A three-level converter two-dimensional optimization model predictive control method and device

Abstract

This invention discloses a two-dimensional optimization model predictive control method and device for a three-level inverter. The method includes: calculating the inverter's performance using the deadbeat principle. k The reference voltage vector and its phase angle at each moment are determined. Based on the two-dimensional optimization principle, the voltage vector region of the three-level converter is divided into 6 large sectors, each of which is further divided into 6 small sectors. The optimal voltage vector corresponding to the small sector in each large sector is taken as the preliminary optimal voltage vector, and a table of the corresponding preliminary optimal voltage vectors for each sector is created. Using the table of the corresponding preliminary optimal voltage vectors for each sector, the optimal voltage vector is selected. k The preliminary optimal voltage vector corresponding to the reference voltage vector at a given time; the optimal voltage vector is determined based on the preliminary optimal voltage vector and the midpoint voltage; this invention can reduce current ripple and computational burden while achieving midpoint voltage balance and stable operation of a three-level converter.

Description

Technical Field

[0001] This invention belongs to the field of three-level inverter control, and particularly relates to a two-dimensional optimization model predictive control method and device for three-level converters. Background Technology

[0002] As the proportion of new energy sources in the power system increases, the inertia of the power system decreases, and its stability declines. Therefore, additional energy storage devices are needed to improve system stability and compensate for the intermittent and uncertain nature of new energy power generation. Power electronic converters, as the interface between photovoltaic, wind power, and energy storage batteries and the traditional power grid, play a crucial role in the efficiency and stability of the entire system. Compared to two-level converters, three-level converters have advantages such as larger capacity, higher voltage levels, and better output current quality, and are widely used in medium-voltage, high-power applications.

[0003] Model predictive control (MDI) offers numerous advantages, including fast dynamic response, high flexibility, robustness, ease of design and tuning, and the ability to handle multivariable constraints and implement multivariable control within a single control loop. The basic principle of MDI is to calculate the cost function value of each feasible voltage vector in each control cycle and select the voltage vector corresponding to the minimum cost function value as the optimal voltage vector, which is then implemented in the next control cycle. This principle results in a large computational load for MDI, and the computational load increases exponentially with the number of voltage levels in the power electronic converter, limiting the widespread adoption and low-cost implementation of MDI.

[0004] To address the aforementioned issues, there is an urgent need to develop an efficient and computationally inefficient model predictive control method. Summary of the Invention

[0005] The purpose of this invention is to provide a two-dimensional optimization model predictive control method and device for a three-level converter. This addresses the problem of high computational complexity in traditional model predictive control methods. The proposed two-dimensional optimization method avoids voltage vector enumeration, effectively reducing the computational burden of the algorithm while retaining the advantages of model prediction.

[0006] To achieve the above objectives, the embodiments of the present invention provide the following technical solutions:

[0007] This invention provides a two-dimensional optimization model predictive control method for a three-level converter, characterized in that the method includes:

[0008] The state variables of the T-type three-level converter at time k are collected; the state information includes grid current, grid voltage, and DC side upper and lower bus capacitor voltages.

[0009] A discrete mathematical model of a three-level converter in a two-phase stationary α-β coordinate system is established, and the reference value of the grid current at time k+1 in the α-β coordinate system is obtained according to the Lagrange extrapolation theorem.

[0010] The reference voltage vector and its phase angle of the inverter at time k are calculated using the deadbeat principle.

[0011] Based on the two-dimensional optimization principle, the voltage vector region of the three-level converter is divided into sectors;

[0012] The optimal voltage vector corresponding to the sector is used as the preliminary optimal voltage vector, and a table of the preliminary optimal voltage vector correspondence for each sector is created.

[0013] Using the table of pre-optimal voltage vectors for each sector, select the pre-optimal voltage vector corresponding to the reference voltage vector at time k;

[0014] The optimal voltage vector is determined based on the pre-selected optimal voltage vector and the midpoint voltage;

[0015] The gate drive signal corresponding to the optimal voltage vector is applied to the power electronic semiconductor device of the three-level converter.

[0016] The corresponding gate drive signal is applied to the power electronic semiconductor device of the T-type three-level energy storage converter.

[0017] In one embodiment, the discrete mathematical model of the T-type three-level energy storage converter in the two-phase stationary α-β coordinate system is as follows:

[0018]

[0019] In the formula, L and R are the inductance of the filter inductor and its equivalent resistance, respectively, and T is the value of the filter inductor. s i is the sampling period; α (k), i β (k) represents the sampled value of the grid current in the α-β coordinate system at time k; i α (k+1), i β (k+1) represents the predicted grid current in the α-β coordinate system at time k+1; e α (k), e β (k) represents the sampled value of the grid voltage in the α-β coordinate system at time k; u α (k), u β (k) represents the AC output voltage of the converter in the α-β coordinate system at time k, u o (k), u o (k+1) represent the DC side midpoint voltage values ​​at times k and k+1, respectively; i o(k) represents the DC side midpoint current value at time k; C1 and C2 are the capacitance values ​​of the upper and lower DC side bus capacitors, respectively; T s This refers to the control cycle of the control system.

[0020] In one implementation, the reference value of the grid current at time k+1 calculated according to the Lagrange extrapolation theorem is:

[0021]

[0022] In the formula, These are the reference values ​​for the α-axis grid current at times k+1, k, k-1, and k-2, respectively. These are the reference values ​​for the β-axis grid current at times k+1, k, k-1, and k-2, respectively.

[0023] In one implementation, the deadbeat principle states that the predicted value of the grid-side current at time k+1 is equal to the reference value of the grid-side current obtained through the Lagrange extrapolation theorem, and then the reference voltage vector of the inverter at time k is calculated as follows:

[0024]

[0025] In the formula, These are the components of the reference voltage along the α and β axes, respectively.

[0026] The phase angle θ of the reference voltage vector is:

[0027]

[0028] In one embodiment, the voltage vector region of the three-level converter is divided into 6 large sectors, and each large sector is further divided into 6 small sectors. The 6 large sectors are divided according to the magnitude of the phase angle of the reference voltage vector. The small sectors are divided by rotating the reference voltage vector to the first large sector to obtain the equivalent phase angle, and then dividing according to the magnitude of the equivalent phase angle.

[0029] The reference voltage vector in the α-β coordinate system Positioning the voltage vector along the β-axis and α-axis, the reference voltage vector can be represented as:

[0030]

[0031] Where u ref and θ ref These are the amplitude and phase angle of the reference voltage, respectively;

[0032] The relationship between the phase angles of the six large sectors and the reference voltage vector is as follows:

[0033] The phase angle corresponding to the first major sector is 0 < θ ref ≤π / 3;

[0034] The phase angle corresponding to the second largest sector is π / 3 < θ ref ≤2π / 3;

[0035] The phase angle corresponding to the third largest sector is 2π / 3 < θ ref ≤π;

[0036] The phase angle corresponding to the fourth major sector is -π < θ ref ≤-2π / 3;

[0037] The phase angle corresponding to the 5th sector is -2π / 3 < θ ref ≤-π / 3;

[0038] The phase angle corresponding to the 6th sector is -π / 3 < θ ref ≤0.

[0039] In the two-dimensional optimization model predictive control method for three-level converters, to reduce computational complexity, the reference voltage vector is rotated to the first major sector, with the equivalent phase angle being:

[0040] θ refR =θ ref -(n-1)*π / 3

[0041] Where n is the sector where the reference voltage is located;

[0042] Equivalent reference voltage vector for:

[0043]

[0044] The relationship between the 6 small sectors and the equivalent reference voltage vector is as follows:

[0045] Phase angle limit 0≤θ refR ≤π / 6;

[0046] Boundary restrictions Corresponding to sector I;

[0047] Boundary restrictions and Corresponding to sector IV;

[0048] Boundary restrictions and Corresponding to sector V;

[0049] Boundary restrictions and Corresponding to sector II;

[0050] Boundary restrictions Corresponding to sector I;

[0051] Boundary restrictions and Corresponding to sector VI;

[0052] Boundary restrictions and Corresponding to sector V;

[0053] Boundary restrictions and Corresponding to sector III.

[0054] In one implementation, the zero voltage vector only considers the "000" state, i.e., V1, and the optimal voltage vector corresponding to the small sector in each large sector is:

[0055] In the first major sector, the optimal voltage vector for the first minor sector is V1, the optimal voltage vectors for the second minor sector are V4 and V5, the optimal voltage vectors for the third minor sector are V6 and V7, and the optimal voltage vector for the fourth minor sector is V... 22 The optimal voltage vector for sector V is V. 16 The optimal voltage vector for sector VI is V. 23 ;

[0056] In the second major sector, the optimal voltage vector for the first sub-sector is V1, the optimal voltage vectors for the second sub-sector are V6 and V7, the optimal voltage vectors for the third sub-sector are V8 and V9, and the optimal voltage vector for the fourth sub-sector is V... 23 The optimal voltage vector for sector V is V. 17 The optimal voltage vector for sector VI is V. 24 ;

[0057] In the third major sector, the optimal voltage vector for the first sub-sector is V1, the optimal voltage vectors for the second sub-sector are V8 and V9, and the optimal voltage vector for the third sub-sector is V... 10 and V 11 The optimal voltage vector for sector IV is V. 24 The optimal voltage vector for sector V is V. 18 The optimal voltage vector for sector VI is V. 25 ;

[0058] In the fourth major sector, the optimal voltage vector for the first minor sector is V1, and the optimal voltage vector for the second minor sector is V. 10 and V 11 The optimal voltage vector for sector III is V. 12 and V 13 The optimal voltage vector for sector IV is V. 25 The optimal voltage vector for sector V is V. 19 The optimal voltage vector for sector VI is V. 26 ;

[0059] In the 5th major sector, the optimal voltage vector for the first minor sector is V1, and the optimal voltage vector for the second minor sector is V. 12 and V 13 The optimal voltage vector for sector III is V. 14 and V 15 The optimal voltage vector for sector IV is V. 26 The optimal voltage vector for sector V is V. 20 The optimal voltage vector for sector VI is V. 27 ;

[0060] In the 6th major sector, the optimal voltage vector for the first minor sector is V1, and the optimal voltage vector for the second minor sector is V. 14 and V 15 The optimal voltage vectors for sector III are V4 and V5, and the optimal voltage vector for sector IV is V. 27 The optimal voltage vector for sector V is V. 21 The optimal voltage vector for sector VI is V. 22 .

[0061] In one implementation, determining the optimal voltage vector based on the pre-selected optimal voltage vector and the midpoint voltage includes:

[0062] When the preparatory optimal voltage vector is zero, medium, or large voltage vector, the preparatory optimal voltage vector is the optimal voltage vector;

[0063] When the pre-selected optimal voltage vector is a small voltage vector, the optimal voltage vector is selected from the pre-selected optimal voltage vector by combining the midpoint voltage.

[0064] In one embodiment, the small voltage vector is divided into a P-type voltage vector and an N-type voltage vector; the P-type voltage vector can increase the midpoint voltage, and the N-type voltage vector can decrease the midpoint voltage.

[0065] Based on the dynamic mathematical model of the DC side midpoint voltage, when the midpoint voltage is greater than zero, an N-type voltage vector is selected; when the midpoint voltage is less than zero, a P-type voltage vector is selected.

[0066] The present invention also provides a two-dimensional optimization model predictive control device for a three-level converter, the device comprising:

[0067] The acquisition module is used to acquire the state variables of the T-type three-level energy storage converter at time k; the state variables include grid current, grid-side voltage and capacitor voltage;

[0068] The discrete mathematical model module is used to establish a discrete mathematical model of the T-type three-level energy storage converter in a two-phase stationary α-β coordinate system, and obtain the reference value of the grid current at time k+1 based on the Lagrange extrapolation theorem.

[0069] The calculation module is used to calculate the reference voltage vector and its phase angle of the inverter at time k using the deadbeat principle;

[0070] The two-dimensional optimization voltage vector sector partitioning module is used to partition the voltage vector region of a three-level converter into sectors based on the two-dimensional optimization principle.

[0071] The module for preparing the optimal voltage vector table is used to take the optimal voltage vector corresponding to the small sector in each large sector as the prepared optimal voltage vector and create a table of the prepared optimal voltage vector correspondence for each sector.

[0072] The module for determining the optimal voltage vector uses the table of optimal voltage vectors for each sector to select the optimal voltage vector corresponding to the reference voltage vector at time k.

[0073] The optimal voltage vector confirmation module is used to determine the optimal voltage vector based on the pre-optimal voltage vector and the midpoint voltage.

[0074] The action module is used to apply the gate drive signal corresponding to the optimal voltage vector and its action time to the power electronic semiconductor device of the T-type three-level energy storage converter.

[0075] The technical solutions provided in this application embodiment may include the following beneficial effects:

[0076] This invention reduces current ripple and improves current quality while achieving voltage balance and stable operation at the midpoint of a three-level energy storage converter. The proposed hybrid model predictive control differs from traditional model predictive control with discrete output characteristics, where the optimal voltage vector is executed at the start of the control cycle. Instead, it switches at specific moments within the control cycle through calculation, resulting in a time-continuous output characteristic and improved current quality. Attached Figure Description

[0077] The accompanying drawings, as part of this invention, are provided to further illustrate the invention. The illustrative embodiments and descriptions of the invention are used to explain the invention, but do not constitute an undue limitation thereof. Clearly, the drawings described below are merely some embodiments, and those skilled in the art can obtain other drawings based on these drawings without any creative effort.

[0078] Figure 1 This is a diagram of a three-level converter topology provided in an embodiment of the present invention;

[0079] Figure 2 This is a voltage vector distribution diagram of a three-level converter provided in an embodiment of the present invention;

[0080] Figure 3This is a flowchart of the two-dimensional optimization model predictive control method for a three-level converter provided in this embodiment of the invention;

[0081] Figure 4 This is the unmodified voltage vector sector partitioning diagram of the three-level converter provided in this embodiment of the invention;

[0082] Figure 5 This is a voltage vector region diagram of the three-level energy storage converter to be improved in the embodiments of the present invention;

[0083] Figure 6 This is a voltage vector sector partitioning diagram based on two-dimensional optimization for a three-level converter provided in this embodiment of the invention;

[0084] Figure 7 The above are comparison diagrams of steady-state simulation waveforms of finite set model predictive control and two-dimensional optimization model predictive control provided in the embodiments of the present invention. Figure 7 (a) shows the steady-state waveform of the predictive control using a finite set model. Figure 7 (b) shows the steady-state waveform of the predictive control of the two-dimensional optimization model;

[0085] Figure 8 This is a comparison of dynamic simulation waveforms of finite set model predictive control and two-dimensional optimization model predictive control provided in this embodiment of the invention. Figure 8 (a) shows the dynamic waveform of the finite set model predictive control. Figure 8 (b) is the dynamic waveform of the two-dimensional optimization model predictive control.

[0086] It should be noted that these accompanying drawings and textual descriptions are not intended to limit the scope of the invention in any way, but rather to illustrate the concept of the invention to those skilled in the art by referring to specific embodiments. Detailed Implementation

[0087] To enhance understanding of the present invention, the technical solution of the present invention will be further described below in conjunction with the accompanying drawings and specific embodiments. The following embodiments are explanations of the present invention, but the present invention is not limited to the following embodiments.

[0088] It should be understood that the described embodiments are merely some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0089] Figure 1The topology of a T-type three-level energy storage converter is given. Each phase arm consists of four power electronic semiconductor devices. The DC side is composed of capacitors C1 and C2 connected in series, with identical parameters for C1 and C2. The midpoint of the DC side is defined as o, with zero potential. The grid-side filtering stage consists of a single L-type filter, with resistor R being the equivalent resistance of the filter. x i x Let x be the grid voltage and current, respectively (x = a, b, c). c1 and u c2 The voltages of capacitors C1 and C2 are respectively, u dc It is DC voltage. Each arm of the T-type three-level energy storage converter has three effective switching states: S x ∈{1, 0, -1}. Assuming the capacitor voltages are balanced, i.e., the voltage across each capacitor is equal to half the DC voltage, then the output voltage generated by these three switching states is u. xo ∈{u dc / 2,0,-u dc Table 1 summarizes the relationship between the output voltage, switching state, and gate signal generated by the converter.

[0090] Table 1 shows the relationship between output voltage, switching state, and gate signal, where x = (a, b, c).

[0091]

[0092] To establish a mathematical model for a T-type three-level energy storage converter, it is assumed that all power electronic semiconductor devices are ideal switching devices, and nonlinear effects such as on-state voltage drop and switching delay of power electronic semiconductor devices are ignored.

[0093] According to Kirchhoff's voltage law, the dynamic response of the grid current in a three-phase stationary coordinate system is as follows:

[0094]

[0095] The T-type three-level energy storage converter has a total of 27 (3) switching states. 3 ) types, such as Figure 2 As shown. In the α-β coordinate system, these switching states generate a total of 19 non-redundant voltage vectors and 8 redundant voltage vectors. Based on the magnitude of the output voltage, the voltage vectors are divided into zero vectors (V1-V3), small vectors (V4-V5), and small vectors (V6-V7). 15 ), medium vector (V) 16 -V 21 ) and large vector (V) 22 -V 27 There is only one type of zero vector, with two redundant vectors; there are six types of small vectors, each with one redundant vector; there are six types of medium and large vectors, with no redundant vectors. The various voltage vectors are shown in Table 2.

[0096] Table 2 Voltage Vector Table

[0097]

[0098] like Figure 3 As shown in the disclosed embodiment, a hybrid model predictive control method for a T-type three-level energy storage converter is provided. This method specifically includes the following steps:

[0099] Step S100: Collect the state variables of the T-type three-level energy storage converter at time k.

[0100] Specifically, the grid current i at time k is collected using voltage and current sensors. a (k), i b (k), i c (k), grid voltage e a (k), e b (k), e c (k), and capacitor voltage u c1 (k), u c2 (k).

[0101] Step S200: Establish a discrete mathematical model of the T-type three-level energy storage converter in a two-phase stationary α-β coordinate system, and obtain the reference value of the grid current at time k+1 according to the Lagrange extrapolation theorem.

[0102] A three-phase stationary coordinate system can be converted to a two-phase stationary coordinate system using the Clarke transformation. The Clarke transformation is as follows:

[0103]

[0104] The mathematical model of the three-level energy storage converter in the two-phase stationary coordinate system is as follows:

[0105]

[0106] Using the forward Euler method, the discrete mathematical model of the T-type three-level energy storage converter in a two-phase stationary coordinate system is as follows:

[0107]

[0108] In the formula, L and R are the inductance of the filter inductor and its equivalent resistance, respectively, and T is the value of the filter inductor. s i is the sampling period; α (k), i β (k) represents the sampled value of the grid current in the α-β coordinate system at time k; i α (k+1), i β (k+1) represents the predicted grid current in the α-β coordinate system at time k+1; e α(k), e β (k) represents the sampled value of the grid voltage in the α-β coordinate system at time k; u α (k), u β (k) represents the AC output voltage of the converter in the α-β coordinate system at time k.

[0109]

[0110] The DC side midpoint voltage is:

[0111] u o =u c2 -u c1

[0112] Assuming equal capacitor voltages and balanced grid currents, the dynamic process of the DC-side midpoint voltage can be modeled as follows:

[0113]

[0114] i o The DC-side midpoint current is given by the following formula:

[0115] i o =|S abc |i abc

[0116] In the formula, |S abc |=[1-|S a |,1-|S b |,1-|S c |],i abc =[i a i b i c ].

[0117] The predicted value of the midpoint voltage is:

[0118]

[0119] In the formula, u o (k), u o (k+1) represent the DC side midpoint voltage values ​​at times k and k+1, respectively; i o (k) represents the DC side midpoint current value at time k; C1 and C2 are the capacitance values ​​of the upper and lower DC side bus capacitors, respectively; T s This refers to the control cycle of the control system.

[0120] According to the Lagrange extrapolation theorem, in the α-β coordinate system, the reference value of the grid current at time k+1 is:

[0121]

[0122] In the formula, in the formula, These are the reference values ​​for the α-axis grid current at times k+1, k, k-1, and k-2, respectively. These are the reference values ​​for the β-axis grid current at times k+1, k, k-1, and k-2, respectively.

[0123] Step S300: Calculate the reference voltage vector and its phase angle of the inverter at time k using the deadbeat principle.

[0124] The deadbeat principle states that the predicted value of the grid-side current at time k+1 is equal to the reference value of the grid-side current obtained through the Lagrange extrapolation theorem, and then the reference voltage vector of the inverter at time k is calculated as follows:

[0125]

[0126] In the formula, These are the components of the reference voltage along the α and β axes, respectively.

[0127] The phase angle θ of the reference voltage vector is:

[0128]

[0129] Step S400: Divide the voltage vector region of the three-level converter into sectors based on the two-dimensional optimization principle.

[0130] In the α-β coordinate system, for a reference voltage vector The voltage vector can be located sequentially along the β-axis and α-axis. To facilitate the division of the two-dimensional voltage vector sectors, regions are divided along the symmetry axes of adjacent voltage vectors in both the α-axis and β-axis directions, as shown in Tables 3 and 4. Therefore, after determining the reference voltage vector, the optimal voltage vector can be selected simply by locating it sequentially according to Tables 3 and 4, without enumerating all feasible voltage vectors, thus greatly reducing the computational load. Figure 4 This is a voltage vector region division diagram based on the above analysis.

[0131] Table 3. Division of β-axis coordinate regions

[0132]

[0133] Table 4. Division of α-axis coordinate regions

[0134]

[0135] While the aforementioned two-dimensional sector partitioning effectively reduces computational load, it has some shortcomings. (Using the reference voltage vector...) For example, according to Tables 3 and 4, V4 or V5 will ultimately be selected as the optimal voltage vector and implemented in the next control cycle. However, among all voltage vectors, V6 and V7 are closest to the reference voltage vector and should be considered the optimal voltage vectors. Areas where the above problem exists include... Figure 5 As shown. To address the above problems, a voltage vector sector partitioning method based on two-dimensional optimization is proposed, as follows: Figure 6 As shown.

[0136] In this embodiment of the application, the voltage vector region of the three-level converter is divided into sectors based on the two-dimensional optimization principle, including:

[0137] The voltage vector region of the three-level converter is divided into 6 large sectors, and each large sector is further divided into 6 small sectors. The 6 large sectors are divided according to the phase angle of the reference voltage vector. The small sectors are divided by rotating the reference voltage vector to the first large sector to obtain the equivalent phase angle, and then dividing according to the magnitude of the equivalent phase angle.

[0138] The reference voltage vector in the α-β coordinate system Positioning the voltage vector along the β-axis and α-axis, the reference voltage vector can be represented as:

[0139]

[0140] In the formula, u ref and θ ref These represent the amplitude and phase angle of the reference voltage, respectively.

[0141] The voltage vector diagram is divided into six large sectors, and the relationship between the sector and the phase angle of the reference voltage vector is shown in Table 5.

[0142] Table 5. Sector Division

[0143] <![CDATA[θ ref ]]> Large sector <![CDATA[0<θ ref ≤π / 3]]> 1 <![CDATA[π / 3<θ ref ≤2π / 3]]> 2 <![CDATA[2π / 3<θ ref ≤π]]> 3 <![CDATA[-π<θ ref ≤-2π / 3]]> 4 <![CDATA[-2π / 3<θ ref ≤-π / 3]]> 5 <![CDATA[-π / 3<θ ref ≤0]]> 6

[0144] To reduce computational complexity, the reference voltage will be uniformly rotated to sector 1, with an equivalent phase angle of:

[0145] θ refR =θ ref -(n-1)*π / 3

[0146] In the formula, n represents the sector where the reference voltage is located.

[0147] Equivalent reference voltage vector for:

[0148]

[0149] Each large sector is divided into 6 smaller sectors. The relationship between the smaller sectors and the equivalent reference voltage vector is shown in Table 6.

[0150] Table 6. Sector Division

[0151]

[0152] Step S500: Use the optimal voltage vector corresponding to the divided sector as the preliminary optimal voltage vector, and create a table of the corresponding preliminary optimal voltage vectors for each sector.

[0153] Combination Figure 6 The optimal voltage vectors for the smaller sectors within each large sector are shown in Table 7. Specifically, to reduce common-mode voltage and switching frequency, the zero voltage vector only considers the "000" state, i.e., V1.

[0154] Table 7. Correspondence of Preliminary Optimal Voltage Vectors for Each Sector

[0155]

[0156]

[0157] Step S600: Using the table of pre-optimal voltage vectors for each sector, select the pre-optimal voltage vector corresponding to the reference voltage vector at time k.

[0158] For example, when the large sector of the reference voltage vector at time k is 1 and the small sector is I, the corresponding pre-optimal voltage vector is V1. When the large sector of the reference voltage vector at time k is 1 and the small sector is II, the corresponding pre-optimal voltage vectors are V4 and V5.

[0159] Step S700: Determine the optimal voltage vector based on the pre-selected optimal voltage vector and the midpoint voltage.

[0160] As shown in Table 7, when the small sector is II or III, there are two potential optimal voltage vectors. This is due to the redundancy of the small voltage vectors. The two small voltage vectors at the same location have the same control effect on the grid current; however, they have opposite effects on the midpoint voltage. Therefore, it is necessary to combine the midpoint voltage to select the final optimal voltage vector.

[0161] Based on the dynamic mathematical model of the DC-side midpoint voltage derived in step S200, the effect of the small voltage vector on the midpoint voltage is related to the midpoint current i. o Relevant. Specifically, the midpoint current i corresponding to the small voltage vector. o As shown in Table 8.

[0162] Table 8 Relationship between voltage vector and midpoint current

[0163] Small voltage vector <![CDATA[i o ]]> Small voltage vector <![CDATA[i o ]]> <![CDATA[V4]]> <![CDATA[-i a ]]> <![CDATA[V5]]> <![CDATA[i a ]]> <![CDATA[V6]]> <![CDATA[-i c ]]> <![CDATA[V7]]> <![CDATA[i c ]]> <![CDATA[V8]]> <![CDATA[-i b ]]> <![CDATA[V9]]> <![CDATA[i b ]]> <![CDATA[V 10 ]]> <![CDATA[-i a ]]> <![CDATA[V 11 ]]> <![CDATA[i a ]]> <![CDATA[V 12 ]]> <![CDATA[-i c ]]> <![CDATA[V 13 ]]> <![CDATA[i c ]]> <![CDATA[V 14 ]]> <![CDATA[-i b ]]> <![CDATA[V 15 ]]> <![CDATA[i b ]]>

[0164] When the pre-selected optimal voltage vector is zero, medium, or large, the pre-selected optimal voltage vector is unique, i.e., it is the optimal voltage vector. When the pre-selected optimal voltage vector is a small voltage vector, it is necessary to combine the midpoint voltage and select the optimal voltage vector from the pre-selected optimal voltage vectors.

[0165] Small voltage vectors are classified into P-type and N-type voltage vectors. P-type voltage vectors can increase the midpoint voltage, while N-type voltage vectors can decrease it. Combining this with the dynamic mathematical model of the DC-side midpoint voltage derived in step S200, it can be seen that when i o When i is greater than zero, the voltage vector is an N-type voltage vector; when i o When the voltage is less than zero, the voltage vector is a P-type voltage vector. Therefore, when the midpoint voltage is greater than zero, an N-type voltage vector is selected; when the midpoint voltage is less than zero, a P-type voltage vector is selected.

[0166] Step S800: Apply the gate drive signal corresponding to the optimal voltage vector to the power electronic semiconductor device of the three-level converter.

[0167] After a series of calculations in steps S100-S600, the control cycle value, comparison value and other information are transmitted to the FPGA through the DSP's communication module. The FPGA is then used to implement functions such as pulse distribution and dead-time delay for the power devices.

[0168] The following is an embodiment of the two-dimensional optimization model predictive control device for a three-level converter according to the present invention, which can be used to execute the embodiment of the two-dimensional optimization model predictive control method for a three-level converter according to the present invention. For details not disclosed in the embodiment of the two-dimensional optimization model predictive control device for a three-level converter according to the present invention, please refer to the embodiment of the two-dimensional optimization model predictive control method for a three-level converter according to the present invention.

[0169] In one embodiment, a two-dimensional optimization model predictive control device for a three-level converter is proposed, the device comprising:

[0170] The acquisition module is used to acquire the state variables of the T-type three-level energy storage converter at time k; the state variables include grid current, grid-side voltage and capacitor voltage;

[0171] The discrete mathematical model module is used to establish a discrete mathematical model of the T-type three-level energy storage converter in a two-phase stationary α-β coordinate system, and obtain the reference value of the grid current at time k+1 based on the Lagrange extrapolation theorem.

[0172] The calculation module is used to calculate the reference voltage vector and its phase angle of the inverter at time k using the deadbeat principle;

[0173] The two-dimensional optimization voltage vector sector partitioning module is used to partition the voltage vector region of a three-level converter into sectors based on the two-dimensional optimization principle.

[0174] The module for preparing the optimal voltage vector table is used to take the optimal voltage vector corresponding to the small sector in each large sector as the prepared optimal voltage vector and create a table of the prepared optimal voltage vector correspondence for each sector.

[0175] The module for determining the optimal voltage vector uses the table of optimal voltage vectors for each sector to select the optimal voltage vector corresponding to the reference voltage vector at time k.

[0176] The optimal voltage vector confirmation module is used to determine the optimal voltage vector based on the pre-optimal voltage vector and the midpoint voltage.

[0177] The action module is used to apply the gate drive signal corresponding to the optimal voltage vector and its action time to the power electronic semiconductor device of the T-type three-level energy storage converter.

[0178] The functional modules in this embodiment of the invention can be integrated into one processing module, or each unit can exist as a separate physical entity, or two or more units can be integrated into one module. The integrated module can be implemented in hardware or as a software functional module.

[0179] As a specific example of this invention, a three-level converter simulation model was built in MATLAB / Simulink to test and verify the invention. The three-level converter's AC side is connected to a 220V AC power grid, and the DC side is powered by a battery at 600V. The DC side capacitor is 2200μF, and the filter inductor is 4mH. The sampling and control period is 100μs. To highlight the performance advantages of this invention, the control performance of traditional finite set model predictive control and the two-dimensional optimization model predictive control proposed in this invention were compared.

[0180] Figure 7 This chart compares the steady-state simulation results of traditional finite set model predictive control and two-dimensional optimization model predictive control when the grid reference current is 50A. The simulation waveforms include the three-phase grid current and the DC-side upper and lower bus capacitor voltages. Figure 7 (a) shows the steady-state waveform of the predictive control using a finite set model. Figure 7(b) shows the steady-state waveform of the two-dimensional optimization model predictive control. The simulation waveforms demonstrate that both control strategies can achieve stable control of the three-level converter. The current THD of finite set model predictive control and two-dimensional optimization model predictive control are 3.14% and 2.78%, respectively, with the two-dimensional optimization model predictive control exhibiting better current quality. Both finite set model predictive control and two-dimensional optimization model predictive control can keep the midpoint voltage below 5V, demonstrating good capacitor voltage control capability.

[0181] Figure 8 This is a comparison of steady-state dynamic simulation results between traditional finite control set model predictive control and two-dimensional optimization model predictive control. The simulation waveforms include the phase a grid current and the DC side upper and lower bus capacitor voltages. Figure 8 (a) shows the dynamic waveform of the finite set model predictive control. Figure 8 (b) shows the dynamic waveforms of the two-dimensional optimization model predictive control. The two control strategies exhibit similar dynamic performance. When the current reference value jumps from 25A to 50A, the dynamic response time of both control strategies is approximately 2ms. When the current reference value jumps from 50A to 25A, the dynamic response time of both control strategies is approximately 1ms. Simulation results show that regardless of the current change trend, the output current can quickly track the current command change, indicating that the present invention has a fast dynamic response. During the dynamic process, both control strategies exhibit good capacitor voltage balance capability.

[0182] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-described technical content to create equivalent embodiments without departing from the scope of the present invention. Any simple modifications, equivalent changes, and alterations made to the above embodiments based on the technical essence of the invention without departing from the scope of the present invention shall still fall within the scope of the present invention.

Claims

1. A two-dimensional optimization model predictive control method for a three-level converter, characterized in that, The method includes: The state variables of the T-type three-level converter at time k are collected; the state variables include grid current, grid voltage, and DC side upper and lower bus capacitor voltages. A discrete mathematical model of a three-level converter in a two-phase stationary α-β coordinate system is established, and the reference value of the grid current at time k+1 in the α-β coordinate system is obtained according to the Lagrange extrapolation theorem. The reference voltage vector and its phase angle of the inverter at time k are calculated using the deadbeat principle. Based on the two-dimensional optimization principle, the voltage vector region of the three-level converter is divided into sectors; The method of dividing the voltage vector region of the three-level converter into sectors based on the two-dimensional optimization principle includes: The voltage vector region of the three-level converter is divided into 6 large sectors, and each large sector is further divided into 6 small sectors. The 6 large sectors are divided according to the magnitude of the phase angle of the reference voltage vector. The small sectors are divided by rotating the reference voltage vector to the first large sector to obtain the equivalent phase angle, and then dividing according to the magnitude of the equivalent phase angle. The reference voltage vector in the α-β coordinate system ( , The voltage vector is located along two dimensions, the β-axis and the α-axis, and the reference voltage vector is represented as follows: , In the formula, and These are the magnitude and phase angle of the reference voltage vector, respectively; The relationship between the phase angles of the six large sectors and the reference voltage vector is as follows: The phase angle corresponding to the first major sector is 0 < ≤ π / 3; The phase angle corresponding to the second largest sector is π / 3. ≤ 2π / 3; The phase angle corresponding to the third largest sector is 2π / 3. ≤ π; The phase angle corresponding to the fourth major sector is -π< ≤ -2π / 3; The phase angle corresponding to the 5th sector is -2π / 3 < ≤ -π / 3; The phase angle corresponding to the 6th sector is -π / 3. ≤ 0; To reduce computational complexity, the reference voltage vector is rotated to the first largest sector, with the equivalent phase angle being: , In the formula, n is the sector where the reference voltage vector is located; Equivalent reference voltage vector ( , )for: , The relationship between the 6 small sectors and the equivalent reference voltage vector is as follows: When the phase angle is limited to hour; Boundary restrictions Corresponding to the I-th sector, It is a DC voltage; Boundary restrictions and This corresponds to sector IV; Boundary restrictions and This corresponds to sector V. Boundary restrictions , and This corresponds to sector II; When the phase angle is limited to hour, Boundary restrictions This corresponds to the I-th sector; Boundary restrictions and This corresponds to sector VI; Boundary restrictions and This corresponds to sector V; Boundary restrictions , and This corresponds to sector III; The voltage vectors corresponding to the sectors are used as preliminary optimal voltage vectors, and a table of preliminary optimal voltage vectors for each sector is created. Using the table of pre-optimal voltage vectors for each sector, select the pre-optimal voltage vector corresponding to the reference voltage vector at time k; The optimal voltage vector is determined based on the pre-selected optimal voltage vector and the midpoint voltage; The gate drive signal corresponding to the optimal voltage vector is applied to the power electronic semiconductor device of the three-level converter.

2. The two-dimensional optimization model predictive control method for a three-level converter according to claim 1, characterized in that, The discrete mathematical model of the T-type three-level converter in the two-phase stationary α-β coordinate system is as follows: , , In the formula, L and R are the inductance of the filter inductor and its equivalent resistance, respectively, and T is the value of the filter inductor. s The sampling period; , The sampled value of the power grid current in the α-β coordinate system at time k; , The predicted value of the power grid current in the α-β coordinate system at time k+1; , The voltage sample value of the power grid in the α-β coordinate system at time k; , Let k be the AC output voltage of the converter in the α-β coordinate system at time k. , These are the DC side midpoint voltage values ​​at times k and k+1, respectively; C1 represents the DC side midpoint current value at time k; C2 and C1 represent the capacitance values ​​of the upper and lower bus capacitors on the DC side, respectively.

3. The two-dimensional optimization model predictive control method for a three-level converter according to claim 2, characterized in that, According to the Lagrange extrapolation theorem, in the α-β coordinate system, the reference value of the grid current at time k+1 is: , In the formula, , , , These are the reference values ​​for the α-axis grid current at times k+1, k, k-1, and k-2, respectively. , , , These are the reference values ​​for the β-axis grid current at times k+1, k, k-1, and k-2, respectively.

4. The two-dimensional optimization model predictive control method for a three-level converter according to claim 3, characterized in that, The deadbeat principle states that the predicted value of the grid current at time k+1 is equal to the reference value of the grid current obtained through the Lagrange extrapolation theorem, and then the reference voltage vector of the inverter at time k is calculated as follows: , In the formula, , These are the components of the reference voltage vector along the α and β axes, respectively. Phase angle of the reference voltage vector for: 。 5. The two-dimensional optimization model predictive control method for a three-level converter according to claim 4, characterized in that, The zero voltage vector only considers the "000" state, i.e., V1. The optimal voltage vector corresponding to the small sector in each large sector is: In the first major sector, the optimal voltage vector for the first minor sector is V1, the optimal voltage vectors for the second minor sector are V4 and V5, the optimal voltage vectors for the third minor sector are V6 and V7, and the optimal voltage vector for the fourth minor sector is V... 22 The optimal voltage vector for sector V is V. 16 The optimal voltage vector for sector VI is V. 23 ; In the second major sector, the optimal voltage vector for the first sub-sector is V1, the optimal voltage vectors for the second sub-sector are V6 and V7, the optimal voltage vectors for the third sub-sector are V8 and V9, and the optimal voltage vector for the fourth sub-sector is V... 23 The optimal voltage vector for sector V is V. 17 The optimal voltage vector for sector VI is V. 24 ; In the third major sector, the optimal voltage vector for the first sub-sector is V1, the optimal voltage vectors for the second sub-sector are V8 and V9, and the optimal voltage vector for the third sub-sector is V... 10 and V 11 The optimal voltage vector for sector IV is V. 24 The optimal voltage vector for sector V is V. 18 The optimal voltage vector for sector VI is V. 25 ; In the fourth major sector, the optimal voltage vector for the first minor sector is V1, and the optimal voltage vector for the second minor sector is V. 10 and V 11 The optimal voltage vector for sector III is V. 12 and V 13 The optimal voltage vector for sector IV is V. 25 The optimal voltage vector for sector V is V. 19 The optimal voltage vector for sector VI is V. 26 ; In the 5th major sector, the optimal voltage vector for the first minor sector is V1, and the optimal voltage vector for the second minor sector is V. 12 and V 13 The optimal voltage vector for sector III is V. 14 and V 15 The optimal voltage vector for sector IV is V. 26 The optimal voltage vector for sector V is V. 20 The optimal voltage vector for sector VI is V. 27 ; In the 6th major sector, the optimal voltage vector for the first minor sector is V1, and the optimal voltage vector for the second minor sector is V. 14 and V 15 The optimal voltage vectors for sector III are V4 and V5, and the optimal voltage vector for sector IV is V. 27 The optimal voltage vector for sector V is V. 21 The optimal voltage vector for sector VI is V. 22 .

6. The two-dimensional optimization model predictive control method for a three-level converter according to claim 1, characterized in that, The process of determining the optimal voltage vector based on the pre-defined optimal voltage vector and the midpoint voltage includes: When the preparatory optimal voltage vector is a zero, medium, or large voltage vector, the preparatory optimal voltage vector is the optimal voltage vector. When the pre-selected optimal voltage vector is a small voltage vector, the optimal voltage vector is selected from the pre-selected optimal voltage vector by combining the midpoint voltage.

7. The two-dimensional optimization model predictive control method for a three-level converter according to claim 6, characterized in that, Small voltage vectors are divided into P-type voltage vectors and N-type voltage vectors; the P-type voltage vector can increase the midpoint voltage, and the N-type voltage vector can decrease the midpoint voltage. The midpoint voltage is derived by combining the dynamic mathematical model of the DC side midpoint voltage; when the midpoint voltage is greater than zero, an N-type voltage vector is selected; when the midpoint voltage is less than zero, a P-type voltage vector is selected.

8. A two-dimensional optimization model predictive control device for a three-level converter, characterized in that, The apparatus for implementing the two-dimensional optimization model predictive control method for a three-level converter as described in claim 1 includes: The acquisition module is used to acquire the state variables of the T-type three-level converter at time k; the state variables include grid current, grid voltage, and DC side upper and lower bus capacitor voltages; The discrete mathematical model module is used to establish a discrete mathematical model of the T-type three-level converter in a two-phase stationary α-β coordinate system, and to obtain the reference value of the grid current at time k+1 based on the Lagrange extrapolation theorem. The calculation module is used to calculate the reference voltage vector and its phase angle of the inverter at time k using the deadbeat principle; The two-dimensional optimization voltage vector sector partitioning module is used to partition the voltage vector region of a three-level converter into sectors based on the two-dimensional optimization principle. The module for preparing the optimal voltage vector table is used to take the optimal voltage vector corresponding to the small sector in each large sector as the prepared optimal voltage vector and create a table of the prepared optimal voltage vector correspondence for each sector. The module for determining the optimal voltage vector uses the table of optimal voltage vectors for each sector to select the optimal voltage vector corresponding to the reference voltage vector at time k. The optimal voltage vector confirmation module is used to determine the optimal voltage vector based on the pre-optimal voltage vector and the midpoint voltage. The action module is used to apply the gate drive signal corresponding to the optimal voltage vector and its action time to the power electronic semiconductor device of the T-type three-level converter.

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