Energy storage system, control method, electronic device, storage medium and program product

Abstract

The present application relates to the technical field of power systems, and discloses an energy storage system, a control method, an electronic device, a storage medium and a program product, the energy storage system comprising a plurality of energy storage modules, each energy storage module comprising: a communication unit for sharing operation state data among the plurality of energy storage modules; and the control unit is configured to acquire the operation state data of other energy storage modules through the communication unit, and dynamically elect two energy storage modules in the plurality of energy storage modules to form a cooperative host pair based on a multi-agent decision rule, and the cooperative host pair cooperatively adjusts the power grid voltage and the power grid frequency of the energy storage system. According to the invention, each energy storage module is configured with the control unit, and the communication unit is utilized to share the operation state data, so that the system can dynamically elect a collaborative host pair composed of two energy storage modules based on a multi-agent decision rule. And the problem that the reliability of the whole system is reduced due to the fault of the fixed host is effectively solved.

Description

Technical Field

[0001] This application relates to the field of power system technology, specifically to energy storage systems, control methods, electronic devices, storage media, and program products. Background Technology

[0002] Distributed off-grid energy storage systems are critical infrastructure in the renewable energy sector, used to improve grid stability and energy dispatch efficiency. Among related technologies, the master-slave architecture is a typical solution for distributed off-grid energy storage systems. This architecture designates a fixed master device to perform voltage / frequency (V / F) control functions to maintain the stability of the grid within the system; the remaining devices operate as slaves dependent on the master device.

[0003] However, in this master-slave architecture, the lack of fault tolerance mechanisms leads to reduced reliability when the fixed host device fails. Summary of the Invention

[0004] This application provides an energy storage system, control method, electronic device, storage medium, and program product to solve the problem of low reliability of distributed off-grid energy storage systems in related technologies.

[0005] In a first aspect, this application provides an energy storage system, comprising: multiple energy storage modules for collaboratively storing and releasing electrical energy; each energy storage module comprising: a communication unit for connecting its own energy storage module with other energy storage modules to share operational status data among the multiple energy storage modules; and a control unit configured to acquire operational status data of other energy storage modules through the communication unit, and dynamically elect two energy storage modules from the multiple energy storage modules to form a collaborative host pair based on multi-agent decision rules, wherein the collaborative host pair collaboratively adjusts the grid voltage and grid frequency of the energy storage system.

[0006] Beneficial Effects: The energy storage system provided in this application, by configuring a control unit for each energy storage module and utilizing a communication unit to share operational status data, enables the system to dynamically elect a cooperative host pair consisting of two energy storage modules based on multi-agent decision-making rules, to jointly regulate grid voltage and frequency. This dynamic election and cooperative working mechanism completely changes the architecture of related technologies that rely on a single fixed host, thereby effectively solving the technical problem of reduced system reliability due to fixed host failure. When any host in the cooperative host pair malfunctions, the system can quickly initiate a re-election process to ensure the continuity of critical regulation functions, greatly improving the fault tolerance and overall operational reliability of the distributed off-grid energy storage system.

[0007] In one optional implementation, the operating status data includes at least one of power capacity, depth of discharge, fault status, power generation forecast status, and load forecast status.

[0008] Beneficial effects: By specifically defining the operating status data to include multiple key parameters such as power capacity, depth of discharge, fault status, power generation prediction status, and load prediction status, the control unit can more accurately assess the current performance, health status, and future task execution capabilities of each energy storage module when electing the coordinating host pair. This allows for the selection of the host pair most suitable for undertaking the coordinating regulation task at a specific time, avoiding the bias that may arise from decision-making based on a single parameter. This further optimizes the dynamic regulation performance of the system and enhances the rationality of the election results and the stability of the system.

[0009] In one optional implementation, the control unit includes: a fault detection subunit configured to monitor the operating status of the cooperative host pair and generate and send a trigger signal when an anomaly is detected; and a decision subunit configured to, in response to the trigger signal, execute the multi-agent decision rule, determine the election weights based on the discharge depth and / or power generation prediction status of each energy storage module, and elect a new cooperative host pair from the plurality of energy storage modules based on the election weights.

[0010] Beneficial Effects: By employing dedicated fault detection and decision-making subunits to implement the election process, hardware-level acceleration and professional processing of fault response and decision execution are achieved. When the fault detection subunit detects an anomaly and triggers the decision-making subunit, the subunit can efficiently determine the election weights based on core parameters reflecting the potential power supply capacity of the energy storage module (such as depth of discharge and power generation prediction status). This ensures that the election process for the new host pair is not only responsive but also that the weight allocation is based on evidence, significantly improving the automation, speed, and scientific nature of the fault switching process. This ensures that the system can achieve rapid, smooth, and reliable host switching in the event of a fault, minimizing the risk window for voltage and frequency runaway.

[0011] In one optional implementation, the control unit further includes a prediction subunit configured to generate an exit command when it predicts that its own energy storage module is about to experience an anomaly, and to send the exit command through the communication unit to cause its own energy storage module to exit the cooperative host pair.

[0012] Beneficial Effects: By adding a predictive sub-unit, the energy storage system acquires proactive preventative fault tolerance capabilities. This module can proactively diagnose and issue a shutdown command before the energy storage module itself is about to fail but has not yet completely failed, enabling the unit to orderly exit the cooperative host pair. This proactive shutdown mechanism effectively avoids system disturbances or control interruptions that may be caused by sudden node failures, providing the system with a longer safety margin and a smoother switching window, thereby enhancing the system's reliability and stability to a higher level.

[0013] Secondly, this application provides a control method applied to an energy storage system according to the first aspect above or any corresponding embodiment, comprising: acquiring operating status data of multiple energy storage modules through a communication unit; dynamically electing two energy storage modules from the multiple energy storage modules to form a cooperative host pair based on multi-agent decision rules and the operating status data; and having the cooperative host pair coordinately adjust the grid voltage and grid frequency of the energy storage system.

[0014] In one optional implementation, the step of dynamically electing two energy storage modules from the plurality of energy storage modules to form a cooperative host pair based on multi-agent decision rules and the operating status data includes determining the election weights based on the discharge depth and / or power generation prediction status of each energy storage module when an abnormality is detected in the current cooperative host pair, and electing a new cooperative host pair based on the election weights.

[0015] In an optional implementation, the control method further includes: generating and sending an exit command when any energy storage module in the current collaborative host pair predicts that it is about to experience an anomaly, so as to exit the collaborative host pair.

[0016] Thirdly, this application provides an electronic device, including: a memory and a processor, which are communicatively connected to each other. The memory stores computer instructions, and the processor executes the computer instructions to perform the control method described in the first aspect or any corresponding embodiment.

[0017] Fourthly, this application provides a computer-readable storage medium storing computer instructions for causing a computer to perform the control method described in the first aspect or any corresponding embodiment thereof.

[0018] Fifthly, this application provides a computer program product, including computer instructions for causing a computer to execute the control method described in the first aspect or any corresponding embodiment thereof. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the specific embodiments of this application or the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0020] Figure 1 This is a schematic diagram of a module of an energy storage system according to an embodiment of this application; Figure 2 This is a schematic diagram of a control unit according to an embodiment of this application; Figure 3 This is a schematic diagram illustrating an application scenario of an energy storage system according to an embodiment of this application; Figure 4 This is a structural block diagram of a control device according to an embodiment of this application; Figure 5 This is a flowchart illustrating multi-agent decision-making according to an embodiment of this application; Figure 6 This is a schematic diagram of the hardware structure of an electronic device according to an embodiment of this application.

[0021] Explanation of the reference numerals in the figure: 10. Energy storage system; 100. Energy storage module; 110. Communication unit; 120. Control unit; 121. Fault detection subunit; 122. Decision subunit; 123. Prediction subunit. Detailed Implementation

[0022] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0023] It is understood that before using the technical solutions disclosed in the various embodiments of this application, users should be informed of the types, scope of use, and usage scenarios of the personal information involved in this application in an appropriate manner in accordance with relevant laws and regulations, and user authorization should be obtained.

[0024] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this application, "multiple" means two or more, unless otherwise explicitly specified.

[0025] In related technologies, a complete off-grid distributed energy storage system 10 typically adopts a master-slave architecture, where one distributed energy storage system 10 acts as the system master and the others act as slaves. The system master is responsible for regulating the stability of the grid voltage and frequency of the entire system.

[0026] If the main unit of the system fails and goes down, and the load in the residential area suddenly increases, the voltage of the entire power grid will drop, leading to grid voltage instability. Conversely, if the load in the residential area suddenly decreases, the frequency of the entire power grid will rise, also causing grid frequency instability. Therefore, the drawbacks of distributed off-grid energy storage technology with a single fixed main unit are obvious.

[0027] According to an embodiment of this application, an energy storage system 10 is provided, which can solve the technical drawbacks of the current distributed off-grid energy storage system with a single fixed host.

[0028] Reference Figure 1 As shown, this embodiment provides an energy storage system 10. As used below, the term "module" can refer to a combination of software and / or hardware that implements a predetermined function. Although the apparatus described in the following embodiments is preferably implemented in software, implementation in hardware, or a combination of software and hardware, is also possible and contemplated.

[0029] Specifically, the energy storage system 10 includes multiple energy storage modules 100 for collaborative storage and release of electrical energy. Each energy storage module 100 includes: The communication unit 110 connects its own energy storage module 100 with other energy storage modules 100 to share operating status data among multiple energy storage modules 100; The control unit 120 is configured to acquire the operating status data of other energy storage modules 100 through the communication unit 110, and dynamically elect two energy storage modules 100 from multiple energy storage modules 100 to form a cooperative host pair based on multi-agent decision rules, and the cooperative host pair coordinates the grid voltage and grid frequency of the energy storage system 10.

[0030] Among them, the energy storage module 100 is a complete energy storage and management unit, which typically includes basic components such as battery pack, battery management system (BMS), and power conversion system (PCS).

[0031] Multi-agent decision-making rules refer to algorithmic rules based on distributed artificial intelligence theory, where each energy storage module 100 acts as an autonomous agent, communicating and cooperating with each other to jointly complete complex decision-making tasks. A cooperative host pair refers to two energy storage modules 100 elected through a primary-backup or load-balancing mechanism, which jointly undertake the task of regulating system voltage and frequency, forming redundant backups.

[0032] In practical implementation, the communication unit 110 can be implemented using industrial fieldbus (such as CAN bus, Modbus), industrial Ethernet (such as Profinet, EtherCAT), or wireless communication (such as ZigBee, LoRa). The control unit 120 is typically based on a microprocessor or microcontroller and implements the functions by executing control programs stored in memory.

[0033] The energy storage system 10 of this application configures a control unit 120 for each energy storage module 100 and uses a communication unit 110 to share operating status data. This enables the system to dynamically elect a cooperative host pair consisting of two energy storage modules 100 based on multi-agent decision-making rules to jointly regulate grid voltage and frequency. This dynamic election and cooperative working mechanism completely changes the architecture of related technologies that rely on a single fixed host, thereby effectively solving the technical problem of reduced system reliability due to fixed host failure. When any host in the cooperative host pair malfunctions, the system can quickly initiate a re-election process to ensure the continuity of critical regulation functions, greatly improving the fault tolerance and overall operational reliability of the distributed off-grid energy storage system 10.

[0034] Optionally, in some embodiments of this application, the operating status data includes at least one of power capacity, depth of discharge, fault status, power generation prediction status, and load prediction status.

[0035] Specifically, the energy capacity refers to the ratio of the current remaining available energy of the energy storage module 100 to its rated capacity; the depth of discharge reflects the percentage of the current discharge relative to the rated capacity; fault status includes abnormal operating states such as overvoltage, undervoltage, overcurrent, and overheating; power generation forecast status includes future power generation predicted based on weather forecasts and historical data; and load forecast status includes future load demand predicted based on electricity consumption habits and calendar effects. These parameters are acquired in real time through sensors and algorithms, providing a comprehensive and accurate data foundation for multi-agent decision-making.

[0036] In these embodiments, by specifically defining the operating status data as including multiple key parameters such as power capacity, depth of discharge, fault status, power generation prediction status, and load prediction status, the control unit 120 can more accurately evaluate the current performance, health status, and future task execution capability of each energy storage module 100 when electing the coordinating host pair. This allows for the election of the host pair most suitable for undertaking the coordinating adjustment task at a specific time, avoiding the bias that may arise from decision-making based on a single parameter, further optimizing the dynamic adjustment performance of the system, and enhancing the rationality of the election results and the stability of the system.

[0037] Reference Figure 2 As shown, optionally, in some embodiments of this application, the control unit 120 includes: The fault detection subunit 121 is configured to monitor the working status of the collaborative host pair and generate and send a trigger signal when an abnormality is detected. The decision subunit 122 is configured to execute multi-agent decision rules in response to a trigger signal, determine the election weights based on the discharge depth and / or power generation prediction status of each energy storage module 100, and elect a new cooperative host pair from multiple energy storage modules 100 based on the election weights.

[0038] In practical implementation, the fault detection subunit 121 identifies anomalies by real-time monitoring parameters such as voltage, current, and temperature, and employing threshold comparison or algorithmic diagnosis (such as Kalman filtering). The decision-making subunit 122 uses an election weight determination algorithm that may include weighted average method, fuzzy logic method, or neural network algorithm. The election process can adopt typical multi-agent decision-making methods such as voting mechanism, bidding mechanism, or negotiation mechanism. The trigger signal can be a hardware interrupt signal or a software event flag, used to initiate the emergency election process.

[0039] In these embodiments, the election process is implemented using a dedicated fault detection subunit 121 and decision-making subunit 122, achieving hardware-level acceleration and professional processing of fault response and decision execution. When the fault detection subunit 121 detects an anomaly and triggers the decision-making subunit 122, the decision-making subunit 122 can efficiently determine the election weights based on core parameters reflecting the potential power supply capacity of the energy storage module 100 (such as depth of discharge and power generation prediction status). This makes the election process of the new host pair not only responsive but also based on evidence-based weight allocation, significantly improving the automation, speed, and scientific nature of the fault switching process. This ensures that the system can achieve fast, smooth, and reliable host switching when a fault occurs, minimizing the risk window of voltage and frequency runaway.

[0040] Reference Figure 2 As shown, optionally, in some embodiments of this application, the control unit 120 further includes: The prediction subunit 123 is configured to generate an exit command when it predicts that its own energy storage module 100 is about to malfunction, and send the exit command through the communication unit 110 so that its own energy storage module 100 exits the cooperative host pair.

[0041] It should be noted that the prediction subunit 123 can predict faults by analyzing early fault characteristics such as battery internal resistance change trends, capacity decay rates, and temperature rise slopes, using time series prediction algorithms (such as the ARIMA model) or machine learning methods. Based on this, the exit instruction includes information such as the exit reason, timestamp, and recommended replacement. The exit process can employ a smooth exit mechanism, including steps such as early warning, work handover, and resource release, ultimately achieving a non-disruptive exit from the work sequence, ensuring that work handover is completed before complete exit, and avoiding impact on the system.

[0042] In these embodiments, the addition of a prediction subunit 123 enables the energy storage system 10 to possess proactive preventative fault tolerance. This module can proactively diagnose and issue an exit command before the energy storage module 100 itself is about to fail but has not yet completely failed, allowing the unit to exit the cooperative host pair in an orderly manner. This proactive exit mechanism effectively avoids system disturbances or control interruptions that may be caused by sudden node failures, providing the system with a longer safety margin and a smoother switching window, thereby enhancing the system's reliability and stability to a higher level.

[0043] Reference Figure 3 As shown, based on the above embodiments, a complete energy storage system 10 consisting of four off-grid energy storage modules 100 is used as an example for explanation. This energy storage system 10 forms a complete distributed MAS multi-agent decision-making system.

[0044] Among them, the control unit 120 can use the existing distributed off-grid energy storage EMS controller to form a MAS multi-agent distributed decision system. The MAS multi-agent members can achieve real-time data sharing through the fieldbus, and each MAS member can build its own distributed decision system through the same software algorithm.

[0045] Under normal working conditions, refer to Figure 4 As shown, if the MAS inference engine decides that MAS System 1 and MAS System 4 form a cooperative dual-host system, and performs V / F control output according to a known weight ratio to adjust the grid voltage and frequency of the entire system, and if MAS System 1 diagnoses that its current state is about to become abnormal, MAS System 1 automatically relinquishes its allocation rights. At this time, MAS System 3 takes over the allocation rights of MAS System 1, and MAS System 1 automatically exits the dual-host combination. Then, MAS System 3 and the original MAS System 4 re-enter the dual-host combination, achieving a smooth and fault-free system switchover.

[0046] The MAS multi-intelligent inference engine enables autonomous decision-making and information sharing among distributed off-grid energy storage systems, and allows for dynamic adjustment of the host system. This avoids the harm caused by the lack of host control due to the failure of a single fixed host system. The dynamic adjustment of the host system and the weakening of the host system enhance the stability and robustness of the distributed off-grid energy storage system in grid operation.

[0047] According to an embodiment of this application, a control method embodiment is also provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0048] This embodiment provides a control method that can be used in the energy storage system 10 described above. Figure 5 This is a flowchart of a control method according to an embodiment of this application, such as... Figure 5 As shown, the process includes the following steps: Step S201: Obtain the operating status data of multiple energy storage modules 100 through the communication unit 110.

[0049] Step S202: Based on the multi-agent decision-making rules and operating status data, dynamically elect two energy storage modules 100 from multiple energy storage modules 100 to form a cooperative host pair.

[0050] Specifically, in step S202, the process of dynamically electing a cooperative host pair based on multi-agent decision rules and operational status data includes: If an abnormality is detected in the current coordinating host pair, the election weight is determined based on the discharge depth and / or power generation prediction status of each energy storage module 100, and a new coordinating host pair is elected based on the election weight.

[0051] In step S203, the coordinating host adjusts the grid voltage and grid frequency of the energy storage system 10.

[0052] In addition, the control method of this application also includes: Step A: If any energy storage module 100 in the current collaborative host pair predicts that it is about to experience an anomaly, it generates and sends an exit command to exit the collaborative host pair.

[0053] The control method provided in this application can be applied to the energy storage system 10 provided in any embodiment of this application, and has corresponding beneficial effects. Further descriptions of the effects of each of the above steps are the same as in the corresponding embodiments described above, and will not be repeated here.

[0054] Figure 6 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application.

[0055] The following is a detailed reference. Figure 6 This diagram illustrates a suitable structural schematic for implementing the electronic device described in the embodiments of this application. The electronic device may include a processor (e.g., a central processing unit, graphics processor, etc.) 601, which can perform various appropriate actions and processes according to a program stored in read-only memory (ROM) 602 or a program loaded from memory 608 into random access memory (RAM) 603. The RAM 603 also stores various programs and data required for the operation of the electronic device. The processor 601, ROM 602, and RAM 603 are interconnected via a bus 604. An input / output (I / O) interface 605 is also connected to the bus 604.

[0056] Typically, the following devices can be connected to I / O interface 605: input devices 606 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 607 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; memory devices 608 including, for example, magnetic tapes, hard disks, etc.; and communication devices 609. Communication device 609 allows electronic devices to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 6 Electronic devices with various devices are shown, but it should be understood that it is not required to implement or have all of the devices shown, and more or fewer devices may be implemented or have instead.

[0057] Specifically, according to embodiments of this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of this application include a computer program product comprising a computer program carried on a non-transitory computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device 609, or installed from a memory 608, or installed from a ROM 602. When the computer program is executed by the processor 601, it performs the functions defined in the control method of embodiments of this application.

[0058] Figure 6 The electronic device shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of this application.

[0059] This application also provides a computer-readable storage medium. The methods described in this application can be implemented in hardware or firmware, or implemented as recordable on a storage medium, or implemented as computer code downloaded via a network and originally stored on a remote storage medium or a non-transitory machine-readable storage medium and subsequently stored on a local storage medium. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium can also include combinations of the above types of memory. It is understood that computers, processors, microprocessor controllers, or programmable hardware include storage components capable of storing or receiving software or computer code. When the software or computer code is accessed and executed by the computer, processor, or hardware, the control methods shown in the above embodiments are implemented.

[0060] A portion of this application can be applied as a computer program product, such as computer program instructions, which, when executed by a computer, can invoke or provide the methods and / or technical solutions according to this application through the operation of the computer. Those skilled in the art will understand that the forms in which computer program instructions exist in a computer-readable medium include, but are not limited to, source files, executable files, installation package files, etc. Correspondingly, the ways in which computer program instructions are executed by a computer include, but are not limited to: the computer directly executing the instructions, or the computer compiling the instructions and then executing the corresponding compiled program, or the computer reading and executing the instructions, or the computer reading and installing the instructions and then executing the corresponding installed program. Here, the computer-readable medium can be any available computer-readable storage medium or communication medium accessible to a computer.

[0061] Although embodiments of this application have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of this application, and all such modifications and variations fall within the scope defined by the appended claims.

Claims

1. An energy storage system, characterized in that, include: Multiple energy storage modules are used to collaboratively store and release electrical energy; Each of the energy storage modules includes: A communication unit connects the energy storage module to other energy storage modules to share operational status data among the multiple energy storage modules; The control unit is configured to acquire the operating status data of other energy storage modules through the communication unit, and dynamically elect two energy storage modules from the plurality of energy storage modules to form a cooperative host pair based on multi-agent decision rules, and the cooperative host pair coordinates the grid voltage and grid frequency of the energy storage system.

2. The energy storage system according to claim 1, characterized in that, The operational status data includes at least one of the following: power capacity, depth of discharge, fault status, power generation forecast status, and load forecast status.

3. The energy storage system according to claim 1, characterized in that, The control unit includes: The fault detection subunit is configured to monitor the working status of the collaborative host pair and generate and send a trigger signal when an anomaly is detected. The decision subunit is configured to respond to the trigger signal, execute the multi-agent decision rule, determine the election weights based on the discharge depth and / or power generation prediction status of each energy storage module, and elect a new cooperative host pair from the plurality of energy storage modules based on the election weights.

4. The energy storage system according to claim 3, characterized in that, The control unit further includes: The prediction subunit is configured to generate an exit command when it predicts that its own energy storage module is about to malfunction, and send the exit command through the communication unit to cause its own energy storage module to exit the cooperative host pair.

5. A control method applied to the energy storage system according to any one of claims 1 to 4, characterized in that, include: The operating status data of multiple energy storage modules are obtained through the communication unit; Based on the multi-agent decision-making rules and the operational status data, two energy storage modules from the multiple energy storage modules are dynamically elected to form a collaborative host pair. The coordinating host unit coordinates and adjusts the grid voltage and grid frequency of the energy storage system.

6. The control method according to claim 5, characterized in that, The dynamic election of two energy storage modules from the plurality of energy storage modules to form a cooperative host pair based on multi-agent decision rules and the operational status data includes: If an abnormality is detected in the current cooperating host pair, the election weight is determined based on the discharge depth and / or power generation prediction status of each energy storage module, and a new cooperating host pair is elected based on the election weight.

7. The control method according to claim 5, characterized in that, The control method further includes: If any energy storage module in the current collaborative host pair predicts that it is about to experience an anomaly, it generates and sends an exit command to exit the collaborative host pair.

8. An electronic device, characterized in that, include: A memory and a processor are communicatively connected, the memory storing computer instructions, and the processor executing the computer instructions to perform the control method of any one of claims 5 to 7.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing the computer to perform the control method according to any one of claims 5 to 7.

10. A computer program product, characterized in that, It includes computer instructions for causing a computer to perform the control method according to any one of claims 5 to 7.

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