1. Use of cellular communication masts for wind measurements in Latvia: wind flow CFD models and preparation for experiment
Vladislavs Bezrukovs, Valerijs Bezrukovs, Sabine Upnere, Linda Gulbe, Normunds Jekabsons, Aleksejs Zacepins
Ventspils University College,
Institute of Physical Energetics
SOWE 2017
27-28 April 2017
Pamplona, Spain

2. Cellular communication masts available in Latvia

3. Cellular communication masts available in Latvia
3 mobile networks operators - each operator has his own masts;
Types: tower type with base up to 7 m or guyed type with side width 0.74 – 1.4 m;
Heights from 60 to 100 m;
Location - throughout the territory.
Mast of the tower type.
Mast of the guyed type.

4. Cellular communication masts available in Latvia
Towers
1 – Staldzene, Ventspils, 100 m
2 – Tebra, Liepāja, 99 m
3 – Rozēni, Ainaži,100 m
Agreement with LMT;
Guyed type masts with side width m;
Height – 99 or 100 m;
Location – Baltic sea coast;

5. Arrangement of sensors on 100 m LMT mast
5 m: data logger; barometer; power supply;
30 m: wind direction Nr.1; wind anemometer Nr 1.;
temperature sensor Nr.1;
50 m: wind anemometers Nr 2, 3, 4;
75 m: wind anemometer Nr. 5;
95 m: wind direction Nr.2; wind anemometer Nr 6.7;
temperature sensor Nr.2.

6. IEC standard requirements for the length of the boom depending of mast side width and solidity
By the international standard IEC , it is of importance that the mast structure does not introduce distortions into the air flow that cause > 1% error at measuring the wind speed.
Mast side width – 1.2 m;
Solidity up to 0.35 including ladders and communications cable lines;
Curves of the distance from the mast centre, R, m, vs. mast structure solidity t.

7. CFD modeling of mast structure distortions into the air flow
Sketch of analysed triangular lattice communication mast of guyed type and its horizontal cross-section.
Directions of the wind flows with respect to the triangular lattice mast.

8. Numerical implementation
CFD modeling of mast structure distortions into the air flow
Numerical implementation
Incompressible, steady-state and turbulent flow;
Turbulence intensity is assumed to be 15 %;
Reynolds Averaged Navier-Stokes equations;
Standard k-epsilon turbulence model;
Convergence is assumed when residuals are less than 5 x 10-6;
OpenFOAM 2.4.x, simpleFoam solver;
Parallel computing, 16 cores per 1 case.

9. CFD modeling of mast structure distortions into the air flow
Boundary conditions
Inlet – constant inflow velocity - U, turbulent kinetic energy - k, and turbulent dissipation - epsilon; next step –logarithmic profile for neutral atmospheric boundary layer for U and epsilon;
Outlet – constant pressure, p=0;
Walls – no-slip for U and standard OF wall functions for k, epsilon and turbulent viscosity, t;
Top & bottom – mirror symmetry conditions;
Sides (parallel to the flow direction) – slip conditions.

10. Computational domain & mesh
CFD modeling of mast structure distortions into the air flow
Computational domain & mesh
Computational domain (streamwise × spanwise × height): 30 m x 9 m x 5 m;
11x106 cells;
Mast surface is created using NetGen and saved as STL files;
Mesh generation: blockMesh and snappyHexMesh;
The wall function parameter y+ in average is less than 400 for U = 10 m/s, and approximately 200 for U = 5 m/s.
Qualitative mesh generation is a challenge.
Mesh around the mast surface, vertical cross-section.

11. CFD modeling of mast structure distortions into the air flow (No ladders and no cable lines; Solidity ~ 0.2)
The grey regions speed 99 – 101%;
The green regions speed 101 – 101.5%;
The red regions speed > 101.5%,
The violet regions speed 98.5 – 99%;
The brown regions speed < 98.5%.
Here the flow speed values in the grey, green, and violet meet the IEC standart requirements
In the red and brown regions the deviations exceed the allowed values.
CFD model of the air flow interaction with a triangular lattice mast, side width 0.74 m, at the wind speed U = 10.0 m/s and angles α = 0° and 180°, relative to the position of a boom with sensor S.

12. CFD modeling of mast structure distortions into the air flow (ladders and cable lines included in the model)
CFD modelling results of the air flow interaction with a triangular lattice mast, side width 0.74 m, at the wind speed U = 10.0 m/s and angle α = 0, 30, 150, 180, 210 and 330°, relative to the position of a boom with sensor S.

13. CFD modeling of mast structure distortions into the air flow (ladders and cable lines included in the model)
CFD modelling results of the air flow interaction with a triangular lattice mast, side width 0.74 m, at the wind speed U = 5.0 m/s and angle α = 0, 30, 150, 180, 210 and 330°, relative to the position of a boom with sensor S.

14. CFD modeling of mast structure distortions into the air flow (ladders and cable lines included in the model)
CFD modelling results of the air flow interaction with a triangular lattice mast, side width 0.74 m, at the wind speed U = 10.0 m/s and angle α = 60, 90, 120, 240, 270 and 300°, relative to the position of a boom with sensor S.

15. CFD modeling of mast structure distortions into the air flow (ladders and cable lines included in the model)
CFD modelling results of the air flow interaction with a triangular lattice mast, side width 0.74 m, at the wind speed U = 5.0 m/s and angle α = 60, 90, 120, 240, 270 and 300°, relative to the position of a boom with sensor S.

16. Describing study sites using remote sensing data: input data
Lidar points
Orthophoto
Data acquisition:
Spatial resolution: >4 points/m2
Data acquisition:
Visible light (RGB) bands
Spatial resolution: 0.4 m
Airborne data are provided by Latvian Geospatial Information Agency under the Cooperation Agreement
Orthophoto scale 1:10 000
© by Latvian Geospatial Information Agency 2014

17. Describing study sites using remote sensing data: data products
Lidar points -> Digital Terrain Model (DTM), Digital Surface Model (DSM), low and high object classification;
DTM and DSM are generated by FUSION software and postprocessed using workflow based on image morphological processing and local analysis.
DTM
DSM
High objects

18. Describing study sites using remote sensing data: data products
Orthophoto and low and high object classification-> Land cover classification;
Workflow is based on spectral clustering and decision trees.
Sand, asphalt
Agricultural land, pasture, grassland
Water
Tree cover
Urban
Swamp
Orthophoto scale 1:10 000
© by Latvian Geospatial Information Agency 2014

19. Describing study sites using remote sensing data: usage of the data products
Digital Surface Models and Land Cover Maps will be employed to simulate air flow around towers in the study sites;
Possible use of NEWAfoam?
Digital Surface Model with land cover classification overlay.
Surface roughness coefficients are assigned according to land cover

20. Compare wind measurements with CFD modeling.
Conclusions
3 sites for wind measurements in Latvian coast are selected and obtained agreement from LMT mobile communication company to use 100 m masts.
Procurement procedure for sensors are finished;
CFD model of guyed type mast created;
Digital Surface Models and Land Cover Maps will be employed to simulate air flow around towers in the study sites;
The CFD modelling results are obtained for simulations of air flow interaction with a triangular lattice mast, with side width 0.74 m: with and without taking into account the cable lines at the wind speed U = 5 and 10 m/s.
Comparison of the modelling results for wind speeds 5.0 and 10.0 m/s shows that with the wind speed increasing the regions where the flow distortion exceeds ± 1.0% becomes smaller.
Presence of cable lines in triangular lattice cellular communication mast slows down the air flow speed greater than 1.5%, which looks like as a narrow train with the length of sizes of mast side width. In the limits of 350° the region with distortions > ±1.5 % does not exceed the distance of 2 – 3 sizes of mast side width from the center.
Future tasks:
Compare wind measurements with CFD modeling.

21. Acknowledgements
Acknowledgements to Encom LTD for provided support. The work is carried out within the project New European Wind Atlas (NEWA), ENER/FP7/618122/NEWA ERA-NET PLUS, supported by the EUROPEAN COMMISSION under the 7th Framework Programme for Research, Technological Development and Demonstration. NEWA Latvian partners