Uncertainty quantification pertinent to wind farm flow physics and modeling

Pankaj K. Jha, Aleksandar Jemcov, Chris Sideroff, Guolei Wang, Sven Schmitz

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

Abstract

This paper attempts to identify and quantify the uncertainties associated with the wind farm modeling and flow physics in wind farms. Different aspects and types of uncertainties in modeling the atmosphere and rotor using different fidelity methods are presented. A description of the uncertainty quantification algorithms is also presented. This is followed by some case studies on the identification and quantification of relevant uncertainties. The first one pertains to the input parameters and model constants for a wind resource assessment problem on a complex terrain. The second one explains the uncertainties associated with a turbine-turbine interaction problem in atmospheric boundary-layer flow using different actuator line modeling approaches for rotors. This is further exemplified using the aleatoric and epistemic uncertainties in blade loads as a result of using an actuator line method, followed by a discussion on the physical propagation of these uncertainties downstream. The third type of case study is that of a 3-D cosine hill where the polynomial chaos algorithm is applied to propagate the uncertainties in model constants for Reynolds-averaged Navier-Stokes equations and to investigate their effect on the flow-field.

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

Publication series

NameWind Energy Symposium, 2018

Conference

ConferenceWind Energy Symposium, 2018
Country/TerritoryUnited States
CityKissimmee
Period1/8/181/12/18

All Science Journal Classification (ASJC) codes

  • Renewable Energy, Sustainability and the Environment
  • Mechanical Engineering

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