WO2020238182A1 - 风电机组的前馈控制方法、装置以及控制系统 - Google Patents

风电机组的前馈控制方法、装置以及控制系统 Download PDF

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Publication number
WO2020238182A1
WO2020238182A1 PCT/CN2019/127920 CN2019127920W WO2020238182A1 WO 2020238182 A1 WO2020238182 A1 WO 2020238182A1 CN 2019127920 W CN2019127920 W CN 2019127920W WO 2020238182 A1 WO2020238182 A1 WO 2020238182A1
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Prior art keywords
wind
wind speed
target
inflow
section
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PCT/CN2019/127920
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English (en)
French (fr)
Inventor
卞凤娇
刘磊
姜明渊
姚世刚
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Beijing Goldwind Science and Creation Windpower Equipment Co Ltd
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Beijing Goldwind Science and Creation Windpower Equipment Co Ltd
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Priority to US17/615,095 priority Critical patent/US12098707B2/en
Priority to AU2019447706A priority patent/AU2019447706B2/en
Priority to CA3139756A priority patent/CA3139756A1/en
Priority to EP19931285.1A priority patent/EP3978749A4/en
Publication of WO2020238182A1 publication Critical patent/WO2020238182A1/zh
Anticipated expiration legal-status Critical
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    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F03—MACHINES OR ENGINES FOR LIQUIDS; WIND, SPRING, OR WEIGHT MOTORS; PRODUCING MECHANICAL POWER OR A REACTIVE PROPULSIVE THRUST, NOT OTHERWISE PROVIDED FOR
    • F03D—WIND MOTORS
    • F03D7/00—Controlling wind motors 
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F03—MACHINES OR ENGINES FOR LIQUIDS; WIND, SPRING, OR WEIGHT MOTORS; PRODUCING MECHANICAL POWER OR A REACTIVE PROPULSIVE THRUST, NOT OTHERWISE PROVIDED FOR
    • F03D—WIND MOTORS
    • F03D7/00—Controlling wind motors 
    • F03D7/02—Controlling wind motors  the wind motors having rotation axis substantially parallel to the air flow entering the rotor
    • F03D7/04—Automatic control; Regulation
    • F03D7/042—Automatic control; Regulation by means of an electrical or electronic controller
    • F03D7/043—Automatic control; Regulation by means of an electrical or electronic controller characterised by the type of control logic
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F03—MACHINES OR ENGINES FOR LIQUIDS; WIND, SPRING, OR WEIGHT MOTORS; PRODUCING MECHANICAL POWER OR A REACTIVE PROPULSIVE THRUST, NOT OTHERWISE PROVIDED FOR
    • F03D—WIND MOTORS
    • F03D7/00—Controlling wind motors 
    • F03D7/02—Controlling wind motors  the wind motors having rotation axis substantially parallel to the air flow entering the rotor
    • F03D7/04—Automatic control; Regulation
    • F03D7/042—Automatic control; Regulation by means of an electrical or electronic controller
    • F03D7/043—Automatic control; Regulation by means of an electrical or electronic controller characterised by the type of control logic
    • F03D7/045—Automatic control; Regulation by means of an electrical or electronic controller characterised by the type of control logic with model-based controls
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F05—INDEXING SCHEMES RELATING TO ENGINES OR PUMPS IN VARIOUS SUBCLASSES OF CLASSES F01-F04
    • F05B—INDEXING SCHEME RELATING TO WIND, SPRING, WEIGHT, INERTIA OR LIKE MOTORS, TO MACHINES OR ENGINES FOR LIQUIDS COVERED BY SUBCLASSES F03B, F03D AND F03G
    • F05B2270/00—Control
    • F05B2270/30—Control parameters, e.g. input parameters
    • F05B2270/32—Wind speeds
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F05—INDEXING SCHEMES RELATING TO ENGINES OR PUMPS IN VARIOUS SUBCLASSES OF CLASSES F01-F04
    • F05B—INDEXING SCHEME RELATING TO WIND, SPRING, WEIGHT, INERTIA OR LIKE MOTORS, TO MACHINES OR ENGINES FOR LIQUIDS COVERED BY SUBCLASSES F03B, F03D AND F03G
    • F05B2270/00—Control
    • F05B2270/30—Control parameters, e.g. input parameters
    • F05B2270/321—Wind directions
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F05—INDEXING SCHEMES RELATING TO ENGINES OR PUMPS IN VARIOUS SUBCLASSES OF CLASSES F01-F04
    • F05B—INDEXING SCHEME RELATING TO WIND, SPRING, WEIGHT, INERTIA OR LIKE MOTORS, TO MACHINES OR ENGINES FOR LIQUIDS COVERED BY SUBCLASSES F03B, F03D AND F03G
    • F05B2270/00—Control
    • F05B2270/40—Type of control system
    • F05B2270/404—Type of control system active, predictive, or anticipative
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F05—INDEXING SCHEMES RELATING TO ENGINES OR PUMPS IN VARIOUS SUBCLASSES OF CLASSES F01-F04
    • F05B—INDEXING SCHEME RELATING TO WIND, SPRING, WEIGHT, INERTIA OR LIKE MOTORS, TO MACHINES OR ENGINES FOR LIQUIDS COVERED BY SUBCLASSES F03B, F03D AND F03G
    • F05B2270/00—Control
    • F05B2270/80—Devices generating input signals, e.g. transducers, sensors, cameras or strain gauges
    • F05B2270/804—Optical devices
    • F05B2270/8042—Lidar systems
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
    • Y02A30/00—Adapting or protecting infrastructure or their operation
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E10/00—Energy generation through renewable energy sources
    • Y02E10/70—Wind energy
    • Y02E10/72—Wind turbines with rotation axis in wind direction

Definitions

  • the present disclosure generally relates to the field of wind power technology, and more specifically, to a feedforward control method, device and control system of a wind turbine.
  • Exemplary embodiments of the present disclosure provide a feedforward control method, device, and control system of a wind turbine to overcome at least one of the above-mentioned drawbacks.
  • a feedforward control method for a wind turbine including: acquiring inflow wind information at multiple spatial points in front of the wind turbine through a remote sensing measurement device, the multiple spatial points are distributed in multiple For different cross sections, the distances of the multiple different cross sections to the wind turbine are different; use the acquired inflow wind information to synthesize the target wind speed; based on the synthesized target wind speed, predict the incoming flow required for the inflow wind at the target point to reach the impeller plane Arrival time: feed forward control of wind turbines based on the predicted arrival time of incoming flow.
  • a feedforward control device for a wind turbine including: an inflow wind information acquisition module, which acquires inflow wind information at multiple spatial points in front of the wind turbine through a remote sensing measurement device. The three spatial points are distributed in multiple different sections, and the multiple different sections have different distances from the wind turbine; the wind speed synthesis module uses the acquired inflow wind information to synthesize the target wind speed; the time prediction module is based on the synthesized target wind speed , Predict the arrival time of the incoming flow required for the inflow wind at the target point to reach the impeller plane; the feedforward control module performs feedforward control on the wind turbine according to the predicted arrival time of the incoming flow.
  • a controller for a wind turbine generator including: a processor; an input ⁇ output interface; and a memory for storing a computer program that, when executed by the processor, realizes the above-mentioned wind turbine generator The feedforward control method.
  • a control system for a wind turbine including: a remote sensing measurement device that detects inflow wind information at multiple spatial points in front of the wind turbine, and the multiple spatial points are distributed in multiple different locations. The distance between the multiple different sections and the wind turbine is different, and the controller obtains the inflow wind information at multiple spatial point positions from the remote sensing measurement device to realize the above-mentioned feedforward control method for the wind turbine.
  • a computer-readable storage medium storing a computer program
  • the above-mentioned feedforward control method of a wind turbine is realized.
  • the feedforward control method, device, and control system of the wind turbine generator set according to the exemplary embodiments of the present disclosure, it is possible to accurately calculate the time for the incoming flow to reach the impeller plane based on the accurate wind speed, so that the wind turbine generator can be actively controlled to minimize wind power.
  • the unit is subjected to the load caused by the uncertainty of the inflow wind.
  • Fig. 1 shows a flowchart of a feedforward control method for a wind turbine according to an exemplary embodiment of the present disclosure
  • FIG. 2 shows a schematic diagram of the remote sensing measurement device detecting inflow wind information at multiple spatial point positions according to an exemplary embodiment of the present disclosure
  • FIG. 3 shows a schematic diagram of the two-dimensional spatial distribution of inflow wind information at multiple spatial point positions detected by the remote sensing measurement device according to an exemplary embodiment of the present disclosure
  • Fig. 4 shows a schematic diagram of a wind speed change curve according to an exemplary embodiment of the present disclosure
  • Fig. 5 shows a flow chart of the steps of performing feedforward control on a wind turbine generator according to the predicted arrival time of the incoming flow according to an exemplary embodiment of the present disclosure
  • Fig. 6 shows a flowchart of steps for performing feedforward control of a wind turbine according to an exemplary embodiment of the present disclosure
  • FIG. 7 shows a flowchart of the steps of calculating a target wind shear factor according to an exemplary embodiment of the present disclosure
  • FIG. 8 shows a flowchart of the steps of determining a target wind direction according to an exemplary embodiment of the present disclosure
  • Fig. 9 shows a block diagram of a feedforward control device of a wind turbine according to an exemplary embodiment of the present disclosure
  • Fig. 10 shows a block diagram of a control system of a wind turbine according to an exemplary embodiment of the present disclosure.
  • Fig. 1 shows a flowchart of a feedforward control method of a wind turbine according to an exemplary embodiment of the present disclosure.
  • step S10 the inflow wind information at a plurality of spatial points in front of the wind turbine generator is acquired by the remote sensing measurement device.
  • the inflow wind information may include, but is not limited to, the wind speed of the inflow wind at each spatial point position.
  • a remote sensing measurement device may be provided on the top of the nacelle of the wind turbine generator for detecting inflow wind information at multiple spatial points.
  • the inflow wind information at multiple spatial point positions is acquired from the remote sensing measurement device.
  • the remote sensing measurement device may refer to a non-contact, long-distance detection technology.
  • the remote sensing measurement device may include but not limited to laser radium, and other devices may also be used to detect the inflow wind information at each spatial point position, such as , Ultrasonic wind measuring device.
  • the above-mentioned multiple spatial points are located in front of the impeller plane of the wind turbine (that is, on the windward side).
  • the laser beam is emitted to the front of the impeller plane to detect the impeller plane of the wind turbine. Inflow wind information at multiple spatial points in front of.
  • Fig. 2 shows a schematic diagram of the remote sensing measurement device detecting inflow wind information at multiple spatial point positions according to an exemplary embodiment of the present disclosure.
  • the remote sensing measurement device is a laser radium as an example. It is assumed that the laser radium emits four beams. Based on the emitted beams, the laser radium can detect multiple spatial points on each beam. Inflow wind information at the location.
  • the space point with the same distance as the laser radium forms a cross section.
  • the laser radium has multiple cross sections, that is, multiple space points are distributed in multiple different cross sections, and the multiple different cross sections have different distances from the wind turbine.
  • each section can be parallel to the plane of the impeller.
  • the distance between the section and the laser radium refers to the detection distance, and the position of section N can refer to the farthest distance the laser radium can detect.
  • Fig. 3 shows a schematic diagram of a two-dimensional spatial distribution of inflow wind information at multiple spatial point positions detected by a remote sensing measurement device according to an exemplary embodiment of the present disclosure.
  • the position of each spatial point on the beam includes not only the distance value from the remote sensing measurement device (that is, the detection distance along the centerline of the beam), but also The height value of the space point (such as height z, height z+k), therefore, the wind speed of the inflow wind at each space point at different detection distances and different heights can be detected by the remote sensing measuring device.
  • the inflow wind information at each spatial point position detected by the remote sensing measuring device may include the wind speed along the direction of the beam center line and the wind speed in the direction perpendicular to the beam center line.
  • RAW i,j is the wind speed of the inflow wind of the i-th beam of the remote sensing measuring device at the j-th section
  • U i,j is the ith beam along the beam centerline at the j-th section
  • the wind speed in the direction, Vi ,j is the wind speed of the i-th beam perpendicular to the beam centerline at the j-th section
  • ⁇ i is the zenith angle of the i-th beam
  • the predetermined plane refers to the plane in the middle of the upper and lower beams of the remote sensing measuring device.
  • both the zenith angle and the azimuth angle are inherent parameters of the remote sensing measurement device.
  • step S20 the target wind speed is synthesized by using the acquired inflow wind information at the multiple spatial point positions.
  • the induction effect In front of the impeller of the wind turbine, due to the obstruction of the impeller, an area where the wind speed is lower than the incoming wind speed will appear. This phenomenon is called the induction effect.
  • the area where the wind speed is weakened by the induction effect is called the induction zone.
  • the existing remote sensing measurement device wind measurement method is susceptible to the inductive effect, resulting in inaccurate wind speed measurement.
  • the target wind speed is obtained through wind speed synthesis, thereby removing the influence of the inductive effect on the wind speed, so as to obtain a more accurate inflow wind speed, and realize precise control of the wind turbine based on the inflow wind speed.
  • the target wind speed obtained after synthesis is the wind speed of the inflow wind that is not affected by the induction effect.
  • the remote sensing measurement device can emit multiple beams to detect the inflow wind information at different cross-sections. Based on this, in the exemplary embodiment of the present disclosure, it is proposed that wind speed synthesis can be performed for each beam or for each beam. Wind speed synthesis is performed on the cross-section, and the different wind speed synthesis methods will be introduced separately below.
  • wind speed synthesis is performed based on each section of the remote sensing measurement device to obtain the target wind speed.
  • the average wind speed of the section is determined based on the inflow wind information at each spatial point position of the section, and the target wind speed is obtained based on the average wind speed of each section.
  • the cross-sectional average wind speed of any cross-section may be the average value of the wind speed of the inflow wind at each spatial point position of the any cross-section.
  • the present disclosure is not limited to this, and the average cross-sectional wind speed can also be calculated in other ways, for example, selecting the median value or the average value of the maximum and minimum wind speeds of the inflow wind at each spatial point position of any cross-section, etc. .
  • the following will exemplarily introduce the method of obtaining the target wind speed based on the average wind speed of each section.
  • the target wind speed can be obtained according to the cross-sectional average wind speed of all cross-sections and the corresponding inductive effect coefficients of all cross-sections.
  • each cross-section set the corresponding weight value for the cross-section, calculate the ratio of the average wind speed of the cross-section to the inductive effect coefficient corresponding to the cross-section, and calculate the ratio of the calculated ratio for each cross-section to the corresponding weight value.
  • the weighted sum is determined as the target wind speed.
  • the inductive effect influence coefficient corresponding to each section varies with the distance from each spatial point to the impeller plane.
  • the inductive effect coefficient corresponding to each section can be determined in the following manner.
  • the reference section can be any one of all sections.
  • the reference section may be a section at a position where the wind speed is least affected by the induced effect among all sections.
  • the historical wind resource data of the wind turbine can be used to find the position in front of the impeller plane of the wind turbine that is least affected by the induced effect, and the section at that position (or the section closest to the position) among all the sections is determined as the reference section.
  • the reference section may also be selected in other ways. For example, a section may be selected from all sections as the reference section based on experience.
  • the inductive effect coefficient corresponding to the reference cross section can be set to 1, and the inductive effect coefficient corresponding to the reference cross section can be adjusted according to the distance between other cross sections and the reference cross section. For example, as the distance between each other cross-section and the reference cross-section increases, the inductive effect coefficient corresponding to each other cross-section gradually decreases from 1.
  • the inductive effect influence coefficient corresponding to any other cross section may be the reciprocal of the distance between the any other cross section and the reference cross section.
  • the historical wind resource data of the wind turbine can also be used to determine the inductive effect coefficient corresponding to each section through a machine learning algorithm.
  • the historical wind resource data may include the actual wind speed and the detected wind speed of the inflow wind at each cross-section, and based on this, build data samples of the machine learning algorithm, and obtain the inductive effect influence coefficient corresponding to each cross-section through the machine learning algorithm.
  • the machine learning algorithm may include but is not limited to ELM (Extreme Learning Machine), and may also be other machine learning algorithms.
  • the target wind speed can also be obtained by eliminating the time phase difference of the cross-sectional average wind speed of each section.
  • the influence coefficient of a given induction effect can be determined in the following manner.
  • the inductive effect coefficient corresponding to each cross-section can be obtained by adjusting the inductive effect coefficient of the reference cross-section as described above.
  • the above-mentioned method of determining the influence coefficient of a given inductive effect given in the exemplary embodiments of the present disclosure is only an example, and the influence coefficient of a given inductive effect may also be determined in other ways, for example, the given inductive effect
  • the influence coefficient can be set based on experience.
  • the intermediate wind speed can be obtained in the following way.
  • For each section determine the estimated wind speed when the inflow wind flows from the section to the specified section according to the distance from the section to the specified section and the average wind speed of the section, and determine the average of all estimated wind speeds as the intermediate wind speed.
  • the estimated wind speed when the inflow wind flows from any cross section to a specified cross section can be determined in the following way.
  • the flow time required for the inflow wind to flow from any section to the designated section is calculated; the section of the designated section determined after the flow time has elapsed
  • the average wind speed is determined as the estimated wind speed when the inflow wind flows from any section to the specified section.
  • the above-mentioned designated section may be any one of all sections.
  • the ratio of the distance from any section to the designated section to the average wind speed of any section can be determined as the inflow wind flowing from any section to Specify the flow time required for the section.
  • the above method of removing the time phase difference of the average wind speed of multiple sections to synthesize the intermediate wind speed considering that the wind speeds of the inflow wind at different section positions at any time are different, and the time required for the inflow wind to flow from different sections to the impeller plane Also different. Assuming that the wind flow field space is frozen, based on the distance between two adjacent sections and the average wind speed of the section, the flow time required for the inflow wind to flow within this distance can be calculated.
  • the inflow wind information at each spatial point position is acquired in real time, and the cross-sectional average wind speed of each section is calculated in real time.
  • the wind speed of the inflow wind at each spatial point position obtained when the inflow wind flows to the designated section after the flow time has passed, and the section average wind speed of the designated section calculated at this time is determined as The wind speed is estimated, and the average value of the estimated wind speed when the inflow wind flows from each section to the specified section is determined as the intermediate wind speed.
  • wind speed synthesis is performed based on each beam emitted by the laser laser to obtain the target wind speed.
  • the combined wind speed of any beam can be determined by the following method: set the corresponding weight value for each spatial point position, calculate the inflow wind information at each spatial point position on the any beam and the corresponding inductive effect influence
  • the ratio of the coefficients is determined by the weighted summation of each ratio and the corresponding weight value as the beam composite wind speed of any beam.
  • the aforementioned method of determining the inductive effect coefficient corresponding to each cross-section can be referred to to determine the inductive effect coefficient corresponding to each spatial point position.
  • the target wind speed may also be obtained based on a wind speed fitting curve.
  • wind speed synthesis can be performed based on a beam of ultrasonic waves emitted by the ultrasonic wind measurement device.
  • the target wind speed is obtained based on the wind speed fitting curve of the inflow wind information at multiple spatial point positions.
  • the wind speed change curve of the inflow wind flowing from the target point to the impeller plane is obtained, and the obtained wind speed change curve is integrated, and the integrated area is compared to the target point.
  • the ratio of the distance to the impeller plane is determined as the target wind speed.
  • Fig. 4 shows a schematic diagram of a wind speed change curve according to an exemplary embodiment of the present disclosure.
  • the target point can be any point within a finite distance from the impeller plane, and the target point can be an inflow point within a finite distance from the impeller plane without the influence of inductive effects (for example, point Q shown in Fig. 4) .
  • the target wind speed may be defined as the wind speed of the inflow wind at the target point.
  • various fitting, filtering, and smoothing methods can be used to obtain the wind speed change curve of the inflow wind from the target point to the impeller plane (that is, the smooth wind speed change curve) , To determine the target wind speed based on the wind speed change curve.
  • the methods of fitting, filtering, and smoothing multiple values are common knowledge in the art, and the content of this part will not be repeated in this disclosure.
  • different calculation methods can be selected based on the location of the target point to determine the target wind speed.
  • the turbulent freezing theory is introduced, and it is assumed that the wind flow domain in front of the impeller plane has not evolved. If the position of the target point Q x OPT (that is, the distance from the target point to the impeller plane of the wind turbine) is greater than or Equal to the farthest detection distance D(N) of the remote sensing measuring device, the method shown in the following formula (2) can be used to calculate the target wind speed.
  • U OPT is the target wind speed
  • RAWS j is the average wind speed of the j-th section of the remote sensing measurement device
  • x OPT is the distance from the target point to the impeller plane
  • x j is the distance from the j-th section to the impeller plane.
  • Distance, 1 ⁇ j ⁇ n, n is the number of cross-sections used to calculate the target wind speed
  • t m is the flow time required for the inflow wind to flow from the target point to the impeller plane
  • Is the average wind speed of the inflow wind from the jth section to the adjacent j-1th section.
  • the method shown in formula (3) can be used to calculate the target wind speed.
  • the wind speed of the above formula (2) and formula (3) can be obtained by removing the time phase difference of the cross-sectional average wind speed of each section and then performing the average calculation to obtain the target wind speed that is not affected by the induction.
  • the average wind speed in the above formula It can be obtained by using the wind speed change curve shown in Figure 4.
  • the wind speed change curve from the jth section to the adjacent j-1th section can be integrated, and the ratio of the integral area to the distance difference ⁇ d between the two sections can be determined as the average wind speed
  • ⁇ U represents the difference between the average wind speeds of the two sections
  • t j represents the flow time required for the inflow wind to flow from the Nth section to the jth section.
  • the flow field in front of the impeller is affected by the input of multiple spatial points.
  • the flow wind information is synthesized to obtain the target wind speed that is not affected by the induction effect, which is used in the active control and evaluation of the wind turbine.
  • step S30 based on the synthesized target wind speed, the arrival time of the incoming flow required for the inflow wind at the target point to reach the impeller plane is predicted.
  • the turbulence freezing theory when predicting the arrival time of the incoming flow, the turbulence freezing theory can be introduced, that is, assuming that the wind flow domain in front of the impeller plane has not evolved, under this precondition, the incoming flow arrival time is predicted based on the synthesized target wind speed. .
  • the arrival time can be predicted in the following manner.
  • the arrival time of the incoming flow can be predicted based on the distance from the position of the target point to the impeller plane and the target wind speed.
  • the ratio of the distance from the position of the target point to the plane of the impeller and the target wind speed can be determined as the arrival time of the incoming flow.
  • the arrival time of the incoming flow can be predicted based on the wind speed change curve and the target wind speed.
  • the wind speed change curve from the target point to the impeller plane can be integrated, and the ratio of its integrated area to the target wind speed can be integrated , Determined as the arrival time of the inflow wind required by the target point to reach the impeller plane.
  • the arrival time of the incoming flow required for the inflow wind at the target point to reach the impeller plane can be predicted.
  • a deep learning method can be used to establish in advance the corresponding relationship between the target wind speed and the flow time required for the inflow wind at the target point to reach the impeller plane based on the historical wind resource data of the wind turbine.
  • the flow time corresponding to the synthesized target wind speed can be searched according to the pre-established correspondence relationship, and the found flow time can be determined as the arrival time of the incoming flow.
  • the target wind speed and flow time used to establish the correspondence relationship may be obtained using the above-mentioned method in the exemplary embodiment of the present disclosure.
  • the arrival time of the incoming flow can be calculated in sections to predict the incoming flow arrival time required for the inflow wind at the target point to reach the impeller plane.
  • each predetermined section may refer to a section whose distance from the plane of the impeller is greater than the distance from the designated section to the plane of the impeller.
  • the arrival time required for the inflow wind at the target point to reach the impeller plane can be predicted by the following formula:
  • t OPT is the arrival time required for the inflow wind at the target point to reach the impeller plane
  • t b is the first flow time required for the inflow wind to flow from the b-th predetermined section to the designated section a
  • t a is the second flow time required for the inflow wind to flow from the designated section a to the plane of the impeller
  • c is the number of the predetermined section.
  • the ratio of the distance from the b-th section to the designated section a to the average wind speed of the b-th section can be determined as the first flow time t b , or the wind speed from the b-th section to the designated section a
  • the change curve is integrated, and the ratio of its integrated area to the average wind speed of the b-th section is determined as the first flow time t b .
  • the ratio of the distance from the designated section a to the impeller plane to the average wind speed of the designated section a can be determined as the second flow time t a , or the wind speed change curve from the designated section a to the impeller plane can be integrated , The ratio of its integral area to the average wind speed of the designated section a is determined as the second flow time t a .
  • the above formula (4) can be used to predict the arrival time. If the location of the target point Q is greater than the farthest detection distance D(N) of the remote sensing measuring device, then In addition to the first flow time t b and the second flow time t a mentioned above, the third flow time t d should also be included.
  • the third flow time t d refers to the inflow wind flowing from the target point to the farthest detection distance D(N ) The required flow time.
  • the third flow time t d may be determined by the ratio of the distance from the target point to the farthest detection distance D(N) and the cross-sectional average wind speed at the farthest detection distance D(N).
  • the method of predicting the arrival time of the incoming flow based on the target wind speed listed in the above exemplary embodiment of the present disclosure is only an example, and the arrival time of the incoming flow may also be predicted in other ways.
  • step S40 feedforward control is performed on the wind turbine according to the predicted arrival time of the incoming flow.
  • the target wind speed of the shearing inflow wind outside the induction area can be accurately calculated, so as to perform feedforward control on the wind turbine when the inflow wind arrives.
  • FIG. 5 shows a flowchart of the steps of performing feedforward control of a wind turbine according to a predicted arrival time of an incoming flow according to an exemplary embodiment of the present disclosure.
  • step S31 the control response time required for the wind turbine generator to execute the feedforward control is determined.
  • the time required to perform feedforward control once in the history of the wind turbine can be used as the control response time, or the control response time required for the wind turbine to perform feedforward control can also be artificially set based on experience.
  • step S32 according to the predicted arrival time of the incoming flow and the determined control response time, the waiting time for the wind turbine generator to execute the feedforward control is determined.
  • the difference between the predicted arrival time of the incoming flow and the determined control response time may be determined as the waiting time for the wind turbine to execute the feedforward control.
  • step S33 when the determined waiting time is reached, feedforward control is performed on the wind turbine.
  • feedforward control can perform feedforward control on the wind turbine when the predicted arrival time of the incoming flow is reached.
  • Fig. 6 shows a flowchart of the steps of performing feedforward control on a wind turbine according to an exemplary embodiment of the present disclosure.
  • step S331 when the determined waiting time is reached, the target wind speed at the current moment is determined.
  • the inflow wind information at each spatial point position is acquired in real time, and the synthesized target wind speed is calculated in real time.
  • the target wind speed at the time when the waiting time is reached is acquired.
  • step S332 the control strategy corresponding to the target wind speed at the current moment is determined.
  • the wind speed and the control strategy corresponding to the wind speed may be stored in the control strategy look-up table.
  • the control strategy look-up table may be searched for a control strategy matching the target wind speed at the current moment.
  • control strategy corresponding to the target wind speed based on the control strategy look-up table is only an example, and the present disclosure is not limited to this, and the control strategy corresponding to the target wind speed may also be determined in other ways.
  • step S333 the wind turbine generator is controlled to execute the determined control strategy.
  • the feedforward control method for a wind turbine can obtain a target wind speed that is not affected by an inductive effect, and can also obtain a target wind direction that is not affected by an inductive effect (which can be referred to as inflow wind). Wind direction), target turbulence intensity, target wind shear factor.
  • the feedforward control method of a wind turbine generator may further include: determining the target wind shear factor, target wind direction, and/or target turbulence by using the acquired inflow wind information at multiple spatial point positions strength.
  • the target wind shear factor, target wind direction and/or target turbulence intensity at the current moment may also be determined.
  • the control strategy executed by controlling the wind turbine may be a control strategy corresponding to at least one of the target wind shear factor, target wind direction, target turbulence intensity, and target wind speed at the current moment.
  • control strategy look-up table may store wind resource parameters and control strategies corresponding to the wind resource parameters.
  • the wind resource parameters include at least one of wind shear factor, wind direction, turbulence intensity, and wind speed.
  • control strategy may include, but is not limited to, at least one of the following items: yaw control, pitch control, load reduction control, shutdown control, and torque adjustment control of the wind turbine.
  • the control strategy of the control strategy look-up table can store the control parameters corresponding to the above-mentioned control methods, such as the yaw angle value, the pitch angle value, etc. At this time, the wind resource at the current time can be searched from the control strategy look-up table. Each control parameter under the control strategy corresponding to the parameter is sent to the wind turbine generator so that the wind turbine generator operates based on each control parameter.
  • the control strategy may also include calculating predetermined parameters (such as power generation) of the wind turbine, for example, based on the obtained target wind shear factor, target wind direction, target turbulence intensity and/or target wind speed. Evaluate the power generation of wind turbines.
  • control strategy corresponding to the target wind speed may be the pitch control of the wind turbine
  • control strategy corresponding to the target wind speed and target wind direction may be the yaw control and shutdown control of the wind turbine
  • the strategy can be to adjust the torque of the wind turbine. It should be understood that the corresponding relationship between the wind resource parameters and the control strategy listed above is only an example, and the present disclosure is not limited to this, and those skilled in the art can establish a control strategy lookup table according to actual needs.
  • the wind turbine will respond to “just in time” through active control, and finally realize “follow the wind and follow the trend”.
  • the acquired inflow wind information at multiple spatial point positions can be divided into first inflow wind information and second inflow wind information.
  • first inflow wind information may include the inflow wind information at each spatial point above the plane where the beam centerline of the remote sensing measurement device is located
  • second inflow wind information may include the inflow wind information located below the plane where the beam centerline of the remote sensing measurement device is located. Inflow wind information at each spatial point location.
  • Fig. 7 shows a flowchart of steps of calculating a target wind shear factor according to an exemplary embodiment of the present disclosure.
  • step S701 the first synthetic wind speed is obtained by synthesizing the first inflow wind information.
  • the average value of the wind speed of the inflow wind at each spatial point position above the plane where the beam center line of the remote sensing measurement device is located can be determined as the first synthetic wind speed, but the present disclosure is not limited to this, and can also be obtained in other ways Synthetic wind speed.
  • step S702 the second synthesized wind speed is obtained by synthesizing the second inflow wind information.
  • the average value of the wind speed of the inflow wind at each spatial point position below the plane where the beam center line of the remote sensing measurement device is located can be determined as the second synthetic wind speed, but the present disclosure is not limited to this, and can also be obtained in other ways Synthetic wind speed.
  • step S703 the average value of the height value of each spatial point position above the plane where the beam center line of the remote sensing measurement device is located is calculated to obtain the first height value.
  • the acquired inflow wind information at multiple spatial point positions may also include the height value of each spatial point position. Therefore, at this time, the height value of each spatial point position above the plane where the beam center line of the remote sensing measurement device is located The average value of is determined as the first height value.
  • step S704 the average value of the height value of each spatial point position below the plane where the beam center line of the remote sensing measurement device is located is calculated to obtain the second height value.
  • step S705 the target wind shear factor is calculated according to the first synthetic wind speed, the second synthetic wind speed, the first height value and the second height value.
  • V Shear represents the target wind shear factor (vertical wind shear factor)
  • HWS + represents the first synthetic wind speed
  • HWS - represents the second synthetic wind speed
  • H + represents the first height value
  • H - represents the first Two height value.
  • the above process is to calculate a target wind shear factor for multiple spatial point positions, but the present disclosure is not limited to this, and the corresponding wind shear factor can also be calculated for each section.
  • the target wind shear The factor includes the wind shear factor corresponding to each section.
  • the wind shear factor corresponding to any cross-section can be calculated based on the inflow wind information at each spatial point position at any cross-section position, and formula (5) is used to calculate the wind shear factor corresponding to any cross-section.
  • FIG. 8 shows a flowchart of steps of determining a target wind direction according to an exemplary embodiment of the present disclosure.
  • step S801 the horizontal wind direction of the inflow wind is calculated based on the first inflow wind information, the second inflow wind information, and the zenith angle of each beam of the remote sensing measuring device.
  • U + represents the horizontal wind direction of the inflow wind
  • It represents the average value of the wind speed of the inflow wind at each spatial point position below the plane where the beam center line of the remote sensing measurement device is located
  • ⁇ is the average value of the zenith angle of each beam.
  • step S802 the vertical wind direction of the inflow wind is calculated according to the first inflow wind information, the second inflow wind information, the zenith angles of the beams of the remote sensing measuring device, and the azimuth angles of the beams of the remote sensing measuring device and the plane of the beam centerline.
  • V + represents the vertical wind direction of the inflow wind, It is the average value of the azimuth angle of each beam and the predetermined plane.
  • step S803 the angle between the horizontal wind direction and the vertical wind direction of the inflow wind is determined as the target wind direction.
  • ⁇ + represents the target wind direction
  • atan2() represents a function used to calculate the angle between the horizontal wind direction and the vertical wind direction of the inflow wind.
  • the following describes the steps to determine the target turbulence intensity by using the inflow wind information obtained at multiple spatial point positions.
  • the target turbulence intensity can be obtained by the following method: synthesize the target wind speed with the acquired inflow wind information, calculate the wind speed standard deviation of the target wind speed in a predetermined time period and the average wind speed of the target wind speed in the predetermined time period, and calculate the wind speed standard The ratio of the difference to the average wind speed is determined as the target turbulence intensity.
  • the above process is to calculate a target turbulence intensity for multiple spatial point positions, but the present disclosure is not limited to this, and the corresponding turbulence intensity can also be calculated for each section.
  • the target turbulence intensity includes the turbulence intensity corresponding to each section.
  • the turbulence intensity corresponding to any cross-section can be calculated based on the inflow wind information at each spatial point position at the any cross-section position, and the turbulence intensity corresponding to any cross-section can be calculated using the methods listed above.
  • the above methods for determining the target wind direction, the target wind shear factor, and the target turbulence intensity are only examples.
  • the present disclosure is not limited to this, and the target wind direction, the target wind shear factor, and the target turbulence intensity can also be determined by other methods. .
  • Fig. 9 shows a block diagram of a feedforward control device of a wind turbine according to an exemplary embodiment of the present disclosure.
  • the feedforward control device of the wind turbine includes: an inflow wind information acquisition module 10, a wind speed synthesis module 20, a time prediction module 30 and a feedforward control module 40.
  • the inflow wind information acquisition module 10 acquires the inflow wind information at multiple spatial point positions in front of the wind turbine through a remote sensing measurement device.
  • multiple spatial points are distributed in multiple different sections, and the multiple different sections have different distances from the wind turbine.
  • the inflow wind information may include, but is not limited to, the wind speed of the inflow wind at each spatial point position.
  • a remote sensing measurement device may be provided on the top of the nacelle of the wind turbine to detect the inflow wind information at multiple spatial points.
  • the inflow wind information acquisition module 10 can acquire inflow wind information at multiple spatial point positions from the remote sensing measurement device.
  • the remote sensing measurement device may include but is not limited to laser radium.
  • the wind speed synthesis module 20 uses the acquired inflow wind information to synthesize the target wind speed.
  • the wind speed synthesis module 20 may perform wind speed synthesis for each light beam or wind speed synthesis for each cross section. The following will separately introduce different wind speed synthesis methods.
  • the wind speed synthesis module 20 performs wind speed synthesis based on each section of the remote sensing measurement device to obtain the target wind speed.
  • the wind speed synthesis module 20 determines the average wind speed of the section according to the inflow wind information at each spatial point position of the section, and obtains the target wind speed according to the average wind speed of each section.
  • the cross-sectional average wind speed of any cross-section may be the average value of the wind speed of the inflow wind at each spatial point position of the any cross-section.
  • the following introduces two ways to obtain the target wind speed based on the average wind speed of each section.
  • the wind speed synthesis module 20 can obtain the target wind speed according to the cross-sectional average wind speed of all the cross-sections and the inductive effect influence coefficient corresponding to all the cross-sections.
  • the wind speed synthesis module 20 sets a corresponding weight value for the section, calculates the ratio of the average wind speed of the section to the inductive effect coefficient corresponding to the section, and compares the ratio calculated for each section to the corresponding The weighted summation of the weight values of is determined as the target wind speed.
  • the wind speed synthesis module 20 may determine the inductive effect influence coefficient corresponding to each section in the following manner.
  • the inductive effect coefficient of the reference cross-section is used to obtain the inductive effect coefficient of other cross sections.
  • the reference section can be any one of all sections. Ground, the reference section may be the section at the position where the wind speed is least affected by the induced effect among all sections.
  • the wind speed synthesis module 20 can obtain the target wind speed by eliminating the time phase difference of the cross-sectional average wind speed of each section.
  • the wind speed synthesis module 20 obtains the intermediate wind speed by synthesizing the cross-sectional average wind speed of each cross-section to remove the time phase difference between the cross-sectional average wind speed of each cross-section, and obtains the target wind speed according to the intermediate wind speed and a given inductive effect coefficient.
  • the wind speed synthesis module 20 can determine the influence coefficient of a given induction effect in the following manner.
  • the wind speed synthesis module 20 may obtain the intermediate wind speed in the following manner.
  • For each section determine the estimated wind speed when the inflow wind flows from the section to the specified section according to the distance from the section to the specified section and the average wind speed of the section, and determine the average of all estimated wind speeds as the intermediate wind speed.
  • the wind speed synthesis module 20 can determine the estimated wind speed when the inflow wind flows from any cross section to a specified cross section in the following manner.
  • the flow time required for the inflow wind to flow from any section to the designated section is calculated; the section of the designated section determined after the flow time has elapsed
  • the average wind speed is determined as the estimated wind speed when the inflow wind flows from any section to the specified section.
  • the wind speed synthesis module 20 performs wind speed synthesis based on each light beam emitted by the remote sensing measurement device to obtain the target wind speed.
  • the wind speed synthesis module 20 determines the light beam according to the inflow wind information at each spatial point position on the beam and the inductive effect influence coefficient corresponding to each spatial point position The combined wind speed of all beams is determined as the target wind speed.
  • the wind speed synthesis module 20 can determine the beam synthesis wind speed of any beam in the following manner: set a corresponding weight value for each spatial point position, and calculate the inflow wind information at each spatial point position on the any beam and the corresponding The ratio of the inductive effect influence coefficient of, and the weighted sum of each ratio and the corresponding weight value is determined as the beam composite wind speed of any beam.
  • the target wind speed may also be obtained based on a wind speed fitting curve.
  • the wind speed synthesis module 20 obtains the target wind speed based on the wind speed fitting curve of the inflow wind information at multiple spatial point positions.
  • the wind speed synthesis module 20 obtains the wind speed change curve of the inflow wind from the target point to the impeller plane according to the obtained inflow wind information at multiple spatial point positions, integrates the obtained wind speed change curve, and integrates the area The ratio of the distance from the target point to the impeller plane is determined as the target wind speed.
  • the time prediction module 30 predicts the arrival time of the incoming flow required for the inflow wind at the target point to reach the impeller plane based on the synthesized target wind speed.
  • the time prediction module 30 can predict the arrival time of the incoming flow according to the distance from the position of the target point to the impeller plane and the target wind speed.
  • the time prediction module 30 may determine the ratio of the distance from the position of the target point to the impeller plane to the target wind speed as the arrival time of the incoming flow.
  • the time prediction module 30 can predict the arrival time of the incoming flow according to the wind speed change curve and the target wind speed.
  • the time prediction module 30 can integrate the wind speed change curve from the target point to the impeller plane, and the integrated area is compared with The ratio of the target wind speed is determined as the arrival time of the incoming flow required for the inflow wind at the target point to reach the plane of the impeller.
  • the time prediction module 30 can predict the arrival time of the incoming flow required for the inflow wind at the target point to reach the impeller plane according to the corresponding relationship between the target wind speed and the arrival time of the incoming flow.
  • the time prediction module 30 may pre-establish the corresponding relationship between the target wind speed and the flow time required for the inflow wind at the target point to reach the impeller plane.
  • the time prediction module 30 can search for the flow time corresponding to the synthesized target wind speed according to the pre-established correspondence, and determine the found flow time as the arrival time of the incoming flow.
  • the time prediction module 30 can predict the arrival time of the incoming flow required for the inflow wind at the target point to reach the impeller plane by calculating the arrival time of the incoming flow in sections.
  • the time prediction module 30 can calculate the first flow time required for the inflow wind to flow from each predetermined section to the designated section and the second flow time required for the inflow wind to flow from the designated section to the plane of the impeller, and calculate the first The sum of the flow time and the second flow time is determined as the incoming flow arrival time required for the inflow wind at the target point to reach the impeller plane.
  • each predetermined section may refer to a section whose distance from the plane of the impeller is greater than the distance from the designated section to the plane of the impeller.
  • the feedforward control module 40 performs feedforward control of the wind turbine according to the predicted arrival time of the incoming flow.
  • the feedforward control module 40 can determine the control response time required for the wind turbine to perform the feedforward control, and determine the waiting time for the wind turbine to perform the feedforward control according to the predicted arrival time and the determined control response time. When the determined waiting time is reached, feed forward control is performed on the wind turbine.
  • the difference between the predicted arrival time of the incoming flow and the determined control response time may be determined as the waiting time for the wind turbine to execute the feedforward control.
  • the feedforward control module 40 can perform feedforward control of the wind turbine generator in the following manner: when the determined waiting time is reached, the target wind speed at the current moment is determined, and the control strategy corresponding to the target wind speed at the current moment is determined. Control the wind turbine to implement the determined control strategy.
  • the wind speed and the control strategy corresponding to the wind speed may be stored in the control strategy look-up table.
  • the feedforward control module 40 may search the control strategy look-up table for a control strategy that matches the target wind speed at the current moment.
  • the feedforward control device of a wind turbine can obtain a target wind direction, a target turbulence intensity, and a target wind speed that are not affected by an inductive effect, in addition to obtaining a target wind speed that is not affected by an inductive effect.
  • Target wind shear factor can be obtained.
  • the feedforward control device of a wind turbine generator may further include: a target parameter determination module (not shown in the figure), which uses the acquired inflow wind information at multiple spatial point positions, Determine the target wind shear factor, target wind direction and/or target turbulence intensity.
  • a target parameter determination module (not shown in the figure), which uses the acquired inflow wind information at multiple spatial point positions, Determine the target wind shear factor, target wind direction and/or target turbulence intensity.
  • the feedforward control module 40 may determine the target wind shear factor, target wind direction, and/or target turbulence intensity at the current moment in addition to determining the target wind speed at the current moment.
  • the control strategy executed by controlling the wind turbine may be a control strategy corresponding to at least one of the target wind shear factor, target wind direction, target turbulence intensity, and target wind speed at the current moment.
  • control strategy look-up table may store wind resource parameters and control strategies corresponding to the wind resource parameters.
  • the wind resource parameters include at least one of wind shear factor, wind direction, turbulence intensity, and wind speed.
  • the inflow wind information at the multiple spatial point positions acquired by the inflow wind information acquisition module 10 may be divided into the first inflow wind information and the second inflow wind information.
  • the first inflow wind information may include the inflow wind information at each spatial point above the plane where the beam centerline of the remote sensing measurement device is located
  • the second inflow wind information may include the inflow wind information located below the plane where the beam centerline of the remote sensing measurement device is located. Inflow wind information at each spatial point location.
  • the process of determining the target wind shear factor, target wind direction, and target turbulence intensity by the target parameter determination module is respectively introduced below.
  • the target parameter determination module can calculate the target wind shear factor in the following manner.
  • the target parameter determination module can obtain the first synthesized wind speed by synthesizing the first inflow wind information, and obtain the second synthesized wind speed by synthesizing the second inflow wind information, and calculate the distance above the plane where the beam centerline of the remote sensing measurement device is located.
  • the average value of the height value of each spatial point position is obtained, and the first height value is obtained.
  • the average value of the height value of each spatial point position under the plane where the beam center line of the remote sensing measurement device is located is calculated to obtain the second height value.
  • the synthetic wind speed, the second synthetic wind speed, the first height value and the second height value are used to calculate the target wind shear factor.
  • the target parameter determination module can determine the target wind direction in the following manner.
  • the target parameter determination module can calculate the horizontal wind direction of the inflow wind according to the first inflow wind information, the second inflow wind information, and the zenith angle of each beam of the remote sensing measurement device, and according to the first inflow wind information, the second inflow wind information,
  • the zenith angle of each beam of the remote sensing measurement device and the azimuth angle of each beam of the remote sensing measurement device and the plane of the beam centerline are used to calculate the vertical wind direction of the inflow wind, and determine the angle between the horizontal and vertical wind directions of the inflow wind as the target wind direction.
  • the target parameter determination module can determine the target turbulence intensity in the following manner.
  • the target parameter determination module can use the acquired inflow wind information to synthesize the target wind speed, calculate the wind speed standard deviation of the target wind speed in a predetermined time period and the average wind speed of the target wind speed in the predetermined time period, and combine the wind speed standard deviation and the average wind speed The ratio of is determined as the target turbulence intensity.
  • Fig. 10 shows a block diagram of a controller of a wind turbine according to an exemplary embodiment of the present disclosure.
  • the controller of the wind turbine generator includes: a processor 100, a memory 200 for storing a computer program, and an input/output interface 300, which is used by the processor When 100 is executed, the above-mentioned feedforward control method of the wind turbine is realized.
  • the input/output interface 300 is used to connect various input/output devices.
  • the controller may be a main controller inside the wind turbine generator set, or a sub-controller that interacts with the main controller.
  • the controller may also be a controller deployed in a centralized control system of a wind farm, and is used to send instructions to all wind power generators in the wind farm.
  • the instructions include control instructions or operation scheduling instructions from the power grid.
  • the feedforward control method of the wind turbine generator shown in FIG. 1 may be executed in the processor 100 shown in FIG. 10.
  • the modules shown in Figure 9 can be implemented by general-purpose hardware processors such as digital signal processors, field programmable gate arrays, etc., can also be implemented by dedicated hardware processors such as dedicated chips, or can be implemented entirely through computer programs. It is implemented in software, for example, it may be implemented as various modules in the processor 100 shown in FIG. 10.
  • the storage 200 may include: a data storage 210 for storing inflow wind information at a plurality of spatial point positions acquired from a remote sensing measurement device.
  • the data storage 210 may be various storages capable of storing data for a long time.
  • the processor 100 After the processor 100 obtains the inflow wind information at multiple spatial point positions from the remote sensing measurement device, it stores the obtained inflow wind information in the data storage 210. In addition, the processor 100 may also store the obtained target wind speed, target wind direction, target wind shear factor, and target turbulence intensity in the data storage 210.
  • control strategy look-up table can be stored in the processor 100.
  • directly searching locally can increase the processing speed.
  • present disclosure is not limited to this.
  • the control strategy look-up table can also be stored in other memory besides the processor.
  • the control strategy look-up table can be stored in the data storage 210.
  • the data storage 210 reads and searches the control strategy look-up table, which can reduce the storage burden of the processor.
  • the memory 200 may further include: a data buffer 220.
  • the data buffer 220 is a storage unit with a fixed storage capacity, and the storage unit only stores the current time to the forward value. For the input data of a certain length of time, as the subsequent data is continuously input, the previously stored data is automatically overwritten.
  • the data buffer 220 may be various memories capable of storing data for a short period of time for the processor 100 to use.
  • the target wind speed, target wind direction, target wind shear factor, and target turbulence intensity obtained by the processor 100 may be stored in the data memory 210 or in the data buffer 220.
  • the processor 100 can search the data buffer 220 for the target wind speed (or other wind resource parameters) calculated at the current moment (the moment when the waiting time is reached), and obtain the target wind speed (or other wind resource parameters) based on the current moment.
  • the target wind speed is to search for a matching control strategy from the control strategy lookup table to control the wind turbine to perform actions.
  • a control system of a wind turbine including a remote sensing measurement device and a controller.
  • the remote sensing measurement device detects inflow wind information at multiple spatial points in front of the wind turbine.
  • multiple spatial points are distributed on multiple different cross sections, and the multiple different cross sections have different distances from the wind turbine.
  • the remote sensing measurement device may be set on the top of the nacelle of the wind turbine.
  • the remote sensing measurement device may include, but is not limited to, laser radium.
  • the controller obtains the inflow wind information at multiple spatial point positions from the remote sensing measurement device, so as to realize the above-mentioned feedforward control method of the wind turbine.
  • Exemplary embodiments according to the present disclosure also provide a computer-readable storage medium storing a computer program.
  • the computer-readable storage medium stores a computer program that, when executed by a processor, causes the processor to execute the above-mentioned feedforward control method of the wind turbine.
  • the computer-readable recording medium is any data storage device that can store data read by a computer system. Examples of the computer-readable recording medium include read-only memory, random access memory, read-only optical disk, magnetic tape, floppy disk, optical data storage device, and carrier wave (such as data transmission through the Internet via a wired or wireless transmission path).
  • the wind speed of the inflow wind that is not affected by the induction effect is obtained through an effective wind speed synthesis method, which avoids the measurement of wind speed by the existing wind measuring device The problem of inaccuracy.
  • the influence of the induction effect can be effectively corrected, and the wind speed, direction, turbulence intensity and wind shear of the inflow wind that are not affected by the induction effect can be obtained.
  • the wind speed is obtained by synthesizing the inflow wind information at multiple spatial point positions, which is compared with the currently widely used induced effect. In terms of measuring wind speed at a single point in space, the wind speed value of the inflow wind obtained is more accurate.

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Abstract

提供一种风电机组的前馈控制方法、装置以及控制系统，该前馈控制方法包括：通过遥感测量装置获取风电机组前方的多个空间点位置处的入流风信息，多个空间点分布在多个不同的截面，多个不同的截面相对风电机组的距离不同；利用获取的入流风信息合成目标风速；基于合成的目标风速，预测目标点的入流风到达叶轮平面所需的来流到达时间；根据所预测的来流到达时间对风电机组进行前馈控制。

Description

风电机组的前馈控制方法、装置以及控制系统 技术领域
本公开总体说来涉及风电技术领域，更具体地讲，涉及一种风电机组的前馈控制方法、装置以及控制系统。
背景技术
随着技术的发展，新型遥感测量装置已逐渐应用于风电机组的测试和控制中，但是由于叶轮前方不可避免的存在诱导效应，实际到达叶轮平面的风速的大小并非是自由来流的大小，且来流风速不同，诱导效应的影响也不同，到达叶轮平面的速度衰减率也不同。受诱导效应的影响，导致来流从不同截面处的风速到叶轮平面处的风速并非呈线性变化的，使得对入流风速的检测不够准确。
因此，如何获得精准的入流风信息，从而加强对大型风电机组的控制是当前风电技术研发的焦点之一。
发明内容
本公开的示例性实施例提供一种风电机组的前馈控制方法、装置以及控制系统，以克服上述至少一个缺陷。
在一个总体方面，提供一种风电机组的前馈控制方法，包括：通过遥感测量装置获取所述风电机组前方的多个空间点位置处的入流风信息，所述多个空间点分布在多个不同的截面，所述多个不同的截面相对所述风电机组的距离不同；利用获取的入流风信息合成目标风速；基于合成的目标风速，预测目标点的入流风到达叶轮平面所需的来流到达时间；根据所预测的来流到达时间对风电机组进行前馈控制。
在另一总体方面，提供一种风电机组的前馈控制装置，包括：入流风信息获取模块，通过遥感测量装置获取所述风电机组前方的多个空间点位置处的入流风信息，所述多个空间点分布在多个不同的截面，所述多个不同的截面相对所述风电机组的距离不同；风速合成模块，利用获取的入流风信息合 成目标风速；时间预测模块，基于合成的目标风速，预测目标点的入流风到达叶轮平面所需的来流到达时间；前馈控制模块，根据所预测的来流到达时间对风电机组进行前馈控制。
在另一总体方面，提供一种风电机组的控制器，包括：处理器；输入\输出接口；存储器，用于存储计算机程序，所述计算机程序在被所述处理器执行时实现上述的风电机组的前馈控制方法。
在另一总体方面，提供一种风电机组的控制系统，包括：遥感测量装置，探测所述风电机组前方的多个空间点位置处的入流风信息，所述多个空间点分布在多个不同的截面，所述多个不同的截面相对所述风电机组的距离不同，控制器，从遥感测量装置获取多个空间点位置处的入流风信息，以实现上述的风电机组的前馈控制方法。
在另一总体方面，提供一种存储有计算机程序的计算机可读存储介质，当所述计算机程序在被处理器执行时实现上述的风电机组的前馈控制方法。
采用本公开示例性实施例的风电机组的前馈控制方法、装置以及控制系统，能够基于准确的风速精确推算来流到达叶轮平面的时间，以使风电机组能够通过主动控制来最大程度地降低风电机组受入流风的不确定性导致的载荷。
附图说明
通过下面结合附图进行的描述，本公开的上述和其他目的和特点将会变得更加清楚，其中：
图1示出根据本公开示例性实施例的风电机组的前馈控制方法的流程图；
图2示出根据本公开示例性实施例的遥感测量装置探测多个空间点位置处的入流风信息的示意图；
图3示出根据本公开示例性实施例的遥感测量装置探测多个空间点位置处的入流风信息的二维空间分布示意图；
图4示出根据本公开示例性实施例的风速变化曲线的示意图；
图5示出根据本公开示例性实施例的根据所预测的来流到达时间对风电机组进行前馈控制的步骤的流程图；
图6示出根据本公开示例性实施例的对风电机组进行前馈控制的步骤的流程图；
图7示出根据本公开示例性实施例的计算目标风剪切因子的步骤的流程图；
图8示出根据本公开示例性实施例的确定目标风向的步骤的流程图；
图9示出根据本公开示例性实施例的风电机组的前馈控制装置的框图；
图10示出根据本公开示例性实施例的风电机组的控制系统的框图。
具体实施方式
现在，将参照附图更充分地描述不同的示例实施例，一些示例性实施例在附图中示出。
图1示出根据本公开示例性实施例的风电机组的前馈控制方法的流程图。
参照图1，在步骤S10中，通过遥感测量装置获取风电机组前方的多个空间点位置处的入流风信息。
作为示例，该入流风信息可包括但不限于在各空间点位置处的入流风的风速。
在一个实施例中，在风电机组的机舱顶部可设置遥感测量装置，用于探测多个空间点位置处的入流风信息。在此情况下，步骤S10中从遥感测量装置获取多个空间点位置处的入流风信息。
这里，遥感测量装置可指无接触、远距离的探测技术，作为示例，该遥感测量装置可包括但不限于激光镭达，也可以通过其他装置来探测各空间点位置处的入流风信息，例如，超声波测风装置。
这里，上述多个空间点位于风电机组的叶轮平面的前方(即，迎风一侧)，以激光镭达为例，激光镭达的光束向叶轮平面的前方发射，从而探测位于风电机组的叶轮平面的前方的多个空间点位置处的入流风信息。
图2示出根据本公开示例性实施例的遥感测量装置探测多个空间点位置处的入流风信息的示意图。
在图2所示的示例中，以遥感测量装置为激光镭达为例，假设激光镭达共发射四根光束，基于所发射的光束激光镭达能够探测位于各根光束上的多个空间点位置处的入流风信息。
与激光镭达距离相同的空间点形成一截面，换言之，激光镭达具有多个截面，即，多个空间点分布在多个不同的截面，多个不同的截面相对风电机组的距离不同。通过调整激光镭达的安装角度，可以使得每个截面与叶轮平 面平行，截面与激光镭达之间距离指探测距离，截面N所在位置可指激光镭达能够探测到的最远距离。
图3示出根据本公开示例性实施例的遥感测量装置探测多个空间点位置处的入流风信息的二维空间分布示意图。
如图3所示，对于遥感测量装置所发射的每根光束，光束上的各空间点的位置不仅包括与遥感测量装置的距离值(即，沿光束中心线方向的探测距离)，还包括各空间点的高度值(如高度z、高度z+k)，因此，通过遥感测量装置能够探测到不同探测距离处、不同高度处的各空间点的入流风的风速。遥感测量装置探测的每个空间点位置处的入流风信息可包括沿光束中心线方向的风速和垂直于光束中心线方向的风速。
作为示例，可通过如下公式来表示任一空间点位置处的入流风信息：
Figure PCTCN2019127920-appb-000001
公式(1)中，RAW i,j为遥感测量装置的第i根光束在第j个截面处的入流风的风速，U i,j为第i根光束在第j个截面处沿光束中心线方向的风速，V i,j为第i根光束在第j个截面处垂直于光束中心线方向的风速，θ i为第i根光束的天顶角，
Figure PCTCN2019127920-appb-000002
为第i根光束与预定平面的方位角，该预定平面指处于遥感测量装置上下光束中间的平面。这里，天顶角和方位角均为遥感测量装置的固有参数。
在步骤S20中，利用获取的多个空间点位置处的入流风信息合成目标风速。
在风电机组的叶轮前方，由于叶轮的阻碍作用，会出现一个风速低于来流风速的区域，这种现象被称为诱导效应，风速受诱导效应影响而减弱的区域被称为诱导区。
现有的遥感测量装置测风方式易受诱导效应影响，导致风速测量不准确。在本公开示例性实施例中，通过风速合成来获得目标风速，从而去除诱导效应对风速的影响，以获得更为准确的入流风风速，并基于该入流风风速实现对风电机组的精确控制。也就是说，合成后获得的目标风速为不受诱导效应影响的入流风的风速。
应理解，这里，可利用各种合成方法来将多个空间点位置处的入流风信息合成为目标风速。本公开示例性实施例中所列举的风速合成方法仅为示例，本公开不限于此，还可以利用其他风速合成算法来获得上述目标风速。
由上述介绍可知，遥感测量装置能够发射多根光束用以探测在不同截面处的入流风信息，基于此，在本公开示例性实施例中，提出可以针对每根光束进行风速合成或者针对每个截面进行风速合成，下面将针对不同的风速合成方式分别进行介绍。
第一种情况，基于遥感测量装置的每个截面进行风速合成，以获得目标风速。
在此情况下，针对每个截面，根据处于该截面的各空间点位置处的入流风信息，确定该截面的截面平均风速，根据各截面的截面平均风速来获得目标风速。
例如，任一截面的截面平均风速可为处于该任一截面的各空间点位置处的入流风的风速的平均值。但本公开不限于此，还可通过其他方式来计算截面平均风速，例如，选取处于该任一截面的各空间点位置处的入流风的风速的中间值或者最大值与最小值的平均值等。
下面将示例性地介绍基于每个截面的截面平均风速来获得目标风速的方式。
作为示例，可以根据所有截面的截面平均风速以及所有截面对应的诱导效应影响系数来获得目标风速。
例如，针对每个截面，为该截面设置对应的权重值，计算该截面的截面平均风速与该截面对应的诱导效应影响系数的比值，将针对每个截面计算得到的比值与对应的权重值的加权求和确定为目标风速。
各截面对应的诱导效应影响系数随着各空间点到叶轮平面的距离的远近而不同。作为示例，可通过如下方式来确定每个截面对应的诱导效应影响系数。
具体地，从所有截面中选择一截面作为参考截面，设定该参考截面的诱导效应影响系数，根据所有截面中除参考截面之外的其他截面与该参考截面之间的距离，调整设定的参考截面的诱导效应影响系数，以获得其他截面的诱导效应影响系数。
作为示例，该参考截面可为所有截面中的任意一个截面。具体地，该参考截面可为所有截面中处于风速受诱导效应影响最小的位置处的截面。
例如，可利用风电机组的历史风资源数据找到风电机组的叶轮平面的前方受诱导效应影响最小的位置，将所有截面中处于该位置处的截面(或者离 该位置处最近的截面)确定为参考截面。但本公开不限于此，还可以通过其他方式来选取参考截面，例如，可依据经验从所有截面中选取一截面作为参考截面。
作为示例，可将参考截面对应的诱导效应影响系数设置为1，根据其他截面与该参考截面之间的距离的远近来调整参考截面对应的诱导效应影响系数。例如，可随着各其他截面与参考截面的距离的增大，各其他截面对应的诱导效应影响系数从1开始逐渐减小。作为示例，任一其他截面对应的诱导效应影响系数可为该任一其他截面与参考截面的距离的倒数。
应理解，上述对参考截面对应的诱导效应影响系数的数值的设定仅为示例，本公开不限于此，本领域技术人员可以根据实际需求将参考截面对应的诱导效应影响系数设定为其他值。
除上述确定各截面对应的诱导效应影响系数的方法之外，还可以利用风电机组的历史风资源数据，通过机器学习算法来确定各截面对应的诱导效应影响系数。
例如，历史风资源数据可包括各截面处的入流风的实际风速和探测风速，并基于此来构建机器学习算法的数据样本，通过机器学习算法来获得各截面对应的诱导效应影响系数。可以理解的是，机器学习算法可包括但不限于ELM(Extreme Learning Machine，极限学习机)，还可以是其他机器学习算法。
作为示例，还可以通过消除各截面的截面平均风速的时间相位差来获得目标风速。
例如，通过对各截面的截面平均风速进行合成，获得中间风速，以去除各截面的截面平均风速之间的时间相位差，根据中间风速与给定诱导效应影响系数，获得目标风速。
在一实施例中，可通过以下方式确定给定诱导效应影响系数。
例如，为每个截面设置对应的权重值，确定每个截面对应的诱导效应影响系数，将每个截面对应的诱导效应影响系数与对应的权重值的加权求和，确定为给定诱导效应影响系数。
这里，每个截面对应的诱导效应影响系数可采用上述的通过调整参考截面的诱导效应影响系数的方式来获得。此外，应理解，本公开示例性实施例中给出的上述确定给定诱导效应影响系数的方式仅为示例，也可以通过其他方式来确定给定诱导效应影响系数，例如，该给定诱导效应影响系数可依据 经验来设定。
作为示例，可通过以下方式来获得中间风速。
针对每个截面，根据该截面到指定截面的距离以及该截面的截面平均风速，确定入流风由该截面流动到指定截面时的估测风速，将所有估测风速的平均值确定为中间风速。
例如，可通过以下方式确定入流风由任一截面流动到指定截面时的估测风速。
根据该任一截面到指定截面的距离以及该任一截面的截面平均风速，计算入流风由该任一截面流动到指定截面所需的流动时间；将经过流动时间之后所确定的指定截面的截面平均风速，确定为入流风由该任一截面流动到指定截面时的估测风速。
这里，上述指定截面可为所有截面中的任意一个截面，例如，可将任一截面到指定截面的距离与该任一截面的截面平均风速的比值，确定为入流风由该任一截面流动到指定截面所需的流动时间。
上述去除多个截面平均风速的时间相位差来合成中间风速的方法，考虑到在任意时刻的不同截面位置处的入流风的风速大小不同，且入流风由不同截面流动到叶轮平面所需的时间也不同。假设风流场空间被冻结，则根据相邻两个截面之间的距离和截面平均风速，可以计算出入流风在此距离内流动所需的流动时间。
在本公开示例性实施例中，实时获取各空间点位置处的入流风信息，并且实时计算各截面的截面平均风速。根据遥感测量装置的采样频率，可以获得在经过流动时间之后入流风流动到指定截面时获取的各空间点位置处的入流风的风速，并将此时计算得到的指定截面的截面平均风速确定为估测风速，再将入流风由每个截面流动到指定截面时的估测风速的平均值确定为中间风速。
第二种情况，基于激光镭达发射的每根光束进行风速合成，以获得目标风速。
在此情况下，针对激光镭达发射的每根光束，根据该光束上的各空间点位置处的入流风信息以及与各空间点位置处对应的诱导效应影响系数，确定该光束的光束合成风速，将所有光束的光束合成风速的平均值，确定为目标风速。
例如，可通过以下方式确定任一光束的光束合成风速：为每个空间点位置设置对应的权重值，计算该任一光束上的每个空间点位置处的入流风信息与对应的诱导效应影响系数的比值，将每个比值与对应的权重值的加权求和确定为该任一光束的光束合成风速。
这里，可参考上述确定每个截面对应的诱导效应影响系数的方法来确定与每个空间点位置处对应的诱导效应影响系数。
在本公开示例性实施例中，除上述针对每根光束或者针对每个截面进行风速合成的方法之外，还可以基于风速拟合曲线来获得目标风速。
这里，应理解，对于除激光镭达之外的其他种类的遥感测量装置，以超声波测风装置为例，可以基于超声波测风装置所发射的一束超声波进行风速合成。
第三种情况，基于多个空间点位置处的入流风信息的风速拟合曲线来获得目标风速。
在此情况下，根据获取的多个空间点位置处的入流风信息，获得入流风从目标点流动到叶轮平面的风速变化曲线，对获得的风速变化曲线进行积分，将积分面积与目标点到叶轮平面的距离的比值，确定为目标风速。
图4示出根据本公开示例性实施例的风速变化曲线的示意图。
应理解，目标点可以是距离叶轮平面有限远范围内任意一点，地，目标点可为距离叶轮平面有限远范围内、无诱导效应影响的入流点(如，图4中所示的Q点)。这里，该目标风速可被定义为是指该目标点处的入流风的风速。
在获取到多个空间点位置处的入流风信息之后，可以利用各种拟合、滤波、平滑方法来获得入流风从目标点流动到叶轮平面的风速变化曲线(即，光顺风速变化曲线)，以基于该风速变化曲线来确定目标风速。这里，对多个数值进行拟合、滤波、平滑的方法为本领域的公知常识，本公开对此部分的内容不再赘述。
在一实施例中，可基于目标点所在位置来选取不同的计算方式来确定目标风速。
在本公开示例性实施例中，引入湍流冻结理论，假设在叶轮平面的前方的风流域未演化，如果目标点Q所在位置x OPT(即，目标点到风电机组的叶轮平面的距离)大于或者等于遥感测量装置的最远探测距离D(N)，则可以采 用如下公式(2)所示的方法来计算目标风速。
Figure PCTCN2019127920-appb-000003
公式(2)中，U OPT为目标风速，RAWS j为遥感测量装置的第j个截面的截面平均风速，x OPT为目标点到叶轮平面的距离，x j为第j个截面到叶轮平面的距离，1≤j≤n，n为计算目标风速所用到的截面的个数，t m为入流风从目标点流动到叶轮平面所需的流动时间，
Figure PCTCN2019127920-appb-000004
为入流风从第j个截面流动到相邻的第j-1个截面的平均风速。
如果目标点Q所在位置小于遥感测量装置的最远探测距离D(N)，则可以采用公式(3)所示的方法来计算目标风速。
Figure PCTCN2019127920-appb-000005
在本公开示例性实施例中，公式(3)中的第p个截面可指处于目标点与叶轮平面之间的多个截面中距离目标点最近的截面，假设距离遥感测量装置最近的截面为第一个截面(即，j＝1)。
上述公式(2)和公式(3)的风速通过去除各个截面的截面平均风速的时间相位差，再进行平均计算，可获得不受诱导影响的目标风速。
此外，上述公式中的平均风速
Figure PCTCN2019127920-appb-000006
可利用图4所示的风速变化曲线来获得。例如，可对从第j个截面到相邻的第j-1个截面之间的风速变化曲线进行积分，将积分面积与两个截面的距离差值Δd的比值确定为平均风速
Figure PCTCN2019127920-appb-000007
图4中ΔU表示两个截面的截面平均风速的差值，t j表示入流风从第N个截面流动到第j个截面所需的流动时间。
在本公开示例性实施例中，根据复杂风场中存在的垂直风剪切效应、水平风剪切效应以及诱导效应等对叶轮前方流场的影响规律，通过对多个空间点位置处的入流风信息进行合成来获得不受诱导效应影响的目标风速，以用于对风电机组的主动控制和评估中。
返回图1，在步骤S30中，基于合成的目标风速，预测目标点的入流风到达叶轮平面所需的来流到达时间。
在本公开一实施例中，在预测来流到达时间时，可以引入湍流冻结理论， 即，假设在叶轮平面前的风流域未演化，在此前提条件下来基于合成的目标风速预测来流到达时间。
可选地，可通过以下方式来预测来流到达时间。
第一种情况，可根据目标点所在位置处到叶轮平面的距离以及目标风速来预测来流到达时间。
例如，可将目标点所在位置处到叶轮平面的距离与目标风速的比值，确定为来流到达时间。
第二种情况，可根据风速变化曲线以及目标风速来预测来流到达时间。
针对上述基于多个空间点位置处的入流风信息的风速变化曲线来获得目标风速的情况，可以对从目标点到叶轮平面之间的风速变化曲线进行积分，将其积分面积与目标风速的比值，确定为目标点的入流风到达叶轮平面所需的来流到达时间。
第三种情况，可根据目标风速与来流到达时间的对应关系，来预测目标点的入流风到达叶轮平面所需的来流到达时间。
例如，可以通过深度学习的方法，根据风电机组的历史风资源数据预先建立目标风速与目标点的入流风到达叶轮平面所需的流动时间的对应关系。当合成得到目标风速之后，可依据预先建立的对应关系查找与合成得到的目标风速对应的流动时间，并将查找到的流动时间确定为来流到达时间。这里，用于建立对应关系的目标风速和流动时间可采用本公开示例性实施例中的上述方法来获得。
第四种情况，可通过分段计算来流到达时间的方式来预测目标点的入流风到达叶轮平面所需的来流到达时间。
例如，可计算入流风从各预定截面流动到指定截面所需的第一流动时间以及入流风从指定截面流动到叶轮平面所需的第二流动时间，将上述计算得到的第一流动时间和第二流动时间之和确定为目标点的入流风到达叶轮平面所需的来流到达时间。这里，各预定截面可指到叶轮平面的距离大于指定截面到叶轮平面的距离的截面。
作为示例，目标点的入流风到达叶轮平面所需的来流到达时间可通过如下公式预测：
Figure PCTCN2019127920-appb-000008
公式(4)中，t OPT为目标点的入流风到达叶轮平面所需的来流到达时间，t b为入流风从第b个预定截面流动到指定截面a所需的第一流动时间，t a为入流风从指定截面a流动到叶轮平面所需的第二流动时间，c为预定截面的个数。
这里，可将第b个截面到指定截面a的距离与第b个截面的截面平均风速的比值确定为第一流动时间t b，或者可对从第b个截面到指定截面a之间的风速变化曲线进行积分，将其积分面积与第b个截面的截面平均风速的比值确定为第一流动时间t b。
相应地，可将指定截面a到叶轮平面的距离与指定截面a的截面平均风速的比值确定为第二流动时间t a，或者可对从指定截面a到叶轮平面之间的风速变化曲线进行积分，将其积分面积与指定截面a的截面平均风速的比值确定为第二流动时间t a。
如果目标点Q所在位置小于或者等于遥感测量装置的最远探测距离D(N)，则可利用上述的公式(4)来预测来流到达时间。如果目标点Q所在位置大于遥感测量装置的最远探测距离D(N)，则
Figure PCTCN2019127920-appb-000009
除包括上述第一流动时间t b和第二流动时间t a之外，还应包括第三流动时间t d，第三流动时间t d指入流风从目标点流动到最远探测距离D(N)处所需的流动时间。例如，第三流动时间t d可由目标点到最远探测距离D(N)处的距离与最远探测距离D(N)处的截面平均风速的比值来确定。
应理解，上述本公开示例性实施例中所列举的基于目标风速预测来流到达时间的方法仅为示例，还可以通过其他方式来预测来流到达时间。
在步骤S40中，根据所预测的来流到达时间对风电机组进行前馈控制。
通过上述步骤可以准确计算得到诱导区之外的剪切入流风的目标风速，以在入流风到来时对风电机组进行前馈控制。
在一实施例中，可利用图5所示的方式对风电机组进行前馈控制。图5示出根据本公开示例性实施例的根据所预测的来流到达时间对风电机组进行前馈控制的步骤的流程图。
参照图5，在步骤S31中，确定风电机组执行前馈控制所需的控制响应时间。
例如，可将风电机组历史上执行一次前馈控制所需的时间作为该控制响应时间，或者也可以依据经验来人为设定风电机组执行前馈控制所需的控制响应时间。
在步骤S32中，根据所预测的来流到达时间和所确定的控制响应时间，确定风电机组执行前馈控制的等待时间。
这里，可将所预测的来流到达时间与所确定的控制响应时间的差值确定为风电机组执行前馈控制的等待时间。
在步骤S33中，在到达所确定的等待时间时，对风电机组进行前馈控制。
应理解，图5所示的根据所预测的来流到达时间对风电机组进行前馈控制的方式进行为示例，本公开不限于此，还可以通过其他方式来基于来流到达时间对风电机组进行前馈控制，例如，可以在到达所预测的来流到达时间时对风电机组进行前馈控制。
图6示出根据本公开示例性实施例的对风电机组进行前馈控制的步骤的流程图。
参照图6，在步骤S331中，在到达所确定的等待时间时，确定当前时刻的目标风速。
在本公开示例性实施例中，实时获取各空间点位置处的入流风信息，并且实时计算合成的目标风速。在此情况下，当当前时刻到达所确定的等待时间时，获取到达等待时间这一时刻的目标风速。
在步骤S332中，确定与当前时刻的目标风速所对应的控制策略。
在一实施例中，在控制策略查找表中可存储有风速以及与风速对应的控制策略，在此情况下，可从控制策略查找表中搜索与当前时刻的目标风速匹配的控制策略。
应理解，上述基于控制策略查找表来确定与目标风速对应的控制策略的方式仅为示例，本公开不限于此，还可以通过其他方式来确定与目标风速对应的控制策略。
在步骤S333中，控制风电机组执行所确定的控制策略。
在一实施例中，根据本公开示例性实施例的风电机组的前馈控制方法除获得不受诱导效应影响的目标风速之外，可还获得不受诱导效应影响的目标风向(可指入流风的风向)、目标湍流强度、目标风剪切因子。
作为示例，根据本公开示例性实施例的风电机组的前馈控制方法可还包括：利用获取的多个空间点位置处的入流风信息，确定目标风剪切因子、目标风向和/或目标湍流强度。
在此情况下，在到达所确定的等待时间时，除确定当前时刻的目标风速 之外，可还确定当前时刻的目标风剪切因子、目标风向和/或目标湍流强度。此时，控制风电机组执行的控制策略可为与当前时刻的目标风剪切因子、目标风向、目标湍流强度中的至少一项以及目标风速所对应的控制策略。
在此情况下，控制策略查找表中可存储有风资源参数以及与风资源参数对应的控制策略，该风资源参数包括风剪切因子、风向、湍流强度中的至少一项以及风速。
作为示例，控制策略可包括但不限于以下项中的至少一项：对风电机组的偏航控制、变桨控制、降载控制、停机控制、转矩调整控制。
在控制策略查找表的控制策略中可存储与上述各控制方式对应的控制参数，例如，偏航角度值、变桨角度值等，此时可从控制策略查找表中查找与当前时刻的风资源参数对应的控制策略下的各控制参数，发送至风电机组以使风电机组基于各控制参数进行动作。这里，控制策略除包括上述各控制方式之外，可还包括计算风电机组的预定参量(如发电量)，例如基于获得的目标风剪切因子、目标风向、目标湍流强度和/或目标风速来评估风电机组的发电量。
作为示例，与目标风速对应的控制策略可为对风电机组进行变桨控制，与目标风速和目标风向对应的控制策略可为对风电机组进行偏航控制、停机控制，与目标湍流强度对应的控制策略可为对风电机组进行转矩调整控制。应理解，上述所列举的风资源参数与控制策略的对应关系仅为示例，本公开不限于此，本领域技术人员可以根据实际需求来建立控制策略查找表。
通过上述前馈控制方式使得风电机组通过主动控制“适时”响应，最终实现“随风而动，顺势而为”。
地，获取的多个空间点位置处的入流风信息可被划分为第一入流风信息和第二入流风信息。例如，第一入流风信息可包括处于遥感测量装置的光束中心线所在平面上方的各空间点位置处的入流风信息，第二入流风信息可包括处于遥感测量装置的光束中心线所在平面下方的各空间点位置处的入流风信息。
下面来分别介绍确定目标风剪切因子、目标风向、目标湍流强度的过程。
下面参照图7来介绍利用获取的多个空间点位置处的入流风信息计算目标风剪切因子的步骤。
图7示出根据本公开示例性实施例的计算目标风剪切因子的步骤的流程 图。
参照图7，在步骤S701中，通过对第一入流风信息进行合成获得第一合成风速。
例如，可将处于遥感测量装置的光束中心线所在平面上方的各空间点位置处的入流风的风速的平均值确定为第一合成风速，但本公开不限于此，还可以通过其他方式来获得合成风速。
在步骤S702中，通过对第二入流风信息进行合成获得第二合成风速。
例如，可将处于遥感测量装置的光束中心线所在平面下方的各空间点位置处的入流风的风速的平均值确定为第二合成风速，但本公开不限于此，还可以通过其他方式来获得合成风速。
在步骤S703中，计算处于遥感测量装置的光束中心线所在平面上方的各空间点位置的高度值的平均值，获得第一高度值。
这里，获取的多个空间点位置处的入流风信息可还包括各空间点位置的高度值，因此，此时可将处于遥感测量装置的光束中心线所在平面上方的各空间点位置的高度值的平均值确定为第一高度值。
在步骤S704中，计算处于遥感测量装置的光束中心线所在平面下方的各空间点位置的高度值的平均值，获得第二高度值。
在步骤S705中，根据第一合成风速、第二合成风速、第一高度值和第二高度值，计算目标风剪切因子。
作为示例，可利用如下公式来计算目标风剪切因子：
Figure PCTCN2019127920-appb-000010
公式(5)中，V Shear表示目标风剪切因子(垂直风剪切因子)，HWS +表示第一合成风速，HWS -表示第二合成风速，H +表示第一高度值，H -表示第二高度值。
这里，应理解，上述过程是针对多个空间点位置计算一目标风剪切因子，但本公开不限于此，还可以针对每个截面计算对应的风剪切因子，此时，目标风剪切因子包括各截面对应的风剪切因子。作为示例，任一截面对应的风剪切因子可以基于处于该任一截面位置处的各空间点位置处入流风信息，利 用公式(5)来计算该任一截面对应的风剪切因子。
下面参照图8来介绍利用获取的多个空间点位置处的入流风信息计算目标风向的步骤。
图8示出根据本公开示例性实施例的确定目标风向的步骤的流程图。
参照图8，在步骤S801中，根据第一入流风信息、第二入流风信息、遥感测量装置各光束的天顶角，计算入流风的水平风向。
作为示例，可利用如下公式来计算入流风的水平风向：
Figure PCTCN2019127920-appb-000011
公式(6)中，U +表示入流风的水平风向，
Figure PCTCN2019127920-appb-000012
表示处于遥感测量装置的光束中心线所在平面上方的各空间点位置处的入流风的风速的平均值，
Figure PCTCN2019127920-appb-000013
表示处于遥感测量装置的光束中心线所在平面下方的各空间点位置处的入流风的风速的平均值，θ为各光束的天顶角的平均值。
在步骤S802中，根据第一入流风信息、第二入流风信息、遥感测量装置各光束的天顶角、遥感测量装置各光束与光束中心线所在平面的方位角，计算入流风的垂直风向。
作为示例，可利用如下公式来计算入流风的垂直风向：
Figure PCTCN2019127920-appb-000014
公式(7)中，V +表示入流风的垂直风向，
Figure PCTCN2019127920-appb-000015
为各光束与预定平面的方位角的平均值。
在步骤S803中，将入流风的水平风向与垂直风向的夹角，确定为目标风向。
作为示例，可利用如下公式来计算目标风向：
Ω +＝atan2(U +；V +)      (8)
公式(8)中，Ω +表示目标风向，atan2()表示用于计算入流风的水平风向与垂直风向之间的夹角的角度值的函数。
下面介绍利用获取的多个空间点位置处的入流风信息确定目标湍流强度的步骤。
例如，可通过如下方式来获得目标湍流强度：利用获取的入流风信息合成目标风速，计算预定时间段内的目标风速的风速标准差以及预定时间段内的目标风速的风速平均值，将风速标准差与风速平均值的比值，确定为目标湍流强度。
应理解，上述过程是针对多个空间点位置计算一目标湍流强度，但本公开不限于此，还可以针对每个截面计算对应的湍流强度，此时，目标湍流强度包括各截面对应的湍流强度。作为示例，任一截面对应的湍流强度可以基于处于该任一截面位置处的各空间点位置处入流风信息，利用上述所列举的方式来计算该任一截面对应的湍流强度。
这里，应理解，上述确定目标风向、目标风剪切因子、目标湍流强度的方式仅为示例，本公开不限于此，还可以通过其他方式来确定目标风向、目标风剪切因子、目标湍流强度。
图9示出根据本公开示例性实施例的风电机组的前馈控制装置的框图。
如图9所示，根据本公开示例性实施例的风电机组的前馈控制装置包括：入流风信息获取模块10、风速合成模块20、时间预测模块30和前馈控制模块40。
具体说来，入流风信息获取模块10通过遥感测量装置获取风电机组前方的获取多个空间点位置处的入流风信息。这里，多个空间点分布在多个不同的截面，多个不同的截面相对风电机组的距离不同。作为示例，该入流风信息可包括但不限于在各空间点位置处的入流风的风速。
在一实施例中，在风电机组的机舱顶部可设置遥感测量装置，用于探测多个空间点位置处的入流风信息。在此情况下，入流风信息获取模块10可从遥感测量装置获取多个空间点位置处的入流风信息。作为示例，该遥感测量装置可包括但不限于激光镭达。
风速合成模块20利用获取的入流风信息合成目标风速。
在本公开示例性实施例中，风速合成模块20可以针对每根光束进行风速合成或者针对每个截面进行风速合成，下面将针对不同的风速合成方式分别进行介绍。
第一种情况，风速合成模块20基于遥感测量装置的每个截面进行风速合成，以获得目标风速。
在此情况下，风速合成模块20针对每个截面，根据处于该截面的各空间 点位置处的入流风信息，确定该截面的截面平均风速，根据各截面的截面平均风速来获得目标风速。
例如，任一截面的截面平均风速可为处于该任一截面的各空间点位置处的入流风的风速的平均值。
下面分别介绍两种基于每个截面的截面平均风速来获得目标风速的方式。
在第一实施例中，风速合成模块20可以根据所有截面的截面平均风速以及所有截面对应的诱导效应影响系数来获得目标风速。
例如，风速合成模块20针对每个截面，为该截面设置对应的权重值，计算该截面的截面平均风速与该截面对应的诱导效应影响系数的比值，将针对每个截面计算得到的比值与对应的权重值的加权求和确定为目标风速。
在一实施例中，风速合成模块20可通过如下方式来确定每个截面对应的诱导效应影响系数。
例如，从所有截面中选择一截面作为参考截面，设定该参考截面的诱导效应影响系数，根据所有截面中除参考截面之外的其他截面与该参考截面之间的距离，调整设定的参考截面的诱导效应影响系数，以获得其他截面的诱导效应影响系数。
作为示例，该参考截面可为所有截面中的任意一个截面。地，该参考截面可为所有截面中处于风速受诱导效应影响最小的位置处的截面。
在第二实施例中，风速合成模块20可通过消除各截面的截面平均风速的时间相位差来获得目标风速。
例如，风速合成模块20通过对各截面的截面平均风速进行合成，获得中间风速，以去除各截面的截面平均风速之间的时间相位差，根据中间风速与给定诱导效应影响系数，获得目标风速。
在一实施例中，风速合成模块20可通过以下方式确定给定诱导效应影响系数。
例如，为每个截面设置对应的权重值，确定每个截面对应的诱导效应影响系数，将每个截面对应的诱导效应影响系数与对应的权重值的加权求和，确定为给定诱导效应影响系数。
作为示例，风速合成模块20可通过以下方式来获得中间风速。
针对每个截面，根据该截面到指定截面的距离以及该截面的截面平均风速，确定入流风由该截面流动到指定截面时的估测风速，将所有估测风速的 平均值确定为中间风速。
例如，风速合成模块20可通过以下方式确定入流风由任一截面流动到指定截面时的估测风速。
根据该任一截面到指定截面的距离以及该任一截面的截面平均风速，计算入流风由该任一截面流动到指定截面所需的流动时间；将经过流动时间之后所确定的指定截面的截面平均风速，确定为入流风由该任一截面流动到指定截面时的估测风速。
第二种情况，风速合成模块20基于遥感测量装置发射的每根光束进行风速合成，以获得目标风速。
在此情况下，风速合成模块20针对遥感测量装置发射的每根光束，根据该光束上的各空间点位置处的入流风信息以及与各空间点位置处对应的诱导效应影响系数，确定该光束的光束合成风速，将所有光束的光束合成风速的平均值，确定为目标风速。
例如，风速合成模块20可通过以下方式确定任一光束的光束合成风速：为每个空间点位置设置对应的权重值，计算该任一光束上的每个空间点位置处的入流风信息与对应的诱导效应影响系数的比值，将每个比值与对应的权重值的加权求和确定为该任一光束的光束合成风速。
在本公开示例性实施例中，除上述针对每根光束或者针对每个截面进行风速合成的方式之外，还可以基于风速拟合曲线来获得目标风速。
第三种情况，风速合成模块20基于多个空间点位置处的入流风信息的风速拟合曲线来获得目标风速。
在此情况下，风速合成模块20根据获取的多个空间点位置处的入流风信息，获得入流风从目标点流动到叶轮平面的风速变化曲线，对获得的风速变化曲线进行积分，将积分面积与目标点到叶轮平面的距离的比值，确定为目标风速。
时间预测模块30基于合成的目标风速，预测目标点的入流风到达叶轮平面所需的来流到达时间。
第一种情况，时间预测模块30可根据目标点所在位置处到叶轮平面的距离以及目标风速来预测来流到达时间。
例如，时间预测模块30可将目标点所在位置处到叶轮平面的距离与目标风速的比值，确定为来流到达时间。
第二种情况，时间预测模块30可根据风速变化曲线以及目标风速来预测来流到达时间。
针对上述基于多个空间点位置处的入流风信息的风速变化曲线来获得目标风速的情况，时间预测模块30可以对从目标点到叶轮平面之间的风速变化曲线进行积分，将其积分面积与目标风速的比值，确定为目标点的入流风到达叶轮平面所需的来流到达时间。
第三种情况，时间预测模块30可根据目标风速与来流到达时间的对应关系，来预测目标点的入流风到达叶轮平面所需的来流到达时间。
例如，时间预测模块30可预先建立目标风速与目标点的入流风到达叶轮平面所需的流动时间的对应关系。
当风速合成模块20合成得到目标风速之后，时间预测模块30可依据预先建立的对应关系查找与合成得到的目标风速对应的流动时间，并将查找到的流动时间确定为来流到达时间。
第四种情况，时间预测模块30可通过分段计算来流到达时间的方式来预测目标点的入流风到达叶轮平面所需的来流到达时间。
例如，时间预测模块30可计算入流风从各预定截面流动到指定截面所需的第一流动时间以及入流风从指定截面流动到叶轮平面所需的第二流动时间，将上述计算得到的第一流动时间和第二流动时间之和确定为目标点的入流风到达叶轮平面所需的来流到达时间。这里，各预定截面可指到叶轮平面的距离大于指定截面到叶轮平面的距离的截面。
前馈控制模块40根据所预测的来流到达时间对风电机组进行前馈控制。
例如，前馈控制模块40可确定风电机组执行前馈控制所需的控制响应时间，根据所预测的来流到达时间和所确定的控制响应时间，确定风电机组执行前馈控制的等待时间，在到达所确定的等待时间时，对风电机组进行前馈控制。
这里，可将所预测的来流到达时间与所确定的控制响应时间的差值确定为风电机组执行前馈控制的等待时间。
作为示例，前馈控制模块40可通过如下方式来对风电机组进行前馈控制：在到达所确定的等待时间时，确定当前时刻的目标风速，确定与当前时刻的目标风速所对应的控制策略，控制风电机组执行所确定的控制策略。
这里，在控制策略查找表中可存储有风速以及与风速对应的控制策略， 在此情况下，前馈控制模块40可从控制策略查找表中搜索与当前时刻的目标风速匹配的控制策略。
在一实施例中，根据本公开示例性实施例的风电机组的前馈控制装置除获得不受诱导效应影响的目标风速之外，可还获得不受诱导效应影响的目标风向、目标湍流强度、目标风剪切因子。
在此情况下，根据本公开示例性实施例的风电机组的前馈控制装置可还包括：目标参数确定模块(图中未示出)，利用获取的多个空间点位置处的入流风信息，确定目标风剪切因子、目标风向和/或目标湍流强度。
此时，在到达所确定的等待时间时，前馈控制模块40除确定当前时刻的目标风速之外，可还确定当前时刻的目标风剪切因子、目标风向和/或目标湍流强度。此时，控制风电机组执行的控制策略可为与当前时刻的目标风剪切因子、目标风向、目标湍流强度中的至少一项以及目标风速所对应的控制策略。
在此情况下，控制策略查找表中可存储有风资源参数以及与风资源参数对应的控制策略，该风资源参数包括风剪切因子、风向、湍流强度中的至少一项以及风速。
地，入流风信息获取模块10获取的多个空间点位置处的入流风信息可被划分为第一入流风信息和第二入流风信息。例如，第一入流风信息可包括处于遥感测量装置的光束中心线所在平面上方的各空间点位置处的入流风信息，第二入流风信息可包括处于遥感测量装置的光束中心线所在平面下方的各空间点位置处的入流风信息。
下面来分别介绍目标参数确定模块确定目标风剪切因子、目标风向、目标湍流强度的过程。
目标参数确定模块可通过如下方式来计算目标风剪切因子。
例如，目标参数确定模块可通过对第一入流风信息进行合成获得第一合成风速，通过对第二入流风信息进行合成获得第二合成风速，计算处于遥感测量装置的光束中心线所在平面上方的各空间点位置的高度值的平均值，获得第一高度值，计算处于遥感测量装置的光束中心线所在平面下方的各空间点位置的高度值的平均值，获得第二高度值，根据第一合成风速、第二合成风速、第一高度值和第二高度值，计算目标风剪切因子。
目标参数确定模块可通过如下方式来确定目标风向。
例如，目标参数确定模块可根据第一入流风信息、第二入流风信息、遥感测量装置各光束的天顶角，计算入流风的水平风向，根据第一入流风信息、第二入流风信息、遥感测量装置各光束的天顶角、遥感测量装置各光束与光束中心线所在平面的方位角，计算入流风的垂直风向，将入流风的水平风向与垂直风向的夹角，确定为目标风向。
目标参数确定模块可通过如下方式来确定目标湍流强度。
例如，目标参数确定模块可利用获取的入流风信息合成目标风速，计算预定时间段内的目标风速的风速标准差以及预定时间段内的目标风速的风速平均值，将风速标准差与风速平均值的比值，确定为目标湍流强度。
图10示出根据本公开示例性实施例的风电机组的控制器的框图。
如图10所示，根据本公开示例性实施例的风电机组的控制器包括：处理器100，存储器200，用于存储计算机程序，输入\输出接口300，所述计算机程序在被所述处理器100执行时实现上述的风电机组的前馈控制方法。该输入\输出接口300用于连接各种输入\输出设备。所述控制器可以是风力发电机组内部的主控制器，亦或者是与主控制器交互的子控制器。在一个实施例中，该控制器还可以是部署在风电场集中控制系统中的控制器，用于向风电场内所有的风力发电机组发送指令。所述指令包括控制指令或者来自电网的运行调度指令等。
这里，图1所示的风电机组的前馈控制方法可在图10所示的处理器100中执行。也就是说，图9所示的各模块可由数字信号处理器、现场可编程门阵列等通用硬件处理器来实现，也可通过专用芯片等专用硬件处理器来实现，还可完全通过计算机程序来以软件方式实现，例如，可被实现为图10中所示的处理器100中的各个模块。
在一实施例中，根据本公开示例性实施例的存储器200可包括：数据存储器210，用于存储从遥感测量装置获取的多个空间点位置处的入流风信息。作为示例，数据存储器210可为各种能够长期存储数据的存储器。
处理器100从遥感测量装置获取到多个空间点位置处的入流风信息之后，将获取到的入流风信息存储到数据存储器210中。此外，处理器100还可将获得的目标风速、目标风向、目标风剪切因子、目标湍流强度存储到数据存储器210中。
可选地，控制策略查找表可被存储在处理器100中，在确定控制策略时， 直接从本地进行搜索可以提高处理速度。但本公开不限于此，也可以将控制策略查找表存储在处理器之外的其他存储器中，例如，可以将控制策略查找表存储在数据存储器210中，处理器100在确定控制策略时，从数据存储器210读取控制策略查找表并进行搜索，这样可以减轻处理器的存储负担。
在一实施例中，根据本公开示例性实施例的存储器200可还包括：数据缓存器220，数据缓存器220是一个具有固定存储量的存储单元，该存储单元仅存储当前时刻到向前给定时间长度的输入数据，随着后期数据的不断输入，早先存入的数据被自动被覆盖。
作为示例，数据缓存器220可为各种能够短时存储数据的存储器，以供处理器100使用。
在本公开示例性实施例中，处理器100获得的目标风速、目标风向、目标风剪切因子、目标湍流强度除存储到数据存储器210中，也可以存储到数据缓存器220中。
在此情况下，在到达等待时间时，处理器100可以从数据缓存器220中查找在当前时刻(到达等待时间这一时刻)计算得到的目标风速(或其他风资源参数)，基于当前时刻得到的目标风速来从控制策略查找表中搜索相匹配的控制策略，以控制风电机组进行动作。
根据本公开示例性实施例还提供一种风电机组的控制系统，包括遥感测量装置和控制器。
具体说来，遥感测量装置探测风电机组前方的多个空间点位置处的入流风信息。这里，多个空间点分布在多个不同的截面，多个不同的截面相对所述风电机组的距离不同。
在一实施例中，遥感测量装置可被设置在风电机组的机舱顶部，作为示例，该遥感测量装置可包括但不限于激光镭达。
控制器从遥感测量装置获取多个空间点位置处的入流风信息，以实现上述的风电机组的前馈控制方法。
根据本公开的示例性实施例还提供一种存储有计算机程序的计算机可读存储介质。该计算机可读存储介质存储有当被处理器执行时使得处理器执行上述风电机组的前馈控制方法的计算机程序。该计算机可读记录介质是可存储由计算机系统读出的数据的任意数据存储装置。计算机可读记录介质的示例包括：只读存储器、随机存取存储器、只读光盘、磁带、软盘、光数据存 储装置和载波(诸如经有线或无线传输路径通过互联网的数据传输)。
根据本公开示例性实施例的风电机组的前馈控制方法、装置以及控制系统，通过有效的风速合成方法得到不受诱导效应影响的入流风的风速，避免了现有的测风装置对风速测量不准确的问题。
此外，根据本公开示例性实施例的风电机组的前馈控制方法、装置以及控制系统，可以有效修正诱导效应影响，获得不受诱导效应影响的入流风的风速、风向、湍流强度以及风剪切因子，最终实现风电机组的精准发电量评估和控制，同时可以最大程度地降低风电机组受入流风的不确定性导致的载荷。
此外，根据本公开示例性实施例的风电机组的前馈控制方法、装置以及控制系统，通过对多个空间点位置处的入流风信息进行合成来获得风速，相对于目前广泛采用的受诱导效应影响的单一空间点测量风速的方式而言，所获得的入流风的风速值更为准确。
尽管已参照实施例表示和描述了本公开，但本领域技术人员应该理解，在不脱离由权利要求限定的本公开的精神和范围的情况下，可以对这些实施例进行各种修改和变换。

Claims (28)

  1. 一种风电机组的前馈控制方法，包括：
    通过遥感测量装置获取所述风电机组前方的多个空间点位置处的入流风信息，所述多个空间点分布在多个不同的截面，所述多个不同的截面相对所述风电机组的距离不同；
    利用获取的入流风信息合成目标风速；
    基于合成的目标风速，预测目标点的入流风到达叶轮平面所需的来流到达时间；
    根据所预测的来流到达时间对风电机组进行前馈控制。
  2. 如权利要求1所述的前馈控制方法，其中，利用获取的入流风信息合成目标风速包括：
    针对入流风的每个截面，根据处于该截面的各空间点位置处的入流风信息，确定该截面的截面平均风速；
    根据各截面的截面平均风速来获得目标风速。
  3. 如权利要求2所述的前馈控制方法，其中，利用获取的入流风信息合成目标风速还包括：确定每个截面对应的诱导效应影响系数，
    其中，根据各截面的截面平均风速来获得目标风速包括：根据所有截面的截面平均风速以及对应的诱导效应影响系数，获得目标风速。
  4. 如权利要求3所述的前馈控制方法，其中，确定每个截面对应的诱导效应影响系数包括：
    从所有截面中选择一截面作为参考截面；
    设定所述参考截面的诱导效应影响系数；
    根据所有截面中除所述参考截面之外的其他截面与所述参考截面之间的距离，调整所述参考截面的诱导效应影响系数，以获得所述其他截面的诱导效应影响系数。
  5. 如权利要求3所述的前馈控制方法，其中，根据所有截面的截面平均风速以及对应的诱导效应影响系数，获得目标风速包括：
    为每个截面设置对应的权重值；
    分别计算每个截面的截面平均风速与对应的诱导效应影响系数的比值，将每个比值与对应的权重值的加权求和确定为目标风速。
  6. 如权利要求2所述的前馈控制方法，其中，根据各截面的截面平均风速来获得目标风速包括：
    通过对各截面的截面平均风速进行合成，获得中间风速，以去除各截面的截面平均风速之间的时间相位差；
    根据中间风速与给定诱导效应影响系数，获得目标风速；
    其中，通过以下方式确定给定诱导效应影响系数：
    为每个截面设置对应的权重值；
    确定每个截面对应的诱导效应影响系数；
    将每个截面对应的诱导效应影响系数与对应的权重值的加权求和，确定为所述给定诱导效应影响系数。
  7. 如权利要求6所述的前馈控制方法，其中，通过对各截面的截面平均风速进行合成，获得中间风速包括：
    针对每个截面，根据该截面到指定截面的距离以及该截面的截面平均风速，确定入流风由该截面流动到所述指定截面时的估测风速；
    将所有估测风速的平均值确定为中间风速。
  8. 如权利要求7所述的前馈控制方法，其中，通过以下方式确定入流风由任一截面流动到所述指定截面时的估测风速：
    根据所述任一截面到所述指定截面的距离以及所述任一截面的截面平均风速，计算入流风由所述任一截面流动到所述指定截面所需的流动时间；
    将经过所述流动时间之后所确定的所述指定截面的截面平均风速，确定为入流风由所述任一截面流动到所述指定截面时的估测风速。
  9. 如权利要求1所述的前馈控制方法，其中，所述遥感测量装置包括激光镭达。
  10. 如权利要求9所述的前馈控制方法，其中，利用获取的入流风信息合成目标风速包括：
    针对激光镭达发射的每根光束，根据该光束上的各空间点位置处的入流风信息以及与各空间点位置处对应的诱导效应影响系数，确定该光束的光束合成风速；
    将所有光束的光束合成风速的平均值，确定为目标风速。
  11. 如权利要求10所述的前馈控制方法，其中，通过以下方式确定任一光束的光束合成风速：
    为每个空间点位置设置对应的权重值；
    计算所述任一光束上的每个空间点位置处的入流风信息与对应的诱导效应影响系数的比值，将每个比值与对应的权重值的加权求和确定为所述任一光束的光束合成风速。
  12. 如权利要求1所述的前馈控制方法，其中，基于合成的目标风速，预测目标点的入流风到达叶轮平面所需的来流到达时间包括：
    确定目标点所在位置处到叶轮平面的距离；
    将所确定的距离与合成的目标风速的比值，确定为来流到达时间。
  13. 如权利要求1所述的前馈控制方法，其中，利用获取的入流风信息合成目标风速包括：
    根据获取的多个空间点位置处的入流风信息，获得入流风从目标点流动到叶轮平面的风速变化曲线，
    对获得的风速变化曲线进行积分，将积分面积与目标点到叶轮平面的距离的比值，确定为目标风速，
    其中，基于合成的目标风速，预测目标点的入流风到达叶轮平面所需的来流到达时间包括：
    将积分面积与所述目标风速的比值，确定为目标点的入流风到达叶轮平面所需的来流到达时间。
  14. 如权利要求1所述的前馈控制方法，其中，基于合成的目标风速，预测目标点的入流风到达叶轮平面所需的来流到达时间包括：
    根据目标风速与来流到达时间的对应关系，查找与合成的目标风速对应的来流到达时间，并将查找到的来流到达时间确定为目标点的入流风到达叶轮平面所需的来流到达时间。
  15. 如权利要求1所述的前馈控制方法，其中，基于合成的目标风速，预测目标点的入流风到达叶轮平面所需的来流到达时间包括：
    确定入流风从各预定截面流动到指定截面所需的第一流动时间；
    确定入流风从指定截面流动到叶轮平面所需的第二流动时间；
    根据所确定的第一流动时间和第二流动时间，获得目标点的入流风到达叶轮平面所需的来流到达时间。
  16. 如权利要求15所述的前馈控制方法，其中，基于合成的目标风速，预测目标点的入流风到达叶轮平面所需的来流到达时间还包括：
    当目标点所在位置大于遥感测量装置的最远探测距离时，还确定入流风从目标点流动到最远探测距离处所需的第三流动时间，
    其中，根据所确定的第一流动时间、第二流动时间和第三流动时间，获得目标点的入流风到达叶轮平面所需的来流到达时间。
  17. 如权利要求1所述的前馈控制方法，其中，根据所预测的来流到达时间对风电机组进行前馈控制包括：
    确定风电机组执行前馈控制所需的控制响应时间；
    根据所预测的来流到达时间和所确定的控制响应时间，确定风电机组执行前馈控制的等待时间；
    在到达所确定的等待时间时，对风电机组进行前馈控制。
  18. 如权利要求17所述的前馈控制方法，其中，风电机组执行前馈控制的等待时间为所预测的来流到达时间与所确定的控制响应时间的差值。
  19. 如权利要求17所述的前馈控制方法，其中，在到达所确定的等待时间时，对风电机组进行前馈控制包括：
    在到达所确定的等待时间时，确定当前时刻的目标风速；
    确定与当前时刻的目标风速所对应的控制策略；
    控制风电机组执行所确定的控制策略。
  20. 如权利要求19所述的前馈控制方法，其中，确定与当前时刻的目标风速所对应的控制策略包括：从控制策略查找表中搜索与当前时刻的目标风速匹配的控制策略，
    其中，控制策略查找表中存储有风速以及与风速对应的控制策略。
  21. 如权利要求19所述的前馈控制方法，其中，所述前馈控制方法还包括：利用获取的多个空间点位置处的入流风信息，至少确定目标风剪切因子、目标风向或目标湍流强度，
    其中，在到达所确定的等待时间时，对风电机组进行前馈控制还包括：在到达所确定的等待时间时，还至少确定当前时刻的目标风剪切因子、目标风向或目标湍流强度，
    其中，所确定的控制策略为与当前时刻的目标风剪切因子、目标风向、目标湍流强度中的至少一项以及目标风速所对应的控制策略。
  22. 如权利要求21所述的前馈控制方法，其中，获取的入流风信息包括第一入流风信息和第二入流风信息，第一入流风信息包括处于遥感测量装置 的光束中心线所在平面上方的各空间点位置处的入流风信息，第二入流风信息包括处于遥感测量装置的光束中心线所在平面下方的各空间点位置处的入流风信息，
    其中，确定目标风剪切因子包括：
    通过对第一入流风信息进行合成获得第一合成风速；
    通过对第二入流风信息进行合成获得第二合成风速；
    计算处于遥感测量装置的光束中心线所在平面上方的各空间点位置的高度值的平均值，获得第一高度值；
    计算处于遥感测量装置的光束中心线所在平面下方的各空间点位置的高度值的平均值，获得第二高度值；
    根据第一合成风速、第二合成风速、第一高度值和第二高度值，计算目标风剪切因子。
  23. 如权利要求22所述的前馈控制方法，其中，确定目标风向包括：
    根据第一入流风信息、第二入流风信息、遥感测量装置各光束的天顶角，计算入流风的水平风向；
    根据第一入流风信息、第二入流风信息、遥感测量装置各光束的天顶角、遥感测量装置各光束与光束中心线所在平面的方位角，计算入流风的垂直风向；
    将入流风的水平风向与垂直风向的夹角，确定为目标风向。
  24. 如权利要求21所述的前馈控制方法，其中，确定目标湍流强度包括：
    利用获取的多个空间点位置处的入流风信息合成目标风速；
    计算预定时间段内的目标风速的风速标准差以及风速平均值；
    将风速标准差与风速平均值的比值，确定为目标湍流强度。
  25. 一种风电机组的前馈控制装置，其中，包括：
    入流风信息获取模块，通过遥感测量装置获取所述风电机组前方的多个空间点位置处的入流风信息，所述多个空间点分布在多个不同的截面，所述多个不同的截面相对所述风电机组的距离不同；
    风速合成模块，利用获取的入流风信息合成目标风速；
    时间预测模块，基于合成的目标风速，预测目标点的入流风到达叶轮平面所需的来流到达时间；
    前馈控制模块，根据所预测的来流到达时间对风电机组进行前馈控制。
  26. 一种风电机组的控制器，其中，包括：
    处理器；
    输入\输出接口；
    存储器，用于存储计算机程序，所述计算机程序在被所述处理器执行时实现如权利要求1至24中任意一项所述的风电机组的前馈控制方法。
  27. 一种风电机组的控制系统，其中，包括：
    遥感测量装置，探测所述风电机组前方的多个空间点位置处的入流风信息，所述多个空间点分布在多个不同的截面，所述多个不同的截面相对所述风电机组的距离不同，
    控制器，从遥感测量装置获取多个空间点位置处的入流风信息，以实现如权利要求1至24中任意一项所述的风电机组的前馈控制方法。
  28. 一种存储有计算机程序的计算机可读存储介质，其中，当所述计算机程序在被处理器执行时实现如权利要求1至24中任意一项所述的风电机组的前馈控制方法。
PCT/CN2019/127920 2019-05-30 2019-12-24 风电机组的前馈控制方法、装置以及控制系统 Ceased WO2020238182A1 (zh)

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