Systems and methods of coordinated yaw control of multiple wind turbines
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.
1 . A method of control and optimization of wind turbines comprising:
analyzing environmental conditions across an area occupied by a plurality of wind turbines;
collecting and analyzing yaw control data of one or more of the plurality of wind turbines;
collecting and analyzing wind direction data across the area occupied by the plurality of wind turbines and determining a collective wind direction across the area;
determining whether the one or more of the plurality of wind turbines has a relative wind direction measurement bias causing yaw misalignment;
if the one or more of the plurality of wind turbines has a yaw misalignment, calculating a static yaw misalignment error based on the environmental conditions; and
applying the yaw misalignment error as an offset correction regularly to account for the environmental conditions and correct the static yaw misalignment error.
2 . The method of claim 1 wherein the environmental conditions comprise one or more of: air density, temperature, and turbulence.
3 . The method of claim 1 wherein the regular application of the static yaw misalignment error as an offset correction is at intervals of seconds, minutes, or hours.
4 . The method of claim 1 further comprising performing data analytics and optimization and the calculating of the static yaw misalignment error as an offset correction in a cloud.
5 . The method of claim 1 further comprising providing monitoring and control capability via a graphical user interface.
6 . The method of claim 1 wherein the calculating and applying of the static yaw misalignment error as an offset correction is performed for only a subset of the plurality of wind turbines.
7 . A method of autonomous farm-level control and optimization of wind turbines comprising:
collecting and analyzing yaw control data of one or more of a plurality of wind turbines;
collecting and analyzing wind direction data across an area occupied by the plurality of wind turbines;
predicting area conditions across an area occupied by the plurality of wind turbines, the area conditions including one or more of: wind direction change, wind speed change, onset of icing, and extreme wind events;
determining desired nacelle yaw positions of one or more of the plurality of wind turbines from a collective yaw optimization of the plurality of wind turbines based upon analysis of the yaw control data, wind direction data, and power production data; and
sending yaw control signals including instructions for the desired nacelle yaw positions to one or more of the plurality of wind turbines in advance of the predicted area conditions such that the wind turbines move dynamically and each wind turbine aligns its nacelle to its respective desired nacelle yaw position to improve performance of the plurality of wind turbines as a function of time.
8 . The method of claim 7 further comprising determining which of the plurality of wind turbines are upstream wind turbines and derating one or more of the upstream wind turbines to prepare for one or more of the predicted area conditions.
9 . The method of claim 7 further comprising providing monitoring and control capability via a graphical user interface.
10 . A method of control and optimization of wind turbines comprising:
collecting and analyzing yaw control data of a plurality of wind turbines;
collecting and analyzing wind direction data across an area occupied by the plurality of wind turbines;
determining a subset of the plurality of wind turbines to control;
determining desired nacelle yaw positions for the subset of the plurality of wind turbines from a collective yaw optimization of the plurality of wind turbines based upon analysis of the yaw control data and the wind direction data; and
sending nacelle yaw position instructions to the subset of the plurality of wind turbines such that the subset of the plurality of wind turbines moves dynamically and each of the subset of the plurality of wind turbines aligns its nacelle to a collectively determined wind direction correcting the bias in the relative wind direction measurement on each turbine.
11 . The method of claim 10 further comprising determining which of the subset of the plurality of wind turbines are upstream wind turbines and assigning the upstream wind turbines desired nacelle yaw positions of the nacelle relative to its respective tower such that the downstream wind turbines increase power production.
12 . The method of claim 10 further comprising performing data analytics and optimization in a cloud.
13 . A system of collective yaw control of a plurality of wind turbines comprising:
a turbine control module in a turbine control unit of each of a plurality of wind turbines, each wind turbine including a tower and a nacelle mounted to the top of the tower;
a software module in the turbine control unit of each of the plurality of wind turbines, the software module collecting and analyzing yaw control data of a plurality of wind turbines and wind direction data relating to the plurality of wind turbines, determining collective wind direction across an area occupied by the plurality of wind turbines, determining desired nacelle yaw position from a collective yaw optimization of the wind turbines, and sending yaw control signals including desired nacelle yaw position instructions to the turbine control module such that each wind turbine moves its nacelle to the desired yaw position relative to true north;
wherein one or more of the plurality of wind turbines communicates wind information to another of the plurality of wind turbines to maximize performance of the plurality of wind turbines.
14 . The system of claim 13 wherein the software module aligns the plurality of wind turbines to achieve collective yaw optimization.
15 . The system of claim 13 wherein the software module performs wake steering to reduce wake interaction and wake losses.
16 . The system of claim 13 further comprising a graphical user interface for remote monitoring and controlling of the system.
17 . The system of claim 16 wherein the graphical user interface includes real-time feedback on behavior of the decentralized system and an on/off control.
18 . The system of claim 13 wherein the desired nacelle yaw position instructions are computed for the plurality of turbines in bins of wind speed, wind direction, and nacelle turbulence intensity present in SCADA data.