Thermal management method and system for network construction type energy storage converter

Abstract

The invention relates to the technical field of power system monitoring, and particularly discloses a thermal management method and system for a network-building type energy storage converter, and the method comprises the steps: obtaining the historical part temperature information and real-time operation information of all parts of the network-building type energy storage converter, and obtaining the real-time thermal stress grade of the network-building type energy storage converter according to the real-time operation information, the real-time thermal stress grade comprises high-grade thermal stress, middle-grade thermal stress and low-grade thermal stress; obtaining physical information of each component material of the network-forming type energy storage converter, and generating component temperature distribution information according to the physical information of each component and the real-time thermal stress grade; and obtaining a temperature mapping value of each component according to the component temperature distribution information and the historical component temperature information. Through comprehensive consideration of input and output power, frequency, environment temperature and the like of components, thermal stress is accurately evaluated, risks are prevented in advance, and stable operation of the system is guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of power system monitoring, and in particular to a thermal management method and system for a network-forming energy storage converter. Background Art

[0002] The network-forming energy storage converter is mainly used to realize the conversion and control of electric energy, and can bidirectionally convert electric energy between the DC side and the AC side at different voltage levels and frequencies. On the DC side, it can convert the DC electric energy from a battery pack or other energy storage devices into high-quality AC electric energy.

[0003] Existing thermal management may only simply monitor some temperature information, and fail to comprehensively collect the historical component temperature information and real-time operation information of each component of the converter, including multi-faceted data such as power, frequency, and ambient temperature. It is difficult to comprehensively consider the influence of these factors on thermal stress, so it is impossible to accurately evaluate the thermal state of the components, easily miss early thermal risks, and increase the risk of component damage. Summary of the Invention

[0004] The purpose of the present invention is to provide a thermal management method and system for a network-forming energy storage converter to solve the technical problems raised in the above background art.

[0005] To achieve the above purpose, the present invention provides the following technical solutions:

[0006] A thermal management method for a network-forming energy storage converter includes:

[0007] Obtain the historical component temperature information and real-time operation information of each component of the network-forming energy storage converter, and obtain the real-time thermal stress level of the network-forming energy storage converter according to the real-time operation information, where the real-time thermal stress level includes high-level thermal stress, medium-level thermal stress, and low-level thermal stress;

[0008] Obtain the physical information of the materials of each component of the network-forming energy storage converter, and generate component temperature distribution information according to the physical information of each component and the real-time thermal stress level;

[0009] Obtain the temperature mapping value of each component according to the component temperature distribution information and the historical component temperature information;

[0010] Obtain the real-time monitored ambient temperature value of each component according to the real-time operation information, and obtain the thermal state evaluation information of each component according to the real-time monitored ambient temperature value and the temperature mapping value;

[0011] Obtain the operating thermal state evaluation value of the corresponding component according to the thermal state evaluation information;

[0012] Judge whether the operating thermal state evaluation value is less than the preset threshold interval;

[0013] If it is less than the minimum value of the preset threshold range, it is determined that the component is in a normal state and no adjustment is required;

[0014] If it is within the preset threshold range, it is determined that the component is in an overheat warning state and a warning signal is generated;

[0015] If it is greater than the maximum value of the preset threshold range, it is determined that the component is in an overheat state, and a temperature adjustment value is obtained based on the operating thermal state evaluation value, and the component is cooled and adjusted based on the temperature adjustment value.

[0016] Preferably, the step of obtaining the real-time thermal stress level of the grid-forming energy storage converter according to the real-time operation information includes:

[0017] Obtain component power data according to the real-time operation information, where the component power data includes a component input power value and a component output power value;

[0018] Obtain the component operating frequency according to the real-time operation information;

[0019] Obtain the frequency loss coefficient according to the component operating frequency;

[0020] Calculate the frequency power loss value according to the component input power value, the component output power value, the component operating frequency and the frequency loss coefficient, where the calculation formula is:

[0021] P f =(P in -P out )*(k f *f);

[0022] Among them, P f represents the frequency power loss value, P in represents the component input power value, P out represents the component output power value, k f represents the frequency loss coefficient, and f represents the component operating frequency;

[0023] Obtain the ambient temperature and obtain the heat transfer quantity value according to the ambient temperature;

[0024] Obtain the corrected power loss value according to the heat transfer quantity value and the frequency power loss value;

[0025] Judge whether the corrected power loss value is less than the preset threshold range;

[0026] If it is less, it is determined that the corresponding component is in a low-level thermal stress;

[0027] If it is in, it is determined that the corresponding component is in a medium-level thermal stress;

[0028] If it is greater than, it is determined that the corresponding component is in a high-level thermal stress.

[0029] Preferably, the step of generating component temperature distribution information according to the physical information and real-time thermal stress level of each component includes:

[0030] Obtain the thermal conductivity value, specific heat capacity value, and density value according to the physical information;

[0031] Obtain the material thermal diffusivity corresponding to each component according to the thermal conductivity value, specific heat capacity value, and density value;

[0032] Correct the material thermal diffusivity according to the real-time thermal stress level to obtain the corrected material thermal diffusivity;

[0033] Obtain the real-time heat generation value of the component according to the corrected power loss value;

[0034] Obtain the corrected component temperature value corresponding to each component according to the corrected material thermal diffusivity and the real-time heat generation value of the component;

[0035] Obtain the position information of each component in the energy storage converter;

[0036] Generate component temperature distribution information according to the position information and corrected component temperature value corresponding to all components.

[0037] Preferably, the step of obtaining the temperature mapping value of each component according to the component temperature distribution information and historical component temperature information includes:

[0038] Obtain the corrected component temperature value of each component according to the component temperature distribution information, and use the corrected component temperature value as the real-time data point temperature value;

[0039] Obtain the maximum temperature value and minimum temperature value corresponding to each component according to the historical component temperature information;

[0040] Normalize and calculate the temperature mapping value of the corresponding component according to the real-time data point temperature value, maximum temperature value, and minimum temperature value. The calculation formula is:

[0041]

[0042] Where, T NORM represents the temperature mapping value, T represents the real-time data point temperature value, T min represents the minimum temperature value, T max represents the maximum temperature value.

[0043] Preferably, the step of obtaining the thermal state fluctuation value of each component according to the real-time monitored environmental temperature value and temperature mapping value includes:

[0044] Obtain a preset interval time;

[0045] Based on the preset interval time, obtain multiple ambient interval temperatures according to the real-time monitored ambient temperature value;

[0046] Obtain the ambient temperature change rate according to the multiple ambient interval temperatures;

[0047] Obtain the ambient temperature change coefficient according to the ambient temperature change rate;

[0048] Obtain the thermal state fluctuation value according to the ambient temperature change rate, the ambient temperature change coefficient and the temperature mapping value.

[0049] Preferably, the step of obtaining the running thermal state evaluation value of the corresponding component according to the thermal state fluctuation value includes:

[0050] Obtain the thermal expansion coefficient according to the physical information;

[0051] Obtain the component material influence value according to the thermal expansion coefficient and the thermal state fluctuation value;

[0052] Obtain the operation duty cycle of each component;

[0053] Obtain the component frequency influence value according to the operation duty cycle and the component working frequency;

[0054] Obtain the running thermal state evaluation value according to the component material influence value, the component frequency influence value and the thermal state fluctuation value.

[0055] Preferably, the step of obtaining the temperature adjustment value according to the running thermal state evaluation value and performing a cooling adjustment on the component based on the temperature adjustment value includes:

[0056] Obtain the corrected material thermal diffusivity of the corresponding component according to the running thermal state evaluation value;

[0057] Obtain the heat diffusion area value around the component based on the corrected material thermal diffusivity;

[0058] Obtain the heat diffusion efficiency value according to the heat diffusion area value and the corrected component temperature value;

[0059] Obtain the preset convective heat transfer coefficient according to the heat diffusion efficiency value;

[0060] Obtain the diffused heat value according to the heat diffusion efficiency value and the preset convective heat transfer coefficient, and obtain the temperature adjustment value according to the diffused heat value;

[0061] Obtain the laminar flow heat dissipation wind speed of the regulating component according to the temperature adjustment value;

[0062] Obtain the real-time fan heat dissipation wind speed for the temperature control fan;

[0063] Adjust the temperature control fan based on the real-time fan heat dissipation wind speed until the real-time fan heat dissipation wind speed is equal to the laminar flow heat dissipation wind speed of the control component layer.

[0064] The present invention also provides a grid-forming energy storage converter thermal management system, including:

[0065] A first acquisition module, configured to acquire the historical component temperature information and real-time operation information of each component of the grid-forming energy storage converter, and acquire the real-time thermal stress level of the grid-forming energy storage converter according to the real-time operation information, wherein the real-time thermal stress level includes high-level thermal stress, medium-level thermal stress, and low-level thermal stress;

[0066] A second acquisition module, configured to acquire the physical information of the materials of each component of the grid-forming energy storage converter, and generate component temperature distribution information according to the physical information of each component and the real-time thermal stress level;

[0067] A third acquisition module, configured to acquire the temperature mapping value of each component according to the component temperature distribution information and the historical component temperature information;

[0068] A fourth acquisition module, configured to acquire the real-time monitored ambient temperature value of each component according to the real-time operation information, and acquire the thermal state evaluation information of each component according to the real-time monitored ambient temperature value and the temperature mapping value;

[0069] A fifth acquisition module, configured to acquire the operating thermal state evaluation value of the corresponding component according to the thermal state evaluation information;

[0070] A judgment module, configured to judge whether the operating thermal state evaluation value is less than a preset threshold interval;

[0071] If it is less than the minimum value of the preset threshold interval, it is judged that the component is in a normal state and no adjustment is required;

[0072] If it is within the preset threshold interval, it is judged that the component is in an overheat warning state and a warning signal is generated;

[0073] If it is greater than the maximum value of the preset threshold interval, it is judged that the component is in an overheat state, and a temperature adjustment value is acquired according to the operating thermal state evaluation value, and the component is cooled and adjusted based on the temperature adjustment value.

[0074] Preferably, the first acquisition module includes:

[0075] A first acquisition unit, configured to acquire component power data according to the real-time operation information, wherein the component power data includes a component input power value and a component output power value;

[0076] A second acquisition unit, configured to acquire the component operating frequency according to the real-time operation information;

[0077] A third acquisition unit, configured to acquire a frequency loss coefficient according to the component operating frequency;

[0078] A first calculation unit, configured to calculate a frequency power loss value according to the component input power value, the component output power value, the component operating frequency, and the frequency loss coefficient, where the calculation formula is:

[0079] P f = (P in - P out ) * (k f * f);

[0080] Wherein, P f represents the frequency power loss value, P in represents the component input power value, P out represents the component output power value, k f represents the frequency loss coefficient, and f represents the component operating frequency;

[0081] A fourth acquisition unit, configured to acquire the ambient temperature and acquire a heat transfer quantity value according to the ambient temperature;

[0082] A fifth acquisition unit, configured to acquire a corrected power loss value according to the heat transfer quantity value and the frequency power loss value;

[0083] A sixth acquisition unit, configured to determine whether the corrected power loss value is less than a preset threshold range;

[0084] If it is less, it is determined that the corresponding component is in a low-level thermal stress;

[0085] If it is in, it is determined that the corresponding component is in a medium-level thermal stress;

[0086] If it is greater, it is determined that the corresponding component is in a high-level thermal stress.

[0087] Preferably, the second acquisition module includes:

[0088] A seventh acquisition unit, configured to acquire a thermal conductivity value, a specific heat capacity value, and a density value according to the physical information;

[0089] An eighth acquisition unit, configured to acquire a material thermal diffusivity corresponding to each component according to the thermal conductivity value, the specific heat capacity value, and the density value;

[0090] A ninth acquisition unit, configured to correct the material thermal diffusivity according to the real-time thermal stress level to obtain a corrected material thermal diffusivity;

[0091] A tenth acquisition unit, configured to acquire a real-time heat generation value of the component according to the corrected power loss value;

[0092] An eleventh acquisition unit, configured to obtain a component corrected temperature value corresponding to each component according to the corrected material thermal diffusivity and the real-time heat generation value of the component;

[0093] A twelfth acquisition unit, configured to obtain the position information of each component in the energy storage converter;

[0094] A thirteenth acquisition unit, configured to generate component temperature distribution information according to the position information and the component corrected temperature value corresponding to all components.

[0095] The beneficial effects of the present application are as follows: By comprehensively considering the input and output power, frequency, ambient temperature, etc. of components, the present invention accurately evaluates thermal stress, prevents risks in advance, and ensures the stable operation of the system. Generating an accurate temperature distribution using component physical information can effectively improve heat dissipation. By means of normalized calculation to obtain a temperature mapping value, it can accurately judge abnormal component temperatures and avoid misjudgment. Dynamically monitoring the ambient temperature to obtain a thermal state fluctuation value for timely adjustment. Also, forming an operating thermal state evaluation value by integrating the thermal expansion coefficient, duty cycle, etc., providing a basis for maintenance decisions, optimizing resource allocation, significantly enhancing the reliability, efficiency, and lifespan of the system, and being applicable to various application scenarios. Description of the Drawings

[0096] Figure 1 It is a schematic flowchart of the method according to an embodiment of the present application.

[0097] Figure 2 It is a schematic structural diagram of the system according to an embodiment of the present application.

[0098] The realization, functional features, and advantages of the purpose of the present application will be further described in conjunction with the embodiments with reference to the drawings. Detailed Embodiments

[0099] It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0100] As Figure 1 shown, the present application provides a grid-forming energy storage converter thermal management method, including:

[0101] S1. Obtain the historical component temperature information and real-time operation information of each component of the grid-forming energy storage converter, and obtain the real-time thermal stress level of the grid-forming energy storage converter according to the real-time operation information, where the real-time thermal stress level includes high-level thermal stress, medium-level thermal stress, and low-level thermal stress;

[0102] S2. Obtain the physical information of the materials of each component of the grid-forming energy storage converter, and generate component temperature distribution information according to the physical information of each component and the real-time thermal stress level;

[0103] S3. Obtain the temperature mapping value of each component according to the component temperature distribution information and the historical component temperature information;

[0104] S4. Obtain the real-time monitored ambient temperature value of each component according to the real-time operation information, and obtain the thermal state evaluation information of each component according to the real-time monitored ambient temperature value and the temperature mapping value;

[0105] S5. Obtain the running thermal state evaluation value of the corresponding component according to the thermal state evaluation information;

[0106] S6. Determine whether the running thermal state evaluation value is less than the preset threshold range;

[0107] If it is less than the minimum value of the preset threshold range, determine that the component is in a normal state and no adjustment is required;

[0108] If it is within the preset threshold range, determine that the component is in an overheat warning state and generate a warning signal;

[0109] If it is greater than the maximum value of the preset threshold range, determine that the component is in an overheat state, obtain the temperature adjustment value according to the thermal state evaluation value, and perform a cooling adjustment on the component based on the temperature adjustment value.

[0110] As described in the above steps S1 - S6, traditional technologies often can only perform simple temperature monitoring on the converter components, and cannot comprehensively and dynamically obtain the historical component temperature information and real-time operation information of each component to comprehensively determine the thermal stress level. This results in that in actual operation, it is difficult for operation and maintenance personnel to detect potential thermal risks in advance and easily miss early fault hazards. For example, in some traditional small energy storage systems, the component temperature may only be manually recorded at specific time periods, and it is impossible to track in real time the impact of key operation information such as power change and working frequency on the thermal state. When the thermal stress of the component gradually accumulates, it cannot be discovered and measures cannot be taken in time, increasing the risk of component damage and system failure;

[0111] The present invention obtains the historical component temperature information and real-time operation information of each component, and then obtains the real-time thermal stress level of the grid-type energy storage converter according to the real-time operation information. By continuously collecting its historical temperature data and combining real-time operation information such as input and output power and operating frequency to calculate the thermal stress level, the operation and maintenance personnel can detect potential thermal risks in advance and avoid component damage or performance degradation due to thermal stress accumulation. Then, the physical information of the materials of each component of the grid-type energy storage converter is obtained, and the component temperature distribution information is generated based on this information and the determined real-time thermal stress level. It takes into account the correlation between the material properties of the component and the thermal stress level, so that it can more accurately reflect the temperature field condition inside the converter, which helps to accurately identify the key areas with higher temperatures and the weak components that are easily affected by temperature. For example, the capacitor group in the energy storage converter, due to the thermal conductivity and specific heat capacity characteristics of its material, under high-level thermal stress, the temperature abnormality of the central part can be found with the help of the generated temperature distribution information, and then targeted measures such as adding heat sinks can be taken to ensure its stable operation. Subsequently, the temperature mapping value of each component is obtained according to the component temperature distribution information and the historical component temperature information. It integrates the current temperature with the historical data to realize the normalized evaluation of the component temperature change, making the temperature change trends between different components comparable, greatly improving the accuracy and effectiveness of thermal status monitoring. The real-time monitoring environment temperature value of each component is obtained according to the real-time operation information, and then the thermal status evaluation information of each component is obtained in combination with the temperature mapping value, so that the thermal status evaluation is more in line with the actual operation situation, effectively reducing the possibility of misjudgment and missed judgment, just like introducing the key variable of the external environment in thermal management. The evaluation results are more real and reliable. Then, the operating thermal state evaluation value of the corresponding component is obtained based on the thermal state evaluation information, which is convenient for comparing and ranking the thermal performance of different components, helping operation and maintenance personnel to quickly determine the focus of attention and reasonably allocate maintenance resources. Finally, it is determined whether the operating thermal state evaluation value is less than the preset threshold interval. If it is less than the minimum value, the component is judged to be in a normal state and no adjustment is required; if it is within the interval, it is judged to be in an overheating warning state and a warning signal is generated; if it is greater than the maximum value, it is determined to be in an overheating state, and the temperature adjustment value is obtained based on the thermal state evaluation value, based on which the component is cooled and adjusted. This link realizes the automation and intelligence of thermal management, can timely detect overheating problems and effectively deal with them, avoid damage to components due to overheating, extend service life, reduce manual intervention, and improve system reliability and operation and maintenance efficiency.

[0112] In one embodiment, the step of obtaining the real-time thermal stress level of the grid-connected energy storage converter according to the real-time operation information includes:

[0113] S101, acquiring component power data according to the real-time operation information, wherein the component power data includes a component input power value and a component output power value;

[0114] S102. Obtain the component working frequency according to the real-time operation information;

[0115] S103. Obtain the frequency loss coefficient according to the component working frequency;

[0116] S104. Calculate the frequency power loss value according to the component input power value, component output power value, component working frequency and frequency loss coefficient, where the calculation formula is:

[0117] P f =(P in -P out )*(k f *f);

[0118] Among them, P f represents the frequency power loss value, P in represents the component input power value, P out represents the component output power value, k f represents the frequency loss coefficient, and f represents the component working frequency;

[0119] S105. Obtain the ambient temperature and obtain the heat transfer quantity value according to the ambient temperature;

[0120] S106. Obtain the corrected power loss value according to the heat transfer quantity value and the frequency power loss value;

[0121] S107. Determine whether the corrected power loss value is less than the preset threshold range;

[0122] If it is less, determine that the corresponding component is in a low-level thermal stress;

[0123] If it is in, determine that the corresponding component is in a medium-level thermal stress;

[0124] If it is greater, determine that the corresponding component is in a high-level thermal stress.

[0125] As described in the above steps S101 - S107, the basis for the present invention to evaluate the thermal stress of the converter is to obtain the component power data. By accurately grasping the input and output power values of the components, it is possible to directly understand the working intensity of the components during the energy conversion process, solving the problem of vague understanding of the power load of components in traditional management. In the past technologies, only the overall power situation of the converter might be concerned, while ignoring the power differences among various components. Then, by obtaining the component working frequency, different working frequencies will cause changes in the electromagnetic and mechanical losses inside the components, thereby affecting the generation of heat. Accurately obtaining the working frequency enables the operation and maintenance personnel to deeply understand the operating state of the components from the frequency dimension, solving the defect of insufficient consideration of the relationship between the working frequency and heat generation in previous thermal management. Traditional thermal management methods may not fully recognize the importance of the working frequency on component heating. After that, by obtaining the frequency loss coefficient, which reflects the quantitative relationship between the working frequency and power loss, it enables more accurate consideration of the influence of frequency factors on heating when evaluating thermal stress, improving the accuracy and reliability of thermal stress calculation, and solving the problem of lacking an accurate coefficient when calculating frequency power loss. By obtaining the frequency power loss value through an accurate calculation formula, it can comprehensively reflect the heat generated by the components during operation due to the combined action of power and frequency factors, enabling the operation and maintenance personnel to more scientifically judge the heating degree of the components, making up for the problem in traditional methods that cannot accurately quantify the heating caused by the combined action of power and frequency. Then, considering the environmental temperature and obtaining the heat transfer quantity value can incorporate external environmental factors into the thermal stress evaluation system. The level of the environmental temperature directly affects the heat dissipation efficiency of the components. By quantifying the heat transfer quantity value, the operation and maintenance personnel can clearly understand the degree of influence of the environment on component heat dissipation, thereby more accurately judging the actual thermal state of the components, solving the problem of ignoring the influence of environmental temperature on component heat dissipation in traditional thermal management. In actual operation, the change of environmental temperature may greatly change the heat dissipation conditions of the components, which may lead to misjudgment of the thermal state of the components and affect the effect of thermal management. After that, by obtaining the corrected power loss value, which combines the influence of frequency power loss and environmental factors on heat, it makes the evaluation of component heating conditions closer to the actual operating conditions. It can more accurately reflect the thermal stress level of the components in the real environment, providing a more reliable basis for subsequent thermal state judgment, overcoming the limitation of evaluating thermal stress only relying on a single power loss value in the past. Traditional methods may not consider the correction effect of environmental factors on power loss, resulting in inaccurate evaluation of thermal stress. Finally, through clear threshold judgment and grade division, it is possible to intuitively classify the thermal stress state of the components. This enables the operation and maintenance personnel to quickly understand the degree of thermal risk of the components, facilitating the adoption of corresponding management measures, improving the efficiency and pertinence of thermal management, ensuring the safe and stable operation of the system, and solving the problem of difficultly quickly judging the thermal stress grade of components in a complex converter system.In the past, there may not have been a clear judgment standard and grading, and operation and maintenance personnel needed to spend a lot of time and energy analyzing the thermal state of components, which was prone to misjudgment or missed judgment.

[0126] In one embodiment, the step of generating component temperature distribution information according to the physical information and real-time thermal stress level of each component includes:

[0127] S201. Obtain the thermal conductivity value, specific heat capacity value, and density value according to the physical information;

[0128] S202. Obtain the material thermal diffusivity corresponding to each component according to the thermal conductivity value, specific heat capacity value, and density value;

[0129] S203. Correct the material thermal diffusivity according to the real-time thermal stress level to obtain the corrected material thermal diffusivity;

[0130] S204. Obtain the real-time heat generation value of the component according to the corrected power loss value;

[0131] S205. Obtain the corrected temperature value of each component according to the corrected material thermal diffusivity and the real-time heat generation value of the component;

[0132] S206. Obtain the position information of each component in the energy storage converter;

[0133] S207. Generate component temperature distribution information according to the position information and corrected temperature value of all components.

[0134] As described in the above steps S201-S207, the present invention obtains the thermal conductivity value, specific heat capacity value, and density value according to the physical information. For example, in the insulating ceramic component of a high-voltage DC transmission energy storage system, its thermal conductivity is 2.0 W / (m·K), specific heat capacity is 800 J / (kg·K), and density is 3500 kg / m 3, which helps to deeply understand the heat transfer and storage mechanisms of components in a thermal environment, solves the problem of inaccurate understanding of the thermal properties of component materials in traditional thermal management, and provides an important basis for subsequent thermal management. Then, the thermal diffusivity of each component's corresponding material is calculated based on the obtained thermal conductivity value, specific heat capacity value, and density value. It comprehensively reflects the speed of heat propagation in the material when heated and can intuitively compare the heat transfer performance of different component materials. Just like in the converter of a new energy energy storage power station, by calculating the thermal diffusivity of the aluminum heat sink and copper terminal, the difference between them is found. Then, when designing the cooling system, it is possible to reasonably arrange according to this characteristic, solving the problem that it was impossible to quantitatively compare the heat transfer speeds of different component materials in the past. Subsequently, the thermal diffusivity of the material is corrected according to the real-time thermal stress level to obtain the corrected thermal diffusivity of the material. During actual operation, the thermal stress borne by the component will affect its material's microstructure and thermophysical properties. Considering this factor can make the prediction of the component temperature distribution more in line with reality. For example, when the power module of an industrial variable frequency speed regulation energy storage system is under high-level thermal stress, the thermal diffusivity of its material is corrected, avoiding the temperature distribution calculation deviation caused by ignoring the influence of thermal stress on the thermal diffusivity of the material. Then, the maintenance personnel can adjust the cooling strategy according to the correction result to ensure the stable operation of the component. Then, the real-time heat generation value of the component is obtained based on the corrected power loss value. This step accurately quantifies the heat generation situation of the component during actual operation. It considers various factors such as the operating power, frequency, and environment of the component, making up for the deficiency of inaccurate calculation of the actual heat generation of the component in traditional methods. Taking the inductor component in the grid energy storage converter as an example, by calculating its heat generation value within a certain period of time, the maintenance personnel can clearly master its heat generation source and provide a basis for cooling measures under different load conditions. After that, the corrected temperature value of each component is obtained based on the corrected thermal diffusivity of the material and the real-time heat generation value of the component. This step comprehensively considers the material heat transfer characteristics and actual heat generation and can more accurately reflect the actual temperature change of the component, overcoming the problems of simplistic and inaccurate temperature calculation of components in traditional thermal management. For example, in the MOSFET device of an electronic device energy storage converter, by accurately calculating its corrected temperature value, the maintenance personnel can timely discover potential overheating hazards and take corresponding cooling measures to avoid device damage due to overheating. At the same time, the position information of each component in the energy storage converter is obtained. The position of the component will affect its cooling conditions and heat transfer path, which is crucial for analyzing the thermal interaction between components and the overall thermal distribution. Just like in the converter of a large energy storage power station, by analyzing the structural design drawings or three-dimensional modeling to determine the component position, it is found that the ventilation condition of the battery management system module located in the bottom corner is poor, so its cooling conditions can be improved targeted, solving the problem of lack of attention to the position relationship of components in the past. Finally, the component temperature distribution information is generated based on the position information and corrected temperature value of all components. It is convenient for the maintenance personnel to discover components and areas with abnormal temperatures.For example, in a smart grid energy storage converter, the temperature distribution is presented as a color heat map, and the operation and maintenance personnel can clearly see the temperature differences in different regions, so as to strengthen the heat dissipation measures for high-temperature regions, solve the problem that traditional thermal management cannot comprehensively grasp the temperature distribution of the converter, provide a visual basis for formulating a comprehensive thermal management plan, and ensure the stable operation of the system.

[0135] In one embodiment, the step of obtaining the temperature mapping value of each component according to the component temperature distribution information and the historical component temperature information includes:

[0136] S301. Obtain the component correction temperature value of each component according to the component temperature distribution information, and use the component correction temperature value as the real-time data point temperature value;

[0137] S302. Obtain the maximum temperature value and the minimum temperature value corresponding to each component according to the historical component temperature information;

[0138] S303. Calculate the temperature mapping value of the corresponding component by normalizing the real-time data point temperature value, the maximum temperature value and the minimum temperature value, where the calculation formula is:

[0139]

[0140] Where, T NORM represents the temperature mapping value, T represents the real-time data point temperature value, T min represents the minimum temperature value, T max represents the maximum temperature value.

[0141] As described in the above steps S301-S303, the present invention obtains the component correction temperature value of each component according to the component temperature distribution information, and uses it as the real-time data point temperature value, because it uses advanced temperature sensor networks or thermal imaging technology, combined with various factors, to accurately reflect the actual temperature of the component under the current complex working state. Taking the power semiconductor module in a large industrial energy storage inverter system as an example, by arranging multiple temperature sensors at key positions and combining multiple calculations and analyses, an accurate component correction temperature value, such as 75°C, is obtained. As a real-time data point temperature value, it more accurately shows the current thermal state of the component than the traditional temperature measured by a single sensor, providing a reliable data basis for subsequent evaluation, and solving the problem that traditional temperature monitoring cannot accurately grasp the current temperature of the component. Then, the maximum temperature value and the minimum temperature value corresponding to each component are obtained based on the historical component temperature information. The importance of this step is that it allows us to know the temperature fluctuation range of the components in the past operation by screening and statistically analyzing the historical temperature data stored in the database or data recording system. For example, in the capacitor group component in the distributed energy storage system, by analyzing its historical data, we found that the maximum temperature was 80°C and the minimum temperature was 30°C. This allows us to grasp the temperature change law of the component from the time dimension, and then explore the reasons for the temperature fluctuation, such as whether it is affected by factors such as season and load, which provides a basis for subsequent targeted measures, so that we have a clearer understanding of the long-term thermal performance and temperature stability of the component. Then, according to the real-time data point temperature value, the maximum temperature value and the minimum temperature value, the normalization calculation is performed to obtain the temperature mapping value of the corresponding component. This step uses a specific calculation formula to evaluate the real-time temperature of the component in the context of its historical temperature range, so that the temperatures of different components can be compared and judged on the same scale. For example, in the energy storage converter of the smart grid, for the power semiconductor module, the real-time data point temperature value is 75°C, the maximum temperature value is 85°C, the minimum temperature value is 60°C, and the calculated temperature mapping value is 0.6; for the inductor component, the real-time data point temperature value is 45°C, the maximum temperature value is 55°C, the minimum temperature value is 35°C, and its temperature mapping value is 0.5. Through this normalized calculation, the problem that it is difficult to directly compare the degree of temperature anomaly of different components due to different working characteristics and materials is solved, so that we can clearly judge which components have a greater degree of temperature deviation from the normal range, which helps to identify the temperature anomaly of the component and avoid misjudgment, so that operation and maintenance personnel can more reasonably allocate maintenance resources and adjust maintenance strategies.

[0142] In one embodiment, the step of acquiring the thermal state fluctuation value of each component according to the real-time monitoring ambient temperature value and the temperature mapping value includes:

[0143] S401, obtaining a preset interval time;

[0144] S402. Obtain multiple ambient interval temperatures based on the real-time monitored ambient temperature value according to the preset interval time;

[0145] S403. Obtain the ambient temperature change rate according to the multiple ambient interval temperatures;

[0146] S404. Obtain the ambient temperature change coefficient according to the ambient temperature change rate;

[0147] S405. Obtain the thermal state fluctuation value according to the ambient temperature change rate, the ambient temperature change coefficient, and the temperature mapping value.

[0148] As described in the above steps S401 - S405, the present invention avoids the problems of data chaos and inaccurate evaluation caused by irregular time selection in previous thermal state monitoring by obtaining a preset interval time. For example, in the energy storage converter in an industrial environment, according to its operating characteristics and past experience, the preset interval time can be set to 30 minutes, which provides a consistent time reference for subsequent temperature monitoring and analysis. Then, based on the preset interval time, multiple ambient interval temperatures are obtained according to the real - time monitored ambient temperature value. This step can obtain the time - series data of the ambient temperature by measuring the ambient temperature multiple times within the specified time interval, thus reflecting the change of the ambient temperature over time and solving the problem of insufficient understanding of the dynamic information of the ambient temperature in traditional monitoring. Taking the energy storage converter system located on the edge of the city as an example, according to the preset interval time of 15 minutes and using a high - precision temperature sensor for regular measurement, a temperature sequence such as [25℃, 26℃, 27℃, 28℃, 25.5℃, 26.5℃…] can be obtained, enabling us to clearly see the fluctuation of the ambient temperature within a day, rather than only focusing on the temperatures at a few fixed time points. Subsequently, the ambient temperature change rate is obtained according to multiple ambient interval temperatures. The beneficial effect of this step is to quantify the change of the ambient temperature, allowing us to intuitively understand how fast the ambient temperature changes and overcoming the difficulty of quantitatively analyzing the change trend of the ambient temperature in traditional monitoring. It can be calculated by ambient temperature change rate = (current ambient interval temperature - previous ambient interval temperature) / preset interval time. In the energy storage converter system of the smart grid, when the ambient temperature change rate at noon is calculated to be 10℃ / hour, the operation and maintenance personnel can know that the ambient temperature is rising rapidly, providing a quantitative basis for subsequent corresponding heat dissipation measures, such as starting additional heat dissipation measures like increasing the rotation speed of the cooling fan to prevent components from overheating due to rapid changes in ambient temperature. Then, the ambient temperature change coefficient is obtained according to the ambient temperature change rate. Different ambient temperature change rates will correspond to different coefficients, solving the problem that the difference in the influence degree of different rates was not considered in previous evaluations. A mapping relationship is established based on a large amount of experimental data and theoretical analysis. For example, when the ambient temperature change rate is less than 5℃ / hour, the ambient temperature change coefficient is 0.5; between 5℃ / hour and 10℃ / hour, the coefficient is 0.8; greater than 10℃ / hour, the coefficient is 1.2. Taking the energy storage converter system in the desert area as an example, when the ambient temperature change rate is 12℃ / hour, the coefficient is 1.2, indicating that the change of the ambient temperature has a greater impact on the thermal state of the components. The operation and maintenance personnel can adjust the parameters of the heat dissipation system accordingly to ensure the thermal stability of the components in extreme environments. Finally, the thermal state fluctuation value is obtained according to the ambient temperature change rate, the ambient temperature change coefficient, and the temperature mapping value. This step comprehensively considers the dynamic change of the ambient temperature and the temperature state of the components themselves, forming a comprehensive index, solving the limitation of traditional evaluation that only focuses on a single factor and providing a more comprehensive basis for evaluating the thermal state fluctuation of components.Calculated by a specific formula (such as thermal state fluctuation value = environmental temperature change rate × environmental temperature change coefficient × temperature mapping value), in the energy storage converter of a data center, for key power conversion components, when the calculated thermal state fluctuation value is 3.84, the operation and maintenance personnel can judge whether the component is in a stable thermal state range based on this value. If it exceeds the threshold, corresponding adjustment measures will be taken, such as optimizing the cooling system or adjusting operation parameters, to ensure the stable operation of the component under different environmental temperature changes and ensure the stability of the data center.

[0149] In one embodiment, the step of obtaining the operating thermal state evaluation value of the corresponding component according to the thermal state fluctuation value includes:

[0150] S501. Obtain the thermal expansion coefficient according to the physical information;

[0151] S502. Obtain the component material influence value according to the thermal expansion coefficient and the thermal state fluctuation value;

[0152] S503. Obtain the operation duty cycle of each component;

[0153] S504. Obtain the component frequency influence value according to the operation duty cycle and the component working frequency;

[0154] S505. Obtain the operating thermal state evaluation value according to the component material influence value, the component frequency influence value and the thermal state fluctuation value.

[0155] As described in the above steps S501 - S505, the present invention obtains the coefficient of thermal expansion based on physical information. The coefficient of thermal expansion reflects the physical property changes of the component material when the temperature changes, and can help us predict the dimensional changes of the component due to heat. If this coefficient is not considered, the internal structure of the enclosure may be damaged due to expansion when the temperature changes. After obtaining this coefficient, the operation and maintenance personnel can reserve an expansion gap or use elastic connection components to ensure the reliability of the system. Then, the component material impact value is obtained based on the coefficient of thermal expansion and the thermal state fluctuation value. This step combines the two to quantify the comprehensive impact of the thermal expansion characteristics of the material on the component performance during thermal state fluctuations, providing an index from the material perspective for evaluating the thermal state of the component. For example, by calculating the component material impact value = coefficient of thermal expansion × thermal state fluctuation value, we can more accurately judge the material stability of the component under thermal state fluctuations. In the energy storage converter of an automotive electronic system, for the components on the circuit board substrate, calculating the component material impact value allows us to know whether there will be solder joint cracking or circuit board deformation due to material expansion, so as to take reinforcement measures. Subsequently, it is required to obtain the operation duty cycle of each component. The operation duty cycle reflects the proportion of the working time of the component in the total time and is an important indicator for evaluating the operation load of the component. By monitoring the start and stop signals of the component and calculating the ratio of the working time to the total time, this value can be obtained, which solves the problem of only focusing on the instantaneous or average power in the past and ignoring the working duration. In the energy storage converter of an industrial automation production line, for the power module controlling the motor, obtaining its operation duty cycle allows us to know its high - load operation situation. For example, when the operation duty cycle is 0.8, the cooling system can be adjusted in advance to avoid overheating damage caused by long - term high - load operation. Then, the component frequency impact value is obtained based on the operation duty cycle and the component working frequency. This step combines the working frequency and working time of the component to consider the impact on the thermal state, avoiding the problem of inaccurate evaluation when considering these two factors separately. By establishing a formula (such as component frequency impact value = operation duty cycle × component working frequency × relevant constant) for calculation, in the energy storage converter of a communication base station, the component frequency impact value of the radio frequency power amplifier component changes with the traffic volume. According to this value, the cooling strategy can be adjusted to ensure the stable operation of the system. Finally, the operating thermal state evaluation value is obtained based on the component material impact value, the component frequency impact value, and the thermal state fluctuation value. This step comprehensively considers the above - mentioned factors, providing a comprehensive thermal state evaluation index for the component, which helps to overall judge the actual situation of the component. By calculating with a formula (such as operating thermal state evaluation value = component material impact value + component frequency impact value + thermal state fluctuation value), in the energy storage converter of a large - scale data center, different components have different operating thermal state evaluation values. The operation and maintenance personnel can compare the component states based on this and give priority to maintaining the components with high evaluation values. For example, for a transformer, its insulation material can be inspected, the working frequency can be adjusted, or the cooling system can be optimized to ensure the stable operation of the power supply system.

[0156] In one embodiment, the step of obtaining a temperature adjustment value according to the operating thermal state evaluation value and performing a cooling adjustment on the component based on the temperature adjustment value includes:

[0157] S601. Obtain the corrected material thermal diffusivity of the corresponding component according to the operating thermal state evaluation value;

[0158] S602. Obtain the heat diffusion area value around the component based on the corrected material thermal diffusivity;

[0159] S603. Obtain the heat diffusion efficiency value according to the heat diffusion area value and the corrected temperature value of the component;

[0160] S604. Obtain the preset convective heat transfer coefficient according to the heat diffusion efficiency value;

[0161] S605. Obtain the diffused heat value according to the heat diffusion efficiency value and the preset convective heat transfer coefficient, and obtain the temperature adjustment value according to the diffused heat value;

[0162] S606. Obtain the laminar flow heat dissipation wind speed for regulating the component according to the temperature adjustment value;

[0163] S607. Obtain the real-time fan heat dissipation wind speed for the temperature control fan;

[0164] S608. Adjust the temperature control fan based on the real-time fan heat dissipation wind speed until the real-time fan heat dissipation wind speed is equal to the laminar flow heat dissipation wind speed of the regulating component.

[0165] As described in the above steps S601 - S608, according to the evaluated value of the operating thermal state of the component, in step S601, since the thermal diffusion performance of different materials is affected by factors such as temperature and usage duration, for example, the thermal diffusivity of metal components will change at high temperatures, it is necessary to combine material characteristics, real - time temperature, etc., and through specific algorithms such as correction by the heat conduction model, calculate the corrected material thermal diffusivity of the corresponding component, which lays the foundation for subsequent heat dissipation calculations; then, in step S602, using the obtained corrected thermal diffusivity, combined with the geometric information of the shape and size of the component, such as the length, width, and height of a cuboid heat sink and the heat diffusion direction, etc., according to the heat conduction geometric model, calculate the heat diffusion area value around the component, and this value will affect the heat dissipation range and efficiency; then, in step S603, according to the heat convection and heat conduction collaborative model (the prior art will not be described in detail here), after knowing the heat diffusion area value and the corrected temperature value of the component, calculate the heat diffusion efficiency value, which comprehensively reflects the speed of heat conduction from the inside of the component to the surface and then diffusing to the surrounding environment, considering factors such as temperature difference and area; furthermore, in step S604, according to the calculated heat diffusion efficiency value, by looking up the standard coefficient under the preset working conditions, or fine - tuning according to theoretical formulas such as the laminar flow heat transfer correlation formula, obtain the preset convective heat transfer coefficient. After all, at different efficiencies, the heat transfer ability between the air flow and the component surface is different; then, in step S605, combine the heat diffusion efficiency value and the preset convective heat transfer coefficient, calculate the diffused heat value, that is, the heat dissipated from the component per unit time, and then, according to the specific heat capacity, mass, etc. of the component, use the heat balance equation to calculate the temperature adjustment value. For example, knowing the mass and specific heat capacity of an aluminum component, it can be calculated how much heat needs to be dissipated to cool it to the safe range; subsequently, in step S606, according to the temperature adjustment value, combined with the shape of the component, the thermophysical properties of the air, etc., through formula derivation such as the deformation of Newton's cooling law, calculate the laminar flow heat dissipation wind speed for regulating the component, because different temperature adjustment ranges require different wind speeds to take away heat; then, in step S607, with the help of devices such as a wind speed sensor, directly obtain the real - time fan heat dissipation wind speed for the temperature - controlled fan, so as to understand the current actual heat dissipation wind speed situation and prepare for subsequent adjustment; finally, in step S608, compare the real - time fan heat dissipation wind speed with the laminar flow heat dissipation wind speed for regulating the component. If they are not equal, control the motor speed of the temperature - controlled fan through a fan speed regulation device such as a frequency converter until the two are equal, realizing accurate matching of the heat dissipation wind speed and keeping the component stable at an appropriate temperature.This process repeats in a cycle, and the entire process is dynamically adjusted in real time according to the thermal state of the components. On the one hand, it brings the effect of precise temperature control. It can accurately calculate the temperature adjustment value based on the evaluated value of the operating thermal state of the components, and accordingly precisely control the cooling air speed, so that the temperature of the components is stabilized within the ideal range, effectively avoiding the risks of component performance degradation, shortened lifespan or even damage caused by excessive temperature, ensuring the stable operation of the entire system and ensuring smooth use by users. On the other hand, it realizes the optimization of heat dissipation resources. Instead of relying on a fixed heat dissipation mode, it flexibly adjusts according to the real-time thermal state of the components, accurately calculates the parameters related to heat diffusion, and reasonably allocates the air speed of the temperature control fan. It neither excessively consumes energy for heat dissipation (the fan does not need to operate at high speed all the time), nor can it meet the cooling requirements, improving the energy utilization efficiency and reducing the equipment operation cost.

[0166] As Figure 2 shown, the present invention also provides a grid-forming energy storage converter thermal management system, including:

[0167] The first acquisition module 1 is used to acquire the historical component temperature information and real-time operation information of each component of the grid-forming energy storage converter, and obtain the real-time thermal stress level of the grid-forming energy storage converter according to the real-time operation information, wherein the real-time thermal stress level includes high-level thermal stress, medium-level thermal stress and low-level thermal stress;

[0168] The second acquisition module 2 is used to acquire the physical information of the materials of each component of the grid-forming energy storage converter, and generate component temperature distribution information according to the physical information of each component and the real-time thermal stress level;

[0169] The third acquisition module 3 is used to obtain the temperature mapping value of each component according to the component temperature distribution information and the historical component temperature information;

[0170] The fourth acquisition module 4 is used to obtain the real-time monitored ambient temperature value of each component according to the real-time operation information, and obtain the thermal state evaluation information of each component according to the real-time monitored ambient temperature value and the temperature mapping value;

[0171] The fifth acquisition module 5 is used to obtain the operating thermal state evaluation value of the corresponding component according to the thermal state evaluation information;

[0172] The judgment module 6 is used to judge whether the operating thermal state evaluation value is less than the preset threshold interval;

[0173] If it is less than the minimum value of the preset threshold interval, it is judged that the component is in a normal state and no adjustment is required;

[0174] If it is within the preset threshold interval, it is judged that the component is in an overheat warning state and a warning signal is generated;

[0175] If it is greater than the maximum value of the preset threshold range, it is determined that the component is in an overheated state, and a temperature adjustment value is obtained based on the operating thermal state evaluation value, and the component is cooled and adjusted based on the temperature adjustment value.

[0176] In one embodiment, the first acquisition module 1 includes:

[0177] The first acquisition unit is configured to acquire component power data according to the real-time operation information, where the component power data includes a component input power value and a component output power value;

[0178] The second acquisition unit is configured to acquire the component operating frequency according to the real-time operation information;

[0179] The third acquisition unit is configured to acquire a frequency loss coefficient according to the component operating frequency;

[0180] The first calculation unit is configured to calculate a frequency power loss value according to the component input power value, the component output power value, the component operating frequency, and the frequency loss coefficient, where the calculation formula is:

[0181] P f =(P in -P out )*(k f *f);

[0182] Where, P f represents the frequency power loss value, P in represents the component input power value, P out represents the component output power value, k f represents the frequency loss coefficient, and f represents the component operating frequency;

[0183] The fourth acquisition unit is configured to acquire the ambient temperature and acquire a heat transfer amount value according to the ambient temperature;

[0184] The fifth acquisition unit is configured to acquire a corrected power loss value according to the heat transfer amount value and the frequency power loss value;

[0185] The sixth acquisition unit is configured to determine whether the corrected power loss value is less than a preset threshold range;

[0186] If it is less, it is determined that the corresponding component is in a low-level thermal stress;

[0187] If it is in, it is determined that the corresponding component is in a medium-level thermal stress;

[0188] If it is greater, it is determined that the corresponding component is in a high-level thermal stress.

[0189] In one embodiment, the second acquisition module 2 includes:

[0190] A seventh acquisition unit, configured to acquire a thermal conductivity value, a specific heat capacity value, and a density value according to the physical information;

[0191] An eighth acquisition unit, configured to acquire a material thermal diffusivity corresponding to each component according to the thermal conductivity value, the specific heat capacity value, and the density value;

[0192] A ninth acquisition unit, configured to correct the material thermal diffusivity according to the real-time thermal stress level to obtain a corrected material thermal diffusivity;

[0193] A tenth acquisition unit, configured to acquire a real-time heat generation value of a component according to the corrected power loss value;

[0194] An eleventh acquisition unit, configured to acquire a corrected temperature value of each component according to the corrected material thermal diffusivity and the real-time heat generation value of the component;

[0195] A twelfth acquisition unit, configured to acquire position information of each component in the energy storage converter;

[0196] A thirteenth acquisition unit, configured to generate component temperature distribution information according to the position information corresponding to all components and the generated corrected temperature value of the component.

[0197] Those of ordinary skill in the art can understand that all or part of the processes of implementing the methods in the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the above method embodiments. Among them, any reference to a memory, storage, value library, or other medium provided in this application and used in the embodiments can include non-volatile and / or volatile memories. Non-volatile memories can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memories can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (SSRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0198] It should be noted that in this text, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, such that a process, apparatus, article or method comprising a series of elements not only includes those elements but also other elements not expressly listed, or elements inherent to such process, apparatus, article or method. Without further limitation, an element defined by the statement "comprising an..." does not exclude the presence of additional identical elements in the process, apparatus, article or method comprising such element.

[0199] The above are only the preferred embodiments of the present invention, and do not limit the patent scope of the present invention accordingly. Any equivalent results or equivalent process transformations made by using the content of the specification and drawings of the present invention, or directly or indirectly applied in other related technical fields, are similarly included within the patent protection scope of the present invention.

Claims

1. A thermal management method for a network-forming energy storage converter, characterized in that Including: Obtain the historical component temperature information and real-time operation information of each component of the grid-forming energy storage converter, and obtain the real-time thermal stress level of the grid-forming energy storage converter according to the real-time operation information, where the real-time thermal stress level includes high-level thermal stress, medium-level thermal stress, and low-level thermal stress; Obtain the physical information of the materials of each component of the grid-forming energy storage converter, and generate component temperature distribution information according to the physical information of each component and the real-time thermal stress level; Obtain the temperature mapping value of each component according to the component temperature distribution information and the historical component temperature information; Obtain the real-time monitored ambient temperature value of each component according to the real-time operation information, and obtain the thermal state evaluation information of each component according to the real-time monitored ambient temperature value and the temperature mapping value; Obtain the operation thermal state evaluation value of the corresponding component according to the thermal state evaluation information; Judge whether the operation thermal state evaluation value is less than the preset threshold range; If it is less than the minimum value of the preset threshold range, judge that the component is in a normal state and no adjustment is required; If it is within the preset threshold range, judge that the component is in an overheat warning state and generate a warning signal; If it is greater than the maximum value of the preset threshold range, judge that the component is in an overheat state, obtain the temperature adjustment value according to the operation thermal state evaluation value, and perform a cooling adjustment on the component based on the temperature adjustment value.

2. The thermal management method of a network-forming energy storage converter according to claim 1, characterized in that, The step of obtaining the real-time thermal stress level of the grid-forming energy storage converter according to the real-time operation information includes: Obtain the component power data according to the real-time operation information, where the component power data includes the component input power value and the component output power value; Obtain the component operating frequency according to the real-time operation information; Obtain the frequency loss coefficient according to the component operating frequency; Calculate the frequency power loss value according to the component input power value, the component output power value, the component operating frequency, and the frequency loss coefficient, where the calculation formula is: P f = (P in - P out ) * (k f * f); Among them, P f represents the frequency power loss value, P in represents the component input power value, P out represents the component output power value, k f represents the frequency loss coefficient, and f represents the operating frequency of the component; Obtain the ambient temperature, and obtain the heat transfer quantity value according to the ambient temperature; Obtain the corrected power loss value according to the heat transfer quantity value and the frequency power loss value; Judge whether the corrected power loss value is less than the preset threshold range; If it is less, judge that the corresponding component is in low-level thermal stress; If it is within, judge that the corresponding component is in medium-level thermal stress; If it is greater, judge that the corresponding component is in high-level thermal stress.

3. A thermal management method for a network-forming energy storage converter according to claim 1, characterized in that, The step of generating component temperature distribution information according to the physical information of each component and the real-time thermal stress level includes: Obtain the thermal conductivity value, specific heat capacity value, and density value according to the physical information; Obtain the material thermal diffusivity corresponding to each component according to the thermal conductivity value, specific heat capacity value, and density value; Correct the material thermal diffusivity according to the real-time thermal stress level to obtain the corrected material thermal diffusivity; Obtain the real-time heat generation value of the component according to the corrected power loss value; Obtain the component corrected temperature value corresponding to each component according to the corrected material thermal diffusivity and the real-time heat generation value of the component; Obtain the position information of each component in the energy storage converter; Generate component temperature distribution information according to the position information corresponding to all components and the component corrected temperature value.

4. A grid-forming energy storage converter thermal management method according to claim 1, characterized in that The step of obtaining the temperature mapping value of each component according to the component temperature distribution information and the historical component temperature information includes: Obtaining the component correction temperature value of each component according to the component temperature distribution information, and using the component correction temperature value as the real-time data point temperature value; Obtaining the maximum temperature value and the minimum temperature value corresponding to each component according to the historical component temperature information; Normalizing and calculating the temperature mapping value of the corresponding component according to the real-time data point temperature value, the maximum temperature value and the minimum temperature value, where the calculation formula is: Among them, T NORM represents the temperature mapping value, T represents the real-time data point temperature value, T min represents the minimum temperature value, T max represents the maximum temperature value.

5. A thermal management method for a network-forming energy storage converter according to claim 1, characterized in that, The step of obtaining the thermal state fluctuation value of each component according to the real-time monitored environmental temperature value and the temperature mapping value includes: Obtaining a preset interval time; Obtaining a plurality of environmental interval temperatures according to the real-time monitored environmental temperature value based on the preset interval time; Obtaining the environmental temperature change rate according to the plurality of environmental interval temperatures; Obtaining the environmental temperature change coefficient according to the environmental temperature change rate; Obtaining the thermal state fluctuation value according to the environmental temperature change rate, the environmental temperature change coefficient and the temperature mapping value.

6. The thermal management method of a network-forming energy storage converter according to claim 1, wherein The step of obtaining the operating thermal state evaluation value of the corresponding component according to the thermal state fluctuation value includes: Obtaining the thermal expansion coefficient according to the physical information; Obtaining the component material influence value according to the thermal expansion coefficient and the thermal state fluctuation value; Obtaining the operation duty cycle of each component; Obtaining the component frequency influence value according to the operation duty cycle and the component working frequency; Obtaining the operating thermal state evaluation value according to the component material influence value, the component frequency influence value and the thermal state fluctuation value.

7. A thermal management method for a network-forming energy storage converter according to claim 1, characterized in that The step of obtaining the temperature regulation value according to the operating thermal state evaluation value and performing a cooling adjustment on the component based on the temperature regulation value includes: Obtaining the corrected material thermal diffusivity of the corresponding component according to the operating thermal state evaluation value; Obtaining the heat diffusion area value around the component based on the corrected material thermal diffusivity; Obtaining the heat diffusion efficiency value according to the heat diffusion area value and the component correction temperature value; Obtaining a preset convective heat transfer coefficient according to the heat diffusion efficiency value; Obtaining the diffused heat value according to the heat diffusion efficiency value and the preset convective heat transfer coefficient, and obtaining the temperature regulation value according to the diffused heat value; Obtaining the regulated component laminar flow heat dissipation wind speed according to the temperature regulation value; Obtaining the real-time fan heat dissipation wind speed for the temperature control fan; Adjusting the temperature control fan based on the real-time fan heat dissipation wind speed until the real-time fan heat dissipation wind speed is equal to the regulated component laminar flow heat dissipation wind speed.

8. A thermal management system for a network-forming energy storage converter, characterized in that, Including: A first acquisition module, configured to acquire the historical component temperature information and the real-time operation information of each component of the grid-forming energy storage converter, and acquire the real-time thermal stress level of the grid-forming energy storage converter according to the real-time operation information, where the real-time thermal stress level includes a high-level thermal stress, a medium-level thermal stress, and a low-level thermal stress; A second acquisition module, configured to acquire the physical information of each component material of the grid-forming energy storage converter, and generate the component temperature distribution information according to the physical information of each component and the real-time thermal stress level; A third acquisition module, configured to acquire the temperature mapping value of each component according to the component temperature distribution information and the historical component temperature information; A fourth acquisition module, configured to obtain the real-time monitored ambient temperature values of each component according to the real-time operation information, and obtain the thermal state evaluation information of each component according to the real-time monitored ambient temperature values and the temperature mapping values; A fifth acquisition module, configured to obtain the running thermal state evaluation value of the corresponding component according to the thermal state evaluation information; A judgment module, configured to judge whether the running thermal state evaluation value is less than a preset threshold range; If it is less than the minimum value of the preset threshold range, it is judged that the component is in a normal state and no adjustment is required; If it is within the preset threshold range, it is judged that the component is in an overheat warning state and a warning signal is generated; If it is greater than the maximum value of the preset threshold range, it is judged that the component is in an overheat state, and a temperature adjustment value is obtained according to the running thermal state evaluation value, and the component is cooled and adjusted based on the temperature adjustment value.

9. The thermal management system of a network-forming energy storage converter according to claim 7, characterized in that The first acquisition module includes: A first acquisition unit, configured to obtain component power data according to the real-time operation information, where the component power data includes a component input power value and a component output power value; A second acquisition unit, configured to obtain the component operating frequency according to the real-time operation information; A third acquisition unit, configured to obtain a frequency loss coefficient according to the component operating frequency; A first calculation unit, configured to calculate a frequency power loss value according to the component input power value, the component output power value, the component operating frequency, and the frequency loss coefficient, where the calculation formula is: P f = (P in - P out ) * (k f * f); Among them, P f represents the frequency power loss value, P in represents the component input power value, P out represents the component output power value, k f represents the frequency loss coefficient, and f represents the operating frequency of the component; A fourth acquisition unit, configured to obtain the ambient temperature and obtain a heat transfer quantity value according to the ambient temperature; A fifth acquisition unit, configured to obtain a corrected power loss value according to the heat transfer quantity value and the frequency power loss value; A sixth acquisition unit, configured to judge whether the corrected power loss value is less than a preset threshold range; If it is less, it is judged that the corresponding component is in a low-level thermal stress; If it is within, it is judged that the corresponding component is in a medium-level thermal stress; If it is greater, it is judged that the corresponding component is in a high-level thermal stress.

10. A grid-forming energy storage converter thermal management system according to claim 7, characterized in that, The second acquisition module includes: A seventh acquisition unit, configured to obtain a thermal conductivity value, a specific heat capacity value, and a density value according to the physical information; An eighth acquisition unit, configured to obtain the material thermal diffusivity corresponding to each component according to the thermal conductivity value, the specific heat capacity value, and the density value; A ninth acquisition unit, configured to correct the material thermal diffusivity according to the real-time thermal stress level to obtain a corrected material thermal diffusivity; A tenth acquisition unit, configured to obtain the real-time heat generation value of the component according to the corrected power loss value; An eleventh acquisition unit, configured to obtain the component corrected temperature value corresponding to each component according to the corrected material thermal diffusivity and the real-time heat generation value of the component; A twelfth acquisition unit, configured to obtain the position information of each component in the energy storage converter; A thirteenth acquisition unit, configured to generate component temperature distribution information according to the position information corresponding to all components and the component corrected temperature value generation value.

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