A trajectory tracking based model predictive control method for voltage source inverter

Abstract

The present application relates to a kind of voltage source inverter model predictive control method based on trajectory tracking, comprising the following steps: S1, establish voltage source inverter LC filter prediction model, the LC filter prediction model is calculated next control period output reference voltage by given current output reference voltage reference angular frequency and amplitude;S2, multiple target output reference voltage points are set in single control period based on trajectory tracking's model predictive control module, voltage trajectory tracking is carried out, and the optimal next control period output reference voltage is obtained, to replace LC filter prediction model next control period output reference voltage;S3, the duty ratio of three-phase full-bridge upper and lower bridge arm switch is calculated based on carrier's space vector adjustment module, and three-phase full-bridge upper and lower bridge arm switch tube of voltage source inverter is sequentially controlled, the synthesis of output reference voltage is realized.Affirmative effect is that it has good steady state and dynamic performance, and the required computing power is less.

Description

Technical Field

[0001] This invention relates to the field of AC microgrid technology, and specifically to a model predictive control method for voltage source inverters based on trajectory tracking. Background Technology

[0002] With the rapid increase in the penetration rate of renewable energy generation in the power system, distributed generation, as a flexible and reliable power supply method, can not only reduce the use of fossil fuels but also actively participate in the demand response of the distribution network. To address the issue of the coordinated and reliable operation of a large number of diverse distributed power sources in the distribution network, microgrid technology is considered a reliable solution. Among them, AC microgrids, due to their simple structure and flexible networking capabilities with the main power grid, have occupied a major position in the development of microgrids.

[0003] In the hierarchical control architecture of microgrids, the cascaded structure of voltage and current dual closed loops can precisely control the output voltage and current, serving as a prerequisite and foundation for supporting distributed power generation and achieving economical dispatch, and is currently widely used in engineering practice. However, its cascaded loop control architecture limits its control bandwidth and restricts its dynamic response speed, making it difficult to adapt to the complex operating conditions in microgrids with a large number of new energy power generation and energy storage systems connected.

[0004] Thanks to the rapid development of digital signal processors (DSPs) and their heuristic operation in recent years, model predictive control (MMC), as a novel nonlinear control method, is a powerful alternative to the aforementioned control architectures. The basic principle of MMC is to establish a mathematical model of the system, using the current state as the initial state of the control optimization problem, and then predicting and controlling the system's state in the next control cycle by optimizing the solution based on different control actions. Finite set MMC is the most widely used due to its ease of implementation and ability to easily incorporate constraints; however, it only has one switching state within a control cycle, resulting in a wide distribution of harmonic frequencies. Deadbeat control has also received widespread attention due to its simple control principle and short algorithm execution time; however, it does not support the simultaneous achievement of multiple optimization objectives.

[0005] This invention makes technical improvements to the model predictive control method for voltage source inverters. Summary of the Invention

[0006] The purpose of this invention is to propose a model predictive control method that is suitable for single-layer control of AC microgrids, has good steady-state and dynamic performance, and requires less computing power.

[0007] To achieve the above objectives, the technical solution adopted by this invention is a model predictive control method for voltage source inverters based on trajectory tracking, used for control of voltage source inverters in islanded mode of AC microgrids, including the following steps:

[0008] S1. Establish a prediction model for the LC filter of the voltage source inverter. The prediction model calculates the output reference voltage for the next control cycle by giving the reference angular frequency and amplitude of the current output reference voltage.

[0009] S2. The model predictive control module based on trajectory tracking sets multiple target output reference voltage points within a single control cycle. It performs voltage trajectory tracking by optimizing the new trajectory determined by the current output reference voltage and the output reference voltage of the next control cycle to minimize the error between the reference voltage trajectory and the current trajectory. The optimal output reference voltage for the next control cycle is then obtained to replace the output reference voltage of the LC filter predictive model for the next control cycle.

[0010] S3. The carrier-based space vector adjustment module calculates the duty cycle of the upper and lower bridge arm switches of the three-phase full-bridge using the carrier-based space vector modulation method, and orderly controls the upper and lower bridge arm switches of the three-phase full-bridge of the voltage source inverter to achieve the synthesis of the output reference voltage obtained by voltage trajectory tracking in step S2.

[0011] Preferably, in the above-described model predictive control method for a voltage source inverter based on trajectory tracking, the LC filter prediction model in step S1 is: , where L f and C f These are the inductance and capacitance values ​​of the LC filter, respectively, v i and v f These are the input and output voltages of the LC filter, i f and i o These are the input and output currents of the LC filter, T. s Let k be the sampling period, and k be the current control period.

[0012] Preferably, in the above-described model predictive control method for voltage source inverters based on trajectory tracking, the cost function of the optimization problem in step S2 is: Where N is the number of target output reference voltage points. It refers to setting multiple target output reference voltage points within a single control cycle. and For optimal output reference voltage In the two-phase rotating coordinate system, α and β components represent the voltage sample value at the current moment. Output reference voltage to the optimal next control cycle The direction vector, ti yes and The time interval between, e i Then it is because and The determined new trajectory and the reference voltage trajectory at t i Error at that point.

[0013] Preferably, in the above-mentioned model predictive control method for voltage source inverters based on trajectory tracking, step S2 involves sampling the voltage at the current moment through a sampling module and converting the three-phase output voltage into α and β components in a two-phase rotating coordinate system through a Clark coordinate transformation module.

[0014] Preferably, in the above-described model predictive control method for a voltage source inverter based on trajectory tracking, step S5 involves carrier-based space vector modulation using the following formula: , , ,in, It is the three-phase input reference voltage ( ), d x It is the three-phase duty cycle, V dc V is the DC bus voltage, and V0 is the zero-sequence voltage.

[0015] The present invention provides a model predictive control method for voltage source inverters based on trajectory tracking, which has the following advantages: 1. It is applicable to the single-layer control of AC microgrids, replacing the cascaded structure of voltage and current dual closed loops in traditional bottom-layer control, enabling the voltage source inverter to operate stably under rated conditions; 2. The trajectory tracking-based model predictive control method can consider tracking errors and the dynamic changes of the reference waveform within a single control cycle, exhibiting good steady-state and dynamic performance, and requiring less computational power; 3. Compared to widely used linear controllers, the trajectory tracking-based model predictive control method can guarantee voltage quality under nonlinear load conditions; 4. Compared to existing model predictive control methods, the trajectory tracking-based model predictive control method has smaller steady-state errors and lower total harmonic distortion (THD), which is of great significance for the control of voltage source inverters in AC microgrids. Attached Figure Description

[0016] Figure 1 This is a control block diagram of a model predictive control method for voltage source inverters based on trajectory tracking.

[0017] Figure 2 This is a schematic diagram of the trajectory tracking waveform for a voltage source inverter model predictive control method based on trajectory tracking when N=2.

[0018] Figure 3This is a time-domain simulation diagram of a voltage source inverter using proportional-integral control under linear load conditions.

[0019] Figure 4 This is a time-domain simulation diagram of a voltage source inverter using finite set model predictive control under linear load conditions.

[0020] Figure 5 This is a time-domain simulation diagram of a voltage source inverter using deadbeat control under linear load conditions.

[0021] Figure 6 This is a time-domain simulation diagram of a voltage source inverter using trajectory tracking model predictive control under linear load conditions.

[0022] Figure 7 This is a spectrum comparison chart of voltage source inverters under linear load conditions using proportional-integral control, finite set model predictive control, deadbeat control, and trajectory tracking model predictive control.

[0023] Figure 8 This is a time-domain simulation diagram of a voltage source inverter using proportional-integral control under nonlinear load conditions.

[0024] Figure 9 This is a time-domain simulation diagram of a voltage source inverter using finite set model predictive control under nonlinear load conditions.

[0025] Figure 10 This is a time-domain simulation diagram of a voltage source inverter using deadbeat control under nonlinear load conditions.

[0026] Figure 11 This is a time-domain simulation diagram of a voltage source inverter using trajectory tracking model predictive control under nonlinear load conditions.

[0027] Figure 12 A comparison chart of the spectrum of voltage source inverters using proportional-integral control, finite set model predictive control, deadbeat control, and trajectory tracking model predictive control under nonlinear load conditions. Detailed Implementation

[0028] The features and exemplary embodiments of various aspects of the present invention will now be described in detail. In the following detailed description, numerous specific details are set forth in order to provide a thorough understanding of the invention. However, it will be apparent to those skilled in the art that the invention may be practiced without requiring some of these specific details. The following description of embodiments is merely intended to provide a better understanding of the invention by illustrating examples of the invention. The invention is by no means limited to any specific configurations and algorithms presented below, but covers any modifications, substitutions, and improvements to elements, components, and algorithms without departing from the inventive concept. In the accompanying drawings and the following description, well-known structures and techniques are not shown in order to avoid unnecessarily obscuring the invention.

[0029] Example

[0030] This embodiment implements a model predictive control method for voltage source inverters based on trajectory tracking.

[0031] This embodiment presents a model predictive control method for voltage source inverters based on trajectory tracking, applied to voltage source inverters in islanded mode. Compared to traditional linear controllers, this method improves control bandwidth and dynamic response capability, avoids cumbersome parameter adjustment processes, and ensures voltage quality under nonlinear load conditions. Compared to existing model predictive control methods, it has better total harmonic distortion and root mean square error.

[0032] This embodiment presents a model predictive control method for voltage source inverters based on trajectory tracking, applicable to the first-level control of AC microgrids. It replaces the cascaded structure of voltage and current dual closed loops in traditional low-level control, enabling the voltage source inverter to operate stably under rated conditions. This embodiment of the model predictive control method for voltage source inverters based on trajectory tracking is based on the following program modules: a sampling module, a Clark coordinate transformation module, a carrier-based space vector modulation module, and a trajectory tracking-based model predictive control module. This embodiment of the model predictive control method for voltage source inverters based on trajectory tracking, building upon traditional model predictive control methods, considers the dynamic changes of the reference waveform within a single control cycle, establishes a cost function that minimizes the control error, and improves power quality by adjusting the voltage reference value at the next moment. Compared to existing model predictive control methods, this embodiment considers the dynamic changes of the reference waveform within a single control cycle, exhibiting good steady-state and dynamic performance, requiring less computational power, and showing promising application prospects.

[0033] This embodiment presents a model predictive control method for a voltage source inverter based on trajectory tracking. The specific implementation steps are as follows:

[0034] The prediction model of the LC filter can be expressed as:

[0035]

[0036] Among them, L f and C f These are the inductance and capacitance values ​​of the LC filter, respectively; v i and v f These are the input and output voltages of the LC filter, respectively; i f and i o These are the input and output currents of the LC filter, respectively; T s Let k be the sampling period and k be the current control period. Given the reference angular frequency and amplitude of the output voltage, the output reference voltage for the next control period can be calculated. Thus, the input reference voltage for the next control cycle can be obtained through the predictive model. .

[0037] By controlling the switching transistors of the upper and lower arms of the three-phase full-bridge inverter in an orderly manner, the input reference voltage can be controlled. The synthesis. To simplify the modulation process, the duty cycle of the three-phase switch is calculated using a carrier-based space vector modulation method:

[0038]

[0039]

[0040]

[0041] in, It is the three-phase input reference voltage ( ); d x It is the three-phase duty cycle; V dc V is the DC bus voltage; v0 is the zero-sequence voltage. The specific calculation process is shown in equations 1, 2, and 3.

[0042] Figure 1 This is a control block diagram of a model predictive control method for voltage source inverters based on trajectory tracking. (See attached diagram.) Figure 1 As shown in the figure, this embodiment presents a model predictive control method for a voltage source inverter based on trajectory tracking, along with the corresponding equivalent circuit diagram and control block diagram of the voltage source inverter. During model predictive control, due to limitations in switching frequency and sampling frequency, it is difficult to simultaneously consider the dynamic changes of the waveform within a single control cycle. To account for the dynamic changes of the reference voltage within a single control cycle and achieve voltage trajectory tracking, multiple target points are set within a single control cycle. An optimal output reference voltage is obtained through the following optimization problem. , to replace the output reference voltage .

[0043]

[0044] Where N is the number of target points set; and For optimal output reference voltage The α and β components in the two-phase rotating coordinate system; s represents the voltage sample value at the current moment. To the optimal output reference voltage The direction vector; t i yes and The time interval between; e i Then it is because and The determined new trajectory and the reference voltage trajectory at t i The error at that point. By minimizing the sum of squared distances of this error, the optimal output reference voltage is finally calculated. .

[0045] Figure 2 This is a schematic diagram of the trajectory tracking waveform for a voltage source inverter model predictive control method based on trajectory tracking when N=2. (See attached diagram.) Figure 2 As shown, the working principle of a model predictive control based on trajectory tracking when N=2 is illustrated. In addition to the target point at the end of the control cycle, an additional target point is added in the middle of the control cycle. Furthermore, due to discretization and errors caused by system parameters, it is difficult to achieve ideal zero-error tracking. The error between the sampled value and the reference value at this moment is also included in the above cost function.

[0046] The following are simulation comparison results of trajectory tracking model predictive control, proportional-integral control, finite set model predictive control, and deadbeat control under linear and nonlinear load conditions in this embodiment.

[0047] Figure 3 This is a time-domain simulation diagram of a voltage source inverter using proportional-integral control under linear load conditions. Figure 4 This is a time-domain simulation diagram of a voltage source inverter using finite set model predictive control under linear load conditions. Figure 5 This is a time-domain simulation diagram of a voltage source inverter using deadbeat control under linear load conditions. Figure 6 This is a time-domain simulation diagram of a voltage source inverter using trajectory tracking model predictive control under linear load conditions. (Attached) Figure 3 To the attached Figure 6 From top to bottom, these represent the input voltages V of phase A of the LC filter. ia Three-phase output voltage V f and the error V between phase A voltage and output reference voltage fa,errA-phase duty cycle d a . Figure 7 This is a comparison chart of the spectrum of voltage source inverters under linear load conditions using proportional-integral control, finite set model predictive control, deadbeat control, and trajectory tracking model predictive control. The comparison shows the steady-state spectrum under various control methods, and the corresponding total harmonic distortion rate and root mean square error are calculated.

[0048] Figure 8 This is a time-domain simulation diagram of a voltage source inverter using proportional-integral control under nonlinear load conditions. Figure 9 This is a time-domain simulation diagram of a voltage source inverter using finite set model predictive control under nonlinear load conditions. Figure 10 Time-domain simulation diagram of a voltage source inverter with deadbeat control under nonlinear load conditions. Figure 11 Time-domain simulation diagram of a voltage source inverter using trajectory tracking model predictive control under nonlinear load conditions. (Attached) Figure 8 To the attached Figure 11 From top to bottom, these represent the three-phase output voltages V of the LC filter. f and the error V between phase A voltage and output reference voltage fa,err Three-phase output current I o . Figure 12 The spectrum comparison chart of voltage source inverters under nonlinear load conditions using proportional-integral control, finite set model predictive control, deadbeat control, and trajectory tracking model predictive control shows the steady-state spectrum under various control methods, and calculates the corresponding total harmonic distortion rate and root mean square error.

[0049] The main parameters corresponding to the simulation comparison experiment are shown below:

[0050] Number of target points N: 4;

[0051] DC side voltage V dc 500V;

[0052] AC output voltage rated amplitude V nom 100V;

[0053] AC output voltage rated frequency f nom 50Hz;

[0054] Sampling period T s 100μs;

[0055] Filter inductance L f 2.4mH;

[0056] Filter capacitance C f 25μF;

[0057] Linear load Rd 10Ω;

[0058] Nonlinear load resistance R r 60Ω;

[0059] Nonlinear load inductance value L r : 2mH;

[0060] Nonlinear load capacitance C r 3000μF.

[0061] The simulation scenarios corresponding to the simulation comparison experiment are shown below:

[0062] Under linear load conditions, at t=0.1s, the load-side power increases by 100%.

[0063] As attached Figure 3 To the attached Figure 12 As shown in the simulation comparison results, the model predictive control method for voltage source inverters based on trajectory tracking in this embodiment has smaller steady-state error and total harmonic distortion rate, and also has significant advantages under nonlinear load conditions, verifying the effectiveness of this embodiment in voltage source inverter control.

[0064] Those skilled in the art will understand that all or part of the steps of the above embodiments can be implemented by hardware or by a program instructing related hardware. The program can be stored in a computer-readable storage medium, such as a magnetic disk, optical disk, read-only memory (ROM), or random access memory (RAM).

[0065] The above description is only a preferred embodiment of the present invention. It should be noted that those skilled in the art can make several improvements and additions without departing from the principle of the present invention, and these improvements and additions should also be considered within the scope of protection of the present invention.

Claims

1. A model predictive control method for voltage source inverters based on trajectory tracking, used for voltage source inverter control in islanded mode of AC microgrids, characterized in that... Includes the following steps: S1. Establish a prediction model for the LC filter of the voltage source inverter. The prediction model calculates the output reference voltage for the next control cycle by giving the reference angular frequency and amplitude of the current output reference voltage. S2. The model predictive control module based on trajectory tracking sets multiple target output reference voltage points within a single control cycle. It performs voltage trajectory tracking by optimizing the new trajectory determined by the current output reference voltage and the output reference voltage of the next control cycle to minimize the error between the reference voltage trajectory and the current trajectory. The optimal output reference voltage for the next control cycle is then obtained to replace the output reference voltage of the LC filter predictive model for the next control cycle. S3. The carrier-based space vector adjustment module calculates the duty cycle of the upper and lower bridge arm switches of the three-phase full-bridge using the carrier-based space vector modulation method, and orderly controls the upper and lower bridge arm switches of the three-phase full-bridge of the voltage source inverter to achieve the synthesis of the output reference voltage obtained by voltage trajectory tracking in step S2.

2. The model predictive control method for a voltage source inverter based on trajectory tracking according to claim 1, characterized in that... The LC filter prediction model described in step S1 is as follows: , where L f and C f These are the inductance and capacitance values ​​of the LC filter, respectively, v i and v f These are the input and output voltages of the LC filter, i f and i o These are the input and output currents of the LC filter, T. s Let k be the sampling period, and k be the current control period.

3. The model predictive control method for a voltage source inverter based on trajectory tracking according to claim 2, characterized in that... The cost function for the optimization problem in step S2 is: Where N is the number of target output reference voltage points. It refers to setting multiple target output reference voltage points within a single control cycle. and For optimal output reference voltage In the two-phase rotating coordinate system, α and β components represent the voltage sample value at the current moment. To the optimal next control cycle output reference voltage The direction vector, t i yes and The time interval between, e i Then it is because and The determined new trajectory and the reference voltage trajectory at t i Error at that point.

4. The model predictive control method for a voltage source inverter based on trajectory tracking according to claim 3, characterized in that: Step S2 involves sampling the voltage at the current moment using the sampling module and converting the three-phase output voltage into α and β components in a two-phase rotating coordinate system using the Clark coordinate transformation module.

5. The model predictive control method for a voltage source inverter based on trajectory tracking according to claim 3, characterized in that... Step S3 performs carrier-based space vector modulation using the following formula: , , ,in, It is the three-phase input reference voltage, d x It is the three-phase duty cycle, V dc V is the DC bus voltage, and V0 is the zero-sequence voltage.

Images