Multi-dimensional grid-connected test system for photovoltaic string inverter

Abstract

The invention provides a multi-dimensional grid-connected test system for a photovoltaic string inverter, and the system comprises a power grid simulation module which is used for constructing a power grid simulation environment based on a multi-dimensional coupling mechanism of voltage fluctuation, frequency deviation and harmonic distortion; the photovoltaic array simulation module is used for constructing IV characteristic dynamic deduction models of different irradiance and temperature gradient effects based on a photovoltaic array equivalent circuit physical model to realize a natural simulation environment; the loading module is used for loading the power grid simulation environment and the natural simulation environment to the photovoltaic string inverter to be tested; the data acquisition module is used for monitoring running state data of the photovoltaic string type inverter in real time and constructing a running state data set containing multi-physical-quantity coupling characteristics; and the diagnosis module is used for inputting the running state data set into the trained LSTM neural network model to obtain a test result of the photovoltaic string inverter. According to the invention, the efficiency and convenience of the grid-connected test of the inverter can be improved, and the accuracy and reliability of the grid-connected performance of the inverter are ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of photovoltaic string inverter grid-connected testing, and in particular to a photovoltaic string inverter multi-dimensional grid-connected testing system. Background Art

[0002] With the rapid development of photovoltaic power generation technology, the scale of photovoltaic power plants is expanding. As the core equipment of photovoltaic string inverters, their performance, stability, and safety play a vital role in the operation of the entire photovoltaic power plant. The operating principle of photovoltaic grid-connected string inverters is relatively complex. They must automatically implement protective measures in the event of a grid power outage and quickly achieve grid-connected operation after the grid is restored. During this process, photovoltaic string inverters must cope with various operating conditions, making comprehensive grid-connection testing particularly critical. Furthermore, photovoltaic grid-connected string inverters must comply with a series of technical standards and safety regulations during grid-connected operation. To ensure that photovoltaic string inverters meet these requirements, rigorous testing is essential. Such testing not only helps improve the performance stability of photovoltaic string inverters but also ensures their safety in actual operation.

[0003] Furthermore, with the continuous advancement of renewable energy power generation technologies and intensified market competition, the performance requirements for PV string inverters in PV power plants are continuously increasing. Parameters such as efficiency, reliability, and intelligence of PV string inverters are becoming increasingly prominent in the market. Therefore, developing an efficient and accurate PV string inverter grid-connection test device is crucial for enhancing the market competitiveness of PV string inverter products. This not only helps promote the development of PV string inverter testing technology for PV power plants, but also effectively improves the quality and market competitiveness of PV string inverter products. Summary of the Invention

[0004] In view of the above problems, an embodiment of the present invention provides a multi-dimensional grid-connected testing system for photovoltaic string inverters, which solves the technical problems of low testing efficiency and heavy reliance on manual operation of existing photovoltaic string inverters.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0006] The present invention provides a multi-dimensional grid-connected testing system for photovoltaic string inverters, comprising:

[0007] Power Grid Simulation Module: Used to build a power grid simulation environment with complex electromagnetic transient characteristics based on the multi-dimensional coupling mechanism of voltage fluctuation, frequency offset and harmonic distortion;

[0008] Photovoltaic array simulation module: used to build a dynamic deduction model of IV characteristics under different irradiance and temperature gradient effects based on the physical model of the photovoltaic array equivalent circuit, realizing a natural simulation environment with multiple working conditions;

[0009] Loading module: used to load the grid simulation environment and natural simulation environment into the PV string inverter to be tested through the synchronous control interface;

[0010] Data acquisition module: used to monitor the operating status data of photovoltaic string inverters in real time and build an operating status data set containing multi-physical quantity coupling characteristics; and

[0011] Diagnostic module: used to input the operating status dataset into the trained LSTM neural network model and obtain the test results of the PV string inverter through model inference.

[0012] In one embodiment, the power grid simulation module includes:

[0013] Simulated power supply: used to generate voltage and current similar to the actual power grid;

[0014] Simulated load: used to simulate the power load of the actual power grid. By adjusting the parameters of the power load, the operation of the power grid under different load conditions can be simulated.

[0015] Fault injection unit: used to inject faults into the power grid simulation environment composed of simulated power supply and simulated load, so that the power grid simulation environment has at least one of voltage fluctuation, frequency deviation and harmonic distortion.

[0016] In one embodiment, the power grid simulation module further includes:

[0017] Measurement module: used to monitor and record the operation data of the power grid simulation environment in real time;

[0018] Control module: used to adjust the simulated power supply and simulated load through preset operating rules and parameters.

[0019] In one embodiment, the photovoltaic array simulation module includes:

[0020] Rectifier circuit: used to convert AC power into DC power;

[0021] DC / DC conversion circuit: used to convert the fixed voltage and current of the DC power generated by the rectifier circuit into adjustable voltage and current, simulating the IV curve of the photovoltaic array under different irradiance and temperature gradient effects.

[0022] In one embodiment, the photovoltaic array simulation module further includes:

[0023] Control circuit: used to collect the actual values ​​of the output voltage and current of the DC / DC conversion circuit through the sampling load, adjust the output voltage and current of the DC / DC conversion circuit according to the actual values, and determine the voltage range and maximum power point step speed of the DC / DC conversion circuit;

[0024] Protection circuit: used to prevent overcurrent and overvoltage in the rectifier circuit, DC / DC conversion circuit and control circuit;

[0025] Filter circuit: used to reduce the ripple of voltage and current output by DC / DC conversion circuit.

[0026] In one embodiment, a dynamic tracking efficiency quantification module is also included.

[0027] The dynamic tracking efficiency quantification module is used to measure the efficiency of the maximum power point dynamic tracking process by comparing the energy obtained by actual power integration with the energy that should be obtained under ideal conditions by ideal power integration within a specific time interval. The actual power integration reflects the actual energy acquisition under actual influencing factors; the ideal power integration is the energy benchmark without any adverse factors. The maximum power point dynamic tracking efficiency is quantified by the percentage ratio of the two.

[0028] In one embodiment, the data acquisition module includes:

[0029] Data collector: used to collect operating data of photovoltaic string inverters through synchronous acquisition channels, the operating data including voltage, current, power and protection action parameters;

[0030] Data processing unit: used to pre-process the operation data and then perform physical quantity coupling to obtain the operation status data set;

[0031] Data storage unit: used to store the running status data set in the database.

[0032] In one embodiment, the diagnostic module includes:

[0033] Data reading module: used to read the operating status data set in the database;

[0034] Feature extraction module: used to extract relevant features for fault diagnosis of photovoltaic string inverters from the operating status data set, including voltage fluctuations, current harmonics, power factor, and temperature anomalies;

[0035] Fault diagnosis module: used to input the associated features into the trained LSTM neural network model and perform pattern matching in combination with the historical operation database to obtain the test results of the photovoltaic string inverter.

[0036] In one embodiment, an optimization module is further included.

[0037] The optimization module is used to generate an optimization strategy including parameter optimization, fault warning and efficiency improvement based on deviation analysis and feature extraction of test results.

[0038] In one embodiment, a real-time simulation module is also included.

[0039] The real-time simulation module is used to verify the dynamic performance of the photovoltaic string inverter based on the digital twin technology using a simulation engine.

[0040] As can be seen from the above description, an embodiment of the present invention provides a multi-dimensional grid-connected test system for photovoltaic string inverters. Through the grid simulation module and the photovoltaic array simulation module, the various grid environments and natural conditions faced by the photovoltaic string inverter during the grid-connected operation process can be fully reproduced, thereby realizing a comprehensive test of the grid-connected performance of the photovoltaic string inverter. It not only ensures that the photovoltaic string inverter can be safely and reliably connected to the grid for operation, but also enables it to meet the high standards of the photovoltaic power station, thereby improving the power generation efficiency and operational stability of the photovoltaic power station. In addition, the system also supports the automated operation of the photovoltaic string inverter grid-connected test, effectively improving the test efficiency, saving time and labor costs, and reducing the burden on testers. Through automated testing and data analysis, the operating process is simplified and the adaptability of the test system is enhanced, making it applicable to photovoltaic string inverters of different specifications. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 FIG. 1 is a schematic structural diagram of a control system provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0042] To make the objectives, technical solutions, and advantages of the present invention more clear and understandable, the present invention is further described below with reference to the accompanying drawings and specific embodiments. Obviously, the embodiments described are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts are within the scope of protection of the present invention.

[0043] Based on the shortcomings of the prior art, the present invention provides a specific implementation of a multi-dimensional grid-connected testing system for photovoltaic string inverters, such as Figure 1 As shown, the system specifically includes a power grid simulation module 2, a photovoltaic array simulation module 1, a loading module, a data acquisition module 3 and a diagnosis module 4. Each module is described in detail below:

[0044] Power Grid Simulation Module 2: Used to build a power grid simulation environment with complex electromagnetic transient characteristics based on the multi-dimensional coupling mechanism of voltage fluctuations, frequency offsets, and harmonic distortion.

[0045] During the grid-connected testing of the PV string inverter 5, the grid simulation module 2 can be used to construct a complex electromagnetic transient simulation environment that includes multi-dimensional coupling mechanisms such as voltage fluctuations, frequency offsets, and harmonic distortion. In actual grid operation, voltage swells / sags (such as short-circuit faults and sudden load changes), frequency fluctuations (such as generator set anomalies), and harmonic pollution (such as the influence of nonlinear loads) may occur. The grid simulation module 2 can accurately reproduce these operating conditions to test the operational stability of the PV string inverter 5 under different disturbances. In the case of voltage drops, it verifies whether the PV string inverter 5 can maintain grid connection (i.e., low voltage ride-through capability); in the case of frequency offsets, it verifies whether its power regulation strategy can adapt to changes in grid frequency. In addition, the coupling of voltage, frequency, and harmonics may produce more complex effects than a single disturbance. By simulating scenarios with multiple factors superimposed, the comprehensive adaptability of the PV string inverter 5 under complex grid conditions can be evaluated, avoiding the limitations of a single test scenario. In the electromagnetic transient simulation environment, the dynamic response of the PV string inverter 5 control algorithm during rapid transient events can be captured. Under conditions of harmonic distortion, the effectiveness of the PV string inverter 5's filtering algorithm in suppressing grid-connected current distortion (THD) can be tested. Under conditions of voltage fluctuation, the robustness of the maximum power point tracking (MPPT) algorithm can be evaluated to prevent large fluctuations in power output caused by grid disturbances. Secondly, by simulating the response of the PV string inverter 5 under different grid conditions, control parameters can be adjusted specifically to ensure that it meets grid connection standards under various operating conditions. Directly conducting extreme operating condition testing in an actual grid could cause grid failures or damage equipment. However, the simulation environment can replicate dangerous scenarios under risk-free conditions, ensuring safe testing. Traditional testing relies on actual grid disturbances or the construction of physical test platforms, which is time-consuming and costly. The simulation environment allows for rapid switching between different test scenarios, significantly improving testing efficiency and is particularly suitable for comparing and optimizing multiple solutions during the R&D phase. Overall, the grid simulation module 2 uses multi-dimensional electromagnetic transient simulation to create a controllable, safe, and efficient virtual grid testing environment for grid-connected testing of the PV string inverter 5. This digital approach proactively exposes potential product issues in the actual grid, improving the grid-connected adaptability, reliability, and compliance of the PV string inverter 5 from the outset. This reduces testing costs and accelerates the industrialization of the PV string inverter 5.

[0046] Photovoltaic array simulation module 1: used to build a dynamic deduction model of IV characteristics under different irradiance and temperature gradient effects based on the physical model of the photovoltaic array equivalent circuit, and realize a natural simulation environment with multiple working conditions.

[0047] The PV array simulation module 1 constructs a dynamic IV characteristic deduction model based on an equivalent circuit physical model. This model comprehensively considers the effects of irradiance and temperature gradients, and simulates the actual output characteristics of the PV array under natural conditions. This helps R&D personnel verify the MPPT strategy, power conversion efficiency, and adaptability to extreme operating conditions of the PV string inverter 5 from the DC side. This reduces outdoor testing costs, accelerates product iteration, and ensures the high reliability and power generation efficiency of the PV string inverter 5 during actual grid-connected operation. The PV array simulation module 1 simulates the output characteristics of a real PV array from multiple dimensions during grid-connected testing of the PV string inverter 5. By combining the equivalent circuit model with real-time environmental parameters, the IV characteristics can be dynamically deduced, ensuring that the DC input received by the PV string inverter 5 during testing more closely resembles the output of the actual PV array. Temperature differences between cells within a string can cause offsets in the array's output characteristics. By setting temperature gradient parameters, the PV array simulation module 1 can test the adaptability of the PV string inverter 5 under non-uniform array temperature distribution, thereby avoiding test deviations caused by model simplification. In traditional tests, fixed resistance loads or simple DC power supplies cannot simulate the nonlinear IV characteristics of photovoltaic arrays. Through dynamic IV models, the low-light MPPT efficiency under low irradiance, the tracking speed and accuracy under rapid irradiance changes, and the global optimization capability under multiple peak power points (such as partial shading) can be reproduced in a laboratory environment to avoid falling into local extreme values. In traditional outdoor tests, irradiance and temperature are uncontrollable, and it is difficult to reproduce extreme working conditions. The photovoltaic array simulation module 1 can simulate any environmental parameters indoors all day long, significantly shortening the test cycle. In an actual photovoltaic power station, multiple strings are connected in parallel to the photovoltaic string inverter 5, and each string may output different IV characteristics due to differences in orientation and shading. The photovoltaic array simulation module 1 can set independent irradiance and temperature parameters for multiple strings to test the power aggregation capability of the photovoltaic string inverter 5 when the strings are mismatched, avoiding power loss during on-site parallel operation due to simplified testing. By setting extreme parameters in the PV array simulation module 1, the startup characteristics, efficiency degradation, and long-term reliability of the PV string inverter 5 under extreme conditions can be tested, providing data support for product selection and scenario adaptation. By simulating rapid changes in array characteristics, the PV string inverter 5's ability to prevent islanding during power sags can be tested, as well as its coordinated control of low voltage ride-through and array energy discharge during grid faults, improving system reliability. By coupling physical models with dynamic parameters, the PV array simulation module 1 provides a precisely controlled, fully reproducible natural environment for testing the PV string inverter 5.

[0048] Loading module: used to load the power grid simulation environment and the natural simulation environment into the photovoltaic string inverter 5 to be tested through the synchronous control interface.

[0049] The loading module integrates the grid simulation environment and the natural simulation environment through a synchronous control interface and loads them to the photovoltaic string inverter 5 to be tested. This dual-environment coupling loading mechanism can realize multi-dimensional collaborative verification in the grid-connected test. In actual grid-connected operation, the output characteristics of the photovoltaic array (such as power fluctuations caused by changes in irradiance) and the grid conditions (such as voltage fluctuations and frequency offsets) will affect each other. The loading module can synchronously trigger the dynamic changes of the two. Through the hardware synchronization interface (such as IEEE 1588 clock synchronization and hard-line triggering), the timing consistency of the grid simulation signal and the photovoltaic array simulation signal is ensured to avoid test deviations caused by signal delays. By presetting different grid-photovoltaic array coupling conditions, the loading module can realize the automated cycle of the test process, completing hundreds of sets of working condition verifications in a single day, and improving the efficiency by more than 50% compared with traditional manual step-by-step testing. The loading module can realize the upgrade from single-environment testing to source-grid collaborative verification. The loading module can break the independent testing mode of grid simulation and photovoltaic array simulation, and realize dual-environment coupled loading through synchronous control. This can not only restore the on-site operation scene more realistically, but also expose design defects through parameter linkage and extreme working conditions, and accelerate the optimization of key performance of photovoltaic string inverters.

[0050] Data acquisition module 3: used to monitor the operating status data of the photovoltaic string inverter 5 in real time and construct an operating status data set containing multi-physical quantity coupling characteristics.

[0051] Data acquisition module 3 accurately reflects the dynamic characteristics of PV string inverter 5 during grid-connected operation by collecting multi-physical quantity data such as voltage, current, temperature, and power in real time. The acquisition of coupled characteristics of multiple physical quantities (such as the phase difference between voltage and current, and the correlation between power factor and temperature) can reveal hidden issues that are difficult to detect using traditional single-parameter monitoring. Under varying irradiance levels, temperature gradients, and grid disturbance conditions, data acquisition module 3 can construct a dataset covering the entire operating range.

[0052] Diagnostic module 4: used to input the operating status data set into the trained LSTM neural network model, and obtain the test results of the photovoltaic string inverter 5 through model reasoning.

[0053] The LSTM neural network model excels at processing long-term dependencies in time series data and can perform deep learning on temporal features in operating status datasets (such as historical traces of voltage fluctuations and temperature trends over time). For example, when a grid-connected current anomaly occurs in the PV string inverter 5, the diagnostic module 4 can analyze temporal data such as the voltage fluctuation history and switching frequency changes to distinguish whether the anomaly is caused by a transient grid disturbance or an internal hardware fault in the PV string inverter 5. Compared to traditional threshold judgment (such as an alarm when the current exceeds the rated value), the LSTM neural network model can combine multi-parameter coupling relationships for comprehensive diagnosis. After inputting the dataset into the trained model, the diagnostic module 4 can output the test results in real time, replacing manual data analysis. The model can continuously learn new fault samples and improve diagnostic capabilities through iterative training. When a new topology of the PV string inverter 5 is introduced, the LSTM neural network model can adaptively update the diagnostic rules by simply adding new operating data, reducing reliance on manual experience. The LSTM model trained based on historical data can predict potential faults in the PV string inverter 5. By analyzing long-term trends in parameters like capacitor voltage ripple and switching loss, the LSTM neural network model can provide early warning of capacitor aging risks, helping R&D personnel optimize circuit design or develop maintenance plans to reduce the probability of field failures. The data analysis results from the diagnostic module 4 can guide the optimization of the control strategy for the photovoltaic string inverter 5. For example, by analyzing power output fluctuations under low irradiance, the model can identify weak links in the control algorithm, assisting engineers in adjusting PI parameters or optimizing the MPPT strategy to improve system efficiency.

[0054] When the data module and the diagnostic module 4 are used together, a closed-loop empowerment from data collection to intelligent diagnosis can be achieved. The data acquisition module 3 provides high-fidelity operating data, and the diagnostic module 4 mines the data value through AI algorithms to form a closed loop of monitoring-analysis-optimization. Through the accumulation of data sets and model iteration, extreme working conditions that are difficult to reproduce in reality (such as violent oscillations of the photovoltaic array caused by continuous strong gusts of wind) can be simulated, reducing the number of physical tests, reducing hardware loss and time costs, and covering more comprehensive risk scenarios. In general, the combination of the data acquisition module 3 and the diagnostic module 4 not only improves the efficiency and accuracy of the grid-connected test, but also provides core support for the reliability optimization, fault prediction and performance iteration of the photovoltaic string inverter 5 through data-driven intelligent analysis, and promotes the development of photovoltaic grid-connected technology towards intelligence and high reliability.

[0055] The test system provided by the present invention can also be used in conjunction with a host computer. During the grid-connected test, after the user starts the test through the host computer system, the automated test platform synchronously sends control instructions to the power grid simulation module 2 and the photovoltaic array simulation module 1, respectively constructing the abnormal power grid environment and the photovoltaic array multi-operating condition scenario. The data acquisition module 3 synchronously captures the key parameters such as voltage, current, power and protection action of the photovoltaic string inverter 5. The diagnosis module 4 uses an LSTM neural network to extract abnormal features of the collected waveform, combines the historical operation database for pattern matching, and finally generates efficiency optimization suggestions and recommends the optimal working point, realizing a closed-loop process from test execution to analysis and optimization. The entire system effectively solves the problem of robustness testing of the photovoltaic string inverter 5 under complex working conditions through a multi-module collaborative working mechanism. Its innovation lies in the deep integration of power grid simulation, photovoltaic simulation, real-time simulation and AI diagnostic technology to form a standardized and intelligent testing system.

[0056] In one embodiment of the present invention, the power grid simulation module 2 includes a simulated power source, a simulated load, a fault injection unit, a measurement module, and a control module.

[0057] Simulated power supply: used to generate voltage and current similar to the actual power grid.

[0058] The simulated power supply first converts AC power into DC power, and then converts DC power into controllable AC power. This controllable AC power precisely controls the voltage and current output of the simulated power supply, generating voltage and current waveforms consistent with the actual power grid. This simulates the standard characteristics of different power grids and ensures the compatibility of the PV string inverter 5 in various power grid environments. Furthermore, the simulated power supply can precisely control dynamic processes such as voltage swells and sags and frequency jumps.

[0059] Simulated load: used to simulate the power load of the actual power grid. By adjusting the parameters of the power load, the operation of the power grid under different load conditions can be simulated.

[0060] The simulated load includes resistive load, inductive load, capacitive load and their combination. By adjusting the parameters of each type of load, the purpose of adjustable power load is achieved. Alternatively, by adjusting the active / reactive parameters of the simulated load (such as a combination of resistance, inductance, and capacitance), the grid load characteristics in different scenarios such as residential electricity consumption, industrial load, and weak grid impedance can be reproduced. The efficiency characteristics of the photovoltaic string inverter 5 at different power outputs are tested by controlling the active power consumption through the simulated load, and the reactive power compensation capability of the photovoltaic string inverter 5 is tested by adjusting the reactive power of the simulated load.

[0061] Fault injection unit: used to inject faults into the power grid simulation environment composed of simulated power supply and simulated load, so that the power grid simulation environment has at least one of voltage fluctuation, frequency deviation and harmonic distortion.

[0062] The fault injection unit can inject faults such as three-phase voltage imbalance, voltage swell, and voltage sag, causing the grid voltage to fluctuate within ±20% to verify the voltage tolerance limit of the PV string inverter 5. The fault injection unit can also inject frequency deviations to simulate conditions where the grid frequency is not within the rated frequency, such as 45-65Hz, to test the frequency adaptability of the PV string inverter 5. The fault injection unit can also inject harmonics to control the THD between 0% and 30% to test the PV string inverter 5 control algorithm's ability to suppress harmonics.

[0063] By simulating the power supply to provide a basic grid environment, simulating the load to reproduce the real load scenario, and the fault injection unit to introduce abnormal working conditions, the combination of the three can cover the full-scenario requirements of the grid-connected operation of the photovoltaic string inverter 5. For example, when testing the "low voltage ride-through + harmonic suppression" composite capability of the photovoltaic string inverter 5, a voltage drop can be injected through the simulated power supply, and harmonic current can be generated by the simulated load at the same time to simultaneously verify the operating stability of the photovoltaic string inverter 5 under multiple disturbances. The grid simulation module 2 can provide a controllable, repeatable, and full-scenario test environment for the grid-connected test of the photovoltaic string inverter 5 through the coordinated mechanism of grid environment simulation, load scenario simulation, and fault condition injection. It can not only ensure that the photovoltaic string inverter 5 meets the grid specification requirements, but also pass the robustness test under extreme working conditions.

[0064] Measurement module: used to monitor and record the operation data of the power grid simulation environment in real time.

[0065] The measurement module collects key parameters such as voltage, current, power, and harmonics in real time (sampling rate ≥ 10kHz) within the grid simulation environment. For example, during a voltage sag, it monitors the voltage recovery time and reactive power compensation of the photovoltaic string inverter 5; during harmonic injection, it records the grid-connected current THD, harmonic amplitude, and phase offset. High-precision measurements ensure data accuracy and real-time performance. The measurement module also collects waveform data during transient processes, such as voltage drops, transient response to voltage recovery, overvoltage protection action time, and active power regulation rate.

[0066] Control module: used to adjust the simulated power supply and simulated load through preset operating rules and parameters.

[0067] The control module can customize the working condition programming to achieve accurate reproduction of complex scenarios. Through preset operating rules, it can combine various power grid working conditions.

[0068] In this embodiment, through the linkage of the measurement module and the control module, real-time feedback adjustment can be performed to enhance the authenticity of the power grid simulation environment. The control module can dynamically adjust the power grid operating conditions according to the real-time operating data of the measurement module to form a closed-loop controlled power grid environment simulation. Through this closed-loop control, the power grid simulation scenario is closer to the nonlinear and time-varying characteristics of the actual power grid, avoiding the evaluation deviation caused by static simulation.

[0069] In one embodiment of the present invention, the photovoltaic array simulation module 1 includes a rectifier circuit, a DC / DC conversion circuit, a control circuit, a protection circuit, and a filter circuit.

[0070] Rectifier circuit: used to convert AC power into DC power.

[0071] DC / DC conversion circuit: used to convert the fixed voltage and current of the DC power generated by the rectifier circuit into adjustable voltage and current, simulating the IV curve of the photovoltaic array under different irradiance and temperature gradient effects.

[0072] The DC / DC converter circuit adjusts the output voltage and current according to varying irradiance and temperature gradients, accurately simulating the current-voltage (IV) characteristic curve of a photovoltaic array under actual operating conditions. For example, as temperature rises, the simulation circuit reduces the output voltage and adjusts the current, recreating the actual efficiency degradation of a photovoltaic panel. This ensures that the MPPT (maximum power point tracking) algorithm of the photovoltaic string inverter 5 is effectively tested under different light and temperature conditions.

[0073] Control circuit: used to collect the actual values ​​of the output voltage and current of the DC / DC conversion circuit through the sampling load, adjust the output voltage and current of the DC / DC conversion circuit according to the actual values, and determine the voltage range and maximum power point step speed of the DC / DC conversion circuit.

[0074] The control circuit samples load data in real time and dynamically adjusts the voltage / current output range and maximum power point step speed, ensuring that the simulated IV curve more closely matches the dynamic response characteristics of an actual PV array, thus preventing the test environment from being disconnected from the real-world scenario. Combining rectifier and filter circuits, the system can simulate voltage and current fluctuations in the PV array during periods of varying light intensity, such as early morning and dusk, as well as the effects of partial shading caused by cloud cover. For example, by adjusting the output parameters of the DC / DC converter circuit, the multi-peak IV curve of the PV array under partial shading can be simulated to test the MPPT tracking accuracy and stability of the PV string inverter 5 under complex operating conditions.

[0075] Protection circuit: used to prevent overcurrent and overvoltage in the rectifier circuit, DC / DC conversion circuit and control circuit.

[0076] The protection circuit can monitor the current / voltage values ​​of the rectifier circuit and DC / DC conversion circuit in real time. When an abnormality occurs (such as a short-circuit current caused by a failure of the photovoltaic string inverter 5), it will immediately cut off the circuit or limit the output to avoid damage to the test equipment due to overcurrent / overvoltage. At the same time, it prevents hardware damage caused by the operation of the photovoltaic string inverter 5 under abnormal working conditions, thereby improving the safety of the test process.

[0077] Filter circuit: used to reduce the ripple of voltage and current output by DC / DC conversion circuit.

[0078] The filter circuit reduces the voltage and current ripple output by the DC / DC converter circuit, preventing high-frequency noise from interfering with the control chip and sampling circuit of the photovoltaic string inverter 5. For example, when testing the grid-connected current harmonic characteristics of the photovoltaic string inverter 5, the stable DC input ensures more accurate AC power quality data output by the photovoltaic string inverter 5, avoiding test result deviations caused by simulated source ripple.

[0079] In this embodiment, the photovoltaic array simulation module 1 realizes the digital reproduction of the photovoltaic array characteristics through the coordination of circuit design and control logic, which not only ensures the safety and standardization of grid-connected testing, but also covers the full-dimensional testing requirements from normal operating conditions to extreme scenarios, and provides efficient and reliable technical support for the performance optimization, fault diagnosis and certification compliance of the photovoltaic string inverter 5.

[0080] In one embodiment of the present invention, a dynamic tracking efficiency quantification module is further included.

[0081] Dynamic tracking efficiency quantification module: This module measures the efficiency of the maximum power point dynamic tracking process by comparing the energy obtained by actual power integration with the energy that should be obtained under ideal conditions by ideal power integration within a specific time interval. The actual power integration reflects the actual energy acquisition under actual influencing factors; the ideal power integration is the energy benchmark without any adverse factors. The maximum power point dynamic tracking efficiency is quantified by the percentage ratio of the two.

[0082] In this embodiment, the dynamic tracking efficiency quantification module quantifies the maximum power point dynamic tracking efficiency by comparing energy integration, providing an accurate efficiency assessment tool for grid-connected testing of PV string inverter 5. By using a quantitative method of comparing theoretical and actual energy, the dynamic tracking efficiency quantification module fills the gap in dynamic performance evaluation in traditional MPPT testing and provides an accurate efficiency metric for design optimization, certification, and compliance of PV string inverter 5.

[0083] In one embodiment of the present invention, the data acquisition module 3 includes a data collector, a data processing unit and a data storage unit.

[0084] Data collector: used to collect operating data of the photovoltaic string inverter 5 through a synchronous acquisition channel. The operating data includes voltage, current, power and protection action parameters.

[0085] The data collector is a high-speed acquisition unit that uses 16-channel synchronous acquisition with an acquisition accuracy of ±0.05% and a bandwidth of DC-500KHz to capture high-frequency switching harmonics. It can capture data at regular intervals or in real time to ensure data accuracy and timeliness.

[0086] Data processing unit: used to pre-process the operation data and then couple the physical quantities to obtain the operation status data set.

[0087] The data processing unit preprocesses the collected data, including data cleaning and format conversion. This step aims to improve data quality and lay the foundation for subsequent data storage and analysis. After preprocessing, a multidimensional feature vector is constructed by coupling physical quantities. For example, parameters such as the three-phase voltage RMS values, current harmonic components, and DC-side voltage fluctuations are coupled to generate a feature set reflecting grid compatibility. A heat loss model is then developed, combining power output with ambient temperature, to evaluate the heat dissipation efficiency of the PV string inverter 5 under different loads.

[0088] Data storage unit: used to store the running status data set in the database.

[0089] The data storage unit is responsible for storing the processed data in the database. During the storage process, it is necessary to define the data tables in the database, define the connection relationship between data tables, insert data, and other functions.

[0090] In this embodiment, the data acquisition module 3, through a full-process design encompassing synchronous data acquisition, coupled analysis, and data storage, not only provides high-precision real-time monitoring capabilities for grid-connected testing but also supports full lifecycle management, from design verification and fault diagnosis to long-term operation and maintenance, through the accumulation of data assets. By coupling dispersed physical quantities into a correlated knowledge graph, the operating status of the PV string inverter 5 becomes quantifiable, traceable, and optimizable, ultimately improving the reliability, efficiency, and cost-effectiveness of grid-connected testing.

[0091] In one embodiment of the present invention, the diagnosis module 4 includes a data reading module, a feature extraction module and a fault diagnosis module 4 .

[0092] Data reading module: used to read the operating status data set in the database.

[0093] Feature extraction module: used to extract relevant features for fault diagnosis of photovoltaic string inverter 5 from the operating status data set, including voltage fluctuation, current harmonics, power factor, and temperature anomaly.

[0094] Fault diagnosis module 4: used to input the associated features into the trained LSTM neural network model and perform pattern matching in combination with the historical operation database to obtain the test results of the photovoltaic string inverter 5.

[0095] In this embodiment, by extracting correlated features such as voltage fluctuations, current harmonics, power factor, and temperature anomalies, the electrical performance and thermal stability issues of the PV string inverter 5 during grid-connected operation can be addressed. Feature extraction correlates real-time operating data with historical data, enabling the detection of hidden fault signs of the PV string inverter 5 under varying loads and environmental conditions. An LSTM neural network is integrated with historical data to enable intelligent fault location. Integrating historical operating data, the model can establish a fault pattern library, enabling dual diagnosis through data-driven and empirical reasoning. By continuously monitoring operating status features, early warnings can be issued at the incipient stage of a fault. After inputting these features into the model, the test results can be quantified into specific indicators, facilitating performance comparisons of different PV string inverters 5. Traditional manual diagnosis relies on engineer experience and is susceptible to subjective factors. However, the diagnostic module 4 eliminates human oversight through standardized feature extraction and model calculation. Combined with the data acquisition and storage modules, the diagnostic module 4 implements a closed "acquisition-processing-diagnosis" loop, generating test reports without manual intervention. By diagnosing the characteristic responses of the PV string inverter 5 under fault injection (such as voltage fluctuations and frequency offsets), its impact on the grid can be assessed. During the grid-connected test, the diagnostic module 4 can provide real-time monitoring and early warning of potential safety hazards such as overvoltage, overcurrent, and islanding effects, enabling timely measures to prevent accidents and ensure the safety of test personnel and devices. The diagnostic module 4 provides full-chain support for the PV string inverter 5, from fault warning and location to performance optimization. This not only improves the efficiency and accuracy of grid-connected testing, but also ensures the safety and reliability of the PV system after it is connected to the grid.

[0096] In one embodiment of the present invention, an optimization module is further included.

[0097] Optimization module: used for deviation analysis and feature extraction based on test results, and generates optimization strategies including parameter optimization, fault warning and efficiency improvement.

[0098] Based on deviation analysis of test results, the optimization module automatically generates parameter adjustment strategies. For different grid conditions, the optimization module can combine fault injection test data to generate customized parameter solutions. By identifying early fault signs through feature extraction, the optimization module generates early warning strategies and coordinates the control module to adjust the operating mode. Based on the fault injection test results from the grid simulation module 2, the optimization module generates an improved control strategy for the PV string inverter 5. Integrating the IV curve characteristics of the PV array simulation module 1, the optimization module matches the parameters of the PV string inverter 5 with the PV array, avoiding efficiency losses caused by array characteristic drift. By accumulating optimization cases from different scenarios, the optimization module forms a standardized knowledge base, providing data support for next-generation product development. The optimization module can also rapidly simulate test scenarios under new regulations and generate adaptive strategies. Through intelligent logic from data deviation analysis to feature modeling to strategy generation, the optimization module upgrades grid-connection testing from result verification to a closed-loop process for performance improvement, quickly identifying defects in the grid-connected operation of the PV string inverter 5.

[0099] In one embodiment of the present invention, a real-time simulation module is also included.

[0100] Real-time simulation module: used to verify the dynamic performance of the photovoltaic string inverter 5 based on the digital twin technology using the simulation engine.

[0101] The real-time simulation module leverages digital twin technology to replicate scenarios difficult to achieve with traditional physical testing, eliminating the cost of expensive environmental chamber construction and the wait times for extreme weather conditions. Based on a full-link digital twin model of the PV array, PV string inverter 5 topology, and control algorithms, real-time simulation can capture component-level defects. The real-time simulation module connects to the actual PV string inverter 5 controller hardware, inputting the simulated PV array IV curve and grid disturbance signals into the controller while simultaneously collecting the PWM signals output by the controller to drive the simulation circuit, forming a "digital-physical" closed loop. Real-time simulation simulates the dynamic response of the PV string inverter 5 as it participates in grid frequency and voltage regulation. Physical testing requires multiple starts and stops of the PV string inverter 5 to switch between operating modes, which can cause component wear. However, real-time simulation allows for unlimited repeatability, with each simulation taking only a few minutes. The real-time simulation module covers extreme operating conditions and long-term reliability testing in a low-cost, highly secure manner. It exposes design flaws in advance through digital models and accelerates the test-iteration closed-loop process by combining hardware-in-the-loop and parameter optimization. Ultimately, it provides technical support for high-reliability grid connection, grid interactivity optimization, and full lifecycle cost control of photovoltaic string inverters.

[0102] The above description is merely a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be based on the scope of protection of the claims.

Claims

1. A multi-dimensional grid-connected testing system for photovoltaic string inverters, characterized in that: include: Power Grid Simulation Module: Used to build a power grid simulation environment with complex electromagnetic transient characteristics based on the multi-dimensional coupling mechanism of voltage fluctuation, frequency offset and harmonic distortion; Photovoltaic array simulation module: used to build a dynamic deduction model of IV characteristics under different irradiance and temperature gradient effects based on the physical model of the photovoltaic array equivalent circuit, realizing a natural simulation environment with multiple working conditions; Loading module: used to load the grid simulation environment and natural simulation environment into the PV string inverter to be tested through the synchronous control interface; Data acquisition module: used to monitor the operating status data of photovoltaic string inverters in real time and build an operating status data set containing multi-physical quantity coupling characteristics; and Diagnostic module: used to input the operating status dataset into the trained LSTM neural network model and obtain the test results of the PV string inverter through model inference.

2. A photovoltaic string inverter multi-dimensional grid-connected testing system according to claim 1, characterized in that: The power grid simulation module includes: Simulated power supply: used to generate voltage and current similar to the actual power grid; Simulated load: used to simulate the power load of the actual power grid. By adjusting the parameters of the power load, the operation of the power grid under different load conditions can be simulated. Fault injection unit: used to inject faults into the power grid simulation environment composed of simulated power supply and simulated load, so that the power grid simulation environment has at least one of voltage fluctuation, frequency deviation and harmonic distortion.

3. A photovoltaic string inverter multi-dimensional grid-connected testing system according to claim 2, characterized in that: The power grid simulation module also includes: Measurement module: used to monitor and record the operation data of the power grid simulation environment in real time; Control module: used to adjust the simulated power supply and simulated load through preset operating rules and parameters.

4. A photovoltaic string inverter multi-dimensional grid-connected testing system according to claim 3, characterized in that: The photovoltaic array simulation module includes: Rectifier circuit: used to convert AC power into DC power; DC / DC conversion circuit: used to convert the fixed voltage and current of the DC power generated by the rectifier circuit into adjustable voltage and current, simulating the IV curve of the photovoltaic array under different irradiance and temperature gradient effects.

5. A photovoltaic string inverter multi-dimensional grid-connected testing system according to claim 4, characterized in that: The photovoltaic array simulation module further includes: Control circuit: used to collect the actual values ​​of the output voltage and current of the DC / DC conversion circuit through the sampling load, adjust the output voltage and current of the DC / DC conversion circuit according to the actual values, and determine the voltage range and maximum power point step speed of the DC / DC conversion circuit; Protection circuit: used to prevent overcurrent and overvoltage in the rectifier circuit, DC / DC conversion circuit and control circuit; Filter circuit: used to reduce the ripple of voltage and current output by DC / DC conversion circuit.

6. A photovoltaic string inverter multi-dimensional grid-connected testing system according to claim 5, characterized in that: It also includes a dynamic tracking efficiency quantification module, The dynamic tracking efficiency quantification module is used to measure the efficiency of the maximum power point dynamic tracking process by comparing the energy obtained by actual power integration with the energy that should be obtained under ideal conditions by ideal power integration within a specific time interval. The actual power integration reflects the actual energy acquisition under actual influencing factors; the ideal power integration is the energy benchmark without any adverse factors. The maximum power point dynamic tracking efficiency is quantified by the percentage ratio of the two.

7. A photovoltaic string inverter multi-dimensional grid-connected testing system according to claim 6, characterized in that: The data acquisition module includes: Data collector: used to collect operating data of photovoltaic string inverters through synchronous acquisition channels, the operating data including voltage, current, power and protection action parameters; Data processing unit: used to pre-process the operation data and then perform physical quantity coupling to obtain the operation status data set; Data storage unit: used to store the running status data set in the database.

8. A photovoltaic string inverter multi-dimensional grid-connected testing system according to claim 7, characterized in that: The diagnostic module includes: Data reading module: used to read the operating status data set in the database; Feature extraction module: used to extract relevant features for fault diagnosis of photovoltaic string inverters from the operating status data set, including voltage fluctuations, current harmonics, power factor, and temperature anomalies; Fault diagnosis module: used to input the associated features into the trained LSTM neural network model and perform pattern matching in combination with the historical operation database to obtain the test results of the photovoltaic string inverter.

9. A photovoltaic string inverter multi-dimensional grid-connected testing system according to claim 8, characterized in that: Also includes optimization modules, The optimization module is used to generate an optimization strategy including parameter optimization, fault warning and efficiency improvement based on deviation analysis and feature extraction of test results.

10. A photovoltaic string inverter multi-dimensional grid-connected testing system according to claim 9, characterized in that: Also includes real-time simulation module, The real-time simulation module is used to verify the dynamic performance of the photovoltaic string inverter based on the digital twin technology using a simulation engine.

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