Photovoltaic booster station SVG on-load test method, system, device and medium

Abstract

The invention belongs to the technical field of electrical debugging, and discloses a photovoltaic booster station SVG on-load test method, system and device and a medium. The method comprises the following steps: checking and debugging SVG equipment and secondary equipment in the photovoltaic booster station; setting a plurality of working condition simulation schemes, performing reactive current output by the SVG, and performing on-load test on secondary equipment; acquiring actual measurement data of each secondary device, and carrying out multi-dimensional comparison on the actual measurement data and the theoretical calculation data to obtain a test result of each secondary device; and smoothly switching different operation conditions according to the various condition simulation schemes to obtain a test result under each condition, and analyzing all the test results to obtain a test result. According to the invention, multi-interval and multi-device simultaneous testing is supported. The SVG has overcurrent, overvoltage, overheating and other protection functions, the controllability of the test process is high, the risk is low, smooth adjustment can be achieved, and current sudden change impact is avoided.

Description

Technical Field

[0001] This invention relates to the field of electrical commissioning technology, and in particular to a method, system, equipment, and medium for testing photovoltaic booster substations under load. Background Technology

[0002] Before a photovoltaic booster station is put into operation, the accuracy and integrity of the wiring of secondary equipment (such as relay protection devices, measuring instruments, remote control devices, etc.) must be verified. Current and voltage tests can only check individual bays and cannot verify their integrity; the main transformer short-circuit test has limitations if the CT ratio is too large, the secondary circuit current cannot be displayed or the display is inaccurate; traditional load testing methods require connecting to a real active load or using voltage regulators, transformers, and other equipment to simulate the load, which is not only complicated in wiring and time-consuming, but also has problems such as insufficient capacity, low regulation accuracy, and inability to simulate different operating conditions. Summary of the Invention

[0003] This invention provides a method, system, equipment, and medium for testing photovoltaic booster substations using SVG (Static Var Generator) under load. By utilizing the controllable reactive current output of the SVG, different operating conditions are simulated without connecting an actual active load. The amplitude and phase relationship of the current and voltage of each secondary device in the substation are examined through testing to verify the correctness and integrity of the secondary device and circuit wiring.

[0004] According to one aspect of the present invention, a method for testing photovoltaic booster substations under load is provided, comprising: Inspect and debug the SVG equipment and secondary equipment in the photovoltaic booster station; Multiple operating condition simulation schemes are set up, and the SVG outputs reactive current to perform load testing on secondary equipment. The actual measurement data of each secondary device is collected and compared with the theoretical calculation data in multiple dimensions to obtain the test results of each secondary device; By smoothly switching between different operating conditions using various operating condition simulation schemes, test results are obtained for each operating condition. All test results are then analyzed to obtain the experimental results.

[0005] In some embodiments, the multiple operating conditions include: Steady-state reactive power compensation conditions under light and heavy loads; Under conditions of voltage fluctuations and reactive power abrupt changes, a time-varying impedance network is used to synchronously trigger voltage amplitude / phase abrupt changes and reactive power step changes. Under the reactive power compensation condition of harmonic interference, an interaction model of harmonic current and reactive power is established based on the multi-band harmonic decomposition algorithm to optimize harmonic suppression and reactive power compensation. Extreme operating conditions with multi-physics coupling: A multi-physics coupling model integrating temperature, electromagnetic field and mechanical stress is used to simulate sudden changes in equipment thermal stress caused by overload, short circuit and harmonic superposition. In some embodiments, the process of setting up multiple working condition simulation schemes includes: Acquire historical operating data of photovoltaic booster stations, including grid load and meteorological data; By extracting the diurnal fluctuation pattern of grid load through time series analysis, a mapping relationship between meteorological data and inverter reactive power output is established. Obtain the patterns of multiple operating conditions, transform these patterns into test constraints, and obtain the mapping between failure modes and test requirements; The mapping between the fault modes and test requirements is used to generate an optimal operating condition sequence through the Q-learning algorithm, which serves as the operating condition simulation scheme.

[0006] In some embodiments, the process of the SVG outputting reactive current to perform load testing on secondary equipment includes: The SVG injects reactive current into the bus according to the set value and maintains output stability through closed-loop control. Maintain stable output for a preset time to sample data for load testing of secondary equipment.

[0007] In some embodiments, the process of collecting actual measurement data from each secondary device and comparing it with theoretical calculation data in multiple dimensions to obtain the test results of each secondary device includes: The actual measurement data and theoretical calculation data are used to calculate waveform similarity using a dynamic time warping algorithm; The actual measurement data and theoretical calculation data with waveform similarity exceeding the threshold are subjected to Fast Fourier Transform to obtain the frequency domain harmonic deviation evaluation results; The statistical characteristic consistency test was performed on the frequency domain harmonic deviation assessment results to obtain the mean deviation and variance deviation. Anomaly detection is performed on data that meet the thresholds for mean deviation and variance deviation, and anomaly detection reports are obtained as the test results for each secondary device.

[0008] In some embodiments, the process of analyzing all test results to obtain experimental results includes: Cluster analysis was performed on multiple test data under the same working condition to calculate the dispersion index of each cluster and label the discrete cluster data. The system calculates the compliance rate of equipment response parameters, generates a radar chart to compare the deviation between actual values ​​and benchmark values, correlates the marked discrete cluster data with equipment logs, locates potential fault points, and obtains performance evaluation results. The performance evaluation results will be used to generate a traceable test report document, which will serve as the test outcome.

[0009] In some embodiments, the process of inspecting and debugging the SVG equipment and secondary equipment in the photovoltaic booster station includes: Perform a functional self-test on the SVG device; Check the data mapping relationship between the secondary device and the SVG device through the communication interface; Static debugging is performed on the secondary equipment to calibrate the sampling accuracy of the measurement and control unit.

[0010] This invention proposes a photovoltaic booster station SVG load test system, comprising: The inspection unit is configured to inspect and debug the SVG equipment and secondary equipment in the photovoltaic booster station; The simulation unit is configured to set up various operating condition simulation schemes, and the SVG outputs reactive current to perform load testing for secondary equipment. The comparison unit is configured to collect actual measurement data from each secondary device and compare it with theoretical calculation data in multiple dimensions to obtain the test results of each secondary device. The switching unit is configured to smoothly switch between different operating conditions according to multiple operating condition simulation schemes, obtain test results under each operating condition, analyze all test results, and obtain experimental results.

[0011] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, which enables the at least one processor to perform the photovoltaic booster station SVG load test method according to any embodiment of the present invention.

[0012] According to another aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing computer instructions for causing a processor to execute and implement the photovoltaic booster station SVG load test method according to any embodiment of the present invention.

[0013] The technical solution of this invention includes the following method: The SVG equipment and secondary equipment in the photovoltaic booster station were inspected and debugged; multiple operating condition simulation schemes were set up, and the SVG output reactive current to conduct load tests on the secondary equipment; actual measurement data of each secondary equipment were collected and compared with theoretical calculation data in multiple dimensions to obtain the test results of each secondary equipment; different operating conditions were smoothly switched according to multiple operating condition simulation schemes to obtain the test results under each operating condition, and all test results were analyzed to obtain the experimental results.

[0014] This invention requires no actual load, eliminating the need for purchasing, transporting, and installing high-power load equipment, significantly reducing testing costs and site requirements. Precise and controllable reactive power output allows for precise control of the reactive current amplitude, phase, and power factor; rapid switching between multiple operating states improves testing efficiency; and it supports simultaneous testing of multiple intervals and devices. The SVG (Static Var Generator) incorporates overcurrent, overvoltage, and overheat protection functions, ensuring high controllability and low risk during the testing process, enabling smooth adjustment and avoiding sudden current surges.

[0015] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 The flowchart of the photovoltaic booster station SVG load test method provided by the present invention.

[0018] Figure 2 A module diagram of the SVG load test system for photovoltaic booster stations provided by the present invention.

[0019] Figure 3 A schematic diagram of the structure of an embodiment of the computer device provided by the present invention.

[0020] Figure 4 This is a schematic diagram of an embodiment of the computer-readable storage medium provided by the present invention.

[0021] Figure 5 A schematic diagram of the primary wiring of a photovoltaic booster station for the SVG load test method provided by the present invention.

[0022] Figure 6 This is a flowchart of an embodiment of the photovoltaic booster station SVG load test method provided by the present invention.

[0023] Figure 7 The photovoltaic booster station SVG load test report diagram is provided for the photovoltaic booster station SVG load test method provided by the present invention. Detailed Implementation

[0024] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. 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 should fall within the scope of protection of the present invention.

[0025] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "including" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that includes a series of steps or units is not necessarily limited to those explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0026] As a flexible reactive power compensation device, SVG can quickly and accurately output controllable reactive current. It is commonly used in photovoltaic power plants to stabilize bus voltage and improve power factor, making it an essential device for photovoltaic power plants. This invention utilizes SVG to simulate different load conditions during the power receiving phase of the substation, providing ideal conditions for load testing of secondary equipment.

[0027] In the photovoltaic step-up substation of a large-scale photovoltaic power plant, a comprehensive and in-depth performance evaluation of the secondary equipment is necessary to ensure the stable operation and efficient power generation of the entire power plant. This photovoltaic power plant is large-scale, with an installed capacity of hundreds of megawatts. As a key hub connecting the power plant to the grid, the photovoltaic step-up substation undertakes important functions such as voltage transformation, energy metering, and protection control. The substation contains a wide variety of secondary equipment, including relay protection devices, measurement and control devices, and energy metering devices. The performance of these devices directly affects the safe and stable operation of the step-up substation and even the entire photovoltaic power plant. As the power plant's operating time increases, some secondary equipment gradually exhibits performance degradation and abnormal response issues.

[0028] Before the evaluation began, a test environment was set up to simulate common operating conditions of photovoltaic booster stations—sudden changes in sunlight intensity causing significant fluctuations in photovoltaic power generation, while short-term voltage fluctuations occurred on the grid side. Under this condition, various secondary devices underwent repeated tests, with intervals between each test to ensure data independence. A high-precision data acquisition system recorded the response parameters of each secondary device at different times, the operating time of relay protection devices, the measurement accuracy of monitoring and control devices, and the errors of power metering devices. After several days of continuous testing, a large amount of rich and representative test data was accumulated.

[0029] After acquiring massive amounts of test data, clustering analysis algorithms were first applied to process multiple test data under the same operating conditions. The clustering algorithm divides the test data into multiple distinct clusters based on the similarity between the data points. During the division process, the algorithm comprehensively considers multiple dimensions of the response parameters of each device, such as numerical magnitude and trends. After clustering, the dispersion index of each cluster is calculated, reflecting the degree of data dispersion within the cluster. By setting a reasonable threshold, discrete clusters with significantly higher dispersion than other clusters are identified. These discrete clusters indicate that the response of the secondary equipment exhibited abnormal fluctuations during the corresponding test process.

[0030] For the response parameters of each secondary device, the compliance rate is calculated based on pre-set industry standards and equipment technical specifications. The compliance rate directly reflects the degree to which the equipment response parameters meet the standard requirements, providing a quantitative indicator for evaluating equipment performance. For the operating time of relay protection devices, if the standard requires the operating time to not exceed 100ms under specific fault conditions, but the operating time of some data in actual testing exceeds this standard, calculating the compliance rate clearly shows what percentage of the test data meets the requirements and what percentage exceeds the standard.

[0031] Radar charts plot actual and baseline values ​​for each of the device's response parameters, distinguished by different colored lines or areas. The radar chart clearly shows the device's performance across various parameters, identifying which parameters deviate significantly from the baseline and which perform well. If the error parameters of the electricity metering device deviate significantly from the baseline on the radar chart, it indicates a problem with the device's metering accuracy, requiring close monitoring. Within a specific time period corresponding to a discrete cluster of data, the equipment log records a fault alarm from a sensor in the measurement and control device. Combined with the abnormal fluctuations in the measurement parameters of this device in the discrete cluster data, it can be preliminarily determined that the sensor fault is the cause of the data anomaly. The performance evaluation results generate a traceable test report document, recording relevant data charts.

[0032] According to one aspect of the present invention, a method for testing photovoltaic booster stations (SVG) under load is provided; please refer to [reference needed]. Figure 1 ,include: S1. Inspect and debug the SVG equipment and secondary equipment in the photovoltaic booster station; S2. Set up multiple operating condition simulation schemes, and SVG outputs reactive current to perform load testing on secondary equipment; S3. Collect the actual measurement data of each secondary device and compare it with the theoretical calculation data in multiple dimensions to obtain the test results of each secondary device. S4. Smoothly switch between different operating conditions according to multiple operating condition simulation schemes, obtain the test results under each operating condition, analyze all the test results, and obtain the experimental results.

[0033] This invention addresses the fundamental role of inspecting and debugging SVG (Static Var Generator) equipment and secondary equipment in ensuring their normal operation. A comprehensive and meticulous inspection allows for the timely detection of potential problems, such as worn components and loose wiring connections, enabling proactive repair and replacement. This prevents equipment malfunctions during operation, reducing power outages and maintenance costs. Debugging ensures that all equipment parameters are set appropriately and operate accurately according to design requirements. By setting up various operating condition simulations and conducting reactive current output tests on the SVG for load testing of the secondary equipment, the performance and responsiveness of the secondary equipment under complex operating conditions are comprehensively verified. This helps identify potential problems during actual operation, allowing for proactive optimization and improvement, thereby enhancing the equipment's reliability and stability.

[0034] By collecting actual measurement data from various secondary devices and comparing it with theoretical calculation data in multiple dimensions, the measurement accuracy and operational status of the secondary devices can be accurately assessed. This comparative analysis allows for the timely detection of measurement errors, determining whether they are within a reasonable range. If the errors exceed the range, the problem can be quickly located, allowing for targeted calibration and adjustments to ensure the accuracy of the equipment measurement data and provide a reliable basis for the operation monitoring and decision-making of photovoltaic booster stations. By smoothly switching between different operating conditions based on various simulation schemes and analyzing the test results, a comprehensive understanding of the equipment's adaptability and performance variation patterns under different operating conditions can be achieved.

[0035] In some embodiments, the multiple operating conditions include: Steady-state reactive power compensation conditions under light and heavy loads; Under conditions of voltage fluctuations and reactive power abrupt changes, a time-varying impedance network is used to synchronously trigger voltage amplitude / phase abrupt changes and reactive power step changes. Under the reactive power compensation condition of harmonic interference, an interaction model of harmonic current and reactive power is established based on the multi-band harmonic decomposition algorithm to optimize harmonic suppression and reactive power compensation. Extreme operating conditions with multi-physics coupling: A multi-physics coupling model integrating temperature, electromagnetic field and mechanical stress is used to simulate sudden changes in equipment thermal stress caused by overload, short circuit and harmonic superposition.

[0036] This invention accurately simulates the normal operating conditions of a photovoltaic booster station under different load levels, demonstrating steady-state reactive power compensation under both light and heavy loads. Under light load, the system's reactive power demand is relatively low, while under heavy load, the demand increases significantly. By testing under these various conditions, the steady-state reactive power compensation capability of the SVG equipment under different load intensities can be comprehensively verified, ensuring that it can stably output appropriate reactive current in various daily operating scenarios, maintaining system voltage stability and improving power quality. Simultaneously, it also verifies the monitoring and control accuracy of secondary equipment under these steady-state conditions, guaranteeing the reliability and stability of the entire system during normal operation.

[0037] Voltage fluctuations and reactive power surges present significant challenges. By using a time-varying impedance network to synchronously trigger voltage amplitude / phase surges and reactive power step jumps, the system highly replicates sudden faults or anomalies that may occur in a real power grid. Under these extreme conditions, SVG devices need to respond rapidly to changes in voltage and reactive power, adjusting their output in a timely manner to maintain system stability.

[0038] The reactive power compensation condition under harmonic interference closely reflects the increasingly prominent harmonic problems in modern power systems. By establishing an interaction model between harmonic current and reactive power based on a multi-band harmonic decomposition algorithm, the impact mechanism of harmonics on reactive power compensation can be analyzed in depth. Testing under this condition allows for the optimization of harmonic suppression and reactive power compensation strategies for SVG equipment.

[0039] The multiphysics coupling extreme operating condition takes into account the comprehensive performance of the equipment under complex physical environments. The multiphysics coupling model integrating temperature, electromagnetic field and mechanical stress simulates the sudden change of thermal stress in the equipment caused by overload, short circuit and harmonic superposition. This comprehensive simulation can realistically reflect the worst situation that the equipment may face in actual operation.

[0040] In some embodiments, the process of setting up multiple working condition simulation schemes includes: Acquire historical operating data of photovoltaic booster stations, including grid load and meteorological data; By extracting the diurnal fluctuation pattern of grid load through time series analysis, a mapping relationship between meteorological data and inverter reactive power output is established. Obtain the patterns of multiple operating conditions, transform these patterns into test constraints, and obtain the mapping between failure modes and test requirements; The mapping between the fault modes and test requirements is used to generate an optimal operating condition sequence through the Q-learning algorithm, which serves as the operating condition simulation scheme.

[0041] This invention acquires historical operating data of photovoltaic booster stations, encompassing grid load and meteorological data, which forms the basis for constructing a scientifically sound simulation scheme. Grid load data reflects the system's electricity demand over different time periods; its diurnal variation patterns and seasonal fluctuations provide important references for simulating actual operating conditions. Meteorological data is closely related to photovoltaic power generation; factors such as sunlight intensity, temperature, and wind speed directly affect the inverter's output power and reactive power regulation capabilities. By deeply analyzing this historical data, we can accurately grasp the various states and trends of the photovoltaic booster station during its past operation, improving the reliability and practicality of the test results.

[0042] By extracting the diurnal fluctuation pattern of grid load through time-series analysis and establishing a mapping relationship between meteorological data and inverter reactive power output, the accuracy of operating condition simulation is improved. The diurnal fluctuation pattern reveals the daily variation pattern of grid load, helping to simulate the system's reactive power demand at different times, thus enabling more accurate setting of steady-state reactive power compensation conditions such as light load and heavy load. The mapping relationship between meteorological data and inverter reactive power output considers the impact of external environmental factors on photovoltaic power generation, allowing for reasonable adjustment of inverter reactive power output according to different meteorological conditions during simulation, more realistically reflecting various situations that may occur in actual operation. Multiple operating condition patterns are acquired and transformed into test constraints, resulting in a mapping between fault modes and test requirements. This mapping relationship clarifies the specific content and requirements to be tested under different fault modes, making the simulation scheme more targeted and systematic. The Q-learning algorithm can automatically learn and optimize the operating condition sequence based on historical data and test requirements, enabling the simulation scheme to meet various test requirements while covering as many possible combinations of operating conditions in actual operation as possible, improving the comprehensiveness and effectiveness of the test. The operating condition simulation schemes generated in this way can more effectively identify problems in equipment and systems under various complex operating conditions.

[0043] In some embodiments, the process of the SVG outputting reactive current to perform load testing on secondary equipment includes: The SVG injects reactive current into the bus according to the set value and maintains output stability through closed-loop control. Maintain stable output for a preset time to sample data for load testing of secondary equipment.

[0044] This invention, through advanced control algorithms and precise parameter settings, enables the SVG to output reactive current of specific magnitude and direction according to test requirements, ensuring that the reactive power injected into the bus meets preset requirements. It creates a realistic and controllable load-bearing operating environment for secondary equipment, allowing them to be tested under conditions close to actual operating conditions. This effectively avoids test errors caused by inaccurate reactive current injection, improving the reliability and accuracy of test results. When simulating light or heavy load conditions, the SVG can precisely adjust the injected reactive current magnitude according to the reactive power demand under different conditions, providing matching load conditions for the secondary equipment, making the test results more reflective of the equipment's performance in actual operation.

[0045] After reactive current is injected, the SVG maintains output stability through closed-loop control, which is a core element in ensuring test quality. The closed-loop control system monitors the reactive current output by the SVG in real time and compares it with the set value. Once a deviation is detected, the system quickly and automatically adjusts the control parameters to correct the deviation, ensuring that the reactive current output remains stable near the set value. This ensures that the secondary equipment operates in a stable electrical environment during load testing, avoiding measurement errors and equipment malfunctions caused by reactive current fluctuations. In simulations of voltage fluctuations and sudden reactive power changes, even if external factors cause sudden changes in bus voltage or reactive power, the SVG's closed-loop control system can respond quickly and stably output reactive current, providing a relatively stable test platform for the secondary equipment. This ensures that the secondary equipment can accurately collect data and operate normally, thus truly reflecting its performance and response capabilities under complex operating conditions.

[0046] Maintaining stable output for a preset time allows for sufficient sampling during load testing of secondary equipment. Within this preset time, the secondary equipment continuously collects various parameters such as bus voltage, current, and power, obtaining a sufficient number of data samples. In reactive power compensation testing under harmonic interference conditions, long-term stable output sampling enables the secondary equipment to fully capture the impact of harmonics on reactive power compensation and accurately measure various performance indicators of the equipment under harmonic environments.

[0047] In some embodiments, the process of collecting actual measurement data from each secondary device and comparing it with theoretical calculation data in multiple dimensions to obtain the test results of each secondary device includes: The actual measurement data and theoretical calculation data are used to calculate waveform similarity using a dynamic time warping algorithm; The actual measurement data and theoretical calculation data with waveform similarity exceeding the threshold are subjected to Fast Fourier Transform to obtain the frequency domain harmonic deviation evaluation results; The statistical characteristic consistency test was performed on the frequency domain harmonic deviation assessment results to obtain the mean deviation and variance deviation. Anomaly detection is performed on data that meet the thresholds for mean deviation and variance deviation, and anomaly detection reports are obtained as the test results for each secondary device.

[0048] In actual operation, the measurement data and theoretical calculation data of secondary equipment may be misaligned or deformed on the time axis due to various factors. The dynamic time warping algorithm can flexibly handle such time differences and accurately measure the similarity between the two waveforms by finding the optimal matching path.

[0049] Once the waveform similarity exceeds a threshold, Fast Fourier Transform (FFT) is performed on both the actual measured data and the theoretically calculated data to obtain the frequency domain harmonic deviation assessment results. FFT converts time-domain signals into frequency-domain signals, clearly showing the components and amplitudes of each harmonic in the signal. By comparing the harmonic distributions of the actual measured data and the theoretically calculated data in the frequency domain, problems in the equipment's harmonic measurement and processing can be accurately identified. If the amplitude of a certain harmonic in the actual measured data is significantly higher than the theoretically calculated value, it indicates a defect in the equipment's harmonic suppression or measurement stages. A statistical consistency test is performed on the frequency domain harmonic deviation assessment results to obtain the mean deviation and variance deviation, further quantifying the data differences from a statistical perspective. The mean deviation reflects the degree of deviation between the actual measured data and the theoretically calculated data at the average level, while the variance deviation reflects the difference in the dispersion of the data.

[0050] In some embodiments, the process of analyzing all test results to obtain experimental results includes: Cluster analysis was performed on multiple test data under the same working condition to calculate the dispersion index of each cluster and label the discrete cluster data. The system calculates the compliance rate of equipment response parameters, generates a radar chart to compare the deviation between actual values ​​and benchmark values, correlates the marked discrete cluster data with equipment logs, locates potential fault points, and obtains performance evaluation results. The performance evaluation results will be used to generate a traceable test report document, which will serve as the test outcome.

[0051] This invention groups similar data into categories, forming different clusters, while the dispersion index quantifies the degree of data dispersion within each cluster. By labeling discrete clusters, it identifies anomalous data clusters that differ significantly from the overall data distribution, reflecting abnormal operating states or potential problems of the equipment under specific conditions. Under conditions of voltage fluctuations and sudden changes in reactive power, if the dispersion of a certain cluster is significantly higher than that of other clusters, it means that there are unstable factors in the equipment's response under these conditions.

[0052] In some embodiments, the process of inspecting and debugging the SVG equipment and secondary equipment in the photovoltaic booster station includes: Perform a functional self-test on the SVG device; Check the data mapping relationship between the secondary device and the SVG device through the communication interface; Static debugging is performed on the secondary equipment to calibrate the sampling accuracy of the measurement and control unit.

[0053] This invention proposes a photovoltaic booster station SVG load testing system; please refer to [link / reference]. Figure 2 ,include: Inspection unit 100 is configured to inspect and debug the SVG equipment and secondary equipment in the photovoltaic booster station; The simulation unit 200 is configured to set up various operating condition simulation schemes, and the SVG outputs reactive current to perform load testing for secondary equipment. The comparison unit 300 is configured to collect the actual measurement data of each secondary device and compare it with the theoretical calculation data in multiple dimensions to obtain the test results of each secondary device. The switching unit 400 is configured to smoothly switch between different operating conditions according to multiple operating condition simulation schemes, obtain the test results under each operating condition, analyze all the test results, and obtain the experimental results.

[0054] In some embodiments, please refer to Figure 5 , Figure 6 and Figure 7 The specific operation process of this invention is as follows: Reference Figure 5 A load-bearing test method for SVG (Static Var Generator) in photovoltaic (PV) booster substations is described. During the power receiving phase of the booster substation, the 110kV power supply from the grid is transmitted to the 35kV busbar via an SF6 enclosed switchgear and main transformer, and then to the SVG reactive power compensation device via a 35kV feeder switch. The SVG injects controllable reactive current into the primary system through its power module. By testing various equipment such as protection, measurement, and metering devices, the polarity, transformation ratio, and phase relationship of the CT / PT circuit are accurately verified, effectively identifying problems such as wiring errors and reverse polarity connections. The secondary devices involved in the testing include: main transformer protection panel (differential), main transformer protection panel (high backup), 110kV fault recorder, frequency and voltage emergency control panel, 110kV line protection panel, power quality online monitoring device, line transformer group measurement and control panel, wideband measurement panel, SVG control cabinet, fast frequency response device, gate metering cabinet, main transformer protection panel (low backup), 35kV bus protection cabinet, main transformer incoming line cabinet metering device, 35kV fault recorder, SVG cabinet protection device, SVG cabinet measurement device, and SVG cabinet metering device, collectively referred to as secondary equipment below.

[0055] Connection testing comprehensively verifies the correctness of circuits between equipment. Power from the grid is delivered to the SVG reactive power compensation device via multiple devices, involving numerous secondary equipment connections. Through testing, the polarity, transformation ratio, and phase relationship of the CT / PT circuits can be accurately verified, and wiring errors, reverse polarity connections, and other problems can be detected in a timely manner, ensuring accurate electrical connections between equipment and normal signal transmission. Each secondary device forms a complete protection and measurement system through specific connections. Testing can check the collaborative working capability between equipment, whether protection devices can operate accurately in the event of a fault, and whether measuring devices can accurately collect data. This ensures the system can respond promptly to various operating conditions, effectively protect equipment and grid safety, accurately measure electrical energy, achieve reactive power compensation functions, improve the reliability and stability of the entire power system, and guarantee the quality and security of power supply.

[0056] Reference Figure 6 The detailed operating steps are explained in detail.

[0057] I. Preparations before the experiment 1. Pre-inspection of secondary equipment (before the substation receives power): (1) Power on all secondary equipment (protection devices, measurement and control devices, energy meters, etc.) in the substation and check that there are no abnormal alarms. (2) Simulate secondary circuit signals to confirm that the instruments and devices display functions are normal; the wiring of the CT / PT secondary circuit is correct and the terminal strips are tightened; the settings of each protection device are correct and the control words and pressure plates are correct. (3) Check that the SVG device body has no external damage, the insulation of the SVG primary circuit (including incoming cable, disconnector, circuit breaker) is qualified and the grounding is reliable; the power module, cooling system and control unit are operating normally and have the conditions for primary power-on commissioning.

[0058] 2. Equipment status verification: At that time, the 35kV busbar will be energized, and all 35kV feeder circuit switchgear will be in cold standby mode. The 110kV voltage transformer and 35kV voltage transformer will be in operation. Check that the amplitude and phase of the sampled voltage of all secondary equipment are correct. All devices can be checked simultaneously.

[0059] 3. Safety measures must be implemented. A work permit for SVG load testing must be issued, a test isolation area must be demarcated, and warning signs must be set up. Test personnel must wear insulated protective equipment, and unauthorized personnel are strictly prohibited from entering the test area.

[0060] II. Primary equipment power-on operation: 1. Close the isolating switch QS11 of the 35kV SVG feeder cabinet. 2. Close the circuit breaker QF1 of the 35kV SVG feeder cabinet. 3. Observe that the protection and control devices of the 35kV feeder cabinet and SVG control cabinet are normal, and there are no alarms such as short circuit or overvoltage.

[0061] III. SVG Device Commissioning and Reactive Current Setting: 1. Start the SVG control system, activate the cooling system, and wait for the device to complete its self-test (no fault code indication). 2. Switch the SVG control mode to reactive current control mode, and set the reactive current output direction (inductive / capacitive) and initial amplitude (it is recommended to start from 10% of the rated reactive power).

[0062] IV. Simulated operating conditions and secondary circuit verification Operating Condition 1: Capacitive reactive current output test (current leads voltage by 90°). Set the SVG output capacitive primary reactive current to 20A and operate stably. The test is based on a 110kV line protection cabinet: (1) Using a phase volt-ammeter with the A phase voltage as the reference, measure the phase and amplitude of the currents in phases A, B, and C respectively. The measured results are: A phase angle 89.8°, amplitude 19.5mA; B phase angle 209.5°, amplitude 19.6mA; C phase angle 329.1°, amplitude 19.6mA. This result is the angle by which the A, B, and C phase currents lead the A phase voltage. The comprehensive analysis shows that the three phase currents are in positive phase sequence. Compare the design drawings with the theoretical calculation values ​​(based on the phase relationship between reactive current and voltage) to verify the accuracy of the secondary circuit wiring. (2) The measured current amplitude should correspond to the CT ratio. (3) Check and record that the current and voltage information displayed by the protection and control device are consistent with the test results. Test all secondary equipment using the same method. Multiple intervals and multiple devices can be tested simultaneously. The test results should meet the design requirements. Note: Determine the primary current amplitude according to the transformer ratio of each CT, and ensure that the secondary current is greater than 5mA for it to be effective; the current angle difference between the upper and lower stages of the 35kV bus differential protection is 180°; the current angle difference between the high and low sides of the main transformer differential protection is 210° (main transformer connection group number YNd11); check that there is no differential current in the main transformer differential protection and the 35kV bus differential protection.

[0063] Operating Condition 2: Inductive Reactive Current Output Test (Voltage Leads Current by 90°). Set the SVG output inductive primary reactive current to 30A and operate stably. The operating procedures are the same as in Operating Condition 1. Precautions: During the test, assign a dedicated person to monitor the SVG device and secondary equipment status. If any abnormality is found (such as secondary circuit signal distortion, device overheating), immediately stop the test and troubleshoot the fault. Reactive current adjustment should be performed slowly and in stages to avoid equipment impact or secondary circuit malfunction due to sudden current changes.

[0064] V. Post-Test Recovery 1. Gradually reduce the reactive current output of the SVG to 0, stop the SVG device, and disconnect the cooling system power supply. 2. Disconnect the circuit breaker QF1 of the SVG circuit, then disconnect the isolating switch QS11, restoring the equipment to cold standby mode. 3. Compile the test records and generate a test report, such as... Figure 7 4. Compare the amplitude and phase relationship of the secondary current and voltage under different operating conditions to confirm the accuracy and completeness of the secondary equipment and circuit wiring, and to ensure that it is ready for commissioning.

[0065] Figure 7 It covers detailed test data for multiple bays, including the main transformer protection panel (differential, high backup), 110kV fault recording, and frequency and voltage emergency control panel. Each bay records relevant parameters for the three phases A, B, and C, as well as N (neutral line), providing a comprehensive basis for the performance evaluation and fault diagnosis of the electrical system.

[0066] The transformation ratio varies depending on the interval and phase. For example, the A-phase transformation ratio of the main transformer protection panel (differential) T11-1 is 1000 / 1, while the A-phase transformation ratio of the power quality online monitoring T11-5 is 500 / 1. The transformation ratio reflects the proportional relationship between the electrical quantities on the primary and secondary sides of the current transformer or voltage transformer, and is an important basic parameter for electrical measurement and protection.

[0067] The secondary voltage in most bays is relatively stable, ranging from 57.3V to 57.5V. The stability of the secondary voltage is crucial for the normal operation of secondary equipment; devices such as protection systems and measuring instruments rely on a stable secondary voltage to accurately obtain electrical information.

[0068] The values ​​of primary and secondary currents vary accordingly based on the transformation ratio. For example, in phase A of the main transformer protection panel (differential) T11-1, the primary current is 19.3A and the secondary current is 19.5mA (which is basically reasonable according to the 1000 / 1 transformation ratio). By comparing the primary and secondary currents, it can be verified whether the current transformer is operating normally.

[0069] The angle data of each phase reflects the phase relationship between electrical quantities. For protection devices based on the phase principle, such as differential protection, the accuracy of the angle directly affects the correct operation of the protection. For example, the angle difference between each phase of the main transformer protection panel (differential) is close to 120° (89.8°, 209.6°, 329.1°, with an interval of about 120°), which is consistent with the phase characteristics of a three-phase balanced system.

[0070] Differential protection determines faults by comparing the vector sum of currents on each side of the protected equipment, with differential current being the key indicator. Most of the differential current values ​​in the table are relatively small. For example, the differential currents of phases A, B, and C of the main transformer protection panel (differential) T11-1 are 0.001A, 0.001A, and 0.002A respectively, which are within the normal range. This indicates that there is no internal fault in the equipment, and the differential protection has not malfunctioned.

[0071] By analyzing this data, the operational status of primary equipment such as current transformers and voltage transformers, as well as secondary equipment such as protection and measurement systems, can be assessed. For example, excessive differential current may indicate equipment malfunction or an incorrect transformer ratio. When an electrical system malfunctions, comparing normal operating data with data during a fault allows for rapid location of the fault, analysis of the cause, and implementation of appropriate solutions.

[0072] This disclosure also provides an electronic device, including: at least one processor; a memory for storing processor-executable instructions; wherein the at least one processor is configured to execute the instructions to implement the methods disclosed in this disclosure.

[0073] Figure 3 This is a schematic diagram of the structure of an electronic device provided as an exemplary embodiment of this disclosure. For example... Figure 3 As shown, the electronic device 300 includes at least one processor 301 and a memory 302 coupled to the processor 301, which can perform the corresponding steps in the methods disclosed in the embodiments of this disclosure.

[0074] The processor 301 described above can also be called a central processing unit (CPU), which can be an integrated circuit chip with signal processing capabilities. Each step in the method disclosed in this embodiment can be implemented by the integrated logic circuitry in the processor 301 or by software instructions. The processor 301 can be a general-purpose processor, a digital signal processor (DSP), an ASIC (Application Specific Integrated Circuit), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in this embodiment can be directly implemented by a hardware decoding processor, or by a combination of hardware and software modules in the decoding processor. The software modules can be located in the memory 302, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. The processor 301 reads information from the memory 302 and, in conjunction with its hardware, completes the steps of the method described above.

[0075] Furthermore, various operations / processes according to this disclosure, implemented via software and / or firmware, can be transmitted from a storage medium or network to a computer system with a dedicated hardware architecture, such as... Figure 4 The computer system 1900 shown is equipped with the programs that constitute the software. When various programs are installed, the computer system is able to perform various functions, including those described above. Figure 4 A block diagram of a computer system provided for an exemplary embodiment of this disclosure.

[0076] Computer System 1900 is intended to represent various forms of digital electronic computer devices, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. Electronic devices can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0077] like Figure 4 As shown, the computer system 1900 includes a computing unit 1901, which can perform various appropriate actions and processes based on a computer program stored in a read-only memory (ROM) 1902 or a computer program loaded from a storage unit 1908 into a random access memory (RAM) 1903. The RAM 1903 may also store various programs and data required for the operation of the computer system 1900. The computing unit 1901, ROM 1902, and RAM 1903 are interconnected via a bus 1904. An input / output (I / O) interface 1905 is also connected to the bus 1904.

[0078] Multiple components in computer system 1900 are connected to I / O interface 1905, including: input unit 1906, output unit 1907, storage unit 1908, and communication unit 1909. Input unit 1906 can be any type of device capable of inputting information into computer system 1900. Input unit 1906 can receive input digital or character information and generate key signal inputs related to user settings and / or function control of the electronic device. Output unit 1907 can be any type of device capable of presenting information and may include, but is not limited to, a monitor, speaker, video / audio output terminal, vibrator, and / or printer. Storage unit 1908 may include, but is not limited to, hard disks and optical disks. Communication unit 1909 allows computer system 1900 to exchange information / data with other devices via a network such as the Internet, and may include, but is not limited to, modems, network cards, infrared communication devices, wireless communication transceivers, and / or chipsets, such as Bluetooth™ devices, WiFi devices, WiMax devices, cellular communication devices, and / or the like.

[0079] The computing unit 1901 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 1901 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 1901 performs the various methods and processes described above. In some embodiments, the methods disclosed in this disclosure can be implemented as a computer software program tangibly contained in a machine-readable medium, such as storage unit 1908. In some embodiments, part or all of the computer program can be loaded and / or installed on an electronic device via ROM 1902 and / or communication unit 1909. In some embodiments, the computing unit 1901 can be configured by any other suitable means (by means of firmware) to perform the methods disclosed in this disclosure.

[0080] This disclosure also provides a computer-readable storage medium, wherein when the instructions in the computer-readable storage medium are executed by a processor of an electronic device, the electronic device is able to perform the methods disclosed in this disclosure.

[0081] The computer-readable storage medium in this disclosure can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. The aforementioned computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specifically, the aforementioned computer-readable storage medium may include electrical connections based on one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0082] The aforementioned computer-readable medium may be included in the aforementioned electronic device; or it may exist independently and not assembled into the electronic device.

[0083] This disclosure also provides a computer program product, including a computer program, wherein the computer program, when executed by a processor, implements the methods disclosed in the embodiments of this disclosure.

[0084] In embodiments of this disclosure, computer program code for performing the operations of this disclosure can be written in one or more programming languages ​​or a combination thereof. These programming languages ​​include, but are not limited to, object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as C or similar languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network (including a local area network (LAN) or a wide area network (WAN)), or it can be connected to an external computer.

[0085] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. Two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0086] The modules, components, or units described in the embodiments of this disclosure can be implemented in software or hardware. The names of the modules, components, or units do not necessarily constitute a limitation on the module, component, or unit itself.

[0087] The functions described above in this document can be performed, at least in part, by one or more hardware logic components. Exemplary hardware logic components that may be used, without limitation, include: Field Programmable Gate Arrays (FPGAs), Application-Specific Integrated Circuits (ASICs), Application Standard Products (ASSPs), System-on-Chip (SoCs), Complex Programmable Logic Devices (CPLDs), and so on.

[0088] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0089] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0090] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0091] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0092] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or middleware components (e.g., application servers), or frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0093] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0094] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and no limitation is imposed herein.

[0095] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for testing SVG (Static Var Generator) under load at a photovoltaic booster station, characterized in that, include: Inspect and debug the SVG equipment and secondary equipment in the photovoltaic booster station; Multiple operating condition simulation schemes are set up, and the SVG outputs reactive current to perform load testing on secondary equipment. The actual measurement data of each secondary device is collected and compared with the theoretical calculation data in multiple dimensions to obtain the test results of each secondary device; By smoothly switching between different operating conditions using various operating condition simulation schemes, test results are obtained for each operating condition. All test results are then analyzed to obtain the experimental results.

2. The method for testing SVG (Static Var Generator) under load at a photovoltaic booster station according to claim 1, characterized in that, The various operating conditions include: Steady-state reactive power compensation conditions under light and heavy loads; Under conditions of voltage fluctuations and reactive power abrupt changes, a time-varying impedance network is used to synchronously trigger voltage amplitude / phase abrupt changes and reactive power step changes. Under the reactive power compensation condition of harmonic interference, an interaction model of harmonic current and reactive power is established based on the multi-band harmonic decomposition algorithm to optimize harmonic suppression and reactive power compensation. Extreme operating conditions with multi-physics coupling: A multi-physics coupling model integrating temperature, electromagnetic field and mechanical stress is used to simulate sudden changes in equipment thermal stress caused by overload, short circuit and harmonic superposition.

3. The method for testing the SVG (Static Var Generator) of a photovoltaic booster station under load according to claim 2, characterized in that, The process of setting up multiple working condition simulation schemes includes: Acquire historical operating data of photovoltaic booster stations, including grid load and meteorological data; By extracting the diurnal fluctuation pattern of grid load through time series analysis, a mapping relationship between meteorological data and inverter reactive power output is established. Obtain the patterns of multiple operating conditions, transform these patterns into test constraints, and obtain the mapping between failure modes and test requirements; The mapping between the fault modes and test requirements is used to generate an optimal operating condition sequence through the Q-learning algorithm, which serves as the operating condition simulation scheme.

4. The method for testing the SVG (Static Var Generator) of a photovoltaic booster station under load according to claim 1, characterized in that, The process by which the SVG outputs reactive current for load testing of secondary equipment includes: The SVG injects reactive current into the bus according to the set value and maintains output stability through closed-loop control. Maintain stable output for a preset time to sample data for load testing of secondary equipment.

5. The method for testing the SVG (Static Var Generator) of a photovoltaic booster station under load according to claim 1, characterized in that, The process of collecting actual measurement data from each secondary device and comparing it with theoretical calculation data in multiple dimensions to obtain the test results of each secondary device includes: The actual measurement data and theoretical calculation data are used to calculate waveform similarity using a dynamic time warping algorithm; The actual measurement data and theoretical calculation data with waveform similarity exceeding the threshold are subjected to Fast Fourier Transform to obtain the frequency domain harmonic deviation evaluation results; The statistical characteristic consistency test was performed on the frequency domain harmonic deviation assessment results to obtain the mean deviation and variance deviation. Anomaly detection is performed on data that meet the thresholds for mean deviation and variance deviation, and anomaly detection reports are obtained as the test results for each secondary device.

6. The method for testing SVG (Static Var Generator) under load at a photovoltaic booster station according to claim 1, characterized in that, The process of analyzing all test results to obtain the experimental results includes: Cluster analysis was performed on multiple test data under the same working condition to calculate the dispersion index of each cluster and label the discrete cluster data. The system calculates the compliance rate of equipment response parameters, generates a radar chart to compare the deviation between actual values ​​and benchmark values, correlates the marked discrete cluster data with equipment logs, locates potential fault points, and obtains performance evaluation results. The performance evaluation results will be used to generate a traceable test report document, which will serve as the test outcome.

7. The method for testing SVG (Static Var Generator) under load at a photovoltaic booster station according to claim 1, characterized in that, The process of inspecting and debugging the SVG equipment and secondary equipment in the photovoltaic booster station includes: Perform a functional self-test on the SVG device; Check the data mapping relationship between the secondary device and the SVG device through the communication interface; Static debugging is performed on the secondary equipment to calibrate the sampling accuracy of the measurement and control unit.

8. A photovoltaic booster station SVG load test system, characterized in that, include: The inspection unit is configured to inspect and debug the SVG equipment and secondary equipment in the photovoltaic booster station; The simulation unit is configured to set up various operating condition simulation schemes, and the SVG outputs reactive current to perform load testing for secondary equipment. The comparison unit is configured to collect actual measurement data from each secondary device and compare it with theoretical calculation data in multiple dimensions to obtain the test results of each secondary device. The switching unit is configured to smoothly switch between different operating conditions according to multiple operating condition simulation schemes, obtain test results under each operating condition, analyze all test results, and obtain experimental results.

9. An electronic device, characterized in that, include: At least one processor; Memory for storing the at least one processor-executable instruction; The at least one processor is configured to execute the instructions to implement the method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, When the instructions in the computer-readable storage medium are executed by the processor of the electronic device, the electronic device is enabled to perform the method as described in any one of claims 1 to 7.

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