CN107681915A - Based on the multi-electrical level inverter combination method and device for determining frequency finite aggregate model prediction - Google Patents

Based on the multi-electrical level inverter combination method and device for determining frequency finite aggregate model prediction Download PDF

Info

Publication number
CN107681915A
CN107681915A CN201710963903.3A CN201710963903A CN107681915A CN 107681915 A CN107681915 A CN 107681915A CN 201710963903 A CN201710963903 A CN 201710963903A CN 107681915 A CN107681915 A CN 107681915A
Authority
CN
China
Prior art keywords
inverter
phase
voltage
detection circuit
grid
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN201710963903.3A
Other languages
Chinese (zh)
Inventor
吕建国
马丙辉
王纪东
阎亦然
范林勇
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Nanjing University of Science and Technology
Original Assignee
Nanjing University of Science and Technology
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Nanjing University of Science and Technology filed Critical Nanjing University of Science and Technology
Priority to CN201710963903.3A priority Critical patent/CN107681915A/en
Publication of CN107681915A publication Critical patent/CN107681915A/en
Pending legal-status Critical Current

Links

Classifications

    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02M—APPARATUS FOR CONVERSION BETWEEN AC AND AC, BETWEEN AC AND DC, OR BETWEEN DC AND DC, AND FOR USE WITH MAINS OR SIMILAR POWER SUPPLY SYSTEMS; CONVERSION OF DC OR AC INPUT POWER INTO SURGE OUTPUT POWER; CONTROL OR REGULATION THEREOF
    • H02M7/00—Conversion of ac power input into dc power output; Conversion of dc power input into ac power output
    • H02M7/42—Conversion of dc power input into ac power output without possibility of reversal
    • H02M7/44—Conversion of dc power input into ac power output without possibility of reversal by static converters
    • H02M7/48—Conversion of dc power input into ac power output without possibility of reversal by static converters using discharge tubes with control electrode or semiconductor devices with control electrode
    • H02M7/483—Converters with outputs that each can have more than two voltages levels
    • H02M7/487—Neutral point clamped inverters
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers

Landscapes

  • Engineering & Computer Science (AREA)
  • Power Engineering (AREA)
  • Inverter Devices (AREA)

Abstract

The invention discloses a kind of based on the multi-electrical level inverter combination method and device of determining frequency finite aggregate model prediction.This method is：Three-phase networking electric current and three-phase power grid voltage are sampled first, and Clark conversion is carried out to sampled value；Then using frequency model prediction algorithm is determined, under conditions of maintained switch frequency-invariant, control and DC side restraint of NP potential are tracked to three-phase networking electric current.The device includes main power circuit, control circuit and detection circuit, wherein main power circuit includes NPC three-phase tri-levels inverter and L-type low pass filter, and detection circuit includes networking current detection circuit, power grid voltage detection circuit and DC side mid-point voltage detection circuit.The present invention under conditions of maintained switch frequency-invariant, can realize the finite aggregate model prediction cutting-in control of multi-electrical level inverter.

Description

Multilevel inverter grid-connected method and device based on fixed-frequency finite set model prediction
Technical Field
The invention relates to the technical field of direct current-alternating current converters of electric energy conversion devices, in particular to a multilevel inverter grid-connected method and device based on fixed-frequency finite set model prediction.
Background
An NPC (Neutral Point Clamped) three-phase three-level grid-connected inverter is a multi-level inverter widely applied to a medium-and-large-capacity distributed grid-connected power generation system, and the control strategy mainly comprises the following steps: PI control, PR control, hysteresis control and finite set model predictive control. The finite set model predictive control has the advantages of strong robustness, rapidity, easiness in digital realization, consideration of inverter nonlinearity and the like, and is widely applied to grid-connected control of the multi-level inverter.
However, the finite set model predictive control belongs to a nonlinear control strategy, and when the finite set model predictive control is applied to the grid-connected control of the multilevel inverter, a constant switching frequency cannot be formed, so that the design of a grid-connected filter of the inverter at the later stage becomes very difficult, and the problems of electromagnetic compatibility and the like can be brought.
Disclosure of Invention
The invention aims to provide a multilevel inverter grid-connected method and device based on fixed-frequency finite set model prediction, so as to realize multilevel inverter finite set model prediction grid-connected control with constant switching frequency.
The technical solution for realizing the purpose of the invention is as follows: a multilevel inverter grid-connected method based on fixed-frequency finite set model prediction adopts a finite set model prediction control algorithm with constant switching frequency, and comprises the following steps:
step one, sampling and transforming: detecting the network access current to obtain a, b and c three-phase network access current i a(k) 、i b(k) 、i c(k) And to i a(k) 、i b(k) 、i c(k) Clark transformation to obtain i α(k) 、i β(k) (ii) a The three-phase grid voltage e of a, b and c is obtained by detecting the grid voltage a(k) 、e b(k) 、e c(k) And to e a(k) 、e b(k) 、e c(k) Clark transformation to obtain e α(k) 、e β(k) (ii) a According to the three-phase grid voltage obtained by detection, the active power P of the given network is combined * 0 And given network-access reactive power Q * 0 Calculating the network access reference current under the alpha beta coordinate systemDetecting the capacitor voltage to obtain the midpoint voltage deltav of the direct current side c(k) ；
Step two, traversing calculation: binding i α(k) 、i β(k) 、e α(k) 、e β(k) 、Δv c(k) 、i a(k) 、i b(k) 、i c(k) Calculating the network access current i of the (k + 1) th sampling period corresponding to the (27) groups of phase switch function states according to the voltage vector value of the alternating current output side of the inverter and the phase switch function state corresponding to the voltage vector value of the alternating current output side of the inverter and the midpoint voltage model of the direct current side of the inverter α(k+1)(i) 、i β(k+1)(i) And the DC side midpoint voltage Deltav c(k+1)(i) Wherein i =1, 2 \ 823027;
step three, establishing an objective function g, and calculating objective function values g corresponding to 27 groups of phase switch function states (i) I =1, 2 \ 823027 as the optimal 3 groups of phase switching function states S _one 、S _two 、S _three And corresponding duty cycle d _one 、d _two 、d _three The basis of (1);
step four, fixed frequency output: according to a symmetrical output mode, outputting a first minimum value g of the target function g _one Corresponding switch state S _one And its duty cycle d _one The second to last decimal value g of the objective function g _two Corresponding switch state S _two And its duty cycle d _two Third to last decimal value g of objective function g _three Corresponding switch state S _three And its duty cycle d _three Controlling the inverter;
and step five, waiting for the end of the sampling period time, returning to the step one, and entering the next cycle.
Go toStep two, the traversal calculation: binding i α(k) 、i β(k) 、e α(k) 、e β(k) 、Δv c(k) 、i a(k) 、i b(k) 、i c(k) Calculating the network access current i of the (k + 1) th sampling period corresponding to the (27) groups of phase switch function states according to the voltage vector value of the alternating current output side of the inverter and the phase switch function state corresponding to the voltage vector value of the alternating current output side of the inverter and the midpoint voltage model of the direct current side of the inverter α(k+1)(i) 、i β(k+1)(i) And the DC side midpoint voltage Deltav c(k+1)(i) Wherein i =1, 2 \ 823027, the concrete formula is as follows:
wherein, L is the inductance value of the filter inductor, R is the resistance value of the equivalent resistance after the bridge arm resistance of the inverter and the filter inductor resistance are folded, i =1, 2 \8230, 27, u α(i) 、u β(i) Is the voltage vector value, S, of the i-th inverter AC output side a(i) 、S b(i) 、S c(i) And the voltage vector value of the i-th group of inverters at the alternating current output side corresponds to the phase switching function state.
Further, the step three establishes an objective function g, and calculates the objective function value g corresponding to the state of 27 groups of phase switch functions (i) I =1, 2 \ 823027 as the optimal 3 groups of phase switching function states S _one 、S _two 、S _three And corresponding duty cycle d _one 、d _two 、d _three The concrete formula is as follows:
wherein i =1,2……27，λ dc Is the DC side midpoint voltage weight coefficient.
Further, the fixed frequency output in the step four is: according to a symmetrical output mode, outputting a first minimum value g of the target function g _one Corresponding switch state S _one And its duty cycle d _one The second to last decimal value g of the objective function g _two Corresponding switch state S _two And its duty cycle d _two Third to last decimal value g of objective function g _three Corresponding switch state S _three And its duty cycle d _three The inverter is controlled as follows:
(4.1) selecting the switching period T s According to the three steps, 27 sets of objective function values g are calculated in a traversing mode (i) Wherein i =1, 2 \823027, and the smallest 3 groups g are selected _one 、g _two 、g _three And g is a radical of _one <g _two <g _three Calculate g _one Corresponding duty cycle d _one 、g _two Corresponding duty cycle d _two And g _three Corresponding duty cycle d _three The concrete formula is as follows:
(4.2) during a switching period T s The method comprises the following steps of (1) time length and sequence: 0.5T s *d _three 、0.5T s *d _two 、T s *d _one 、0.5T s *d _two 、0.5T s *d _three Symmetric output switch state S _three 、S _two 、S _one 、S _two 、S _three 。
A multi-level inverter grid-connected device based on fixed-frequency finite set model prediction comprises a main power circuit, a control circuit and a detection circuit, wherein the main power circuit comprises an input voltage source V dc NPC three-phase three-level inverter, L-type low-pass filter and three-phase power grid e a 、e b 、e c Wherein a voltage source V is input dc The output end of the NPC three-phase three-level inverter is connected with the input end of an L-shaped low-pass filter, and the output end of the L-shaped low-pass filter is connected with a three-phase power grid e a 、e b 、e c Connecting;
the detection circuit comprises a network access current detection circuit, a power grid voltage detection circuit and a direct current side midpoint voltage detection circuit, wherein the input end of the network access current detection circuit is connected with a three-phase power grid, the output end of the network access current detection circuit is connected with the first input end of a control circuit, the input end of the power grid voltage detection circuit is connected with the three-phase power grid, the output end of the power grid voltage detection circuit is connected with the second input end of the control circuit, the input end of the direct current side midpoint voltage detection circuit is connected with a direct current side capacitor of an inverter, and the output end of the direct current side midpoint voltage detection circuit is connected with the third input end of the control circuit;
the control circuit comprises a reference current calculation module, a Clark transformation module and a prediction calculation module.
Further, the control circuit adopts DSP chip TMS320F28335.
Compared with the prior art, the invention has the remarkable advantages that: (1) The constant switching frequency control can be realized only by performing simple software algorithm improvement on the basis of the traditional finite set model prediction control; and (2) the method is simple and reliable and is easy to realize digitally.
Drawings
Fig. 1 is a schematic structural diagram of a multilevel inverter grid-connected device based on fixed-frequency finite set model prediction.
FIG. 2 is a schematic diagram of a NPC three-phase three-level grid-connected inverter main power circuit.
Fig. 3 is an output voltage vector diagram of an alternating current side of the NPC three-phase three-level grid-connected inverter.
FIG. 4 is a flow chart of a fixed frequency finite set model predictive control algorithm.
Fig. 5 is a diagram of dc side midpoint voltage after predictive control using a fixed frequency finite set model.
Fig. 6 is a diagram of network-access active power after predictive control by using a fixed-frequency finite-set model.
Fig. 7 is a diagram of network-access reactive power after predictive control by using a fixed-frequency finite-set model.
Fig. 8 is a graph of actual network access current and given network access current after predictive control using a fixed-frequency finite-set model.
FIG. 9 shows a voltage u of an AC output side (a) of the inverter with respect to a DC side midpoint (O) after predictive control using a fixed frequency finite set model ao The spectral distribution of (a).
Detailed Description
The invention is further described in detail below with reference to the drawings and specific embodiments.
Referring to fig. 1, the multilevel inverter grid-connected device based on fixed-frequency finite set model prediction of the invention comprises a main power circuit 1, a control circuit 5 and a detection circuit, wherein the main power circuit 1 comprises an input voltage source V dc NPC three-phase three-level inverter, L-type low-pass filter and three-phase power grid e a 、e b 、e c Wherein a voltage source V is input dc The output end of the NPC three-phase three-level inverter is connected with the input end of an L-shaped low-pass filter, and the output end of the L-shaped low-pass filter is connected with a three-phase power grid e a 、e b 、e c Connecting;
the detection circuit comprises a network access current detection circuit 2, a power grid voltage detection circuit 3 and a direct current side midpoint voltage detection circuit 4, wherein the input end of the network access current detection circuit 2 is connected with a three-phase power grid, the output end of the network access current detection circuit 2 is connected with the first input end of a control circuit 5, the input end of the power grid voltage detection circuit 3 is connected with the three-phase power grid, the output end of the power grid voltage detection circuit 3 is connected with the second input end of the control circuit 5, the input end of the direct current side midpoint voltage detection circuit 4 is connected with an inverter direct current side capacitor, and the output end of the direct current side midpoint voltage detection circuit 4 is connected with the third input end of the control circuit 5; the control circuit 5 comprises a reference current calculation module, a Clark transformation module and a prediction calculation module. The control circuit 5 adopts a DSP chip TMS320F28335.
1. NPC three-phase three-level grid-connected inverter discrete mathematical model and objective function
FIG. 2 is a NPC three-phase three-level grid-connected inverter main power circuit, the system adopts a three-phase three-wire system connection method, the invention sets: DC side capacitor C 1 ＝C 2 = C, and C is sufficiently large, DC side capacitance voltageInductance value L of three-phase filter inductor a ＝L b ＝L c = L, equivalent resistance R of inverter AC side a ＝R b ＝R c ＝R。
Defining: phase switching function
Wherein: i = a, b, c, S i Marking as state P, S, =1 i Marking as state O, S with =0 i And =1 is recorded as state N.
The voltage on the ac output side (a, b, c) of the inverter with respect to the dc side midpoint (O):
using a Clark transformation:
the voltage vector distribution of the AC output side (a, b, c) of the inverter relative to the midpoint (O) of the DC side in the α β coordinate system is obtained, and as shown in FIG. 3, the three-phase three-level inverter has 3 3 =27 switch states, corresponding to output 27 voltage vectors, 19 different voltage vectors, "OPN" in fig. 3 represents S a ＝0，S b ＝1，S c =1, and so on for the rest.
Obtaining a voltage balance equation of an alternating current output side of the inverter according to kirchhoff voltage law:
wherein v is no Clark transformation is carried out on two ends of the formula (4) for the voltage of a power grid voltage neutral point (n) relative to a direct current side middle point (O) to obtain a voltage balance equation of an inverter alternating current output side under an alpha beta coordinate system:
taking the sampling period (i.e. the switching period) as T s Using a first order forward difference equation (6):
obtaining a discrete mathematical model of the network access current under the alpha beta coordinate system:
in the formula i α(k) 、i β(k) For the kth sampling period, the value u of the sampling value of the three-phase network access current after Clark transformation α(k) 、u β(k) For the coordinate value of the voltage vector used for the kth sampling period in the α β coordinate system, e α(k) 、e β(k) For the kth sampling period, the value of the sampling value of the grid voltage after Clark conversion, i α(k+1) 、i β(k+1) The predicted calculation value of the grid-connected current in the k +1 th sampling period under the alpha beta coordinate system is obtained.
The current balance equation of the midpoint (O) of the direct current side can be obtained according to kirchhoff current law:
i o ＝i c1 -i c2 (8)
wherein:
let the DC side midpoint voltage Deltav c ＝v c1 -v c2 And simultaneously substituting expressions (9), (10) and (11) into expression (8) to obtain:
taking the sampling period as T s Using a first order forward difference equation (13):
obtaining a discrete mathematical model of the midpoint voltage on the direct current side under a natural coordinate system:
in the formula,. DELTA.v c(k) Is a sampling value of the midpoint voltage on the direct current side of the kth sampling period under a natural coordinate system, delta v c(k+1) Predicting and calculating the midpoint voltage of the DC side of the (k + 1) th sampling period in a natural coordinate system a(k) 、S b(k) 、S c(k) The phase switching function state value adopted for the kth sampling period.
The model predictive control belongs to the optimal control category, an objective function g related to a controlled variable is defined as the basis of optimal selection, and the method needs to control the three-phase network access current i a 、i b 、i c Clark transform value of (i) α 、i β Tracking a network-entry reference current And suppressing the DC-side midpoint voltage Deltav c The objective function g is defined as follows:
wherein λ is dc Is a DC side midpoint voltage weight coefficient, λ dc The larger, for Δ v c The better the inhibition effect, the relatively worse the current tracking effect; lambda dc The smaller, for Δ v c The worse the suppression effect, the better the current tracking effect becomes relatively.
2. Fixed-frequency finite set model prediction control algorithm
After a single sampling period is used for prediction calculation, the traditional finite set model prediction control only outputs a voltage vector corresponding to the minimum objective function value, which is the root cause of unfixed switching frequency of the inverter. Therefore, the invention adopts an optimal 3-voltage vector synthesis output method to ensure that the switching frequency of the inverter is constant, and as shown in figure 4, the method comprises the following specific steps:
step one, sampling and transforming: detecting the network access current to obtain a, b and c three-phase network access current i a(k) 、i b(k) 、i c(k) And to i a(k) 、i b(k) 、i c(k) Clark transformation to obtain i α(k) 、i β(k) (ii) a The three-phase grid voltage e of a, b and c is obtained by detecting the grid voltage a(k) 、e b(k) 、e c(k) And to e a(k) 、e b(k) 、e c(k) Clark transformation to obtain e α(k) 、e β(k) (ii) a According to the three-phase power grid voltage obtained by detection, the active power P of the given power grid is combined * 0 And given network-access reactive power Q * 0 Calculating the network access reference current under the alpha beta coordinate systemDetecting the capacitor voltage to obtain the midpoint voltage delta v of the direct current side c(k) ；
Step two, traversing calculation: binding i α(k) 、i β(k) 、e α(k) 、e β(k) 、Δv c(k) 、i a(k) 、i b(k) 、i c(k) Calculating the network access current i of the (k + 1) th sampling period corresponding to the (27) groups of phase switch function states according to the voltage vector value of the alternating current output side of the inverter and the phase switch function state corresponding to the voltage vector value of the alternating current output side of the inverter and the midpoint voltage model of the direct current side of the inverter α(k+1)(i) 、i β(k+1)(i) And the DC side midpoint voltage Deltav c(k+1)(i) Wherein i =1, 2 \ 823027, the concrete formula is as follows:
wherein, L is the inductance value of the filter inductor, and R is the bridge arm resistance and the filter inductor resistance of the inverterThe resistance values of the equivalent resistors after combination are i =1, 2\8230, 823027, u α(i) 、u β(i) Is the voltage vector value, S, of the i-th inverter AC output side a(i) 、S b(i) 、S c(i) And the voltage vector value of the i-th group of inverters at the alternating current output side corresponds to the phase switching function state.
Step three, establishing an objective function g, and calculating objective function values g corresponding to 27 groups of phase switch function states (i) I =1, 2 \ 823027 as the optimal 3 groups of phase switching function states S _one 、S _two 、S _three And corresponding duty cycle d _one 、d _two 、d _three The concrete formula is as follows:
wherein i =1, 2, 8230, 823027, λ dc Is the DC side midpoint voltage weight coefficient.
Step four, fixed frequency output: outputting the reciprocal first small value g of the target function g according to a symmetrical output mode _one Corresponding switch state S _one And its duty cycle d _one The second to last decimal value g of the objective function g _two Corresponding switch state S _two And its duty cycle d _two The third to last decimal value g of the objective function g _three Corresponding switch state S _three And its duty cycle d _three The inverter is controlled as follows:
(4.1) selecting the switching period T s According to the 27 groups of objective function values g calculated by the three steps of traversal (i) Wherein i =1, 2 \ 823027, the smallest of which 3 groups g are selected _one 、g _two 、g _three And g is a radical of _one <g _two <g _three Calculate g _one Corresponding duty cycle d _one 、g _two Corresponding duty cycle d _two And g _three Corresponding duty cycle d _three The concrete formula is as follows:
(4.2) during a switching period T s The middle time length and the sequence are as follows: 0.5T s *d _three 、0.5T s *d _two 、T s *d _one 、0.5T s *d _two 、0.5T s *d _three Symmetrical output switch state S _three 、S _two 、S _one 、S _two 、S _three 。
And step five, waiting for the end of the sampling period time, returning to the step one, and entering the next cycle.
Example 1
Simulation results for the examples are shown in the figure: fig. 5 dc-side midpoint voltage, fig. 6 grid active power, fig. 7 grid reactive power, fig. 8 actual grid current and reference grid current, fig. 9 voltage u of the inverter ac output side (a) relative to the dc-side midpoint (O) ao The simulation parameters are shown in table 1.
TABLE 1 simulation parameters
Grid voltage e a (＝e b ＝e c ) Amplitude value 311(V)
V dc 800(V)
C 1 (＝C 2 ) 500e-6(F)
λ dc 1
T s 25e-6(s)
R 1(Ω)
L 4e-3(H)
P * 0 10(kW)
Q * 0 500(Var)
From the simulation result of the embodiment 1, it can be seen that the multilevel inverter grid-connected device and the method for fixed-frequency finite set model predictive control can suppress the midpoint voltage on the direct current side and control the actual grid-connected current to track the given reference current under the condition of keeping the switching frequency constant, thereby realizing the control of the grid-connected active power and the reactive power.
In conclusion, the multilevel inverter grid-connected device and the method for fixed-frequency finite set model predictive control can solve the problem that the switching frequency of the traditional model predictive control is not constant under the condition that the algorithm complexity is hardly increased.

Claims (6)

1. A multilevel inverter grid-connected method based on fixed-frequency finite set model prediction is characterized in that a finite set model prediction control algorithm with constant switching frequency is adopted, and the method comprises the following steps:
step one, sampling and transformation: the network access current is detected to obtain a, b and c three-phase network access current i a(k) 、i b(k) 、i c(k) And to i a(k) 、i b(k) 、i c(k) Clark transformation is carried out to obtain i α(k) 、i β(k) (ii) a The three-phase grid voltage e of a, b and c is obtained by detecting the grid voltage a(k) 、e b(k) 、e c(k) And to e a(k) 、e b(k) 、e c(k) Clark transformation to obtain e α(k) 、e β(k) (ii) a According to the three-phase power grid voltage obtained by detection, the active power P of the given power grid is combined * 0 And given network-access reactive power Q * 0 Calculating the network access reference current i under the alpha beta coordinate system * α(k) 、i * β(k) (ii) a Detecting the capacitor voltage to obtain the midpoint voltage delta v of the direct current side c(k) ；
Step two, traversing calculation: binding i α(k) 、i β(k) 、e α(k) 、e β(k) 、Δv c(k) 、i a(k) 、i b(k) 、i c(k) Calculating the network access current i of the (k + 1) th sampling period corresponding to the (27) groups of phase switch function states according to the voltage vector value of the alternating current output side of the inverter and the phase switch function state corresponding to the voltage vector value of the alternating current output side of the inverter and the midpoint voltage model of the direct current side of the inverter α(k+1)(i) 、i β(k+1)(i) And the midpoint voltage Deltav on the DC side c(k+1)(i) Wherein i =1, 2 \ 823027;
step three, establishing a targetA function g for calculating the target function values g corresponding to the states of 27 groups of phase switch functions (i) I =1, 2 \ 823027 as the optimal 3 groups of phase switching function states S _one 、S _two 、S _three And corresponding duty cycle d _one 、d _two 、d _three The basis of (1);
step four, fixed frequency output: according to a symmetrical output mode, outputting a first minimum value g of the target function g _one Corresponding switch state S _one And its duty cycle d _one The second to last decimal value g of the objective function g _two Corresponding switch state S _two And its duty cycle d _two The third to last decimal value g of the objective function g _three Corresponding switch state S _three And its duty cycle d _three Controlling the inverter;
and step five, waiting for the end of the sampling period time, returning to the step one, and entering the next cycle.
2. The multilevel inverter grid-connected method based on fixed-frequency finite-set model prediction of claim 1, wherein the traversal calculation in the second step is as follows: binding i α(k) 、i β(k) 、e α(k) 、e β(k) 、Δv c(k) 、i a(k) 、i b(k) 、i c(k) Calculating the network access current i of the (k + 1) th sampling period corresponding to the (27) groups of phase switch function states according to the voltage vector value of the alternating current output side of the inverter and the phase switch function state corresponding to the voltage vector value of the alternating current output side of the inverter and the midpoint voltage model of the direct current side of the inverter α(k+1)(i) 、i β(k+1)(i) And the midpoint voltage Deltav on the DC side c(k+1)(i) Wherein i =1, 2 \ 823027, the concrete formula is as follows:
wherein, L is the inductance value of the filter inductor, R is the resistance value of the equivalent resistance after the bridge arm resistance of the inverter and the filter inductor resistance are folded, i =1, 2 \8230, 27, u α(i) 、u β(i) Is the voltage vector value, S, of the i-th inverter AC output side a(i) 、S b(i) 、S c(i) And the phase switching function state corresponding to the voltage vector value of the i-th group of inverters on the alternating current output side.
3. The multilevel inverter grid-connected method based on fixed-frequency finite set model prediction according to claim 1, characterized in that the target function g is established in the third step, and the target function values g corresponding to 27 groups of phase switch function states are calculated (i) I =1, 2 \ 823027 as the optimal 3 groups of phase switching function states S _one 、S _two 、S _three And corresponding duty cycle d _one 、d _two 、d _three The concrete formula is as follows:
wherein, i =1, 2 \8230 \823027 \ 823027 dc Is the DC side midpoint voltage weight coefficient.
4. The multilevel inverter grid-connected method based on the fixed-frequency finite set model prediction of claim 1, wherein the fixed-frequency output of the step four is as follows: outputting the reciprocal first small value g of the target function g according to a symmetrical output mode _one Corresponding switch state S _one And its duty cycle d _one The second to last decimal value g of the objective function g _two Corresponding switch state S _two And its duty cycle d _two The third to last decimal value g of the objective function g _three Corresponding switch state S _three And its duty cycle d _three The inverter is controlled as follows:
(4.1) selecting the switching period T s According to the 27 groups of objective function values g calculated by the three steps of traversal (i) Wherein i =1, 2 \ 823027, the smallest of which 3 groups g are selected _one 、g _two 、g _three And g is _one <g _two <g _three Calculate g _one Corresponding duty cycle d _one 、g _two Corresponding duty cycle d _two And g _three Corresponding duty cycle d _three The concrete formula is as follows:
(4.2) during a switching period T s The method comprises the following steps of (1) time length and sequence: 0.5T s *d _three 、0.5T s *d _two 、T s *d _one 、0.5T s *d _two 、0.5T s *d _three Symmetrical output switch state S _three 、S _two 、S _one 、S _two 、S _three 。
5. The multilevel inverter grid-connected device based on fixed-frequency finite set model prediction is characterized by comprising a main power circuit (1), a control circuit (5) and a detection circuit, wherein the main power circuit (1) comprises an input voltage source V dc NPC three-phase three-level inverter, L-type low-pass filter and three-phase power grid e a 、e b 、e c Wherein a voltage source V is input dc The output end of the NPC three-phase three-level inverter is connected with the input end of an L-shaped low-pass filter, and the output end of the L-shaped low-pass filter is connected with the input end of the three-phase three-level inverterElectric network e a 、e b 、e c Connecting;
the detection circuit comprises a network access current detection circuit (2), a power grid voltage detection circuit (3) and a direct current side midpoint voltage detection circuit (4), wherein the input end of the network access current detection circuit (2) is connected with a three-phase power grid, the output end of the network access current detection circuit (2) is connected with the first input end of a control circuit (5), the input end of the power grid voltage detection circuit (3) is connected with the three-phase power grid, the output end of the power grid voltage detection circuit (3) is connected with the second input end of the control circuit (5), the input end of the direct current side midpoint voltage detection circuit (4) is connected with an inverter direct current side capacitor, and the output end of the direct current side midpoint voltage detection circuit (4) is connected with the third input end of the control circuit (5);
the control circuit (5) comprises a reference current calculation module, a Clark transformation module and a prediction calculation module.
6. The multilevel inverter grid-connected device based on the fixed-frequency finite set model prediction of claim 5, wherein the control circuit (5) adopts a DSP chip TMS320F28335.
CN201710963903.3A 2017-10-17 2017-10-17 Based on the multi-electrical level inverter combination method and device for determining frequency finite aggregate model prediction Pending CN107681915A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201710963903.3A CN107681915A (en) 2017-10-17 2017-10-17 Based on the multi-electrical level inverter combination method and device for determining frequency finite aggregate model prediction

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201710963903.3A CN107681915A (en) 2017-10-17 2017-10-17 Based on the multi-electrical level inverter combination method and device for determining frequency finite aggregate model prediction

Publications (1)

Publication Number Publication Date
CN107681915A true CN107681915A (en) 2018-02-09

Family

ID=61140568

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201710963903.3A Pending CN107681915A (en) 2017-10-17 2017-10-17 Based on the multi-electrical level inverter combination method and device for determining frequency finite aggregate model prediction

Country Status (1)

Country Link
CN (1) CN107681915A (en)

Cited By (14)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108696170A (en) * 2018-04-25 2018-10-23 华南理工大学 Determine frequency finite aggregate model predictive control method for two level three-phase inverters
CN109038673A (en) * 2018-08-27 2018-12-18 上海理工大学 The model prediction optimal control method of photovoltaic generating system
CN109981056A (en) * 2019-03-28 2019-07-05 广东志成冠军集团有限公司 A kind of output control method of the digital power amplifier based on NPC inverter
CN110045610A (en) * 2019-04-18 2019-07-23 中国地质大学（武汉） Inverter modified multistep model predictive control method, equipment and storage equipment
CN110429629A (en) * 2019-08-16 2019-11-08 广西电网有限责任公司电力科学研究院 A kind of energy accumulation current converter and its control method based on NPC three-level topology
CN110572054A (en) * 2019-09-06 2019-12-13 西南交通大学 Space vector modulation model voltage prediction method
CN110601579A (en) * 2019-11-01 2019-12-20 中国工程物理研究院材料研究所 Three-level inverter model prediction direct power control method
CN110932309A (en) * 2019-10-30 2020-03-27 东北大学 Inverter control system and method based on ACSF-MPC and PI dual-mode switching
CN111009924A (en) * 2019-12-26 2020-04-14 中国工程物理研究院材料研究所 Wide-range change compensation method for filter inductance value of single-phase three-level inverter
CN111030486A (en) * 2019-12-06 2020-04-17 合肥工业大学 Non-parameter finite set model prediction control method of three-level grid-connected inverter
CN111541267A (en) * 2020-04-07 2020-08-14 南通大学 Multi-vector model prediction control method for two-level grid-connected inverter
CN111697857A (en) * 2020-06-29 2020-09-22 浙江大学 Novel MPC control method suitable for single-phase cascade rectifier of direct-current micro-grid
CN111740632A (en) * 2020-06-29 2020-10-02 国网辽宁省电力有限公司电力科学研究院 quasi-Z-source inverter discrete time average model prediction control device and method
CN112260290A (en) * 2020-10-13 2021-01-22 合肥工业大学 Grid-connected control method of voltage source type permanent magnet synchronous wind turbine generator under weak grid

Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20080188957A1 (en) * 2006-10-13 2008-08-07 Cutler Charles R Adaptive multivariable MPC controller with LP constraints
CN107171584A (en) * 2017-06-22 2017-09-15 南京理工大学 The model predictive control method and device of NPC three-phase tri-level combining inverters

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20080188957A1 (en) * 2006-10-13 2008-08-07 Cutler Charles R Adaptive multivariable MPC controller with LP constraints
CN107171584A (en) * 2017-06-22 2017-09-15 南京理工大学 The model predictive control method and device of NPC three-phase tri-level combining inverters

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
M. RIVERA: "Predictive Current Control with fixed switching frequency for an NPC converter", 《2015 IEEE 24TH ISIE 》 *

Cited By (21)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108696170A (en) * 2018-04-25 2018-10-23 华南理工大学 Determine frequency finite aggregate model predictive control method for two level three-phase inverters
CN109038673A (en) * 2018-08-27 2018-12-18 上海理工大学 The model prediction optimal control method of photovoltaic generating system
CN109038673B (en) * 2018-08-27 2022-05-27 上海理工大学 Model prediction optimization control method of photovoltaic power generation system
CN109981056A (en) * 2019-03-28 2019-07-05 广东志成冠军集团有限公司 A kind of output control method of the digital power amplifier based on NPC inverter
CN109981056B (en) * 2019-03-28 2023-06-27 广东志成冠军集团有限公司 Output control method of digital power amplifier based on NPC inverter
CN110045610A (en) * 2019-04-18 2019-07-23 中国地质大学（武汉） Inverter modified multistep model predictive control method, equipment and storage equipment
CN110429629A (en) * 2019-08-16 2019-11-08 广西电网有限责任公司电力科学研究院 A kind of energy accumulation current converter and its control method based on NPC three-level topology
CN110429629B (en) * 2019-08-16 2022-06-24 广西电网有限责任公司电力科学研究院 Control method of energy storage converter based on NPC three-level topology
CN110572054B (en) * 2019-09-06 2021-05-14 西南交通大学 Space vector modulation model voltage prediction method
CN110572054A (en) * 2019-09-06 2019-12-13 西南交通大学 Space vector modulation model voltage prediction method
CN110932309A (en) * 2019-10-30 2020-03-27 东北大学 Inverter control system and method based on ACSF-MPC and PI dual-mode switching
CN110601579A (en) * 2019-11-01 2019-12-20 中国工程物理研究院材料研究所 Three-level inverter model prediction direct power control method
CN111030486A (en) * 2019-12-06 2020-04-17 合肥工业大学 Non-parameter finite set model prediction control method of three-level grid-connected inverter
CN111009924A (en) * 2019-12-26 2020-04-14 中国工程物理研究院材料研究所 Wide-range change compensation method for filter inductance value of single-phase three-level inverter
CN111541267A (en) * 2020-04-07 2020-08-14 南通大学 Multi-vector model prediction control method for two-level grid-connected inverter
CN111697857A (en) * 2020-06-29 2020-09-22 浙江大学 Novel MPC control method suitable for single-phase cascade rectifier of direct-current micro-grid
CN111740632A (en) * 2020-06-29 2020-10-02 国网辽宁省电力有限公司电力科学研究院 quasi-Z-source inverter discrete time average model prediction control device and method
CN111697857B (en) * 2020-06-29 2021-05-11 浙江大学 MPC control method of single-phase cascade rectifier suitable for direct-current micro-grid
CN111740632B (en) * 2020-06-29 2021-08-24 国网辽宁省电力有限公司电力科学研究院 quasi-Z-source inverter discrete time average model prediction control device and method
CN112260290A (en) * 2020-10-13 2021-01-22 合肥工业大学 Grid-connected control method of voltage source type permanent magnet synchronous wind turbine generator under weak grid
CN112260290B (en) * 2020-10-13 2022-09-13 合肥工业大学 Grid-connected control method of voltage source type permanent magnet synchronous wind turbine generator under weak grid

Similar Documents

Publication Publication Date Title
CN107681915A (en) Based on the multi-electrical level inverter combination method and device for determining frequency finite aggregate model prediction
CN110867887B (en) NPC three-level inverter optimal sequence model prediction control device and method
CN107546994B (en) Multi-level inverter grid-connected system and method
CN111953223B (en) Neutral point voltage balancing method for three-phase four-wire system three-level converter
WO2012048518A1 (en) Direct-current side control method for midline arm control model of four bridge arm photovoltaic inverter
CN111416540B (en) Multi-level converter midpoint potential rapid balance control system and method
Rong et al. Output feedback control of single-phase UPQC based on a novel model
CN112865173A (en) Photovoltaic grid-connected inverter resonance suppression method based on model predictive control
CN109378989A (en) A kind of small-signal modeling and method for analyzing stability of single-phase cascade isolated island type inversion system
CN112310991B (en) Energy storage converter improved finite set model prediction control method based on disturbance observation
CN111555339A (en) Converter grid-connected general sequence impedance model for stability analysis and modeling method
CN111224416B (en) Cascaded energy storage converter parallel control method and system based on SOC balance
CN109347352B (en) Cascaded converter submodule capacitor voltage balance control method
Devi et al. Solar PV array integrated UPQC for power quality improvement based on modified GI
Salim et al. Shunt active filter based on three–level (NPC) Inverter using Current and DC voltage artificial neural network controllers
CN115276439A (en) LCL type grid-connected inverter resonance suppression method adapting to impedance change of weak grid
Zhong et al. $ H^ infty $ control of the neutral point in four-wire three-phase DC–AC converters
CN115333345A (en) Common mode current resonance suppression method based on virtual common mode resistor
CN109802405B (en) Inverter resonance suppression method based on power grid voltage abnormal state feedback
MACİT et al. Modelling and Simulation of 1 MW Grid-Connected PV System Regulated by Sliding Mode Control, Model Predictive Control and PI Control
Laxmi et al. Different control strategies for Unified Power Quality Conditioner at load side
Bansal et al. Control of multilevel inverter as shunt active power filter using maximum Versoria criterion
Chatterjee et al. Single-phase average power measurement using instantaneous power theory in a fixed point processor
Kuo et al. FPGA control of a single-phase T-type NPC grid inverter for low THD and robust performance
CN113224963B (en) Output control method of T-type three-level voltage type inverter and related equipment

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
RJ01 Rejection of invention patent application after publication

Application publication date: 20180209

RJ01 Rejection of invention patent application after publication