Energy storage capacity configuration method considering regional power grid toughness and distributed photovoltaic consumption

Abstract

The invention relates to the technical field of energy storage capacity planning, in particular to an energy storage capacity configuration method considering regional power grid toughness and distributed photovoltaic consumption, which comprises the following steps: S1, acquiring system data of a researched regional power grid; s2, analyzing the wind power characteristic, the photovoltaic characteristic and the load characteristic of the regional power grid under the typical load day, and solving the chargeable electric quantity and the electric quantity needing to be discharged of the regional power grid; s3, multiple constraint conditions are established, and energy storage configuration capacity is obtained through calculation according to the multiple constraint conditions; and S4, defining and solving the toughness index of the regional power grid, and evaluating the capability of the regional power grid for resisting system disturbance after configuration according to the energy storage configuration capacity obtained in the S3 under the condition that the main transformer N-1 of the transformer substation has a main transformer N-1 fault. According to the method, the regional power grid toughness index is defined and used for representing the supporting capacity of the transformer substation main transformer on the regional power grid after energy storage is configured under the main transformer N-1 fault condition, and a scientific basis is provided for energy storage capacity planning.

Description

Technical Field

[0001] The present invention relates to the technical field of energy storage capacity planning, and in particular to an energy storage capacity configuration method that takes into account regional power grid resilience and distributed photovoltaic consumption. Background Art

[0002] In recent years, with the continuous increase in the penetration rate of wind and solar power in distribution networks, the rapid expansion of renewable energy and the reduction in the proportion of non-clean energy have improved the green and low-carbon level of the energy industry. However, at the same time, due to the typical uncertainty of renewable energy output, the power grid with a high proportion of renewable energy access will face many challenges such as increased system load fluctuations, insufficient flexible adjustment of resource allocation, and difficulty in balancing source and load scheduling.

[0003] Due to the intermittent and volatile characteristics of distributed photovoltaics, as the proportion of access to the grid increases, the grid's ability to absorb distributed photovoltaics and the quality of grid power are facing huge challenges. At the same time, the high proportion of distributed photovoltaic access poses a threat to the normal and safe operation of the grid. Distributed photovoltaics are a distributed resource that can increase the flexibility, elasticity, and flexibility of the energy supply and demand system and serve the dynamic supply and demand balance of the energy consumption system. For photovoltaic power generation, its output characteristics are as follows: high output in summer and low output in winter; high output during the day and no output at night; high output on sunny days and low output on rainy days.

[0004] The output characteristics of distributed photovoltaics are highly volatile, which places higher demands on energy storage capacity planning. In addition, the current energy storage capacity planning lacks an indicator for judging the system's ability to resist disturbances. It is unclear how well the system can resist disturbances after being configured according to the planned energy storage capacity. Therefore, there is an urgent need for an energy storage capacity configuration method that takes into account the resilience of the regional power grid and the absorption of distributed photovoltaics. Summary of the invention

[0005] The present invention provides a method for configuring energy storage capacity taking into account regional power grid resilience and distributed photovoltaic absorption, so as to solve the technical problems mentioned in the background technology.

[0006] To achieve the above object, the technical solution of the present invention is achieved as follows:

[0007] The present invention provides a method for configuring energy storage capacity taking into account regional power grid resilience and distributed photovoltaic consumption, comprising the following steps:

[0008] S1. Collect and obtain the system data of the power grid in the studied area;

[0009] S2. Analyze the wind power characteristics, photovoltaic characteristics, and load characteristics of the regional power grid on a typical load day, and solve the chargeable power and discharge power required by the regional power grid;

[0010] S3. Establish multiple constraint conditions, and then calculate the energy storage configuration capacity based on the multiple constraint conditions;

[0011] S4. Define the regional power grid resilience index, and solve the regional power grid resilience index based on the chargeable power and the required discharge power. Then, use the regional power grid resilience index to evaluate the ability of the regional power grid to resist system disturbances after the energy storage configuration capacity obtained in S3 is configured in the event of a failure of the main transformer N-1 of the substation main transformer.

[0012] Furthermore, the S2 specifically includes the following steps:

[0013] S21. Analyze the wind power characteristics, photovoltaic characteristics, and load characteristics of the regional power grid on a typical load day;

[0014] S22. Then, a regional power supply and demand balance equation is established, and based on the regional power supply and demand balance equation, the chargeable power and the required discharge power of the regional power grid are solved.

[0015] Furthermore, the photovoltaic characteristics in S21 are specifically as follows:

[0016] The increase in distributed photovoltaic output under the midday mode will lead to a large amount of electricity surplus, so it is necessary to consider storing the excess electricity by configuring energy storage; at the same time, the output characteristics of distributed photovoltaics are different in different seasons throughout the year. The output coefficient of photovoltaics and load is the highest in the summer and the lowest in the winter; photovoltaic power generation is concentrated in the daytime, while the load output is relatively dispersed throughout the day.

[0017] Furthermore, the regional power supply and demand balance equation in S21 is as follows:

[0018] P sub (t)+P PV (t)+P wind (t) = P load (t)+P ESS (t) (1)

[0019] Among them, P sub (t) represents the power supply of the substation in the regional power grid, P PV (t) represents the photovoltaic output in the regional power grid, P wind (t) represents the wind power output in the regional power grid, P load (t) represents the regional power grid load; P ESS (t) represents the energy storage power in the regional power grid. ESS (t)≥0, indicating energy storage charging. ESS When (t)<0, it indicates energy storage discharge.

[0020] Furthermore, the S3 specifically includes the following steps:

[0021] S31. Establish peak load power support constraints, energy storage charge state constraints, main transformer N-1 fault constraints, energy storage discharge power constraints, energy storage charging power constraints, and substation main transformer overload constraints;

[0022] S32, then calculate the energy storage configuration capacity based on all constraints obtained in S31 and the regional power supply and demand balance relationship.

[0023] Furthermore, the peak load power quantity support constraint in S31 is specifically:

[0024] In order to support peak load electricity, energy storage must not only meet the power demand at peak load times, but also have sufficient electricity to be charged, that is, a power source of a certain scale is required to provide the required electricity;

[0025] The energy storage charge state constraint is specifically:

[0026] The real-time state of charge of the energy storage within a day needs to be between the lower limit constraint of the energy storage state of charge and the upper limit constraint of the energy storage state of charge, and the lower limit constraint of the energy storage state of charge should be equal to the state of charge at 0:00 and 23:00 of the energy storage within each cycle;

[0027] The main transformer N-1 fault constraint is specifically:

[0028] Especially when setting a high peak load period, it is necessary to consider the failure of the main transformer N-1 of the substation in the regional power grid, and to meet the power supply demand of the load without causing load shedding;

[0029] The energy storage discharge power constraint is specifically: the energy storage discharge power must meet the power shortage;

[0030] The energy storage charging power constraint is specifically:

[0031] During the lunch hour, the energy storage charging power must meet the power surplus of the regional power grid;

[0032] The substation main transformer overload constraint is specifically:

[0033] During the lunch and evening hours, after considering the energy storage charging, the main transformer of the substation in the regional power grid is not overloaded when it is connected to the grid; when the transformer power exceeds 80% of its rated power, the main transformer of the substation is considered to be overloaded.

[0034] Furthermore, the peak load power quantity support constraint is expressed by a formula, which is as follows:

[0035] ΔP(t)=P sub (t)+P PV (t)+P wind (t)-Pload (t) (2)

[0036]

[0037] Among them, ΔP(t) represents the power surplus or deficit of the regional power grid, Δt represents the time period, and δ represents the energy storage efficiency; Indicates the amount of electricity stored by the system's surplus electricity through energy storage charging; It indicates the amount of power that is insufficient in the system and is discharged through energy storage to support the power demand of the system during the set peak load period;

[0038] The energy storage charge state constraint is expressed by a formula, as follows:

[0039] SOC min ≤SOC(t)≤SOC max (4)

[0040]

[0041] Among them, SOC min Represents the lower limit constraint of the energy storage state of charge; SOC max Indicates the upper limit of the energy storage charge state; SOC(t) indicates the real-time charge state of the energy storage within one day, which is a function of time t; S ESS Represents the capacity of the energy storage system.

[0042] Furthermore, the main transformer N-1 fault constraint is expressed by a formula, which is as follows:

[0043]

[0044] in, Indicates the power surplus in the regional power grid from 9:00 a.m. to 15:00 p.m. Indicates the power shortage in the regional power grid during the period from 6pm to 12am; P sub，N-1 (t) represents the power supply that can be provided by the substation after the main transformer N-1 of the substation in the regional power grid;

[0045] The energy storage discharge power constraint is expressed by a formula, which is as follows:

[0046] P ESS (t) min <P sub，N-1 (t)+P wind (t)-P load (t) (7)

[0047] Where P ESS (t) min Indicates the minimum discharge power of energy storage.

[0048] Furthermore, the energy storage charging power constraint is expressed by a formula, which is as follows:

[0049] P ESS (t) max ≥P sub (t)+P PV (t)+P wind (t)-P load (t) (8)

[0050] Where P ESS (t) max Indicates the maximum charging power of energy storage;

[0051] The overload constraint of the main transformer of the substation is expressed by a formula, which is as follows:

[0052] P PV (t)+P wind (t)-P load (t)-P ESS (t) max ≤0.8P sub，N (9)

[0053] Where P sub，N Indicates the rated power of the main transformer of the substation.

[0054] Furthermore, the regional power grid resilience indicators are as follows:

[0055]

[0056] Among them, W ESS，charge Represents the energy storage charging capacity, that is, the rechargeable capacity of the regional power grid obtained by S2, W ESS，discharge represents the energy storage discharge capacity, that is, the required discharge capacity of the regional power grid obtained by S2; · represents the multiplication sign.

[0057] Beneficial effects of the present invention:

[0058] The present invention provides a method for configuring energy storage capacity that takes into account the resilience of regional power grids and the absorption of distributed photovoltaic power. The energy storage capacity can satisfy the storage of distributed photovoltaic surplus electricity through charging, and can also meet the power demand at peak load times. The present invention is based on the actual operation of the power grid. Considering the failure of the main transformer N-1 of the substation in the regional power grid, the energy storage capacity can meet the power supply demand of the load without causing load shedding.

[0059] The present invention also defines a regional power grid resilience index, which is used to characterize the support capacity of the regional power grid and the ability to resist system disturbances after the regional power grid is configured according to the energy storage configuration capacity obtained by S3 when the main transformer N-1 of the substation main transformer fails, providing a scientific basis for energy storage capacity planning. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] Figure 1 It is a flowchart of the present invention;

[0061] Figure 2 1 is a graph showing the daily power generation characteristics of distributed photovoltaic power plants in typical four seasons in an embodiment of the present invention, wherein (a) is a graph showing the daily power generation characteristics of distributed photovoltaic power plants in a typical spring scenario; (b) is a graph showing the daily power generation characteristics of distributed photovoltaic power plants in a typical summer scenario; (c) is a graph showing the daily power generation characteristics of distributed photovoltaic power plants in a typical autumn scenario; and (d) is a graph showing the daily power generation characteristics of distributed photovoltaic power plants in a typical winter scenario;

[0062] Figure 3 This is a curve diagram of load, photovoltaic output, and new energy output of the regional power grid on a typical load day in winter in an embodiment of the present invention. DETAILED DESCRIPTION

[0063] In order to facilitate the understanding of the present invention, the present invention will be described more fully below with reference to the relevant drawings. Preferred embodiments of the present invention are provided in the drawings. However, the present invention can be implemented in many other different forms and is not limited to the embodiments described herein. On the contrary, the purpose of providing these embodiments is to make the understanding of the disclosure of the present invention more thorough and comprehensive.

[0064] Reference Figure 1 The embodiment of the present application provides a method for configuring energy storage capacity taking into account regional power grid resilience and distributed photovoltaic consumption, including the following steps:

[0065] S1. Collect and obtain the system data of the power grid in the studied area;

[0066] S2. Analyze the wind power characteristics, photovoltaic characteristics, and load characteristics of the regional power grid on a typical load day, and solve the chargeable power and discharge power required by the regional power grid;

[0067] S3. Establish multiple constraint conditions, and then calculate the energy storage configuration capacity based on the multiple constraint conditions;

[0068] S4. Define the regional power grid resilience index, and solve the regional power grid resilience index based on the chargeable power and the required discharge power. Then, use the regional power grid resilience index to evaluate the ability of the regional power grid to resist system disturbances after the energy storage configuration capacity obtained in S3 is configured in the event of a failure of the main transformer N-1 of the substation main transformer.

[0069] In some embodiments, S2 specifically includes the following steps:

[0070] S21. Analyze the wind power characteristics, photovoltaic characteristics, and load characteristics of the regional power grid on a typical load day;

[0071] S22. Then, a regional power supply and demand balance equation is established, and based on the regional power supply and demand balance equation, the chargeable power and the required discharge power of the regional power grid are solved.

[0072] In some embodiments, the photovoltaic characteristics in S21 are specifically as follows:

[0073] The increase in distributed photovoltaic output under the noon mode will lead to a large amount of power surplus, so it is necessary to consider storing the excess power by configuring energy storage; refer to Figure 2 , Figure 2 The following is the daily output characteristic curve of distributed photovoltaic power generation in typical four seasons. The output characteristics of distributed photovoltaic power generation in different seasons are different. Figure 2 It can be seen that the output coefficient of photovoltaic and load in summer is the highest in the whole year. Figure 2 As shown in Figure (b), the lowest temperature is in winter. Figure 2 As shown in Figure (d), photovoltaic power generation is concentrated in the daytime, while the load output is relatively dispersed throughout the day. Therefore, there is a relatively obvious time sequence characteristic between distributed photovoltaic power generation and load.

[0074] In some embodiments, the regional power supply and demand balance equation in S21 is specifically as follows:

[0075] P sub (t)+P PV (t)+P wind (t) = P load (t)+P ESS (t) (1)

[0076] Among them, P sub (t) represents the power supply of the substation in the regional power grid, P PV (t) represents the photovoltaic output in the regional power grid, P wind (t) represents the wind power output in the regional power grid, P load (t) represents the regional power grid load; P ESS (t) represents the energy storage power in the regional power grid. ESS (t)≥0, indicating energy storage charging. ESS When (t) < 0, it indicates energy storage discharge. The above variables are all functions of time t.

[0077] In some embodiments, S3 specifically includes the following steps:

[0078] S31. Establish peak load power support constraints, energy storage charge state constraints, main transformer N-1 fault constraints, energy storage discharge power constraints, energy storage charging power constraints, and substation main transformer overload constraints;

[0079] S32, then calculate the energy storage configuration capacity based on all constraints obtained in S31 and the regional power supply and demand balance relationship.

[0080] In some embodiments, the peak load power support constraint in S31 is specifically as follows: to meet the peak load power support, the energy storage must not only meet the power demand at the peak load moment, but also have sufficient power to be charged, that is, a power source of a certain scale that can provide the required power is required;

[0081] The peak load power quantity support constraint is expressed by a formula, which is as follows:

[0082] ΔP(t)=P sub (t)+P PV (t)+P wind (t)-P load (t) (2)

[0083]

[0084] Among them, ΔP(t) represents the power surplus or deficit of the regional power grid, Δt represents the time period, and since the analysis is performed hourly, Δt = 1h; δ represents the energy storage efficiency, which is usually between 0.7 and 0.9; Indicates the amount of electricity stored by the system's surplus electricity through energy storage charging; It indicates the amount of power that is discharged from the energy storage system to support the power demand during the peak load period of the system.

[0085] In some embodiments, the energy storage charge state constraint is specifically: the real-time charge state of the energy storage within one day needs to be between the lower limit constraint of the energy storage charge state and the upper limit constraint of the energy storage charge state, and the lower limit constraint of the energy storage charge state should be ensured to be equal to the charge state of the energy storage at 0 o'clock and 23 o'clock within one day in each cycle; that is, SOC(0)=SOC(23)=SOC min , where SOC(0) represents the state of charge at 0 o'clock in a day; SOC(23) represents the state of charge at 23 o'clock in a day;

[0086] The energy storage charge state constraint is expressed by a formula, as follows:

[0087] SOC min ≤SOC(t)≤SOC max (4)

[0088]

[0089] Among them, SOC min Represents the lower limit constraint of the energy storage state of charge, which is usually 0.2; SOC max It indicates the upper limit of the energy storage state of charge, which is usually 1; SOC(t) indicates the real-time state of charge of the energy storage within one day, which is a function of time t; S Ess Represents the capacity of the energy storage system.

[0090] In some embodiments, the main transformer N-1 fault constraint is specifically: when analyzing the actual operation of the power grid, especially when setting a high peak load period, the peak values ​​below the set high peak value are all peak values. When the main transformer N-1 of the substation in the regional power grid fails, it is necessary to meet the power supply demand of the load without causing load shedding;

[0091] The main transformer N-1 fault constraint is expressed by a formula, which is as follows:

[0092]

[0093] in, It shows the power surplus in the regional power grid during the period of high photovoltaic output from 9:00 a.m. to 15:00 p.m. Indicates the power shortage in the regional power grid during the peak load period from 6pm to 12am; P sub,N-1 (t) represents the power supply that can be provided by the substation after the main transformer N-1 of the substation in the regional power grid.

[0094] In some embodiments, the energy storage discharge power constraint is specifically: the energy storage discharge power must meet the power shortage;

[0095] The energy storage discharge power constraint is expressed by a formula, which is as follows:

[0096] P ESS (t) min <P sub,N-1 (t)+P wind (t)-P load (t) (7)

[0097] Where P ESS (t) min Indicates the minimum discharge power of energy storage.

[0098] In some embodiments, the energy storage charging power constraint is specifically: during the midday period when the distributed photovoltaic output power is relatively large, the energy storage charging power must meet the power surplus of the regional power grid;

[0099] The energy storage charging power constraint is expressed by a formula, which is as follows:

[0100] P ESS (t) max ≥P sub (t)+P PV (t)+P wind (t)-P load (t) (8)

[0101] Where P ESS (t) max Indicates the maximum charging power of energy storage.

[0102] In some embodiments, the substation main transformer overload constraint is specifically: during the midday period when the distributed photovoltaic output power is relatively large and the evening period when the output power is low, after considering the energy storage charging, the substation main transformer in the regional power grid is connected to the grid without overload; when the transformer power exceeds 80% of its rated power, the substation main transformer is considered to be overloaded. Midday is 12:00-14:00 noon; evening is 19:00-21:00 pm.

[0103] The overload constraint of the main transformer of the substation is expressed by a formula, which is as follows:

[0104] P PV (t)+P wind (t)-P load (t)-P ESS (t) max ≤0.8P sub,N (9)

[0105] Where P sub，N Indicates the rated power of the substation main transformer; when the transformer power exceeds 80% of its rated power, the substation main transformer is considered to be overloaded.

[0106] In some embodiments, the regional power grid resilience index in S4 is specifically as follows:

[0107]

[0108] Among them, W ESS，charge Represents the energy storage charging capacity, that is, the rechargeable capacity of the regional power grid obtained by S2, W ESS,discharge represents the energy storage discharge capacity, that is, the required discharge capacity of the regional power grid obtained by S2, and · represents the multiplication sign.

[0109] If the seasonal differences in distributed photovoltaic output are taken into account, the objective function F is established, and the objective function is shown as follows:

[0110] F=max(S ESS,spring , S ESS,summer , S ESS,autumn , S ESS，winter ) (13)

[0111] S ESS ≥2P ESS (t) max (14)

[0112] In the formula, S ESS Represents the energy storage configuration capacity, S ESS,spring represents the energy storage configuration capacity obtained based on the distributed photovoltaic output characteristics in spring and equations (1) to (9), S ESS，summer represents the energy storage configuration capacity obtained based on the summer distributed photovoltaic output characteristics and equations (1) to (9), S ESS,autumn represents the energy storage configuration capacity obtained based on the distributed photovoltaic output characteristics in autumn and equations (1) to (9), S ESS，winter It represents the energy storage configuration capacity obtained based on the winter distributed photovoltaic output characteristics and equations (1) to (9).

[0113] The following is an example for easier understanding:

[0114] Taking a 220 kV regional power grid in a provincial power grid rich in new energy as an example, the load, photovoltaic output, and new energy output curves of the regional power grid on a typical load day in winter are as follows: Figure 3 There is only one 220 kV substation in this area, which is powered by two 120 MVA main transformers.

[0115] According to the steps described in S2, it is calculated that under typical load days, the energy storage chargeable capacity is 129.297MWh and the maximum charging power is 73.738MW.

[0116] During the peak load period, when the main transformer is N-1, the required energy storage discharge power is 108.259MWh. Considering the energy storage conversion efficiency of 0.85, the charging power during the midday period with high photovoltaic output can meet the power demand during the peak load period. From the curve analysis, it can be seen that the maximum discharge power during the peak load period is 40.789MW.

[0117] Therefore, considering the conventional electrochemical energy storage configuration, the regional power grid energy storage configuration capacity is 150MWh. The regional power grid resilience index is calculated as shown in the following formula.

[0118]

[0119] Based on the above analysis of typical winter load days, it can be concluded that the regional power grid energy storage configuration capacity in spring is 86MWh, the regional power grid energy storage configuration capacity in summer is 118MWh, and the regional power grid energy storage configuration capacity in autumn is 96MWh.

[0120] Therefore, in summary, the energy storage configuration capacity of the regional power grid is 150MWh.

[0121] The regional power grid resilience index is equal to 2.16, which represents the ability of the regional power grid to resist system disturbances after being equipped with 150MWh of energy storage. The larger this value (regional power grid resilience index) is, the stronger the system's ability to resist disturbances is.

[0122] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be covered within the protection scope of the present invention. In addition, the technical solutions between the various embodiments of the present invention can be combined with each other, but it must be based on the ability of ordinary technicians in the field to implement. When the combination of technical solutions is contradictory or cannot be implemented, it should be considered that such a combination of technical solutions does not exist and is not within the protection scope of the present invention. Therefore, the protection scope of the present invention shall be based on the protection scope of the claims.

Claims

1. A method for configuring energy storage capacity considering regional power grid resilience and distributed photovoltaic consumption, characterized in that: The steps include: S1. Collect and obtain the system data of the power grid in the studied area; S2. Analyze the wind power characteristics, photovoltaic characteristics, and load characteristics of the regional power grid on a typical load day, and solve the chargeable power and discharge power required by the regional power grid; S3. Establish multiple constraint conditions, and then calculate the energy storage configuration capacity based on the multiple constraint conditions; S4. Define the regional power grid resilience index, and solve the regional power grid resilience index based on the chargeable power and the required discharge power. Then, use the regional power grid resilience index to evaluate the ability of the regional power grid to resist system disturbances after the energy storage configuration capacity obtained in S3 is configured in the event of a failure of the main transformer N-1 of the substation main transformer.

2. The energy storage capacity configuration method according to claim 1, characterized in that: The S2 specifically includes the following steps: S21. Analyze the wind power characteristics, photovoltaic characteristics, and load characteristics of the regional power grid on a typical load day; S22. Then, a regional power supply and demand balance equation is established, and based on the regional power supply and demand balance equation, the chargeable power and the required discharge power of the regional power grid are solved.

3. The energy storage capacity configuration method according to claim 2, characterized in that: The photovoltaic characteristics in S21 are as follows: The increase in distributed photovoltaic output under the midday mode will lead to a large amount of electricity surplus, so it is necessary to consider storing the excess electricity by configuring energy storage; at the same time, the output characteristics of distributed photovoltaics are different in different seasons throughout the year. The output coefficient of photovoltaics and load is the highest in the summer and the lowest in the winter; photovoltaic power generation is concentrated in the daytime, while the load output is relatively dispersed throughout the day.

4. The energy storage capacity configuration method according to claim 2, characterized in that: The regional power supply and demand balance equation in S21 is as follows: P sub (t)+P PV (t)+P wind (t)=P load (t)+P ESS (t) (1) Among them, P sub (t) represents the power supply of the substation in the regional power grid, P PV (t) represents the photovoltaic output in the regional power grid, P wind (t) represents the wind power output in the regional power grid, P load (t) represents the regional power grid load; P ESS (t) represents the energy storage power in the regional power grid. ESS (t)≥0, indicating energy storage charging. ESS When (t)<0, it indicates energy storage discharge.

5. The energy storage capacity configuration method according to claim 4, characterized in that: The S3 specifically includes the following steps: S31. Establish peak load power support constraints, energy storage charge state constraints, main transformer N-1 fault constraints, energy storage discharge power constraints, energy storage charging power constraints, and substation main transformer overload constraints; S32, then calculate the energy storage configuration capacity based on all constraints obtained in S31 and the regional power supply and demand balance relationship.

6. The energy storage capacity configuration method according to claim 5, characterized in that: The peak load power quantity support constraint in S31 is specifically: In order to support peak load electricity, energy storage must not only meet the power demand at peak load times, but also have sufficient electricity to be charged, that is, a power source of a certain scale is required to provide the required electricity; The energy storage charge state constraint is specifically: The real-time state of charge of the energy storage within a day needs to be between the lower limit constraint of the energy storage state of charge and the upper limit constraint of the energy storage state of charge, and the lower limit constraint of the energy storage state of charge should be equal to the state of charge at 0:00 and 23:00 of the energy storage within each cycle; The main transformer N-1 fault constraint is specifically: Especially when setting high peak load periods, it is necessary to consider that when the main transformer N-1 of the substation in the regional power grid fails, the power supply demand of the load needs to be met without causing load shedding; The energy storage discharge power constraint is specifically: the energy storage discharge power must meet the power shortage; The energy storage charging power constraint is specifically: During the lunch hour, the energy storage charging power must meet the power surplus of the regional power grid; The substation main transformer overload constraint is specifically: During the lunch and evening hours, after considering the energy storage charging, the main transformer of the substation in the regional power grid is not overloaded when it is connected to the grid; when the transformer power exceeds 80% of its rated power, the main transformer of the substation is considered to be overloaded.

7. The energy storage capacity configuration method according to claim 5, characterized in that: The peak load power quantity support constraint is expressed by a formula, which is as follows: ΔP(t)=P sub (t)+P PV (t)+P wind (t)-P load (t) (2) Among them, ΔP(t) represents the power surplus or deficit of the regional power grid, Δt represents the time period, and δ represents the energy storage efficiency; Indicates the amount of electricity stored by the system's surplus electricity through energy storage charging; It indicates the amount of power that is insufficient in the system and is discharged through energy storage to support the power demand of the system during the set peak load period; The energy storage charge state constraint is expressed by a formula, as follows: SOC min ≤SOC(t)≤SOC max (4) Among them, SOC min Represents the lower limit constraint of the energy storage state of charge; SOC max Indicates the upper limit of the energy storage charge state; SOC(t) indicates the real-time charge state of the energy storage within one day, which is a function of time t; S ESS Represents the capacity of the energy storage system.

8. The energy storage capacity configuration method according to claim 7, characterized in that: The main transformer N-1 fault constraint is expressed by a formula, which is as follows: in, Indicates the power surplus in the regional power grid from 9:00 a.m. to 15:00 p.m. Indicates the power shortage in the regional power grid during the period from 6pm to 12am; P sub,N-1 (t) represents the power supply that can be provided by the substation after the main transformer N-1 of the substation in the regional power grid; The energy storage discharge power constraint is expressed by a formula, which is as follows: P ESS (t) min <P sub,N-1 (t)+P wind (t)-P load (t) (7) Where P ESS (t) min Indicates the minimum discharge power of energy storage.

9. The energy storage capacity configuration method according to claim 8, characterized in that: The energy storage charging power constraint is expressed by a formula, which is as follows: P ESS (t) max ≥P sub (t)+P PV (t)+P wind (t)-P load (t) (8) Where P ESS (t) max Indicates the maximum charging power of energy storage; The overload constraint of the main transformer of the substation is expressed by a formula, which is as follows: P PV (t)+P wind (t)-P load (t)-P ESS (t) max ≤0.8P sub,N (9) Where P sub，N Indicates the rated power of the main transformer of the substation.

10. The energy storage capacity configuration method according to claim 9, characterized in that: The specific indicators of regional power grid resilience are as follows: Among them, W ESS，charge Represents the energy storage charging capacity, that is, the rechargeable capacity of the regional power grid obtained by S2, W Ess,discharge represents the energy storage discharge capacity, that is, the required discharge capacity of the regional power grid obtained by S2, and · represents the multiplication sign.

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