Micro-grid inverter voltage control method and device

Abstract

The application provides a micro-grid inverter voltage control method and device, the method comprises the following steps: obtaining the inductance current, actual voltage and reference voltage of the inverter and inputting them into a linear quadratic optimal controller to determine a voltage adjustment amount; controlling the inverter voltage according to the voltage adjustment amount; wherein the three-phase inverter circuit state space equation of the linear quadratic optimal controller comprises an internal disturbance term and an external disturbance term; the internal disturbance term is determined according to the equivalent resistance, inductance value, filter capacitor of the filter inductance on the alternating current side of the inverter, inductance uncertainty, capacitance uncertainty; the external disturbance term is determined according to the external disturbance input value of the inverter and the filter capacitor on the alternating current side. By considering the changes of the inductance capacitor and other devices in the actual operation of the power grid, the influence of the internal disturbance on the inverter output is determined, the dynamic response performance of the linear quadratic optimal controller is further improved, and the anti-interference ability of the inverter is effectively improved.

Description

Technical Field

[0001] The present application belongs to the field of microgrid control technology, and in particular relates to a microgrid inverter voltage control method and device. Background Art

[0002] Microgrids currently mainly include three types: DC, AC and hybrid. DC microgrids have low energy loss, high efficiency and do not need to consider issues such as phase and frequency, which greatly reduces the control burden. However, AC loads still account for the majority, so AC microgrids are the most widely used.

[0003] Existing technologies generally use methods such as disturbance observer controller compensation control strategy, improved distributed quadratic control, and linear quadratic optimal control to control the inverter of AC microgrids. However, the dynamic response speed of the above methods is low and they are easily affected by disturbances. The voltage amplitude still fluctuates greatly when the load is switched on and off. Summary of the Invention

[0004] In view of this, the present invention provides a microgrid inverter voltage control method and device, aiming to solve the problem of low dynamic response speed during microgrid inverter voltage control in the prior art.

[0005] A first aspect of an embodiment of the present invention provides a microgrid inverter voltage control method, including:

[0006] Obtain the inductor current, actual voltage and reference voltage of the inverter;

[0007] inputting the actual voltage, the reference voltage, and the inductor current into a linear quadratic optimal controller to determine a voltage adjustment amount;

[0008] controlling the inverter voltage according to the voltage adjustment amount;

[0009] Among them, the state space equation of the three-phase inverter circuit of the linear quadratic optimal controller includes internal disturbance terms and external disturbance terms; the internal disturbance terms are determined according to the equivalent resistance, inductance value, filter capacitance, inductance uncertainty, and capacitance uncertainty of the filter inductor on the AC side of the inverter; and the external disturbance terms are determined according to the external disturbance input value of the inverter and the filter capacitance on the AC side.

[0010] A second aspect of an embodiment of the present invention provides a microgrid inverter voltage control device, comprising:

[0011] An acquisition module is used to obtain the inductor current, actual voltage and reference voltage of the inverter;

[0012] a calculation module, configured to input the actual voltage, the reference voltage, and the inductor current into a linear quadratic optimal controller to determine a voltage adjustment amount;

[0013] A control module, configured to control the inverter voltage according to the voltage adjustment amount;

[0014] Among them, the state space equation of the three-phase inverter circuit of the linear quadratic optimal controller includes internal disturbance terms and external disturbance terms; the internal disturbance terms are determined according to the equivalent resistance, inductance value, filter capacitance, inductance uncertainty, and capacitance uncertainty of the filter inductor on the AC side of the inverter; and the external disturbance terms are determined according to the external disturbance input value of the inverter and the filter capacitance on the AC side.

[0015] A third aspect of an embodiment of the present invention provides a control device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the microgrid inverter voltage control method described in the first aspect above are implemented.

[0016] A fourth aspect of an embodiment of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the microgrid inverter voltage control method described in the first aspect above are implemented.

[0017] The microgrid inverter voltage control method and device provided by the embodiments of the present invention include: obtaining the inductor current, actual voltage, and reference voltage of the inverter; inputting the actual voltage, reference voltage, and inductor current into a linear quadratic optimal controller to determine a voltage adjustment; and controlling the inverter voltage based on the voltage adjustment. The state-space equation of the three-phase inverter circuit of the linear quadratic optimal controller includes internal and external disturbance terms. The internal disturbance term is determined based on the equivalent resistance, inductance value, filter capacitor, inductance uncertainty, and capacitance uncertainty of the filter inductor on the AC side of the inverter; and the external disturbance term is determined based on the external disturbance input value of the inverter and the filter capacitor on the AC side. The method takes into account the variations of components such as inductors and capacitors during actual grid operation and determines the impact of internal disturbances on the inverter output based on the equivalent resistance, inductance value, filter capacitor, inductance uncertainty, and capacitance uncertainty of the filter inductor on the AC side of the inverter, thereby further improving the dynamic response performance of the linear quadratic optimal controller and effectively enhancing the anti-interference capability of the inverter. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments or descriptions of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0019] Figure 1 This is an application scenario diagram of the microgrid inverter voltage control method provided by an embodiment of the present invention;

[0020] Figure 2 This is a flowchart of an implementation method of a microgrid inverter voltage control method provided by an embodiment of the present invention;

[0021] Figure 3 1 is a topological diagram of a three-phase inverter circuit provided by an embodiment of the present invention;

[0022] Figure 4 It is a traditional state feedback control structure diagram;

[0023] Figure 5 is a state feedback control structure diagram provided by an embodiment of the present invention;

[0024] Figure 6 is a control structure diagram of a linear quadratic optimal controller provided by an embodiment of the present invention;

[0025] Figure 7 It is a conventional control structure diagram;

[0026] Figure 8 Compensation structure for existing technologies;

[0027] Figure 9 The d-axis compensation structure after decoupling of the three-phase inverter based on the LQR controller;

[0028] Figure 10 This is a diagram of a voltage control structure of a microgrid inverter provided by an embodiment of the present invention;

[0029] Figure 11 1 is a schematic structural diagram of a microgrid inverter voltage control device provided by an embodiment of the present invention;

[0030] Figure 12 It is a structural diagram of a control device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0031] In the following description, specific details such as particular system structures and techniques are provided for purposes of illustration, not limitation, to facilitate a thorough understanding of the embodiments of the present invention. However, it will be apparent to those skilled in the art that the present invention may be practiced in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present invention with unnecessary detail.

[0032] Distributed power sources, energy storage devices, loads, and various control systems combine to form microgrids. These microgrids can be connected to the main grid or operate independently. This places demands on the microgrid itself for flexibility, controllability, and robust resilience, while also posing significant challenges to its safety and reliability. Currently, microgrids primarily include DC, AC, and hybrid types. DC microgrids offer low energy loss, high efficiency, and no need to consider phase and frequency issues, significantly reducing the control burden. However, AC loads still account for the majority, making AC microgrids the most widely used.

[0033] In response to the existing external and internal disturbance problems of microgrids, the main existing solutions are as follows: a controller compensation control strategy based on a disturbance observer, which is compared with traditional PID control to improve the robustness of the system. However, the voltage amplitude of this existing technology still fluctuates greatly when the load is switched on and off. The current feedforward control method based on the disturbance observer suppresses the output voltage fluctuation without adding additional sensors, and provides a universal parameter calculation method. However, this existing method has the disadvantages of large technical calculation amount and complex structure. The two-stage converter combines power balancing and time-lag compensation methods, and suppresses bus voltage fluctuations through feedforward. It has a simple structure and is easy to implement, but requires external sensors to extract the corresponding current, which is not easy to implement. The voltage control method based on the nonlinear disturbance observer can effectively suppress bus voltage fluctuations, but the inverter has a dq axis coupling relationship, which makes the system very complicated.

[0034] The present invention provides a microgrid inverter voltage control method, which can quickly extract disturbances and achieve compensation when external and internal disturbances occur without the need for additional voltage and current sensors, thereby improving the steady-state performance and dynamic performance of the system, and can improve the anti-interference ability of the inverter while ensuring that the transient response speed remains unchanged, thereby reducing the sensor cost of the inverter.

[0035] Figure 1 This is an application scenario diagram of the microgrid inverter voltage control method provided by the embodiment of the present invention. Figure 1 As shown, the microgrid inverter voltage control method provided by the embodiment of the present invention can be applied to, but not limited to, this application scenario. Figure 1 As shown, the system includes a control device 11, a DC power supply 12, an inverter 13, and a load 14. The inverter 13 is used to convert the DC power generated by the DC power supply into AC power and transmit it to the load 14. The control device 11 is connected to the inverter 13 and is used to collect the voltage and current output by the inverter 13. Based on the collected voltage and current, the control device 11 generates a control signal to control the output voltage of the inverter 13, thereby providing stable power supply to the load 14.

[0036] The control device 11 may be a single chip microcomputer, an MCU, a power grid dedicated control device or a control platform, etc., which are not limited here. The load 14 may be an unbalanced load, a nonlinear load, a switchable load, etc., which are not limited here.

[0037] The control device 11 in the above system can use PWM modulation to control the inverter 13. A filter can also be added between the inverter 13 and the load 14 to ensure stable power supply.

[0038] Figure 2 FIG is a flow chart of the implementation of the microgrid inverter voltage control method provided by the embodiment of the present invention. Figure 2 As shown, in some embodiments, the microgrid inverter voltage control method is applied to Figure 1 The control device 11 shown in FIG. 1 , the method includes:

[0039] S201, obtaining the inductor current, actual voltage, and reference voltage of the inverter.

[0040] In this embodiment, the inductor current and the actual voltage can be directly acquired from the output terminal of the inverter, and the reference voltage is a given value.

[0041] S202 , inputting the actual voltage, the reference voltage, and the inductor current into a linear quadratic optimal controller to determine a voltage adjustment amount.

[0042] In this embodiment, the linear quadratic regulator (LQR) is a linear system expressed in state space. Its objective function is a quadratic function of the plant state and the control input. The inductor current, actual voltage, and the difference between the actual voltage and a reference voltage are used as state variables to establish the LQR's three-phase inverter circuit state space equations. This determines the voltage adjustment and achieves inverter control.

[0043] S203: Control the inverter voltage according to the voltage adjustment amount.

[0044] In this embodiment, the voltage adjustment amount may be input into a PWM modulator, and the generated modulation signal may be used as a control signal to implement control of the inverter.

[0045] Among them, the state space equation of the three-phase inverter circuit of the linear quadratic optimal controller includes internal disturbance terms and external disturbance terms; the internal disturbance terms are determined according to the equivalent resistance, inductance value, filter capacitance, inductance uncertainty, and capacitance uncertainty of the filter inductor on the AC side of the inverter; the external disturbance terms are determined according to the external disturbance input value of the inverter and the filter capacitance on the AC side.

[0046] The LQR cannot solve the tracking problem in the load switching scenario, and the dynamic response performance is poor. The existing technology usually takes the load current as an external disturbance input to improve the dynamic response performance, but the tracking effect is still poor. In the embodiment, the changes of inductance, capacitance and other devices in the actual operation of the power grid are considered, and the equivalent resistance of the filter inductance on the AC side of the inverter, the inductance value, the filter capacitance, the inductance uncertainty, and the capacitance uncertainty are determined to determine the internal disturbance term, so as to further improve the dynamic response performance of the linear quadratic optimal controller and effectively improve the anti-interference ability of the inverter.

[0047] In some embodiments, the internal disturbance term is:

[0048]

[0049] Wherein, Δf is the internal disturbance term, R f is the equivalent resistance of the filter inductance, L f is the inductance value, C f is the filter capacitance, ΔL is the inductance uncertainty, and ΔC is the capacitance uncertainty.

[0050] In the embodiment, the equivalent resistance of the filter inductance, the inductance value, and the filter capacitance are all fixed parameters of the inverter, which can be obtained in advance. The inductance uncertainty and the capacitance uncertainty are the change amounts of the inductance and the capacitance caused by factors such as temperature, humidity, operating state, and service life, which can be determined by an expert-provided experience curve or predicted by a neural network, without limitation.

[0051] In some embodiments, the state space equation of the three-phase inverter circuit of the linear quadratic optimal controller is:

[0052]

[0053]

[0054]

[0055] Wherein, x * =[x1 x2 x3] T , K=[k1 k2 k3],x1=[i Ld i Lq ] Τ ,x2=[u od u oq ] T ,x3=[e d e q ] T ;

[0056] Wherein, iLd 、i Lq is the inductor current component in the dq rotating coordinate system, u od 、u oq is the system output voltage component in the dq rotating coordinate system, e d , e q are the differences between the given voltage and the actual voltage of the d and q axes, respectively; k1 and k2 are the state current and voltage feedback parameters; k3 is the integral parameter; x1 and x2 are based on Sure;

[0057] in, is the state variable of the state space equation, y is the output variable of the state space equation, ω is the fundamental angular frequency, Ed is the external disturbance term, d is the external disturbance input, u i is the output voltage of the linear quadratic regulator, for u i The derivative of v i Enter values ​​for the state space.

[0058] Figure 3 : is a topological diagram of a three-phase inverter circuit provided by an embodiment of the present invention. Figure 3 As shown, u dc is the DC side voltage, u i,abc is the three-phase voltage on the AC side, i L,abc is the inductor current on the AC side, u o,abc 、i o,abc is the AC side load voltage and current, R f , L f is the equivalent resistance and inductance of the AC side filter inductor, C f In this embodiment, according to the topology of the three-phase inverter circuit, the three-phase stationary coordinate system is converted to the dq rotating coordinate system, and the load voltage u is selected. od 、u oq , inductor current i Ld 、i Lq is the state variable, the inverter bridge output voltage u id 、u iq is the input, the load current i od 、i oq is the external disturbance input d,u od 、u oq As the system output, the state space equation of the linearized three-phase inverter circuit can be obtained, namely the above formulas (3) and (4).

[0059] In this embodiment, the state space equation of the three-phase inverter circuit based on the linear quadratic regulator is generated according to the state space equation of the linearized three-phase inverter circuit and the optimal control theory, that is, the above-mentioned formula (2).

[0060] In some embodiments, the performance index of the state space equation of the three-phase inverter circuit of the linear quadratic regulator is:

[0061]

[0062] Among them, J(u i ) is the target performance value, Q is the third coefficient matrix, and R is the fourth coefficient matrix.

[0063] In modern control theory, state feedback can fully reflect the internal characteristics of a system, and through pole placement, good dynamic performance can be achieved. However, since the loaded three-phase inverter circuit is a zero-type system, according to the terminal value theorem, a step input signal will produce a steady-state error in the output, affecting the system's steady-state operation. Therefore, it is necessary to add an integral controller to eliminate the steady-state error. In addition, it is not necessary to use a proportional-integral controller instead of an integral controller, as this would introduce a new zero point in the system, affecting the system's dynamic response. This leads to the system structure. Figure 4 This is a traditional state feedback control structure diagram. Figure 4 As shown, k1 and k2 are state current and voltage feedback parameters, k3 is the integral parameter, e is the difference between the given voltage and the actual output voltage, and u o * is the given input of the inverter circuit.

[0064] The essence of LQR is a regulation. In modern control theory, the Riccati equation is usually used to solve a constant positive definite matrix P to obtain the optimal control input u i *. By selecting the appropriate error weighting matrix Q and the control signal weighting matrix R and substituting them into the Riccati equation, the optimal control parameters k1, k2, and k3 can be obtained. i The solution of * is shown in formula (6):

[0065]

[0066] In order to find the optimal control input u i *, can be solved by redefining the state variables. Let:

[0067]

[0068]

[0069] Without considering the disturbance, equation (3) can be transformed into the following new state equation (i.e., the above equation (2)):

[0070]

[0071] in,

[0072]

[0073] Figure 5 This is a state feedback control structure diagram provided by an embodiment of the present invention. The system control block diagram after redefining the state variables is as follows: Figure 5 As shown, the performance index of the new system can be expressed as the above formula (5).

[0074] Figure 6 This is the control structure diagram of the linear quadratic optimal controller provided by the embodiment of the present invention. As can be seen from formula (5), the problem of solving the controller parameters is transformed into an LQR adjustment problem. It only needs to select appropriate values ​​of Q and R to obtain the optimized control parameter matrix K and the desired system performance. Figure 6 The system control structure shown.

[0075] The LQR controller can improve the system's transient response speed and steady-state accuracy. However, during the system's stable operation, the system's control performance degrades due to the presence of external and internal disturbances. Therefore, to further enhance the system's anti-interference capabilities, a performance-enhancing structure based on a residual generator is designed based on the original LQR controller. The residual value is extracted and compensated to the input. According to the superposition principle, the compensation signal and the disturbance signal add up to zero at the output, which can effectively improve the dynamic and steady-state performance of the inverter.

[0076] In some embodiments, the microgrid inverter voltage control method further includes:

[0077] The actual voltage, reference voltage and inductor current are input into the residual controller to obtain a residual signal; wherein the residual signal includes an external disturbance residual and an internal disturbance residual.

[0078] In some embodiments, the state space equation of the three-phase inverter circuit of the residual controller is:

[0079]

[0080] Where L is the observer gain matrix, is the reconstructed state vector, is the reconstructed output, u is the actual controller output, r is the residual signal, r e is the external disturbance residual, r i is the internal disturbance residual.

[0081] In some embodiments, S202 may include:

[0082] Get the residual signal;

[0083] The residual signal is input into the performance improvement controller to obtain the compensation voltage;

[0084] The actual voltage, the compensation voltage, the reference voltage and the inductor current are input into the linear quadratic optimal controller to determine the given voltage adjustment amount;

[0085] The transfer function of the performance improvement controller is:

[0086]

[0087] Among them, Q c (s) is the function value of the transfer function, η is the compensation coefficient, s is a complex variable, I is the unit matrix, L is the gain matrix, and λ is the first variable, which is optimized according to the voltage adjustment amount.

[0088] In this embodiment, a performance improvement control model can be established based on Euler parameterization and coprime decomposition theory to solve the matrix expression of the performance improvement controller.

[0089] Traditional performance improvement controllers usually improve performance directly based on the output value of the linear quadratic optimal controller. In this embodiment, by optimizing the output value of the linear quadratic optimal controller, an optimal variable, namely the first variable, is obtained and input into the performance improvement controller, which can also improve the effect of the performance improvement controller and make the linear quadratic optimal controller have better dynamic performance.

[0090] The derivation process of the transfer function of the above performance improvement controller is as follows:

[0091] Figure 7 This is a conventional control structure diagram. Figure 7 As shown, if for a true rational transfer function G(s), it is controllable and observable, and the external controller K(s) remains stable.

[0092] Then, this proper rational transfer function G(s) can be expressed as RH ∞ The left coprime matrix on represents:

[0093]

[0094] Similarly, the controller K(s) can also be RH ∞ The left coprime representation on is:

[0095]

[0096] There are M(s), N(s), X(s), Y(s), Satisfies the Bezout equation, that is:

[0097]

[0098] For the control object described by formula (14), its kernel function can be expressed as:

[0099]

[0100] Where r is the residual value. When external and internal disturbances are not considered, the residual is defined as a zero vector.

[0101] When there is model uncertainty in the controlled object, it can be expressed by its left and right coprime decomposition as follows:

[0102]

[0103] in, Δ N (s) and Δ M (s) represents the uncertainty of the model and is an internal disturbance. When the controlled object described by formula (16) has an external disturbance signal d, its output signal is expressed as:

[0104] y=G Δ (s)u+G Δf (s)d (17)

[0105] Among them, G Δf (s) is the transfer function from the disturbance signal to the output.

[0106] From formulas (15) to (17), we can get the kernel function expression when the controlled object has external disturbance and internal disturbance:

[0107]

[0108] By introducing the matrix Q c (s) The parameterized form of the stabilized controller can be obtained, namely the Euler parameterization:

[0109]

[0110] Theorem 1: Given a control loop of the controlled plant G(s) and a control signal u1 provided by an existing controller K(s), if the control loop is internally stable, then all internally stable controllers can be parameterized as:

[0111] u(s)=u1(s)+Q c (s)r(s) (20)

[0112] Among them, u1 is the output of the original controller, u is the actual controller output, Q c is the transfer function matrix of the compensation signal, and r is the residual signal.

[0113] Figure 8 For the compensation structure of the prior art, such as Figure 8 As shown in Figure 1, when the original system is stable, the system remains stable after the compensation controller is added. When there are external and internal disturbances, the difference between the observed voltage and the actual output voltage can be obtained through the residual generator, which is the residual signal. c Perform reverse compensation to offset the impact of external and internal disturbances on the system voltage. The structure of the residual generator is:

[0114]

[0115] Where L is the observer gain matrix, is the reconstructed state vector, is the reconstructed output. As L increases, the response speeds up, but it also introduces unnecessary noise and other signal interference. Therefore, the observer poles are usually 2-5 times the real part of the system poles.

[0116] The performance improvement structure is independent of the original controller and does not affect the stability of the original system. Combining equations (3) and (21) yields the following expression for the inverter residual generator:

[0117]

[0118] Among them, e x is the state vector of the residual generator, d is the external perturbation input, and △f is the internal perturbation input. The residual generator can be equivalent to a system with perturbations d and △f as input and residual r as output.

[0119] Figure 9 The d-axis compensation structure after decoupling of the three-phase inverter based on the LQR controller is shown in Figure 9 As shown. od * is the input reference voltage of the d-axis, u od is the d-axis output voltage, i Ld is the inductor current, I o is the external disturbance input, △L, △C and △R are the unknown parameter changes of inductance, capacitance and resistance respectively, which belong to internal disturbance, r is the output residual signal of the residual generator, Q c is the transfer function matrix of the voltage compensation signal, u rd is the voltage compensation output, u id Controller output.

[0120] For external disturbance current I o, the transfer function of the system under external disturbance can be obtained through the Mason gain formula, and the equivalent open-loop transfer function can be obtained. Through the open-loop transfer function, it can be found that the voltage of the entire system will be affected by the disturbance and will fluctuate briefly, causing the dynamic performance of the system to degrade. For the internal disturbances △L, △C, and △R, since they are unknown parameter changes and difficult to obtain through measurement, they will cause the system voltage to have a steady-state deviation, resulting in a degradation of steady-state performance. Based on formula (18), it can be seen that the residual signal r can simultaneously obtain the degree of influence of external and internal disturbances on the system.

[0121] By adding a residual generator and a performance-enhancing controller Q c To achieve the performance improvement of external and internal perturbations. When there is no external and internal perturbation, the output of the residual generator is 0, Q c The output compensation voltage signal is 0. When there is a disturbance, the residual generator will quickly output a residual signal r, which is then passed through the compensation transfer function matrix Q. c Output a compensation signal u rd ,The compensation signal can be used to suppress disturbances and improve the control performance of the system.

[0122] According to the Euler parameterization and coprime decomposition theory, a performance improvement control model based on the residual generator is established, and the matrix expression of the computational performance improvement controller can be solved.

[0123] In some embodiments, the microgrid inverter voltage control method further includes:

[0124] Optimizing the first variable according to the voltage adjustment amount and the online optimization algorithm;

[0125] The objective function of the online optimization algorithm is:

[0126]

[0127] Among them, J is the target optimization value, N is the length of the optimization window, n0 is the starting value of the optimization window, and W e is the first coefficient matrix, e k is the state error of the state variable at the kth moment, W u is the second coefficient matrix, u k is the actual voltage of the inverter at the kth moment.

[0128] In this embodiment, according to Figure 9 It can be seen that when the internal disturbance is not considered, the external disturbance I o Acting on the inductor current I ld Therefore, based on the disturbance cancellation principle, based on the external disturbance r e Reconstructed disturbance signal I oRealize reverse compensation of disturbance. According to formula (22) and the principle that the denominator order of the controller is greater than or equal to the numerator, the initial solution Q of the performance improvement controller is obtained c1 (s) expression:

[0129]

[0130] Based on the initial expression of the performance-enhancing controller, the complete expression of the performance-enhancing controller is designed, taking into account the internal disturbances of the system. Since the internal disturbances ΔL, ΔC, and ΔR are unknown parameter variations and difficult to obtain through measurement, an online optimization method is used to optimize the performance-enhancing controller. Therefore, the parameter λ is defined, and the optimization objective function of the performance-enhancing controller is designed (i.e., Equation (23)).

[0131] Improve the performance of the controller Q c (s), the prediction model of the inductor current, the voltage PI controller and the residual generator based on the state observer are combined to obtain the discrete state space equation of the overall controller:

[0132] x c (k+1)=A c x c (k)+B c,1 u c,1 (k)+B c,2 u c,2 (k) (25)

[0133] y c (k) = C c x c (k)+D c,1 u c,1 (k)+D c,2 u c,2 (k)

[0134] According to the discrete state space equation of the overall controller, the performance improvement controller Q is obtained c (s) Gradient formula of parameter λ:

[0135]

[0136]

[0137] The parameter λ is optimized online in real time by combining the performance improvement controller optimization objective function and the gradient formula, thus obtaining the above formula (11).

[0138] Figure 10 This is a diagram of the voltage control structure of the microgrid inverter provided by the embodiment of the present invention. Figure 10As shown, the LQR control outputs a voltage adjustment amount in the dq rotating coordinate system according to the actual voltage and inductive current of the inverter in the dq rotating coordinate system, the reference current, and the compensation signal in the dq rotating coordinate system output by the performance improvement controller. After the voltage adjustment amount is converted through dq / abc conversion, it becomes a PWM modulation signal, which is used to control the inverter.

[0139] The performance improvement controller determines the compensation signal according to the voltage adjustment amount in the dq rotating coordinate system and the residual error. The residual error controller determines the residual error output to the performance improvement controller according to the actual voltage and inductive current of the inverter in the dq rotating coordinate system, the reference current, and the compensation signal in the dq rotating coordinate system output by the performance improvement controller.

[0140] It should be understood that the size of the serial number of each step in the above embodiment does not mean the order of execution, and the execution order of each process should be determined according to its function and inherent logic, and should not constitute any limitation on the implementation process of the embodiment of the present application.

[0141] Figure 11 is a structural schematic diagram of a micro-grid inverter voltage control device provided by the embodiment of the present application. As shown in the figure, Figure 11 The micro-grid inverter voltage control device 11 comprises:

[0142] The acquisition module 1110 is configured to acquire the inductive current, actual voltage, and reference voltage of the inverter.

[0143] The calculation module 11200 is configured to input the actual voltage, reference voltage, and inductive current into a linear quadratic optimal controller to determine a voltage adjustment amount.

[0144] The control module 1130 is configured to control the inverter voltage according to the voltage adjustment amount.

[0145] The three-phase inverter circuit state space equation of the linear quadratic optimal controller comprises an internal disturbance term and an external disturbance term. The internal disturbance term is determined according to the filter inductance equivalent resistance, inductance value, filter capacitance, inductance uncertainty, and capacitance uncertainty of the inverter alternating current side. The external disturbance term is determined according to the external disturbance input value of the inverter and the filter capacitance of the alternating current side.

[0146] Optionally, the internal disturbance term is:

[0147]

[0148] wherein, Δf is the internal disturbance term, R f is the filter inductance equivalent resistance, L f is the inductance value, C f is the filter capacitance, ΔL is the inductance uncertainty, and ΔC is the capacitance uncertainty.

[0149] Alternatively, the state space equation of the three-phase inverter circuit of the linear quadratic optimal controller is:

[0150]

[0151]

[0152]

[0153] in, x * =[x1 x2 x3] T , K=[k1 k2 k3],x1=[i Ld i Lq ] Τ ,x2=[u od u oq ] T , x3=[e d e q ] T ;

[0154] Among them, i Ld 、i Lq is the inductor current component in the dq rotating coordinate system, u od 、u oq is the system output voltage component in the dq rotating coordinate system, e d , e q are the differences between the given voltage and the actual voltage of the d and q axes, respectively; k1 and k2 are the state current and voltage feedback parameters; k3 is the integral parameter; x1 and x2 are based on Sure;

[0155] in, is the state variable of the state space equation, y is the output variable of the state space equation, ω is the fundamental angular frequency, Ed is the external disturbance term, d is the external disturbance input, u i is the output voltage of the linear quadratic regulator, for u i The derivative of v i Enter values ​​for the state space.

[0156] Optionally, the calculation module 11200 is specifically configured to:

[0157] Get the residual signal;

[0158] The residual signal is input into the performance improvement controller to obtain the compensation voltage;

[0159] The actual voltage, the compensation voltage, the reference voltage and the inductor current are input into the linear quadratic optimal controller to determine the given voltage adjustment amount;

[0160] The transfer function of the performance improvement controller is:

[0161]

[0162] Among them, Q c (s) is the function value of the transfer function, η is the compensation coefficient, s is a complex variable, I is the unit matrix, L is the gain matrix, and λ is the first variable, which is optimized according to the voltage adjustment amount.

[0163] Optionally, the device further includes: an optimization module 1140 .

[0164] An optimization module 1140, configured to optimize the first variable according to the voltage adjustment amount and an online optimization algorithm;

[0165] The objective function of the online optimization algorithm is:

[0166]

[0167] Among them, J is the target optimization value, N is the length of the optimization window, n0 is the starting value of the optimization window, and W e is the first coefficient matrix, e k is the state error of the state variable at the kth moment, W u is the second coefficient matrix, u k is the actual voltage of the inverter at the kth moment.

[0168] Optionally, the device further includes: a residual calculation module 1150.

[0169] The residual calculation module 1150 is used to input the actual voltage, the reference voltage and the inductor current into the residual controller to obtain a residual signal; wherein the residual signal includes the external disturbance residual and the internal disturbance residual.

[0170] Optionally, the state space equation of the three-phase inverter circuit of the residual controller is:

[0171]

[0172] Where L is the observer gain matrix, is the reconstructed state vector, is the reconstructed output, u is the actual controller output, r is the residual signal, r e is the external disturbance residual, r i is the internal disturbance residual.

[0173] Optionally, the performance index of the state space equation of the three-phase inverter circuit of the linear quadratic regulator is:

[0174]

[0175] Among them, J(u i ) is the target performance value, Q is the third coefficient matrix, and R is the fourth coefficient matrix.

[0176] The train traction motor leakage current detection device provided in this embodiment can be used to execute the above method embodiment. Its implementation principle and technical effects are similar, and this embodiment will not be repeated here.

[0177] Figure 12 Schematic diagram of the detection device provided by the embodiment of the present invention. Figure 12 As shown, an embodiment of the present invention provides a detection device 12, which includes: a processor 1200, a memory 1210, and a computer program 1220 stored in the memory 1210 and executable on the processor 1200. When the processor 1200 executes the computer program 1220, the steps in the above-mentioned embodiments of the train traction motor leakage current detection method are implemented, such as Figure 2 Alternatively, when the processor 1200 executes the computer program 1220, the functions of the modules / units in the above-mentioned system embodiments are realized, for example, Figure 4 Functions of modules 410 to 430 are shown.

[0178] Exemplarily, the computer program 1220 may be divided into one or more modules / units, one or more of which are stored in the memory 1210 and executed by the processor 1200 to implement the present invention. The one or more modules / units may be a series of computer program instruction segments capable of implementing specific functions, and the instruction segments are used to describe the execution process of the computer program 1220 in the detection device 12.

[0179] The detection device 12 can be a single chip microcomputer, MCU, desktop computer, notebook, PDA and other computing devices. The terminal can include, but is not limited to, a processor 1200 and a memory 1210. Those skilled in the art will understand that Figure 12 This is merely an example of the detection device 12 and does not constitute a limitation on the detection device 12. The detection device 12 may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, the terminal may also include input and output devices, network access devices, buses, etc.

[0180] The processor 1200 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor.

[0181] Memory 1210 can be the internal storage unit of detection device 12, for example the hard disk or the memory of detection device 12. Memory 1210 can also be the external storage device of detection device 12, for example the plug-in hard disk equipped on detection device 12, smart memory card (Smart Media Card, SMC), secure digital (Secure Digital, SD) card, flash memory card (FlashCard) etc. Further, memory 1210 can also comprise both the internal storage unit of detection device 12 and external storage device. Memory 1210 is used for storing other programs and data required for computer program and terminal. Memory 1210 can also be used for temporarily storing data that has been output or will be output.

[0182] An embodiment of the present invention provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, the steps in the above-mentioned train traction motor leakage current detection system embodiment are implemented.

[0183] A computer-readable storage medium stores a computer program 1220, which includes program instructions. When the program instructions are executed by the processor 1200, all or part of the process in the method of the above embodiment is implemented. The computer program 1220 can also be used to instruct related hardware to complete the process. The computer program 1220 can be stored in a computer-readable storage medium. When the computer program 1220 is executed by the processor 1200, it can implement the steps of each of the above method embodiments. Among them, the computer program 1220 includes computer program code, which can be in source code form, object code form, executable file or some intermediate form. Computer-readable media can include: any entity or device capable of carrying computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal and software distribution medium. It should be noted that the content contained in computer-readable media can be appropriately increased or decreased according to the requirements of legislation and patent practices in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practices, computer-readable media does not include electrical carrier signals and telecommunications signals.

[0184] The computer-readable storage medium may be an internal storage unit of the terminal in any of the aforementioned embodiments, such as a hard disk or memory of the terminal. The computer-readable storage medium may also be an external storage device of the terminal, such as a plug-in hard disk equipped on the terminal, a smart memory card (SMC), a secure digital (SD) card, a flash memory card, etc. Furthermore, the computer-readable storage medium may include both an internal storage unit of the terminal and an external storage device. The computer-readable storage medium is used to store computer programs and other programs and data required by the terminal. The computer-readable storage medium may also be used to temporarily store data that has been output or is about to be output.

[0185] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0186] Those skilled in the art can clearly understand that, for the convenience and brevity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0187] In the above embodiments, the description of each embodiment has its own focus. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant description of other embodiments.

[0188] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present invention.

[0189] In the embodiments provided herein, it should be understood that the disclosed devices / terminals and methods can be implemented in other ways. For example, the device / terminal embodiments described above are merely illustrative. For example, the division of modules or units is merely a logical functional division. In actual implementation, other division methods may be used, such as multiple units or components being combined or integrated into another system, or some features being ignored or not implemented. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interface, or the indirect coupling or communication connection of devices or units may be electrical, mechanical, or other forms.

[0190] Units described as separate components may or may not be physically separate, and components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0191] In addition, the functional units in the various embodiments of the present invention may be integrated into a single processing unit, each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0192] If the integrated module / unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present invention implements all or part of the process in the above-mentioned embodiment method, and can also be completed by a computer program to instruct the relevant hardware. The computer program can be stored in a computer-readable storage medium, and when the computer program is executed by the processor, it can implement the steps of each of the above-mentioned method embodiments. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium. It should be noted that the content contained in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media does not include electric carrier signals and telecommunication signals.

[0193] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention, and should all be included in the scope of protection of the present invention.

Claims

1. A microgrid inverter voltage control method, characterized in that: include: Obtain the inductor current, actual voltage and reference voltage of the inverter; inputting the actual voltage, the reference voltage, and the inductor current into a linear quadratic optimal controller to determine a voltage adjustment amount; controlling the inverter voltage according to the voltage adjustment amount; The state space equation of the three-phase inverter circuit of the linear quadratic optimal controller includes an internal disturbance term and an external disturbance term; the internal disturbance term is determined according to the equivalent resistance, inductance value, filter capacitance, inductance uncertainty, and capacitance uncertainty of the filter inductor on the AC side of the inverter; and the external disturbance term is determined according to the external disturbance input value of the inverter and the filter capacitance on the AC side. The internal disturbance term is: Wherein, Δf is the internal disturbance term, R f is the equivalent resistance of the filter inductor, L f is the inductance value, C f is the filter capacitor, ΔL is the inductance uncertainty, and ΔC is the capacitance uncertainty.

2. The microgrid inverter voltage control method according to claim 1, characterized in that: The state space equation of the three-phase inverter circuit of the linear quadratic optimal controller is: Among them, x * = [x1 x2 x3] T , K = [k1 k2 k3], x1 = [i Ld i Lq ] Τ ,x2=[u od u oq ] T , x3=[e d e q ] T ; Among them, i Ld 、i Lq is the inductor current component in the dq rotating coordinate system, u od 、u oq is the system output voltage component in the dq rotating coordinate system, e d , e q are the differences between the given voltage and the actual voltage of the d and q axes, respectively; k1 and k2 are the state current and voltage feedback parameters; k3 is the integral parameter; x1 and x2 are based on Sure; in, is the state variable of the state space equation, y is the output variable of the state space equation, ω is the fundamental angular frequency, Ed is the external disturbance term, d is the external disturbance input, u i is the output voltage of the linear quadratic regulator, for u i The derivative of v i Enter values ​​for the state space.

3. The microgrid inverter voltage control method according to claim 2, characterized in that: Inputting the actual voltage and the reference voltage into a linear quadratic optimal controller to determine a voltage adjustment amount includes: Get the residual signal; Inputting the residual signal into a performance improvement controller to obtain a compensation voltage; inputting the actual voltage, the compensation voltage, the reference voltage and the inductor current into a linear quadratic optimal controller to determine a given voltage adjustment amount; The transfer function of the performance improvement controller is: Among them, Q c (s) is the function value of the transfer function, η is the compensation coefficient, s is a complex variable, I is the unit matrix, L is the gain matrix, λ is the first variable, and the first variable is optimized according to the voltage adjustment amount.

4. The microgrid inverter voltage control method according to claim 3, characterized in that: The method further comprises: Optimizing the first variable according to the voltage adjustment amount and an online optimization algorithm; The objective function of the online optimization algorithm is: Among them, J is the target optimization value, N is the length of the optimization window, n0 is the starting value of the optimization window, and W e is the first coefficient matrix, e k is the state error of the state variable at the kth moment, W u is the second coefficient matrix, u k is the actual voltage of the inverter at the kth moment.

5. The microgrid inverter voltage control method according to claim 3, characterized in that: The method further comprises: The actual voltage, the reference voltage, and the inductor current are input into a residual controller to obtain the residual signal; wherein the residual signal includes an external disturbance residual and an internal disturbance residual.

6. The microgrid inverter voltage control method according to claim 5, characterized in that: The state space equation of the three-phase inverter circuit of the residual controller is: Where L is the observer gain matrix, is the reconstructed state vector, is the reconstructed output, u is the actual controller output, r is the residual signal, r e is the external disturbance residual, r i is the internal disturbance residual.

7. The microgrid inverter voltage control method according to claim 2, characterized in that: The performance index of the three-phase inverter circuit state space equation of the linear quadratic regulator is: Among them, J(u i ) is the target performance value, Q is the third coefficient matrix, and R is the fourth coefficient matrix.

8. A control device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the steps of the microgrid inverter voltage control method as described in any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the microgrid inverter voltage control method as described in any one of claims 1 to 6 above are implemented.

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