Energy storage system configuration method, device, equipment, medium and program product

Abstract

The invention provides an energy storage system configuration method and device, equipment, a medium and a program product. The method comprises the following steps: acquiring configuration parameters such as a capacity value of a distribution transformer, load values at a plurality of historical moments, and unit power cost, unit capacity cost, operation and maintenance coefficient, discount rate of unit time length, use time length, charging power upper limit, discharging power upper limit, charging and discharging efficiency and the like of an energy storage system; a multi-target planning model is constructed according to the configuration parameters, then the rated power, the rated capacity, the charging power at each historical moment and the discharging power at each historical moment of the energy storage system are solved, and finally the energy storage system is configured according to the rated power and the rated capacity. And controlling the energy storage system to operate according to the charging power at each historical moment and the discharging power at each historical moment to realize configuration. The configuration data is determined by using the parameters of the distribution transformer and the energy storage system, so that the matching property of the energy storage system and the distribution transformer is improved.

Description

Technical Field

[0001] The present application relates to the technical field of energy storage configuration, and in particular to an energy storage system configuration method, device, equipment, medium and program product. Background Art

[0002] As electricity demand continues to grow, the load on distribution transformers may exceed the rated capacity, that is, there will be a problem of distribution transformer overload, which may not only lead to power supply interruptions, but also cause damage to equipment, thereby affecting the stability and safety of the entire power system.

[0003] In the prior art, the problem of heavy overload of distribution transformers is usually alleviated by replacing distribution transformers with larger capacity, which will lead to the problem of light load operation of transformers and complicated construction. Therefore, an energy storage system can be connected to the distribution transformer, and the distribution transformer can charge the energy storage system. Both the distribution transformer and the energy storage system can supply power to the load, reduce the load of the distribution transformer, and alleviate the problem of heavy overload of distribution transformers. However, energy storage systems with different configurations have different effects on the load of distribution transformers, and are usually configured by staff based on their own experience.

[0004] In summary, the existing energy storage system configuration method is configured by staff based on their own experience, which will result in low matching between the energy storage system and the distribution transformer. Summary of the invention

[0005] The embodiments of the present application provide energy storage system configuration methods, devices, equipment, media and program products to solve the problem that the existing energy storage system configuration method is configured by staff based on their own experience, resulting in low matching between the energy storage system and the distribution transformer.

[0006] In a first aspect, an embodiment of the present application provides an energy storage system configuration method, comprising:

[0007] Obtain configuration parameters, including the capacity value of the distribution transformer, load values ​​at multiple historical moments, and the unit power cost, unit capacity cost, operation and maintenance coefficient, unit time discount rate, usage time, charging power upper limit, discharging power upper limit, and charging and discharging efficiency of the energy storage system;

[0008] Constructing a multi-objective programming model according to the configuration parameters;

[0009] Solving the multi-objective programming model to obtain configuration data, the configuration data including the rated power, rated capacity, charging power at each of the historical moments, and discharging power at each of the historical moments of the energy storage system;

[0010] The energy storage system is configured according to the rated power and the rated capacity, and the energy storage system is controlled to operate according to the charging power at each of the historical moments and the discharging power at each of the historical moments.

[0011] In a possible implementation, constructing a multi-objective programming model according to the configuration parameters includes:

[0012] Constructing a first objective function of the multi-objective programming model according to the capacity value of the distribution transformer and the load values ​​at multiple historical moments;

[0013] Constructing a second objective function of the multi-objective programming model according to the unit power cost, unit capacity cost, operation and maintenance coefficient, unit time discount rate and usage time of the energy storage system;

[0014] According to the charging power upper limit, discharging power upper limit, and charging and discharging efficiency of the energy storage system, four types of constraint conditions of the multi-objective programming model are constructed.

[0015] In a possible implementation manner, the first objective function is:

[0016] ;

[0017] in, represents the i-th historical moment, represents the load value of the distribution transformer at the i-th historical moment, S represents the capacity value of the distribution transformer, represents the discharge power of the energy storage system at the i-th historical moment, represents the charging power of the energy storage system at the i-th historical moment, K represents the preset load rate of the distribution transformer, and M represents the number of historical moments;

[0018] The first objective function represents minimizing the difference between the load rate of the distribution transformer and the preset load rate.

[0019] In a possible implementation manner, the second objective function is:

[0020] ;

[0021] in, , ;

[0022] represents the unit power cost of the energy storage system, represents the unit capacity cost of the energy storage system, N represents the usage time of the energy storage system, represents the discount rate per unit time of the energy storage system, represents the operation and maintenance coefficient of the energy storage system, represents the rated power of the energy storage system, and E represents the rated capacity of the energy storage system;

[0023] The second objective function represents minimizing the cost of the energy storage system.

[0024] In a possible implementation manner, the first type of constraint conditions among the four types of constraint conditions are: , i=1,…,M, indicating that the charging power of the energy storage system at each of the historical moments is less than or equal to the upper limit of the charging power of the energy storage system, and greater than or equal to 0;

[0025] The second type of constraint conditions among the four types of constraint conditions are: , i=1,…,M, indicating that the discharge power of the energy storage system at each of the historical moments is less than or equal to the upper limit of the discharge power of the energy storage system, and greater than or equal to 0;

[0026] The third type of constraint among the four types of constraints is: , indicating that the rated power of the energy storage system is greater than or equal to 0;

[0027] The fourth type of constraint conditions among the four types of constraint conditions are: , i=1,…,M, indicating that the rated capacity of the energy storage system is greater than or equal to the used capacity of the energy storage system at each of the historical moments;

[0028] in, , i=1,…,M, ;

[0029] represents the i-th historical moment, represents the charging power of the energy storage system at the i-th historical moment, represents the upper limit of the charging power of the energy storage system, M represents the number of historical moments, represents the discharge power of the energy storage system at the i-th historical moment, represents the upper limit of the discharge power of the energy storage system, represents the rated power of the energy storage system, E represents the rated capacity of the energy storage system, Indicates the preset time interval, It represents the charging and discharging efficiency of the energy storage system.

[0030] In a possible implementation, the method further includes:

[0031] Obtaining a state of charge of the energy storage system;

[0032] If the state of charge is less than a preset first state of charge threshold, controlling the energy storage system to stop discharging;

[0033] If the state of charge is greater than a preset second state of charge threshold, the energy storage system is controlled to stop charging; and the preset first state of charge threshold is less than the preset second state of charge threshold.

[0034] In a possible implementation, the method further includes:

[0035] Obtaining the current discharge power of the energy storage system and the historical load value of each substation corresponding to the distribution transformer;

[0036] Determining a target load value for each of the substations according to a historical load value for each of the substations;

[0037] Determining the target discharge power of each of the substations according to the discharge power and the target load value of each of the substations;

[0038] For each of the substations, the energy storage system is controlled to supply power to the substation according to the target discharge power of the substation.

[0039] In a second aspect, an embodiment of the present application provides an energy storage system configuration device, including:

[0040] An acquisition module is used to acquire configuration parameters, wherein the configuration parameters include the capacity value of the distribution transformer, the load values ​​at multiple historical moments, and the unit power cost, unit capacity cost, operation and maintenance coefficient, unit time discount rate, usage time, charging power upper limit, discharging power upper limit and charging and discharging efficiency of the energy storage system;

[0041] A model building module, used to build a multi-objective planning model according to the configuration parameters;

[0042] A processing module, configured to solve the multi-objective programming model to obtain configuration data, wherein the configuration data includes the rated power, rated capacity, charging power at each of the historical moments, and discharging power at each of the historical moments of the energy storage system;

[0043] A configuration module is used to configure the energy storage system according to the rated power and the rated capacity, and control the energy storage system to operate according to the charging power at each historical moment and the discharging power at each historical moment.

[0044] In a third aspect, an embodiment of the present application provides an electronic device, including:

[0045] Processor, memory, communication interface;

[0046] The memory is used to store executable instructions of the processor;

[0047] Wherein, the processor is configured to execute the energy storage system configuration method described in any one of the first aspects by executing the executable instructions.

[0048] In a fourth aspect, an embodiment of the present application provides a readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the energy storage system configuration method described in any one of the first aspects.

[0049] In a fifth aspect, an embodiment of the present application provides a computer program product, including a computer program, which, when executed by a processor, is used to implement the energy storage system configuration method described in any one of the first aspects.

[0050] The energy storage system configuration method, device, equipment, medium and program product provided in the embodiments of the present application, after acquiring the capacity value of the distribution transformer, the load values ​​at multiple historical moments, and the configuration parameters such as the unit power cost, unit capacity cost, operation and maintenance coefficient, unit time discount rate, usage time, charging power upper limit, discharge power upper limit and charging and discharging efficiency of the energy storage system, a multi-objective planning model is constructed according to the configuration parameters, and then the multi-objective planning model is solved to obtain the rated power, rated capacity, charging power at each historical moment and discharge power at each historical moment of the energy storage system, and finally the energy storage system is configured according to the rated power and rated capacity, and the energy storage system is controlled to operate according to the charging power at each historical moment and the discharge power at each historical moment to achieve configuration. The present application improves the matching of the energy storage system and the distribution transformer by using the parameters of the distribution transformer and the energy storage system to determine the configuration data. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0052] Figure 1 A schematic diagram of a flow chart of a first embodiment of a method for configuring an energy storage system provided in the present application;

[0053] Figure 2 A schematic diagram of a flow chart of Embodiment 2 of the energy storage system configuration method provided in this application;

[0054] Figure 3 A schematic diagram of a flow chart of Embodiment 3 of the energy storage system configuration method provided in this application;

[0055] Figure 4 A structural schematic diagram of an embodiment of an energy storage system configuration device is provided for this application;

[0056] Figure 5 A schematic diagram of the structure of an electronic device provided in this application.

[0057] The above drawings have shown clear embodiments of the present application, which will be described in more detail later. These drawings and text descriptions are not intended to limit the scope of the present application in any way, but to illustrate the concept of the present application to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0058] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0059] The terms "first", "second", "third", "fourth", etc. (if any) in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0060] As electricity demand continues to grow, the load on distribution transformers may exceed the rated capacity, and the load rate of distribution transformers may exceed 100%, which means that the distribution transformer is overloaded. This may not only cause power supply interruptions, but also cause damage to equipment, thereby affecting the stability and safety of the entire power system.

[0061] In the prior art, the problem of heavy overload of distribution transformers is usually alleviated by replacing distribution transformers with larger capacity, which will lead to problems such as light load operation of transformers and complicated construction. Therefore, an energy storage system can be connected to the distribution transformer, and the distribution transformer can charge the energy storage system. Both the distribution transformer and the energy storage system can supply power to the load, reduce the load of the distribution transformer, and alleviate the problem of heavy overload of distribution transformers. However, energy storage systems with different configurations have different effects on the load of distribution transformers, and are usually configured by staff based on their own experience, so there will be a problem of low matching between the energy storage system and the distribution transformer.

[0062] In view of the problems existing in the prior art, the inventors found in the process of studying the energy storage system configuration method that in order to improve the matching of the existing energy storage system and the distribution transformer, the parameters of the distribution transformer and the parameters of the energy storage system can be used to construct a multi-objective planning function, and the rated power, rated capacity, charging power and discharging power required to be configured can be obtained by solving the energy storage system. After the energy storage system is configured and operated according to these configuration data, not only the load rate of the distribution transformer is close to the preset load rate, that is, the matching of the energy storage system and the distribution transformer is high, but also the cost of the energy storage system is low. Based on the above invention concept, the energy storage system configuration scheme in this application is designed.

[0063] The execution subject of the energy storage system configuration method in this application can be a computer, a server, a terminal device, etc. This application does not limit it. The following description will be given using a computer as an example.

[0064] The following is an example of an application scenario of the energy storage system configuration method provided in this application.

[0065] For example, in this application scenario, the distribution transformer has a distribution transformer overload problem, and an energy storage system needs to be installed to alleviate the distribution transformer overload problem. The energy storage system needs to be configured before installation.

[0066] The computer first obtains the configuration parameters, which include the capacity value of the distribution transformer, the load values ​​at multiple historical moments, and the unit power cost, unit capacity cost, operation and maintenance coefficient, unit time discount rate, usage time, charging power limit, discharging power limit and charging and discharging efficiency of the energy storage system.

[0067] Then, a multi-objective planning model is constructed according to the configuration parameters. The multi-objective planning model is solved to obtain configuration data, which includes the rated power, rated capacity, charging power at each historical moment, and discharging power at each historical moment of the energy storage system.

[0068] The computer configures the energy storage system according to the rated power and rated capacity, and controls the energy storage system to operate according to the charging power and discharging power at each historical moment. That is, the computer determines the components of the energy storage system according to the rated power and rated capacity, so that the rated power and rated capacity of these components after forming the energy storage system are the rated power and rated capacity solved by the computer. After the energy storage system is installed, the computer controls the operation of the energy storage system according to the charging power and discharging power at each historical moment in the order of historical moments from morning to night, with a preset duration at each interval.

[0069] It should be noted that the preset time length is 10 minutes, 15 minutes, 20 minutes, etc. The embodiment of the present application does not limit the preset time length and can be determined according to actual conditions.

[0070] It should be noted that the above scenario is only an example of an application scenario provided by an embodiment of the present application. The embodiment of the present application does not limit the actual form of the various devices included in the scenario, nor does it limit the interaction method between the devices. In the specific application of the solution, it can be set according to actual needs.

[0071] The technical solution of the present application is described in detail below through specific embodiments. It should be noted that the following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described in detail in some embodiments.

[0072] Figure 1 This is a flow chart of the first embodiment of the energy storage system configuration method provided by the present application. The present embodiment of the application describes the configuration of the energy storage system after the computer constructs a multi-objective planning model according to the configuration parameters and then solves and obtains the configuration data. The method in this embodiment can be implemented by software, hardware, or a combination of software and hardware. Figure 1 As shown, the energy storage system configuration method specifically includes the following steps:

[0073] S101: Obtain configuration parameters.

[0074] In this step, in order to configure the energy storage system and make the configured energy storage system more compatible with the distribution transformer, it is necessary to first obtain the configuration parameters.

[0075] Among them, the configuration parameters include the capacity value of the distribution transformer, the load values ​​at multiple historical moments, as well as the unit power cost, unit capacity cost, operation and maintenance coefficient, unit time discount rate, usage time, charging power limit, discharge power limit and charging and discharging efficiency of the energy storage system.

[0076] It should be noted that the time interval between every two adjacent historical moments is the same and is a preset time interval. The preset time interval can be 10 minutes, 15 minutes, 20 minutes, etc. The embodiment of the present application does not limit the preset time interval and can be determined according to actual conditions.

[0077] It should be noted that the unit power can be 1 kW, 10 kW, 1 MW, etc., the unit capacity can be 1 kVA, 10 kVA, 1 MVA, etc., and the unit duration can be 1 month, 6 months, 1 year, etc. The embodiments of the present application do not limit the unit power, unit capacity and unit duration, and can be determined according to actual conditions.

[0078] It should be noted that the method for the computer to obtain the load values ​​of the distribution transformer at multiple historical moments can be: a monitoring device, such as a load sensor or a smart meter, is installed on the distribution transformer, and the monitoring device sends the load value of the distribution transformer obtained by monitoring to the computer, and the computer can obtain the load value. It can also be: the monitoring device sends the voltage value and current value of the distribution transformer to the computer, and the computer calculates the load value based on the voltage value and the current value. It can also be: the staff uses the terminal device to send the load value to the computer, and the computer can obtain the load value.

[0079] It should be noted that the method for the computer to obtain the capacity value of the distribution transformer can be: the staff uses the terminal device to send the rated capacity to the computer, and the computer uses the rated capacity as the capacity value. It can also be: the staff uses the terminal device to send the rated voltage and rated current of the distribution transformer to the computer, and the computer calculates the capacity value based on the rated voltage and rated current. It can also be: after the staff uses the measuring equipment to measure the capacity value of the distribution transformer, the measuring equipment sends the capacity value to the computer, and the computer can obtain the capacity value.

[0080] The embodiments of the present application do not limit the manner in which the computer obtains the load values ​​of the distribution transformer at multiple historical moments or the manner in which the computer obtains the capacity value of the distribution transformer, which can be determined according to actual conditions.

[0081] It should be noted that the unit power cost, unit capacity cost, operation and maintenance coefficient, discount rate per unit time, usage time, charging power upper limit, discharging power upper limit and charging and discharging efficiency of the energy storage system are parameters that can be determined in advance, so they can be obtained.

[0082] S102: Construct a multi-objective planning model according to the configuration parameters.

[0083] In this step, after the computer obtains the configuration parameters, a multi-objective planning model can be constructed according to the configuration parameters.

[0084] Specifically, according to the capacity value of the distribution transformer and the load values ​​at multiple historical moments, the first objective function of the multi-objective programming model is constructed.

[0085] The first objective function is:

[0086] ;

[0087] in, represents the i-th historical moment, represents the load value of the distribution transformer at the i-th historical moment, S represents the capacity value of the distribution transformer, represents the discharge power of the energy storage system at the i-th historical moment, represents the charging power of the energy storage system at the i-th historical moment, K represents the preset load rate of the distribution transformer, M represents the number of historical moments, It represents the load rate of the distribution transformer at the i-th historical moment.

[0088] The first objective function represents minimizing the difference between the load factor of the distribution transformer and a preset load factor.

[0089] It should be noted that the preset load rate may be 30%, 40%, 50%, 60%, etc., and the preset load rate may also be selected from a preset load rate range, and the preset load rate range may be [30%, 70%], [40%, 60%], [30%, 65%], etc. The embodiment of the present application does not limit the preset load rate and the preset load rate range, and may be determined according to actual conditions.

[0090] The second objective function of the multi-objective programming model is constructed based on the unit power cost, unit capacity cost, operation and maintenance coefficient, unit time discount rate and usage time of the energy storage system;

[0091] The second objective function is:

[0092] ;

[0093] in, , ;

[0094] represents the unit power cost of the energy storage system, represents the unit capacity cost of the energy storage system, N represents the usage time of the energy storage system, represents the discount rate per unit time of the energy storage system, represents the operation and maintenance coefficient of the energy storage system, represents the rated power of the energy storage system, and E represents the rated capacity of the energy storage system. represents the operating cost of the energy storage system, It represents the operating cost of the energy storage system in the nth unit time. represents the operation and maintenance cost of the energy storage system in the nth unit time, Represents the operation and maintenance cost of the energy storage system during its service life.

[0095] The second objective function represents minimizing the cost of the energy storage system.

[0096] In one implementation, the configuration parameters also include the effective energy and unit energy gain of the energy storage system, where the effective energy represents the energy of the energy storage system that effectively participates in solving the distribution transformer overload problem. The second objective function may also be: .

[0097] in, , represents the unit energy gain of the energy storage system, Represents the effective energy of the energy storage system.

[0098] At this time, the second objective function represents maximizing the benefits of the energy storage system.

[0099] It should be noted that the unit energy can be 1 kWh, 10 kWh, 1000 kWh, etc. The embodiment of the present application does not limit the unit energy and can be determined according to actual conditions.

[0100] According to the upper limit of charging power, upper limit of discharging power, and charging and discharging efficiency of the energy storage system, four types of constraints of the multi-objective planning model are constructed.

[0101] The first of the four types of constraints is: , i=1,…,M, indicating that the charging power of the energy storage system at each historical moment is less than or equal to the upper limit of the charging power of the energy storage system, and greater than or equal to 0;

[0102] The second type of constraints among the four types of constraints are: , i=1,…,M, indicating that the discharge power of the energy storage system at each historical moment is less than or equal to the upper limit of the discharge power of the energy storage system, and greater than or equal to 0;

[0103] The third type of constraints among the four types of constraints are: , indicating that the rated power of the energy storage system is greater than or equal to 0;

[0104] The fourth type of constraints among the four types of constraints are: , i=1,…,M, indicating that the rated capacity of the energy storage system is greater than or equal to the used capacity of the energy storage system at each historical moment;

[0105] in, , i=1,…,M, ;

[0106] represents the i-th historical moment, represents the charging power of the energy storage system at the i-th historical moment, represents the upper limit of the charging power of the energy storage system, M represents the number of historical moments, represents the discharge power of the energy storage system at the i-th historical moment, represents the upper limit of the discharge power of the energy storage system, represents the rated power of the energy storage system, E represents the rated capacity of the energy storage system, Indicates the preset time interval, It represents the charging and discharging efficiency of the energy storage system.

[0107] S103: Solve the multi-objective programming model to obtain configuration data.

[0108] In this step, after the computer constructs the multi-objective planning model, it solves it to obtain configuration data, which includes the rated power, rated capacity, charging power at each historical moment, and discharging power at each historical moment of the energy storage system.

[0109] Discharge power refers to the rate at which the energy storage system provides electrical energy to the outside, while charging power refers to the rate at which the energy storage system receives electrical energy and stores it.

[0110] It should be noted that the multi-objective programming model can be solved by genetic algorithms, particle swarm optimization algorithms, simulated annealing algorithms and other algorithms. The embodiment of the present application does not limit the solution method of the multi-objective programming model, which can be determined according to actual conditions.

[0111] S104: configuring the energy storage system according to the rated power and the rated capacity, and controlling the energy storage system to operate according to the charging power at each historical moment and the discharging power at each historical moment.

[0112] In this step, after the computer obtains the configuration data, it configures the energy storage system according to the configuration data, that is, it configures the energy storage system according to the rated power and rated capacity, and controls the energy storage system to operate according to the charging power at each historical moment and the discharging power at each historical moment.

[0113] Specifically, the computer determines the components of the energy storage system based on the rated power and rated capacity, so that the rated power and rated capacity of the energy storage system after these components are combined are the rated power and rated capacity solved by the computer. After the energy storage system is installed, the computer controls the operation of the energy storage system according to the charging power and discharging power of the historical moments in the order from morning to night, at each preset interval.

[0114] After controlling the energy storage system to operate according to the charging power and discharging power of the last historical moment, the energy storage system is controlled to operate according to the charging power and discharging power of the historical moments in sequence from morning to night at each preset interval.

[0115] Since electricity consumption is cyclical, the charging power and discharging power at historical moments can be used to control the operation of the energy storage system, which can alleviate the problem of heavy overload of distribution transformers.

[0116] The energy storage system configuration method provided in this embodiment obtains the capacity value of the distribution transformer, the load values ​​at multiple historical moments, and the configuration parameters of the energy storage system such as the unit power cost, unit capacity cost, operation and maintenance coefficient, unit time discount rate, usage time, charging power upper limit, discharge power upper limit and charging and discharging efficiency, and then constructs a multi-objective planning model according to the configuration parameters, and then solves the multi-objective planning model to obtain the rated power, rated capacity, charging power at each historical moment and discharge power at each historical moment of the energy storage system, and finally configures the energy storage system according to the rated power and rated capacity, and controls the energy storage system to operate according to the charging power at each historical moment and the discharge power at each historical moment to achieve configuration. This application improves the matching of the energy storage system and the distribution transformer by using the parameters of the distribution transformer and the energy storage system to determine the configuration data.

[0117] In addition, since the first objective function is to minimize the difference between the load rate of the distribution transformer and the preset load rate, after the energy storage system is configured according to the configuration data, the load rate of the distribution transformer is close to the preset load rate, which can alleviate the problem of heavy overload of the distribution transformer and improve the stability of the power system. The second objective function is to minimize the cost of the energy storage system, so that after the energy storage system is configured and operated according to the configuration data, the cost of the energy storage system is low.

[0118] Figure 2 This is a flow chart of the second embodiment of the energy storage system configuration method provided by this application. Based on the above embodiment, this embodiment of the application describes the situation in which the computer controls the energy storage system according to the state of charge (SOC) of the energy storage system after the energy storage system configuration is completed. Figure 2 As shown, the energy storage system configuration method specifically includes the following steps:

[0119] S201: Obtaining the state of charge of the energy storage system.

[0120] In this step, after the energy storage system is configured, in order to avoid safety problems with the energy storage system, it is necessary to obtain the charge state of the energy storage system.

[0121] The state of charge refers to the ratio between the amount of electricity currently stored in the energy storage system and its maximum capacity, usually expressed as a percentage.

[0122] S202: Determine whether the state of charge is less than a preset first state of charge threshold; if the state of charge is less than the preset first state of charge threshold, execute step S203; if the state of charge is greater than or equal to the preset first state of charge threshold, execute step S204.

[0123] In this step, after the computer obtains the state of charge of the energy storage system, in order to avoid failure of the energy storage system due to low power, it is necessary to determine whether the state of charge is less than a preset first state of charge threshold.

[0124] It should be noted that the preset first state of charge threshold may be 5%, 10%, 20%, etc. The embodiment of the present application does not limit the preset first state of charge threshold, which may be determined according to actual conditions.

[0125] S203: Control the energy storage system to stop discharging.

[0126] In this step, if the computer determines that the state of charge is less than the preset first state of charge threshold, it means that the energy storage system has less power and continuing to discharge may cause a malfunction, so the computer controls the energy storage system to stop discharging.

[0127] S204: Determine whether the state of charge is greater than a preset second state of charge threshold; if the state of charge is greater than the preset second state of charge threshold, execute step S205; if the state of charge is less than or equal to the preset second state of charge threshold, execute step S206.

[0128] If the computer determines that the state of charge is greater than or equal to the preset first state of charge threshold, it means that the power of the energy storage system is not very small. In order to avoid overheating and gas generation due to excessive power in the energy storage system, it is necessary to determine whether the state of charge is greater than the preset second state of charge threshold.

[0129] It should be noted that the preset first state of charge threshold is less than the preset second state of charge threshold, and the preset second state of charge threshold may be 80%, 85%, 90%, etc. The embodiment of the present application does not limit the preset second state of charge threshold, and may be determined according to actual conditions.

[0130] S205: Control the energy storage system to stop charging.

[0131] In this step, if the computer determines that the state of charge is greater than the preset second state of charge threshold, it means that the energy storage system has a large amount of electricity and continued charging may cause a malfunction, so the energy storage system is controlled to stop charging.

[0132] S206: Control the energy storage system to operate according to the charging power at each historical moment and the discharging power at each historical moment.

[0133] In this step, if the computer determines that the state of charge is less than or equal to the preset second state of charge threshold, it means that the power of the energy storage system is moderate, and the energy storage system is controlled to operate according to the charging power at each historical moment and the discharging power at each historical moment.

[0134] It should be noted that the computer may first determine whether the state of charge is greater than a preset second state of charge threshold, and when it is determined that the state of charge is greater than the preset second state of charge threshold, control the energy storage system to stop charging; when it is determined that the state of charge is less than or equal to the preset second state of charge threshold, determine whether the state of charge is less than the preset first state of charge threshold. If the state of charge is less than the preset first state of charge threshold, control the energy storage system to stop discharging; if the state of charge is greater than or equal to the preset first state of charge threshold, control the energy storage system to operate according to the charging power at each historical moment and the discharging power at each historical moment.

[0135] The computer can also simultaneously determine whether the state of charge is less than a preset first state of charge threshold, and whether the state of charge is greater than a preset second state of charge threshold; if the state of charge is greater than the preset second state of charge threshold, the energy storage system is controlled to stop charging; if the state of charge is less than the preset first state of charge threshold, the energy storage system is controlled to stop discharging; if the state of charge is less than or equal to the preset second state of charge threshold, and the state of charge is greater than or equal to the preset first state of charge threshold, the energy storage system is controlled to operate according to the charging power at each historical moment and the discharging power at each historical moment.

[0136] It should be noted that the computer can also monitor the energy storage system and its key components (such as battery packs, inverters, cooling systems, etc.) in real time. By setting reasonable thresholds, abnormal conditions can be identified, such as overheating of distribution transformers, too high or too low temperature of energy storage equipment, and degradation of battery pack performance. Once an abnormal condition is detected, the alarm mechanism is triggered, and an alarm message is sent to the operation and maintenance personnel. At the same time, emergency strategies are implemented, such as reducing the load of the energy storage system, switching to backup power, starting the cooling system, or adjusting the charging and discharging strategy, etc., to prevent the fault from expanding.

[0137] It should be noted that the energy storage system is also equipped with a communication interface to transmit data with other devices (such as distribution transformers, distributed energy, load management equipment, etc.).

[0138] The communication interface can achieve communication through wireless communication technology and wired communication technology. The wireless communication technology can be Long Range Radio (LoRa) technology, Zigbee technology, 4th Generation "mobile communication technology (4G), 5th Generation "mobile communication technology (5G), etc. The simultaneous use of wireless communication technology and wired communication technology can provide the energy storage system with a variety of communication means, so that the energy storage system can flexibly select the most appropriate communication method according to the specific application scenario. For example, in remote areas or places where wiring is difficult, wireless communication technology is more applicable; in places where the amount of data is large and the communication rate requirement is high, wired communication technology can be considered.

[0139] Through the communication interface, the energy storage system can obtain real-time information such as the load of the distribution network, the operating status of other equipment, and grid dispatch instructions. This information provides a decision-making basis for the intelligent dispatch of the energy storage system, enabling it to adjust the charging and discharging strategy according to the global optimal principle and achieve optimal configuration of power resources.

[0140] The energy storage system configuration method provided in this embodiment ensures the safety of the energy storage system and increases the service life of the energy storage system by stopping discharging when the energy storage system has less power and stopping charging when the power is more. It can also ensure that the power of the energy storage system is moderate and improve the stability of the energy storage system.

[0141] Figure 3 This is a flow chart of the third embodiment of the energy storage system configuration method provided by the present application. Based on the above embodiment, the present embodiment of the present application describes the situation in which the computer allocates discharge power to each substation corresponding to the distribution transformer. Figure 3 As shown, the energy storage system configuration method specifically includes the following steps:

[0142] S301: Obtain the current discharge power of the energy storage system and the historical load value of each substation corresponding to the distribution transformer.

[0143] Since the distribution transformer supplies power to multiple substations, after the energy storage system is installed, the energy storage system also supplies power to these substations. In order to realize the distribution of power supply to the substations by the energy storage system, it is necessary to determine the discharge power of the energy storage system for each substation.

[0144] In this step, the computer first obtains the current discharge power of the energy storage system and the historical load value of each substation corresponding to the distribution transformer.

[0145] S302: Determine the target load value of each substation based on the historical load value of each substation.

[0146] In this step, after the computer obtains the historical load value of each substation, it determines the target load value of each substation according to the historical load value of each substation.

[0147] It should be noted that the target load value of each substation can be determined based on the historical load value of each substation by: using the training data to train the initial model to obtain a prediction model, and then for each substation, the historical load value of the substation is input into the prediction model to obtain the target load value of the substation. The initial model can be a time series model, a machine learning model, a neural network model, a support vector machine model, etc.

[0148] According to the historical load value of each substation, the target load value of each substation can be determined by: for each substation, the average value of the historical load value of the substation is used as the target load value of the substation. It can also be: for each substation, the mode of the historical load value of the substation is used as the target load value of the substation.

[0149] The embodiment of the present application does not limit the method of determining the target load value of each substation based on the historical load value of each substation, and can be determined according to actual conditions.

[0150] S303: Determine the target discharge power of each substation according to the discharge power and the target load value of each substation.

[0151] In this step, after obtaining the target load value of each substation, the computer determines the target discharge power of each substation according to the discharge power and the target load value of each substation.

[0152] Specifically, for each substation, the ratio of the target load value of the substation to the target load values ​​of all substations is used as the allocation ratio of the substation, and then the discharge power is multiplied by the allocation ratio of the substation to obtain the target discharge power of the substation.

[0153] S304: For each substation, control the energy storage system to supply power to the substation according to the target discharge power of the substation.

[0154] In this step, after the computer determines the target discharge power of each substation, for each substation, the energy storage system is controlled to supply power to the substation according to the target discharge power of the substation.

[0155] The energy storage system configuration method provided in this embodiment determines the target discharge power of each substation based on the historical load value of each substation and the current discharge power of the energy storage system, and then controls the energy storage system to supply power to the substation according to the target discharge power of each substation, thereby realizing power distribution and improving energy utilization.

[0156] Based on the above embodiments, the present application uses a fourth embodiment of the energy storage system configuration method to illustrate the situation where after the energy storage system is configured with rated power and rated capacity, the computer determines the charging period and the discharging period, and then redetermines the charging power and the discharging power.

[0157] After the energy storage system is configured with rated power and rated capacity, the charging and discharging of the energy storage system can be further scheduled to reduce the peak-to-valley difference of the power grid and reduce the peak-shaving pressure of the power grid.

[0158] The computer obtains the historical load value of the distribution transformer, and then determines the peak power consumption period and the low power consumption period based on the historical load value data.

[0159] The historical load values ​​can be sorted in order from early to late according to the corresponding collection time to obtain a load sequence. Then the reference value is calculated based on the historical load values. For every two adjacent historical load values ​​in the load sequence, if there is a load value equal to the reference value in the two historical load values, the load value equal to the reference value in the two historical load values ​​is used as the reference load value. If there is no load value equal to the reference value in the two historical load values, and one of the two historical load values ​​is greater than the reference value and the other is less than the reference value, the latter of the two historical load values ​​is used as the reference load value.

[0160] Furthermore, for the last reference load value in the load sequence, the reference load value and the historical load values ​​after the reference load value are taken as a load group. For each reference load value except the last reference load value in the load sequence, the reference load value and the historical load values ​​between the reference load value and the first reference load value after the reference load value are taken as a load group. The historical load values ​​before the first reference load value in the load sequence are taken as a load group.

[0161] For each load group, if the load values ​​in the load group are greater than or equal to the reference value, the period between the earliest collection time and the latest collection time of the load values ​​in the load group is regarded as the peak power consumption period. If the load values ​​in the load group are less than or equal to the reference value, the period between the earliest collection time and the latest collection time of the load values ​​in the load group is regarded as the valley power consumption period.

[0162] It should be noted that the method of calculating the benchmark value based on historical load values ​​can be: taking the average value of historical load values ​​as the benchmark value; it can also be: taking the average value of the maximum and minimum values ​​in the historical load values ​​as the benchmark value; it can also be: taking the median of the historical load values ​​as the benchmark value.

[0163] It should be noted that the peak electricity consumption period and the low electricity consumption period are time periods within a electricity consumption cycle. A electricity consumption cycle can be one day, one month, three months, etc.

[0164] After the computer determines the peak and valley periods of electricity consumption, during each peak period of electricity consumption, the computer obtains the current load value of the distribution transformer at preset intervals, and then constructs the first objective planning function, solves the discharge power, and controls the energy storage system to discharge according to the discharge power.

[0165] It should be noted that when the energy storage system discharges according to the discharge power, it can supply power to each substation in the manner of the third embodiment.

[0166] During each period of low electricity consumption, the computer obtains the current load value of the distribution transformer at preset intervals, and then constructs a second objective planning function to solve the charging power and control the energy storage system to charge according to the charging power.

[0167] The objective function in the first goal programming model is: , which means minimizing the difference between the distribution transformer load factor and the preset load factor.

[0168] The constraints in the first objective programming model include:

[0169] , indicating that the discharge power of the energy storage system is less than or equal to the upper limit of the discharge power of the energy storage system, and greater than or equal to 0;

[0170] , indicating that the discharge power of the energy storage system is less than or equal to the rated power of the energy storage system, and greater than or equal to 0;

[0171] in, Indicates the current load value of the distribution transformer, represents the discharge power, S represents the capacity value of the distribution transformer, K represents the preset load rate of the distribution transformer, Indicates the upper limit of the discharge power of the energy storage system, Indicates the rated power of the energy storage system.

[0172] The objective function in the second objective programming model is: , which means minimizing the difference between the distribution transformer load factor and the preset load factor.

[0173] The constraints in the second objective programming model include:

[0174] , indicating that the charging power of the energy storage system is less than or equal to the upper limit of the charging power of the energy storage system, and greater than or equal to 0;

[0175] in, Indicates the current load value of the distribution transformer, represents the charging power, S represents the capacity value of the distribution transformer, K represents the preset load rate of the distribution transformer, Indicates the upper limit of the charging power of the energy storage system.

[0176] It should be noted that the first objective planning model and the second objective planning model can be solved by algorithms such as genetic algorithm, particle swarm optimization algorithm, simulated annealing algorithm, etc. The embodiment of the present application does not limit the solution method of the first objective planning model and the second objective planning model, which can be determined according to actual conditions.

[0177] The energy storage system configuration method provided in this embodiment determines the peak power consumption period and the valley power consumption period. During the peak power consumption period, after the discharge power is determined according to the first target planning function, the energy storage system is controlled to discharge according to the discharge power; during the valley power consumption period, after the charging power is determined according to the second target planning function, the energy storage system is controlled to charge according to the charging power, thereby reducing the peak-valley difference of the power grid, reducing the peak-shaving pressure of the power grid, and improving the operation efficiency and stability of the power grid. In addition, through the first target planning function and the second target planning function, the load rate of the distribution transformer is close to the preset load rate, which can alleviate the problem of heavy overload of the distribution transformer and improve the stability of the power system.

[0178] The following is an embodiment of the device of the present application, which can be used to execute the embodiment of the method of the present application. For details not disclosed in the embodiment of the device of the present application, please refer to the embodiment of the method of the present application.

[0179] Figure 4 The present application provides a schematic diagram of the structure of an embodiment of an energy storage system configuration device. Figure 4 As shown, the energy storage system configuration device 40 includes:

[0180] An acquisition module 41 is used to acquire configuration parameters, wherein the configuration parameters include the capacity value of the distribution transformer, the load values ​​at multiple historical moments, and the unit power cost, unit capacity cost, operation and maintenance coefficient, unit time discount rate, usage time, charging power upper limit, discharging power upper limit and charging and discharging efficiency of the energy storage system;

[0181] A model building module 42, used to build a multi-objective planning model according to the configuration parameters;

[0182] A processing module 43 is used to solve the multi-objective programming model to obtain configuration data, wherein the configuration data includes the rated power, rated capacity, charging power at each historical moment, and discharging power at each historical moment of the energy storage system;

[0183] The configuration module 44 is used to configure the energy storage system according to the rated power and the rated capacity, and control the energy storage system to operate according to the charging power at each of the historical moments and the discharging power at each of the historical moments.

[0184] Furthermore, the model building module 42 is specifically used for:

[0185] Constructing a first objective function of the multi-objective programming model according to the capacity value of the distribution transformer and the load values ​​at multiple historical moments;

[0186] Constructing a second objective function of the multi-objective programming model according to the unit power cost, unit capacity cost, operation and maintenance coefficient, unit time discount rate and usage time of the energy storage system;

[0187] According to the charging power upper limit, discharging power upper limit, and charging and discharging efficiency of the energy storage system, four types of constraint conditions of the multi-objective programming model are constructed.

[0188] Furthermore, the first objective function is:

[0189] ;

[0190] in, represents the i-th historical moment, represents the load value of the distribution transformer at the i-th historical moment, S represents the capacity value of the distribution transformer, represents the discharge power of the energy storage system at the i-th historical moment, represents the charging power of the energy storage system at the i-th historical moment, K represents the preset load rate of the distribution transformer, and M represents the number of historical moments;

[0191] The first objective function represents minimizing the difference between the load rate of the distribution transformer and the preset load rate.

[0192] Furthermore, the second objective function is:

[0193] ;

[0194] in, , ;

[0195] represents the unit power cost of the energy storage system, represents the unit capacity cost of the energy storage system, N represents the usage time of the energy storage system, represents the discount rate per unit time of the energy storage system, represents the operation and maintenance coefficient of the energy storage system, represents the rated power of the energy storage system, and E represents the rated capacity of the energy storage system;

[0196] The second objective function represents minimizing the cost of the energy storage system.

[0197] Furthermore, the first type of constraint conditions among the four types of constraint conditions are: , i=1,…,M, indicating that the charging power of the energy storage system at each of the historical moments is less than or equal to the upper limit of the charging power of the energy storage system, and greater than or equal to 0;

[0198] The second type of constraint conditions among the four types of constraint conditions are: , i=1,…,M, indicating that the discharge power of the energy storage system at each of the historical moments is less than or equal to the upper limit of the discharge power of the energy storage system, and greater than or equal to 0;

[0199] The third type of constraint among the four types of constraints is: , indicating that the rated power of the energy storage system is greater than or equal to 0;

[0200] The fourth type of constraint conditions among the four types of constraint conditions are: , i=1,…,M, indicating that the rated capacity of the energy storage system is greater than or equal to the used capacity of the energy storage system at each of the historical moments;

[0201] in, , i=1,…,M, ;

[0202] represents the i-th historical moment, represents the charging power of the energy storage system at the i-th historical moment, represents the upper limit of the charging power of the energy storage system, M represents the number of historical moments, represents the discharge power of the energy storage system at the i-th historical moment, represents the upper limit of the discharge power of the energy storage system, represents the rated power of the energy storage system, E represents the rated capacity of the energy storage system, Indicates the preset time interval, It represents the charging and discharging efficiency of the energy storage system.

[0203] Furthermore, the acquisition module 41 is also used to acquire the state of charge of the energy storage system;

[0204] The processing module 43 is further used for:

[0205] If the state of charge is less than a preset first state of charge threshold, controlling the energy storage system to stop discharging;

[0206] If the state of charge is greater than a preset second state of charge threshold, the energy storage system is controlled to stop charging; and the preset first state of charge threshold is less than the preset second state of charge threshold.

[0207] Furthermore, the acquisition module 41 is also used to acquire the current discharge power of the energy storage system and the historical load value of each substation corresponding to the distribution transformer;

[0208] The processing module 43 is further used for:

[0209] Determining a target load value for each of the substations according to a historical load value for each of the substations;

[0210] Determining the target discharge power of each of the substations according to the discharge power and the target load value of each of the substations;

[0211] For each of the substations, the energy storage system is controlled to supply power to the substation according to the target discharge power of the substation.

[0212] The energy storage system configuration device provided in this embodiment is used to execute the technical solution in any of the aforementioned method embodiments. Its implementation principle and technical effects are similar and will not be described in detail here.

[0213] Figure 5 This is a schematic diagram of the structure of an electronic device provided in this application. Figure 5 As shown, the electronic device 50 includes:

[0214] Processor 51, memory 52, and communication interface 53;

[0215] The memory 52 is used to store executable instructions of the processor 51;

[0216] The processor 51 is configured to execute the technical solution in any of the aforementioned method embodiments by executing the executable instructions.

[0217] Optionally, the memory 52 may be independent or integrated with the processor 51 .

[0218] Optionally, when the memory 52 is a device independent of the processor 51, the electronic device 50 may further include:

[0219] The bus 54 , the memory 52 and the communication interface 53 are connected to the processor 51 via the bus 54 and communicate with each other. The communication interface 53 is used to communicate with other devices.

[0220] Optionally, the communication interface 53 may be implemented by a transceiver. The communication interface is used to implement communication between the database access device and other devices (such as a client, a read-write library, and a read-only library). The memory may include a random access memory (RAM) and may also include a non-volatile memory (non-volatile memory), such as at least one disk storage.

[0221] The bus 54 may be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, only one thick line is used in the figure, but it does not mean that there is only one bus or one type of bus.

[0222] The above-mentioned processor can be a general-purpose processor, including a central processing unit CPU, a network processor (NP), etc.; it can also be a digital signal processor DSP, an application-specific integrated circuit ASIC, a field programmable gate array FPGA or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.

[0223] The electronic device is used to execute the technical solution in any of the aforementioned method embodiments, and its implementation principle and technical effect are similar and will not be repeated here.

[0224] An embodiment of the present application also provides a readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the technical solution provided by any of the aforementioned method embodiments is implemented.

[0225] An embodiment of the present application also provides a computer program product, including a computer program, which is used to implement the technical solution provided by any of the aforementioned method embodiments when executed by a processor.

[0226] Those skilled in the art can understand that all or part of the steps of implementing the above-mentioned method embodiments can be completed by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, the steps of the above-mentioned method embodiments are executed; and the aforementioned storage medium includes: ROM, RAM, disk or optical disk and other media that can store program codes.

[0227] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for configuring an energy storage system, characterized in that: include: Obtain configuration parameters, including the capacity value of the distribution transformer, load values ​​at multiple historical moments, and the unit power cost, unit capacity cost, operation and maintenance coefficient, unit time discount rate, usage time, charging power upper limit, discharging power upper limit, and charging and discharging efficiency of the energy storage system; Constructing a multi-objective programming model according to the configuration parameters; Solving the multi-objective programming model to obtain configuration data, the configuration data including the rated power, rated capacity, charging power at each of the historical moments, and discharging power at each of the historical moments of the energy storage system; The energy storage system is configured according to the rated power and the rated capacity, and the energy storage system is controlled to operate according to the charging power at each of the historical moments and the discharging power at each of the historical moments; Wherein, constructing a multi-objective planning model according to the configuration parameters includes: Constructing a first objective function of the multi-objective programming model according to the capacity value of the distribution transformer and the load values ​​at multiple historical moments; Constructing a second objective function of the multi-objective programming model according to the unit power cost, unit capacity cost, operation and maintenance coefficient, unit time discount rate and usage time of the energy storage system; According to the charging power upper limit, discharging power upper limit, and charging and discharging efficiency of the energy storage system, four types of constraint conditions of the multi-objective programming model are constructed.

2. The method according to claim 1, characterized in that The first objective function is: ； in, represents the i-th historical moment, represents the load value of the distribution transformer at the i-th historical moment, S represents the capacity value of the distribution transformer, represents the discharge power of the energy storage system at the i-th historical moment, represents the charging power of the energy storage system at the i-th historical moment, K represents the preset load rate of the distribution transformer, and M represents the number of historical moments; The first objective function represents minimizing the difference between the load rate of the distribution transformer and the preset load rate.

3. The method according to claim 1, characterized in that The second objective function is: ； in, , ; represents the unit power cost of the energy storage system, represents the unit capacity cost of the energy storage system, N represents the usage time of the energy storage system, represents the discount rate per unit time of the energy storage system, represents the operation and maintenance coefficient of the energy storage system, represents the rated power of the energy storage system, and E represents the rated capacity of the energy storage system; The second objective function represents minimizing the cost of the energy storage system.

4. The method according to claim 1, characterized in that: The first type of constraint conditions among the four types of constraint conditions are: , i=1,…,M, indicating that the charging power of the energy storage system at each of the historical moments is less than or equal to the upper limit of the charging power of the energy storage system, and greater than or equal to 0; The second type of constraint conditions among the four types of constraint conditions are: , i=1,…,M, indicating that the discharge power of the energy storage system at each of the historical moments is less than or equal to the upper limit of the discharge power of the energy storage system, and greater than or equal to 0; The third type of constraint among the four types of constraints is: , indicating that the rated power of the energy storage system is greater than or equal to 0; The fourth type of constraint conditions among the four types of constraint conditions are: , i=1,…,M, indicating that the rated capacity of the energy storage system is greater than or equal to the used capacity of the energy storage system at each of the historical moments; in, , i=1,…,M, ; represents the i-th historical moment, represents the charging power of the energy storage system at the i-th historical moment, represents the upper limit of the charging power of the energy storage system, M represents the number of historical moments, represents the discharge power of the energy storage system at the i-th historical moment, represents the upper limit of the discharge power of the energy storage system, represents the rated power of the energy storage system, E represents the rated capacity of the energy storage system, Indicates the preset time interval, It represents the charging and discharging efficiency of the energy storage system.

5. The method according to any one of claims 1 to 4, characterized in that: The method further comprises: Obtaining a state of charge of the energy storage system; If the state of charge is less than a preset first state of charge threshold, controlling the energy storage system to stop discharging; If the state of charge is greater than a preset second state of charge threshold, the energy storage system is controlled to stop charging; and the preset first state of charge threshold is less than the preset second state of charge threshold.

6. The method according to any one of claims 1 to 4, characterized in that: The method further comprises: Obtaining the current discharge power of the energy storage system and the historical load value of each substation corresponding to the distribution transformer; Determining a target load value for each of the substations according to a historical load value for each of the substations; Determining the target discharge power of each of the substations according to the discharge power and the target load value of each of the substations; For each of the substations, the energy storage system is controlled to supply power to the substation according to the target discharge power of the substation.

7. An energy storage system configuration device, characterized in that: include: An acquisition module is used to acquire configuration parameters, wherein the configuration parameters include the capacity value of the distribution transformer, the load values ​​at multiple historical moments, and the unit power cost, unit capacity cost, operation and maintenance coefficient, unit time discount rate, usage time, charging power upper limit, discharging power upper limit and charging and discharging efficiency of the energy storage system; A model building module, used to build a multi-objective planning model according to the configuration parameters; A processing module, configured to solve the multi-objective programming model to obtain configuration data, wherein the configuration data includes the rated power, rated capacity, charging power at each of the historical moments, and discharging power at each of the historical moments of the energy storage system; A configuration module, configured to configure the energy storage system according to the rated power and the rated capacity, and control the energy storage system to operate according to the charging power at each of the historical moments and the discharging power at each of the historical moments; The model building module, when used to build a multi-objective programming model according to the configuration parameters, is specifically used to: Constructing a first objective function of the multi-objective programming model according to the capacity value of the distribution transformer and the load values ​​at multiple historical moments; Constructing a second objective function of the multi-objective programming model according to the unit power cost, unit capacity cost, operation and maintenance coefficient, unit time discount rate and usage time of the energy storage system; According to the charging power upper limit, discharging power upper limit, and charging and discharging efficiency of the energy storage system, four types of constraint conditions of the multi-objective programming model are constructed.

8. An electronic device, characterized in that: include: Processor, memory, communication interface; The memory is used to store executable instructions of the processor; Wherein, the processor is configured to execute the energy storage system configuration method according to any one of claims 1 to 6 by executing the executable instructions.

9. A readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the energy storage system configuration method according to any one of claims 1 to 6 is implemented.

10. A computer program product, characterized in that It includes a computer program, which is used to implement the energy storage system configuration method according to any one of claims 1 to 6 when executed by a processor.

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