Power grid node recovery priority evaluation method and system in extreme environment

Abstract

The invention discloses a power grid node recovery priority evaluation method and system in an extreme environment, and the method comprises the steps: calculating and determining a disaster influence factor of each node according to the fault probability of a line in each node; according to the disaster influence factor and the disaster information of each node, determining unit output and node load in the node influenced by the disaster; according to the unit output in the node influenced by the disaster and the unit recovery income of the unit in the node, determining the corrected expected recovery income of the unit in the node; according to the node load influenced by the disaster and the unit recovery income of the load in the node, determining the corrected expected recovery income of the load in the node; adding the corrected expected recovery income of the unit in each node and the corrected expected recovery income of the load to obtain the expected recovery income of each node; and determining the recovery priority of each node in the power grid according to the expected recovery income of each node. The recovery priority of each node in the power grid is accurately determined.

Description

Technical Field

[0001] The present invention relates to the technical field of power grid restoration, and in particular to a method and system for evaluating power grid node restoration priorities under extreme environments. Background Art

[0002] The statements in this section merely provide background information related to the present invention and do not necessarily constitute prior art.

[0003] Natural disasters are the main cause of blackouts and increase the risk of power grid restoration and control. How to reasonably consider disaster factors in restoration and control decisions and avoid their adverse effects is an urgent problem to be solved. To this end, it is necessary to quantify the degree of impact of disasters on the restored power grid, establish quantitative analysis indicators, and evaluate the changes in node power generation and load restoration benefits under different degrees of disaster impact.

[0004] The academic community has conducted a lot of research on the dispatching and defense technology of power grids in response to disasters. The document "Concept of Power Outage Defense System in Extreme External Disasters (I) New Challenges and Reflections" further proposed the construction of an online defense system for disaster response and its key links based on the traditional online preventive control, emergency control, correction control and their coordinated optimization research, and proposed the defense idea of ​​"active decoupling and zoning power supply" under extreme disaster conditions. The document "Review of Dispatching Defense Technology for Interconnected Power Grids in Response to Extreme External Disasters" pointed out that the research on the candidate measure set adjustment technology that adapts to environmental changes and the research on multi-level dispatching collaborative control should be strengthened, including the research on online recovery control decision-making of multi-level dispatching collaboration. However, there is no research on how to consider the impact of disasters on the importance of node recovery in recovery control decisions, so it is difficult to ensure the correctness of the recovery control decision results under disaster conditions. Summary of the invention

[0005] In order to solve the above problems, the present invention proposes a method and system for evaluating the priority of power grid node restoration under extreme environments, which realizes the accurate determination of the restoration priority of each node in the power grid.

[0006] To achieve the above object, the present invention adopts the following technical solution:

[0007] First, a method for evaluating the priority of power grid node restoration in extreme environments is proposed, including:

[0008] Obtain disaster information of each node in the power grid, as well as the failure probability of the line in each node, the unit recovery benefit of the unit and the unit recovery benefit of the load;

[0009] According to the failure probability of the line in each node, calculate and determine the disaster impact factor of each node;

[0010] According to the disaster impact factors and disaster information of each node, determine the unit output and node load in the node affected by the disaster;

[0011] Determine the revised expected recovery benefits of the units in the node based on the output of the units in the node after the disaster and the unit recovery benefits of the units in the node;

[0012] According to the node load after being affected by the disaster and the unit recovery benefit of the load in the node, the revised expected recovery benefit of the load in the node is determined;

[0013] Add the corrected expected recovery benefits of the units in each node and the corrected expected recovery benefits of the load to obtain the expected recovery benefits of each node;

[0014] The restoration priority of each node in the power grid is determined based on the expected restoration benefit of each node.

[0015] Furthermore, it obtains grid operation data, equipment outage status, maintenance plans, equipment geographic information and equipment design parameters, as well as abnormal and alarm data;

[0016] The failure probability of the line in each node is determined based on the grid operation data, equipment power outage status, maintenance plan, equipment geographic information, disaster information, equipment design parameters, and abnormal and alarm data.

[0017] Furthermore, the failure probabilities of the transmission lines in the node whose failure probability is greater than the set probability threshold are added together to obtain the total failure probability of the transmission lines in the node;

[0018] Calculate the proportion of transmission lines in the node whose failure probability is greater than the set probability threshold among all transmission lines in the node, and obtain the proportion of faulty lines in the node;

[0019] The total failure probability of the node transmission line and the proportion of node fault lines are weighted and summed to obtain the initial disaster impact factor of each node;

[0020] The initial disaster impact factors of all nodes are normalized to obtain the disaster impact factor of each node.

[0021] Furthermore, according to the disaster information of the node, the disaster impact factor and the dynamic adjustment function of the unit recovery benefit, the unit output in the node affected by the disaster is determined;

[0022] According to the node's disaster information, disaster impact factors and load recovery benefit dynamic adjustment function, determine the node load after the disaster;

[0023] Among them, the dynamic adjustment function of the node's unit recovery benefit is obtained by fitting the disaster impact factors corresponding to the known different disaster information of the node and the unit output in the node after the disaster;

[0024] The dynamic adjustment function of the node's load recovery benefit is obtained by fitting the disaster impact factors corresponding to the known disaster information of the node and the node load after the disaster.

[0025] Furthermore, the output of the units in the node affected by the disaster is multiplied by the unit recovery benefit of the units in the node to obtain the revised expected recovery benefit of the units in the node;

[0026] Multiply the node load affected by the disaster by the unit recovery benefit of the load in the node to obtain the corrected expected recovery benefit of the load in the node.

[0027] Furthermore, the recovery priority of each node is determined according to the expected recovery benefit of each node;

[0028] Among them, the greater the expected recovery benefit of the node, the higher the recovery priority of the node, and the earlier the node is restored.

[0029] Secondly, a grid node restoration priority assessment system under extreme environments is proposed, including:

[0030] An information acquisition module is used to obtain disaster information of each node in the power grid, as well as the failure probability of the line in each node, the unit recovery benefit of the unit and the unit recovery benefit of the load;

[0031] The impact factor evaluation module is used to calculate and determine the disaster impact factor of each node based on the failure probability of the line in each node;

[0032] The expected recovery benefit adjustment module is used to determine the unit output and node load in the node affected by the disaster according to the disaster impact factor and disaster information of each node; determine the revised expected recovery benefit of the unit in the node according to the unit output in the node affected by the disaster and the unit recovery benefit of the unit in the node; determine the revised expected recovery benefit of the load in the node according to the node load after the disaster and the unit recovery benefit of the load in the node;

[0033] A node benefit evaluation module is used to add the corrected expected recovery benefit of the units in each node and the corrected expected recovery benefit of the load to obtain the expected recovery benefit of each node;

[0034] The node restoration priority determination module is used to determine the restoration priority of each node in the power grid according to the expected restoration benefit of each node.

[0035] In a third aspect, a computer device is provided, the device comprising:

[0036] a processor adapted to execute a computer program;

[0037] A computer-readable storage medium having a computer program stored therein, wherein when the computer program is executed by the processor, a method for evaluating the priority of power grid node restoration under extreme environments proposed in the first aspect is implemented.

[0038] In a fourth aspect, a computer-readable storage medium is proposed, wherein the computer-readable storage medium stores a computer program, and the computer program is suitable for being loaded by a processor and executing a method for evaluating power grid node restoration priority under extreme environments proposed in the first aspect.

[0039] In a fifth aspect, a computer program product is proposed, which includes a computer program. When the computer program is executed by a processor, it implements a method for evaluating power grid node restoration priority under extreme environments proposed in the first aspect.

[0040] Compared with the prior art, the present invention has the following beneficial effects:

[0041] The present invention proposes a method and system for evaluating the priority of power grid node restoration under extreme environments. The method can realize dynamic evaluation of line failure probability, and determine the disaster impact factor of each node on this basis. The unit output and node load in the node affected by the disaster are determined by the determined disaster impact factor and disaster information. Then, according to the unit output and node load in the node affected by the disaster, the corrected expected restoration benefit of the unit in the node and the corrected expected restoration benefit of the load are determined, so as to correct the expected restoration benefit of the unit and load in each node, and finally accurately obtain the expected restoration benefit of the node; according to the expected restoration benefit of each node, the restoration priority of the node is determined. It can adapt to the changes in the external environment, accurately determine the expected restoration benefit of the node, and then accurately determine the restoration priority of the node, improve the quantitative evaluation ability of the degree of disaster impact on the restored power grid, and ensure the feasibility, economy and practicality of the power grid node restoration control decision.

[0042] Advantages of additional aspects of the present invention will be given in part in the following description, and in part will become obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] The drawings in the specification, which constitute a part of the present application, are used to provide further understanding of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute improper limitations on the present application.

[0044] Figure 1 A flow chart of a method for evaluating power grid node restoration priority in an extreme environment disclosed in an embodiment;

[0045] Figure 2A block diagram of a power grid node restoration priority evaluation system under extreme environments disclosed in an embodiment. DETAILED DESCRIPTION

[0046] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0047] It should be noted that the following detailed descriptions are illustrative and are intended to provide further explanation of the present application. Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those commonly understood by those skilled in the art to which the present application belongs.

[0048] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present application. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprise" and / or "include" are used in this specification, it indicates the presence of features, steps, operations, devices, components and / or combinations thereof.

[0049] In the absence of conflict, the embodiments of the present invention and the features of the embodiments may be combined with each other.

[0050] Example 1

[0051] Natural disasters are the main cause of blackouts and increase the risk of power grid restoration and control. How to reasonably consider disaster factors in restoration and control decisions and avoid their adverse effects is an urgent problem to be solved. To this end, it is necessary to quantify the degree of impact of disasters on the restored power grid, establish quantitative analysis indicators, and evaluate the changes in node power generation and load restoration benefits under different degrees of disaster impact.

[0052] The academic community has conducted a lot of research on the dispatching and defense technology of power grids in response to disasters. The document "Concept of Power Outage Defense System in Extreme External Disasters (I) New Challenges and Reflections" further proposed the construction of an online defense system for disaster response and its key links based on the traditional online preventive control, emergency control, correction control and their coordinated optimization research, and proposed the defense idea of ​​"active decoupling and zoning power supply" under extreme disaster conditions. The document "Review of Dispatching Defense Technology for Interconnected Power Grids in Response to Extreme External Disasters" pointed out that the research on the candidate measure set adjustment technology that adapts to environmental changes and the research on multi-level dispatching collaborative control should be strengthened, including the research on online recovery control decision-making of multi-level dispatching collaboration. However, there is no research on how to consider the impact of disasters on the importance of node recovery in recovery control decisions, so it is difficult to ensure the correctness of the recovery control decision results under disaster conditions.

[0053] In addition, under the influence of disasters, the expected recovery benefits and recovery importance of the units and loads in each node will change. For example, under typhoon disasters, the risk of wind power cut-out increases due to the greater impact of the typhoon, and the recovery benefit of the starting power of the wind turbine unit should be reduced according to the typhoon disaster impact factor of the node; because the typhoon reduces the recovery reliability of the load feeder, the load recovery benefit of the affected node should be reduced according to the disaster impact factor of the node; for example, in extremely high or low temperature weather, the recovery benefit of residential loads can be fitted and adjusted based on historical data. The current power grid restoration control methods do not consider the impact of different disaster conditions on the expected recovery benefits of nodes, so the final determined power grid restoration sequence cannot reach the optimal.

[0054] Therefore, in order to further improve the online decision-making technology of power grid restoration control, this embodiment is based on existing research results, especially on the basis of quantitative assessment of the probability of line failure caused by disasters. It focuses on explaining how to realize online automatic assessment of node disaster impact factors for power grid restoration control under the premise of realizing automatic collection of environmental information and dynamic assessment of line failure probability according to environmental changes, so as to further calculate and adjust the node restoration priority online, so that the recovery control decision results can adapt to changes in the external environment and ensure the feasibility, economy and practicality of the control decision.

[0055] A method for evaluating power grid node restoration priority under an extreme environment disclosed in this embodiment is described in detail.

[0056] like Figure 1 As shown, this embodiment discloses a method for evaluating the priority of power grid node restoration in an extreme environment, including:

[0057] S1: Obtain disaster information of each node in the power grid, as well as the failure probability of the line in each node, the unit recovery benefit of the unit and the unit recovery benefit of the load.

[0058] This embodiment obtains power grid operation data, equipment power outage status, maintenance plan, equipment geographic information and equipment design parameters and abnormal and alarm data;

[0059] The failure probability of the line in each node is determined based on the grid operation data, equipment power outage status, maintenance plan, equipment geographic information, disaster information, equipment design parameters, and abnormal and alarm data.

[0060] In specific implementation, the restorable status of the line is determined based on the grid operation data, equipment power outage status, maintenance plan, and abnormal and alarm data;

[0061] When the recoverable state of a line is determined to be unrecoverable, the failure probability of the line is 1.

[0062] When a line is determined to be a restorable line, the failure probability of the line is determined based on power grid operation data, disaster information, equipment geographic information and equipment design parameters.

[0063] S2: Calculate and determine the disaster impact factor of each node based on the failure probability of the line in the node.

[0064] The process of determining the disaster impact factor of each node in this embodiment includes:

[0065] Add the failure probabilities of the transmission lines in the node whose failure probability is greater than the set probability threshold to obtain the total failure probability of the transmission lines in the node;

[0066] Calculate the proportion of transmission lines in the node whose failure probability is greater than the set probability threshold among all transmission lines in the node, and obtain the proportion of faulty lines in the node;

[0067] The total failure probability of the node transmission line and the proportion of node fault lines are weighted and summed to obtain the initial disaster impact factor of each node;

[0068] The initial disaster impact factors of all nodes are normalized to obtain the disaster impact factor of each node.

[0069] Among them, the total failure probability of the node transmission line is α d,m :

[0070]

[0071] In the formula, α m,k is the failure probability of the kth transmission line connected to node m, N L,m is the total number of transmission lines connected to node m, N D,m N L,m The total number of transmission lines with medium disaster failure probability greater than the set probability threshold.

[0072] N D,m In N L,m The proportion of α d,m After correction, the initial disaster impact factor β is obtained m ;ω d,1 ,ω d,2 is the weight, usually ω d,1 ≥ω d,2 ,ω d,1 +ω d,2 =1.

[0073] β m =ω d,1 α d,m +ω d,2 (N D,m / N L,m ) (2)

[0074] The process of normalizing the initial disaster impact factors of all nodes is as follows:

[0075]

[0076] Where β' m is the disaster impact factor of node m, β f is the maximum value of the initial disaster impact factor of all nodes. Among them, the node is a power plant or substation in a completely stopped state.

[0077] S3: According to the disaster impact factors and disaster information of each node, determine the unit output and node load in the node affected by the disaster;

[0078] Determine the revised expected recovery benefits of the units in the node based on the output of the units in the node after the disaster and the unit recovery benefits of the units in the node;

[0079] According to the node load after being affected by the disaster and the unit recovery benefit of the load in the node, the revised expected recovery benefit of the load in the node is determined.

[0080] In the specific implementation, the unit output in the node affected by the disaster is determined according to the node's disaster information, disaster impact factors and unit recovery benefit dynamic adjustment function;

[0081] According to the node's disaster information, disaster impact factors and load recovery benefit dynamic adjustment function, the node load affected by the disaster is determined.

[0082] Among them, the dynamic adjustment function of the node unit recovery benefit is obtained by fitting the disaster impact factors corresponding to the known different disaster information of the node and the unit output in the node after the disaster; where, D m is the disaster information of node m.

[0083] The dynamic adjustment function of the node's load recovery benefit is obtained by fitting the disaster impact factors corresponding to the known disaster information of the node and the node load after the disaster.

[0084] In this embodiment, the unit output g of the node affected by the disaster is obtained. G (D m ,β' m ) and node load g L (D m ,β' m ) and then the unit output g in the node affected by the disaster G (D m ,β' m ) and the unit recovery benefit R of the unit in the node G,m,iMultiply them to obtain the modified expected recovery benefit R' of the unit in the node G,m,i .

[0085] R' G,m,i =g G (D m ,β' m )R G,m,i (4)

[0086] Where i is the number of the generator set in node m, i = 1, 2...N G,m , N G,m is the total number of generator sets in node m.

[0087] The node load g after the disaster is affected L (D m ,β' m ) and the unit recovery benefit R of the node load L,m,j Multiply them to obtain the modified expected restoration benefit R' of the load in the node L,m,j .

[0088] R' L,m,j =g L (D m ,β' m )R L,m,j (5)

[0089] Where j is the number of the load in node m, j = 1, 2...N L,m , N L,m is the total number of loads in node m.

[0090] S4: Add the corrected expected recovery benefits of the units in each node and the corrected expected recovery benefits of the load to obtain the expected recovery benefits V of each node m .

[0091]

[0092] S5: Determine the restoration priority of each node in the power grid based on the expected restoration benefit of each node.

[0093] This embodiment determines the recovery priority of each node according to the expected recovery benefit of each node; wherein, the greater the expected recovery benefit of a node, the higher the recovery priority of the node, and the node is recovered earlier.

[0094] In the specific implementation, the expected recovery benefit of each node is ranked from large to small, and the nodes with higher rankings are restored to a limited extent.

[0095] The present embodiment discloses a method for evaluating the priority of power grid node restoration under extreme environments, which can realize dynamic evaluation of line failure probability, and determine the disaster impact factor of each node on this basis, determine the unit output and node load in the node affected by the disaster through the determined disaster impact factor and disaster information, and then determine the corrected expected restoration benefit of the unit in the node and the corrected expected restoration benefit of the load according to the unit output and node load in the node affected by the disaster, thereby realizing the correction of the expected restoration benefit of the unit and load in each node, and finally accurately obtaining the expected restoration benefit of the node; according to the expected restoration benefit of each node, determine the restoration priority of the node. It can adapt to the changes in the external environment, accurately determine the expected restoration benefit of the node, and then accurately determine the restoration priority of the node, improve the quantitative evaluation ability of the degree of disaster impact on the restored power grid, and ensure the feasibility, economy and practicality of the power grid node restoration control decision.

[0096] Example 2

[0097] In this embodiment, a power grid node restoration priority evaluation system in an extreme environment is disclosed, such as Figure 2 As shown, including:

[0098] An information acquisition module is used to obtain disaster information of each node in the power grid, as well as the failure probability of the line in each node, the unit recovery benefit of the unit and the unit recovery benefit of the load;

[0099] The impact factor evaluation module is used to calculate and determine the disaster impact factor of each node based on the failure probability of the line in each node;

[0100] The expected recovery benefit adjustment module is used to determine the unit output and node load in the node affected by the disaster according to the disaster impact factor and disaster information of each node; determine the revised expected recovery benefit of the unit in the node according to the unit output in the node affected by the disaster and the unit recovery benefit of the unit in the node; determine the revised expected recovery benefit of the load in the node according to the node load after the disaster and the unit recovery benefit of the load in the node;

[0101] A node benefit evaluation module is used to add the corrected expected recovery benefit of the units in each node and the corrected expected recovery benefit of the load to obtain the expected recovery benefit of each node;

[0102] The node restoration priority determination module is used to determine the restoration priority of each node in the power grid according to the expected restoration benefit of each node.

[0103] Among them, the expected recovery revenue adjustment module includes a power generation revenue adjustment module and a load revenue adjustment module.

[0104] The power generation revenue adjustment module is used to determine the output of the units in the nodes affected by the disaster according to the disaster impact factors and disaster information of each node, and to determine the revised expected recovery revenue of the units in the nodes according to the output of the units in the nodes affected by the disaster and the unit recovery revenue of the units in the nodes.

[0105] In the specific implementation, the load benefit adjustment module is used to determine the node load after the disaster is affected according to the disaster impact factor and disaster information of each node, and to determine the corrected expected recovery benefit of the load in the node according to the node load after the disaster and the unit recovery benefit of the load in the node.

[0106] The expected recovery benefit adjustment module is used to determine the unit output in the node affected by the disaster according to the node's disaster information, disaster impact factors and unit recovery benefit dynamic adjustment function;

[0107] According to the node's disaster information, disaster impact factors and load recovery benefit dynamic adjustment function, determine the node load after the disaster;

[0108] Among them, the dynamic adjustment function of the node's unit recovery benefit is obtained by fitting the disaster impact factors corresponding to the known different disaster information of the node and the unit output in the node after the disaster;

[0109] The dynamic adjustment function of the node's load recovery benefit is obtained by fitting the disaster impact factors corresponding to the known disaster information of the node and the node load after the disaster.

[0110] The load benefit adjustment module is used to multiply the output of the units in the node affected by the disaster by the unit recovery benefit of the units in the node to obtain the corrected expected recovery benefit of the units in the node;

[0111] Multiply the node load affected by the disaster by the unit recovery benefit of the load in the node to obtain the corrected expected recovery benefit of the load in the node.

[0112] The present invention also discloses a computer device, which includes:

[0113] a processor adapted to execute a computer program;

[0114] A computer-readable storage medium, wherein a computer program is stored in the computer-readable storage medium, and when the computer program is executed by the processor, a method for evaluating the priority of power grid node restoration under an extreme environment disclosed in Example 1 is implemented.

[0115] The present invention also discloses a computer-readable storage medium storing a computer program, wherein the computer program is suitable for being loaded by a processor and executing a method for evaluating the priority of power grid node restoration under an extreme environment disclosed in Example 1.

[0116] The present invention also discloses a computer program product, which includes a computer program. When the computer program is executed by a processor, it implements a method for evaluating power grid node restoration priority under extreme environments disclosed in Example 1.

[0117] The method disclosed in Example 1 can be directly embodied as a hardware processor, or can be executed by a combination of hardware and software modules in the processor. The software module can be located in a mature storage medium in the field such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory, or an electrically erasable programmable memory, a register, etc. The storage medium is located in the memory, and the processor reads the information in the memory and completes the steps of the above method in combination with its hardware. To avoid repetition, it will not be described in detail here.

[0118] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with this embodiment can be implemented in electronic hardware or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0119] Although the above describes the specific implementation mode of the present invention in conjunction with the accompanying drawings, it is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art on the basis of the technical solution of the present invention without creative work are still within the scope of protection of the present invention.

Claims

1. A method for evaluating the priority of power grid node restoration under extreme conditions, characterized in that: include: Obtain disaster information of each node in the power grid, as well as the failure probability of the line in each node, the unit recovery benefit of the unit and the unit recovery benefit of the load; According to the failure probability of the line in each node, calculate and determine the disaster impact factor of each node; According to the disaster impact factors and disaster information of each node, determine the unit output and node load in the node affected by the disaster; Determine the revised expected recovery benefits of the units in the node based on the output of the units in the node after the disaster and the unit recovery benefits of the units in the node; According to the node load after being affected by the disaster and the unit recovery benefit of the load in the node, the revised expected recovery benefit of the load in the node is determined; Add the corrected expected recovery benefits of the units in each node and the corrected expected recovery benefits of the load to obtain the expected recovery benefits of each node; The restoration priority of each node in the power grid is determined based on the expected restoration benefit of each node.

2. A method for evaluating the priority of power grid node restoration under extreme conditions according to claim 1, characterized in that: Obtain power grid operation data, equipment outage status, maintenance plan, equipment geographic information and equipment design parameters as well as abnormal and alarm data; The failure probability of the line in each node is determined based on the grid operation data, equipment power outage status, maintenance plan, equipment geographic information, disaster information, equipment design parameters, and abnormal and alarm data.

3. A method for evaluating the priority of power grid node restoration under extreme conditions according to claim 1, characterized in that: Add the failure probabilities of the transmission lines in the node whose failure probability is greater than the set probability threshold to obtain the total failure probability of the transmission lines in the node; Calculate the proportion of transmission lines in the node whose failure probability is greater than the set probability threshold among all transmission lines in the node, and obtain the proportion of faulty lines in the node; The total failure probability of the node transmission line and the proportion of node fault lines are weighted and summed to obtain the initial disaster impact factor of each node; The initial disaster impact factors of all nodes are normalized to obtain the disaster impact factor of each node.

4. A method for evaluating the priority of power grid node restoration under extreme conditions according to claim 1, characterized in that: According to the node's disaster information, disaster impact factors and unit recovery benefit dynamic adjustment function, determine the unit output in the node affected by the disaster; According to the node's disaster information, disaster impact factors and load recovery benefit dynamic adjustment function, determine the node load after the disaster; Among them, the dynamic adjustment function of the node's unit recovery benefit is obtained by fitting the disaster impact factors corresponding to the known different disaster information of the node and the unit output in the node after the disaster; The dynamic adjustment function of the node's load recovery benefit is obtained by fitting the disaster impact factors corresponding to the known disaster information of the node and the node load after the disaster.

5. A method for evaluating the priority of power grid node restoration under extreme conditions according to claim 1, characterized in that: Multiply the output of the units in the node affected by the disaster by the unit recovery benefit of the units in the node to obtain the revised expected recovery benefit of the units in the node; Multiply the node load affected by the disaster by the unit recovery benefit of the load in the node to obtain the corrected expected recovery benefit of the load in the node.

6. A method for evaluating the priority of power grid node restoration under extreme conditions according to claim 1, characterized in that: Determine the recovery priority of each node according to the expected recovery benefit of each node; Among them, the greater the expected recovery benefit of the node, the higher the recovery priority of the node, and the node is recovered first.

7. A power grid node restoration priority assessment system under extreme environments, characterized in that: include: An information acquisition module is used to obtain disaster information of each node in the power grid, as well as the failure probability of the line in each node, the unit recovery benefit of the unit and the unit recovery benefit of the load; The impact factor evaluation module is used to calculate and determine the disaster impact factor of each node based on the failure probability of the line in each node; The expected recovery benefit adjustment module is used to determine the unit output and node load in the node affected by the disaster according to the disaster impact factor and disaster information of each node; determine the revised expected recovery benefit of the unit in the node according to the unit output in the node affected by the disaster and the unit recovery benefit of the unit in the node; determine the revised expected recovery benefit of the load in the node according to the node load after the disaster and the unit recovery benefit of the load in the node; A node benefit evaluation module is used to add the corrected expected recovery benefit of the units in each node and the corrected expected recovery benefit of the load to obtain the expected recovery benefit of each node; The node restoration priority determination module is used to determine the restoration priority of each node in the power grid according to the expected restoration benefit of each node.

8. An electronic device, characterized in that: The device comprises: a processor adapted to execute a computer program; A computer-readable storage medium, wherein a computer program is stored in the computer-readable storage medium, and when the computer program is executed by the processor, the method for evaluating the priority of power grid node restoration under extreme environments as described in any one of claims 1 to 6 is implemented.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and the computer program is suitable for being loaded by a processor and executing a method for evaluating the priority of power grid node restoration under extreme environments as described in any one of claims 1 to 6.

10. A computer program product, characterized in that The computer program product comprises a computer program, and when the computer program is executed by a processor, the method for evaluating the priority of power grid node restoration under extreme environment as described in any one of claims 1 to 6 is implemented.

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