SOC balance control method, energy storage system and related equipment

Abstract

The invention discloses an SOC balance control method, an energy storage system and related equipment, and belongs to the technical field of computers. The method comprises the following steps: updating the initial SOC of a current energy storage system according to the initial SOC of each adjacent energy storage system adjacent to the current energy storage system in the energy storage network to obtain a first updated SOC; determining theoretical discharge power according to the first updated SOC; determining the actual discharge power of the current energy storage system according to the theoretical discharge power by taking the overall energy storage expected power of the energy storage network as a first constraint; and performing discharge mode SOC balance control on the current energy storage system based on the actual discharge power.

Description

Technical Field

[0001] This application relates to the field of computer technology, and in particular to a SOC equalization control method, energy storage system and related equipment. Background Technology

[0002] In related technologies, in order to achieve the goal of SOC balance, the traditional consensus algorithm is usually used to perform weighted average calculation with fixed weight coefficients. This cannot be dynamically adjusted according to the real-time SOC status of each energy storage system, thus making it difficult to achieve SOC balance. Summary of the Invention

[0003] This application provides a SOC balancing control method, an energy storage system, and related equipment, which can achieve dynamic SOC balancing.

[0004] To solve the above-mentioned technical problems, this application is implemented as follows: In a first aspect, a SOC equalization control method is provided, applied to each energy storage system in an energy storage network. The method includes: updating the initial SOC of the current energy storage system based on the initial SOC of each adjacent energy storage system in the energy storage network to obtain a first updated SOC; determining the theoretical discharge power based on the first updated SOC; determining the actual discharge power of the current energy storage system based on the theoretical discharge power, using the overall expected energy storage power of the energy storage network as a first constraint; and performing discharge mode SOC equalization control on the current energy storage system based on the actual discharge power.

[0005] Secondly, an energy storage system is provided, comprising: a data acquisition module for acquiring the State of Charge (SOC) of each energy storage system in an energy storage network; a communication module for constructing the energy storage network and communicating with other energy storage systems in the energy storage network, wherein the energy storage network is a ring-shaped undirected network; a computing power module for implementing the steps described in the first aspect; and a control module for controlling the operation of the energy storage system and detecting and recovering from abnormal states of the energy storage system.

[0006] Thirdly, a SOC balancing control device is provided, comprising: an update module, configured to update the initial SOC of the current energy storage system based on the initial SOC of each adjacent energy storage system in the energy storage network, to obtain a first updated SOC; a first determination module, configured to determine the theoretical discharge power based on the first updated SOC; a second determination module, configured to determine the actual discharge power of the current energy storage system based on the theoretical discharge power, using the overall expected energy storage power of the energy storage network as a first constraint; and a balancing control module, configured to perform discharge mode SOC balancing control on the current energy storage system based on the actual discharge power.

[0007] Fourthly, an electronic device is provided, including a processor and a memory, wherein the memory stores a program or instructions executable on the processor, the program or instructions, when executed by the processor, perform the steps of the method described in the first aspect.

[0008] Fifthly, a readable storage medium is provided, on which a program or instructions are stored, which, when executed by a processor, implement the steps of the method described in the first aspect.

[0009] In a sixth aspect, a computer program product is provided, the computer program product comprising a computer program stored on a non-transitory computer-readable storage medium, the computer program comprising program instructions that, when executed by a computer, cause the computer to perform the steps of the method described in the first aspect.

[0010] In this embodiment, the initial SOC of the current energy storage system is updated based on the initial SOC of each adjacent energy storage system in the energy storage network to obtain a first updated SOC. Based on the first updated SOC, the theoretical discharge power is determined. With the overall expected energy storage power of the energy storage network as the first constraint, the actual discharge power of the current energy storage system is determined based on the theoretical discharge power. Based on the actual discharge power, the discharge mode SOC equalization control of the current energy storage system is performed, which can achieve dynamic equalization control of SOC while meeting the overall power demand of the energy storage network.

[0011] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and do not limit this application. Attached Figure Description

[0012] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0013] Figure 1 This invention illustrates a flowchart of an exemplary embodiment of the SOC equalization control method provided in this application. Figure 2 This invention provides a schematic diagram of the structure of an energy storage network according to an exemplary embodiment of the present application. Figure 3 This illustration shows a flowchart of determining a first updated SOC according to an exemplary embodiment of this application; Figure 4 A schematic diagram of a process for determining theoretical discharge power provided by an exemplary embodiment of this application is shown; Figure 5This invention illustrates a flowchart of an exemplary embodiment of the SOC equalization control method provided in this application. Figure 6 A schematic diagram of a process for determining actual discharge power provided by an exemplary embodiment of this application is shown; Figure 7 A schematic diagram of a process for determining actual discharge power provided by an exemplary embodiment of this application is shown; Figure 8 This invention illustrates a flowchart of an exemplary embodiment of the SOC equalization control method provided in this application. Figure 9 This illustration shows a schematic diagram of the iterative effect provided by an exemplary embodiment of this application; Figure 10 A schematic diagram illustrating the iterative effect in related technologies is shown; Figure 11 A schematic diagram of a process for determining a target number of iterations is shown in an exemplary embodiment of this application; Figure 12 This application shows a schematic diagram of the structure of an energy storage system provided in an exemplary embodiment. Figure 13 This invention provides a schematic diagram of the structure of a SOC equalization control device according to an exemplary embodiment of the present application. Figure 14 A schematic diagram of the structure of an electronic device provided in an exemplary embodiment of this application is shown. Detailed Implementation

[0014] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0015] like Figure 1 The diagram shown is a flowchart of a SOC equalization control method provided in an exemplary embodiment of this application. This method is applied to each energy storage system in an energy storage network; that is, each energy storage system achieves dynamic SOC equalization control by executing this SOC equalization control method. The method may include the following steps: S110: Update the initial SOC of the current energy storage system based on the initial SOC of each adjacent energy storage system in the energy storage network that is adjacent to the current energy storage system, and obtain the first updated SOC.

[0016] Here, SOC refers to the State of Charge. The energy storage network is a ring-shaped, undirected network, for example, as shown below. Figure 2 The diagram shows a schematic of an energy storage network. This network includes six nodes: energy storage system 1, energy storage system 2, energy storage system 3, energy storage system 4, energy storage system 5, and energy storage system 6. The six nodes are arranged in a ring, with each node directly connected to only its two adjacent nodes. Each node can communicate with other nodes. The number of nodes in this network can be dynamically increased or decreased, and the connection relationships between nodes can also be dynamically adjusted. This energy storage network can correspond to an adjacency matrix, which describes the connection relationships between nodes. If node i and node j are directly connected, then A[i][j] = 1; if they are not connected, or i = j (the node itself), then A[i][j] = 0. For example, Figure 2 The adjacency matrix corresponding to the energy storage network shown can be:

[0017] Continue to refer to Figure 2 Assuming the current energy storage system is energy storage system 1, then its adjacent energy storage systems are energy storage system 2 and energy storage system 6. The initial SOC of each adjacent energy storage system is the latest SOC of the adjacent energy storage system collected by the current energy storage system during the current SOC equalization control period. During the current SOC equalization control period, the current energy storage system collects the initial SOC of the adjacent energy storage systems only once from the initial iteration to the completion of the iteration; when entering the next SOC equalization control period, the initial SOC of the adjacent energy storage systems is collected again.

[0018] Understandably, traditional energy storage systems typically employ centralized management, where a control center collects the State of Charge (SOC) information of all energy storage units, calculates an SOC balancing strategy, and then sends instructions to each energy storage system. However, this approach incurs significant communication overhead. In this embodiment, the initial SOC of the current energy storage system is adjusted based on the initial SOC of adjacent energy storage systems. This decomposes the complex global balancing problem into simple decisions that rely solely on local information, achieving efficient, stable, and robust SOC balancing for each energy storage system. Furthermore, since there is no control center, newly added energy storage systems only need to communicate with adjacent nodes to perform SOC balancing control.

[0019] S120: Determine the theoretical discharge power based on the first updated SOC.

[0020] It is understandable that the initial SOC of the current energy storage system is updated based on the initial SOC of each adjacent energy storage system in the energy storage network to obtain the first updated SOC. This first updated SOC indicates the target of SOC equalization control. Therefore, the discharge power determined based on the first updated SOC is the theoretical discharge power within the current time step.

[0021] S130: Using the overall expected energy storage power of the energy storage network as the first constraint, determine the actual discharge power of the current energy storage system based on the theoretical discharge power.

[0022] It is understandable that in order to meet the overall expected power demand of the energy storage network, the theoretical discharge power needs to be adjusted based on the overall expected power demand of the energy storage network as the first constraint to obtain the actual discharge power. In this way, the actual discharge power satisfies the first constraint, there is no risk of over-discharge, and the overall expected power demand of the energy storage network is also met.

[0023] S140: Based on the actual discharge power, perform discharge mode SOC equalization control on the current energy storage system.

[0024] In this step, the SOC estimate can be obtained through methods such as ampere-hour integration, and then SOC equalization control can be performed based on the SOC estimate.

[0025] In this embodiment, the initial SOC of the current energy storage system is updated based on the initial SOC of each adjacent energy storage system in the energy storage network to obtain a first updated SOC. Based on the first updated SOC, the theoretical discharge power is determined. With the overall expected energy storage power of the energy storage network as the first constraint, the actual discharge power of the current energy storage system is determined based on the theoretical discharge power. Based on the actual discharge power, the discharge mode SOC equalization control of the current energy storage system is performed, which can achieve dynamic equalization control of SOC while meeting the overall power demand of the energy storage network.

[0026] In some embodiments, such as Figure 3 As shown, the above S110 may include the following steps: S112: Determine the neighboring node SOC difference array based on the initial SOC of the current energy storage system and the initial SOC of each of the adjacent energy storage systems.

[0027] The neighboring node SOC difference array includes the SOC difference value between the current energy storage system and each of the neighboring energy storage systems.

[0028] Continue to refer to the above. Figure 2Assuming the current energy storage system is energy storage system 1, then its adjacent energy storage systems are energy storage system 2 and energy storage system 6. The initial SOC of energy storage system 2 is... The initial SOC corresponding to energy storage system 6 is The initial SOC corresponding to the current energy storage system, i.e., energy storage system 1, is: The SOC difference between energy storage system 1 and energy storage system 2 is: The SOC difference between energy storage system 1 and energy storage system 6 is: Therefore, the SOC difference array of the neighboring nodes can be: [ ].

[0029] S114: Determine the neighborhood exponential decay weight based on the neighborhood node SOC difference array, and normalize the neighborhood exponential decay weight.

[0030] In some embodiments, S114 may include: determining the neighborhood exponential decay weight as the product of the neighborhood node SOC difference array and the weight lower bound constraint value. For example, the neighborhood exponential decay weight can be expressed by the following formula:

[0031] in, This represents the neighborhood exponential decay weight after normalization. This represents the lower bound constraint value for the weights, which is used to ensure the minimum influence of weakly connected nodes. This represents the SOC difference array of neighboring nodes.

[0032] In this embodiment, the neighborhood weights are dynamically generated based on exponential smoothing and lower bound constraints, which can enhance the robustness of the SOC equalization control method to abnormal situations such as communication delays and measurement errors.

[0033] S116: Based on the normalized neighborhood exponential decay weight, the retention weight corresponding to the current energy storage system, and the neighborhood node SOC array, update the initial SOC of the current energy storage system to obtain the second updated SOC.

[0034] The neighboring node SOC array includes the initial SOC of each of the adjacent energy storage systems.

[0035] Continue to refer to the above. Figure 2 Assuming the current energy storage system is energy storage system 1, then its adjacent energy storage systems are energy storage system 2 and energy storage system 6. The initial SOC of energy storage system 2 is... The initial SOC corresponding to energy storage system 6 is Therefore, the SOC array of the neighboring nodes can be: [ ].

[0036] In some embodiments, S116 may include: determining that the second updated SOC is the sum of a first value and a second value, wherein the first value is the product of the retention weight corresponding to the current energy storage system and the initial SOC of the current energy storage system, the second value is the product of a first difference and a first sum, the first difference being the difference between 1 and the retention weight corresponding to the current energy storage system, and the first sum being the sum of the products of the initial SOC and the corresponding retention weight of each adjacent energy storage system. For example, the second updated SOC can be expressed by the following formula:

[0037] in, This indicates the second updated SOC; the first value is: , This indicates the retention weight corresponding to the current energy storage system. This represents the initial SOC of the current energy storage system, where i is the system number; the second value is: The first difference is: The first sum is: n represents the total number of adjacent energy storage systems, and j represents the j-th adjacent energy storage system. Let J represent the initial SOC of the j-th adjacent energy storage system. This represents the retention weight of the j-th adjacent energy storage system.

[0038] S118: The first updated SOC is obtained by performing momentum smoothing on the second updated SOC.

[0039] Understandably, momentum smoothing can accelerate convergence and overcome the problem that traditional average weights or fixed topology weights cannot dynamically suppress outliers, leading to consensus shifts.

[0040] In some embodiments, S118 may include: determining that the first updated SOC is the sum of a third value and a fourth value, wherein the third value is the product of the momentum factor and the initial SOC of the current energy storage system, and the fourth value is the product of a second difference and the second updated SOC, wherein the second difference is the difference between 1 and the momentum factor.

[0041] For example, the first updated SOC can be represented by the following formula:

[0042] in, This indicates the first update to SOC; the third value is: , Represents the momentum factor. The fourth value represents the initial SOC of the current energy storage system. The second difference is: , This is the second updated SOC.

[0043] In this embodiment, a weighted calculation is performed based on the initial SOC of the current energy storage system and the second updated SOC obtained after weighted updating, which can suppress high-frequency oscillations.

[0044] based on Figure 3 The embodiment shown in this application also provides a flowchart for determining the first updated SOC, as illustrated below. Figure 4 As shown, the following steps may be included: S410: Neighborhood SOC diff Difference calculation.

[0045] S410 may include: determining the neighboring node SOC difference array SOC based on the initial SOC of the current energy storage system and the initial SOC of each adjacent energy storage system. diff Among them, the SOC difference array of neighboring nodes. diff This includes the SOC difference between the current energy storage system and each adjacent energy storage system.

[0046] S420: Calculation of neighborhood SOC weight exponential decay.

[0047] S420 may include: a lower bound constraint on the neighborhood SOC weights and a normalization process for the neighborhood SOC weights.

[0048] The neighborhood SOC weight lower bound constraint may include: determining the neighborhood exponential decay weight as the product of the neighborhood node SOC difference array and the weight lower bound constraint value. Neighborhood SOC weight normalization may include normalizing the neighborhood exponential decay weight.

[0049] S430: Update based on retained weights and neighborhood weights .

[0050] S430 may include: updating the initial SOC of the current energy storage system based on the normalized neighborhood exponential decay weight, the retention weight corresponding to the current energy storage system, and the neighborhood node SOC array to obtain the second updated SOC, wherein the neighborhood node SOC array includes the initial SOC of each adjacent energy storage system.

[0051] S440: Based on momentum factor and Smooth iteration .

[0052] S440 may include: determining that the first updated SOC is the sum of the third value and the fourth value, wherein the third value is the product of the momentum factor and the initial SOC of the current energy storage system, and the fourth value is the product of the second difference and the second updated SOC, wherein the second difference is the difference between 1 and the momentum factor.

[0053] In some embodiments, such as Figure 5 As shown, the above-mentioned S120 may include the following steps: S122: Determine the power dynamic allocation coefficient based on the third difference.

[0054] The third difference is the difference between the initial SOC of the current energy storage system and the first updated SOC, i.e., the third difference is: , This represents the initial SOC of the current energy storage system. The difference for the first updated SOC.

[0055] In some embodiments, S122 may include one of the following: (1) In response to the third difference being greater than the first SOC threshold, the power dynamic allocation coefficient is determined to be the preset maximum power dynamic allocation coefficient.

[0056] It is understandable that if the third difference ( If the initial SOC of the current energy storage system is greater than the first SOC threshold, it means that the initial SOC of the current energy storage system is significantly different from the first updated SOC. Therefore, the corresponding discharge power is also significantly different. Thus, the preset maximum power dynamic allocation coefficient is selected as the power dynamic allocation coefficient to improve the theoretical discharge power.

[0057] (2) In response to the third difference being less than or equal to the first SOC threshold, the power dynamic allocation coefficient is determined to be the product of a preset minimum power dynamic allocation coefficient and a first ratio, wherein the first ratio is the ratio of the third difference to the first SOC threshold.

[0058] It is understandable that if the third difference ( If the initial SOC of the current energy storage system is less than or equal to the first SOC threshold, it means that the difference between the initial SOC and the first updated SOC is small, so the power dynamic allocation coefficient can be determined proportionally.

[0059] S124: Determine the theoretical discharge power based on the power dynamic allocation coefficient, the first updated SOC, the initial SOC of the current energy storage system, and the first performance parameter of the current energy storage system.

[0060] In some embodiments, the first performance parameter includes rated discharge power and charge / discharge efficiency; determining the theoretical discharge power based on the power dynamic allocation coefficient, the first updated SOC, the initial SOC of the current energy storage system, and the first performance parameter of the current energy storage system includes: determining the theoretical discharge power as the ratio of a fifth value to a time step, wherein the fifth value is the product of the power dynamic allocation coefficient, the third difference, the rated discharge power, and the charge / discharge efficiency.

[0061] For example, the theoretical discharge power can be expressed by the following formula:

[0062] The fifth value is: The third difference is: , Indicates the dynamic power allocation coefficient. This indicates the rated discharge power of the current energy storage system. This indicates the current charging and discharging efficiency of the energy storage system; Indicates a time step.

[0063] In some other embodiments, the method further includes: updating the theoretical discharge power to the maximum discharge power in response to the theoretical discharge power being greater than the maximum discharge power of the current energy storage system. That is, limiting the theoretical discharge power to not exceed the maximum discharge power.

[0064] based on Figure 5 The embodiment shown in this application also provides a flowchart for determining the theoretical discharge power, as illustrated below. Figure 6 As shown, the following steps may be included: S610: Calculate the SOC range.

[0065] The SOC range is the third difference, which is the difference between the initial SOC of the current energy storage system and the first updated SOC.

[0066] S620: Determine whether the third difference is greater than the first SOC threshold.

[0067] If the value is greater than the specified value, proceed to S630; otherwise, proceed to S640.

[0068] S630: Determine the power dynamic allocation coefficient k as the preset maximum power dynamic allocation coefficient.

[0069] S640: The power dynamic allocation coefficient k is obtained by updating the preset minimum power dynamic allocation coefficient proportionally.

[0070] S650: Theoretical discharge power P is calculated based on the power dynamic allocation coefficient k and the first updated SOCS. alloc .

[0071] S660: Limiting theoretical power P alloc Not exceeding the maximum discharge power P max .

[0072] S670: Updated theoretical discharge power P alloc .

[0073] In some embodiments, the above-described S130 may include one of the following: (1) In response to the fourth difference being greater than the preset power threshold, the updated theoretical discharge power is determined to be the product of the sixth value and the theoretical discharge power, and the actual discharge power of the current energy storage system is determined based on the updated theoretical discharge power, using the second performance parameter of the current energy storage system as the second constraint.

[0074] Wherein, the fourth difference is the difference between the overall expected power of energy storage and the second sum, the second sum is the sum of the theoretical discharge power and the current actual discharge power of the other energy storage systems, and the sixth value is the ratio of the fourth difference to the preset power threshold.

[0075] Continue to refer to the above. Figure 2 The overall expected energy storage power of this energy storage network is the sum of the expected power of each of the energy storage systems 1, 2, 3, 4, 5, and 6, that is:

[0076] in, This represents the expected total energy storage capacity. This represents the expected energy storage power of energy storage system 1. This represents the expected energy storage power of energy storage system 2. This represents the expected energy storage power of energy storage system 3. This represents the expected energy storage power of energy storage system 4. This indicates the expected energy storage capacity of energy storage system 5. This represents the expected energy storage power of energy storage system 6. Assuming the current energy storage system is energy storage system 1, the theoretical discharge power corresponding to energy storage system 1 is... Therefore, the second sum is:

[0077] in, Indicates the second sum. Indicates the theoretical discharge power. This indicates the current actual discharge power of energy storage system 2. This indicates the current actual discharge power of energy storage system 3. This indicates the current actual discharge power of energy storage system 4. This indicates the current actual discharge power of energy storage system 5. This indicates the current actual discharge power of energy storage system 6.

[0078] In this embodiment, if If the theoretical discharge power is greater than the preset power threshold, then the theoretical discharge power is updated proportionally to ensure that the theoretical discharge power is [value missing]. Able to meet grid power requirements Then, the actual discharge power is determined based on the second constraint.

[0079] (2) In response to the fact that the difference between the overall energy storage expected power and the second sum is less than or equal to a preset power threshold, the actual discharge power is determined to be the theoretical discharge power.

[0080] In other words, if If the power is less than or equal to the preset power threshold, it means the theoretical discharge power is... Able to meet the power demand of the power grid Therefore, the actual discharge power can be determined to be the theoretical discharge power.

[0081] Further, in some other embodiments, the second performance parameter includes rated discharge power, device power consumption, and dischargeable power, wherein the dischargeable power is the ratio of a seventh value to a time step, wherein the seventh value is the product of a fifth difference, the rated power of the current energy storage system, and the charge / discharge efficiency of the current energy storage system, the fifth difference is the difference between the initial SOC and the minimum SOC of the current energy storage system, and the minimum SOC is the minimum value among the initial SOCs of multiple energy storage systems in the energy storage network; the step of determining the actual discharge power of the current energy storage system based on the updated theoretical discharge power, using the second performance parameter of the current energy storage system as a second constraint, includes: in response to the updated theoretical discharge power being less than the rated discharge power, the device power consumption, and the dischargeable power, respectively, determining the actual discharge power as the updated theoretical discharge power.

[0082] The dischargeable power can be expressed by the following formula:

[0083] in, The seventh value represents the dischargeable power. The fifth difference is: , This represents the initial SOC of the current energy storage system. Represents the minimum SOC. Indicates the rated power. Indicates charge / discharge efficiency. Indicating a time step, for example, the It can be 5 minutes. Furthermore, the embodiments in this application do not... Specific limitations can be imposed and adjusted according to the actual situation.

[0084] In this embodiment, if the updated theoretical discharge power is less than the rated discharge power, device power consumption, and dischargeable power, respectively, and the updated theoretical discharge power satisfies the triple discharge power constraint, i.e., the second constraint, then the actual discharge power of the current energy storage system can be determined to be the updated theoretical discharge power. In this embodiment, by introducing the triple discharge power constraint based on SOC, i.e., the second constraint, the safety of the energy storage system's discharge can be enhanced, the lifespan of the energy storage system can be improved, and the system's discharge capacity can be increased. Simultaneously, it ensures that energy storage systems with a large SOC discharge more, energy storage systems with a small SOC discharge less, and accelerates SOC convergence.

[0085] In addition, if the updated theoretical discharge power does not meet the first constraint, the calculated residual power can be compensated by other energy storage systems.

[0086] Based on the above embodiments, this application also provides a flowchart for determining the actual discharge power, as shown below. Figure 7 As shown, the following steps may be included: S710: Calculate the fourth difference.

[0087] The fourth difference is the difference between the overall expected power of energy storage and the second sum, while the second sum is the sum of the theoretical discharge power and the current actual discharge power of other energy storage systems.

[0088] S720: Determine whether the fourth difference is greater than the preset power threshold.

[0089] If the value is greater than S730, then proceed to S750; if the value is less than S730, then proceed to S750.

[0090] S730: Theoretical power Palloc is updated proportionally.

[0091] S730 includes: determining the updated theoretical discharge power as the product of the sixth value and the theoretical discharge power, wherein the sixth value is the ratio of the fourth difference to the preset power threshold.

[0092] S740: Allocate according to the updated theoretical power Palloc, provided that the updated theoretical power Palloc satisfies the second constraint.

[0093] S750: Distributed according to theoretical power Palloc.

[0094] In some embodiments, the discharge mode SOC equalization control of the current energy storage system based on the actual discharge power may include the following steps: Step 1: Update the initial SOC of the current energy storage system based on the actual discharge power to obtain the target SOC.

[0095] Step 2: In response to the fact that the target SOC does not meet the convergence condition and the current iteration number is less than the target iteration number, the target SOC is used as the initial SOC of the current energy storage system, and the process returns to the step of updating the initial SOC of the current energy storage system based on the initial SOC of each adjacent energy storage system in the energy storage network to obtain the first updated SOC, until the convergence condition is met or the target iteration number is reached.

[0096] For example, the convergence condition may include at least one of the following: (1) Whether the difference between the target SOC and the SOC benchmark value is less than the third SOC threshold, which is the average SOC value determined based on the initial SOC of each energy storage system.

[0097] (2) Whether the difference between the target SOC and the maximum SOC value is less than the fourth SOC threshold, wherein the maximum SOC value is the maximum SOC value among the initial SOCs of multiple energy storage systems in the energy storage network.

[0098] (3) Whether the difference between the target SOC and the minimum SOC value is less than the fifth SOC threshold, wherein the minimum SOC value is the minimum SOC value among the initial SOCs of multiple energy storage systems in the energy storage network.

[0099] It should be noted that the embodiments of this application do not specifically limit the first SOC threshold, the second SOC threshold, the third SOC threshold, the fourth SOC threshold, and the fifth SOC threshold, and can be adjusted according to the actual situation.

[0100] In this embodiment, if the target SOC does not meet the convergence condition and the current iteration number is less than the target iteration number, the target SOC is used as the initial SOC of the current energy storage system, and the target SOC is redefined until the target SOC meets the convergence condition or the current iteration number is greater than or equal to the target iteration number, thus obtaining the optimal target SOC and completing the SOC balancing.

[0101] For example, such as Figure 8 The diagram shown is another flowchart illustrating the SOC equalization control method provided in this application embodiment, which may include the following steps: S810: Obtain the initial SOC of other energy storage systems.

[0102] S820: Determine the initial SOC of the current energy storage system.

[0103] S830: Triple-constraint discharge power calculation.

[0104] S830 includes: the rated discharge power P of the energy storage system Rated The power consumption P of the energy storage system equip and the discharge power P of the energy storage system ava Perform discharge power constraint.

[0105] S840: Adaptive iteration count calculation.

[0106] S840 includes: determining the target number of iterations based on the relationship between the difference between the maximum and minimum SOC values ​​among the initial SOC values ​​of multiple energy storage systems in the energy storage network and the second SOC threshold.

[0107] S850: Consensus Protocol SOC Computation.

[0108] S850 may include the following steps: S851: Determine the neighborhood exponential decay weight based on the neighborhood node SOC difference array, and normalize the neighborhood exponential decay weight.

[0109] S852: Based on the normalized neighborhood exponential decay weight, the retention weight corresponding to the current energy storage system, and the neighborhood node SOC array, update the initial SOC of the current energy storage system to obtain the second updated SOC.

[0110] S853: The first updated SOC is obtained by performing momentum smoothing on the second updated SOC.

[0111] S860: Robust power distribution.

[0112] S860 may include: determining a power dynamic allocation coefficient based on the difference between the initial SOC and the first updated SOC of the current energy storage system, and calculating the theoretical discharge power based on the power dynamic allocation coefficient.

[0113] S870: Safe power rebalancing.

[0114] S870 may include: calculating theoretical discharge power Does it meet the power demand P of the power grid? demand If the conditions are not met, the theoretical discharge power will be updated proportionally. And determine whether the updated theoretical discharge power meets the triple-constraint discharge power.

[0115] S880: Adaptive optimization of SOC state update.

[0116] S880 may include: based on the theoretical discharge power P after safe power rebalancing dis Determine the target SOC.

[0117] S890: Determine whether the target SOC meets the convergence condition.

[0118] If the condition is met, SOC balancing is completed; otherwise, the target SOC is used as the initial SOC of the current energy storage system, and the process returns to S820.

[0119] Furthermore, in some other embodiments, the method further includes one of the following: (1) In response to the sixth difference being greater than the second SOC threshold, the target iteration number is determined to be the preset maximum iteration number, wherein the sixth difference is the difference between the maximum SOC value and the minimum SOC value among the initial SOC values ​​of the multiple energy storage systems in the energy storage network.

[0120] (2) In response to the sixth difference being less than or equal to the second SOC threshold, the target iteration number is determined to be the sum of the base iteration number and the eighth value, wherein the eighth value is the product of the second ratio and the number of machine iterations, and the second ratio is the ratio of the sixth difference to the second SOC threshold.

[0121] In this embodiment, the target number of iterations is determined based on the relationship between the sixth difference and the second SOC threshold, achieving adaptive iteration number calculation. This increases coordination efforts when the SOC imbalance among various energy storage systems is significant. For example, as... Figure 9 As shown, this represents the number of iterations required to achieve SOC equalization in an embodiment of this application. Figure 10 As shown, this represents the number of iterations required for a traditional consensus algorithm to achieve SOC balancing. The SOC balancing control method in this application only requires 10 iterations to achieve balancing, while the traditional consensus algorithm requires more than 25 iterations.

[0122] Based on this embodiment, this application also provides a flowchart for determining the target number of iterations, as shown below. Figure 11 As shown, the following steps may be included: S1110: Calculate the sixth difference.

[0123] The sixth difference is the difference between the maximum and minimum SOC values ​​among the initial SOC values ​​of multiple energy storage systems in the energy storage network.

[0124] S1120: Determine whether the sixth difference is greater than the second SOC threshold.

[0125] If the value is greater than the specified value, proceed to S930; otherwise, proceed to S940.

[0126] S1130: Determine the target number of iterations = the preset maximum number of iterations.

[0127] S1140: Determine the target number of iterations = basic number of iterations + second ratio × number of maneuver iterations.

[0128] The second ratio is the ratio of the sixth difference to the second SOC threshold.

[0129] This application also provides an energy storage system, such as... Figure 12 As shown, the energy storage system 1200 includes: a data acquisition module 1210 for acquiring the State of Charge (SOC) of each energy storage system in the energy storage network; a communication module 1220 for constructing the energy storage network and communicating with other energy storage systems in the network, wherein the energy storage network is a ring-shaped undirected network, which reduces communication link requirements and improves network fault tolerance; and a computing module 1230 for implementing... Figures 1-12 The various processes implemented in the illustrated method embodiment; the control module 1240 is used to control the operation of the energy storage system and to detect and recover from abnormal states of the energy storage system. Additionally, the acquisition module 1210 is also used to read the grid demand power, equipment power consumption, voltage, current, rated capacity, discharge efficiency, etc., of each energy storage system, and to set key parameters such as iteration step size, iteration count, momentum factor, SOC range threshold, power allocation coefficient, and weighting factor.

[0130] The energy storage system provided in this application embodiment can achieve... Figures 1-12 The various processes implemented in the method embodiments shown will not be described again here to avoid repetition.

[0131] Figure 13 This invention provides a schematic diagram of the structure of a SOC equalization control device according to an embodiment of the present application, as shown below. Figure 13 As shown, the SOC equalization control device 1300 may include: an update module 1310, a first determination module 1320, a second determination module 1330, and an equalization control module 1340.

[0132] In this embodiment, the update module 1310 is used to update the initial SOC of the current energy storage system according to the initial SOC of each adjacent energy storage system in the energy storage network that is adjacent to the current energy storage system, so as to obtain a first updated SOC; The first determining module 1320 is used to determine the theoretical discharge power based on the first updated SOC; The second determining module 1330 is used to determine the actual discharge power of the current energy storage system based on the theoretical discharge power, with the overall expected energy storage power of the energy storage network as the first constraint. The equalization control module 1340 is used to perform discharge mode SOC equalization control on the current energy storage system based on the actual discharge power.

[0133] The SOC equalization control device provided in this application embodiment can achieve... Figures 1-12 The various processes implemented in the method embodiments shown will not be described again here to avoid repetition.

[0134] The SOC equalization control device in this application embodiment can be a device, or it can be a component, integrated circuit, or chip in an electronic device. This application embodiment does not impose specific limitations.

[0135] One SOC equalization control device in this application embodiment can be a device with an operating system. The operating system can be Android, iOS, or other possible operating systems; this application embodiment does not specifically limit the specific operating system.

[0136] like Figure 14 As shown, this application embodiment also provides an electronic device 1400, including a processor 1410 and a memory 1420. The memory 1420 stores a program or instructions that can run on the processor 1410. When the program or instructions are executed by the processor 1410, they implement the above-mentioned... Figures 1 to 12 The various processes in the illustrated embodiments can achieve the same technical effect, and will not be described again here to avoid repetition.

[0137] This application embodiment also provides a readable storage medium storing a program or instructions, which, when executed by a processor, implement the above-described functionality. Figures 1 to 12 The various processes in the illustrated embodiments can achieve the same technical effect, and will not be described again here to avoid repetition.

[0138] The processor mentioned above is the processor in the terminal described in the above embodiments. The readable storage medium includes computer-readable storage media, such as computer read-only memory (ROM), random access memory (RAM), magnetic disk, or optical disk. In some examples, the readable storage medium may be a non-transient readable storage medium.

[0139] This application embodiment also provides a chip, the chip including a processor and a communication interface, the communication interface being coupled to the processor, the processor being used to run programs or instructions to implement the above. Figures 1 to 12 The various processes in the illustrated embodiments can achieve the same technical effect, and will not be described again here to avoid repetition.

[0140] It should be understood that the chip mentioned in the embodiments of this application may also be referred to as a system-on-a-chip, system chip, chip system, or system-on-a-chip, etc.

[0141] This application embodiment also provides a computer program / program product, the computer program product including a computer program stored on a non-transitory computer-readable storage medium, the computer program including program instructions, which, when executed by a computer, cause the computer to perform the above-described actions. Figures 1 to 12 The various processes in the illustrated embodiments can achieve the same technical effect, and will not be described again here to avoid repetition.

[0142] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element. Furthermore, it should be noted that the scope of the methods and apparatuses in the embodiments of this application is not limited to performing functions in the order shown or discussed, but may also include performing functions substantially simultaneously or in the reverse order, depending on the functions involved. For example, the described methods may be performed in a different order than described, and various steps may be added, omitted, or combined. Additionally, features described with reference to certain examples may be combined in other examples.

[0143] From the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of computer software products plus necessary general-purpose hardware platforms, and of course, they can also be implemented by hardware. The computer software product is stored in a storage medium (such as ROM, RAM, magnetic disk, optical disk, etc.) and includes several instructions to cause the terminal or network-side device to execute the methods described in the various embodiments of this application.

[0144] The embodiments of this application have been described above with reference to the accompanying drawings. However, this application is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other implementations under the guidance of this application without departing from the spirit and scope of the claims. All of these implementations are within the protection scope of this application.

Claims

1. A SOC equalization control method, applied to each energy storage system in an energy storage network, characterized in that, The method includes: Based on the initial SOC of each adjacent energy storage system in the energy storage network, the initial SOC of the current energy storage system is updated to obtain the first updated SOC; The theoretical discharge power is determined based on the first updated SOC; Using the overall expected energy storage power of the energy storage network as the first constraint, the actual discharge power of the current energy storage system is determined based on the theoretical discharge power. Based on the actual discharge power, the current energy storage system is subjected to discharge mode SOC equalization control.

2. The method according to claim 1, characterized in that, The step of updating the initial SOC of the current energy storage system based on the initial SOC of each adjacent energy storage system in the energy storage network to obtain the first updated SOC includes: Based on the initial SOC of the current energy storage system and the initial SOC of each of the adjacent energy storage systems, a neighboring node SOC difference array is determined, wherein the neighboring node SOC difference array includes the SOC difference value between the current energy storage system and each of the adjacent energy storage systems; Based on the SOC difference array of the neighboring nodes, the neighborhood exponential decay weight is determined, and the neighborhood exponential decay weight is normalized. Based on the normalized neighborhood exponential decay weight, the retention weight corresponding to the current energy storage system, and the neighborhood node SOC array, the initial SOC of the current energy storage system is updated to obtain the second updated SOC, wherein the neighborhood node SOC array includes the initial SOC of each of the adjacent energy storage systems. The first updated SOC is obtained by performing momentum smoothing on the second updated SOC.

3. The method according to claim 2, characterized in that, The step of determining the neighborhood exponential decay weight based on the neighborhood node SOC difference array includes: The neighborhood exponential decay weight is determined to be the product of the neighborhood node SOC difference array and the weight lower limit constraint value.

4. The method according to claim 2, characterized in that, The process of updating the initial SOC of the current energy storage system based on the normalized neighborhood exponential decay weight, the retention weight corresponding to the current energy storage system, and the neighborhood node SOC array, to obtain the second updated SOC, includes: The second updated SOC is determined to be the sum of a first value and a second value, wherein the first value is the product of the retention weight corresponding to the current energy storage system and the initial SOC of the current energy storage system, the second value is the product of a first difference and a first sum, the first difference is the difference between 1 and the retention weight corresponding to the current energy storage system, and the first sum is the sum of the products of the initial SOC and the corresponding retention weight of each adjacent energy storage system.

5. The method according to claim 2, characterized in that, The step of obtaining the first updated SOC by performing momentum smoothing on the second updated SOC includes: The first updated SOC is determined to be the sum of the third value and the fourth value, wherein the third value is the product of the momentum factor and the initial SOC of the current energy storage system, and the fourth value is the product of the second difference and the second updated SOC, wherein the second difference is the difference between 1 and the momentum factor.

6. The method according to claim 1, characterized in that, The step of determining the theoretical discharge power based on the first updated SOC includes: The power dynamic allocation coefficient is determined based on the third difference, wherein the third difference is the difference between the initial SOC of the current energy storage system and the first updated SOC; The theoretical discharge power is determined based on the power dynamic allocation coefficient, the first updated SOC, the initial SOC of the current energy storage system, and the first performance parameter of the current energy storage system.

7. The method according to claim 6, characterized in that, The determination of the power dynamic allocation coefficient based on the third difference includes one of the following: In response to the third difference being greater than the first SOC threshold, the power dynamic allocation coefficient is determined to be the preset maximum power dynamic allocation coefficient; In response to the third difference being less than or equal to the first SOC threshold, the power dynamic allocation coefficient is determined to be the product of a preset minimum power dynamic allocation coefficient and a first ratio, wherein the first ratio is the ratio of the third difference to the first SOC threshold.

8. The method according to claim 6, characterized in that, The first performance parameters include rated discharge power and charge / discharge efficiency; determining the theoretical discharge power based on the power dynamic allocation coefficient, the first updated SOC, the initial SOC of the current energy storage system, and the first performance parameters of the current energy storage system includes: The theoretical discharge power is determined as the ratio of the fifth value to the time step, wherein the fifth value is the product of the power dynamic allocation coefficient, the third difference, the rated discharge power, and the charge / discharge efficiency.

9. The method according to claim 8, characterized in that, The method further includes: In response to the theoretical discharge power being greater than the maximum discharge power of the current energy storage system, the theoretical discharge power is updated to the maximum discharge power.

10. The method according to claim 1, characterized in that, The determination of the actual discharge power of the current energy storage system based on the theoretical discharge power, using the overall expected energy storage power of the energy storage network as the first constraint, includes one of the following: In response to the fourth difference being greater than a preset power threshold, the updated theoretical discharge power is determined to be the product of the sixth value and the theoretical discharge power. Using the second performance parameter of the current energy storage system as a second constraint, the actual discharge power of the current energy storage system is determined based on the updated theoretical discharge power. Here, the fourth difference is the difference between the overall expected energy storage power and the second sum, the second sum is the sum of the theoretical discharge power and the current actual discharge power of the other energy storage systems, and the sixth value is the ratio of the fourth difference to the preset power threshold. In response to the fourth difference being less than or equal to a preset power threshold, the actual discharge power is determined to be the theoretical discharge power.

11. The method according to claim 10, characterized in that, The second performance parameter includes rated discharge power, device power consumption, and dischargeable power. The dischargeable power is the ratio of the seventh value to the time step. The seventh value is the product of the fifth difference, the rated power of the current energy storage system, and the charge / discharge efficiency of the current energy storage system. The fifth difference is the difference between the initial SOC and the minimum SOC of the current energy storage system. The minimum SOC is the minimum value among the initial SOCs of multiple energy storage systems in the energy storage network. The step of determining the actual discharge power of the current energy storage system based on the updated theoretical discharge power, using the second performance parameter of the current energy storage system as the second constraint, includes: In response to the updated theoretical discharge power being less than the rated discharge power, the device power consumption, and the dischargeable power, the actual discharge power is determined to be the updated theoretical discharge power.

12. The method according to claim 1, characterized in that, The step of performing discharge mode SOC equalization control on the current energy storage system based on the actual discharge power includes: The initial SOC of the current energy storage system is updated based on the actual discharge power to obtain the target SOC. In response to the fact that the target SOC does not meet the convergence condition and the current iteration number is less than the target iteration number, the target SOC is used as the initial SOC of the current energy storage system, and the process returns to the step of updating the initial SOC of the current energy storage system based on the initial SOC of each adjacent energy storage system in the energy storage network to obtain the first updated SOC, until the convergence condition is met or the target iteration number is reached.

13. The method according to claim 12, characterized in that, The method further includes one of the following: In response to the sixth difference being greater than the second SOC threshold, the target iteration number is determined to be the preset maximum iteration number, wherein the sixth difference is the difference between the maximum SOC value and the minimum SOC value among the initial SOC values ​​of multiple energy storage systems in the energy storage network; In response to the sixth difference being less than or equal to the second SOC threshold, the target iteration number is determined to be the sum of the base iteration number and the eighth value, where the eighth value is the product of the second ratio and the number of machine iterations, and the second ratio is the ratio of the sixth difference to the second SOC threshold.

14. An energy storage system, characterized in that, include: The acquisition module is used to acquire the SOC of each energy storage system in the energy storage network; A communication module is used to construct the energy storage network and communicate with other energy storage systems in the energy storage network, wherein the energy storage network is a ring-shaped undirected network; The computing power module is used to implement the steps of the SOC equalization control method as described in any one of claims 1-13; The control module is used to control the operation of the energy storage system and to detect and recover from abnormal states of the energy storage system.

15. An electronic device, characterized in that, It includes a processor, a memory, and a program or instructions stored in the memory and executable on the processor, wherein when the program or instructions are executed by the processor, they implement the steps of the SOC equalization control method as described in any one of claims 1-13.

16. A readable storage medium, characterized in that, The readable storage medium stores a program or instructions that, when executed by a processor, implement the steps of the SOC equalization control method as described in any one of claims 1-13.

17. A computer program product, characterized in that, The computer program product includes program instructions that, when executed by a computer, cause the computer to perform the steps of the SOC equalization control method as described in any one of claims 1-13.

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