Shorter wind measurement campaigns Re-thinking with LiDAR
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1 Shorter wind measurement campaigns Re-thinking with LiDAR 31/05/2013 Ecofys Lidewij van den Brink, Anthony Crockford, Hector Villanueva, Jean Grassin
2 Introducing Ecofys > Consultancy, 30 year experience in Wind Energy > Operating a wind turbine test site in Lelystad > Operating 6 LiDARs (4 ZephIRs, 2 Windcubes) > Looking for clever/efficient way of using our LiDARs
3 Standard campaign for yield prediction. Why? > 12 month wind measurement campaign > Extended to long-term using MCP to a long-term reference > Shorter measurement campaign yield poor results (even after MCP)
4 Standard campaign for yield prediction. Why? > MCP Shorter method measurement is a statistical campaign method. yield Does poor to results account (even for physical after MCP) reality > Significant seasonal variation of a number of physical characteristics o o o Stability Wind farm surrounding Weather patterns Monthly wind speed variations 6 measurement heights
5 How can we go for shorter measurement campaigns Without decreasing the resulting WS accuracy!!
6 How can we go for shorter measurement campaigns Without decreasing the resulting WS accuracy!! > Method 1: Seasonally sampled wind measurement campaign > Method 2: implementing stability correction during MCP
7 Method 1 Seasonally Sampled Wind measurement campaign
8 Seasonally sampled wind measurement campaign Site 1 Site 1 Site 1 Site 1 12 months Site 2 Site 2 Site 2 Site 2 > Pros: all seasons covered, 2 sites assessed with one machine in one year > Cons: More deployment effort / costs > Testing the accuracy at Dutch site (simple terrain)
9 Pushing the concept further > Carrying out four 4x3 weeks measurement across the year > Future work: Optimize approach (4 x 4 weeks 3 sites, 4x3 weeks) > Future work: verify in different climate
10 Method 2 Implementing stability correction in the MCP method
11 Implementing a stability correction in MCP method > Extrapolate the long-term reference wind speed to hub height > Include correction for stability in extrapolation At LT measurement location At short-term measurement location Target height MCP
12 Implementing a stability correction in MCP method > Extrapolate the long-term reference wind speed to hub height > Include correction for stability in extrapolation At LT measurement location Target height > 2 Layer model (Holtslag) > Stability correction based on A. P. van Ulden and A. A. M. Holtslag (1985) > Inputs required Air temperature Humidity Global radiation Cloud cover Air pressure
13 Testing the stability correction > Cabauw Met Mast, 213 m tall, operated since 1973 > Use MCP (Matrix) to hindcast wind at 140m over period based on measurement in 2012 > Comparison of MCP results using 4 different reference time-series KNMI Meteorological station (10m height) Re-analysis data MERRA (50m height) KNMI incl. stability correction MERRA incl stability correction > MCP based on 1 year to reproduce 10 y > MCP based on 3 months (winter) > MCP based on 3 months (summer)
14 Testing the stability correction > Comparison between measured and modeled 10y time series > Focus on physical characteristics of wind time series modeled Seasonal variation of wind speed Diurnal variations Correlation of time series Weibull parameters Resulting AEP using assumed WTG
15 MCP based on 10m meteo station records No stability correction Seasonal variations > Seasonal variation of wind speed (at 140m) > Measured pattern (red) vs modeled pattern (green) MCP based on full year 2012 MCP based on winter 2012 MCP based on summer 2012
16 MCP based on 10m meteo station records With stability correction Seasonal variations > Seasonal variations of wind speed (at 140m) > Measured (red); 10m without stability correction (green) and 10m with stability correction (purple) MCP based on full year 2012 MCP based on winter 2012 MCP based on summer 2012
17 MCP -10m measurement With or without stability correction - Diurnal pattern > Diurnal variations of wind speed (at 140m) > Measured (red); 10m without stability correction (green) and 10m with stability correction (purple) MCP based on full year 2012 MCP based on winter 2012 MCP based on summer 2012
18 MCP based on MERRA 50m measurement with or without correction for stability seasonal pattern > Seasonal variations of wind speed (at 140m) > Measured (red); 50m without stability correction (blue) and 10m with stability correction (Grey) MCP based on full year 2012 MCP based on winter 2012 MCP based on summer 2012
19 MCP based on MERRA 50m measurement with or without correction for stability Diurnal pattern > Diurnal variations of wind speed (at 140m) > Measured (red); 50m without stability correction (blue) and 10m with stability correction (Grey) MCP based on full year 2012 MCP based on winter 2012 MCP based on summer 2012
20 Comparison of results 140m whole 2012 Measured 10m 10m corrected MERRA MERRA Corrected Correlation Wind Speed Weibul k Delta AEP % -1.9% -2.4% -3.8%
21 Comparison of results 140m whole 2012 Measured 10m 10m corrected MERRA MERRA Corrected Correlation Wind Speed Weibul k Delta AEP % -1.9% -2.4% -3.8% Delta AEP Base summer 2012 Delta AEP Base winter % -4.00% -7.90% -6.10% 10.4% -16.7% 1.4% -5.3%
22 So shorter measurement campaign with stability correction? Consecutive measurements Consecutive measurements with Stability correction in MCP 12 months 6 months 3 months Measurement length
23 Conclusion 1. Seasonally sampled wind measurement is promising and cost effective 2. Stability correction will be necessary as we go for larger WTG 3. Simple stability model improves significantly the physical behavior of the modeled time series 4. But significant modeling effort still required Implement new solutions? Meso-scale model
24 Additional information > Question me now > Further details: Lidewij van den Brink +31(0) Jean Grassin +31(0)
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