{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,13]],"date-time":"2026-02-13T08:54:05Z","timestamp":1770972845818,"version":"3.50.1"},"reference-count":24,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2018,3,25]],"date-time":"2018-03-25T00:00:00Z","timestamp":1521936000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100008421","name":"Electric Power Research Institute","doi-asserted-by":"publisher","award":["10001389"],"award-info":[{"award-number":["10001389"]}],"id":[{"id":"10.13039\/100008421","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000006","name":"Office of Naval Research","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000006","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Wind gusts on a scale from 100 m to 1000 m are studied due to their significant influence on wind turbine performance. A detecting and tracking algorithm is proposed to extract gusts from a wind field and track their movement. The algorithm utilizes the \u201cpeak over threshold method,\u201d Moore-Neighbor tracing algorithm, and Taylor\u2019s frozen turbulence hypothesis. The algorithm was implemented for a three-hour, two-dimensional wind field retrieved from the measurements of a coherent Doppler lidar. The Gaussian shape distribution of the gust spanwise deviation from the streamline was demonstrated. Size dependency of gust deviations is discussed, and an empirical power function is derived. A prediction model estimating the impact of gusts with respect to arrival time and the probability of arrival locations is introduced, in which the Gaussian plume model and random walk theory including size dependency are applied. The prediction model was tested and the results reveal that the prediction model can represent the spanwise deviation of the gusts and capture the effect of gust size. The prediction model was applied to a virtual wind turbine array, and estimates are given for which wind turbines would be impacted.<\/jats:p>","DOI":"10.3390\/rs10040514","type":"journal-article","created":{"date-parts":[[2018,3,26]],"date-time":"2018-03-26T03:43:29Z","timestamp":1522035809000},"page":"514","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":27,"title":["Wind Gust Detection and Impact Prediction for Wind Turbines"],"prefix":"10.3390","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7190-6710","authenticated-orcid":false,"given":"Kai","family":"Zhou","sequence":"first","affiliation":[{"name":"Mechanical Engineering, Arizona State University, Tempe, AZ 85287, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nihanth","family":"Cherukuru","sequence":"additional","affiliation":[{"name":"National Center for Atmospheric Research, Boulder, CO 80305, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaoyu","family":"Sun","sequence":"additional","affiliation":[{"name":"Data Science Group, SAP, 1101 W Washington St #401, Tempe, AZ 85281, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ronald","family":"Calhoun","sequence":"additional","affiliation":[{"name":"Mechanical Engineering, Arizona State University, Tempe, AZ 85287, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2018,3,25]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Schlipf, D., Pao, L.Y., and Cheng, P.W. (2012, January 10\u201313). Comparison of feedforward and model predictive control of wind turbines using LIDAR. Proceedings of the Conference on Decision and Control, Maui, HI, USA.","DOI":"10.1109\/CDC.2012.6426063"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Scholbrock, A., Fleming, P., Fingersh, L., Wright, A., Schlipf, D., Haizmann, F., and Belen, F. (2013, January 7\u201310). Field testing LIDAR based feed-forward controls on the NREL controls advanced research turbine. Proceedings of the 51th AIAA Aerospace Sciences Meeting Including the New Horizons Forum and Aerospace Exposition, Grapevine, TX, USA.","DOI":"10.2514\/6.2013-818"},{"key":"ref_3","unstructured":"Kumar, A.A., Bossanyi, E.A., Scholbrock, A.K., Fleming, P., Boquet, M., and Krishnamurthy, R. (2015, January 17\u201320). Field Testing of LIDAR-Assisted Feedforward Control Algorithms for Improved Speed Control and Fatigue Load Reduction on a 600-kW Wind Turbine: Preprint. Presented at the EWEA 2015 Annual Event, Golden, CO, USA."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Kristalny, M., and Madjidian, D. (2011, January 12\u201315). Decentralized feedforward control of wind farms: Prospects and open problems. Proceedings of the 2011 50th IEEE Conference on Decision and Control and European Control Conference, Orlando, FL, USA.","DOI":"10.1109\/CDC.2011.6161332"},{"key":"ref_5","unstructured":"International Electrotechnical Commission (2005). International Standard, IEC 61400-1, Wind Turbines\u2014Part 1: Design Requirements, International Electrotechnical Commission. [3rd ed.]."},{"key":"ref_6","unstructured":"Branlard, E. (2009). Wind energy: On the statistics of gusts and their propagation through a wind farm. [ECN-Wind-Memo-09-005Master\u2019s Thesis, Energy research Centre of the Netherlands]."},{"key":"ref_7","unstructured":"Beljaars, A.C. (1987). The Measurement of Gustiness at Routine Wind Stations: A Review, World Meteorological Organization."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Kelley, N., Shirazi, M., Jager, D., Wilde, S., Adams, J., Buhl, M., and Patton, E. (2004). Lamar Low-Level Jet Project Interim Report.","DOI":"10.2172\/15006544"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"339","DOI":"10.1002\/we.1700","article-title":"Turbulence effects on a full-scale 2.5 MW horizontal-axis wind turbine under neutrally stratified conditions","volume":"18","author":"Chamorro","year":"2015","journal-title":"Wind Energy"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1585","DOI":"10.1175\/JTECH-D-11-00225.1","article-title":"Two-component horizontal aerosol motion vectors in the atmospheric surface layer from a cross-correlation algorithm applied to scanning elastic backscatter lidar data","volume":"29","author":"Mayor","year":"2012","journal-title":"J. Atmos. Ocean. Technol."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Mayor, S.D., D\u00e9rian, P., Mauzey, C.F., and Hamada, M. (2013, January 17). Two-component wind fields from scanning aerosol lidar and motion estimation algorithms. Proceedings of the SPIE Optical Engineering+ Applications, San Diego, CA, USA.","DOI":"10.1117\/12.2025337"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"497","DOI":"10.1016\/j.egypro.2017.10.378","article-title":"2D VAR single Doppler lidar vector retrieval and its application in offshore wind energy","volume":"137","author":"Cherukuru","year":"2017","journal-title":"Energy Proced."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"157","DOI":"10.1117\/1.1455013","article-title":"Scattered data interpolation methods for electronic imaging systems: A survey","volume":"11","author":"Amidror","year":"2002","journal-title":"J. Electron. Imaging"},{"key":"ref_14","unstructured":"(2017, October 09). Moore-Neighbor Tracing. Available online: http:\/\/www.imageprocessingplace.com\/downloads_V3\/root_downloads\/tutorials\/contour_tracing_Abeer_George_Ghuneim\/moore.html."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Batchelor, G.K. (1952). Diffusion in a field of homogeneous turbulence: II. The relative motion of particles. Mathematical Proceedings of the Cambridge Philosophical Society, Cambridge University Press.","DOI":"10.1017\/S0305004100027687"},{"key":"ref_16","unstructured":"Petersen, W.B., Catalano, J.A., Chico, T., and Yuen, T.S. (1984). INPUFF-A Single Source Gaussian Puff Dispersion Algorithm: User\u2019s Guide."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Hanna, S.R., Briggs, G.A., and Hosker, R.P. (1982). Handbook on Atmospheric Dispersion.","DOI":"10.2172\/5591108"},{"key":"ref_18","unstructured":"Sykes, R.I., Parker, S.F., Henn, D.S., Cerasoli, C.P., and Santos, L.P. (1998). PC-SCIPUFF Version 1.2 PD Technical Documentation, Titan Corporation, Titan Research & Technology Division, ARAP Group. ARAP Report No. 718."},{"key":"ref_19","unstructured":"Thykier-Nielsen, S., Deme, S., and Mikkelsen, T. (2018, March 25). Description of the atmospheric dispersion module RIMPUFF. Available online: https:\/\/s3.amazonaws.com\/academia.edu.documents\/39632120\/Description_of_the_atmospheric_dispersio20151103-1858-w1thfx.pdf?AWSAccessKeyId=AKIAIWOWYYGZ2Y53UL3A&Expires=1521966958&Signature=vnkIK16SU2hvkTa3L7PZWujwIB8%3D&response-content-disposition=inline%3B%20filename%3DDescription_of_the_atmospheric_dispersio.pdf."},{"key":"ref_20","unstructured":"Leone, J.M., Nasstrom, J.S., Maddix, D.M., Larson, D.J., Sugiyama, G., and Ermak, D.L. (2005). Lagrangian Operational Dispersion Integrator (LODI) User\u2019s Guide."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"2394","DOI":"10.1175\/JAS-D-14-0335.1","article-title":"Revisiting the turbulent Prandtl number in an idealized atmospheric surface layer","volume":"72","author":"Li","year":"2015","journal-title":"J. Atmos. Sci."},{"key":"ref_22","unstructured":"Kundu, P.K., Cohen, I.M., and Dowling, D.W. (2008). Fluid Mechanics, Academic Press. [4th ed.]."},{"key":"ref_23","unstructured":"Price, J.F. (2005). Lagrangian and Eulerian representations of fluid flow: Part I, kinematics and the equations of Motion, Clark Laboratory Woods Hole Oceanographic Institution."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1175","DOI":"10.1175\/JAS3393.1","article-title":"Relating Eulerian and Lagrangian statistics for the turbulent dispersion in the atmospheric convective boundary layer","volume":"62","author":"Dosio","year":"2005","journal-title":"J. Atmos. Sci."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/10\/4\/514\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T14:58:27Z","timestamp":1760194707000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/10\/4\/514"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,3,25]]},"references-count":24,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2018,4]]}},"alternative-id":["rs10040514"],"URL":"https:\/\/doi.org\/10.3390\/rs10040514","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,3,25]]}}}