A method and system for energy storage capacity planning considering power supply in emergency scenarios

Abstract

The present invention discloses a method and system for energy storage capacity planning considering power supply in emergency scenarios. The method includes: obtaining annual operation data, and constructing an energy scheduling optimization model for the energy storage in normal scenarios and emergency power supply scenarios based on the annual operation data; according to the energy scheduling optimization model, considering the configuration parameters of the energy storage and the uncertainty brought about by fluctuations in grid operation parameters, establishing an energy storage capacity optimization model considering emergency power supply scenarios; inputting relevant parameters of the energy storage into the energy storage capacity optimization model, and the energy storage capacity optimization model outputs the energy storage capacity planning result. It realizes the maximization of the contribution to the power grid during the energy storage planning period and improves the utilization efficiency of the energy storage system.

Description

Technical Field

[0001] The present invention belongs to the technical field of energy storage planning, and particularly relates to a method and system for energy storage capacity planning considering power supply in emergency scenarios. Background Art

[0002] As a high-quality regulation resource, the energy storage system plays a crucial role in ensuring the stability of power supply. Especially in addressing the power supply guarantee issues at the weak links at the end of the distribution system, the energy storage system has shown significant advantages. By configuring energy storage devices at key nodes, the pressure on the distribution system in emergency situations can be effectively alleviated, ensuring the continuity and stability of power supply. However, due to the relatively low frequency of disaster scenarios, optimizing the energy storage configuration only for disaster scenarios often leads to waste of resources and low utilization rate of the energy storage system. Therefore, how to comprehensively optimize the configuration of the energy storage system in both normal operation and disaster response scenarios has become an urgent problem to be solved. Summary of the Invention

[0003] The present invention provides a method and system for energy storage capacity planning considering power supply in emergency scenarios, which is used to solve the technical problem that the configuration of the energy storage system cannot be comprehensively optimized in both normal operation and disaster response scenarios.

[0004] In a first aspect, the present invention provides a method for energy storage capacity planning considering power supply in emergency scenarios, including:

[0005] Obtain annual operation data, and construct an energy optimization scheduling model for the energy storage in normal scenarios and emergency power supply scenarios according to the annual operation data;

[0006] According to the energy optimization scheduling model, considering the equipment configuration parameters of the energy storage and the uncertainties caused by fluctuations in grid operation parameters, establish an energy storage capacity optimization model considering emergency power supply scenarios, where the expression of the objective function of the energy storage capacity optimization model is:

[0007] ,

[0008] ,

[0009] In the formula, is the total objective function, is the time period, is the contribution of the energy storage to the system operation efficiency in normal scenarios and emergency power supply scenarios, is the risk aversion index, which is a constant, is the comprehensive uncertainty of the energy storage in normal scenarios and emergency power supply scenarios, is the conversion coefficient, is the unit power cost of energy storage, is the power of energy storage configuration, is the unit capacity cost of energy storage, is the capacity of energy storage configuration, is the discount rate, is the designed service life of energy storage conversion;

[0010] Input the target parameters of energy storage into the energy storage capacity optimization model, and the energy storage capacity optimization model outputs the energy storage capacity planning result. The target parameters include unit power cost, unit capacity cost, charge-discharge efficiency, designed service life of energy storage, and historical electricity price data under normal and emergency scenarios.

[0011] In a second aspect, the present invention provides an energy storage capacity planning system considering power supply in an emergency scenario, including:

[0012] An acquisition module configured to acquire annual operation data and construct an energy optimization scheduling model of energy storage in normal and emergency power supply scenarios according to the annual operation data;

[0013] A construction module configured to establish an energy storage capacity optimization model considering an emergency power supply scenario according to the energy optimization scheduling model, considering the equipment configuration parameters of energy storage and the uncertainty caused by fluctuations in power grid operation parameters. The expression of the objective function of the energy storage capacity optimization model is:

[0014] ,

[0015] ,

[0016] In the formula, is the total objective function, is the time period, is the contribution of energy storage to the system operation efficiency in normal and emergency power supply scenarios, is the risk aversion index, is the uncertainty of energy storage in normal and emergency power supply scenarios, is the conversion coefficient, is the unit power of energy storage, is the power of energy storage configuration, is the unit capacity cost of energy storage, is the capacity of energy storage configuration, is the discount rate, is the designed service life of energy storage conversion;

[0017] An output module configured to input target parameters of energy storage into the energy storage capacity optimization model, where the energy storage capacity optimization model outputs an energy storage capacity planning result, and the target parameters include unit power cost, unit capacity cost, charge-discharge efficiency, designed service life of energy storage, and historical electricity price data under normal and emergency scenarios.

[0018] In a third aspect, an electronic device is provided, which includes: at least one processor, and a memory communicatively connected to the at least one processor, wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the steps of the energy storage capacity planning method considering emergency scenario power supply according to any embodiment of the present invention.

[0019] In a fourth aspect, the present invention further provides a computer-readable storage medium, on which a computer program is stored. When the program instructions are executed by a processor, the processor is enabled to execute the steps of the energy storage capacity planning method considering emergency scenario power supply according to any embodiment of the present invention.

[0020] The energy storage capacity planning method and system considering emergency scenario power supply of the present application, based on the annual electricity price data, load data, and emergency power supply demand situation data of a certain regional power grid, uses the k-means clustering algorithm to cluster the annual historical data, establishes an emergency power supply demand curve under typical day conditions, and at the same time quantifies the fluctuation of the contribution of energy storage to the system based on historical power grid operation data using standard deviation, and respectively establishes an energy optimization scheduling model for energy storage under normal and emergency power supply scenarios. Under normal scenarios, energy storage charges during peak loads and discharges during low loads to level the load curve for the system; under emergency power supply scenarios, energy storage responds to emergency power supply demands to ensure user power supply, and establishes the contributions of energy storage to the system operation efficiency and the uncertainties faced in the two scenarios, where the uncertainty is represented by the standard deviation between unit scenario contributions. Considering factors such as the contributions of energy storage to the system operation efficiency in the two scenarios, the equipment configuration parameters of energy storage, and the uncertainties brought by the fluctuations of power grid operation parameters, an energy storage capacity optimization model is established with the contribution of energy storage to the system operation efficiency as the objective function. The constraint conditions of the model include energy storage charge-discharge power constraints, energy storage charge-discharge energy constraints, and system power demand constraints. By constructing a distributed energy storage capacity optimization model considering emergency power supply scenarios, the contribution of energy storage to the system operation efficiency during the energy storage planning period is maximized, and the utilization efficiency of the energy storage system is improved. Description of the Drawings

[0021] To more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for the description of the embodiments. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0022] Figure 1 It is a flowchart of a method for planning energy storage capacity considering power supply in emergency scenarios provided by an embodiment of the present invention.

[0023] Figure 2 It is a structural block diagram of a system for planning energy storage capacity considering power supply in emergency scenarios provided by an embodiment of the present invention.

[0024] Figure 3 It is a schematic structural diagram of an electronic device provided by an embodiment of the present invention. Detailed implementation manners

[0025] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts fall within the scope of protection of the present invention.

[0026] Please refer to Figure 1 , which shows a flowchart of a method for planning energy storage capacity considering power supply in emergency scenarios of the present application.

[0027] As Figure 1 shown, the method for planning energy storage capacity considering power supply in emergency scenarios specifically includes the following steps:

[0028] Step S101, obtain annual operation data, and construct an energy optimization scheduling model for energy storage in normal scenarios and emergency power supply scenarios according to the annual operation data.

[0029] In this step, obtain the annual electricity price data, load data, and emergency power supply demand situation data of a regional power grid. Based on the annual operation data of the load data and the emergency power supply demand situation data, use the k-means clustering algorithm to cluster the annual historical data and establish an emergency power supply demand curve under typical day conditions. Based on the historical electricity price data, calculate the standard deviation of the contribution to the system operation efficiency at the same time of the whole year to quantify its fluctuation situation.

[0030] It should be noted that in the normal scenario, the energy storage is charged at the peak load and discharged at the low load. Then, the contribution of the energy storage to the system operation efficiency in the normal scenario is:

[0031] ,

[0032] In the formula, is the contribution of the energy storage to the system operation efficiency in the normal scenario, is the charging power of the energy storage participating in the normal scenario at time t, is the discharging power of the energy storage participating in the emergency scenario at time t, is the peak-valley electricity price;

[0033] In the emergency power supply scenario, the energy storage responds to the emergency power supply demand to ensure power supply to users. Then, the contribution of the energy storage to the system operation efficiency in the emergency power supply scenario is:

[0034] ,

[0035] In the formula, is the benefit of the energy storage participating in the emergency power supply scenario, is the unit system benefit of the emergency power supply scenario, is the discharging power of the energy storage in the emergency scenario.

[0036] In the process of planning and constructing the energy storage participating in multiple scenarios, the expression of the energy storage collected in each scenario is:

[0037] .

[0038] Step S102: According to the energy optimization scheduling model, considering the equipment configuration parameters of the energy storage and the uncertainty caused by the fluctuation of the power grid operation parameters, establish an energy storage capacity optimization model considering the emergency power supply scenario.

[0039] In this step, the expression of the objective function of the energy storage capacity optimization model is:

[0040] ,

[0041] ,

[0042] In the formula, is the total objective function, is the time period, is the contribution of the energy storage to the system operation efficiency in the normal scenario and the emergency power supply scenario, is the risk aversion index, is the comprehensive uncertainty of the energy storage in the normal scenario and the emergency power supply scenario, is the conversion coefficient, is the unit power of energy storage, is the power of energy storage configuration, is the unit capacity cost of energy storage, is the capacity of energy storage configuration, is the discount rate, is the designed service life of energy storage conversion;

[0043] The expression for calculating the comprehensive uncertainty of energy storage in normal scenarios and emergency power supply scenarios is:

[0044] ,

[0045] ,

[0046] In the formula, , are the uncertainties of energy storage participating in normal scenarios and emergency power supply scenarios at time t, respectively, , are the percentages of energy storage participating in normal scenarios at time t and the percentages of energy storage participating in emergency power supply scenarios at time t, respectively, is the correlation coefficient between normal scenarios and emergency power supply scenarios at time t, is the percentage of energy storage participating in scenario at time t, is the percentage of energy storage participating in scenario at time t, is the percentage of energy storage participating in scenario at time t, is scenario and scenario 's correlation coefficient at time t, is the uncertainty of energy storage participating in scenario at time t, is the sequence composed of electricity prices of normal scenarios throughout the year at time t, is the electricity price sequence composed of unit benefits of emergency power supply scenarios throughout the year at time t, is the variance function, is the covariance function.

[0047] It should be noted that the constraints of the energy storage capacity optimization model include the energy storage charge and discharge power constraint, the energy storage charge and discharge energy constraint, and the energy storage power demand constraint.

[0048] The expression of the energy storage charge and discharge power constraint is:

[0049] ,

[0050] ,

[0051] ,

[0052] ,

[0053] In the formula, is the charging power of the energy storage in the normal scenario, is the charging power of the energy storage participating in the normal scenario at time t, is the discharging power of the energy storage participating in the emergency scenario at time t, is a 0-1 variable;

[0054] The linearization of the energy storage charging and discharging power constraint is carried out by the big M method, and the expression is:

[0055] ,

[0056] ,

[0057] In the formula, M is an infinitely large number;

[0058] The expression of the energy constraint of the energy storage charging and discharging is:

[0059] ,

[0060] ,

[0061] ,

[0062] ,

[0063] ,

[0064] In the formula, is the energy state of the energy storage participating in the normal scenario at time t, is the energy state of the energy storage participating in the normal scenario at time t-1, is the charging power of the energy storage participating in the normal scenario at time t, is the discharging power of the energy storage participating in the emergency scenario at time t, is the discharging power of the energy storage participating in the emergency scenario at time t, is the charging power of the energy storage participating in the emergency scenario at time t, is the energy state of the energy storage participating in the emergency scenario at time (t-1), is the energy state of the energy storage participating in the emergency scenario at time t, is the capacity percentage of the energy storage participating in the normal and emergency scenarios, is the capacity percentage of the energy storage participating in the emergency scenario, is the configured capacity of the energy storage, is the SOC value of the energy storage for normal and emergency scenarios, is the self-discharge rate, is the charging efficiency, is the discharging efficiency, is the scenario in which the energy storage participates the SOC value at time t, is the lower limit of the SOC of the energy storage, is the upper limit of the SOC of the energy storage, is the SOC value of the energy storage at the first moment of the operating day, is the SOC value of the energy storage at the last moment of the operating day;

[0065] The expression of the power demand constraint of the energy storage is:

[0066] ,

[0067] In the formula, is the emergency power supply demand power at time t.

[0068] Among them, the energy storage capacity optimization model takes the power and capacity of the energy storage planning as decision variables, takes the maximum contribution to the system operation efficiency during the energy storage planning period as the objective function, and takes the energy storage charging and discharging power, the energy storage charging and discharging energy, and the emergency power supply demand as constraint conditions.

[0069] Step S103, input the target parameters of the energy storage into the energy storage capacity optimization model, and the energy storage capacity optimization model outputs the energy storage capacity planning result.

[0070] In this step, the target parameters include the unit power cost, the unit capacity cost, the charging and discharging efficiency, the designed service life of the energy storage, and the historical electricity price data in normal and emergency scenarios.

[0071] In summary, the method of the present application, based on the annual electricity price data, load data, and emergency power supply demand situation data of a certain regional power grid, uses the k-means clustering algorithm to cluster the annual historical data, establish an emergency power supply demand curve under typical day conditions, and at the same time uses standard deviation quantization based on historical electricity price data to quantify the fluctuations in the contribution of the system operation efficiency unit. Energy optimization scheduling models for energy storage in normal and emergency power supply scenarios are established respectively. In the normal scenario, the energy storage charges during peak load and discharges during low load to shave peaks and fill valleys for the system; in the emergency power supply scenario, the energy storage responds to the emergency power supply demand to ensure user power supply. The comprehensive contribution and uncertainty of the energy storage to the system operation efficiency in the two scenarios are established, where the uncertainty is expressed as the standard deviation between the contributions of the system operation efficiency unit. Considering factors such as the comprehensive contribution of the energy storage to the system operation efficiency in the two scenarios, the equipment configuration parameters of the energy storage, and the uncertainty brought by the fluctuations of the power grid parameters, an energy storage capacity optimization model is established with the maximum contribution to the system operation efficiency as the objective function. The constraint conditions of the model include the energy storage charge and discharge power constraint, the energy storage charge and discharge energy constraint, and the system power demand constraint. By constructing a distributed energy storage capacity optimization model considering the emergency power supply scenario, the contribution of the energy storage to the system operation efficiency during the energy storage planning period is maximized, and the utilization efficiency of the energy storage system is improved.

[0072] Please refer to Figure 2 , which shows a structural block diagram of an energy storage capacity planning system considering emergency scenario power supply of the present application.

[0073] As Figure 2 shown, the energy storage capacity planning system 200 includes an acquisition module 210, a construction module 220, and an output module 230.

[0074] Among them, the acquisition module 210 is configured to acquire annual operation data and construct an energy optimization scheduling model for energy storage in normal and emergency power supply scenarios according to the annual operation data;

[0075] The construction module 220 is configured to establish an energy storage capacity optimization model considering the emergency power supply scenario according to the energy optimization scheduling model, considering the equipment configuration parameters of the energy storage and the uncertainty brought by the fluctuations of the power grid operation parameters. The expression of the objective function of the energy storage capacity optimization model is:

[0076] ,

[0077] ,

[0078] In the formula, is the total objective function, is the time period, For the contribution of energy storage to the system operation efficiency in normal scenarios and emergency power supply scenarios, is the risk aversion index, which is a constant, is the comprehensive uncertainty of energy storage in normal scenarios and emergency power supply scenarios, is the conversion coefficient, is the unit power of energy storage, is the configured power of energy storage, is the unit capacity cost of energy storage, is the configured capacity of energy storage, is the discount rate, is the designed service life of energy storage after conversion;

[0079] The output module 230 is configured to input the target parameters of the energy storage into the energy storage capacity optimization model, and the energy storage capacity optimization model outputs the energy storage capacity planning result. The target parameters include the unit power cost, unit capacity cost, charge-discharge efficiency, designed service life of energy storage, and historical electricity price data in normal and emergency scenarios.

[0080] It should be understood that, Figure 2 The various modules described in Figure 1 correspond to the respective steps in the method described in Figure 2 Therefore, the operations, features, and corresponding technical effects described above for the method also apply to the various modules in

[0081] In some other embodiments, the embodiments of the present invention also provide a computer-readable storage medium, on which a computer program is stored. When the program instructions are executed by a processor, the processor is caused to execute the energy storage capacity planning method considering emergency scenario power supply in any of the above method embodiments;

[0082] As an implementation manner, the computer-readable storage medium of the present invention stores computer-executable instructions, and the computer-executable instructions are set as:

[0083] Obtain the annual operation data, and construct an energy dispatch optimization model of energy storage in normal scenarios and emergency power supply scenarios according to the annual operation data;

[0084] According to the energy dispatch optimization model, considering the equipment configuration parameters of the energy storage and the uncertainty caused by the fluctuation of the grid operation parameters, establish an energy storage capacity optimization model considering emergency power supply scenarios. Among them, the expression of the objective function of the energy storage capacity optimization model is:

[0085] ,

[0086] ,

[0087] In the formula, is the total objective function, is the time period, is the contribution of the energy storage to the system operation efficiency in normal scenarios and emergency power supply scenarios, is the risk aversion index, which is a constant, is the comprehensive uncertainty of the energy storage in normal scenarios and emergency power supply scenarios, is the conversion coefficient, is the unit power of the energy storage, is the configured power of the energy storage, is the unit capacity cost of the energy storage, is the configured capacity of the energy storage, is the discount rate, is the designed service life of the energy storage after conversion;

[0088] Input the target parameters of the energy storage into the energy storage capacity optimization model, and the energy storage capacity optimization model outputs the energy storage capacity planning result. The target parameters include the unit power cost, unit capacity cost, charge-discharge efficiency, designed service life of the energy storage, and historical electricity price data in normal and emergency scenarios.

[0089] A computer-readable storage medium may include a storage program area and a storage data area. Among them, the storage program area can store an operating system and application programs required for at least one function; the storage data area can store data created according to the use of the energy storage capacity planning system considering emergency scenario power supply, etc. In addition, the computer-readable storage medium may include high-speed random access memory, and may also include memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid-state storage devices. In some embodiments, the computer-readable storage medium may optionally include a memory remotely provided with respect to the processor, and these remote memories can be connected to the energy storage capacity planning system considering emergency scenario power supply through a network. Examples of the above network include but are not limited to the Internet, enterprise intranet, local area network, mobile communication network, and their combinations.

[0090] Figure 3 is a schematic structural diagram of the electronic device provided by an embodiment of the present invention, as Figure 3 shown. The device includes: a processor 310 and a memory 320. The electronic device may further include: an input device 330 and an output device 340. The processor 310, the memory 320, the input device 330, and the output device 340 may be connected through a bus or other means, Figure 3Take the bus connection as an example. The memory 320 is the above-mentioned computer-readable storage medium. The processor 310 executes various functional applications and data processing of the server by running the non-volatile software programs, instructions, and modules stored in the memory 320, that is, implements the energy storage capacity planning method under emergency scenario power supply in the above method embodiment. The input device 330 can receive input digital or character information, and generate key signal inputs related to user settings and function controls of the energy storage capacity planning system under emergency scenario power supply. The output device 340 may include display devices such as a display screen.

[0091] The above electronic device can execute the method provided by the embodiment of the present invention, and has corresponding functional modules and beneficial effects for executing the method. For technical details not described in detail in this embodiment, reference can be made to the method provided by the embodiment of the present invention.

[0092] As an implementation manner, the above electronic device is applied to an energy storage capacity planning system under emergency scenario power supply, and is used for a client, including: at least one processor; and a memory communicatively connected to the at least one processor; wherein, the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to:

[0093] Obtain annual operation data, and construct an energy optimization scheduling model for the energy storage under normal scenarios and emergency power supply scenarios according to the annual operation data;

[0094] According to the energy optimization scheduling model, considering the equipment configuration parameters of the energy storage and the uncertainties caused by fluctuations in grid operation parameters, establish an energy storage capacity optimization model under emergency power supply scenarios, wherein the expression of the objective function of the energy storage capacity optimization model is:

[0095] ,

[0096] ,

[0097] In the formula, is the total objective function, is the time period, is the contribution of the energy storage to the system operation efficiency under normal scenarios and emergency power supply scenarios, is the risk aversion index, which is a constant, is the comprehensive uncertainty of the energy storage under normal scenarios and emergency power supply scenarios, is the conversion coefficient, is the unit power of the energy storage, is the configured power of the energy storage, is the unit capacity cost of the energy storage, is the configured capacity of the energy storage, is the discount rate, is the designed service life of the energy storage conversion;

[0098] Input the target parameters of the energy storage into the energy storage capacity optimization model, and the energy storage capacity optimization model outputs the energy storage capacity planning result. The target parameters include the unit power cost, the unit capacity cost, the charge-discharge efficiency, the designed service life of the energy storage, and the historical electricity price data under normal and emergency scenarios.

[0099] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them; although the present invention 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 recorded in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for energy storage capacity planning considering power supply in emergency scenarios, characterized in that Including: Obtain annual operation data, and construct an energy scheduling optimization model for energy storage in normal scenarios and emergency power supply scenarios based on the annual operation data; According to the energy scheduling optimization model, considering the equipment configuration parameters of the energy storage and the uncertainty brought about by the fluctuations of grid operation parameters, establish an energy storage capacity optimization model considering emergency power supply scenarios. Among them, the expression of the objective function of the energy storage capacity optimization model is: ， ， In the formula, is the total objective function, is the time period, is the contribution of energy storage to the system operation efficiency in normal scenarios and emergency power supply scenarios, is the risk aversion index, which is a constant, is the comprehensive uncertainty of energy storage in normal scenarios and emergency power supply scenarios, is the conversion coefficient, is the unit power cost of energy storage, is the power configured for energy storage, is the unit capacity cost of energy storage, is the capacity configured for energy storage, is the discount rate, is the designed service life of energy storage conversion; Among them, in the normal scenario, the energy storage charges during the peak load period and discharges during the low load period, which can shave peaks and fill valleys for the system. Then, the contribution of the energy storage to the system operation efficiency in the normal scenario is: ， In the formula, The contribution to the system operation efficiency in the normal scenario is the charging power of the energy storage participating in the normal scenario at time t, is the discharging power of the energy storage participating in the emergency scenario at time t, is the peak-valley electricity price; In the emergency power supply scenario, the energy storage responds to the emergency power supply demand to ensure user power supply. Then, the contribution of the energy storage to the system operation efficiency in the emergency power supply scenario is: ， In the formula, is the contribution of energy storage to the system operation efficiency in the emergency power supply scenario, is the unit system benefit of the emergency power supply scenario, is the discharge power of energy storage in the emergency scenario; Calculate the contribution of the energy storage to the system operation efficiency in normal scenarios and emergency power supply scenarios. The expression is: ， Calculate the expression of the comprehensive uncertainty of the energy storage in normal scenarios and emergency power supply scenarios: ， ， In the formula, , are the uncertainties of the energy storage at time t when participating in the normal scenario and the emergency power supply scenario respectively, , are the percentages of the energy storage at time t when participating in the normal scenario and the emergency power supply scenario respectively, is the correlation coefficient between the normal scenario and the emergency power supply scenario at time t, is the percentage of the energy storage at time t when participating in scenario , is the uncertainty of the energy storage at time t when participating in scenario , is the percentage of the energy storage at time t when participating in scenario , is the correlation coefficient between scenario and scenario at time t, is the uncertainty of the energy storage at time t when participating in scenario , is the sequence of the electricity price components of the normal scenario throughout the year at time t, is the sequence of the unit benefits of the emergency power supply scenario throughout the year at time t, is the variance function, is the covariance function; Input the target parameters of the energy storage into the energy storage capacity optimization model, and the energy storage capacity optimization model outputs the energy storage capacity planning result. The target parameters include the unit power cost, unit capacity cost, charge and discharge efficiency, designed service life of the energy storage, and historical electricity price data in normal and emergency scenarios.

2. The energy storage capacity planning method considering power supply in emergency scenarios according to claim 1, wherein The constraints of the energy storage capacity optimization model include the energy storage charge and discharge power constraint, the energy storage charge and discharge energy constraint, and the energy storage power demand constraint.

3. A method for planning energy storage capacity considering power supply in emergency scenarios according to claim 2, characterized in that, Among them, The expression of the energy storage charge and discharge power constraint is: ， ， ， ， Wherein, is the charging power of the energy storage participating in the normal scenario at time t, is the discharging power of the energy storage participating in the emergency scenario at time t, is the power configured for the energy storage, is a 0-1 variable; Use the big M method to linearize the energy storage charge and discharge power constraint. The expression is: ， ， In the formula, M is an infinitely large number; The expression of the energy storage charge and discharge energy constraint is: ， ， ， ， ， Wherein, is the energy state of the energy storage participating in the normal scenario at time t, is the energy state of the energy storage participating in the normal scenario at time t-1, is the discharge power of the energy storage participating in the emergency scenario at time t, is the charging power of the energy storage participating in the emergency scenario at time t, is the energy state of the energy storage participating in the emergency scenario at time t-1, is the energy state of the energy storage participating in the emergency scenario at time t, is the capacity percentage of the energy storage participating in the normal and emergency scenarios, and is the capacity percentage of the energy storage participating in the emergency scenario, is the configured capacity of the energy storage, is the SOC value of the energy storage in the normal and emergency scenarios, is the self-discharge rate, is the charging efficiency, is the discharge efficiency, is the scenario in which the energy storage participates is the SOC value at time t when the energy storage participates in the scenario, is the lower limit of the SOC of the energy storage, is the upper limit of the SOC of the energy storage, is the SOC value of the energy storage at the first moment of the operating day, is the SOC value of the energy storage at the last moment of the operating day; The expression of the energy storage power demand constraint is: ， In the formula, The emergency power supply demand power at time t.

4. A energy storage capacity planning system considering power supply in emergency scenarios, characterized in that, Including: An acquisition module configured to obtain annual operation data and construct an energy scheduling optimization model for energy storage in normal scenarios and emergency power supply scenarios based on the annual operation data; A construction module configured to establish an energy storage capacity optimization model considering emergency power supply scenarios according to the energy scheduling optimization model, considering the configuration parameters of the energy storage and the uncertainty brought about by the fluctuations of grid operation parameters. Among them, the expression of the objective function of the energy storage capacity optimization model is: ， ， In the formula, is the total objective function, is the time period, is the contribution of energy storage to the system operation efficiency in normal scenarios and emergency power supply scenarios, is the risk aversion index, is the comprehensive uncertainty of energy storage in normal scenarios and emergency power supply scenarios, is the conversion coefficient, is the unit power cost of energy storage, is the power configured for energy storage, is the unit capacity cost of energy storage, is the capacity configured for energy storage, is the discount rate, is the designed service life of energy storage after conversion; Among them, in the normal scenario, the energy storage charges during the peak load period and discharges during the low load period, which can shave peaks and fill valleys for the system. Then, the contribution of the energy storage to the system operation efficiency in the normal scenario is: ， Wherein, The contribution to the system operation efficiency in the normal scenario, is the charging power of the energy storage participating in the normal scenario at time t, is the discharging power of the energy storage participating in the emergency scenario at time t, is the peak-valley electricity price; In the emergency power supply scenario, the energy storage responds to the emergency power supply demand to ensure user power supply. Then, the contribution of the energy storage to the system operation efficiency in the emergency power supply scenario is: ， wherein, is the contribution of energy storage to the system operation efficiency in the emergency power supply scenario, is the unit system benefit of the emergency power supply scenario, is the discharge power of energy storage in the emergency scenario; Calculate the contribution of the energy storage to the system operation efficiency in normal scenarios and emergency power supply scenarios. The expression is: ， Calculate the expression of the comprehensive uncertainty of the energy storage in normal scenarios and emergency power supply scenarios: ， ， Wherein, and are the uncertainties of the energy storage participating in the normal scenario and the emergency power supply scenario at time t, respectively. and are the percentages of the energy storage participating in the normal scenario and the emergency power supply scenario at time t, respectively. is the correlation coefficient between the normal scenario and the emergency power supply scenario at time t. is the percentage of the energy storage participating in scenario at time t. is the uncertainty of the energy storage participating in scenario at time t. is the percentage of the energy storage participating in scenario at time t. is the correlation coefficient between scenario and scenario at time t. is the uncertainty of the energy storage participating in scenario at time t. is the sequence composed of the electricity prices of the normal scenario throughout the year at time t. is the sequence composed of the unit benefits of the emergency power supply scenario throughout the year at time t. is the variance function. is the covariance function. An output module configured to input the target parameters of the energy storage into the energy storage capacity optimization model, and the energy storage capacity optimization model outputs the energy storage capacity planning result. The target parameters include the unit power cost, unit capacity cost, charge and discharge efficiency, designed service life of the energy storage, and historical system operation data in normal and emergency scenarios.

5. An electronic device, characterized in that, Including: At least one processor, and a memory communicatively connected to the at least one processor, wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the method according to any one of claims 1 to 3.

6. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by a processor, the method according to any one of claims 1 to 3 is implemented.

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