MEASUREMENT AND MODELLING OF THE PROFILE AND TURBULENCE OF COASTAL WIND

Jørgen Løvseth, Svein Erik Aasen and Rune Lende

Department of Physics, Norwegian University of Science and Technology

N-7055 Dragvoll, NORWAY

ABSTRACT: To study the structure of the coastal wind field two measurement stations have been established on the island Frøya, which borders the Norwegian sea outside Mid-Norway. A brief discussion of these measurement stations is given.

The situation for wind energy in Norway is briefly discussed. Mean monthly production from a wind energy converter (WEC) is shown, and compared to electricity consumption and inflow to the hydro power magazines.

Typical wind speed profiles are shown and compared to the logarithmic law. Very low values of the aero-dynamical roughness length is found. In the maritime sector, is found to vary with the wind speed in accordance with the Charnock relation. Examples of turbulence spectra for one hour periods are shown and discussed. The spectra indicate much energy for low frequencies, and the expected gap for periods around one hour is missing.

Keywords: Wind Speed Profile, Boundary Layer, Turbulence, Energy Costs

1. INTRODUCTION

The Norwegian electricity market is dominated by hydro power. Wind energy is the most promising of the new, renewable sources for electricity production, and Norway has large areas suitable for development. The highest average wind-speed during a year is found along the coast of Mid- and Northern-Norway. Developing wind energy in these areas would also offer most welcome job opportunities, and contribute to keep the rural, coastal areas populated. The Norwegian hydro power system has a large regulatory capacity to smooth out variations in the wind energy. As discussed below, wind power is in phase with consumption on an annual scale, whereas hydro power has opposite phase. Thus, there will be synergy effects between wind and hydro power.

Since 1981 the Department of Physics at Norwegian University of Science and Technology has been involved in measurement programs for describing the wind resources and the establishment of guidelines for wind loads on maritime installations.

2.THE MEASUREMENT STATIONS

We are currently operating two measurement stations; Skipheia and Sletringen. Both are located on the coast, 100 km to the west of Trondheim.

The measurement system for the stations has been developed at the institute. The wind speed sensors are commercially available cup-anemometers with a distance constant of 1.5 m. The temperature sensors have been made at the institute. Two thermistors are mounted in a radiation shielded house with fan ventilation. The thermistors are separately calibrated and the temperature-voltage relation is fitted by a formula accurate to 0.001 K. The resulting overall accuracy is better than approximately ±0.02K. Sensors for wind direction and radiation are good quality commercially available units.

The logging is operated by a PC running under the real time system OS-9000[1]. This is a multi-user system which makes it easy to monitor and manage the system via modem from Trondheim.

Figure 1 OS-9000 Data acquisition system.

A great effort has been made during the design of the system to make uninterrupted operation possible. If a (non fatal) failure occurs, a watch dog will cause automatic reboot of the system. Special care was taken to avoid or minimise damage by atmospheric discharges. Optical links separate the sensors from the computer to prevent a fatal system failure if one of the sensors should be hit by lightening. External telephone and power connections have advanced filter systems. An overview of the monitoring system is shown in Figure 1.

Logged data (approx. 7Mb/day) are saved on tape every night. Once a month, the tape is shipped to our office by a local person. The data are then further controlled, and errors due to e.g. electric sparks and restart of the computer are removed. Further details about the station can be found in [1] and [8]. For a more detailed description, see S. E. Aasen [2].

2.1 The Skipheia station

This is the main station located on the western part of the island Frøya. Figure 2 shows a map of the area, and the location of two nearby WECs and the masts. A more detailed description may be found in [1] and [2].

Figure 2 Map showing the location of the Skipheia station. Contour distance 5 m.

The station has three masts placed in a triangle. Two masts separated by 79 m have a height of 100m, and a third mast of 45m is found at a distance of 170 m. Approx. 40 sensors are mounted in the masts measuring:

  • temperature (ground, in the sea and in the masts at 1 m, 3 m, 10 m, 40 m, 70 m and 100 m)
  • wind speed and direction (10 m, 20 m, 40 m, 70 m and 100 m)
  • radiation measurements: solar and total radiation
  • rainfall
  • humidity

The wind sensors are placed on slender rods at a distance of 2.65 m from the mast. In the 100 m masts the wind speed sensors are duplicated to avoid shading from the mast, and the up-wind sensor may be selected automatically. The logging frequency for all the sensors are 0.85 Hz (512/10 minute).

The terrain around the station are varying from open view in the southern direction to the Norwegian sea, to an approximately 3 km of rocky plain when the wind comes from west and north. Mast 3 (see Figure 2) is located on a small hill which causes a speed-up effect from some directions.

2.2 The Sletringen station

The Sletringen station is located on a small island 4 km west of Skipheia (not shown on the map). The islet has a maximum height of around 4m above mean sea level. It has a naked, rocky surface, and is exposed to maritime wind in a sector from south through west to north.

The station is equipped with a 45 m mast with sensors for temperature, wind speed and direction. The monitoring PC is placed in an unmanned lighthouse 150 m east of the mast (in the non-maritime sector). This station will serve as a reference station in studying the effect of land on the wind from the maritime sector.

3. WIND ENERGY IN NORWAY

Norway has vast areas with good wind conditions which are suitable for wind energy development, Various estimates range from 15 to 40 TWh/a for the economically interesting potential.

The main obstacle for development of wind energy in Norway has been a surplus of cheap hydropower. This period now seems to have come to an end, because consumption equals production on an annual scale. The introduction of a free market for electricity in Europe will probably contribute to bring the Norwegian electricity prices up to the European level.

Figure 3 Annual distribution (percent per month) of WEC production, water influx and electricity consumption.

In figure 3 the monthly distribution of wind power is shown. The data are based on 10 min mean wind speed for 12 years from our station at Frøya and has been folded with the power curve for a 3 MW wind energy converter. Also shown are the electricity consumption and the influx to the hydro power magazines in 1991, which are in opposite phases. In the critical periods for the hydro-electric production (winter to April) the hydro influx is low. Production from hydro-electric power stations, with small or no reservoir facilities, is therefore lower in this period, which means that the prices are normally higher. A yearly deviation of the mean price around 20% is common. As Fig. 3 indicate, the adding of wind power to the Norwegian system would ease the need for hydro reservoirs with an annual capacity. The typical production of a modern WEC at Skipheia is 3 kWh per watt nominal capacity. Increasing the generator size for a given turbine would increase winter production further.

For a large scale development, the electricity price for wind energy is expected to be competitive with hydro power [10] and with prices on the European market. As discussed in other sessions in this conference, wind energy is still in a position on the learning curve where prices are rapidly decreasing. The Norwegian resources should therefore be developed. A more detailed description of the renewable energy potential of Norway can be found in [9].

4. WIND PROFILES

We will here limit the discussion to data for neutral atmospheric stability. This will correspond to a negative temperature gradient[2] in the range of 8-12 K/km in the surface layer. The temperature gradient is estimated by a least square fit to hourly mean values of all the temperature sensors in the mast.

For neutral stability, the logarithmic law is assumed to describe the wind profile in the surface layer [3]

.(4.1)

Here, is the speed at height , is the friction velocity and is the aero-dynamical roughness length. is von Karman constant, here set to .

Experimentally, wind speed ratios are evaluated. It is easily shown that eq.(4.1) implies

, (4.2)

where ur is the wind speed at a reference height . The parameter  is both experimentally and numerically very robust, and is to first order equal to the exponent in the popular power law for the wind speed profile. It is related to the parameters in eq. (4.1) by

.(4.3)

One may also express  by the speeds at arbitrary heights and giving

.(4.4)

In figure 3, the  parameter calculated from one hour mean values of the wind speed is shown for successive heights in mast 2 for various wind speed classes versus wind direction. Strict validity of the logarithmic law would give a constant value of  independent of height for a given direction. For the sake of brevity, we will only comment on the gross features of fig. 3. In the sector 20° - 60o, the upwind WECs are causing a large scatter. In the south direction, with a short distance to the sea shore, a Charnock effect is seen, i.e. the roughness length is given by [7]

,(4.5)

where is the acceleration due to gravity, and is the Charnock constant usually found to be around [8]. A further discussion of this effect can be found in [1].

Figure 4 as a function of the direction taken from mast 2. The fraction on the y-axis corresponds to the heights. The data are divided into 5 bins. The legend corresponds to the different mean wind classes. The values are plotted with a span of  one standarddeviation.

In the sector 250° to 360o, there is a distance of land in the upwind direction of at least 2 km, and a fully developed internal boundary layer should be expected. Again, we cannot go into details, but we observe that a typical value of  around 0.1 found in this sector corresponds to z0 = 0.45 mm. This is a very low value for this rather rough terrain. However, there are very little energy absorption in the surface itself, only patches of low heather. But the structure of small hills will introduce turbulence in the surface layer, which in the thermal case is known to give a low value of .

The profile of turbulence intensity,

,(4.6)

where  is the standard deviation assumed to be independent of height, has also been studied. Modelling u(z) by eq. (4.1), values of are found which are about two orders of magnitude larger, more in line with what one would expect.

5.TURBULENCE SPECTRA

The turbulence spectral function represents the distribution of turbulent energy versus the frequency . In the literature many investigations have found a minimum in the spectral density for periods about one hour. Mechanical turbulence is supposed to give a peak in the 1/min region. The contribution from convective turbulence are considered to be small in the 1/h region. In the case of neutral stability it should not be present at all.

In Gjerstad et al. [4] is was shown that the expected gap around h-1 is present in the case of a stable atmosphere. These investigations were based on 10 h 40 min. time series measured at Sletringen. We will here only discuss the case of neutral stability. The spectra are based on one hour periods. Linear trend removal was performed prior to analyses of the time series.

Figure 5 Measured spectra compared to the Kaimal model for mast 2 for the land and sea sector and heights 20 - 100 m. The spectra are based on 1 hour time series for neutral stability.

A classical paper by Kaimal et al [5] gave a model for the turbulence spectrum which was written on the form

where .(5.7)

Kaimal et al [5] used , and . The form of this model, with various values for , and is the basis for many models developed later. Figure 4 show experimental spectra for neutral stability compared to the Kaimal model (original parameters) for 4 heights in the land (270 - 360o) and sea (200-240o) sectors for mast 2. There are obvious deviations in the scaling properties for f < 0.1 Hz, and too much energy for f < 3 mHz. A more detailed discussion of the spectra are found in [2], and will be reported elsewhere

6. ACKNOWLEDGEMENTS

We are grateful to Oddbjørn Grandum for work related to the station and Arild Gustavsen for providing one of the figures.

REFERENCES

[1] J. Løvseth, S. E. Aasen, T. Heggem, EWEC’94,p207.

[2] S. E. Aasen, «The Skipheia Wind Measurement Station», Ph. D thesis, University of Trondheim, 1995.

[3] R. A. Dobbins, «Atmospheric motion and air pollution: an introduction for students of engineering and science», Chap. 6, Wiley, New York, USA.

[4] J. A. Dutton, «Dynamics of atmosphere motion», p 48-51, Dover Publications Inc., New York, 1995.

[5] J. Gjerstad, S. E. Aasen, H.I. Andersson, I: Brevik, J. Løvseth, «An analysis of low frequency maritime atmospheric turbulence», J. Atmos. Sci, Vol. 52, No. 15, 1995.

[6] J.C. Kaimal, J. C. Wyngaard, Y. Izumi, O.R. Cotê, «Spectral characteristics of surface-layer turbulence», Quart. J. Roy. Meteorol. Soc. 98, p 563-589, 1972.

[7] H. Charnock, «Wind stress on a water surface», Quart. J. Roy. Met. Soc. p81, 1955.

[8] J. Andersen and J. Løvseth: The Frøya database for gale force maritime wind. Structural Dynamics, T.Moan et al. (eds), p. 1091- 1097, A.A. Bakkemna, Rotterdam 1993.

[9] J. Løvseth: The renewable energy potential of Norway and strategies for development. Renewable Energy 6, p. 207 - 214, 1995.

[10] Knut Benonisen, Nord-Trøndelag Power Company, Seminar report.