Temperature Management Method and System for Liquid-Cooled String-Type PCS Energy Storage Inverters

Abstract

The present invention provides a temperature management method and system for a liquid-cooled string-type PCS energy storage converter. The method includes: collecting temperature data of each string in the liquid-cooled string-type PCS energy storage converter and calculating temperature characteristic parameters to obtain a string temperature state matrix; dividing the cooling priorities of each string according to the string temperature state matrix and performing cooling resource allocation to obtain a dynamic cooling execution instruction set; identifying hot-spot strings and cold-spot strings based on the dynamic cooling execution instruction set and the string temperature state matrix and calculating a power adjustment scheme to obtain a power distribution execution matrix; selecting corresponding temperature control strategies according to environmental state parameters and the power distribution execution matrix and setting parameters for each component of the cooling system. The present invention combines dynamic cooling resource allocation, power dynamic balance, and environmental adaptability temperature control strategies, solves the problems of unreasonable cooling resource allocation and low temperature management efficiency, and realizes precise temperature management of the liquid-cooled string-type PCS energy storage converter under various working conditions.

Description

Technical Field

[0001] The present invention relates to the field of simulation technology, and in particular to a temperature management method and system for a liquid-cooled string-type PCS energy storage converter. Background Art

[0002] With the wide application of energy storage systems in scenarios such as power grid frequency modulation and peak shaving and valley filling, the liquid-cooled string-type PCS energy storage converter has gradually become the core equipment of large-scale energy storage systems due to its modular design and efficient heat dissipation characteristics. The existing temperature management methods for liquid-cooled string-type PCS energy storage converters usually manage all strings using a unified temperature threshold and a fixed cooling strategy, ignoring the temperature differences and working state differences between different strings. Especially in high-temperature environments or under high-load operating conditions, the unified cooling strategy cannot meet the personalized cooling needs of different strings, resulting in the situation that the temperature of some strings is too high while the cooling resources of some other strings are wasted. In addition, the existing technology rarely considers the coordinated control of cooling resources and power adjustment, relying only on increasing cooling resources to cope with temperature anomalies, while ignoring the possibility of achieving temperature balance through dynamic power adjustment, making the overall temperature management efficiency of the system low and unable to fully exert the performance advantages of the liquid-cooled string-type PCS energy storage converter. Summary of the Invention

[0003] The main purpose of the present invention is to solve the technical problems of unreasonable cooling resource allocation and low temperature management efficiency caused by using a unified temperature threshold and a fixed cooling strategy in the existing temperature management method for liquid-cooled string-type PCS energy storage converters;

[0004] The first aspect of the present invention provides a temperature management method for a liquid-cooled string-type PCS energy storage converter, and the temperature management method for the liquid-cooled string-type PCS energy storage converter includes:

[0005] Collect temperature data of each string in the liquid-cooled string-type PCS energy storage converter, and calculate temperature characteristic parameters based on the temperature data to obtain a string temperature state matrix;

[0006] Divide the cooling priorities of each string according to the string temperature state matrix, and allocate cooling resources according to the cooling priorities to obtain a dynamic cooling execution instruction set;

[0007] Identify a string temperature distribution map including hot spot strings and cold spot strings based on the dynamic cooling execution instruction set and the string temperature state matrix, and calculate a power adjustment scheme according to the string temperature distribution map to obtain a power allocation execution matrix;

[0008] Select a corresponding temperature control strategy according to the environmental state parameters of the liquid-cooled string-type PCS energy storage converter and the power distribution execution matrix, where the temperature control strategy is used to set parameters for each component of the cooling system corresponding to the liquid-cooled string-type PCS energy storage converter, so as to realize the temperature management of the liquid-cooled string-type PCS energy storage converter.

[0009] Optionally, in the first implementation manner of the first aspect of the present invention, the temperature data collection for each string in the liquid-cooled string-type PCS energy storage converter and the calculation of temperature characteristic parameters based on the temperature data to obtain the string temperature status matrix include:

[0010] Collect temperature data through the temperature sensor array arranged at the key points of each string PCS module and battery cluster of the liquid-cooled string-type PCS energy storage converter to obtain the original temperature data set;

[0011] Perform differential processing on the original temperature data set based on the current power state and position information of each string to obtain the string temperature threshold setting matrix;

[0012] Calculate the difference between the current temperature of each string and the corresponding threshold in the string temperature threshold setting matrix to obtain the temperature safety margin of each string;

[0013] Calculate the ratio of the temperature difference between adjacent strings to the physical distance to obtain the inter-string temperature gradient vector;

[0014] Organize the temperature safety margin and the temperature gradient vector in a matrix form according to the string number to obtain the string temperature status matrix.

[0015] Optionally, in the second implementation manner of the first aspect of the present invention, the division of the cooling priority of each string according to the string temperature status matrix and the allocation of cooling resources according to the cooling priority to obtain the dynamic cooling execution instruction set include:

[0016] Perform three-level cooling priority division on each string according to the temperature safety margin in the string temperature status matrix to obtain the string cooling priority classification table;

[0017] Adjust and calculate the speed of the main circulation pump of the cooling system of the liquid-cooled string-type PCS energy storage converter based on the string cooling priority classification table to obtain the main circulation flow control parameter;

[0018] Calculate the flow distribution ratio of the coolant pipe section corresponding to each string according to the main circulation flow control parameter and the string cooling priority classification table to obtain the grouped pipeline control instruction;

[0019] Calculate the microchannel flow adjustment scheme inside each PCS module based on the grouped pipeline control instruction and the internal thermal distribution data of each string, and obtain the microchannel control instruction;

[0020] Perform collaborative optimization processing on the main circulation flow control parameter, the grouped pipeline control instruction, and the microchannel control instruction to obtain a dynamic cooling execution instruction set.

[0021] Optionally, in the third implementation manner of the first aspect of the present invention, the adjustment calculation of the main circulation pump speed of the liquid-cooled string-type PCS energy storage converter based on the string cooling priority grading table to obtain the main circulation flow control parameter includes:

[0022] Statistically analyze the number and temperature safety margin of each priority string in the string cooling priority grading table to obtain the overall system cooling demand value;

[0023] Query the preset pump speed-flow mapping table according to the overall system cooling demand value to obtain the basic main circulation pump speed value;

[0024] When the proportion of high-priority strings exceeds the threshold, correct the basic main circulation pump speed value for emergency cooling demand to obtain the corrected pump speed value;

[0025] Based on the corrected pump speed value, calculate the pump power control curve in combination with the system pipeline pressure data to obtain the pump speed control sequence, and convert the pump speed control sequence into the pulse width modulation signal parameters recognized by the pump controller to obtain the main circulation flow control parameter.

[0026] Optionally, in the fourth implementation manner of the first aspect of the present invention, the recognition of the string temperature distribution map including the hot spot string and the cold spot string based on the dynamic cooling execution instruction set and the string temperature status matrix, and the calculation of the power adjustment scheme according to the string temperature distribution map to obtain the power distribution execution matrix includes:

[0027] Calculate the temperature deviation value of each string according to the string temperature status matrix and the cooling resource allocation in the dynamic cooling execution instruction set to obtain the string temperature deviation table;

[0028] Based on the string temperature deviation table, mark the strings with temperatures higher than the average value as hot spot strings, and mark the strings with temperatures lower than the average value as cold spot strings to obtain the string temperature distribution map;

[0029] Calculate the power reduction amount of the hot spot string and the power increase amount of the cold spot string according to the cooling resource allocation to obtain the maximum allowable power transfer amount;

[0030] Determine a power gradient transfer scheme according to the maximum allowable power transfer amount, and set hysteresis control parameters for the power transfer timing table in the gradient transfer scheme to obtain a power distribution execution matrix.

[0031] Optionally, in the fifth implementation manner of the first aspect of the present invention, the calculating the maximum power reduction amount of the hot spot string and the maximum power increase amount of the cold spot string according to the cooling resource allocation situation to obtain the maximum allowable power transfer amount includes:

[0032] Obtain the cooling resource allocation data and actual cooling capacity data of each string in the dynamic cooling execution instruction set to obtain a string cooling efficiency table;

[0033] Calculate the maximum power reduction amount of each hot spot string according to the string cooling efficiency table and the temperature deviation value of each hot spot string to obtain a hot spot power adjustable scale table;

[0034] Calculate the maximum power increase amount of each cold spot string based on the temperature margin and power carrying capacity of each cold spot string to obtain a cold spot power adjustable scale table;

[0035] Perform matching analysis on the hot spot power adjustable scale table and the cold spot power adjustable scale table to obtain an initial power transfer matching matrix;

[0036] Check the constraint conditions according to the power transfer direction and value in the initial power transfer matching matrix to obtain the maximum allowable power transfer amount.

[0037] Optionally, in the sixth implementation manner of the first aspect of the present invention, the selecting a corresponding temperature control strategy according to the environmental state parameters of the liquid-cooled string type PCS energy storage converter and the power distribution execution matrix includes:

[0038] Collect environmental temperature, humidity and prediction data to obtain an environmental state parameter set, and combine the environmental state parameter set with the power distribution execution matrix to perform operation mode recognition to obtain the current system working condition type;

[0039] Match the corresponding basic strategy group from the preset temperature control strategy library according to the current system working condition type to obtain a candidate temperature control strategy set;

[0040] Calculate and evaluate the cooling efficiency ratio of each strategy in the candidate temperature control strategy set to obtain a strategy scoring result;

[0041] Select a corresponding temperature control strategy based on the strategy scoring result, and generate control parameters for each component of the cooling system according to the temperature control strategy.

[0042] The second aspect of the present invention provides a temperature management system for a liquid-cooled string-type PCS energy storage converter. The temperature management system for the liquid-cooled string-type PCS energy storage converter includes:

[0043] A temperature monitoring module, configured to collect temperature data for each string in the liquid-cooled string-type PCS energy storage converter, and calculate temperature characteristic parameters based on the temperature data to obtain a string temperature status matrix;

[0044] A resource allocation module, configured to divide the cooling priority levels of each string according to the string temperature status matrix, and perform cooling resource allocation according to the cooling priority levels to obtain a dynamic cooling execution instruction set;

[0045] A power balance module, configured to identify a string temperature distribution map including hot spot strings and cold spot strings based on the dynamic cooling execution instruction set and the string temperature status matrix, and calculate a power adjustment scheme according to the string temperature distribution map to obtain a power allocation execution matrix;

[0046] A strategy execution module, configured to select a corresponding temperature control strategy according to the environmental status parameters of the liquid-cooled string-type PCS energy storage converter and the power allocation execution matrix, wherein the temperature control strategy is used to set parameters for each component of the cooling system corresponding to the liquid-cooled string-type PCS energy storage converter to achieve temperature management of the liquid-cooled string-type PCS energy storage converter.

[0047] The above temperature management method and system for the liquid-cooled string-type PCS energy storage converter collect temperature data for each string in the liquid-cooled string-type PCS energy storage converter and calculate temperature characteristic parameters to obtain a string temperature status matrix; divide the cooling priority levels of each string according to the string temperature status matrix and perform cooling resource allocation to obtain a dynamic cooling execution instruction set; identify hot spot strings and cold spot strings based on the dynamic cooling execution instruction set and the string temperature status matrix and calculate a power adjustment scheme to obtain a power allocation execution matrix; select a corresponding temperature control strategy according to the environmental status parameters and the power allocation execution matrix, and set parameters for each component of the cooling system. The present invention combines dynamic cooling resource allocation, power dynamic balance, and environmental adaptability temperature control strategies to solve the problems of unreasonable cooling resource allocation and low temperature management efficiency, and realizes precise temperature management of the liquid-cooled string-type PCS energy storage converter under various working conditions.

[0048] Other features and advantages of the present invention will be described in the following specification, and, in part, will be obvious from the specification, or will be understood by implementing the present invention. The objectives and other advantages of the present invention are achieved and obtained by the structures specifically pointed out in the specification, claims, and drawings.

[0049] To make the above objects, features, and advantages of the present invention more obvious and understandable, the following provides preferred embodiments in conjunction with the accompanying drawings for detailed description as follows. Description of the Drawings

[0050] Figure 1 It is a schematic diagram of the first embodiment of the temperature management method for the liquid-cooled string-type PCS energy storage converter in the embodiment of the present invention;

[0051] Figure 2 It is a schematic diagram of an embodiment of the temperature management system for the liquid-cooled string-type PCS energy storage converter in the embodiment of the present invention. Detailed Embodiments

[0052] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts fall within the scope of protection of the present invention.

[0053] The terms "including" and "having" and any variations thereof mentioned in the embodiments of the present invention are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units is not limited to the listed steps or units, but optionally further includes other unlisted steps or units, or optionally further includes other steps or units inherent to these processes, methods, products, or devices.

[0054] To facilitate the understanding of this embodiment, first, a detailed introduction is given to a temperature management method for a liquid-cooled string-type PCS energy storage converter disclosed in the embodiments of the present invention. As Figure 1 shown, this method includes the following steps:

[0055] 101. Collect temperature data for each string in the liquid-cooled string-type PCS energy storage converter, and calculate temperature characteristic parameters based on the temperature data to obtain a string temperature state matrix;

[0056] In one embodiment of the present invention, the acquisition of temperature data for each string in the liquid-cooled string-type PCS energy storage converter and the calculation of temperature characteristic parameters based on the temperature data to obtain the string temperature status matrix include: collecting temperature data through a temperature sensor array arranged at key points of each string PCS module and battery cluster of the liquid-cooled string-type PCS energy storage converter to obtain an original temperature data set; performing differential processing on the original temperature data set based on the current power status and position information of each string to obtain a string temperature threshold setting matrix; calculating the difference between the current temperature of each string and the corresponding threshold in the string temperature threshold setting matrix to obtain the temperature safety margin of each string; calculating the ratio of the temperature difference between adjacent strings to the physical distance to obtain the inter-string temperature gradient vector; and organizing the temperature safety margin and the temperature gradient vector in a matrix form according to the string number to obtain the string temperature status matrix.

[0057] Specifically, first, temperature data is collected through the temperature sensor array arranged at key points of each string PCS module and battery cluster of the liquid-cooled string-type PCS energy storage converter to obtain the original temperature dataset. Each string of this converter contains several key heat sources, including components such as IGBT modules, inductors, busbars, and the supporting battery clusters. Therefore, the sensors need to be arranged to cover these areas that are prone to generating heat or being affected by heat. The sensor types include thermocouples installed on the surface of the IGBT heat sink, fiber optic temperature sensors fixed at the outer shell or terminals of the battery cluster, temperature sensors attached to the busbar joints, and protective thermistors that can monitor the external environmental temperature. Each sensor uploads temperature data at fixed time intervals through a distributed sampling node or a bus network, and the sampling frequency is set according to the thermal inertia of the components, so as to ensure sufficient resolution for thermal changes without generating excessive data accumulation. Each sensor is calibrated before installation to ensure reliable data output in an environment with high current, electromagnetic interference, and humidity fluctuations. The original data collected by the sensors is centrally sent to the central measurement and control unit of the converter. This unit marks each temperature data with the corresponding sensor ID and timestamp, and stores these records uniformly in the original temperature dataset for subsequent query, comparison, or further calculation. This original dataset retains the sampled values without denoising or correction and has a complete record of abnormal fluctuations, so that the specific temperature readings and sensor positions can be traced back at any time when needed. To cover a variety of working scenarios, the spatial distribution of each layer inside the container is also considered in the sensor array to ensure that both the hot spot temperature in the high-load area and the overall heat diffusion in the low-power area can be obtained. The information transmission uses a communication protocol with error correction and verification functions. If sensor communication disorders or data conflicts occur, the measurement and control unit will record an abnormal identifier in the original temperature dataset. The original temperature dataset formed in this way can be output to the subsequent processing program in a timed or triggered manner, and the detection positions of each sensor are also associated with the actual physical coordinates through a mapping table for further differential analysis or model calculation. The whole process ensures the comprehensiveness of temperature data and the integrity of the acquisition process.

[0058] Next, based on the current power status and location information of each string, the original temperature dataset is differentially processed to obtain a string temperature threshold setting matrix. Here, the power status indicates the charge and discharge amplitude, load duration, and corresponding current fluctuations of each string at a certain moment, and the location information indicates the location characteristics of the environment where the string is located, such as being close to the heat dissipation air duct, far from the liquid cooling pipeline, or close to the container wall, etc. When performing differential processing, the system will first read the power resume of each string, including the average power magnitude and instantaneous peak current within a previous period of time, and combine the coordinate tags of the string in physical space to determine whether it is in a section prone to heat concentration. If a string has been in a high-power output or long-time full-load state recently, the upper limit of the reference temperature corresponding to its sensor is tightened during the threshold setting process, so that the string has a more stringent temperature critical value to timely reflect the relatively large heat dissipation pressure that the string may face. On the contrary, for strings with stable power status and good heat dissipation positions, the system reserves a relatively loose temperature allowable range for them. During this process, each sensor is assigned a weighting coefficient, which consists of a power weight and a location weight. These weights not only refer to the historical power status but also consider whether there is dense stacking of internal components or high-temperature interference from surrounding strings. Once the weighting is completed, the system corrects the reference temperature thresholds of each sensor, making the thresholds of nodes with higher heat risks lower to improve the monitoring sensitivity. All the corrected thresholds are arranged into a multi-dimensional matrix, with each row or column identifying a specific sensor or string, and the matrix elements being the corresponding temperature thresholds. For the convenience of indexing and updating, the matrix also contains a time dimension label to ensure that the threshold recalculation is triggered every time the power status is updated. The resulting string temperature threshold setting matrix can be flexibly adjusted under different working conditions, and it will not cause monitoring lags for high-load strings or over-strict monitoring for low-load strings due to a single fixed threshold. This differential processing provides a basis for subsequent data comparison and safety margin assessment.

[0059] Subsequently, the difference between the current temperature of each string and the corresponding threshold in the string temperature threshold setting matrix is calculated to obtain the temperature safety margin of each string. In this step, the current average temperature or the key sensor temperature of each string is extracted from the original temperature dataset, and then matched to the corresponding threshold entry in the threshold setting matrix generated in the previous step. The difference between the two is obtained through a simple subtraction operation, and this difference is the temperature safety margin. If the safety margin remains at a high level, it indicates that there is still a significant heat dissipation margin for the corresponding string and the over-temperature warning will not be triggered. If the safety margin approaches zero or becomes negative, it means that the current temperature of the string is close to or even exceeds the dynamic threshold, and further cooling or power limitation measures need to be taken. When implementing the calculation, the system calculates the difference for each temperature sensor under each string one by one and summarizes it into a set of safety margins in the internal data structure to accurately reflect the thermal health of each component within the string. For some data anomalies, such as a large instantaneous jump in the temperature reading of a certain sensor, it is combined with the previous change trend of the sensor to determine whether it truly reflects a thermal shock. If there is indeed a phenomenon of rapid temperature increase, the safety margin will be pulled down in real time. If it is determined to be an instantaneous interference, the system will mark this reading as a suspicious value, but still retain it in the calculation trajectory of the safety margin to avoid discarding potential information that may indicate component failure. The safety margin is not only a set of simple numerical values but can also be extended to a temperature trend curve. By observing the decrease or increase of the margin over time, it helps to locate the parts with poor heat dissipation. The whole process aims to convert the original temperature data into an intuitive risk index, facilitating the faster detection of temperature deviations and the execution of processing, while also taking into account stability and accuracy. After the difference calculation is completed, the system generates a safety margin list with numbers and timestamps for each string. The margin value of each string can be directly retrieved during query, thus helping the operation and maintenance personnel or the automatic control logic to more timely understand the thermal response situation of this string.

[0060] Next, calculate the ratio of the temperature difference between adjacent strings to the physical distance to obtain the inter-string temperature gradient vector. This step first obtains the adjacent relationship and corresponding spatial distance of each string through topological mapping. The spatial distance can be the straight-line distance between the center points of the strings, or the effective heat dissipation path formed by considering factors such as partitions and pipelines in the actual structure. Subsequently, the system obtains the temperature values of adjacent strings at the same moment from the original temperature data or the already calculated average temperature, and subtracts the two to obtain the temperature difference. Using the aforementioned physical distance, divide the temperature difference by this distance to obtain a numerical gradient. The positive or negative of the gradient indicates which side has a higher temperature. After the calculation is completed, the gradients are combined into a vector form and recorded, for example, labeled as "the temperature gradient vector from string A to string B", which is used to describe the possible heat migration trend. If the distance between two strings is relatively close and the temperature difference is large, the gradient vector will show a high heat flux density, which is particularly obvious when multiple strings are highly loaded simultaneously. For dynamic update, this calculation is performed at the same frequency as the temperature acquisition, so that observing a significant spike in a certain gradient at a certain moment can indicate that one side has started to heat up rapidly or the other side has insufficient heat dissipation. In some container designs, the orientation of the liquid cooling channels also affects the lateral heat transfer. If two adjacent strings share the same liquid cooling branch, the system will specifically identify whether there is a common cooling circuit when recording the gradient vector for reference when allocating cooling resources later. The gradient vector also helps to identify the actual heat source center. For example, if a certain string shows a high positive gradient in multiple directions, it means that the temperature of this string is much higher than that of the adjacent strings, and there will be a more obvious heat diffusion trend. This numerical gradient measurement reduces the error of relying on manual experience to judge the heat diffusion risk. The series of ratios of the temperature differences and distances between adjacent strings obtained after the operation will be centrally stored in a data table, and the heat gradient intensity of any pair of strings can be quickly indexed during query. In this way, a real-time heat transfer map can be formed in the system, providing a more targeted reference for overall temperature management.

[0061] Finally, the temperature safety margin and the temperature gradient vector are organized in a matrix according to the string number to obtain the string temperature state matrix. Starting from the safety margin list of each string and the gradient vector data table corresponding to the adjacent string, the process assigns a unique row or column identifier to each string, records the safety margin value in the corresponding unit, and then fills in the relevant temperature gradient information in the interactive unit with the adjacent string. If a string has a gradient with multiple adjacent strings, multiple non-zero fields will appear in the matrix structure, indicating different degrees of heat exchange trends between each other. The matrix organization method can simultaneously display the absolute temperature risk (i.e., safety margin) and the relative temperature relationship (i.e., gradient vector) of each string in a table, so that any analysis or calculation module can retrieve all thermal characteristic values in one place. To ensure the timeliness of the data, the system adds the timestamp correction of each string and the adjacent relationship when writing the matrix, and uniformly calibrates the exact time of data update through the internal clock to avoid inconsistent matrix data due to differences in acquisition timing. In a large-scale scenario with multiple strings in parallel, this matrix can reflect which strings are in a critical state close to the threshold and whether they will have a significant thermal load impact on adjacent strings. The safety margin and gradient information are stored in different hierarchical indexes in the matrix for differentiated reading; the safety margin item is used to judge the degree of proximity of the temperature to the respective thresholds, and the gradient item is used to judge the intensity of heat propagation between adjacent strings. Such a data structure can be directly read and incorporated into various management and control strategies after real-time updates, combining absolute temperature with relative heat diffusion information to form a complete picture covering static thermal risks and dynamic thermal interactions. At this point, the string temperature state matrix is successfully generated in this embodiment. By integrating the safety margin of each string and the gradient vector between adjacent strings, it provides an intuitive and efficient method for the system to understand and characterize the thermal distribution conditions within the liquid-cooled string PCS energy storage inverter.

[0062] 102. Divide the cooling priority of each string according to the string temperature state matrix, and allocate cooling resources according to the cooling priority to obtain a dynamic cooling execution instruction set;

[0063] In an embodiment of the present invention, the step of dividing the cooling priorities of each string according to the string temperature status matrix and allocating cooling resources according to the cooling priorities to obtain a dynamic cooling execution instruction set includes: performing a three-level cooling priority division on each string according to the temperature safety margin in the string temperature status matrix to obtain a string cooling priority classification table; adjusting and calculating the speed of the main circulation pump of the cooling system of the liquid-cooled string-type PCS energy storage converter based on the string cooling priority classification table to obtain a main circulation flow control parameter; calculating the flow distribution ratio of the coolant pipe sections corresponding to each string according to the main circulation flow control parameter and the string cooling priority classification table to obtain a grouped pipeline control instruction; calculating a microchannel flow adjustment scheme inside each PCS module based on the grouped pipeline control instruction and the internal heat distribution data of each string to obtain a microchannel control instruction; and performing collaborative optimization processing on the main circulation flow control parameter, the grouped pipeline control instruction, and the microchannel control instruction to obtain a dynamic cooling execution instruction set.

[0064] Specifically, the process of dividing each string into three levels of cooling priority according to the temperature safety margin in the string temperature status matrix to obtain a string cooling priority classification table starts with reading the temperature safety margin values of each string. These values include the measurement of the difference between the actual temperature and the acceptable threshold, thus reflecting the pressure faced by each string in terms of heat dissipation. At this time, the system scans all strings and divides them into three levels: the emergency cooling group, the high-demand cooling group, and the normal cooling group according to the pre-designed temperature margin zoning method. The temperature safety margin of the emergency cooling group is lower than a certain critical value, indicating that its temperature is very close to the set threshold; the margin of the high-demand cooling group is slightly higher than the emergency range but still shows a certain degree of temperature rise pressure; the normal cooling group has a relatively generous temperature margin. To form a clear and executable classification table, the system will list the IDs of all strings and their margin values after scanning and mark the corresponding priority labels beside them. Each priority paragraph has a clearly defined numerical range. For example, if the margin is less than a certain limit value, it belongs to the emergency cooling group, and if the margin is large enough, it is classified into the normal cooling group, and the middle part is automatically assigned to the high-demand cooling group. Such a classification process is usually executed within a fixed time period or immediately triggered when a sudden drop in the temperature margin of a certain string is detected to avoid missing the timely identification of emergencies. The system records the time stamp of the classification result of each string and stores it in a database structure that can be called to retrieve the priority allocation information at the current moment. If the same string has been in the emergency cooling level for a long time, it means that both the cooling measures and the temperature warning need to be strengthened. Therefore, this classification table can assist in making targeted decisions for all subsequent temperature management operations. The three-level cooling priority classification table is essentially a mapping list, with each row listing the string number, the real-time temperature safety margin, the classification category to which it belongs, and its update time. Once the classification table is generated, it can be compared with other data sources, such as the temperature trend information of other measurement points near the string, to determine whether there is regional temperature rise or local heat dissipation difficulties. After the classification table is established, there is no need to repeatedly present the absolute temperature or heat dissipation details of each string. Only the priority labels need to be retained in the same table to complete the preliminary preparation for a large number of cooling decisions. The classification table directly reflects the thermal pressure relationship between each string and its surrounding environment and can find the objects that most need cooling through quick indexing. The thresholds and intervals of the classification are often configured in combination with the specific situation of the site and the heat resistance level of the equipment. Fixed intervals can be used or dynamic fine-tuning can be made according to on-site experience. Once the table is updated, it immediately enters the next stage of cooling allocation calculation.

[0065] During the process of adjusting and calculating the speed of the main circulation pump of the liquid-cooled string-type PCS energy storage converter based on the above-mentioned string cooling priority classification table to obtain the main circulation flow control parameters, the system will first collect the maximum flow rate that the current cooling system can provide and the corresponding pump power range. With the reference of the priority provided by the classification table, the system can determine how many strings are in the emergency cooling group or the high-demand cooling group, so as to preliminarily estimate the overall cooling demand. If there are more strings in the emergency cooling group, it means that the whole system needs a higher cooling capacity. At this time, the main circulation pump speed often needs to be increased to a relatively high level so that the coolant can circulate quickly in the pipeline and take away more heat. If most strings are in the normal cooling group, the requirement for the pump speed is relatively low, which can not only meet the heat dissipation but also reduce the energy consumption of the cooling system itself. For more accurate calculations, the system often maintains a pump speed-flow mapping table, which lists the theoretical flow rate that the main circuit can reach under different pump speed settings and the average flow rate range during actual measurement, and also includes data such as pressure loss. The algorithm will add the number of strings in the emergency cooling group and the high-demand cooling group and combine the depth of the temperature safety margin of each string to calculate an overall cooling demand index, and then compare it with the pump speed-flow mapping table to directly find the basic pump speed value that can match this demand. After counting the priority distribution, once it is found that the number of strings in the emergency cooling group exceeds the set threshold, the system will introduce a correction coefficient to increase the basic pump speed value upward to meet the centralized emergency cooling requirements. Then the system will further fine-tune the pump speed in combination with the pipeline pressure condition returned by the loop pressure monitor. The main circulation flow control parameters obtained in this way usually include a target speed or speed range and the corresponding power limit, which are used to command the variable-frequency drive module of the main pump. When the circulation pump reaches the new speed, the system will also observe the pressure change of the liquid-cooled loop and whether the temperature of each string has a rapid decline trend in a short time. If there are still many strings in the emergency cooling level, the system will increase the main circulation flow again until the number of strings in the emergency cooling group is significantly relieved or the pump speed reaches the maximum limit that can be tolerated. This adjustment process will be executed multiple times within a certain time window, and by continuously comparing the latest situation of the classification table, it is decided whether to continue to increase or slightly decrease the pump speed. The main circulation flow control parameters obtained in this way can not only adapt to the sudden change of local heat dissipation urgency but also save energy consumption when the cooling demand is reduced, so as to achieve more effective scheduling of liquid-cooled resources.

[0066] The process of calculating the flow distribution ratio of the coolant pipe sections corresponding to each string according to the main circulation flow control parameter and the string cooling priority classification table regards the total flow output by the main circulation pump as the allocable resource, and then allocates each branch according to the priority information obtained from the classification table. To clarify the cooling channels of each string, in the design of this system, the inlet and outlet ports of several strings are often connected in parallel to the same branch pipeline, and this branch pipeline is then connected to the main circulation pump through a regulating valve or a proportional valve. When the number of emergency cooling strings is large, it is necessary to allocate a higher flow rate to the branches where these strings are located. A common method is to increase the opening of the valve in the corresponding branch or reduce the diversion ratio of other non-emergency branches. In specific implementation, the system first retrieves the string IDs of the emergency cooling strings from the classification table, marks the corresponding branch pipeline as the "high-priority branch", marks the pipeline where the high-demand cooling strings are located as the "medium-priority branch", and regards the pipeline where the normal cooling strings are located as the "low-priority branch". Subsequently, the system obtains the current available total flow rate in the main circulation flow control parameter, determines its minimum and upper limit ratios according to the number of high-priority branches, and then calculates a target flow rate or opening percentage for each pipeline by considering the demand status of the medium-priority and low-priority branches. To prevent the phenomenon that a certain high-priority branch monopolizes the flow rate and causes serious undercooling of other branches, the system usually sets a limit condition to ensure that each pipeline in the main circulation can maintain a certain minimum flow rate to maintain the basic heat dissipation cycle. After such allocation is completed, the system outputs a set of branch pipeline control instructions, which are often the target opening or pulse modulation mode data for each branch valve. The valve controller will adjust the valve position according to the instructions and transmit the information back to the main control module during real-time operation. When it is found that the temperature of a string in the high-priority branch drops to a certain range, the system will update the classification table and iterate the allocation algorithm again to make the flow distribution of each branch always fit the current priority layout. Different loops may also refer to the pressure or flow rate sensors installed on-site during flow distribution. If the pressure of a certain pipeline fluctuates greatly, corresponding compensation adjustments will be triggered. In this way, each pipeline can obtain a liquid cooling supply volume that matches its current heat dissipation demand, and the allocation instructions are coordinated with the rotational speed control of the main circulation pump in terms of timing, forming a multi-level dynamic heat dissipation management architecture.

[0067] In the process of calculating the microchannel flow adjustment scheme inside each PCS module based on the grouped pipeline control instruction and the internal thermal distribution data of each string to obtain the microchannel control instruction, the focus of the system further descends from the pipeline level to inside the module. Such converters usually design microchannel cold plates under components such as IGBT modules, heat dissipation substrates, or inductors, in order to achieve more efficient cooling around high heat density components. When the main circulation and branch pipelines are both allocated with flow rates, the amount of coolant entering the module is generally guaranteed, but the flow distribution between each microchannel still needs to be further fine-tuned, so that the area with the most concentrated heat source can be preferentially exposed to more liquid cooling contact. This kind of microchannel flow adjustment often relies on micro valves or adjustable throttling mechanisms to complete, and the control methods include analog signal regulation or digital proportional valve control, etc. For calculation, the system first needs to understand the temperature conditions of several core heat dissipation surfaces inside the module from the thermal distribution data, which are usually provided by small temperature sensors arranged near the IGBT or inductor. By comparing the values of these sensors, the system can judge which area has the highest heat dissipation pressure. Subsequently, the system refers to the flow rate upper limit in the grouped pipeline control instruction to fit the local increase and decrease strategy for this microchannel network. For example, if the temperature of the IGBT area rises the fastest, the microchannel control instruction tends to increase the opening degree of the flow channel valve in this area, while reducing the flow rate in other relatively temperature-safe parts. In order to prevent insufficient supply in the downstream area due to excessive flow in a single channel, the control algorithm often constraints and optimizes the channels inside the entire module. On the premise of keeping the total flow rate unchanged, differential cooling of different heat sources is achieved through local distribution. This process can cope with the regional high heat brought by high transient loads or large current impacts, and can also reduce the consumption of excessive cooling when the heat dissipation demand weakens. After the microchannel control instruction is issued, the small valves inside the module open and close according to the adjustment ratio of the instruction, and in real time distribute the coolant to the parts that most urgently need to be cooled. The microchannel adjustment often executes repeatedly in a very short cycle to avoid heat accumulation in local hot spots. Subsequently, the system collects the sensor temperature values of this module again to evaluate the actual cooling effect, and will correct the microchannel distribution parameters in the next round of scheduling. This ensures that the flow distribution inside each PCS module truly reflects the current thermal load characteristics and realizes more refined heat dissipation management.

[0068] The process of jointly optimizing the main loop flow control parameters, the grouped pipeline control instructions, and the microchannel control instructions to obtain a dynamic cooling execution instruction set is uniformly managed at the system level. To avoid conflicts or excessive responses between individual instructions, the algorithm usually integrates and adapts these instructions. First, the system reads the target pump speed and the overall flow upper limit set in the main loop flow control parameters. Then, based on this, it analyzes the opening ratio of the grouped pipeline control instructions to check whether there is a phenomenon of over-allocation or insufficient flow in some pipelines due to priority conflicts, and makes a relative balance of the opening of some valves if necessary. Next, the system enters the inspection procedure at the microchannel level. According to the local heat load situation reflected by the microchannel control instructions, it judges whether to make additional adjustments to the flow of the grouped pipelines, so as to avoid maintaining a large opening of the high-priority branch while the local microchannel has already increased the flow significantly, resulting in an imbalance in the overall flow distribution or the high-load operation of the circulation pump. In the specific implementation of the joint optimization, the algorithm usually follows the principle of first macroscopic and then microscopic. First, it determines the distribution of the overall heat dissipation capacity of the system with the pump speed and the grouped valves, and then makes a fine correction at the terminal by the microchannel strategy. If it is found that the local temperature of the high-priority branch has been significantly reduced by microchannel measures, while other branches continue to be under-cooled, the system will make a corresponding flow callback for the grouped pipeline control instructions and reallocate resources to the branches with still high temperatures, so that the string temperatures in the entire converter can converge towards the safe range. The mutual influence between instructions at each layer is realized in the integrated optimization algorithm. The algorithm mainly selects the optimal overall matching scheme according to whether there are still a large number of strings in the temperature state matrix showing low margin or a tendency to rapidly increase temperature, and combines the real-time power consumption and pressure limit of the cooling system. The finally formed dynamic cooling execution instruction set will be written into a structured instruction document or data packet, which contains specific information such as the pump speed setting value, the opening of the grouped pipeline valves, and the microchannel adjustment ratio, and lists the effective order within the specified time period. Once the instruction set is issued, the controllers at all levels execute operations according to the established protocol and continuously transmit new temperature and pressure data during the execution process for re-joint optimization in the next cycle.

[0069] Furthermore, the main circulation pump speed of the cooling system of the liquid-cooled string PCS energy storage inverter is adjusted and calculated based on the string cooling priority grading table to obtain the main circulation flow control parameters, including: statistical analysis of the number of strings of each priority level in the string cooling priority grading table and the temperature safety margin to obtain the overall cooling demand value of the system; querying a preset pump speed-flow mapping table according to the overall cooling demand value of the system to obtain a basic main circulation pump speed value; when the proportion of high-priority strings exceeds a threshold, the basic main circulation pump speed value is corrected for emergency cooling demand to obtain a corrected pump speed value; based on the corrected pump speed value and combined with the system pipeline pressure data, a pump power control curve is calculated to obtain a pump speed control sequence, and the pump speed control sequence is converted into a pulse width modulation signal parameter recognized by a pump controller to obtain a main circulation flow control parameter.

[0070] Specifically, the technical solution first statistically analyzes the number and temperature safety margin of each priority string in the string cooling priority classification table to obtain the overall cooling demand value of the system. The implementation process starts with reading the existing classification table, which usually contains several record rows, each row identifying the real-time priority level of a string and the corresponding temperature safety margin. The system traverses all records in a scanning manner. When encountering a string marked as a high priority, its temperature safety margin is multiplied by the internally defined severity coefficient and then accumulated. Similarly, the temperature safety margin of the medium priority string will also be multiplied by the weight constant of another level and added to the sum, while the low priority string usually does not significantly increase the global cooling demand, so only sporadic numerical accumulation is performed or its impact is directly ignored. In this way, the pressure level of resources faced by each priority segment at the temperature level can be obtained. When counting, the number of high priority strings and medium priority strings will be paid attention to. If the number of high priority strings is particularly large, a higher weighting factor will be given in the final synthesis to reflect its urgency for cooling. In order to more accurately characterize the difference in heat dissipation load between different strings, the system will also reference a time decay function for each priority string, and assign a moderately weighted reduction coefficient to the strings that remain in a high temperature state for a long time but are not supercritical, so that the truly urgent strings can occupy the main weight in the comprehensive statistics. Statistical algorithms sometimes use piecewise functions or linear-exponential mixed functions to complete the mapping of temperature safety margins. For example, a nonlinear accumulation process can be set so that extremely low safety margins bring higher increments when accumulated. For example, if the safety margin of a high-priority string is The safety margin for medium priority is , then the following relationship can be set in the statistical process:

[0071]

[0072] HP represents a high priority set, and MP represents a medium priority set. , , γ, are constants used to adjust weights and sensitivities. By performing operations on this formula, the combined cooling requirements of different priority strings at the current moment can be quantified. Finally, the result of the above sum formula is defined as the overall cooling requirement value of the system, forming a scalar that can be directly called by subsequent modules. When it is detected that there is a sign of rapid temperature increase in the high-priority string, the statistical algorithm will continue to monitor the evolution trend of its safety margin, and dynamically increase or decrease the relevant weights during the periodic refresh process. If some strings still remain in a state of urgent need for cooling during several refreshes, these strings will be individually marked, and the possible heat dissipation bottlenecks will be found through a small-scale search and the information will be provided to the flow distribution mechanism in the next stage. This overall cooling requirement value can be synchronously stored in an easily accessible data area, combined with time stamps and priority tags, to be used to trace back the current heat dissipation pressure of the system at any time and provide a basis for liquid cooling scheduling. In this way, the integration and statistics of the number of strings and temperature safety margins in the priority classification table are completed, and the overall cooling requirement value of the system is successfully output.

[0073] Next, according to the overall cooling requirement value of the system, query the preset pump speed-flow mapping table to obtain the basic main circulation pump speed value. The implementation process will first load a mapping table compiled during the experimental or on-site test phase. This table often presents in a two-dimensional or three-dimensional structure: the abscissa corresponds to the pump speed, the ordinate corresponds to the net flow of the system, and the third dimension may record the corresponding rated power consumption or pipeline pressure. The system uses the overall cooling requirement value obtained in the previous step to find the matching interval in this table. The process usually includes an interpolation calculation to locate a more accurate speed setting value between the discretized pump speed marks. The construction of the mapping table depends on a large amount of test data, covering the actual flow performance under low-speed, high-speed, and medium-speed conditions, and combining different pipeline layouts and environmental temperature factors. The system will compare the cooling requirement value with the requirement thresholds listed in the table. When finding the mapping row and column closest to this requirement value, read the corresponding pump speed entry. For example, when the requirement value is low, a relatively low rotation speed will be matched to maintain the necessary liquid cooling cycle and avoid unnecessary energy waste; when the requirement value is close to the highest interval, a higher rotation speed will be read from the table, corresponding to the large flow mode. To make the result more refined, the interpolation algorithm often needs to use piecewise polynomials or bicubic splines, allowing for the calculation of smoother speed values between known discrete measurement points. For example, when the requirement value is between m and n, it can be calculated through the following interpolation function with weighting coefficients:

[0074]

[0075] where and are the rotation speeds of adjacent measurement points respectively, and are the upper and lower boundaries of the corresponding demand value range, is the smoothing factor used to fine-tune the shape of the interpolation curve. The output of this function is the basic main circulating pump speed value. When querying the mapping table and performing interpolation, the system ensures that the pipeline structure is consistent with the structure targeted by the mapping table, and checks the deviation correction coefficient of the ambient temperature or coolant temperature before reading the data. If the temperature difference exceeds a certain range, this coefficient will be incorporated into the interpolation algorithm to make the finally obtained speed value closer to the real-time working conditions. The output at this stage is a specific value or a set of upper and lower limits of the interval, representing the currently most suitable basic pump speed, which is used to support subsequent pump speed correction operations.

[0076] When the proportion of high-priority strings exceeds the threshold, an emergency cooling demand correction is performed on the basic main circulating pump speed value to obtain the corrected pump speed value. The implementation process will first scan the overall proportion of high-priority strings from the grading table and compare this proportion with the predefined threshold. If the proportion is still within the normal range, the basic pump speed value does not need to be modified. If the proportion breaks through the threshold, it means that there are relatively intensive and urgent heat dissipation demands during the current period, and an incremental correction factor needs to be added to the basic pump speed value. The calculation of the correction factor can be implemented by a linear or non-linear function. If a linear function is selected, the system gives a proportional coefficient to multiply with the proportion of high-priority strings to obtain the correction increment. If a non-linear method is selected, a growth curve can be defined to increase exponentially or stepwise with the proportion. When the proportion is relatively high, the correction amount reaches a large amplitude, causing the pump speed to increase significantly in a short time, so as to provide more flow for the most urgent heat dissipation objects. When performing the correction, the mechanical characteristics of the pump, such as the maximum safe speed and acceleration limit, also need to be considered. The system will limit the correction amount so that the pump does not directly jump to the limit value and cause unnecessary shocks. At the same time, after each correction calculation, the pipeline pressure loss and heat energy removal speed that may be caused by the current flow rate will be included in the review link. If the proportion of high-priority strings is too high but the actual temperature has been alleviated, no further correction will be performed. In some algorithms, a second judgment will be made after the corrected pump speed is maintained for a period of time. If the temperature of the high-priority strings still does not drop, a new round of correction will be performed again. The corrected pump speed value formed in this way is defined to be closer to the real-time heat dissipation situation than the basic pump speed value, which is manifested as the ability to quickly increase the supply to the liquid cooling circuit in a short cycle. Monitoring the proportion of high-priority strings can ensure a quick response when local hot spots appear, especially during periods of large power mutations or sharp rises in ambient temperature, playing a role in supplementary cooling protection. Once the corrected pump speed value is confirmed, it will be stored in a special data segment and marked as the actual set value at the current moment to complete the final pump scheduling preparation.

[0077] Based on the corrected pump speed value and combined with the system pipeline pressure data, calculate the pump power control curve, obtain the pump speed control sequence, and convert the pump speed control sequence into pulse width modulation signal parameters recognized by the pump controller to obtain the main circulation flow control parameters. The implementation process starts from the corrected pump speed value, first queries the pipeline pressure or pressure distribution data recorded in real time in the system to determine whether the pressure during pump operation at this speed will exceed the safe operating range. In many cases, a set of pressure detection points are used to reflect the resistance load situation in the pipeline. If the detected resistance is low, the power demand of the pump will not increase excessively after the speed is increased; on the contrary, if the resistance is large, it may be necessary to make fine adjustments on the power distribution side to prevent the pump from entering the overcurrent or overload state. According to the corrected pump speed value v_ref and the pipeline pressure p_line, the system constructs a power control curve, which often gives a piecewise function for different pressure segments to specify the pump torque or load current. When the pressure rises beyond a specific threshold, the power upper limit is increased on the curve to maintain the established flow target. At the actual operation level, the curve consists of a set of point sequences (pressure, power) and corresponding control strategies. The pump speed control sequence can be defined as one or more linear functions, or a step function with overload protection. After generating the pump speed control sequence, each speed target in this sequence is converted into pulse width modulation (PWM) parameters through reverse look-up table or built-in drive mapping program. The pump controller often relies on PWM signals with fixed duty cycle and frequency for speed regulation. Therefore, the system needs to disassemble the speed control sequence into a series of discrete time points, each time point with a PWM duty cycle value and possible acceleration time arrangement. This enables the pump to smoothly switch from the original speed to the new target speed and select the matching power curve section under different pressure conditions. The final output is the main circulation flow control parameter, including the entire time series and the corresponding PWM configuration. When the control program starts to execute, the pump immediately follows the sequence to gradually increase or decrease the speed, and at the same time checks the value returned by the pressure sensor after each section is completed. If the actual pressure or flow deviates too much from the expectation, dynamic fine adjustment will be performed in the next time slice. This set of control parameters can be directly sent to the variable frequency drive unit and keep the data link with the monitoring center unobstructed for re-refreshing when sudden changes in cooling and heating loads occur. In this way, the mapping from the corrected pump speed to the final required hardware signal is completed, and a reasonable and effective main circulation flow distribution is achieved for the cooling system of the liquid-cooled string-type PCS energy storage converter.

[0078] 103. Identify the string temperature distribution map including the hot string and the cold string based on the dynamic cooling execution instruction set and the string temperature status matrix, and calculate the power adjustment plan according to the string temperature distribution map to obtain the power distribution execution matrix;

[0079] In an embodiment of the present invention, the method for identifying a temperature distribution map of strings including hot strings and cold strings based on the dynamic cooling execution instruction set and the string temperature status matrix, and calculating a power adjustment scheme according to the temperature distribution map of strings to obtain a power distribution execution matrix includes: calculating temperature deviation values of each string according to the cooling resource allocation in the string temperature status matrix and the dynamic cooling execution instruction set to obtain a string temperature deviation table; marking the strings with temperatures higher than the average value as hot strings and the strings with temperatures lower than the average value as cold strings based on the string temperature deviation table to obtain a temperature distribution map of strings; calculating the power reduction amount that can be achieved by the hot strings and the power increase amount that can be achieved by the cold strings according to the cooling resource allocation to obtain the maximum allowable power transfer amount; determining a power gradient transfer scheme according to the maximum allowable power transfer amount, and setting a hysteresis control parameter for the power transfer time sequence table in the gradient transfer scheme to obtain a power distribution execution matrix.

[0080] Specifically, in the process of calculating the temperature deviation values of each string according to the cooling resource allocation in the string temperature status matrix and the dynamic cooling execution instruction set to obtain a string temperature deviation table, the actual temperature or equivalent average temperature of each string at the current moment is first obtained, and the cooling resource information allocated to the string is read from the dynamic cooling execution instruction set. The temperature status matrix records the temperature safety margin, temperature gradient, and mutual heat conduction characteristics of each string, and the resource allocation in the dynamic cooling execution instruction set includes data such as flow rate, valve opening, or microchannel adjustment. When calculating the temperature deviation value, the system corrects according to the difference between the cooling resource received by each string and its temperature rise or fall rate, so as to avoid judgment imbalance caused by simply relying on temperature readings. The implementation method can obtain a temperature deviation reference by subtracting the actual temperature from the theoretical temperature expectation of the string, and then calculate the correction value in combination with the cooling potential brought by the cooling resource allocation. When the resource allocation amount is large but the actual temperature is still high, the deviation value will show a significant positive deviation, indicating insufficient heat dissipation or excessive heat source intensity; if the resource is small and the temperature still remains at a low level, the deviation value is negatively distributed, suggesting that the heat generation burden of the string is limited or the cooling effect of the surrounding environment is good. After statistically analyzing such differences, a temperature deviation table is generated. The temperature deviation values are listed in the table according to the string numbers, and the cooling resource allocation status of each string can be attached. If an extreme positive deviation occurs, it usually indicates that the current cooling strategy cannot meet the heat demand of the string. Before outputting the temperature deviation table, the system also filters or marks abnormal readings, such as sensor failure or short data jitter time, to maintain the usability of the records in the table. Each deviation value is written into the database together with the time stamp for quick retrieval in subsequent temperature distribution analysis and power adjustment processes.

[0081] Based on the string temperature deviation table, strings with temperatures higher than the average are marked as hot spot strings, and strings with temperatures lower than the average are marked as cold spot strings. The process of obtaining the string temperature distribution map takes the temperature deviation table as input and extracts the current deviation values of each string from it. The system first calculates a global average temperature deviation by statistically analyzing all the deviation values, which is used as the baseline for dividing hot spots and cold spots. For each string, if the deviation value is greater than this baseline, it means that its overall temperature level or local temperature peak deviates from the normal range, and the string is defined as a hot spot string; if the deviation value is much lower than the baseline, it indicates that its temperature is relatively stable and can bear more heat dissipation margin, and it is marked as a cold spot string. The units marked as hot spot strings usually have positive or significant high-temperature deviations in the temperature deviation table. In most cases, the cooling resources of these units are insufficiently allocated or their internal loads are too heavy. The generation of the distribution map arranges all strings in spatial topology or number order, highlighting hot spot strings with different colors or symbols, and cold spot strings also have special markings, so that the distribution trends of high-temperature and low-temperature areas can be visually distinguished on the map. The map can also embed gradient information in the temperature status matrix, enabling users to observe the heat flow direction in two-dimensional or three-dimensional coordinates. To ensure the determination accuracy, it is necessary to periodically update the deviation values and recalculate the global average value, so that the hot spot and cold spot markings always conform to the latest heat dissipation effect. After generating the temperature distribution map, the system stores the map in memory or a database and can be called for the next power transfer operation. Especially when multiple hot spot strings are concentrated in a certain area, the distribution map can characterize the local heat dissipation imbalance phenomenon and prompt corresponding power distribution measures.

[0082] Based on the described cooling resource allocation, calculating the power reduction amount of the hot spot string and the power increase amount of the cold spot string to obtain the maximum allowable power transfer amount will call the previously generated temperature distribution map and extract the current cooling resource boundary from the dynamic cooling execution instruction set. Hot spot strings usually need to reduce power output or current load in high-temperature states to alleviate internal heat generation; cold spot strings have a higher heat dissipation margin and can withstand a certain amount of power increase. The specific implementation often relies on a power margin model. The model will reference the temperature deviation value and structure level of the hot spot string to set an upper limit for deducting the current peak of its operating power, indicating how many kilowatts or amperes can be deducted without triggering safety hazards. Similarly, the power configuration of the cold spot string will combine its low-temperature condition and the module safety range to calculate the rated upper limit that can be increased, forming a power increase comparison table. The system then matches the power deduction and increase amounts of these hot and cold spots item by item, and obtains the maximum allowable power transfer amount through cumulative calculation. This transfer amount neither breaks the total output balance nor allows the cold spot string to exceed its own heat dissipation capacity. If the cooling resources are still relatively sufficient, the system will allow a larger range of transfer; if the resources are in a tight state, the transfer amount will be compressed. A power reduction list for hot spot strings and a power expansion list for cold spot strings can be established in the data structure, and the two can be cross-compared to find feasible pairing points. After each hot spot string and the corresponding cold spot string complete a transfer protocol together, the remaining transferable space is updated. This operation ensures that local hot spots can quickly get the opportunity to reduce load, and cold spots are moderately increased in load, so that the overall power output still maintains the required level.

[0083] The power gradient transfer scheme is determined according to the maximum allowable power transfer amount, and the hysteresis control parameters are set for the power transfer timing table in the gradient transfer scheme. In the process of obtaining the power allocation execution matrix, the system will first make a transfer gradient plan based on the maximum allowable power transfer amount, and allocate the load reduction of the hot spot string from the most urgent unit to the cold spot string with the greatest ability to increase power. In order to ensure the smooth power scheduling process, the step-by-step down and step-by-step up methods are adopted. In each period, a part of the hot spot string can be reduced in load, and the other part of the cold spot string can be synchronously increased in output. When constructing the transfer timing table, the algorithm allocates a short delay interval according to the number of strings and the differentiated distance, so that the load change will not instantly impact the electrical balance of the entire system. After that, the hysteresis control parameter setting is applied to the timing table, and an upper and lower threshold is used to determine when to trigger the next stage transfer and when to maintain the current allocation plan. The introduction of hysteresis is mainly to avoid repeated oscillations or frequent small adjustments, so that the load adjustment presents a more continuous behavior. If the temperature fluctuates greatly in a short period of time, the hysteresis can delay the occurrence of frequent switching and reduce the impact on the inverter and battery. Finally, a power allocation execution matrix is formed, which lists the target power range of each string in each time period, and is accompanied by auxiliary information such as transfer sequence number and hysteresis limit. When executing the matrix, the system will implement power regulation section by section, and repeat the same process in the next round of temperature measurement and cooling allocation update. The matrix formed in this way can take into account both real-time cooling and overall grid needs, prevent any hot spot string from being overheated for a long time, and make full use of the available margin of the cold spot string.

[0084] Furthermore, the method of calculating the amount of power that can be reduced by the hot spot string and the amount of power that can be increased by the cold spot string according to the cooling resource allocation to obtain the maximum allowable power transfer includes: obtaining the cooling resource allocation data and actual cooling capacity data of each string in the dynamic cooling execution instruction set to obtain a string cooling efficiency table; calculating the maximum amount of power that can be reduced for each hot spot string according to the string cooling efficiency table and the temperature deviation value of each hot spot string to obtain a hot spot power adjustable scale; calculating the maximum amount of power that can be increased for each cold spot string based on the temperature margin and power carrying capacity of each cold spot string to obtain a cold spot power adjustable scale; performing matching analysis on the hot spot power adjustable scale and the cold spot power adjustable scale to obtain an initial power transfer matching matrix; performing constraint check according to the power transfer direction and value in the initial power transfer matching matrix to obtain the maximum allowable power transfer.

[0085] 104. Select a corresponding temperature control strategy based on the environmental state parameters of the liquid-cooled string-type PCS energy storage inverter and the power allocation execution matrix, wherein the temperature control strategy is used to set parameters of various components of the cooling system corresponding to the liquid-cooled string-type PCS energy storage inverter to achieve temperature management of the liquid-cooled string-type PCS energy storage inverter.

[0086] In one embodiment of the present invention, the step of selecting a corresponding temperature control strategy according to the environmental state parameters and the power distribution execution matrix of the liquid-cooled string-type PCS energy storage converter includes: collecting the environmental temperature, humidity and prediction data to obtain an environmental state parameter set, and combining the environmental state parameter set with the power distribution execution matrix to perform operation mode recognition to obtain the current system operating condition type; matching a corresponding basic strategy group from a preset temperature control strategy library according to the current system operating condition type to obtain a candidate temperature control strategy set; calculating and evaluating the cooling efficiency ratio of each strategy in the candidate temperature control strategy set to obtain a strategy scoring result; selecting a corresponding temperature control strategy based on the strategy scoring result, and generating control parameters for each component of the cooling system according to the temperature control strategy.

[0087] In this embodiment, by collecting temperature data of each string in the liquid-cooled string-type PCS energy storage converter and calculating temperature characteristic parameters, a string temperature state matrix is obtained; the cooling priority of each string is divided according to the string temperature state matrix, and cooling resource allocation is performed according to the cooling priority to obtain a dynamic cooling execution instruction set; based on the dynamic cooling execution instruction set and the string temperature state matrix, the hot string and the cold string are identified and a power adjustment scheme is calculated to obtain a power distribution execution matrix; a corresponding temperature control strategy is selected according to the environmental state parameters and the power distribution execution matrix, and parameter settings are performed on each component of the cooling system. The present invention combines dynamic cooling resource allocation, power dynamic balance and environmental adaptability temperature control strategy to solve the problems of unreasonable cooling resource allocation and low temperature management efficiency, and realizes precise temperature management of the liquid-cooled string-type PCS energy storage converter under various working conditions.

[0088] The temperature management method of the liquid-cooled string-type PCS energy storage converter in the embodiment of the present invention is described above. Next, the temperature management system of the liquid-cooled string-type PCS energy storage converter in the embodiment of the present invention will be described. Please refer to Figure 2 One embodiment of the temperature management system of the liquid-cooled string-type PCS energy storage converter in the embodiment of the present invention includes:

[0089] A temperature monitoring module 201, configured to collect temperature data of each string in the liquid-cooled string-type PCS energy storage converter, and calculate temperature characteristic parameters based on the temperature data to obtain a string temperature state matrix;

[0090] A resource allocation module 202, configured to divide the cooling priority of each string according to the string temperature state matrix, and perform cooling resource allocation according to the cooling priority to obtain a dynamic cooling execution instruction set;

[0091] The power balance module 203 is configured to identify a string temperature distribution map including hot spot strings and cold spot strings based on the dynamic cooling execution instruction set and the string temperature status matrix, and calculate a power adjustment scheme according to the string temperature distribution map to obtain a power distribution execution matrix;

[0092] The policy execution module 204 is configured to select a corresponding temperature control policy according to the environmental status parameters of the liquid-cooled string type PCS energy storage converter and the power distribution execution matrix, where the temperature control policy is used to set parameters for each component of the cooling system corresponding to the liquid-cooled string type PCS energy storage converter to implement temperature management of the liquid-cooled string type PCS energy storage converter.

[0093] In the embodiment of the present invention, the temperature management system of the liquid-cooled string type PCS energy storage converter runs the temperature management method of the liquid-cooled string type PCS energy storage converter. The temperature management system of the liquid-cooled string type PCS energy storage converter collects temperature data of each string in the liquid-cooled string type PCS energy storage converter and calculates temperature characteristic parameters to obtain a string temperature status matrix; divides the cooling priorities of each string according to the string temperature status matrix and allocates cooling resources to obtain a dynamic cooling execution instruction set; identifies hot spot strings and cold spot strings based on the dynamic cooling execution instruction set and the string temperature status matrix and calculates a power adjustment scheme to obtain a power distribution execution matrix; selects a corresponding temperature control policy according to the environmental status parameters and the power distribution execution matrix, and sets parameters for each component of the cooling system. The present invention combines dynamic cooling resource allocation, power dynamic balance and environment-adaptive temperature control strategies to solve the problems of unreasonable cooling resource allocation and low temperature management efficiency, and realizes precise temperature management of the liquid-cooled string type PCS energy storage converter under various working conditions.

[0094] Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working processes of the above-described system or device and unit can refer to the corresponding processes in the foregoing method embodiments, and will not be described herein again.

[0095] When the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The foregoing storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical discs that can store program codes.

[0096] As described above, the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A temperature management method for a liquid-cooled string-type PCS energy storage converter, characterized in that The temperature management method of the liquid-cooled string-type PCS energy storage converter includes: Collect temperature data for each string in the liquid-cooled string-type PCS energy storage converter, and calculate temperature characteristic parameters based on the temperature data to obtain a string temperature status matrix; Perform three-level cooling priority classification on each string according to the temperature safety margin in the string temperature status matrix to obtain a string cooling priority classification table; perform adjustment calculation on the speed of the main circulation pump of the cooling system of the liquid-cooled string-type PCS energy storage converter based on the string cooling priority classification table to obtain a main circulation flow control parameter; calculate the flow distribution ratio of the coolant pipe section corresponding to each string according to the main circulation flow control parameter and the string cooling priority classification table to obtain a grouped pipeline control instruction; calculate the micro-channel flow adjustment scheme inside each PCS module based on the grouped pipeline control instruction and the internal heat distribution data of each string to obtain a micro-channel control instruction; perform collaborative optimization processing on the main circulation flow control parameter, the grouped pipeline control instruction, and the micro-channel control instruction to obtain a dynamic cooling execution instruction set; Based on the dynamic cooling execution instruction set and the string temperature status matrix, identify a string temperature distribution map including hot spot strings and cold spot strings, and calculate a power adjustment scheme according to the string temperature distribution map to obtain a power distribution execution matrix; Select a corresponding temperature control strategy according to the environmental status parameters of the liquid-cooled string-type PCS energy storage converter and the power distribution execution matrix, where the temperature control strategy is used to set parameters for each component of the cooling system corresponding to the liquid-cooled string-type PCS energy storage converter to achieve the temperature management of the liquid-cooled string-type PCS energy storage converter.

2. The temperature management method of the liquid-cooled string-type PCS energy storage converter according to claim 1, wherein, The step of collecting temperature data for each string in the liquid-cooled string-type PCS energy storage converter and calculating temperature characteristic parameters based on the temperature data to obtain a string temperature status matrix includes: Collect temperature data through the temperature sensor array arranged at the key points of each string PCS module and battery cluster of the liquid-cooled string-type PCS energy storage converter to obtain a temperature original data set; Perform differential processing on the temperature original data set based on the current power state and position information of each string to obtain a string temperature threshold setting matrix; Calculate the difference between the current temperature of each string and the corresponding threshold in the string temperature threshold setting matrix to obtain the temperature safety margin of each string; Calculate the ratio of the temperature difference between adjacent strings to the physical distance to obtain a string-to-string temperature gradient vector; Organize the temperature safety margin and the temperature gradient vector in a matrix form according to the string number to obtain a string temperature status matrix.

3. The temperature management method of the liquid-cooled string-type PCS energy storage converter according to claim 1, wherein, The step of performing adjustment calculation on the speed of the main circulation pump of the cooling system of the liquid-cooled string-type PCS energy storage converter based on the string cooling priority classification table to obtain a main circulation flow control parameter includes: Perform statistical analysis on the number and temperature safety margin of the strings with each priority level in the string cooling priority classification table to obtain the overall system cooling demand value; Query the preset pump speed-flow mapping table according to the overall system cooling demand value to obtain the basic main circulation pump speed value; When the proportion of high - priority strings exceeds the threshold, perform emergency cooling demand correction on the basic main circulation pump speed value to obtain the corrected pump speed value; Based on the corrected pump speed value, calculate the pump power control curve in combination with the system pipeline pressure data to obtain a pump speed control sequence, and convert the pump speed control sequence into pulse - width modulation signal parameters recognized by the pump controller to obtain the main circulation flow control parameters.

4. The temperature management method of the liquid-cooled string-type PCS energy storage converter according to claim 1, wherein, The method of identifying the string temperature distribution map including hot - spot strings and cold - spot strings based on the dynamic cooling execution instruction set and the string temperature status matrix, and calculating the power adjustment scheme according to the string temperature distribution map to obtain the power distribution execution matrix includes: Calculate the temperature deviation value of each string according to the cooling resource allocation in the string temperature status matrix and the dynamic cooling execution instruction set to obtain a string temperature deviation table; Based on the string temperature deviation table, mark the strings with temperatures higher than the average as hot - spot strings and the strings with temperatures lower than the average as cold - spot strings to obtain a string temperature distribution map; Calculate the power reduction amount that can be reduced for hot - spot strings and the power increase amount that can be increased for cold - spot strings according to the cooling resource allocation to obtain the maximum allowable power transfer amount; Determine the power gradient transfer scheme according to the maximum allowable power transfer amount, and set the hysteresis control parameters for the power transfer time - sequence table in the gradient transfer scheme to obtain the power distribution execution matrix.

5. The temperature management method of the liquid-cooled string-type PCS energy storage converter according to claim 4, characterized in that, The method of calculating the power reduction amount that can be reduced for hot - spot strings and the power increase amount that can be increased for cold - spot strings according to the cooling resource allocation to obtain the maximum allowable power transfer amount includes: Obtain the cooling resource allocation data and actual cooling capacity data of each string in the dynamic cooling execution instruction set to obtain a string cooling efficiency table; Calculate the maximum reducible power amount of each hot - spot string according to the string cooling efficiency table and the temperature deviation value of each hot - spot string to obtain a hot - spot power adjustable scale table; Calculate the maximum increasable power amount of each cold - spot string based on the temperature margin and power - bearing capacity of each cold - spot string to obtain a cold - spot power adjustable scale table; Perform matching analysis on the hot - spot power adjustable scale table and the cold - spot power adjustable scale table to obtain an initial power transfer matching matrix; Check the constraint conditions according to the power transfer direction and value in the initial power transfer matching matrix to obtain the maximum allowable power transfer amount.

6. The temperature management method of the liquid-cooled string-type PCS energy storage converter according to claim 1, characterized in that, The method of selecting the corresponding temperature control strategy according to the environmental state parameters of the liquid - cooled string - type PCS energy storage converter and the power distribution execution matrix includes: Collect environmental temperature, humidity and prediction data to obtain an environmental state parameter set, and combine the environmental state parameter set with the power distribution execution matrix to perform operation mode recognition to obtain the current system working condition type; Match the corresponding basic strategy group from the preset temperature control strategy library according to the current system working condition type to obtain a candidate temperature control strategy set; Calculate and evaluate the cooling efficiency ratio of each strategy in the candidate temperature control strategy set to obtain a strategy scoring result; Select the corresponding temperature control strategy based on the strategy scoring result, and generate control parameters for each component of the cooling system according to the temperature control strategy.

7. A temperature management system for a liquid-cooled string-type PCS energy storage converter, characterized in that, The temperature management system of the liquid - cooled string - type PCS energy storage converter includes: A temperature monitoring module, which is used to collect temperature data of each string in the liquid-cooled string-type PCS energy storage converter, and calculate temperature characteristic parameters based on the temperature data to obtain a string temperature status matrix; A resource allocation module, which is used to divide the cooling priorities of each string into three levels according to the temperature safety margin in the string temperature status matrix to obtain a string cooling priority classification table; perform adjustment calculations on the speed of the main circulation pump of the cooling system of the liquid-cooled string-type PCS energy storage converter based on the string cooling priority classification table to obtain main circulation flow control parameters; calculate the flow distribution ratio of the coolant pipeline section corresponding to each string according to the main circulation flow control parameters and the string cooling priority classification table to obtain a grouped pipeline control instruction; calculate the micro-channel flow adjustment scheme inside each PCS module based on the grouped pipeline control instruction and the internal heat distribution data of each string to obtain a micro-channel control instruction; perform collaborative optimization processing on the main circulation flow control parameter, the grouped pipeline control instruction and the micro-channel control instruction to obtain a dynamic cooling execution instruction set; A power balance module, which is used to identify a string temperature distribution map including hot-spot strings and cold-spot strings based on the dynamic cooling execution instruction set and the string temperature status matrix, and calculate a power adjustment scheme according to the string temperature distribution map to obtain a power distribution execution matrix; A strategy execution module, which is used to select a corresponding temperature control strategy according to the environmental status parameters of the liquid-cooled string-type PCS energy storage converter and the power distribution execution matrix, wherein the temperature control strategy is used to set parameters for each component of the cooling system corresponding to the liquid-cooled string-type PCS energy storage converter to realize the temperature management of the liquid-cooled string-type PCS energy storage converter.

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