Power supply and electric energy storage control method and system of distributed energy storage system

Abstract

The invention relates to a power supply and electric energy storage control method and system of a distributed energy storage system, and relates to the technical field of distributed energy storage. The method mainly comprises the following steps: acquiring a power estimated value of a current energy storage node; the power estimated value is a power optimal value obtained by iterating temporary prices and temporary powers of the current energy storage node and the corresponding neighbor energy storage node for multiple times; determining a safe power set value of the current energy storage node according to the attribute information of the current energy storage node and the power estimated value; if the safe power set value is a positive number, calculating the residual power value of the current energy storage node according to the safe power set value of the current energy storage node and the number of the corresponding charging piles; and distributing charging power for each charging pile according to the residual power value of the current energy storage node and the attribute information of the charging pile, so that the charging pile charges an automobile connected with the charging pile based on the charging power.

Description

Technical Field

[0001] This invention relates to the field of distributed energy storage technology, and in particular to a power supply and energy storage control method and system for a distributed energy storage system. Background Technology

[0002] Centralized charging management involves aggregating real-time status data from various electric vehicles, charging stations, energy storage systems, and distributed power sources into a central controller. Based on this global data, the central controller uses specific optimization algorithms to calculate a globally optimal or near-optimal charging schedule. The central controller then directly issues the calculated charging and discharging commands to each charging station or vehicle for execution.

[0003] However, charging management through central control is highly dependent on the reliability of the central controller and the smooth operation of the communication network. If the central node fails or communication is interrupted, the control of the entire system will face the risk of paralysis. Summary of the Invention

[0004] The present invention aims to provide a power supply and energy storage control method and system for a distributed energy storage system to overcome the shortcomings of the prior art. The technical problem to be solved by the present invention is achieved through the following technical solution.

[0005] This invention provides a power supply and energy storage control method for a distributed energy storage system. The method is applied to the power supply and energy storage control system of the distributed energy storage system, which includes a current energy storage node and its corresponding neighboring energy storage nodes. The method is applied to the current energy storage node and includes: Obtain the power estimate of the current energy storage node; the power estimate is the optimal power value obtained by iterating through the temporary prices and temporary power of the current energy storage node and its corresponding neighboring energy storage nodes multiple times. The safe power setting value of the current energy storage node is determined by the attribute information of the current energy storage node and the power estimate. If the safety power setting value is positive, then the remaining power value of the current energy storage node is calculated based on the safety power setting value of the current energy storage node and the number of charging piles corresponding to it. Based on the remaining power value of the current energy storage node and the attribute information of the charging pile, charging power is allocated to each charging pile, so that the charging pile charges the car connected to it based on the charging power.

[0006] In an optional embodiment, obtaining the power estimate of the current energy storage node includes: Calculate the temporary power of the current energy storage node in the next iteration based on the temporary price and temporary power of the current energy storage node corresponding to the current iteration; Calculate the temporary price of the current energy storage node in the next iteration based on the temporary prices of the current energy storage node and its corresponding neighboring energy storage nodes in the next iteration; The iterative power of the current energy storage node in the next iteration is calculated using the temporary price of the current energy storage node in the next iteration and the temporary power of the current energy storage node corresponding to the current iteration. If the iteration power and temporary price of the two most recent iterations meet the preset conditions, the iteration power of the current energy storage node calculated in the last iteration will be used as the power estimate of the current energy storage node.

[0007] In an optional embodiment, calculating the temporary price of the current energy storage node in the next iteration based on the temporary prices of the current energy storage node and its corresponding neighboring energy storage nodes in the next iteration includes: Get the temporary price of the current energy storage node in the next iteration and the temporary prices of all neighboring energy storage nodes in the next iteration; The temporary price of the current energy storage node in the next iteration is obtained by taking a weighted average of the temporary prices of all neighboring energy storage nodes.

[0008] In an optional embodiment, obtaining the temporary price of the current energy storage node for the next iteration includes: The temporary price of the current energy storage node in the next iteration is calculated based on the temporary power of the current energy storage node in the current iteration and the temporary price of the current energy storage node in the current iteration.

[0009] In an optional embodiment, determining the safe power setting value of the current energy storage node using the attribute information of the current energy storage node and the estimated power value includes: The maximum allowable discharge power and the maximum allowable charging power are determined based on the attribute information of the current energy storage node. The estimated power value is matched with the maximum allowable discharge power and the maximum allowable charging power to determine the safe power setting value of the current energy storage node.

[0010] In an optional embodiment, determining the maximum allowable discharge power and the maximum allowable charging power using the attribute information of the current energy storage node includes: The maximum allowable discharge power and maximum allowable charging power are determined by using the current SOC, temperature, rated power, rated capacity, time interval, minimum SOC, and maximum SOC from the attribute information of the current energy storage node.

[0011] In an optional embodiment, calculating the remaining power value of the current energy storage node based on its safe power setting value and the corresponding number of charging piles includes: The basic total power is obtained by multiplying the number of charging piles by the minimum guaranteed power. The remaining power value of the current energy storage node is obtained by calculating the difference between the safe power setting value of the current energy storage node and the basic total power.

[0012] In an optional embodiment, the step of allocating charging power to each charging pile based on the remaining power value of the current energy storage node and the attribute information of the charging pile includes: Obtain the vehicle's current maximum power demand, the vehicle's expected full charge time, and the charging unit price from the attribute information of the charging pile; Priority weights are calculated based on the expected time required to fully charge the vehicle and the charging unit price. Charging power is allocated to each charging station based on the product of the vehicle's current maximum power demand and the priority weight.

[0013] In an optional embodiment, calculating the priority weight based on the expected time required to fully charge the vehicle and the charging unit price includes: Based on the expected time required to fully charge the vehicle and the charging unit price, a cost score and a time urgency score are determined respectively. The priority weight is obtained by weighting the cost score and the time urgency score.

[0014] This invention provides a power supply and energy storage control system for a distributed energy storage system. The system includes a current energy storage node and its corresponding neighboring energy storage nodes. The current energy storage node includes: The acquisition module is used to acquire the power estimate of the current energy storage node; the power estimate is the optimal power value obtained by iterating through the temporary prices and temporary power of the current energy storage node and its corresponding neighboring energy storage nodes multiple times. The determination module is used to determine the safe power setting value of the current energy storage node based on the attribute information of the current energy storage node and the power estimate. The calculation module is used to calculate the remaining power value of the current energy storage node based on the safe power setting value of the current energy storage node and the number of charging piles corresponding to it if the safe power setting value is positive. The allocation module is used to allocate charging power to each charging pile according to the remaining power value of the current energy storage node and the attribute information of the charging pile, so that the charging pile charges the car connected to it based on the charging power.

[0015] The embodiments of the present invention have the following advantages: This invention provides a power supply and energy storage control method and system for a distributed energy storage system. The system includes a current energy storage node and its corresponding neighboring energy storage nodes. First, the power estimate of the current energy storage node is obtained. This power estimate is the optimal power value obtained through multiple iterations of the temporary price and temporary power of the current energy storage node and its corresponding neighboring energy storage nodes. Then, a safe power setting value for the current energy storage node is determined based on its attribute information and the power estimate. If the safe power setting value is positive, the remaining power value of the current energy storage node is calculated based on its safe power setting value and the number of corresponding charging piles. Finally, charging power is allocated to each charging pile based on its remaining power value and the attribute information of the charging piles, enabling the charging piles to charge the connected vehicles based on the charging power. Currently, existing technologies heavily rely on the reliability of the central controller and the smooth operation of the communication network. In this application, the energy storage nodes are distributed, and each energy storage node can automatically allocate charging power to each charging pile based on its remaining power value calculated from the safe power setting value, thus improving the reliability and effectiveness of power supply. Attached Figure Description

[0016] Figure 1 This is a flowchart of a power supply and energy storage control method for a distributed energy storage system provided in an embodiment of the present invention; Figure 2 This is a schematic diagram of the power supply and energy storage control system of a distributed energy storage system provided in an embodiment of the present invention. Detailed Implementation

[0017] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0018] Please see Figure 1 This invention provides a power supply and energy storage control method for a distributed energy storage system. The method is applied to the power supply and energy storage control system of the distributed energy storage system. The system includes the current energy storage node and its corresponding neighboring energy storage nodes. Each energy storage node acts as an autonomous intelligent agent, exchanging information only with its physical or communication topology neighboring energy storage nodes. This allows the charging and discharging behavior of all energy storage nodes to converge to a common optimized global objective without the need for coordination by any central node. Specifically, this embodiment uses the current energy storage node as the executing entity, and the method specifically includes steps S101-S104: S101, obtain the power estimate of the current energy storage node.

[0019] The power estimate is the optimal power value obtained by iterating through multiple iterations of the temporary price and temporary power of the current energy storage node and its corresponding neighboring energy storage nodes.

[0020] In one embodiment provided in this application, obtaining the estimated power of the current energy storage node includes: S1011, calculate the temporary power of the current energy storage node in the next iteration based on the temporary price and temporary power of the current energy storage node corresponding to the current iteration.

[0021] In this embodiment, the k-th iteration (k=0,1,2,...) is taken as the current iteration, and the next iteration is taken as the (k+1)-th iteration. In the initial iteration, each energy storage node randomly sets a corresponding temporary power. Temporary prices The subscript i represents the energy storage node. Specifically, in this embodiment, the temporary power of the current energy storage node in each iteration is calculated using the following formula: in, This is the temporary power of the current energy storage node for the next iteration. This represents the temporary power of the current energy storage node corresponding to the current iteration. It is a constant coefficient (a small positive number) used to control the update magnitude. This is the temporary price for the current energy storage node corresponding to the current iteration.

[0022] This represents the marginal cost of increasing power per unit, and the goal of each energy storage node i is to minimize its own operating cost. It is a constant greater than 0, used to represent the cost curvature coefficient, which reflects the marginal cost increase rate caused by power changes (such as battery loss). This represents the linear cost coefficient, which is related to real-time electricity prices, charging and discharging efficiency-based cost conversion, etc.

[0023] S1012, Calculate the temporary price of the current energy storage node in the next iteration based on the temporary prices of the current energy storage node and its corresponding neighboring energy storage nodes in the next iteration.

[0024] Specifically, the step of calculating the temporary price of the current energy storage node in the next iteration based on the temporary prices of the current energy storage node and its corresponding neighboring energy storage nodes includes: S10121, obtain the temporary price of the current energy storage node in the next iteration and the temporary prices of all neighboring energy storage nodes in the next iteration.

[0025] The step of obtaining the temporary price of the current energy storage node in the next iteration includes: calculating the temporary price of the current energy storage node in the next iteration based on the temporary power of the current energy storage node in the current iteration and the next iteration, as well as the temporary price of the current energy storage node in the current iteration.

[0026] Specifically, the temporary price of the current energy storage node in the next iteration can be calculated using the following formula: in, The temporary price for the current energy storage node in the next iteration. A parameter greater than 0, used to represent the iteration step size. This is the temporary power of the current energy storage node for the next iteration. This represents the temporary power of the current energy storage node corresponding to the current iteration. This is the temporary price for the current energy storage node corresponding to the current iteration.

[0027] It should be noted that the temporary price of all energy storage nodes in this embodiment is calculated using the above calculation formula. This embodiment only provides an explanation based on the calculation of the current energy storage node.

[0028] S10122, the temporary price of the current energy storage node in the next iteration is obtained by weighted averaging of the temporary prices of all neighboring energy storage nodes of the current energy storage node.

[0029] In this embodiment, the current energy storage node receives the temporary price of its neighboring energy storage nodes broadcast by its corresponding neighboring energy storage nodes. Then, the temporary price of the current energy storage node in the next iteration is obtained by weighted averaging the temporary prices of all neighboring energy storage nodes. : in, Let be the temporary price of the current energy storage node in the next iteration, and let be the set of neighboring energy storage nodes of the current energy storage node i. The preset consensus weight between the current energy storage node i and its neighboring energy storage node j is usually set to 1 / (number of neighbors + 1) or optimized based on the topology.

[0030] S1013, calculate the iterative power of the current energy storage node in the next iteration using the temporary price of the current energy storage node in the next iteration and the temporary power of the current energy storage node corresponding to the current iteration.

[0031] Specifically, the iteration power of the current energy storage node in the next iteration is calculated using the following formula: in, The iteration power of the current energy storage node in the next iteration. It is a small positive number used to control the update magnitude. This represents the temporary power of the current energy storage node corresponding to the current iteration. This is the temporary price for the current energy storage node in the next iteration.

[0032] S1014, when the iteration power and temporary price of the two most recent iterations meet the preset conditions, the iteration power of the current energy storage node calculated in the last iteration is used as the power estimate of the current energy storage node.

[0033] The iteration will continue until the state changes of all energy storage nodes are below a preset threshold, indicating that the algorithm has converged. The preset conditions can be expressed by the following formula: in, and Very small positive numbers (such as 10) 4 Each energy storage node needs to solve for its own power prediction. A power prediction greater than 0 indicates discharging; a power prediction less than 0 indicates charging. When the stopping condition is met, the final value of each energy storage node is... This is the estimated power value of the energy storage node.

[0034] In this embodiment, the calculation relies solely on temporary price exchanges between neighboring energy storage nodes, eliminating the need for a central controller. Any addition, removal, or local parameter changes of any energy storage node are automatically absorbed by the system through iterative calculations, ultimately converging back to a new optimal state, resulting in extremely robust overall system performance. In other words, through iterative information exchange between neighbors, each energy storage node independently calculates a power estimate that satisfies the global optimal conditions.

[0035] S102, determine the safe power setting value of the current energy storage node based on the attribute information and power estimate of the current energy storage node.

[0036] In this embodiment, the safe power setting value The calculation is based on a dynamic limiting process with multi-dimensional real-time constraints. Its core is to strictly limit the power estimate of the energy storage node within a safe operating range jointly determined by the real-time status of the battery, equipment, and grid.

[0037] In one optional embodiment provided in this application, determining the safe power setting value of the current energy storage node using the attribute information of the current energy storage node and the estimated power value includes: S1021, determine the maximum allowable discharge power and the maximum allowable charging power based on the attribute information of the current energy storage node.

[0038] Specifically, the maximum allowable discharge power and the maximum allowable charging power are determined by the attribute information of the current energy storage node, including: determining the maximum allowable discharge power and the maximum allowable charging power by using the current SOC, temperature, rated power, rated capacity, time interval, minimum SOC value, and maximum SOC value in the attribute information of the current energy storage node.

[0039] Specifically, this embodiment can calculate the maximum allowable charging power at the current moment based on the attribute information of the current energy storage node. and maximum allowable discharge power First, calculate the dischargeable energy and rechargeable energy based on the current SOC, minimum SOC, and maximum SOC: in, It is dischargeable energy. Rechargeable energy; SOC refers to the current SOC. This is the minimum SOC value. This represents the maximum SOC value. This is the rated capacity.

[0040] In this embodiment, a time interval is considered. (For example, in the next scheduling cycle, say 15 minutes), the power boundary can be initially set as: Then, the actual maximum discharge power and the actual maximum charging power are calculated based on the initially set boundaries: Actual maximum discharge power: Actual maximum charging power: in, This is the temperature derating factor (its value is between 0 and 1, obtained from the current temperature T through a table lookup or a simple function, for example, when T is within the normal range). The value is 1; if it is too high or too low... Less than 1). Rated power (maximum continuous charge and discharge power).

[0041] Finally, the maximum allowable charging power is determined using the following formula. and maximum allowable discharge power : S1022, Match the power estimate with the maximum allowable discharge power and the maximum allowable charging power to determine the safe power setting value of the current energy storage node.

[0042] In this embodiment, the safety boundary at the current moment is obtained. Next, the power estimate will be... By limiting the power output to this range, a safe power setting value can be obtained. .

[0043] if ,but ; if ,but ; otherwise, .

[0044] S103, if the safe power setting value is positive, then calculate the remaining power value of the current energy storage node based on the safe power setting value of the current energy storage node and the number of charging piles corresponding to it.

[0045] A positive safe power setting value indicates that the current energy storage node can discharge and provide power to the charging pile; if it is negative or zero, the current energy storage node cannot discharge.

[0046] In this embodiment, the remaining power value of the current energy storage node is calculated based on the safe power setting value of the current energy storage node and the corresponding number of charging piles, including: calculating the product of the number of charging piles and the minimum guaranteed power to obtain the basic total power; and calculating the difference between the safe power setting value of the current energy storage node and the basic total power to obtain the remaining power value of the current energy storage node.

[0047] The minimum guaranteed power is the minimum required power for each charging station, used to maintain the vehicle's most basic charging or communication functions (e.g., 1kW-3kW). Specifically, the remaining power of the current energy storage node can be calculated using the following formula: in, This represents the remaining power value of the current energy storage node. To ensure the minimum guaranteed power, N represents the number of charging piles included in the current energy storage node. Set the safe power setting value for the current energy storage node.

[0048] S104: Based on the remaining power value of the current energy storage node and the attribute information of the charging pile, allocate charging power to each charging pile so that the charging pile charges the connected car based on the charging power.

[0049] In this embodiment, if A value greater than or equal to 0 indicates that the current energy storage node has sufficient power budget, and charging power can be allocated to each charging pile based on the remaining power value of the current energy storage node and the attribute information of the charging pile; if A value less than 0 indicates that the budget cannot even meet the basic needs, and in this case, the basic power of each charging station can only be reduced proportionally.

[0050] First, calculate the excess demand for each charging station. , The charging station i reports its current maximum acceptable power (determined by the vehicle's BMS and the station's own capabilities). To attempt to allocate its minimum guaranteed power to each charging station i, the additional allocated charging power is then calculated using the following formula: Afterwards, the final allocated charging power for each charging station is: .

[0051] In one optional embodiment provided in this application, the step of allocating charging power to each charging pile based on the remaining power value of the current energy storage node and the attribute information of the charging pile includes: S1041, Obtain the vehicle's current maximum power demand, the vehicle's expected full charge time, and the charging unit price from the attribute information of the charging pile.

[0052] S1042, calculate the priority weight based on the expected time required for the vehicle to be fully charged and the charging unit price.

[0053] In this embodiment, the step of calculating the priority weight based on the expected time required to fully charge the vehicle and the charging unit price includes: determining a cost score and a time urgency score based on the expected time required to fully charge the vehicle and the charging unit price, respectively; and performing a weighted calculation on the cost score and the time urgency score to obtain the priority weight.

[0054] Specifically, the unit price of different charging piles is first normalized to a score between 0 and 1, with higher prices resulting in higher scores. Then, the highest charging unit price among all currently active charging orders at the charging station is obtained. The unit price of the charging pile is divided by the highest charging unit price to get the cost score. This ensures that users who pay higher unit prices receive higher scores, reflecting the principle that those who pay more get priority in charging.

[0055] The urgency of a user's charging needs is quantified; the shorter the remaining time, the higher the score. The user's target charging level is subtracted from the vehicle's current battery level, and then divided by the current battery level to obtain the expected charging time. Next, 1 is subtracted from the expected charging time of the current charging station, and divided by the maximum expected charging time within the charging area to obtain the time urgency score. Finally, the cost score and the time urgency score are weighted to obtain a priority score.

[0056] For example, a car that has just started charging and needs 5 hours to fully charge is the least urgent vehicle in the entire charging station (T_max=5), and its time score is 1-5 / 5=0. Another car can be fully charged in just 0.5 hours (30 minutes), and its time score is 1-0.5 / 5=0.9. Vehicles that are about to be fully charged will receive a very high urgency score, and the system will prioritize allocating power to them to complete charging as quickly as possible, thereby freeing up charging slots.

[0057] S1043 allocates charging power to each charging station based on the product of the vehicle's current maximum power demand and priority weight.

[0058] This embodiment provides a power supply and energy storage control method for a distributed energy storage system. First, the estimated power value of the current energy storage node is obtained. This estimated power value is the optimal power value obtained through multiple iterations of the temporary price and temporary power of the current energy storage node and its corresponding neighboring energy storage nodes. Then, the safe power setting value of the current energy storage node is determined based on the attribute information of the current energy storage node and the estimated power value. If the safe power setting value is positive, the remaining power value of the current energy storage node is calculated based on the safe power setting value and the number of corresponding charging piles. Finally, charging power is allocated to each charging pile based on the remaining power value of the current energy storage node and the attribute information of the charging piles, enabling the charging piles to charge the connected vehicles based on the charging power. Currently, existing technologies heavily rely on the reliability of the central controller and the smooth operation of the communication network. In this application, the energy storage nodes are distributed, and each energy storage node can allocate charging power to each charging pile based on the remaining power value calculated from the safe power setting value, thus improving the reliability and effectiveness of power supply.

[0059] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0060] In one embodiment, a power supply and energy storage control system for a distributed energy storage system is provided. For example... Figure 2 As shown, the system includes the current energy storage node and its corresponding neighboring energy storage nodes. The current energy storage node includes: The acquisition module 21 is used to acquire the power estimate of the current energy storage node; the power estimate is the optimal power value obtained by iterating through the temporary price and temporary power of the current energy storage node and its corresponding neighboring energy storage nodes multiple times. The determination module 22 is used to determine the safe power setting value of the current energy storage node through the attribute information of the current energy storage node and the power estimate; The calculation module 23 is used to calculate the remaining power value of the current energy storage node based on the safe power setting value of the current energy storage node and the number of charging piles corresponding to it if the safe power setting value is positive. The allocation module 24 is used to allocate charging power to each charging pile according to the remaining power value of the current energy storage node and the attribute information of the charging pile, so that the charging pile charges the car connected to it based on the charging power.

[0061] In an optional embodiment, the acquisition module 21 is specifically used for: Calculate the temporary power of the current energy storage node in the next iteration based on the temporary price and temporary power of the current energy storage node corresponding to the current iteration; Calculate the temporary price of the current energy storage node in the next iteration based on the temporary prices of the current energy storage node and its corresponding neighboring energy storage nodes in the next iteration; The iterative power of the current energy storage node in the next iteration is calculated using the temporary price of the current energy storage node in the next iteration and the temporary power of the current energy storage node corresponding to the current iteration. If the iteration power and temporary price of the two most recent iterations meet the preset conditions, the iteration power of the current energy storage node calculated in the last iteration will be used as the power estimate of the current energy storage node.

[0062] In an optional embodiment, the acquisition module 21 is specifically used for: Get the temporary price of the current energy storage node in the next iteration and the temporary prices of all neighboring energy storage nodes in the next iteration; The temporary price of the current energy storage node in the next iteration is obtained by taking a weighted average of the temporary prices of all neighboring energy storage nodes.

[0063] In an optional embodiment, the acquisition module 21 is specifically used for: The temporary price of the current energy storage node in the next iteration is calculated based on the temporary power of the current energy storage node in the current iteration and the temporary price of the current energy storage node in the current iteration.

[0064] In an optional embodiment, the determining module 22 is specifically used for: The maximum allowable discharge power and the maximum allowable charging power are determined based on the attribute information of the current energy storage node. The estimated power value is matched with the maximum allowable discharge power and the maximum allowable charging power to determine the safe power setting value of the current energy storage node.

[0065] In an optional embodiment, the determining module 22 is specifically used for: The maximum allowable discharge power and maximum allowable charging power are determined by using the current SOC, temperature, rated power, rated capacity, time interval, minimum SOC, and maximum SOC from the attribute information of the current energy storage node.

[0066] In an optional embodiment, the calculation module 23 is specifically used for: The basic total power is obtained by multiplying the number of charging piles by the minimum guaranteed power. The remaining power value of the current energy storage node is obtained by calculating the difference between the safe power setting value of the current energy storage node and the basic total power.

[0067] In an optional embodiment, the allocation module 24 is specifically used for: Obtain the vehicle's current maximum power demand, the vehicle's expected full charge time, and the charging unit price from the attribute information of the charging pile; Priority weights are calculated based on the expected time required to fully charge the vehicle and the charging unit price. Charging power is allocated to each charging station based on the product of the vehicle's current maximum power demand and the priority weight.

[0068] In an optional embodiment, the allocation module 24 is specifically used for: Based on the expected time required to fully charge the vehicle and the charging unit price, a cost score and a time urgency score are determined respectively. The priority weight is obtained by weighting the cost score and the time urgency score.

[0069] It should be noted that the above detailed descriptions are exemplary and intended to provide further explanation of this application. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains.

[0070] Specific limitations regarding the power supply and energy storage control system of the distributed energy storage system can be found in the limitations of the power supply and energy storage control methods of the distributed energy storage system mentioned above, and will not be repeated here. Each module in the above-mentioned equipment can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in the processor of the computer device in hardware form or independent of it, or stored in the memory of the computer device in software form, so that the processor can call and execute the corresponding operations of each module.

[0071] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is used as an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the system can be divided into different functional units or modules to complete all or part of the functions described above.

[0072] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A power supply and energy storage control method for a distributed energy storage system, characterized in that, The method is applied to the power supply and energy storage control system of a distributed energy storage system, the system including the current energy storage node and its corresponding neighboring energy storage nodes, the method being applied to the current energy storage node, the method comprising: Obtain the power estimate of the current energy storage node; the power estimate is the optimal power value obtained by iterating through the temporary prices and temporary power of the current energy storage node and its corresponding neighboring energy storage nodes multiple times. The safe power setting value of the current energy storage node is determined by the attribute information of the current energy storage node and the power estimate. If the safety power setting value is positive, then the remaining power value of the current energy storage node is calculated based on the safety power setting value of the current energy storage node and the number of charging piles corresponding to it. Based on the remaining power value of the current energy storage node and the attribute information of the charging pile, charging power is allocated to each charging pile, so that the charging pile charges the car connected to it based on the charging power.

2. The method according to claim 1, characterized in that, The process of obtaining the power estimate of the current energy storage node includes: Calculate the temporary power of the current energy storage node in the next iteration based on the temporary price and temporary power of the current energy storage node corresponding to the current iteration; Calculate the temporary price of the current energy storage node in the next iteration based on the temporary prices of the current energy storage node and its corresponding neighboring energy storage nodes in the next iteration; The iterative power of the current energy storage node in the next iteration is calculated using the temporary price of the current energy storage node in the next iteration and the temporary power of the current energy storage node corresponding to the current iteration. If the iteration power and temporary price of the two most recent iterations meet the preset conditions, the iteration power of the current energy storage node calculated in the last iteration will be used as the power estimate of the current energy storage node.

3. The method according to claim 2, characterized in that, The step of calculating the temporary price of the current energy storage node in the next iteration based on the temporary prices of the current energy storage node and its corresponding neighboring energy storage nodes includes: Get the temporary price of the current energy storage node in the next iteration and the temporary prices of all neighboring energy storage nodes in the next iteration; The temporary price of the current energy storage node in the next iteration is obtained by taking a weighted average of the temporary prices of all neighboring energy storage nodes.

4. The method according to claim 3, characterized in that, The step of obtaining the temporary price of the current energy storage node for the next iteration includes: The temporary price of the current energy storage node in the next iteration is calculated based on the temporary power of the current energy storage node in the current iteration and the temporary price of the current energy storage node in the current iteration.

5. The method according to claim 1, characterized in that, The step of determining the safe power setting value of the current energy storage node using the attribute information of the current energy storage node and the power estimate includes: The maximum allowable discharge power and the maximum allowable charging power are determined based on the attribute information of the current energy storage node. The estimated power value is matched with the maximum allowable discharge power and the maximum allowable charging power to determine the safe power setting value of the current energy storage node.

6. The method according to claim 5, characterized in that, The step of determining the maximum allowable discharge power and the maximum allowable charging power based on the attribute information of the current energy storage node includes: The maximum allowable discharge power and maximum allowable charging power are determined by using the current SOC, temperature, rated power, rated capacity, time interval, minimum SOC, and maximum SOC from the attribute information of the current energy storage node.

7. The method according to claim 1, characterized in that, The step of calculating the remaining power value of the current energy storage node based on its safe power setting value and the corresponding number of charging piles includes: The basic total power is obtained by multiplying the number of charging piles by the minimum guaranteed power. The remaining power value of the current energy storage node is obtained by calculating the difference between the safe power setting value of the current energy storage node and the basic total power.

8. The method according to any one of claims 1-7, characterized in that, The step of allocating charging power to each charging pile based on the remaining power value of the current energy storage node and the attribute information of the charging pile includes: Obtain the vehicle's current maximum power demand, the vehicle's expected full charge time, and the charging unit price from the attribute information of the charging pile; Calculate the priority weight based on the expected time required to fully charge the vehicle and the charging unit price; Charging power is allocated to each charging station based on the product of the vehicle's current maximum power demand and the priority weight.

9. The method according to claim 8, characterized in that, The calculation of priority weights based on the expected time required for the vehicle to fully charge and the charging unit price includes: A cost score and a time urgency score are determined based on the expected time required to fully charge the vehicle and the charging unit price, respectively. The priority weight is obtained by weighting the cost score and the time urgency score.

10. A power supply and energy storage control system for a distributed energy storage system, characterized in that, The system includes the current energy storage node and its corresponding neighboring energy storage nodes. The current energy storage node includes: The acquisition module is used to acquire the power estimate of the current energy storage node; the power estimate is the optimal power value obtained by iterating through the temporary prices and temporary power of the current energy storage node and its corresponding neighboring energy storage nodes multiple times. The determination module is used to determine the safe power setting value of the current energy storage node based on the attribute information of the current energy storage node and the power estimate. The calculation module is used to calculate the remaining power value of the current energy storage node based on the safe power setting value of the current energy storage node and the number of charging piles corresponding to it if the safe power setting value is positive. The allocation module is used to allocate charging power to each charging pile according to the remaining power value of the current energy storage node and the attribute information of the charging pile, so that the charging pile charges the car connected to it based on the charging power.

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