Micro-grid-oriented photovoltaic inverter multi-machine parallel synchronous control method and micro-grid-oriented photovoltaic inverter multi-machine parallel synchronous control system

Abstract

The invention provides a micro-grid-oriented photovoltaic inverter multi-machine parallel synchronous control method and system, and relates to the technical field of photovoltaic inverters, and the method comprises the steps: building a virtual generator model of a photovoltaic inverter in a micro-grid, and generating a virtual control scheme through the virtual generator model; performing dynamic monitoring on a photovoltaic array in the micro-grid to obtain photovoltaic output information, and performing control analysis on the photovoltaic output information according to a tracking control mechanism to obtain a dynamic control scheme; and performing multi-machine parallel synchronous control execution on the photovoltaic inverter in cooperation with the virtual control scheme and the dynamic control scheme. The technical problems that in the prior art, photovoltaic inverter multi-machine control generally depends on a fixed synchronization algorithm, quick response cannot be achieved under complex loads and environment changes, output imbalance between photovoltaic inverters is caused, and then the power quality and reliability of a micro-grid are affected are solved.

Description

Technical Field

[0001] This invention relates to the field of photovoltaic inverter technology, and more specifically to a method and system for multi-unit parallel synchronous control of photovoltaic inverters for microgrids. Background Technology

[0002] As a key component in microgrids, photovoltaic (PV) inverters are responsible for converting the direct current (DC) power from photovoltaic arrays into alternating current (AC) power for grid connection. In multi-inverter parallel operation, multiple PV inverters work together on the grid, requiring coordinated and synchronized operation. To ensure system stability and power quality, precise synchronization between PV inverters is essential, along with the ability to effectively handle fluctuations in PV power generation and external disturbances. However, in traditional multi-inverter parallel synchronization control, PV inverters typically rely on fixed synchronization algorithms. These algorithms may fail to respond quickly under complex loads and varying light levels, leading to misalignment between inverter outputs. This misalignment can cause grid frequency instability, excessive voltage fluctuations, and even grid outages, severely impacting the power quality and reliability of the microgrid. Summary of the Invention

[0003] This application provides a method and system for parallel synchronous control of multiple photovoltaic inverters in microgrids, aiming to solve the technical problem that existing technologies for controlling multiple photovoltaic inverters usually rely on fixed synchronization algorithms, which cannot respond quickly under complex loads and environmental changes, resulting in misalignment between photovoltaic inverter outputs, and thus affecting the power quality and reliability of microgrids.

[0004] The first aspect disclosed in this application provides a method for multi-unit parallel synchronous control of photovoltaic inverters for microgrids. The method includes: establishing a virtual generator model of the photovoltaic inverters in the microgrid, and generating a virtual control scheme through the virtual generator model; dynamically monitoring the photovoltaic array in the microgrid to obtain photovoltaic output information, and performing control analysis on the photovoltaic output information according to a tracking control mechanism to obtain a dynamic control scheme; and coordinating the virtual control scheme and the dynamic control scheme to perform multi-unit parallel synchronous control execution of the photovoltaic inverters.

[0005] The second aspect of this application discloses a multi-unit parallel synchronous control system for photovoltaic inverters in microgrids. The system is used in the aforementioned multi-unit parallel synchronous control method for photovoltaic inverters in microgrids. The system includes: a virtual control scheme generation module for establishing a virtual generator model of the photovoltaic inverters in the microgrid and generating a virtual control scheme through the virtual generator model; a dynamic control scheme generation module for dynamically monitoring the photovoltaic array in the microgrid to obtain photovoltaic output information and performing control analysis on the photovoltaic output information according to a tracking control mechanism to obtain a dynamic control scheme; and a multi-unit parallel synchronous control module for coordinating the virtual control scheme and the dynamic control scheme to perform multi-unit parallel synchronous control execution on the photovoltaic inverters.

[0006] One or more technical solutions provided in this application have at least the following beneficial effects: By establishing a virtual generator model, the photovoltaic inverter not only acts as a power converter but also provides inertial support and damping through a virtual control scheme. This helps improve the frequency and voltage stability of the microgrid under load fluctuations and external interference, thereby enhancing system reliability. Dynamic monitoring of the photovoltaic array allows for real-time acquisition of its output information, reflecting its power generation status. This data helps the tracking control mechanism perform precise power optimization. By analyzing the photovoltaic output information, the tracking control mechanism dynamically adjusts the inverter's operation to ensure the photovoltaic array always operates at its maximum power point, thus improving the overall power generation efficiency of the system. Coordinating the virtual control scheme with the dynamic control scheme for multi-unit parallel synchronous control effectively coordinates the operation of multiple photovoltaic inverters, keeping them synchronized and avoiding inconsistencies in inverter output or grid frequency instability. This not only improves the grid connection efficiency of the photovoltaic array but also ensures the power quality and system stability of the microgrid.

[0007] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, the following are specific embodiments of this application. Attached Figure Description

[0008] Figure 1 This is a schematic flowchart of a method for controlling the parallel synchronization of multiple photovoltaic inverters in a microgrid, provided in an embodiment of this application.

[0009] Figure 2 This is a schematic diagram of a multi-unit parallel synchronous control system for photovoltaic inverters in a microgrid, provided in an embodiment of this application.

[0010] Explanation of reference numerals in the attached diagram: Virtual control scheme generation module 10, dynamic control scheme generation module 20, multi-machine parallel synchronous control module 30. Detailed Implementation

[0011] This application provides a method and system for parallel synchronous control of multiple photovoltaic inverters in microgrids. It solves the technical problem that the existing technology for controlling multiple photovoltaic inverters usually relies on fixed synchronization algorithms, which cannot respond quickly under complex load and environmental changes, resulting in misalignment between the outputs of photovoltaic inverters, and thus affecting the power quality and reliability of the microgrid.

[0012] After introducing the basic principles of this application, various non-limiting embodiments of this application will be described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are merely illustrative of this application and are not intended to limit this application.

[0013] Example 1, as Figure 1 As shown in the embodiments of this application, a method for multi-unit parallel synchronous control of photovoltaic inverters for microgrids is provided, the method comprising: A virtual generator model of a photovoltaic inverter in a microgrid is established, and a virtual control scheme is generated through the virtual generator model.

[0014] The virtual generator model simulates the behavior of a photovoltaic (PV) inverter in a microgrid through mathematical modeling. Essentially, it treats the PV inverter as a virtual generator whose output characteristics can be controlled and optimized. While PV inverters typically convert solar energy into alternating current (AC) and connect to the microgrid via grid connection, in the virtual generator model, the PV inverter is not only seen as an energy conversion device but also plays a crucial role in providing stable power within the microgrid. Virtual control is achieved through this virtual generator model. The model predicts the microgrid's state, load, and generation capacity. Mathematical analysis determines the optimal control strategy, generating a virtual control scheme. This scheme includes how to adjust the PV inverter's output voltage and power to ensure microgrid stability, meet load demands, and satisfy grid connection requirements.

[0015] The photovoltaic array in the microgrid is dynamically monitored to obtain photovoltaic output information, and the photovoltaic output information is controlled and analyzed according to the tracking control mechanism to obtain a dynamic control scheme.

[0016] In microgrids, the output of photovoltaic (PV) arrays is directly affected by factors such as sunlight intensity, weather changes, and temperature. Therefore, real-time dynamic monitoring of the PV array output is necessary to obtain information on PV output parameters such as voltage, current, and power. This output information is used to assess the current operating status of the PV array and provide input data for subsequent control strategies. A tracking control mechanism is used to adjust the inverter's control strategy based on the current PV output information, optimizing PV power generation efficiency. Specifically, the tracking control mechanism dynamically adjusts the inverter's operating point to ensure maximum PV array output power under changing environmental conditions. By comparing the current output power with a preset maximum power value, optimization algorithms are used to adjust the inverter's operating state to guarantee power generation efficiency. Through control analysis, a dynamic control scheme is obtained, which includes strategies for adjusting voltage, current, and power to cope with the impact of load and environmental changes.

[0017] The virtual control scheme and the dynamic control scheme work together to perform multi-machine parallel synchronous control of the photovoltaic inverter.

[0018] In microgrids, photovoltaic (PV) inverters operate in parallel, requiring coordination of their outputs for grid-connected synchronous control. A virtual control scheme simulates a virtual generator model for overall system stability control, while a dynamic control scheme dynamically adjusts the inverters' operations based on the PV array's output to ensure efficient operation under varying conditions. This collaborative approach guarantees coordination among multiple PV inverters under different loads and power generation conditions, ensuring both efficient power generation and stable power supply in the microgrid. Multi-inverter parallel synchronous control refers to maintaining synchronized operation and output when multiple PV inverters operate in parallel. This is crucial for stable microgrid operation, as frequency and voltage deviations in any single inverter can affect the overall stability. By coordinating these two control schemes, the operating status of each PV inverter can be monitored in real-time, and their outputs can be adjusted to achieve parallel operation synchronization. Specifically, when output fluctuations are detected in a particular PV inverter, the virtual and dynamic control schemes can compensate for the inverter's shortcomings by adjusting the parameters of other PV inverters, ensuring the stability of voltage, frequency, and other parameters of the entire microgrid.

[0019] Furthermore, the virtual generator model is virtually controlled through a virtual control strategy. This virtual control strategy adjusts the system frequency through a power frequency controller, regulates the output voltage through an excitation controller, and provides system inertia support through virtual rotational inertia and damping coefficient.

[0020] The virtual control strategy is a control algorithm designed based on a virtual generator model. It guides how to regulate the microgrid through the photovoltaic inverter. This virtual control strategy adjusts in real time according to the microgrid's operating status to ensure system stability and efficiently handle load fluctuations and changes in photovoltaic array power generation. In a microgrid, system frequency is a critical indicator; fluctuations in system frequency can lead to power system instability. To ensure stable operation, the power frequency controller achieves frequency stabilization by adjusting the output frequency of the photovoltaic inverter. The power frequency controller works by calculating the deviation between the current microgrid frequency and the set frequency, and reducing this deviation by adjusting the inverter's power output. In this way, the microgrid frequency is kept within an acceptable range. The excitation controller adjusts the output voltage of the photovoltaic inverter to ensure voltage stability in the microgrid, preventing equipment damage or power outages caused by excessively high or low voltage. Especially when photovoltaic power generation fluctuates significantly, the excitation controller can adjust the voltage output in real time to adapt to load changes.

[0021] In traditional power systems, the rotational inertia of generators provides a certain amount of inertial support to absorb frequency fluctuations. However, in microgrids, especially in photovoltaic-dominated systems, traditional rotating mechanical inertia is lacking. Therefore, virtual generator models supplement this deficiency by introducing virtual rotational inertia and damping coefficients. Virtual rotational inertia, by simulating mechanical inertia, slows down rapid frequency changes in the microgrid; the damping coefficient, by reducing frequency oscillations, allows the system to recover to a stable state more quickly. Adjusting these two parameters helps the microgrid maintain a relatively stable frequency response when experiencing sudden load changes or fluctuations in photovoltaic power generation, improving system stability and anti-interference capabilities.

[0022] Furthermore, the photovoltaic array in the microgrid is dynamically monitored to obtain photovoltaic output information, and the photovoltaic output information is controlled and analyzed according to a tracking control mechanism to obtain a dynamic control scheme, including: Extract the first output information corresponding to the first operating point from the photovoltaic output information, wherein the first output information includes first voltage data and first current data; calculate the first output power value based on the first voltage data and the first current data; sort the first operating points in descending order according to the first output power value to obtain the operating point sequence; analyze the operating point sequence according to the tracking control mechanism to obtain the dynamic control scheme.

[0023] A photovoltaic (PV) array consists of multiple solar panels distributed at different locations. The light intensity, temperature, and other environmental factors vary at each location, resulting in differences in the voltage and current output of the PV units at each location. The first operating point can be understood as a specific location within the PV array; the light, temperature, and other conditions at that location may affect the voltage and current output. Using the first operating point as a retrieval criterion, corresponding first output information is extracted from the PV output information. The first voltage and first current data come from sensors or the measurement system of the PV inverter, and these data represent the output characteristics of the PV unit at that location at a specific moment.

[0024] The first output power value is determined by the first voltage data and the first current data. The calculation formula is the first voltage data multiplied by the first current data. The first output power value represents the actual power generation of the photovoltaic array at that moment, providing necessary parameters for subsequent control analysis.

[0025] Based on the first output power value, all operating points (including the first operating point) are sorted in descending order to obtain the operating point sequence. The sorting is based on the output power value corresponding to each operating point. The sorted operating point sequence reflects the power generation efficiency of the photovoltaic array at different operating points, which helps the control system select the best operating point for operation.

[0026] Based on the operating point sequence of the photovoltaic array, the operation of the inverter is adjusted in real time to ensure that the system always operates at the optimal power point. The tracking control mechanism analyzes the output power value of each operating point in the operating point sequence and matches the output power value of any operating point with the corresponding predetermined search step size. This ensures that the adjustment of the operating point is neither too excessive nor too slow. Based on the predetermined search step size obtained by matching, the control system adjusts the output of the inverter to form a dynamic control scheme to optimize the power generation efficiency of the photovoltaic array.

[0027] Furthermore, the dynamic control scheme is obtained by analyzing the operating point sequence based on the tracking control mechanism, including: Extract any operating point from the operating point sequence; according to the tracking control mechanism, match any predetermined search step size for any output power value corresponding to any operating point; control the any operating point according to the predetermined search step size, and form the dynamic control scheme; wherein, the tracking control mechanism refers to a control mechanism inversely proportional to the output power value.

[0028] Extracting an arbitrary working point means randomly selecting any working point from the working point sequence for further analysis and optimization. In practice, the arbitrary working point is usually determined based on a random algorithm, which iterates through each working point in the working point sequence by random selection.

[0029] The search step size refers to the adjustment range of the control system to the operating point during the search process. The search step size determines the adjustment force and speed when selecting the optimal power point. In maximum power point tracking control, the search step size controls the rate at which the output power is adjusted. A larger step size may lead to overshoot or instability, while a smaller step size can ensure finer adjustment, but may require more time.

[0030] For any extracted operating point, a corresponding predetermined search step size is matched based on any output power value of that operating point. The search step size is usually dynamically calculated to adapt to different operating points. The tracking control mechanism refers to adjusting the search step size based on the inverse relationship between the search step size and the output power value; that is, the higher the output power, the smaller the search step size; and the lower the output power, the larger the search step size. This method ensures that the system can make fine adjustments at high power output and larger adjustments at low power, quickly finding the optimal power point.

[0031] The output of any operating point is adjusted according to a predetermined search step size. The control objective is to adjust any operating point as close to the maximum power point as possible. This control process involves real-time adjustment of the voltage and current output of the photovoltaic inverter to push the photovoltaic array's operating point towards a higher power output region. As the operating point is adjusted, a dynamic control scheme is formed, instructing how to continue adjusting the photovoltaic inverter's output based on the photovoltaic array's current operating state to ensure the system maintains optimal power generation efficiency under different load and environmental conditions.

[0032] Furthermore, after controlling the arbitrary operating point according to the arbitrary predetermined search step size and forming the dynamic control scheme, the method further includes: The first operating point is continuously monitored to obtain a second output power value; a first power value timing sequence is generated based on the correspondence between the first time zone and the first output power value, and the second time zone and the second output power value; the first power value timing sequence is analyzed according to the adaptive control plan in the tracking control mechanism to obtain a target rate of change; it is determined whether the target rate of change reaches a predetermined threshold to obtain a target judgment result; the dynamic control scheme is adaptively adjusted according to the target judgment result; wherein, the process includes: if the target rate of change reaches the predetermined threshold, the first predetermined search step size corresponding to the first operating point is adaptively increased to obtain a first adaptive search step size; if the target rate of change does not reach the predetermined threshold, the first predetermined search step size corresponding to the first operating point is adaptively decreased to obtain a second adaptive search step size; the dynamic control scheme is adaptively adjusted according to the first adaptive search step size or the second adaptive search step size.

[0033] During the operation of the photovoltaic array, the output power changes dynamically. The first operating point of the photovoltaic array is continuously monitored to capture changes in the first operating point, and the second output power value is recorded in real time.

[0034] The first time zone is associated with the corresponding first output power value, and the second time zone is associated with the corresponding second output power value to form a one-to-one correspondence. The first power value time sequence is generated by arranging the time sequence, which describes the output power characteristics of the photovoltaic system as it changes over time.

[0035] The adaptive control scheme is a control strategy designed based on changes in system operating status and power output. It dynamically adjusts the operation of the photovoltaic inverter according to the changing trend of the first power value time series to optimize power generation efficiency and ensure system stability. For example, if the power output changes rapidly, the inverter's operating point needs to be adjusted to stabilize the power output. Based on the generated first power value time series, a target rate of change is calculated. The target rate of change describes the rate of change of power output within a given time period, reflecting the system's responsiveness to adjustments in power generation capacity. A higher target rate of change indicates that the system is experiencing significant load fluctuations or changes in the external environment. By analyzing the target rate of change, it can be determined whether further adjustments to the control strategy are needed.

[0036] The predetermined threshold is a value set according to system operating requirements and environmental factors. It represents the maximum allowable power variation range of the system. The target rate of change is compared with the predetermined threshold. If the target rate of change reaches the predetermined threshold, it indicates that the power output of the system is fluctuating excessively and the strategy needs to be further adjusted. If the target rate of change does not reach the predetermined threshold, it means that the current power variation of the system is within an acceptable range and the existing control strategy can be maintained without making significant adjustments.

[0037] If the target rate of change reaches a predetermined threshold, it means that the power output of the photovoltaic array has fluctuated excessively. This is usually caused by drastic load changes, environmental fluctuations, or internal system instability. To cope with this fluctuation, the first operating point is adjusted more quickly by adjusting the first predetermined search step size corresponding to the first operating point, and the system is restored to a stable optimal power generation state as soon as possible. Specifically, since the target rate of change is large, the adjustment process needs to be accelerated. Therefore, the search step size is increased to speed up the adjustment of the operating point. In this case, the first predetermined search step size is adaptively increased, that is, the magnitude of the first predetermined search step size is increased through an appropriate algorithm or strategy, so that the control system can find the operating point closer to the maximum power more quickly. The final first adaptive search step size is obtained and used for subsequent inverter output control, so that the system can respond more quickly to power output fluctuations and reduce the impact of fluctuations on system stability.

[0038] If the target rate of change does not reach the predetermined threshold, it indicates that the power output change of the system is within an acceptable range, possibly just a slight fluctuation or temporary load change. In this case, there is no need to quickly adjust the system. When the power change is relatively stable, a smaller search step size is used to avoid over-adjustment. Specifically, the first predetermined search step size is adaptively reduced according to the current system state, i.e., the adjustment amplitude is reduced. This method allows the system to make fine adjustments in a stable state to maintain the optimal operating point and avoid over-adjustment of the system output. Through an adaptive algorithm, a second adaptive search step size is obtained. This step size is smaller than the increased search step size and is suitable for situations where the system is relatively stable and the power fluctuation is small, thereby reducing unnecessary adjustments.

[0039] Based on the obtained first or second adaptive search step size, the voltage, current, and power output parameters of the photovoltaic inverter are adjusted to ensure that the system continues to adjust towards the direction of maximum power output. This update enables the control system to cope with different photovoltaic array output conditions, allowing for rapid adjustment when the load changes drastically and fine adjustment when the system is stable.

[0040] Furthermore, based on the adaptive control plan in the tracking control mechanism, the time series of the first power value is analyzed to obtain the target rate of change, including: The time series of the first power value is subjected to regression fitting to obtain a first fitting formula; a first fitting curve is obtained based on the first fitting formula, and the target slope of the first fitting curve is obtained by combining the target time zone; the target slope is standardized to obtain the target rate of change.

[0041] Regression fitting is a statistical method that aims to describe the relationship between variables by fitting a curve to data. In this step, regression fitting is performed on the first power value time series (i.e., the data on the power change of the photovoltaic array over time) to analyze the trend of power change. During the regression fitting process, the first power value time series is processed by a regression fitting algorithm. Common regression methods include the least squares method, etc. The goal is to find the best fitting curve and minimize the fitting error. The first fitting formula is the mathematical expression obtained by regression fitting, which describes the relationship between the power value time series and time.

[0042] Based on the first fitting equation obtained from regression fitting, a first fitting curve is plotted. This first fitting curve is a smooth representation of the power value changing over time, describing the power change trend of the photovoltaic array within a certain time interval and reflecting the system's power generation characteristics. The target time zone is a pre-set time period that we want to focus on. Combining the target time zone with the first fitting curve allows us to determine the specific characteristics of power changes within that target time zone, further providing a basis for control adjustments. The target slope refers to the rate of change of the fitting curve within the target time zone, i.e., the speed at which power changes over time. By calculating the target slope of the first fitting curve within the target time zone, we can quantify the speed of power change in the photovoltaic array. The magnitude of the target slope reflects the speed of system change; a larger target slope means faster power change, while a smaller target slope indicates a more stable power change.

[0043] The purpose of standardization is to transform the target slope into a dimensionless value so that it can be compared and analyzed under different system conditions. Standardization is usually achieved by dividing by the standard deviation or by using minimum-maximum normalization. Through standardization, the target slope is transformed into a standardized value called the target rate of change, which represents the relative speed of change of the photovoltaic array power.

[0044] Furthermore, the coordinated execution of multi-machine parallel synchronous control of the photovoltaic inverter by the virtual control scheme and the dynamic control scheme also includes: The microgrid is monitored and controlled by multiple parallel synchronous controllers to obtain dynamic monitoring records. When the voltage distortion rate obtained from analyzing the dynamic monitoring records reaches a predetermined distortion rate threshold, the microgrid is in a weak grid state. The virtual control scheme is dynamically adjusted according to the intensity level of the weak grid state.

[0045] A microgrid consists of multiple photovoltaic (PV) inverters connected in parallel to supply power to the grid. In this configuration, the outputs of these inverters must remain synchronized to ensure power stability and efficient transmission. Multi-inverter parallel synchronization control and monitoring refers to real-time monitoring of the operating status of all PV inverters to ensure they operate as expected within a synchronized control framework, avoiding output inconsistencies or phase shifts between inverters. During monitoring, key operating data of all PV inverters are recorded, resulting in dynamic monitoring records, including output voltage, frequency, and current. These data reflect whether each PV inverter is operating normally and whether there are synchronization problems or fluctuations.

[0046] Voltage distortion rate refers to the degree of distortion of the voltage waveform in a microgrid. It is measured by comparing it with an ideal sinusoidal voltage. Voltage waveform distortion is caused by various factors, including load fluctuations, system instability, and equipment failures. A high voltage distortion rate means that the voltage waveform in the grid is severely distorted, which may affect the normal operation of equipment and power quality. By analyzing the voltage data collected from dynamic monitoring records and calculating the voltage distortion rate, when the voltage distortion rate exceeds a predetermined distortion rate threshold, it means that the voltage quality of the grid is poor and the system is in an unstable state. At this point, the microgrid is determined to have entered a weak grid state. A weak grid state means that the power system has poor stability and may have large voltage or frequency fluctuations, posing a threat to the reliability of the system and power supply.

[0047] The severity level of a weak power grid is measured based on the voltage distortion rate. This severity level can be divided into several different grades, such as: slightly weak grid (voltage distortion rate is slightly high, but not to the level of severe instability); moderately weak grid (voltage distortion rate is relatively high, which may affect system stability); and severely weak grid (voltage distortion rate is excessively high, and the system may face significant stability problems, even power outages). These severity levels reflect the degree of weakness in the power grid and influence the regulation methods of the control system.

[0048] Based on the intensity level of the weak grid condition, the virtual control scheme is adjusted accordingly. The virtual control scheme is a control strategy that simulates a generator model in the microgrid. It provides control commands to the photovoltaic inverter in terms of frequency, power, etc. The adjustment scheme includes: increasing the virtual moment of inertia to provide more inertial support and mitigate grid frequency fluctuations; reducing system frequency oscillations and quickly restoring to a stable state by enhancing the damping coefficient; and adjusting the power output of the photovoltaic inverter according to the weak grid condition to better adapt to voltage and frequency fluctuations in the grid. The purpose of dynamic adjustment is to enhance the system's anti-interference capability and improve grid stability under weak grid conditions, avoiding system paralysis or shutdown due to excessive voltage and frequency fluctuations.

[0049] Furthermore, before dynamically adjusting the virtual control scheme according to the intensity level of the weak power grid state, the method further includes: The voltage harmonic components of the microgrid are obtained based on the dynamic monitoring records, and a reverse harmonic current command is generated; the multi-resonant controller is activated based on the reverse harmonic current command to suppress harmonics at a predetermined frequency.

[0050] During the operation of a microgrid, voltage waveform distortion and harmonics are generated due to the influence of nonlinear loads and system components. These harmonics typically manifest as higher-order harmonics, affecting the voltage quality of the power grid. Dynamic monitoring records contain microgrid voltage data. Using signal processing methods such as Fourier transform, voltage harmonic components are extracted from the voltage waveform. These harmonic components reflect the magnitude and frequency characteristics of each frequency component in the voltage waveform. To suppress voltage harmonics, a reverse harmonic current command is generated. This command is a current signal with the opposite phase and frequency to the voltage harmonics. It interferes with the harmonic current, thus eliminating harmonics. The purpose of this command is to instruct the photovoltaic inverter to generate a corresponding current based on the voltage harmonic components of the power grid, thereby reducing the harmonic content in the grid and improving power quality.

[0051] A multiresonant controller is a control device used to eliminate various harmonics in a power grid. It generates corresponding suppression signals based on the harmonic components of different frequencies. By adjusting these signals, the multiresonant controller can effectively reduce harmonics and ensure the purity of the voltage waveform. The multiresonant controller is activated by a generated reverse harmonic current command. The controller then produces a corresponding current output to eliminate harmonics of various frequencies in the power grid. A predetermined frequency is used to determine when harmonic suppression should be performed and to adjust the suppression frequency. In this way, the impact of harmonics can be effectively reduced within a specific frequency range, ensuring the power quality of the microgrid.

[0052] Furthermore, after dynamically adjusting the virtual control scheme according to the intensity level of the weak power grid state, the method further includes: Read the predetermined monitoring indicators and combine them with the dynamic monitoring records to obtain the indicator parameter set; when the indicator parameter set does not meet the predetermined condition constraints, issue an abnormal command and switch to the island operation mode based on the abnormal command.

[0053] The predetermined monitoring indicators include key signals such as voltage, frequency, power, and load. These indicators comprehensively reflect the operating status and power quality of the microgrid. If these indicators fail to meet specific requirements, it may affect the operational safety of equipment and the power grid. Based on data obtained from dynamic monitoring records, each predetermined monitoring indicator is analyzed to generate an indicator parameter set. This parameter set is a collection of all predetermined monitoring indicators, including their change values ​​and fluctuation ranges over a certain period of time.

[0054] Each predefined monitoring indicator has a predetermined constraint, meaning that during system operation, parameters such as voltage and frequency must fall within a certain range. For example, excessive voltage fluctuations or frequency deviations from normal values ​​are considered abnormal states. If certain monitoring indicators in the parameter set fail to meet the predetermined constraints, such as excessive voltage deviations or frequency fluctuations, it indicates that the microgrid has entered an unstable or faulty state. In this case, an abnormal command is issued to inform the system that its current operating state does not meet normal requirements. Based on the abnormal command, islanded operation mode is activated. Islanded operation mode means that the microgrid is disconnected from the main grid and operates independently. The purpose of switching to islanded operation mode is to avoid continuing to supply power to the grid when the grid is unstable, reducing the negative impact on the main grid. At the same time, in islanded operation mode, the microgrid will autonomously adjust to protect internal equipment from further damage.

[0055] In summary, the multi-unit parallel synchronous control method for photovoltaic inverters in microgrids provided in this application has the following technical effects: By establishing a virtual generator model, the photovoltaic inverter not only acts as a power converter but also provides inertial support and damping through a virtual control scheme. This helps improve the frequency and voltage stability of the microgrid under load fluctuations and external interference, thereby enhancing system reliability. Dynamic monitoring of the photovoltaic array allows for real-time acquisition of its output information, reflecting its power generation status. This data helps the tracking control mechanism perform precise power optimization. By analyzing the photovoltaic output information, the tracking control mechanism dynamically adjusts the inverter's operation to ensure the photovoltaic array always operates at its maximum power point, thus improving the overall power generation efficiency of the system. Coordinating the virtual control scheme with the dynamic control scheme for multi-unit parallel synchronous control effectively coordinates the operation of multiple photovoltaic inverters, keeping them synchronized and avoiding inconsistencies in inverter output or grid frequency instability. This not only improves the grid connection efficiency of the photovoltaic array but also ensures the power quality and system stability of the microgrid.

[0056] Example 2, based on the same inventive concept as the multi-machine parallel synchronous control method for photovoltaic inverters in microgrids in the previous examples, such as... Figure 2 As shown in the embodiment of this application, a multi-unit parallel synchronous control system for photovoltaic inverters in microgrids is provided, the system comprising: The virtual control scheme generation module 10 is used to establish a virtual generator model of the photovoltaic inverter in the microgrid and generate a virtual control scheme through the virtual generator model; the dynamic control scheme generation module 20 is used to dynamically monitor the photovoltaic array in the microgrid to obtain photovoltaic output information, and to perform control analysis on the photovoltaic output information according to the tracking control mechanism to obtain a dynamic control scheme; the multi-machine parallel synchronous control module 30 is used to coordinate the virtual control scheme and the dynamic control scheme to perform multi-machine parallel synchronous control execution of the photovoltaic inverter.

[0057] Furthermore, the virtual generator model is virtually controlled through a virtual control strategy. This virtual control strategy adjusts the system frequency through a power frequency controller, regulates the output voltage through an excitation controller, and provides system inertia support through virtual rotational inertia and damping coefficient.

[0058] Furthermore, the dynamic control scheme generation module 20 is used to perform the following operation steps: Extract the first output information corresponding to the first operating point from the photovoltaic output information, wherein the first output information includes first voltage data and first current data; calculate the first output power value based on the first voltage data and the first current data; sort the first operating points in descending order according to the first output power value to obtain the operating point sequence; analyze the operating point sequence according to the tracking control mechanism to obtain the dynamic control scheme.

[0059] Furthermore, the dynamic control scheme generation module 20 is used to perform the following operation steps: Extract any operating point from the operating point sequence; according to the tracking control mechanism, match any predetermined search step size for any output power value corresponding to any operating point; control the any operating point according to the predetermined search step size, and form the dynamic control scheme; wherein, the tracking control mechanism refers to a control mechanism inversely proportional to the output power value.

[0060] Furthermore, the dynamic control scheme generation module 20 is used to perform the following operation steps: The first operating point is continuously monitored to obtain a second output power value; a first power value timing sequence is generated based on the correspondence between the first time zone and the first output power value, and the second time zone and the second output power value; the first power value timing sequence is analyzed according to the adaptive control plan in the tracking control mechanism to obtain a target rate of change; it is determined whether the target rate of change reaches a predetermined threshold to obtain a target judgment result; the dynamic control scheme is adaptively adjusted according to the target judgment result; wherein, the process includes: if the target rate of change reaches the predetermined threshold, the first predetermined search step size corresponding to the first operating point is adaptively increased to obtain a first adaptive search step size; if the target rate of change does not reach the predetermined threshold, the first predetermined search step size corresponding to the first operating point is adaptively decreased to obtain a second adaptive search step size; the dynamic control scheme is adaptively adjusted according to the first adaptive search step size or the second adaptive search step size.

[0061] Furthermore, the dynamic control scheme generation module 20 is used to perform the following operation steps: The time series of the first power value is subjected to regression fitting to obtain a first fitting formula; a first fitting curve is obtained based on the first fitting formula, and the target slope of the first fitting curve is obtained by combining the target time zone; the target slope is standardized to obtain the target rate of change.

[0062] Furthermore, the multi-machine parallel synchronization control module 30 is used to perform the following operation steps: The microgrid is monitored and controlled by multiple parallel synchronous controllers to obtain dynamic monitoring records. When the voltage distortion rate obtained from analyzing the dynamic monitoring records reaches a predetermined distortion rate threshold, the microgrid is in a weak grid state. The virtual control scheme is dynamically adjusted according to the intensity level of the weak grid state.

[0063] Furthermore, the multi-machine parallel synchronization control module 30 is used to perform the following operation steps: The voltage harmonic components of the microgrid are obtained based on the dynamic monitoring records, and a reverse harmonic current command is generated; the multi-resonant controller is activated based on the reverse harmonic current command to suppress harmonics at a predetermined frequency.

[0064] Furthermore, the multi-machine parallel synchronization control module 30 is used to perform the following operation steps: Read the predetermined monitoring indicators and combine them with the dynamic monitoring records to obtain the indicator parameter set; when the indicator parameter set does not meet the predetermined condition constraints, issue an abnormal command and switch to the island operation mode based on the abnormal command.

[0065] Through the foregoing detailed description of the method for parallel synchronous control of multiple photovoltaic inverters for microgrids, those skilled in the art can clearly understand the parallel synchronous control system for multiple photovoltaic inverters for microgrids in this embodiment. Since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and relevant parts can be referred to in the method section.

[0066] The above description of the disclosed embodiments enables those skilled in the art to make or use this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for parallel synchronous control of multiple photovoltaic inverters in microgrids, characterized in that, The method includes: A virtual generator model of a photovoltaic inverter in a microgrid is established, and a virtual control scheme is generated based on the virtual generator model. The photovoltaic array in the microgrid is dynamically monitored to obtain photovoltaic output information, and the photovoltaic output information is controlled and analyzed according to the tracking control mechanism to obtain a dynamic control scheme; The virtual control scheme and the dynamic control scheme work together to perform multi-machine parallel synchronous control of the photovoltaic inverter.

2. The method for multi-unit parallel synchronous control of photovoltaic inverters for microgrids as described in claim 1, characterized in that, The virtual generator model is controlled virtually through a virtual control strategy. This strategy adjusts the system frequency through a power frequency controller, regulates the output voltage through an excitation controller, and provides system inertia support through virtual rotational inertia and damping coefficient.

3. The method for multi-unit parallel synchronous control of photovoltaic inverters for microgrids as described in claim 1, characterized in that, The photovoltaic array in the microgrid is dynamically monitored to obtain photovoltaic output information, and the photovoltaic output information is controlled and analyzed according to a tracking control mechanism to obtain a dynamic control scheme, including: Extract the first output information corresponding to the first operating point from the photovoltaic output information, wherein the first output information includes first voltage data and first current data; The first output power value is calculated based on the first voltage data and the first current data; The first operating points are sorted in descending order based on the first output power value to obtain the operating point sequence. The dynamic control scheme is obtained by analyzing the operating point sequence based on the tracking control mechanism.

4. The method for multi-unit parallel synchronous control of photovoltaic inverters for microgrids as described in claim 3, characterized in that, The dynamic control scheme is obtained by analyzing the operating point sequence based on the tracking control mechanism, including: Extract any working point from the working point sequence; According to the tracking control mechanism, match any predetermined search step size for any output power value corresponding to any operating point; The arbitrary operating point is controlled according to the arbitrary predetermined search step size, and the dynamic control scheme is formed. The tracking control mechanism refers to a control mechanism in which the search step size is inversely proportional to the output power value.

5. The method for multi-unit parallel synchronous control of photovoltaic inverters for microgrids as described in claim 4, characterized in that, After controlling the arbitrary operating point according to the arbitrary predetermined search step size and forming the dynamic control scheme, the method further includes: The first operating point is continuously monitored to obtain the second output power value; Based on the correspondence between the first time zone and the first output power value, and the second time zone and the second output power value, a timing sequence for the first power value is generated. Based on the adaptive control plan in the tracking control mechanism, the time sequence of the first power value is analyzed to obtain the target rate of change; Determine whether the target rate of change has reached a predetermined threshold, and obtain the target determination result; The dynamic control scheme is adaptively adjusted based on the target judgment result. This includes: If the target change rate reaches a predetermined threshold, the first predetermined search step size corresponding to the first working point is adaptively increased and adjusted to obtain the first adaptive search step size. If the target rate of change does not reach the predetermined threshold, the first predetermined search step size corresponding to the first working point is adaptively reduced and adjusted to obtain the second adaptive search step size. The dynamic control scheme is adaptively adjusted based on either the first or the second adaptive search step size.

6. The method for multi-unit parallel synchronous control of photovoltaic inverters for microgrids as described in claim 5, characterized in that, Based on the adaptive control plan in the tracking control mechanism, the time series of the first power value is analyzed to obtain the target rate of change, including: The first power value time series is subjected to regression fitting to obtain the first fitting formula; The first fitting curve is obtained based on the first fitting formula, and the target slope of the first fitting curve is obtained by combining the target time zone. The target slope is standardized to obtain the target rate of change.

7. The method for multi-unit parallel synchronous control of photovoltaic inverters for microgrids as described in claim 1, characterized in that, The method of coordinating the virtual control scheme and the dynamic control scheme to perform multi-machine parallel synchronous control of the photovoltaic inverter also includes: The microgrid is subjected to multi-machine parallel synchronous control and monitoring to obtain dynamic monitoring records; When the voltage distortion rate obtained from the analysis of the dynamic monitoring records reaches a predetermined distortion rate threshold, the microgrid is in a weak grid state. The virtual control scheme is dynamically adjusted according to the intensity level of the weak power grid condition.

8. The method for multi-unit parallel synchronous control of photovoltaic inverters for microgrids as described in claim 7, characterized in that, Before dynamically adjusting the virtual control scheme according to the intensity level of the weak power grid state, the method further includes: The voltage harmonic components of the microgrid are obtained based on the dynamic monitoring records, and a reverse harmonic current command is generated. The multi-resonant controller is activated according to the reverse harmonic current command to suppress harmonics at a predetermined frequency.

9. The method for multi-unit parallel synchronous control of photovoltaic inverters for microgrids as described in claim 7, characterized in that, After dynamically adjusting the virtual control scheme according to the intensity level of the weak power grid state, the method further includes: Read the predetermined monitoring indicators and combine them with the dynamic monitoring records to obtain the indicator parameter set; When the set of indicator parameters does not meet the predetermined constraints, an abnormal command is issued, and the isolated operation mode is switched based on the abnormal command.

10. A multi-unit parallel synchronous control system for photovoltaic inverters in microgrids, characterized in that, For implementing the multi-unit parallel synchronous control method for photovoltaic inverters in microgrids according to any one of claims 1-9, the system comprises: The virtual control scheme generation module is used to establish a virtual generator model of the photovoltaic inverter in the microgrid and generate a virtual control scheme through the virtual generator model. The dynamic control scheme generation module is used to dynamically monitor the photovoltaic array in the microgrid to obtain photovoltaic output information, and to perform control analysis on the photovoltaic output information according to the tracking control mechanism to obtain a dynamic control scheme. The multi-machine parallel synchronous control module is used to coordinate the virtual control scheme and the dynamic control scheme to perform multi-machine parallel synchronous control of the photovoltaic inverter.

Images