公开(公告)号：US11789034B1

公开(公告)日：2023-10-17

申请号：US18126027

申请日：2023-03-24

Applicant: North China Electric Power University ,  Huaneng Group Technology Innovation Center Co., Ltd

Inventor： Yang Hu ,  Fang Fang ,  Siqi Chen ,  Jizhen Liu ,  Xiaojiang Guo ,  Qinghua Wang

IPC: G01P5/26 ,  G01S17/58 ,  G01S17/95

CPC classification number: G01P5/26 ,  G01S17/58 ,  G01S17/95

Abstract: The present invention discloses an intelligent soft measurement method for wind speed in front of a wind turbine. The method includes: first using laser radar data as a data sample, judging delay orders between input and output by using an AIC or BIC criterion, defining a dynamic difference regression vector according to the delay orders, dividing hyperplanes according to a clustering result by using a machine learning algorithm, and performing dynamic differential input/output nonlinear mapping modeling in a global scope and sub-scopes by using an artificial intelligence dynamic regression algorithm, respectively. Empirical mode decomposition and power spectral density analysis are performed on the wind speed in front of a laser radar measuring machine and the wind speed in front of a soft measurement machine, thereby further verifying the estimation performance of intelligent soft measurement for the wind speed in front of a wind turbine.