A cooperative charging method, device, equipment and readable storage medium

Abstract

The application discloses a kind of cooperative charging method, device, equipment and readable storage medium, design distributed direct current energy storage device technical field, for improving the power supply stability of distributed energy storage device, its method includes obtaining each direct current energy storage device with the historical delay data of the central controller, based on the standard network delay of each direct current energy storage device calculated based on the historical delay data;Response external charging instruction, determine charging target based on the external charging instruction, determine target area based on the charging target and preset division rule, determine several target direct current energy storage devices based on the SOC state and health state of each direct current energy storage device in the target area;The standard network delay of each target direct current energy storage device is obtained, and the output proportion of each target direct current energy storage device is calculated based on the standard network delay, and each target direct current energy storage device is controlled based on the output proportion to the charging target cooperative charging.

Description

Technical Field

[0001] This invention relates to the field of DC energy storage technology, and in particular to a collaborative charging method, apparatus, device, and readable storage medium. Background Technology

[0002] Currently, with the continuous growth of global demand for renewable energy, electric vehicles, as a key component of low-carbon transportation, are experiencing rapid market expansion. Simultaneously, charging infrastructure closely related to electric vehicles has also developed rapidly. However, with the large-scale connection of charging piles, the power grid faces enormous pressure and impact. Distributed energy storage systems, as a flexible energy storage method, can help mitigate these impacts, ensuring timely control and management of charging power. In practical applications, due to network latency, communication bandwidth limitations, and other technical factors, information transmission often exhibits a certain time lag. This time lag may slow down the convergence speed of charging management algorithms, and in some cases, the algorithm may even fail to reach the expected convergence state, leading to grid instability.

[0003] Existing collaborative charging methods reduce latency through cloud-edge collaboration and edge priority, and optimize collaborative charging by selecting target charging stations based on edge nodes and uploading data to the cloud. However, they do not consider the statistics of historical response delays to directly calculate and allocate the output ratio of each distributed energy storage device, resulting in poor power supply stability of the energy storage device. Summary of the Invention

[0004] This invention provides a collaborative charging method, apparatus, device, and readable storage medium to improve the power supply stability of distributed energy storage devices.

[0005] To address the aforementioned technical problems, this invention provides a collaborative charging method applicable to distributed DC energy storage systems. The distributed DC energy storage system includes a central controller and several DC energy storage devices, characterized by comprising: Obtain historical delay data between each DC energy storage device and the central controller, and calculate the standard network delay of each DC energy storage device based on the historical delay data; In response to an external charging command, a charging target is determined based on the external charging command, a target area is determined based on the charging target and a preset division rule, and several target DC energy storage devices are determined based on the SOC status and health status of each DC energy storage device in the target area. Obtain the standard network delay of each target DC energy storage device, calculate the output ratio of each target DC energy storage device based on the standard network delay, and control each target DC energy storage device to perform coordinated charging of the charging target based on the output ratio.

[0006] This invention acquires historical delay data between each DC energy storage device and the central controller and calculates the standard network delay accordingly. It then combines this with target identification of external charging commands, determination of target areas based on preset partitioning rules, and screening of target devices based on the SOC and health status of devices within those areas. Finally, it calculates the output ratio of each target device using its standard network delay and issues coordinated control. By calculating the output ratio through delay perception and allocating resources accordingly, devices with faster response and more reliable communication are prioritized for short-time-window tasks, reducing compensation and rescheduling actions caused by command delays. Furthermore, incorporating the standard network delay into allocation constraints helps suppress oscillations during scheduling iterations and shortens convergence time, thereby improving the steady-state accuracy and robustness of the system's dynamic response. Simultaneously, by using candidate screening based on target areas and combining SOC and health thresholds, it effectively reduces unnecessary communication and computational overhead, ensuring matching of energy availability and reliability among participating energy storage devices, thus reducing unnecessary charge-discharge cycles and maintenance costs, and ultimately improving the stability and reliability of coordinated charging.

[0007] Furthermore, the process of responding to an external charging command, determining a charging target based on the external charging command, determining a target area based on the charging target and a preset division rule, and determining several target DC energy storage devices based on the SOC status and health status of each DC energy storage device within the target area, includes: In response to an external charging command, a charging target is determined based on the external charging command, and a DC energy storage device connected to the charging target is identified as a connection device. Obtain the coordinates of the connecting device, and determine the target area based on the coordinates and a preset division rule; Several target DC energy storage devices are identified based on the SOC status and health status of each DC energy storage device within the target area.

[0008] When responding to external charging commands, this invention explicitly identifies devices directly connected to the charging target as connecting devices, and determines the target area based on the spatial information of the connecting devices and preset partitioning rules, thereby achieving localized constraints on collaborative charging resources in the spatial dimension. By limiting the scheduling candidate set through prior geometric or topological constraints, it not only reduces global communication and computational overhead, but also leverages geographical proximity to reduce actual communication latency and execution delay, improving the fulfillment rate of short-term response events. Simultaneously, by selecting target devices based on the SOC and health status of devices within the region, it ensures that the selected participating units meet scheduling requirements in terms of energy availability and reliability, thereby enhancing the stability of collaborative charging.

[0009] Furthermore, obtaining the coordinates of the connecting device and determining the target area based on the coordinates and a preset division rule includes: Obtain the coordinates of the connecting device, use the coordinates of the connecting device as the center and a preset distance threshold as the radius to determine a geometric circle region, and define the geometric circle as the target region.

[0010] This invention constructs a geometric circle region as the target area, using the coordinates of the connecting device as the center and a preset distance threshold as the radius. This geometric circle method has low computational complexity and allows for parameterized adjustment of the coverage radius to adapt to different energy storage densities. Furthermore, by using a clear radius threshold, geographical proximity and communication link quality can be indirectly coupled for candidate device pre-screening, thereby reducing the risk of remote slow-response devices being mistakenly included in the scheduling set and improving the success rate of short-time-window support tasks.

[0011] Furthermore, the determination of several target DC energy storage devices based on the SOC status and health status of each DC energy storage device within the target area includes: All DC energy storage devices within the target area are marked as candidate DC energy storage devices, and the SOC status value and health status value of the candidate DC energy storage devices are obtained. Candidate DC energy storage devices with SOC values ​​greater than a preset first threshold and health status values ​​greater than a preset second threshold are selected as target DC energy storage devices.

[0012] This invention identifies target DC energy storage devices within a target area using screening rules based on State of Charge (SOC) and health status thresholds. This ensures the compatibility of energy storage devices participating in power supply from two dimensions: energy availability and equipment lifespan. It avoids devices with low charge or severe degradation from participating in high-intensity discharge, reducing the risk of failures and accelerated degradation caused by over-discharge or health deterioration. Simultaneously, it ensures a reasonable overall SOC distribution, and the threshold-based judgment logic facilitates rapid adjustment of thresholds under different operating strategies, thereby achieving online control that balances performance, safety, and economy.

[0013] Furthermore, the step of obtaining the standard network delay of each target DC energy storage device, calculating the output ratio of each target DC energy storage device based on the standard network delay, and controlling each target DC energy storage device to collaboratively charge the charging target based on the output ratio includes: Obtain the standard network delay of each target DC energy storage device, and calculate the delay ratio between the target DC energy storage devices based on the standard network delay; The output ratio of each target DC energy storage device is calculated based on the delay ratio and a preset linear algorithm. Based on the output ratio control, each target DC energy storage device coordinates the charging target for charging.

[0014] This invention calculates the standard network delay of the target device and derives the inter-device delay ratio. Then, it obtains the output ratio through a preset linear algorithm, thus realizing the mapping relationship between delay and power allocation. This linear weighting mechanism assigns a higher output ratio to devices with faster response and more reliable communication, promoting control convergence and reducing real-time compensation overhead.

[0015] Furthermore, the step of acquiring historical delay data between each DC energy storage device and the central controller, and calculating the standard network delay of each DC energy storage device based on the historical delay data, includes: Historical delay data between each DC energy storage device and the central controller are obtained based on a preset time interval. Based on the historical delay data, the delay statistical characteristics of each DC energy storage device are calculated, and based on the delay statistical characteristics, the standard network delay of each DC energy storage device is calculated.

[0016] This invention collects historical latency data based on a preset time interval and calculates latency statistical characteristics to generate standard network latency. By introducing online estimation of statistical characteristics, it can simultaneously take into account historical behavior and recent fluctuations, thereby enhancing the ability to identify abnormal latency events and trend degradation.

[0017] Furthermore, the step of acquiring historical delay data between each DC energy storage device and the central controller based on a preset time interval includes: Obtain raw data on the historical response delay between each DC energy storage device and the central controller; The raw data is normalized and cleaned to obtain historical delay data for each DC energy storage device.

[0018] This invention normalizes and cleans the raw data of historical response delays, thereby improving the accuracy and reliability of statistical analysis and delay estimation. It eliminates sampling noise, outliers and dimensional differences, ensures that delay statistical characteristics are not distorted by isolated anomalies or sensor failures, and makes delay indicators between different devices comparable and aggregateable.

[0019] Secondly, the present invention provides a collaborative charging device suitable for a distributed DC energy storage system, wherein the distributed DC energy storage system includes a central controller and several DC energy storage devices, including: a standard delay calculation module, a target device determination module and a charging control module; The standard delay calculation module is used to obtain historical delay data between each DC energy storage device and the central controller, and to calculate the standard network delay of each DC energy storage device based on the historical delay data. The target device determination module is used to respond to external charging commands, determine charging targets based on the external charging commands, determine target areas based on the charging targets and preset division rules, and determine several target DC energy storage devices based on the SOC status and health status of each DC energy storage device in the target area. The charging control module is used to obtain the standard network delay of each target DC energy storage device, calculate the output ratio of each target DC energy storage device based on the standard network delay, and control each target DC energy storage device to perform coordinated charging of the charging target based on the output ratio.

[0020] Thirdly, the present invention provides a terminal device including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor executes the computer program to implement a cooperative charging method as described above.

[0021] Fourthly, the present invention provides a computer-readable storage medium comprising a stored computer program, wherein, when the computer program is executed, it controls the device on which the computer-readable storage medium is located to perform a cooperative charging method as described above. Attached Figure Description

[0022] Figure 1 This is a schematic flowchart of a collaborative charging method provided in an embodiment of the present invention; Figure 2 This is a schematic diagram of a collaborative charging device provided in an embodiment of the present invention. Detailed Implementation

[0023] The specific embodiments of the present invention will be described in further detail below with reference to the accompanying drawings and examples. The following examples are for illustrative purposes only and are not intended to limit the scope of the invention.

[0024] The terms "first" and "second," etc., in the specification, claims, and drawings of this application are used to distinguish different objects, not to describe a specific order. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to such processes, methods, products, or apparatus.

[0025] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0026] Example 1 See Figure 1 , Figure 1 This is a schematic flowchart illustrating a collaborative charging method provided by an embodiment of the present invention. The embodiment of the present invention provides a collaborative charging method applicable to a distributed DC energy storage system, wherein the distributed DC energy storage system includes a central controller and several DC energy storage devices, and includes steps 101 to 103, as detailed below: Step 101: Obtain historical delay data between each DC energy storage device and the central controller, and calculate the standard network delay of each DC energy storage device based on the historical delay data; In this embodiment, a distributed DC energy storage system consisting of several charging piles as distributed DC energy storage devices is used as an example for illustration. The system includes one or more central controllers and several charging pile units. Each charging pile unit includes a DC energy storage unit, a charge-discharge converter, a local control module, a communication module, and a monitoring subsystem for recording SOC (State of Charge) and health status (e.g., SOH, battery temperature, abnormal cell voltage, etc.). Each charging pile is assigned a unique identifier and coordinate information during deployment and can periodically report status information and communication interaction timestamps to the central controller.

[0027] In this embodiment, the central controller is responsible for collecting and storing the original historical response delay data between each charging pile and the central controller according to a preset time interval.

[0028] In this embodiment, acquiring historical latency data between each DC energy storage device and the central controller, and calculating the standard network latency of each DC energy storage device based on the historical latency data, includes: Historical delay data between each DC energy storage device and the central controller are obtained based on a preset time interval. Based on the historical delay data, the delay statistical characteristics of each DC energy storage device are calculated, and based on the delay statistical characteristics, the standard network delay of each DC energy storage device is calculated.

[0029] In this embodiment, acquiring historical delay data between each DC energy storage device and the central controller based on a preset time interval includes: Obtain raw data on the historical response delay between each DC energy storage device and the central controller; The raw data is normalized and cleaned to obtain historical delay data for each DC energy storage device.

[0030] In this embodiment, firstly, based on a preset time interval, such as the most recent N days, raw data on historical response delays between each device and the central controller are collected in batches. This raw data includes timestamps and delay values. Then, the raw data undergoes data cleaning and normalization: during the data cleaning stage, statistical or machine learning methods are preferably used to identify and remove outliers. For example, the interquartile range (IQR) method can be used to determine extreme outliers, or anomaly detection algorithms such as Isolation Forest and DBSCAN can be used for multidimensional anomaly identification. For missing data points, incomplete records are deleted or imputation strategies are used to complete them, such as mean imputation, linear or spline interpolation, to avoid statistical bias. After cleaning, the data is normalized to eliminate differences in units and scales between different devices. This normalization can use min-max normalization or Z-score normalization to ensure that subsequent delay statistical characteristics are comparable under the same units.

[0031] In this embodiment, the historical delay data of each device obtained after preprocessing is a high-quality input dataset for calculating standard network delay. This dataset improves the robustness and accuracy of delay estimation, thereby ensuring the reliability and repeatability of delay-based power allocation and collaborative charging decisions.

[0032] In one alternative embodiment, for each DC energy storage device, the average of the historical delay data between the DC energy storage device and the central controller is calculated to obtain the standard historical network delay of the distributed DC energy storage device.

[0033] In this embodiment, normalization and data cleaning are performed after acquiring the raw data of historical response delays, which can improve the accuracy and reliability of statistical analysis and delay estimation, eliminate sampling noise, outliers and dimensional differences, ensure that delay statistical characteristics are not distorted by isolated anomalies or sensor failures, and make delay indicators between different devices comparable and aggregateable.

[0034] Step 102: Respond to an external charging command, determine a charging target based on the external charging command, determine a target area based on the charging target and a preset division rule, and determine several target DC energy storage devices based on the SOC status and health status of each DC energy storage device within the target area. In this embodiment, the steps of responding to an external charging command, determining a charging target based on the external charging command, determining a target area based on the charging target and a preset division rule, and determining several target DC energy storage devices based on the SOC status and health status of each DC energy storage device within the target area include: In response to an external charging command, a charging target is determined based on the external charging command, and a DC energy storage device connected to the charging target is identified as a connection device. Obtain the coordinates of the connecting device, and determine the target area based on the coordinates and a preset division rule; Several target DC energy storage devices are identified based on the SOC status and health status of each DC energy storage device within the target area.

[0035] In this embodiment, upon receiving an external charging command, a specific charging target (e.g., a specific charging pile or load unit) is determined. Then, DC energy storage devices directly connected to the charging target electrically or topologically are identified as connected devices. The coordinates of the connected devices are acquired in real time, and a target area is constructed based on these coordinates according to preset partitioning rules. This target area serves as a candidate space for subsequent scheduling. For all devices within the determined target area, their latest SOC and health status values ​​are read. Based on preset SOC and health thresholds, candidate devices are screened, and devices that meet the energy availability and reliability requirements are confirmed as target DC energy storage devices.

[0036] In one optional embodiment, when an electric vehicle is connected to a charging station, the charging station directly connected to the electric vehicle is identified as the connection device.

[0037] In this embodiment, the preset partitioning rules include coordinate-based distance thresholds, grid partitioning, or topological neighborhood rules.

[0038] In this embodiment, obtaining the coordinates of the connecting device and determining the target area based on the coordinates and a preset division rule includes: Obtain the coordinates of the connecting device, use the coordinates of the connecting device as the center and a preset distance threshold as the radius to determine a geometric circle region, and define the geometric circle as the target region.

[0039] This invention constructs a geometric circle region as the target area, using the coordinates of the connecting device as the center and a preset distance threshold as the radius. This geometric circle method has low computational complexity and allows for parameterized adjustment of the coverage radius to adapt to different energy storage densities. Furthermore, by using a clear radius threshold, geographical proximity and communication link quality can be indirectly coupled for candidate device pre-screening, thereby reducing the risk of remote slow-response devices being mistakenly included in the scheduling set and improving the success rate of short-time-window support tasks.

[0040] In this embodiment, the coordinates of the connecting device are first obtained, that is, the coordinates of the geometric reference. Based on a preset distance threshold, the coordinates are used as the center and the threshold is used as the radius to construct a geometric circle region as the target region.

[0041] In this embodiment, by comparing the Euclidean distance between the coordinates of each DC energy storage device and the coordinates of the center of the circle, the device falling within the geometric circle is determined and the device within the circle is designated as a candidate device within the target area.

[0042] In this embodiment, after constructing the geometric circle, the system calculates the coordinate distance of each device. Any device whose distance is less than or equal to a preset distance threshold is included in the target area and used as the input set for subsequent screening and scheduling based on SOC and health status.

[0043] In this embodiment, the target area can also be determined based on a preset grid. Specifically, a regular grid division is established on the system's geographic coordinate system or deployment plane, dividing the coverage area into several uniform rectangular or square grid cells according to a preset row and column spacing, and recording the grid cell index to which each DC energy storage device belongs. After the coordinates of the connected device are determined, the grid cell corresponding to the coordinates is first located, and then a set of several grid cells containing the connected device cell and several surrounding layers of cells can be selected as the target area according to a preset neighborhood scale (e.g., using cell radius or Chebyshev distance as a metric).

[0044] In this embodiment, the target area can also be determined based on the topological neighborhood partitioning method. Specifically, the topological graph of all DC energy storage devices in the distributed DC energy storage system is G=(V, E), where vertex V represents each DC energy storage device and edge E represents the electrical connection or communication link between devices. After the connecting device is determined, a breadth-first search isograph traversal algorithm is used to select all nodes whose topological distance (shortest path hop count) to the connecting device does not exceed K according to the set hop count threshold K as the candidate set of the target area.

[0045] In this embodiment, determining a plurality of target DC energy storage devices based on the SOC status and health status of each DC energy storage device within the target area includes: All DC energy storage devices within the target area are marked as candidate DC energy storage devices, and the SOC status value and health status value of the candidate DC energy storage devices are obtained. Candidate DC energy storage devices with SOC values ​​greater than a preset first threshold and health status values ​​greater than a preset second threshold are selected as target DC energy storage devices.

[0046] In this embodiment, within the determined target area, all DC energy storage devices within the area are first marked as candidate DC energy storage devices, and their current SOC state value and health state value are obtained for each candidate DC energy storage device. Subsequently, the obtained SOC state value is compared with a preset first threshold, and the health state value is compared with a preset second threshold. Only candidate devices that simultaneously meet the conditions of "SOC state value greater than the preset first threshold" and "health state value greater than the preset second threshold" are confirmed as target DC energy storage devices and included in the subsequent power allocation and collaborative charging sequence.

[0047] In this embodiment, the first threshold and the second threshold are judgment thresholds pre-configured in the system and can be adjusted according to operating strategies or operating experience. By using dual threshold screening based on energy availability (SOC) and device availability (health status), the basic compatibility of the devices participating in collaborative charging in terms of energy reserves and operational reliability is ensured, thereby improving the executability of subsequent scheduling commands and the robustness of the overall collaborative charging scheme.

[0048] This invention identifies target DC energy storage devices within a target area using screening rules based on State of Charge (SOC) and health status thresholds. This ensures the compatibility of energy storage devices participating in power supply from two dimensions: energy availability and equipment lifespan. It avoids devices with low charge or severe degradation from participating in high-intensity discharge, reducing the risk of failures and accelerated degradation caused by over-discharge or health deterioration. Simultaneously, it ensures a reasonable overall SOC distribution, and the threshold-based judgment logic facilitates rapid adjustment of thresholds under different operating strategies, thereby achieving online control that balances performance, safety, and economy.

[0049] When responding to external charging commands, this invention explicitly identifies devices directly connected to the charging target as connecting devices, and determines the target area based on the spatial information of the connecting devices and preset partitioning rules, thereby achieving localized constraints on collaborative charging resources in the spatial dimension. By limiting the scheduling candidate set through prior geometric or topological constraints, it not only reduces global communication and computational overhead, but also leverages geographical proximity to reduce actual communication latency and execution delay, improving the fulfillment rate of short-term response events. Simultaneously, by selecting target devices based on the SOC and health status of devices within the region, it ensures that the selected participating units meet scheduling requirements in terms of energy availability and reliability, thereby enhancing the stability of collaborative charging.

[0050] Step 103: Obtain the standard network delay of each target DC energy storage device, calculate the output ratio of each target DC energy storage device based on the standard network delay, and control each target DC energy storage device to perform coordinated charging of the charging target based on the output ratio.

[0051] In this embodiment, the steps of obtaining the standard network delay of each target DC energy storage device, calculating the output ratio of each target DC energy storage device based on the standard network delay, and controlling each target DC energy storage device to collaboratively charge the charging target based on the output ratio include: Obtain the standard network delay of each target DC energy storage device, and calculate the delay ratio between the target DC energy storage devices based on the standard network delay; The output ratio of each target DC energy storage device is calculated based on the delay ratio and a preset linear algorithm. Based on the output ratio control, each target DC energy storage device coordinates the charging target for charging.

[0052] In this embodiment, after determining the target DC energy storage device set, the standard network delay value of each target device relative to the central controller is first obtained. This standard network delay reflects the typical response time of the device in the communication link. Subsequently, the delay ratio between the devices is calculated based on the standard network delay of each target DC energy storage device. This delay ratio is used to characterize the relative speed of communication response of different energy storage devices.

[0053] For example, given target DC energy storage device A, target DC energy storage device B, and target DC energy storage device C, with standard network delays of 20ms for target DC energy storage device A, 30ms for target DC energy storage device B, and 50ms for target DC energy storage device C, the delay ratio is: target DC energy storage device A : target DC energy storage device B : target DC energy storage device C = 2 : 3 : 5.

[0054] In this embodiment, the output ratio of each target energy storage device is calculated based on the delay ratio and in combination with a preset linear algorithm, so that devices with faster response speed and lower communication latency bear a higher output ratio, while devices with higher latency bear a lower output ratio. The linear algorithm includes weighting by the reciprocal of the delay.

[0055] For example, if the delay ratio of target DC energy storage device A, target DC energy storage device B, and target DC energy storage device C is A:B:C = 2:3:5, then the corresponding output ratios of target DC energy storage device A, target DC energy storage device B, and target DC energy storage device C can be: , and This ensures that the distributed DC energy storage device with the lowest latency has the highest output ratio.

[0056] Finally, the output ratio issues a power allocation command to control each target energy storage device to perform a coordinated charging operation on the charging target according to the output ratio. This can effectively reduce the power allocation imbalance caused by communication delay differences, improve the synchronization and convergence efficiency of the coordinated control, and thus enhance the dynamic coordination performance of the distributed DC energy storage system during the charging process.

[0057] In this embodiment, the standard network delay of the target device is calculated and the inter-device delay ratio is derived. Then, the output ratio is obtained through a preset linear algorithm, thus realizing the mapping relationship between delay and power allocation. This linear weighting mechanism assigns a higher output ratio to devices with faster response and more reliable communication, promoting control convergence and reducing real-time compensation overhead.

[0058] In this embodiment, historical delay data between each DC energy storage device and the central controller is acquired and the standard network delay is calculated accordingly. This is combined with target identification of external charging commands, determination of target areas based on preset partitioning rules, and screening of target devices based on the SOC and health status of devices within the area. Finally, the output ratio of each target device is calculated using its standard network delay, and collaborative control is issued. The output ratio is calculated through delay sensing and used for processing and allocation, allowing devices with faster response and more reliable communication to be prioritized in short-time-window tasks, reducing compensation and rescheduling actions caused by command delays. Furthermore, incorporating the standard network delay into allocation constraints helps suppress oscillations during scheduling iterations and shortens convergence time, thereby improving the steady-state accuracy and robustness of the system's dynamic response. Simultaneously, by using candidate screening based on target areas and combining SOC and health thresholds, invalid communication and computational overhead can be effectively reduced, ensuring the matching of energy availability and reliability among participating energy storage devices, thereby reducing unnecessary charge-discharge cycles and maintenance costs, and ultimately improving the stability and reliability of collaborative charging.

[0059] In this embodiment, by analyzing the historical response delay between each distributed DC energy storage device and the central controller, the standard historical network delay of each distributed DC energy storage device can be determined. Based on these standard historical network delays, the output ratio of each distributed DC energy storage device can be further determined. Thus, by identifying the standard historical network delay, the response speed of each distributed DC energy storage device can be distinguished, and the maximum output ratio can be allocated to the distributed DC energy storage device with the shortest response delay. When the charging station needs charging, the reasonable allocation based on the output ratio of the distributed DC energy storage devices can provide most of the required power in a timely manner, reducing the impact of time lag. Even if time lag occurs, because the distributed DC energy storage devices with slower response speeds bear a smaller share of power, even if these devices need to draw power from the grid, their demand is within the grid's capacity, thereby ensuring grid stability.

[0060] Please refer to Figure 2 , Figure 2 This is a schematic diagram of a collaborative charging device provided in an embodiment of the present invention. The present invention provides a collaborative charging device suitable for a distributed DC energy storage system, the distributed DC energy storage system including a central controller and several DC energy storage devices, including: a standard delay calculation module 201, a target device determination module 202, and a charging control module 203; The standard delay calculation module 201 is used to acquire historical delay data between each DC energy storage device and the central controller, and to calculate the standard network delay of each DC energy storage device based on the historical delay data. The target device determination module 202 is used to respond to an external charging command, determine a charging target based on the external charging command, determine a target area based on the charging target and a preset division rule, and determine a number of target DC energy storage devices based on the SOC status and health status of each DC energy storage device in the target area. The charging control module 203 is used to obtain the standard network delay of each target DC energy storage device, calculate the output ratio of each target DC energy storage device based on the standard network delay, and control each target DC energy storage device to perform coordinated charging of the charging target based on the output ratio.

[0061] In this embodiment, the target device determination module 202 is used to respond to an external charging command, determine a charging target based on the external charging command, determine a target area based on the charging target and a preset division rule, and determine a plurality of target DC energy storage devices based on the SOC status and health status of each DC energy storage device within the target area, including: In response to an external charging command, a charging target is determined based on the external charging command, and a DC energy storage device connected to the charging target is identified as a connection device. Obtain the coordinates of the connecting device, and determine the target area based on the coordinates and a preset division rule; Several target DC energy storage devices are identified based on the SOC status and health status of each DC energy storage device within the target area.

[0062] In this embodiment, the target device determination module 202 is used to obtain the coordinate points of the connecting device and determine the target area based on the coordinate points and a preset division rule, including: Obtain the coordinates of the connecting device, use the coordinates of the connecting device as the center and a preset distance threshold as the radius to determine a geometric circle region, and define the geometric circle as the target region.

[0063] In this embodiment, the target device determination module 202 is used to determine a plurality of target DC energy storage devices based on the SOC status and health status of each DC energy storage device in the target area, including: All DC energy storage devices within the target area are marked as candidate DC energy storage devices, and the SOC status value and health status value of the candidate DC energy storage devices are obtained. Candidate DC energy storage devices with SOC values ​​greater than a preset first threshold and health status values ​​greater than a preset second threshold are selected as target DC energy storage devices.

[0064] In this embodiment, the charging control module 203 is used to acquire the standard network delay of each target DC energy storage device, calculate the output ratio of each target DC energy storage device based on the standard network delay, and control each target DC energy storage device to perform coordinated charging of the charging target based on the output ratio, including: Obtain the standard network delay of each target DC energy storage device, and calculate the delay ratio between the target DC energy storage devices based on the standard network delay; The output ratio of each target DC energy storage device is calculated based on the delay ratio and a preset linear algorithm. Based on the output ratio control, each target DC energy storage device coordinates the charging target for charging.

[0065] In this embodiment, the standard delay calculation module 201 is used to acquire historical delay data between each DC energy storage device and the central controller, and to calculate the standard network delay of each DC energy storage device based on the historical delay data, including: Historical delay data between each DC energy storage device and the central controller are obtained based on a preset time interval. Based on the historical delay data, the delay statistical characteristics of each DC energy storage device are calculated, and based on the delay statistical characteristics, the standard network delay of each DC energy storage device is calculated.

[0066] In this embodiment, the standard delay calculation module 201 is used to obtain historical delay data between each DC energy storage device and the central controller based on a preset time interval, including: Obtain raw data on the historical response delay between each DC energy storage device and the central controller; The raw data is normalized and cleaned to obtain historical delay data for each DC energy storage device.

[0067] In this embodiment of the invention, a terminal device is also provided, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements the above-described collaborative charging method.

[0068] In this embodiment of the invention, a computer-readable storage medium is also provided, which includes a stored computer program, wherein the computer program controls the device where the computer-readable storage medium is located to execute the above-described cooperative charging method when it is running.

[0069] For example, a computer program can be divided into one or more modules, one or more of which are stored in memory and executed by a processor to perform the present invention. The one or more modules can be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of the computer program in a terminal device.

[0070] The terminal device may be a desktop computer, laptop, handheld computer, or cloud server, etc. The terminal device may include, but is not limited to, a processor, memory, and display. Those skilled in the art will understand that the above components are merely examples of terminal devices and do not constitute a limitation on the terminal device. It may include more or fewer components, or combinations of certain components, or different components. For example, the terminal device may also include input / output devices, network access devices, buses, etc.

[0071] The processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor. The processor is the control center of the terminal device, connecting all parts of the terminal device through various interfaces and lines.

[0072] Memory can be used to store computer programs and / or modules. The processor implements various functions of the terminal device by running or executing the computer programs and / or modules stored in the memory, and by accessing data stored in the memory. Memory can mainly include a program storage area and a data storage area. The program storage area can store the operating system, application programs required for at least one function (such as sound playback, text conversion, etc.), etc.; the data storage area can store data created based on the use of the mobile phone (such as audio data, text message data, etc.). In addition, memory can include high-speed random access memory, and can also include non-volatile memory, such as hard disks, RAM, plug-in hard disks, smart media cards (SMC), secure digital cards (SD cards), flash cards, at least one disk storage device, flash memory device, or other volatile solid-state storage devices.

[0073] Wherein, if the module for collaborative charging is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments of the present invention can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc. Those skilled in the art can understand and implement this without any inventive effort.

[0074] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the scope of protection of the present invention. In particular, it should be noted that any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention for those skilled in the art.

Claims

1. A collaborative charging method applicable to a distributed DC energy storage system, wherein the distributed DC energy storage system includes a central controller and several DC energy storage devices, characterized in that, include: Acquire historical delay data between each DC energy storage device and the central controller, and calculate the standard network delay of each DC energy storage device based on the historical delay data; In response to an external charging command, a charging target is determined based on the external charging command, a target area is determined based on the charging target and a preset division rule, and several target DC energy storage devices are determined based on the SOC status and health status of each DC energy storage device in the target area. Obtain the standard network delay of each target DC energy storage device, calculate the output ratio of each target DC energy storage device based on the standard network delay, and control each target DC energy storage device to perform coordinated charging of the charging target based on the output ratio.

2. The collaborative charging method as described in claim 1, characterized in that, The process involves responding to an external charging command, determining a charging target based on the command, determining a target area based on the target and a preset division rule, and determining several target DC energy storage devices based on the SOC and health status of each DC energy storage device within the target area, including: In response to an external charging command, a charging target is determined based on the external charging command, and a DC energy storage device connected to the charging target is identified as a connection device. Obtain the coordinates of the connecting device, and determine the target area based on the coordinates and a preset division rule; Several target DC energy storage devices are identified based on the SOC status and health status of each DC energy storage device within the target area.

3. The collaborative charging method as described in claim 2, characterized in that, The step of obtaining the coordinates of the connecting device and determining the target area based on the coordinates and a preset division rule includes: Obtain the coordinates of the connecting device, use the coordinates of the connecting device as the center and a preset distance threshold as the radius to determine a geometric circle region, and define the geometric circle as the target region.

4. The collaborative charging method as described in claim 3, characterized in that, The determination of several target DC energy storage devices based on the SOC status and health status of each DC energy storage device within the target area includes: All DC energy storage devices within the target area are marked as candidate DC energy storage devices, and the SOC status value and health status value of the candidate DC energy storage devices are obtained. Candidate DC energy storage devices with SOC values ​​greater than a preset first threshold and health status values ​​greater than a preset second threshold are selected as target DC energy storage devices.

5. The collaborative charging method as described in claim 4, characterized in that, The process of acquiring the standard network delay of each target DC energy storage device, calculating the output ratio of each target DC energy storage device based on the standard network delay, and controlling each target DC energy storage device to collaboratively charge the charging target based on the output ratio includes: Obtain the standard network delay of each target DC energy storage device, and calculate the delay ratio between the target DC energy storage devices based on the standard network delay; The output ratio of each target DC energy storage device is calculated based on the delay ratio and a preset linear algorithm. Based on the output ratio control, each target DC energy storage device coordinates the charging target for charging.

6. The collaborative charging method as described in claim 5, characterized in that, The step of acquiring historical latency data between each DC energy storage device and the central controller, and calculating the standard network latency of each DC energy storage device based on the historical latency data, includes: Historical delay data between each DC energy storage device and the central controller are obtained based on a preset time interval. Based on the historical delay data, the delay statistical characteristics of each DC energy storage device are calculated, and based on the delay statistical characteristics, the standard network delay of each DC energy storage device is calculated.

7. A cooperative charging method as described in any one of claims 1 to 6, characterized in that, The process of acquiring historical delay data between each DC energy storage device and the central controller based on a preset time interval includes: Obtain raw data on the historical response delay between each DC energy storage device and the central controller; The raw data is normalized and cleaned to obtain historical delay data for each DC energy storage device.

8. A collaborative charging device suitable for a distributed DC energy storage system, the distributed DC energy storage system comprising a central controller and a plurality of DC energy storage devices, characterized in that, include: Standard delay calculation module, target device determination module, and charging control module; The standard delay calculation module is used to obtain historical delay data between each DC energy storage device and the central controller, and to calculate the standard network delay of each DC energy storage device based on the historical delay data. The target device determination module is used to respond to external charging commands, determine charging targets based on the external charging commands, determine target areas based on the charging targets and preset division rules, and determine several target DC energy storage devices based on the SOC status and health status of each DC energy storage device in the target area. The charging control module is used to obtain the standard network delay of each target DC energy storage device, calculate the output ratio of each target DC energy storage device based on the standard network delay, and control each target DC energy storage device to perform coordinated charging of the charging target based on the output ratio.

9. A terminal device, characterized in that, It includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor executes the computer program to implement a cooperative charging method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored computer program, wherein, when the computer program is executed, it controls the device on which the computer-readable storage medium is located to perform a cooperative charging method as described in any one of claims 1 to 7.

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