CN108678902A - The straight disturbance sensing control method for driving PMSM wind generator systems MPPT - Google Patents
The straight disturbance sensing control method for driving PMSM wind generator systems MPPT Download PDFInfo
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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
- F03D7/0276—Controlling wind motors the wind motors having rotation axis substantially parallel to the air flow entering the rotor controlling rotor speed, e.g. variable speed
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- G—PHYSICS
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- G05F—SYSTEMS FOR REGULATING ELECTRIC OR MAGNETIC VARIABLES
- G05F1/00—Automatic systems in which deviations of an electric quantity from one or more predetermined values are detected at the output of the system and fed back to a device within the system to restore the detected quantity to its predetermined value or values, i.e. retroactive systems
- G05F1/66—Regulating electric power
- G05F1/67—Regulating electric power to the maximum power available from a generator, e.g. from solar cell
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- 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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Abstract
There are problems that parameter is difficult to adjust for traditional PI D, the problem that various modified PID are computationally intensive, Ability of Resisting Disturbance is poor, there is high frequency buffeting and Active Disturbance Rejection Control (ADRC) there are calculation amounts the problems such as too big, gain parameter is excessive in sliding formwork control (SMC), the present invention proposes " the straight disturbance sensing control method for driving PMSM wind generator systems MPPT ".The controller parameter of the present invention has prodigious nargin, not only has the characteristics that calculation amount is small, control accuracy is high, Ability of Resisting Disturbance is strong, but also has globally asymptotically stable characteristic.Especially need not also calm when acute variation occurs for external environment gain parameter online, overturn the control strategy of classical control theory and modern control theory completely.The present invention is to realizing that the straight control for driving PMSM wind generator systems MPPT has great theory significance and application value.
Description
Technical field
Wind generator system, motor operation and control.
Background technology
Green energy resource one of of the wind energy as today's society most economic value, has obtained the common concern of countries in the world
With greatly develop.It is how reliable and effectively utilize with the continuous increase of permanent magnet direct-drive wind power generation system installed capacity
Wind energy becomes the research hotspot of wind generating technology.Complete machine enlargement and control technology intelligence are current wind generator systems
Two developing directions.MPPT maximum power point tracking (maximum power point tracking, MPPT) is Wind turbines complete machine
Control the technology being most widely used.It is controlled at present about MPPT maximum power point tracking, domestic and foreign scholars successively propose best leaf
Tip-speed ratio method, power signal feedback transmitter, search by hill climbing method, optimum torque method scheduling algorithm and related innovatory algorithm, but these are calculated
There are different degrees of defects in engineer application for method.In Practical Project, most operating units are still using based on maximum power
The optimum torque method of curve applies unit using rotating speed according to group setup power curve (or discrete table is made) and controls
System, this control algolithm is simple in structure, stable, reliability is high, is more suited to current large-scale wind electricity unit.But actual set
Correlation curve is not easy accurately to obtain, while outside environmental elements variation easily largely changes actual operation curve, leads to unit
Output power is affected, and efficiency of generating unit reduces.For this purpose, the task of top priority is a kind of simple in structure, calm appearance of parameter of structure
Easily, the tracing control new method that dynamic quality is good, Ability of Resisting Disturbance is strong.This method determines wind with optimum tip-speed ratio and wind speed
The expectation angular speed of machine, or determine by PMSM actual motions power the expectation angular speed of wind turbine, by rotation speed of fan
Control obtain q axis instruction currentsAnd then by current control link come acquisition instruction voltageWithTo realize
MPPT is controlled.
Invention content
Under rated wind speed, the expectation rotating speed of wind turbine is determined according to optimum tip-speed ratio and wind speed first, or is passed through
The actual motion power (can calculate acquisition) of PMSM determines the expectation rotating speed of wind turbine, is obtained by the control to rotation speed of fan
Q axis instruction currentsAnd then by current control link come acquisition instruction voltageWithTo realize maximum power point with
Track controls.The outstanding advantage of " a kind of straight disturbance sensing control method for driving PMSM wind generator systems MPPT " of the present invention is main
Including：(1) there is global asymptotic stability；(2) it is calm to exempt from parameter；(3) simple in structure, calculation amount is small, real-time is good；(4) it rings
Answer speed it is fast, without buffet, the dynamic qualities such as Ability of Resisting Disturbance is strong.
Description of the drawings
Fig. 1 it is expected rotating-speed tracking differentiator (Tracking Differentiator, TDm)
Fig. 2 der Geschwindigkeitkreis disturbance observers DOm
Fig. 3 disturbs sensing controller (Disturbance Perception Controller, DPC), and (a) der Geschwindigkeitkreis is disturbed
Dynamic sensing controller (DPCm), (b) d axis stator current disturbance sensing controller (DPCd), (c) q axis stator current disturbance perception
Controller (DPCq)
Fig. 4 directly drives PMSM wind power generating sets MPPT disturbance sensing controllers (MPPT-DPC)
Fig. 5 directly drives PMSM wind power generating set MPPT control system schematic diagrams
When Fig. 6 7m/s wind speed, the straight PMSM wind power generating sets MPPT that drives controls simulation result, and the control of (a) rotating-speed tracking is bent
Line, (b) q axis stator current iqChange curve, (c) wind energy conversion system output torque TmWith generator electromagnetic torque TeChange curve, (d)
Power coefficient CpCurve
Fig. 7 is at the 2.5s moment, and when wind speed is down to 6m/s by 7m/s, PMSM wind power generating sets MPPT controls simulation result,
(a) rotating-speed tracking controlling curve, (b) q axis stator current iqChange curve, (c) wind energy conversion system output torque TmTurn with generator electromagnetism
Square TeChange curve, (d) power coefficient CpCurve
Fig. 8 directly drives PMSM wind power generating sets in specified random wind speed there are when the extreme case of wind speed mutation
The control simulation result of MPPT, the random wind speed curve of (a) wind speed mutation, (b) rotating-speed tracking controlling curve, (c) q axis stator electricity
Flow iqChange curve, (d) wind energy conversion system output torque and generator electromagnetic torque change curve, (e) power coefficient curve
Specific implementation mode
1. wind energy conversion system it is expected the acquisition methods of rotating speed
(1) wind energy conversion system output characteristics
Wind energy conversion system output mechanical energy be
Pm=0.5 ρ π R2Cpv3 (1)
Cp=0.5176 (116/ β -0.4 θ -5) exp (- 21/ β)+0.0068 λ (2)
In formula, PmIt is the power of wind energy conversion system；CpIt is power coefficient；λ is tip speed ratio；θ is propeller pitch angle；V is wind speed.
Defining tip speed ratio λ is
In formula, ωmFor wind mill rotor rotating speed (rad/s)；R is pneumatic equipment bladess radius.
By formula (2) it is found that CpIt is the nonlinear function about λ and θ, under rated wind speed, usually makes θ=0, therefore, CpOnly
It is related with λ.By calculating it is found that working as λ=λoptWhen=8.1, Cp=Cpmax=0.488.At this point, the maximum power that wind energy conversion system obtains
For：
Pmax=0.5 ρ π R2Cpmaxv3 (5)
It is defined it is found that in optimal tip speed ratio λ=λ by the tip speed ratio of formula (4)optWhen=8.1, the expectation of wind energy conversion system turns
Speed is：
Therefore, theoretically, wind energy conversion system maximum output machine torque TmFor
Or
(2) direct-driving type PMSM wind power systems MPPT is controlled
When wind generator system is run, need to control wind energy conversion system rotating speed, i.e., as electromagnetic torque Te, machine torque Tm
With viscous friction torque B ωmMeet condition：Tm-Te-BωmWhen=0, wind power system enters stable state.Ignoring viscous friction torque
BωmWhen, wind energy conversion system it is expected that rotating speed may be defined as
Wherein,(constant), and
Te=1.5pniq[id(Ld-Lq)+ψf] (10)
At synchronous rotating frame d-q, the mathematical model of PMSM is：
The physical significance of each parameter：ud、uqIt is the d-q axis components of stator voltage respectively；id、iqIt is stator current respectively
D-q axis components；Ld、LqIt is d-q axle inductances component (H) respectively；RsIt is stator resistance；ψfIt is rotor permanent magnet magnetic linkage (Wb)；ωmIt is
The mechanical angular speed (rad/s) of wind turbine, and the angular rate ω of motoreFor ωe=pnωm；pnIt is number of pole-pairs；TmIt is wind turbine torque
(Nm)；B is damped coefficient (Nms)；J is rotary inertia (kgm2)。
By formula (10) and formula (11) it is found that direct-driving type PMSM wind power generating sets are a typical non-linear strong couplings of MIMO
Close object.Wherein udAnd uqIt is the control input quantity of system, T respectivelymIt is external wind energy disturbance input；id、iqAnd ωmIt is respectively
The state output of system.For the ease of theory analysis, defining constant parameter is：b0=-1.5pnψf/ J and Correlative Perturbation component point
It is not：d1=(pnLqiqωm-Rsid)/Ld, d2=-(pnLdidωm+pnψfωm+Rsiq)/Lq, d3=[Tm-Bωm-1.5pnid
(Ld-Lq)]/J, system (11) then may be defined as perturbed system：
Wherein, | d1| ＜ ∞, | d2| ＜ ∞, | d3| ＜ ∞.
In view of the quantity of state of PMSM is there are measurement error, thus disturbance component d1、d2And d3There are uncertainties, therefore,
How effectively control, exactly core of the invention technology are applied to perturbed system (12), i.e. the disturbance of MPPT perceives control technology.
2. Nonlinear Tracking Differentiator (Tracking Differentiator, TD)
When wind speed occurs to change at random under rated wind speed, in order to realize the MPPT maximum power point tracking of wind energy, it is desirable that wind
The expectation rotating speed of machine is enable to respond quickly, in other words, it is desirable that the expectation rotating speed of wind turbine can follow the variation of wind speed and change.By
In the expectation rotating speed of wind turbine be the physical quantity of a time-varying, and to rotation speed of fan apply control when also need to obtain it is expected rotating speed
Differential information.In view of that can not know that wind turbine it is expected the concrete mathematical model of rotating speed, therefore, it is difficult to be obtained by conventional method
It must it is expected the differential information of rotating speed.For this purpose, the present invention it is expected that the tracking of rotating speed is believed using Nonlinear Tracking Differentiator technology to obtain wind turbine
Number and its differential signal, on the one hand can effectively solve the problems, such as wind turbine it is expected rotating speed differential information be difficult to obtain, another party
Face can also effectively solve control, and there are the contradictions between rapidity and overshoot in the process.The specific method is as follows：
(1) Nonlinear Tracking Differentiator technology
If wind turbine it is expected angular speed and isAnd v1And v2It is respectivelyTracking signal and differential signal, definition tracking miss
Difference isThen corresponding Nonlinear Tracking Differentiator (TDm) model is：
Wherein, zv＞ 0 is the gain coefficient of TDm, such as Fig. 1.
(2) Nonlinear Tracking Differentiator stability analysis
Theorem 1. assumes the expectation acceleration bounded of wind energy conversion system：Then and if only if zvWhen ＞ 0, it is expected that rotating speed with
Track differentiator (13) is globally asymptotically stable.
It proves：According to rotating-speed tracking errorAnd (13) are combined, it can obtain:Cause
This has
IfLars is taken to convert formula (14), i.e.,
：
It considers：V2(s)=sV1(s)、Therefore,It substitutes into
Formula (15), arranges：I.e.
Since system (16) is one in desired tach signalThe lower error dynamics system of excitation, according to signal and
System complex frequency domain analysis theories are it is found that work as zvWhen ＞ 0, error dynamics system (16) be it is globally asymptotically stable, therefore, as long asThen have：Accordingly, it is desirable to which rotating-speed tracking differentiator (13) is globally asymptotically stable.ByIt is found that as t → ∞, have：Such as Fig. 1.
3 der Geschwindigkeitkreis state of disturbance are estimated
(1) der Geschwindigkeitkreis state observer
Use z31And z32To estimate rotational speed omega respectivelymWith disturbance d3.If observation error is：ezm=z31-ωm, then accordingly
Disturbance observer DOm is：
Wherein, zo＞ 0, to realize z31≈ωm、z32≈d3, such as Fig. 2.
(2) der Geschwindigkeitkreis state observer stability analysis
Theorem 2. assumes der Geschwindigkeitkreis state of disturbance bounded：|d3| ＜ ∞, then when zo ＞ 0, disturbance observer
(17) it is globally asymptotically stable.
It proves：According to the 3rd formula of formula (17) and formula (12), can obtain state observation error system is：
IfIt takes Lars to convert and arrange formula (19), obtains
Disturbance observation error system shown in formula (20) is one in state of disturbance d3Excitation under observation error power
System, if state of disturbance bounded：|d3| ＜ ∞, then and if only if zoWhen ＞ 0, error system (20) is asymptotically stable in the large
, andThus disturbance observer (17) is globally asymptotically stable.
The disturbance sensing controller (Disturbance Perception Controller, MPPT-DPC) of 4.MPPT is set
Meter
For the straight control problem for driving PMSM Wind turbines, if outer shroud controls for rotating speed, inner ring is current control, and usually
Set the expectation electric current of inner ring d axis as zero, i.e.,
(1) der Geschwindigkeitkreis disturbance sensing controller (DPCm) designs
If it is ω directly to drive PMSM wind power system actual machine angular speedm, since wind turbine it is expected that angular speed is a time-varying object
Reason amount, therefore, the present invention is using TD to it is expected angular speedInto line trace and corresponding differential information is obtained, i.e., Therefore, wind turbine angular speed tracing control error is represented by：
em=v1-z31 (21)
According to the 3rd formula of system (12), then there is the differential signal of tracking error to be：
Obviously, formula (22) be a first-order perturbation error system (Disturbance Error dynamics System,
DEDS).With the quantity of state i of the 3rd formula in perturbed system (12)qThe virtual controlling amount of (q shaft currents) as rotating speed controlling unit is
Make DEDS asymptotically stable in the larges, defines q shaft currents iqExpectation instructionFor：
Wherein, zm＞ 0, zo＞ 0,ezm=z31-ωm.Der Geschwindigkeitkreis disturbs sensing controller (DPCm),
Such as Fig. 3 (a).
Due toWithRespectively PMSM inner ring current control link provides d-q shaft current expectation instructions and is therefore
Design inner ring current controller has established theoretical foundation, is described below respectively：
(2) d shaft currents disturbance sensing controller (DPCd) designs
If inner ring d shaft current tracing control errors are：In conjunction with the 1st formula of system (12),
Then the differential signal of error is：
Obviously, formula (24) is a first-order perturbation error system (DES).Defining d axis disturbance perception control law is：
Wherein, zd＞ 0,D shaft currents disturb sensing controller (DPCd), such as Fig. 3 (b).
(3) q shaft currents disturbance sensing controller (DPCq) designs
If inner ring q shaft current tracing control errors are：
In conjunction with the 2nd formula of system (12), then the differential signal of error is：
Defining q shaft currents disturbance perception control law is：
Wherein, zq＞ 0,Q shaft currents disturb sensing controller (DPCq), such as Fig. 3 (c).
TDm, DPCm, DPCd and DPCq are integrated to the straight drive PMSM wind power generating sets MPPT to be formed disturbance perception
Controller (MPPT-DPC), such as Fig. 4.
5. disturbance perception stability analysis of control system
In order to ensure directly to drive the stability of PMSM wind power control systems, it is desirable that der Geschwindigkeitkreis disturbs sensing controller (DPCm), d
It is all stable that shaft current, which disturbs sensing controller (DPCd) and q shaft currents disturbance sensing controller (DPCq),.Separately below
Theory analysis is carried out to the stability of three disturbance sensing controllers.
(1) d shaft currents disturb sensing controller (DPCd) stability analysis
Theorem 3. assumes disturbance d1Bounded：|d1| ＜ ∞, then and if only if zdWhen ＞ 0, d shaft currents are disturbed shown in formula (25)
Dynamic sensing controller (DPCd)：
It is globally asymptotically stable.Wherein, tracing control error ed=-id、LdIt is d axle inductances point
Amount.
It proves：D shaft currents are disturbed into perception control law (25) and substitute into agitation error system (DES) shown in formula (24), i.e.,
：
IfIt considersLars is taken to convert and arrange formula (29),
Then
Formula (30) is one by disturbing d1The error dynamics system of excitation.Obviously, as long as | d1| ＜ ∞, then and if only if
zdWhen ＞ 0, error dynamics system (30) be it is globally asymptotically stable, i.e.,：Therefore, d axis shown in formula (25)
Current disturbing sensing controller (DPCd) is globally asymptotically stable, and card is finished.
(2) q shaft currents disturb sensing controller (DPCq) stability analysis
Theorem 4. assumes the differential bounded of q axis expectation electric currents：And disturbance d2Bounded：|d2| ＜ ∞, then when and only
As gain parameter zqWhen ＞ 0, q shaft currents disturbance sensing controller (DPCq) shown in formula (28)：
It is globally asymptotically stable.
Wherein,LqIt is q axle inductance components.
It proves：Q shaft currents are disturbed into perception control law uq(28) agitation error system (DES) shown in formula (27) is substituted into,
To obtain the final product：
IfIfThen haveIt sets again
It considersTake Lars to convert and arrange formula (31), then
Formula (32) is one by Bounded PerturbationsThe error dynamics system of excitation.Obviously, as long as|d2| ＜ ∞,
To haveThen and if only if zqWhen ＞ 0, error dynamics system (32) be it is globally asymptotically stable, i.e.,：Therefore, q shaft currents disturbance sensing controller (DPCq) shown in formula (28) is globally asymptotically stable, and card is finished.
(3) der Geschwindigkeitkreis disturbs sensing controller (DPCm) stability analysis
Theorem 5. is assumed|d2| ＜ ∞, then and if only if zmWhen ＞ 0, der Geschwindigkeitkreis disturbance perception shown in formula (23)
Controller (DPCm)：
It is globally asymptotically stable.Wherein, em=v1-z31、v1It is that wind turbine it is expected angular speed's
Track signal, v2It isDifferential tracking information, z32It is to disturbing d3State estimation, i.e. z32≈d3。
It proves：Due to the quantity of state i of the 3rd formula in perturbed system (12)qThe virtual controlling of (q shaft currents) as rotating speed controlling unit
The target of amount, control is to make q shaft currents iqTrack desired instruction currentIf by theorem 4 it is found thatWith | d2| ＜ ∞,
Then and if only if zqWhen ＞ 0, q shaft currents disturbance sensing controller (DPCq) shown in formula (28) is globally asymptotically stable, i.e.,：Therefore, byIt is found that as t → ∞,
Substituted into shown in formula (22) disturb perceptual error system to get：
If the original state of speed error is：em(0) ≠ 0, then the solution of formula (33) is：
And
Obviously, as long as|d2| ＜ ∞, then and if only if zmWhen ＞ 0,AndShow
Speed error can approach origin from the initial point being arbitrarily not zero, i.e.,And zmIt is bigger, rotating speed
The speed that error approaches origin from the initial point being arbitrarily not zero is then faster, therefore, der Geschwindigkeitkreis disturbance perception shown in formula (23)
Controller (DPCm) is globally asymptotically stable, and card is finished.
6. directly driving the calm method of PMSM wind-powered electricity generation MPPT control system gain parameters
Include der Geschwindigkeitkreis disturbance sensing controller (DPCm) and electricity due to directly driving PMSM wind-powered electricity generation MPPT control systems not only
It flows ring and disturbs sensing controller DPCd and DPCq, but also include the function parts such as Nonlinear Tracking Differentiator and der Geschwindigkeitkreis disturbance observer
Part, therefore be related to 5 gain parameters in total and need to calm.Although 1~theorem of theorem 5 demonstrates respectively：Work as zvWhen ＞ 0, it is expected that
The Nonlinear Tracking Differentiator of rotating speed is globally asymptotically stable；Work as zoWhen ＞ 0, der Geschwindigkeitkreis disturbance observer is globally asymptotically stable；
When | di| ＜ ∞ (i=1,2,3), and zd＞ 0, zq＞ 0, zmWhen ＞ 0, current loop controller and rotating speed ring controller are all global
Asymptotically stable, this shows that the related gain parameter of patent of the present invention adjusts nargin with prodigious.However, global in addition to ensureing
Other than asymptotic stability, Nonlinear Tracking Differentiator, disturbance observer and current loop controller and rotating speed ring controller is also required all to have
There are fast response speed and high tracking accuracy or high accuracy of observation or high tracing control precision.Therefore, relevant 5
Parameter request value in optimized scope, it is too small to reduce response speed, it can then cause oscillatory occurences greatly very much.If h is integration step
Long, related gain parameter tuning is as follows：
(1)zd=zq=zm=zc, wherein 700≤zc≤1000；
(2)100≤zv≤500；
(3)zo=1/ (2h).
7. direct-driving type PMSM wind power control systems emulation experiment and analysis
In order to verify the validity of the present invention " the straight disturbance sensing control method for driving PMSM wind generator systems MPPT ", into
The following emulation experiment of row.Straight to drive PMSM wind power generating set MPPT control system schematic diagrams, such as Fig. 5 has ignored in emulation experiment
The influence of PWM inverter.Related simulated conditions setting is as follows：
(1) three-phase PMSM relevant parameters
pn=40, Ld=Lq=5mH, Rs=0.01 Ω, ψf=0.175Wb, J=0.05kgm2, B=0.008Nms；
(2) wind turbine relevant parameter
Blade radius R=5m, atmospheric density ρ=1.29kg/m3, propeller pitch angle β=0；
(3) disturbance perception control system relevant parameter
If integration step h=1/4000, takes zd=zq=zm=850；zv=300；zo=1/ (2h).
When 1. wind speed of example is 7m/s, magneto alternator rotational speed omegam, quadrature axis current iq, wind energy conversion system output torque TmWith
Generator electromagnetic torque Te, power coefficient CpEqual curves such as Fig. 6.Fig. 6 shows control method of the invention not only in response to speed
Degree is fast, and steady-state tracking precision is high, and wind energy conversion system maximal wind-energy usage factor CpmaxReach 0.483.
Example 2. at the 2.5s moment, wind speed by 7m/s busts to 6m/s when, magneto alternator rotational speed omegam, quadrature axis electricity
Flow iq, wind energy conversion system output torque TmWith generator electromagnetic torque Te, power coefficient CpEqual curves such as Fig. 7.The further tables of Fig. 7
Bright, control method of the invention not only fast response time, steady-state tracking precision is high, and wind energy conversion system maximal wind-energy usage factor
CpmaxReach 0.483 or so.Fig. 7 demonstrates the MPPT control method of the present invention in the extreme case of wind speed mutation, has fast
The tracking performance of speed and very high tracking accuracy.
Example 3. is under specified random wind speed and extreme case there are wind speed mutation, random wind speed v, permanent-magnet synchronous hair
Motor speed ωm, quadrature axis current iq, wind energy conversion system output torque TmWith generator electromagnetic torque Te, power coefficient CpEqual curves
Such as Fig. 8.Fig. 8 further demonstrates that, control method of the invention not only fast response time, steady-state tracking precision is high, and wind energy conversion system
Maximal wind-energy usage factor CpmaxIt can reach 0.478~0.488.Fig. 8 demonstrates the MPPT control method of the present invention in RANDOM WIND
Under the extreme case of speed mutation, there is quick tracking performance and very high tracking accuracy.
8. conclusion
PID controller, sliding mode controller (SMC) based on cybernetics strategy (eliminating error based on error) and from anti-
It is current control widely used three big mainstream controller of engineering field to disturb controller (ADRC).However, conventional PID controllers
Gain parameter changes with the variation of work condition state, lacks Ability of Resisting Disturbance, thus there are parameter quelling difficulties；And sliding formwork control
The strong Ability of Resisting Disturbance of device (SMC) processed be exchanged for by the dynamic quality of sacrificial system, thus Ability of Resisting Disturbance with it is high
There are implacable contradictions between frequency is buffeted；Automatic disturbance rejection controller (ADRC) although have stronger Ability of Resisting Disturbance, however,
The parameter that controller is related to is more, and certain nonlinear smoothing functions there is a problem of computationally intensive.The disturbance perception control of the present invention
Device (DPC) processed has concentrated the respective advantage of three big mainstream controllers, not only has fast response time, control accuracy height, robust steady
Qualitative feature good, Ability of Resisting Disturbance is strong, and controller architecture is simple, calculation amount is small, gain parameter has prodigious adjust
Nargin, and under the extreme case that work condition state mutates, also need not again be calmed to gain parameter.Three realities
The simulation result of example shows the operating mode in entirely different wind speed, the identical disturbance sensing controller of gain parameter
(DPC) effective control of straight drive PMSM wind generator systems MPPT is realized, thus demonstrates the correct of theory analysis of the present invention
Property.
The present invention is to realizing that the MPPT controls of direct-driving type PMSM have important theoretical and practical significance.
Claims (1)
- " the straight disturbance sensing control method for driving PMSM wind generator systems MPPT " 1. of the present invention, which is, packet Include following steps：1) since wind turbine it is expected that angular speed is a time-varying physical quantity, the present invention it is expected angular speed using TDm to wind energy conversion systemInto line trace and corresponding differential information is obtained, i.e.,Using disturbance observer Dom to wind energy conversion system Actual angular speed carries out disturbance estimation, to which wind turbine angular speed tracing control error is represented by：em=v1-z31, and define q The expectation instruction of shaft current is：Wherein, 700≤zm≤1000、zo=1/ (2h),ezm=z31-ωm。2) according to the expectation instruction for 1) obtaining q shaft currentsAfterwards, establishing q shaft current tracking errors isAnd define q axis Current disturbing sensing controller is：Wherein, 700≤zq≤ 1000,LqIt is q axle inductance components；3) according to d shaft current desired valuesIt is e that tracking error, which can be established,d=-id, define d shaft currents and disturb sensing controller For：Wherein, 700≤zd≤ 1000,LdIt is d axle inductance components；3) and 2) 4) by obtaining the expectation voltage of d axis and q axis respectivelyWithAfterwards, synchronous rotary can be sat according to anti-Park transformation Under mark systemWithIt transforms under rest frameWithAnd withWithSVPWM is encouraged to generate desired pulsewidth tune Signal processed；Or it is changed commanders under synchronous rotating frame according to anti-Park transformation and anti-Clark changesWithTransform to three-phase nature V under coordinate ABCa、VbAnd Vc, and with Va、VbAnd VcTo encourage SVPWM to generate desired pulse-width signal；5) after 4) obtaining the desired pulse width modulated signal that SVPWM is generated, inverter is driven it so as to from direct-driving type PMSM Peak power output is obtained, to realize the disturbance sensing control method of direct-driving type PMSM wind power systems MPPT.
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