Improving the Analysis of Wind Turbine Interactions with Weather Radar through the Addition of GIS Tools

Transcription

1 Improving the Analysis of Wind Turbine Interactions with Weather Radar through the Addition of GIS Tools Carolyn J. Rennie Norman Donaldson Jim M.C. Young Environment Canada 2012 CMOS Congress Friday June 1, 2012 Contact:

2 What returns are weather and what are turbines? Wind Farms Page 2

3 Projected Growth of Wind Turbines Our tallest radar tower Page 3

4 Goals / Motivation / Objectives Wind energy proponents contact the National Radar Program Consultation of any potential impacts Information required for analysis includes individual turbine coordinates and height Need to find a efficient way to analyze the volume of proposals Monthly Average of Canadian Wind Farm Proposals Received Average Jan 1- May 23, 2012 Year Page 4

5 Canadian Weather Radar Network and Existing Wind Farms 31 Canadian Weather Radars ~ 267 proposals received 69 within 50 km 155 are within 80 km ~ 121 existing wind farms in Canada 12 are within 50 km of a Radar 31 are within 80 km Page 5

6 Page 6

7 Doppler Radar Filters Radar s transmit energy and receive a portion back from targets Radar energy is sometimes reflected off terrain, vegetation, or buildings causing Ground Clutter Doppler radar can measure relative velocity thus eliminating stationary Ground Clutter Wind turbine blades move and confuse Doppler filters Close, large targets can cause beam blockage Page 7

8 Wind Farm and Weather Radar Interactions Wind Turbine Clutter Precipitation Accumulations Wind Farms Wind Farms Blockage from Communication Tower Weather Page 8 7 day precipitation accumulation image

9 Wind Farm and Weather Radar Interactions Blockage Multi-Path Scattering Com Towers Turbines 3 spikes of lower precipitation are due to blockage communication towers Page 9 Edward Ciardi NEXRAD Radar Operations Centre

10 Previous Analysis Methods for Impact on Weather Radar Software developed by Dr. Norman Donaldson and Bob Paterson (Cloud Physics and Severe Weather Research Group of Environment Canada) Inputs: Locations, tower heights, blade lengths Software estimates radar visibility using: standard radar propagation SRTM03 Digital Elevation Map Outputs: azimuth and elevation angles affected KML files of nearest Weather Radar and specific turbines Page 10

11 Addition of Geographic Information Systems (GIS) Needed an easy way to visualize multiple proposals Produce maps for public, forecasters, wind farm proponents, and government ESRI s ArcGIS used Easy input and interface allow for efficient updates of information in KML, CSV, Shapefile, Raster or Vector format Page 11

12 Radar Visibility Maps Radar-centric view of surrounding terrain with values representing maximum height of a tower that can be seen by the radar Point values converted into raster to create smoother view Colours represent range of tower heights that can be seen by the radar Ex: 150 meter tower can be seen by radar in purple but not in yellow Page 12

13 Radar Visibility Maps Takes into account blockage by terrain (land) Does not account for other sources of blockage: such as towers, buildings and vegetation Although a wind farm may be visible to the radar it does not necessarily imply negative interactions Allows a first step analysis for wind farm proponents Page 13

14 Upcoming Website Contains background information about the interaction between wind farm and weather radar Contains national, regional and local radar visibility maps In final publication stages and approvals Page 14

15 Summary Wind farms in proximity to weather radars can cause: Blockage Multi-path scattering Wind turbine clutter Overestimations of precipitation GIS tools have aided in wind farm analysis with respect to Canadian weather radars Easier documentation and visualization Improved efficiency Page 15

16 Thank you! Carolyn Rennie acknowledges the advice, support and contributions from the following people: Norman Donaldson Jim M.C. Young Stephen Holden Marie MacPhee Leonard Szarko Bob Paterson Zlatko Vukovic David Sills Robert Crawford Heather Reynolds & Ryan Pimiskern Damon Wilson Page 16

17 Page 17

18 Additional Slides Page 18

19 Refraction No Refraction Positive Refraction Clear weather after sundown at temperature inversion Super Refraction (Ducting) At high pressure levels with a temperature inversion Prominent in night and morning hours Page 19

20 Wind Turbine Description Wind turbines are massive structures containing a large tower (hub) connecting to three or more large blades Typical hub heights range from 60 m to 120 m Typical blade lengths range from 20 m to 52 m although their sizes are expected to increase Wind turbines generate power by way of the rotating blades Preferable site locations are in higher elevations with strong winds Example of a small wind turbine Page 20

21 Doppler Reflectivity of a Wind Farm This shows the temporal variability of the echoes received Circles indicate locations of turbines Page 21

22 Doppler Correction Example Page 22

23 Doppler Correction Doppler correction can filter out the stationary hubs but leave substantial holes in the radar data corrected dbz Page 23 uncorrected dbz

24 Multi-Path Scattering Multi-path scattering occurs when a radar signal does not take a direct path to the target and back Radar signal normally hits a target and returns the signal In the case of turbines, the signal bounces around and the eventually returns to the radar The signal takes longer than expected but the signal processor cannot figure that out and gets confused Page 24

25 Trent Mesa Wind Farm 100+ turbines Hub height = m Blade length = m 25 km away from KDYX (Dyess Air Force Base) Page 25

26 Spirit River Radar This is Doppler-corrected reflectivity at a single time, with the turbine positions marked. The echoes are not at the turbines! Almost all are behind! Page 26

27 Effect on Point Forecasts Included in the zip file is a animation loop recovered from The Weather Network in which their forecasting algorithm predicts from the last image Since these two wind farms are always visible on radar they are predicted to move south east This is misleading to forecasters and the general public who would not know of the stationary nature of the wind farm returns and may see them as possible storm cells Page 27

28 Typical Data Analysis Output The analysis output by the program includes some of the following information which is helpful to determining possible wind farm impacts Min/Max range from the radar to any turbine Azimuth extent of the wind farm (represents the size of the impacted sector) Maximum tip elevation above terrain (represents the highest angle of elevation in which the radar can still view a turbine blade tip) Maximum hub elevation above terrain (represents the highest angle of elevation in which the radar can still view a turbine hub) Number of turbines with tip-above-terrain > 0.2 (how many turbine blade tips can be seen at a radar elevation angle of 0.2 ) Number of turbines with hub-above-terrain > 0.2 (how many turbine blade tips can be seen at a radar elevation angle of 0.2 ) Page 28

29 Page 29

30 Page 30

31 Page 31

32 Page 32

33 Page 33

34 Page 34

35 Page 35

36 Page 36

37 Page 37

38 Page 38

39 Page 39

40 Page 40

41 Page 41

42 Page 42

43 Page 43

44 Page 44

45 Page 45

46 Page 46

47 Page 47

48 Page 48