Modularized distributed photovoltaic inverter cluster intelligent regulation and control system

Abstract

The invention, which relates to the technical field of distributed power generation, discloses a modularized distributed photovoltaic inverter cluster intelligent regulation and control system comprising an impedance identification module, an impedance control module, a state sensing module, a fault diagnosis and isolation module, a power distribution module and a cluster fault control module. The power grid impedance monitoring module is used for monitoring voltage and current signals of a grid-connected point of the photovoltaic inverter, calculating a power grid equivalent impedance value, an impedance change trend and a harmonic component proportion of the current photovoltaic inverter, and generating power grid impedance information. The impedance identification module and the impedance control module are arranged, adjustment is carried out based on the virtual impedance parameters, the resonance problem caused by power grid impedance fluctuation is effectively suppressed, the situation that grid-connected current distortion affects the electric energy quality is avoided, the photovoltaic inverter cluster stably operates in a power grid impedance change scene, and the power grid impedance change efficiency is improved. And the cluster grid-connected power quality and the adaptability to the power grid environment are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of distributed power generation, in particular to a modular distributed photovoltaic inverter cluster intelligent regulation system. BACKGROUND

[0002] The photovoltaic inverter can convert the variable direct current voltage generated by the photovoltaic solar panel into the inverter of the power frequency alternating current. The most important function of the photovoltaic inverter is to convert the direct current generated by the solar panel into alternating current used by household appliances. The electricity generated by the solar panel must be processed by the inverter before it can be output externally. Through the full-bridge circuit, the SPWM processor is generally used for modulation, filtering, voltage boosting, etc. to obtain a sinusoidal alternating current with a frequency and rated voltage matching the lighting load for system end users. Setting the inverter can use the direct current storage battery to provide alternating current for electrical appliances.

[0003] With the expansion of the distributed photovoltaic inverter cluster, its operation needs to cope with complex scenarios such as grid impedance fluctuation, equipment state change and fault burst. The existing regulation system lacks dynamic perception and targeted control of the grid impedance, which leads to resonance problems caused by grid impedance changes in cluster operation, causing the photovoltaic inverter cluster to reduce the quality of grid-connected power and lack of operation reliability, which cannot meet the needs of efficient and stable operation of the cluster in complex grid environments. SUMMARY

[0004] In view of the deficiencies of the prior art, the present application provides a modular distributed photovoltaic inverter cluster intelligent regulation system, which solves the problems mentioned in the background art.

[0005] To achieve the above purpose, the present application is realized by the following technical scheme: a modular distributed photovoltaic inverter cluster intelligent regulation system, the regulation system comprises: an impedance identification module, an impedance control module, a state perception module, a fault diagnosis and isolation module, a power distribution module and a cluster fault control module;

[0006] The impedance identification module is used to monitor the voltage and current signals of the grid-connected point of the photovoltaic inverter, and calculate the grid equivalent impedance value, impedance change trend and harmonic component proportion of the current photovoltaic inverter, and generate grid impedance information;

[0007] The impedance control module is used to receive and calculate the grid impedance information. After the calculation is completed, the virtual impedance parameters of the photovoltaic inverter output impedance are adjusted according to the results, and the resonance of the photovoltaic inverter is controlled by the adjusted virtual impedance parameters;

[0008] The status sensing module is used to collect the operating parameters of the key components of the photovoltaic inverter and the environmental parameters around the photovoltaic inverter cluster. After preprocessing the operating parameters and the environmental parameters, it generates the equipment health status and the photovoltaic inverter cluster power generation potential parameters.

[0009] The fault diagnosis and isolation module is used to identify faults in the photovoltaic inverter and locate the fault location, and to shut down and isolate the faulty equipment of the photovoltaic inverter based on the identified fault information.

[0010] The power allocation module is used to generate power allocation instructions for each of the photovoltaic inverters based on the cluster power generation potential parameters, the equipment health status and grid dispatch instructions, using a multi-objective optimization algorithm.

[0011] The cluster fault control module is used to receive the fault information, and according to the fault information, to make up for the shutdown and isolated photovoltaic inverter by using other normal photovoltaic inverters, and send the information for making up for the shutdown and operation to the power distribution module for instruction execution.

[0012] Preferably, the cluster fault control module uses a finite state machine for supplementary operation, specifically: the finite state machine divides different operating states according to the number of faulty devices in the photovoltaic inverter;

[0013] When the number of faulty devices is less than the set number, the cluster fault control module adjusts the power load of the remaining photovoltaic inverters through the power distribution module to supplement the output power of the faulty devices;

[0014] When the number of faulty devices exceeds the set number, the cluster fault control module requests a temporary load reduction instruction from the power grid dispatch control center. Based on the information or instructions returned by the power grid dispatch control center, priority is given to ensuring power supply to the power plant's own load and critical user load.

[0015] Preferably, the cluster fault control module calls the normal photovoltaic inverters to perform replacement based on the fault information, and sends a parameter adjustment command for replacement operation to the power distribution module according to the replacement requirement. The power distribution module adjusts the power parameters of the normal photovoltaic inverters around the faulty device according to the parameter adjustment command.

[0016] Preferably, the fault diagnosis and isolation module has a built-in fault diagnosis algorithm, which analyzes the health status of the equipment and related operating parameters to identify the fault type of the photovoltaic inverter and locate the position of the photovoltaic inverter where the fault occurred.

[0017] The fault diagnosis and isolation module includes an isolation execution submodule. When the isolation execution submodule receives a fault information instruction from the fault diagnosis and isolation module, it performs shutdown and electrical isolation processing on the faulty equipment.

[0018] Preferably, the impedance identification module uses an impedance measurement algorithm based on recursive least squares to perform online calculations. The recursive least squares algorithm is used to analyze and calculate the voltage and current signals of the monitored grid connection point to obtain the grid impedance information of the grid equivalent impedance.

[0019] Preferably, the state perception module integrates multiple types of sensors, which are used to collect the operating parameters of key components of the photovoltaic inverter and the environmental parameters around the photovoltaic inverter cluster.

[0020] The preprocessing includes noise removal and feature extraction of the collected operating parameters and environmental parameters around the cluster, generating parameters of the equipment health status and the power generation potential of the cluster.

[0021] Preferably, the impedance identification module calculates and generates the grid impedance information by acquiring the three-phase voltage and current signals at the grid connection point of the photovoltaic inverter, obtaining voltage and current waveform data in the time domain, and filtering the acquired voltage and current signals to remove noise interference.

[0022] Based on the processed voltage and current signals, an impedance measurement algorithm is used to calculate the amplitude and phase of the equivalent impedance of the power grid at a specific frequency point, thereby obtaining the equivalent impedance value of the power grid. The equivalent impedance value of the power grid is continuously acquired at multiple times. A trend analysis algorithm is used to identify the direction and rate of change of the impedance value over time, generating the impedance change trend information. Spectral analysis is performed on the voltage and current signals to decompose each harmonic component, calculate the proportion of different frequency harmonics in the total signal, and determine the information on the proportion of the harmonic components.

[0023] The calculated equivalent impedance value of the power grid, the impedance change trend, and the proportion of harmonic components are fused to form complete power grid impedance information.

[0024] Preferably, the state awareness module classifies and organizes the collected operating parameters and environmental parameters, removes abnormal and invalid data, and retains the valid parameter dataset.

[0025] A signal filtering algorithm is used to suppress the fluctuation noise in the effective parameter dataset, eliminate signal disturbances caused by electromagnetic interference and environmental interference during the acquisition process, and obtain interference-free parameters. Based on the interference-free parameters, health features and environmental features of the equipment health status and the cluster power generation potential of the photovoltaic inverter are extracted.

[0026] The extracted health features and environmental features are standardized. Through a data fusion algorithm, the health features of the same photovoltaic inverter are integrated into an indicator of the equipment health status, and the environmental features of the cluster area are integrated into an indicator of the cluster power generation potential parameter.

[0027] Preferably, the suppression control of the impedance control module is achieved by receiving the grid impedance information generated by the impedance identification module, analyzing the impedance change characteristics based on the control algorithm of the impedance control module, and adjusting the virtual impedance parameters accordingly.

[0028] By changing the combined characteristics of virtual inductance, resistance, and capacitance, the output impedance characteristics of the photovoltaic inverter in the resonant risk frequency band are generated. Based on the impedance characteristics, the resonance formation conditions are determined, and the output current, voltage, and power of the photovoltaic inverter are adjusted according to the resonance formation conditions to achieve resonance suppression control.

[0029] Preferably, the control system further includes: an inverter control module and a central control module;

[0030] The inverter control module is used to execute the basic control functions of the photovoltaic inverter, and to receive the power distribution command and the command signal output by the impedance control module, and to regulate the operating state of the photovoltaic inverter according to the command signal;

[0031] The central control module is used to integrate the grid impedance information, the equipment health status, the cluster power generation potential parameters and the fault information, and upload them to the grid dispatch and control center, as well as receive the control information or instructions from the grid dispatch and control center.

[0032] This invention provides a modular distributed photovoltaic inverter cluster intelligent control system. It has the following advantages:

[0033] (1) By setting an impedance identification module and an impedance control module, the former can monitor the voltage and current signals at the grid connection point in real time to generate grid impedance information, and the latter can dynamically adjust the virtual impedance parameters of the output impedance of the photovoltaic inverter based on the information. Based on the virtual impedance parameters, the adjustment can effectively suppress the resonance problem caused by grid impedance fluctuations, avoid the situation where grid current distortion affects power quality, and enable the photovoltaic inverter cluster to operate stably in the scenario of grid impedance change, thereby improving the grid connection power quality and adaptability to the grid environment of the cluster.

[0034] (2) The photovoltaic inverter’s equipment operation parameters and environmental parameters are collected by the status sensing module. The two sets of parameters are used to generate equipment health status and cluster power generation potential parameters. The fault diagnosis and isolation module can identify equipment faults and isolate faulty equipment based on the above parameters. The cluster fault control module coordinates other inverters to fill in the gap, handles equipment faults in a timely manner and makes up for the power output gap caused by the fault, avoids the spread of faults and interruption of cluster operation, ensures the continuity of photovoltaic inverter cluster operation, and significantly improves overall operational reliability.

[0035] (3) The power allocation module generates power allocation instructions for each photovoltaic inverter based on the cluster power generation potential parameters, equipment health status and grid dispatch instructions through a multi-objective optimization algorithm. This enables each inverter to respond to dispatch requirements while adapting to its own status and environmental conditions, avoiding inefficient operation or equipment overload caused by unreasonable power allocation, and realizing the optimized allocation of photovoltaic inverter cluster power generation resources, so that the cluster can achieve the goal of efficient operation while meeting the grid dispatch requirements. Attached Figure Description

[0036] Figure 1 This is a system structure block diagram of a modular distributed photovoltaic inverter cluster intelligent control system according to the present invention. Detailed Implementation

[0037] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0038] Example 1

[0039] Please see Figure 1 This invention provides a modular distributed photovoltaic inverter cluster intelligent control system. To achieve the above objectives, this invention is implemented through the following technical solution: The control system includes: an impedance identification module, an impedance control module, a status sensing module, a fault diagnosis and isolation module, a power distribution module, and a cluster fault control module.

[0040] The impedance identification module is used to monitor the voltage and current signals at the grid connection point of the photovoltaic inverter, calculate the current grid equivalent impedance value of the photovoltaic inverter, the impedance change trend, and the proportion of harmonic components, and generate grid impedance information.

[0041] The impedance control module is used to receive and calculate grid impedance information. After the calculation is completed, it adjusts the virtual impedance parameter of the photovoltaic inverter output impedance according to the result. The adjusted virtual impedance parameter is used to suppress the resonance of the photovoltaic inverter.

[0042] The status awareness module is used to collect the operating parameters of key components of the photovoltaic inverter and the environmental parameters around the photovoltaic inverter cluster. After preprocessing the operating parameters and environmental parameters, it generates the equipment health status and the photovoltaic inverter cluster power generation potential parameters.

[0043] The fault diagnosis and isolation module is used to identify faults in the photovoltaic inverter, locate the fault location, and shut down and isolate the faulty equipment of the photovoltaic inverter based on the identified fault information.

[0044] The power allocation module is used to generate power allocation instructions for each photovoltaic inverter based on cluster power generation potential parameters, equipment health status and grid dispatch instructions, through a multi-objective optimization algorithm.

[0045] The cluster fault control module is used to receive fault information, and based on the fault information, to enable the shutdown and isolated photovoltaic inverters to operate in place through other normal photovoltaic inverters, and to send the information for the replacement operation to the power distribution module for instruction execution.

[0046] In this embodiment, specifically, upon system initialization and startup, the impedance identification module monitors the voltage and current signals at the grid connection point of the photovoltaic inverter in real time, continuously calculating the equivalent impedance value of the grid, the impedance change trend, and the proportion of harmonic components. This generates grid impedance information and continuously transmits it to the impedance control module. Upon receiving the grid impedance information, the impedance control module analyzes the impedance change characteristics using a built-in control algorithm and adjusts the virtual impedance parameters of the photovoltaic inverter's output impedance accordingly. By changing the combined characteristics of virtual inductance, resistance, and capacitance, it reshapes the inverter's output impedance in the resonant risk frequency band, achieving resonance suppression control. Simultaneously, the status perception module collects operating parameters of key components of the photovoltaic inverter and environmental parameters around the cluster using multiple types of sensors. It classifies, organizes, removes noise, and extracts features from the collected data, generating equipment health status and cluster power generation potential parameters, which are transmitted to the fault diagnosis and isolation module and the power distribution module, respectively. Upon receiving the equipment health status parameters, the fault diagnosis and isolation module analyzes and identifies the fault type and locates the fault location using a fault diagnosis algorithm. When a fault is detected, the isolation execution submodule is triggered. The faulty equipment is shut down and electrically isolated, and the fault information is synchronously sent to the cluster fault control module. The power allocation module, based on the cluster power generation potential parameters and equipment health status provided by the status awareness module, and combined with the received grid dispatch instructions, generates power allocation instructions for each photovoltaic inverter through a multi-objective optimization algorithm and sends them to the corresponding inverter control modules. After receiving the fault information, the cluster fault control module initiates corresponding compensation strategies according to the number of faulty equipment: when the number of faults is small, it sends parameter adjustment instructions to the power allocation module to coordinate normal inverters around the faulty equipment to undertake compensation power; when the number of faults is large, it applies for temporary load reduction instructions from the higher-level grid dispatch center to prioritize power supply to critical loads. The power allocation module re-optimizes and generates a power allocation scheme based on the compensation instructions from the cluster fault control module to ensure accurate execution of compensation operations and maintain the overall stable operation of the cluster. The central control module continuously integrates grid impedance information, equipment health status, cluster power generation potential parameters, and fault information, uploads them to the grid dispatch control center, and receives control instructions to achieve coordinated operation between the system and the external grid.

[0047] Example 2

[0048] Specifically: The cluster fault control module uses a finite state machine for backup operation, which means that the finite state machine divides the operation into different states according to the number of faulty devices in the photovoltaic inverter;

[0049] When the number of faulty devices is less than the set number, the cluster fault control module adjusts the power load of the remaining photovoltaic inverters through the power distribution module to supplement the output power of the faulty devices.

[0050] When the number of faulty devices exceeds the set number, the cluster fault control module requests a temporary load reduction instruction from the power grid dispatch control center. Based on the information or instructions returned by the power grid dispatch control center, priority is given to ensuring power supply to the power plant's own load and critical user load.

[0051] The cluster fault control module calls upon normal photovoltaic inverters to perform replacement based on the fault information. Based on the replacement requirement, the cluster fault control module sends parameter adjustment instructions to the power distribution module for replacement operation. The power distribution module adjusts the power parameters of normal photovoltaic inverters around the faulty device according to the parameter adjustment instructions.

[0052] The fault diagnosis and isolation module has a built-in fault diagnosis algorithm. The algorithm analyzes the health status of the equipment and related operating parameters to identify the fault type of the photovoltaic inverter and locate the position of the photovoltaic inverter where the fault occurred.

[0053] The fault diagnosis and isolation module includes an isolation execution submodule. When the isolation execution submodule receives a fault information command from the fault diagnosis and isolation module, it performs shutdown and electrical isolation processing on the faulty equipment.

[0054] The impedance identification module uses an impedance measurement algorithm based on recursive least squares to perform online calculations. By analyzing and calculating the voltage and current signals at the monitored grid connection point using the recursive least squares algorithm, the grid impedance information of the equivalent grid impedance is obtained.

[0055] The status awareness module integrates multiple types of sensors, which are used to collect the operating parameters of key components of the photovoltaic inverter and the environmental parameters around the photovoltaic inverter cluster.

[0056] Preprocessing includes noise removal and feature extraction of the collected operating parameters and environmental parameters around the cluster to generate equipment health status and cluster power generation potential parameters.

[0057] In this embodiment, the finite state machine uses the number of faulty devices as the core switching condition and combines the total power margin of the cluster to set multiple operating states, such as normal operation (no faults), a small number of faults replacement state (few faulty devices, sufficient normal device margin), and a large number of faults load reduction state (many faulty devices, insufficient device margin). Each state is automatically switched through preset threshold conditions to ensure that the optimal strategy can be matched under different fault scenarios.

[0058] In the case of a small number of faults requiring backup, the cluster fault control module first calculates the total power output value of the faulty device through the power gap, and then, in combination with the health status of the normal devices provided by the status awareness module, filters out a list of devices with backup capabilities, and sends a backup parameter adjustment instruction to the power allocation module. The instruction specifies the power value that each backup device needs to increase to avoid overloading the backup device. After receiving the instruction, the power allocation module updates the power allocation scheme so that the backup device can bear the extra power according to the instruction and maintain the stability of the total power of the cluster.

[0059] In the event of a large number of faults and load reductions, the cluster fault control module establishes communication with the power grid dispatch control center and sends a load reduction request. The request includes the current fault status and the power output value that the cluster can maintain. After receiving the load reduction permission or specific adjustment parameters from the dispatch center, the cluster fault control module uses the load priority sorting unit (preset "power station self-use load > critical user load > ordinary user load") to prioritize the power supply of high-priority loads, and then uses the power distribution module to adjust the power output of normal equipment to ensure that critical power demand is not affected.

[0060] For the fault diagnosis and isolation module, its fault diagnosis algorithm adopts multi-dimensional verification logic: first, it compares the equipment health status indicators with the preset normal threshold; second, it analyzes the changing trend of the indicators; and third, it correlates multiple parameters for verification. Through the triple logic, the accuracy of fault identification is improved, and misjudgment caused by a single parameter abnormality is avoided. At the same time, the algorithm has a built-in fault type library (such as IGBT fault, capacitor leakage, fan jamming, etc.). By matching the indicator features with the fault type, the fault type is accurately identified, and the specific faulty equipment is located by combining the location code of the sensing element, which facilitates subsequent power allocation scheduling and maintenance and repair by operation and maintenance personnel.

[0061] The isolation of photovoltaic inverter faults is divided into two parts. The first part is electrical isolation, which controls the main switch between the photovoltaic inverter and the grid and photovoltaic array to disconnect the power input and output of the faulty equipment. The second part is signal isolation, which disconnects the communication link between the faulty equipment and other modules to prevent the fault signal from interfering with the normal communication of the system. After the isolation is completed, an isolation confirmation signal is sent to the cluster fault control module to ensure that the replacement logic is started in time.

[0062] Example 3

[0063] Specifically: The impedance identification module calculates and generates grid impedance information, acquires voltage and current waveform data in the time domain by collecting three-phase voltage and current signals at the grid connection point of the photovoltaic inverter, and filters the collected voltage and current signals to remove noise interference;

[0064] Based on the processed voltage and current signals, an impedance measurement algorithm is used to calculate the amplitude and phase of the equivalent impedance of the power grid at a specific frequency point, thereby obtaining the equivalent impedance value of the power grid. The equivalent impedance value of the power grid at multiple times is continuously acquired. The direction and rate of change of the impedance value over time are identified through a trend analysis algorithm, generating impedance change trend information. Spectral analysis is performed on the voltage and current signals to decompose each harmonic component, calculate the proportion of different frequency harmonics in the total signal, and determine the information on the proportion of harmonic components.

[0065] The calculated equivalent impedance value of the power grid, the impedance change trend, and the proportion of harmonic components are fused to form complete power grid impedance information.

[0066] The status awareness module categorizes and organizes the collected operating parameters and environmental parameters, removes abnormal and invalid data, and retains the valid parameter dataset.

[0067] A signal filtering algorithm is used to suppress the fluctuation noise in the effective parameter dataset, eliminate signal disturbances caused by electromagnetic interference and environmental interference during the acquisition process, and obtain interference-free parameters. Based on the interference-free parameters, health features and environmental features of the equipment health status and the cluster power generation potential of the photovoltaic inverter are extracted.

[0068] The extracted health and environmental features are standardized. Through data fusion algorithms, the health features of the same photovoltaic inverter are integrated into an indicator of equipment health status, and the environmental features of the cluster area are integrated into an indicator of cluster power generation potential parameters.

[0069] The suppression control of the impedance control module receives the grid impedance information generated by the impedance identification module, analyzes the impedance change characteristics based on the control algorithm of the impedance control module, and adjusts the virtual impedance parameters accordingly.

[0070] By changing the combined characteristics of virtual inductance, resistance and capacitance, the output impedance characteristics of the photovoltaic inverter in the resonant risk frequency band are generated. Based on the impedance characteristics, the resonance formation conditions are determined, and the output current, voltage and power of the photovoltaic inverter are adjusted according to the resonance formation conditions to achieve resonance suppression control.

[0071] In this embodiment, the equivalent impedance of the power grid is the ability of the power grid to impede currents of different frequencies. The amplitude and phase reflect the magnitude of the impediment and the phase relationship, respectively. Trend analysis can predict the trend of changes in the power grid impedance in advance. That is, the current impedance of different frequencies is decomposed into multiple impedance values ​​and phase relationships. This can decompose complex electrical signals into harmonics of different frequencies, understand the harmonic situation of the power grid, and thus predict and suppress the impedance in advance.

[0072] Different combinations of virtual impedance parameters will cause photovoltaic inverters to exhibit different impedance characteristics at specific frequencies. By adjusting these parameter combinations, it is possible to avoid the inverter and the grid forming a resonant circuit at certain frequencies. Combined with the adjustment of output current, voltage and power, resonance can be prevented from occurring from multiple aspects.

[0073] After receiving grid impedance information, the module identifies the resonance risk frequency band (such as the frequency range where impedance amplitude increases sharply) and harmonic interference intensity through impedance characteristic analysis to determine whether a resonance risk exists. Based on the analysis results, it dynamically changes the combination of virtual inductance, resistance, and capacitance through parameter adjustment algorithms. For example, it increases the virtual resistance in the resonance risk frequency band to consume resonance energy, or adjusts the virtual inductance or capacitance to offset the resonance frequency, avoiding the formation of a resonance loop with the grid impedance. Through impedance characteristic calculation algorithms, it generates the inverter's output impedance characteristics (amplitude and phase variation with frequency) in the resonance risk frequency band, ensuring that the reshaped characteristics can break the resonance formation conditions. Through resonance judgment algorithms, it compares the inverter's output impedance with the grid impedance characteristics to verify whether a resonance risk still exists. If a resonance risk exists, it returns to readjust the parameters until the risk is completely eliminated. If no resonance risk is confirmed, it fine-tunes the inverter's output current, voltage, and power through the parameter adjustment unit to ensure that the output power quality meets grid connection standards, achieving the dual goals of resonance suppression and stable operation.

[0074] Example 4

[0075] Specifically, the control system also includes an inverter control module and a central control module;

[0076] The inverter control module is used to execute the basic control functions of the photovoltaic inverter, and to receive power distribution commands and command signals output by the impedance control module, and to regulate the operating status of the photovoltaic inverter according to the command signals.

[0077] The central control module is used to integrate grid impedance information, equipment health status, cluster generation potential parameters and fault information, and upload them to the grid dispatch and control center, as well as receive control information or instructions from the grid dispatch and control center.

[0078] In this embodiment, the basic control functions of the inverter control module include enabling the photovoltaic inverter to perform core operations such as DC to AC conversion and tracking the maximum power generation. The inverter control module is equivalent to the operation actuator of the photovoltaic inverter, adjusting its own operation according to the received instructions to ensure compliance with the overall system regulation requirements, and implementing impedance suppression control and power distribution control within the regulation system.

[0079] The central control module is responsible for aggregating information from all modules to gain a comprehensive understanding of the entire cluster's operational status. It also serves as a bridge for communication with the external dispatch center, enabling the transmission of information between different levels and ensuring that the cluster's operation is coordinated with the overall grid dispatch. The entire photovoltaic inverter cluster is equipped with a central control module, which is located in the local control room of the photovoltaic inverter cluster.

[0080] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention.

Claims

1. A modular distributed photovoltaic inverter cluster intelligent control system, characterized in that: The control system includes: an impedance identification module, an impedance control module, a status sensing module, a fault diagnosis and isolation module, a power distribution module, and a cluster fault control module. The impedance identification module is used to monitor the voltage and current signals at the grid connection point of the photovoltaic inverter, calculate the current grid equivalent impedance value of the photovoltaic inverter, the impedance change trend, and the proportion of harmonic components, and generate grid impedance information. The impedance control module is used to receive and calculate the grid impedance information. After the calculation is completed, it adjusts the virtual impedance parameter of the output impedance of the photovoltaic inverter according to the result, and suppresses the resonance of the photovoltaic inverter through the adjusted virtual impedance parameter. The status sensing module is used to collect the operating parameters of the key components of the photovoltaic inverter and the environmental parameters around the photovoltaic inverter cluster. After preprocessing the operating parameters and the environmental parameters, it generates the equipment health status and the photovoltaic inverter cluster power generation potential parameters. The fault diagnosis and isolation module is used to identify faults in the photovoltaic inverter and locate the fault location, and to shut down and isolate the faulty equipment of the photovoltaic inverter based on the identified fault information. The power allocation module is used to generate power allocation instructions for each of the photovoltaic inverters based on the cluster power generation potential parameters, the equipment health status and grid dispatch instructions, using a multi-objective optimization algorithm. The cluster fault control module is used to receive the fault information, and according to the fault information, to make up for the shutdown and isolated photovoltaic inverter by using other normal photovoltaic inverters, and send the information for making up for the shutdown and operation to the power distribution module for instruction execution.

2. The modular distributed photovoltaic inverter cluster intelligent control system according to claim 1, characterized in that: The cluster fault control module uses a finite state machine for supplementary operation. Specifically, the finite state machine divides the photovoltaic inverter into different operating states according to the number of faulty devices. When the number of faulty devices is less than the set number, the cluster fault control module adjusts the power load of the remaining photovoltaic inverters through the power distribution module to supplement the output power of the faulty devices; When the number of faulty devices exceeds the set number, the cluster fault control module requests a temporary load reduction instruction from the power grid dispatch control center. Based on the information or instructions returned by the power grid dispatch control center, priority is given to ensuring power supply to the power plant's own load and critical user load.

3. The modular distributed photovoltaic inverter cluster intelligent control system according to claim 1, characterized in that: The cluster fault control module calls the normal photovoltaic inverters to perform replacement based on the fault information. The cluster fault control module sends parameter adjustment instructions for replacement operation to the power distribution module according to the replacement requirements. The power distribution module adjusts the power parameters of the normal photovoltaic inverters around the faulty device according to the parameter adjustment instructions.

4. The modular distributed photovoltaic inverter cluster intelligent control system according to claim 1, characterized in that: The fault diagnosis and isolation module has a built-in fault diagnosis algorithm. The fault diagnosis algorithm analyzes the health status of the equipment and related operating parameters, identifies the fault type of the photovoltaic inverter, and locates the position of the photovoltaic inverter where the fault occurred. The fault diagnosis and isolation module includes an isolation execution submodule. When the isolation execution submodule receives a fault information instruction from the fault diagnosis and isolation module, it performs shutdown and electrical isolation processing on the faulty equipment.

5. The modular distributed photovoltaic inverter cluster intelligent control system according to claim 1, characterized in that: The impedance identification module uses an impedance measurement algorithm based on recursive least squares to perform online calculations. The recursive least squares algorithm is used to analyze and calculate the voltage and current signals of the monitored grid connection point to obtain the grid impedance information of the grid equivalent impedance.

6. The modular distributed photovoltaic inverter cluster intelligent control system according to claim 1, characterized in that: The state perception module integrates multiple types of sensors, which are used to collect the operating parameters of the key components of the photovoltaic inverter and the environmental parameters around the photovoltaic inverter cluster. The preprocessing includes noise removal and feature extraction of the collected operating parameters and environmental parameters around the cluster, generating parameters of the equipment health status and the power generation potential of the cluster.

7. The modular distributed photovoltaic inverter cluster intelligent control system according to claim 1, characterized in that: The impedance identification module calculates and generates the grid impedance information. It acquires the voltage and current waveform data in the time domain by collecting the three-phase voltage and current signals at the grid connection point of the photovoltaic inverter. The acquired voltage and current signals are then filtered to remove noise interference. Based on the processed voltage and current signals, an impedance measurement algorithm is used to calculate the amplitude and phase of the equivalent impedance of the power grid at a specific frequency point, thereby obtaining the equivalent impedance value of the power grid. The equivalent impedance value of the power grid is continuously acquired at multiple times. A trend analysis algorithm is used to identify the direction and rate of change of the impedance value over time, generating the impedance change trend information. Spectral analysis is performed on the voltage and current signals to decompose each harmonic component, calculate the proportion of different frequency harmonics in the total signal, and determine the information on the proportion of the harmonic components. The calculated equivalent impedance value of the power grid, the impedance change trend, and the proportion of harmonic components are fused to form complete power grid impedance information.

8. The modular distributed photovoltaic inverter cluster intelligent control system according to claim 1, characterized in that: The state awareness module classifies and organizes the collected operating parameters and environmental parameters, removes abnormal and invalid data, and retains the valid parameter dataset. A signal filtering algorithm is used to suppress the fluctuation noise in the effective parameter dataset, eliminate signal disturbances caused by electromagnetic interference and environmental interference during the acquisition process, and obtain interference-free parameters. Based on the interference-free parameters, health features and environmental features of the equipment health status and the cluster power generation potential of the photovoltaic inverter are extracted. The extracted health features and environmental features are standardized. Through a data fusion algorithm, the health features of the same photovoltaic inverter are integrated into an indicator of the equipment health status, and the environmental features of the cluster area are integrated into an indicator of the cluster power generation potential parameter.

9. The modular distributed photovoltaic inverter cluster intelligent control system according to claim 1, characterized in that: The suppression control of the impedance control module is achieved by receiving the grid impedance information generated by the impedance identification module, analyzing the impedance change characteristics based on the control algorithm of the impedance control module, and adjusting the virtual impedance parameters accordingly. By changing the combined characteristics of virtual inductance, resistance, and capacitance, the output impedance characteristics of the photovoltaic inverter in the resonant risk frequency band are generated. Based on the impedance characteristics, the resonance formation conditions are determined, and the output current, voltage, and power of the photovoltaic inverter are adjusted according to the resonance formation conditions to achieve resonance suppression control.

10. The modular distributed photovoltaic inverter cluster intelligent control system according to claim 1, characterized in that: The control system also includes: an inverter control module and a central control module; The inverter control module is used to execute the basic control functions of the photovoltaic inverter, and to receive the power distribution command and the command signal output by the impedance control module, and to regulate the operating state of the photovoltaic inverter according to the command signal; The central control module is used to integrate the grid impedance information, the equipment health status, the cluster power generation potential parameters and the fault information, and upload them to the grid dispatch and control center, as well as receive the control information or instructions from the grid dispatch and control center.

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