CN109660144A - A method of the three-phase inverter bi-mode control based on minimum variance adaptive structure - Google Patents
A method of the three-phase inverter bi-mode control based on minimum variance adaptive structure Download PDFInfo
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02M—APPARATUS FOR CONVERSION BETWEEN AC AND AC, BETWEEN AC AND DC, OR BETWEEN DC AND DC, AND FOR USE WITH MAINS OR SIMILAR POWER SUPPLY SYSTEMS; CONVERSION OF DC OR AC INPUT POWER INTO SURGE OUTPUT POWER; CONTROL OR REGULATION THEREOF
- H02M7/00—Conversion of ac power input into dc power output; Conversion of dc power input into ac power output
- H02M7/42—Conversion of dc power input into ac power output without possibility of reversal
- H02M7/44—Conversion of dc power input into ac power output without possibility of reversal by static converters
- H02M7/48—Conversion of dc power input into ac power output without possibility of reversal by static converters using discharge tubes with control electrode or semiconductor devices with control electrode
- H02M7/53—Conversion of dc power input into ac power output without possibility of reversal by static converters using discharge tubes with control electrode or semiconductor devices with control electrode using devices of a triode or transistor type requiring continuous application of a control signal
- H02M7/537—Conversion of dc power input into ac power output without possibility of reversal by static converters using discharge tubes with control electrode or semiconductor devices with control electrode using devices of a triode or transistor type requiring continuous application of a control signal using semiconductor devices only, e.g. single switched pulse inverters
- H02M7/5387—Conversion of dc power input into ac power output without possibility of reversal by static converters using discharge tubes with control electrode or semiconductor devices with control electrode using devices of a triode or transistor type requiring continuous application of a control signal using semiconductor devices only, e.g. single switched pulse inverters in a bridge configuration
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Abstract
The present invention relates to a kind of methods of three-phase inverter bi-mode control based on minimum variance adaptive structure, the traditional PI controller design of gird-connected inverter is only limitted to run under fixed-bandwidth, although PR control can mitigate the bandwidth limitation in traditional PI design, but performance is not so good as people's will under off-network mode, the present invention fully takes into account the deficiency of traditional control method, minimum variance adaptive control frame is proposed, the active and reactive power for controlling GCI exports.Parameter in control law is based on system identification online updating, and adaptive feature can adapt to the uncertain energy and still maintain power quality, is more suitable for grid-connected inverters and off-network both of which.
Description
Technical field
The present invention relates to microgrid inverter control field, especially a kind of three-phase based on minimum variance adaptive structure
The method of inverter bi-mode control.
Background technique
In recent years, such as renewable energy (RES) (such as distributed energy based on photovoltaic and wind energy), energy stores are set
It is standby to need gird-connected inverter (GCI) to be connected to the DC equipments rapid growth such as DC power supply of AC network with other.Recently mutually
Even the variation of standard allows these equipment to transmit active power, while according to grid requirements offer or absorbing reactive power.Directly
It is helped avoid using GCI using DC-DC converter or additional energy storage device.However, significant challenge is, with system work
Make point and situation constantly changes, the power flow also constantly variation therewith when occurring continuous load variation in power grid, in system.This is wanted
Ask GCI that can satisfactorily run at different conditions.Therefore, GCI controller should be dynamic and can ensure more
High power quality and keep stability at various operating conditions.Another challenge is, when failure or abnormal conditions are sent out
When raw, GCI can also should form an isolated micro-capacitance sensor as off-network invertor operation.Therefore, design intelligence GCI control
The research of device becomes more and more concerned topic.
With the help of intelligent controller, voltage source inverter can be run under grid-connected and off-network mode.In grid-connected mould
Under formula, GCI obtains its Voltage Reference to keep synchronous, and under off-network mode from power grid, it should generate the Voltage Reference of oneself
And Voltage Reference is updated using voltage amplitude and based on the decline of frequency.It has been directed to GCI and has proposed several control strategies, wrapped
Include proportional integration (PI) control, Delay control, constant switching frequency control, the control based on space vector modulation, Direct Power
Control, control and ratio resonance (PR) control based on electric network impedance identification.
PI controller design is only limitted to run under fixed-bandwidth, and hysteresis controller also can not be in broader working range
Good operation, vector controlled may be implemented to switch with constant switching frequency and more low-loss optimal mode, however, because it
Surround stable work point design, so the complicated design of vector controlled, and the cascade PI controller in these designs
With limited operation window.The controller of other forms in addition to PR design (sweared based on space by such as direct Power Control
Measure the control and electric network impedance identification control of modulation) also use the PI based on fixed-bandwidth to design.PR controller can be enhanced inverse
Become device tracking performance, however for off-network mode, traditional PR design performance is not fully up to expectations.Therefore, need it is a kind of can make it is inverse
Become the intelligent controller that can run very well in both modes of device, so that it is guaranteed that higher power quality and being maintained at various
Stability under service condition.
Summary of the invention
In view of this, the purpose of the present invention is to propose to a kind of three-phase inverter bimodulus based on minimum variance adaptive structure
The method of control, it is advantageously ensured that higher power quality and guaranteeing the stability that system is run in both modes.
The present invention is realized using following scheme: a kind of three-phase inverter bi-mode control based on minimum variance adaptive structure
Method, specifically includes the following steps:
Step S1: judging the operating status of micro-capacitance sensor, and when micro-grid connection operation, inverter is in the shape that is incorporated into the power networks
State enters step S2；When microgrid inverter isolated operation, inverter is in off-grid operation state, enters step S3；
Step S2: abc- α β conversion is carried out to grid side three-phase voltage, calculates the voltage-phase for abc-dq conversion
θe, abc-dq conversion is carried out to grid side three-phase voltage, electric current, respectively obtains rectangular axis voltage, electric current vd, vq, idAnd iq, calculate
Practical active-power P outGCI, reactive power QGCI, respectively with power grid with reference to activeIt is idleIt makes the difference, obtains errorEnter step S4；
Step S3: abc- α β conversion is carried out to point of common coupling voltage, calculates the voltage-phase for abc-dq conversion
θe, then V is converted to by α β-dqdGFI、VqGFI, respectively with reference voltageIt makes the difference, obtains error value epsilonVd0、
εVq0, enter step S4；
Step S4: recurrent least square method identifying system parameter is used；Its basis is square for minimizing error εSystem parameter θ is obtained during minimum；
Step S5: control action v' is obtained using LMS controldi、v'qi；If inverter is in grid-connected state,
Enter step S6；If inverter is in off-grid operation state, S7 is entered step；
Wherein, the system parameter of identification is used in LMS control, inverter outlet side uses the friendship based on inductance
Filter is flowed, therefore selects the first-order linear expression of system that can meet system identification purpose, obtains being described by CARMA model
System: It is the error in model expression；By minimizing errorControl action is calculated, is obtained MVC at this time
Closed-loop system output
Step S6:v'di、v'qiBy controlling electric current idAnd iq, so that the active and reactive power for controlling gird-connected inverter is defeated
Out；Return step S1；
Step S7:v'di、v'qiBy controlling electric current idAnd iq, to control point of common coupling voltage, and return step S1.
Further, step S2 specifically includes the following steps:
Step S21: to analyzing at grid-connected inverters, the balance of voltage of inductance and resistance both ends is obtained:
In formula, Vxi, VxAnd IxIt is inverter three-phase output voltage, power grid three-phase voltage and inverter three-phase output electricity respectively
It flows, wherein x=[a, b, c]；
Step S22: the conversion of abc to dq axis is carried out, is converted to ωeThe dq referential of rad/s synchronous rotary:
In formula, R indicates that line resistance, L indicate line inductance；
By vdiAnd vqiIt is divided into two parts: controls electric current i respectivelydAnd iqV 'diWith v 'qiComponent；Compensate for d axis and q axis
It is coupled between componentWithComponent, it may be assumed that
vdi=v 'di+v″di
vqi=v 'qi+v″qi
In formula, v 'di=(R+pL) id, v 'qi=(R+pL) iq,P is derivative
Operator；
Step S23: the voltage-phase used in abc to dq transformation is obtained by following formula:
In formula, vαAnd vβIt is α the and β component of network voltage vector；
The d axis of referential is aligned along the voltage location obtained from above formula, vqIt is zero, and it is constant to assume that power grid has
Voltage amplitude, then vdIt is also constant；The active and reactive power output of GCI is respectively as follows: PGCI=vdid, QGCI=vdiq, then
It is referred to power grid respectively activeIt is idleIt makes the difference, obtains error
There it can be seen that the active power of GCI is exported by idControl, reactive power are exported by iqControl, id, iqDivide again
Not by v 'dWith v 'qControl.
Further, step S4 specifically includes the following steps:
Step S41: system is indicated by n-th of the domain z transfer function of following form:
It is indicated with difference equation are as follows:
y(k)=-a1y(k-1)-a2y(k-2)-...-any(k-n)
+b0u(k-1)+b1u(k-2)+...bn-1u(k-n)
For sampled point k-1:
y(k-1)=-a1y(k-2)-a2y(k-3)-...any(k-1-n)
+b0u(k-2)+b1u(k-3)+...+bn-1u(k-1-n)
For sampled point k-N+1:
y(k-N+1)=-a1y(k-N)-a2y(k-N-1)-...-any(k-N+1-n)
+b0u(k-N)+...+bn-1u(k-N+1-n)
Wherein N is observation length；
Above-mentioned difference equation is write out with following matrix form:
Wherein, X show that θ is system parameter by formula X=[Y:U], in which:
Step S42: setting ε is real system ΦsystemWith system model ΦmodelPerformance between error, then
ε=Φsystem-Φmodel
By Φmodel=X. θ replacement above formula obtains:
ε=Φsysrem-X.θ
Step S43: the basis of identification theory of the least square method is square for minimizing error ε, Plays J is defined as:
When minimizing standard J, the system parameter θ of expression parameter vector is solved, the following form equation of θ is obtained:
θ (k)=θ (k-1)+K (k) [Φ (k)-Xt(k)θ(k-1)]
Wherein, K (k) is Kalman filter gain, solves the parameter a that above formula obtains system n rank transfer function model1,
a2,...,an,b0,b1,...,bn-1；Utilize the System Parameter Design controller of identification.
Further, step S5 specifically: following two formula is respectively adopted and obtains control action v'di、v'qi:
Wherein, v'di(k)Indicate the d shaft voltage sequence applied in inverter k-th of moment, v'qi(k)It indicates in inverter
In the q shaft voltage sequence that k-th of moment applies；PGCI(k)It is the practical wattful power at k-th of moment
Rate,It is the power grid at k-th of moment with reference to active power； K-th moment
Practical reactive power,It is the power grid at k-th of moment with reference to reactive power.
Specific steps S5 the following steps are included:
Step S51: for the MVC design of inverter active power output, it is assumed that system is by controlled autoregressive sliding average
Model description, i.e.,
Wherein, It is the reference active power of power grid to be transmitted to；
PGCIIt (k) is the practical active power transmitted, v 'diIt (k) is the d shaft voltage sequence applied in inverter k-th of moment, and
AndIt is the error in model expression；
Use system time delay information, expection of the MVC according to the information collected in moment k, relative to the output at k+d
Value minimizes the variance exported at k+d, i.e. the target of controller is to minimize following objective function: J(k)=Ex{εP0(k+d) 2},
The wherein system delay that d is assumed that, ExThe desired value for indicating the following output d step, is zero in this case.Design uses base
In the alternating current filter of inductance L, therefore the first-order linear of system is selected to indicate.The model of the order sufficiently achieves system identification
Purpose.
As can be seen from the above equation
If the time point in prediction, formula can be written as to Forward one
Wherein left output signal mentions back in time, and right side includes about current output signal, current input letter
Number and future models evaluated error information；
Step S52: control action v ' is calculateddi(k)To shift to an earlier date the variance of one-step optimization output in time.Based on current
Time input, current time output and future models evaluated error form equation:
As it is assumed that model evaluated error is white noise, therefore its future value (i.e. C=unrelated with past and current demand signal
1)；
When the sum of the first two component is set as zero, minimum variance will be realized, i.e.,
-a1εP0(k)+b0v′di(k)=0
Therefore, the MVC law of active power controller is given by
Similarly, the MVC law of Reactive Power Control is given by
It is the reference reactive power for being transported to power grid, QGCIIt is practical defeated
The reactive power sent.
Step S53: the closed-loop system model of active power controller is obtained:
Substitute into A (z-1), B(z-1), C (z-1) closed-loop system becomes
Consider thus, it can be observed that realizing that the closed-loop system output (error from reference settings point) of MVC is similar to
White noise for model evaluated error.
Compared with prior art, the invention has the following beneficial effects:
1, controller of the present invention tunes online, without understanding inverter and filter parameter completely.
2, the design of control technology proposed by the invention is simple, robust, and can be easy in existing inverter
Ground is realized, without varying significantly to the control framework in using.
3, method of the invention shows good during changing power grid dynamic and DER power output fluctuates.
4, method of the invention is expansible, and can with realized in the real system that is interconnected compared with bulk power grid.
5, controller of the invention is substantially adaptive, any Parameters variation for causing inverter power output variation
It can be suitable for both of which by procedure identification and identical framework.
Detailed description of the invention
Fig. 1 is the method flow schematic diagram of the embodiment of the present invention.
Fig. 2 is the functional block diagram of the embodiment of the present invention.
Fig. 3 is adaptive M VC schematic diagram under the grid-connect mode of the embodiment of the present invention.
Fig. 4 is adaptive M VC schematic diagram under the off-network mode of the embodiment of the present invention.
Specific embodiment
The present invention will be further described with reference to the accompanying drawings and embodiments.
It is noted that described further below be all exemplary, it is intended to provide further instruction to the application.Unless another
It indicates, all technical and scientific terms used herein has usual with the application person of an ordinary skill in the technical field
The identical meanings of understanding.
It should be noted that term used herein above is merely to describe specific embodiment, and be not intended to restricted root
According to the illustrative embodiments of the application.As used herein, unless the context clearly indicates otherwise, otherwise singular
Also it is intended to include plural form, additionally, it should be understood that, when in the present specification using term "comprising" and/or " packet
Include " when, indicate existing characteristics, step, operation, device, component and/or their combination.
As shown in Figures 1 to 4, it is double to present embodiments provide a kind of three-phase inverter based on minimum variance adaptive structure
The method of mould control, specifically includes the following steps:
Step S1: judging the operating status of micro-capacitance sensor, and when micro-grid connection operation, inverter is in the shape that is incorporated into the power networks
State enters step S2；When microgrid inverter isolated operation, inverter is in off-grid operation state, enters step S3；
Step S2: abc- α β conversion is carried out to grid side three-phase voltage, calculates the voltage-phase for abc-dq conversion
θe, abc-dq conversion is carried out to grid side three-phase voltage, electric current, respectively obtains rectangular axis voltage, electric current vd, vq, idAnd iq, calculate
Practical active-power P outGCI, reactive power QGCI, respectively with power grid with reference to activeIt is idleIt makes the difference, obtains errorEnter step S4；
Step S3: abc- α β conversion is carried out to point of common coupling voltage, calculates the voltage-phase for abc-dq conversion
θe, then V is converted to by α β-dqdGFI、VqGFI, respectively with reference voltageIt makes the difference, obtains error value epsilonVd0、
εVq0, enter step S4；
Step S4: recurrent least square method identifying system parameter is used；Its basis is square for minimizing error εSystem parameter θ is obtained during minimum；
Step S5: control action v' is obtained using LMS controldi、v'qi；If inverter is in grid-connected state,
Enter step S6；If inverter is in off-grid operation state, S7 is entered step；
Wherein, the system parameter of identification is used in LMS control, inverter outlet side uses the friendship based on inductance
Filter is flowed, therefore selects the first-order linear expression of system that can meet system identification purpose, obtains being described by CARMA model
System:It is the error in model expression；By minimizing errorControl action is calculated, is obtained MVC at this time
Closed-loop system output
Step S6:v'di、v'qiBy controlling electric current idAnd iq, so that the active and reactive power for controlling gird-connected inverter is defeated
Out；Return step S1；
Step S7:v'di、v'qiBy controlling electric current idAnd iq, to control point of common coupling voltage, and return step S1.
In the present embodiment, step S2 specifically includes the following steps:
Step S21: to analyzing at grid-connected inverters, the balance of voltage of inductance and resistance both ends is obtained:
In formula, Vxi, VxAnd IxIt is inverter three-phase output voltage, power grid three-phase voltage and inverter three-phase output electricity respectively
It flows, wherein x=[a, b, c]；
Step S22: the conversion of abc to dq axis is carried out, is converted to ωeThe dq referential of rad/s synchronous rotary:
In formula, R indicates that line resistance, L indicate line inductance；
By vdiAnd vqiIt is divided into two parts: controls electric current i respectivelydAnd iqV'diAnd v'qiComponent；Compensate for d axis and q axis
It is coupled between componentWithComponent, it may be assumed that
vdi=v 'di+v″di
vqi=v 'qi+v″qi
In formula, v 'di=(R+pL) id, v 'qi=(R+pL) iq,P is derivative
Operator；
Step S23: the voltage-phase used in abc to dq transformation is obtained by following formula:
In formula, vαAnd vβIt is α the and β component of network voltage vector；
The d axis of referential is aligned along the voltage location obtained from above formula, vqIt is zero, and it is constant to assume that power grid has
Voltage amplitude, then vdIt is also constant；The active and reactive power output of GCI is respectively as follows: PGCI=vdid, QGCI=vdiq, then
It is referred to power grid respectively activeIt is idleIt makes the difference, obtains error
There it can be seen that the active power of GCI is exported by idControl, reactive power are exported by iqControl, id, iqDivide again
Not by v 'dWith v 'qControl.
In the present embodiment, step S4 specifically includes the following steps:
Step S41: system is indicated by n-th of the domain z transfer function of following form:
It is indicated with difference equation are as follows:
y(k)=-a1y(k-1)-a2y(k-2)-...-any(k-n)
+b0u(k-1)+b1u(k-2)+...+bn-1u(k-n)
For sampled point k-1:
y(k-1)=-a1y(k-2)-a2y(k-3)-...-any(k-1-n)
+b0u(k-2)+b1u(k-3)+...+bn-1u(k-1-n)
For sampled point k-N+1:
y(k-N+1)=-a1y(k-N)-a2y(k-N-1)-...-any(k-N+1-n)
+b0u(k-N)+...+bn-1u(k-N+1-n)
Wherein N is observation length；
Above-mentioned difference equation is write out with following matrix form:
Wherein, X show that θ is system parameter by formula X=[Y:U], in which:
Step S42: setting ε is real system ΦsystemWith system model ΦmodelPerformance between error, then
ε=Φsystem-Φmodel
By Φmodel=X. θ replacement above formula obtains:
ε=Φsystem-X.θ
Step S43: the basis of identification theory of the least square method is square for minimizing error ε, Plays J is defined as:
When minimizing standard J, the system parameter θ of expression parameter vector is solved, the following form equation of θ is obtained:
θ (k)=θ (k-1)+K (k) [Φ (k)-Xt(k)θ(k-1)]
Wherein, K (k) is Kalman filter gain, solves the parameter a that above formula obtains system n rank transfer function model1,
a2,...,an,b0,b1,...,bn-1；Utilize the System Parameter Design controller of identification.
In the present embodiment, step S5 specifically: following two formula is respectively adopted and obtains control action v'di、v'qi:
Wherein, v'di(k)Indicate the d shaft voltage sequence applied in inverter k-th of moment, v'qi(k)It indicates in inverter
In the q shaft voltage sequence that k-th of moment applies；PGCI(k)It is the practical wattful power at k-th of moment
Rate,It is the power grid at k-th of moment with reference to active power；QGCIIt is the reality at k-th of moment
Border reactive power,It is the power grid at k-th of moment with reference to reactive power.
Specific steps S5 the following steps are included:
Step S51: for the MVC design of inverter active power output, it is assumed that system is by controlled autoregressive sliding average
Model description, i.e.,
Wherein, It is the reference active power of power grid to be transmitted to；
PGCI(k)It is the practical active power of transmitting, v 'di(k)It is the d shaft voltage sequence applied in inverter k-th of moment, andIt is the error in model expression；
Use system time delay information, expection of the MVC according to the information collected in moment k, relative to the output at k+d
Value minimizes the variance exported at k+d, i.e. the target of controller is to minimize following objective function: J(k)=Ex{εP0(k+d) 2},
The wherein system delay that d is assumed that, ExThe desired value for indicating the following output d step, is zero in this case.Design uses base
In the alternating current filter of inductance L, therefore the first-order linear of system is selected to indicate.The model of the order sufficiently achieves system identification
Purpose.
As can be seen from the above equation
If the time point in prediction, formula can be written as to Forward one
Wherein left output signal mentions back in time, and right side includes about current output signal, current input letter
Number and future models evaluated error information；
Step S52: control action v ' is calculateddi(k)To shift to an earlier date the variance of one-step optimization output in time.Based on current
Time input, current time output and future models evaluated error form equation:
As it is assumed that model evaluated error is white noise, therefore its future value (i.e. C=unrelated with past and current demand signal
1)；
When the sum of the first two component is set as zero, minimum variance will be realized, i.e.,
-a1εP0(k)+b0v′di(k)=0
Therefore, the MVC law of active power controller is given by
Similarly, the MVC law of Reactive Power Control is given by
It is the reference reactive power for being transported to power grid, QGCIIt is practical defeated
The reactive power sent.
Step S53: the closed-loop system model of active power controller is obtained:
Substitute into A (z-1), B(z-1), C (z-1) closed-loop system becomes
Consider thus, it can be observed that realizing that the closed-loop system output (error from reference settings point) of MVC is similar to
White noise for model evaluated error.
The traditional PI controller design of gird-connected inverter is only limitted to run under fixed-bandwidth, although PR control can mitigate
Bandwidth limitation in traditional PI design, but performance is not so good as people's will under off-network mode, and the present embodiment fully takes into account Traditional control
The deficiency of method proposes minimum variance adaptive control frame, and the active and reactive power for controlling GCI exports.Control
Parameter in law is based on system identification online updating, and adaptive feature can adapt to the uncertain energy and still
Power quality is kept, grid-connected inverters and off-network both of which are more suitable for.
It should be understood by those skilled in the art that, embodiments herein can provide as method, system or computer program
Product.Therefore, complete hardware embodiment, complete software embodiment or reality combining software and hardware aspects can be used in the application
Apply the form of example.Moreover, it wherein includes the computer of computer usable program code that the application, which can be used in one or more,
The computer program implemented in usable storage medium (including but not limited to magnetic disk storage, CD-ROM, optical memory etc.) produces
The form of product.
The application is referring to method, the process of equipment (system) and computer program product according to the embodiment of the present application
Figure and/or block diagram describe.It should be understood that every one stream in flowchart and/or the block diagram can be realized by computer program instructions
The combination of process and/or box in journey and/or box and flowchart and/or the block diagram.It can provide these computer programs
Instruct the processor of general purpose computer, special purpose computer, Embedded Processor or other programmable data processing devices to produce
A raw machine, so that being generated by the instruction that computer or the processor of other programmable data processing devices execute for real
The device for the function of being specified in present one or more flows of the flowchart and/or one or more blocks of the block diagram.
These computer program instructions, which may also be stored in, is able to guide computer or other programmable data processing devices with spy
Determine in the computer-readable memory that mode works, so that it includes referring to that instruction stored in the computer readable memory, which generates,
Enable the manufacture of device, the command device realize in one box of one or more flows of the flowchart and/or block diagram or
The function of being specified in multiple boxes.
These computer program instructions also can be loaded onto a computer or other programmable data processing device, so that counting
Series of operation steps are executed on calculation machine or other programmable devices to generate computer implemented processing, thus in computer or
The instruction executed on other programmable devices is provided for realizing in one or more flows of the flowchart and/or block diagram one
The step of function of being specified in a box or multiple boxes.
The above described is only a preferred embodiment of the present invention, being not that the invention has other forms of limitations, appoint
What those skilled in the art changed or be modified as possibly also with the technology contents of the disclosure above equivalent variations etc.
Imitate embodiment.But without departing from the technical solutions of the present invention, according to the technical essence of the invention to above embodiments institute
Any simple modification, equivalent variations and the remodeling made, still fall within the protection scope of technical solution of the present invention.
Claims (4)
1. a kind of method of the three-phase inverter bi-mode control based on minimum variance adaptive structure, it is characterised in that: including with
Lower step:
Step S1: judging the operating status of micro-capacitance sensor, and when micro-grid connection operation, inverter is in grid-connected state, into
Enter step S2；When microgrid inverter isolated operation, inverter is in off-grid operation state, enters step S3；
Step S2: abc- α β conversion is carried out to grid side three-phase voltage, calculates the voltage-phase θ for abc-dq conversione, right
Grid side three-phase voltage, electric current carry out abc-dq conversion, respectively obtain rectangular axis voltage, electric current vd, vq, idAnd iq, calculate reality
Border active-power PGCI, reactive power QGCI, respectively with power grid with reference to activeIt is idleIt makes the difference, obtains errorEnter step S4；
Step S3: abc- α β conversion is carried out to point of common coupling voltage, calculates the voltage-phase θ for abc-dq conversione, then
V is converted to by α β-dqdGFI、VqGFI, respectively with reference voltageIt makes the difference, obtains error value epsilonVd0、εVq0, into
Enter step S4；
Step S4: recurrent least square method identifying system parameter is used；
Step S5: control action v' is obtained using LMS controldi、v'qi；If inverter is in grid-connected state, enter
Step S6；If inverter is in off-grid operation state, S7 is entered step；
Step S6:v'di、v'qiBy controlling electric current idAnd iq, to control the active and reactive power output of gird-connected inverter；It returns
Return step S1；
Step S7:v'di、v'qiBy controlling electric current idAnd iq, to control point of common coupling voltage, and return step S1.
2. a kind of side of three-phase inverter bi-mode control based on minimum variance adaptive structure according to claim 1
Method, it is characterised in that: step S2 specifically includes the following steps:
Step S21: to analyzing at grid-connected inverters, the balance of voltage of inductance and resistance both ends is obtained:
In formula, Vxi, VxAnd IxIt is that inverter three-phase output voltage, power grid three-phase voltage and inverter three-phase export electric current respectively,
Middle x=[a, b, c]；
Step S22: the conversion of abc to dq axis is carried out, is converted to ωeThe dq referential of rad/s synchronous rotary:
In formula, R indicates that line resistance, L indicate line inductance；
By vdiAnd vqiIt is divided into two parts: controls electric current i respectivelydAnd iqV'diAnd v'qiComponent；Compensate for d axis and q axis component
Between coupleWithComponent, it may be assumed that
vdi=v 'di+v″di
vqi=v 'qi+v″qi
In formula, v'di=(R+pL) id, v'qi=(R+pL) iq,P is derivative operator；
Step S23: the voltage-phase used in abc to dq transformation is obtained by following formula:
In formula, vαAnd vβIt is α the and β component of network voltage vector；
The d axis of referential is aligned along the voltage location obtained from above formula, vqIt is zero, and assumes that power grid has constant electricity
Pressure amplitude degree, then vdIt is also constant；The active and reactive power output of GCI is respectively as follows: PGCI=vdid, QGCI=vdiq, then distinguish
By it with power grid with reference to activeIt is idleIt makes the difference, obtains error
3. a kind of side of three-phase inverter bi-mode control based on minimum variance adaptive structure according to claim 1
Method, it is characterised in that: step S4 specifically includes the following steps:
Step S41: system is indicated by n-th of the domain z transfer function of following form:
It is indicated with difference equation are as follows:
y(k)=-a1y(k-1)-a2y(k-2)-...any(k-n)
+b0u(k-1)+b1u(k-2)+...bn-1u(k-n)
For sampled point k-1:
y(k-1)=-a1y(k-2)-a2y(k-3)-...-any(k-1-n)
+b0u(k-2)+b1u(k-3)+...+bn-1u(k-1-n)
For sampled point k-N+1:
y(k-N+1)=-a1y(k-N)-a2y(k-N-1)-…-any(k-N+1-n)
+b0u(k-N)+...+bn-1u(k-N+1-n)
Wherein N is observation length；
Above-mentioned difference equation is write out with following matrix form:
Wherein, X show that θ is system parameter by formula X=[Y:U], in which:
Step S42: setting ε is real system ΦsystemWith system model ΦmodelPerformance between error, then
ε=Φsystem-Φmodel
By Φmodel=X. θ replacement above formula obtains:
ε=Φsystem-X.θ
Step S43: the basis of identification theory of the least square method is square for minimizing error ε, Plays J is defined as:
When minimizing standard J, the system parameter θ of expression parameter vector is solved, the following form equation of θ is obtained:
θ (k)=θ (k-1)+K (k) [Φ (K)-Xt(k)θ(k-1)]
Wherein, K (k) is Kalman filter gain, solves the parameter a that above formula obtains system n rank transfer function model1,
a2,...,an,b0,b1,...,bn-1；Utilize the System Parameter Design controller of identification.
4. a kind of side of three-phase inverter bi-mode control based on minimum variance adaptive structure according to claim 3
Method, it is characterised in that: step S5 specifically: following two formula is respectively adopted and obtains control action v'di、v'qi:
Wherein, v'di(k)Indicate the d shaft voltage sequence applied in inverter k-th of moment, v'qi(k)It indicates in inverter in kth
The q shaft voltage sequence that a moment applies；PGCI(k)It is the practical active power at k-th of moment,It is the power grid at k-th of moment with reference to active power；QGCIIt is the reality at k-th of moment
Reactive power,It is the power grid at k-th of moment with reference to reactive power.
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| CN110311407A (en) * | 2019-06-12 | 2019-10-08 | 合肥工业大学 | Cascaded inverter double mode seamless switching control method based on voltage close loop |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106099977A (en) * | 2016-07-01 | 2016-11-09 | 广州供电局有限公司 | Be suitable to energy storage control method and the system of the switching of single-phase micro-capacitance sensor pattern |
-
2019
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106099977A (en) * | 2016-07-01 | 2016-11-09 | 广州供电局有限公司 | Be suitable to energy storage control method and the system of the switching of single-phase micro-capacitance sensor pattern |
Non-Patent Citations (1)
| Title |
|---|
| ROJAN BHATTARAI ET AL.: "Dual Mode Control of a Three-Phase Inverter Using Minimum Variance Adaptive Architecture", 《IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS》 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110311407A (en) * | 2019-06-12 | 2019-10-08 | 合肥工业大学 | Cascaded inverter double mode seamless switching control method based on voltage close loop |
| CN110311407B (en) * | 2019-06-12 | 2022-09-27 | 合肥工业大学 | Double-mode seamless switching control method for cascade inverter based on voltage closed loop |
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