CN109599889B - Fuzzy active disturbance rejection based ride-through control method and system under unbalanced voltage - Google Patents
Fuzzy active disturbance rejection based ride-through control method and system under unbalanced voltage Download PDFInfo
- Publication number
- CN109599889B CN109599889B CN201811256506.3A CN201811256506A CN109599889B CN 109599889 B CN109599889 B CN 109599889B CN 201811256506 A CN201811256506 A CN 201811256506A CN 109599889 B CN109599889 B CN 109599889B
- Authority
- CN
- China
- Prior art keywords
- fuzzy
- dfig
- current
- rotor
- disturbance rejection
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 32
- 230000004907 flux Effects 0.000 claims abstract description 15
- 230000008859 change Effects 0.000 claims description 13
- 230000006870 function Effects 0.000 claims description 9
- 230000009977 dual effect Effects 0.000 claims 1
- 230000008569 process Effects 0.000 abstract description 9
- 230000004044 response Effects 0.000 abstract description 7
- 230000007704 transition Effects 0.000 abstract description 2
- 230000001360 synchronised effect Effects 0.000 abstract 1
- 238000011217 control strategy Methods 0.000 description 11
- 230000014509 gene expression Effects 0.000 description 11
- 238000010248 power generation Methods 0.000 description 8
- 238000004088 simulation Methods 0.000 description 7
- 238000010586 diagram Methods 0.000 description 5
- 230000006698 induction Effects 0.000 description 5
- 230000001052 transient effect Effects 0.000 description 5
- 238000004364 calculation method Methods 0.000 description 4
- 230000005284 excitation Effects 0.000 description 3
- 238000013178 mathematical model Methods 0.000 description 3
- 230000009471 action Effects 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 2
- 230000008878 coupling Effects 0.000 description 2
- 238000010168 coupling process Methods 0.000 description 2
- 238000005859 coupling reaction Methods 0.000 description 2
- 238000011161 development Methods 0.000 description 2
- 238000002474 experimental method Methods 0.000 description 2
- 238000011160 research Methods 0.000 description 2
- 241000284466 Antarctothoa delta Species 0.000 description 1
- 206010044565 Tremor Diseases 0.000 description 1
- 238000004422 calculation algorithm Methods 0.000 description 1
- 150000001875 compounds Chemical class 0.000 description 1
- 230000001808 coupling effect Effects 0.000 description 1
- 230000001627 detrimental effect Effects 0.000 description 1
- 238000010438 heat treatment Methods 0.000 description 1
- 239000011159 matrix material Substances 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000002035 prolonged effect Effects 0.000 description 1
- 238000004804 winding Methods 0.000 description 1
Images
Classifications
-
- H02J3/386—
-
- 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
- Y02E10/76—Power conversion electric or electronic aspects
Landscapes
- Control Of Eletrric Generators (AREA)
Abstract
The invention relates to a DFIG low voltage ride through control method and a system based on fuzzy active disturbance rejection unbalanced voltage.A fuzzy active disturbance rejection controller is designed by establishing current, voltage and flux linkage equations of the DFIG under a synchronous rotating coordinate system, and a tracking differentiator is used for realizing a reasonable transition process and reducing output overshoot; and estimating the total system disturbance by the extended state observer, compensating, and calculating Fuzzy-ADRC control on the rotor side. The scheme disclosed restrains negative sequence current, slows down the impact of current and voltage, reduces the adjustable parameters of the system and simultaneously enables the system to have stronger robustness and faster dynamic response to disturbance.
Description
Technical Field
The invention aims to provide a DFIG low-voltage ride-through control method based on fuzzy active disturbance rejection under unbalanced voltage, which is suitable for DFIG grid-connected control, the voltage drop of a stator end is classified into unknown disturbance quantity, the total disturbance of a system is estimated and compensated, and the DFIG low-voltage ride-through control is realized.
Background
Wind power generation is one of the most mature and scale power generation modes with the best development conditions and commercial development prospects in new energy power generation. The doubly-fed wind generator is widely applied to wind power generation, and the doubly-fed wind generator mainly realizes the variable-speed constant-frequency power generation of the DFIG by controlling the excitation, the phase and the amplitude of the rotor side because the generator can run under the double-side feed of the stator and the rotor. Because the stator side of the DFIG unit is directly connected to the grid, the unit is sensitive to grid voltage faults. When the voltage drops, the DFIG unit generates a serious electromagnetic transient process, which causes overcurrent at the stator and rotor sides and fluctuation of the DC bus voltage. Therefore, the research on the low voltage ride through capability of the wind turbine generator is of great significance.
Relevant researchers at home and abroad have made relevant research in the field and put forward some relevant solutions. In the text of modeling and controlling a doubly-fed wind generator under grid voltage dip fault in the power system automation, a mathematical model for converting positive and negative sequence components of voltage, current and flux linkage of a wind turbine under unbalanced voltage to a dq axis is established in 8 th 2006. In the 'doubly-fed wind power system control strategy under unbalanced and harmonic distortion grid voltage' published in 'power system automation' in 2012, the positive and negative sequence components of the voltage, the current and the flux linkage of a wind motor under unbalanced voltage are converted to dq axis for decoupling control, the dynamic characteristics of the stator and rotor currents of the DFIG after the stator voltage drops are thoroughly analyzed, and the dynamic characteristics and the simulation result are compared and analyzed, but the control strategy structure is too complex, the designed controller depends on too many parameters and is inconvenient to adjust, so the robustness is poor, and the dynamic response is slow. In the 'low voltage ride through strategy simulation of doubly-fed wind power generation system' in the 'power automation equipment' at the 6 th stage in 2010, an Active Crowbar and a direct-current side load shedding circuit are used for consuming excessive energy caused by stator voltage drop to realize LVRT of the wind turbine generator, but the control condition of DFIG when the voltage is unbalanced is not considered.
Disclosure of Invention
Aiming at the problems, the invention provides a DFIG low voltage ride through control method under unbalanced voltage based on fuzzy active disturbance rejection, and solves the problem of rotor side overcurrent under unbalanced power grid. Simulation and experiment results show that the device can effectively improve the low voltage ride through level of the wind power generation system and has higher engineering application value.
The structure of the doubly-fed induction wind generating set is shown in figure 1. The double-fed induction wind generating set mainly comprises a wind turbine, a double-fed induction generator, a frequency converter and a Crowbar circuit. The wind turbine converts wind energy into mechanical energy, a rotor winding of the doubly-fed induction generator is connected with a rotor side converter of the frequency converter, and the mechanical energy is converted into electric energy under the control action of the frequency converter. The frequency converter is composed of a rotor side converter and a network side converter. The rotor side converter provides excitation current with variable power supply amplitude, phase and frequency for the doubly-fed induction generator. The network side converter is actually a voltage type PWM rectifier, and the alternating current side has unique controlled current source characteristics and can realize four-quadrant operation.
The rotor-side converter current fuzzy active disturbance rejection control structure is shown in fig. 2, and due to the fact that an electromagnetic transient process can occur inside a DFIG system under the condition of grid voltage drop, analysis can be conducted in a dq + and dq-coordinate system, and expressions of DFIG current, voltage and flux linkage under the condition are obtained. The falling process of the three-phase voltage of the stator under the condition of low-voltage unbalance fault can be regarded as disturbance of the system, and the total disturbance is estimated.
The invention provides a DFIG low voltage ride through control method under unbalanced voltage based on fuzzy active disturbance rejection, which solves the problem of rotor side overcurrent under unbalanced power grid. The low voltage ride through capability of the wind power generation system can be obviously improved, and the specific principle and the method are as follows:
the DFIG low voltage ride through control method under the unbalanced voltage based on the fuzzy active disturbance rejection is characterized by comprising the following steps:
firstly, according to a DFIG model under unbalanced grid voltage, differential forms of voltage, current and flux linkage are written on a double-synchronous rotation coordinate axis.
And step two, fuzzy active disturbance rejection control is carried out: take the error as e 1xy The rate of change is e 2xy 。
According to the active disturbance rejection control principle and the motor model, a tracking differentiator is taken as
The extended observer is
By taking the Mamdani type as a fuzzy reasoning theory and taking an average weighting method as a defuzzification algorithm, a fuzzy control table is designed to modify the nonlinear feedback rate on line, and the control table 1 is as follows:
TABLE 1. DELTA.beta 3 、△β 4 Fuzzy control table
The nonlinear feedback rate is then:
beta' = beta + delta beta, where beta is the initial value, beta 0i, a i And delta i are all adjustable quantities.
Thirdly, designing a current control method by taking the power as an outer ring signal and the current as an inner ring signal, and enabling the negative sequence current to inhibit the negative sequence current
A positive sequence current of
When the voltage of the power grid drops, the rotor side does not generate large impact current, and the stable value is recovered in a short time.
Further, the S1 step DFIG model formula is as follows:
the voltage equation in the dq +, dq-coordinate system is:
in the formula of U s And U r For stator and rotor voltages, psi is flux linkage, omega 1 Is the angular velocity, omega slip For slip angular velocity, R s And R r The resistance of the stator and the rotor is set;
at dq + ,dq - The DFIG flux linkage equation in the coordinate system is:
in the formula, psi sd+ ，Ψ sq+ ，Ψ sd- ，Ψ sq- ，Ψ rd+ ，Ψ rq+ ，Ψ rd- ，Ψ rq- Is a stator, and is characterized in that,d of rotor flux linkage + ,q + ,d - ,q - Axial component L s 、L r For self-inductance of stator and rotor, L m The stator and the rotor are mutually inducted.
Further, the fuzzy active disturbance rejection control is double-current inner-loop fuzzy active disturbance rejection control.
Further, the DFIG system controller adopts the DFIG low voltage ride through control method under the unbalanced voltage based on the fuzzy active disturbance rejection.
Further, the stator of the DFIG system is connected with a power grid, and the rotor is connected with the power grid through a rotor side converter.
Further, the DFIG system controller decomposes the input signal into an approximate quantity and a product of a state quantity and a step length through a tracking differentiator, so that the system is free of overshoot; and receiving the observed value of each state variable and the observed value of the system disturbance through the extended observer.
Compared with the prior art, the invention has the beneficial effects that:
by adopting the fuzzy active disturbance rejection control method, the current disturbance time is shortened, and the impact of current fluctuation on a system is reduced. By improving the nonlinear feedback rate, a fuzzy control table is designed to modify the nonlinear feedback rate on line, and when the external fault causes system current disturbance, the disturbance is compensated by parameter adjustment, so that the current amplitude is smaller, the time for recovering to a stable value is short, and the system response is improved.
Drawings
FIG. 1 is a structural diagram of a rotor-side converter current active disturbance rejection control;
FIG. 2 is a schematic diagram of a rotor-side converter current fuzzy active disturbance rejection control;
FIG. 3 is a simulation voltage fluctuation diagram of a DFIG wind turbine generator set of 6 MW;
FIG. 4 is a conventional control strategy dq axis current;
FIG. 5 fuzzy auto-disturbance rejection control strategy dq axis currents;
FIG. 6 illustrates a conventional control strategy for dq axis voltage;
FIG. 7 is a diagram of a fuzzy active disturbance rejection control strategy dq axis voltages;
FIG. 8 illustrates a conventional control strategy torque;
FIG. 9 fuzzy active disturbance rejection control strategy torques;
FIG. 10 illustrates a conventional control strategy power;
fig. 11 illustrates a conventional control strategy power.
Detailed Description
The invention provides a DFIG low voltage ride through control method under unbalanced voltage based on fuzzy active disturbance rejection, which comprises the following steps:
s1, according to a DFIG model under unbalanced grid voltage, differential forms of voltage, current and flux linkage are written on a double-synchronous rotation coordinate axis.
Because the transformer can eliminate zero sequence voltage when the transformer is connected from star to triangle, only positive sequence and negative sequence components need to be considered when analyzing the asymmetric fault of the power grid. And positioning the ABC coordinate system on the dq axis to obtain positive sequence and negative sequence mathematical models of the DFIG. The voltage equation of DFIG in dq +, dq-coordinate system is:
in the formula of U s And U r For stator and rotor voltages, psi is flux linkage, omega 1 Is angular velocity, ω slip For slip angular velocity, R s And R r The resistance of the stator and the rotor is adopted.
At dq + ,dq - The DFIG flux linkage equation in the coordinate system is:
in the formula, Ψ sd+ ，Ψ sq+ ，Ψ sd- ，Ψ sq- ，Ψ rd+ ，Ψ rq+ ，Ψ rd- ，Ψ rq- D for stator, rotor flux linkage + ,q + ,d - ,q - Axial component L s 、L r For self-inductance of stator and rotor, L m Is the stator-rotor mutual inductance.
S2, carrying out fuzzy active disturbance rejection control on the DFIG model;
s21, establishing a fuzzy active disturbance rejection control system;
an Active Disturbance Rejection Controller (ADRC) is improved on the basis of classical PID control, and does not need to directly measure the action of external disturbance and predict the law of the disturbance. Due to the characteristic of the ADRC, the coupling effect between the subsystems of the multivariable can be regarded as an uncertain quantity and is classified as unknown disturbance, so that the accurate mathematical model of the controlled object is not required to be relied on in the using process. As shown in FIG. 1, the active disturbance rejection control system diagram is shown, TD is a tracking differentiator, ESO is an extended observer, a rotor side current i is input into the tracking differentiator, and an output is i 1 、i 2 I represents the tracking rotor current value and the "approximate differential" of the rotor current, respectively 1 、i 2 Respectively with the observed values z formed in the extended observer 1 、z 2 Comparing to obtain an error e 1 And rate of change e 2 E is to be 1 、e 2 Inputting the nonlinear state error feedback control expression to obtain U 0 (t), U (t), mixing U 0 (t), U (t) generating new observed value z calculated by extended observer 1 、z 2 Will generate a new z 1 、z 2 I respectively with the output of the next round in the tracking differentiator 1 、i 2 Comparing and calculating a new error e 1 And rate of change e 2 And then the current change is tracked and controlled through the circulation by counting through the nonlinear state error feedback control rate.
The fuzzy active disturbance rejection control system is based on the active disturbance rejection controller, adds a fuzzy control table, and introduces a fuzzy control process in a nonlinear state error feedback expression. The system structure is shown in FIG. 2, error e 1 And rate of change e 2 And adjusting and modifying in the fuzzy control table to obtain the optimal change rate.
a. The input parameters of the fuzzy active disturbance rejection control system are designed as follows:
partial coupling terms exist in the system according to the state equation of the rotor-side converter, so that the component on the d axis and the component on the q axis influence each otherThis is detrimental to the transient performance of the control system. The method adopts fuzzy active disturbance rejection control to estimate the coupling quantity, so that the system is not easy to deviate from a target when the outside of the system is disturbed. The DFIG active power P under unbalance can be obtained from the power output characteristic under the unbalance of the grid voltage 0 And reactive power Q 0 Comprises the following steps:
to reduce the negative sequence component of the rotor-side current, the negative sequence current is taken to be 0, i.e.
The reference value of the positive-sequence rotor current can be obtained from the formulas (1), (2), (3) and (4):
therefore, when the rotor-side current is input in the fuzzy active disturbance rejection controller, the negative sequence current is 0, and the positive sequence current reference value is as shown in expression 5.
b. The tracking differentiator of the fuzzy active disturbance rejection controller is designed as follows:
the nonlinear uncertain object of unknown interference x (n) is represented as follows:
in the formula (I), the compound is shown in the specification,
is an unknown function, w (t) is an unknown external disturbance, x (t) is a measurable quantity, and b is an actual controlled quantity obtained by the object.
Set schedule transitionIs a rotor current reference value
An output of i 1xy ，i 2xy (ii) a Wherein i 1xy To track rotor current values, i 2xy Is the "approximate derivative" of the rotor current. The TD parameter expression is:
wherein x represents d or q axis, y represents positive or negative sequence, i 1xy For the rotor current tracking value, z 1xy And h is the step length and e is the error of the observed value of the rotor current.
In order to reduce the overshoot of output and avoid the phenomenon of high-frequency tremble generated when the system enters a steady state after the discretization of a tracking-differentiator, a nonlinear function g in the TD is as follows:
(1) the nonlinear function g (z) is continuously differentiable;
②g(0)＝0；
(3) derivative thereof
The expression for the fal function can be taken as follows:
in the formula, a is 0-1, delta is a filter influence constant (generally, 5T is less than or equal to delta is less than or equal to 10T), and e is a state estimation error. The tracking differentiator parameter expression is as follows:
c. the extended observer of the fuzzy active disturbance rejection controller is designed as follows:
the observation equation for the expandable system that can be constructed for this system is expressed as follows:
due to z i Respectively tracking the expanded state quantities x (i-1) (t) and the parameter b 0 As is known, the control quantity can be chosen as: u = u 0 -z 3 /b 0 。
Since the nonlinear function is a fal function, the form of ESO is:
wherein beta is 0i Is an optional parameter.
To achieve the ESO observation of the state, a compensation matrix of equation (9) is written
According to the essential condition of system stability, the characteristic root of A is on the left half of the complex plane and is sufficiently negative (namely lambda) 3 +λ 2 k 1 +λk 2 +k 3 = 0), let a be a characteristic value λ 1 ,λ 2 ,λ 3 And a parameter k 1 ,k 2 ,k 3 Satisfies the following conditions:
s 3 +k 1 s 2 +k 2 s+k 3 ＝(s-λ 1 )(s-λ 2 )(s-λ 3 )
k can be obtained according to undetermined coefficient method 1 ,k 2 ,k 3 A value of (b) from 0i ＝k i The initial value beta can be obtained from/fal (e, a, delta) 0i 。
With i rd+ ,i rq+ ,i rd- ,i rq- For measurement input, w 1 ,w 2 ,w 3 ,w 4 For estimating the disturbance quantity, a state extended observer parameter expression is constructed as follows:
wherein x represents d or q axis, y represents positive or negative sequence, z 1xy And (4) a rotor current disturbance observed value.
S22, introducing a fuzzy control table, and designing a modifiable fuzzy nonlinear feedback rate;
and introducing a fuzzy control table, carrying out online modification on the nonlinear state error feedback rate in the active disturbance rejection control system, and then carrying out optimal parameter setting. With e 1 ,e 2 As input, the output is Δ β, defining 7 language subsets, which are { "positive large (PB)", "Positive (PM)", "Positive Small (PS)", "Zero (ZO)", "negative large (NB)", "Negative Middle (NM)", "Negative Small (NS)" }. With e 1 ，e 2 As input, its membership function is gausssf, e 1 And e 2 The fuzzy subsets of (a) are: { PB, PM, PS, ZO, NS, NM, NB }, take e 1 ,e 2 All domains are { -3, -2, -1,0,1,2,3}. At a.DELTA.beta 03 And Δ β 04 For output, the membership function is trimf, the output subset is PB, PM, PS, ZO, NS, NM, NB, and Δ β 03 The domain of discourse of (1) is: { -0.3, -0.2, -0.1,0,0.1,0.2,0.3}. Delta beta 04 The domain of discourse of (1) is: { -0.06, -0.04, -0.02,0.02,0.04,0.06}. Delta beta 3 、△β 4 The fuzzy control table is as follows:
the fuzzy nonlinear feedback expression is
Beta' = beta + delta beta, where beta is the initial value, beta i 、a i And delta are both adjustable quantities.
S23, controlling system parameters through fuzzy nonlinear state error feedback control rate;
when the fuzzy nonlinear state error feedback control rate control system is adopted, the error e is calculated 1 Rate of change e 2 Inputting fuzzy control table, performing fuzzy calculation to obtain output quantity delta beta 3 、△β 4 Corresponding to the parameter, will delta beta 3 、△β 4 Substituting the fuzzy nonlinear feedback expression to calculate U 0 (t), U (t); will U 0 (t), U (t) calculating z by the extended observer 1 、z 2 . For example, take the input error e 1 And rate of change e 2 PB and ZO respectively, the value of PB in the domain is 3, the value of ZO in the domain is 0, and the fuzzy calculation table is inquired to find out that e 1 And e 2 The corresponding output is MN/PM, the output value is delta beta 3 And Δ β 4 Respectively MN and PM, corresponding values Delta beta in the domain of discourse 3 Is 0.2,. DELTA.beta 4 Is-0.04. Will delta beta 3 Is 0.2,. DELTA.beta 4 Substituting nonlinear feedback expression into-0.04 to calculate U 0 And (t) and U (t) for fuzzy control.
S24, circularly controlling input current parameters;
the negative sequence current is set to 0, and the positive sequence current is input into tracking differentiator to form two components i 1 、i 2 And z formed in the extended observer 1 、z 2 Comparing to obtain new error e 1 And rate of change e 2 Error e to be newly formed 1 And rate of change e 2 Performing fuzzy calculation again, and inputting the fuzzy calculation into the nonlinear feedback rate table to calculate U 0 And (t) and U (t), and influencing the current input of the next round through the extended observer and sequentially circulating.
The method designs the fuzzy control table to modify the nonlinear feedback rate on line, and when the external fault causes the current disturbance of the system, the disturbance is compensated through parameter adjustment, so that the current amplitude is smaller, the time for recovering to a stable value is short, and the system response is improved.
The following simulation and experiment are carried out by adopting a fuzzy active disturbance rejection control method: and (4) establishing a simulation model of a DFIG wind turbine generator set of 6MW, and simulating wind power plants consisting of 1.5 MW. The simulation motor is taken as follows: rated power is 1.5MW, rated stator voltage is 690V, stator resistance is 0.0071 (pu), and stator leakage inductance is 0.175 (pu). Rotor resistance 0.004 (pu), rotor leakage inductance 0.154 (pu), excitation inductance 2.7 (pu), inertia time constant 5.0s, and pole pair number 3. The proposed solution was simulated and the results are shown in figures 3-11. As can be seen from fig. 3, the grid voltage is unbalanced by 5% at 0.24s, and returns to the grid voltage balanced state at 0.80 s. The traditional vector control strategy ignores the negative sequence component of the electromagnetic quantity in the electromagnetic transient process caused by the voltage drop of the power grid, so that the smaller unbalanced voltage fluctuation can also generate the impact current with larger amplitude. The impact current can cause the unbalanced heating of the wind turbine generator and seriously damage the normal operation of the wind turbine generator. In addition, when the grid voltage returns to the normal state within 0.8s, the time for the current on the rotor side to return to the stable value is long, and the dynamic response of the system is slow. As can be seen from the attached drawings 4 and 5, the fuzzy active disturbance rejection control adopted by the invention modifies the controller parameters on line to adapt to a system model in the electromagnetic transient process, and when the voltage of a power grid is unbalanced and dropped, the amplitude of the generated current at the rotor side is smaller, so that the overcurrent at the rotor side is effectively prevented. As can be seen from the attached figures 6 and 7, when the voltage of the power grid fluctuates, the fuzzy active disturbance rejection control scheme can better inhibit the vibration of the torque, and the operation life of the wind turbine generator is prolonged. As can be seen from fig. 8-11, the power of the rotor side is low when the voltage of the power grid drops, which is beneficial to the safe operation of the converter, and the time for the current, the torque and the power of the rotor side to be stable is shorter after the voltage of the power grid is recovered, so that the system has stronger robustness and faster dynamic response.
The invention aims to provide DFIG low voltage ride through control under unbalanced voltage based on fuzzy active disturbance rejection, a fuzzy active disturbance rejection controller is designed, a tracking differentiator is used for realizing a reasonable transition process, and the overshoot of output is reduced; the extended state observer estimates the total disturbance of the system and compensates the total disturbance; the Fuzzy-ADRC control of the rotor side is calculated, the negative sequence current is restrained by the scheme, the impact of the current is relieved, the adjustable parameters of the system are reduced, and meanwhile the system has stronger robustness and faster dynamic response to disturbance.
Claims (8)
1. The DFIG low voltage ride through control method based on the fuzzy active disturbance rejection under the unbalanced voltage is characterized by comprising the following steps of:
s1, establishing a DFIG model formula under the unbalanced power grid voltage;
s2, designing a fuzzy active disturbance rejection control system;
s21, establishing an active disturbance rejection control system;
designing a tracking differentiator and an extended observer, taking current as an input parameter and taking error as e 1xy The rate of change is e 2xy According to the active disturbance rejection control principle and a motor model, obtaining a tracking differentiator as follows:
the extended observer is:
wherein x represents d-axis or q-axis, y represents positive sequence or negative sequence, i 1xy (t) is the rotor current tracking value, i 2xy (t) is the "approximate differential" of the rotor current, z 1xy As observed rotor current, h is step size, fal (e) 1xy ，a 1 ，δ 1 ) B is the actual control quantity obtained by the object, which is a nonlinear function;
s22, introducing a fuzzy control table, and designing a modifiable fuzzy nonlinear feedback rate;
applying fuzzy control in the auto-disturbance rejection control model with e 1xy 、e 2xy For input,. DELTA.beta 03 And Δ β 04 Is an output; defining 7 language subsets, namely { "Positive Big (PB)", "Positive Middle (PM)", "Positive Small (PS)", "Zero (ZO)", "Negative Big (NB)", "Negative Middle (NM)", "Negative Small (NS)" };
the fuzzy control table is established as follows:
in the fuzzy control table, calculating an output parameter according to an input parameter; output parameter Delta beta 03 And Δ β 04 Substituting into a nonlinear feedback rate formula to calculate u 0xy (t) and u (t), where u (t) is a control quantity, and observing the current error e by a dilated observer 1xy And rate of change e 2xy (ii) a The nonlinear feedback rate formula is as follows:
in the formula, beta 0i ，a i ，δ i Are all adjustable;
s3, carrying out fuzzy active disturbance rejection control on the DFIG model;
s31, taking power as an outer ring signal and current as an inner ring signal to enable negative sequence current
The positive sequence current is:
in the formula, P 0 Active power, Q, of DFIG in case of unbalance 0 For reactive power of DFIG in case of unbalance, L s For stator self-inductance, L m The stator and the rotor are mutually inducted;
inputting the positive sequence and negative sequence current on each coordinate axis into a tracking differentiator of the fuzzy active disturbance rejection control system, comparing the output parameters with observation parameters generated by an extended observer, and forming a current error e 1xy And rate of change e 2xy A 1, e 1xy 、e 2xy Generating new observation parameters by fuzzy nonlinear feedback rate tracking;
s32, circulating the step S31.
2. The method for controlling DFIG low voltage ride through under unbalanced voltage based on fuzzy active disturbance rejection as claimed in claim 1, wherein e is in the fuzzy control table 1xy ,e 2xy All domains are { -3, -2, -1,0,1,2,3}.
3. The method for controlling DFIG low voltage ride-through under fuzzy active disturbance based unbalanced voltage as claimed in claim 1, wherein Δ β 03 The domain of discourse of (1) is: { -0.3, -0.2, -0.1,0,0.1,0.2,0.3}, [ delta ] β 04 The domain of discourse of (1) is: { -0.06, -0.04, -0.02,0.02,0.04,0.06}.
4. The method for controlling low voltage ride-through of the DFIG under the unbalanced voltage based on the fuzzy active disturbance rejection as claimed in claim 1, wherein the S1 step DFIG model formula is as follows:
the voltage equation in the dq +, dq-coordinate system is:
in the formula of U s And U r For stator and rotor voltages, U sdq+ 、U rdq+ 、U sdq- 、U rdq- Dq +, dq-axis components of the stator voltage and the rotor voltage, respectively, psi is flux linkage, omega 1 Is the angular velocity, omega slip For slip angular velocity, R s And R r The resistance of the stator and the rotor is adopted;
the DFIG flux linkage equation in the dq +, dq-coordinate system is:
in the formula, # sdq+ 、ψ rdq+ 、ψ sdq- 、ψ rdq- Is the dq +, dq-axis component of the stator, rotor flux linkage, L s 、L r Is self-inductance of stator and rotor，L m For stator-rotor mutual inductance, i sdq+ 、i sdq- 、i rdq+ 、 irdq- The dq +, dq-axis components of the stator current and the rotor current, respectively.
5. The method for controlling low voltage ride-through of the DFIG under the unbalanced voltage based on the fuzzy active disturbance rejection as claimed in claim 1, wherein the fuzzy active disturbance rejection control is a dual current inner loop fuzzy active disturbance rejection control.
6. A DFIG system, characterized in that a DFIG system controller adopts the method for controlling the ride-through of the low voltage of the DFIG under the unbalanced voltage based on the fuzzy active disturbance rejection as claimed in any one of claims 1 to 3.
7. The DFIG system of claim 6, wherein the DFIG system stator is coupled to a grid and the rotor is coupled to the grid via a rotor side converter.
8. The DFIG system of claim 6, wherein the DFIG system controller resolves the input signal into an approximation quantity and a product of a state quantity and a step size by a tracking differentiator to make the system free of overshoot; and receiving the observed value of each state variable and the observed value of the system disturbance through the extended observer.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811256506.3A CN109599889B (en) | 2018-10-25 | 2018-10-25 | Fuzzy active disturbance rejection based ride-through control method and system under unbalanced voltage |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811256506.3A CN109599889B (en) | 2018-10-25 | 2018-10-25 | Fuzzy active disturbance rejection based ride-through control method and system under unbalanced voltage |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN109599889A CN109599889A (en) | 2019-04-09 |
| CN109599889B true CN109599889B (en) | 2022-10-18 |
Family
ID=65957469
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201811256506.3A Active CN109599889B (en) | 2018-10-25 | 2018-10-25 | Fuzzy active disturbance rejection based ride-through control method and system under unbalanced voltage |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109599889B (en) |
Families Citing this family (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112003321B (en) * | 2020-08-11 | 2022-05-17 | 宝鸡文理学院 | Low-voltage ride through control method for dynamic resistor of double-feeder rotor string |
| CN113141024B (en) * | 2021-04-22 | 2022-08-02 | 太原理工大学 | DFIG rotor side converter fault ride-through control method adopting additional compensation term |
| CN114928281B (en) * | 2022-04-21 | 2024-04-16 | 合肥工业大学 | Voltage control type doubly-fed wind turbine generator fault ride-through method based on improved active disturbance rejection |
| CN115036971A (en) * | 2022-06-21 | 2022-09-09 | 淮阴工学院 | Robust control strategy for island microgrid inverter based on fuzzy observer |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102055205A (en) * | 2010-10-26 | 2011-05-11 | 天津理工大学 | Voltage unbalanced mathematical model-based control strategy for brushless double-feed motor grid-side converter |
| CN108429277A (en) * | 2018-01-29 | 2018-08-21 | 浙江工业大学 | A kind of both end voltage source type transverter HVDC transmission system control method based on fuzzy Active Disturbance Rejection Control |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP2447792A1 (en) * | 2005-09-19 | 2012-05-02 | Cleveland State University | Controllers, observer, and applications thereof |
-
2018
- 2018-10-25 CN CN201811256506.3A patent/CN109599889B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102055205A (en) * | 2010-10-26 | 2011-05-11 | 天津理工大学 | Voltage unbalanced mathematical model-based control strategy for brushless double-feed motor grid-side converter |
| CN108429277A (en) * | 2018-01-29 | 2018-08-21 | 浙江工业大学 | A kind of both end voltage source type transverter HVDC transmission system control method based on fuzzy Active Disturbance Rejection Control |
Non-Patent Citations (1)
| Title |
|---|
| 基于模糊自抗扰的风电系统独立变桨距控制;任丽娜等;《动力工程学报》;20180731;第38卷(第7期);第564-571页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN109599889A (en) | 2019-04-09 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109599889B (en) | Fuzzy active disturbance rejection based ride-through control method and system under unbalanced voltage | |
| Hossain et al. | Simultaneous STATCOM and pitch angle control for improved LVRT capability of fixed-speed wind turbines | |
| US9124140B2 (en) | Intelligent power converter control for grid integration of renewable energies | |
| CN102082543A (en) | Method for controlling double-feed wind driven generator under imbalanced power grid voltage | |
| Abo-Khalil et al. | Sensorless control for DFIG wind turbines based on support vector regression | |
| WO2021110171A1 (en) | P-u droop characteristic-based virtual direct current motor control method | |
| Dida et al. | A complete modeling and simulation of DFIG based wind turbine system using fuzzy logic control | |
| Zamzoum et al. | Active and reactive power control of wind turbine based on doubly fed induction generator using adaptive sliding mode approach | |
| Rosyadi et al. | Transient stability enhancement of variable speed permanent magnet wind generator using adaptive PI-Fuzzy controller | |
| CN110970925A (en) | Double-fed fan based damping and modeling method for improving system through fast active power modulation | |
| Zhang et al. | Maximum power point tracking algorithms for wind power generation system: Review, comparison and analysis | |
| Djoudi et al. | Adaptive sensorless SM-DPC of DFIG-based WECS under disturbed grid: Study and experimental results | |
| Li et al. | Dynamic modeling and controller design for a novel front-end speed regulation (FESR) wind turbine | |
| Chatri et al. | Improved high-order integral fast terminal sliding mode-based disturbance-observer for the tracking problem of PMSG in WECS | |
| Barambones et al. | Adaptive robust control to maximizing the power generation of a variable speed wind turbine | |
| Hemeyine et al. | Robust takagi sugeno fuzzy models control for a variable speed wind turbine based a DFI-generator | |
| CN110417047B (en) | Method for analyzing SSCI damping characteristics of doubly-fed fan based on complex torque coefficient | |
| Barambones et al. | Wind turbine control scheme based on adaptive sliding mode controller and observer | |
| Majdoub et al. | Variable speed control of DFIG-wind turbine with wind estimation | |
| Barambones et al. | An adaptive sliding mode control law for the power maximization of the wind turbine system | |
| Srinivasan et al. | Machine Learning Controller for DFIG Based Wind Conversion System. | |
| Vali et al. | Control of doubly-fed induction generator with extended state observer under unbalanced grid conditions | |
| Abulizi et al. | Research of current control strategies for doubly-fed wind power generation system | |
| Yang et al. | Fuzzy PID control of induction generators | |
| Mousavi et al. | Observer-Based High-Order Sliding Mode Control of DFIG-Based Wind Energy Conversion Systems Subjected to Sensor Faults |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |