CN107612047A - The power module Predictive Control System and its control method of brushless double feed generator - Google Patents

The power module Predictive Control System and its control method of brushless double feed generator Download PDF

Info

Publication number
CN107612047A
CN107612047A CN201710934617.4A CN201710934617A CN107612047A CN 107612047 A CN107612047 A CN 107612047A CN 201710934617 A CN201710934617 A CN 201710934617A CN 107612047 A CN107612047 A CN 107612047A
Authority
CN
China
Prior art keywords
power
mrow
msub
winding
module
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.)
Pending
Application number
CN201710934617.4A
Other languages
Chinese (zh)
Inventor
程明
魏新迟
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Southeast University
Original Assignee
Southeast University
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by Southeast University filed Critical Southeast University
Priority to CN201710934617.4A priority Critical patent/CN107612047A/en
Publication of CN107612047A publication Critical patent/CN107612047A/en
Pending legal-status Critical Current

Links

Landscapes

  • Control Of Eletrric Generators (AREA)

Abstract

The invention discloses the power module Predictive Control System and its control method of a kind of brushless double feed generator, the k moment power winding voltages and electric current input power estimation module and power prediction module gathered；The k moment DC bus-bar voltages gathered are connected to voltage structure module, the voltage vector input power prediction module of structure；The k moment controling winding electric currents and rotary speed information input power prediction module gathered；The k+1 moment power winding complex powers that power prediction module obtains are connected to cost function optimization module；Exported by the on off state that cost function optimization module obtains as optimal come drive control winding side power inverter, realize the control to brushless double feed generator.Power module forecast Control Algorithm provided by the invention, solve the problems, such as to be difficult to active power and the accurate control of reactive power and uneoupled control in conventional brush-less double feedback electric engine control algolithm, it is properer in brushless dual-feed motor high-order, non-linear, close coupling characteristic.

Description

The power module Predictive Control System and its control method of brushless double feed generator
Technical field
The present invention relates to the power module Predictive Control System and its control method of a kind of brushless double feed generator, belong to nothing Brush double feedback electric engine technical field of power generation control.
Background technology
With the increase of demand and the development of energy industry, variable speed constant frequency generator system is sent out progressively towards hicap Exhibition, and be more likely to installation at sea, the remote districts such as mountain area.Therefore, high reliability, the variable speed constant frequency generator system of low cost Will be more competitive.Brushless dual-feed motor has two alternating-current feeding ports and a mechanical ports, passes through the side of stator excitation Formula realizes non-brushing, has the advantages that reliability is high, maintenance cost is low, required power inverter capacity is small, turns into and become in recent years A kind of novel AC that constant frequency generation field is paid close attention to.But because the complex electromagnetism of brushless dual-feed motor closes System, it controls difficulty larger, and this is also the main barrier for restricting its development.Research to brushless dual-feed motor control performance turns into One problem urgently broken through.
Occur mainly having for the generate electricity by way of merging two or more grid systems control method of operation of brushless dual-feed motor at present：
1. vector control method.The vector controlled of brushless double feed generator has controling winding current inner loop, active power With the cascaded control structure of reactive power outer shroud, voltage/flux linkage orientation of power winding is typically based on, by controling winding electric current line Property resolve into active and reactive current component and be independently controlled.The vector control method is based on modulator calculating power device and existed One controlling cycle turns on and off the time, is generally melted into independent continuous voltage source by power inverter is preferable.In addition, this The double-closed-loop control structure of kind linearisation needs to make mediation between stability and dynamic response, and dynamic property is significantly limited, And it is difficult to realize the full decoupled control of active power and reactive power.
2. direct Power Control method.The direct Power Control of brushless double feed generator is by selecting suitable converter shape The error for controlling variable set-point and value of feedback is limited in given bandwidth range by state, it is not necessary to current regulator, coordinate Conversion and PWM signal generator, the direct contact that can be established between control variable and power device on off state, properer work( The discrete feature of rate converter.Compared to vector control strategy, the control structure of direct Power Control method is simple, robustness By force, transient performance greatly improves.But selected in direct Power Control using a heuristic vector table in some regions Vector be invalid or even wrong, the accurate control of power can not be ensured, therefore power pulsations are larger.
The content of the invention
The present invention proposes a kind of power module of brushless double feed generator to overcome technological deficiency present in prior art Predictive Control System and its forecast Control Algorithm, the power module of foundation it is properer in brushless dual-feed motor high-order, it is non-linear, strong The characteristic of coupling, realize brushless double feed generator active power and the accurate control of reactive power and uneoupled control.
In order to solve the above technical problems, the invention provides a kind of power module PREDICTIVE CONTROL system of brushless double feed generator System, including three phase network, brushless dual-feed motor, controling winding side power inverter, DC bus capacitor, power winding side power become Parallel operation, power winding voltages measuring cell, power winding current measuring cell, controling winding current measurement device, DC side electricity Press measuring cell, brushless dual-feed motor speed measuring element, power winding complex power estimation block, voltage vector structure module, Power prediction module and cost function optimization module；
Power winding is connected to three phase network, controling winding Access Control winding side power inverter, controling winding side work( Rate converter is connected by DC bus capacitor with power winding side power inverter, and power winding side power inverter is connected to work( Rate winding；
Power winding voltages measuring cell and power winding current measuring cell be arranged on power winding and three phase network it Between, it is respectively used for measuring power winding voltages and electric current, and the power winding voltages measuring cell and power winding current measurement The output access power winding complex power estimation block of element；
Controling winding current measurement device is arranged between controling winding and controling winding side power inverter, for measuring Controling winding electric current；
DC voltage measuring cell be arranged on controling winding side power inverter and power winding side power inverter it Between, for measuring DC voltage, and input of the output of the DC voltage measuring cell as voltage vector structure module；
Brushless dual-feed motor speed measuring element is arranged in brushless dual-feed motor rotating shaft, for the rotating speed of measurement motor；
Controling winding current measurement device, brushless dual-feed motor speed measuring element, Power estimation module and voltage vector The output end of structure module is connected to the input of power prediction module；The output access cost function of power prediction module is excellent Change module, while value of import function optimization module also includes power winding complex power set-point, cost function optimization module Obtained on off state carrys out drive control winding side power inverter as optimal output, realizes the control to brushless double feed generator System.
Present invention also offers a kind of brushless double feed generator power module forecast Control Algorithm, comprise the following steps：
Step 1：Measure k moment power winding voltages uspAnd electric current i (k)sp(k), controling winding electric current isc(k), direct current Side voltage udcAnd rotary speed information ω (k)m(k)；
Step 2：By the k moment power winding voltages u measured in step 1spAnd electric current i (k)sp(k), according to formula (1) Estimate k moment power winding complex powers Sp(k)：
In formula, uspAnd i (k)sp(k) voltage and current of k moment power windings, S are represented respectivelyp(k) k moment power is represented The complex power of winding；
Step 3：By the k moment DC voltages u measured in step 1dc(k), with reference to controling winding side power conversion The switching tube state of device, structure are input to the voltage vector v of power prediction modeli(k)：
In formula, sa,b,cRepresent the switching tube state of controling winding side power inverter, udc(k) k moment DC side electricity is represented Pressure, vi(k) the k moment voltage vectors of structure are represented；
Step 4：By the power winding voltages u measured in step 1spAnd electric current i (k)sp(k), controling winding electric current isc (k), DC voltage udcAnd rotary speed information ω (k)m(k), k moment power winding complex power S in step 2pAnd step 3 (k) The voltage vector v of middle structurei(k) the complex power S of k+1 moment power windings, is predictedp(k+1)i；
Step 5：The cost function optimization of brushless double feed generator power module predictive control algorithm, is specifically included following Step：
1st, the control targe that brushless dual-feed motor generates electricity by way of merging two or more grid systems when running is the active power and reactive power of power winding, It is as follows that desired control targe by the restriction of weight coefficient is converted into single cost function：
In formula, k ∈ N are sampling instant；Active power set-point Pp refWith reactive power set-point Qp refSelection by power network Demand determines；The predicted value P of k+1 moment active powerp(k+1)iWith the predicted value Q of reactive powerp(k+1)iCan be by step 4 The S measured in advancep(k+1)iThe decomposition for carrying out real and imaginary parts obtains；δ be weigh active power and Reactive Power Control weight be Number；
2nd, with the minimum optimizing index of cost function so that cost function CiMinimum voltage vector viAs optimal voltage Vector；
Step 6：According to the voltage vector that the cost function minimum optimizing index defined in step 5 selects as control The output of device, obtain corresponding drive signal and the switching tube of controling winding side converter is driven.
Step 4 specifically includes following steps：
A, power winding current i is chosensp, controling winding electric current iscWith power winding magnetic linkage ψspFor state variable, nothing is established The state-space equation of brush double feedback electric engine mathematical modeling is：
SX=AX+BV (3)
In formula, s is differential operator；X=[ispiscψsp]T, wherein, isp,isc,ψspIt is power winding current, control respectively Winding current and power winding magnetic linkage；V=[uspuscur]T, wherein, usp,usc,urIt is power winding voltages, controling winding respectively Voltage and rotor voltage；A and B is 3 × 3 matrixes, includes the electricity of brushless double-fed acc power winding, controling winding and rotor windings Resistance and inductance parameters and rotary speed information；
B, the state-space equation based on the brushless dual-feed motor obtained in step a, and combine power winding complex power table Up to formulaThe power module for obtaining brushless dual-feed motor is：
In formula, s is differential operator；uspAnd uscPower winding voltages and controling winding voltage are represented respectively；iscRepresent control Winding current；SpRepresent the complex power of power winding；Λ1、Λ2、Λ3And Λ4Be with the resistance of brushless dual-feed motor, inductance and turn The related coefficient entry of fast information；
C, to Euler's sliding-model control, will be obtained before the power module progress single order of the brushless dual-feed motor obtained in step b To with input voltage vector vi(k) predictor formula of k+1 moment complex powers is corresponding to：
In formula, k ∈ N are sampling instant；TsFor the sampling period；uspAnd uscPower winding voltages and controling winding are represented respectively Voltage；iscRepresent controling winding electric current；SpRepresent the complex power of power winding；viRepresent input voltage vector；Coefficient entry Λ1、 Λ2、Λ3And Λ4Same formula (4).
Beneficial effect：Compared with prior art, the power module of brushless double feed generator provided by the invention is pre- by the present invention Control system and its control method are surveyed, solves and active power and idle is difficult in conventional brush-less double feedback electric engine control algolithm It is the problem of accurate control of power and uneoupled control, properer in brushless dual-feed motor high-order, non-linear, close coupling characteristic. Have the following advantages that：
1st, control structure is simple, has quick power dynamic response.
The vector controlled of brushless double feed generator has power outer shroud, the double circle structure of current inner loop, it is necessary to cumbersome PI parameters are adjusted, mediation is made between steady-state behaviour and dynamic response.Method provided by the invention directly establishes on off state Non-linear relation between power, control structure is simple, without modulator, without parameter regulation, there is quick power to move State is corresponding.
2nd, the accurate control of active power and reactive power can be realized.
Compared to the direct Power Control of brushless double feed generator, method provided by the invention is with accurate power module generation For heuristic vector table, it is invalid or even wrong ask to avoid the vector selected in direct Power Control in some operation areas Topic, the accurate control of power is can effectively ensure that, reduce power pulsations.
3rd, the complete all characteristics for containing motor, can realize active and reactive power uneoupled control.
Existing brushless dual-feed motor vector controlled and direct Power Control method are by simplifying or ignoring rotor Influence to design controller.Method provided by the invention contains all parameter characteristics including rotor influences, and establishes The full rank power module of brushless double feed generator, it can really realize the uneoupled control of active power and reactive power.
Brief description of the drawings
Fig. 1 is the structural representation of brushless double feed generator power module forecast Control Algorithm provided by the invention.
Fig. 2 is the flow signal that brushless double feed generator power module forecast Control Algorithm provided by the invention performs step Figure.
Fig. 3 is motor operation in 600r/m, active power and reactive power to the simulation result under the conditions of being fixed value.
Fig. 4 is emulation knot of the motor operation under the conditions of 600r/m, active power and reactive power set-point Spline smoothing Fruit.
Fig. 5 be motor from metasynchronism speed 500r/m to supersynchronous fast 1000r/m variable-speed operations, active power is given sinusoidal becomes Change, the simulation result under the conditions of the given Spline smoothing of reactive power.
Embodiment
The present invention is further described below in conjunction with the accompanying drawings.
Here, coaxially being cascaded with two wound-rotor induction machines, the connected mode of its rotor windings negative-phase sequence forms one Platform brushless dual-feed motor.It is referred to as power motor with the motor that power network is joined directly together, its stator winding is power winding；With converter The motor being joined directly together is referred to as controlled motor, and its stator winding is controling winding.
As shown in figure 1, implementing brushless double feed generator power module forecast Control Algorithm of the present invention, it is realized should The device of method is by three phase network 1 (380V, 50Hz), brushless dual-feed motor 2, controling winding side power inverter 3, DC side Electric capacity 4, power winding side power inverter 5, power winding voltages measuring cell 6, power winding current measuring cell 7, control The multiple work(of winding current measuring cell 8, DC voltage measuring cell 9, brushless dual-feed motor speed measuring element 10, power winding Rate estimation block 11, voltage vector structure module 12, power prediction module 13 and cost function optimization module 14 are formed.Power around Group is connected to three phase network 1, and controling winding Access Control winding side power inverter 3, controling winding side power inverter 3 passes through Middle DC bus capacitor 4 is connected with power winding side power inverter 5, and power winding side power inverter 5 is connected to power Winding.Power winding voltages measuring cell 6 and power winding current measuring cell 7 between power winding and three phase network 1 divide Power winding voltages u Yong Lai not measuredspWith electric current isp, control between controling winding and controling winding side power inverter 3 around Group current measurement device 8 is used for measuring controling winding electric current isc, controling winding side power inverter 3 and power winding side power become DC voltage measuring cell 9 between parallel operation 5 is used for measuring DC voltage udc, it is brushless in the rotating shaft of brushless dual-feed motor 2 Double feedback electric engine speed measuring element 10 is used for the rotational speed omega of measurement motorm.Power winding voltages u during the k measuredsp(k) it is and electric Flow isp(k) the complex power S that k moment work(windings to power winding complex power estimation block 11, are calculated is inputtedp(k) work(is accessed Rate prediction module 13.Also to input to the k moment power winding voltages u that measures of having of power prediction module 13spAnd electric current (k) isp(k), controling winding electric current isc(k), DC voltage udc(k), rotary speed information ωmAnd voltage vector v (k)i(k), wherein electricity Press vector vi(k) obtained by voltage vector structure module 12.Power prediction module 13 predicts obtain and viThe corresponding k+1 moment Power winding complex power Sp(k+1)iCost function optimization module 14 is accessed, is equally inputted as cost function optimization module 14 Also k+1 moment power winding complex power set-point Sref(k+1).The on off state obtained by cost function optimization module 14 is made Carry out drive control winding side power inverter 3 for the output of controller, realize the control to brushless double feed generator.
As shown in Fig. 2 the execution step for realizing above-mentioned brushless double feed generator power module forecast Control Algorithm is specially：
Step 1：Measure k moment power winding voltages uspAnd electric current i (k)sp(k), controling winding electric current isc(k), direct current Side voltage udcAnd rotary speed information ω (k)m(k)。
Step 2：By the k moment power winding voltages u measured in step 1spAnd electric current i (k)sp(k) the k moment, is estimated Power winding complex power Sp(k) it is as follows：
In formula, uspAnd i (k)sp(k) voltage and current of k moment power windings, S are represented respectivelyp(k) k moment power is represented The complex power of winding.
Step 3：By the k moment DC voltages u measured in step 1dc(k), with reference to controling winding side power conversion The switching tube state of device, structure are input to the voltage vector v of power prediction modeli(k), the present embodiment is based on two level voltage types Converter, sa,b,cWith (0,0,0) to (1,1,1) 8 kinds of states：
In formula, sa,b,cRepresent the switching tube state of controling winding side power inverter, udc(k) k moment DC side electricity is represented Pressure, vi(k) the k moment voltage vectors of structure are represented.
Step 4：By the u measured in step 1sp(k)、isp(k)、isc(k)、udcAnd ω (k)m(k), estimate in step 2 The S of calculationp(k) v, built in step 3i(k) the complex power S of k+1 moment power windings, is predictedp(k+1)i, it is specially：
(a) power winding current i is chosensp, controling winding electric current iscWith power winding magnetic linkage ψspFor state variable, establish The state-space equation of brushless dual-feed motor mathematical modeling is：
SX=AX+BV (3)
In formula, s is differential operator；X=[ispiscψsp]T, wherein, isp,isc,ψspIt is power winding current, control respectively Winding current and power winding magnetic linkage；V=[uspuscur]T, wherein, usp,usc,urIt is power winding voltages, controling winding respectively Voltage and rotor voltage, for brushless dual-feed motor, its rotor is typically that the closure of special cage modle or winding-type structure is returned Road, rotor voltage ur=0, controling winding voltage uscEqual to voltage vector vi；A and B is 3 × 3 matrixes, respectively comprising matrix element AijAnd Bij, wherein, subscript i represents row, and j represents row, and expression is as follows：
Wherein, λ=1/ (LspLscLr-LspLmc 2-LscLmp 2), LspAnd LmpThe self-induction and excitation electricity of power winding are represented respectively Sense, LscAnd LmcThe self-induction and magnetizing inductance of controling winding, L are represented respectivelyrRepresent the self-induction of rotor windings, Rsp, RscAnd RrRespectively Represent the resistance of power winding, controling winding and rotor windings, ppAnd pcThe extremely right of power winding and controling winding is represented respectively Number, ωmRepresent the rotor machinery angular speed of brushless dual-feed motor.
(b) state-space equation of brushless dual-feed motor obtained in step (a) is based on, and combines power winding complex power Expression formulaThe power module for obtaining brushless dual-feed motor is：
In formula, s is differential operator；uspAnd uscPower winding voltages and controling winding voltage are represented respectively；iscRepresent control Winding current；SpRepresent the complex power of power winding；Coefficient entry Λ1,Λ2,Λ3,andΛ4Expression formula it is as follows：
Wherein, λ=1/ (LspLscLr-LspLmc 2-LscLmp 2), LspAnd LmpThe self-induction and excitation electricity of power winding are represented respectively Sense, LscAnd LmcThe self-induction and magnetizing inductance of controling winding, L are represented respectivelyrRepresent the self-induction of rotor windings, Rsp, RscAnd RrRespectively Represent the resistance of power winding, controling winding and rotor windings, ppAnd pcThe extremely right of power winding and controling winding is represented respectively Number, ωmRepresent the rotor machinery angular speed of brushless dual-feed motor, ωpRepresent the angular frequency of power winding voltages/electric current.
(c) power module of the brushless dual-feed motor obtained in step (b) is carried out before single order to Euler's sliding-model control, It can obtain and input voltage vector vi(k) predictor formula of k+1 moment complex powers is corresponding to：
In formula, k ∈ N are sampling instant；TsFor the sampling period；uspAnd uscPower winding voltages and controling winding are represented respectively Voltage；iscRepresent controling winding electric current；SpRepresent the complex power of power winding；viRepresent input voltage vector；Coefficient entry Λ1, Λ2,Λ3,andΛ4The same formula of expression formula (4) in definition.
Step 5：The cost function optimization of brushless double feed generator power module predictive control algorithm, it is specially：
(a) active power and idle work(of the control targe that brushless dual-feed motor generates electricity by way of merging two or more grid systems when running for power winding Rate, it is as follows desired control targe by the restriction of weight coefficient can be converted to single cost function
In formula, k ∈ N are sampling instant；Active power set-point Pp refWith reactive power set-point Qp refSelection by power network Demand determines；The predicted value P of k+1 moment active powerp(k+1)iWith the predicted value Q of reactive powerp(k+1)iCan be by step 4 The S measured in advancep(k+1)iThe decomposition for carrying out real and imaginary parts obtains；δ be weigh active power and Reactive Power Control weight be Number, the present embodiment consider δ=1, namely distribute same control weight to active power and reactive power.
(b) with the minimum optimizing index of cost function so that cost function CiMinimum voltage vector viAs optimal voltage Vector.
Step 6：According to the voltage vector that the cost function minimum optimizing index defined in step 5 selects as control The output of device, obtain corresponding drive signal and the switching tube of controling winding side converter is driven.
Using the brushless double feed generator power module forecast Control Algorithm described in the present embodiment simulation result such as Fig. 3~ Shown in Fig. 5.The model machine parameter used in emulation is as follows：The number of pole-pairs of power/controling winding is 2；The rated power of power winding For 20kW, the rated power of controling winding is 10kW；The resistance of power/controling winding is 0.207 Ω；The resistance of rotor windings is 0.218Ω；The inductance of power/controling winding excitation is 85.003mH；The leakage inductance of power/controling winding is 2.426mH.Fig. 3 is For motor operation in 600r/m, active power is given as -10kW, and reactive power is given as the simulation result under the conditions of 0kvar.Fig. 4 - 10kW is stepped to, in 0.7s steps to -5kW, nothing by -5kW in 0.3s in 600r/m, active power set-point for motor operation Work(power set-point is stepped to 2kvar, the simulation result under the conditions of 0.8s steps to -2kvar by 0kvar in 0.5s.Fig. 5 is Motor is from metasynchronism speed 500r/m to supersynchronous fast 1000r/m variable-speed operations, the given change sinusoidal from 0kW to -20kW of active power Change, reactive power set-point is stepped to 2kvar, the simulation result under the conditions of 0.8s steps to -2kvar by 0kvar in 0.4s. As a result show, the brushless double feed generator power module forecast Control Algorithm of the present embodiment has quick dynamic response and excellent Steady-state behaviour, accurate Power Control and good uneoupled control effect can be realized under stable state and current intelligence, realize The variable speed constant frequency operation of brushless double feed generator.

Claims (3)

  1. A kind of 1. power module Predictive Control System of brushless double feed generator, it is characterised in that：Including three phase network (1), nothing Brush double feedback electric engine (2), controling winding side power inverter (3), DC bus capacitor (4), power winding side power inverter (5), Power winding voltages measuring cell (6), power winding current measuring cell (7), controling winding current measurement device (8), direct current Side voltage measurement element (9), brushless dual-feed motor speed measuring element (10), power winding complex power estimation block (11), electricity Press vector structure module (12), power prediction module (13) and cost function optimization module (14)；
    The power winding is connected to three phase network (1), controling winding Access Control winding side power inverter (3), control around Group side power inverter (3) is connected by DC bus capacitor (4) with power winding side power inverter (5), power winding side work( Rate converter (5) is connected to power winding；
    The power winding voltages measuring cell (6) and power winding current measuring cell (7) are arranged on power winding and three-phase Between power network (1), power winding voltages and electric current, and the power winding voltages measuring cell (6) and power are respectively used for measuring The output access power winding complex power estimation block (11) of winding current measuring cell (7)；
    The controling winding current measurement device (8) is arranged between controling winding and controling winding side power inverter (3), is used To measure controling winding electric current；
    The DC voltage measuring cell (9) is arranged on controling winding side power inverter (3) and power winding side power becomes Between parallel operation (5), for measuring DC voltage, and the output of the DC voltage measuring cell (9) is as voltage vector structure Model the input of block (12)；
    The brushless dual-feed motor speed measuring element (12) is arranged in brushless dual-feed motor (2) rotating shaft, for measurement motor Rotating speed；
    The controling winding current measurement device (8), brushless dual-feed motor speed measuring element (10), Power estimation module (11) The input of power prediction module (13) is connected to the output end of voltage vector structure module (12)；Power prediction module (13) output access cost function optimization module (14), while value of import function optimization module (14) also include power around Group complex power set-point, the on off state that cost function optimization module (14) obtains come drive control winding side as optimal output Power inverter (3), realizes the control to brushless double feed generator.
  2. 2. based on a kind of control method of brushless double feed generator power module Predictive Control System described in claim 1, its It is characterised by：Comprise the following steps：
    Step 1：Measure k moment power winding voltages uspAnd electric current i (k)sp(k), controling winding electric current isc(k), DC side electricity Press udcAnd rotary speed information ω (k)m(k)；
    Step 2：By the k moment power winding voltages u measured in step 1spAnd electric current i (k)sp(k) k, is estimated according to formula (1) Moment power winding complex power Sp(k)：
    <mrow> <msub> <mi>S</mi> <mi>p</mi> </msub> <mrow> <mo>(</mo> <mi>k</mi> <mo>)</mo> </mrow> <mo>=</mo> <mfrac> <mn>3</mn> <mn>2</mn> </mfrac> <msubsup> <mi>i</mi> <mrow> <mi>s</mi> <mi>p</mi> </mrow> <mo>*</mo> </msubsup> <mrow> <mo>(</mo> <mi>k</mi> <mo>)</mo> </mrow> <msub> <mi>u</mi> <mrow> <mi>s</mi> <mi>p</mi> </mrow> </msub> <mrow> <mo>(</mo> <mi>k</mi> <mo>)</mo> </mrow> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>1</mn> <mo>)</mo> </mrow> </mrow>
    In formula, uspAnd i (k)sp(k) voltage and current of k moment power windings, S are represented respectivelyp(k) k moment power windings are represented Complex power；
    Step 3：By the k moment DC voltages u measured in step 1dc(k), with reference to controling winding side power inverter Switching tube state, structure are input to the voltage vector v of power prediction modeli(k)：
    <mrow> <msub> <mi>v</mi> <mi>i</mi> </msub> <mrow> <mo>(</mo> <mi>k</mi> <mo>)</mo> </mrow> <mo>=</mo> <mfrac> <mn>2</mn> <mn>3</mn> </mfrac> <msub> <mi>u</mi> <mrow> <mi>d</mi> <mi>c</mi> </mrow> </msub> <mrow> <mo>(</mo> <mi>k</mi> <mo>)</mo> </mrow> <msub> <mi>s</mi> <mrow> <mi>a</mi> <mo>,</mo> <mi>b</mi> <mo>,</mo> <mi>c</mi> </mrow> </msub> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>2</mn> <mo>)</mo> </mrow> </mrow>
    In formula, sa,b,cRepresent the switching tube state of controling winding side power inverter, udc(k) k moment DC voltages, v are representedi (k) the k moment voltage vectors of structure are represented；
    Step 4：By the power winding voltages u measured in step 1spAnd electric current i (k)sp(k), controling winding electric current isc(k)、 DC voltage udcAnd rotary speed information ω (k)m(k), k moment power winding complex power S in step 2p(k) and step 3 in structure The voltage vector v builti(k) the complex power S of k+1 moment power windings, is predictedp(k+1)i；
    Step 5：The cost function optimization of brushless double feed generator power module predictive control algorithm, specifically includes following steps：
    1st, the control targe that brushless dual-feed motor generates electricity by way of merging two or more grid systems when running is the active power and reactive power of power winding, by the phase It is as follows that the control targe of prestige by the restriction of weight coefficient is converted to single cost function：
    <mrow> <msub> <mi>C</mi> <mi>i</mi> </msub> <mo>=</mo> <mo>|</mo> <msubsup> <mi>P</mi> <mi>p</mi> <mrow> <mi>r</mi> <mi>e</mi> <mi>f</mi> </mrow> </msubsup> <mo>-</mo> <msub> <mi>P</mi> <mi>p</mi> </msub> <msub> <mrow> <mo>(</mo> <mi>k</mi> <mo>+</mo> <mn>1</mn> <mo>)</mo> </mrow> <mi>i</mi> </msub> <mo>|</mo> <mo>+</mo> <mi>&amp;delta;</mi> <mo>|</mo> <msubsup> <mi>Q</mi> <mi>p</mi> <mrow> <mi>r</mi> <mi>e</mi> <mi>f</mi> </mrow> </msubsup> <mo>-</mo> <msub> <mi>Q</mi> <mi>p</mi> </msub> <msub> <mrow> <mo>(</mo> <mi>k</mi> <mo>+</mo> <mn>1</mn> <mo>)</mo> </mrow> <mi>i</mi> </msub> <mo>|</mo> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>6</mn> <mo>)</mo> </mrow> </mrow>
    In formula, k ∈ N are sampling instant；Active power set-point Pp refWith reactive power set-point Qp refSelection by power network demand Determine；The predicted value P of k+1 moment active powerp(k+1)iWith the predicted value Q of reactive powerp(k+1)iCan be by being predicted in step 4 The S obtainedp(k+1)iThe decomposition for carrying out real and imaginary parts obtains；δ is the coefficient for weighing active power and Reactive Power Control weight；
    2nd, with the minimum optimizing index of cost function so that cost function CiMinimum voltage vector viAs optimal voltage vector；
    Step 6：The voltage vector that cost function minimum optimizing index defined in foundation step 5 selects is as controller Output, obtains corresponding drive signal and the switching tube of controling winding side converter is driven.
  3. A kind of 3. brushless double feed generator power module forecast Control Algorithm according to claim 2, it is characterised in that：Institute State step 4 and specifically include following steps：
    A, power winding current i is chosensp, controling winding electric current iscWith power winding magnetic linkage ψspFor state variable, establish brushless double The state-space equation of generating aid mathematical modeling is：
    SX=AX+BV (3)
    In formula, s is differential operator；X=[ispiscψsp]T, wherein, isp,isc,ψspIt is power winding current, controling winding electricity respectively Stream and power winding magnetic linkage；V=[uspuscur]T, wherein, usp,usc,urBe respectively power winding voltages, controling winding voltage and Rotor voltage；A and B is 3 × 3 matrixes, includes the resistance and electricity of brushless double-fed acc power winding, controling winding and rotor windings Feel parameter and rotary speed information；
    B, the state-space equation based on the brushless dual-feed motor obtained in step a, and combine power winding complex power expression formulaThe power module for obtaining brushless dual-feed motor is：
    <mrow> <msub> <mi>sS</mi> <mi>p</mi> </msub> <mo>=</mo> <msub> <mi>&amp;Lambda;</mi> <mn>1</mn> </msub> <msub> <mi>S</mi> <mi>p</mi> </msub> <mo>+</mo> <msub> <mi>&amp;Lambda;</mi> <mn>2</mn> </msub> <msubsup> <mi>i</mi> <mrow> <mi>s</mi> <mi>c</mi> </mrow> <mo>*</mo> </msubsup> <msub> <mi>u</mi> <mrow> <mi>s</mi> <mi>p</mi> </mrow> </msub> <mo>+</mo> <msub> <mi>&amp;Lambda;</mi> <mn>3</mn> </msub> <msubsup> <mi>u</mi> <mrow> <mi>s</mi> <mi>c</mi> </mrow> <mo>*</mo> </msubsup> <msub> <mi>u</mi> <mrow> <mi>s</mi> <mi>p</mi> </mrow> </msub> <mo>+</mo> <msub> <mi>&amp;Lambda;</mi> <mn>4</mn> </msub> <mo>|</mo> <msub> <mi>u</mi> <mrow> <mi>s</mi> <mi>p</mi> </mrow> </msub> <msup> <mo>|</mo> <mn>2</mn> </msup> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>4</mn> <mo>)</mo> </mrow> </mrow>
    In formula, s is differential operator；uspAnd uscPower winding voltages and controling winding voltage are represented respectively；iscRepresent controling winding Electric current；SpRepresent the complex power of power winding；Λ1、Λ2、Λ3And Λ4It is to believe with the resistance, inductance and rotating speed of brushless dual-feed motor The coefficient entry that manner of breathing closes；
    C, by the power module of the brushless dual-feed motor obtained in step b obtain to Euler's sliding-model control before single order with Input voltage vector vi(k) predictor formula of k+1 moment complex powers is corresponding to：
    <mrow> <msub> <mi>S</mi> <mi>p</mi> </msub> <msub> <mrow> <mo>(</mo> <mrow> <mi>k</mi> <mo>+</mo> <mn>1</mn> </mrow> <mo>)</mo> </mrow> <mi>i</mi> </msub> <mo>=</mo> <msub> <mi>S</mi> <mi>p</mi> </msub> <mrow> <mo>(</mo> <mi>k</mi> <mo>)</mo> </mrow> <mo>+</mo> <msub> <mi>T</mi> <mi>s</mi> </msub> <mrow> <mo>(</mo> <mrow> <msub> <mi>&amp;Lambda;</mi> <mn>1</mn> </msub> <msub> <mi>S</mi> <mi>p</mi> </msub> <mrow> <mo>(</mo> <mi>k</mi> <mo>)</mo> </mrow> <mo>+</mo> <msub> <mi>&amp;Lambda;</mi> <mn>2</mn> </msub> <msubsup> <mi>i</mi> <mrow> <mi>s</mi> <mi>c</mi> </mrow> <mo>*</mo> </msubsup> <mrow> <mo>(</mo> <mi>k</mi> <mo>)</mo> </mrow> <msub> <mi>u</mi> <mrow> <mi>s</mi> <mi>p</mi> </mrow> </msub> <mrow> <mo>(</mo> <mi>k</mi> <mo>)</mo> </mrow> <mo>+</mo> <msub> <mi>&amp;Lambda;</mi> <mn>3</mn> </msub> <msubsup> <mi>v</mi> <mi>i</mi> <mo>*</mo> </msubsup> <mrow> <mo>(</mo> <mi>k</mi> <mo>)</mo> </mrow> <msub> <mi>u</mi> <mrow> <mi>s</mi> <mi>p</mi> </mrow> </msub> <mrow> <mo>(</mo> <mi>k</mi> <mo>)</mo> </mrow> <mo>+</mo> <msub> <mi>&amp;Lambda;</mi> <mn>4</mn> </msub> <mo>|</mo> <msub> <mi>u</mi> <mrow> <mi>s</mi> <mi>p</mi> </mrow> </msub> <mrow> <mo>(</mo> <mi>k</mi> <mo>)</mo> </mrow> <msup> <mo>|</mo> <mn>2</mn> </msup> </mrow> <mo>)</mo> </mrow> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>5</mn> <mo>)</mo> </mrow> </mrow>
    In formula, k ∈ N are sampling instant；TsFor the sampling period；uspAnd uscPower winding voltages and controling winding electricity are represented respectively Pressure；iscRepresent controling winding electric current；SpRepresent the complex power of power winding；viRepresent input voltage vector；Coefficient entry Λ1、Λ2、 Λ3And Λ4Same formula (4).
CN201710934617.4A 2017-10-10 2017-10-10 The power module Predictive Control System and its control method of brushless double feed generator Pending CN107612047A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201710934617.4A CN107612047A (en) 2017-10-10 2017-10-10 The power module Predictive Control System and its control method of brushless double feed generator

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201710934617.4A CN107612047A (en) 2017-10-10 2017-10-10 The power module Predictive Control System and its control method of brushless double feed generator

Publications (1)

Publication Number Publication Date
CN107612047A true CN107612047A (en) 2018-01-19

Family

ID=61068256

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201710934617.4A Pending CN107612047A (en) 2017-10-10 2017-10-10 The power module Predictive Control System and its control method of brushless double feed generator

Country Status (1)

Country Link
CN (1) CN107612047A (en)

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109193773A (en) * 2018-09-29 2019-01-11 北方工业大学 A kind of double feedback electric engine prediction power control method and device
CN114826048A (en) * 2022-04-14 2022-07-29 郑州轻工业大学 Method for controlling direct power of brushless doubly-fed generator

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20120119722A1 (en) * 2010-11-11 2012-05-17 David Sole Lopez Power converter control method
CN103107534A (en) * 2013-01-16 2013-05-15 浙江大学 Double-fed induction power generation system optimization power prediction control method
CN103219732A (en) * 2013-04-24 2013-07-24 上海电力学院 reactive voltage controlling method of power distribution network with variable speed constant frequency wind farm
CN103986189A (en) * 2014-05-19 2014-08-13 华北电力大学（保定） Method for establishing energy-storage type double-fed wind power plant simplified model
CN106877408A (en) * 2017-03-29 2017-06-20 燕山大学 Improve the method that T-shaped three level permanent magnet direct-drive wind power system predicts Direct Power

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20120119722A1 (en) * 2010-11-11 2012-05-17 David Sole Lopez Power converter control method
CN103107534A (en) * 2013-01-16 2013-05-15 浙江大学 Double-fed induction power generation system optimization power prediction control method
CN103219732A (en) * 2013-04-24 2013-07-24 上海电力学院 reactive voltage controlling method of power distribution network with variable speed constant frequency wind farm
CN103986189A (en) * 2014-05-19 2014-08-13 华北电力大学（保定） Method for establishing energy-storage type double-fed wind power plant simplified model
CN106877408A (en) * 2017-03-29 2017-06-20 燕山大学 Improve the method that T-shaped three level permanent magnet direct-drive wind power system predicts Direct Power

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
XINCHI WEI ET AL: "Model Predictive Control of Brushless Doubly Fed Twin Stator Induction Machine: A Model Reduction Approach", 《IEEE》 *

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109193773A (en) * 2018-09-29 2019-01-11 北方工业大学 A kind of double feedback electric engine prediction power control method and device
CN109193773B (en) * 2018-09-29 2020-06-30 北方工业大学 Method and device for controlling predicted power of double feeders
CN114826048A (en) * 2022-04-14 2022-07-29 郑州轻工业大学 Method for controlling direct power of brushless doubly-fed generator
CN114826048B (en) * 2022-04-14 2024-10-01 郑州轻工业大学 Direct power control method of brushless doubly-fed generator

Similar Documents

Publication Publication Date Title
CN100539391C (en) Synchronous machine controller
Ghedamsi et al. Improvement of the performances for wind energy conversions systems
CN102150356B (en) Direct power control with component separation
Ghedamsi et al. Control of wind generator associated to a flywheel energy storage system
Kassem et al. Robust control of an isolated hybrid wind–diesel power system using linear quadratic Gaussian approach
CN102792545B (en) Solar power system and electric power system
EP2936643B1 (en) Coordinated control method of generator and svc for improving power plant active power throughput and controller thereof
Adzic et al. Maximum power search in wind turbine based on fuzzy logic control
CN105162380A (en) Six-phase permanent-magnet synchronous motor model predictive control method
CN106877402A (en) The double pwm converter system coordination control methods of double-fed wind power generator group
CN106451470A (en) Grid-side converter control method of dual-feed motor under voltage unbalance of power grid
GB2410386A (en) Controlling reactive power output
CN103414209B (en) DFIG direct current grid-connected power generation system based on RMC and torque control method of DFIG direct current grid-connected power generation system
Abo-Khalil et al. Sensorless control for DFIG wind turbines based on support vector regression
Mossa et al. Enhanced control and power management for a renewable energy-based water pumping system
CN103427738A (en) Optimal predictive direct power control method of doubly fed induction generator
CN114172176A (en) Flywheel energy storage array control method and system applied to wind generating set
CN106992514A (en) A kind of wind stores up the analysis on Small Disturbance Stability method of Isolated Network System
CN107294137A (en) Dual feedback wind power generation system pusher side current transformer is counter to push away variable structure control system and method
CN106982017A (en) A kind of induction machine Current Sensorless direct predictive control method
CN103972899A (en) STATCOM access point voltage compensation method
CN106786805A (en) The straight trend section of friendship that a kind of meter and photovoltaic cluster are accessed coordinates method for optimally controlling
CN115765028A (en) Wind, light and water storage direct current collection synchronous motor grid-connected system and application method thereof
CN107612047A (en) The power module Predictive Control System and its control method of brushless double feed generator
Mishra et al. D, Q reference frames for the simulation of multiphase (six phase) wound rotor induction generator driven by a wind turbine for disperse generation

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
RJ01 Rejection of invention patent application after publication
RJ01 Rejection of invention patent application after publication

Application publication date: 20180119