Method, device, equipment and medium for evaluating toughness of power system under extreme disasters

Abstract

The invention relates to the technical field of electric power systems, and particularly provides an electric power system toughness evaluation method and device under an extreme disaster, equipment and a medium, and the method comprises the steps: collecting a topological structure of an electric power system; based on the topological structure, determining a scene state of the power system in an extreme disaster evolution process; establishing a network public opinion set according to the levels corresponding to the network public opinions; based on the scene state, evaluating the power supply performance of the power system at each moment after the extreme disaster occurs; based on the network public opinion set, evaluating the network public opinion intensity of the power system at each moment after the extreme disaster occurs; based on the power supply performance of the power system at each moment after the extreme disaster and the network public opinion intensity of the power system at each moment after the extreme disaster, the power system toughness under the extreme disaster is evaluated, the stability of the power system can be improved, and the influence of the disaster is reduced.

Description

Technical Field

[0001] The present application relates to the technical field of power systems, and in particular to a method, device, equipment, and medium for evaluating the resilience of power systems under extreme disasters. Background Art

[0002] Extreme natural disasters, such as typhoons, floods, and earthquakes, have a devastating impact on the power system. The occurrence of disasters not only directly damages the physical infrastructure of the power grid, such as transmission lines and substations, resulting in power supply interruptions, but also its impact will quickly spread to the entire power system, triggering a chain reaction. This impact is not only reflected in the reduction of power supply, but also involves significant changes in the operating status of the power grid, such as reduced power supply capacity, communication and control system failures, etc., posing a serious threat to the stability and reliability of the power grid. As extreme disasters evolve, their impact on the power system will be further intensified. Disasters may trigger secondary disasters, such as landslides and mudslides, which will further damage power grid facilities and make power restoration more difficult. At the same time, the complexity and interconnectedness of the power grid allow faults to spread rapidly, exacerbating the vulnerability of the power grid. In addition, disasters may also cause the power grid to face risks such as overload and overvoltage, further increasing the possibility of damage and failure of power grid equipment.

[0003] As an indicator that characterizes the degree of damage to power system functions after extreme events, power system resilience has become a hot research direction. However, in actual operating scenarios, the evolution of extreme natural disasters is complex, and it is difficult to assess power system damage, making it difficult for power grids to respond effectively. Existing resilience assessment methods often only consider single impact scenarios, making it difficult to accurately characterize the power system damage and performance recovery stages during the evolution of extreme natural disasters. There is an urgent need for a power system resilience assessment framework that can comprehensively consider disaster evolution, emergency response, and external environmental factors, identify weak links in the power system, and characterize the performance level of the power grid under extreme natural disasters. Summary of the invention

[0004] In order to solve one of the above-mentioned technical defects, the present application provides a method, device, equipment and medium for evaluating the resilience of a power system under extreme disasters.

[0005] In a first aspect, the present application provides a method for evaluating the resilience of a power system under extreme disasters, the method comprising: Collect the topology of the power system; Based on the topological structure, determine the scenario status of the power system during the evolution of extreme disasters; Establish a collection of online public opinions according to the corresponding levels of online public opinions; Based on the scenario status, evaluate the power supply performance of the power system at each moment after an extreme disaster occurs; Based on the network public opinion collection, the intensity of network public opinion in the power system at each moment after the extreme disaster occurs is evaluated; The resilience of the power system under extreme disasters is evaluated based on the power supply performance of the power system at each moment after the occurrence of extreme disasters and the intensity of online public opinion of the power system at each moment after the occurrence of extreme disasters.

[0006] In a second aspect of the present application, a device for evaluating the resilience of a power system under extreme disasters is provided, the device comprising: A collection module, used to collect the topological structure of the power system; A determination module is used to determine the scenario state of the power system during the evolution of extreme disasters based on the topological structure collected by the collection module; Establishing a module for establishing a network public opinion collection according to the corresponding levels of network public opinion; A first evaluation module is used to evaluate the power supply performance of the power system at each moment after the extreme disaster occurs based on the scenario state determined by the determination module; The second evaluation module is used to evaluate the intensity of network public opinion of the power system at each moment after the occurrence of extreme disasters based on the network public opinion set established by the establishment module; The third evaluation module is used to evaluate the resilience of the power system under extreme disasters based on the power supply performance of the power system at each moment after the extreme disaster occurs evaluated by the first evaluation module and the intensity of network public opinion of the power system at each moment after the extreme disaster occurs evaluated by the second evaluation module.

[0007] In a third aspect of the present application, an electronic device is provided, including: Memory; processor; and computer program; The computer program is stored in the memory and is configured to be executed by the processor to implement the method as described in the first aspect above.

[0008] In a fourth aspect of the present application, a computer-readable storage medium is provided, on which a computer program is stored; the computer program is executed by a processor to implement the method described in the first aspect above.

[0009] The present application provides a method, device, equipment, and medium for evaluating the resilience of an electric power system under extreme disasters. The method includes: collecting the topological structure of the electric power system; determining the scenario state of the electric power system during the evolution of extreme disasters based on the topological structure; establishing a network public opinion set according to the level corresponding to the network public opinion; evaluating the power supply performance of the electric power system at each moment after the occurrence of an extreme disaster based on the scenario state; evaluating the strength of the network public opinion of the electric power system at each moment after the occurrence of an extreme disaster based on the network public opinion set; evaluating the resilience of the electric power system under extreme disasters based on the power supply performance of the electric power system at each moment after the occurrence of an extreme disaster and the strength of the network public opinion of the electric power system at each moment after the occurrence of an extreme disaster, which can improve the stability of the electric power system and reduce the impact of disasters. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] The drawings described herein are used to provide a further understanding of the present application and constitute a part 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 an improper limitation on the present application. In the drawings: Figure 1 A schematic diagram of a flow chart of a method for evaluating the resilience of a power system under extreme disasters provided in an embodiment of the present application; Figure 2 A schematic diagram of a power system provided in an embodiment of the present application; Figure 3 A schematic diagram of a comprehensive performance evolution curve of a power system at various moments after an extreme disaster occurs, provided in an embodiment of the present application; Figure 4 A schematic diagram of establishing a dynamic Bayesian network model for emergency response in a power system provided in an embodiment of the present application; Figure 5 A schematic diagram of a dynamic Bayesian network model for emergency response of a power system established within 10 days provided in an embodiment of the present application; Figure 6 A schematic diagram of another comprehensive performance evolution curve of a power system at various moments after an extreme disaster occurs provided in an embodiment of the present application; Figure 7 A schematic diagram of the structure of a device for assessing the resilience of a power system under extreme disasters provided in an embodiment of the present application; Figure 8 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0011] In order to make the technical solutions and advantages in the embodiments of the present application more clearly understood, the exemplary embodiments of the present application are further described in detail below in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present application, rather than an exhaustive list of all the embodiments. It should be noted that the embodiments in the present application and the features in the embodiments can be combined with each other without conflict.

[0012] In the process of realizing this application, the inventors found that power system resilience, as an indicator to characterize the degree of damage to power system functions after extreme events, has become a hot research direction. However, in actual operating scenarios, the evolution scenarios of extreme natural disasters are complex, and the assessment of power system damage is difficult, making it difficult for the power grid to respond effectively. Existing resilience assessment methods often only consider single impact scenarios, and it is difficult to accurately characterize the power system damage and performance recovery stages during the evolution of extreme natural disasters. There is an urgent need for a power system resilience assessment framework that can comprehensively consider disaster evolution, emergency response and external environmental factors, identify the weak links in the power system, and characterize the performance level of the power grid under extreme natural disasters.

[0013] In response to the above problems, an embodiment of the present application provides a method, device, equipment, and medium for evaluating the resilience of a power system under extreme disasters. The method includes: collecting the topological structure of the power system; based on the topological structure, determining the scenario state of the power system during the evolution of extreme disasters; establishing a network public opinion set according to the level corresponding to the network public opinion; based on the scenario state, evaluating the power supply performance of the power system at each moment after the occurrence of an extreme disaster; based on the network public opinion set, evaluating the network public opinion intensity of the power system at each moment after the occurrence of an extreme disaster; based on the power supply performance of the power system at each moment after the occurrence of an extreme disaster and the network public opinion intensity of the power system at each moment after the occurrence of an extreme disaster, evaluating the resilience of the power system under extreme disasters. The method provided in this embodiment evaluates the power supply performance of the power system at each moment after the occurrence of an extreme disaster based on the scenario state; based on the network public opinion set, evaluating the network public opinion intensity of the power system at each moment after the occurrence of an extreme disaster; based on the power supply performance of the power system at each moment after the occurrence of an extreme disaster and the network public opinion intensity of the power system at each moment after the occurrence of an extreme disaster, evaluating the resilience of the power system under extreme disasters, which can improve the stability of the power system and reduce the impact of disasters.

[0014] See also Figure 1 This embodiment provides a method for evaluating the resilience of a power system under extreme disasters. The implementation process of the method is as follows: 101, collect the topology of the power system.

[0015] When executing step 101, in addition to collecting the topological structure of the power system, the geographical location of the power system can also be collected to determine the connection method of the power generation nodes, substation nodes, transmission nodes, distribution nodes and user nodes, and determine the environmental information of each node and the location of the transmission line.

[0016] For example, the power system is an IEEE39 node standard system. Figure 2 As shown, there are 10 power generation nodes, 39 load nodes and 46 transmission lines.

[0017] 102. Based on the topological structure, the scenario state of the power system during the evolution of extreme disasters is determined.

[0018] The scenario state is used to describe the performance level of the power system after suffering an extreme natural disaster, mainly including three aspects: power generation performance, transmission performance, and load demand.

[0019] Therefore, in step 102, the possible performance states of the disaster-susceptible bodies (including power nodes, transmission lines and user loads in the power system) during the power system emergency process can be determined and combined to form a scenario state.

[0020] The scenario status includes: the performance status of the power generation node, the performance status of the transmission node, the performance status of the transmission line, and the performance status of the load node.

[0021] The implementation process of step 102 is: divide the power system into four categories: power generation nodes, transmission nodes, transmission lines, and user loads, classify their performance levels during the evolution of extreme natural disasters, and establish a scenario state set. This is specifically implemented through steps 102-1 and 102-2.

[0022] 102-1, determining the power generation nodes, transmission nodes, transmission lines, and load nodes in the power system based on the topological structure.

[0023] 1. Power generation node Power generation nodes include thermal power generation, hydropower generation, wind power generation, photovoltaic power generation and nuclear power generation.

[0024] 2. Transmission Node Transmission nodes include converter stations, substations, and connection substations.

[0025] 3. Load nodes Load nodes include households, commercial facilities, and industrial facilities.

[0026] 102-2, determine the performance status of the power generation node, the performance status of the power transmission node, the performance status of the power transmission line, and the performance status of the load node.

[0027] 1. Performance status of power generation nodes The power generation nodes mainly include thermal power generation, hydropower generation, wind power generation, photovoltaic power generation and nuclear power generation, etc. The method provided in this embodiment uniformly uses power generation as an indicator to measure their performance, takes the installed design capacity as a reference value, and divides the performance level of the power generation node according to the percentage of its actual power supply capacity meeting the installed design capacity, which is specifically divided into five states: "0~20%", "20%~40%", "40%~60%", "60%~80%" and "80%~100%".

[0028] Therefore, the performance states of the power generation nodes include: 0~20%, 20%~40%, 40%~60%, 60%~80%, and 80%~100%.

[0029] The performance status of any power generation node is determined based on the percentage of its actual power supply capacity that meets the installed design capacity.

[0030] 2. Performance status of transmission nodes The transmission nodes mainly include converter stations, substations, connection substations, etc., which are responsible for the collection, distribution, conversion and transmission of electric energy. The method provided in this embodiment uniformly uses the transmission power upper limit as an indicator to measure the performance of such nodes, takes the rated power as a reference value, and divides the performance level of the transmission nodes according to the percentage of their actual transmission power upper limit meeting the rated power. Specifically, it is divided into five states: "0~20%", "20%~40%", "40%~60%", "60%~80%" and "80%~100%".

[0031] Therefore, the performance states of the transmission nodes include: 0~20%, 20%~40%, 40%~60%, 60%~80%, and 80%~100%.

[0032] The performance status of any transmission node is determined by the percentage of its actual transmission power upper limit meeting the rated power.

[0033] 3. Performance status of transmission lines The method provided in this embodiment divides the performance level of the transmission line into five states: "0-20%", "20%-40%", "40%-60%", "60%-80%" and "80%-100%".

[0034] Therefore, the performance states of the transmission lines include: 0~20%, 20%~40%, 40%~60%, 60%~80%, and 80%~100%.

[0035] The performance status of any transmission line is determined based on the percentage of damaged lines.

[0036] 4. Performance status of load nodes Load nodes mainly include households, commercial facilities, industrial facilities, etc. After a disaster occurs, due to factors such as increased emergency demand, increased basic living needs of residents, and electricity demand for reconstruction and restoration work, the post-disaster load demand may exceed the normal scenario demand by several times. The method provided in this embodiment uses load demand as an indicator to measure the performance of load nodes, takes the average load demand in normal scenarios as a reference value, and divides the load node performance level according to the ratio of actual load demand to the average load demand in normal scenarios, specifically divided into five states: "0~33%", "33%~66%", "66%~100%", "100%~150%" and "150%~200%".

[0037] Among them, the performance status of load nodes includes: 0~33%, 33%~66%, 66%~100%, 100%~150%, 150%~200. The performance status of any load node is determined according to the ratio of its actual load demand to the average load demand under normal scenarios.

[0038] In addition, a scenario state set can also be formed. For example, a set of vectors containing four types of subject performance states is formed by the performance state of the power generation node, the performance state of the transmission node, the performance state of the transmission line, and the performance state of the load node to obtain a scenario state set.

[0039] In addition, when executing the method provided in the embodiment itself, the disposal measures of the power system during the emergency process, the disaster characteristics of extreme natural disasters and environmental factors will also be determined.

[0040] 1. Disposal measures Among them, the disposal measures are determined by the emergency response degree of the key departments of the power system during the emergency process. For example, the functional division of the key departments in the power system emergency process is determined to obtain the disposal measures.

[0041] Key departments include: power grid dispatching group, production recovery group, electricity marketing group, security group, information release group and material support group.

[0042] The emergency response level of any key department is one of the following: Level I, Level II, Level III and Level IV.

[0043] In addition, in specific implementation, a set of disposal measures can also be constructed based on disposal measures. For example, according to the emergency organizational structure and management system of the power system, the departments involved in emergency activities are divided into power grid dispatching group, production recovery group, power marketing group, security group, information release group and material support group. The emergency response level of each group includes four levels: Level I (especially serious), Level II (serious), Level III (large) and Level IV (general). The emergency response levels of the five groups constitute a set of disposal measures, that is, a five-dimensional vector containing the response levels of different departments.

[0044] 2. Disaster characteristics of extreme natural disasters When the extreme natural disaster is an earthquake, the disaster characteristic is intensity, which is graded as follows: 0 (not occurring), Ⅰ~Ⅳ, Ⅴ~VI, Ⅶ~VIII, Ⅸ~X, and Ⅺ~XII.

[0045] When the extreme natural disaster is a landslide, the disaster characteristic is the volume of the landslide, which is graded as follows: 0 (not occurring), less than 100,000 cubic meters (small landslide), 100,000 to 1 million cubic meters (medium-sized landslide), 1 to 10 million cubic meters (large landslide), and more than 10 million cubic meters (giant landslide).

[0046] When the extreme natural disaster is a rainstorm, the disaster characteristic is the precipitation, which is graded as follows: less than 49.9 mm (non-rainstorm), 50.0~99.9 mm (rainstorm), 100.0~249.9 mm (heavy rainstorm), and more than 250.0 mm (extremely heavy rainstorm).

[0047] When the extreme natural disaster is a flood, the disaster characteristic is the peak flow, which is graded as follows: 0 (not occurring), less than 500 cubic meters per second, 500-1000 cubic meters per second, 1000-1500 cubic meters per second, and more than 1500 cubic meters per second.

[0048] When the extreme natural disaster is waterlogging, the disaster characteristic is the depth of water accumulation, which is graded as follows: below 15 cm, 15-27 cm, 27-40 cm, 40-60 cm, and above 60 cm.

[0049] For example, according to the disaster type, the disaster characteristic elements and the corresponding classification method are determined to obtain the disaster characteristics shown in Table 1. For the disaster types not included in the table, the corresponding characteristic indicators can be considered. When the natural disaster set is dimensional vector.

[0050] Table 1

[0051] 3. Environmental factors Environmental factors include: altitude, geological structure, 24-hour precipitation, air humidity (relative humidity), and temperature (weighted average temperature).

[0052] Among them, the altitude classification is: below 500 meters, 500~1000 meters, 1000~1500 meters, 1500~2000 meters, and above 2000 meters.

[0053] The geological structures are classified into: monocline structure, fold structure, fault structure and block structure.

[0054] The 24-hour precipitation classification is: less than 0.1 mm (trace rainfall), 0.1~9.9 mm (light rain), 10.0~24.9 mm (moderate rain), 25.0~49.9 mm (heavy rain), 50.0~99.9 mm (rainstorm), 100.0~249.9 mm (heavy rainstorm), and above 250.0 mm (extremely heavy rainstorm).

[0055] The air humidity levels are: 0~40%, 40%~60%, 60%~80%, and above 80%.

[0056] The temperature is classified into: below 25 degrees Celsius, 25~30 degrees Celsius, 30~35 degrees Celsius, 35~40 degrees Celsius, and above 40 degrees Celsius.

[0057] For example, environmental factors related to disaster breeding and development are determined according to the disaster type, and the environmental factors shown in Table 2 are obtained. For environmental factors not included in the table, corresponding classification standards can be considered. When the natural disaster set is the level of various environmental factors dimensional vector.

[0058] Table 2

[0059] In addition, in specific implementation, it is also possible to construct a natural disaster set and an external environment set based on the disaster characteristics and environmental factors of extreme natural disasters.

[0060] 103. Establish a network public opinion collection according to the corresponding levels of network public opinions.

[0061] The network public opinion set is a one-dimensional vector corresponding to the level of actual network public opinion.

[0062] The collection of online public opinion includes: particularly serious Internet public opinion events (Level IV), serious Internet public opinion events (Level III), relatively large Internet public opinion events (Level II), general Internet public opinion events (Level I), and no negative public opinion.

[0063] For example, online public opinion is divided into four levels according to the speed of propagation and the scope of influence. The specific meanings are shown in Table 3.

[0064] Table 3

[0065] 104. Based on the scenario status, evaluate the power supply performance of the power system at each moment after an extreme disaster occurs.

[0066] The power supply performance of the power system at each moment after an extreme disaster occurs is determined according to the value of the scenario state set at that moment, that is, according to the actual states of power generation nodes, transmission nodes, transmission lines and load nodes.

[0067] Since the scenario status includes: the performance status of the power generation node, the performance status of the transmission node, the performance status of the transmission line, and the performance status of the load node, therefore, step 104 will evaluate the power supply performance of the power system at any time after the extreme disaster occurs through the following formula: .

[0068] in, To mark the moment, To strengthen the power system after extreme disasters The power supply performance at the moment, the value range is [0, 1].

[0069] is the supply-demand ratio, that is, the ratio of the upper limit of load supply to the load demand of the power system. , To strengthen the power system after extreme disasters The performance status of the power generation node at the moment, To strengthen the power system after extreme disasters The performance status of the transmission node at the time, To protect the power system after extreme disasters The performance status of the transmission line at the transmission node at the time, To protect the power system after extreme disasters The performance status of the load node at the moment.

[0070] It is the supply and demand factor, which is generally not less than 1. , It is the upper limit of load supply during normal operation of the power system. It is the average load demand during normal operation of the power system.

[0071] 105. Based on the network public opinion collection, the intensity of network public opinion on the power system at each moment after the extreme disaster occurs is evaluated.

[0072] The intensity of online public opinion is obtained based on the set of online public opinions, where no negative public opinion, level I, level II, level III, and level IV correspond to 1, 0.75, 0.5, 0.25, and 0, respectively, and is used to characterize the impact of online public opinion in actual scenarios. That is, the smaller the public opinion, the higher the network performance.

[0073] 106. Evaluate the resilience of the power system under extreme disasters based on the power supply performance of the power system at each moment after the occurrence of extreme disasters and the intensity of online public opinion on the power system at each moment after the occurrence of extreme disasters.

[0074] In specific implementation, the following formula can be used to evaluate the resilience of the power system under extreme disasters: .

[0075] in, To improve the resilience of power systems under extreme disasters, When extreme disasters occur, is the total duration of the power system resilience assessment, is the initial comprehensive performance of the power system, which is 1.

[0076] To strengthen the power system after extreme disasters The comprehensive performance of the power system at all times after an extreme disaster The power supply performance and network public opinion strength at the moment are jointly characterized, and the value range is [0, 1]. , To strengthen the power system after extreme disasters Power supply performance at all times, To strengthen the power system after extreme disasters The intensity of online public opinion at all times, is the power supply performance weight, is the network public opinion intensity weight, .

[0077] For example, Figure 3 The figure shows the comprehensive performance evolution curve of the power system at each moment after an extreme disaster occurs, where the shaded area represents the resilience of the power system under the corresponding extreme disaster.

[0078] If the power system's emergency response measures, disaster characteristics and environmental factors of extreme natural disasters are also determined during the specific implementation, step 106 can also evaluate the power system's resilience under extreme disasters based on the power system's emergency response measures, disaster characteristics and environmental factors of extreme natural disasters, the power supply performance of the power system at each moment after the extreme disaster occurs, and the intensity of network public opinion of the power system at each moment after the extreme disaster occurs.

[0079] Based on the power system's emergency response measures, the disaster characteristics and environmental factors of extreme natural disasters, the power supply performance of the power system at each moment after the extreme disaster, and the intensity of online public opinion at each moment after the extreme disaster, the resilience of the power system under extreme disasters can be assessed through the following steps: 1. Couple the scenario status, disposal measures, natural disasters, disaster characteristics of extreme natural disasters and environmental factors to establish a dynamic Bayesian network model for emergency disposal of power system.

[0080] For example, the scenario status, disposal measures, natural disasters, external environment and network public opinion collection are coupled. In actual scenarios, environmental factors affect natural disasters at the current moment, and disaster characteristics affect network public opinion and power grid scenario status. The emergency management department formulates emergency plans for each department based on the scenario status and network public opinion. After the emergency plan is implemented, the scenario status and network public opinion at the next moment are updated according to the current scenario status and network public opinion status. At the same time, environmental factors and natural disasters will be updated as time evolves, thereby establishing a dynamic Bayesian network model for emergency disposal of the power system, such as Figure 4 shown.

[0081] For example, a dynamic Bayesian network model for emergency response of power system can be established within 10 days with a unit of 24 hours. Figure 5 shown.

[0082] 2. Based on the dynamic Bayesian network model of power system emergency response, the power supply performance of the power system at each moment after the occurrence of extreme disasters, and the intensity of network public opinion of the power system at each moment after the occurrence of extreme disasters, the resilience of the power system under extreme disasters is evaluated.

[0083] The specific implementation process here is as follows: (1) Determine the initial status of the power system, natural disasters, external environment, and online public opinion.

[0084] For example, when determining the initial state of the power system, the power generation nodes, load nodes and transmission lines are all in normal working state.

[0085] (2) Based on the dynamic Bayesian network model of power system emergency response, the power supply performance of the power system at each moment after the occurrence of extreme disasters, the intensity of network public opinion of the power system at each moment after the occurrence of extreme disasters, the initial state of the power system, natural disasters, external environment and network public opinion, an inference algorithm is used to obtain the evolution of the power system and network public opinion, and the resilience index is calculated.

[0086] For example, based on the power supply performance of the power system at each moment after the occurrence of extreme disasters, the intensity of online public opinion of the power system at each moment after the occurrence of extreme disasters, the initial state of the power system, natural disasters, external environment and online public opinion, the data shown in Table 4 are obtained, where the values ​​"1-7" in "precipitation" represent the corresponding state intervals in the Bayesian network corresponding to the actual data, respectively corresponding to less than 0.1 mm, 0.1-9.9 mm, 10.0-24.9 mm, 25.0-49.9 mm, 50.0-99.9 mm, 100.0-249.9 mm, and more than 250.0 mm. The numerical sequence represents the evolution of precipitation in the area in the next 10 days. Other environmental factors such as the normalized vegetation index and watershed area are fixed values ​​and do not change over time.

[0087] Table 4

[0088] The above data shown in Table 4 are input into the dynamic Bayesian network model of power system emergency response, and the connection tree inference algorithm is used to obtain the situation status and network public opinion evolution. Figure 6 The comprehensive performance evolution curve of the power system shown in the formula is The calculated toughness index is 89.6%.

[0089] The power system resilience assessment method under extreme disasters provided in this embodiment is a resilience assessment method that can characterize the evolution mode of extreme natural disasters, the execution of emergency response plans, and the evolution scenarios of damage and power supply levels, thereby characterizing the power supply performance of the power system during the entire disaster cycle. It can help operators carry out power system resilience assessment work under the evolution of extreme natural disasters, and provide theoretical support for improving the stability of the power system and reducing the impact of disasters.

[0090] The present embodiment provides a method for evaluating the resilience of a power system under extreme disasters, the method comprising: collecting the topological structure of the power system; based on the topological structure, determining the scenario state of the power system during the evolution of extreme disasters; establishing a network public opinion set according to the level corresponding to the network public opinion; based on the scenario state, evaluating the power supply performance of the power system at each moment after the occurrence of an extreme disaster; based on the network public opinion set, evaluating the network public opinion intensity of the power system at each moment after the occurrence of an extreme disaster; based on the power supply performance of the power system at each moment after the occurrence of an extreme disaster and the network public opinion intensity of the power system at each moment after the occurrence of an extreme disaster, evaluating the resilience of the power system under extreme disasters. The method provided in the present embodiment evaluates the power supply performance of the power system at each moment after the occurrence of an extreme disaster based on the scenario state; based on the network public opinion set, evaluating the network public opinion intensity of the power system at each moment after the occurrence of an extreme disaster; based on the power supply performance of the power system at each moment after the occurrence of an extreme disaster and the network public opinion intensity of the power system at each moment after the occurrence of an extreme disaster, evaluating the resilience of the power system under extreme disasters, which can improve the stability of the power system and reduce the impact of disasters.

[0091] Based on the same inventive concept of the method for evaluating the resilience of a power system under extreme disasters, this embodiment provides an electronic device, see Figure 7 , the device comprises: The acquisition module 701 is used to acquire the topological structure of the power system.

[0092] The determination module 702 is used to determine the scenario state of the power system during the evolution of extreme disasters based on the topological structure collected by the collection module 701.

[0093] The establishment module 703 is used to establish a network public opinion set according to the corresponding level of the network public opinion.

[0094] The first evaluation module 704 is used to evaluate the power supply performance of the power system at each moment after the extreme disaster occurs based on the scenario state determined by the determination module 702.

[0095] The second evaluation module 705 is used to evaluate the intensity of network public opinion of the power system at each moment after the extreme disaster occurs based on the network public opinion set established by the establishment module 703.

[0096] The third evaluation module 706 is used to evaluate the resilience of the power system under extreme disasters based on the power supply performance of the power system at each moment after the extreme disaster occurs evaluated by the first evaluation module 704 and the intensity of network public opinion of the power system at each moment after the extreme disaster occurs evaluated by the second evaluation module 705.

[0097] The scenario status includes: the performance status of the power generation node, the performance status of the transmission node, the performance status of the transmission line, and the performance status of the load node.

[0098] Based on the topological structure, determine the scenario status of the power system during the evolution of extreme disasters, including: Based on the topological structure, the power generation nodes, transmission nodes, transmission lines, and load nodes in the power system are determined. Among them, the power generation nodes include thermal power generation, hydropower generation, wind power generation, photovoltaic power generation, and nuclear power generation. The transmission nodes include converter stations, substations, and wiring substations. The load nodes include households, commercial facilities, and industrial facilities.

[0099] Determine the performance status of the power generation node, the performance status of the transmission node, the performance status of the transmission line, and the performance status of the load node. Among them, the performance status of the power generation node includes: 0~20%, 20%~40%, 40%~60%, 60%~80%, 80%~100%, and the performance status of any power generation node is determined according to the percentage of its actual power supply capacity meeting the installed design capacity. The performance status of the transmission node includes: 0~20%, 20%~40%, 40%~60%, 60%~80%, 80%~100%, and the performance status of any transmission node is determined according to the percentage of its actual transmission power upper limit meeting the rated power. The performance status of the transmission line includes: 0~20%, 20%~40%, 40%~60%, 60%~80%, 80%~100%, and the performance status of any transmission line is determined according to the percentage of damaged lines. The performance states of load nodes include: 0~33%, 33%~66%, 66%~100%, 100%~150%, and 150%~200. The performance state of any load node is determined based on the ratio of its actual load demand to the average load demand under normal scenarios.

[0100] The scenario status includes: the performance status of the power generation node, the performance status of the transmission node, the performance status of the transmission line, and the performance status of the load node.

[0101] Based on the scenario status, the power supply performance of the power system at each moment after an extreme disaster occurs is evaluated, including: The power supply performance of the power system at any time after an extreme disaster occurs is evaluated by the following formula: .

[0102] in, To mark the moment, To strengthen the power system after extreme disasters Power supply performance at all times, The supply-demand ratio. , To strengthen the power system after extreme disasters The performance status of the power generation node at the moment, To strengthen the power system after extreme disasters The performance status of the transmission node at the time, To protect the power system after extreme disasters The performance status of the transmission line at the transmission node at the time, To protect the power system after extreme disasters The performance status of the load node at the time, is the supply and demand factor. , It is the upper limit of load supply during normal operation of the power system. It is the average load demand during normal operation of the power system.

[0103] The third evaluation module 706 is used to evaluate the resilience of the power system under extreme disasters by using the following formula: .

[0104] in, To improve the resilience of power systems under extreme disasters, When extreme disasters occur, is the total duration of the power system resilience assessment, is the initial comprehensive performance of the power system, To protect the power system after extreme disasters Comprehensive performance at all times. , To protect the power system after extreme disasters Power supply performance at all times, To protect the power system after extreme disasters The intensity of online public opinion at all times, is the power supply performance weight, is the network public opinion intensity weight, .

[0105] Among them, the collection of online public opinion includes: particularly serious Internet public opinion events, serious Internet public opinion events, relatively large Internet public opinion events, general Internet public opinion events, and no negative public opinion.

[0106] The device further includes a processing module for determining the disposal measures of the power system during an emergency, the disaster characteristics of extreme natural disasters and environmental factors. The disposal measures are determined by the emergency response degree of key departments of the power system during an emergency.

[0107] Among them, the third evaluation module 706 is used to evaluate the resilience of the power system under extreme disasters based on the power system's emergency response measures, disaster characteristics and environmental factors of extreme natural disasters, the power supply performance of the power system at each moment after the extreme disaster occurs, and the intensity of network public opinion of the power system at each moment after the extreme disaster occurs.

[0108] Among them, key departments include: power grid dispatching group, production recovery group, power marketing group, security group, information release group and material support group. The emergency response level of any key department is one of the following: Level I, Level II, Level III and Level IV.

[0109] When the extreme natural disaster is an earthquake, the disaster characteristic is intensity, which is graded as follows: 0, Ⅰ~Ⅳ, Ⅴ~VI, Ⅶ~VIII, Ⅸ~X, Ⅺ~XII.

[0110] When the extreme natural disaster is a landslide, the disaster characteristic is the volume of the landslide, which is graded as follows: 0, less than 100,000 cubic meters, 100,000 to 1 million cubic meters, 1 million to 10 million cubic meters, and more than 10 million cubic meters.

[0111] When the extreme natural disaster is rainstorm, the disaster characteristic is precipitation, which is graded as follows: less than 49.9 mm, 50.0~99.9 mm, 100.0~249.9 mm, and above 250.0 mm.

[0112] When the extreme natural disaster is a flood, the disaster characteristic is the peak flow, which is graded as follows: 0, less than 500 cubic meters per second, 500-1000 cubic meters per second, 1000-1500 cubic meters per second, and more than 1500 cubic meters per second.

[0113] When the extreme natural disaster is waterlogging, the disaster characteristic is the depth of water accumulation, which is graded as follows: below 15 cm, 15-27 cm, 27-40 cm, 40-60 cm, and above 60 cm.

[0114] Environmental factors include: altitude, geological structure, 24-hour precipitation, air humidity, and temperature.

[0115] Among them, the altitude classification is: below 500 meters, 500~1000 meters, 1000~1500 meters, 1500~2000 meters, and above 2000 meters.

[0116] The geological structures are classified into: monocline structure, fold structure, fault structure and block structure.

[0117] The 24-hour precipitation levels are: below 0.1 mm, 0.1~9.9 mm, 10.0~24.9 mm, 25.0~49.9 mm, 50.0~99.9 mm, 100.0~249.9 mm, and above 250.0 mm.

[0118] The air humidity levels are: 0~40%, 40%~60%, 60%~80%, and above 80%.

[0119] The temperature is classified into: below 25 degrees Celsius, 25~30 degrees Celsius, 30~35 degrees Celsius, 35~40 degrees Celsius, and above 40 degrees Celsius.

[0120] The device provided in this embodiment evaluates the power supply performance of the power system at each moment after the occurrence of an extreme disaster based on the situational state; evaluates the strength of the network public opinion of the power system at each moment after the occurrence of an extreme disaster based on the network public opinion set; and evaluates the resilience of the power system under extreme disasters based on the power supply performance of the power system at each moment after the occurrence of an extreme disaster and the strength of the network public opinion of the power system at each moment after the occurrence of an extreme disaster, which can improve the stability of the power system and reduce the impact of disasters.

[0121] Based on the same inventive concept of a method for evaluating the resilience of a power system under extreme disasters, this embodiment provides an electronic device, such as Figure 8 As shown, it includes: a memory 801, a processor 802, and a computer program.

[0122] The computer program is stored in the memory 801 and is configured to be executed by the processor 802 to implement the above-mentioned method for assessing the resilience of the power system under extreme disasters.

[0123] Specifically, Collect the topology of the power system.

[0124] Based on the topological structure, the scenario state of the power system during the evolution of extreme disasters is determined.

[0125] Establish a collection of online public opinions according to the corresponding levels of online public opinions.

[0126] Based on the scenario status, the power supply performance of the power system at each moment after an extreme disaster occurs is evaluated.

[0127] Based on the collection of online public opinion, the intensity of online public opinion in the power system at each moment after an extreme disaster occurs is evaluated.

[0128] The resilience of the power system under extreme disasters is evaluated based on the power supply performance of the power system at each moment after the occurrence of extreme disasters and the intensity of online public opinion of the power system at each moment after the occurrence of extreme disasters.

[0129] Optionally, the scenario status includes: the performance status of the power generation node, the performance status of the power transmission node, the performance status of the power transmission line, and the performance status of the load node.

[0130] Based on the topological structure, determine the scenario status of the power system during the evolution of extreme disasters, including: Based on the topological structure, the power generation nodes, transmission nodes, transmission lines, and load nodes in the power system are determined. Among them, the power generation nodes include thermal power generation, hydropower generation, wind power generation, photovoltaic power generation, and nuclear power generation. The transmission nodes include converter stations, substations, and wiring substations. The load nodes include households, commercial facilities, and industrial facilities.

[0131] Determine the performance status of the power generation node, the performance status of the transmission node, the performance status of the transmission line, and the performance status of the load node. Among them, the performance status of the power generation node includes: 0~20%, 20%~40%, 40%~60%, 60%~80%, 80%~100%, and the performance status of any power generation node is determined according to the percentage of its actual power supply capacity meeting the installed design capacity. The performance status of the transmission node includes: 0~20%, 20%~40%, 40%~60%, 60%~80%, 80%~100%, and the performance status of any transmission node is determined according to the percentage of its actual transmission power upper limit meeting the rated power. The performance status of the transmission line includes: 0~20%, 20%~40%, 40%~60%, 60%~80%, 80%~100%, and the performance status of any transmission line is determined according to the percentage of damaged lines. The performance states of load nodes include: 0~33%, 33%~66%, 66%~100%, 100%~150%, and 150%~200. The performance state of any load node is determined based on the ratio of its actual load demand to the average load demand under normal scenarios.

[0132] Optionally, the scenario status includes: the performance status of the power generation node, the performance status of the power transmission node, the performance status of the power transmission line, and the performance status of the load node.

[0133] Based on the scenario status, the power supply performance of the power system at each moment after an extreme disaster occurs is evaluated, including: The power supply performance of the power system at any time after an extreme disaster occurs is evaluated by the following formula: .

[0134] in, To mark the moment, To strengthen the power system after extreme disasters Power supply performance at all times, The supply-demand ratio. , To strengthen the power system after extreme disasters The performance status of the power generation node at the moment, To strengthen the power system after extreme disasters The performance status of the transmission node at the time, To strengthen the power system after extreme disasters The performance status of the transmission line at the transmission node at the time, To protect the power system after extreme disasters The performance status of the load node at the time, is the supply and demand factor. , It is the upper limit of load supply during normal operation of the power system. It is the average load demand during normal operation of the power system.

[0135] Optionally, based on the power supply performance of the power system at each moment after the extreme disaster occurs and the intensity of network public opinion of the power system at each moment after the extreme disaster occurs, the resilience of the power system under extreme disasters is evaluated, including: The resilience of the power system under extreme disasters is evaluated by the following formula: .

[0136] in, To improve the resilience of power systems under extreme disasters, When extreme disasters occur, is the total duration of the power system resilience assessment, is the initial comprehensive performance of the power system, To protect the power system after extreme disasters Comprehensive performance at all times. , To protect the power system after extreme disasters Power supply performance at all times, To protect the power system after extreme disasters The intensity of online public opinion at all times, is the power supply performance weight, is the network public opinion intensity weight, .

[0137] Optionally, the network public opinion collection includes: particularly serious Internet public opinion events, serious Internet public opinion events, relatively serious Internet public opinion events, general Internet public opinion events, and no negative public opinion.

[0138] Optionally, the method further includes: Determine the power system's response measures during emergencies, the disaster characteristics of extreme natural disasters, and environmental factors. The response measures are determined by the emergency response level of key departments in the power system during emergencies.

[0139] Based on the power supply performance of the power system at each moment after the extreme disaster occurs and the intensity of online public opinion of the power system at each moment after the extreme disaster occurs, the resilience of the power system under extreme disasters is evaluated, including: The resilience of the power system under extreme disasters is assessed based on the power system's emergency response measures, the disaster characteristics and environmental factors of extreme natural disasters, the power supply performance of the power system at each moment after the extreme disaster occurs, and the intensity of online public opinion of the power system at each moment after the extreme disaster occurs.

[0140] Optionally, the key departments include: power grid dispatching group, production recovery group, power marketing group, security group, information release group and material support group. The emergency response level of any key department is one of the following: level I, level II, level III and level IV.

[0141] When the extreme natural disaster is an earthquake, the disaster characteristic is intensity, which is graded as follows: 0, Ⅰ~Ⅳ, Ⅴ~VI, Ⅶ~VIII, Ⅸ~X, Ⅺ~XII.

[0142] When the extreme natural disaster is a landslide, the disaster characteristic is the volume of the landslide, which is graded as follows: 0, less than 100,000 cubic meters, 100,000 to 1 million cubic meters, 1 million to 10 million cubic meters, and more than 10 million cubic meters.

[0143] When the extreme natural disaster is rainstorm, the disaster characteristic is precipitation, which is graded as follows: less than 49.9 mm, 50.0~99.9 mm, 100.0~249.9 mm, and above 250.0 mm.

[0144] When the extreme natural disaster is a flood, the disaster characteristic is the peak flow, which is graded as follows: 0, less than 500 cubic meters per second, 500-1000 cubic meters per second, 1000-1500 cubic meters per second, and more than 1500 cubic meters per second.

[0145] When the extreme natural disaster is waterlogging, the disaster characteristic is the depth of water accumulation, which is graded as follows: below 15 cm, 15-27 cm, 27-40 cm, 40-60 cm, and above 60 cm.

[0146] Environmental factors include: altitude, geological structure, 24-hour precipitation, air humidity, and temperature.

[0147] Among them, the altitude classification is: below 500 meters, 500~1000 meters, 1000~1500 meters, 1500~2000 meters, and above 2000 meters.

[0148] The geological structures are classified into: monocline structure, fold structure, fault structure and block structure.

[0149] The 24-hour precipitation levels are: below 0.1 mm, 0.1~9.9 mm, 10.0~24.9 mm, 25.0~49.9 mm, 50.0~99.9 mm, 100.0~249.9 mm, and above 250.0 mm.

[0150] The air humidity levels are: 0~40%, 40%~60%, 60%~80%, and above 80%.

[0151] The temperature is classified into: below 25 degrees Celsius, 25~30 degrees Celsius, 30~35 degrees Celsius, 35~40 degrees Celsius, and above 40 degrees Celsius.

[0152] The electronic device provided in this embodiment has a computer program executed by a processor to evaluate the power supply performance of the power system at each moment after the occurrence of an extreme disaster based on the scenario state; to evaluate the strength of the network public opinion of the power system at each moment after the occurrence of an extreme disaster based on a set of network public opinions; and to evaluate the resilience of the power system under extreme disasters based on the power supply performance of the power system at each moment after the occurrence of an extreme disaster and the strength of the network public opinion of the power system at each moment after the occurrence of an extreme disaster, thereby improving the stability of the power system and reducing the impact of disasters.

[0153] Based on the same inventive concept of the method for assessing the resilience of a power system under extreme disasters, this embodiment provides a computer-readable storage medium on which a computer program is stored. The computer program is executed by a processor to implement the method for assessing the resilience of a power system under extreme disasters.

[0154] Specifically, Collect the topology of the power system.

[0155] Based on the topological structure, the scenario state of the power system during the evolution of extreme disasters is determined.

[0156] Establish a collection of online public opinions according to the corresponding levels of online public opinions.

[0157] Based on the scenario status, the power supply performance of the power system at each moment after an extreme disaster occurs is evaluated.

[0158] Based on the collection of online public opinion, the intensity of online public opinion in the power system at each moment after an extreme disaster occurs is evaluated.

[0159] The resilience of the power system under extreme disasters is evaluated based on the power supply performance of the power system at each moment after the occurrence of extreme disasters and the intensity of online public opinion of the power system at each moment after the occurrence of extreme disasters.

[0160] Optionally, the scenario status includes: the performance status of the power generation node, the performance status of the power transmission node, the performance status of the power transmission line, and the performance status of the load node.

[0161] Based on the topological structure, determine the scenario status of the power system during the evolution of extreme disasters, including: Based on the topological structure, the power generation nodes, transmission nodes, transmission lines, and load nodes in the power system are determined. Among them, the power generation nodes include thermal power generation, hydropower generation, wind power generation, photovoltaic power generation, and nuclear power generation. The transmission nodes include converter stations, substations, and wiring substations. The load nodes include households, commercial facilities, and industrial facilities.

[0162] Determine the performance status of the power generation node, the performance status of the transmission node, the performance status of the transmission line, and the performance status of the load node. Among them, the performance status of the power generation node includes: 0~20%, 20%~40%, 40%~60%, 60%~80%, 80%~100%, and the performance status of any power generation node is determined according to the percentage of its actual power supply capacity meeting the installed design capacity. The performance status of the transmission node includes: 0~20%, 20%~40%, 40%~60%, 60%~80%, 80%~100%, and the performance status of any transmission node is determined according to the percentage of its actual transmission power upper limit meeting the rated power. The performance status of the transmission line includes: 0~20%, 20%~40%, 40%~60%, 60%~80%, 80%~100%, and the performance status of any transmission line is determined according to the percentage of damaged lines. The performance states of load nodes include: 0~33%, 33%~66%, 66%~100%, 100%~150%, and 150%~200. The performance state of any load node is determined based on the ratio of its actual load demand to the average load demand under normal scenarios.

[0163] Optionally, the scenario status includes: the performance status of the power generation node, the performance status of the power transmission node, the performance status of the power transmission line, and the performance status of the load node.

[0164] Based on the scenario status, the power supply performance of the power system at each moment after an extreme disaster occurs is evaluated, including: The power supply performance of the power system at any time after an extreme disaster occurs is evaluated by the following formula: .

[0165] in, To mark the moment, To protect the power system after extreme disasters Power supply performance at all times, The supply-demand ratio. , To protect the power system after extreme disasters The performance status of the power generation node at the moment, To protect the power system after extreme disasters The performance status of the transmission node at the time, To protect the power system after extreme disasters The performance status of the transmission line at the transmission node at the time, To protect the power system after extreme disasters The performance status of the load node at the time, is the supply and demand factor. , It is the upper limit of load supply during normal operation of the power system. It is the average load demand during normal operation of the power system.

[0166] Optionally, based on the power supply performance of the power system at each moment after the extreme disaster occurs and the intensity of network public opinion of the power system at each moment after the extreme disaster occurs, the resilience of the power system under extreme disasters is evaluated, including: The resilience of the power system under extreme disasters is evaluated by the following formula: .

[0167] in, To improve the resilience of power systems under extreme disasters, When extreme disasters occur, is the total duration of the power system resilience assessment, is the initial comprehensive performance of the power system, To protect the power system after extreme disasters Comprehensive performance at all times. , To protect the power system after extreme disasters Power supply performance at all times, To protect the power system after extreme disasters The intensity of online public opinion at all times, is the power supply performance weight, is the network public opinion intensity weight, .

[0168] Optionally, the network public opinion collection includes: particularly serious Internet public opinion events, serious Internet public opinion events, relatively serious Internet public opinion events, general Internet public opinion events, and no negative public opinion.

[0169] Optionally, the method further includes: Determine the power system's response measures during emergencies, the disaster characteristics of extreme natural disasters, and environmental factors. The response measures are determined by the emergency response level of key departments in the power system during emergencies.

[0170] Based on the power supply performance of the power system at each moment after the extreme disaster occurs and the intensity of online public opinion of the power system at each moment after the extreme disaster occurs, the resilience of the power system under extreme disasters is evaluated, including: The resilience of the power system under extreme disasters is assessed based on the power system's emergency response measures, the disaster characteristics and environmental factors of extreme natural disasters, the power supply performance of the power system at each moment after the extreme disaster occurs, and the intensity of online public opinion of the power system at each moment after the extreme disaster occurs.

[0171] Optionally, the key departments include: power grid dispatching group, production recovery group, power marketing group, security group, information release group and material support group. The emergency response level of any key department is one of the following: level I, level II, level III and level IV.

[0172] When the extreme natural disaster is an earthquake, the disaster characteristic is intensity, which is graded as follows: 0, Ⅰ~Ⅳ, Ⅴ~VI, Ⅶ~VIII, Ⅸ~X, Ⅺ~XII.

[0173] When the extreme natural disaster is a landslide, the disaster characteristic is the volume of the landslide, which is graded as follows: 0, less than 100,000 cubic meters, 100,000 to 1 million cubic meters, 1 million to 10 million cubic meters, and more than 10 million cubic meters.

[0174] When the extreme natural disaster is rainstorm, the disaster characteristic is precipitation, which is graded as follows: less than 49.9 mm, 50.0~99.9 mm, 100.0~249.9 mm, and above 250.0 mm.

[0175] When the extreme natural disaster is a flood, the disaster characteristic is the peak flow, which is graded as follows: 0, less than 500 cubic meters per second, 500-1000 cubic meters per second, 1000-1500 cubic meters per second, and more than 1500 cubic meters per second.

[0176] When the extreme natural disaster is waterlogging, the disaster characteristic is the depth of water accumulation, which is graded as follows: below 15 cm, 15-27 cm, 27-40 cm, 40-60 cm, and above 60 cm.

[0177] Environmental factors include: altitude, geological structure, 24-hour precipitation, air humidity, and temperature.

[0178] Among them, the altitude classification is: below 500 meters, 500~1000 meters, 1000~1500 meters, 1500~2000 meters, and above 2000 meters.

[0179] The geological structures are classified into: monocline structure, fold structure, fault structure and block structure.

[0180] The 24-hour precipitation levels are: below 0.1 mm, 0.1~9.9 mm, 10.0~24.9 mm, 25.0~49.9 mm, 50.0~99.9 mm, 100.0~249.9 mm, and above 250.0 mm.

[0181] The air humidity levels are: 0~40%, 40%~60%, 60%~80%, and above 80%.

[0182] The temperature is classified into: below 25 degrees Celsius, 25~30 degrees Celsius, 30~35 degrees Celsius, 35~40 degrees Celsius, and above 40 degrees Celsius.

[0183] The computer-readable storage medium provided in this embodiment has a computer program executed by a processor to evaluate the power supply performance of the power system at each moment after the occurrence of an extreme disaster based on the scenario state; to evaluate the strength of the network public opinion of the power system at each moment after the occurrence of an extreme disaster based on a set of network public opinions; and to evaluate the resilience of the power system under extreme disasters based on the power supply performance of the power system at each moment after the occurrence of an extreme disaster and the strength of the network public opinion of the power system at each moment after the occurrence of an extreme disaster, thereby improving the stability of the power system and reducing the impact of disasters.

[0184] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes. The schemes in the embodiments of the present application may be implemented in various computer languages, for example, object-oriented programming language Java and literal scripting language JavaScript, etc.

[0185] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0186] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0187] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0188] Although the preferred embodiments of the present application have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications falling within the scope of the present application.

[0189] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include these modifications and variations.

Claims

1. A method for assessing the resilience of a power system under extreme disasters, characterized in that: The method comprises: Collect the topology of the power system; Based on the topological structure, determining the scenario state of the power system during the evolution of extreme disasters; Establish a collection of online public opinions according to the corresponding levels of online public opinions; Based on the scenario status, evaluate the power supply performance of the power system at each moment after the extreme disaster occurs; Based on the network public opinion set, evaluate the network public opinion intensity of the power system at each moment after the extreme disaster occurs; The resilience of the power system under extreme disasters is evaluated based on the power supply performance of the power system at each moment after the occurrence of extreme disasters and the intensity of online public opinion of the power system at each moment after the occurrence of extreme disasters.

2. The method for evaluating the resilience of a power system under extreme disasters according to claim 1 is characterized in that: The scenario status includes: the performance status of the power generation node, the performance status of the power transmission node, the performance status of the power transmission line, and the performance status of the load node; Determining the scenario state of the power system during the evolution of extreme disasters based on the topological structure includes: Based on the topological structure, the power generation nodes, transmission nodes, transmission lines, and load nodes in the power system are determined; wherein the power generation nodes include thermal power generation, hydropower generation, wind power generation, photovoltaic power generation, and nuclear power generation; the transmission nodes include converter stations, substations, and wiring substations; and the load nodes include households, commercial facilities, and industrial facilities; Determine the performance status of power generation nodes, transmission nodes, transmission lines, and load nodes; the performance status of power generation nodes includes: 0~20%, 20%~40%, 40%~60%, 60%~80%, 80%~100%, and the performance status of any power generation node is determined based on the percentage of its actual power supply capacity meeting the installed design capacity; the performance status of transmission nodes includes: 0~20%, 20%~40%, 40%~60%, 60%~80%, 80%~100%, and the performance status of any transmission node The status is determined according to the percentage of the actual transmission power upper limit meeting the rated power; the performance status of the transmission line includes: 0~20%, 20%~40%, 40%~60%, 60%~80%, 80%~100%, and the performance status of any transmission line is determined according to the percentage of damaged lines; the performance status of the load node includes: 0~33%, 33%~66%, 66%~100%, 100%~150%, 150%~200, and the performance status of any load node is determined according to the ratio of its actual load demand to the average load demand under normal scenarios.

3. The method for evaluating the resilience of a power system under extreme disasters according to claim 1 is characterized in that: The scenario status includes: the performance status of the power generation node, the performance status of the power transmission node, the performance status of the power transmission line, and the performance status of the load node; The evaluating the power supply performance of the power system at each moment after the extreme disaster occurs based on the scenario state includes: The power supply performance of the power system at any time after an extreme disaster occurs is evaluated by the following formula: ； in, To mark the moment, To protect the power system after extreme disasters Power supply performance at all times, is the supply-demand ratio; , To protect the power system after extreme disasters The performance status of the power generation node at the moment, To strengthen the power system after extreme disasters The performance status of the transmission node at the time, To protect the power system after extreme disasters The performance status of the transmission line at the transmission node at the time, To protect the power system after extreme disasters The performance status of the load node at the moment, is the supply and demand factor; , It is the upper limit of load supply during normal operation of the power system. It is the average load demand during normal operation of the power system.

4. The method for evaluating the resilience of a power system under extreme disasters according to claim 1, characterized in that: The assessment of the resilience of the power system under extreme disasters based on the power supply performance of the power system at each moment after the extreme disaster occurs and the intensity of network public opinion of the power system at each moment after the extreme disaster occurs includes: The resilience of the power system under extreme disasters is evaluated by the following formula: ； in, To improve the resilience of power systems under extreme disasters, When extreme disasters occur, is the total duration of the power system resilience assessment, is the initial comprehensive performance of the power system, To protect the power system after extreme disasters Comprehensive performance at all times; , To protect the power system after extreme disasters Power supply performance at all times, To protect the power system after extreme disasters The intensity of online public opinion at all times, is the power supply performance weight, is the network public opinion intensity weight, .

5. The method for evaluating the resilience of a power system under extreme disasters according to claim 1, characterized in that: The collection of online public opinion includes: particularly serious Internet public opinion events, serious Internet public opinion events, relatively serious Internet public opinion events, general Internet public opinion events, and no negative public opinion.

6. The method for evaluating the resilience of a power system under extreme disasters according to claim 1 is characterized in that: The method further comprises: Determine the disposal measures of the power system during the emergency process, the disaster characteristics of extreme natural disasters and environmental factors; wherein the disposal measures are determined by the emergency response level of key departments of the power system during the emergency process; The assessment of the resilience of the power system under extreme disasters based on the power supply performance of the power system at each moment after the extreme disaster occurs and the intensity of network public opinion of the power system at each moment after the extreme disaster occurs includes: The resilience of the power system under extreme disasters is assessed based on the power system's emergency response measures, the disaster characteristics and environmental factors of extreme natural disasters, the power supply performance of the power system at each moment after the extreme disaster occurs, and the intensity of online public opinion of the power system at each moment after the extreme disaster occurs.

7. The method for evaluating the resilience of a power system under extreme disasters according to claim 6, characterized in that: The key departments include: power grid dispatching group, production recovery group, power marketing group, security group, information release group and material support group; the emergency response level of any key department is one of the following: level I, level II, level III and level IV; When the extreme natural disaster is an earthquake, the disaster characteristic is the intensity, which is graded as follows: 0, I~IV, V~VI, VII~VIII, IX~X, XI~XII; When the extreme natural disaster is a landslide, the disaster characteristic is the volume of the landslide, which is classified as follows: 0, less than 100,000 cubic meters, 100,000 to 1 million cubic meters, 1 million to 10 million cubic meters, and more than 10 million cubic meters; When the extreme natural disaster is a rainstorm, the disaster characteristic is the precipitation, which is classified as follows: less than 49.9 mm, 50.0-99.9 mm, 100.0-249.9 mm, and more than 250.0 mm; When the extreme natural disaster is a flood, the disaster characteristic is the peak flow, which is classified as follows: 0, less than 500 cubic meters per second, 500-1000 cubic meters per second, 1000-1500 cubic meters per second, and more than 1500 cubic meters per second; When the extreme natural disaster is waterlogging, the disaster characteristic is the depth of water accumulation, which is classified as follows: less than 15 cm, 15-27 cm, 27-40 cm, 40-60 cm, and more than 60 cm; The environmental factors include: altitude, geological structure, 24-hour precipitation, air humidity, and temperature; The altitude classification is as follows: below 500 meters, 500-1000 meters, 1000-1500 meters, 1500-2000 meters, and above 2000 meters; The geological structures are classified into: monocline structure, fold structure, fault structure, and block structure; The 24-hour precipitation classification is: less than 0.1 mm, 0.1-9.9 mm, 10.0-24.9 mm, 25.0-49.9 mm, 50.0-99.9 mm, 100.0-249.9 mm, and more than 250.0 mm; Air humidity is graded as follows: 0~40%, 40%~60%, 60%~80%, and above 80%; The temperature is classified into: below 25 degrees Celsius, 25~30 degrees Celsius, 30~35 degrees Celsius, 35~40 degrees Celsius, and above 40 degrees Celsius.

8. A device for evaluating the resilience of a power system under extreme disasters, characterized in that: The device comprises: A collection module, used to collect the topological structure of the power system; A determination module, used to determine the scenario state of the power system during the evolution of extreme disasters based on the topological structure collected by the collection module; Establishing a module for establishing a network public opinion collection according to the corresponding levels of network public opinion; A first evaluation module, used to evaluate the power supply performance of the power system at each moment after the occurrence of an extreme disaster based on the scenario state determined by the determination module; A second evaluation module is used to evaluate the intensity of network public opinion of the power system at each moment after the occurrence of an extreme disaster based on the network public opinion set established by the establishment module; The third evaluation module is used to evaluate the resilience of the power system under extreme disasters based on the power supply performance of the power system at each moment after the extreme disaster occurs evaluated by the first evaluation module and the intensity of network public opinion of the power system at each moment after the extreme disaster occurs evaluated by the second evaluation module.

9. An electronic device, characterized in that: include: Memory; processor; as well as Computer programs; Wherein, the computer program is stored in the memory and is configured to be executed by the processor to implement the method for assessing the resilience of a power system under extreme disasters as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that: A computer program is stored thereon; the computer program is executed by a processor to implement the method for assessing the resilience of a power system under extreme disasters as described in any one of claims 1-7.

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