CN114296345B - Electric energy multiport low-voltage alternating current hybrid H2/HinfOptimization control method - Google Patents
Electric energy multiport low-voltage alternating current hybrid H2/HinfOptimization control method Download PDFInfo
- Publication number
- CN114296345B CN114296345B CN202111530426.4A CN202111530426A CN114296345B CN 114296345 B CN114296345 B CN 114296345B CN 202111530426 A CN202111530426 A CN 202111530426A CN 114296345 B CN114296345 B CN 114296345B
- Authority
- CN
- China
- Prior art keywords
- inverter
- cvrc
- control
- inf
- matrix
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 31
- 239000011159 matrix material Substances 0.000 claims abstract description 45
- 238000005457 optimization Methods 0.000 claims abstract description 29
- 238000006243 chemical reaction Methods 0.000 claims abstract description 3
- 238000013461 design Methods 0.000 claims description 13
- 239000013598 vector Substances 0.000 claims description 12
- 230000003190 augmentative effect Effects 0.000 claims description 6
- 239000003990 capacitor Substances 0.000 claims description 6
- 238000012546 transfer Methods 0.000 claims description 5
- 230000003416 augmentation Effects 0.000 claims description 3
- 230000007547 defect Effects 0.000 abstract description 2
- 238000010586 diagram Methods 0.000 description 4
- 238000013016 damping Methods 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 230000015572 biosynthetic process Effects 0.000 description 1
- 230000000295 complement effect Effects 0.000 description 1
- 238000009795 derivation Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000008030 elimination Effects 0.000 description 1
- 238000003379 elimination reaction Methods 0.000 description 1
- 230000010354 integration Effects 0.000 description 1
- 230000010355 oscillation Effects 0.000 description 1
- 238000010248 power generation Methods 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 230000001360 synchronised effect Effects 0.000 description 1
- 238000003786 synthesis reaction Methods 0.000 description 1
Abstract
The invention provides an electric energy multiport low-voltage alternating current hybrid H 2/Hinf optimal control method, which comprises the following steps: establishing an inverter complex variable model after Clark conversion to an alpha beta coordinate system based on complex variables; combining CVRC complex variable models with inverter complex variable models, and designing to obtain an inverter system state space model containing multiple CVRC so as to establish a state feedback control law; the method comprises the steps of designing a state feedback control law by a mixed H 2/Hinf optimization control method, and establishing three constraint conditions: and (3) carrying out mixed optimization solving by comprehensively considering three constraint conditions, namely linear secondary performance index constraint, H inf performance index constraint and regional pole allocation constraint of the system. The invention adopts H inf norm and closed-loop pole allocation as additional constraint for optimizing the LQ weight matrix, and the introduction of H inf norm and closed-loop pole allocation overcomes the defect that LQ control is difficult to directly regulate the system performance.
Description
Technical Field
The invention relates to the technical field of inverter control of a distributed power generation interface, in particular to an electric energy multiport low-voltage alternating current hybrid H 2/Hinf optimal control method.
Background
The traditional inverter is mainly applied to the fields of uninterruptible power supply systems, motor control, electric energy quality management and the like; with the widespread use of distributed power supplies, voltage-controlled power electronic inverter interface devices have also been widely developed and studied. The voltage-current double-loop control method based on the classical linear control theory is wide in application and clear in physical meaning, the controller is flexible to select, and a proportional integral controller under a synchronous coordinate system, a proportional resonance controller under a static coordinate system and the like can achieve steady-state error-free control of sinusoidal alternating current signals. With the development of state space theory, modern control theory and optimal control theory, some novel control methods based on state space are successfully applied to inverter voltage control design, such as model predictive control, lyapunov function control method, H inf control, linear quadratic control and the like. The optimal control method based on the time domain carries out optimal design through various time domain indexes, thereby bringing new design thought and good dynamic performance to the design of the inverter and obtaining wide research and application.
Disclosure of Invention
The invention aims to provide an electric energy multiport low-voltage alternating current hybrid H 2/Hinf optimal control method, which provides an improved linear quadratic optimal control with a weight matrix as an optimal variable, adopts H inf norm and closed-loop pole allocation as additional constraint for optimizing an LQ weight matrix to form an inverter multi-objective optimal design algorithm, and is used for optimally designing gain parameters of multiple controllers, and the introduction of H inf norm and closed-loop pole allocation overcomes the defect that the LQ control is difficult to directly adjust the system performance.
The invention adopts the following technical scheme:
An electric energy multiport low-voltage alternating current hybrid H 2/Hinf optimal control method comprises the following steps:
(1) The method comprises the steps that a three-phase inversion system which is connected into an alternating current bus through an LC filter is used for establishing an inverter complex variable model which is transformed into an alpha beta coordinate system based on complex variables;
(2) Combining CVRC complex variable models with the inverter complex variable models established in the step (1), and designing to obtain an inverter system state space model containing multiple CVRC so as to establish a state feedback control law;
(3) Designing the state feedback control law established in the step (2) by a hybrid H 2/Hinf optimizing control method, and establishing three constraint conditions: and finally, comprehensively considering the three constraint conditions to carry out mixed optimization solution.
Further, in the step (1), an inverter complex variable model is built based on complex variables after Clark conversion to an alpha beta coordinate system, specifically:
The inverter power supply is connected to an alternating current bus through an LC filter, the inverter controls output voltage to provide stable alternating voltage for the alternating current bus, u c、iL、vc、wp respectively represents three-phase output voltage vectors, three-phase inductance current vectors, three-phase modulation voltage vectors and three-phase load current vectors of the inverter, and complex variables shown in formula (1) are also represented; after the three-phase system is transformed to an alpha beta coordinate system through Clark, the basic model of the inverter is shown in (2) - (3):
vαβ＝vα+jvβ (1)
Wherein v αβ represents the complex variable representation in the αβ coordinate system, and v α、vβ represents the α -axis component and the β -axis component of the complex variable v αβ, respectively;
Equation (2) is an inverter state space model, where x p＝[iL uc represents a state complex variable, i L、uc is an inductor current and a capacitor voltage, y represents an inverter output, and a p、Bp1、Bp2、Cp is a state space matrix, which is specifically as follows:
Wherein L, C represents the filter inductance and capacitance, respectively, and R represents the line resistance.
Further, in the step (2), the CVRC complex variable model is combined with the inverter complex variable model established in the step (1), and an inverter system state space model containing multiple CVRC is designed, so that a state feedback control law is established, and the specific steps are as follows:
design CVRC controls the inverter, the transfer function of CVRC is as follows:
Wherein ω is a center angular frequency, j represents an imaginary unit;
the CVRC simplified state space model is as follows:
where x c is the state variable of CVRC, u c represents the control input;
The feedback control of CVRC is divided into two parts, namely, state feedback of actual physical state quantity, wherein the feedback control law is , and the feedback gain of inductance current and capacitance voltage is represented; the other part is tracking control, the part is completed by CVRC, the feedback control law of the tracking control part is K c, and the control gain of CVRC under the central angular frequency is represented;
Designing an inverter control structure comprising multiple CVRC, wherein the fundamental angular frequency ω 0 =100 pi rad/s;
By the error expression:
uc＝y*-Cxp (6)
wherein y represents a reference voltage, substituting formula (6) into formula (2) to obtain a system augmented state space equation containing multiple CVRC as follows:
the augmentation state variables are:
x＝[iLuCxc1 xc2 … xcn]T (8)
An augmented state space equation description matrix comprising multiple CVRC:
B1＝[Bp1 0 0 … 0 0]T (10)
C＝[Cp 0 0 … 0 0] (11)
B2＝[Bp2 0 0 … 0 0]T (12)
R∑＝[0 1 1 … 1 1]T (13)
Designing a state feedback control law:
Wherein represents the inductor current feedback gain and the capacitor voltage feedback gain, respectively; and/> denotes the control gain of CVRC at each resonance frequency point.
Further, the three constraint conditions established in the step (3) specifically include the following steps:
establishing linear quadratic performance index constraint: firstly, defining linear quadratic performance indexes as follows:
wherein Q and R are respectively weighting matrixes, Q is more than or equal to 0, R is more than or equal to 0, and if positive definite matrixes P and K exist in the formula (7), the inequality is caused
Q+KTRK+P(A-B1K)+(A-B1K)TP＜0 (16)
If so, v c = Kx is the optimal LQ control, that is, the H 2 control, and the minimum LQ performance index is , so that the system is stable;
given matrix R, if there is a symmetric positive definite matrix W 1, positive definite matrices M and Q inv, matrix V 1＝KW1 makes the following optimization problem:
With a solution, and if the solution is /> is the optimal LQ control, the performance index is:
Establishing H inf index constraint: if there is a symmetric positive definite matrix W 2 and a matrix V 2＝KW2 such that
It holds that with solution /> is the H inf control of the system, such that the infinite norm of the system is minimal:
Establishing a region pole allocation constraint: the following inequality is defined:
Wherein denotes the matrix Kronecker product, an
L1＝2σ M1＝1
If the presence of the symmetric positive definite matrix W 2 and the matrix V 2＝KW2 results in the equation (30), then the control rate causes the system closed loop pole to fall into the region D (σ, r, θ).
Further, in the step (3), the three constraint conditions are comprehensively considered to perform hybrid optimization solution, and the method specifically comprises the following steps:
For the mixed optimization part, the three constraint conditions are comprehensively considered, and the following Lyapunov matrix is defined:
W＝W1＝W2＝W3,V＝KW (31)
The following mixing optimization problem is obtained:
If the optimization problem has a solution, the control rate v c＝-Kx＝-VW-1 x ensures the optimization of LQ performance and H inf norm of the system, and meanwhile, the closed loop pole of the system falls into a region D (sigma, r, theta); the coefficients a and b are weight coefficients used to trade-off the H inf norm and LQ index.
Further, the coefficients a and b are each taken to be 1.
Compared with the prior art, the invention has the following advantages:
(1) Integrating a state space control structure and a state feedback control law, and converting the gain of the multiple-repetition variable resonant controller and the feedback control gain design of the inductance current and the capacitance voltage into a standard state feedback control comprehensive problem;
(2) The multi-objective optimization framework is used for designing the inverter voltage controller, the framework is based on improving LQR control, and the LQR weight matrix is selected by utilizing the H inf performance index and the regional pole allocation, so that complex weight matrix selection work is avoided, and the effect of improving the inverter control performance is achieved due to the minimization of the H inf performance index and the regional pole allocation.
Drawings
FIG. 1 is a block diagram of an electrical energy multi-port low voltage inverter system;
FIG. 2 is a complex variable resonance control block diagram of the present invention;
FIG. 3 is a diagram of multiple complex variable resonance control in accordance with the present invention;
FIG. 4 is a schematic representation of a pole placement region of the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The embodiment of the invention discloses an electric energy multiport low-voltage alternating current hybrid H 2/Hinf optimal control method, which comprises the following steps:
step 1: and (3) establishing an inverter model which is converted into an alpha beta coordinate system by the Clark based on a complex variable by a three-phase inverter system which is connected into an alternating current bus through an LC filter. The method mainly comprises the following implementation steps:
Fig. 1 is a diagram showing a system structure of an electric energy multiport low-voltage inverter system, an inverter power supply is connected to an ac bus through an LC filter, and an inverter controls an output voltage to provide a stable ac voltage to the ac bus. For convenience of description, u c、iL、vc、wp in fig. 1 may represent either an inverter three-phase output voltage vector, a three-phase inductance current vector, a three-phase modulation voltage vector, and a three-phase load current vector, or a complex variable as shown in formula (1). After the three-phase system is transformed to an alpha beta coordinate system by Clark, the basic model of the inverter shown in fig. 1 is as follows (2) - (3):
vαβ＝vα+jvβ (1)
Wherein v αβ represents the complex variable representation in the αβ coordinate system, and v α、vβ represents the α -axis component and the β -axis component of the complex variable v αβ, respectively;
Equation (2) is an inverter state space model, where x p＝[iL uc represents a state complex variable, i L、uc is an inductor current and a capacitor voltage, y represents an inverter output, and a p、Bp1、Bp2、Cp is a state space matrix, which is specifically as follows:
Wherein L, C represents the filter inductance and capacitance, respectively, and R represents the line resistance.
Step 2: based on basic circuit theory, CVRC complex variable models are combined with the inverter complex variable models established in the step 1, and an inverter system state space model containing multiple CVRC is designed, so that a state feedback control law is established. The method comprises the following specific steps:
For inverter control, elimination of steady state error is typically one of the control objectives, and thus the present invention employs a complex variable resonant controller (complex variables resonant controller, CVRC) to achieve zero steady state error control effect, the transfer function of CVRC is as follows:
Where ω is the center angular frequency and j is the imaginary unit.
The CVRC in the form of transfer function is only suitable for a double-loop control algorithm based on a transfer function model of classical control theory, and in order to realize the optimal design under CVRC control parameter state space, the invention provides a simplified state space model:
Where x c is the state variable of CVRC and u c represents the control input.
The introduction of complex variables, as shown in equation (5), makes CVRC a very compact form.
In combination with the controller shown in (5), the invention designs a complex variable resonance control structure, as shown in figure 2. In fig. 2, feedback control is divided into two parts, namely, state feedback of actual physical state quantity, the part control is mainly used for optimizing and configuring natural poles of a system and improving stability of the system, and a feedback control law is , which represents inductance current feedback gain and capacitance voltage feedback gain; the other part is tracking control, which is completed by CVRC, and the tracking control part in fig. 2 can be regarded as state feedback of CVRC by considering CVRC state space representation shown in formula (8), and the feedback control law is K c, which represents control gain of CVRC at the center angular frequency.
In fig. 2, a single CVRC can only track the signal with a single frequency without dead error, and often cannot meet the performance requirement of the inverter with nonlinear load. To improve the nonlinear load capacity of the inverter, the invention provides an inverter control structure with multiple CVRC, as shown in fig. 3, wherein ω 0 =100 pi rad/s represents the fundamental wave angular frequency.
Thus, by the error expression:
uc＝y*-Cxp (6)
wherein y represents a reference voltage, substituting formula (6) into formula (2) to obtain a system augmented state space equation containing multiple CVRC as follows:
the augmentation state variables are:
x＝[iLuCxc1 xc2 … xcn]T (8)
An augmented state space equation description matrix comprising multiple CVRC:
B1＝[Bp1 0 0 … 0 0]T (10)
C＝[Cp 0 0 … 0 0] (11)
B2＝[Bp2 0 0 … 0 0]T (12)
R∑＝[0 1 1 … 1 1]T (13)
Designing a state feedback control law:
Wherein represents the inductor current feedback gain and the capacitor voltage feedback gain, respectively; and/> denotes the control gain of CVRC at each resonance frequency point.
The inverter control design is converted into a standard state feedback control comprehensive problem by the formulas (7) and (14), and the invention aims to design the gain of the state feedback controller by adopting a multi-objective optimization method. Hereinafter, the present invention mainly discusses a design method of the gain of the controller to obtain better control performance.
Step 3: designing the state feedback control law established in the step (2) by a hybrid H 2/Hinf optimizing control method, and establishing three constraint conditions: and finally, comprehensively considering the three constraint conditions to carry out mixed optimization solution. The main implementation steps are as follows, three constraint conditions are established first:
And establishing linear secondary performance index constraint of the system. Firstly, defining the linear quadratic (Linear Quadratic) performance index as follows:
Wherein Q and R are respectively weighting matrixes, Q is more than or equal to 0, and R is more than or equal to 0. For equation (7), if positive definite matrix P, matrix K is present such that the inequality is
Q+KTRK+P(A-B1K)+(A-B1K)TP＜0 (16)
If so, v c =kx is the optimal LQ control, i.e. the H 2 control according to the present invention. The minimum LQ performance index is and stabilizes the system. The closed loop equation for the system is demonstrated as follows:
defining the lyapunov function V (x) =x T Px, the time derivative of the lyapunov function is:
Can be obtained from formula (16)
The closed loop system (17) progressively stabilizes according to the lyapunov stability theory. Two-side integration of (19) can be obtained
The (20) uses Property V # -, infinity) =0, thereby obtaining
Consider a minimum performance index that depends on the initial shape x 0. Let x 0 be zero mean random variable satisfied where E represents the expectation and I represents the identity matrix. The minimization of x 0 TPx0 at this time can be obtained by minimizing the trace of matrix P: /(I)
The following optimization problem can thus be defined: given matrix R, if there is a symmetric positive definite matrix W 1, positive definite matrices M and Q inv, matrix V 1＝KW1 makes the following optimization problem
With a solution, and if the solution is /> is the optimal LQ control, the performance index is:
The optimization problems (21) - (23) can be derived from the following derivation process: first, according to the Schur complement property, an equivalent linear matrix inequality can be obtained from equation (19):
The diagonal matrix diag ([ P -1, I, I ]) is multiplied by the above formula and W 1＝P-1,V1＝KP-1＝KW1 is defined
V c＝-Kx＝-V1W1 -1 x is the optimal LQ performance controller for the system, as equation (26) is equivalent to (16), and is also the H 2 controller in the present invention.
H inf performance index constraint establishment. The traditional LQ control weight matrix Q is converted into an optimized variable, so that the feasible region space is enlarged, and the system (17) has the following optimization problems according to the bounded real theorem: if there is a symmetric positive definite matrix W 2 and a matrix V 2＝KW2 such that
It holds that with solution /> is H inf control of system (17) such that the infinite norm of the system is minimal:
Region pole allocation constraints are established. The LQ and H inf control does not explicitly normalize the dynamic response of the system, so that the dynamic response of the system cannot intuitively reflect in the process of control synthesis. Typically the dynamic response of a system is directly related to the location of the closed loop pole of the system, as the closed loop pole determines the decay rate, natural angular frequency, damping coefficient, etc. of the system. This section thus introduces the region pole allocation method as an additional constraint for determining the optimization variable Q inv.
Given the region shown in fig. 4: d (σ, r, θ), if all the closed loop poles of the system fall in region D, the decay rate of the system is determined by σ, the natural angular frequency is r, and the minimum damping ratio is ζ=cos (θ), which parameters specify the dynamic response of the system, such as oscillation mode, tuning time, and decay constant.
The following inequality is defined:
Wherein denotes the matrix Kronecker product, an
L1＝2σ M1＝1
If the presence of the symmetric positive definite matrix W 2 and the matrix V 2＝KW2 results in the equation (30), then the control rate causes the system closed loop pole to fall into the region D (σ, r, θ).
Secondly, for the hybrid optimization part, the three constraint conditions are comprehensively considered, and the following Lyapunov matrix is defined:
W＝W1＝W2＝W3,V＝KW (31)
the following mixing optimization problem can be obtained:
If the optimization problem is solved, the control rate v c＝-Kx＝-VW-1 x can ensure the optimization of LQ performance and H inf norms of the system, and the closed loop pole of the system falls into the region D (sigma, r, theta). The optimization problem can be conveniently solved by MATLAB solver mincx (). The coefficients a and b are weight coefficients for compromising the H inf norm and LQ index. In the invention, a and b are taken as 1 so that the system simultaneously considers the H inf norm and the LQ index.
The foregoing is merely illustrative embodiments of the present invention, and the present invention is not limited thereto, and any changes or substitutions that may be easily contemplated by those skilled in the art within the scope of the present invention should be included in the scope of the present invention. Therefore, the protection scope of the present invention should be subject to the protection scope of the claims.
Claims (4)
1. The electric energy multiport low-voltage alternating current hybrid H 2/Hinf optimal control method is characterized by comprising the following steps of:
(1) The method comprises the steps that a three-phase inversion system which is connected into an alternating current bus through an LC filter is used for establishing an inverter complex variable model which is transformed into an alpha beta coordinate system based on complex variables;
(2) Combining CVRC complex variable models with the inverter complex variable models established in the step (1), and designing to obtain an inverter system state space model containing multiple CVRC so as to establish a state feedback control law;
(3) Designing the state feedback control law established in the step (2) by a hybrid H 2/Hinf optimizing control method, and establishing three constraint conditions: performing linear secondary performance index constraint, H inf performance index constraint and regional pole allocation constraint on the system, and finally comprehensively considering the three constraint conditions to perform mixed optimization solution;
In the step (2), the CVRC complex variable model is combined with the inverter complex variable model established in the step (1), and an inverter system state space model containing multiple CVRC is designed, so that a state feedback control law is established, and the specific steps are as follows:
design CVRC controls the inverter, the transfer function of CVRC is as follows:
Wherein ω is a center angular frequency, j represents an imaginary unit;
the CVRC simplified state space model is as follows:
where x c is the state variable of CVRC, u c represents the control input;
The feedback control of CVRC is divided into two parts, namely, state feedback of actual physical state quantity, wherein the feedback control law is , and the feedback gain of inductance current and capacitance voltage is represented; the other part is tracking control, the part is completed by CVRC, the feedback control law of the tracking control part is K c, and the control gain of CVRC under the central angular frequency is represented;
Designing an inverter control structure comprising multiple CVRC, wherein the fundamental angular frequency ω 0 =100 pi rad/s;
By the error expression:
uc＝y*-Cxp (6)
wherein y represents a reference voltage, substituting formula (6) into formula (2) to obtain a system augmented state space equation containing multiple CVRC as follows:
the augmentation state variables are:
x＝[iLuCxc1 xc2…xcn]T (8)
An augmented state space equation description matrix comprising multiple CVRC:
B1＝[Bp1 0 0…0 0]T (10)
C＝[Cp 0 0…0 0] (11)
B2＝[Bp2 0 0…0 0]T (12)
R∑＝[0 1 1…1 1]T (13)
Designing a state feedback control law:
Wherein represents the inductor current feedback gain and the capacitor voltage feedback gain, respectively; the/> represents the control gain of CVRC at each resonance frequency point;
the three constraint conditions established in the step (3) specifically comprise the following steps:
1) Establishing linear quadratic performance index constraint: firstly, defining linear quadratic performance indexes as follows:
wherein Q and R are respectively weighting matrixes, Q is more than or equal to 0, R is more than or equal to 0, and if positive definite matrixes P and K exist in the formula (7), the inequality is caused
Q+KTRK+P(A-B1K)+(A-B1K)TP＜0 (16)
If so, v c = Kx is the optimal LQ control, that is, the H 2 control, and the minimum LQ performance index is , so that the system is stable;
given matrix R, if there is a symmetric positive definite matrix W 1, positive definite matrices M and Q inv, matrix V 1＝KW1 makes the following optimization problem:
With a solution, and if the solution is /> is the optimal LQ control, the performance index is:
2) Standing H inf index constraints: if there is a symmetric positive definite matrix W 2 and a matrix V 2＝KW2 such that
It holds that with solution /> is the H inf control of the system, such that the infinite norm of the system is minimal:
3) Establishing a region pole allocation constraint: the following inequality is defined:
Wherein denotes the matrix Kronecker product, an
If the presence of the symmetric positive definite matrix W 2 and the matrix V 2＝KW2 makes equation (30) true, then the control rate V c＝-Kx＝-V3W3 -1 x causes the system closed loop pole to fall into region D (σ, r, θ).
2. The method for optimizing and controlling the electric energy multiport low-voltage alternating current hybrid H 2/Hinf according to claim 1, wherein in the step (1), an inverter complex variable model after Clark conversion to an alpha beta coordinate system is established based on complex variables, specifically:
The inverter power supply is connected to an alternating current bus through an LC filter, the inverter controls output voltage to provide stable alternating voltage for the alternating current bus, u c、iL、vc、wp respectively represents three-phase output voltage vectors, three-phase inductance current vectors, three-phase modulation voltage vectors and three-phase load current vectors of the inverter, and complex variables shown in formula (1) are also represented; after the three-phase system is transformed to an alpha beta coordinate system through Clark, the basic model of the inverter is shown in (2) - (3):
vαβ＝vα+jvβ (1)
Wherein v αβ represents the complex variable representation in the αβ coordinate system, and v α、vβ represents the α -axis component and the β -axis component of the complex variable v αβ, respectively;
Equation (2) is an inverter state space model, where x p＝[iL uc represents a state complex variable, i L、uc is an inductor current and a capacitor voltage, y represents an inverter output, and a p、Bp1、Bp2、Cp is a state space matrix, which is specifically as follows:
Wherein L, C represents the filter inductance and capacitance, respectively, and R represents the line resistance.
3. The method for optimizing and controlling the electric energy multiport low-voltage alternating current hybrid H 2/Hinf according to claim 1, wherein in the step (3), the three constraint conditions are comprehensively considered for carrying out hybrid optimization solving, and the method specifically comprises the following steps:
For the mixed optimization part, the three constraint conditions are comprehensively considered, and the following Lyapunov matrix is defined:
W＝W1＝W2＝W3,V＝KW (31)
The following mixing optimization problem is obtained:
If the optimization problem has a solution, the control rate v c＝-Kx＝-VW-1 x ensures the optimization of LQ performance and H inf norm of the system, and meanwhile, the closed loop pole of the system falls into a region D (sigma, r, theta); the coefficients a and b are weight coefficients used to trade-off the H inf norm and LQ index.
4. The method for optimizing control of a multi-port low voltage ac hybrid H 2/Hinf as set forth in claim 3, wherein the coefficients a and b are each 1.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111530426.4A CN114296345B (en) | 2021-12-14 | 2021-12-14 | Electric energy multiport low-voltage alternating current hybrid H2/HinfOptimization control method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111530426.4A CN114296345B (en) | 2021-12-14 | 2021-12-14 | Electric energy multiport low-voltage alternating current hybrid H2/HinfOptimization control method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN114296345A CN114296345A (en) | 2022-04-08 |
| CN114296345B true CN114296345B (en) | 2024-04-16 |
Family
ID=80967971
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111530426.4A Active CN114296345B (en) | 2021-12-14 | 2021-12-14 | Electric energy multiport low-voltage alternating current hybrid H2/HinfOptimization control method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114296345B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115173705A (en) * | 2022-07-13 | 2022-10-11 | 国网湖北省电力有限公司电力科学研究院 | Bidirectional DC/DC robust LQ optimal control design method for AC/DC multi-port flexible interconnection device |
Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101013858A (en) * | 2006-12-14 | 2007-08-08 | 上海交通大学 | Cascaded multiple matrix rectifier |
| CN101030733A (en) * | 2007-03-21 | 2007-09-05 | 中国科学院电工研究所 | Multi-level power converter of light unit cascade |
| WO2012010063A1 (en) * | 2010-07-22 | 2012-01-26 | 荣信电力电子股份有限公司 | H-bridge based transformerless wind power grid-connected topological structure |
| WO2012126306A1 (en) * | 2011-03-02 | 2012-09-27 | 荣信电力电子股份有限公司 | Topology for lightweight dc electrical transmission system |
| CN105978024A (en) * | 2016-06-07 | 2016-09-28 | 东南大学 | Energy storage inverter grid-connected and stand-alone seamless switching control algorithm based on complex variables |
| CN209120078U (en) * | 2018-07-16 | 2019-07-16 | 江苏力普电子科技有限公司 | A kind of H bridge cascaded multilevel inverter |
| WO2019178919A1 (en) * | 2018-03-20 | 2019-09-26 | 东南大学 | Micro-grid distributed controller parameter determination method based on linear quadratic optimization |
| CN110299728A (en) * | 2019-07-10 | 2019-10-01 | 东南大学 | A kind of leading dynamic elimination control system and control method of voltage control type inverter |
| CN111654056A (en) * | 2020-05-14 | 2020-09-11 | 华南理工大学 | Voltage tracking control method and system for photovoltaic grid-connected inverter system |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108616141B (en) * | 2018-03-13 | 2021-07-06 | 上海交通大学 | Control method for LCL grid-connected inverter power nonlinearity in microgrid |
-
2021
- 2021-12-14 CN CN202111530426.4A patent/CN114296345B/en active Active
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101013858A (en) * | 2006-12-14 | 2007-08-08 | 上海交通大学 | Cascaded multiple matrix rectifier |
| CN101030733A (en) * | 2007-03-21 | 2007-09-05 | 中国科学院电工研究所 | Multi-level power converter of light unit cascade |
| WO2012010063A1 (en) * | 2010-07-22 | 2012-01-26 | 荣信电力电子股份有限公司 | H-bridge based transformerless wind power grid-connected topological structure |
| WO2012126306A1 (en) * | 2011-03-02 | 2012-09-27 | 荣信电力电子股份有限公司 | Topology for lightweight dc electrical transmission system |
| CN105978024A (en) * | 2016-06-07 | 2016-09-28 | 东南大学 | Energy storage inverter grid-connected and stand-alone seamless switching control algorithm based on complex variables |
| WO2019178919A1 (en) * | 2018-03-20 | 2019-09-26 | 东南大学 | Micro-grid distributed controller parameter determination method based on linear quadratic optimization |
| CN209120078U (en) * | 2018-07-16 | 2019-07-16 | 江苏力普电子科技有限公司 | A kind of H bridge cascaded multilevel inverter |
| CN110299728A (en) * | 2019-07-10 | 2019-10-01 | 东南大学 | A kind of leading dynamic elimination control system and control method of voltage control type inverter |
| CN111654056A (en) * | 2020-05-14 | 2020-09-11 | 华南理工大学 | Voltage tracking control method and system for photovoltaic grid-connected inverter system |
Non-Patent Citations (1)
| Title |
|---|
| 逆变器电压复变量谐振优化控制;全相军;窦晓波;龙昌明;吴在军;胡敏强;陈锋;;中国电机工程学报;20160803(第15期);全文 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN114296345A (en) | 2022-04-08 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Babu et al. | An improved adaptive control strategy in grid-tied PV system with active power filter for power quality enhancement | |
| Zhang et al. | Harmonic transfer-function-based impedance modeling of a three-phase VSC for asymmetric AC grid stability analysis | |
| Zhang et al. | Stability problems of PV inverter in weak grid: a review | |
| Swain et al. | A new grid synchronisation scheme for a three‐phase PV system using self‐tuning filtering approach | |
| Liston et al. | A robust design of active damping with a current estimator for single-phase grid-tied inverters | |
| Zou et al. | Smart transformer-fed variable frequency distribution grid | |
| Renduchintala et al. | ANFIS‐fuzzy logic based UPQC in interconnected microgrid distribution systems: Modeling, simulation and implementation | |
| Soliman et al. | Experimental validation for artificial data-driven tracking control for enhanced three-phase grid-connected boost rectifier in DC microgrids | |
| Ma et al. | Modeling of interconnected voltage and current controlled converters with coupled LC–LCL filters | |
| CN114296345B (en) | Electric energy multiport low-voltage alternating current hybrid H2/HinfOptimization control method | |
| Zhu et al. | Stability assessment of modular multilevel converters based on linear time-periodic theory: Time-domain vs. frequency-domain | |
| Sánchez-Sánchez et al. | Systematic and optimal design of droop-controlled MMCs in MT-HVDC networks | |
| Liao et al. | Controller design-oriented analysis of grid-forming converters for stability robustness enhancement | |
| Fang et al. | Robustness investigation of multi-inverter paralleled grid-connected system with LCL-filter based on the grid-impedance allocation mechanism | |
| Qiu et al. | An improved electric spring topology based on LCL filter | |
| Zhang et al. | Robust control method of grid-connected inverters with enhanced current quality while connected to a weak power grid | |
| Bouzid et al. | Robust control based on linear matrix inequalities criterion of single phase distributed electrical energy systems operating in islanded and grid-connected modes | |
| Xie et al. | Harmonic resonance analysis and stability improvement for grid-connected inverters | |
| Costa et al. | Performance-based tuning for a model predictive direct power control in a grid-tied converter with l-filter | |
| Luo et al. | Direct prediction compensation strategy of unified power quality conditioner based on FCS–MPC | |
| Zhang et al. | Multivariable sequential model predictive control of LCL‐type grid connected inverter | |
| Ghanizadeh et al. | Control of inverter-interfaced distributed generation units for voltage and current harmonics compensation in grid-connected microgrids | |
| Khefifi et al. | Robust IDA-PBC based load voltage controller for power quality enhancement of standalone microgrids | |
| Moutevelis et al. | Bifurcation analysis of active electrical distribution networks considering load tap changers and power converter capacity limits | |
| Li et al. | Active damping adaptive controller for grid-connected inverter under weak grid |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |