A method and system for emergency dispatching of distribution network resilience restoration based on photovoltaic access

Abstract

This invention discloses an emergency dispatch method for distribution network resilience restoration based on photovoltaic (PV) access. It constructs a resilience assessment index system to obtain resilience index values ​​for PV power supply access nodes. By comprehensively judging each index value, a comprehensive index value is calculated and categorized, effectively enabling reasonable dispatching of distribution network nodes with different resilience capabilities. Based on different resilience levels, economic optimization dispatching is implemented for access nodes with better resilience, while for nodes with poor resilience, the primary consideration is the degree of network loss, thereby improving the operating efficiency and stability of the distribution network. This invention also provides a corresponding emergency dispatch system for distribution network resilience restoration based on PV access.

Description

Technical Field

[0001] This invention relates to the field of distributed photovoltaic power distribution networks, and in particular to a method and system for emergency dispatching to restore the resilience of distribution networks based on photovoltaic access. Background Technology

[0002] With the continuous development and widespread application of distributed photovoltaic (PV) power sources in distribution networks, power supply companies are investing more and more in PV. However, as the voltage level of the power source increases, system instability also becomes more severe. Due to different voltage levels, PV power sources connected to the distribution network will have different impacts on different nodes in the system. Therefore, damage to the system by these nodes will lead to unsatisfactory power quality. In response, many scholars at home and abroad have conducted extensive research on improving the stability of PV power sources connected to the distribution network and enhancing the source-load coordination and scheduling capabilities of the distribution network. This scheduling method can plan for different nodes in the distribution network, but it cannot fully restore the system and cannot arrange for the degree of damage to different nodes themselves. Summary of the Invention

[0003] Purpose of the invention: The purpose of this invention is to provide an emergency dispatch method and system for distribution network resilience recovery based on photovoltaic access. The method calculates the different resilience values ​​and different index weights of each node after the photovoltaic power source is connected, determines the dispatch mode, and realizes emergency dispatch based on the results of different resilience indices.

[0004] Technical Solution: This invention provides an emergency dispatch method for distribution network resilience restoration based on photovoltaic access, comprising the following steps:

[0005] S101. Considering the grid-connected operation principle of photovoltaic power sources, construct a resilience assessment index system;

[0006] S102. Based on the resilience assessment index system, obtain the resilience index values ​​and different index weights of the photovoltaic power grid access node location, and perform normalization processing to establish a comprehensive index method and determine the standard comprehensive resilience judgment formula.

[0007] S103. Based on the standard comprehensive toughness judgment formula, the toughness of different nodes is comprehensively calculated to obtain the toughness value. The toughness value is classified into a better range and a worse range.

[0008] S104. Determine whether the affected nodes can be restored to normal operation through scheduling. If they can be restored to normal, the resilience value is in a good range, and economic optimization scheduling is performed until the problem is completely repaired. If they cannot be restored to normal, the resilience value is in a poor range, and network loss optimization scheduling is performed. Load scheduling is carried out with the goal of minimizing the distribution network loss value until the problem is completely repaired, and the task ends.

[0009] Furthermore, in step S102, the photovoltaic power access node has different resilience index values, including voltage drop, network failure probability, economic performance, and network loss degree.

[0010] Furthermore, in step S102, the weights of different indicators at the photovoltaic power supply access node are normalized to establish a comprehensive indicator method and obtain the comprehensive indicator value. The formula for the comprehensive indicator value is as follows:

[0011]

[0012] in, This is a comprehensive indicator value. This is a matrix representing the voltage drop index. This is a matrix representing the probability of network crashes. This is a matrix of indicators for economic performance. This is a matrix of indicators representing the degree of network loss. Indicator matrix The weighting coefficients, Indicator matrix The weighting coefficients, Indicator matrix The weighting coefficients, Indicator matrix The weighting coefficients.

[0013] Furthermore, in step S103, the toughness values ​​are divided according to the comprehensive index values:

[0014] ;

[0015] in, for The median of the set, if the comprehensive index value Less than or equal to If the resilience value is good, then economic optimization scheduling is performed. The constraints of this economic optimization scheduling are power balance constraints and power source constraints. If the comprehensive index value is... Greater than If the resilience value is poor, then the minimum network loss optimization scheduling is performed. The constraint condition for the minimum network loss optimization scheduling is the power flow constraint of the distribution network.

[0016] This invention provides a distribution network resilience recovery emergency dispatch system based on photovoltaic access, which includes a module for constructing a resilience assessment index system, a module for establishing a comprehensive index method, a classification module, and a judgment module.

[0017] A resilience assessment index system module is constructed to consider the grid-connected operation principle of photovoltaic power sources, and a resilience assessment index system is constructed.

[0018] A comprehensive index method module is established to obtain the resilience index values ​​and different index weights of the photovoltaic power grid access node location based on the resilience assessment index system, and to perform normalization processing to establish a comprehensive index method and determine the standard comprehensive resilience judgment formula.

[0019] The classification module is used to perform comprehensive calculations on the toughness of different nodes according to the standard comprehensive toughness judgment formula, obtain toughness values, classify the toughness values, and divide the toughness values ​​into better and worse ranges.

[0020] The judgment module is used to determine whether the affected nodes can be restored to normal operation through scheduling. If they can be restored to normal, the resilience value is in the better range, and economic optimization scheduling is performed until the problem is completely repaired. If they cannot be restored to normal, the resilience value is in the poor range, and network loss optimization scheduling is performed. Load scheduling is performed with the goal of minimizing the distribution network loss value until the problem is completely repaired, and the task ends.

[0021] Furthermore, in the comprehensive index method module, photovoltaic power access nodes have different resilience index values, including voltage drop, network failure probability, economic performance, and network loss degree.

[0022] Furthermore, in the module for establishing the comprehensive index method, the weights of different indicators at the photovoltaic power supply access node are normalized to establish the comprehensive index method and obtain the comprehensive index value. The formula for the comprehensive index value is as follows:

[0023]

[0024] in, This is a comprehensive indicator value. This is a matrix representing the voltage drop index. This is a matrix representing the probability of network crashes. This is a matrix of indicators for economic performance. This is a matrix of indicators representing the degree of network loss. Indicator matrix The weighting coefficients, Indicator matrix The weighting coefficients, Indicator matrix The weighting coefficients, Indicator matrix The weighting coefficients.

[0025] Furthermore, in the classification module, the toughness value is divided according to the comprehensive index value:

[0026] ;

[0027] in, for The median of the set, if the comprehensive index value Less than or equal to If the resilience value is good, then economic optimization scheduling is performed. The constraints of this economic optimization scheduling are power balance constraints and power source constraints. If the comprehensive index value is... Greater than If the resilience value is poor, then the minimum network loss optimization scheduling is performed. The constraint condition for the minimum network loss optimization scheduling is the power flow constraint of the distribution network.

[0028] Beneficial effects: Compared with the prior art, the significant feature of this invention is that it obtains the resilience index value of the photovoltaic power supply access node by constructing a resilience assessment index system; by comprehensively judging each index value, a comprehensive index value is calculated, and the comprehensive index value is classified, so as to effectively carry out reasonable scheduling for distribution network nodes with different resilience capabilities; according to the scheduling of different resilience, economic optimization scheduling is implemented for access nodes with better resilience, while for nodes with poor resilience, the main consideration is the degree of network loss, thereby improving the operating efficiency and stability of the distribution network. Attached Figure Description

[0029] Figure 1 This is a flowchart illustrating the present invention;

[0030] Figure 2 This is a framework diagram of the scheduling model in this invention. Detailed Implementation

[0031] The present invention will now be described in further detail with reference to specific embodiments and accompanying drawings.

[0032] Example 1

[0033] This invention provides a method for emergency dispatching of distribution network resilience restoration based on photovoltaic access. Please refer to [link to relevant documentation]. Figure 1 As shown, it includes the following steps:

[0034] S101. Considering the grid-connected operation principle of photovoltaic power sources, construct a resilience assessment index system.

[0035] An indicator system is established based on four indicators, which include voltage sag, system failure probability, system economy, and damage level.

[0036] (1) Voltage sag:

[0037] (1)

[0038] In the formula: Number of sensitive load types; This represents the number of load nodes. This represents the connection capacity on node b. The percentage of type k on node b; For type k devices, the recovery time is [not specified]. The total load point designed in the evaluation; for The load points affected in the scenario; This represents the probability of the scenario occurring.

[0039] (2) System crash probability:

[0040] (2)

[0041] In the formula: for The number of times a crash occurred within a given time period; The probability of a system crash; Approximately follows the parameter: The Poisson distribution.

[0042] (3) System economy:

[0043] (3)

[0044] In the formula: It is a system economic index; The economic cost of system operation, scheduling, and maintenance; For the economic losses of maintaining Class K equipment, To mitigate the economic losses associated with the maintenance of the first k types of equipment, To cover the economic losses incurred in maintaining the equipment of category k. For direct economic losses; This constitutes an indirect economic loss.

[0045] (4) Degree of damage:

[0046] (4)

[0047] In the formula: The size of the load deficit in the distribution network. Let n be the probability of scenario n occurring. The total number of distributed power sources connected to the distribution network system at the same time; This is the normal target load curve; This is the actual load curve; At the moment of power connection, This is the moment when the power distribution network system is fully restored.

[0048] S102. Based on the resilience assessment index system, obtain the resilience index values ​​and different index weights of the photovoltaic power grid access node locations, and perform normalization processing to establish a comprehensive index method and determine the standard comprehensive resilience judgment formula.

[0049] Photovoltaic power grid connection nodes have different resilience indicators, including voltage drop, network failure probability, economic performance, and network loss.

[0050] The weights of different indicators at the photovoltaic power supply node location are normalized to establish a comprehensive indicator method, and the comprehensive indicator value is obtained. The formula of the comprehensive indicator method is as follows:

[0051] (5)

[0052] In the formula: For the distribution network system index matrix One indicator; for The maximum value of the indicator; for The minimum value of the indicator; for The range of normalized index values ; Number of access points; For photovoltaic power supply levels;

[0053] The formula for the comprehensive index value is as follows:

[0054] (6)

[0055] in, This is a comprehensive indicator value. This is a matrix representing the voltage drop index. This is a matrix representing the probability of network crashes. This is a matrix of indicators for economic performance. This is a matrix of indicators representing the degree of network loss. Normalized system voltage sag index matrix Weighting coefficients; Normalized system crash probability index matrix Weighting coefficients; Normalized system economic index matrix Weighting coefficients; Normalized system damage index matrix The weighting coefficients.

[0056] S103. Based on the standard comprehensive toughness judgment formula, the toughness of different nodes is comprehensively calculated to obtain the toughness value. The toughness value is then classified into a better range and a worse range.

[0057] Please see Figure 2 As shown, the recovery range is adjusted through load dispatching in the distribution network based on the magnitude of the resilience index value. Considering the load nodes with high resilience in the distribution network, the recovery range formula is as follows:

[0058] (7)

[0059] in, for The median of the set, if the comprehensive index value Less than or equal to If the resilience value is good, then economic optimization scheduling is performed. The constraints of this economic optimization scheduling are power balance constraints and power source constraints. If the comprehensive index value is... Greater than If the resilience value is poor, then the minimum network loss optimization scheduling is performed. The constraint condition for the minimum network loss optimization scheduling is the power flow constraint of the distribution network.

[0060] S104. Determine whether the affected nodes can be restored to normal operation through scheduling in the short term. If they can be restored to normal, the resilience value is in a good range, and economic optimization scheduling is performed until the problem is fully repaired. If they cannot be restored to normal, the resilience value is in a poor range, and network loss optimization scheduling is performed. Load scheduling is carried out with the goal of minimizing the distribution network loss value until the problem is fully repaired, and the task ends.

[0061] Poor toughness value, i.e., comprehensive index value Greater than Perform minimum network loss optimization scheduling, with minimum network loss as the objective function:

[0062] (8)

[0063] In the formula: This represents the total operating losses of the distribution network. This is the function of the total network loss of the distribution network during the scheduling cycle; This is the difference between the expected switching power and the actual power. The scheduling period; Number of distribution network lines; The scheduling period; For distribution network line number; This represents the number of scheduling cycles. For the line Power loss; This is the sum of the number of distribution networks and microgrids; Each is assigned a number; For the actual power obtained; To obtain the desired power.

[0064] The constraint condition for this minimum network loss optimal scheduling is the distribution network power flow constraint:

[0065] (9)

[0066] In the formula: Power for power distribution operators; For virtual microgrid power; For load power; For line conductance; For line susceptance; This is the phase angle difference; Number the nodes; To summarize the points.

[0067] Good toughness value is a comprehensive index value Less than or equal to To perform economic optimization scheduling, the objective function is to achieve optimal economic efficiency.

[0068] (10)

[0069] In the formula: Electricity purchase and sale fees for power distribution operators; The fee charged to users for selling electricity; For startup and wear and tear costs; This refers to the operation and maintenance costs of distributed power sources.

[0070] (11)

[0071] In the formula: The number of time periods within a scheduling cycle; The unit cost of purchasing and selling electricity from the main grid; To purchase and sell electrical power from the upper-level power grid.

[0072] (12)

[0073] In the formula: The unit cost of selling electricity to users; The power output sold to users.

[0074] (13)

[0075] In the formula: This represents the total number of distributed power sources. Number of distributed power sources; For power supply costs; The coefficient for the operating and maintenance cost per unit of electricity of the power supply; To provide power to the generator unit; For unit start-up costs; For unit start-up decision variables; The present value of the unit capacity installation cost of the power supply; This is the capacity factor of the power supply; This refers to the lifespan of the power supply.

[0076] (14)

[0077] In the formula: The maintenance cost per unit power supplied for power supply operation; This refers to the power of the power supply. This represents the number of distributed power sources.

[0078] The constraints for this economic optimization scheduling are power balance constraints and power source constraints. The power balance constraints are as follows:

[0079] (15)

[0080] In the formula: This is the predicted value of photovoltaic power.

[0081] The power supply constraints are as follows:

[0082] (16)

[0083] In the formula: Contribute to photovoltaic forecasting.

[0084] Example 2

[0085] Corresponding to the photovoltaic-based distribution network resilience restoration emergency dispatch method in Embodiment 1, this Embodiment 2 provides a photovoltaic-based distribution network resilience restoration emergency dispatch system. Please refer to [link to Embodiment 2]. Figure 1 As shown, it includes a module for constructing a resilience assessment index system, a module for establishing a comprehensive index method, a classification module, and a judgment module;

[0086] A resilience assessment index system module is constructed to consider the grid-connected operation principle of photovoltaic power sources and to build a resilience assessment index system.

[0087] An indicator system is established based on four indicators, which include voltage sag, system failure probability, system economy, and damage level.

[0088] (1) Voltage sag:

[0089] (1)

[0090] In the formula: Number of sensitive load types; This represents the number of load nodes. This represents the connection capacity on node b. The percentage of type k on node b; For type k devices, the recovery time is [not specified]. The total load point designed in the evaluation; for The load points affected in the scenario; This represents the probability of the scenario occurring.

[0091] (2) System crash probability:

[0092] (2)

[0093] In the formula: for The number of times a crash occurred within a given time period; The probability of a system crash; Approximately follows the parameter: The Poisson distribution.

[0094] (3) System economy:

[0095] (3)

[0096] In the formula: It is a system economic index; The economic cost of system operation, scheduling, and maintenance; For the economic losses of maintaining Class K equipment, To mitigate the economic losses associated with the maintenance of the first k types of equipment, To cover the economic losses incurred in maintaining the equipment of category k. For direct economic losses; This constitutes an indirect economic loss.

[0097] (4) Degree of damage:

[0098] (4)

[0099] In the formula: The size of the load deficit in the distribution network. Let n be the probability of scenario n occurring. The total number of distributed power sources connected to the distribution network system at the same time; This is the normal target load curve; This is the actual load curve; At the moment of power connection, This is the moment when the power distribution network system is fully restored.

[0100] A comprehensive index method module is established to obtain the resilience index values ​​and different index weights of the photovoltaic power grid access node based on the resilience assessment index system, and to perform normalization processing to establish a comprehensive index method and determine the standard comprehensive resilience judgment formula.

[0101] Photovoltaic power grid connection nodes have different resilience indicators, including voltage drop, network failure probability, economic performance, and network loss.

[0102] The weights of different indicators at the photovoltaic power supply node location are normalized to establish a comprehensive indicator method, and the comprehensive indicator value is obtained. The formula of the comprehensive indicator method is as follows:

[0103] (5)

[0104] In the formula: For the distribution network system index matrix One indicator; for The maximum value of the indicator; for The minimum value of the indicator; for The range of normalized index values ; Number of access points; For photovoltaic power supply levels;

[0105] The formula for the comprehensive index value is as follows:

[0106] (6)

[0107] in, This is a comprehensive indicator value. This is a matrix representing the voltage drop index. This is a matrix representing the probability of network crashes. This is a matrix of indicators for economic performance. This is a matrix of indicators representing the degree of network loss. Normalized system voltage sag index matrix Weighting coefficients; Normalized system crash probability index matrix Weighting coefficients; Normalized system economic index matrix Weighting coefficients; Normalized system damage index matrix The weighting coefficients.

[0108] The classification module is used to perform comprehensive calculations on the toughness of different nodes according to the standard comprehensive toughness judgment formula, obtain toughness values, classify the toughness values ​​into better and worse ranges.

[0109] Please see Figure 2 As shown, the recovery range is adjusted through load dispatching in the distribution network based on the magnitude of the resilience index value. Considering the load nodes with high resilience in the distribution network, the recovery range formula is as follows:

[0110] (7)

[0111] in, for The median of the set, if the comprehensive index value Less than or equal to If the resilience value is good, then economic optimization scheduling is performed. The constraints of this economic optimization scheduling are power balance constraints and power source constraints. If the comprehensive index value is... Greater than If the resilience value is poor, then the minimum network loss optimization scheduling is performed. The constraint condition for the minimum network loss optimization scheduling is the power flow constraint of the distribution network.

[0112] The judgment module is used to determine whether the affected nodes can resume normal operation in the short term through scheduling. If they can resume normal operation, the resilience value is in the better range, and economic optimization scheduling is performed until the problem is fully repaired. If they cannot resume normal operation, the resilience value is in the poor range, and network loss optimization scheduling is performed. Load scheduling is performed with the goal of minimizing the distribution network loss value until the problem is fully repaired, and the task ends.

[0113] Poor toughness value, i.e., comprehensive index value Greater than Perform minimum network loss optimization scheduling, with minimum network loss as the objective function:

[0114] (8)

[0115] In the formula: This represents the total operating losses of the distribution network. This is the function of the total network loss of the distribution network during the scheduling cycle; This is the difference between the expected switching power and the actual power. The scheduling period; Number of distribution network lines; The scheduling period; For distribution network line number; This represents the number of scheduling cycles. For the line Power loss; This is the sum of the number of distribution networks and microgrids; Each is assigned a number; For the actual power obtained; To obtain the desired power.

[0116] The constraint condition for this minimum network loss optimal scheduling is the distribution network power flow constraint:

[0117] (9)

[0118] In the formula: Power for power distribution operators; For virtual microgrid power; For load power; For line conductance; For line susceptance; This is the phase angle difference; Number the nodes; To summarize the points.

[0119] Good toughness value is a comprehensive index value Less than or equal to To perform economic optimization scheduling, the objective function is to achieve optimal economic efficiency.

[0120] (10)

[0121] In the formula: Electricity purchase and sale fees for power distribution operators; The fee charged to users for selling electricity; For startup and wear and tear costs; This refers to the operation and maintenance costs of distributed power sources.

[0122] (11)

[0123] In the formula: The number of time periods within a scheduling cycle; The unit cost of purchasing and selling electricity from the main grid; To purchase and sell electrical power from the upper-level power grid.

[0124] (12)

[0125] In the formula: The unit cost of selling electricity to users; The power output sold to users.

[0126] (13)

[0127] In the formula: This represents the total number of distributed power sources. Number of distributed power sources; For power supply costs; The coefficient for the operating and maintenance cost per unit of electricity of the power supply; To provide power to the generator unit; For unit start-up costs; For unit start-up decision variables; The present value of the unit capacity installation cost of the power supply; This is the capacity factor of the power supply; This refers to the lifespan of the power supply.

[0128] (14)

[0129] In the formula: The maintenance cost per unit power supplied for power supply operation; This refers to the power of the power supply. This represents the number of distributed power sources.

[0130] The constraints for this economic optimization scheduling are power balance constraints and power source constraints. The power balance constraints are as follows:

[0131] (15)

[0132] In the formula: This is the predicted value of photovoltaic power.

[0133] The power supply constraints are as follows:

[0134] (16)

[0135] In the formula: Contribute to photovoltaic forecasting.

Claims

1. A method for emergency dispatching of distribution network resilience restoration based on photovoltaic access, characterized in that, Includes the following steps: S101. Considering the grid-connected operation principle of photovoltaic power sources, construct a resilience assessment index system; S102. Based on the resilience assessment index system, obtain the resilience index values ​​and different index weights of the photovoltaic power grid access node location, and perform normalization processing to establish a comprehensive index method and determine the standard comprehensive resilience judgment formula. S103. Based on the standard comprehensive toughness assessment formula, the toughness of different nodes is comprehensively calculated to obtain toughness values. These toughness values ​​are then classified into a better range and a worse range, as shown in the formula: ； in, for The median of the set, if the comprehensive index value Less than or equal to If the resilience value is good, then economic optimization scheduling is performed. The constraints of this economic optimization scheduling are power balance constraints and power source constraints. If the comprehensive index value is... Greater than If the resilience value is poor, then the minimum network loss optimization scheduling is performed. The constraint condition for the minimum network loss optimization scheduling is the distribution network power flow constraint. S104. Determine whether the affected nodes can be restored to normal operation through scheduling. If they can be restored to normal, the resilience value is in a good range, and economic optimization scheduling is performed until the problem is completely repaired. If they cannot be restored to normal, the resilience value is in a poor range, and network loss optimization scheduling is performed. Load scheduling is carried out with the goal of minimizing the distribution network loss value until the problem is completely repaired, and the task ends.

2. The emergency dispatch method for distribution network resilience restoration based on photovoltaic access according to claim 1, characterized in that, In step S102, the photovoltaic power access nodes have different resilience index values, including voltage drop, network failure probability, economic performance, and network loss degree.

3. The emergency dispatch method for distribution network resilience restoration based on photovoltaic access according to claim 2, characterized in that, In step S102, the weights of different indicators at the photovoltaic power supply node location are normalized to establish a comprehensive indicator method and obtain the comprehensive indicator value. The formula for the comprehensive indicator value is as follows: ； in, This is a comprehensive indicator value. This is a matrix representing the voltage drop index. This is a matrix representing the probability of network crashes. This is a matrix of indicators for economic performance. This is a matrix of indicators representing the degree of network loss. Indicator matrix The weighting coefficients, Indicator matrix The weighting coefficients, Indicator matrix The weighting coefficients, Indicator matrix The weighting coefficients.

4. A distribution network resilience restoration emergency dispatch system based on photovoltaic access, characterized in that, It includes modules for constructing a resilience assessment index system, establishing a comprehensive index method, classification, and judgment. A resilience assessment index system module is constructed to consider the grid-connected operation principle of photovoltaic power sources, and a resilience assessment index system is constructed. A comprehensive index method module is established to obtain the resilience index values ​​and different index weights of the photovoltaic power grid access node location based on the resilience assessment index system, and to perform normalization processing to establish a comprehensive index method and determine the standard comprehensive resilience judgment formula. The classification module is used to comprehensively calculate the toughness of different nodes according to the standard integrated toughness assessment formula, obtain a toughness value, and classify the toughness value into a better range and a worse range. The formula is as follows: ; in, for The median of the set, if the comprehensive index value Less than or equal to If the resilience value is good, then economic optimization scheduling is performed. The constraints of this economic optimization scheduling are power balance constraints and power source constraints. If the comprehensive index value is... Greater than If the resilience value is poor, then the minimum network loss optimization scheduling is performed. The constraint condition for the minimum network loss optimization scheduling is the distribution network power flow constraint. The judgment module is used to determine whether the affected nodes can be restored to normal operation through scheduling. If they can be restored to normal, the resilience value is in the better range, and economic optimization scheduling is performed until the problem is completely repaired. If they cannot be restored to normal, the resilience value is in the poor range, and network loss optimization scheduling is performed. Load scheduling is performed with the goal of minimizing the distribution network loss value until the problem is completely repaired, and the task ends.

5. The emergency dispatch system for distribution network resilience restoration based on photovoltaic access according to claim 4, characterized in that, In the module of establishing the comprehensive index method, photovoltaic power access nodes have different resilience index values, including voltage drop, network failure probability, economic performance, and network loss degree.

6. The emergency dispatch system for distribution network resilience restoration based on photovoltaic access according to claim 5, characterized in that, In the module for establishing the comprehensive index method, the weights of different indicators at the photovoltaic power supply node location are normalized to establish the comprehensive index method and obtain the comprehensive index value. The formula for the comprehensive index value is as follows: ； in, This is a comprehensive indicator value. This is a matrix representing the voltage drop index. This is a matrix representing the probability of network crashes. This is a matrix of indicators for economic performance. This is a matrix of indicators representing the degree of network loss. Indicator matrix The weighting coefficients, Indicator matrix The weighting coefficients, Indicator matrix The weighting coefficients, Indicator matrix The weighting coefficients.

7. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 3.

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

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