Browse > Article
http://dx.doi.org/10.7836/kses.2017.37.6.025

Analysis of Factors Influencing the Measurement Error of Ground-based LiDAR  

Kang, Dong-Bum (Multidisciplinary Graduate School Program for Wind Energy, Graduate School, Jeju National University)
Huh, Jong-Chul (Faculty of Mechanical Engineering, College of Engineering, Jeju National University)
Ko, Kyung-Nam (Faculty of Wind Energy Engineering, Graduate School, Jeju National University)
Publication Information
Journal of the Korean Solar Energy Society / v.37, no.6, 2017 , pp. 25-37 More about this Journal
Abstract
A study on factors influencing measurement error of Ground-based LiDAR(Light Detection And Ranging) system was conducted in Kimnyeong wind turbine test site on Jeju Island. Three properties of wind including inclined angle, turbulence intensity and power law exponent were taken into account as factors influencing the measurement error of Ground-based LiDAR. In order to calculate LiDAR measurements error, 2.5-month wind speed data collected from LiDAR (WindCube v2) were compared with concurrent data from the anemometer on a nearby 120m-high meteorological mast. In addition, data filtering was performed and its filtering criteria was based on the findings at previous researches. As a result, at 100m above ground level, absolute LiDAR error rate with absolute inclined angle showed 4.58~13.40% and 0.77 of the coefficients of determination, $R^2$. That with turbulence intensity showed 3.58~23.94% and 0.93 of $R^2$ while that with power law exponent showed 4.71~9.53% and 0.41 of $R^2$. Therefore, it was confirmed that the LiDAR measurement error was highly affected by inclined angle and turbulence intensity, while that did not much depend on power law exponent.
Keywords
Wind energy; Wind data; Light detection and ranging (LiDAR) system; Inclined angle; Turbulence intensity; Wind shear;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
연도 인용수 순위
1 B. Canadillas, A. Westerhellweg, T. Neumann, Testing the Performance of a Ground-based Wind LiDAR System, DEWI Magazine, No. 38, pp. 58-64, 2011.
2 Measnet, Evaluation of Site-specific Wind Conditions, Version 1, pp. 14-18, 2009.
3 A., Gonzalez-Jorge, H., Laguela, S., Diaz-Vilarino, L., and Arias, P., Quantifying the influence of rain in LiDAR performance, Measurement, Vol. 95, pp. 143-148, 2017.   DOI
4 International Electrotechnical Commission (IEC), IEC 61400-12-1, Wind Turbines - Power performance measurements of electricity producing wind turbines, 1st ed., IEC, pp. 15, 33-35, 2005.
5 Kang, D., Hyeon, J., Yang, K., Huh, J., and Ko, K., Analysis and Verification of Wind Data from Ground-based LiDAR, International Journal of Renewable Energy Research, Vol. 7, No. 2, 2017.
6 International Electrotechnical Commission (IEC), IEC 61400-1, Wind Turbines - Design requirements, 3rd ed., IEC, pp. 21-23, 2005.
7 Windographer 3.3.11 User Manual, https://www.windographer.com.
8 International Electrotechnical Commission (IEC), IEC 61400-12-1, Wind Turbines - power performance measurements of electricity producing wind turbines, Draft FDIS, IEC, pp. 31, 2016.
9 Boquet, M., Ribstein, B., Parmentier, R., Sauvage, L., and Cariou, J., Analysis and Optimisation of Pulsed Doppler Lidar Wind Profile Measurement Process in Complex Terrain, 15th Coherent Laser Radar Conference Proceedings, pp. 69-72, 2008.
10 Kim, H. and Meissner, C., 2017, Correction of LiDAR Measurement Error in Complex Terrain by CFD: Case Study of the Yangyang Pumped Storage Plant, Wind Engineering, Vol. 41, No. 4, pp. 226-234.   DOI
11 Jain Pramod, Wind Energy Engineering, Mc GrawHill Companies, Inc., pp. 101-104, 2011.
12 Deutsche WindGuard Consulting GmbH, Evaluation of ZephIR(Project No: VC 05250, Report No: PWG 06005), Deutsche WindGuard Consulting GmbH, 2006.
13 Manwell J. F., McGowan J. G., and Rogers A. L., Wind Energy Explained: Theory, Design and Application, 2nd ed., Wiley, pp. 39-48, 2009.
14 World Wind Energy Association (WWEA). Wind Energy International 2014/2015, WWEC, pp. 9-24, 2013.
15 Joint Research Centre (JRC). 2014 JRC wind status report, JRC, pp. 16-17, 2015.
16 Kim, H. G., Chyng, C. W., An, H. J., and Ji, Y. M., Comparative Validation of WindCube LIDAR and Remtech SODAR for Wind Resource Assessment - Remote Sensing Campaign at Pohang Accelerator Laboratory, Journal of the Korean Solar Energy Society, Vol. 31, No. 2, pp. 63-71, 2011.   DOI
17 Kim, H. G. and Choi, J. H., Uncertainty Analysis on Wind Speed Profile Measurements of LIDAR by Applying SODAR Measurements as a Virtual True Value, Journal of the Korean Solar Energy Society, Vol. 30, No. 4, pp. 79-85, 2010.
18 Renewable Energy Research Laboratory, MTC Final Progress Report-LIDAR, University of Massachusetts, 2007.
19 Kindler, D., Courtney, M., and Oldroyd, A., 2009, Testing and calibration of various lidar remote sensing devices for a 2 year offshore wind measurement campaign, EWEC, pp. 141-143.
20 Kim, D., Kim, T., Oh, G., Huh, J., and Ko, K., A Comparison of Ground-based LiDAR and Met Mast Wind Measurements for Wind Resource Assessment Over Various Terrain Conditions, Journal of Wind Engineering and Industrial Aerodynamics, Vol. 158, pp. 109-121, 2016.   DOI
21 Hyundai Heavy Industries, Business - Green Energy, https://english.hhi.co.kr.
22 Hyosung Power & Industrial systems, Products & Solutions - Green Energy, https://www.hyosungpni.co.kr.
23 Leosphere, WindCube v2 LiDAR Remote Sensor User Manual version 06, Leosphere, pp.18-19.
24 Brower M. C., Wind Resource Assessment, John Wiley & Sons, Inc, pp. 105-114, 2012.
25 Thies Clima, The product information, https://www.thiesclima.com.