High-Order Grid-Connected Inverter Control Method and System Based on Virtual Dual-Machine Parallel Technology

Abstract

The present invention proposes a control method and system for a high-order grid-connected converter based on virtual dual-machine parallel technology, which relates to the field of converter control. Based on virtual dual-machine parallel technology, the short-circuit ratio of the grid-connected converter system is calculated, and the reference power of the virtual grid-following converter and grid-forming converter is allocated; based on the generated reference power, the reference signals required for full-variable model predictive control are generated; the reference signals are input into the full-variable model predictive control to generate the control signals of the grid-connected converter. The present invention adopts full-variable unbiased model predictive control, virtualizes a single-machine grid-connected converter into a parallel grid-following converter and grid-forming converter, improves the quality of the grid-connected current, realizes continuous adjustment of the capacity ratio of the single-machine grid-following and grid-forming, maintains the stability of the system voltage and frequency while achieving the maximum output of new energy power generation under weak grid and island conditions, and improves the economy and reliability of a new power system with power electronic equipment as the core.

Description

Technical Field

[0001] The present invention belongs to the field of converter control, and particularly relates to a control method and system for a high-order grid-connected converter based on virtual dual-machine parallel technology. Background Technique

[0002] The statements in this part only provide background technical information related to the present invention and do not necessarily constitute prior art.

[0003] Distributed generation systems based on renewable energy have the advantages of environmental friendliness, energy security, reduced losses, high reliability, and investment savings. Power electronic converters are an important part of distributed generation systems, and grid-connected inverters are used to convert DC electrical energy into high-quality AC electrical energy and feed it into the grid. Grid-connected inverters are of two types: single-phase and three-phase. The former is mainly used in small-capacity household power generation systems, while the latter is widely used in large-scale renewable energy distributed power generation stations. To reduce the switching harmonics rich in the grid-connected current, grid-connected converters usually adopt three types of filters: L-type, LC-type, and LCL-type. On the premise of achieving the same filtering effect, the sum of the two inductances in the LCL filter is smaller than the inductance of a single inductor in the L and LC filters. Therefore, its volume is smaller, the cost is lower, and the application range is gradually increasing.

[0004] Existing grid-connected converter control schemes are mainly divided into grid-following control and grid-forming control. Grid-following converters generally adopt constant power control. When the frequency and reference voltage of the system connected to the grid-connected converter change within the allowable range, the active power and reactive power output by the distributed power source are controlled. Grid-following converters can quickly track the maximum power point, generate electricity and connect to the grid efficiently, have a fast power response, and high-quality grid-connected current; however, grid-following converters show weak stability and cannot provide voltage and frequency support for the system in weak grid and island modes.

[0005] Grid-forming converters generally adopt constant voltage and constant frequency control, droop control, or virtual synchronous generator control, and control the active and reactive power output by the converter by adjusting the voltage frequency and amplitude. In weak grid conditions, the control stability margin of grid-forming converters is larger than that of grid-following converters, and they can operate independently of the large grid; however, grid-forming converters are prone to oscillation in strong grid conditions.

[0006] Regarding the advantages and disadvantages of grid-following and grid-forming grid-connected converters, when facing changes in grid strength, existing grid-following and grid-forming switching methods use the short-circuit ratio to measure the grid strength. When the grid changes from a strong grid to a weak grid, the converter switches from grid-following control to grid-forming control; when the grid changes from a weak grid to a strong grid, the converter switches from grid-forming control to grid-following control. Specifically, while ensuring system stability, it is necessary to maximize the generator output as much as possible. Therefore, the minimum grid-forming capacity is generally adopted. However, after calculating the minimum grid-forming capacity ratio, since the grid-following and grid-forming switching strategy can only achieve the switching of the whole machine, the grid-forming capacity after switching is generally higher than the required minimum grid-forming capacity, making it difficult to maximize the economy; and some converters have a generally shorter remaining service life than those that do not often change their working modes because they often change their working modes, increasing the operation and maintenance costs; therefore, the existing grid-connected converter control scheme has insufficient regulation ability under weak grid conditions and high operation and maintenance costs. Summary of the Invention

[0007] To overcome the deficiencies of the above-mentioned prior art, the present invention provides a high-order grid-connected converter control method and system based on virtual dual-machine parallel technology, which adopts full-variable unbiased model predictive control, virtualizes a single-grid-connected converter into a parallel grid-following converter and grid-forming converter, improves the quality of grid-connected current, realizes continuous adjustment of the single-machine grid-following and grid-forming capacity ratio, maintains the stability of system voltage and frequency while achieving maximum output of new energy power generation under weak grid and island conditions, and improves the economy and reliability of a new power system with power electronic equipment as the core.

[0008] To achieve the above object, one or more embodiments of the present invention provide the following technical solutions:

[0009] The first aspect of the present invention provides a high-order grid-connected converter control method based on virtual dual-machine parallel technology.

[0010] The high-order grid-connected converter control method based on virtual dual-machine parallel technology includes:

[0011] Adopt virtual dual-machine parallel technology to virtualize a single converter in the grid-connected converter system into two parallel grid-following converters and grid-forming converters;

[0012] Calculate the short-circuit ratio of the grid-connected converter system according to the grid impedance identified by the extended Kalman filter;

[0013] According to the short-circuit ratio, allocate the reference power of the virtual grid-following converter and grid-forming converter to simulate the configuration of the single-machine grid-following and grid-forming capacity;

[0014] The generated reference power is respectively input into a virtual grid-following controller and a grid-forming controller, and combined with the unbiased compensation strategy of the full-feedforward of the grid voltage and the extended state observer, a reference signal required for the full-variable model predictive control is generated;

[0015] The reference signal is input into the full-variable model predictive control to generate a control signal for the grid-connected converter.

[0016] Furthermore, the grid impedance identified by the extended Kalman filter, the specific identification method is:

[0017] Based on the voltage and current information sampled from the grid-connected converter system, a state-space model of the line impedance is constructed;

[0018] According to the state-space model, combined with the extended Kalman filter recurrence formula, the line impedance value is estimated in real time to obtain the grid impedance.

[0019] Furthermore, the state-space model of the line impedance is expressed by the formula:

[0020]

[0021] where, i L2α (k + 1), i L2β (k + 1) respectively represent the current values of the grid-side filter inductor in the αβ coordinate system at the (k + 1)-th sampling moment, e α (k + 1), e β (k + 1) respectively represent the output voltages of the grid-connected converter system in the αβ coordinate system at the (k + 1)-th sampling moment, v pccα (k + 1), v pccβ (k + 1) respectively represent the grid voltages in the αβ coordinate system at the (k + 1)-th sampling moment, R g (k + 1) represents the estimated grid resistance value at the (k + 1)-th sampling moment, l g (k + 1) represents the reciprocal of the estimated grid inductance value at the (k + 1)-th sampling moment; T s is the control / sampling period; i L2α (k), i L2β (k) respectively represent the current values of the grid-side filter inductor in the αβ coordinate system at the k-th sampling moment, e α (k), e β (k) respectively represent the output voltages of the grid-connected converter system in the αβ coordinate system at the k-th sampling moment, v pccα (k), v pccβ (k) respectively represent the grid voltages in the αβ coordinate system at the k-th sampling moment, R g (k) represents the estimated grid resistance value at the k-th sampling moment, l g(k) represents the reciprocal of the estimated grid inductance value at the k-th sampling moment.

[0022] Furthermore, the short-circuit ratio of the grid-connected converter system is calculated by the following formula:

[0023]

[0024] where S ac is the system short-circuit capacity, P inv is the equipment capacity, K SCR is the short-circuit ratio of the grid-connected converter system, V gn is the phase voltage of the grid-connected converter, and Z g is the grid impedance.

[0025] Furthermore, for the full feed-forward of the grid voltage, the generated reference power is respectively input into the virtual grid-following controller and the grid-forming controller to obtain the reference current and reference voltage, and the corresponding future current value and future filter capacitor voltage value are predicted through the system circuit parameters.

[0026] Furthermore, for the full-variable model predictive control, based on the measured and estimated data and combined with the system model, the state changes of the grid-connected converter system at multiple future moments are predicted, and the optimal operation at this moment is determined according to the principle of minimizing the cost function.

[0027] Furthermore, the following auxiliary measures are also included:

[0028] At the starting stage, the converter operates in the full grid-following mode;

[0029] In the full grid-following mode, the virtual grid-forming converter and the grid-following converter are voltage-synchronized;

[0030] When the grid-forming and grid-following capacity changes significantly, the capacity change is restricted so that the capacity slowly climbs to the new target ratio.

[0031] The second aspect of the present invention provides a high-order grid-connected converter control system based on virtual dual-machine parallel technology.

[0032] The high-order grid-connected converter control system based on virtual dual-machine parallel technology includes a dual-machine virtual module, a short-circuit ratio calculation module, a power distribution module, a reference signal generation module, and a control signal generation module:

[0033] The dual-machine virtual module is configured to: adopt the virtual dual-machine parallel technology to virtualize the single converter in the grid-connected converter system into two parallel grid-following converters and grid-forming converters;

[0034] The short-circuit ratio calculation module is configured to: calculate the short-circuit ratio of the grid-connected converter system according to the grid impedance identified by the extended Kalman filter;

[0035] A power distribution module, configured to: allocate the reference powers of a virtual grid-following converter and a grid-forming converter according to a short-circuit ratio, and simulate the configuration of the single-machine grid-following and grid-forming capacities;

[0036] A reference signal generation module, configured to: respectively input the generated reference powers into a virtual grid-following controller and a grid-forming controller, and generate the reference signals required for full-variable model predictive control by combining the strategy of no-deviation compensation of the full feedforward of the grid voltage and an extended state observer;

[0037] A control signal generation module, configured to: input the reference signals into the full-variable model predictive control to generate the control signals of the grid-connected converter.

[0038] The third aspect of the present invention provides a computer-readable storage medium, on which a program is stored, and when the program is executed by a processor, the steps in the high-order grid-connected converter control method based on the virtual dual-machine parallel technology as described in the first aspect of the present invention are implemented.

[0039] The fourth aspect of the present invention provides an electronic device, including a memory, a processor, and a program stored on the memory and executable on the processor, and when the processor executes the program, the steps in the high-order grid-connected converter control method based on the virtual dual-machine parallel technology as described in the first aspect of the present invention are implemented.

[0040] The above one or more technical solutions have the following beneficial effects:

[0041] The present invention is directed to the energy transfer equipment in systems such as renewable energy power generation grid connection, energy storage, and microgrids, and proposes a high-order grid-connected converter control method based on the virtual dual-machine parallel technology; in the framework of full-variable no-deviation model predictive control, the single-machine grid-connected converter is virtualized into a parallel grid-following converter and a grid-forming converter; the grid impedance is identified by an extended Kalman filter to measure the short-circuit ratio of the system; based on the measurement of the grid strength, the power reference of the virtual converter is adjusted, and then the continuous adjustment of the single-machine grid-following and grid-forming capacity ratio is realized.

[0042] The present invention does not require additional hardware circuits; adopting full-variable no-deviation model predictive control, compared with traditional modulation methods, the transient response is faster, and compared with single-variable model predictive control, the quality of the grid-connected current is improved; the continuous adjustment of the single-machine grid-following and grid-forming capacity ratio is realized, and under weak grid and island conditions, while maintaining the stability of the system voltage and frequency, the maximum output of new energy power generation is realized, and the economy and reliability of the new power system with power electronic equipment as the core are improved.

[0043] The advantages of the additional aspects of the present invention will be partially given in the following description, partially will become obvious from the following description, or will be understood through the practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] The accompanying drawings forming a part of this invention are used to provide a further understanding of the invention. The schematic embodiments and descriptions thereof of the invention are used to explain the invention and shall not unduly limit the invention.

[0045] Figure 1 It is a flowchart of the method for the first embodiment.

[0046] Figure 2 It is a topological diagram of the LCL - type grid - connected converter for the first embodiment.

[0047] Figure 3 It is a control block diagram of the traditional grid - following grid - connected converter for the first embodiment.

[0048] Figure 4 It is a control block diagram of the traditional grid - forming grid - connected converter for the first embodiment.

[0049] Figure 5 It is a control block diagram of the full - variable model predictive control based on virtual dual - machine parallel connection for the first embodiment. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0050] It should be noted that the following detailed description is exemplary and is intended to provide further explanation of the present application. Unless otherwise specified, all technical and scientific terms used in the present invention have the same meaning as commonly understood by those of ordinary skill in the technical field to which this application belongs.

[0051] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present application. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprise" and / or "include" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0052] Inverters in large - scale new - energy power plants usually adopt the same model for construction and maintenance, and have the same input - output characteristics. Multiple converters are connected in parallel to form a multi - inverter system, and the multi - inverter system usually operates in a single current - source mode. However, with the weakening of the grid strength, the output current of the grid - connected converter is extremely prone to resonance spikes, and the coupling degree between inverters and between the inverter and the grid gradually increases. The traditional grid - following / grid - forming switching strategy is adopted to switch some inverters from grid - following converters to grid - forming converters to cope with weak - grid conditions.

[0053] However, traditional configuration switching strategies are difficult to maximize the economy; moreover, since some converters often change their operating modes, their remaining service life is generally shorter than that of converters that do not often change their operating modes, increasing the operation and maintenance costs; therefore, existing grid-connected converter control schemes can only achieve the switching of the whole machine, resulting in the grid-forming capacity after switching being generally higher than the required minimum grid-forming capacity, making it difficult to maximize the economy; moreover, since some converters often change their operating modes, their remaining service life is generally shorter than that of converters that do not often change their operating modes, increasing the operation and maintenance costs.

[0054] To solve the above problems, in the framework of full-variable unbiased model predictive control, the present invention virtualizes a single-machine grid-connected converter into a parallel grid-following converter and a grid-forming converter; the grid impedance is identified by an extended Kalman filter to measure the short-circuit ratio of the system; based on the measurement of the grid strength, the power reference of the virtual converter is adjusted, and then the single-machine converter is enabled to have both grid-following and grid-forming characteristics from a single grid-following / forming characteristic. The grid-following and grid-forming capacity configuration changes from discrete to continuous, ensuring that the multi-inverter system can always exactly reach the minimum grid-forming capacity, providing a new idea for the cluster converters to adapt to weak grid conditions; the converters in the converter cluster operate in similar operating modes, and their remaining service lives are basically the same, which can reduce the operation and maintenance costs to a certain extent.

[0055] Embodiment 1

[0056] In an embodiment of the present disclosure, a high-order grid-connected converter control method based on virtual dual-machine parallel technology is provided, as Figure 1 shown, including the following steps:

[0057] Step S1: Adopt virtual dual-machine parallel technology to virtualize the single-machine converter in the grid-connected converter system into two parallel grid-following converters and a grid-forming converter;

[0058] Step S2: Calculate the short-circuit ratio of the grid-connected converter system according to the grid impedance identified by the extended Kalman filter;

[0059] Step S3: Allocate the reference powers of the virtual grid-following converter and grid-forming converter according to the short-circuit ratio to simulate the configuration of the single-machine grid-following and grid-forming capacities;

[0060] Step S4: Input the generated reference powers into the virtual grid-following controller and grid-forming controller respectively, and combine the grid voltage full feedforward and the unbiased compensation strategy of the extended state observer to generate the reference signals required for the full-variable model predictive control;

[0061] Step S5: Input the reference signals into the full-variable model predictive control to generate the control signals of the grid-connected converter.

[0062] The implementation process of the high - order grid - connected converter control method based on the virtual dual - machine parallel technology in this embodiment will be described in detail below.

[0063] The core point of this embodiment is to propose a high - order grid - connected converter control based on the virtual dual - machine parallel technology for the grid - connected converter system, enabling the converter to adaptively change the proportion of its own structure capacity according to the grid strength. Taking the LCL - type two - level grid - connected converter as an example, the LCL - type grid - connected converter model, the control of traditional grid - following converters and grid - forming converters, the grid impedance identification technology method based on the extended Kalman filter, and the full - variable model predictive control method based on the virtual dual - machine parallel technology proposed in this embodiment will be introduced respectively.

[0064] 1. LCL - type grid - connected converter

[0065] The topology of the LCL - type two - level grid - connected converter is as Figure 2 shown. This converter system includes a three - phase voltage source (v pccx ), converter filter inductance (L1), converter - side equivalent resistance (R1), filter capacitor (C f ), filter capacitor resistance (R c ), grid - side filter inductance (L2), grid - side equivalent resistance (R2), weak - grid equivalent series inductance (L g ), weak - grid equivalent series resistance (R g ), six insulated gate bipolar transistors IGBT six anti - parallel diodes and the DC - bus capacitor (C). V dc is the DC - bus capacitor voltage, i L1x , v cx , i L2x , e x and v pccx ( {a, b, c}) are the filter capacitor voltage, the output current after the filter, the converter output voltage, and the grid - connection point voltage respectively. By controlling the conduction state of the IGBT, the two - level converter can output two levels, and the corresponding voltage values v x are V dc , 0 respectively.

[0066] 2. Control of traditional grid - following converters and grid - forming converters

[0067] The control schemes of traditional grid - following converters mainly include constant - current control and PQ control, and the control schemes of grid - forming converters mainly include constant - voltage and constant - frequency control, droop control, and virtual synchronous generator control. Taking PQ control and droop control as examples, the control methods of grid - following converters and grid - forming converters will be introduced respectively.

[0068] The grid-following converter tracks the specified reference active power and reactive power (P * , Q * ), and generates the reference current (i P ) through the power outer loop (C * ), and delivers active and reactive power to the point of common coupling or the AC bus, as Figure 3 shown; the grid-following converter can quickly track the maximum power point and efficiently generate power and connect to the grid; and it has a fast power response and high-quality grid-connected current; however, for the grid-following converter, as the grid strength weakens, the stability domain of the current inner loop parameters decreases, showing weak stability under weak grid conditions.

[0069] The grid-forming converter tracks the specified reference voltage and frequency (E * , ω * ), provides voltage and frequency support to the point of common coupling or the AC bus, and tries to track the active and reactive references (P * , Q * ), and combines with the specified reference voltage and frequency through the power outer loop to generate the input to the voltage vector as Figure 4 shown; under weak grid conditions, the grid-forming converter has a larger control stability margin and can operate independently of the large grid to form a network, that is, it can work in the island mode and provide voltage and frequency support for the islanded micro energy system; however, for the grid-forming converter, as the grid strength increases, the stability domain of the parameters decreases, and it is prone to oscillation under strong grid conditions.

[0070] 3. Grid impedance identification based on the extended Kalman filter

[0071] Due to the complex structure of the grid-connected converter, and due to the use of LCL filters and the variable structure of the converter cluster for network operation, the LCL-type grid-connected converter system is a complex non-linear system; while the general Kalman filter can achieve the optimal estimation of the target state of the linear Gaussian model and obtain relatively accurate observation results; the least squares method has insufficient resistance to measurement noise and external disturbances; the harmonic injection method for identification will reduce the output current generated by the converter. Therefore, the extended Kalman filter method is used to identify the grid impedance, specifically as follows:

[0072] For the voltage and current information obtained by sampling the LCL-type grid-connected converter system, perform Clark transformation. In the αβ coordinate system, the dynamic characteristics of the feeder system are as follows:

[0073]

[0074] Among them, i L2α , i L2β respectively represent the current values of the grid-side filter inductance in the αβ coordinate system, and e α , e βrespectively represent the output voltages of the grid-connected converter system in the αβ coordinate system, v pccα , v pccβ respectively represent the grid voltages in the αβ coordinate system, R g represents the estimated value of the grid resistance, l g represents the reciprocal of the estimated value of the grid inductance.

[0075] Assume that the voltage at the point of common coupling (PCC) and the output voltage of the converter remain unchanged within the sampling period, then there is:

[0076]

[0077] where, i L2α , i L2β respectively represent the current values of the grid-side filter inductance in the αβ coordinate system, e α , e β respectively represent the output voltages of the grid-connected converter system in the αβ coordinate system, v pccα , v pccβ respectively represent the grid voltages in the αβ coordinate system, R g represents the estimated value of the grid resistance, l g represents the reciprocal of the estimated value of the grid inductance.

[0078] Since the sampling system for measuring the voltage and current of the LCL-type grid-connected converter system using the extended Kalman filter algorithm has zero-order hold characteristics, the following transformation is performed:

[0079]

[0080]

[0081] where, R g represents the estimated value of the grid resistance, L g represents the estimated value of the grid inductance, l g represents the reciprocal of the estimated value of the grid inductance, T s is the control / sampling period.

[0082] Thus, the state-space model of the line impedance is obtained to realize the real-time estimation of the line impedance value. The state-space model is expressed by the formula as:

[0083]

[0084] where, i L2α (k + 1), i L2β (k + 1) respectively represent the current values of the grid-side filter inductance in the αβ coordinate system at the (k + 1)-th sampling moment, e α (k + 1), e β(k + 1) represents the output voltage of the grid-connected converter system at the (k + 1)-th sampling moment in the αβ coordinate system, v pccα (k + 1), v pccβ (k + 1) represents the grid voltage at the (k + 1)-th sampling moment in the αβ coordinate system, R g (k + 1) represents the estimated grid resistance value at the (k + 1)-th sampling moment, l g (k + 1) represents the reciprocal of the estimated grid inductance value at the (k + 1)-th sampling moment; T s is the control / sampling period; i L2α (k), i L2β (k) represents the current value of the grid-side filter inductance in the αβ coordinate system at the k-th sampling moment, e α (k), e β (k) represents the output voltage of the grid-connected converter system at the k-th sampling moment in the αβ coordinate system, v pccα (k), v pccβ (k) represents the grid voltage at the k-th sampling moment in the αβ coordinate system, R g (k) represents the estimated grid resistance value at the k-th sampling moment, l g (k) represents the reciprocal of the estimated grid inductance value at the k-th sampling moment.

[0085] 4. Full-Variable Model Predictive Control Based on Virtual Dual-Machine Parallel Connection

[0086] The full-variable model predictive control based on virtual dual-machine parallel connection is generally divided into five steps:

[0087] ① The single converter is virtualized into two parallel grid-following converters and grid-forming converters;

[0088] ② According to the grid impedance identified by the extended Kalman filter, calculate the short-circuit ratio of the converter system to complete the detection of the grid strength from the perspective of the converter;

[0089] The specific formula for the short-circuit ratio is:

[0090]

[0091] Among them, S ac is the system short-circuit capacity, P inv is the equipment capacity, K SCR is the short-circuit ratio of the grid-connected converter system, V gn is the phase voltage of the grid-connected converter, Z g is the grid impedance. Strong grid, Weak grid, Extremely weak grid.

[0092] ③Allocate the reference power of the virtual grid-following converter and grid-forming converter according to the short-circuit ratio comparison, and then realize the configuration of the single-machine grid-following and grid-forming capacities. The specific capacity configuration scheme is as follows:

[0093]

[0094] Among them, S ref is the reference power, ω GFL is the grid-following capacity weight coefficient, ω GFM is the grid-forming capacity weight coefficient, is the grid-following capacity, is the grid-forming capacity, K SCR is the short-circuit ratio of the grid-connected converter system.

[0095] ④Input the generated reference power into the virtual grid-following controller and grid-forming controller respectively, and combine the unbiased compensation strategy of the full feed-forward of the grid voltage and the extended state observer to generate the reference signals required for the full-variable model predictive control of the LCL-type grid-connected converter, that is, the current value and the filter capacitor voltage value.

[0096] ⑤Input the reference signals in the previous step into the full-variable model predictive control, so as to generate the PWM signal for controlling the switching state of the switching tubes in the grid-connected converter.

[0097] The overall control block diagram is as shown in Figure 5 where S ref is the reference power, θ e is the phase of the converter output voltage, θ GFM is the phase generated by the droop control, ω GFL is the grid-following capacity weight coefficient, ω GFM is the grid-forming capacity weight coefficient.

[0098] Since this embodiment hopes that the converter can quickly track the change of the capacity ratio, and the advantage of the model predictive control is that it has better transient performance compared with the traditional modulation strategy; at the same time, considering that the single-variable model predictive control has poor control performance for the LCL-type high-order grid-connected converter, the full-variable model predictive control is adopted, that is, based on the measured and estimated data, combined with the system prediction model, predict the state changes of the system at the next n moments, that is, the changes of the current and voltage, and make a decision on the best operation at this moment according to the principle of minimizing the cost function. The reference current and the reference voltage are obtained by the virtual dual-machine parallel method, and the corresponding future current value and the future filter capacitor voltage value v c (k + 1)

[0099]

[0100] Among them,

[0101]

[0102]

[0103]

[0104] To solve the problem caused by the calculation delay of the above digital controller, a delay compensation strategy is usually adopted, that is: at time k, directly derive the system prediction model at time k+2:

[0105]

[0106] The controller traverses 8 independent switch states, calculates the cost function corresponding to each switch state, and selects the switch state corresponding to the minimum value of the cost function as the output switch state. Among them, the formula of the cost function is:

[0107]

[0108] The smallest switch state is used as the switch state at the next moment. Among them, T s is the sampling period, λ L1 is the weight coefficient of the converter output current, λ L2 is the weight coefficient of the filter output current, λ Cf is the weight coefficient of the capacitor voltage.

[0109] It should be noted that in order to cope with the asynchrony between the phase angle generated in the grid-forming control and the output phase angle of the inverter, and the over-current phenomenon that is likely to occur when the capacity of the grid-forming converter changes, the following three measures are adopted in this embodiment:

[0110] ① Smooth start algorithm. In this algorithm, during startup, since it takes a certain amount of time to identify the grid impedance, the reference power allocated to the virtual grid-following converter and the grid-forming converter during startup fluctuates violently, affecting the stability of the converter. Therefore, the converter operates in the full grid-following mode during the startup stage.

[0111] ② Pre-synchronization. After startup, if it is necessary to enter the grid-following and grid-forming hybrid mode, it is necessary to synchronize the output voltage phase angle and amplitude of the virtual grid-following converter and the grid-forming converter in advance. Therefore, in the full grid-following mode, it is necessary to synchronize the voltage of the virtual grid-forming converter and the grid-following converter.

[0112] ③ Slow change algorithm. Since this algorithm is prone to over-current and power surge phenomena when the grid-following and grid-forming capacity ratio is changed significantly, especially when the grid-forming capacity increases significantly. Therefore, when the grid-following and grid-forming capacity changes significantly, a certain limit is placed on the capacity change, so that the capacity slowly climbs to the new target ratio.

[0113] Different from the traditional structure-switching strategy, in this embodiment, without the need to additionally install any adoption or hardware circuit, a single-machine converter is virtualized into two grid-following converters and a grid-forming converter connected in parallel, and can adaptively track the change of grid strength to allocate the structure-following capacity of the converter. It realizes the configuration of the structure-following capacity of the single-machine grid-connected converter from discrete to continuous, ensures that the multi-inverter system can always just reach the minimum grid-forming capacity, and provides a new idea for the cluster converter to adapt to weak grid conditions; the converters in the converter cluster work in similar working modes, and the remaining service lives are basically the same, which can reduce the operation and maintenance costs to a certain extent. The invention can also be extended to any converter system, such as the back-to-back converter system in wind power generation, the two-stage grid-connected converter system in photovoltaic power generation, etc.

[0114] Embodiment 2

[0115] In an embodiment of the present disclosure, a high-order grid-connected converter control system based on virtual dual-machine parallel technology is provided, including a dual-machine virtual module, a short-circuit ratio calculation module, a power distribution module, a reference signal generation module, and a control signal generation module:

[0116] The dual-machine virtual module is configured to: adopt virtual dual-machine parallel technology to virtualize the single-machine converter in the grid-connected converter system into two grid-following converters and a grid-forming converter connected in parallel;

[0117] The short-circuit ratio calculation module is configured to: calculate the short-circuit ratio of the grid-connected converter system according to the grid impedance identified by the extended Kalman filter;

[0118] The power distribution module is configured to: allocate the reference powers of the virtual grid-following converter and grid-forming converter according to the short-circuit ratio to simulate the configuration of the single-machine structure-following capacity;

[0119] The reference signal generation module is configured to: input the generated reference powers into the virtual grid-following controller and grid-forming controller respectively, and combine the full feed-forward of the grid voltage and the unbiased compensation strategy of the extended state observer to generate the reference signals required for the full-variable model predictive control;

[0120] The control signal generation module is configured to: input the reference signals into the full-variable model predictive control to generate the control signals of the grid-connected converter.

[0121] Embodiment 3

[0122] The purpose of this embodiment is to provide a computer-readable storage medium.

[0123] A computer-readable storage medium stores a computer program thereon. When the program is executed by a processor, the steps in the high-order grid-connected converter control method based on the virtual dual-machine parallel technology described in Embodiment 1 of the present disclosure are implemented.

[0124] Embodiment 4

[0125] The purpose of this embodiment is to provide an electronic device.

[0126] An electronic device includes a memory, a processor, and a program stored on the memory and executable on the processor. When the processor executes the program, the steps in the high-order grid-connected converter control method based on the virtual dual-machine parallel technology described in Embodiment 1 of the present disclosure are implemented.

[0127] The above are only the preferred embodiments of the present invention and are not used to limit the present invention. For those skilled in the art, the present invention may have various changes and modifications. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A control method for a high-order grid-connected converter based on virtual dual-machine parallel technology, characterized in that Including: Adopting the virtual dual-machine parallel technology, virtualizing the single-inverter in the grid-connected inverter system into two parallel grid-following inverters and grid-forming inverters; Calculating the short-circuit ratio of the grid-connected inverter system according to the grid impedance identified by the extended Kalman filter; According to the short-circuit ratio, distributing the reference power of the virtual grid-following inverter and grid-forming inverter, and simulating the configuration of the single-inverter's grid-following and grid-forming capacities; Respectively inputting the generated reference power into the virtual grid-following controller and grid-forming controller, and combining the full feed-forward of the grid voltage and the unbiased compensation strategy of the extended state observer to generate the reference signals required for the full-variable model predictive control; Inputting the reference signals into the full-variable model predictive control to generate the control signals of the grid-connected inverter.

2. The high-order grid-connected converter control method based on the virtual dual-machine parallel technology according to claim 1, wherein, The grid impedance identified by the extended Kalman filter, the specific identification method is: Based on the voltage and current information sampled from the grid-connected inverter system, constructing the state-space model of the line impedance; According to the state-space model, combining the recursive formula of the extended Kalman filter, estimating the line impedance value in real time to obtain the grid impedance.

3. The high-order grid-connected converter control method based on virtual dual-machine parallel technology according to claim 2, wherein The state-space model of the line impedance is expressed by the formula: where, i L2α (k + 1), i L2β (k + 1) respectively represent the current values of the grid-side filter inductor in the αβ coordinate system at the (k + 1)-th sampling moment, e α (k + 1), e β (k + 1) respectively represent the output voltages of the grid-connected converter system in the αβ coordinate system at the (k + 1)-th sampling moment, v pccα (k + 1), v pccβ (k + 1) respectively represent the grid voltages in the αβ coordinate system at the (k + 1)-th sampling moment, R g (k + 1) represents the estimated grid resistance value at the (k + 1)-th sampling moment, l g (k + 1) represents the reciprocal of the estimated grid inductance value at the (k + 1)-th sampling moment; T s is the control / sampling period; i L2α (k), i L2β (k) respectively represent the current values of the grid-side filter inductor in the αβ coordinate system at the k-th sampling moment, e α (k), e β (k) respectively represent the output voltages of the grid-connected converter system in the αβ coordinate system at the k-th sampling moment, v pccα (k), v pccβ (k) respectively represent the grid voltages in the αβ coordinate system at the k-th sampling moment, R g (k) represents the estimated grid resistance value at the k-th sampling moment, l g (k) represents the reciprocal of the estimated grid inductance value at the k-th sampling moment.

4. The high-order grid-connected converter control method based on virtual dual-machine parallel technology according to claim 1, wherein, The calculation formula of the short-circuit ratio of the grid-connected inverter system is: Among them, S ac is the system short-circuit capacity, P inv is the equipment capacity, K SCR is the short-circuit ratio of the grid-connected converter system, V gn is the phase voltage of the grid-connected converter, Z g is the grid impedance.

5. The control method of the high-order grid-connected inverter based on the virtual dual-machine parallel technology according to claim 1, characterized in that The full feed-forward of the grid voltage is to respectively input the generated reference power into the virtual grid-following controller and grid-forming controller, obtain the reference current and reference voltage, and predict the corresponding future current value and future filter capacitor voltage value through the system circuit parameters.

6. The high-order grid-connected converter control method based on virtual dual-machine parallel technology according to claim 1, characterized in that, The full-variable model predictive control is to predict the state changes of the grid-connected inverter system at multiple future moments based on the measured and estimated data, and make a decision on the best operation at this moment according to the principle of minimizing the cost function.

7. The high-order grid-connected converter control method based on the virtual dual-machine parallel technology according to claim 1, characterized in that It also includes the following auxiliary measures: In the starting stage, the inverter operates in the full grid-following mode; In the full grid-following mode, synchronize the voltage of the virtual grid-forming inverter and the grid-following inverter; When the grid-following and grid-forming capacities change significantly, limit the capacity change so that the capacity slowly climbs to the new target ratio.

8. A high-order grid-connected converter control system based on virtual dual-machine parallel technology, characterized in that Including a dual-machine virtual module, a short-circuit ratio calculation module, a power distribution module, a reference signal generation module, and a control signal generation module: The dual-machine virtual module is configured to: adopt the virtual dual-machine parallel technology to virtualize the single-inverter in the grid-connected inverter system into two parallel grid-following inverters and grid-forming inverters; The short-circuit ratio calculation module is configured to: calculate the short-circuit ratio of the grid-connected inverter system according to the grid impedance identified by the extended Kalman filter; The power distribution module is configured to: distribute the reference power of the virtual grid-following inverter and grid-forming inverter according to the short-circuit ratio, and simulate the configuration of the single-inverter's grid-following and grid-forming capacities; The reference signal generation module is configured to: respectively input the generated reference power into the virtual grid-following controller and grid-forming controller, and combine the full feed-forward of the grid voltage and the unbiased compensation strategy of the extended state observer to generate the reference signals required for the full-variable model predictive control; The control signal generation module is configured to: input the reference signals into the full-variable model predictive control to generate the control signals of the grid-connected inverter.

9. An electronic device, characterized in that it includes: A memory for non - transitory storage of computer - readable instructions; and a processor for running the computer - readable instructions, wherein, when the computer - readable instructions are run by the processor, the method according to any one of claims 1 - 7 above is performed.

10. A storage medium, characterized in that, Instructions for non - transitorily storing computer - readable instructions, wherein when the computer - readable instructions are executed by a computer, the method according to any one of claims 1 - 7 is performed.

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