公开(公告)号：US20240328387A1

公开(公告)日：2024-10-03

申请号：US18619629

申请日：2024-03-28

申请人： WindESCo, Inc.

发明人： Peter Bachant ,  Peter Ireland ,  Brian Burrows ,  Venkatakrishna Vadlamudi ,  Nathan L. Post ,  Mohit Dua ,  Danian Zheng

IPC分类号： F03D7/04

CPC分类号： F03D7/049 ,  F03D7/045 ,  F03D7/046 ,  F05B2260/84 ,  F05B2270/32 ,  F05B2270/321

摘要： Systems and methods of predicting performance of one or more wind turbines are provided. Exemplary methods include entering data inputs and analyzing and estimating the data inputs. The data inputs include nacelle position information and/or wind condition information. A wake model is determined based on the analysis and estimating of the data inputs. Wind turbine behavior predictions are generated including predicted power outputs of the wind turbines and predicted effects of waking on the predicted power outputs. The data inputs can be adjusted to improve the wind turbine behavior predictions, and the wake model can be corrected by machine learning. By focusing on an observable quantity—power—based on other observable quantities like wind speed, yaw error, nacelle position, disclosed embodiments enable optimization to start immediately after the hardware and software are installed, and as the controller operates more in the field, additional training and validation data are collected.