Data-driven parameter calibration in wake models

Bingjie Liu, Eunshin Byon, Matthew Plumlee

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

Abstract

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
Edition210029
ISBN (Print)9781624105227
DOIs
StatePublished - Jan 1 2018
EventWind Energy Symposium, 2018 - Kissimmee, United States
Duration: Jan 8 2018Jan 12 2018

Publication series

NameWind Energy Symposium, 2018
Number210029

Other

OtherWind Energy Symposium, 2018
CountryUnited States
CityKissimmee
Period1/8/181/12/18

ASJC Scopus subject areas

  • Mechanical Engineering
  • Renewable Energy, Sustainability and the Environment

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