A power transmission network planning method and system considering wind power reliable reserve capacity

Abstract

The present disclosure relates to a power transmission network planning method and system considering wind power reliable reserve capacity, belonging to the technical field of power grid planning. The power transmission network planning method considering wind power reliable reserve capacity comprises: calculating wind power reliable reserve for quantifying the reliable reserve capacity that a wind farm can provide under different operation modes; based on the wind power reliable reserve, constructing an objective function aiming to minimize the total cost of power transmission network planning, and constructing constraint conditions, constructing a power transmission network planning model considering wind power reserve capacity based on the objective function and the constraint conditions; performing linearization analysis and solving on the power transmission network planning model to obtain an optimal power transmission network planning scheme. The present disclosure quantifies the reserve supply capacity of wind power under different operation modes on the premise of meeting the system operation safety constraint, thereby providing stable and controllable reserve resources for the power system and improving the system dispatching flexibility and the consumption level of new energy resources.

Description

Technical Field

[0001] This disclosure belongs to the field of power grid planning technology, and in particular relates to a transmission network planning method and system that takes into account the reliable backup capability of wind power. Background Technology

[0002] With the rapid development of new energy sources, especially wind power, the proportion of wind power in the power system is gradually increasing. However, wind power output is volatile and uncertain, and its high proportion of integration places higher demands on the dispatch flexibility and operational reliability of the power system. Traditional transmission network planning is mainly based on load growth and power source layout, ignoring the uncertainty of new energy output and its potential in system reserves. This leads to the underutilization of wind power in some areas or insufficient system reserve capacity under high load conditions, thus affecting the safe and stable operation of the power grid.

[0003] Some studies have considered incorporating the uncertainty of wind power into power grid planning, but most methods only use scenario-based methods and robust optimization to model wind power fluctuations. They have failed to fully explore the backup potential of wind power at the operational level, especially the functions of wind power load reduction operation and providing frequency regulation and peak shaving backup capabilities have not been effectively incorporated into the planning model.

[0004] Therefore, it is necessary to provide a new transmission network planning method and system that takes into account the reliable backup capability of wind power to solve the above-mentioned technical problems. Summary of the Invention

[0005] The purpose of this disclosure is to provide a transmission network planning method and system that takes into account the reliable backup capability of wind power in order to solve the above-mentioned problems.

[0006] This disclosure achieves the above objectives through the following technical solutions:

[0007] A power grid planning method that considers the reliable backup capacity of wind power includes the following steps:

[0008] The reliable backup capacity of wind power is estimated to quantify the reliable backup capacity that a wind farm can provide under different operating modes.

[0009] Based on reliable wind power backup, an objective function is constructed to minimize the total cost of transmission network planning, and constraints are constructed. Based on the objective function and the constraints, a transmission network planning model considering wind power backup capacity is constructed.

[0010] The transmission network planning model is linearized and solved to obtain the optimal transmission network planning scheme.

[0011] As a further optimization of this disclosure, the wind power reliable reserve used to quantify the reliable reserve capacity that a wind farm can provide under different operating modes is calculated, including:

[0012] Analysis of wind power reduced output operation mode, and calculation of wind power reserve capacity based on the obtained wind power dispatch value;

[0013] Quantify the reliability of wind power backup capacity, so that the reliable backup provided by wind power can be quantified through backup reliability indicators;

[0014] Calculate wind power reliable backup based on backup reliability indicators.

[0015] As a further optimization of this disclosure, the analysis of wind power reduced output operation mode, based on the obtained wind power dispatch values, calculates wind power reserve capacity, including:

[0016] The expression for calculating the interval between the lower limit of the disturbance range and the predicted wind power output value, and the interval below the lower limit of the disturbance range, represents the reserve capacity of the wind power dispatch value under different operating intervals.

[0017] As a further optimization of this disclosure, the total cost of the power transmission network planning includes the investment cost of the power transmission lines, the system reserve cost, the system reliability cost, and the system operating cost.

[0018] As a further optimization of this disclosure, the constraints include line construction constraints, node power balance constraints, DC power flow constraints, generator constraints, and reserve capacity constraints.

[0019] As a further optimization of this disclosure, the transmission network planning model is linearized and solved to obtain the optimal transmission network planning scheme, including:

[0020] The nonlinear terms in the power transmission network planning model are linearized, and the planning model is converted into a mixed integer linear programming model, which is then solved using a solver.

[0021] As a further optimization of this disclosure, the linearization process includes: performing piecewise linearization on the integral expression of wind power reliable backup and the quadratic term of unit operating cost.

[0022] A power grid planning system that considers the reliable backup capability of wind power includes:

[0023] The wind power reliable backup calculation module is used to calculate the reliable backup capacity that a wind farm can provide under different operating modes.

[0024] The planning model construction module is used to construct an objective function that minimizes the total cost of transmission network planning based on wind power reliable backup, and to construct constraints. Based on the objective function and the constraints, a transmission network planning model that considers wind power backup capacity is constructed.

[0025] The model solving module is used to perform linearization analysis and solve the power transmission network planning model to obtain the optimal power transmission network planning scheme.

[0026] As a further optimization of this disclosure, the wind power reliable reserve calculation module calculates the wind power reliable reserve used to quantify the reliable reserve capacity that a wind farm can provide under different operating modes, including:

[0027] Analysis of wind power reduced output operation mode, and calculation of wind power reserve capacity based on the obtained wind power dispatch value;

[0028] Quantify the reliability of wind power backup capacity, so that the reliable backup provided by wind power can be quantified through backup reliability indicators;

[0029] Calculate wind power reliable backup based on backup reliability indicators.

[0030] As a further optimization of this disclosure, the analysis of wind power reduced output operation mode, based on the obtained wind power dispatch values, calculates wind power reserve capacity, including:

[0031] The expression for calculating the interval between the lower limit of the disturbance range and the predicted wind power output value, and the interval below the lower limit of the disturbance range, represents the reserve capacity of the wind power dispatch value under different operating intervals.

[0032] As a further optimization of this disclosure, the total cost of the power transmission network planning includes the investment cost of the power transmission lines, the system reserve cost, the system reliability cost, and the system operating cost.

[0033] As a further optimization of this disclosure, the constraints include line construction constraints, node power balance constraints, DC power flow constraints, generator constraints, and reserve capacity constraints.

[0034] As a further optimization of this disclosure, the model solving module performs linearization analysis and solution on the transmission network planning model to obtain the optimal transmission network planning scheme, including:

[0035] The nonlinear terms in the power transmission network planning model are linearized, and the planning model is converted into a mixed integer linear programming model, which is then solved using a solver.

[0036] As a further optimization of this disclosure, the linearization process includes: performing piecewise linearization on the integral expression of wind power reliable backup and the quadratic term of unit operating cost.

[0037] An electronic device includes a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus;

[0038] Memory, used to store computer programs;

[0039] The processor is used to execute the program stored in the memory to implement the power grid planning method that takes into account the reliable backup capability of wind power.

[0040] A computer-readable storage medium storing a computer program that, when executed by a processor, implements the aforementioned transmission network planning method considering wind power reliable backup capability.

[0041] The beneficial effects of this disclosure are as follows:

[0042] This disclosure comprehensively considers the uncertainty of wind power output and the output recovery capability after wind power load reduction. Under the premise of meeting the system operation safety constraints, it quantifies the backup supply capacity of wind power under different operating modes, thereby providing stable and controllable backup resources for the power system and improving the system dispatch flexibility and the absorption level of new energy resources.

[0043] This disclosure addresses the issue of reserve coordination in transmission network planning under high-proportion wind power integration. It constructs a cost-benefit balance optimization model with the objective of minimizing line construction costs, system operating costs, and reserve supply costs. Based on a comprehensive evaluation of wind power reserve capacity, this model achieves synergistic optimization of wind power utilization and system reserve resource allocation, thereby improving wind power absorption, enhancing system operation flexibility and reliability, and bringing better economic operating results. Attached Figure Description

[0044] Figure 1 This is a flowchart of a method in an embodiment of this disclosure;

[0045] Figure 2 This is a system structure block diagram of an embodiment of this disclosure;

[0046] Figure 3 This is a block diagram of the device structure in an embodiment of this disclosure. Detailed Implementation

[0047] The present application will now be described in further detail with reference to the accompanying drawings. It should be noted that the following specific embodiments are only used to further illustrate the present application and should not be construed as limiting the scope of protection of the present application. Those skilled in the art can make some non-essential improvements and adjustments to the present application based on the above application content.

[0048] like Figure 1 As shown, a power grid planning method considering the reliable backup capacity of wind power includes the following steps:

[0049] S1. Calculate the reliable backup capacity of wind power to quantify the reliable backup capacity that a wind farm can provide under different operating modes, specifically including:

[0050] Analysis of S1.1 Wind Power Reduced Output Operation Mode:

[0051] Wind turbines can provide a margin for active power adjustment by actively reducing the turbine output dispatch value. This margin can be regarded as the active adjustment range of wind power output, that is, the wind power reserve capacity. However, wind power output has uncertainty and volatility, and the maximum output is described in a range, which means that it is impossible to cover all possible operating modes of wind power with a single mode. However, the wind power operating status can be described in segments according to the range in which the wind power dispatch value is located. When the wind power dispatch value is compressed to the range between the lower limit of the disturbance range and the wind power output prediction value as shown in Equation (1), the wind power reserve status is shown in Equations (2) and (3):

[0052] (1)

[0053] (2)

[0054] (3)

[0055] In the formula: This is the lower limit of the wind power disturbance range. This is the predicted value of wind power output. For wind power output dispatch value variables, Upward reserve provided for wind power Downward reserve provided for wind power Upward adjustment of reserves with reliability constraints for wind power. Downward reserve with reliability constraints provided for wind power This represents the lower limit of the controllable output of the wind turbine.

[0056] When the wind power dispatch value is compressed to the range below the lower limit of the disturbance range as shown in equation (4), the wind power standby status is shown in equations (5) and (6):

[0057] (4)

[0058] (5)

[0059] (6)

[0060] The two sets of formulas above represent the reserve capacity of wind power dispatch values ​​under different operating ranges. They indicate that the reserve provided by wind turbines is divided into two parts based on the reliability of the supply capacity: fully reliable reserve and partially reliable reserve. Therefore, further quantification and evaluation of the supply capacity of partially reliable reserve are needed.

[0061] S1.2 Quantification of wind power backup capacity reliability:

[0062] Since wind power output varies with wind speed, its backup power is not as reliable as that of thermal power units, and there are certain reliability issues. To measure the reliability of wind power backup in this situation, the concept of wind power backup reliability has been proposed. Reliability is usually measured by the expected load shedding. In this model, the value of wind power dispatch is limited by the expected load shedding, as shown in equation (7):

[0063] (7)

[0064] In the formula: EENS w,t Let be the expected load shedding of the wind turbine at time t. This represents the actual output of wind power.

[0065] Because wind power operates at reduced output, its output has the potential to rebound, meaning that wind power may provide more power than the dispatch value. This portion of power is considered as wind power reserve. Taking the upward dispatch reserve as an example, the wind power reserve that can be provided at any given time is as shown in equation (8):

[0066] (8)

[0067] In the formula: Let w be the actual backup value that the wind turbine can provide at time t; Let w be the output scheduling value of the wind turbine at time t.

[0068] However, reserves are a pre-set flexibility resource. This property of being coupled with the real-time output of wind power contradicts the nature of reserves. Furthermore, when the wind power output is less than the dispatch value, wind power obviously cannot provide reserves. Therefore, by combining the probability density function of wind power output, the reliable reserves provided by wind power can be quantified using expectation, as shown in Equation (9):

[0069] (9)

[0070] To calculate the expected value of the actual value of wind power reserves; Mathematical symbols used for performing expected calculations.

[0071] In summary, the reliable backup provided by wind power has been quantified through backup reliability indicators. This derivation supplements the nonlinear part of wind power backup in equations (3) and (5), which means that as long as equation (9) is integrally expressed and linearized, the corresponding backup constraints can be constructed and the backup cost can be calculated.

[0072] S1.3 Calculation method for reliable backup of wind power:

[0073] Since the probability density function of the reserve cannot be obtained directly, this characteristic can be estimated by piecewise linearization. Then, the wind power reserve can be quantitatively expressed as shown in equation (10):

[0074] (10)

[0075] In the formula: Let s be the segmentation point of the actual wind power output of wind turbine w at time t, and let s be the parameter; The probability that the actual wind power output is exactly the value at the segment point; is the probability calculation function; S is the set of segment points for wind power output scheduling values; s is the index of S; s' is the number of the nearest segment point to the left of the wind power output scheduling value.

[0076] By continuously reducing the distance between the segment points, it can be integrated, as shown in equation (11):

[0077] (11)

[0078] In the formula, x represents wind power output. Similarly, the integral expression for reliable reserve reduction can be obtained, as shown in equation (12):

[0079] (12)

[0080] In summary, an expression for reliable backup power provided by wind power was obtained using integral form, which provides a possible solution and a suitable method.

[0081] S2. Based on reliable wind power backup, construct an objective function to minimize the total cost of transmission network planning, and establish constraints. Based on the objective function and constraints, construct a transmission network planning model that considers wind power backup capacity, specifically including:

[0082] S2.1 Establish the objective function:

[0083] (1) Programming objective function:

[0084] (13)

[0085] In the formula: TC Represents the total cost of power transmission network planning. C inv For the investment cost of power transmission lines, C res For system backup costs, C rel For system reliability costs, C oper This refers to the system operating cost.

[0086] (2) Line investment cost:

[0087] (14)

[0088] In the formula: NL is the total number of transmission corridors, and the index is l; The minimum number of lines required for power transmission corridors; The number of lines with the most power transmission corridors; c l The cost of establishing a line in the transmission corridor; k is the line number in the transmission corridor; It is a binary variable, indicating whether it is in l Establish the first k A line is assigned a value of 1 if it is true, and 0 otherwise.

[0089] (3) Contingency costs:

[0090] (15)

[0091] In the formula: NT is the number of time periods, here we take a typical 24-hour day, indexed as t; NG is the total number of thermal power units, indexed as g; NW is the total number of wind power units, indexed as w; d The planning cycle is 365 days per year. The upward reserve provided for thermal power plants Reserves provided for thermal power plants The cost factor for providing backup power to thermal power unit g. The cost factor for providing backup for wind turbine unit w.

[0092] (4) Operating costs:

[0093] (16)

[0094] In the formula, a g , b g , c g This represents the cost coefficient for thermal power units. This refers to the dispatch value for thermal power units.

[0095] (5) Reliability cost:

[0096] (17)

[0097] In the formula: π eens The price coefficient for load shedding penalty.

[0098] S2.2 Establish constraints:

[0099] (1) Constraints on line construction:

[0100] (18)

[0101] (19)

[0102] In the formula: This is a binary variable indicating whether the k-th line should be established at l; 1 indicates yes, 0 indicates no. and These represent the minimum and maximum number of the same type of transmission lines that are allowed to be built on transmission corridor l, respectively.

[0103] (2) Node power balance constraints:

[0104] (20)

[0105] In the formula: i is the node index number in the system; This is the location matrix of thermal power units. This is the position matrix of the wind turbine units. For line power flow matrix, Forecast values ​​of node load For line power flow.

[0106] (3) DC power flow constraint:

[0107] ;(twenty one)

[0108] ;(twenty two)

[0109] ;(twenty three)

[0110] ;(twenty four)

[0111] In the formula: For the power flow on the k-th line, θ i,t B is the node voltage phase angle. l Here, M is the line impedance matrix, and M is a relatively large constant used for linearization calculations using the bigM method. Generally, 50 is sufficient.

[0112] (4) Generator constraints:

[0113] (25)

[0114] (26)

[0115] (27)

[0116] In the formula: This represents the maximum output power of the generator, g. UR represents the minimum output of generator g. g DR represents the climb capability of unit g. g This indicates the downhill climbing capability of unit g, where Δt is the climbing time interval set by the system, which is 1 hour here.

[0117] (5) Reserve capacity constraints:

[0118] (28)

[0119] (29)

[0120] (30)

[0121] In the formula: NI is the set of all nodes in the system, with index i; To adjust the reserve requirement parameters for load increase, Parameters for adjusting reserve requirements to accommodate load reduction.

[0122] S3. Perform linearization analysis and solution on the aforementioned power transmission network planning model to obtain the optimal power transmission network planning scheme, specifically including:

[0123] (1) Elimination of integral sign:

[0124] The above analysis demonstrates the complementary nature between reliable wind power reserves and wind power losses, but it still contains an integral sign, is not linearized, and cannot be solved directly.

[0125] Taking the upward reserve provided by wind power as an example, the integral change is used to transform equation (11), as shown in equation (31):

[0126] (31)

[0127] In the formula, f(x) is the probability density function of wind power output, and x is the wind power output. The above formula can be directly integrated and substituted to obtain the direct calculation formula for wind power providing backup, as shown in formula (32):

[0128] (32)

[0129] In the formula, f(x) is the probability distribution function of wind power output, and F(x) is the cumulative probability distribution function of wind power output.

[0130] By using linear interpolation to process the last two terms of the equation and combining them into g(x), we obtain the following expression:

[0131] (33)

[0132] In the formula, g(·) is the exponential function of the nonlinear part of the constraint; g rel_up (·) represents the exponential function of the nonlinear component of the reliable backup for wind power up-regulation; g rel_up ( Let be the exponential function of the nonlinear part of the wind power upward adjustment of reliable reserve, with the wind power output dispatch value as the independent variable. Then, equation (32) can be equivalently expressed as follows:

[0133] (34)

[0134] The nonlinear terms are separated using the g(x) function, and can be processed separately without disrupting the mathematical structure of equation (34). Specifically, s segments are taken between the minimum and the predicted value, and g(s) for each segment can be calculated. Then, linear constraints as shown in equations (35)-(37) can be constructed.

[0135] (35)

[0136] In the formula, Let be the output ratio variable of the w-th wind turbine at time t, with values ​​only for two adjacent segments and zero for the rest. For g rel_up ( In wind power dispatch value The function value is the parameter.

[0137] (36)

[0138] (37)

[0139] For the down-regulation reserve provided by wind power, a similar method can be used for linearization. The final result is obtained through linear interpolation. Since the independent variables are all wind power dispatch values, only one set of interpolation coefficient variables is needed, as shown in equation (38):

[0140] (38)

[0141] It is the exponential function of the nonlinear part of the wind power downshoring reliable reserve, with the wind power output dispatch value as the independent variable.

[0142] (2) Linearization of quadratic term operating costs:

[0143] The quadratic polynomial of unit operating cost can be approximated using piecewise linearization, typically using a three-part piecewise linear function.

[0144] A three-part linear function can be expressed in the following form, including equations (39)-(44):

[0145] (39)

[0146] (40)

[0147] (41)

[0148] (42)

[0149] (43)

[0150] (44)

[0151] In the formula: m is the segment index; P m,g,t Let g be the active power of unit g in the m-th segment of time period t; Let g be the maximum active power of unit g in segment m; Let g be the minimum active power of unit g in segment m; This refers to the operating cost at the lower limit of the unit's output g. Let g be the slope of unit g in segment m.

[0152] Therefore, this model is converted into a mixed-integer linear programming model, which can be solved using the CPLEX solver.

[0153] This method addresses scenarios where a high proportion of wind power is integrated into the power system. During the transmission network planning phase, it comprehensively considers both the reliability and economy of system operation, constructing an optimization model capable of reasonably assessing the backup capacity provided by wind power under various operating modes. This model uses minimizing line construction costs, system operating costs, and backup supply costs as its objective function. At the planning level, it achieves coordinated allocation of wind power backup capacity and grid structure, optimizing the linkage between power source resource layout and grid structure, thereby improving the overall economic efficiency and security of the system.

[0154] like Figure 2 As shown, embodiments of this disclosure provide a power grid planning system that considers wind power reliable backup capability, including:

[0155] The wind power reliable backup calculation module is used to calculate the reliable backup capacity that a wind farm can provide under different operating modes.

[0156] The planning model construction module is used to construct an objective function that minimizes the total cost of transmission network planning based on wind power reliable backup, and to construct constraints. Based on the objective function and the constraints, a transmission network planning model that considers wind power backup capacity is constructed.

[0157] The model solving module is used to perform linearization analysis and solve the power transmission network planning model to obtain the optimal power transmission network planning scheme.

[0158] The implementation process of the functions and roles of each module in the above system is detailed in the implementation process of the corresponding steps in the above method, and will not be repeated here.

[0159] For the system embodiments, since they basically correspond to the method embodiments, the relevant parts can be referred to in the description of the method embodiments. The system embodiments described above are merely illustrative. The modules described as separate components may or may not be physically separate, and the components shown as modules may or may not be physical modules, that is, they may be located in one place or distributed across multiple network modules. Some or all of the modules can be selected to achieve the purpose of this disclosure according to actual needs. Those skilled in the art can understand and implement this without creative effort.

[0160] See Figure 3 The electronic device provided in the embodiments of this disclosure includes a processor 1110, a communication interface 1120, a memory 1130 and a communication bus 1140, wherein the processor 1110, the communication interface 1120 and the memory 1130 communicate with each other through the communication bus 1140.

[0161] Memory 1130 is used to store computer programs;

[0162] The processor 1110, when executing the program stored in the memory 1130, implements the above-described transmission network planning method that takes into account the reliable backup capability of wind power.

[0163] The aforementioned communication bus 1140 can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. This communication bus 1140 can be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, it is represented by only one thick line in the figure, but this does not indicate that there is only one bus or one type of bus.

[0164] The communication interface 1120 is used for communication between the above-mentioned electronic device and other devices.

[0165] The memory 1130 may include random access memory (RAM) or non-volatile memory, such as at least one disk storage device. Optionally, the memory 1130 may also be at least one storage device located remotely from the aforementioned processor 1110.

[0166] Embodiments of this disclosure also provide a computer-readable storage medium. The computer-readable storage medium stores a computer program that, when executed by a processor, implements the transmission network planning method considering wind power reliable backup capability as described above.

[0167] The embodiments described above are merely examples of several implementations of this disclosure, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent disclosure. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this disclosure, and these modifications and improvements all fall within the protection scope of this disclosure.

Claims

1. A power grid planning method considering the reliable backup capacity of wind power, characterized in that, Includes the following steps: The calculation of reliable wind power reserve, used to quantify the reliable reserve capacity that a wind farm can provide under different operating modes, includes: calculating expressions for the intervals between the lower limit of the disturbance range and the predicted wind power output when the wind power dispatch value is compressed to the lower limit of the disturbance range, and when the wind power dispatch value is compressed to below the lower limit of the disturbance range, representing the reserve capacity of the wind power dispatch value under different operating ranges: When the wind power dispatch value is compressed to the range between the lower limit of the disturbance interval and the predicted wind power output value as shown in equation (1), the wind power standby status is shown in equations (2) and (3): ；(1) ；(2) ；(3) In the formula: This is the lower limit of the wind power disturbance range. This is the predicted value of wind power output. For wind power output dispatch value variables, Upward reserve provided for wind power Downward reserve provided for wind power Upward adjustment of reserves with reliability constraints for wind power. Downward reserve with reliability constraints provided for wind power This represents the lower limit of the controllable output of the wind turbine. When the wind power dispatch value is compressed to the range below the lower limit of the disturbance range as shown in equation (4), the wind power standby status is shown in equations (5) and (6): ；(4) ；(5) ；(6) The reliability of wind power backup capacity is quantified, so that the reliable backup provided by wind power is quantified through backup reliability indicators; the reliable backup of wind power is calculated based on the backup reliability indicators. Based on reliable wind power backup, an objective function is constructed to minimize the total cost of transmission network planning, and constraints are constructed. Based on the objective function and the constraints, a transmission network planning model considering wind power backup capacity is constructed. The transmission network planning model is linearized and solved to obtain the optimal transmission network planning scheme.

2. The power grid planning method considering wind power reliable backup capability according to claim 1, characterized in that, The total cost of the power transmission network plan includes the investment cost of the power transmission lines, the system reserve cost, the system reliability cost, and the system operation cost.

3. The power grid planning method considering wind power reliable backup capability according to claim 1, characterized in that, The constraints include line construction constraints, node power balance constraints, DC power flow constraints, generator constraints, and reserve capacity constraints.

4. A power grid planning method considering wind power reliable backup capability according to claim 1, characterized in that, The transmission network planning model is linearized and solved to obtain the optimal transmission network planning scheme, including: The nonlinear terms in the power transmission network planning model are linearized, and the planning model is converted into a mixed integer linear programming model, which is then solved using a solver.

5. A power grid planning method considering wind power reliable backup capability according to claim 4, characterized in that, The linearization process includes piecewise linearization of the integral expression for reliable wind power backup and the quadratic term of the unit operating cost.

6. A power grid planning system that considers the reliable backup capability of wind power, characterized in that, include: The wind power reliable reserve calculation module is used to calculate the reliable reserve capacity that a wind farm can provide under different operating modes. This includes: calculating expressions for the intervals between the wind power dispatch value and the predicted wind power output when the wind power dispatch value is compressed to the lower limit of the disturbance interval and when the wind power dispatch value is compressed below the lower limit of the disturbance interval, representing the reserve capacity of the wind power dispatch value under different operating intervals. When the wind power dispatch value is compressed to the range between the lower limit of the disturbance interval and the predicted wind power output value as shown in equation (1), the wind power standby status is shown in equations (2) and (3): ；(1) ；(2) ；(3) In the formula: This is the lower limit of the wind power disturbance range. This is the predicted value of wind power output. For wind power output dispatch value variables, Upward reserve provided for wind power Downward reserve provided for wind power Upward adjustment of reserves with reliability constraints for wind power. Downward reserve with reliability constraints provided for wind power This represents the lower limit of the controllable output of the wind turbine. When the wind power dispatch value is compressed to the range below the lower limit of the disturbance range as shown in equation (4), the wind power standby status is shown in equations (5) and (6): ；(4) ；(5) ；(6) The reliability of wind power backup capacity is quantified, so that the reliable backup provided by wind power is quantified through backup reliability indicators; the reliable backup of wind power is calculated based on the backup reliability indicators. The planning model construction module is used to construct an objective function that minimizes the total cost of transmission network planning based on wind power reliable backup, and to construct constraints. Based on the objective function and the constraints, a transmission network planning model that considers wind power backup capacity is constructed. The model solving module is used to perform linearization analysis and solve the power transmission network planning model to obtain the optimal power transmission network planning scheme.

7. A power grid planning system considering wind power reliable backup capability according to claim 6, characterized in that, The total cost of the power transmission network plan includes the investment cost of the power transmission lines, the system reserve cost, the system reliability cost, and the system operation cost.

8. A power grid planning system considering wind power reliable backup capability according to claim 6, characterized in that, The constraints include line construction constraints, node power balance constraints, DC power flow constraints, generator constraints, and reserve capacity constraints.

9. A power grid planning system considering wind power reliable backup capability according to claim 6, characterized in that, The model solving module performs linearization analysis and solves the transmission network planning model to obtain the optimal transmission network planning scheme, including: The nonlinear terms in the power transmission network planning model are linearized, and the planning model is converted into a mixed integer linear programming model, which is then solved using a solver.

10. A power grid planning system considering wind power reliable backup capability according to claim 9, characterized in that, The linearization process includes piecewise linearization of the integral expression for reliable wind power backup and the quadratic term of the unit operating cost.

11. An electronic device, characterized in that, It includes a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus; Memory, used to store computer programs; A processor is used to execute a program stored in a memory to implement the power grid planning method that takes into account the reliable backup capability of wind power as described in any one of claims 1-5.

12. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the power grid planning method that takes into account the reliable backup capability of wind power as described in any one of claims 1-5.

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