Inverter unbalanced voltage compensation control method based on model predictive control

Abstract

The present invention discloses an inverter unbalanced voltage compensation control method based on model predictive control, which solves the technical problems of the existing inverter unbalanced voltage compensation method, such as complex structure, cumbersome adjustment process and time-consuming. The method comprises: constructing a continuous-time state space model of the inverter; discretizing the continuous-time state space model to obtain a discrete-time state space model; embedding negative-sequence virtual impedance in the discrete-time state space model to construct a virtual state space model; using the virtual state space model to predict the virtual three-phase output voltage of the inverter under the action of all inverter voltage vectors; using an evaluation function to evaluate the virtual three-phase output voltage, determining the inverter voltage vector that meets the preset conditions and the switch sequence corresponding to the inverter voltage vector that meets the preset conditions; and controlling the inverter using the switch sequence corresponding to the inverter voltage vector that meets the preset conditions.

Description

Technical Field

[0001] The present invention belongs to the technical field of power electronics, and in particular, relates to an inverter unbalanced voltage compensation control method, and more particularly, relates to an inverter unbalanced voltage compensation control method based on model predictive control. Background Art

[0002] With the rapid increase of distributed power sources and diversified loads, today's power grid has become more and more complex, the threats it faces are more diversified, and the problems that arise also show a multi-dimensional development trend. Among them, voltage imbalance, as a basic problem, often occurs at the same time as other problems, seriously affecting the stable operation of the power grid. For example, under voltage imbalance conditions, stationary equipment is prone to power fluctuations and overload problems, while rotating equipment may have problems such as torque pulsation and angle oscillation. Voltage imbalance is mainly caused by asymmetric parameters of lines and loads, grid failures and other reasons. More serious situations occur in remote areas such as islands, rural areas, and mountainous areas. Most of these places are at the end of the power grid, called terminal grids. Most terminal grids are connected to the grid using a single-line long-distance transmission method. The line impedance is large, and voltage fluctuations are greatly affected by load changes. Therefore, the voltage imbalance problem of the terminal grid is more serious and frequent. And it is precisely remote areas that have unique advantages in renewable energy power generation. However, due to the voltage imbalance problem, the stability of the renewable energy power generation system is subject to a very severe test.

[0003] In a power grid equipped with renewable energy generation, using renewable energy generation devices to solve the imbalance problem is a good solution. Since renewable energy generation devices are mostly interfaced with inverters, the compensation strategy for unbalanced voltage is mostly achieved through the control of the inverter. At this time, in addition to the basic control of voltage and current, unbalanced voltage compensation control must also be applied to the inverter. Currently, the commonly used unbalanced voltage compensation solutions can be roughly divided into two types: voltage compensation and current compensation.

[0004] Among them, the current compensation scheme is an indirect scheme that controls the inverter to inject compensation current into the power grid to compensate for the unbalanced voltage. This method is based on voltage-current dual-loop control, and the injection of compensation current is achieved by superimposing the compensation current reference on the current inner loop. The key to this scheme lies in the generation of compensation current reference, that is, how to generate a suitable compensation current reference based on the unbalanced voltage. The commonly used method at present is to use virtual admittance technology to generate compensation current reference based on the unbalanced voltage of the power grid.

[0005] Unlike the current-type compensation scheme, voltage-type compensation is a more direct scheme, which is generally achieved by directly superimposing the compensation voltage on the inverter output. In this scheme, the compensation voltage and the base voltage need to be controlled at the same time, and a voltage-current dual-loop controller is often used to implement it. If the proportional integral (PI) control method based on Park transformation is adopted, the base voltage (generally positive sequence voltage) and the compensation voltage (generally negative sequence voltage) need to be controlled by four sets of parallel dual-loop controllers. The complex structure will increase the burden on the processor, and the parameter adjustment process inherent in PI control is very cumbersome and time-consuming. If the proportional resonant (PR) control method based on Clarke transformation is adopted, the base voltage and the compensation voltage can be superimposed for control, but two sets of dual-loop controllers are still required to implement it. Moreover, the PR control method is more sensitive to frequency and has higher requirements for parameter design.

[0006] Whether it is a current-type unbalanced compensation scheme or a voltage-type unbalanced compensation scheme, both are based on voltage-current dual-loop control. The cascade structure is relatively complex, and the parameter adjustment process is cumbersome and time-consuming. In actual implementation, the complex structure will greatly increase the burden on the processor, especially when the positive sequence voltage and current components and the negative sequence voltage and current components need to be processed in parallel. The variability of the inverter operating conditions puts higher requirements on the controller parameter adjustment. Once the parameters are inappropriate, it is easy to cause the existing unbalanced voltage compensation method to have unstable performance and the compensation effect is not ideal. Summary of the invention

[0007] The purpose of the present invention is to provide an inverter unbalanced voltage compensation control method based on model predictive control, so as to solve the technical problems of the existing inverter unbalanced voltage compensation method, such as complex structure and cumbersome and time-consuming control parameter adjustment process.

[0008] In order to achieve the above-mentioned purpose, the present invention adopts the following technical solutions:

[0009] A method for controlling unbalanced voltage compensation of an inverter based on model predictive control, the method comprising:

[0010] Construct a continuous-time state-space model of the inverter;

[0011] discretizing the continuous-time state-space model to obtain a discrete-time state-space model;

[0012] Embedding negative sequence virtual impedance in the discrete time state space model to construct a virtual state space model;

[0013] Predicting a virtual three-phase output voltage of the inverter under the action of all inverter voltage vectors using the virtual state space model;

[0014] Using an evaluation function to evaluate the virtual three-phase output voltage, determining an inverter voltage vector that meets a preset condition and a switch sequence corresponding to the inverter voltage vector that meets the preset condition;

[0015] The inverter is controlled using the switching sequence corresponding to the inverter voltage vector that meets the preset condition.

[0016] In some embodiments of the present application, constructing the continuous-time state-space model of the inverter includes:

[0017] Get the three-phase output voltage u of the inverter in the main circuit where the inverter is located oabc , inverter three-phase output current i oabc And the three-phase filter inductor current i fabc ;

[0018] For the u oabc 、The i oabc and the i fabc Perform Clarke transformation respectively to obtain the three-phase output voltage u of the inverter in the αβ coordinate system o , the quantity i of the inverter three-phase output current in the αβ coordinate system o The current i of the inverter three-phase filter inductor in the αβ coordinate system is f ;

[0019] Based on the u o 、The i o and the i f The continuous-time state-space model is constructed.

[0020] In some embodiments of the present application, based on the u o 、The i o and the i f The continuous-time state-space model constructed is:

[0021]

[0022] in, are the system state, system input, system matrix, and input matrix in the continuous-time state-space model respectively; t is the differential time, L f is the filter inductor in the main circuit where the inverter is located; C f is the filter capacitor in the main circuit where the inverter is located; V m is the mth inverter voltage vector, m=0,1,L,M-1, M is determined according to the number of output levels of the inverter.

[0023] In some embodiments of the present application, the discrete time state space model is:

[0024]

[0025] in, are all second-order matrices; T S is the sampling step length, and k is the sampling time.

[0026] In some embodiments of the present application, the negative sequence virtual impedance is embedded in the discrete time state space model to obtain the following virtual state space model:

[0027]

[0028] in, is the virtual system state in the virtual state space model; i fv is the virtual three-phase filter inductor current, u ov is the virtual three-phase output voltage of the inverter, Z vir_nn is the negative sequence virtual impedance, is a known value, i o_n For the i o The negative sequence component of represents the negative-sequence compensation voltage generated by the negative-sequence virtual impedance.

[0029] In some embodiments of the present application, using the virtual state space model to predict the virtual three-phase output voltage of the inverter under the action of all inverter voltage vectors includes:

[0030] Based on the inverter three-phase filter inductor current i in the αβ coordinate system at the kth moment f (k), the three-phase output voltage u of the inverter in the αβ coordinate system at the kth moment o (k), the value i of the inverter three-phase output current in the αβ coordinate system at the kth moment o (k), the inverter voltage vector V calculated at the k-1th moment m (k-1) and the discrete time state space model, predicting the system state variable i at the k+1th moment f (k+1),u o (k+1):

[0031]

[0032] Predict the inverter three-phase output current i in the αβ coordinate system at the k+1th moment o (k+1):

[0033]

[0034] Based on the virtual state space model, at the kth moment, all inverter voltage vectors V m (k), predict the virtual system state variable i at the k+2th momentfv (k+2),u ov (k+2), obtain the voltage vector V m (k) A virtual three-phase output voltage u of the plurality of inverters corresponding to each other ov_m (k+2):

[0035]

[0036] i o_n (k+1) is the i o The negative sequence component of (k+1).

[0037] In some embodiments of the present application, an evaluation function is used to evaluate the virtual three-phase output voltage, and an inverter voltage vector that meets a preset condition and a switch sequence corresponding to the inverter voltage vector that meets the preset condition are determined, specifically including:

[0038] Get the virtual three-phase output voltage u of the inverter ov (k+2) corresponds to the voltage reference signal u o_ref (k+2):

[0039]

[0040] The evaluation function is used to evaluate each u ov (k+2) respectively with the u o_ref (k+2) is compared to determine whether the u ov (k+2) and the u o_ref When the difference of (k+2) is the smallest, the corresponding virtual three-phase output voltage of the inverter is u ov_m' (k+2), determine the ov_m' The inverter voltage vector V corresponding to (k+2) m' (k+2) is the inverter voltage vector that meets the preset condition, and a switching sequence corresponding to the inverter voltage vector that meets the preset condition is determined;

[0041] ω is the system operating frequency of the main circuit where the inverter is located, which is a known value; m' is the serial number of the inverter voltage vector that meets the preset condition.

[0042] In some embodiments of the present application, the evaluation function is:

[0043] J m =(u o_ref (k+2)-u ov (k+2)) 2 +ξ 1 +ξ 2 ;

[0044]

[0045] Among them, I max and U max They are respectively the maximum output current and the maximum output voltage allowed by the inverter, both of which are known values.

[0046] In some embodiments of the present application, the negative sequence virtual impedance is determined by the following method:

[0047] Determine the negative sequence virtual resistance R vir_nn : R vir_nn =R vir_nn0 ;

[0048] Determine the negative sequence virtual inductance L vir_nn :L vir_nn =L vir_nn0 -k L q n ;

[0049] Determine the negative sequence virtual impedance Z vir_nn :Z vir_nn =R vir_nn +jωL vir_nn ;

[0050] Among them, R vir_nn0 is the initial value of the negative sequence virtual resistance, which is a known value; L vir_nn0 is the initial value of negative sequence virtual inductance, which is a known value; k L is the droop coefficient, which is a known value; q n is the negative sequence power; u rms is the system rated voltage peak value of the main circuit where the inverter is located, which is a known value; k is the sampling time, i onα 、i onβ are respectively o The negative sequence component i o_n The real and imaginary parts of o_n =i onα +ji onβ .

[0051] Compared with the prior art, the advantages and positive effects of the present invention are:

[0052] The inverter unbalanced voltage compensation control method provided by the present invention is based on model predictive control, embeds negative-sequence virtual impedance in the inverter model to construct a virtual state space model, performs predictive control based on the virtual state space model, and realizes inverter unbalanced voltage compensation. Compared with the voltage-current linear control method based on the prior art, the positive and negative sequence components of the voltage and current are integrated together for control, the structure is simpler, and the difficulty of implementation is reduced; the implementation of model predictive control does not require cumbersome and time-consuming parameter adjustment process, and the implementation is simple and fast; with the help of the negative-sequence virtual impedance to adjust the negative-sequence voltage, the voltage compensation performance is more stable and the compensation effect is better.

[0053] After reading the specific embodiments of the present invention in conjunction with the accompanying drawings, other features and advantages of the present invention will become more clear. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] 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. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0055] Figure 1 It is an overall principle block diagram of an inverter system according to an embodiment of the present invention corresponding to the inverter unbalanced voltage compensation control method based on model predictive control;

[0056] Figure 2 It is a flow chart of an embodiment of an inverter unbalanced voltage compensation control method based on model predictive control of the present invention;

[0057] Figure 3 A three-phase voltage waveform diagram in an embodiment of an inverter unbalanced voltage compensation control method based on model predictive control of the present invention;

[0058] Figure 4 A voltage unbalance degree response waveform diagram in an embodiment of an inverter unbalance voltage compensation control method based on model predictive control of the present invention;

[0059] Figure 5 This is a waveform diagram showing the voltage imbalance response when the unbalanced load is suddenly added using the PR control of the prior art;

[0060] Figure 6 This is a waveform diagram showing the voltage imbalance response when the unbalanced load is suddenly added using the existing PI control technology. DETAILED DESCRIPTION

[0061] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments.

[0062] In order to solve the technical problems in the prior art of realizing inverter unbalanced voltage compensation based on voltage-current dual-loop control, such as complex structure, cumbersome and time-consuming parameter adjustment process, and unstable compensation performance, the present invention creatively proposes to apply nonlinear model predictive control technology to the unbalanced voltage compensation control of the inverter. By embedding negative-sequence virtual impedance in the model to compensate for the unbalanced voltage, a simple, fast and easy-to-implement inverter unbalanced voltage compensation control is achieved, and the technical effect of stable control performance and better voltage compensation effect is obtained.

[0063] Figure 1 The figure shows an overall principle block diagram of an inverter system according to an embodiment of the present invention corresponding to the inverter unbalanced voltage compensation control method based on model predictive control.

[0064] like Figure 1 As shown, the inverter system of this embodiment includes a three-phase inverter main circuit 11, a signal processing module 12 and a model prediction control module 13. In order to simplify the structure, Figure 1 A single line is used to represent the actual three-phase system loop, and three slashes are used to represent the three-phase cable.

[0065] In the three-phase inverter main circuit 11, V dc is the DC power supply voltage, L f is the filter inductor, C f is the filter capacitor, R f is the damping resistor, Z ln is the line impedance, Z vir_nn is the negative sequence virtual impedance, and PCC is the public grid-connected node. oabc 、i oabc 、i fabc They are the inverter three-phase output voltage, inverter three-phase output current, three-phase filter inductor current, V m , S m is the mth inverter voltage vector and the mth switch sequence corresponding to the inverter voltage vector, m=0,1,L,M-1, M is determined according to the output level number of the inverter. m It is the voltage at the junction of the inverter bridge and the filter inductor of the inverter. For a three-level inverter, m has 27 different values ​​from 0 to 26; for a two-level inverter, m has 8 different values ​​from 0 to 7.

[0066] The signal processing module 12 mainly performs functions such as Clarke transformation, phase sequence separation and power calculation. Among them, Clarke transformation is used to convert the three-phase sampling signal into a quantity in the two-phase static αβ coordinate system. Specifically, u oabc 、i oabc and i fabc After Clarke transformation, the three-phase output voltage u of the inverter in the αβ coordinate system is obtained. o , the quantity i of the inverter three-phase output current in the αβ coordinate system o The current i of the inverter three-phase filter inductor in the αβ coordinate system is f . Moreover, the quantity after Clarke transformation is generally expressed as a complex number including a real part and an imaginary part, where the real part is the quantity of the α axis and the imaginary part is the quantity of the β axis. Phase sequence separation refers to separating the quantity in the αβ coordinate system into positive sequence components and negative sequence components. For example, the quantity u of the three-phase output voltage of the inverter in the αβ coordinate system is o After separation, the positive and negative sequence components u are obtained o_pn , whose positive sequence component is u o_p , the negative sequence component is u o_n ; The inverter three-phase output current i in the αβ coordinate system o After separation, the positive and negative sequence components i are obtained o_pn , whose positive sequence component is i o_p , the negative sequence component is i o_n The positive sequence component and negative sequence component after phase sequence separation can be used to obtain the required positive sequence power and negative sequence power through power calculation.

[0067] The model prediction control module 13 is the core module for realizing the unbalanced voltage compensation control of the inverter, receives the reference voltage given signal and the converted sampling signal, and completes the unbalanced voltage compensation control. Figure 2 Embodiments and description of some other embodiments.

[0068] Figure 2 The figure is a flow chart of an embodiment of the inverter unbalanced voltage compensation control method based on model predictive control of the present invention. Figure 1 The principle block diagram shown is used to specifically describe the implementation process of this embodiment.

[0069] like Figure 2 As shown, this embodiment uses the following process to implement inverter unbalanced voltage compensation control:

[0070] Step 21: Construct a continuous-time state-space model of the inverter.

[0071] refer to Figure 1 The principle block diagram shown in this step is based on the u obtained after Clarke transformation.o 、i o and i f Construct the following continuous-time state-space model:

[0072]

[0073] In the above formula (1), t is the differential time, is the system state in the continuous-time state-space model, u o and i f The structures are two system state variables; Input for the system in the continuous-time state-space model; are the system matrix and input matrix in the continuous-time state-space model, respectively.

[0074] Step 22: Discretize the continuous-time state-space model to obtain a discrete-time state-space model.

[0075] The continuous-time state-space model of formula (1) is accurately discretized to obtain the following corresponding discrete-time state-space model:

[0076]

[0077]

[0078] Among them, Φ and Γ are both second-order matrices; T S is the sampling step length, and k is the sampling time.

[0079] The discrete process is implemented using existing technology and will not be elaborated in detail here.

[0080] Step 23: Embed the negative sequence virtual impedance in the discrete time state space model to construct a virtual state space model.

[0081] In order to compensate for the unbalanced voltage at the PCC node, the negative sequence virtual impedance is embedded in formula (2) to obtain the following virtual state space model (corresponding to Figure 1 Inverter virtual model in ):

[0082]

[0083] In the above formula (4), is the virtual system state in the virtual state space model. fv is the virtual three-phase filter inductor current, and the virtual system state variable u ov is the virtual three-phase output voltage of the inverter; Z vir_nn is the negative sequence virtual impedance, which is a known value; i o_n for i oThe negative sequence component of o_n =i onα +ji onβ ,i onα 、i onβ i o_n The real and imaginary parts of Represented by the negative sequence virtual impedance Z vir_nn The generated negative sequence compensation voltage.

[0084] Step 24: Use the virtual state space model to predict the virtual three-phase output voltage of the inverter under the action of all inverter voltage vectors.

[0085] There are many methods in the prior art for predicting the system state variables in the model using the state space model, and this embodiment does not limit the specific implementation process.

[0086] Step 25: Use the evaluation function to evaluate the virtual three-phase output voltage to determine the inverter voltage vector and the corresponding switching sequence that meet the preset conditions.

[0087] The evaluation function is used to evaluate the obtained state variable virtual three-phase output voltage. Specifically, the evaluation function is used to compare the virtual three-phase output voltage with Figure 1 The reference voltage given shown is compared to obtain the optimal model input, that is, the inverter voltage vector. The optimal inverter voltage vector is determined to be the inverter voltage vector that meets the preset conditions. Furthermore, based on the correspondence between the inverter voltage vector and the switching sequence, the switching sequence corresponding to the inverter voltage vector that meets the preset conditions can be determined.

[0088] Step 26: Control the inverter using the switching sequence.

[0089] The switching sequence determined in step 25 is used as the actual control switching sequence to control the inverter, thereby obtaining the inverter output after performing unbalanced voltage compensation on the inverter.

[0090] The above-mentioned inverter unbalanced voltage compensation control method is adopted, based on model predictive control, and negative-sequence virtual impedance is embedded in the inverter model to construct a virtual state space model. Predictive control is performed based on the virtual state space model to realize inverter unbalanced voltage compensation. Compared with the prior art voltage-current based linear control method, the positive and negative sequence components of voltage and current are integrated together for control, the structure is simpler, and the implementation difficulty is reduced; the implementation of model predictive control does not require cumbersome and time-consuming parameter adjustment process, and the implementation is simple and fast; with the help of negative-sequence virtual impedance to adjust the negative-sequence voltage, the voltage compensation performance is more stable and the compensation effect is better.

[0091] The negative sequence virtual impedance is embedded in the discrete time state space model of the inverter to form a virtual state space model. When the virtual state space model is used to implement predictive control, it is equivalent to inserting a negative sequence virtual impedance in series at the output end of the inverter, such as Figure 1 As shown. For the embedded negative sequence virtual impedance value, it can be a fixed set value, and the size of the set value is determined according to the line impedance parameter between the inverter output terminal and the load. In some other embodiments, considering that the line impedance parameter is difficult to obtain accurately, in order to improve the accuracy and effectiveness of unbalanced voltage compensation, the value of the negative sequence virtual impedance is preferably obtained online in real time to obtain a compensation target that meets the specific needs of the inverter system.

[0092] A specific method for obtaining the value of negative sequence virtual impedance online is to use a method based on negative sequence power droop to obtain the value:

[0093] Determine the negative sequence virtual resistance R vir_nn : R vir_nn =R vir_nn0 ;

[0094] Determine the negative sequence virtual inductance L vir_nn :L vir_nn =L vir_nn0 -k L q n ;

[0095] Determine the negative sequence virtual impedance Z vir_nn :Z vir_nn =R vir_nn +jωL vir_nn ;

[0096] Among them, R vir_nn0 is the initial value of the negative sequence virtual resistance, which is a known value; L vir_nn0 is the initial value of negative sequence virtual inductance, which is a known value; k L is the droop coefficient, which is a known value; q n is the negative sequence power; u rms is the system rated voltage peak value of the main circuit where the inverter is located, which is a known value; k is the sampling time, i onα 、i onβ i o The negative sequence component i o_n The real and imaginary parts of o_n =i onα +ji onβ .

[0097] When using the virtual state space model to predict the virtual three-phase output voltage of the inverter, in some embodiments, in order to reduce the impact of the inherent delay of the system on the predictive control performance of the virtual model, the present invention adopts a delay compensation method based on two-step prediction (corresponding to Figure 1 delay compensation in ).

[0098] First, based on the inverter three-phase filter inductor current i in the αβ coordinate system at the kth moment f (k), the three-phase output voltage u of the inverter in the αβ coordinate system at the kth moment o (k), the value i of the inverter three-phase output current in the αβ coordinate system at the kth moment o (k), the inverter voltage vector V calculated at the k-1th moment m (k-1) and the discrete time state space model to predict the system state variable i at time k+1 f (k+1),u o (k+1):

[0099]

[0100] Among them, i f (k) and u o (k) and i o (k) can be obtained by collecting signal i at the kth moment fabc (k) and u oabc (k) and i oabc (k) obtained by Clarke transformation; V m (k-1) has been determined at the previous sampling time and is also a known value. Then, using formula (5), we can predict the system state variable i at the k+1th time. f (k+1),u o (k+1).

[0101] Ignore the damping resistor R f The influence of the three-phase output current i of the inverter in the αβ coordinate system at the k+1th moment o (k+1) can be predicted based on the change in the three-phase output voltage of the inverter, that is:

[0102]

[0103] Then, based on the virtual state space model, at the kth moment, all inverter voltage vectors V m (k), the virtual system state variable i at the k+2th moment fv (k+2),u ov (k+2) is predicted to obtain the voltage vector V m (k) Virtual three-phase output voltage u of multiple inverters corresponding to each other ov (k+2):

[0104]

[0105] i o_n (k+1) is the i o The negative sequence component of (k+1) is obtained by o (k+1) is obtained by phase sequence separation. It should be understood that when m takes different values, different V m (k), accordingly, each time using a V m (k), using the above formula (7), we can get a m (k) The corresponding virtual three-phase output voltage u ov (k+2). The number of values ​​of m can be the corresponding number of u. ov (k+2).

[0106] Corresponding to the delayed prediction of the virtual three-phase output voltage of the inverter using two-step prediction, Figure 1 The voltage reference signal given as the reference voltage also adopts the value after two-step prediction, that is, the virtual three-phase output voltage u ov_m (k+2) corresponds to the voltage reference signal u o_ref (k+2) is:

[0107]

[0108] In formula (8), ω is the system operating frequency of the main circuit where the inverter is located, which is a known value.

[0109] The virtual three-phase output voltage u of each inverter predicted by formula (7) is ov (k+2), the voltage reference signal u determined by the evaluation function and formula (8) needs to be o_ref (k+2) is evaluated to determine the inverter voltage vector that meets the preset conditions and the switching sequence corresponding to the inverter voltage vector that meets the preset conditions. The preset conditions here refer to the virtual three-phase output voltage u ov (k+2) and the voltage reference signal u o_ref (k+2) is closest. Specifically, the evaluation function is used to evaluate u ov (k+2) and u o_ref (k+2) to determine whether u is satisfied ov (k+2) and u o_ref When the difference of (k+2) is the smallest, the corresponding virtual three-phase output voltage of the inverter is u ov_m' (k+2), determine the ov_m' The inverter voltage vector V corresponding to (k+2) m'(k+2) is an inverter voltage vector that satisfies the preset conditions, that is, an optimal inverter voltage vector that is closest to the reference inverter voltage vector. Then, the inverter voltage vector V that satisfies the preset conditions is determined. m' (k+2) corresponding switch sequence S m' (k+2), as the switching sequence for actual inverter control at the k+2th moment. Wherein, ω is the system operating frequency of the main circuit where the inverter is located, which is a known value; m' is the sequence number of the inverter voltage vector that meets the preset conditions.

[0110] In some preferred embodiments, the evaluation function is expressed as:

[0111] J m =(u o_ref (k+2)-u ov (k+2)) 2 +ξ 1 +ξ 2 (9)

[0112]

[0113]

[0114] Among them, I max and U max are the maximum output current and maximum output voltage allowed by the inverter, respectively, both of which are known values. In formula (9), the difference in the first part realizes the control of the inverter output voltage, while ξ 1 and 2 Realize over-current protection and over-voltage protection respectively.

[0115] The technical effect of the inverter unbalanced voltage compensation control method based on model predictive control is further explained in the following in the form of a graph.

[0116] Figure 3 The figure shows a three-phase voltage waveform diagram in an embodiment of the inverter unbalanced voltage compensation control method based on model predictive control of the present invention. Figure 1 The principle block diagram shown in FIG. 1 shows the unbalanced voltage compensation at time t1. FIG. (a) shows the three-phase voltage waveform of the PCC node, wherein the lower half waveform U2 includes u pcc_a 、u pcc_b and u pcc_c The upper waveform U1 is the enlarged waveform of the positive peak area U21 in the waveform U2; (b) is the three-phase output voltage waveform of the inverter, and the lower waveform U4 is the waveform including the u oa 、u ob and u ocThe upper waveform U3 is the enlarged waveform of the positive peak area U41 in the waveform U4. Figure 3 It can be seen that when the unbalanced voltage compensation control is not applied before time t1, the three-phase voltage of the PCC node is obviously unbalanced, while the three-phase output voltage of the inverter is well balanced. When the unbalanced compensation control is applied at time t1, the three-phase unbalance of the three-phase output voltage of the inverter becomes larger, thereby compensating the three-phase voltage of the PCC node, thereby greatly reducing the unbalance of the three-phase voltage of the PCC node.

[0117] In order to accurately analyze the changes in the three-phase voltage unbalance, the voltage unbalance VUF is defined as:

[0118]

[0119] Among them, u nα 、u nβ is the real and imaginary part of the negative sequence component of the voltage, u pα 、u pβ are the real and imaginary parts of the positive sequence component of the voltage.

[0120] Figure 4 The following is a waveform diagram showing a voltage imbalance response in an embodiment of an inverter unbalanced voltage compensation control method based on model predictive control according to the present invention.

[0121] Among them, Figure (a) shows the voltage imbalance response waveform C1 of the three-phase voltage of the PCC node and the voltage imbalance response waveform C2 of the three-phase output voltage of the inverter calculated by formula (12). It can be seen from Figure (a) that when the imbalance compensation control is applied at time t2, the voltage imbalance of the three-phase voltage of the PCC node is greatly reduced, and the voltage compensation effect is better.

[0122] (b) shows the voltage imbalance response waveform when an unbalanced load is suddenly added. At time t3, an unbalanced load is suddenly added. C3 is the voltage imbalance response waveform of the three-phase voltage of the PCC node, and C4 is the voltage imbalance response waveform of the three-phase output voltage of the inverter. It can be seen from the figure that when the unbalanced load is suddenly added, the imbalance of the PCC three-phase voltage increases rapidly. The inverter then compensates for the PCC voltage by increasing its own output voltage imbalance, so that the imbalance of the PCC voltage is reduced.

[0123] In order to further analyze the superiority of the inverter unbalanced voltage compensation control method based on model predictive control proposed in the present invention compared with the linear control method in the prior art, the following are respectively shown: Figure 5 The voltage unbalance response waveform diagram when the unbalanced load is suddenly added using the existing PR (proportional resonance) control technology and Figure 6The voltage unbalance response waveform diagram when the unbalanced load is suddenly added using the existing PI (proportional integral) control technology is similar to Figure 4 PR control and PI control also add unbalanced load suddenly at time t3.

[0124] Figure 5 Figure (a) shows the imbalance response waveform when the PR fast control parameters are used, where C5 is the imbalance response waveform of the PCC voltage, and C6 is the voltage imbalance response waveform of the inverter three-phase output voltage. Figure 5 Figure (b) shows the imbalance response waveform when the PR slow control parameters are used, where C7 is the imbalance response waveform of the PCC voltage, and C8 is the voltage imbalance response waveform of the inverter three-phase output voltage.

[0125] Figure 6 Figure (a) shows the imbalance response waveform when using PI fast control parameters, where C9 is the imbalance response waveform of the PCC voltage, and C10 is the voltage imbalance response waveform of the inverter three-phase output voltage. Figure 6 Figure (b) shows the imbalance response waveform when the PI slow control parameters are used, where C11 is the imbalance response waveform of the PCC voltage, and C12 is the voltage imbalance response waveform of the inverter three-phase output voltage.

[0126] analyze Figure 5 and Figure 6 It can be seen that the response waveforms of the PR and PI controllers are Figure 4 The response waveform of the model predictive control shown in (b) has a similar change trend. By comparison, it can be found that for the model predictive control, the adjustment time of its response waveform is about 55ms (see Figure 4 (b)), the VUF peak value of the PCC voltage during the regulation process is about 1.24pu. For PR control, the regulation time under the two sets of parameters is 80ms (see Figure 5 (a)) and 160ms (see Figure 5 (b)), the VUF peak values ​​of the PCC voltage during the regulation process are approximately 1.4pu and 2.98pu. For PI control, the regulation time under the two sets of parameters is 75ms respectively (see Figure 6 (a)) and 100ms (see Figure 6 (b)), the corresponding PCC voltage VUF peaks during the regulation process are approximately 2.2pu and 2.4pu respectively. By comparison, it can be found that the dynamic response of the model predictive control is faster, and the peak value of the PCC voltage imbalance during the regulation process is relatively small. For PR and PI control, Figure 5 and Figure 6It can be seen that its dynamic response is greatly affected by parameter changes. The adjustment time and peak index need to be weighed by adjusting the control parameters, which is a cumbersome and time-consuming process. In addition, by comparing the steady-state values ​​of PCC voltage imbalance, it can be seen that compared with the model predictive control method, the unbalanced voltage compensation effect achieved by the PR and PI control methods is relatively poor, and is very sensitive to parameter changes.

[0127] Therefore, it can be seen from the above comparative analysis results that, compared with the linear control method, the model predictive control method proposed in the present invention has more stable performance, better compensation effect, and does not require a complicated parameter adjustment process.

[0128] 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, it is still possible for a person skilled in the art to modify the technical solutions described in the aforementioned embodiments, or to replace some of the technical features therein by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions claimed to be protected by the present invention.

Claims

1. A method for inverter unbalanced voltage compensation control based on model predictive control, It is characterized in that The method comprises: Construct a continuous-time state-space model of the inverter; discretizing the continuous-time state-space model to obtain a discrete-time state-space model; Embedding negative sequence virtual impedance in the discrete time state space model to construct a virtual state space model; Predicting a virtual three-phase output voltage of the inverter under the action of all inverter voltage vectors using the virtual state space model; Using an evaluation function to evaluate the virtual three-phase output voltage, determining an inverter voltage vector that meets a preset condition and a switch sequence corresponding to the inverter voltage vector that meets the preset condition; The inverter is controlled using the switching sequence corresponding to the inverter voltage vector that meets the preset condition.

2. The inverter unbalanced voltage compensation control method based on model predictive control according to claim 1, It is characterized in that Constructing the continuous-time state-space model of the inverter includes: Get the three-phase output voltage u of the inverter in the main circuit where the inverter is located oabc , inverter three-phase output current i oabc And the three-phase filter inductor current i fabc ; For the u oabc 、The i oabc and the i fabc Perform Clarke transformation respectively to obtain the three-phase output voltage u of the inverter in the αβ coordinate system o , the quantity i of the inverter three-phase output current in the αβ coordinate system o The current i of the inverter three-phase filter inductor in the αβ coordinate system is f ; Based on the u o 、The i o and the i f The continuous-time state-space model is constructed.

3. The inverter unbalanced voltage compensation control method based on model predictive control according to claim 2, It is characterized in that Based on the u o 、The i o and the i f The continuous-time state-space model constructed is: in, are the system state, system input, system matrix, and input matrix in the continuous-time state-space model respectively; t is the differential time, L f is the filter inductor in the main circuit where the inverter is located; C f is the filter capacitor in the main circuit where the inverter is located; V m is the mth inverter voltage vector, m=0, 1, ..., M-1, and M is determined according to the number of output levels of the inverter.

4. The inverter unbalanced voltage compensation control method based on model predictive control according to claim 3, It is characterized in that The discrete-time state-space model is: in, are all second-order matrices; T S is the sampling step length, and k is the sampling time.

5. The inverter unbalanced voltage compensation control method based on model predictive control according to claim 4, It is characterized in that The negative sequence virtual impedance is embedded in the discrete time state space model to obtain the following virtual state space model: in, is the virtual system state in the virtual state space model; i fv is the virtual three-phase filter inductor current, u ov is the virtual three-phase output voltage of the inverter, Z vir_nn is the negative sequence virtual impedance, is a known value, i o_n For the i o The negative sequence component of represents the negative-sequence compensation voltage generated by the negative-sequence virtual impedance.

6. The inverter unbalanced voltage compensation control method based on model predictive control according to claim 5, It is characterized in that The virtual state space model is used to predict the virtual three-phase output voltage of the inverter under the action of all inverter voltage vectors, including: Based on the inverter three-phase filter inductor current i in the αβ coordinate system at the kth moment f (k), the three-phase output voltage u of the inverter in the αβ coordinate system at the kth moment o (k), the value i of the inverter three-phase output current in the αβ coordinate system at the kth moment o (k), the inverter voltage vector V calculated at the k-1th moment m (k-1) and the discrete time state space model, predicting the system state variable i at the k+1th moment f (k+1),u o (k+1): Predict the inverter three-phase output current i in the αβ coordinate system at the k+1th moment o (k+1): Based on the virtual state space model, at the kth moment, all inverter voltage vectors V m (k), predict the virtual system state variable i at the k+2th moment fv (k+2),u ov (k+2), obtain the voltage vector V m (k) A virtual three-phase output voltage u of the plurality of inverters corresponding to each other ov (k+2): i o_n (k+1) is the i o The negative sequence component of (k+1).

7. The inverter unbalanced voltage compensation control method based on model predictive control according to claim 6, It is characterized in that The virtual three-phase output voltage is evaluated by using an evaluation function to determine an inverter voltage vector that meets a preset condition and a switch sequence corresponding to the inverter voltage vector that meets the preset condition, specifically including: Get the virtual three-phase output voltage u of the inverter ov (k+2) corresponds to the voltage reference signal u o_ref (k+2): The evaluation function is used to evaluate each u ov (k+2) respectively with the u o_ref (k+2) is compared to determine whether the u ov (k+2) and the u o_ref When the difference of (k+2) is the smallest, the corresponding virtual three-phase output voltage of the inverter is u ov_m' (k+2), determine the ov_m' The inverter voltage vector V corresponding to (k+2) m' (k+2) is the inverter voltage vector that meets the preset condition, and a switching sequence corresponding to the inverter voltage vector that meets the preset condition is determined; ω is the system operating frequency of the main circuit where the inverter is located, which is a known value; m' is the serial number of the inverter voltage vector that meets the preset condition.

8. The inverter unbalanced voltage compensation control method based on model predictive control according to claim 7, It is characterized in that The evaluation function is: J m =(u o_ref (k+2)-u ov (k+2)) 2 +ξ 1 +ξ 2 ; Among them, I max and U max They are respectively the maximum output current and the maximum output voltage allowed by the inverter, both of which are known values.

9. The inverter unbalanced voltage compensation control method based on model predictive control according to any one of claims 2 to 8, It is characterized in that The negative sequence virtual impedance is determined by the following method: Determine the negative sequence virtual resistance R vir_nn : R vir_nn =R vir_nn0 ; Determine the negative sequence virtual inductance L vir_nn :L vir_nn =L vir_nn0 -k L q n ; Determine the negative sequence virtual impedance Z vir_nn :Z vir_nn =R vir_nn +jωL vir_nn ; Among them, R vir_nn0 is the initial value of the negative sequence virtual resistance, which is a known value; L vir_nn0 is the initial value of negative sequence virtual inductance, which is a known value; k L is the droop coefficient, which is a known value; q n is the negative sequence power; u rms is the system rated voltage peak value of the main circuit where the inverter is located, which is a known value; k is the sampling time, i onα 、i onβ are respectively o The negative sequence component i o_n The real and imaginary parts of o_n =i onα +ji onβ .

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