Patent №
US 11,639,710
Granted
2023-05-02
Filed 2022
Owner
WINDESCO, INC.
Lab
—
AI components
1
planning
Assignment
Recorded
Dataset
AIPD
2023_r1 edition
Application
17847701
Systems and methods of autonomous farm-level control and optimization of wind turbines are provided. Exemplary embodiments comprise a site controller running on a site server. The site controller collects and analyzes yaw control data of a plurality of wind turbines and wind direction data relating to the plurality of wind turbines. The site server determines collective wind direction across an area occupied by the plurality of wind turbines and sends yaw control signals including desired nacelle yaw position instructions to the plurality of wind turbines. The site controller performs wake modeling analysis and determines desired nacelle positions of one or more of the plurality of wind turbines. The desired nacelle yaw position instructions systematically correct static yaw misalignment for all of the plurality of wind turbines. Embodiments of the disclosure provide means to perform whole site or partial site level controls of the yaw controllers of a utility scale wind turbine farm. The overall effect of the coordinated yaw control of wind turbines across the whole or partial site is intended to keep the wake loss of the wind turbines from the upstream wind turbines to the minimum and to maximize the production of turbines that are not waking other turbines.
AI classification
Ownership
WINDESCO, INC.
assignment · 611230855
Assignors
POST, NATHAN L., ZHENG, DANIAN, BACHANT, PETER
On an employer assignment, the assignors are typically the inventors.