Systems and methods for optimizing operation of a wind farm
IPC분류정보
국가/구분
United States(US) Patent
등록
국제특허분류(IPC7판)
G05D-003/12
G05D-005/00
G05D-009/00
G05D-011/00
G05D-017/00
F03D-009/00
H02P-009/04
F03D-007/04
G05B-013/04
출원번호
US-0692115
(2015-04-21)
등록번호
US-9551322
(2017-01-24)
우선권정보
IN-2155/CHE/2014 (2014-04-29)
발명자
/ 주소
Ambekar, Akshay Krishnamurty
Dhuri, Krishnarao Dattaram
Chandrashekar, Siddhanth
Desai, Kalpit Vikrambhai
Menon, Anup
출원인 / 주소
GENERAL ELECTRIC COMPANY
대리인 / 주소
GE Global Patent Operation
인용정보
피인용 횟수 :
1인용 특허 :
13
초록▼
Embodiments of methods and systems for optimizing operation of a wind farm are presented. The method includes receiving new values corresponding to at least some wake parameters for wind turbines in the wind farm. The method further includes identifying new sets of interacting wind turbines from the
Embodiments of methods and systems for optimizing operation of a wind farm are presented. The method includes receiving new values corresponding to at least some wake parameters for wind turbines in the wind farm. The method further includes identifying new sets of interacting wind turbines from the wind turbines based on the new values. Additionally, the method includes developing a farm-level predictive wake model for the new sets of interacting wind turbines based on the new values and historical wake models determined using historical values of the wake parameters corresponding to reference sets of interacting wind turbines in the wind farm. Furthermore, the method includes adjusting one or more control settings for at least the new sets of interacting wind turbines based on the farm-level predictive wake model.
대표청구항▼
1. A method for optimizing operation of a wind farm, comprising: receiving historical values corresponding to at least some historic wake parameters for wind turbines in the wind farm;identifying reference sets of interacting wind turbines from the wind turbines based on the historical values;determ
1. A method for optimizing operation of a wind farm, comprising: receiving historical values corresponding to at least some historic wake parameters for wind turbines in the wind farm;identifying reference sets of interacting wind turbines from the wind turbines based on the historical values;determining one or more historical wake models for the reference sets of interacting wind turbines based on the historical values;receiving new values corresponding to at least some new wake parameters for wind turbines in the wind farm;identifying new sets of interacting wind turbines from the wind turbines based on the new values;developing a farm-level predictive wake model for the new sets of interacting wind turbines based on the new values and the historical wake models;adjusting one or more control settings for at least the new sets of interacting wind turbines based on the farm-level predictive wake model; andcontrolling the new sets of interacting wind turbines based on the adjusted one or more control settings. 2. The method of claim 1, wherein determining the historical wake models comprises fitting the historical values corresponding to each of the reference sets of interacting wind turbines using to regression-based model. 3. The method of claim 1, wherein determining the historical wake models comprises computing a ratio of downstream wind speed to upstream wind speed as a function of wind direction at an upstream wind turbine, relative locations of upstream and downstream wind turbines, and the one or more control settings corresponding to the upstream wind turbine using the regression-based model. 4. The method of claim 1, wherein identifying the new sets of interacting wind turbines comprises using at least a subset of the new values and the geometrical layout of the wind farm. 5. The method of claim 1, wherein the receiving, the identifying, the developing, and the adjusting are performed at one or more designated intervals of time. 6. The method of claim 1, further comprising: continually monitoring the wake parameters for the wind turbines; andrepeating the receiving, the identifying, the developing, and the adjusting when a change in a monitored value of one or more of the wake parameters is outside a corresponding threshold. 7. The method of claim 1, wherein different historical wake models are determined for different combinations of the wake parameters. 8. The method of claim 1, wherein the wake parameters comprise wind direction, wind speed at an upstream wind turbine, wind speed at a downstream wind turbine, wind turbulence, wind shear, wind veer, ambient temperature, pressure, humidity, or combinations thereof. 9. The method of claim 1, wherein the wake parameters comprise at least one of a tip speed ratio, a pitch angle, a yaw misalignment, and an operational state of each of the wind turbines. 10. The method of claim 1, wherein the wake parameters comprise geometrical layout information of the wind farm. 11. The method of claim 1, wherein adjusting the control settings comprises sequentially determining, the control settings for a downstream wind turbine followed by an upstream wind turbine in each of the new sets of interacting wind turbines to achieve one or more desired performance goals. 12. The method of claim 1, wherein adjusting the control settings comprises sequentially determining the control settings for each of the new sets of interacting wind turbines positioned in the wind farm in a sparse tree structure such that, at each positional level in the sparse tree structure, a combined power output of the wind turbines at that positional level and preceding positional levels in the sparse tree structure is maximized. 13. The method of claim 12, further comprising re-adjusting the control settings for a subset of the wind turbines if the control settings determined for the subset of the wind turbines results in a performance parameter that falls outside a permissible limit specified for a wind speed expected at the subset of wind turbines, wherein re-adjusting the control settings comprises sequentially determining the control settings for each of the subset of wind turbines in a top-down manner. 14. The method of claim 1, wherein achieving the desired performance goals comprises reducing fatigue loads on the wind turbines in the new sets of interacting wind turbines below a first threshold, increasing an annual energy production of the wind farm above a second threshold, or a combination thereof. 15. The method of claim 1, wherein each of the interacting sets of wind turbines comprises a pair of wind turbines. 16. A method for operating a wind farm, comprising: receiving historical values corresponding to at least some historic wake parameters for wind turbines in the wind farm;identifying reference sets of interacting wind turbines from the wind turbines based on the historical values;assembling historical wake models for the reference sets of interacting wind turbines in the wind farm based on historical values of selected combinations of wake parameters corresponding to the sets of interacting wind turbines;determining optimal control settings for each wind turbine in the sets of interacting wind turbines for each of the selected combinations of wake parameters based on the historical wake models;storing the optimal control settings for each wind turbine as a function of the selected combination of wake parameters;receiving new values of the wake parameters acquired over a subsequent period of time following acquisition of the historical values;determining the control settings for the wind turbines in each of a new sets of wind turbines using the new values and the stored control settings; andcontrolling the wind turbines in each of the new sets of wind turbines based on the determined control settings. 17. A system for optimizing operation of a wind farm, comprising: a plurality of wind turbines;one or more monitoring devices configured to measure values of a plurality of wake parameters for one or more of the plurality of wind turbines; anda farm control subsystem operatively coupled to at least the monitoring devices and programmed to: receive historical values corresponding to at least some historic wake parameters for the wind turbines in the wind farm;identify reference sets of interacting wind turbines from the wind turbines based on the historical values;determine one or more historical wake models for the reference sets of interacting wind turbines based on the historical values;receive new values corresponding to at least some new wake parameters for wind turbines in the wind farm;identify new sets of interacting wind turbines from the plurality of wind turbines based on the new values;develop a farm-level predictive wake model for the new sets of interacting wind turbines based on the new values and the historical wake models;adjust one or more control settings for at least the new sets of interacting wind turbines based on the farm-level predictive wake model; andcontrol the new sets of interacting wind turbines based on the adjusted one or more control settings. 18. The system of claim 17, wherein the monitoring devices comprise rotor speed encoders, pitch angle encoders, electrical power transducers, anemometers, wind vanes, yaw position encoders, or combinations thereof. 19. The system of claim 17, wherein the farm control subsystem comprises a centralized processing system.
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