An energy storage transformer with automatic filtering function

Abstract

This invention relates to the field of transformer technology, and more particularly to an energy storage transformer with automatic filtering function. The transformer includes: a data acquisition module for real-time acquisition of input current and voltage data from the power grid and energy storage equipment, as well as operational data from the energy storage system and filtering device; a filtering device analysis module for determining whether the filtering device's health status is abnormal based on a comprehensive filtering device index; a harmonic component analysis module for determining whether harmonic components are qualified based on harmonic characteristic parameters and adjusting filtering parameters based on the difference; a harmonic degradation risk analysis module for determining whether the harmonic degradation risk meets the standard based on harmonic variation characterization coefficients and adjusting the filter response frequency based on the relative difference; and a filtering efficiency analysis module for determining whether the filtering device's working efficiency meets the standard based on filtering efficiency loss values ​​and optimizing capacitor values ​​or inductor temperatures based on ratios. This invention improves the operating efficiency of the energy storage transformer.

Description

Technical Field

[0001] This invention relates to the field of transformer technology, and in particular to an energy storage transformer with automatic filtering function. Background Technology

[0002] The large-scale development and efficient utilization of new energy sources have become the core path for energy system transformation. Energy storage systems, as a key component coordinating the intermittency and volatility of new energy sources with the stable operation requirements of the power grid, are playing an increasingly important role. Energy storage transformers, as the core equipment in the system for realizing power conversion and transmission, directly affect the power quality of grid-connected points. However, in actual operation, energy storage systems, especially those connected to the grid via power electronic devices, generate a large amount of harmonic current. These harmonics, once injected into the grid, can easily cause voltage distortion, resonant overvoltage, and other problems, not only affecting power quality but also potentially damaging electrical equipment and even leading to local grid failures. Traditional harmonic mitigation technologies typically use active or passive filters with fixed parameters. While these can suppress harmonics to some extent, they are still significantly insufficient when dealing with dynamic loads like energy storage systems. Existing mitigation solutions largely rely on harmonic monitoring on the grid side, lacking coordinated perception of the filter's own operating status and the real-time operating conditions of the energy storage system. This results in a lack of timely warnings when filter failures occur, potentially causing harmonic suppression functionality to fail. In addition, the parameters of traditional filtering equipment are mostly preset at the factory or rely on manual periodic adjustment, which makes it difficult to adapt to the dynamic changes of harmonics in energy storage systems under various operating modes, thus restricting the level of intelligent management of the interaction process between energy storage systems and the power grid.

[0003] Chinese Patent Application Publication No. CN114070025A discloses an optimized design method for an adjustable LCL filter in a T-type three-level energy storage converter. The method includes: using the leakage inductance of the AC-side isolation transformer to replace the AC-side inductance of the LCL filter; establishing a filter model, solving the transfer function, and defining clear constraints on the function; designing a parameter calculation module based on these constraints; calculating the LCL filter parameters based on collected relevant values; combining these parameters with actual empirical values ​​to determine the actual parameters; and designing adjustable filter capacitors and inductors, which can adjust the filter parameters according to changes in actual output power, thereby further improving the quality of the grid-connected power.

[0004] However, the existing technology has the following problems: the fixed parameter filtering mode cannot monitor the changes in power grid harmonics and the status of the filtering components in real time, and it is difficult to dynamically adjust the filtering parameters according to the harmonic components, resulting in poor filtering effect and low transformer operating efficiency. Summary of the Invention

[0005] To address this issue, the present invention provides an energy storage transformer with automatic filtering function, which overcomes the problem in the prior art that uses a fixed parameter filtering mode, which cannot monitor the changes in grid harmonics and the status of filtering components in real time, and is difficult to dynamically adjust the filtering parameters according to the harmonic components, resulting in poor filtering effect and low operating efficiency of hydrogen energy storage transformers.

[0006] To achieve the above objectives, the present invention provides an energy storage transformer with automatic filtering function, comprising:

[0007] The data acquisition module is used to acquire real-time input current and voltage data of the power grid, input current and voltage data of energy storage devices, operating parameters of energy storage systems, and operating data of filtering devices.

[0008] The filter device analysis module is used to determine the comprehensive index of the filter device based on the operating parameters of the energy storage system and the operating data of the filter device, so as to determine whether there is any abnormality in the health status of the filter device;

[0009] The harmonic component analysis module is used to determine the harmonic characteristic parameters based on the input current and voltage data of the power grid, in order to determine whether the harmonic components are qualified, and to determine the adjustment filter parameters based on the difference between the harmonic characteristic parameters and the preset harmonic characteristic parameters.

[0010] The harmonic degradation risk analysis module is used to determine the harmonic variation characterization coefficient based on the operating parameters of the energy storage system, in order to determine whether the harmonic degradation risk meets the standard, and to determine the adjustment filter response frequency based on the relative difference between the harmonic variation characterization coefficient and the preset harmonic variation characterization coefficient.

[0011] The filter performance analysis module is used to determine the filter performance loss value based on the operating data of the filter device, so as to determine whether the working efficiency of the filter device meets the standard, and to determine the optimized capacitor value or inductor temperature based on the ratio of the filter performance loss value to the preset filter performance loss value.

[0012] Furthermore, the filter device analysis module determines that the filter device's health status is abnormal based on the comparison result that the filter device's comprehensive index is greater than the preset filter device comprehensive index.

[0013] Furthermore, the harmonic component analysis module determines that the harmonic component is unqualified based on the comparison result of the harmonic characteristic characterization parameter being greater than the preset harmonic characteristic characterization parameter.

[0014] Furthermore, the process of obtaining the harmonic characteristic parameters includes:

[0015] The real-time collected power grid input current and voltage data are decomposed by fast Fourier transform to obtain the effective values ​​of the fundamental wave and each harmonic.

[0016] Calculate the total harmonic distortion (THD);

[0017] Extract the 3rd, 5th, and 7th harmonic components and calculate the ratio of each major harmonic to the fundamental frequency.

[0018] The harmonic characteristic parameters are the product of the total harmonic distortion rate and a weight of 0.4, the product of the 3rd harmonic component and a weight of 0.3, the product of the 5th harmonic component and a weight of 0.2, and the product of the 7th harmonic component and a weight of 0.1.

[0019] Furthermore, when the harmonic component analysis module determines that a harmonic component is unqualified, it determines the adjustment filter parameters based on a comparison between the difference between the harmonic characteristic characterization parameters and the preset harmonic characteristic characterization parameters and a preset difference.

[0020] Based on the comparison results where the difference is less than or equal to the preset difference, the number of capacitors to be switched is increased by a preset capacitor switching quantity adjustment coefficient.

[0021] Based on the comparison results where the difference is greater than the preset difference, a preset inductance value adjustment coefficient is used to reduce the filter inductance value.

[0022] Furthermore, the harmonic degradation risk analysis module determines that the harmonic degradation risk does not meet the standard based on the comparison result of the harmonic variation characterization coefficient being greater than the preset harmonic variation characterization coefficient.

[0023] Furthermore, the harmonic variation characterization coefficient is the product of the difference between the current harmonic characteristic characterization parameter and the previous period's harmonic characteristic characterization parameter, multiplied by the previous period's harmonic characteristic characterization parameter and a weight of 0.5, plus the product of the energy storage system's state of charge change rate and a weight of 0.3, plus the product of the energy conversion efficiency fluctuation value and a weight of 0.2. The energy storage system's state of charge change rate is the absolute value of the difference between the current energy storage system's state of charge and the previous period's state of charge, divided by the previous period's state of charge. The energy conversion efficiency fluctuation value is the standard deviation of the conversion efficiency over several sampling periods.

[0024] Furthermore, the harmonic degradation risk analysis module, under the condition that the harmonic degradation risk does not meet the standard, determines the adjustment filter response frequency based on the comparison result of the relative difference between the harmonic variation characterization coefficient and the preset harmonic variation characterization coefficient and the preset relative difference, wherein,

[0025] Based on the comparison results where the relative difference is less than or equal to a preset relative difference, the filter response frequency is increased by a first preset response frequency adjustment coefficient.

[0026] Based on the comparison result where the relative difference is greater than the preset relative difference, the filter response frequency is increased by a first preset response frequency adjustment coefficient.

[0027] Furthermore, the filter performance analysis module determines that the working efficiency of the filter device is substandard based on the comparison result that the filter performance loss value is greater than the preset filter performance loss value.

[0028] Furthermore, when the filtering device's efficiency is substandard, the filtering performance analysis module determines the optimal capacitor value or inductor temperature based on a comparison between the ratio of the filtering performance loss value to a preset filtering performance loss value and a preset ratio.

[0029] Based on the comparison results where the ratio is less than or equal to a preset ratio, the capacitor value is increased by a preset capacitor value adjustment coefficient.

[0030] Based on the comparison results where the ratio is greater than the preset ratio, the inductor temperature is determined to be reduced using a preset inductor temperature adjustment coefficient.

[0031] Compared with existing technologies, the beneficial effects of this invention are as follows: This invention assesses the health status through a comprehensive index; the harmonic component analysis module judges the harmonic compliance based on data characteristics and adjusts the filter parameters; the harmonic degradation risk analysis module assesses the risk and adjusts the response frequency in conjunction with energy storage parameters; and the filter efficiency analysis module detects efficiency based on loss values ​​and optimizes capacitor values ​​or inductor temperatures. The collaboration of multiple modules enables intelligent management of energy storage and grid interaction scenarios. Multi-source data acquisition avoids the information gaps of traditional single-point monitoring. The health status assessment and harmonic compliance judgment of the filter device can identify hidden dangers such as aging and faults of the filter device in advance, and simultaneously verify the suppression effect of the filter device on grid harmonics. By calculating the harmonic variation coefficient through the operating parameters of energy storage under different operating conditions, the harmonic distortion trend can be accurately predicted, and the filter response frequency can be adjusted in advance to avoid the expansion of grid pollution. Furthermore, the optimization of capacitors or inductors based on filter efficiency loss values ​​improves the filtering effect and reduces energy loss by adjusting parameters to improve equipment efficiency, thereby enhancing the stability of energy storage connection to the grid and improving transformer operating efficiency.

[0032] Furthermore, this invention judges the health status of the filter device through a comprehensive index, and achieves accurate diagnosis and dynamic early warning of the filter device's health status through multi-dimensional quantitative evaluation. It can not only capture hidden equipment problems such as capacitor aging and inductor temperature rise, but also correlate the impact of sudden charging and discharging of the energy storage system on the filter device, improve the accuracy of fault prediction, transform vague anomaly perception into quantified risk levels, avoid over-maintenance or missed detection, identify filter device anomalies in advance and trigger protection strategies in a timely manner, adjust filter parameters or switch to backup devices, prevent harmonic resonance, voltage distortion and other problems caused by filter failure, ensure stable operation of the power grid, reduce the risk of equipment damage caused by harmonic pollution, and enhance the universality and practicality of the system.

[0033] Furthermore, this invention determines whether harmonics are within acceptable limits by using harmonic characteristic parameters. If they are not, the number of capacitors switched or the inductance value is reduced to adjust the parameters for excessive harmonics. The harmonic characteristic parameters integrate the total harmonic distortion rate and the 3rd / 5th / 7th major harmonic components, improving the accuracy of diagnosis and ensuring that the filter device can still operate stably after adjustment. This reduces the risk of secondary faults caused by sudden parameter changes. Timely adjustment for excessive harmonics can effectively suppress harmonic resonance, voltage flicker, and other problems, protecting grid equipment from the effects of increased harmonic losses and ensuring stable interaction between the energy storage system and the grid.

[0034] Furthermore, this invention assesses risk by using the harmonic variation characterization coefficient. If the coefficient is not met, the filter response frequency is increased to dynamically suppress the risk of harmonic degradation. The harmonic variation characterization coefficient integrates the evolution trend of harmonics, the operating status of the energy storage system, and energy conversion efficiency, thus improving the foresight of risk warning. When the hydrogen storage capacity continues to decline, leading to an increase in the harmonic variation coefficient, increasing the response frequency in advance can suppress further harmonic degradation and avoid subsequent large-scale harmonic pollution. Timely adjustment of the response frequency can effectively suppress the chain reaction of harmonic degradation, protect key grid equipment from the effects of increased harmonic stress, ensure the safe and stable interaction between the energy storage system and the grid, and thereby improve the operating efficiency of the transformer.

[0035] Furthermore, this invention judges the working efficiency by the filter efficiency loss value. If the efficiency is not up to standard, the capacitor value is increased or the inductor temperature is reduced to optimize the filter efficiency. The filter efficiency loss value is based on the design target, which can reflect the deviation between the actual performance of the filter device and the design expectation, and can also quantify the severity of efficiency loss. This forms a complete closed loop of monitoring, management, and optimization between the filter efficiency optimization module and the front-end harmonic degradation risk analysis and filter parameter adjustment modules, ensuring that the filter device always operates near the design efficiency, improving the stability of the energy storage system and the power grid interaction. Timely efficiency optimization can effectively suppress harmonic rebound caused by the decline in filter performance, reduce the degree of harmonic pollution in the power grid, and protect key equipment such as transformers and motors from the effects of increased harmonic stress, thereby improving the operating efficiency of transformers. Attached Figure Description

[0036] Figure 1 This is a schematic diagram of the module connection of an energy storage transformer with automatic filtering function according to an embodiment of the present invention;

[0037] Figure 2 This is a flowchart illustrating the process of determining whether harmonic components are qualified according to an embodiment of the present invention;

[0038] Figure 3 This is a flowchart illustrating how to determine whether the harmonic degradation risk meets the standards in an embodiment of the present invention.

[0039] Figure 4This is a flowchart for determining whether the working efficiency of the filtering device meets the standard in an embodiment of the present invention. Detailed Implementation

[0040] To make the objectives and advantages of the present invention clearer, the present invention will be further described below with reference to embodiments; it should be understood that the specific embodiments described herein are merely for explaining the present invention and are not intended to limit the present invention.

[0041] Preferred embodiments of the present invention will now be described with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0042] It should be noted that the data in this embodiment are all derived from a comprehensive analysis and evaluation of historical test data and corresponding historical test results from the three months prior to this test. Those skilled in the art will understand that the determination of the above-mentioned parameters for any single item in this invention can be achieved by selecting the value with the highest percentage based on the data distribution as the preset standard parameter, using weighted summation to obtain the value as the preset standard parameter, substituting each historical data point into a specific formula and using the value obtained from that formula as the preset standard parameter, or other selection methods, as long as the invention can clearly define different specific situations in the single-item judgment process through the obtained values.

[0043] Please see Figure 1 As shown, it is a schematic diagram of the module connection of an energy storage transformer with automatic filtering function according to an embodiment of the present invention.

[0044] An embodiment of the present invention includes an energy storage transformer with automatic filtering function, comprising:

[0045] The data acquisition module is used to acquire real-time input current and voltage data of the power grid, input current and voltage data of energy storage devices, operating parameters of energy storage systems, and operating data of filtering devices.

[0046] The filter device analysis module is connected to the data acquisition module and is used to determine the comprehensive index of the filter device based on the operating parameters of the energy storage system and the operating data of the filter device, so as to determine whether there is any abnormality in the health status of the filter device.

[0047] The harmonic component analysis module is connected to the data acquisition module and the filter device analysis module respectively. It is used to determine the harmonic characteristic characterization parameters based on the input current and voltage data of the power grid, so as to determine whether the harmonic components are qualified, and to determine the adjustment of the filter parameters based on the difference between the harmonic characteristic characterization parameters and the preset harmonic characteristic characterization parameters.

[0048] The harmonic degradation risk analysis module is connected to the data acquisition module and the harmonic component analysis module respectively. It is used to determine the harmonic variation characterization coefficient based on the operating parameters of the energy storage system, so as to determine whether the harmonic degradation risk meets the standard, and to determine the adjustment filter response frequency based on the relative difference between the harmonic variation characterization coefficient and the preset harmonic variation characterization coefficient.

[0049] The filter performance analysis module, which is connected to the harmonic degradation risk analysis module, is used to determine the filter performance loss value based on the filter device's operating data, to determine whether the filter device's working efficiency meets the standard, and to determine the optimized capacitor value or inductor temperature based on the ratio of the filter performance loss value to the preset filter performance loss value.

[0050] Specifically, this invention assesses the health status through a comprehensive index, the harmonic component analysis module judges harmonic compliance based on data characteristics and adjusts filter parameters, the harmonic degradation risk analysis module assesses risk and adjusts response frequency in conjunction with energy storage parameters, and the filter efficiency analysis module detects efficiency based on loss values ​​and optimizes capacitor values ​​or inductor temperatures. The collaboration of multiple modules enables intelligent management of energy storage and grid interaction scenarios. Multi-source data acquisition avoids the information gaps of traditional single-point monitoring. The health status assessment and harmonic compliance judgment of the filter device can identify hidden dangers such as aging and faults in the filter device in advance, and simultaneously verify the suppression effect of the filter device on grid harmonics. By calculating the harmonic variation coefficient through the operating parameters of energy storage under different operating conditions, the harmonic distortion trend can be accurately predicted, and the filter response frequency can be adjusted in advance to avoid the expansion of grid pollution. Furthermore, the optimization of capacitors or inductors based on filter efficiency loss values ​​improves the filtering effect through parameter correction, reduces energy loss, and enhances the stability of energy storage connection to the grid, thereby improving transformer operating efficiency.

[0051] Specifically, the filter device analysis module determines whether there is any abnormality in the health status of the filter device by comparing the comprehensive index of the filter device obtained from the operating parameters of the energy storage system and the operating data of the filter device with the preset comprehensive index of the filter device.

[0052] If the comprehensive index of the filter device is less than or equal to the preset comprehensive index of the filter device, then it is determined that the health status of the filter device is not abnormal.

[0053] If the comprehensive index of the filter device is greater than the preset comprehensive index of the filter device, then it is determined that the health status of the filter device is abnormal.

[0054] In this embodiment of the invention, the preset comprehensive index of the filtering device is set to a range of [0.15, 0.25], preferably 0.2. However, the above value is not limited to this, and those skilled in the art can adjust the value according to actual needs.

[0055] In this embodiment of the invention, the process of obtaining the comprehensive index of the filtering device is as follows: the ratio of the difference between the current capacitance value of the filtering device and the initial capacitance value to the initial capacitance value is recorded as the capacitance value change rate; the ratio of the current inductor temperature minus the normal operating temperature of the inductor to the upper limit of the safe operating temperature of the inductor minus the normal operating temperature of the inductor is recorded as the inductor temperature risk rate; the absolute value of the difference between the current power of the energy storage system and the power of the previous cycle is multiplied by the power of the previous cycle to record the energy storage system charging and discharging power mutation rate; the ratio of the energy storage system charging and discharging power mutation rate to the preset power mutation threshold is recorded as the load fluctuation rate; and the result of multiplying the capacitance value change rate by a weight of 0.3, adding the inductor temperature risk rate by a weight of 0.3, and adding the load fluctuation rate by a weight of 0.4 is recorded as the comprehensive index of the filtering device.

[0056] Specifically, this invention judges the health status of the filter device through a comprehensive index, and achieves accurate diagnosis and dynamic early warning of the filter device's health status through multi-dimensional quantitative evaluation. It can not only capture hidden equipment problems such as capacitor aging and inductor temperature rise, but also correlate the impact of sudden charging and discharging changes in the energy storage system on the filter device, improve the accuracy of fault prediction, transform vague anomaly perception into quantified risk levels, avoid over-maintenance or missed detection, identify filter device anomalies in advance and trigger protection strategies in a timely manner, adjust filter parameters or switch to backup devices, prevent harmonic resonance, voltage distortion and other problems caused by filter failure, ensure stable operation of the power grid, reduce the risk of equipment damage caused by harmonic pollution, and enhance the universality and practicality of the system.

[0057] Please see Figure 2 As shown, it is a flowchart for determining whether harmonic components are qualified according to an embodiment of the present invention.

[0058] Specifically, the harmonic component analysis module determines whether the harmonic components are qualified by comparing the harmonic characteristic characterization parameters obtained from the input current and voltage data of the power grid with the preset harmonic characteristic characterization parameters, provided that the filter device is in good health.

[0059] If the harmonic characteristic characterization parameter is less than or equal to the preset harmonic characteristic characterization parameter, then the harmonic component is determined to be qualified.

[0060] If the harmonic characteristic characterization parameter is greater than the preset harmonic characteristic characterization parameter, then the harmonic component is determined to be unqualified.

[0061] In this embodiment of the invention, the preset harmonic characteristic characterization parameter takes a range of [0.3, 0.4], preferably 0.35, but the above value is not limited to this, and those skilled in the art can adjust the value according to actual needs.

[0062] In this embodiment of the invention, the process of obtaining the harmonic characteristic parameters is as follows: real-time collected power grid input current and voltage data are decomposed by fast Fourier transform to obtain the effective values ​​of the fundamental wave and each harmonic; the total harmonic distortion rate is calculated; the 3rd, 5th, and 7th harmonic components are extracted, and the ratio of each major harmonic to the fundamental wave is calculated; the harmonic characteristic parameters are the product of the total harmonic distortion rate and a weight of 0.4, plus the product of the 3rd harmonic component and a weight of 0.3, plus the product of the 5th harmonic component and a weight of 0.2, plus the product of the 7th harmonic component and a weight of 0.1.

[0063] Understandably, when the filter is in normal working order, the total harmonic distortion (THD) and major odd harmonic components should be within a controllable range. By assigning the THD the highest weight of 0.4, the overall impact of THD on power quality is reflected. The 3rd harmonic is prone to causing core magnetic saturation, the 5th harmonic leads to increased capacitor losses, and the 7th harmonic affects equipment lifespan. Therefore, the THD is assigned decreasing weights of 0.3, 0.2, and 0.1 respectively to form a differentiated harmonic hazard assessment. When the harmonic characteristic parameter exceeds the 0.35 threshold, it indicates that the system has a risk of harmonic amplification. A difference range of 0.15-0.20 is set. When the difference is ≤0.17, a capacitor switching coefficient of 1.1 is used to reduce the THD through parallel capacitor compensation. When the difference is >0.17, an inductance value of 0.95 is used to suppress specific harmonics by reducing inductive reactance.

[0064] Specifically, when the harmonic component analysis module determines that the harmonic component is unqualified, it determines the adjustment filter parameters based on the comparison result of the difference between the harmonic characteristic characterization parameter and the preset harmonic characteristic characterization parameter and the preset difference.

[0065] If the difference is less than or equal to the preset difference, then the capacitor switching quantity is increased to the corresponding value by using a preset capacitor switching quantity adjustment coefficient of 1.1.

[0066] If the difference is greater than the preset difference, then it is determined that the filter inductance value will be reduced to the corresponding value by a preset inductance value adjustment coefficient of 0.95;

[0067] Wherein, the difference is the difference between the harmonic characteristic characterization parameter and the preset harmonic characteristic characterization parameter.

[0068] In this embodiment of the invention, the preset difference value range is [0.15, 0.20], preferably 0.17, but the above value is not limited to this, and those skilled in the art can also adjust the value according to actual needs.

[0069] In this embodiment of the invention, the increased number of capacitors switched is the product of the number of capacitors switched and a preset adjustment coefficient for the number of capacitors switched, with the preset adjustment coefficient set to 1.1; the decreased filter inductance is the product of the filter inductance value and a preset adjustment coefficient for the inductance value, with the preset adjustment coefficient set to 0.95. To ensure that the adjusted number of capacitors switched and the filter inductance value meet the actual requirements, the adjustment range should not be too large, so an adjustment coefficient is set to control the adjustment range.

[0070] In this embodiment of the invention, the increase in the number of capacitors switched on is achieved by controlling a relay or power semiconductor switch to connect more capacitor units to the circuit; the decrease in the filter inductance value is achieved by reducing the number of coil turns.

[0071] Specifically, this invention determines whether harmonics are within acceptable limits by using harmonic characteristic parameters. If they are not, the number of capacitors switched or the inductance value is reduced to adjust the parameters for excessive harmonics. The harmonic characteristic parameters integrate the total harmonic distortion rate and the 3rd / 5th / 7th major harmonic components, improving the accuracy of diagnosis and ensuring that the filter device can still operate stably after adjustment. This reduces the risk of secondary faults caused by sudden parameter changes. Timely adjustment for excessive harmonics can effectively suppress harmonic resonance, voltage flicker, and other problems, protecting grid equipment from the effects of increased harmonic losses and ensuring stable interaction between the energy storage system and the grid.

[0072] Please see Figure 3 As shown, it is a flowchart for determining whether the harmonic degradation risk meets the standard in an embodiment of the present invention.

[0073] Specifically, the harmonic degradation risk analysis module determines whether the harmonic degradation risk meets the standard by comparing the harmonic variation characterization coefficient obtained from the energy storage system operating parameters with the preset harmonic variation characterization coefficient, under the condition of determining the adjustment of the filter parameters.

[0074] If the harmonic variation characterization coefficient is less than or equal to the preset harmonic variation characterization coefficient, then the harmonic degradation risk is determined to meet the standard.

[0075] If the harmonic variation characterization coefficient is greater than the preset harmonic variation characterization coefficient, then the harmonic degradation risk is determined to be substandard.

[0076] In this embodiment of the invention, the preset harmonic variation characterization coefficient is set to a value range of [0.05, 0.15], preferably 0.11. However, the value is not limited to this, and those skilled in the art can adjust the value according to actual needs.

[0077] In this embodiment of the invention, the process of obtaining the harmonic variation characterization coefficient is as follows: the difference between the current harmonic characteristic characterization parameter and the previous period harmonic characteristic characterization parameter is divided by the product of the previous period harmonic characteristic characterization parameter and weight 0.5, plus the product of the energy storage system state of charge change rate and weight 0.3, plus the product of the energy conversion efficiency fluctuation value and weight 0.2. The energy storage system state of charge change rate is the absolute value of the difference between the current energy storage system state of charge and the previous period energy storage system state of charge divided by the previous period energy storage system state of charge, and the energy conversion efficiency fluctuation value is the standard deviation of the conversion efficiency over several sampling periods.

[0078] Understandably, the design of the harmonic variation characterization coefficient takes into account the temporal evolution of harmonic characteristics, the dynamic response of the energy storage system, and the nonlinear effects of the power electronic conversion process. Among them, the difference between the current harmonic characteristic characterization parameter and the previous period reflects the degree of abrupt change in harmonic amplitude and directly reflects the immediate risk of harmonic deterioration, and is assigned a weight of 0.5. The state of charge change rate of the energy storage system reflects the modulation effect on harmonics during energy throughput and is assigned a weight of 0.3. The energy conversion efficiency fluctuation value characterizes the additional harmonics generated by efficiency fluctuations in power electronic components such as converters and is assigned a weight of 0.2. When the preset harmonic variation characterization coefficient exceeds 0.15, the total harmonic distortion rate at the grid connection point will increase sharply, triggering a cascading trip of the protection device. This is used to determine that the harmonic deterioration risk does not meet the standard. A preset relative difference range of 0.4-0.6 is set to suppress specific harmonics through high-frequency compensation.

[0079] Specifically, when the risk adjustment module determines that the harmonic degradation risk does not meet the standard, it determines the adjustment filter response frequency based on the comparison result of the relative difference between the harmonic variation characterization coefficient and the preset harmonic variation characterization coefficient and the preset relative difference.

[0080] If the relative difference is less than or equal to the preset relative difference, then the filter response frequency is increased to the corresponding value by adjusting the first preset response frequency by a factor of 1.15.

[0081] If the relative difference is greater than the preset relative difference, then the filter response frequency is increased to the corresponding value by the second preset response frequency adjustment coefficient of 1.25.

[0082] The relative difference is the relative difference between the harmonic variation characterization coefficient and the preset harmonic variation characterization coefficient.

[0083] In this embodiment of the invention, the preset relative difference range is [0.4, 0.6], preferably 0.5, but the above value is not limited to this, and those skilled in the art can adjust the value according to actual needs.

[0084] In this embodiment of the invention, the increased filter response frequency is the product of the filter response frequency and the preset response frequency adjustment coefficient. The preset response frequency adjustment coefficient includes a first preset response frequency adjustment coefficient with a value of 1.15 and a second preset response frequency adjustment coefficient with a value of 1.25. In order to ensure that the adjusted filter response frequency meets the actual requirements, the adjustment range should not be too large. Therefore, an adjustment coefficient is set to control the adjustment range.

[0085] In this embodiment of the invention, the increase in the filter response frequency is achieved by reducing the parameters of the resistor, capacitor, or inductor in the filter circuit.

[0086] Specifically, this invention assesses risk by using the harmonic variation characterization coefficient. If the coefficient is not met, the filter response frequency is increased to dynamically suppress the risk of harmonic deterioration. The harmonic variation characterization coefficient integrates the evolution trend of harmonics, the operating status of the energy storage system, and the energy conversion efficiency, thus improving the foresight of risk warning. When the hydrogen storage capacity continues to decline, causing the harmonic variation coefficient to rise, increasing the response frequency in advance can suppress further harmonic deterioration and avoid subsequent large-scale harmonic pollution. Timely adjustment of the response frequency can effectively suppress the chain reaction of harmonic deterioration, protect key grid equipment from the effects of increased harmonic stress, ensure the safe and stable interaction between the energy storage system and the grid, and thereby improve the operating efficiency of the transformer.

[0087] Please see Figure 4 As shown, it is a flowchart for determining whether the working efficiency of the filtering device meets the standard in an embodiment of the present invention.

[0088] Specifically, the filter performance analysis module, under the condition of determining the adjustment of the filter response frequency, calculates the filter performance loss value based on the operating data of the filter device, and determines whether the working efficiency of the filter device meets the standard based on the comparison result of the filter performance loss value and the preset filter performance loss value.

[0089] If the filtering efficiency loss value is less than or equal to the preset filtering efficiency loss value, then the working efficiency of the filtering device is determined to meet the standard.

[0090] If the filtering efficiency loss value is greater than the preset filtering efficiency loss value, then the working efficiency of the filtering device is determined to be substandard.

[0091] In this embodiment of the invention, the preset filtering efficiency loss value ranges from [0.1, 0.15], preferably 0.12, but the above value is not limited to this, and those skilled in the art can adjust the value according to actual needs.

[0092] In this embodiment of the invention, the process of obtaining the filter efficiency loss value is as follows: the ratio of the target harmonic suppression requirement value to the total harmonic distortion rate at the input end is the filter efficiency of the current filter device; the filter efficiency loss value is the ratio of the difference between the designed filter efficiency and the current filter efficiency to the designed filter efficiency, wherein the designed filter efficiency is determined according to the theoretical calculation value in the filter design specification.

[0093] Understandably, the calculation of the filter efficiency loss value is based on the deviation between the target harmonic suppression requirement and the actual suppression effect: when the filter device is in a high-efficiency working state, the difference between the designed filter efficiency and the current efficiency should be controlled within the preset threshold of 0.15. When the loss value reaches 0.15, the total energy consumption of the system increases too much, the temperature rise of the filter circuit exceeds the limit, triggering derating operation. A preset range of 0.4-0.6 is set. If the relative ratio is ≤0.5, it is judged as mild efficiency decay, and the capacitance value is adjusted to compensate for capacitance aging. If the relative ratio is >0.5, it is judged as severe decay, and the inductor temperature is adjusted to reduce the core loss.

[0094] Specifically, when the filtering efficiency optimization module determines that the working efficiency of the filtering device is not up to standard, it determines the optimized capacitor value or inductor temperature based on the comparison result of the ratio of the filtering efficiency loss value to the preset filtering efficiency loss value and the preset ratio.

[0095] If the ratio is less than or equal to the preset ratio, then the capacitor value is increased to the corresponding value by a preset capacitor value adjustment coefficient of 1.05.

[0096] If the ratio is greater than the preset ratio, then it is determined that the inductor temperature will be reduced to the corresponding value by using a preset inductor temperature adjustment coefficient of 0.98;

[0097] The ratio is the ratio of the filter performance loss value to the preset filter performance loss value.

[0098] In this embodiment of the invention, the preset filtration ratio value range is [1.1, 1.15], preferably 1.12, but the above value is not limited to this, and those skilled in the art can also adjust the value according to actual needs.

[0099] In this embodiment of the invention, the increased capacitance value is the product of the capacitance value and a preset capacitance value adjustment coefficient, which is 1.05; the decreased inductor temperature is the product of the inductor temperature and a preset inductor temperature adjustment coefficient, which is 0.98. To ensure that the adjusted capacitance value and inductor temperature meet the actual requirements, the adjustment range should not be too large, so an adjustment coefficient is set to control the adjustment range.

[0100] In this embodiment of the invention, the increase in capacitance is achieved by reducing the plate spacing of the adjustable capacitor or increasing the plate area, and the decrease in inductor temperature is achieved by increasing the airflow of the cooling system or increasing the liquid cooling flow rate.

[0101] Specifically, this invention judges the working efficiency by the filter efficiency loss value. If the efficiency is not up to standard, the capacitance value is increased or the inductor temperature is reduced to optimize the filter efficiency. The filter efficiency loss value is based on the design target, which can reflect the deviation between the actual performance of the filter device and the design expectation, and can also quantify the severity of efficiency loss. This forms a complete closed loop of monitoring, management and optimization with the filter efficiency optimization module and the front-end harmonic degradation risk analysis and filter parameter adjustment module, ensuring that the filter device always operates near the design efficiency, improving the stability of the energy storage system and the power grid interaction. Timely efficiency optimization can effectively suppress harmonic rebound caused by the decline in filter performance, reduce the degree of harmonic pollution in the power grid, and protect key equipment such as transformers and motors from the effects of increased harmonic stress, thereby improving the operating efficiency of transformers.

[0102] The technical solution of the present invention has been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the scope of protection of the present invention.

Claims

1. An energy storage transformer with automatic filtering function, characterized in that, include: The data acquisition module is used to acquire real-time input current and voltage data of the power grid, input current and voltage data of energy storage devices, operating parameters of energy storage systems, and operating data of filtering devices. The filter device analysis module is used to determine the comprehensive index of the filter device based on the operating parameters of the energy storage system and the operating data of the filter device, so as to determine whether there is any abnormality in the health status of the filter device. The comprehensive index of the filter device is a weighted sum of the capacitance value change rate, the inductor temperature risk rate and the load fluctuation rate. The inductor risk rate is the ratio of the current inductor temperature of the filter device minus the normal operating temperature of the inductor to the upper limit of the safe operating temperature of the inductor minus the normal operating temperature of the inductor. The harmonic component analysis module is used to determine harmonic characteristic parameters based on the input current and voltage data of the power grid, to determine whether the harmonic components are qualified, and to determine the adjustment filter parameters based on the difference between the harmonic characteristic parameters and the preset harmonic characteristic parameters. The harmonic characteristic parameters are a weighted sum of the total harmonic distortion rate, the 3rd harmonic component, the 5th harmonic component and the 7th harmonic component. The harmonic degradation risk analysis module is used to determine the harmonic variation characterization coefficient based on the operating parameters of the energy storage system to determine whether the harmonic degradation risk meets the standard, and to determine the adjustment filter response frequency based on the relative difference between the harmonic variation characterization coefficient and the preset harmonic variation characterization coefficient, wherein the harmonic variation characterization coefficient is based on the weighted sum of the harmonic characteristic change rate, the energy storage system state of charge change rate and energy conversion efficiency. The filter performance analysis module is used to determine the filter performance loss value based on the operating data of the filter device, so as to determine whether the working efficiency of the filter device meets the standard, and to determine the optimized capacitor value or inductor temperature according to the ratio of the filter performance loss value to the preset filter performance loss value. The filter performance loss value is the ratio of the difference between the designed filter performance and the current filter performance to the designed filter performance. The current filter performance is the ratio of the target harmonic suppression requirement value to the total harmonic distortion rate at the input.

2. The energy storage transformer with automatic filtering function according to claim 1, characterized in that, The filter device analysis module determines that the filter device's health status is abnormal based on the comparison result that the filter device's comprehensive index is greater than the preset filter device comprehensive index.

3. The energy storage transformer with automatic filtering function according to claim 2, characterized in that, The harmonic component analysis module determines that the harmonic component is unqualified based on the comparison result of the harmonic characteristic characterization parameter being greater than the preset harmonic characteristic characterization parameter.

4. The energy storage transformer with automatic filtering function according to claim 3, characterized in that, The process of obtaining the harmonic characteristic parameters includes: The real-time collected power grid input current and voltage data are decomposed by fast Fourier transform to obtain the effective values ​​of the fundamental wave and each harmonic. Calculate the total harmonic distortion (THD); Extract the 3rd, 5th, and 7th harmonic components and calculate the ratio of each major harmonic to the fundamental frequency. The harmonic characteristic parameters are the product of the total harmonic distortion rate and a weight of 0.4, the product of the 3rd harmonic component and a weight of 0.3, the product of the 5th harmonic component and a weight of 0.2, and the product of the 7th harmonic component and a weight of 0.

1.

5. The energy storage transformer with automatic filtering function according to claim 4, characterized in that, The harmonic component analysis module, upon determining that the harmonic components are unqualified, determines the adjustment filter parameters based on a comparison between the difference between the harmonic characteristic characterization parameters and the preset harmonic characteristic characterization parameters and a preset difference. Based on the comparison results where the difference is less than or equal to the preset difference, the number of capacitors to be switched is increased by a preset capacitor switching quantity adjustment coefficient. Based on the comparison results where the difference is greater than the preset difference, a preset inductance value adjustment coefficient is used to reduce the filter inductance value.

6. The energy storage transformer with automatic filtering function according to claim 5, characterized in that, The harmonic degradation risk analysis module determines that the harmonic degradation risk does not meet the standard based on the comparison result that the harmonic variation characterization coefficient is greater than the preset harmonic variation characterization coefficient.

7. The energy storage transformer with automatic filtering function according to claim 6, characterized in that, The harmonic variation characterization coefficient is calculated as follows: the difference between the current harmonic characteristic characterization parameter and the previous period's harmonic characteristic characterization parameter divided by the product of the previous period's harmonic characteristic characterization parameter and a weight of 0.5, plus the product of the energy storage system's state of charge change rate and a weight of 0.3, plus the product of the energy conversion efficiency fluctuation value and a weight of 0.

2. The energy storage system's state of charge change rate is the absolute value of the difference between the current energy storage system's state of charge and the previous period's state of charge divided by the previous period's state of charge. The energy conversion efficiency fluctuation value is the standard deviation of the conversion efficiency over several sampling periods.

8. The energy storage transformer with automatic filtering function according to claim 7, characterized in that, The harmonic degradation risk analysis module, under the condition that the harmonic degradation risk does not meet the standard, determines the adjustment filter response frequency based on the comparison result of the relative difference between the harmonic variation characterization coefficient and the preset harmonic variation characterization coefficient and the preset relative difference. Based on the comparison results where the relative difference is less than or equal to a preset relative difference, the filter response frequency is increased by a first preset response frequency adjustment coefficient. Based on the comparison result where the relative difference is greater than the preset relative difference, the filter response frequency is increased by a first preset response frequency adjustment coefficient.

9. The energy storage transformer with automatic filtering function according to claim 8, characterized in that, The filtering efficiency analysis module determines that the working efficiency of the filtering device is substandard based on the comparison result of the filtering efficiency loss value being greater than the preset filtering efficiency loss value.

10. The energy storage transformer with automatic filtering function according to claim 9, characterized in that, The filter performance analysis module, under the condition that the working efficiency of the filter device is not up to standard, determines the optimal capacitor value or inductor temperature based on the comparison result of the ratio of the filter performance loss value to the preset filter performance loss value and the preset ratio. Based on the comparison results where the ratio is less than or equal to a preset ratio, the capacitance value is increased by a preset capacitance value adjustment coefficient. Based on the comparison result where the ratio is greater than the preset ratio, the inductor temperature is determined to be reduced by a preset inductor temperature adjustment coefficient.

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