Distributed photovoltaic converter multi-sequence quantity cooperative control method and device and storage medium

Abstract

The invention discloses a distributed photovoltaic converter multi-sequence quantity cooperative control method and device and a storage medium. The method comprises the following steps: constructing a positive sequence-negative sequence-zero sequence control model of a distributed photovoltaic converter; collecting the output power of the distributed photovoltaic converter; an impedance constraint condition is determined, a voltage reference value of the distributed photovoltaic converter is determined based on the impedance constraint condition, the positive sequence-negative sequence-zero sequence control model and the output power, and the microgrid comprises a positive sequence load, a harmonic load and an unbalanced load; determining a preset droop controller, determining a control input parameter of the preset droop controller based on the voltage reference value, and inputting the control input parameter into the preset droop controller for impedance compensation value prediction to obtain a multi-sequence impedance compensation value; and based on the multi-sequence impedance compensation value, performing impedance compensation on the distributed photovoltaic converter so as to realize uniform distribution of a fundamental wave positive sequence power component, a harmonic power component and an unbalanced power air volume in the micro-grid.

Description

Multi-sequence quantity coordinated control method, device and storage medium for distributed photovoltaic converters Technical Field

[0001] This invention relates to the field of power grid security technology, and in particular to a method, device and storage medium for multi-sequence quantity coordinated control of distributed photovoltaic converters. Background Technology

[0002] Precisely distributing load power among multiple photovoltaic converters is a core challenge for isolated microgrids.

[0003] Currently, the load power of multiple photovoltaic converters is typically allocated in a fixed ratio. However, this fixed-ratio power allocation method leads to inaccurate power distribution due to the different feeder impedances of different converters, which in turn affects grid stability. Summary of the Invention

[0004] This invention provides a method, device, and storage medium for multi-sequence quantity coordinated control of distributed photovoltaic converters, which mainly improves the power distribution accuracy of photovoltaic converters and thus ensures the stable operation of the power grid.

[0005] According to a first aspect of the present invention, a multi-sequence coordinated control method for a distributed photovoltaic (PV) converter is provided, comprising: acquiring grid structure parameters of a microgrid corresponding to the distributed PV converter; constructing a positive-sequence-negative-sequence-zero-sequence control model for the distributed PV converter based on the grid structure parameters; and acquiring the output power of the distributed PV converter, wherein the output power includes output active power and output reactive power; determining the impedance constraint conditions of the distributed PV converter in the multi-sequence coordinated control process; and determining, based on the impedance constraint conditions, the positive-sequence-negative-sequence-zero-sequence control model, and the output power, a voltage reference value for the distributed PV converter to ensure stable operation of the microgrid, wherein the voltage reference value of the distributed PV converter in the microgrid is... The system includes positive-sequence loads, harmonic loads, and unbalanced loads. A preset droop controller is determined, and based on the voltage reference value, the control input parameters of the preset droop controller are determined. These control input parameters are then input to the preset droop controller for impedance compensation value prediction, resulting in the multi-sequence impedance compensation value of the distributed photovoltaic converter. This multi-sequence impedance compensation value includes the fundamental positive-sequence impedance component compensation value, the fundamental negative-sequence impedance component compensation value, and the harmonic impedance component compensation value. Based on these multi-sequence impedance compensation values, impedance compensation is performed on the distributed photovoltaic converter to achieve a uniform distribution of the fundamental positive-sequence power component, harmonic power component, and unbalanced power volume in the microgrid within the distributed photovoltaic converter.

[0006] According to a second aspect of the present invention, a multi-sequence coordinated control device for a distributed photovoltaic (PV) converter is provided, comprising: a construction unit, configured to acquire grid structure parameters of a microgrid corresponding to the distributed PV converter, and based on the grid structure parameters, construct a positive-sequence-negative-sequence-zero-sequence control model for the distributed PV converter; and acquire the output power of the distributed PV converter, wherein the output power includes output active power and output reactive power; and a determination unit, configured to determine the impedance constraint conditions of the distributed PV converter in the multi-sequence coordinated control process, and based on the impedance constraint conditions, the positive-sequence-negative-sequence-zero-sequence control model, and the output power, determine a voltage reference value for the distributed PV converter to ensure stable operation of the microgrid, wherein the voltage reference value of the distributed PV converter in the microgrid is... The system includes positive-sequence load, harmonic load, and unbalanced load; a prediction unit is used to determine a preset droop controller, based on the voltage reference value, determine the control input parameters of the preset droop controller, and input the control input parameters to the preset droop controller for impedance compensation value prediction, thereby obtaining the multi-sequence impedance compensation value of the distributed photovoltaic converter, wherein the multi-sequence impedance compensation value includes the fundamental positive-sequence impedance component compensation value, the fundamental negative-sequence impedance component compensation value, and the harmonic impedance component compensation value; a compensation unit is used to perform impedance compensation on the distributed photovoltaic converter based on the multi-sequence impedance compensation value, so as to achieve the uniform distribution of the fundamental positive-sequence power component, harmonic power component, and unbalanced power volume in the microgrid within the distributed photovoltaic converter.

[0007] According to a third aspect of the present invention, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the above-described distributed photovoltaic converter multi-sequence quantity cooperative control method.

[0008] According to a fourth aspect of the present invention, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the above-described distributed photovoltaic converter multi-sequence quantity cooperative control method.

[0009] According to the present invention, a multi-sequence quantity coordinated control method, device, and storage medium for distributed photovoltaic (PV) converters, compared with the current method of distributing load power among multiple PV converters in a fixed ratio, the present invention, by constructing a positive-sequence-negative-zero-sequence control model and comprehensively considering the grid structure parameters of the microgrid and the output power of the distributed PV converters, can more accurately determine the voltage reference value. Based on this voltage reference value, the impedance compensation value obtained enables the distributed PV converters to achieve a uniform distribution of fundamental positive-sequence power components, harmonic power components, and unbalanced power components among the converters under multi-sequence quantity coordinated control. For the positive-sequence loads, harmonic loads, and unbalanced loads existing in the microgrid, precise impedance compensation effectively suppresses voltage distortion and imbalance at the point of common coupling (PCC). During the multi-sequence quantity coordinated control process, the harmonic power components and unbalanced power components are rationally allocated and processed, reducing the impact of harmonic currents and negative-sequence currents on the system. This significantly improves the power quality of the microgrid, ensuring system stability and power supply reliability, and providing users with higher-quality power. The determined impedance constraints and the voltage reference values ​​based on these constraints and other parameters provide an accurate basis for the control of the distributed photovoltaic converter. By predicting the impedance compensation value through a preset droop controller and implementing impedance compensation, the impedance characteristics of the converter can be dynamically adjusted, enabling the system to maintain stable operation even under various complex loads and operating conditions. The distributed control strategy of this invention only requires local communication between adjacent converters and does not rely on global parameter information, which makes the control method highly flexible and adaptable, and can be easily applied to microgrids of different sizes and structures. Attached Figure Description

[0010] The accompanying drawings, which are included to provide a further understanding of the invention and constitute a part of this application, illustrate exemplary embodiments of the invention and, together with the description thereof, serve to explain the invention and do not constitute an improper limitation thereof. In the drawings: Figure 1 shows a flowchart of a multi-sequence quantity cooperative control method for a distributed photovoltaic converter according to an embodiment of the present invention; Figure 2 shows a schematic diagram of a microgrid structure in which multiple distributed photovoltaic converters are connected in parallel through different feeders according to an embodiment of the present invention; Figure 3 shows a flowchart of another multi-sequence quantity cooperative control method for a distributed photovoltaic converter according to an embodiment of the present invention; Figure 4 shows a schematic diagram of a sequence voltage decomposition diagram according to an embodiment of the present invention; Figure 5 shows a schematic diagram of a simulation test microgrid structure according to an embodiment of the present invention; Figure 6 shows a schematic diagram of simulation results under unbalanced load according to an embodiment of the present invention; Figure 7 shows a schematic diagram of simulation results obtained by applying conventional methods and the method proposed in this invention under unbalanced load according to an embodiment of the present invention; Figure 8 shows a schematic diagram of the structure of a multi-sequence quantity cooperative control device for a distributed photovoltaic converter according to an embodiment of the present invention; Figure 9 shows a schematic diagram of the structure of another multi-sequence quantity cooperative control device for a distributed photovoltaic converter according to an embodiment of the present invention; Figure 10 shows a schematic diagram of the physical structure of a computer device according to an embodiment of the present invention. Detailed Implementation

[0011] The present invention will be described in detail below with reference to the accompanying drawings and embodiments. It should be noted that, unless otherwise specified, the embodiments and features described in the present application can be combined with each other.

[0012] Currently, the method of allocating load power to multiple photovoltaic converters in a fixed ratio results in inaccurate power distribution due to the different feeder impedances of different converters, which in turn affects the stability of the power grid.

[0013] To address the aforementioned issues, this invention provides a multi-sequence coordinated control method for a distributed photovoltaic converter, as shown in Figure 1. The method includes: 101. Obtaining the grid structure parameters of the microgrid corresponding to the distributed photovoltaic converter; constructing a positive-sequence-negative-zero-sequence control model for the distributed photovoltaic converter based on the grid structure parameters; and collecting the output power of the distributed photovoltaic converter, wherein the output power includes output active power and output reactive power.

[0014] For the embodiments of the present invention, the grid structure parameters of the microgrid encompass multiple aspects, mainly including line impedance parameters (including resistance and reactance), transformer parameters (such as turns ratio, short-circuit impedance, etc.), node connection parameters, and photovoltaic converter structural parameters. Based on the above parameters, a positive-sequence-negative-sequence-zero-sequence control model for the distributed photovoltaic converters is constructed. This model is a three-dimensional finite element analysis model of the microgrid containing the distributed photovoltaic converters. The active and reactive power outputs of each distributed photovoltaic converter are collected in real time using sensors and other devices. As shown in Figure 2, a microgrid structure with multiple distributed photovoltaic converters connected in parallel through different feeders is illustrated. By constructing a positive-sequence-negative-sequence-zero-sequence control model and comprehensively considering the grid structure parameters of the microgrid and the output power of the distributed photovoltaic converters, the voltage reference value can be determined more accurately in this embodiment of the present invention.

[0015] 102. Determine the impedance constraints of the distributed photovoltaic converter in the multi-sequence coordinated control process. Based on the impedance constraints, the positive-sequence-negative-zero-sequence control model, and the output power, determine the voltage reference value of the distributed photovoltaic converter to ensure the stable operation of the microgrid. The microgrid includes positive-sequence loads, harmonic loads, and unbalanced loads.

[0016] The impedance constraints include the equivalent fundamental positive-sequence impedance constraint, the equivalent harmonic impedance constraint, and the equivalent fundamental negative-sequence impedance constraint corresponding to the distributed photovoltaic converter; the equivalent fundamental positive-sequence impedance constraint is as follows: ,in, , ..., These are the reactance components of the fundamental positive sequence impedance of the corresponding photovoltaic converter. ,…, These are the rated reactive power capacities of the corresponding photovoltaic converters; the equivalent harmonic impedance constraint condition is: ,in, ,…, These are the reactance components of the equivalent harmonic impedance of the corresponding photovoltaic converter. ,…, These are the rated harmonic powers of the corresponding photovoltaic converters; the equivalent fundamental negative sequence impedance constraint condition is: ,in, ,…, These are the reactance components of the equivalent fundamental negative sequence impedance of the feed line of the corresponding photovoltaic converter. ,…, These are the rated unbalanced power of the corresponding photovoltaic converters.

[0017] For an embodiment of the present invention, consider a microgrid system as shown in Figure 2, consisting of multiple distributed photovoltaic power converters connected in parallel via different feeders. The sequence components and feeder impedance distributions are described, along with the photovoltaic converter voltage reference value containing harmonic components. The characteristic of the sequence components and feeder impedance distributions is that the commonly used generalized droop control is:

[0018]

[0019] in, and These are the virtual rated angular frequency and virtual reference angular frequency of the distributed photovoltaic converter, respectively. and Here, represents the rated voltage amplitude and reference voltage amplitude of the distributed photovoltaic (PV) converter; m and n are the generalized droop coefficients of the controller; P and Q are the active power and reactive power output of the converter, respectively. Unlike active power, which can usually be accurately distributed through frequency regulation, the distribution accuracy and stability of reactive power are more easily affected by the impedance differences of the output feeders of the distributed PV converters. This impedance mismatch will cause the reactive power output of each PV converter to deviate from the expected value, thus affecting the voltage quality and operational balance of the system. To improve the accuracy and robustness of reactive power distribution and ensure that each PV converter fairly bears the reactive load according to its capacity ratio, it is necessary to actively design and coordinate the equivalent fundamental positive sequence impedance of the PV converter. Specifically, the equivalent positive sequence impedance presented by each PV converter at the grid connection point should be inversely proportional to its rated capacity, that is, satisfy the following equivalent fundamental positive sequence impedance constraint condition:

[0020] in , ..., The reactance component of the fundamental positive sequence impedance of all photovoltaic converters. ,…, The rated reactive power capacity of all converters is given. The equivalent fundamental positive sequence impedance consists of two parts: the physical feeder impedance, which cannot be arbitrarily changed, and the virtual fundamental positive sequence impedance, which can be flexibly set through a control algorithm. Differences in physical impedance are the main cause of uneven reactive power distribution. Therefore, it is necessary to dynamically adjust the virtual fundamental positive sequence impedance of each photovoltaic converter through a control strategy, so that its equivalent total impedance satisfies the aforementioned inverse proportional relationship, i.e., the above formula. Through this active compensation mechanism, it is possible to reliably and accurately distribute reactive power according to the photovoltaic converter capacity ratio in actual systems with differences in line parameters. The actual operating environment of microgrids is quite complex, with a large number of nonlinear and unbalanced loads commonly present. Drawing on the fundamental positive sequence power distribution method based on virtual impedance, this can be further extended to the harmonic and negative sequence domains. By introducing a designable fundamental negative sequence virtual impedance and various harmonic virtual impedances into the photovoltaic converter control loop, the output impedance characteristics of the photovoltaic converter under different frequency bands and phase sequences can be actively shaped. The equivalent harmonic impedance of a photovoltaic (PV) converter at harmonic frequencies, and the equivalent fundamental negative-sequence impedance at fundamental frequencies, must be inversely proportional to the rated capacity of the PV converter. This requires satisfying the following constraints on equivalent fundamental positive-sequence impedance and equivalent harmonic impedance:

[0021]

[0022] in, ,…, The reactance component of the equivalent harmonic impedance of the feeder; ,…, The rated harmonic power of the photovoltaic converter. ,…, Reactant component of the equivalent fundamental negative sequence impedance of the feeder ,…, This represents the rated unbalanced power of the photovoltaic converter.

[0023] Furthermore, the basic parameters of the photovoltaic converter, such as rated power, rated voltage, and rated current, are obtained. Simultaneously, detailed measurements are taken of positive-sequence loads, harmonic loads, and unbalanced loads. For positive-sequence loads, the magnitudes of active and reactive power are recorded. For harmonic loads, the content of each harmonic current and harmonic voltage is analyzed. For unbalanced loads, the imbalance of three-phase current and voltage is measured. The impedance characteristics of the system are obtained by measuring the resistance and reactance of the feeders connecting the converter to the grid in the microgrid. Based on the collected parameters, the parameters of the positive-sequence-negative-sequence-zero-sequence control model are set: Positive-sequence control model parameters: Based on the power control target of the distributed photovoltaic converter, the proportional and integral coefficients of the positive-sequence active and reactive current controllers are set. These parameters determine the converter's ability to regulate active and reactive power and its response speed. Negative-sequence control model parameters: The main objective of negative-sequence control is to suppress negative-sequence current. Therefore, the parameters of the negative-sequence current controller are set to make the negative-sequence current reference value zero, thereby reducing the impact on grid imbalance. Zero-sequence control model parameters: To address the potential for neutral point voltage shift caused by zero-sequence current, the parameters of the zero-sequence current controller are set to limit the zero-sequence current within the allowable range. Positive-sequence power balance: Considering the active and reactive power demands of positive-sequence loads, and combining the output power capacity of distributed photovoltaic converters, a positive-sequence power balance equation is established. While meeting the positive-sequence load demands, system power losses must be considered to ensure reasonable power allocation and transmission. Negative-sequence and zero-sequence power balance: For negative-sequence and zero-sequence networks, although the main objective is to suppress negative-sequence current and limit zero-sequence current, power balance also needs to be considered. The impact of negative-sequence and harmonic loads on the system is analyzed to ensure that the system's power flow is reasonable while suppressing undesirable components. Calculation of voltage reference value by combining control model and impedance constraints: Multi-sequence quantity collaborative calculation: The positive-sequence-negative-zero-sequence control model is combined with the determined impedance constraints to establish a comprehensive calculation model. Considering the mutual influence between different order quantities, the voltage reference value to ensure the stable operation of the microgrid is gradually determined through iterative calculation.

[0024] 103. Determine the preset droop controller. Based on the voltage reference value and the local communication information of adjacent converters, determine the control input parameters of the preset droop controller, and input the control input parameters into the preset droop controller to predict the impedance compensation value, thereby obtaining the multi-sequence impedance compensation value of the distributed photovoltaic converter. The multi-sequence impedance compensation value includes the fundamental positive sequence impedance component compensation value, the fundamental negative sequence impedance component compensation value, and the harmonic impedance component compensation value.

[0025] The control input parameters can be harmonic power, reactive power, unbalanced power, etc.

[0026] In this embodiment of the invention, the preset droop controller adopts a droop control structure, which simulates the droop characteristics of a synchronous generator to achieve automatic allocation of active and reactive power of the distributed power source, as well as regulation of voltage and frequency. This droop controller mainly consists of a power calculation module, a droop characteristic curve module, a voltage and frequency regulation module, and an impedance compensation module. The power calculation module is responsible for real-time acquisition of the output current and voltage signals of the distributed photovoltaic converter, and then calculating the active and reactive power. The droop characteristic curve module calculates the active and reactive power based on a preset active-frequency droop characteristic curve. Reactive power-voltage droop characteristic curve ,in, and These are the rated frequency and rated voltage, respectively. and These are the rated active power and the rated reactive power, respectively. and These are the active power-frequency droop factor and the reactive power-voltage droop factor, respectively. The calculated active power P and reactive power Q are converted into pre-set corresponding frequency reference values. and voltage reference value Frequency reference value and voltage reference value The frequency deviation and voltage deviation are obtained by comparing them with the actual frequency d and the actual voltage U. Then, the frequency deviation and voltage deviation are adjusted by a proportional-integral (PI) regulator to generate a control signal for controlling the output of the distributed photovoltaic converter, so as to achieve stable control of frequency and voltage.

[0027] Furthermore, this voltage reference value comprehensively considers factors such as the stable operation requirements of the microgrid, load characteristics, and the output capacity of the distributed photovoltaic converters, providing an accurate voltage control target for the droop controller. In the microgrid, distributed photovoltaic converters are connected via a communication network to exchange local information. The communication information between adjacent converters mainly includes parameters such as the output power, voltage, and frequency of the adjacent converters. Data transmission between adjacent converters is achieved by installing a communication module on each converter and using wired or wireless communication methods (such as Ethernet, ZigBee, etc.). Then, based on the voltage reference value and the local communication information of adjacent converters, the control input parameters of the preset droop controller need to be determined. Based on this, the method includes: taking any converter in the distributed photovoltaic converter as a target converter i, and determining the reactive power of the target converter i based on the voltage reference value of the target converter i. Based on the voltage reference value of the adjacent converter j adjacent to the target converter i, the reactive power of the adjacent converter j is determined. Determine the unbalanced power of the target converter i. And determine the unbalanced power of the adjacent converter j. Determine the harmonic power of the target converter i. And determine the harmonic power of the adjacent converter j. Based on the aforementioned reactive power The reactive power Determine the reactive power control input parameters ,in, , This is the first coupling gain. For distributed photovoltaic converters, graph theory is used to form the Laplace matrix elements. Let i be the generalized droop coefficient of the target converter i under reactive power. The generalized droop coefficient of the adjacent converter j under reactive power, where N is the total number of converters; based on the unbalanced power The unbalanced power Determine the input parameters for unbalanced power control. ,in, , This is the first coupling gain. The generalized droop coefficient of the target converter i under unbalanced power is given. The generalized droop coefficient of the adjacent converter j under unbalanced power; based on the harmonic power The harmonic power Determine the input parameters for harmonic power control. ,in, , This is the first coupling gain. The generalized droop coefficient of the target converter i under harmonic power is given. is the generalized droop coefficient of the adjacent converter j under harmonic power.

[0028] Specifically, to achieve precise power allocation, the reactive power, unbalanced power, and harmonic power of each distributed photovoltaic (PV) converter are determined based on its voltage reference value. Using the reactive power, unbalanced power, and harmonic power information of each distributed PV converter, a first-order linear multi-agent system dynamics is constructed, and a corresponding consensus control protocol is designed, thereby transforming the power allocation problem into a regulator synchronization problem within a first-order linear multi-agent system. The constructed system dynamics are described below:

[0029]

[0030]

[0031] in, , , These are the rates of change of reactive power, unbalanced power, and harmonic power, respectively. , , These are the generalized droop coefficients of the preset droop controller. Furthermore, the rates of change of reactive power, unbalanced power, and harmonic power of the distributed photovoltaic converter are considered as state variables of the system. ; , , It can be viewed as the control input of the preset droop controller. Furthermore, the consistency control input of the adaptive cooperative control protocol is designed as follows:

[0032]

[0033]

[0034] in, , , , represents the coupling gain. Distributed photovoltaic systems use graph theory to form Laplace matrix elements. Furthermore, the consistency control input can be transformed into a matrix-form closed-loop system dynamics:

[0035]

[0036]

[0037] in, , , L is the distributed photovoltaic system that uses graph theory to form a Laplace matrix.

[0038] Furthermore, the fundamental positive sequence control input parameters, fundamental negative sequence control input parameters, and harmonic impedance control input parameters are input to a preset droop controller to predict the impedance compensation value, thereby obtaining the fundamental positive sequence impedance component compensation value, the fundamental negative sequence impedance component compensation value, and the harmonic impedance component compensation value. The impedance compensation value obtained based on the voltage reference value in this embodiment of the invention enables the distributed photovoltaic converter to achieve a uniform distribution of fundamental positive-sequence power components, harmonic power components, and unbalanced power components among the converters under multi-sequence quantity coordinated control. For positive-sequence loads, harmonic loads, and unbalanced loads existing in the microgrid, precise impedance compensation effectively suppresses voltage distortion and imbalance at the point of common coupling (PCC). During the multi-sequence quantity coordinated control process, the harmonic and unbalanced power components are rationally allocated and processed, reducing the impact of harmonic currents and negative-sequence currents on the system. This significantly improves the power quality of the microgrid, ensures system stability and power supply reliability, and provides users with higher-quality power. The determined impedance constraints and the voltage reference value determined based on these conditions and other parameters provide an accurate basis for the control of the distributed photovoltaic converter.

[0039] 104. Based on the multi-sequence impedance compensation value, impedance compensation is performed on the distributed photovoltaic converter to achieve uniform distribution of the fundamental positive sequence power component, harmonic power component, and unbalanced power flow in the microgrid within the distributed photovoltaic converter.

[0040] In this embodiment of the invention, a microgrid system comprising multiple distributed photovoltaic (PV) converters is included. This system also includes different types of loads, such as linear loads (e.g., lighting equipment, resistance heaters) and nonlinear loads (e.g., rectifiers, frequency converters). The distributed PV converters convert solar energy into electrical energy through power electronic interfaces and connect to the microgrid via feeders. The converters are connected through a communication network to achieve information exchange and sharing. High-precision voltage and current measurement devices, such as voltage transformers and current transformers, are installed at the output of each distributed PV converter to acquire the output voltage and current signals in real time. Simultaneously, power analyzers are installed at key nodes of the microgrid to measure and analyze the power distribution within the microgrid, including fundamental positive-sequence power, harmonic power, and unbalanced power. The multi-sequence impedance of each distributed PV converter is measured using either a harmonic injection method or a system identification method. Harmonic injection method: A harmonic current signal of a specific frequency is injected into the output of the distributed PV converter. By measuring the voltage change at the converter output before and after the harmonic current injection, the impedance value at that frequency is calculated according to Ohm's law. By sequentially injecting harmonic currents of different frequencies, the impedance characteristics of the converter at each harmonic frequency can be obtained. Simultaneously, through positive-sequence, negative-sequence, and zero-sequence separation techniques, the fundamental positive-sequence impedance, fundamental negative-sequence impedance, and zero-sequence impedance are obtained respectively. System identification method: Using the collected input and output data of the distributed photovoltaic converter under different operating conditions, a mathematical model of the converter is established. Then, the model parameters are estimated using system identification algorithms (such as least squares method, maximum likelihood method, etc.), thereby obtaining the multi-sequence impedance parameters of the converter. Based on the power distribution requirements of the microgrid and the multi-sequence impedance measurement results of each distributed photovoltaic converter, the required multi-sequence impedance compensation value for each converter is calculated. To achieve uniform distribution of fundamental positive-sequence power among the distributed photovoltaic converters, the fundamental positive-sequence impedance compensation value is calculated based on the difference in fundamental positive-sequence impedance of each converter; for uniform distribution of harmonic power, the harmonic impedance compensation value of each converter is calculated for different harmonic orders; to achieve uniform distribution of unbalanced power, the fundamental negative-sequence impedance compensation value is calculated based on the difference in fundamental negative-sequence impedance of each converter. To address the line impedance mismatch problem, an adaptive adjustment mechanism based on a distributed consensus protocol, including virtual fundamental impedance and harmonic impedance, is introduced to compensate for impedance and ensure the precise proportional distribution of reactive power, harmonic power, and unbalanced power. Furthermore, a dynamic consensus-based control method is proposed to achieve stable recovery of the system output voltage. An impedance compensation device based on power electronics technology can also be designed. This device mainly consists of power electronic devices (such as IGBTs), a control circuit, and a drive circuit. The control circuit generates corresponding control signals based on the calculated multi-sequence impedance compensation values, and the drive circuit amplifies the control signals to drive the power electronic devices, achieving real-time adjustment of the output impedance of the distributed photovoltaic converter.The embodiments of the present invention predict impedance compensation values ​​by using a preset droop controller and implement impedance compensation, which can dynamically adjust the impedance characteristics of the converter, so that the system can still maintain stable operation when facing various complex loads and operating conditions. The distributed control strategy of the present invention only requires local communication between adjacent converters and does not depend on global parameter information, which makes the control method have good flexibility and adaptability, and can be easily applied to microgrids of different sizes and structures.

[0041] According to the present invention, a multi-sequence coordinated control method for distributed photovoltaic (PV) converters, compared with the current method of allocating load power to multiple PV converters in a fixed ratio, allows for more accurate determination of voltage reference values ​​by constructing a positive-sequence-negative-zero-sequence control model and comprehensively considering the grid structure parameters of the microgrid and the output power of the distributed PV converters. Based on this voltage reference value, the impedance compensation value obtained enables the distributed PV converters to achieve uniform distribution of fundamental positive-sequence power components, harmonic power components, and unbalanced power components among the converters under multi-sequence coordinated control. For positive-sequence loads, harmonic loads, and unbalanced loads existing in the microgrid, precise impedance compensation effectively suppresses voltage distortion and imbalance at the point of common coupling (PCC). During the multi-sequence coordinated control process, the harmonic power components and unbalanced power components are rationally allocated and processed, reducing the impact of harmonic currents and negative-sequence currents on the system. This significantly improves the power quality of the microgrid, ensuring system stability and power supply reliability, and providing users with higher-quality power. The determined impedance constraints and the voltage reference values ​​based on these constraints and other parameters provide an accurate basis for the control of the distributed photovoltaic converter. By predicting the impedance compensation value through a preset droop controller and implementing impedance compensation, the impedance characteristics of the converter can be dynamically adjusted, enabling the system to maintain stable operation even under various complex loads and operating conditions. The distributed control strategy of this invention only requires local communication between adjacent converters and does not rely on global parameter information, which makes the control method highly flexible and adaptable, and can be easily applied to microgrids of different sizes and structures.

[0042] Furthermore, to better illustrate the above-described process of coordinated control of multiple sequence quantities of a distributed photovoltaic converter, as a refinement and extension of the above embodiments, this embodiment of the invention provides another method for coordinated control of multiple sequence quantities of a distributed photovoltaic converter, as shown in Figure 3. The method includes: 201. Obtaining the grid structure parameters of the microgrid corresponding to the distributed photovoltaic converter, constructing a positive-sequence-negative-zero-sequence control model of the distributed photovoltaic converter based on the grid structure parameters; and collecting the output power of the distributed photovoltaic converter, wherein the output power includes output active power and output reactive power.

[0043] Specifically, a comprehensive collection of various grid structure parameters for the microgrid to which the distributed photovoltaic (PV) converter is connected is conducted, covering key information such as line impedance, transformer parameters, and topology. Based on the acquired grid structure parameters, a positive-sequence, negative-sequence, and zero-sequence control model for the distributed PV converter is constructed. This model can accurately describe the electrical characteristics and control logic of the converter under different sequence parameters. A power measurement device is installed at the output of the distributed PV converter to collect its output power data in real time and accurately, including output active power and output reactive power, providing a basis for subsequent control strategy adjustments.

[0044] 202. Determine the impedance constraints of the distributed photovoltaic converter in the multi-sequence quantity collaborative control process.

[0045] Specifically, the equivalent fundamental positive sequence impedance constraint, equivalent harmonic impedance constraint, and equivalent fundamental negative sequence impedance constraint are determined in the multi-sequence coordinated control process of the distributed photovoltaic converter, so as to reasonably constrain the adjustment range of impedance.

[0046] 203. Based on impedance constraints, positive-sequence-negative-zero-sequence control model, and output power, determine the reference voltage amplitude under positive-sequence voltage, reference voltage amplitude under harmonic voltage, and reference voltage amplitude under unbalanced voltage for the distributed photovoltaic converter.

[0047] In this embodiment of the invention, to achieve coordinated control of sequence quantities by a distributed photovoltaic converter, it is first necessary to determine the reference voltage amplitude under positive sequence voltage, the reference voltage amplitude under harmonic voltage, and the reference voltage amplitude under unbalanced voltage of the distributed photovoltaic converter. Based on this, step 203 specifically includes: determining the positive sequence generalized droop coefficient n and the harmonic generalized droop coefficient n of the preset droop controller based on the impedance constraint condition and the positive-sequence-negative-zero sequence control model. Unbalanced generalized droop coefficient Based on the active power Q in the output power and the rated power of the distributed photovoltaic converter Determine the reference voltage amplitude under the positive sequence voltage of the distributed photovoltaic converter. ,in, Based on the harmonic reactive power in the output power. The harmonic generalized droop coefficient Determine the reference voltage amplitude of the distributed photovoltaic converter under harmonic voltage. ,in, Based on the unbalanced reactive power in the output power. The unbalanced generalized droop coefficient Determine the reference voltage amplitude of the distributed photovoltaic converter under unbalanced voltage. ,in, .

[0048] Specifically, positive-sequence power in a microgrid is primarily responsible for transmitting active and reactive power, achieving efficient energy distribution. Based on the load distribution of the microgrid and the output of distributed photovoltaic (PV) power sources, the proportion of positive-sequence power that each distributed PV converter needs to handle is analyzed. For example, in areas with concentrated loads, nearby distributed PV converters are required to handle more positive-sequence power to ensure voltage stability and power supply in the area. Based on impedance constraints, the influence of line impedance and converter internal impedance on positive-sequence power distribution is considered. Based on the positive-sequence-negative-zero-sequence control model, the distribution of positive-sequence power under different droop coefficients is analyzed through simulation. The value of the droop coefficient n is gradually adjusted, and the changing trend of the positive-sequence power output of each converter is observed. When the positive-sequence power output by each converter can be distributed according to a predetermined ratio and the impedance constraints are met, the final value of the positive-sequence generalized droop coefficient n is determined.

[0049] In microgrids, nonlinear loads are the main sources of harmonics. Equipment such as rectifiers and frequency converters generate a large amount of harmonic current, which in turn forms harmonic power in the system. By installing harmonic monitoring devices, the harmonic content and harmonic power distribution in the microgrid can be monitored in real time. The frequency, amplitude, and phase characteristics of different harmonics can be analyzed to understand the propagation path and impact of harmonic power among distributed photovoltaic converters. Based on the influence of impedance constraints on harmonic power distribution, different frequencies of harmonics have different propagation characteristics in the system. Line impedance and converter internal impedance play an important role in the attenuation and distribution of harmonic power. Combining the positive-sequence-negative-zero-sequence control model, the relationship between harmonic power distribution and droop coefficient is established. Through simulation and experimentation, the value of the generalized harmonic droop coefficient is adjusted, and the changes in the output harmonic power of each converter are observed. When each converter can share the harmonic power according to certain rules, and the harmonic distortion rate of the system meets the relevant standard requirements, the final value of the generalized harmonic droop coefficient is determined. .

[0050] In microgrids, unbalanced power is generated due to asymmetrical load operation or asymmetrical access of distributed photovoltaic power sources. By measuring the voltage and current of each phase, the negative-sequence power and zero-sequence power in the microgrid are calculated to assess the magnitude and distribution of unbalanced power. The impact of unbalanced power on system equipment is analyzed, such as causing transformer overheating and increased motor vibration, to clarify the objectives for controlling unbalanced power. Considering impedance constraints and a positive-sequence-negative-zero-sequence control model, the propagation and distribution mechanism of unbalanced power in the system is analyzed. Based on the control objectives of unbalanced power, such as limiting negative-sequence and zero-sequence power within a certain range, the generalized droop coefficient of unbalanced power is adjusted through simulation and experiment. The changes in the output unbalanced power of each converter are observed. When the system unbalance meets the relevant standard requirements and each converter can reasonably share the unbalanced power, the final value of the generalized droop coefficient of unbalanced power is determined. .

[0051] Finally, based on the positive-order generalized droop coefficient n and the harmonic generalized droop coefficient... Unbalanced generalized droop coefficient Parameters are used to determine the reference voltage amplitude under the positive sequence voltage of the distributed photovoltaic converter. Reference voltage amplitude under harmonic voltage Reference voltage amplitude under unbalanced voltage .

[0052] 204. Determine the fundamental positive sequence voltage drop, fundamental negative sequence voltage drop, and harmonic voltage drop of the virtual impedance on the distributed photovoltaic converter.

[0053] Specifically, during the normal operation of the microgrid, specialized monitoring equipment is used to collect real-time electrical data such as the output current and output voltage of the distributed photovoltaic converters. Simultaneously, the voltage and current at the microgrid's point of common coupling (PCC) are monitored to gain a comprehensive understanding of the system's operating status. Analysis of this real-time data allows for an understanding of the power flow and voltage fluctuations of the microgrid under different operating conditions, providing a basis for subsequently determining the voltage drop value of the virtual impedance.

[0054] Fundamental positive sequence voltage drop Determination of the fundamental positive-sequence component: A suitable signal processing method, such as Fourier transform or symmetrical component method, is used to extract the fundamental positive-sequence component from the acquired output voltage and current signals of the distributed photovoltaic (PV) converter. Taking the symmetrical component method as an example, the three-phase voltage and current are decomposed into positive-sequence, negative-sequence, and zero-sequence components, from which the fundamental positive-sequence voltage and current are separated. Based on the stable operation requirements of the microgrid and the control objectives of the distributed PV converter, an appropriate virtual impedance value is set. The setting of the virtual impedance needs to consider various factors, such as line impedance, load characteristics, and power distribution requirements. For example, to achieve reasonable power distribution among the distributed PV converters, the virtual impedance can be set according to the capacity ratio of each converter. For example, a converter with a larger capacity can be set with a smaller virtual impedance to handle more power. Calculation of Fundamental Positive Sequence Voltage Drop: After determining the fundamental positive sequence current and virtual impedance, the fundamental positive sequence voltage drop value is determined by analyzing the relationship between the voltage drop across the virtual impedance and the current. The voltage drop across the virtual impedance is caused by the fundamental positive sequence current flowing through it. By analyzing the changes in the fundamental positive sequence current under different operating conditions, combined with the set virtual impedance value, the impact of the fundamental positive sequence voltage drop value on the output voltage of the distributed photovoltaic converter and the voltage stability of the microgrid is evaluated. For example, when the load increases, the fundamental positive sequence current will increase, and the voltage drop across the virtual impedance will also increase accordingly. At this time, it is necessary to ensure that the voltage drop value is within the allowable range to ensure the normal operation of the system. After multiple simulations and experimental verifications, a suitable fundamental positive sequence voltage drop value was finally determined.

[0055] Fundamental negative sequence voltage drop Determination of the fundamental negative sequence component: Using the same signal processing method, the fundamental negative sequence component is extracted from the acquired voltage and current signals. Similar to the extraction of the fundamental positive sequence component, the three-phase signal is decomposed using the symmetrical component method to obtain the fundamental negative sequence voltage and fundamental negative sequence current. The existence of the fundamental negative sequence component is usually due to unbalanced loads or unbalanced faults in the microgrid. Considering that the impact of the fundamental negative sequence component on the system differs from that of the fundamental positive sequence component, the virtual impedance needs to be adjusted according to the characteristics of the fundamental negative sequence component. The fundamental negative sequence current will cause negative sequence voltage in the system, affecting the normal operation of equipment and power quality. Therefore, when setting the virtual impedance, the resistance to the fundamental negative sequence current should be appropriately increased to suppress the generation of negative sequence voltage. For example, a fundamental negative sequence virtual impedance value different from the fundamental positive sequence virtual impedance can be set to better cope with the impact of the fundamental negative sequence component. Determination of the fundamental negative sequence voltage drop: Based on the adjusted fundamental negative sequence virtual impedance and the extracted fundamental negative sequence current, the fundamental negative sequence voltage drop on the virtual impedance is analyzed. Through simulation and experiments, the variation law of the fundamental negative sequence voltage drop under different asymmetrical operating conditions was observed. For example, when different degrees of asymmetrical load are connected, the magnitude and phase of the fundamental negative sequence current will change, thus causing the fundamental negative sequence voltage drop to change accordingly. Based on the power quality requirements of the microgrid, such as the limitation standard of negative sequence voltage imbalance, a suitable fundamental negative sequence voltage drop value was determined to ensure that the system can still operate stably under asymmetrical operating conditions.

[0056] Harmonic voltage drop value Determination of Harmonic Components: Harmonic analysis methods, such as Fast Fourier Transform (FFT), are used to analyze the harmonics of the acquired output voltage and current signals of the distributed photovoltaic converter, extracting each harmonic component. Harmonic voltages and currents at different frequencies can be obtained separately. High precision is required for harmonic component extraction to ensure the accuracy of subsequent calculations. For different harmonics, corresponding virtual harmonic impedances are set according to their characteristics and impact on the system. Harmonics of different frequencies have different propagation and attenuation characteristics in the system, therefore, virtual harmonic impedances need to be set separately. For example, for low-order harmonics (such as the 3rd and 5th harmonics), their impact on the system is greater, and a larger virtual impedance may be needed to suppress their propagation; while for high-order harmonics, due to their faster attenuation, a smaller virtual impedance can be set appropriately. At the same time, the setting of the virtual harmonic impedance also needs to consider the control capability of the distributed photovoltaic converter and the characteristics of the filtering device. Determination of Harmonic Voltage Drop: Based on the set virtual harmonic impedance and the extracted harmonic currents, the harmonic voltage drop across the virtual impedance is analyzed. This study investigates the variation of harmonic voltage drop under different harmonic sources and load conditions through simulation and experiments. For example, when a nonlinear load is connected to a microgrid, a large amount of harmonic current is generated, leading to an increase in harmonic voltage drop. Based on the microgrid's harmonic distortion rate limit standards, the allowable range of harmonic voltage drop for each harmonic order is determined. By adjusting the value of the harmonic virtual impedance, the harmonic voltage drop is made to meet the requirements, thereby improving the power quality of the microgrid.

[0057] 205. Based on the reference voltage amplitude, the reference voltage amplitude under harmonic voltage, the reference voltage amplitude under unbalanced voltage, the fundamental positive sequence voltage drop, the fundamental negative sequence voltage drop, and the harmonic voltage drop, determine the voltage reference value for the distributed photovoltaic converter to ensure the stable operation of the microgrid.

[0058] The microgrid includes positive-sequence loads, harmonic loads, and unbalanced loads. Specifically, the voltage reference value for the distributed photovoltaic converter to ensure stable operation of the microgrid is determined according to the following formula. :

[0059] The specific sequence voltage decomposition diagram is shown in Figure 4. An integrated design of the harmonic / unbalance droop controller and multi-sequence virtual impedance enables coordinated control of the fundamental positive-sequence, negative-sequence, and harmonic impedances. This method ensures that all power components are accurately distributed according to capacity ratios and comprehensively addresses voltage distortion and imbalance at the point of common coupling (PCC), thereby simultaneously achieving power distribution optimization and power quality improvement under a unified control architecture.

[0060] 206. Determine the preset droop controller. Based on the voltage reference value and the local communication information of adjacent converters, determine the control input parameters of the preset droop controller, and input the control input parameters into the preset droop controller to predict the impedance compensation value, thereby obtaining the multi-sequence impedance compensation value of the distributed photovoltaic converter. The multi-sequence impedance compensation value includes the fundamental positive sequence impedance component compensation value, the fundamental negative sequence impedance component compensation value, and the harmonic impedance component compensation value.

[0061] The preset droop controller can be pre-built based on a sample dataset, which includes sample control input parameters labeled with impedance compensation values. These sample control input parameters are related to the power, frequency, voltage, and other parameters associated with the multi-sequence regulation process of the photovoltaic converter.

[0062] Specifically, based on the system characteristics, control requirements, and expected performance indicators of the microgrid where the distributed photovoltaic (PV) converter is located, a suitable pre-set droop controller is selected or designed to ensure its ability to process subsequent input parameters and predict impedance compensation values. Control input parameter determination: On one hand, the voltage reference value of the distributed PV converter itself is collected, reflecting the desired voltage operating state; on the other hand, relevant operating information of adjacent converters, such as voltage and current data, is obtained through local communication. Combining the voltage reference value and the local communication information from adjacent converters, and through specific analysis and processing logic, the control input parameters of the pre-set droop controller are determined. Impedance compensation value prediction: The determined control input parameters are accurately input into the pre-set droop controller. The controller, based on its internal pre-set algorithm and model, calculates and analyzes these input parameters, simulates impedance conditions under different sequence quantities, and then predicts the multi-sequence impedance compensation value of the distributed PV converter. This multi-sequence impedance compensation value covers the fundamental positive-sequence impedance component compensation value, the fundamental negative-sequence impedance component compensation value, and the harmonic impedance component compensation value, enabling comprehensive compensation and adjustment of the distributed PV converter's impedance under different sequence quantities.

[0063] 207. Based on the multi-sequence impedance compensation value, impedance compensation is performed on the distributed photovoltaic converter to achieve uniform distribution of the fundamental positive sequence power component, harmonic power component, and unbalanced power flow in the microgrid within the distributed photovoltaic converter.

[0064] Among them, the multi-sequence impedance compensation value includes the fundamental positive sequence impedance compensation value. Fundamental negative sequence impedance compensation value Harmonic impedance compensation value .

[0065] In this embodiment of the invention, in order to achieve a uniform distribution of the fundamental positive-sequence power component, harmonic power component, and unbalanced power flow of the distributed photovoltaic converter, impedance compensation of the distributed photovoltaic converter is required based on the multi-sequence impedance compensation value. Therefore, step 207 specifically includes: determining the fundamental positive-sequence impedance component of distributed photovoltaic converter i. Fundamental negative sequence impedance component Harmonic impedance components Determine the virtual angular frequency Based on the virtual angular frequency Using the fundamental positive sequence impedance compensation value For the fundamental positive sequence impedance component Compensation is performed to obtain the compensated fundamental positive sequence impedance. ,in, , Adjust the proportional gain for the fundamental positive sequence; based on the virtual angular frequency. Using the fundamental negative sequence impedance compensation value For the fundamental negative sequence impedance component Compensation is performed to obtain the compensated fundamental negative sequence impedance. ,in, , Adjust the proportional gain for the fundamental negative sequence; based on the virtual angular frequency. Using the aforementioned harmonic impedance compensation value For the harmonic impedance components Compensation is performed to obtain the compensated harmonic impedance. ,in, , Adjust the proportional gain for harmonics. This includes determining the virtual angular frequency. The method includes: determining the positive sequence impedance components of the actual feed line of the distributed photovoltaic converter i. Negative sequence impedance components and h-th harmonic impedance components Determine the virtual fundamental positive sequence impedance of distributed photovoltaic converter i. Virtual fundamental negative sequence impedance and h-th virtual harmonic impedance Determine the virtual fundamental positive sequence impedance of distributed photovoltaic converter i. Virtual fundamental negative sequence impedance and integrated virtual harmonic impedance Based on the positive sequence impedance components The positive sequence impedance component The negative sequence impedance component The h-th harmonic impedance component The virtual fundamental positive sequence impedance The virtual fundamental negative sequence impedance The h-th virtual harmonic impedance The virtual fundamental positive sequence impedance The virtual fundamental negative sequence impedance The aforementioned integrated virtual harmonic impedance Determine the virtual angular frequency ,in, , , .

[0066] Specifically, the combined virtual fundamental positive-sequence impedance, the combined virtual fundamental negative-sequence impedance, and the combined virtual harmonic impedance can be further expressed by the following formula:

[0067]

[0068]

[0069] By solving the above formulas simultaneously, the virtual angular frequency can be obtained. Where h is the harmonic order. The comprehensive virtual harmonic impedance can consider up to the 7th harmonic component.

[0070] Furthermore, the linear multi-agent dynamic model of fundamental positive-sequence, negative-sequence, and harmonic virtual reactances, along with an adaptive cooperative control protocol, are presented. The linear multi-agent dynamic model of fundamental positive-sequence, negative-sequence, and harmonic virtual reactances can be understood as follows: In an ideal situation, to achieve accurate power sharing, the corresponding virtual impedance needs to be designed based on the physical feeder parameters of each distributed photovoltaic inverter. However, in actual microgrids, line parameters may vary due to temperature, aging, or installation differences, and are difficult to measure accurately in real time, posing a significant challenge to fixed-parameter design methods. To address this issue, this invention proposes a distributed adaptive control strategy based on consensus theory. This strategy does not rely on prior precise values ​​of feeder parameters but allows each distributed photovoltaic inverter to dynamically and cooperatively adjust its virtual fundamental positive-sequence impedance, virtual fundamental negative-sequence impedance, and virtual harmonic impedances solely through local measurements and limited communication with adjacent nodes. Through this online adaptive adjustment, the system can autonomously meet the aforementioned impedance matching conditions even when parameters are unknown or mismatched, thereby ensuring accurate and robust distribution of reactive power, unbalanced power, and harmonic power among distributed photovoltaic inverters according to their capacity ratios. Furthermore, the compensated fundamental positive sequence impedance is determined using the following formula. Compensated fundamental negative sequence impedance and compensated harmonic impedance :

[0071]

[0072]

[0073] In this embodiment of the invention, the controller is configured to adjust the harmonic and unbalanced components in the output voltage of the distributed photovoltaic inverters (DPV) to match the harmonic and negative-sequence voltage drops generated at the corresponding equivalent output impedance, thereby suppressing voltage distortion and unbalance at the point of common coupling (PCC). Simultaneously, by controlling the equivalent harmonic impedance and the equivalent fundamental negative-sequence impedance, each DPV inverter shares the harmonic and unbalanced power proportionally to its capacity, thus simultaneously achieving improved PCC voltage quality and precise power distribution. A harmonic and unbalanced droop controller is designed to improve the PCC voltage quality while proportionally sharing harmonic and unbalanced power among the DGs.

[0074] in, , These are the output harmonic reactive power and output unbalanced reactive power of a distributed photovoltaic inverter. , These are the harmonic voltage reference values ​​and unbalanced voltage reference values ​​output by the distributed photovoltaic inverter. , These are the droop coefficients. Thus, this harmonic and unbalanced droop control method can improve the voltage quality at the PCC point, while simultaneously enabling the distributed photovoltaic inverter to properly share the harmonic and unbalanced power.

[0075] This invention constructs positive-sequence, negative-sequence, and zero-sequence control models for distributed photovoltaic inverters and designs an adaptive collaborative control strategy based on feeder impedance. It proposes harmonic and unbalanced droop control methods to achieve reasonable distribution of harmonic and unbalanced power among the distributed photovoltaic converters, while improving the voltage quality at the common coupling point. Addressing the line impedance mismatch problem, it introduces an adaptive adjustment mechanism for virtual fundamental and harmonic impedance based on a distributed consensus protocol to ensure precise proportional distribution of reactive power, harmonic power, and unbalanced power. Furthermore, it proposes a control method based on dynamic consensus to achieve stable recovery of the system output voltage.

[0076] In another embodiment of the present invention, the multi-sequence collaborative control method of the present invention was simulated and tested in the MATLAB / SIMULINK simulation environment. The system topology is shown in Figure 5. This simulation connects a linear unbalanced load at the PCC point and assumes that all distributed photovoltaic inverters have the same capacity. Before t=0.5s, the system operates using the traditional control method; from t=0.5s onwards, the unbalanced droop controller proposed in this embodiment of the present invention, as well as the distributed fundamental positive-sequence and negative-sequence virtual impedance controller based on consistency, are activated. The simulation results are shown in Figure 6. Figures 4(a) and (b) show that under the traditional control method, reactive power and unbalanced power cannot be accurately distributed proportionally among the distributed photovoltaic inverters, exhibiting significant deviations. Although all units have the same capacity, due to line impedance mismatch, the reactive power and unbalanced power they bear are not the same. Starting from t=0.5s, after adopting the converter multi-sequence collaborative control method proposed in this embodiment of the present invention, these two types of power are accurately and evenly distributed, as shown in Figures 6(a) and (b), and the distribution of active power is unaffected. Figures 6(c) and (d) further demonstrate that each distributed photovoltaic inverter can reasonably share the load current according to the proposed method. Figure 7 compares the voltage waveforms at the PCC point under the traditional method and the method proposed in this embodiment of the invention. In Figure 7(a) and (b), the PCC voltage waveforms are shown for the two methods, respectively; while Figures 7(c) and (d) show the voltage waveforms under the corresponding conditions. The fundamental negative-sequence voltage component in the coordinate system. It can be seen that, after adopting the method proposed in this embodiment of the invention, the PCC voltage quality is significantly improved. The amplitude of the fundamental negative sequence voltage in the coordinate system decreased from about 7.5V to about 1V.

[0077] According to another distributed photovoltaic (PV) converter multi-sequence coordinated control method provided by the present invention, compared with the current method of allocating load power to multiple PV converters according to a fixed ratio, the present invention constructs a positive-sequence-negative-sequence-zero-sequence control model and comprehensively considers the grid structure parameters of the microgrid and the output power of the distributed PV converters, which can more accurately determine the voltage reference value. Based on the impedance compensation value obtained from this voltage reference value, the distributed PV converter can achieve a uniform distribution of fundamental positive-sequence power components, harmonic power components, and unbalanced power components among the converters under multi-sequence coordinated control. For the positive-sequence load, harmonic load, and unbalanced load existing in the microgrid, the voltage distortion and imbalance at the point of common coupling (PCC) are effectively suppressed through precise impedance compensation. In the process of multi-sequence coordinated control, the harmonic power components and unbalanced power components are reasonably allocated and processed, reducing the impact of harmonic current and negative-sequence current on the system. This significantly improves the power quality of the microgrid, ensuring system stability and power supply reliability, and providing users with higher-quality power. The determined impedance constraints and the voltage reference values ​​based on these constraints and other parameters provide an accurate basis for the control of the distributed photovoltaic converter. By predicting the impedance compensation value through a preset droop controller and implementing impedance compensation, the impedance characteristics of the converter can be dynamically adjusted, enabling the system to maintain stable operation even under various complex loads and operating conditions. The distributed control strategy of this invention only requires local communication between adjacent converters and does not rely on global parameter information, which makes the control method highly flexible and adaptable, and can be easily applied to microgrids of different sizes and structures.

[0078] Furthermore, as a specific implementation of Figure 1, this embodiment of the invention provides a multi-sequence quantity collaborative control device for a distributed photovoltaic converter, as shown in Figure 8. The device includes: a construction unit 31, a determination unit 32, a prediction unit 33, and a compensation unit 34.

[0079] The construction unit 31 can be used to obtain the grid structure parameters of the microgrid corresponding to the distributed photovoltaic converter, construct a positive-sequence-negative-zero-sequence control model of the distributed photovoltaic converter based on the grid structure parameters, and collect the output power of the distributed photovoltaic converter, wherein the output power includes output active power and output reactive power.

[0080] The determining unit 32 can be used to determine the impedance constraint conditions of the distributed photovoltaic converter in the multi-sequence quantity coordinated control process. Based on the impedance constraint conditions, the positive-sequence-negative-zero-sequence control model, and the output power, the voltage reference value of the distributed photovoltaic converter to ensure the stable operation of the microgrid is determined. The microgrid includes positive-sequence loads, harmonic loads, and unbalanced loads.

[0081] The prediction unit 33 can be used to determine a preset droop controller, determine the control input parameters of the preset droop controller based on the voltage reference value, and input the control input parameters to the preset droop controller to predict the impedance compensation value, thereby obtaining the multi-sequence impedance compensation value of the distributed photovoltaic converter. The multi-sequence impedance compensation value includes the fundamental positive sequence impedance component compensation value, the fundamental negative sequence impedance component compensation value, and the harmonic impedance component compensation value.

[0082] The compensation unit 34 can be used to perform impedance compensation on the distributed photovoltaic converter based on the multi-sequence impedance compensation value, so as to achieve uniform distribution of the fundamental positive sequence power component, harmonic power component, and unbalanced power volume in the distributed photovoltaic converter in the microgrid.

[0083] In specific application scenarios, the impedance constraints include the equivalent fundamental positive-sequence impedance constraint, the equivalent harmonic impedance constraint, and the equivalent fundamental negative-sequence impedance constraint corresponding to the distributed photovoltaic converter; the equivalent fundamental positive-sequence impedance constraint is as follows: ,in, , ..., These are the reactance components of the fundamental positive sequence impedance of the corresponding photovoltaic converter. ,…, These are the rated reactive power capacities of the corresponding photovoltaic converters; the equivalent harmonic impedance constraint condition is: ,in, ,…, These are the reactance components of the equivalent harmonic impedance of the corresponding photovoltaic converter. ,…, These are the rated harmonic powers of the corresponding photovoltaic converters; the equivalent fundamental negative sequence impedance constraint condition is: ,in, ,…, These are the reactance components of the equivalent fundamental negative sequence impedance of the feed line of the corresponding photovoltaic converter. ,…, These are the rated unbalanced power of the corresponding photovoltaic converters.

[0084] In specific application scenarios, in order to determine the voltage reference value, the determining unit 32 can be used to determine the reference voltage amplitude under the positive sequence voltage of the distributed photovoltaic converter based on the impedance constraint condition, the positive-sequence-negative-zero-sequence control model, and the output power. Reference voltage amplitude under harmonic voltage Reference voltage amplitude under unbalanced voltage Determine the fundamental positive sequence voltage drop of the virtual impedance on the distributed photovoltaic converter, respectively. Fundamental negative sequence voltage drop value Harmonic voltage drop value Based on the reference voltage amplitude The reference voltage amplitude under the harmonic voltage The reference voltage amplitude under the unbalanced voltage The fundamental positive sequence voltage drop value The fundamental negative sequence voltage drop value The harmonic voltage drop value Determine the voltage reference value of the distributed photovoltaic converter to ensure the stable operation of the microgrid. ,in, .

[0085] In specific application scenarios, in order to determine the reference voltage amplitude under the positive sequence voltage of the distributed photovoltaic converter... Reference voltage amplitude under harmonic voltage Reference voltage amplitude under unbalanced voltage The determining unit 32 can specifically be used to determine the positive-sequence generalized droop coefficient n and the harmonic generalized droop coefficient of the preset droop controller based on the impedance constraint condition and the positive-sequence-negative-zero-sequence control model. Unbalanced generalized droop coefficient Based on the active power Q in the output power and the rated power of the distributed photovoltaic converter Determine the reference voltage amplitude under the positive sequence voltage of the distributed photovoltaic converter. ,in, Based on the harmonic reactive power in the output power. The harmonic generalized droop coefficient Determine the reference voltage amplitude of the distributed photovoltaic converter under harmonic voltage. ,in, Based on the unbalanced reactive power in the output power. The unbalanced generalized droop coefficient Determine the reference voltage amplitude of the distributed photovoltaic converter under unbalanced voltage. ,in, .

[0086] In specific application scenarios, in order to determine the control input parameters of the preset droop controller, the prediction unit 33 can be used to take any one of the distributed photovoltaic converters as a target converter i, and determine the reactive power of the target converter i based on the voltage reference value of the target converter i. Based on the voltage reference value of the adjacent converter j adjacent to the target converter i, the reactive power of the adjacent converter j is determined. Determine the unbalanced power of the target converter i. And determine the unbalanced power of the adjacent converter j. Determine the harmonic power of the target converter i. And determine the harmonic power of the adjacent converter j. Based on the aforementioned reactive power The reactive power Determine the reactive power control input parameters ,in, , This is the first coupling gain. For distributed photovoltaic converters, graph theory is used to form the Laplace matrix elements. Let i be the generalized droop coefficient of the target converter i under reactive power. The generalized droop coefficient of the adjacent converter j under reactive power, where N is the total number of converters; based on the unbalanced power The unbalanced power Determine the input parameters for unbalanced power control. ,in, , This is the first coupling gain. The generalized droop coefficient of the target converter i under unbalanced power is given. The generalized droop coefficient of the adjacent converter j under unbalanced power; based on the harmonic power The harmonic power Determine the input parameters for harmonic power control. ,in, , This is the first coupling gain. The generalized droop coefficient of the target converter i under harmonic power is given. is the generalized droop coefficient of the adjacent converter j under harmonic power.

[0087] In specific application scenarios, the multi-sequence impedance compensation value includes the fundamental positive sequence impedance compensation value. Fundamental negative sequence impedance compensation value Harmonic impedance compensation value To perform impedance compensation for the distributed photovoltaic converter, as shown in Figure 9, the compensation unit 34 includes a determination module 341 and a compensation module 342.

[0088] The determining module 341 can be used to determine the fundamental positive sequence impedance component of the distributed photovoltaic converter i. Fundamental negative sequence impedance component Harmonic impedance components Determine the virtual angular frequency .

[0089] The compensation module 342 can be used to compensate based on the virtual angular frequency. Using the fundamental positive sequence impedance compensation value For the fundamental positive sequence impedance component Compensation is performed to obtain the compensated fundamental positive sequence impedance. ,in, , Adjust the proportional gain for the fundamental positive sequence.

[0090] The compensation module 342 can also be used based on the virtual angular frequency. Using the fundamental negative sequence impedance compensation value For the fundamental negative sequence impedance component Compensation is performed to obtain the compensated fundamental negative sequence impedance. ,in, , Adjust the proportional gain for the fundamental negative sequence.

[0091] The compensation module 342 can also be used based on the virtual angular frequency. Using the aforementioned harmonic impedance compensation value For the harmonic impedance components Compensation is performed to obtain the compensated harmonic impedance. ,in, , Adjust the proportional gain for harmonics.

[0092] In specific application scenarios, in order to determine the virtual angular frequency The determining module 341 can specifically be used to determine the positive sequence impedance component of the actual feeder of the distributed photovoltaic converter i. Negative sequence impedance components and h-th harmonic impedance components Determine the virtual fundamental positive sequence impedance of distributed photovoltaic converter i. Virtual fundamental negative sequence impedance and h-th virtual harmonic impedance Determine the virtual fundamental positive sequence impedance of distributed photovoltaic converter i. Virtual fundamental negative sequence impedance and integrated virtual harmonic impedance Based on the positive sequence impedance components The positive sequence impedance component The negative sequence impedance component The h-th harmonic impedance component The virtual fundamental positive sequence impedance The virtual fundamental negative sequence impedance The h-th virtual harmonic impedance The virtual fundamental positive sequence impedance The virtual fundamental negative sequence impedance The aforementioned integrated virtual harmonic impedance Determine the virtual angular frequency ,in, , , .

[0093] It should be noted that other corresponding descriptions of the functional modules involved in the distributed photovoltaic converter multi-sequence quantity collaborative control device provided in the embodiments of the present invention can be found in the corresponding description of the method shown in Figure 1, and will not be repeated here.

[0094] Based on the method shown in Figure 1, this embodiment of the invention also provides a computer-readable storage medium storing a computer program. When executed by a processor, the program performs the following steps: obtaining the grid structure parameters of the microgrid corresponding to the distributed photovoltaic converter; constructing a positive-sequence-negative-sequence-zero-sequence control model of the distributed photovoltaic converter based on the grid structure parameters; and collecting the output power of the distributed photovoltaic converter, wherein the output power includes output active power and output reactive power; determining the impedance constraint conditions of the distributed photovoltaic converter in the multi-sequence quantity coordinated control process; and determining the voltage reference value of the distributed photovoltaic converter to ensure the stable operation of the microgrid based on the impedance constraint conditions, the positive-sequence-negative-sequence-zero-sequence control model, and the output power. In this process, the microgrid includes positive-sequence loads, harmonic loads, and unbalanced loads. A preset droop controller is determined. Based on the voltage reference value and local communication information of adjacent converters, the control input parameters of the preset droop controller are determined and input to the preset droop controller for impedance compensation value prediction. This yields the multi-sequence impedance compensation values ​​of the distributed photovoltaic converter, which include fundamental positive-sequence impedance component compensation values, fundamental negative-sequence impedance component compensation values, and harmonic impedance component compensation values. Based on these multi-sequence impedance compensation values, impedance compensation is performed on the distributed photovoltaic converter to achieve a uniform distribution of the fundamental positive-sequence power component, harmonic power component, and unbalanced power load in the distributed photovoltaic converter within the microgrid.

[0095] Based on the embodiments of the method shown in Figure 1 and the device shown in Figure 8, this embodiment of the invention also provides a physical structure diagram of a computer device, as shown in Figure 10. The computer device includes: a processor 41, a memory 42, and a computer program stored in the memory 42 and executable on the processor. Both the memory 42 and the processor 41 are mounted on a bus 43. When the processor 41 executes the program, it performs the following steps: determining the impedance constraint conditions of the distributed photovoltaic converter in the multi-sequence coordinated control process; based on the impedance constraint conditions, the positive-sequence-negative-zero-sequence control model, and the output power, determining the voltage reference value of the distributed photovoltaic converter to ensure the stable operation of the microgrid; wherein the microgrid includes positive-sequence... The system identifies load, harmonic load, and unbalanced load. A preset droop controller is determined. Based on the voltage reference value and local communication information between adjacent converters, the control input parameters of the preset droop controller are determined and input to the preset droop controller for impedance compensation value prediction. This yields the multi-sequence impedance compensation value of the distributed photovoltaic converter, which includes fundamental positive-sequence impedance component compensation value, fundamental negative-sequence impedance component compensation value, and harmonic impedance component compensation value. Based on the multi-sequence impedance compensation value, impedance compensation is performed on the distributed photovoltaic converter to achieve a uniform distribution of fundamental positive-sequence power components, harmonic power components, and unbalanced power in the microgrid within the distributed photovoltaic converter.

[0096] Through the technical solution of this invention, by constructing a positive-sequence-negative-sequence-zero-sequence control model and comprehensively considering the grid structure parameters of the microgrid and the output power of the distributed photovoltaic converter, the voltage reference value can be determined more accurately. Based on this voltage reference value, the impedance compensation value obtained enables the distributed photovoltaic converter to achieve a uniform distribution of the fundamental positive-sequence power component, harmonic power component, and unbalanced power component among the converters under multi-sequence quantity collaborative control. For the positive-sequence load, harmonic load, and unbalanced load existing in the microgrid, precise impedance compensation effectively suppresses voltage distortion and imbalance at the point of common coupling (PCC). During the multi-sequence quantity collaborative control process, the harmonic power component and unbalanced power component are rationally allocated and processed, reducing the impact of harmonic current and negative-sequence current on the system. This significantly improves the power quality of the microgrid, ensuring system stability and power supply reliability, and providing users with higher-quality power. The determined impedance constraints and the voltage reference values ​​based on these constraints and other parameters provide an accurate basis for the control of the distributed photovoltaic converter. By predicting the impedance compensation value through a preset droop controller and implementing impedance compensation, the impedance characteristics of the converter can be dynamically adjusted, enabling the system to maintain stable operation even under various complex loads and operating conditions. The distributed control strategy of this invention only requires local communication between adjacent converters and does not rely on global parameter information, which makes the control method highly flexible and adaptable, and can be easily applied to microgrids of different sizes and structures.

[0097] It is obvious to those skilled in the art that the modules or steps of the present invention described above can be implemented using general-purpose computing devices. They can be centralized on a single computing device or distributed across a network of multiple computing devices. Optionally, they can be implemented using computer-executable program code, thereby storing them in a storage device for execution by a computing device. In some cases, the steps shown or described can be performed in a different order than those presented herein, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. Thus, the present invention is not limited to any particular combination of hardware and software.

[0098] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A multi-sequence quantity cooperative control method for a distributed photovoltaic converter, characterized in that, include: Obtain the grid structure parameters of the microgrid corresponding to the distributed photovoltaic (PV) converter. Based on these parameters, construct a positive-sequence-negative-sequence-zero-sequence control model for the PV converter. Collect the output power of the PV converter, including active and reactive power. Determine the impedance constraints of the PV converter during multi-sequence coordinated control. Based on these constraints, the positive-sequence-negative-sequence-zero-sequence control model, and the output power, determine the voltage reference value for the PV converter to ensure stable operation of the microgrid. The microgrid includes positive-sequence loads, harmonic loads, and unbalanced loads. Determine the preset droop control... The controller, based on the voltage reference value and local communication information of adjacent converters, determines the control input parameters of the preset droop controller, and inputs the control input parameters to the preset droop controller for impedance compensation value prediction, thereby obtaining the multi-sequence impedance compensation value of the distributed photovoltaic converter. The multi-sequence impedance compensation value includes the fundamental positive-sequence impedance component compensation value, the fundamental negative-sequence impedance component compensation value, and the harmonic impedance component compensation value. Based on the multi-sequence impedance compensation value, impedance compensation is performed on the distributed photovoltaic converter to achieve uniform distribution of the fundamental positive-sequence power component, harmonic power component, and unbalanced power flow in the microgrid within the distributed photovoltaic converter.

2. The method according to claim 1, characterized in that, The impedance constraints include the equivalent fundamental positive-sequence impedance constraint, the equivalent harmonic impedance constraint, and the equivalent fundamental negative-sequence impedance constraint corresponding to the distributed photovoltaic converter; the equivalent fundamental positive-sequence impedance constraint is: ,in, ，…， These are the reactance components of the fundamental positive sequence impedance of the corresponding photovoltaic converter. ,…, These are the rated reactive power capacities of the corresponding photovoltaic converters; the equivalent harmonic impedance constraint condition is: ,in, ,…, These are the reactance components of the equivalent harmonic impedance of the corresponding photovoltaic converter. ,…, These are the rated harmonic powers of the corresponding photovoltaic converters; the equivalent fundamental negative sequence impedance constraint condition is: ,in, ,…, These are the reactance components of the equivalent fundamental negative sequence impedance of the feed line of the corresponding photovoltaic converter. ,…, These represent the rated unbalanced power of the corresponding photovoltaic converter.

3. The method according to claim 1, characterized in that, The determination of the voltage reference value of the distributed photovoltaic converter to ensure the stable operation of the microgrid based on the impedance constraint condition, the positive-sequence-negative-zero-sequence control model, and the output power includes: determining the reference voltage amplitude of the distributed photovoltaic converter under the positive-sequence voltage based on the impedance constraint condition, the positive-sequence-negative-zero-sequence control model, and the output power. Reference voltage amplitude under harmonic voltage Reference voltage amplitude under unbalanced voltage Determine the fundamental positive sequence voltage drop of the virtual impedance on the distributed photovoltaic converter, respectively. Fundamental negative sequence voltage drop value Harmonic voltage drop value ;Based on the reference voltage amplitude under the positive sequence voltage The reference voltage amplitude under the harmonic voltage The reference voltage amplitude under the unbalanced voltage The fundamental positive sequence voltage drop value The fundamental negative sequence voltage drop value The harmonic voltage drop value Determine the voltage reference value of the distributed photovoltaic converter to ensure the stable operation of the microgrid. ,in, 。 4. The method according to claim 3, characterized in that, Based on the impedance constraint, the positive-sequence-negative-sequence-zero-sequence control model, and the output power, the reference voltage amplitude of the distributed photovoltaic converter under the positive-sequence voltage is determined. This includes: determining the positive-sequence generalized droop coefficient n and the harmonic generalized droop coefficient of the preset droop controller based on the impedance constraint conditions and the positive-sequence-negative-zero-sequence control model. Unbalanced generalized droop coefficient Based on the positive-sequence generalized droop coefficient n, the active power Q in the output power, and the rated power of the distributed photovoltaic converter Determine the reference voltage amplitude under the positive sequence voltage of the distributed photovoltaic converter. ,in, Determine the reference voltage amplitude under harmonic voltage. This includes: harmonic reactive power based on the output power. The harmonic generalized droop coefficient Determine the reference voltage amplitude of the distributed photovoltaic converter under harmonic voltage. ,in, Determine the reference voltage amplitude under unbalanced voltage. This includes: unbalanced reactive power based on the output power. The unbalanced generalized droop coefficient Determine the reference voltage amplitude of the distributed photovoltaic converter under unbalanced voltage. ,in, 。 5. The method according to claim 1, characterized in that, The step of determining the control input parameters of the preset droop controller based on the voltage reference value and the local communication information of adjacent converters includes: taking any converter in the distributed photovoltaic converter as a target converter i, and determining the reactive power of the target converter i based on the voltage reference value of the target converter i. Based on the voltage reference value of the adjacent converter j adjacent to the target converter i, the reactive power of the adjacent converter j is determined. Determine the unbalanced power of the target converter i. And determine the unbalanced power of the adjacent converter j. Determine the harmonic power of the target converter i. And determine the harmonic power of the adjacent converter j. Based on the aforementioned reactive power The reactive power Determine the reactive power control input parameters ,in, ， This is the first coupling gain. For distributed photovoltaic converters, graph theory is used to form the Laplace matrix elements. Let i be the generalized droop coefficient of the target converter i under reactive power. The generalized droop coefficient of the adjacent converter j under reactive power, where N is the total number of converters; based on the unbalanced power The unbalanced power Determine the input parameters for unbalanced power control. ,in, ， This is the first coupling gain. The generalized droop coefficient of the target converter i under unbalanced power is given. The generalized droop coefficient of the adjacent converter j under unbalanced power; based on the harmonic power The harmonic power Determine the input parameters for harmonic power control. ,in, ， This is the first coupling gain. The generalized droop coefficient of the target converter i under harmonic power is given. is the generalized droop coefficient of the adjacent converter j under harmonic power.

6. The method according to claim 1, characterized in that, The multi-sequence impedance compensation value includes the fundamental positive sequence impedance compensation value. Fundamental negative sequence impedance compensation value Harmonic impedance compensation value The impedance compensation of the distributed photovoltaic converter based on the multi-sequence impedance compensation value includes: determining the fundamental positive-sequence impedance component of the distributed photovoltaic converter i. Fundamental negative sequence impedance component Harmonic impedance components Determine the virtual angular frequency Based on the virtual angular frequency Using the fundamental positive sequence impedance compensation value For the fundamental positive sequence impedance component Compensation is performed to obtain the compensated fundamental positive sequence impedance. ,in, ， Adjust the proportional gain for the fundamental positive sequence; based on the virtual angular frequency. Using the fundamental negative sequence impedance compensation value For the fundamental negative sequence impedance component Compensation is performed to obtain the compensated fundamental negative sequence impedance. ,in, ， Adjust the proportional gain for the fundamental negative sequence; based on the virtual angular frequency. Using the aforementioned harmonic impedance compensation value For the harmonic impedance components Compensation is performed to obtain the compensated harmonic impedance. ,in, ， Adjust the proportional gain for harmonics.

7. The method according to claim 6, characterized in that, The determination of virtual angular frequency This includes: determining the positive-sequence impedance component of the actual feed line of the distributed photovoltaic converter i. Negative sequence impedance components and h-th harmonic impedance components Determine the virtual fundamental positive sequence impedance of distributed photovoltaic converter i. Virtual fundamental negative sequence impedance and h-th virtual harmonic impedance Determine the virtual fundamental positive sequence impedance of distributed photovoltaic converter i. Virtual fundamental negative sequence impedance and integrated virtual harmonic impedance Based on the positive sequence impedance components The positive sequence impedance component The negative sequence impedance component The h-th harmonic impedance component The virtual fundamental positive sequence impedance The virtual fundamental negative sequence impedance The h-th virtual harmonic impedance The virtual fundamental positive sequence impedance The virtual fundamental negative sequence impedance The aforementioned integrated virtual harmonic impedance Determine the virtual angular frequency ,in, 、 、 。 8. A multi-sequence quantity coordinated control device for a distributed photovoltaic converter, characterized in that, include: A construction unit is used to acquire the grid structure parameters of the microgrid corresponding to the distributed photovoltaic converter, and based on the grid structure parameters, construct a positive-sequence-negative-sequence-zero-sequence control model for the distributed photovoltaic converter; and collect the output power of the distributed photovoltaic converter, wherein the output power includes output active power and output reactive power; a determination unit is used to determine the impedance constraints of the distributed photovoltaic converter in the multi-sequence quantity coordinated control process, and based on the impedance constraints, the positive-sequence-negative-sequence-zero-sequence control model, and the output power, determine the voltage reference value of the distributed photovoltaic converter to ensure the stable operation of the microgrid, wherein the microgrid includes positive-sequence loads, harmonic loads, and unbalanced loads; and a pre- A measurement unit is used to determine a preset droop controller, determine the control input parameters of the preset droop controller based on the voltage reference value, and input the control input parameters to the preset droop controller for impedance compensation value prediction to obtain the multi-sequence impedance compensation value of the distributed photovoltaic converter. The multi-sequence impedance compensation value includes the fundamental positive sequence impedance component compensation value, the fundamental negative sequence impedance component compensation value, and the harmonic impedance component compensation value. A compensation unit is used to perform impedance compensation on the distributed photovoltaic converter based on the multi-sequence impedance compensation value to achieve uniform distribution of the fundamental positive sequence power component, harmonic power component, and unbalanced power flow in the microgrid within the distributed photovoltaic converter.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 7.

10. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 7.

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