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

Abstract

The present application provides a configuration method, device, equipment, medium and program product for an energy storage system. In this method, after obtaining the capacity value of a distribution transformer, the load values at multiple historical moments, as well as configuration parameters such as the unit power cost, unit capacity cost, operation and maintenance coefficient, discount rate per unit duration, usage duration, charging power upper limit, discharging power upper limit and charge-discharge efficiency of the energy storage system, a multi-objective programming model is constructed based on the configuration parameters, and then the rated power, rated capacity of the energy storage system, the charging power at each historical moment and the discharging power at each historical moment are solved. 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 discharging power at each historical moment, so as to achieve the configuration. The present application determines the configuration data by using the parameters of the distribution transformer and the energy storage system, and improves the matching degree between the energy storage system and the distribution transformer.

Description

Technical Field

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

[0002] With the continuous growth of power demand, there will be a situation where the load of the distribution transformer exceeds the rated capacity, that is, the problem of heavy overload of the distribution transformer occurs, which may not only lead to power supply interruption, but also cause damage to equipment, thus affecting the stability and safety of the entire power system.

[0003] In the prior art, usually replacing the distribution transformer with a larger capacity is adopted to alleviate the problem of heavy overload of the distribution transformer, which will lead to the problems of light load operation of the transformer and complex construction. Therefore, an energy storage system can be used to connect with the distribution transformer. The distribution transformer can charge the energy storage system, and both the distribution transformer and the energy storage system can supply power to the load, reducing the load of the distribution transformer and alleviating the problem of heavy overload of the distribution transformer. However, energy storage systems with different configurations have different impacts on the load of the distribution transformer, and usually, it is configured by the staff according to their own experience.

[0004] To sum up, the existing method for configuring an energy storage system is configured by the staff according to their own experience, which will result in a low matching degree between the energy storage system and the distribution transformer. Summary of the Invention

[0005] Embodiments of the present application provide a method, device, equipment, medium and program product for configuring an energy storage system, so as to solve the problem that the existing method for configuring an energy storage system is configured by the staff according to their own experience, resulting in a low matching degree between the energy storage system and the distribution transformer.

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

[0007] Obtain configuration parameters, where 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, discount rate per unit duration, usage duration, charging power upper limit, discharging power upper limit and charge-discharge efficiency of the energy storage system;

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

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

[0010] 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.

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

[0012] Construct 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] Construct a second objective function of the multi-objective programming model according to the unit power cost, unit capacity cost, operation and maintenance coefficient, discount rate per unit time, and usage time of the energy storage system;

[0014] Construct four types of constraint conditions of the multi-objective programming model according to the charging power upper limit, discharging power upper limit, and charge-discharge efficiency of the energy storage system.

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

[0016] ;

[0017] Wherein, represents the i-th historical moment, represents the load value of the i-th historical moment of the distribution transformer, S represents the capacity value of the distribution transformer, represents the discharging 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] Wherein, , ;

[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 condition among the four types of constraint conditions is: , i = 1, …, M, indicating that the charging power of each of the historical moments 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;

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

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

[0027] The fourth type of constraint condition among the four types of constraint conditions is: , 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] Wherein, , 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, and M represents the number of historical moments, represents the discharging power of the energy storage system at the i-th historical moment, represents the upper limit of the discharging power 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 preset time interval, represents the charge-discharge efficiency of the energy storage system.

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

[0031] Obtain the state of charge of the energy storage system;

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

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

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

[0035] Obtain the current discharge power of the energy storage system and the historical load values of each sub - area corresponding to the distribution transformer;

[0036] Determine the target load value of each sub - area according to the historical load values of each sub - area;

[0037] Determine the target discharge power of each sub - area according to the discharge power and the target load value of each sub - area;

[0038] For each sub - area, control the energy storage system to supply power to the sub - area according to the target discharge power of the sub - area.

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

[0040] An acquisition module, configured to acquire configuration parameters, where 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, discount rate per unit time, usage time, charging power upper limit, discharge power upper limit, and charge - discharge efficiency of the energy storage system;

[0041] A model construction module, configured to construct a multi - objective programming model according to the configuration parameters;

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

[0043] 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 historical moment and the discharge power at each historical moment.

[0044] In a third aspect, an electronic device provided by an embodiment of the present application includes:

[0045] A processor, a memory, and a communication interface;

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

[0047] Wherein, the processor is configured to execute the energy storage system configuration method according to 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, on which a computer program is stored, and when the computer program is executed by a processor, the energy storage system configuration method according to any one of the first aspects is implemented.

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

[0050] The energy storage system configuration method, device, equipment, medium and program product provided by the embodiments of the present application, after obtaining the capacity value of the distribution transformer, the load values at multiple historical moments, and configuration parameters such as the unit power cost, unit capacity cost, operation and maintenance coefficient, discount rate per unit duration, usage duration, charging power upper limit, discharging power upper limit and charge-discharge efficiency of the energy storage system, construct a multi-objective programming model according to the configuration parameters, and then solve the multi-objective programming model to obtain the rated power, rated capacity of the energy storage system, the charging power at each historical moment and the discharging power at each historical moment, and finally configure the energy storage system according to the rated power and rated capacity, and control the energy storage system to operate according to the charging power and the discharging power at each historical moment to achieve the configuration. The present application determines the configuration data by using the parameters of the distribution transformer and the energy storage system, improving the matching between the energy storage system and the distribution transformer. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] The drawings herein are incorporated into the specification and form a part of the specification, showing embodiments consistent with the present application, and are used together with the specification to explain the principles of the present application.

[0052] Figure 1 It is a schematic flowchart of the first embodiment of the energy storage system configuration method provided by the present application;

[0053] Figure 2 It is a schematic flowchart of the second embodiment of the energy storage system configuration method provided by the present application;

[0054] Figure 3 It is a schematic flowchart of the third embodiment of the energy storage system configuration method provided by the present application;

[0055] Figure 4 It is a schematic structural diagram of an embodiment of the energy storage system configuration device provided by the present application;

[0056] Figure 5 It is a schematic structural diagram of an electronic device provided by the present application.

[0057] Through the above-mentioned accompanying drawings, specific embodiments of the present application have been shown, and more detailed descriptions will be provided hereinafter. These drawings and textual descriptions are not intended to limit the scope of the concept 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 of Specific Embodiments

[0058] Here, exemplary embodiments will be described in detail, and examples thereof are shown in the accompanying drawings. When the following description refers to the accompanying drawings, unless otherwise indicated, the same numerals in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. On the contrary, 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, claims and above-mentioned accompanying drawings of the present application are used to distinguish similar objects and do not necessarily have to be used to describe a specific order or sequence. It should be understood that such data can be interchanged under appropriate circumstances so that the embodiments of the present application described here can be implemented in an order other than those illustrated or described here. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device comprising a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0060] With the continuous growth of power demand, there will be a situation where the load of the distribution transformer exceeds the rated capacity, and the load rate of the distribution transformer exceeds 100%, that is, the problem of severe overload of the distribution transformer occurs. This may not only lead to power supply interruption but also cause damage to the equipment, thus affecting the stability and safety of the entire power system.

[0061] In the prior art, usually, a distribution transformer with a larger capacity is replaced to alleviate the problem of severe overload of the distribution transformer, which will result in the problems of light load operation of the transformer and complex construction. Therefore, an energy storage system can be connected to the distribution transformer. The distribution transformer can charge the energy storage system, and both the distribution transformer and the energy storage system can supply power to the load, reducing the load of the distribution transformer and alleviating the problem of severe overload of the distribution transformer. However, energy storage systems with different configurations have different effects on the load of the distribution transformer, and usually, it is configured by the staff according to 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 during the research on the energy storage system configuration method that, in order to improve the matching between the existing energy storage system and the distribution transformer, the parameters of the distribution transformer and the energy storage system can be used to construct a multi-objective programming function, and the rated power, rated capacity, charging power, and discharging power to be configured can be obtained by solving. 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 between the energy storage system and the distribution transformer is relatively high, but also the cost of the energy storage system is relatively low. Based on the above inventive 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., and this application does not limit it. The following will take a computer as an example for illustration.

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

[0065] Exemplarily, in this application scenario, the distribution transformer has a problem of heavy overload of the distribution transformer, and it is necessary to install an energy storage system to alleviate the problem of heavy overload of the distribution transformer. It needs to be configured before installing the energy storage system.

[0066] The computer first obtains configuration parameters, which 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, discount rate per unit duration, usage duration, charging power upper limit, discharging power upper limit, and charge-discharge efficiency of the energy storage system.

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

[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 the energy storage system formed by these components are the rated power and rated capacity obtained by the computer through solution. Furthermore, after the energy storage system is installed, the computer controls the energy storage system to operate according to the charging power and discharging power at the historical moment in order from early to late at intervals of a preset duration.

[0069] It should be noted that the preset duration is 10 minutes, 15 minutes, 20 minutes, etc. The embodiments of this application do not limit the preset duration, and it can be determined according to the actual situation.

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

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

[0072] Figure 1 FIG. is a schematic flowchart of the first embodiment of the energy storage system configuration method provided by the present application. In the embodiments of the present application, after a computer constructs a multi-objective programming model according to configuration parameters and then solves to obtain configuration data, the situation of configuring the energy storage system is described. The method in this embodiment can be implemented by software, hardware, or a combination of software and hardware. As Figure 1 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 have a higher matching degree with the distribution transformer, it is necessary to first obtain 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, discount rate per unit duration, usage duration, charging power upper limit, discharging power upper limit, and charge-discharge 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 embodiments of the present application do not limit the preset time interval and can be determined according to actual situations.

[0077] It should be noted that the unit power can be 1 kilowatt, 10 kilowatts, 1 megawatt, 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 situations.

[0078] It should be noted that the ways for a computer to obtain the load values of a distribution transformer at multiple historical moments can be as follows: Monitoring devices, such as load sensors or smart meters, are installed on the distribution transformer. The monitoring devices send the monitored load values of the distribution transformer to the computer, and the computer can then obtain the load values. It can also be that the monitoring devices send 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 current value. It can also be that the staff uses a 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 ways for a computer to obtain the capacity value of a distribution transformer can be as follows: The staff uses a terminal device to send the rated capacity to the computer, and the computer takes the rated capacity as the capacity value. It can also be that the staff uses a 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 that after the staff uses a measuring device to measure the capacity value of the distribution transformer, the measuring device 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 ways for a computer to obtain the load values of a distribution transformer at multiple historical moments and the ways for a computer to obtain the capacity value of a distribution transformer, which can be determined according to the actual situation.

[0081] It should be noted that the unit power cost, unit capacity cost, operation and maintenance coefficient, discount rate per unit duration, usage duration, charging power upper limit, discharging power upper limit, and charge-discharge 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 programming model according to the configuration parameters.

[0083] In this step, after the computer obtains the configuration parameters, it can construct a multi-objective programming model according to the configuration parameters.

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

[0085] The first objective function is:

[0086] ;

[0087] Among them, 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 discharging power of the energy storage system at the i-th historical moment, The charging power at the i-th historical moment of the energy storage system is represented as, K represents the preset load rate of the distribution transformer, M represents the number of historical moments, 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 rate of the distribution transformer and the preset load rate.

[0089] It should be noted that the preset load rate can be 30%, 40%, 50%, 60%, etc., and the preset load rate can also be selected from the preset load rate range, which can be [30%, 70%], [40%, 60%], [30%, 65%], etc. The embodiments of this application do not limit the preset load rate and the preset load rate range, and can be determined according to the actual situation.

[0090] Construct the second objective function of the multi-objective programming model according to the unit power cost, unit capacity cost, operation and maintenance coefficient, discount rate per unit duration, and usage duration of the energy storage system;

[0091] The second objective function is:

[0092] ;

[0093] Wherein, , ;

[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 duration of the energy storage system, represents the discount rate per unit duration 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, represents the operating cost of the energy storage system in the n-th unit duration, represents the operation and maintenance cost of the energy storage system in the n-th unit duration, represents the operation and maintenance cost of the energy storage system during the usage duration.

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

[0096] In one implementation, the configuration parameters further include the effective energy and unit energy revenue of the energy storage system. The effective energy represents the energy of the energy storage system effectively participating in solving the problem of heavy overload of the distribution transformer. The second objective function can also be: .

[0097] Among them, , represents the unit energy income 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 income of the energy storage system.

[0099] It should be noted that the unit energy can be 1 kWh, 10 kWh, 1000 kWh, etc. The embodiments of this application do not limit the unit energy and can be determined according to the actual situation.

[0100] Construct four types of constraint conditions for the multi-objective programming model according to the charging power upper limit, discharging power upper limit, and charge-discharge efficiency of the energy storage system.

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

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

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

[0104] The fourth type of constraint condition among the four types of constraint conditions is: , 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] Among them, , 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 charging power upper limit of the energy storage system, M represents the number of historical moments, represents the discharging power of the energy storage system at the i-th historical moment, represents the discharging power upper limit of the energy storage system, represents the rated power of the energy storage system, E represents the rated capacity of the energy storage system, represents the preset time interval, Indicates the charge and discharge 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 programming model, it solves the model 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] The discharging power refers to the rate at which the energy storage system provides electrical energy to the outside, while the charging power refers to the rate at which the energy storage system receives and stores electrical energy.

[0110] It should be noted that the solution method of the multi-objective programming model can be solved through algorithms such as genetic algorithm, particle swarm optimization algorithm, simulated annealing algorithm, etc. The embodiments of the present application do not limit the solution method of the multi-objective programming model, which can be determined according to the actual situation.

[0111] S104: Configure the energy storage system according to the rated power and rated capacity, and control the energy storage system to operate according to the charging power and 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, 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.

[0113] Specifically, 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 the energy storage system formed by these components are the rated power and rated capacity obtained by the computer's solution. Furthermore, after the energy storage system is installed, the computer controls the energy storage system to operate according to the charging power and discharging power at historical moments in sequence at preset time intervals in the order from early to late historical moments.

[0114] After controlling the energy storage system to operate according to the charging power and discharging power at the last historical moment, at preset time intervals, again in the order from early to late historical moments, the computer controls the energy storage system to operate according to the charging power and discharging power at historical moments at preset time intervals in sequence.

[0115] Since electricity consumption is periodic, 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 the distribution transformer.

[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 failures 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 can be 5%, 10%, 20%, etc. The embodiments of the present application do not limit the preset first state-of-charge threshold, which can be determined according to actual situations.

[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 power of the energy storage system is low. If discharging continues, it may cause failures. Therefore, 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 low. In order to avoid problems such as overheating and gas generation in the energy storage system due to excessive power, 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. The preset second state-of-charge threshold can be 80%, 85%, 90%, etc. The embodiments of the present application do not limit the preset second state-of-charge threshold, which can be determined according to actual situations.

[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 power of the energy storage system is relatively high. Continuing to charge may cause failures. Therefore, control the energy storage system to stop charging.

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

[0134] It should be noted that the computer can first determine whether the state of charge is greater than a preset second state-of-charge threshold. When it is determined that the state of charge is greater than the preset second state-of-charge threshold, the energy storage system is controlled 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, it is determined 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, the energy storage system is controlled to stop discharging; if 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 and 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 and discharging power at each historical moment.

[0136] It should be noted that the computer can also perform real-time monitoring on the energy storage system and its key components (such as battery packs, inverters, cooling systems, etc.). By setting reasonable thresholds, abnormal situations can be identified, such as overheating of distribution transformers, too high or too low temperatures of energy storage devices, and degradation of battery pack performance. Once an abnormal situation is detected, the alarm mechanism is triggered to send an alarm message to the operation and maintenance personnel, and at the same time, an emergency strategy is executed, for example, reducing the load of the energy storage system, switching to a backup power supply, starting the cooling system, or adjusting the charge and discharge strategy, etc., to prevent the expansion of the fault.

[0137] It should be noted that a communication interface is also set in the energy storage system for transmitting data with other devices (such as distribution transformers, distributed energy sources, load management devices, etc.).

[0138] The communication interface can achieve communication through wireless communication technologies and wired communication technologies. The wireless communication technologies can be Long Range Radio (LoRa) technology, Zigbee technology, 4th Generation mobile communication technology (4G), 5th Generation mobile communication technology (5G), etc. Adopting both wireless communication technologies and wired communication technologies can provide diverse communication means for the energy storage system, enabling the energy storage system to flexibly select the most suitable communication method according to specific application scenarios. For example, in remote or areas where wiring is difficult, wireless communication technologies are more applicable; while in situations with large amounts of data and high requirements for communication speed, wired communication technologies can be considered.

[0139] Through the communication interface, the energy storage system can obtain information such as the load situation of the distribution network, the operating status of other devices, and the power grid dispatching instructions in real time. These information provide a decision-making basis for the intelligent dispatching of the energy storage system, enabling it to adjust the charge and discharge strategies according to the global optimal principle and achieve the optimal allocation of power resources.

[0140] The energy storage system configuration method provided in this embodiment ensures the safety of the energy storage system and extends its service life by stopping discharging when the power of the energy storage system is low and stopping charging when the power is high. Moreover, it can 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 schematic flowchart of Embodiment 3 of the energy storage system configuration method provided in this application. On the basis of the above embodiment, this application embodiment describes the situation of the computer allocating discharge power to each substation area corresponding to the distribution transformer. As Figure 3 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 values of each substation area corresponding to the distribution transformer.

[0143] Since the distribution transformer supplies power to multiple substation areas, after installing the energy storage system, the energy storage system also supplies power to these substation areas. To achieve the allocation of power supply of the energy storage system to the substation areas, it is necessary to determine the discharge power of the energy storage system for each substation area.

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

[0145] S302: Determine the target load value for each substation area according to the historical load values of each substation area.

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

[0147] It should be noted that the method of determining the target load value for each substation area according to the historical load values of each substation area can be: using training data to train an initial model to obtain a prediction model, and then for each substation area, inputting the historical load value of this substation area into the prediction model to obtain the target load value of this substation area. The initial model can be a time series model, a machine learning model, a neural network model, a support vector machine model, etc.

[0148] The method of determining the target load value for each substation area according to the historical load values of each substation area can also be: for each substation area, taking the average value of the historical load values of this substation area as the target load value of this substation area. It can also be: for each substation area, taking the mode in the historical load values of this substation area as the target load value of this substation area.

[0149] The embodiments of the present application do not limit the method of determining the target load value for each substation area according to the historical load values of each substation area, and it can be carried out according to the actual situation.

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

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

[0152] Specifically, for each substation area, taking the ratio of the target load value of this substation area to the target load values of all substation areas as the allocation ratio of this substation area, and then multiplying the discharge power by the allocation ratio of this substation area to obtain the target discharge power of this substation area.

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

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

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

[0156] On the basis of the above embodiment, this application uses Embodiment 4 of the energy storage system configuration method to illustrate the situation where after the rated power and rated capacity of the energy storage system are configured, the computer determines the charging period and the discharging period, and then re-determines the charging power and the discharging power.

[0157] After the rated power and rated capacity of the energy storage system are configured, the charging and discharging of the energy storage system can be further scheduled to reduce the peak-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 valley power consumption period according to the historical load value data.

[0159] The historical load values can be sorted in ascending order according to the corresponding collection times 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 among these two historical load values, then the load value equal to the reference value among these two historical load values is used as the reference load value. If there is no load value equal to the reference value among these two historical load values, and one of these two historical load values is greater than the reference value and the other is less than the reference value, then the latter of these two historical load values is used as the reference load value.

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

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

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

[0163] It should be noted that the peak electricity consumption period and the off-peak electricity consumption period are time periods within an electricity consumption cycle, and an electricity consumption cycle can be one day, one month, 3 months, etc.

[0164] After the computer determines the peak electricity consumption period and the off-peak electricity consumption period, during each peak electricity consumption period, the computer obtains the current load value of the distribution transformer at preset time intervals, and then constructs a first target programming function, solves for 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, the power supply to each substation area can be carried out in the manner of Embodiment 3.

[0166] During each off-peak electricity consumption period, the computer obtains the current load value of the distribution transformer at preset time intervals, and then constructs a second target programming function, solves for the charging power, and controls the energy storage system to charge according to the charging power.

[0167] The objective function in the first target programming model is: , which represents minimizing the difference between the load rate of the distribution transformer and the preset load rate.

[0168] The constraint conditions in the first target programming model include:

[0169] , which means 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] , which means 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] Among them, represents the current load value of the distribution transformer, represents the discharge power of, S represents the capacity value of the distribution transformer, K represents the preset load rate of the distribution transformer, represents the upper limit of the discharge power of the energy storage system, represents the rated power of the energy storage system.

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

[0173] The constraint conditions 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] Among them, represents 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, represents the upper limit of the charging power of the energy storage system.

[0176] It should be noted that the solution methods of the first objective programming model and the second objective programming model can be solved by algorithms such as genetic algorithm, particle swarm optimization algorithm, simulated annealing algorithm, etc. The embodiments of the present application do not limit the solution methods of the first objective programming model and the second objective programming model, and can be determined according to the actual situation.

[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 determining the discharge power according to the first objective programming function, the energy storage system is controlled to discharge according to the discharge power; during the valley power consumption period, after determining the charging power according to the second objective programming function, the energy storage system is controlled to charge according to the charging power, 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 objective programming function and the second objective programming function, the load rate of the distribution transformer is close to the preset load rate, which can relieve 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 method embodiment of the present application. For the details not disclosed in the embodiment of the device of the present application, please refer to the method embodiment of the present application.

[0179] Figure 4 is a schematic structural diagram of an embodiment of the energy storage system configuration device provided by the present application. As Figure 4 shown, the energy storage system configuration device 40 includes:

[0180] An acquisition module 41, configured to acquire configuration parameters, where 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, discount rate per unit time, usage time, upper limit of charging power, upper limit of discharge power, and charge and discharge efficiency of the energy storage system;

[0181] A model construction module 42, configured to construct a multi-objective programming model according to the configuration parameters;

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

[0183] A configuration module 44 is 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 historical moment and the discharging power at each historical moment.

[0184] Further, the model construction module 42 is specifically configured to:

[0185] Construct 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] Construct a second objective function of the multi-objective programming model according to the unit power cost, unit capacity cost, operation and maintenance coefficient, discount rate per unit time, and usage time of the energy storage system;

[0187] Construct four types of constraint conditions of the multi-objective programming model according to the charging power upper limit, discharging power upper limit, and charge-discharge efficiency of the energy storage system.

[0188] Further, the first objective function is:

[0189] ;

[0190] Wherein, represents the i-th historical moment, represents the load value of the i-th historical moment of the distribution transformer, S represents the capacity value of the distribution transformer, represents the discharging 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] Further, the second objective function is:

[0193] ;

[0194] Wherein, , ;

[0195] represents the unit power cost of the energy storage system, represents the cost per unit capacity of the energy storage system, N represents the usage duration of the energy storage system, represents the discount rate per unit duration 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, 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] Further, the first type of constraint condition among the four types of constraint conditions is: , i = 1, …, M, indicating that the charging power at each historical moment 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;

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

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

[0200] The fourth type of constraint condition among the four types of constraint conditions is: , 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;

[0201] Among them, , 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 discharging power of the energy storage system at the i-th historical moment, represents the upper limit of the discharging 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, represents the preset time interval, represents the charge-discharge efficiency of the energy storage system.

[0203] Further, the obtaining module 41 is further configured to obtain the state of charge of the energy storage system;

[0204] The processing module 43 is further configured to:

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

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

[0207] Further, the obtaining module 41 is further configured to obtain the current discharge power of the energy storage system and the historical load values of each substation area corresponding to the distribution transformer;

[0208] The processing module 43 is further configured to:

[0209] Determine the target load value of each substation area according to the historical load values of each substation area;

[0210] Determine the target discharge power of each substation area according to the discharge power and the target load value of each substation area;

[0211] For each substation area, control the energy storage system to supply power to the substation area according to the target discharge power of the substation area.

[0212] The energy storage system configuration device provided in this embodiment is used to execute the technical solutions in any of the foregoing method embodiments, and its implementation principle and technical effects are similar and will not be elaborated here.

[0213] Figure 5 It is a schematic structural diagram of an electronic device provided by the present application. As Figure 5 shown, the electronic device 50 includes:

[0214] A processor 51, a memory 52, and a communication interface 53;

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

[0216] Wherein, the processor 51 is configured to execute the technical solutions in any of the foregoing method embodiments by executing the executable instructions.

[0217] Optionally, the memory 52 can be either 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 complete communication with each other. The communication interface 53 is used to communicate with other devices.

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

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

[0222] The aforementioned 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] This electronic device is used to execute the technical solutions in any of the foregoing method embodiments. Its implementation principle and technical effects are similar and will not be elaborated here.

[0224] This application embodiment also provides a readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it implements the technical solutions provided in any of the foregoing method embodiments.

[0225] This application embodiment also provides a computer program product, including a computer program. When the computer program is executed by a processor, it is used to implement the technical solutions provided in any of the foregoing method embodiments.

[0226] Those of ordinary skill in the art will understand that all or part of the steps of implementing the above method embodiments can be completed by hardware related to program instructions. The foregoing program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps including those of the above method embodiments; and the foregoing storage medium includes various media that can store program codes such as ROM, RAM, magnetic disks, or optical discs.

[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 them; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements on some or all of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions 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 Including: Obtain configuration parameters, where 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, discount rate per unit duration, usage duration, charging power upper limit, discharging power upper limit, and charge-discharge efficiency of the energy storage system; Construct a multi-objective programming model based on the configuration parameters; Solve the multi-objective programming model to obtain configuration data, where the configuration data includes the rated power and rated capacity of the energy storage system, the charging power at each historical moment, and the discharging power at each historical moment; Configure the energy storage system according to the rated power and the rated capacity, and obtain the historical load value of the distribution transformer. Determine the peak power consumption period and the valley power consumption period based on the historical load value data; During each peak power consumption period, at intervals of a preset duration, obtain the current load value of the distribution transformer, construct a first objective programming function, solve to obtain the discharging power, and control the energy storage system to discharge according to the discharging power; During each valley power consumption period, at intervals of a preset duration, obtain the current load value of the distribution transformer, construct a second objective programming function, solve to obtain the charging power, and control the energy storage system to charge according to the charging power; Among them, the objective function in the first target planning model is: , indicating minimizing the difference between the distribution transformer load rate and the preset load rate; The constraint conditions in the first objective programming model include: , 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; , 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; Among them, represents the current load value of the distribution transformer, represents the discharge power, S represents the capacity value of the distribution transformer, and K represents the preset load rate of the distribution transformer, represents the upper limit of the discharge power of the energy storage system, represents the rated power of the energy storage system; The objective function in the second target planning model is as follows: , indicating minimizing the difference between the load rate of the distribution transformer and the preset load rate; The constraint conditions in the second objective programming model include: , 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; Among them, represents the current load value of the distribution transformer, represents the charging power, S represents the capacity value of the distribution transformer, and K represents the preset load rate of the distribution transformer, represents the upper limit of the charging power of the energy storage system; Among them, constructing the multi-objective programming model according to the configuration parameters includes: Construct 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; Construct a second objective function of the multi-objective programming model according to the unit power cost, unit capacity cost, operation and maintenance coefficient, discount rate per unit duration, and usage duration of the energy storage system. The second objective function represents minimizing the cost of the energy storage system; Construct four types of constraint conditions of the multi-objective programming model according to the charging power upper limit, discharging power upper limit, and charge-discharge efficiency of the energy storage system; Among them, the second objective function is: ； Among them, , ; represents the unit power cost of the energy storage system, represents the unit capacity cost of the energy storage system, N represents the usage duration of the energy storage system, represents the discount rate per unit duration 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, E represents the rated capacity of the energy storage system.

2. The method according to claim 1, wherein The first objective function is: ； Among them, 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 first type of constraint condition among the four types of constraint conditions is as follows: , i = 1, …, M, indicating that the charging power at each of the historical moments 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; The second type of the four types of constraint conditions is as follows: , i = 1, …, M, indicating that the discharge power at each of the historical moments 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; The third type of constraint condition among the four types of constraint conditions is as follows: , indicating that the rated power of the energy storage system is greater than or equal to 0; represents the upper limit of the discharge power of the energy storage system, represents the rated power of the energy storage system; Among them, the fourth type of constraint condition in the four types of constraint conditions is: , 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; Among them, , where \(i = 1,\ldots,M\), ; represents the i-th historical moment, represents the charging power of the energy storage system at the i-th historical moment, M represents the number of historical moments, represents the discharging power of the energy storage system at the i-th historical moment, E represents the rated capacity of the energy storage system, represents a preset time interval, represents the charge-discharge efficiency of the energy storage system.

4. The method according to any one of claims 1 to 3, characterized in that, The method further includes: Obtain the state of charge of the energy storage system; If the state of charge is less than a preset first state of charge threshold, control the energy storage system to stop discharging; If the state of charge is greater than a preset second state of charge threshold, control the energy storage system to stop charging; the preset first state of charge threshold is less than the preset second state of charge threshold.

5. The method according to any one of claims 1 to 3, characterized in that, The method further includes: Obtain the current discharging power of the energy storage system and the historical load values of each substation area corresponding to the distribution transformer; Determine the target load value of each substation area according to the historical load value of each substation area; Determine the target discharging power of each substation area according to the discharging power and the target load value of each substation area; For each substation area, control the energy storage system to supply power to the substation area according to the target discharging power of the substation area.

6. An energy storage system configuration device, characterized in that, Including: An acquisition module, configured to acquire configuration parameters, where the configuration parameters include the capacity value of a distribution transformer, load values at multiple historical moments, as well as the unit power cost, unit capacity cost, operation and maintenance coefficient, discount rate per unit duration, usage duration, charging power upper limit, discharging power upper limit, and charge-discharge efficiency of an energy storage system; A model construction module, configured to construct a multi-objective programming model based on the configuration parameters; A processing module, configured to solve the multi-objective programming model to obtain configuration data, where the configuration data includes the rated power and rated capacity of the energy storage system, the charging power at each of the historical moments, and the discharging power at each of the historical moments; A configuration module, configured to configure the energy storage system according to the rated power and the rated capacity, and acquire the historical load value of the distribution transformer, and determine the peak power consumption period and the off-peak power consumption period based on the historical load value data; During each peak power consumption period, at every preset time interval, acquire the current load value of the distribution transformer, construct a first objective programming function, solve to obtain the discharging power, and control the energy storage system to discharge according to the discharging power; During each off-peak power consumption period, at every preset time interval, acquire the current load value of the distribution transformer, construct a second objective programming function, solve to obtain the charging power, and control the energy storage system to charge according to the charging power; Among them, the objective function in the first target planning model is as follows: , indicating minimizing the difference between the distribution transformer load rate and the preset load rate; The constraint conditions in the first objective programming model include: , 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; , 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; Among them, represents the current load value of the distribution transformer, represents the discharge power, S represents the capacity value of the distribution transformer, and K represents the preset load rate of the distribution transformer, represents the upper limit of the discharge power of the energy storage system, represents the rated power of the energy storage system; The objective function in the second target programming model is as follows: , which represents minimizing the difference between the load rate of the distribution transformer and the preset load rate; The constraint conditions in the second objective programming model include: , 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; Among them, represents the current load value of the distribution transformer, represents the charging power, S represents the capacity value of the distribution transformer, and K represents the preset load rate of the distribution transformer, represents the upper limit of the charging power of the energy storage system; When the model construction module is used to construct a multi-objective programming model based on the configuration parameters, it is specifically configured to: Construct 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; Construct a second objective function of the multi-objective programming model according to the unit power cost, unit capacity cost, operation and maintenance coefficient, discount rate per unit duration, and usage duration of the energy storage system, where the second objective function represents minimizing the cost of the energy storage system; Construct four types of constraint conditions of the multi-objective programming model according to the charging power upper limit, discharging power upper limit, and charge-discharge efficiency of the energy storage system; Wherein, the second objective function is: ； Among them, , ; represents the unit power cost of the energy storage system, represents the unit capacity cost of the energy storage system, N represents the usage duration of the energy storage system, represents the discount rate per unit duration 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, E represents the rated capacity of the energy storage system.

7. An electronic device, characterized in that, Including: A processor, a memory, and a 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 5 by executing the executable instructions.

8. A readable storage medium storing a computer program thereon, characterized in that, The computer program, when executed by a processor, implements the energy storage system configuration method according to any one of claims 1 to 5.

9. A computer program product, characterized in that, Including a computer program, which is used to implement the energy storage system configuration method according to any one of claims 1 to 5 when executed by a processor.

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