CN108173279A - The soft grid-connection control device and control method of permanent magnet direct-drive wind turbine - Google Patents
The soft grid-connection control device and control method of permanent magnet direct-drive wind turbine Download PDFInfo
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- CN108173279A CN108173279A CN201611120210.XA CN201611120210A CN108173279A CN 108173279 A CN108173279 A CN 108173279A CN 201611120210 A CN201611120210 A CN 201611120210A CN 108173279 A CN108173279 A CN 108173279A
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- 238000012549 training Methods 0.000 claims description 12
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- 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
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- Y02E10/00—Energy generation through renewable energy sources
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Abstract
The present invention provides a kind of soft grid-connection control device and control method of permanent magnet direct-drive wind turbine, including：MPU controllers, rectifier, LC wave filters, Boost, inverter bridge, LCL filter, the first drive module, the second drive module, assistant load, first contactor, second contactor, first voltage sensor, second voltage sensor, tertiary voltage sensor, the 4th voltage sensor and current sensor.The present invention in simultaneously net side by introducing assistant load, make the grid-connected preceding run with load of permanent magnet direct-drive wind turbine, the shortcomings that stability is poor when can avoid idle grid connection, and, the output voltage of permanent magnet direct-drive wind turbine is controlled by SVM prediction model, its amplitude, frequency, phase can be made preferably to be consistent with network voltage, so as to weaken the impact of Parallel Operation on Power System.
Description
Technical field
The present invention relates to technical field of wind power generation, more specifically, are related to a kind of soft and network control of permanent magnet direct-drive wind turbine
Device processed and control method.
Background technology
Increasingly sharpen with the continuous social and economic development with energy crisis, the utilization of regenerative resource are increasingly
Paid attention to by the world today.Wind-power electricity generation has the advantages that cleaning, contains abundant, and the exploitation in numerous regenerative resources is excellent
Gesture is fairly obvious.The pattern of generating electricity by way of merging two or more grid systems is the principal mode that large-scale wind power exploitation utilizes.It is tided in the grid-connected mistake of Wind turbines
Cheng Zhong easily generates big dash current, power grid is impacted.With the continuous improvement of Wind turbines capacity, how to realize
Its it is soft it is grid-connected become one it is in the urgent need to address the problem of.
For permanent magnet direct-drive wind turbine group, existing grid-connecting apparatus generally under the conditions of wind turbine no-load running, is controlled by PI
Device processed adjusts the net side inverter output voltage of wind turbine, it is made unanimously to implement afterwards simultaneously in amplitude, frequency, phase with network voltage
Net, major defect are：Under the conditions of no-load running, the output voltage of net side inverter has the shortcomings that harmonic content is high, directly
Connect it is grid-connected easily cause rush of current, even result in grid-connected failure.
Invention content
For wind turbine it is grid-connected during be susceptible to dash current the problem of, the present invention provides a kind of permanent magnet direct-drive wind turbine
Soft grid-connection control device and control method, including：MPU controllers, rectifier, LC wave filters, Boost, inverter bridge,
LCL filter, the first drive module, the second drive module, assistant load, first contactor, second contactor, first voltage pass
Sensor, second voltage sensor, tertiary voltage sensor, the 4th voltage sensor and current sensor；Wherein,
The three-phase input end of rectifier is connect with the three-phase output end of permanent magnet direct-drive wind turbine, the single-phase output anode of rectifier
It is connect with the input positive terminal of LC wave filters, the single-phase output negative terminal of rectifier is connect with the input negative terminal of LC wave filters；
The input positive terminal of the output plus terminals of LC wave filters and Boost connects, the output negative terminal of LC wave filters with
The input negative terminal connection of Boost；
The input positive terminal of the output plus terminal of Boost and inverter bridge connects, the output negative terminal of Boost with it is inverse
Become the input negative terminal connection of bridge；
The output plus terminal of inverter bridge and the input positive terminal of LCL filter connect, the output negative terminal and LCL filter of inverter bridge
Input negative terminal connection；
The output plus terminal of LCL filter is connect with the measurement anode of tertiary voltage sensor, the output negative terminal of LCL filter
It is connect with the measurement negative terminal of tertiary voltage sensor；
One end of first contactor and the output plus terminal of LCL filter connect, and the other end and auxiliary of first contactor are negative
One end connection of load, the other end of assistant load are connect with the zero curve terminals of single-phase power grid；
One end of second contactor and the output plus terminal of LCL filter connect, the other end and single-phase electricity of second contactor
The hot terminal connection of net；
The measurement anode of first voltage sensor is connect with the output plus terminal of LC wave filters, the measurement of first voltage sensor
Negative terminal is connect with the output negative terminal of LC wave filters, and the measuring signal output terminal of first voltage sensor is connect with MPU controllers；
The output plus terminal connection for measuring anode and Boost of second voltage sensor, second voltage sensor
The output negative terminal for measuring negative terminal and Boost connects, measuring signal output terminal and the MPU controllers of second voltage sensor
Connection；
The output plus terminal connection for measuring anode and LCL filter of tertiary voltage sensor, the survey of tertiary voltage sensor
The output negative terminal for measuring negative terminal and LCL filter connects, and measuring signal output terminal and the MPU controllers of tertiary voltage sensor connect
It connects；
The measurement anode of 4th voltage sensor is connect with the hot terminal of single-phase power grid, the survey of the 4th voltage sensor
Amount negative terminal is connect with the zero curve terminals of single-phase power grid, and measuring signal output terminal and the MPU controllers of the 4th voltage sensor connect
It connects；
The measurement anode and measurement negative terminal of current sensor are connect respectively with LCL filter, the measurement letter of current sensor
Number output terminal is connect with MPU controllers；
The input terminal of first drive module is connect with MPU controllers, the output terminal and Boost of the first drive module
Connection；
The input terminal of second drive module is connect with MPU controllers, two output terminals of the second drive module respectively with it is inverse
Become bridging to connect.
Additionally, it is preferred that structure be, LC wave filters include the first inductance and the first capacitance；Wherein, one end of the first inductance
It is connect with the single-phase output anode of rectifier, the other end of the first inductance is connect with the anode of the first capacitance, and the first capacitance is born
The single-phase output negative terminal of pole and rectifier connects.
Furthermore it is preferred that structure be that rectifier is uncontrollable rectifier device.
Furthermore preferred structure is, Boost includes the second inductance, the first power tube, diode and the second electricity
Hold；Wherein, one end of the second inductance is connect with the output plus terminal of LC wave filters, the other end of the second inductance and the anode of diode
Connection, the drain electrode of the first power tube and the anode of diode connect, the output of the grid of the first power tube and the first drive module
End connection, the source electrode of the first power tube are connect with the output negative terminal of LC wave filters；The anode of the cathode of diode and the second capacitance
Connection；The anode of second capacitance and the input positive terminal of inverter bridge connect, and the cathode of the second capacitance and the input negative terminal of inverter bridge connect
It connects.
Furthermore it is preferred that structure be, inverter bridge include the second power tube, third power tube, the 4th power tube and the 5th work(
Rate pipe；Wherein, the grid of the grid of the second power tube and the 5th power tube connects respectively with the first output terminal of the second drive module
It connecing, the second output terminal of the grid of the grid of third power tube and the 4th power tube respectively with the second drive module is connect, and second
The source electrode of power tube is connect with the drain electrode of the 4th power tube, and the drain electrode of the second power tube and the output plus terminal of Boost connect
It connects, the drain electrode of third power tube is connect with the drain electrode of the second power tube, the drain electrode of the source electrode of third power tube and the 5th power tube
Connection, the source electrode of the 4th power tube and the output negative terminal of Boost connect, the source electrode and the 4th power tube of the 5th power tube
Source electrode connection.
Furthermore preferred structure is, LCL filter includes third inductance, third capacitance and the 4th inductance；Wherein, third
One end of inductance and the output plus terminal of inverter bridge connect, and the other end of third inductance and the measurement anode of current sensor connect,
The anode of third capacitance and the measurement negative terminal of current sensor connect, and the cathode of third capacitance and the output negative terminal of inverter bridge connect
It connects, one end of the 4th inductance is connect with the anode of third capacitance, the other end of the 4th inductance and the measurement of tertiary voltage sensor
Anode connects.
The control method of the soft grid-connection control device of the permanent magnet direct-drive wind turbine, includes the following steps：
Step 1：Before permanent magnet direct-drive wind turbine is grid-connected, first contactor is closed, carries out the output voltage of permanent magnet direct-drive wind turbine
It adjusts, the MPU controllers is enabled to operate as follows：
At the k moment, the voltage V of the first capacitance is acquired by first voltage sensord(k), pass through second voltage sensor
Acquire the voltage V of the second capacitanceb(k), the first power in Boost is calculated with reference to feed-forward compensator and the first PI controllers
The duty ratio D1 (k) of the pwm control signal of pipe acquires the output voltage V of permanent magnet direct-drive wind turbine by tertiary voltage sensoro
(k), the voltage V of single-phase power grid is acquired by the 4th voltage sensorg(k), it is acquired the in LCL filter by current sensor
The electric current i of three inductanceL(k), the duty ratio D2 (k) of inverter bridge pwm control signal and by SVM prediction model is calculated,
Wherein, electric current i of the first input end of SVM prediction model for the third inductance at k momentL(k), the second input terminal is k
The output voltage V of the permanent magnet direct-drive wind turbine at momento(k), output voltage of the third input terminal for the permanent magnet direct-drive wind turbine at k-1 moment
Vo(k-1), output voltage V of the 4th input terminal for the permanent magnet direct-drive wind turbine at k-2 momento(k-2), the 5th input terminal is the k-1 moment
Inverter bridge pwm control signal duty ratio D2 (k-1), the 6th input terminal accounts for for the inverter bridge pwm control signal at k-2 moment
Sky is than D2 (k-2), voltage V of the 7th input terminal for the single-phase power grid at k momentg(k)；
The output D of above-mentioned feed-forward compensatorb(k) calculation is：
The output D of above-mentioned first PI controllersPI(k) calculation is：
Wherein, Kp1For the scale parameter of the first PI controllers, Ki1For the integral parameter of the first PI controllers, Vb *It is second
The voltage setting value of capacitance；
The calculation of above-mentioned duty ratio D1 (k) is：
D1 (k)=Db(k)+DPI(k)；
Step 2：Second contactor is closed, permanent magnet direct-drive wind turbine output power P is adjusted to a certain using the 2nd PI controllers
Numerical value PT, i.e. the calculation of the duty ratio D2 (k) of inverter bridge pwm control signal is changed to：
Wherein, Kp2For the scale parameter of the 2nd PI controllers, Ki2Integral parameter for the 2nd PI controllers；iL *For third
The current setting value of inductance is in the calculation at k moment：
Wherein, VgmFor single-phase mains voltage VgVirtual value, θ (k) be k moment single-phase mains voltages VgPhase angle；
Then, first contactor is disconnected, to cut off assistant load.
In the control method of the soft grid-connection control device of above-mentioned permanent magnet direct-drive wind turbine, the SVM prediction model
The process of foundation is：
(1) training sample is collected；
A. based on the soft grid-connection control device acquisition operation data of permanent magnet direct-drive wind turbine；
The voltage of the second capacitance is V in Boostb *Operating mode under, be closed first contactor, disconnect second contact
Device acquires the output voltage V of permanent magnet direct-drive wind turbine by tertiary voltage sensoro, acquired by the 4th voltage sensor single-phase
The voltage V of power gridg, pass through the electric current i of third inductance in current sensor acquisition LCL filterL, take the voltage V of single-phase power gridg
For setting value, using single loop PI controllers to the output voltage V of permanent magnet direct-drive wind turbineoIt is controlled, and continuous acquisition M times is forever
The output voltage V of the straight drive blower of magnetico, in LCL filter third inductance electric current iL, single-phase power grid voltage Vg, single loop PI control
The duty ratio D2 for the inverter bridge pwm signal that device processed calculates, so as to form M group operation datas；
B. the operation data construction sample of acquisition is utilized；
For the k moment, the sample constructed is { iL(k), Vo(k), Vo(k-1), Vo(k-2), D2 (k), D2 (k-1), D2
(k-2), Vg(k) }, wherein, iL(k) electric current for third inductance in the LCL filter at k moment, Vo(k) it is straight for the permanent magnetism at k moment
The output voltage of drive blower, Vo(k-1) output voltage for the permanent magnet direct-drive wind turbine at k-1 moment, Vo(k-2) for the k-2 moment forever
The output voltage of the straight drive blower of magnetic, D2 (k) are the duty ratio of inverter bridge pwm signal that the single loop PI controllers at k moment calculate,
D2 (k-1) is the duty ratio of inverter bridge pwm signal that the single loop PI controllers at k-1 moment calculate, and D2 (k-2) is the k-2 moment
Single loop PI controllers calculate inverter bridge pwm signal duty ratio, Vg(k) voltage for the single-phase power grid at k moment.
(2) simultaneously Training Support Vector Machines prediction model is established；
The SVM prediction model for including seven input terminals, output terminal is established, selection Gaussian function is as core
Function, corresponding sample { iL(k), Vo(k), Vo(k-1), Vo(k-2), D2 (k), D2 (k-1), D2 (k-2), Vg(k) }, take its first
A input terminal is iL(k), second input terminal is Vo(k), third input terminal is Vo(k-1), the 4th input terminal is Vo(k-
2), the 5th input terminal is D2 (k-1), and the 6th input terminal is D2 (k-2), and the 7th input terminal is Vg(k), output terminal D2
(k)；
80% in M sample is uniformly extracted as training sample, remaining 20% sample is as test samples, to establishing
SVM prediction model be trained；For prevented study phenomenon or owe study phenomenon, take respectively support to
Gaussian kernel parametric function C=10 in amount machine-1、100、101、102、103；δ2=10-2、10-1、100、101、102, utilize training sample
This is learnt, and calculates the average relative error Δ on test samplesMRE, and select minimum average relative error ΔMRE
Corresponding model is as final prediction model.
Compared with prior art, beneficial effects of the present invention are：
1st, assistant load is introduced in simultaneously net side, makes the grid-connected preceding run with load of permanent magnet direct-drive wind turbine, idle grid connection can be avoided
When stability it is poor the shortcomings that.
2nd, the output voltage of permanent magnet direct-drive wind turbine is controlled by SVM prediction model, its control essence can be effectively improved
Degree, makes its amplitude, frequency, phase are preferably consistent with network voltage, so as to weaken the impact of Parallel Operation on Power System.
Description of the drawings
By reference to the explanation and the content of claims below in conjunction with attached drawing, and with to the present invention more comprehensively
Understand, other purposes of the invention and result will be more apparent and should be readily appreciated that.In the accompanying drawings：
Fig. 1 is the structure chart according to the soft grid-connection control device of the permanent magnet direct-drive wind turbine of the embodiment of the present invention；
Fig. 2 is the prediction-error image on test samples according to the SVM prediction model of the embodiment of the present invention；
Fig. 3 is the grid-connected process simulation curve according to the soft grid-connection control device of the permanent magnet direct-drive wind turbine of the embodiment of the present invention
Figure.
Specific embodiment
In the following description, for purposes of illustration, it in order to provide the comprehensive understanding to one or more embodiments, explains
Many details are stated.It may be evident, however, that these embodiments can also be realized without these specific details.
In other examples, one or more embodiments for ease of description, well known structure and equipment are shown in block form an.
Specific embodiments of the present invention are described in detail below with reference to attached drawing.
As shown in Figure 1, the soft grid-connection control device of permanent magnet direct-drive wind turbine provided in an embodiment of the present invention, including：MPU is controlled
Device 1, rectifier 2, LC wave filters 3, Boost 4, inverter bridge 5, LCL filter 6, assistant load Rz, first contactor
K1, second contactor K2, the first drive module 7, the second drive module 8, first voltage sensor UT1, second voltage sensor
UT2, tertiary voltage sensor UT3, the 4th voltage sensor UT4 and current sensor CT1；Wherein,
The three-phase input end of rectifier 2 is connect with the three-phase output end of permanent magnet direct-drive wind turbine GS, the single-phase output of rectifier 2
Anode is connect with the input positive terminal of LC wave filters 3, and the single-phase output negative terminal of rectifier 2 is connect with the input negative terminal of LC wave filters 3；
The output plus terminal of LC wave filters 3 is connect with the input positive terminal of Boost 4, and output negative terminal and the Boost of LC wave filters 3 become
The input negative terminal connection of parallel operation 4；The output plus terminal of Boost 4 is connect with the input positive terminal of inverter bridge 5, Boost
4 output negative terminal is connect with the input negative terminal of inverter bridge 5；The output plus terminal of inverter bridge 5 connects with the input positive terminal of LCL filter 6
It connects, the output negative terminal of inverter bridge 5 is connect with the input negative terminal of LCL filter 6；The output plus terminal and tertiary voltage of LCL filter 6
The measurement anode connection of sensor UT3, the output negative terminal of LCL filter 6 connect with the measurement negative terminal of tertiary voltage sensor UT3
It connects；One end of first contactor K1 is connect with the output plus terminal of LCL filter 6, and the other end and auxiliary of first contactor K1 is negative
One end connection of Rz is carried, the other end of assistant load Rz is connect with the zero curve terminals of single-phase power grid；The one of second contactor K2
End is connect with the output plus terminal of LCL filter 6, and the other end of second contactor K2 is connect with the hot terminal of single-phase power grid.
The measurement anode of first voltage sensor UT1 is connect with the output plus terminal of LC wave filters 3, first voltage sensor
The measurement negative terminal of UT1 is connect with the output negative terminal of LC wave filters 3, the measuring signal output terminal and MPU of first voltage sensor UT1
Controller 1 connects.
The measurement anode of second voltage sensor UT2 is connect with the output plus terminal of Boost 4, second voltage sensing
The measurement negative terminal of device UT2 is connect with the output negative terminal of Boost 4, the measuring signal output terminal of second voltage sensor UT2
It is connect with MPU controllers 1.
The measurement anode of tertiary voltage sensor UT3 is connect with the output plus terminal of LCL filter 6, tertiary voltage sensor
The measurement negative terminal of UT3 is connect with the output negative terminal of LCL filter 6, the measuring signal output terminal of tertiary voltage sensor UT3 with
MPU controllers 1 connect.
The measurement anode of 4th voltage sensor UT4 is connect with the hot terminal of single-phase power grid, the 4th voltage sensor
The measurement negative terminal of UT4 is connect with the zero curve terminals of single-phase power grid, the measuring signal output terminal of the 4th voltage sensor UT4 with
MPU controllers 1 connect.
The one end of LC wave filters including the first inductance L1 and the first capacitance C1, the first inductance L1 is single-phase defeated with rectifier 2
Go out anode connection, the other end of the first inductance L1 is connect with the anode of the first capacitance C1；The cathode of first capacitance C1 and rectifier 2
Single-phase output negative terminal connection.
In the present invention, rectifier 2 is uncontrollable rectifier device.
Boost 4 includes the second inductance L2, the first power tube Q1, diode D, the second capacitance C2, the second inductance L2
One end connect with the output plus terminal of LC wave filters 3, the other end of the second inductance L2 is connect with the anode of diode D；First work(
The drain electrode of rate pipe Q1 is connect with the anode of diode D, and the output terminal of the grid of the first power tube Q1 and the first drive module 7 connects
It connects, the source electrode of the first power tube Q1 is connect with the output negative terminal of LC wave filters 3；The cathode of diode D and the second capacitance C2 are just
Pole connects；The anode of second capacitance C2 is connect with the input positive terminal of inverter bridge 5, and the cathode of the second capacitance C2 is defeated with inverter bridge 5
Enter negative terminal connection.
Inverter bridge 5 includes the second power tube Q2, third power tube Q3, the 4th power tube Q4 and the 5th power tube Q5；Second
First output terminal of the grid of the grid of power tube Q2 and the 5th power tube Q5 respectively with the second drive module 8 is connect；Third work(
The second output terminal of the grid of rate pipe Q3 and the grid of the 4th power tube Q4 respectively with the second drive module 8 is connect；Second power
The source electrode of pipe Q2 is connect with the drain electrode of the 4th power tube Q4, the drain electrode of the second power tube Q2 and the output plus terminal of Boost 4
Connection, the drain electrode of third power tube Q3 are connect with the drain electrode of the second power tube Q2, the source electrode and the 5th power of third power tube Q3
The drain electrode connection of pipe Q5, the source electrode of the 4th power tube Q4 are connect with the output negative terminal of Boost 4, the 5th power tube Q5's
Source electrode is connect with the source electrode of the 4th power tube Q4.
LCL filter 6 include third inductance L3, third capacitance C3 and the 4th inductance L4, one end of third inductance L3 with it is inverse
Become the output plus terminal connection of bridge 5, the other end of third inductance L3 is connect with the measurement anode of current sensor CT1；Third capacitance
The anode of C3 is connect with the measurement negative terminal of current sensor CT1, and the cathode of third capacitance C3 connects with the output negative terminal of inverter bridge 5
It connects；One end of 4th inductance L4 is connect with the anode of third capacitance C3, the other end and the tertiary voltage sensor of the 4th inductance L4
The measurement anode connection of UT3.
In the specific embodiment of the present invention, for the permanent magnet direct-drive wind-force generation model model machine of a 10kW,
The model of each component：At high performance float-point digital signal of the MPU controllers 1 for the TMS320F28335 models of TI companies production
Manage device；Rectifier 2 is the rectification module of SQL50A/1000V models；First drive module 7 and the second drive module 8 are public for micro- core
Take charge of the driving chip of the MCP14E4-E/P models of production；First power tube Q1 be IRFS4321 types MOSFET, the second to the 5th work(
Rate pipe Q2~Q5 selects the MOSFET of model IPB60R190C6；Assistant load Rz chooses the resistance of 24.2 Ω；First contactor
K1 and second contactor K2 chooses the contactor of CJX2-1210 models；First to fourth voltage sensor UT1~UT4 chooses
The closed loop voltage Hall sensor of CHV-25P models；Current sensor CT1 uses model ACS712ELCTR-05B-T suddenly
That current sensor.
The work step of control method is in the embodiment of the present invention：
Step 1：Before permanent magnet direct-drive wind turbine GS is grid-connected, first contactor K1 is closed, carries out the defeated of permanent magnet direct-drive wind turbine GS
Go out voltage adjusting, the MPU controllers 1 is enabled to operate as follows：
At the k moment, the voltage V of the first capacitance C1 is acquired by first voltage sensor UT1d(k), it is passed by second voltage
Sensor UT2 acquires the voltage V of the second capacitance C2b(k), Boost 4 is calculated with reference to feed-forward compensator and the first PI controllers
In the first power tube Q1 pwm control signal duty ratio D1 (k), pass through tertiary voltage sensor UT3 acquire permanent magnetism direct drive wind
The output voltage V of machine GSo(k), the voltage V of single-phase power grid is acquired by the 4th voltage sensor UT4g(k), pass through current sense
The electric current i of third inductance L3 in device CT1 acquisition LCL filters 6L(k), and pass through SVM prediction model and calculate inverter bridge
The duty ratio D2 (k) of 5 pwm control signal, wherein, the first input end of SVM prediction model is the third at k moment
The electric current i of inductance L3L(k), output voltage V of second input terminal for the permanent magnet direct-drive wind turbine GS at k momento(k), third input terminal
The output voltage V of permanent magnet direct-drive wind turbine GS for the k-1 momento(k-1), the 4th input terminal is the permanent magnet direct-drive wind turbine at k-2 moment
The output voltage V of GSo(k-2), duty ratio D2 (k-1) of the 5th input terminal for the pwm control signal of the inverter bridge 5 at k-1 moment,
Duty ratio D2 (k-2) of 6th input terminal for the pwm control signal of the inverter bridge 5 at k-2 moment, the 7th input terminal are the k moment
The voltage V of single-phase power gridg(k)；
The output D of above-mentioned feed-forward compensatorb(k) calculation is：
The output D of above-mentioned first PI controllersPI(k) calculation is：
Wherein, Kp1For the scale parameter of the first PI controllers, Ki1For the integral parameter of the first PI controllers, Vb *It is second
The voltage setting value of capacitance C2；In the embodiment of the present invention, Kp1=0.01, Ki1=0.08, Vb *=400V；
The calculation of above-mentioned duty ratio D1 (k) is：
D1 (k)=Db(k)+DPI(k)；
Step 2：Be closed second contactor K2, using the 2nd PI controllers adjust permanent magnet direct-drive wind turbine GS output powers P to
A certain numerical value PT, i.e. the calculation of the duty ratio D2 (k) of the pwm control signal of inverter bridge 5 is changed to：
Wherein, Kp2For the scale parameter of the 2nd PI controllers, Ki2Integral parameter for the 2nd PI controllers；In the present invention
In embodiment, the parameter K of the 2nd PI controllersp2=0.005, Ki2=0.01, PT=6kW；iL *Electric current for third inductance L3 is set
Definite value is in the calculation at k moment：
Wherein, VgmFor single-phase mains voltage VgVirtual value, θ (k) be k moment single-phase mains voltages VgPhase angle；
In the present invention, the process of establishing of SVM prediction model is：
(1) training sample is collected
A. based on the soft grid-connection control device acquisition operation data of permanent magnet direct-drive wind turbine；
The voltage of second capacitance C2 is V in Boost 4b *Operating mode under, be closed first contactor K1, disconnect the
Two contactor K2 acquire the output voltage V of permanent magnet direct-drive wind turbine GS by tertiary voltage sensor UT3o, passed by the 4th voltage
Sensor UT4 acquires the voltage V of single-phase power gridg, pass through the electric current of third inductance L3 in current sensor CT1 acquisition LCL filters 6
iL, take the voltage V of single-phase power gridgFor setting value, using single loop PI controllers to the output voltage V of permanent magnet direct-drive wind turbine GSoInto
Row control, and the output voltage V of M permanent magnet direct-drive wind turbine GS of continuous acquisitiono, in LCL filter 6 third inductance L3 electric current iL、
The voltage V of single-phase power gridg, single loop PI controllers calculate inverter bridge pwm signal duty ratio D2, so as to form M groups run
Data；In the embodiment of the present invention, V is takenb *=400V, M=5000 sets the parameter K of single loop PI controllersp=0.008, Ki=
0.05。
B. the operation data construction sample of acquisition is utilized；
For the k moment, the sample constructed is { iL(k), Vo(k), Vo(k-1), Vo(k-2), D2 (k), D2 (k-1), D2
(k-2), Vg(K) }, wherein, iL(k) electric current for third inductance L3 in the LCL filter 6 at k moment, Vo(k) for the k moment forever
The output voltage of the straight drive blower GS of magnetic, Vo(k-1) output voltage for the permanent magnet direct-drive wind turbine GS at k-1 moment, Vo(k-2) it is k-2
The output voltage of the permanent magnet direct-drive wind turbine GS at moment, D2 (k) are the PWM of inverter bridge 5 that the single loop PI controllers at k moment calculate
The duty ratio of signal, D2 (k-1) are the duty ratio of the pwm signal of inverter bridge 5 that the single loop PI controllers at k-1 moment calculate,
The duty ratio of the pwm signal of inverter bridge 5 that D2 (k-2) is calculated for the single loop PI controllers at k-2 moment, Vg(k) it is the k moment
The voltage of single-phase power grid.
(2) simultaneously Training Support Vector Machines prediction model is established
The input space is mapped to the feature space of higher-dimension by Nonlinear Mapping by support vector machines, utilizes a linear letter
Manifold carries out regression estimates.Given sample set(Xk∈RnFor input vector, yk∈ R are corresponding output valve, and N is
Number of samples, n are input vector dimension), the linear regression function used in support vector machines is：
In formula (1), ykIt is exported for linear regression function；It is non-linear from the input space to high-dimensional feature space
Mapping；XkFor input vector；W is weight vector；B is biasing；
It is the Nonlinear Mapping from the input space to high-dimensional feature space, weight vector W and biasing b are by minimizing
Formula (2) calculates：
In formula (2), W is weight vector, the 1stDetermine the generalization ability of regression function；C is penalty factor (C ＞
0), for punishment degree of the control to the sample exceeded；N is number of samples；ξkSlack variable for introducing；ε is error.
Lagrange's equation is established according to formula (2), solve linear regression function is：
In formula (3), K (Xk, Xj) it is kernel function,αjFor Lagrange coefficient,
The α being not zerojCorresponding vector X is known as supporting vector.
After obtaining supporting vector, you can acquire regression function y=f (Xk)。
Select various forms of kernel functions that can generate different support vector machines, common kernel function has：Multinomial letter
Number, Gaussian function, Sigmoid functions etc..It is kernel function that the present invention, which chooses Gaussian function, i.e.,：
In formula (4), δ2Width parameter for gaussian kernel function.
Statistic average relative error Δ is used during the performance of evaluation modelMRE, expression formula is：
In formula (5), ΔMREFor statistic average relative error；Y is the true value of sample；Estimated value for Y.
The SVM prediction model for including seven input terminals, output terminal is established, selection Gaussian function is as core
Function, corresponding sample { iL(k), Vo(k), Vo(k-1), Vo(k-2), D2 (k), D2 (k-1), D2 (k-2), Vg(k) }, take its first
A input terminal is iL(k), second input terminal is Vo(k), third input terminal is Vo(k-1), the 4th input terminal is Vo(k-
2), the 5th input terminal is D2 (k-1), and the 6th input terminal is D2 (k-2), and the 7th input terminal is Vg(k), output terminal D2
(k)；
80% in M sample is uniformly extracted as training sample, remaining 20% sample is as test samples, to establishing
SVM prediction model be trained；For prevented study phenomenon or owe study phenomenon, take respectively support to
Gaussian kernel parametric function C=10 in amount machine-1、100、101、102、-103；δ2=10-2、10-1、100、101、102, utilize training
Sample is learnt, and calculates the average relative error Δ on test samplesMRE, and select minimum average relative error
ΔMRECorresponding model is as final prediction model, in embodiment, minimum average relative error ΔMRE=0.009, it chooses
Its corresponding model is as final prediction model, altogether including 616 supporting vectors, error such as Fig. 2 institutes on test samples
Show, it is known that the model has higher precision of prediction.These supporting vectors are stored in digital signal processor
In case using in the EEPROM of TMS320F28335.
Fig. 3 shows the grid-connected process simulation of the soft grid-connection control device of permanent magnet direct-drive wind turbine according to embodiments of the present invention
Curve.As shown in figure 3, in t=0.02s, first contactor K1 is closed, using SVM prediction model to permanent magnetism direct drive wind
The output voltage V of machine GSoIt is adjusted, it is seen that VoCan in amplitude, frequency, phase with the voltage V of single-phase power gridgPreferably
It is consistent, since second contactor K2 is off, grid-connected current igIt is zero；In t=0.06s, it is closed the second contact
Device K2, it is seen that grid-connected current igSignificant change is not generated, is illustrated to single-phase power grid without impact；In t=0.07s, using the 2nd PI
Controller adjusts permanent magnet direct-drive wind turbine GS output powers P to a certain numerical value PT=6kW；In t=0.10s, first contactor is disconnected
K1 is to cut off assistant load Rz.As it can be seen that it is entire it is grid-connected during, non-impact current generates always, illustrates having for the present invention
Effect property.
Describe the soft and network control according to permanent magnet direct-drive wind turbine proposed by the present invention in an illustrative manner above with reference to attached drawing
Device processed and control method.It will be understood by those skilled in the art, however, that the permanent magnetism direct drive wind proposed for the invention described above
The soft grid-connection control device and control method of machine, can also be on the basis of the content of present invention not be departed to realization details therein
Make various improvement.Therefore, protection scope of the present invention should be determined by the content of appended claims.
Claims (8)
1. a kind of soft grid-connection control device of permanent magnet direct-drive wind turbine, which is characterized in that including：
MPU controllers (1), rectifier (2), LC wave filters (3), Boost (4), inverter bridge (5), LCL filter (6),
First drive module (7), the second drive module (8), assistant load (Rz), first contactor (K1), second contactor (K2),
One voltage sensor (UT1), second voltage sensor (UT2), tertiary voltage sensor (UT3), the 4th voltage sensor (UT4)
With current sensor (CT1)；Wherein,
The three-phase input end of the rectifier (2) is connect with the three-phase output end of permanent magnet direct-drive wind turbine (GS), the rectifier (2)
Single-phase output anode connect with the input positive terminal of the LC wave filters (3), the single-phase output negative terminal of the rectifier (2) and institute
State the input negative terminal connection of LC wave filters (3)；
The output plus terminal of the LC wave filters (3) is connect with the input positive terminal of the Boost (4), the LC wave filters
(3) output negative terminal is connect with the input negative terminal of the Boost (4)；
The output plus terminal of the Boost (5) is connect with the input positive terminal of the inverter bridge (5), the Boost
(5) output negative terminal is connect with the input negative terminal of the inverter bridge (5)；
The output plus terminal of the inverter bridge (5) is connect with the input positive terminal of the LCL filter (6), the inverter bridge (5) it is defeated
The input negative terminal for going out negative terminal with the LCL filter (6) is connect；
The output plus terminal of the LCL filter (6) is connect with the measurement anode of the tertiary voltage sensor (UT3), the LCL
The output negative terminal of wave filter (6) is connect with the measurement negative terminal of the tertiary voltage sensor (UT3)；
One end of the first contactor (K1) is connect with the output plus terminal of the LCL filter (6), the first contactor
(K1) the other end is connect with the one end of the assistant load (Rz), the other end and the single-phase power grid of the assistant load (Rz)
Zero curve terminals connect；
One end of the second contactor (K2) is connect with the output plus terminal of the LCL filter (6), the second contactor
(K2) the other end is connect with the hot terminal of the single-phase power grid；
The measurement anode of the first voltage sensor (UT1) is connect with the output plus terminal of the LC wave filters (3), and described first
The measurement negative terminal of voltage sensor (UT1) is connect with the output negative terminal of the LC wave filters (3), the first voltage sensor
(UT1) measuring signal output terminal is connect with the MPU controllers (1)；
The measurement anode of the second voltage sensor (UT2) is connect with the output plus terminal of the Boost (4), described
The measurement negative terminal of second voltage sensor (UT2) is connect with the output negative terminal of the Boost (4), the second voltage
The measuring signal output terminal of sensor (UT2) is connect with the MPU controllers (1)；
The measurement anode of the tertiary voltage sensor (UT3) is connect with the output plus terminal of the LCL filter (6), and described
The measurement negative terminal of three voltage sensors (UT3) is connect with the output negative terminal of the LCL filter (6), the tertiary voltage sensing
The measuring signal output terminal of device (UT3) is connect with the MPU controllers (1)；
The measurement anode of 4th voltage sensor (UT4) is connect with the hot terminal of the single-phase power grid, and the described 4th
The measurement negative terminal of voltage sensor (UT4) is connect with the zero curve terminals of the single-phase power grid, the 4th voltage sensor
(UT4) measuring signal output terminal is connect with the MPU controllers (1)；
The measurement anode and measurement negative terminal of the current sensor (CT1) are connect respectively with the LCL filter (6), the electricity
The measuring signal output terminal of flow sensor (CT1) is connect with the MPU controllers (1)；
The input terminal of first drive module (7) is connect with the MPU controllers (1), first drive module (7) it is defeated
Outlet is connect with the Boost (4)；
The input terminal of second drive module (8) is connect with the MPU controllers (1), and the two of second drive module (8)
A output terminal is connect respectively with the inverter bridge (5).
2. the soft grid-connection control device of permanent magnet direct-drive wind turbine described in claim 1, which is characterized in that
The LC wave filters (3) include the first inductance (L1) and the first capacitance (C1)；Wherein, one end of first inductance (L1)
It is connect with the single-phase output anode of the rectifier (2), the other end of first inductance (L1) and first capacitance (C1)
Anode connection, the cathode of first capacitance (C1) connect with the single-phase output negative terminal of the rectifier (2).
3. the soft grid-connection control device of the permanent magnet direct-drive wind turbine described in claim 2, which is characterized in that the rectifier (2) is
Uncontrollable rectifier device.
4. the soft grid-connection control device of permanent magnet direct-drive wind turbine described in claim 1, which is characterized in that
The Boost (4) includes the second inductance (L2), the first power tube (Q1), diode (D) and the second capacitance
(C2)；Wherein, one end of second inductance (L2) is connect with the output plus terminal of the LC wave filters (3), second inductance
(L2) the other end is connect with the anode of the diode (D), drain electrode and the diode (D) of first power tube (Q1)
Anode connection, the grid of first power tube (Q1) connect with the output terminal of first drive module (7), described first
The source electrode of power tube (Q1) is connect with the output negative terminal of the LC wave filters (3)；The cathode and described second of the diode (D)
The anode connection of capacitance (C2)；The anode of second capacitance (C2) is connect with the input positive terminal of the inverter bridge (5), and described
The cathode of two capacitances (C2) is connect with the input negative terminal of the inverter bridge (5).
5. the soft grid-connection control device of permanent magnet direct-drive wind turbine described in claim 1, which is characterized in that
The inverter bridge (5) includes the second power tube (Q2), third power tube (Q3), the 4th power tube (Q4) and the 5th power tube
(Q5)；Wherein, the grid of second power tube (Q2) and the grid of the 5th power tube (Q5) drive respectively with described second
The first output terminal connection of dynamic model block (8), the grid of the third power tube (Q3) and the grid of the 4th power tube (Q4)
The second output terminal with second drive module (8) is connect respectively, the source electrode and the described 4th of second power tube (Q2)
The drain electrode connection of power tube (Q4), the drain electrode of second power tube (Q2) connect with the output plus terminal of the Boost (4)
It connects, the drain electrode of the third power tube (Q3) is connect with the drain electrode of second power tube (Q2), the third power tube (Q3)
Source electrode connect with the drain electrode of the 5th power tube (Q5), the source electrode of the 4th power tube (Q4) is converted with the Boost
The output negative terminal connection of device (4), the source electrode of the 5th power tube (Q5) are connect with the source electrode of the 4th power tube (Q4).
6. the soft grid-connection control device of permanent magnet direct-drive wind turbine described in claim 1, which is characterized in that
The LCL filter (6) includes third inductance (L3), third capacitance (C3) and the 4th inductance (L4)；Wherein, the third
One end of inductance (L3) is connect with the output plus terminal of the inverter bridge (5), the other end and the electricity of the third inductance (L3)
The measurement anode connection of flow sensor (CT1), the anode of the third capacitance (C3) and the measurement of the current sensor (CT1)
Negative terminal connects, and the cathode of the third capacitance (C3) is connect with the output negative terminal of the inverter bridge (5), the 4th inductance (L4)
One end connect with the anode of the third capacitance (C3), the other end of the 4th inductance (L4) is sensed with the tertiary voltage
The measurement anode connection of device (UT3).
7. the soft grid-connection control device of permanent magnet direct-drive wind turbine described in claim 1, it is characterised in that the work of its control method
Step is,
Step 1：Before permanent magnet direct-drive wind turbine (GS) is grid-connected, first contactor (K1) is closed, carries out permanent magnet direct-drive wind turbine (GS)
Output voltage is adjusted, and the MPU controllers (1) is enabled to operate as follows：
At the k moment, the voltage V of the first capacitance (C1) is acquired by first voltage sensor (UT1)d(k), it is passed by second voltage
Sensor (UT2) acquires the voltage V of the second capacitance (C2)b(k), Boost is calculated with reference to feed-forward compensator and the first PI controllers to become
The duty ratio D1 (k) of the pwm control signal of first power tube (Q1) in parallel operation (4) is acquired by tertiary voltage sensor (UT3)
The output voltage V of permanent magnet direct-drive wind turbine (GS)o(k), the voltage V of single-phase power grid is acquired by the 4th voltage sensor (UT4)g
(k), the electric current i of third inductance (L3) in LCL filter (6) is acquired by current sensor (CT1)L(k), and pass through support to
Amount machine prediction model calculates the duty ratio D2 (k) of inverter bridge (5) pwm control signal, wherein, the of SVM prediction model
Electric current i of one input terminal for the third inductance (L3) at k momentL(k), the second input terminal is the permanent magnet direct-drive wind turbine (GS) at k moment
Output voltage Vo(k), output voltage V of the third input terminal for the permanent magnet direct-drive wind turbine (GS) at k-1 momento(k-1), the 4th is defeated
Enter output voltage V of the end for the permanent magnet direct-drive wind turbine (GS) at k-2 momento(k-2), the 5th input terminal is the inverter bridge at k-1 moment
(5) the duty ratio D2 (k-1) of pwm control signal, duty of the 6th input terminal for inverter bridge (5) pwm control signal at k-2 moment
Than D2 (k-2), voltage V of the 7th input terminal for the single-phase power grid at k momentg(k)；
The output D of above-mentioned feed-forward compensatorb(k) calculation is：
The output D of above-mentioned first PI controllersPI(k) calculation is：
Wherein, Kp1For the scale parameter of the first PI controllers, Ki1For the integral parameter of the first PI controllers, Vb *For the second capacitance
(C2) voltage setting value；
The calculation of above-mentioned duty ratio D1 (k) is：
D1 (k)=Db(k)+DPI(k)；
Step 2：Be closed second contactor (K2), using the 2nd PI controllers adjust permanent magnet direct-drive wind turbine (GS) output power P to
A certain numerical value PT, i.e. the calculation of the duty ratio D2 (k) of inverter bridge (5) pwm control signal is changed to：
Wherein, Kp2For the scale parameter of the 2nd PI controllers, Ki2Integral parameter for the 2nd PI controllers；iL *For third inductance
(L3) current setting value is in the calculation at k moment：
Wherein, VgmFor single-phase mains voltage VgVirtual value, θ (k) be k moment single-phase mains voltages VgPhase angle；
Then, first contactor (K1) is disconnected, to cut off assistant load (Rz).
8. the control method of the soft grid-connection control device of the permanent magnet direct-drive wind turbine described in claim 7, it is characterised in that the branch
The process of establishing for holding vector machine forecast model includes the following steps：
Step 1：Training sample is collected, specially：
Step a. is based on the soft grid-connection control device acquisition operation data of permanent magnet direct-drive wind turbine；
The voltage of the second capacitance (C2) is V in Boost (4)b *Operating mode under, be closed first contactor (K1), disconnect
Second contactor (K2) acquires the output voltage V of permanent magnet direct-drive wind turbine (GS) by tertiary voltage sensor (UT3)o, pass through
Four voltage sensors (UT4) acquire the voltage V of single-phase power gridg, the is acquired in LCL filter (6) by current sensor (CT1)
The electric current i of three inductance (L3)L, take the voltage V of single-phase power gridgFor setting value, using single loop PI controllers to permanent magnet direct-drive wind turbine
(GS) output voltage VoIt is controlled, and the output voltage V of M permanent magnet direct-drive wind turbine (GS) of continuous acquisitiono, LCL filter
(6) the electric current i of third inductance (L3) inL, single-phase power grid voltage Vg, single loop PI controllers calculate inverter bridge (5) PWM letter
Number duty ratio D2, so as to form M group operation datas；
Step b. constructs sample using the operation data of acquisition；
For the k moment, the sample constructed is { iL(k), Vo(k), Vo(k-1), Vo(k-2), D2 (k), D2 (k-1), D2 (k-2),
Vg(k) }, wherein, iL(k) electric current for third inductance (L3) in the LCL filter (6) at k moment, Vo(k) it is the permanent magnetism at k moment
The output voltage of straight drive blower (GS), Vo(k-1) output voltage for the permanent magnet direct-drive wind turbine (GS) at k-1 moment, Vo(k-2) it is
The output voltage of the permanent magnet direct-drive wind turbine (GS) at k-2 moment, D2 (k) are the inverter bridge that the single loop PI controllers at k moment calculate
(5) duty ratio of pwm signal, D2 (k-1) are accounting for for inverter bridge (5) pwm signal that the single loop PI controllers at k-1 moment calculate
Empty ratio, the duty ratio of inverter bridge (5) pwm signal that D2 (k-2) is calculated for the single loop PI controllers at k-2 moment, Vg(k) it is k
The voltage of the single-phase power grid at moment；
Step 2：Establish simultaneously Training Support Vector Machines prediction model；
Establish the SVM prediction model for including seven input terminals, output terminal, selection Gaussian function as kernel function,
Corresponding sample { iL(k), Vo(k), Vo(k-1), Vo(k-2), D2 (k), D2 (k-1), D2 (k-2), Vg(k) }, take its first it is defeated
Enter end for iL(k), second input terminal is Vo(k), third input terminal is Vo(k-1), the 4th input terminal is Vo(k-2),
Five input terminals are D2 (k-1), and the 6th input terminal is D2 (k-2), and the 7th input terminal is Vg(k), output terminal is D2 (k)；
80% in M sample is uniformly extracted as training sample, remaining 20% sample is as test samples, to the branch of foundation
Vector machine forecast model is held to be trained；To prevent study phenomenon or owing study phenomenon, support vector machines is taken respectively
In Gaussian kernel parametric function C=10-1、100、101、102、103；δ2=10-2、10-1、100、101、102, using training sample into
Row study, calculates the average relative error Δ on test samplesMRE, and select minimum average relative error ΔMREIt is corresponding
Model as final prediction model.
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| RU2726156C1 (en) * | 2019-03-18 | 2020-07-09 | Федеральное государственное унитарное предприятие "Крыловский государственный научный центр" | Boosting voltage rectifier |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2004274893A (en) * | 2003-03-10 | 2004-09-30 | Sharp Corp | Inverter arrangement |
| CN103138291A (en) * | 2013-03-06 | 2013-06-05 | 杨勇 | Wind power generation intelligent single-phase grid-connection controller |
| CN103414330A (en) * | 2013-08-21 | 2013-11-27 | 西安龙腾新能源科技发展有限公司 | Method for restraining grid-connected current spikes of single-phase grid-connected inverter |
| CN103441526A (en) * | 2013-08-14 | 2013-12-11 | 华北电力大学（保定） | Grid-connected off-grid small photovoltaic power generation system and control method |
| CN104967353A (en) * | 2015-07-08 | 2015-10-07 | 华北电力大学（保定） | Off-grid type wind power generation inverter |
| CN106160610A (en) * | 2016-07-14 | 2016-11-23 | 江苏大学 | A kind of building method of Active suspension electromagnetic actuator intelligent controller |
-
2016
- 2016-12-08 CN CN201611120210.XA patent/CN108173279A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2004274893A (en) * | 2003-03-10 | 2004-09-30 | Sharp Corp | Inverter arrangement |
| CN103138291A (en) * | 2013-03-06 | 2013-06-05 | 杨勇 | Wind power generation intelligent single-phase grid-connection controller |
| CN103441526A (en) * | 2013-08-14 | 2013-12-11 | 华北电力大学（保定） | Grid-connected off-grid small photovoltaic power generation system and control method |
| CN103414330A (en) * | 2013-08-21 | 2013-11-27 | 西安龙腾新能源科技发展有限公司 | Method for restraining grid-connected current spikes of single-phase grid-connected inverter |
| CN104967353A (en) * | 2015-07-08 | 2015-10-07 | 华北电力大学（保定） | Off-grid type wind power generation inverter |
| CN106160610A (en) * | 2016-07-14 | 2016-11-23 | 江苏大学 | A kind of building method of Active suspension electromagnetic actuator intelligent controller |
Non-Patent Citations (3)
| Title |
|---|
| WEILIANG LIU ET AL.: "Grid current control of flyback type Micro Inverter based on FASVM", 《2016 35TH CHINESE CONTROL CONFERENCE (CCC)》 * |
| 李继森 等: "基于支持向量机的储能逆变器电压控制策略研究", 《电力科学与工程》 * |
| 蔡逢煌 等: "小型永磁直驱风力发电并网变流器的控制方法", 《电源学报》 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| RU2726156C1 (en) * | 2019-03-18 | 2020-07-09 | Федеральное государственное унитарное предприятие "Крыловский государственный научный центр" | Boosting voltage rectifier |
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