A Multi-Node Cooperative Charging Scheduling Method for Immersed Energy Storage Systems

Abstract

This invention relates to the field of energy storage system technology, specifically to a multi-node collaborative charging scheduling method for immersion energy storage systems. During the charging process of the immersion energy storage system, the method assesses the heat generation and dissipation of each energy storage node to determine its theoretical thermal equilibrium temperature. It calculates the thermal hysteresis deviation between the theoretical thermal equilibrium temperature and the measured temperature of each energy storage node, and identifies thermally hysteretic energy storage nodes. The thermal hysteresis deviation of these nodes is converted into the hidden heat that the node can currently accommodate and into an equivalent safety margin current. The method then calculates the misalignment deviation current between this misalignment deviation current and the original charging command current of the thermally hysteretic energy storage node. Based on the misalignment deviation current and the equivalent safety margin current, the original charging command current of the thermally hysteretic energy storage node is compensated and corrected, and charging control is performed. This invention effectively improves the charging control accuracy of energy storage nodes.

Description

Technical Field

[0001] This invention relates to the field of energy storage system technology, and specifically to a multi-node collaborative charging scheduling method for an immersion energy storage system. Background Technology

[0002] With the increasing proportion of renewable energy generation in the energy structure and the increasingly complex grid load conditions, energy storage systems are playing a crucial role in ensuring stable grid operation and improving power quality. Among these, submerged energy storage technology, as an innovative thermal management solution, directly immerses battery cells in insulating coolant, demonstrating significant advantages in temperature uniformity, system safety, and energy density. It is gradually becoming one of the preferred technologies for large-scale energy storage power plants.

[0003] In submerged energy storage systems, large energy storage arrays are typically composed of numerous distributed energy storage nodes. These nodes are connected to a control center via an internal communication network, forming a typical distributed multi-node energy storage system. Currently, existing charging scheduling methods, such as priority polling based on state of charge and centralized optimal power allocation algorithms, mainly rely on the electrical parameters transmitted back by each energy storage node to formulate a unified charging strategy.

[0004] In existing submerged energy storage systems, charging power is typically adjusted based on the current temperature parameters of each energy storage node during charging scheduling. However, due to the thermal inertia of the coolant, temperature changes within the energy storage nodes significantly lag behind instantaneous current changes. When the system collaboratively charges multiple energy storage nodes sharing a cooling loop, this thermal hysteresis effect causes serious problems: scheduling decisions based on the current temperature cannot accurately reflect the actual current surge experienced by the energy storage nodes at that moment. Specifically, the temperature sensors of energy storage nodes located at the end of the coolant flow path respond slowly. The system continuously increases the charging current before the temperature rises, and by the time the temperature increases, heat accumulation has already occurred, leading to a mismatch between the current state of the energy storage node and the current charging command. Summary of the Invention

[0005] To address the technical problem of misalignment between the current state of an energy storage node and the current charging command caused by the significant lag between temperature changes within the energy storage node and instantaneous current changes when adjusting charging power based on the current temperature parameters of each energy storage node, this invention aims to provide a multi-node collaborative charging scheduling method for an immersion energy storage system. The specific technical solution adopted is as follows: In a first aspect, the present invention provides a multi-node collaborative charging scheduling method for an submerged energy storage system, comprising the following steps: During the charging process of the submerged energy storage system, the heat generation and heat dissipation of each energy storage node in the energy storage system are evaluated to determine the theoretical thermal equilibrium temperature of each energy storage node. Calculate the thermal hysteresis deviation between the theoretical thermal equilibrium temperature and the measured temperature of each energy storage node, and based on the thermal hysteresis deviation, screen out the thermal hysteresis energy storage nodes that are in a thermal hysteresis state from all energy storage nodes. The thermal hysteresis deviation of the thermal hysteresis energy storage node is converted into the hidden heat that the node can currently accommodate, and the hidden heat is converted into an equivalent safety margin current. The misalignment deviation current between the original charging command current and the equivalent safety margin current of the thermal hysteresis energy storage node is calculated. Based on the misalignment deviation current and the equivalent safety margin current, the original charging command current of the thermal hysteresis energy storage node is compensated and corrected, and the charging control of the thermal hysteresis energy storage node is performed based on the corrected charging command current.

[0006] In conjunction with the first aspect above, in some possible implementations, the heat generation and heat dissipation of each energy storage node in the energy storage system are evaluated to determine the theoretical thermal equilibrium temperature of each energy storage node, including: Based on the charging current and internal resistance of each energy storage node within the set observation time window before the current moment, the heat generation of each energy storage node within the set observation time window is determined. Based on the preset heat dissipation coefficient of each energy storage node, the temperature value of each energy storage node within the set observation time window, and the local coolant temperature at the location of each energy storage node, the heat dissipation of each energy storage node within the set observation time window is determined. Based on the rated heat capacity of each energy storage node, the heat difference between the heat generated and the heat dissipated is converted into a temperature value, and then superimposed with the theoretical thermal equilibrium temperature of each energy storage node before the set observation time window to obtain the theoretical thermal equilibrium temperature of each energy storage node at the current moment.

[0007] In conjunction with the first aspect above, in some possible implementations, based on the thermal hysteresis deviation, thermally hysteresis energy storage nodes that are in a thermally hysteresis state are screened from all energy storage nodes, including: Based on the charging current of each energy storage node at the current moment and the maximum allowable temperature deviation of each energy storage node, the dynamic temperature deviation threshold is determined. The thermal hysteresis deviation is compared with the dynamic temperature deviation threshold, and the energy storage node corresponding to the thermal hysteresis deviation that is greater than the dynamic temperature deviation threshold is determined as the thermal hysteresis energy storage node.

[0008] In conjunction with the first aspect mentioned above, among some possible implementation methods, determining the dynamic temperature deviation threshold includes: Determine the ratio of the charging current of each energy storage node to the maximum allowable charging current at the current moment, and perform negative correlation mapping truncation on the ratio to obtain the temperature coefficient; The maximum allowable temperature deviation of each energy storage node is corrected using the temperature coefficient to obtain the dynamic temperature deviation threshold.

[0009] In conjunction with the first aspect above, in some possible implementations, the hidden heat is converted into an equivalent safety margin current, including: Based on the hidden heat, and combined with the charging current and internal resistance of each thermal hysteresis energy storage node at the current moment, the theoretical generation time of the hidden heat is determined. The minimum value between the theoretical generation time and the window duration of the observation time window used to determine the theoretical thermal equilibrium temperature is determined, and the minimum value is taken as the effective generation time of the hidden heat. Based on the hidden heat, and combined with the effective generation time and the internal resistance of each thermal hysteresis energy storage node within the set observation time window used to determine the theoretical thermal equilibrium temperature, the equivalent safety margin current is calculated.

[0010] In conjunction with the first aspect above, in some possible implementations, the original charging command current of the thermally hysteretic energy storage node is compensated and corrected, including: If the equivalent safety margin current is less than the maximum allowable charging current of the thermal hysteresis energy storage node, and the misalignment deviation current is greater than 0, then a compensation coefficient is determined based on the thermal hysteresis deviation and the charging current of the thermal hysteresis energy storage node at the current moment, and the current superposition amount is determined in combination with the misalignment deviation current; the superposition value of the current superposition amount and the equivalent safety margin current is determined as the corrected charging command current of the thermal hysteresis energy storage node. If the equivalent safety margin current is less than the maximum allowable charging current of the thermal hysteresis energy storage node, and the misalignment deviation current is less than or equal to 0, then the original charging command current of the thermal hysteresis energy storage node is determined as the corrected charging command current of the thermal hysteresis energy storage node.

[0011] In conjunction with the first aspect mentioned above, among some possible implementation methods, the compensation coefficient is determined, including: The ratio of the thermal hysteresis deviation to the maximum allowable temperature offset of the thermal hysteresis energy storage node is determined as the degree of thermal hysteresis. The ratio of the current charging current of the thermal hysteresis energy storage node at the current moment to the maximum allowable charging current of the thermal hysteresis energy storage node is determined as the current surge intensity. The thermal hysteresis degree and the current impact intensity are combined to determine the compensation coefficient.

[0012] In conjunction with the first aspect above, some possible implementations of compensating and correcting the original charging command current of the thermally hysteretic energy storage node further include: If the equivalent safety margin current is greater than or equal to the maximum allowable charging current of the thermal hysteresis energy storage node, the minimum charging current will be set as the corrected charging command current of the thermal hysteresis energy storage node.

[0013] In conjunction with the first aspect described above, in some possible implementations, the method further includes: The charging control of other energy storage nodes is based on the original charging command current of the normal energy storage nodes (excluding thermally lagging energy storage nodes) in the energy storage system.

[0014] In conjunction with the first aspect mentioned above, charging control is performed in several possible implementations, including: The charging command current is sent to the local controller of the energy storage node; The local controller converts the received charging command current into a corresponding charging power setting value, and adjusts the actual charging current of the charging module to charge the energy storage node based on the converted charging power setting value.

[0015] Secondly, the present invention also provides a multi-node collaborative charging scheduling system for an immersion energy storage system, including a memory and a processor. The memory is used to store executable computer program code, and the processor is used to call and run the executable computer program code from the memory, so that the system executes a multi-node collaborative charging scheduling method for an immersion energy storage system according to the first aspect or any possible implementation thereof.

[0016] Thirdly, the present invention also provides a computer program product comprising: computer program code, which, when run on a computer, causes the computer to execute a multi-node collaborative charging scheduling method for an immersion energy storage system as described in the first aspect or any possible implementation thereof.

[0017] Fourthly, the present invention also provides a computer-readable storage medium storing computer program code, which, when executed on a computer, causes the computer to perform a multi-node collaborative charging scheduling method for an immersion energy storage system according to the first aspect or any possible implementation thereof.

[0018] This invention offers the following advantages: It determines the theoretical thermal equilibrium temperature by evaluating the heat generated by each energy storage node in an immersion energy storage system, eliminating temperature perception interference caused by the thermal inertia of the coolant; it filters out thermally lagging nodes by utilizing the deviation between theoretical and measured temperatures, identifying energy storage nodes that conceal their heating state; it converts this temperature deviation into hidden heat and equivalent safety margin current, quantifying the thermodynamic hysteresis parameter into an electrical stress index that the control system can handle, revealing the degree of misalignment between the current charging command and the node's actual safety bearing boundary; finally, it corrects the original charging command based on this misalignment, ensuring that scheduling decisions are executed according to the node's real-time thermal bearing state rather than the hysteresis temperature, avoiding the risk of continuous erroneous input of large currents due to slow temperature response, and solving the problem of misalignment between commands and thermal responses in multi-node collaborative charging. Attached Figure Description

[0019] To more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 This is a flowchart illustrating the steps of a multi-node collaborative charging scheduling method for an immersion energy storage system according to an embodiment of the present invention. Figure 2 This is a schematic diagram of the structure of a multi-node collaborative charging scheduling system for an immersion energy storage system according to an embodiment of the present invention. Detailed Implementation

[0021] To clearly illustrate the technical features of this solution, the invention will be described in detail below through specific embodiments and in conjunction with the accompanying drawings.

[0022] Embodiments of the present invention will now be described in more detail with reference to the accompanying drawings. While some embodiments of the invention are shown in the drawings, it should be understood that the invention can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of the invention. It should be understood that the accompanying drawings and embodiments are for illustrative purposes only and are not intended to limit the scope of protection of the invention.

[0023] It should be understood that the various steps described in the method embodiments of the present invention may be performed in different orders and / or in parallel. Furthermore, the method embodiments may include additional steps and / or omit the steps shown. The scope of the present invention is not limited in this respect.

[0024] The term "comprising" and its variations as used herein are open-ended inclusions, meaning "including but not limited to". The term "based on" means "at least partially based on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". Definitions of other terms will be given in the description below.

[0025] It should be noted that the concepts of "first" and "second" mentioned in this invention are only used to distinguish different devices, modules or units, and are not used to limit the order of functions performed by these devices, modules or units or their interdependencies.

[0026] Although operations or steps are described in a specific order in the accompanying drawings in the embodiments of the present invention, this should not be construed as requiring these operations or steps to be performed in the specific order or serial order shown, or requiring all of the shown operations or steps to be performed to obtain the desired result. In the embodiments of the present invention, these operations or steps may be performed serially; they may be performed in parallel; or a portion of these operations or steps may be performed.

[0027] Meanwhile, it is understood that the data involved in the technical solutions of this invention (including but not limited to the data itself, the acquisition or use of the data) shall comply with the requirements of relevant laws, regulations and related provisions. Unless otherwise defined, all technical and scientific terms used in this invention have the same meaning as commonly understood by those skilled in the art to which this invention pertains. Furthermore, in all division and logarithmic operations involved in this invention, a protection mechanism is employed to prevent computational crashes or invalid values ​​due to a zero denominator or zero input. The implementation of this protection mechanism can be reasonably set according to the actual situation. For example, when the denominator term of a division operation or the argument term of a logarithmic function is zero, a protection parameter with the same dimension as or dimensionless as the denominator term or argument term can be added. The value of this protection parameter can be a very small value greater than zero, thereby ensuring the robustness and feasibility of the algorithm under extreme conditions. In addition, the normalization function mentioned in this invention, unless otherwise specifically stated, uses maximum-minimum value normalization to normalize the normalization result to the [0, 1] interval or other continuous intervals. The maximum and minimum values ​​used in the maximum-minimum normalization can be obtained according to the actual situation. For example, when multiple values ​​can be obtained in the implementation process and it is necessary to compare the relationship between different values, multiple values ​​can be counted to obtain the maximum and minimum values. However, when only a single value can be obtained in the implementation process, the maximum and minimum values ​​can be obtained by counting based on a large amount of historical experimental data or prior data obtained in the early stage.

[0028] To address the technical problem that existing methods adjust charging power based on the current temperature parameters of each energy storage node, where changes in the internal temperature of the energy storage node lag significantly behind instantaneous changes in current, leading to a mismatch between the current state of the energy storage node and the current charging command, this invention provides a multi-node collaborative charging scheduling method for an immersion energy storage system. This method calculates the thermal equilibrium temperature of each energy storage node during the charging process and identifies thermally lagging energy storage nodes. It then independently quantifies the remaining unacceptable hidden heat of each thermally lagging energy storage node into an equivalent safety margin current. Based on this, it quantitatively determines the mismatch between the charging command current and the equivalent safety margin current of each thermally lagging energy storage node, and dynamically generates differentiated compensation commands based on the degree of thermal lag and the impact intensity of the command current, which are then sent to each thermally lagging energy storage node for execution. This solution effectively solves the decoupling problem between electrical synchronization commands and thermal asynchronous responses caused by differences in the thermal inertia of the coolant when multiple energy storage nodes are charged in tandem. It enables differentiated and precise charging control for different energy storage nodes, effectively improving the overall charging safety and state-of-charge balance of multi-energy storage node immersion energy storage systems.

[0029] The following will describe in detail, with reference to the accompanying drawings, a multi-node collaborative charging scheduling method for an immersion energy storage system provided by an embodiment of the present invention.

[0030] Figure 1 This diagram illustrates the basic flow of a multi-node collaborative charging scheduling method for an submerged energy storage system according to an embodiment of the present invention. Figure 1 As shown, the method specifically includes the following steps: Step S100: During the charging process of the submerged energy storage system, the heat generation and heat dissipation of each energy storage node in the energy storage system are evaluated to determine the theoretical thermal equilibrium temperature of each energy storage node.

[0031] During the charging process of an immersion energy storage system using charging equipment, the temperature changes of each energy storage node in the system are essentially the result of a dynamic balance between heat generation and heat dissipation. During charging, the charging current generates Joule heat through the internal resistance of the battery cell. Part of this heat raises the cell temperature, while the other part is dissipated through the coolant. To determine whether the current temperature of each energy storage node lags behind the current charging current, the heat generation and heat dissipation of each energy storage node in the system are assessed to determine the theoretical thermal equilibrium temperature of each node. This theoretical thermal equilibrium temperature characterizes the thermal equilibrium temperature value that an energy storage node should reach under the charging current, assuming no thermal inertia (i.e., response delay).

[0032] In a specific example, the heat generation and heat dissipation of each energy storage node in the energy storage system are evaluated to determine the theoretical thermal equilibrium temperature of each energy storage node, including: First, based on the charging current and internal resistance of each energy storage node within the set observation time window before the current moment, the heat generation of each energy storage node within the set observation time window is determined.

[0033] Specifically, the charging current of each energy storage node is collected in real time using current sensors built into each node. Simultaneously, the temperature of each node is collected in real time using temperature sensors attached to the surface of its cells. Based on the collected temperature values, the internal resistance of each node is obtained through interpolation matching using a pre-calibrated temperature-internal resistance lookup table stored in the system. This determines the current state of each energy storage node. The previous setting window size N (e.g., 30s) was used to set the observation time window, and the last moment in the observation time window is set as the current moment. Based on the real-time acquisition of charging current at each energy storage node, the charging current of each node at various moments within a set observation time window is obtained. Since the Joule heat of current is proportional to the square of the current and related to the internal resistance of the conductor, and the internal resistance of the conductor can be considered constant over a short period, the current moment is used as the starting point. Based on the benchmark, for any first The energy storage node, within the set observation time window, observes the first... Integrating the product of the square of the charging current and the internal resistance of the first energy storage node, we obtain the product of the first and second energy storage nodes. The heat generated by each energy storage node within a set observation time window is recorded as follows: It should be understood that in actual digital control systems, the above integral calculation process is achieved by summing discrete data points acquired at a fixed sampling period within a set observation time window. Since this implementation process is existing technology, it will not be described in detail here.

[0034] Secondly, based on the preset heat dissipation coefficient of each energy storage node, the temperature value of each energy storage node within the set observation time window, and the local coolant temperature at the location of each energy storage node, the heat dissipation of each energy storage node within the set observation time window is determined.

[0035] Specifically, the local coolant temperature at the flow channel location corresponding to each energy storage node is collected. Also, taking the current moment as an example. Based on the benchmark, for any first The energy storage node, based on the first The temperature difference between the temperature values ​​of each energy storage node within the same set observation time window and the local coolant temperature at the node's location, combined with the temperature of the first energy storage node within the same set observation time window. The heat dissipation coefficient of the energy storage node is calculated. The cumulative heat dissipation of each energy storage node within the same set observation time window .in, Indicates the first The temperature value of each energy storage node at time u within the set observation time window; This indicates that at time u within the set observation time window... The local coolant temperature at the location of each energy storage node; Indicates the first The heat dissipation coefficient of each energy storage node can be set through factory parameters or obtained through historical heat dissipation constant temperature tests. It should be understood that in actual digital control systems, the integral calculation of the aforementioned cumulative heat dissipation can also be achieved by summing discrete sampled data points.

[0036] Finally, based on the rated heat capacity of each energy storage node, the heat difference between the heat generated and the heat dissipated is converted into a temperature value, and then superimposed with the theoretical thermal equilibrium temperature of each energy storage node before the set observation time window to obtain the theoretical thermal equilibrium temperature of each energy storage node at the current moment.

[0037] Specifically, based on the law of conservation of energy, the change in heat generated and dissipated by each energy storage node is divided by its heat capacity, and combined with the theoretical thermal equilibrium temperature of each energy storage node before the set observation time window, the theoretical thermal equilibrium temperature of each energy storage node at the current moment is determined. For any given... The energy storage node, the first At the current moment, each energy storage node Theoretical thermal equilibrium temperature .in, Indicates the first The theoretical thermal equilibrium temperature of each energy storage node before the set observation time window; Indicates the first The heat generated by each energy storage node within a set observation time window; Indicates the first The cumulative heat dissipation of each energy storage node within the same set observation time window; Indicates the first The rated heat capacity of each energy storage node can be set through the equipment's factory parameters or obtained through historical heat calibration tests.

[0038] In the initial power-on and static state of the energy storage system without charging current, it is assumed that there is no thermal hysteresis at the energy storage nodes, and the measured temperature at the initial moment is used as the initial reference value for the theoretical thermal equilibrium temperature. During subsequent system operation, the theoretical thermal equilibrium temperature calculated at each sampling moment is continuously stored in the sliding data cache; when calculating the theoretical thermal equilibrium temperature at the current moment t, the historical calculation result at the corresponding moment tN is directly read from the sliding data cache as the reference value. .

[0039] Step S200: Calculate the thermal hysteresis deviation between the theoretical thermal equilibrium temperature and the measured temperature of each energy storage node, and based on the thermal hysteresis deviation, screen out the thermal hysteresis energy storage nodes that are in a thermal hysteresis state among all energy storage nodes.

[0040] In an ideal scenario without thermal hysteresis, the measured temperature of each energy storage node should be close to its thermal equilibrium temperature. However, due to the thermal inertia of the coolant, the actual measured temperature change of the energy storage node always lags behind the change in the thermal equilibrium temperature. When an energy storage node is subjected to a large current surge, the thermal equilibrium temperature rises rapidly, while the actual temperature rises slowly due to the thermal buffering effect of the coolant, resulting in a significant positive deviation between the two. Conversely, when the current drops sharply, the thermal equilibrium temperature drops rapidly, while the actual temperature drops slowly, resulting in a negative deviation. Therefore, by comparing the difference between the measured temperature and the theoretical thermal equilibrium temperature of each energy storage node, the thermal hysteresis deviation of each energy storage node can be quantitatively determined. Based on this thermal hysteresis deviation, energy storage nodes in a state of thermal hysteresis can be screened from all energy storage nodes.

[0041] In a specific example, for any first... Each energy storage node is used to calculate its theoretical thermal equilibrium temperature. Rather than at the present moment Measured temperature The difference And take this difference as the first At the current moment, each energy storage node Thermal hysteresis bias This thermal hysteresis bias is used to characterize the energy storage node at the current moment. Temperature increments that did not have time to be reflected due to thermal inertia.

[0042] In a specific example, based on thermal hysteresis bias, thermally hysteresis energy storage nodes that are in a thermally hysteresis state are selected from all energy storage nodes, including: First, based on the charging current of each energy storage node at the current moment and the maximum allowable temperature deviation of each energy storage node, the dynamic temperature deviation threshold is determined.

[0043] Following the physical logic that "the higher the current, the higher the risk and the lower the threshold for judgment," while avoiding oversensitivity caused by the threshold approaching zero under maximum current conditions, a dynamic temperature deviation threshold is determined to identify thermal hysteresis nodes that require special attention among all energy storage nodes.

[0044] In a specific example, determining the dynamic temperature deviation threshold includes: determining the ratio of the charging current of each energy storage node at the current moment to the maximum allowable charging current, and performing negative correlation mapping truncation on the ratio to obtain the temperature coefficient; using the temperature coefficient to correct the maximum allowable temperature deviation of each energy storage node to obtain the dynamic temperature deviation threshold.

[0045] Specifically, for any first The energy storage node, the first At the current moment, each energy storage node Dynamic temperature deviation threshold .in, Indicates the first At the current moment, each energy storage node The charging current; Indicates the first The maximum allowable charging current for each energy storage node; Indicates the first The maximum allowable temperature deviation of each energy storage node refers to the difference between the upper limit of the safe operating temperature of the cell and the rated operating temperature. The reference value can be set to 10℃ to 15℃. This represents the function that takes the maximum value. This indicates the minimum temperature coefficient limit, used to avoid situations where the threshold is too low, such as setting... The larger the charging current, the stronger the current surge, and the higher the risk of thermal hysteresis. The corresponding dynamic temperature deviation threshold should be lowered to make the energy storage node identification more sensitive.

[0046] Secondly, the thermal hysteresis deviation is compared with the dynamic temperature deviation threshold, and the energy storage node corresponding to the thermal hysteresis deviation that is greater than the dynamic temperature deviation threshold is determined as the thermal hysteresis energy storage node.

[0047] Specifically, for any first Each energy storage node, at the current moment Thermal hysteresis bias With dynamic temperature deviation threshold When comparing, When, then determine the current number. At the current moment, each energy storage node It belongs to a thermally lagging energy storage node, meaning its temperature response lags behind the current charging current surge; conversely, when When, then determine the current number. At the current moment, each energy storage node It is in a normal state and does not belong to a thermal hysteresis energy storage node.

[0048] Step S300: Convert the thermal hysteresis deviation of the thermal hysteresis energy storage node into the hidden heat that the node can currently accommodate, and convert the hidden heat into the equivalent safety margin current. Calculate the misalignment deviation current between the original charging command current and the equivalent safety margin current of the thermal hysteresis energy storage node.

[0049] For energy storage nodes identified as having thermal hysteresis characteristics, their current measured temperature cannot fully reflect the node's true heating state. Heat has accumulated inside the node exceeding the level corresponding to the current temperature. This potential heat storage is formed by the accumulation of current surges over historical periods. To achieve subsequent scheduling compensation, this potential heat storage needs to be converted into an equivalent safety margin current. This equivalent current is characterized as the safety limit current value corresponding to the safe hiding of heat when the energy storage node is charged with a constant current within the effective observation time window.

[0050] In a specific example, for any first... The thermal hysteresis energy storage node utilizes this first... Rated heat capacity of each thermal hysteresis energy storage node , the first Maximum allowable temperature offset for each thermal hysteresis energy storage node With thermal hysteresis The difference is converted into the hidden heat that the node can currently hold. .

[0051] After converting the thermal hysteresis deviation of each thermal hysteresis energy storage node into the hidden heat that the node can currently accommodate, the hidden heat is then converted into an equivalent safety margin current.

[0052] In a specific example, converting hidden heat into an equivalent safety margin current includes: First, based on the hidden heat, and combined with the charging current and internal resistance of each thermal hysteresis energy storage node at the current moment, the theoretical generation time of the hidden heat is determined.

[0053] Specifically, for any first The thermal hysteresis energy storage node, based on this... At the current moment, each thermal hysteresis energy storage node... Hidden heat Charging current and internal resistance Calculate the hidden heat The theory took a long time to develop It should be understood that when the charging current is less than a preset micro-current threshold (determined based on the system's sampling resolution and current range, with a reference range of 0.01A to 0.1A, or 1% of the rated charging current, used to distinguish between background noise (leakage current, etc.) and the actual effective charging current), the theoretical generation time will no longer be calculated using the above formula. The effective duration is then directly set as the observation time window duration N.

[0054] Secondly, the minimum value between the theoretical generation time and the window duration of the observation time window used to determine the theoretical thermal equilibrium temperature is determined, and the minimum value is taken as the effective generation time of the hidden heat.

[0055] Specifically, for any first A thermal hysteresis energy storage node, if its theoretical generation time is... Less than its determined theoretical thermal equilibrium temperature The window duration N used to set the observation time window indicates the hidden heat. The current charging current can generate heat in a shorter time than the window period, meaning that heat accumulation is mainly concentrated in the near term, and the actual accumulation time is the theoretical generation time. The duration of theoretical development As a source of hidden heat The effective duration of heat generation can more accurately reflect the degree of heat concentration; conversely, if its theoretical generation duration is less than expected... Greater than or equal to its determined theoretical thermal equilibrium temperature The window duration N used to set the observation time window indicates that even at the current maximum heat production rate, at least the window duration is required to accumulate hidden heat. This implies that the heat accumulation is relatively evenly distributed over time, or that the current is already low. In this case, the window duration N should be used as the effective duration for the generation of hidden heat. Therefore, for any given... Each thermal hysteresis energy storage node was used to determine its theoretical generation time. and determining the theoretical thermal equilibrium temperature The smaller value among the window duration N of the set observation time window is used, and this smaller value is taken as the hidden heat. The effective duration of generation Y.

[0056] Finally, based on the hidden heat, and combined with the effective generation time and the internal resistance of each thermal hysteresis energy storage node within the set observation time window used to determine the theoretical thermal equilibrium temperature, the equivalent safety margin current is calculated.

[0057] Specifically, because the internal resistance change of the energy storage node is relatively small within the set observation time window, for any given... The thermal hysteresis energy storage node is calculated. The average internal resistance of each thermal hysteresis energy storage node within the set observation time window Furthermore, based on hidden heat... Hidden heat The effective duration Y of generation and the average internal resistance The equivalent safety margin current is obtained by inverse solving according to Joule's law. When hiding heat The effective generation duration Y is the theoretical generation duration. This indicates that heat is generated in a shorter time, and the calculated equivalent safety margin current... It can accurately reproduce the actual instantaneous thermal stress level that the node has recently experienced.

[0058] During the charging process of each energy storage node in a submerged energy storage system, the charging scheduling commands issued by the system are usually based on the current measured temperature of the energy storage node. Due to the thermal hysteresis effect, the measured temperature of the node will be lower than the temperature corresponding to its true heat accumulation state. This causes the system to judge that the node still has a large charging margin based on the low temperature, and then issue a higher charging power command. At this time, a large amount of heat has accumulated inside the node, which can easily cause thermal risks.

[0059] For any number A thermal hysteresis energy storage node, based on the thermal hysteresis energy storage node at the current time. The original charging command current With equivalent safety margin current Calculate the misalignment deviation current The misalignment deviation current This value represents the current difference between the current charging command and the node's actual thermal tolerance. If the misalignment deviation current... This indicates that the current system command current is lower than or equal to the actual thermal withstand capacity of the current node, and the risk of misalignment is low.

[0060] Step S400: Based on the misalignment deviation current and the equivalent safety margin current, the original charging command current of the thermal hysteresis energy storage node is compensated and corrected, and the charging control of the thermal hysteresis energy storage node is performed based on the corrected charging command current.

[0061] To avoid directly using the original charging command current as the execution command for charging control, which would lead to an underestimation of the actual thermal stress of the thermally lagging energy storage node, the original charging command current of the thermally lagging energy storage node is compensated and corrected based on the misalignment deviation current and the equivalent safety margin current. This ensures that the compensated and corrected charging command current matches the actual thermal state of the node, thereby improving the charging control accuracy.

[0062] In a specific example, the original charging command current of the thermally hysteresis energy storage node is compensated and corrected, including: First, if the equivalent safety margin current is less than the maximum allowable charging current of the thermally lagging energy storage node and the misalignment deviation current is greater than 0, then the compensation coefficient is determined based on the thermal hysteresis deviation and the original charging command current of the thermally lagging energy storage node at the current moment, and the current superposition amount is determined in combination with the misalignment deviation current; the superposition value of the current superposition amount and the equivalent safety margin current is determined as the corrected charging command current of the thermally lagging energy storage node.

[0063] Specifically, for any first For a thermally hysteresis energy storage node, if its equivalent safety margin current... Less than the maximum allowable charging current And its misalignment deviation current Based on its thermal hysteresis deviation and the original charging command current Adaptive determination of misalignment deviation current Adjusted compensation coefficient When the misalignment deviation current and the original charging command current A larger value indicates severe node thermal hysteresis and an extremely strong impulsive command about to be issued by the system, requiring a significant reduction in command current. This corresponds to a higher compensation coefficient. It should be larger.

[0064] In a specific example, determining the compensation coefficient includes: determining the ratio of the thermal hysteresis deviation to the maximum allowable temperature offset of the thermally hysteretic energy storage node as the degree of thermal hysteresis; determining the ratio of the original charging command current of the thermally hysteretic energy storage node at the current moment to the maximum allowable charging current of the thermally hysteretic energy storage node as the current surge intensity; and fusing the degree of thermal hysteresis and the current surge intensity to determine the compensation coefficient.

[0065] Specifically, for any first Each thermally hysteretic energy storage node, based on its thermal hysteresis bias Maximum allowable temperature offset from thermal hysteresis energy storage node ratio and the original charging command current With the maximum allowable charging current of thermal hysteresis energy storage nodes ratio Determine the compensation coefficient .in This represents the minimum value function, used to ensure that the compensation coefficient does not exceed 1, avoiding overcompensation. Ratio Characterizing the degree of thermal hysteresis, when the ratio The larger the value, the more severe the lag, the greater the deviation between the current temperature and the actual thermal state, and therefore the higher the charging command current compensation intensity should be; the ratio The intensity of the current surge is characterized by the larger the original charging command current, the more heat is expected to be generated per unit time, and the more serious the damage of thermal hysteresis. Therefore, the compensation intensity of the charging command current should also be higher.

[0066] After determining the compensation coefficient using the above method, for any given... Each thermal hysteresis energy storage node, with an equivalent safety margin current Based on, and combined with compensation coefficient and misalignment deviation current to the original command current The direction is adjusted to obtain the corrected charging command current, i.e., based on the compensation coefficient. And combined with misalignment deviation current Determine the superposition of currents The current superposition amount With equivalent safety margin current Superimpose the results to obtain the first... The corrected charging command current for each thermal hysteresis energy storage node when When this occurs, it indicates that the risk is extremely low and no compensation is required. The original charging command current remains unchanged; when When this occurs, it indicates that the risk is extremely high and full compensation is required. Completely downgraded to the equivalent safety margin current level for execution; when At that time, the charging command current is reduced proportionally to the safe state.

[0067] Secondly, if the equivalent safety margin current is less than the maximum allowable charging current of the thermal hysteresis energy storage node, and the misalignment deviation current is less than or equal to 0, then the original charging command current of the thermal hysteresis energy storage node is determined as the corrected charging command current of the thermal hysteresis energy storage node.

[0068] Specifically, for any first For a thermally hysteresis energy storage node, if its equivalent safety margin current... Less than the maximum allowable charging current And its misalignment deviation current This indicates that the charging command current is less than the equivalent safety margin current, meaning the system command is lower than the actual thermal stress level experienced by the node. In this case, no downward compensation correction is needed (i.e., no reduction in the command current is required), and the first... The initial charging command current for each thermally hysteresis energy storage node Determine its corrected charging command current. At this time there is .

[0069] In a specific example, the compensation and correction of the original charging command current of the thermal hysteresis energy storage node also includes: if the equivalent safety margin current is greater than or equal to the maximum charging current allowed by the thermal hysteresis energy storage node, the minimum charging current is set as the corrected charging command current of the thermal hysteresis energy storage node.

[0070] Specifically, for any first For a thermally hysteresis energy storage node, if its equivalent safety margin current... Greater than or equal to the first The maximum allowable charging current for each thermal hysteresis energy storage node. That is, This indicates that the node is in a critical state of severe thermal overload, so the corrected charging command current should be set directly. To set the minimum charging current, this minimum charging current can be 0, or it can be used only as a basic maintenance current to maintain basic communication of the internal monitoring module of the energy storage node, so as to ensure safety during the charging process.

[0071] Based on the above scheme, the original charging command current of the thermally lagging energy storage node is compensated and corrected. The corrected charging command current takes into account the actual thermal stress of the node that is underestimated due to the lag, so that the scheduling decision matches the real state of the energy storage node, thereby improving the control accuracy.

[0072] After compensating and correcting the original charging command current of the thermally lagging energy storage node to obtain the corrected charging command current, the thermally lagging energy storage node is charged based on the corrected charging command current. At the same time, the other energy storage nodes are charged based on the original charging command current of the normal energy storage nodes other than the thermally lagging energy storage nodes in the energy storage system.

[0073] In a specific example, charging control includes: sending a charging command current to the local controller of the energy storage node; the local controller converting the received charging command current into a corresponding charging power setting value, and adjusting the actual charging current of the charging module to charge the energy storage node based on the converted charging power setting value.

[0074] Specifically, the control center calculates the compensated charging command current for each thermally lagging energy storage node. And the raw charging command current of normal energy storage nodes (excluding thermally lagging energy storage nodes) in the energy storage system. The charging command current is transmitted to the local controller of each energy storage node via the communication network. Upon receiving the charging command current, each energy storage node converts it into a corresponding charging power setpoint and adjusts the output of its charging module to ensure the actual charging current follows the command value. For thermally lagging energy storage nodes, the compensated charging command current is often lower than the original charging command current, meaning the charging rate needs to be actively reduced to avoid the risk of heat accumulation due to thermal lag; for normal energy storage nodes, the charging command current remains unchanged.

[0075] After each energy storage node in the energy storage system executes the command, it obtains the actual charging current and measured temperature at the next sampling time t+1, and updates the historical data through a sliding window mechanism: the first data point of the current time window is removed, and the newly obtained data point at time t+1 is added to the end of the window, thereby maintaining the window length N unchanged, and using this as input to enter the thermal hysteresis identification and compensation calculation for the next cycle.

[0076] Based on the same inventive concept, embodiments of the present invention also provide a multi-node collaborative charging scheduling system for an immersion energy storage system, such as... Figure 2 As shown, the system includes: a memory 201, a processor 202, and computer program code 203 stored in the memory 201 and running on the processor 202. When the processor 202 executes the computer program code 203, the system can execute any of the multi-node cooperative charging scheduling methods for submerged energy storage systems described above.

[0077] In this embodiment of the invention, the system can be divided into functional modules according to the above method example. For example, each module can correspond to a separate functional module, or two or more functions can be integrated into one processing module. The integrated module can be implemented in hardware. It should be noted that the module division in this embodiment is illustrative and only represents one logical functional division. In actual implementation, there may be other division methods.

[0078] Based on the same inventive concept, embodiments of the present invention also provide a computer program product, which includes: computer program code, which, when run on a computer, causes the computer to execute any of the aforementioned multi-node collaborative charging scheduling methods for submerged energy storage systems.

[0079] Based on the same inventive concept, embodiments of the present invention also provide a computer-readable storage medium storing computer program code, which, when executed on a computer, causes the computer to perform any of the aforementioned submerged energy storage system multi-node collaborative charging scheduling methods.

[0080] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A multi-node cooperative charging scheduling method for an immersed energy storage system, characterized in that, Includes the following steps: During the charging process of the submerged energy storage system, the heat generation and heat dissipation of each energy storage node in the energy storage system are evaluated to determine the theoretical thermal equilibrium temperature of each energy storage node. Calculate the thermal hysteresis deviation between the theoretical thermal equilibrium temperature and the measured temperature of each energy storage node, and based on the thermal hysteresis deviation, screen out the thermal hysteresis energy storage nodes that are in a thermal hysteresis state from all energy storage nodes. The thermal hysteresis deviation of the thermal hysteresis energy storage node is converted into the hidden heat that the node can currently accommodate, and the hidden heat is converted into an equivalent safety margin current. The misalignment deviation current between the original charging command current and the equivalent safety margin current of the thermal hysteresis energy storage node is calculated. Based on the misalignment deviation current and the equivalent safety margin current, the original charging command current of the thermal hysteresis energy storage node is compensated and corrected, and the charging control of the thermal hysteresis energy storage node is performed based on the corrected charging command current.

2. The multi-node collaborative charging scheduling method for an immersion energy storage system according to claim 1, characterized in that, The heat generation and heat dissipation of each energy storage node in the energy storage system are evaluated to determine the theoretical thermal equilibrium temperature of each energy storage node, including: Based on the charging current and internal resistance of each energy storage node within the set observation time window before the current moment, the heat generation of each energy storage node within the set observation time window is determined. Based on the preset heat dissipation coefficient of each energy storage node, the temperature value of each energy storage node within the set observation time window, and the local coolant temperature at the location of each energy storage node, the heat dissipation of each energy storage node within the set observation time window is determined. Based on the rated heat capacity of each energy storage node, the heat difference between the heat generated and the heat dissipated is converted into a temperature value, and then superimposed with the theoretical thermal equilibrium temperature of each energy storage node before the set observation time window to obtain the theoretical thermal equilibrium temperature of each energy storage node at the current moment.

3. The multi-node collaborative charging scheduling method for an immersion energy storage system according to claim 1, characterized in that, Based on the aforementioned thermal hysteresis bias, thermally hysteresis energy storage nodes in a state of thermal hysteresis are selected from all energy storage nodes, including: Based on the charging current of each energy storage node at the current moment and the maximum allowable temperature deviation of each energy storage node, the dynamic temperature deviation threshold is determined. The thermal hysteresis deviation is compared with the dynamic temperature deviation threshold, and the energy storage node corresponding to the thermal hysteresis deviation that is greater than the dynamic temperature deviation threshold is determined as the thermal hysteresis energy storage node.

4. The multi-node collaborative charging scheduling method for an immersion energy storage system according to claim 3, characterized in that, Determining the dynamic temperature deviation threshold includes: Determine the ratio of the charging current of each energy storage node to the maximum allowable charging current at the current moment, and perform negative correlation mapping truncation on the ratio to obtain the temperature coefficient; The maximum allowable temperature deviation of each energy storage node is corrected using the temperature coefficient to obtain the dynamic temperature deviation threshold.

5. The multi-node collaborative charging scheduling method for an immersion energy storage system according to claim 1, characterized in that, Converting the hidden heat into an equivalent safety margin current includes: Based on the hidden heat, and combined with the charging current and internal resistance of each thermal hysteresis energy storage node at the current moment, the theoretical generation time of the hidden heat is determined. The minimum value between the theoretical generation time and the window duration of the observation time window used to determine the theoretical thermal equilibrium temperature is determined, and the minimum value is taken as the effective generation time of the hidden heat. Based on the hidden heat, and combined with the effective generation time and the internal resistance of each thermal hysteresis energy storage node within the set observation time window used to determine the theoretical thermal equilibrium temperature, the equivalent safety margin current is calculated.

6. The multi-node collaborative charging scheduling method for an immersion energy storage system according to claim 1, characterized in that, The original charging command current of the thermally hysteresis energy storage node is compensated and corrected, including: If the equivalent safety margin current is less than the maximum allowable charging current of the thermal hysteresis energy storage node, and the misalignment deviation current is greater than 0, then a compensation coefficient is determined based on the thermal hysteresis deviation and the original charging command current of the thermal hysteresis energy storage node at the current moment, and the current superposition amount is determined in combination with the misalignment deviation current; the superposition value of the current superposition amount and the equivalent safety margin current is determined as the corrected charging command current of the thermal hysteresis energy storage node. If the equivalent safety margin current is less than the maximum allowable charging current of the thermal hysteresis energy storage node, and the misalignment deviation current is less than or equal to 0, then the original charging command current of the thermal hysteresis energy storage node is determined as the corrected charging command current of the thermal hysteresis energy storage node.

7. The multi-node collaborative charging scheduling method for an immersion energy storage system according to claim 6, characterized in that, Determine the compensation coefficient, including: The ratio of the thermal hysteresis deviation to the maximum allowable temperature offset of the thermal hysteresis energy storage node is determined as the degree of thermal hysteresis. The ratio of the original charging command current of the thermal hysteresis energy storage node at the current moment to the maximum allowable charging current of the thermal hysteresis energy storage node is determined as the current surge intensity. The thermal hysteresis degree and the current impact intensity are combined to determine the compensation coefficient.

8. The multi-node collaborative charging scheduling method for an immersion energy storage system according to claim 6, characterized in that, The compensation and correction of the original charging command current of the thermally hysteretic energy storage node also includes: If the equivalent safety margin current is greater than or equal to the maximum allowable charging current of the thermal hysteresis energy storage node, the minimum charging current will be set as the corrected charging command current of the thermal hysteresis energy storage node.

9. The multi-node collaborative charging scheduling method for an immersion energy storage system according to claim 1, characterized in that, The method further includes: The charging control of other energy storage nodes is based on the original charging command current of the normal energy storage nodes (excluding thermally lagging energy storage nodes) in the energy storage system.

10. A multi-node collaborative charging scheduling method for an immersion energy storage system according to claim 1 or 9, characterized in that, Perform charging control, including: The charging command current is sent to the local controller of the energy storage node; The local controller converts the received charging command current into a corresponding charging power setting value, and adjusts the actual charging current of the charging module to charge the energy storage node based on the converted charging power setting value.

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