Data-driven parameter calibration in wake models

Bingjie Liu, Eunshin Byon, Matthew Plumlee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations


Physical interactions among wind turbines, called wake effects, are known to be one of the significant factors that affect power generation performance in wind power systems. Among several wake modeling approaches, physics-based engineering models, such as Jensen’s model, have been widely used due to their computational tractability. Although substantial efforts have been made to improve the accuracy of engineering wake models, few studies suggest calibrating the model parameters in the literature. We propose a new data-driven calibration approach for adjusting the model parameters using real operational data.

Original languageEnglish (US)
Title of host publicationWind Energy Symposium
PublisherAmerican Institute of Aeronautics and Astronautics Inc, AIAA
ISBN (Print)9781624105227
StatePublished - 2018
EventWind Energy Symposium, 2018 - Kissimmee, United States
Duration: Jan 8 2018Jan 12 2018

Publication series

NameWind Energy Symposium, 2018


OtherWind Energy Symposium, 2018
Country/TerritoryUnited States

ASJC Scopus subject areas

  • Renewable Energy, Sustainability and the Environment
  • Mechanical Engineering


Dive into the research topics of 'Data-driven parameter calibration in wake models'. Together they form a unique fingerprint.

Cite this