changes by resetting the program to select changes over (say) 10 s. The results of this are also plotted in Fig. 2. It is interesting to note the similarity of the shapes of the curves in these plots. Thus it is not surprising that the standard deviations of the 10 minute wind speeds for the 20 ms -1 storm period plotted was 2.6 ms -1 at both anemometer heights while for the 10 ms -t wind flow period it was 1.4 ms -1 at 30 m above ground level and 1.3 ms-1 at 10 m. The turbulence intensities for the two periods are shown in Table 1, along with the means of the 0.2 s shear determinations and the standard deviations of these. Typical turbulence intensities at the Reading University "meteorological field" are of the order of 0.3 at 2 m above ground level in daylight but decrease at night (Ibbetson, 1981). However, it is normal for these to decrease with height. IOmls Island
3@mls ~om l o s ~ m Io=
.
~om lo= l c m I=
0
o£
2-
~. and
~
~00
Fig. 1. Map of New Zealand showing Rocldands Tower site
2
4
6
8
I(}
12
14
16
111
20
speed change (m/s) Fig. 2. Gust plots for SW winds selected over 1 s and 10 s and recorded at 10 m and 30 m AGL.
Table 1. Turbulence intensities (TI) and shears (SH) for the wind flows of Fig.2. Mean wind speeds (_+2 ms -1) Length of period
10 ms -1 12 hours
20 ms -1 12 hours
TI 1 0 m
0.172
0.151
TI 30 m
0.153
0.140
SH
1.17
1.10
standard deviation in SH
0.20
0.16
These types of curves and tables have been produced for a number of storms both in the SW and the NW wind regimes and have proved to be very consistent. It is possible that there is a seasonal trend with NW results but further data is needed before conclusive results can be obtained. The method appears to be suitable for predicting the smoothness of wind flows at potential wind farm sites and shows that at Rocklands there are no particularly regular hazards with regard to gusts. RELATIONSHIPS BETWEEN 10 MINUTE MEANS AND STANDARD DEVIATIONS Graphs of 10 minute mean wind speeds during SW cold front-type storms and NW f6hn-type high wind periods were compared with graphs of the 10 minute standard deviations of the same periods from both the 30 m tower top position and the 10 m level. Typical examples are shown in Fig. 3. A general trend observed with SW storms was that the standard deviation of the wind speed at the tower top was consistently more variable than at the 10 m level. With the NW winds, the most notable feature was that the standard deviations were much more variable during the onset of a high wind period than later on when the wind had been blowing hard for a number of hours, while no particularly strong differences in the ranges of the standard deviations were noticeable between the two heights. It is realised that many subtle reasons may exist for the evidently different patterns in the two wind regimes. Topographic and thermally induced turbulence would be expected to contribute differently to each type of flow. Seasonal studies are hoped to shed further light on some aspects. The method already gives
732
a very graphic insight into the behaviour of the wind during storms at this site, and shows the simplicity of analysis possible when high frequency data is available. oO
t~
speed graph
s.ck graph
speed graph
s.ck graph 10 m anemometers
30 m anemometers
(scale width 800 minutes)
Fig. 3 Ten minute mean wind speeds and associated standard deviations during a NW storm OTHER METHODS OF ANALYSIS A number of other methods of analysis of the storm data were also carried out, and typical results of two methods are shown in Figs. 4 and 5. These methods were (Fig.4) to construct histograms of the number of gusts where the wind changed by a measured amount in a 10 second period, and (Fig.5) to plot the relationship between the maximum wind speed change in a short period (such as 1 s, 3 s, or 10 s) against the 10 minute standard deviation. Both these methods give interesting graphical ways of displaying and assessing turbulence. ~. y ~ *0.6~tg*J.iTalx
R^2=0.903 OE
Sn o~ D. o
o~m
0standard d~*iati~ of wind s~eed (nv~l
Fig.
4. Histogram of wind gust size
Fig. 5. Maximum wind speed changes vs standard deviation
CONCLUSION The collection and analysis of high frequency wind data and the transmission of such data to a laboratory computer for archiving and analysis is a powerful method of assessing the nature of wind regimes at wind farm sites. In the particular application to Rocklands there is a added bonus in that long term correlation with a standard meteorological station at Taiama Head near Dunedin-gives a way of evaluating periods when data of a particular type is unavailable, due to operational problems.
REFERENCES Dawber, K.R. and Neilson G.D. (1992). Detection and analysis of extreme events in wind records from a potential wind turbine site in Central Otago, New Zealand. Proceedings of the Second World Renewable Energy Congress, Reading, U.K. 1702-1706 (Pergamon Press). Ibbetson, A. (1981). Some aspects of the description of atmospheric turbulence. Dynamic Meteorology 138 - 152 (Methuen).
Pergamon
WIND GUST STATISTICS AND TURBULENCE STUDIES DURING STORMS AT A WIND GENERATOR SITE IN CENTRAL OTAGO, NEW ZEALAND K.R. DAWBER, G.D. NEILSON and D.R.A. FRASER Physics Department, University of Otago, P.O. Box 56, Dunedin, New Zealand.
ABSTRACT Wind gust data and turbulence statistics were collected during storms which passed over the Rocklands Atmospheric Tower (Dawber, 1990) located near the Old Dunstan Road in the Lammermoor Range area of Central Otago, and transmitted via a UHF data link to a computer in the Physics Department Laboratories some 50 km away. Wind gust profiles at 10 m and 30 m elevations, wind shear statistics on a 0.2 s basis, the statistical distributions of the gusts of various magnitudes during storms, the 10 minute mean wind speed distributions and the turbulent intensities were evaluated and analysed. KEYWORDS Wind energy; wind turbulence; gusts at a New Zealand site. SITE DESCRIPTION AND METHODOLOGY The site and a description of the equipment was given in a paper presented at the second World Renewable Energy Congress (Dawber and Neilson, 1992). In summary, the basic equipment consisted of Gill-type propeller anemometers mounted horizontally in pairs at 10 m and 30 m above ground level on a freestanding tower at Rocklands, located as shown in Fig. 1. Data from the Rocklands Tower was transmitted in real time to the University of Otago Physics Department Laboratories via a two stage UHF radio link where selected events could be archived on the hard disk of a micro-computer. While the site is not a particularly windy one, its annual mean wind speed being about 6 ms -1, it was subject to strong wind flows from both the NW and the SW directions during storms. These storms correlate closely with domestic electricity usage in the area, making it an attractive potential wind farm site. In this study, therefore, archiving and analysis was limited to these storm periods. The project was partly funded by ECNZ, New Zealand's main electricity generating utility, who were particularly interested in extreme gust reports such as were discussed in the paper referred to above. FURTHER EXTREME EVENT ANAYLSIS Extreme events were defined as gusts where the acceleration or deceleration of the wind averaged more than the "trigger level" over a running average of one second. Measurements were initially taken each 0.1 s but for most of the present series of results, wind speeds were recorded each 0.2 s. The usual trigger level was set at 2.5 ms -1 so an "extreme event" was recorded if the wind changed by more than 2.5 ms -1 in any one second. However, for more gentle wind flow periods, the trigger level was set to 1.0 ms -1. A comparison of the statistics for extreme events for a 12 hour SW storm of 20 ms -1 mean wind speed with those from a similar period of 10 ms -t mean wind speed is shown in Fig. 2. This method of analysis can
730
731 also be extended to show the statistics of less violent speed changes by resetting the program to select changes over (say) 10 s. The results of this are also plotted in Fig. 2. It is interesting to note the similarity of the shapes of the curves in these plots. Thus it is not surprising that the standard deviations of the 10 minute wind speeds for the 20 ms -1 storm period plotted was 2.6 ms -1 at both anemometer heights while for the 10 ms -t wind flow period it was 1.4 ms -1 at 30 m above ground level and 1.3 ms-1 at 10 m. The turbulence intensities for the two periods are shown in Table 1, along with the means of the 0.2 s shear determinations and the standard deviations of these. Typical turbulence intensities at the Reading University "meteorological field" are of the order of 0.3 at 2 m above ground level in daylight but decrease at night (Ibbetson, 1981). However, it is normal for these to decrease with height. IOmls Island
3@mls ~om l o s ~ m Io=
.
~om lo= l c m I=
0
o£
2-
~. and
~
~00
Fig. 1. Map of New Zealand showing Rocldands Tower site
2
4
6
8
I(}
12
14
16
111
20
speed change (m/s) Fig. 2. Gust plots for SW winds selected over 1 s and 10 s and recorded at 10 m and 30 m AGL.
Table 1. Turbulence intensities (TI) and shears (SH) for the wind flows of Fig.2. Mean wind speeds (_+2 ms -1) Length of period
10 ms -1 12 hours
20 ms -1 12 hours
TI 1 0 m
0.172
0.151
TI 30 m
0.153
0.140
SH
1.17
1.10
standard deviation in SH
0.20
0.16
These types of curves and tables have been produced for a number of storms both in the SW and the NW wind regimes and have proved to be very consistent. It is possible that there is a seasonal trend with NW results but further data is needed before conclusive results can be obtained. The method appears to be suitable for predicting the smoothness of wind flows at potential wind farm sites and shows that at Rocklands there are no particularly regular hazards with regard to gusts. RELATIONSHIPS BETWEEN 10 MINUTE MEANS AND STANDARD DEVIATIONS Graphs of 10 minute mean wind speeds during SW cold front-type storms and NW f6hn-type high wind periods were compared with graphs of the 10 minute standard deviations of the same periods from both the 30 m tower top position and the 10 m level. Typical examples are shown in Fig. 3. A general trend observed with SW storms was that the standard deviation of the wind speed at the tower top was consistently more variable than at the 10 m level. With the NW winds, the most notable feature was that the standard deviations were much more variable during the onset of a high wind period than later on when the wind had been blowing hard for a number of hours, while no particularly strong differences in the ranges of the standard deviations were noticeable between the two heights. It is realised that many subtle reasons may exist for the evidently different patterns in the two wind regimes. Topographic and thermally induced turbulence would be expected to contribute differently to each type of flow. Seasonal studies are hoped to shed further light on some aspects. The method already gives
732
a very graphic insight into the behaviour of the wind during storms at this site, and shows the simplicity of analysis possible when high frequency data is available. oO
t~
speed graph
s.ck graph
speed graph
s.ck graph 10 m anemometers
30 m anemometers
(scale width 800 minutes)
Fig. 3 Ten minute mean wind speeds and associated standard deviations during a NW storm OTHER METHODS OF ANALYSIS A number of other methods of analysis of the storm data were also carried out, and typical results of two methods are shown in Figs. 4 and 5. These methods were (Fig.4) to construct histograms of the number of gusts where the wind changed by a measured amount in a 10 second period, and (Fig.5) to plot the relationship between the maximum wind speed change in a short period (such as 1 s, 3 s, or 10 s) against the 10 minute standard deviation. Both these methods give interesting graphical ways of displaying and assessing turbulence. ~. y ~ *0.6~tg*J.iTalx
R^2=0.903 OE
Sn o~ D. o
o~m
0standard d~*iati~ of wind s~eed (nv~l
Fig.
4. Histogram of wind gust size
Fig. 5. Maximum wind speed changes vs standard deviation
CONCLUSION The collection and analysis of high frequency wind data and the transmission of such data to a laboratory computer for archiving and analysis is a powerful method of assessing the nature of wind regimes at wind farm sites. In the particular application to Rocklands there is a added bonus in that long term correlation with a standard meteorological station at Taiama Head near Dunedin-gives a way of evaluating periods when data of a particular type is unavailable, due to operational problems.
REFERENCES Dawber, K.R. and Neilson G.D. (1992). Detection and analysis of extreme events in wind records from a potential wind turbine site in Central Otago, New Zealand. Proceedings of the Second World Renewable Energy Congress, Reading, U.K. 1702-1706 (Pergamon Press). Ibbetson, A. (1981). Some aspects of the description of atmospheric turbulence. Dynamic Meteorology 138 - 152 (Methuen).