CN108488038B - A kind of Yaw control method of wind power generating set - Google Patents

A kind of Yaw control method of wind power generating set Download PDF

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Publication number
CN108488038B
CN108488038B CN201810259908.2A CN201810259908A CN108488038B CN 108488038 B CN108488038 B CN 108488038B CN 201810259908 A CN201810259908 A CN 201810259908A CN 108488038 B CN108488038 B CN 108488038B
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wind
data
wind speed
subsequent time
yaw
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CN108488038A (en
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董密
李力
宋冬然
田小雨
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CHANGSHA VICTORY ELECTRICITY TECH Co.,Ltd.
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Central South University
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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 
    • F03D7/02—Controlling wind motors  the wind motors having rotation axis substantially parallel to the air flow entering the rotor
    • F03D7/022—Adjusting aerodynamic properties of the blades
    • F03D7/0236—Adjusting aerodynamic properties of the blades by changing the active surface of the wind engaging parts, e.g. reefing or furling
    • 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
    • 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
    • F05B2270/30—Control parameters, e.g. input parameters
    • F05B2270/329—Azimuth or yaw angle
    • 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

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  • Engineering & Computer Science (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Sustainable Development (AREA)
  • Sustainable Energy (AREA)
  • Chemical & Material Sciences (AREA)
  • Combustion & Propulsion (AREA)
  • Mechanical Engineering (AREA)
  • General Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Fluid Mechanics (AREA)
  • Wind Motors (AREA)

Abstract

A kind of Yaw control method of wind power generating set, comprising: Step 1: calculating separately wind speed average value and the Mathematics models in preset duration according to the wind speed and direction got, historical wind speed data and history wind direction data are obtained, according to the air speed data and wind direction data of historical wind speed data and history wind direction data prediction subsequent time；Step 2: determining control parameter according to the air speed data of subsequent time, and yaw control is carried out to wind power generating set using control parameter and wind direction data.Compared to traditional Yaw control method, the yaw number of this method increases relative to Traditional control strategy, but the number improved is concentrated mainly on middle high wind speed area, therefore power loss coefficient is substantially reduced.This method can effectively reduce the yaw error in middle high wind speed area, to reduce power loss coefficient (improving the utilization rate of wind energy).

Description

A kind of Yaw control method of wind power generating set
Technical field
The present invention relates to technical field of wind power generation, specifically, being related to a kind of yaw controlling party of wind power generating set Method.
Background technique
Currently, with the depleted of conventional fossil fuel and to the increasingly increase of energy demand, people increasingly focus on The development and utilization of reproducible green clean energy resource.Generation mode one of of the wind-power electricity generation as green regenerative energy sources, by To the attention of various countries' industry and academia, wind generating technology is ripe day by day, the advantage of lower cost in renewable energy, therefore There is vast potential for future development.
Yaw adjustment device is wind power generating set to wind regulating device, it make the wind wheel axis of blower always with wind direction Unanimously, and the control precision of demodulator has significant impact to the power generation performance of wind power generating set.Modern large scale wind hair Motor group is run under the premise of being existing for the yaw error.
On the one hand, the presence of yaw error will lead to the reduction of wind energy amount to obtain, be shown according to related data, yaw error Caused annual energy loss is 2.7%, and when yaw error is 20 °, year, loss amount was up to 11%.On the other hand, partially The presence of boat error can also cause the increase of components ' load, this will lead to, and yaw is unstable to be caused to stop so as to cause generating set concussion Machine.
With being gradually increased for modern wind turbine blade, influence also gradually to highlight brought by yaw adjustment device.Related data Failure rate caused by display yaw system accounts for 12.5%, and the downtime as caused by yaw failure accounts for 13.3%.Cause This, it is necessary to the control device and control strategy of the active yawing of Large-scale Wind Turbines are furtherd investigate.
Summary of the invention
To solve the above problems, the present invention provides a kind of Yaw control method of wind power generating set, the yaw control Method processed includes:
Step 1: calculating separately wind speed average value in preset duration according to the wind speed and direction got and wind direction is average Value, obtains historical wind speed data and history wind direction data, next according to the historical wind speed data and the prediction of history wind direction data The air speed data and wind direction data at moment；
Step 2: determining control parameter according to the air speed data of the subsequent time, and utilize the control parameter and wind Yaw control is carried out to wind power generating set to data.
According to one embodiment of present invention, in said step 1, the preset duration is 10s, 30s or 60s.
According to one embodiment of present invention, in said step 1, the air speed data and wind direction number of subsequent time are predicted According to the step of include:
Wind vector is decomposed according to the historical wind speed data and history wind direction data, obtains the horizontal seat of history wind vector Mark data and history wind vector ordinate data；
It is determined using arma modeling according to the history wind vector abscissa data and history wind vector ordinate data The wind vector abscissa data and wind vector ordinate data of subsequent time；
Determine the wind of subsequent time respectively according to the wind vector abscissa data of subsequent time and wind vector ordinate data Fast data and wind direction data.
According to one embodiment of present invention, wind vector is decomposed according to following expression:
Wherein,WithThe wind vector abscissa data and wind vector ordinate data of t moment are respectively indicated, Indicate air speed data,Indicate the wind direction data of t moment.
According to one embodiment of present invention, the air speed data of subsequent time is determined according to following expression:
Wherein,Indicate the air speed data at t+1 moment,WithRespectively indicate the wind at t+1 moment Vector abscissa data and wind vector ordinate data.
According to one embodiment of present invention, the wind direction data of subsequent time is determined according to following expression:
Wherein,Indicate the wind direction data at t+1 moment,WithRespectively indicate the wind arrow at t+1 moment Measure abscissa data and wind vector ordinate data.
According to one embodiment of present invention, in said step 1, the step of predicting the wind direction data of subsequent time packet It includes:
Round change of variable is carried out to the history wind direction data, obtains the sine value and cosine value of history wind direction data；
The wind direction data of subsequent time is determined according to the sine value and cosine value of history wind direction data using arma modeling Sine value and cosine value, and determine according to the sine value of the wind direction data of the subsequent time and cosine value the wind direction of subsequent time Data.
According to one embodiment of present invention, round variable is carried out to the history wind direction data according to following expression to become It changes:
Wherein,WithThe sine value and cosine value of the wind direction data of t moment are respectively indicated,Indicate t moment Wind direction data.
According to one embodiment of present invention, the wind direction data of the subsequent time is determined according to following expression:
Wherein,Indicate the wind direction data at t+1 moment,WithRespectively indicate the wind direction number at t+1 moment According to sine value and cosine value.
According to one embodiment of present invention, in said step 1, true according to history wind direction data using arma modeling Determine the wind direction data of subsequent time.
According to one embodiment of present invention, in said step 1, true according to historical wind speed data using arma modeling Determine the air speed data of subsequent time.
According to one embodiment of present invention, the step of determining the air speed data of subsequent time include:
Step a, trending is carried out to the historical wind speed data to handle, obtain trending air speed data；
Step b, the auto-correlation function and partial autocorrelation function of trending air speed data are removed according to, determine hangover truncation Mode；
Step c, it is based on the hangover truncation mode, the arma modeling is carried out using pre-set criteria to determine rank, is determined certainly Dynamic regression order, Sliding Mean Number order and difference order；
Step d, it is based on the arma modeling, utilizes the automatic returning order, Sliding Mean Number order and difference order According to the air speed data for going trending air speed data to calculate subsequent time.
According to one embodiment of present invention, in the step 2, belonging to the air speed data for determining the subsequent time Wind speed interval, and the control parameter is determined according to affiliated wind speed interval.
According to one embodiment of present invention, in the step 2, if the air speed data of the subsequent time is less than Default incision wind speed, then control wind power generating set and be in shutdown status.
According to one embodiment of present invention, in the step 2, if the wind direction data of the subsequent time is greater than Or be equal to default cut-out wind speed, then wind generating set yaw is controlled to lower wind direction position and in shutdown status.
According to one embodiment of present invention, in the step 2,
If the air speed data of the subsequent time is greater than or equal to default incision wind speed and less than the first default wind speed threshold Value, then keeping the control parameter is that original control parameters are constant；
And/or if the air speed data of the subsequent time is greater than or equal to the described first default wind speed threshold value and is less than Original control parameters reduction particular value is then obtained required control parameter by default cut-out wind speed.
According to one embodiment of present invention, in the step 2, the described first default wind speed threshold value is preset with described It include several wind speed intervals between rated wind speed, wherein for these wind speed intervals, wind speed is bigger, wind speed interval institute Corresponding control parameter is then smaller.
According to one embodiment of present invention, in the step 2, if the air speed data of the subsequent time is greater than Or be equal to default rated wind speed and be less than default cut-out wind speed, then the wind-force is sent out according to the wind direction data of the subsequent time Motor group carries out yaw control so that the yaw error of the wind power generating set is in default error range.
Compared to traditional Yaw control method, the yaw number of Yaw control method provided by the present invention is relative to tradition Control strategy increases, but the number improved is concentrated mainly on middle high wind speed area, therefore power loss coefficient is substantially reduced.This The forecast Control Algorithm of subregion provided by inventing can effectively reduce the yaw error in middle high wind speed area, to reduce power Loss coefficient (improves the utilization rate of wind energy).
Other features and advantages of the present invention will be illustrated in the following description, also, partly becomes from specification It obtains it is clear that understand through the implementation of the invention.The objectives and other advantages of the invention can be by specification, right Specifically noted structure is achieved and obtained in claim and attached drawing.
Detailed description of the invention
In order to more clearly explain the embodiment of the invention or the technical proposal in the existing technology, to embodiment or will show below There is required attached drawing in technical description to do simple introduction:
Fig. 1 is the structural schematic diagram of the wind power generating set with active yawing adjuster；
Fig. 2 is that yaw system driving motor rotates forward the schematic diagram so that wind energy conversion system cabin tuning clockwise；
Fig. 3 is that yaw system driving motor rotates forward the schematic diagram so that wind energy conversion system cabin tuning counterclockwise；
Fig. 4 is the implementation process schematic diagram of existing yaw logic control algorithm；
Fig. 5~Fig. 7 shows the distribution relation figure between the wind speed and direction of certain southern wind power plant；
Fig. 8~Figure 10 is the actual running results schematic diagram under traditional Yaw Control Strategy；
Figure 11 is the implementation process schematic diagram of wind speed independent prediction method according to an embodiment of the invention；
The auto-correlation function of Figure 12 and Figure 13 wind series 10s average value according to an embodiment of the invention and partial correlation Function schematic diagram；
Figure 14 is the implementation process schematic diagram of wind speed and direction prediction technique according to an embodiment of the invention；
Figure 15 is the implementation process schematic diagram of wind speed and direction prediction technique according to an embodiment of the invention；
Figure 16 shows the original wind direction of one embodiment of the invention and the schematic diagram of the mean wind direction under different durations；
Figure 17 shows the schematic diagrames of the mean wind speed under the original wind speed of one embodiment of the invention and different durations；
Figure 18 and Figure 19 respectively illustrates the obtained 10s wind direction prediction of different prediction techniques of one embodiment of the invention As a result with forecasting wind speed result schematic diagram；
Figure 20 and Figure 21 respectively illustrates the obtained 30s wind direction prediction of different prediction techniques of one embodiment of the invention As a result with forecasting wind speed result schematic diagram；
Figure 22 and Figure 23 respectively illustrates the obtained 60s wind direction prediction of different prediction techniques of one embodiment of the invention As a result with forecasting wind speed result schematic diagram；
Figure 24 shows the implementation process signal of the Yaw control method of the wind power generating set of one embodiment of the invention Figure；
Figure 25 shows the ideal operation power graph of the wind power generating set of one embodiment of the invention；
Figure 26 shows the nacelle position figure under the different control strategies of one embodiment of the invention；
Figure 27 to Figure 30 is respectively illustrated under the different control strategies of one embodiment of the invention in different wind speed intervals Yaw error distribution map.
Specific embodiment
Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings and examples, how to apply to the present invention whereby Technological means solves technical problem, and the realization process for reaching technical effect can fully understand and implement.It needs to illustrate As long as not constituting conflict, each feature in each embodiment and each embodiment in the present invention can be combined with each other, It is within the scope of the present invention to be formed by technical solution.
Meanwhile in the following description, for illustrative purposes and numerous specific details are set forth, to provide to of the invention real Apply the thorough understanding of example.It will be apparent, however, to one skilled in the art, that the present invention can not have to tool here Body details or described ad hoc fashion are implemented.
In addition, step shown in the flowchart of the accompanying drawings can be in the department of computer science of such as a group of computer-executable instructions It is executed in system, although also, logical order is shown in flow charts, and it in some cases, can be to be different from herein Sequence execute shown or described step.
In terms of the control of current yaw system is concentrated mainly on power control, such as maximum power point tracking (maximum Power point tracking, referred to as MPPT) control.Since early stage is limited by measuring technique, yaw control is adopted Use climbing method.But since the MPP of blower is not only related with wind direction, and it is related with wind speed size, MPP can not be accurately positioned, because This this method still has dispute in industry.
With the development of measuring technique, have scholar propose PID and the fuzzy control Yaw control method combined and Logic control method, these methods are using the active yawing control measured based on wind direction, this is also industrially generally to adopt at present Yaw control method.But because the measurement of wind direction is always mingled with interference noise and exceptional value, meanwhile, wind direction is not again Disconnected variation, it is different from the following wind direction.Therefore, this active yawing control based on wind direction feedback cannot significantly improve yaw system The control performance of system.
In recent years, there is scholar to propose by the wind speed and direction immediately ahead of laser radar detection impeller at 150m, and be based on this Propose the PREDICTIVE CONTROL of yaw system.This Yaw Control Strategy based on advanced measuring technique can be improved wind energy acquisition Amount, and reduce the downward load of certain extreme winds.But since this survey wind technical costs is high, at present still in test Stage.
Wind direction is also most important to wind power generating set acquisition maximum power, and the yaw control based on wind direction prediction is blower Axis and wind direction are consistent to provide possibility to obtain maximum power output.Bao et al. proposes a kind of based on round time The method average with Bayes is returned to carry out deviation correction to the obtained prediction data of Forecast Model For Weather.Ergin Erdem etc. People proposes the prediction technique of the combination of the wind speed and direction based on ARMA.Kalsuner et al. proposes a kind of based on " similar day " Method to predict wind vector.The prediction of wind speed and direction is crucial the acquisition rate of wind energy, and wind speed and direction It is two completely different attributes, nowadays for how to predict multiple wind attributes simultaneously and prediction is used for yaw system control Research it is seldom.
Herein on the basis of original wind speed and direction independent prediction method based on ARMA, propose new based on ARMA The wind speed and direction prediction technique of model.
Fig. 1 is the structural schematic diagram of the wind power generating set with active yawing adjuster.
Wind power generating set as shown in Figure 1 includes: motor module 101, pitch control module 102, aerodynamic system mould Block 103, frequency transformer control module 104, yaw control module 105 and pylon and transmission module.Wind in air passes through air Wind machine oar leaf rotation in dynamical system module 103 converts wind energy into the power generation that mechanical energy is come in driving motor module 101 Machine rotor rotation reapplies Frequency conversion control technology and passes through frequency control module 104 for the variable ratio frequency changer as caused by generator Rate, variable voltage are converted to the acceptable fixed frequency of power grid, fixed voltage.
It is hereby theoretical it is found that the power P that wind power generating set can be obtained and be exported from wind by the shellfish in aerodynamicsa Are as follows:
Ve=V0cos(θe)=V0cos(θw-θnp) (2)
Wherein, ρ indicates atmospheric density, ArIndicate the area of wind wheel sweeping, CpIndicate the power coefficient of wind energy conversion system, Ve It is expressed as effective wind speed, V0Indicate free stream wind speed, θeIndicate yaw error, θwAnd θnpRespectively indicate wind direction and wind energy conversion system cabin To Beijiao degree.
According to expression formula (1) and expression formula (2) it is found that the power P of wind energy conversion system captureaWith wind speed virtual value Ve3 powers at Direct ratio, this shows yaw error θeThe power P of bigger wind energy conversion system captureaWith regard to smaller.
Active yawing system is exactly initiatively to be aligned the axis of cabin with wind direction, i.e., according to the wind vane inspection being calculated Wind wheel is adjusted to upwind position by yaw device for regulating direction by the Mathematics models in a period of time measured.When wind energy conversion system cabin position It sets and changes, then the angle that absolute value encoder currently adjusts record starts yaw brake, passes through this series of master Dynamic yaw adjustment movement captures maximal wind-energy for wind power generating set and provides possibility.
It therefore, is the efficiency for improving wind-driven generator, yaw system always requires vertical by rotation according to shortest path Cabin on pylon is directed at wind direction, therefore the relationship between the shortest path and yaw angle of yaw adjustment is as follows:
(1) in the case where the differential seat angle of wind energy conversion system nacelle position and wind direction is less than 180 °, the calculation formula of yaw angle are as follows:
θe=θw-θnp (3)
Yaw system driving motor rotates forward so that wind energy conversion system cabin tuning clockwise, schematic diagram are as shown in Figure 2 at this time；
(2) in the case where the differential seat angle of wind energy conversion system nacelle position and wind direction is greater than 180 °, the calculation formula of yaw angle are as follows:
θe=360 °-| θw-θnp| (4)
Yaw system driving motor reversion at this time is so that wind energy conversion system cabin tuning counterclockwise, schematic diagram are as shown in Figure 3.
Currently, the main integrated distribution of yaw error under the active yawing control strategy fed back based on wind direction [- 15 °, 15°].When wind vector exceeds setting range, yaw system can be then adjusted nacelle position.Below with a certain 1.5MW The yaw logic control algorithm industrially generallyd use is introduced for CMYWP blower, realizes that flow diagram is as shown in Figure 4.
According to Fig. 4 as can be seen that traditional active yawing logic control algorithm first can be to original in implementation process Wind direction measurement data is filtered, and the yaw error in setting time can be then calculated according to filtered wind direction data Average value.
Specifically, which can calculate the yaw error average value in setting time according to following expression:
Wherein,Indicate yaw error average value in 10s,Indicate the yaw error average value in 30s,It indicates Yaw error average value in 60s.
Then, which will judge whether the yaw error average value being calculated exceeds preset corresponding model It encloses.Wherein, if without departing from preset range, yaw system will not be acted.And it is preset if had exceeded Range, then the algorithm can further judge yaw error average value beyond presetting whether the time of range is more than to set Fixed delay duration.Wherein, if yaw error average value is not above the delay of setting beyond the time for presetting range Duration, then same yaw system will not act.
And if yaw error average value exceed preset range time be more than setting delay duration, this When the algorithm will calculate yaw system operation duration tyaw.Specifically, which can calculate yaw according to following expression System operation duration tyaw:
tyaw=θe/vyaw (6)
Wherein, vyawIndicate the speed of service (i.e. the velocity of rotation of yaw system) of yaw system.
Obtaining yaw system operation duration tyawAfterwards, which also can be according to yaw system operation duration tyawTo control Yaw system processed is acted.
However, wind is movement of the air relative to earth surface, its formation by geographical location, meteorological condition etc. it is a variety of because The influence of element, it has apparent diurnal periodicity and effect annual period.In addition, wind speed and direction is there is also certain relationship, Fig. 5~ Fig. 7 shows the distribution relation figure between the wind speed and direction of certain southern wind power plant.
Can be seen that from Fig. 5~Fig. 7 it is more frequent in low wind speed area wind vector, and as the raising wind direction of wind speed also becomes In stabilization.In addition, the wind speed and direction in each place has apparent provincial characteristics, table 1 shows the region wind speed and direction Feature.
Table 1
From Fig. 5~Fig. 7 and table 1 as can be seen that wind speed occupies mainly in 9-15m/s within this period 90.48%.To north wind to 280-330 °, mainly northwest is concentrated mainly on, the 83.71% of total amount is occupied.Mean wind speed is 10.18m/s, the standard deviation of wind speed are 4.02.
The actual running results under traditional Yaw Control Strategy are analyzed using data above, as a result such as Fig. 8 Shown in~Figure 10.Can be seen that under traditional yaw policy control according to Fig. 8~Figure 10, the yaw error mean value of blower and Standard deviation can be gradually reduced with the increase of wind speed.It is being lower than the yaw since wind speed is smaller in this section of wind speed region 2.5m/s System is inactive, therefore the yaw error in the region is larger；In rated value low wind speed area below, wherein this section of 2.5-4m/s Yaw error average value is larger, then gradually stable；High wind speed area more than rated value, yaw error average value are more steady It is fixed.
By analysis, inventors have found that there is following problems for traditional yaw control algolithm:
(1) set yaw is low to wind precision.Existing control strategy is based on the control of wind direction feedback, and place one's entire reliance upon wind direction The accuracy of measurement.However, the accuracy of wind direction is in addition to related with the measurement accuracy of itself wind vane sensor, also and wind vane Installation site have close connection.This is because wake flow can be generated by being located at the wind wheel rotation of wind upwind power generator group Turbulent flow so that the wind vane for being located at lower wind direction do not stop it is dynamic, so that reducing the accuracy of wind direction measurement and surveying wind devices makes With the service life, so that yaw control system cannot get ideal wind direction input signal, and then cause unit lower to wind precision.
(2) yaw control lag.Yaw error used in existing Yaw Control Strategy is in a period of time calculated Average value, and the average value reaction be history yaw state.
(3) entire wind speed region uses same control strategy, and simple dependence wind direction data is without considering wind speed.And root According to research above, wind speed and direction is in the presence of centainly contacting.The yaw strategy of live major part Wind turbines does not differentiate between wind Speed, so that the tolerance at yaw error angle and delay time are fixed value.
(4) yaw system is adaptive horizontal very low.In practical wind field, the shadow of the geographical location of wind energy conversion system to yaw system Sound is also very big, such as the influence between landform, different seats in the plane.And the unit of the even different wind power plants in different seats in the plane is adopted at present With same control strategy, the performance difference between the difference and unit of wind power plant wind regime is had ignored.
(5) it can be seen that for existing Yaw Control Strategy from Fig. 8~Figure 10, although inclined in high wind speed region Error of navigating is more stable, but the average value of yaw error still has exceeded 8 ° of setting.
It follows that existing Yaw Control Strategy effect is not fully up to expectations, it is therefore necessary to yaw control system into Row optimization.
Present invention firstly provides a kind of wind speed, wind direction prediction technique, this method, which can be realized, carries out wind speed and direction Independent prediction in short-term.The realization principle and implementation process predicted due to this method to wind speed and direction are identical, therefore herein Only it is illustrated for predicting wind speed.
Figure 11 shows the implementation process schematic diagram predicted in the present embodiment wind speed.
Figure 11 shows the implementation process schematic diagram for carrying out independent prediction in the present embodiment to wind speed.
As shown in figure 11, in the present embodiment, this method can obtain historical wind speed data in step S1101 first.It needs , it is noted that this method historical wind speed data accessed in step S1101 referred to is preferably that specific length (should Length can be configured to different reasonable values according to actual needs) period in included multiple moment (including current time) Wind speed average value (such as wind speed average value in 10s, 30s or 60s) in corresponding preset duration.Wherein, current time Wind speed average value characterization in corresponding 10s be current time before wind speed in 10s average value.
Certainly, in different embodiments of the invention, above-mentioned preset duration can be configured to different according to actual needs Reasonable value (such as reasonable value in 5s to 240s etc.), the present invention are not defined the specific value of above-mentioned preset duration.
Due to this method be forecasting wind speed is carried out based on arma modeling, and arma modeling require data be smoothly, Therefore the stationarity in order to guarantee data, after obtaining historical wind speed data, this method can be in step S1102 to historical wind speed Data carry out trending and handle, to obtain trending air speed data.
Specifically, in the present embodiment, this method is in step S1102 advantageously according to following expression to the historical juncture Air speed data carries out trending and handles:
Wherein,Indicate the air speed data of t moment gone after trending,Indicate the air speed data value of t moment, It indicates historical wind speed Trend value (i.e. average value).
In the present embodiment, historical wind speed data average valueRefer preferably to the average value of all air speed datas before current time Or the average value of the air speed data before current time in specific duration.
After completing once to go trending treatment process, this method can also be in step S1102 to removing trending wind speed number According to progress stationarity detection.Wherein, if removing trending air speed data is not smoothly that party's rule can be again to this It goes trending air speed data to carry out difference and re-starts stationarity detection, until the obtained trending air speed data that goes is steady 's.
Since there are uneven stabilities for wind velocity signal, in order to which the method for application time sequence predicts it, it is necessary to will Wind velocity signal becomes stable random signal.In the present embodiment, this method preferably take the orderly difference operator of reference (i.e. ▽= Method 1-B), to former nonstationary time series { ytImplement the orderly differential transformation of single order.That is, in the presence of:
▽yt=(1-B) yt=yt-yt-1 (8)
Wherein, ▽ ytIndicate the difference of the data at t moment (i.e. current time) and t-1 moment (i.e. previous moment), B is indicated ytAnd yt-1Proportionality coefficient, ytAnd yt-1Respectively indicate the data of t moment (i.e. current time) and t-1 moment (i.e. previous moment).
It is available after d order difference:
▽dyt=(1-B)dyt (9)
Wherein, ▽dytIndicate d order difference operator.
The stationary sequence obtained after difference can be described with AR, MA, arma modeling, then former time series may be expressed as:
Wherein,Indicate that lag operator multinomial, θ (B) indicate prediction error lag operator multinomial, atIndicate prediction Error.
Here it is one moving average model ARIMA (p, d, q) of accumulating autoregression.
Make data sequence held stationary if necessary, then also just needing to require equation φ (B)=0 and θ (B)=0 Root be respectively positioned on outside unit circle, i.e. the modulus value of root is all larger than 1.Wherein,
Wherein, if the modulus value of above-mentioned equation root is all larger than 1, wind series are stable.And if steadily may be used The test fails for inverse property, can appropriate adjustment difference order be modified, until wind series adjusted are stable.
Certainly, in other embodiments of the invention, this method can also detect trend using other rational methods Change the stationarity of air speed data, the invention is not limited thereto.
In the present embodiment, handled by carrying out trending to historical wind speed data, this method can also determine ARMA Difference order d in model.
After completing that trending is gone to handle, this method can go in step S1103 according to obtained in step S1102 The auto-correlation function (autocorrelative function, ACF) and partial autocorrelation function (partial of gesture air speed data Autocorrelative function, PACF) determine hangover truncation mode.
Specifically, in the present embodiment, above-mentioned auto-correlation function and partial autocorrelation function can be respectively indicated are as follows:
Wherein, ρkIndicate the auto-correlation coefficient for asking lag number to be k,WithRespectively indicate the i moment goes trend The data moment of data and i+k moment afterwards gone after trend, φkkIndicate the partial correlation coefficient that lag number is k, φk-1,jIt indicates J-th of regression coefficient in k-1 rank autoregressive process.
Specifically, in the present embodiment, the auto-correlation function that this method judges trending air speed data is reaching specific Whether be able to maintain after rank is zero.Wherein, if it is possible to, party's rule can be determined that the auto-correlation letter of trending air speed data Number has truncation, otherwise then can be determined that the auto-correlation function of trending air speed data has hangover property.
Similarly, this method can also judge that the partial autocorrelation function of trending air speed data is after reaching specific rank No be able to maintain is zero.Wherein, if it is possible to, party's rule can be determined that the partial autocorrelation function tool of trending air speed data There is truncation, otherwise then can be determined that the partial autocorrelation function of trending air speed data has hangover property.
By judge auto-correlation function and the deviation―related function of trending air speed data as hangover type or truncation type, this Method provided by embodiment is also assured that away the hangover truncation mode of trending air speed data.
Figure 12 and Figure 13 respectively illustrates the auto-correlation function and partial correlation letter of wind series 10s average value in the present embodiment Number schematic diagram.It can be seen that the auto-correlation function for removing trending air speed data and deviation―related function all from Figure 12 and Figure 13 It is hangover type.
It again as shown in figure 11,, should after determining away the hangover truncation mode of trending air speed data in the present embodiment Method can carry out arma modeling to determine rank, so that it is determined that providing in step S1104 based on the hangover truncation mode determined Automatic order, Sliding Mean Number order and difference order.Wherein, the difference order be in step S1102 differential process institute really The number for the difference made.If air speed data is more steady, also there is no need to carry out difference during removing trending Processing, (i.e. difference order d) is also equal to zero to the number of such difference.
After determining the automatic returning order in arma modeling, Sliding Mean Number order and difference order, the present embodiment In, this method can be based on arma modeling in step S1105, the automatic returning order determined in Lai Liyong step S1104, Sliding Mean Number order and difference order are according to going trending air speed data to carry out one-step prediction in advance to air speed data, to count Calculation obtains the air speed data of subsequent time.
Specifically, in the present embodiment, this method determines the air speed data of subsequent time advantageously according to following expression:
Wherein, yt+1Indicate the data of t+1 moment (i.e. subsequent time), ytIndicate the data at t moment (i.e. current time), yt-iIndicating the data at t-i moment, δ indicates constant term,Indicate i-th of autoregressive coefficient, φjIndicate j-th of sliding average system Number, p indicate that the order of automatic returning, q indicate the order of Sliding Mean Number, etIndicate the error term at t moment (i.e. current time) (difference i.e. between the predicted value and observation of t moment).
For air speed data, that is, exist:
Wherein,Indicate the air speed data of t+1 moment (i.e. subsequent time).
So far the air speed data of subsequent time has also just been predicted according to historical wind speed data.
Based on same principle and process, wind speed and direction prediction technique provided by the present invention equally can be according to history wind The wind direction data of subsequent time is predicted to data.
The present invention has also passed through a kind of wind speed and direction prediction technique, and this method is in utilization arma modeling according to historical wind speed number In the case where according to the air speed data for determining subsequent time, the wind direction of subsequent time can be predicted in the way of wind direction circular transform Data.
Figure 14 shows the implementation process schematic diagram of wind speed and direction prediction technique provided by the present embodiment.
As shown in figure 14, in the present embodiment, this method can obtain historical wind speed data and wind direction number in step S1401 According to.It should be pointed out that this method historical wind speed data accessed in step S1101 referred to it is preferably multiple (such as wind speed in 10s, 30s or 60s is average for wind speed average value in preset duration corresponding to moment (including current time) Value).Wherein, the wind speed average value characterization in 10s corresponding to current time be current time before wind speed in 10s it is flat Mean value.
Certainly, in different embodiments of the invention, above-mentioned preset duration can be configured to different according to actual needs Reasonable value (such as reasonable value in 5s to 240s etc.), the present invention are not defined the specific value of above-mentioned preset duration.
In step S1402, this method can predict subsequent time according to historical wind speed data using arma modeling Air speed data.In the present embodiment, this method predicts subsequent time according to historical wind speed data using arma modeling The concrete principle and process of air speed data are similar with the content that above-mentioned steps S1102 is illustrated to step S1105, therefore herein not The contents of the section is repeated again.
Wind direction is a round variable, therefore method provided by the present embodiment uses the prediction more suitable for round variable Method predicts the wind direction data of subsequent time.Specifically, in the present embodiment, this method can be right in step S1403 History wind direction data carries out round change of variable, to obtain the sine value and cosine value of history wind direction data.
Specifically, this method converts history wind direction data advantageously according to following expression:
Wherein,WithThe sine value and cosine value of the wind direction data of t moment are respectively indicated,Indicate t moment Wind direction data.
Based on expression formula (17), the wind direction number at each moment before this method available current time and current time According to sine value and cosine value.
After determining the sine value and cosine value of wind direction data at current time (i.e. t moment), this method can be in step The wind direction at subsequent time (i.e. t+1 moment) is determined in S1404 according to the sine value of the wind direction data at current time and cosine value The sine value of dataAnd cosine value
Specifically, in the present embodiment, this method preferably respectively utilize arma modeling according to history wind direction data just String value and cosine value determine the sine value of the wind direction data of subsequent timeAnd cosine valueIts concrete principle with And process is identical as the content that above-mentioned Figure 11 is illustrated, therefore no longer the contents of the section is repeated herein.
As shown in figure 14, in the present embodiment, in the sine value for the wind direction data for obtaining subsequent timeAnd cosine valueAfterwards, this method can be in step S1405 according to the sine value of the wind direction data at a momentAnd cosine valueDetermine the wind direction data of subsequent time
Specifically, in the present embodiment, this method determines the wind direction data of subsequent time advantageously according to following expression
Wherein,Indicate the wind direction data of t+1 moment (i.e. subsequent time),WithRespectively indicate t+1 The sine value and cosine value of the wind direction data at moment.
It should be pointed out that in other embodiments of the invention, this method can also be using other rational methods come root It is predicted that subsequent time wind direction data sine valueAnd cosine valueDetermine the wind direction data of subsequent time
It should be pointed out that in other embodiments of the invention, it can be according to practical need for the prediction of air speed data It is configured, i.e., obtain air speed data in case of need and air speed data is predicted, in unwanted situation Air speed data is not obtained while air speed data is not predicted, the invention is not limited thereto.In addition, in other implementations of the invention In example, according to actual needs, this method can also predict using other rational methods air speed data that the present invention is same It is without being limited thereto.
The present invention provides a kind of new wind speed and direction prediction technique, wind speed and direction is considered as a vector by this method, And give wind vector come to subsequent time air speed data and wind direction data predict.
Figure 15 shows the implementation process schematic diagram of wind speed and direction prediction technique provided by the present embodiment.
As shown in figure 15, in the present embodiment, which can obtain region to be analyzed in step S1501 Historical wind speed data and history wind direction data.It should be pointed out that the history wind that this method is accessed in step S1101 What fast data were referred to is preferably the wind speed average value (example in preset duration corresponding to multiple moment (including current time) Such as the wind speed average value in 10s, 30s or 60s).Wherein, the wind speed average value characterization in 10s corresponding to current time is The average value of wind speed before current time in 10s.
Certainly, in different embodiments of the invention, above-mentioned preset duration can be configured to different according to actual needs Reasonable value (such as reasonable value in 5s to 240s etc.), the present invention are not defined the specific value of above-mentioned preset duration.
After obtaining historical wind speed data and wind direction data, this method can be in step S1502 according to historical wind speed data Wind vector is decomposed with history wind direction data, to obtain history wind vector abscissa and wind vector ordinate.
Specifically, in the present embodiment, this method decomposes wind vector advantageously according to following expression:
Wherein,WithThe wind vector abscissa data and wind vector ordinate data of t moment are respectively indicated, Indicate air speed data,Indicate the wind direction data of t moment.
Based on expression formula (19), the wind vector at each moment before this method available current time and current time Abscissa data and wind vector ordinate data.
Certainly, in other embodiments of the invention, this method can also using other rational methods come to wind vector into Row decomposes, and the invention is not limited thereto.
After obtaining history wind vector abscissa and wind vector ordinate, this method can utilize ARMA in step S1503 Model determines the wind vector abscissa of subsequent time according to history wind vector abscissa and history wind vector ordinate With wind vector ordinate
In the present embodiment, this method determines the wind vector abscissa of subsequent time using arma modelingAnd wind arrow Measure ordinateConcrete principle and process it is similar with content shown in above-mentioned Figure 11, the method shown in Figure 11 On the basis of historical wind speed data replaced with into history wind vector abscissa and history wind vector ordinate, can determine down respectively The wind vector abscissa at one momentWith wind vector ordinateNo longer the process is repeated herein.
As shown in figure 15, in the present embodiment, this method can be in step S1504 according under obtained in step S1503 The wind vector abscissa at one momentWith wind vector ordinateDetermine the air speed data and wind direction number of subsequent time According to.
Specifically, in the present embodiment, this method determines the air speed data of subsequent time advantageously according to following expression
The wind direction data of subsequent time is determined according to following expression:
Wherein,Indicate the wind direction data of t+1 moment (i.e. subsequent time).
It should be pointed out that in other embodiments of the invention, this method can also be using other rational methods come root According to the wind vector abscissa of subsequent timeWith wind vector ordinateDetermine subsequent time air speed data and Wind direction data, the invention is not limited thereto.
In order to verify the validity and advantage of wind speed and direction prediction technique provided by the present invention, the present embodiment uses south 24 that the SCADA (Supervisory Control and Data Acquisition System) of certain wind field of side is recorded are small When in wind speed and direction data, totally 86400 points.Wherein, mean wind direction such as Figure 16 under original wind direction and different duration Shown, the mean wind speed under original wind speed and different durations is as shown in figure 17, and Figure 18 and Figure 19 respectively illustrate different predictions The obtained 10s wind direction prediction result of method and forecasting wind speed are as a result, Figure 20 and Figure 21 respectively illustrate different prediction technique institutes Obtained 30s wind direction prediction result and forecasting wind speed as a result, Figure 22 and Figure 23 to respectively illustrate different prediction techniques obtained 60s wind direction prediction result and forecasting wind speed result.
According to Figure 16 and Figure 17 it is found that since the fluctuation of wind speed initial data and wind direction initial data is bigger, meter The average value for calculating 10s, 30s and 60s is conducive to filter and reduce the influence of exceptional value.In addition, in wind vane in measurement wind direction When more than 360 °, numerical value will be since 0.This result in wind direction shown in Figure 16 fluctuated in this section of event of 20-22H it is bigger, Precision is not high (the especially circled of Figure 18, Figure 20 and Figure 22) when practical arma modeling individually determines the wind direction in advance, and uses round Quantity method is predicted wind direction the continuity that can more embody wind direction, will not the above-mentioned circled of outlet mutation, to make It is higher to obtain wind direction precision of prediction.And for forecasting wind speed, it can be seen that from Figure 19, Figure 21 and Figure 23 using individually prediction The obtained result of method is more more stable than initial data.
It, can be using absolute in the present embodiment for the accuracy for assessing proposed short-time wind speed and wind direction prediction technique Three average error (MAE), average absolute percentage error (MAPE) and mean square deviation (MSE) expression formulas are tied to compare its prediction Fruit, statistical result are as shown in table 2.Wherein, absolute error average value (MAE), average absolute percentage error (MAPE) He Junfang The calculation expression of poor (MSE) is respectively as follows:
Wherein, N indicates data amount check, xiIndicate actual value,Indicate predicted value.
Table 2
In conjunction with Figure 16~Figure 23 and table 2 it is found that being used alone obtained by ARMA prediction model for wind direction prediction Wind direction prediction result precision lower than wind vector method and round quantity method
It can be seen that from foregoing description kind compared to existing wind speed and direction prediction technique, method provided by the present invention It enables to wind direction prediction result more accurate and stablizes, also just provide number in this way for the yaw control of wind power generating set According to foundation.
Figure 24 shows the implementation process schematic diagram of the Yaw control method of wind power generating set provided by the present embodiment.
As shown in figure 24, in the present embodiment, which first can be in step S2401 according to the wind got Speed and wind direction calculate separately wind speed average value and Mathematics models in preset duration, to obtain historical wind speed data and wind direction Data.
In the present embodiment, above-mentioned preset duration is preferably 10s, 30s and/or 60s.Certainly, real in difference of the invention It applies in example, above-mentioned preset duration can be configured to different reasonable values (such as the reasonable value in 5s to 240s according to actual needs Deng), the present invention is not defined the specific value of above-mentioned preset duration.
After obtaining historical wind speed data and wind direction data, this method can be in step S2402 kind according to historical wind speed data With the air speed data and wind direction data of wind direction data prediction subsequent time.In the present embodiment, this method is preferably become using round Amount method predicts the air speed data and wind direction data of subsequent time, wherein based on round quantity method carries out air speed data and wind direction The concrete principle and process of data prediction have elaborated in the above content, therefore no longer carry out herein to the contents of the section It repeats.
Certainly, in other embodiments of the invention, according to the actual situation, this method can also use other rational methods According to historical wind speed data and wind direction data the air speed data and wind direction data of subsequent time are predicted, the present invention is unlimited In this.Such as it is a in one embodiment of the invention, this method can also be using as shown in figure 11 respectively to air speed data The mode predicted with wind direction data obtains the air speed data and wind direction data of subsequent time, or using as shown in figure 15 The air speed data and wind direction data that subsequent time is obtained based on the prediction mode of wind vector method.
As shown in figure 24, in the present embodiment, after the air speed data and wind direction data for determining subsequent time, this method meeting Control parameter is determined according to the air speed data for the subsequent time predicted in step S2403, then again in step According to the wind direction for the subsequent time determined in the control parameter and step S2402 determined in step S2403 in S2404 Book to wind-force luminous point unit carries out yaw control.
In the present embodiment, this method determines the air speed data for the subsequent time that prediction obtains preferably in step S2403 Affiliated wind speed interval, and control parameter is determined according to its affiliated wind speed interval.
Specifically, as shown in figure 25, in the present embodiment, this method is by the controllable wind speed region of wind power generating set to cut Enter wind speed vcut_in, rated wind speed vnWith cut-out wind speed vcut_out4 sections are divided into for boundary.
Preferably, if the wind speed v obtained by related sensor measurementw< vcut_in(such as vw< 2.5m/s), this Mean that wind speed vw(air speed data for the subsequent time predicted) is in incision wind speed vcut_inFollowing region.Due to this Wind energy contained by region is smaller, therefore this method preferably controls wind power generating set at this time and is in shutdown shape in the wind speed region State.
Preferably, if wind speed vw> vcut_out(such as vw> 25m/s), this means that wind speed vw(i.e. prediction obtains down The air speed data at one moment) it is in cut-out wind speed vcut_outArea above.Since the region wind speed is larger, excessively high wind speed for Wind power generating set load generates large effect to influence safety, reliability and the unit longevity of wind power generating set Life, therefore in the present embodiment, this method preferably controls wind power generating set and yaws to lower wind direction position simultaneously in the wind speed region In shutdown status.
Preferably, if wind speed vwMore than or equal to default incision wind speed and less than the first default wind speed threshold value, that is, exist vcut_in≤vw< v1, then it is that original control parameters are constant that this method, which will keep control parameter,.And if wind speed vwBe greater than or Equal to the first default wind speed threshold value and it is less than default cut-out wind speed, that is, there is v1≤vw< vcut_out, then party's rule can will be former Beginning control parameter reduces particular value to obtain required control parameter.It should be pointed out that in different embodiments of the invention In, above-mentioned first default wind speed threshold value can be configured to different reasonable values according to practical wind energy situation, and the invention is not limited thereto. It is also desirable to, it is noted that in other embodiments of the invention, work as vcut_in≤vw< v1Or v1≤vw< vcut_outWhen, it should Method can also configure control parameter using other rational methods, and the present invention is similarly not so limited to.
For example, if the first default wind speed threshold value is configured to 4m/s, due to wind speed interval [2.5m/s, 4m/s) wind energy account for It is larger to wind error average and standard deviation according to the 9.64% of wind energy total amount, and the region wind direction is more unstable.Together When, since accessed energy is smaller from wind for wind power generating set in the wind speed interval, in the present embodiment, this method It preferably can be by delay time TsetAnd/or yaw starting error angle vsetEtc. control parameters keep original control parameters (i.e. root According to control parameter set in existing Yaw control method) it is constant.
And for wind speed interval [4m/s, 25m/s), in the present embodiment, this method can preferably subtract original control parameters Small particular value, to obtain the new control parameter suitable for the wind speed interval.Partially empty control method also can according to really The new control parameter made controls wind-driven generator unit.
It include several wind speed intervals between the first default wind speed threshold value and default rated wind speed, wherein right in the present embodiment For these wind speed intervals, wind speed is bigger, and control parameter corresponding to wind speed interval is then smaller.
For example, if 4m/s≤vw< 9m/s, since the wind energy that the wind speed interval is contained occupies wind energy total amount 13.61% and be in rated wind speed low wind speed section below, thus under tradition yaw control to wind error average value and mark Quasi- difference is smaller, traditional yawer effect it is lower can compared with [2.5m/s, 4m/s) wind speed interval is promoted, but yaw control performance There is still a need for raisings.Therefore, method provided by the present embodiment also will be by delay time TsetAnd/or yaw starting error angle vsetEtc. control parameters original control parameters value reduce particular value so that yaw control performance can satisfy the wind speed area Between requirement.
If 9m/s≤vw< 12m/s, since the wind energy that the wind speed interval is contained occupies the 33.07% of wind energy total amount And be in rated wind speed middle high wind speed section below, tradition yaw control under to wind error average and standard deviation can relatively on The continuation of one wind speed interval is smaller, but there is still a need for raisings for yaw control performance.Therefore, in the present embodiment, when this method can be by being delayed Between TsetAnd/or yaw starting error angle vsetEtc. the original control parameters values of control parameters continue to reduce so that yaw Control performance can satisfy the requirement of the wind speed interval.
In the present embodiment, if wind speed vwMore than or equal to default incision wind speed and it is less than rated wind speed, then this method Then preferably by adjusting the tip speed ratio of wind energy conversion system, to realize that tracking and the maximal wind-energy of best power curve are captured as mesh Mark.At this point, propeller pitch angle is preferably set to 0 °.Certainly, in other embodiments of the invention, propeller pitch angle can also be according to reality It needs to configure as other reasonable values, the invention is not limited thereto.
In the present embodiment, if air speed data is greater than or equal to default rated wind speed and is less than default cut-out wind speed, Party's rule can carry out yaw control so that the wind-power electricity generation to wind power generating set according to the wind direction data of subsequent time The yaw error of unit is in default error range.Specifically, it in the present embodiment, is preset if air speed data is greater than or equal to Rated wind speed and it is less than default cut-out wind speed, this method, which will adjust propeller pitch angle and change wind energy, obtains coefficient, stable to obtain Output power is to protect unit equipment.
For example, if if 12m/s≤vw< 25m/s, the wind energy which is contained will occupy wind energy total amount 40.32%, and the wind direction of the wind speed interval will stablize enhancing.Since the above wind power generating set of rated wind speed needs to protect Rated output power is held, although the yaw error of the wind speed interval does not play generated energy influence, yaw error is excessive will shadow The complete machine load for ringing wind power generating set causes the amplitude of variation of average induced velocity excessive, therefore in the present embodiment, this method It can configure yaw starting error angle to [- 8 °, -8 °], also can in this way by the yaw control for wind power generating set Being maintained at the yaw error of wind power generating set at [- 8 °, -8 °].
It can be seen that for each wind speed interval included in incision wind speed to excision wind speed, the present embodiment is provided Method control parameter corresponding to each wind speed interval is preferably individually set, specifically be arranged result can be such as 3 institute of table Show.
Table 3
For the Yaw control method of the wind power generating set provided by the present embodiment, arrived used in yaw control Air speed data (such as 10s, 30s and/or 60s wind speed average value) and wind direction data (such as 10s, 30s and/or 60s wind direction are flat Mean value) it one-step prediction can be shifted to an earlier date obtains, then by that will predict obtained air speed data and wind direction data and corresponding threshold value Judged to control the operation of yaw system.
In order to verify the validity of the zone control tactics based on wind speed and direction prediction, the present embodiment is used such as Figure 16 extremely Air speed data and wind direction data shown in Figure 23 use Traditional control strategy and the present invention respectively under Matlab/Simulink environment The zone control tactics based on wind speed and direction prediction proposed are controlled, and are analyzed experimental result.In addition, being The effect of partitioning strategies is clearly stated, the present embodiment is analyzed from five in terms of, is yaw error average value respectively, inclined Navigate error mean square root, yaw time, yaw number and power loss coefficient.
Wherein, yaw error average value is calculated using following expression:
Yaw error root mean square is calculated using following expression:
The yaw time is calculated using following expression:
Yaw number is calculated using following expression:
Following formula is commonly used in practical engineering experience calculates power loss coefficient
Wherein, θyeIt indicates, N indicates the number of yaw error, tyawIndicate the yaw time,It indicates, CyawIndicate yaw Number, ξ indicate power loss coefficient, PredIndicate reduced power, PrealIndicate the power ideally exported, Indicate equivalent yaw error.
Equivalent yaw errorIt can be calculated according to following expression:
Wherein,It is the average error in jth section yaw error region, characterizes the probability in the yaw error region.
Figure 26 shows the nacelle position under Traditional control strategy and zone control tactics provided by the present invention.It will figure 26 result is counted respectively according to wind speed subregion, obtains yaw error distribution map shown in Figure 27 to Figure 30.
Table 4 shows the statistical data under different Yaw control methods.
Table 4
Complex chart 26 is to the statistical result of Figure 30 and table 4 it is found that low wind speed interval (such as [2.5m/s, 4m/s)), by Yaw Control Strategy used by the Yaw control method provided by the present embodiment is consistent with conventional measures, therefore yaw error It is distributed constant.
The low wind speed interval (such as [4m/s, 9m/s) in rated wind speed is below), yaw control provided by the present embodiment The obtained yaw error of method processed is reduced compared with conventional method, while also higher to wind precision, yaw error [- 8 ° ,- 8 °] section by 75.20% is increased to 76.04%.
Below rated wind speed middle high wind speed area (such as [9m/s, 12m/s)), controlling party is yawed provided by the present embodiment The obtained yaw error of method is substantially reduced compared with conventional method, and yaw error is increased in [- 8 °, -8 °] section by 81.75% 82.62%.
The above high wind speed area of rated wind speed (such as [12m/s, 25m/s)), controlling party is yawed provided by the present embodiment The obtained yaw error of method is substantially reduced compared with conventional method, and yaw error is increased in [- 8 °, -8 °] section by 83.83% 84.79%, error distribution and yaw error distribution are more concentrated.
Compared to traditional Yaw control method, the yaw number of Yaw control method provided by the present invention is relative to tradition Control strategy increases, but the number improved is concentrated mainly on middle high wind speed area, therefore power loss coefficient is substantially reduced.
It follows that the forecast Control Algorithm of subregion provided by the present invention can effectively reduce the yaw in middle high wind speed area Error, to reduce power loss coefficient (improving the utilization rate of wind energy).
It should be understood that disclosed embodiment of this invention is not limited to specific structure disclosed herein or processing step Suddenly, the equivalent substitute for these features that those of ordinary skill in the related art are understood should be extended to.It should also be understood that It is that term as used herein is used only for the purpose of describing specific embodiments, and is not intended to limit.
" one embodiment " or " embodiment " mentioned in specification means the special characteristic described in conjunction with the embodiments, structure Or characteristic is included at least one embodiment of the present invention.Therefore, the phrase " reality that specification various places throughout occurs Apply example " or " embodiment " the same embodiment might not be referred both to.
Although above-mentioned example is used to illustrate principle of the present invention in one or more application, for the technology of this field For personnel, without departing from the principles and ideas of the present invention, hence it is evident that can in form, the details of usage and implementation It is upper that various modifications may be made and does not have to make the creative labor.Therefore, the present invention is defined by the appended claims.

Claims (15)

1. a kind of Yaw control method of wind power generating set, which is characterized in that the Yaw control method includes:
Step 1: wind speed average value and Mathematics models in preset duration are calculated separately according to the wind speed and direction got, Historical wind speed data and history wind direction data are obtained, subsequent time is predicted according to the historical wind speed data and history wind direction data Air speed data and wind direction data；
Step 2: determining control parameter according to the air speed data of the subsequent time, and utilize the control parameter and wind direction number Yaw control is carried out according to wind power generating set；
Wherein, in said step 1, the step of predicting the air speed data and wind direction data of subsequent time include:
Wind vector is decomposed according to the historical wind speed data and history wind direction data, obtains history wind vector abscissa number According to history wind vector ordinate data；
It is next to be determined according to the history wind vector abscissa data and history wind vector ordinate data using arma modeling The wind vector abscissa data and wind vector ordinate data at moment；
Determine the wind speed number of subsequent time respectively according to the wind vector abscissa data of subsequent time and wind vector ordinate data According to and wind direction data；
Or,
Round change of variable is carried out to the history wind direction data, obtains the sine value and cosine value of history wind direction data；
The sine of the wind direction data of subsequent time is determined according to the sine value and cosine value of history wind direction data using arma modeling Value and cosine value, and determine according to the sine value of the wind direction data of the subsequent time and cosine value the wind direction number of subsequent time According to.
2. the method as described in claim 1, which is characterized in that in said step 1, the preset duration be 10s, 30s or 60s。
3. the method as described in claim 1, which is characterized in that decomposed according to following expression to wind vector:
Wherein,WithThe wind vector abscissa data and wind vector ordinate data of t moment are respectively indicated,It indicates Air speed data,Indicate the wind direction data of t moment.
4. the method as described in claim 1, which is characterized in that determine the air speed data of subsequent time according to following expression:
Wherein,Indicate the air speed data at t+1 moment,WithRespectively indicate the wind vector at t+1 moment Abscissa data and wind vector ordinate data.
5. the method as described in claim 1, which is characterized in that determine the wind direction data of subsequent time according to following expression:
Wherein,Indicate the wind direction data at t+1 moment,WithThe wind vector for respectively indicating the t+1 moment is horizontal Coordinate data and wind vector ordinate data.
6. the method as described in claim 1, which is characterized in that justified according to following expression to the history wind direction data Deformation change of variable:
Wherein,WithThe sine value and cosine value of the wind direction data of t moment are respectively indicated,Indicate the wind of t moment To data.
7. the method as described in claim 1, which is characterized in that determine the wind direction number of the subsequent time according to following expression According to:
Wherein,Indicate the wind direction data at t+1 moment,WithRespectively indicate the wind direction data at t+1 moment Sine value and cosine value.
8. method as claimed in claim 6, which is characterized in that in said step 1, using arma modeling according to history wind Fast data determine the air speed data of subsequent time.
9. method according to claim 8, which is characterized in that the step of determining the air speed data of subsequent time include:
Step a, trending is carried out to the historical wind speed data to handle, obtain trending air speed data；
Step b, the auto-correlation function and partial autocorrelation function of trending air speed data are removed according to, determine hangover truncation mould Formula；
Step c, it is based on the hangover truncation mode, the arma modeling is carried out using pre-set criteria to determine rank, determines automatic return Return order, Sliding Mean Number order and difference order；
Step d, be based on the arma modeling, using the automatic returning order, Sliding Mean Number order and difference order according to The air speed data for going trending air speed data to calculate subsequent time.
10. such as method according to any one of claims 1 to 9, which is characterized in that in the step 2, determine it is described under The affiliated wind speed interval of the air speed data at one moment, and the control parameter is determined according to affiliated wind speed interval.
11. method as claimed in claim 10, which is characterized in that in the step 2, if the wind of the subsequent time Fast data are less than default incision wind speed, then control wind power generating set and be in shutdown status.
12. method as claimed in claim 10, which is characterized in that in the step 2, if the wind of the subsequent time It is greater than or equal to default cut-out wind speed to data, then controls wind generating set yaw to lower wind direction position and in shutdown shape State.
13. method as claimed in claim 10, which is characterized in that in the step 2,
If the air speed data of the subsequent time is greater than or equal to default incision wind speed and less than the first default wind speed threshold value, Keeping the control parameter is that original control parameters are constant；
And/or if the air speed data of the subsequent time is greater than or equal to the described first default wind speed threshold value and is less than default Original control parameters reduction particular value is then obtained required control parameter by cut-out wind speed.
14. method as claimed in claim 13, which is characterized in that in the step 2, the first default wind speed threshold value It include several wind speed intervals between the default rated wind speed, wherein for these wind speed intervals, wind speed is bigger, Control parameter corresponding to wind speed interval is then smaller.
15. method as claimed in claim 10, which is characterized in that in the step 2, if the wind of the subsequent time Fast data are greater than or equal to default rated wind speed and are less than default cut-out wind speed, then according to the wind direction data pair of the subsequent time The wind power generating set carries out yaw control so that the yaw error of the wind power generating set is in default error range.
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