Incorporating a stochastic data-driven inflow model for uncertainty quantification of wind turbine performance: Incorporating a stochastic data-driven inflow model for uncertainty quantification of wind turbine performance
Title: Incorporating a stochastic data-driven inflow model for uncertainty quantification of wind turbine performance: Incorporating a stochastic data-driven inflow model for uncertainty quantification of wind turbine performance
Duarte, Thays G.; Arunachalam, Srinivasan; Subgranon, Arthriya; Spence, Seymour M.(
, 14th International Conference on Applications of Statistics and Probability in Civil Engineering (ICASP14))
MartÃnez-Tossas, Luis A.; Churchfield, Matthew J.; Yilmaz, Ali Emre; Sarlak, Hamid; Johnson, Perry L.; Sørensen, Jens N.; Meyers, Johan; Meneveau, Charles(
, Journal of Renewable and Sustainable Energy)
Guo, Q., and Ganapathysubramanian, B. Incorporating a stochastic data-driven inflow model for uncertainty quantification of wind turbine performance: Incorporating a stochastic data-driven inflow model for uncertainty quantification of wind turbine performance. Wind Energy 20.9 Web. doi:10.1002/we.2108.
Guo, Q., & Ganapathysubramanian, B. Incorporating a stochastic data-driven inflow model for uncertainty quantification of wind turbine performance: Incorporating a stochastic data-driven inflow model for uncertainty quantification of wind turbine performance. Wind Energy, 20 (9). https://doi.org/10.1002/we.2108
Guo, Q., and Ganapathysubramanian, B.
"Incorporating a stochastic data-driven inflow model for uncertainty quantification of wind turbine performance: Incorporating a stochastic data-driven inflow model for uncertainty quantification of wind turbine performance". Wind Energy 20 (9). United Kingdom: Wiley Blackwell (John Wiley & Sons). https://doi.org/10.1002/we.2108.https://par.nsf.gov/biblio/10036111.
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