Power grid service quality index evaluation system, method, equipment and medium

Abstract

The invention discloses a power grid service quality index evaluation system, method and device and a medium, and relates to the technical field of computers, and the system comprises a power grid service platform, an element classification module, a model construction module, a scene generation module, an anomaly analysis module and an index evaluation module. The element classification module is used for classifying to obtain an element set; the model construction module is used for constructing a power grid topological structure model; the scene generation module is used for determining coupling relation information based on a power grid topological structure model and generating various fault scenes; the anomaly analysis module is used for determining an affected element set and a corresponding fault occurrence probability in each fault scene, and interruption power failure time of each fault scene for power supply of various users; and the index evaluation module is used for determining a power supply reliability index based on the fault occurrence probability and the interruption power failure time and evaluating a service quality index. The fault handling capability of the power grid is improved, and the reliability and the stability of power supply are guaranteed.

Description

Technical Field

[0001] The present invention relates to the field of computer technology, and in particular to a power grid service quality indicator evaluation system, method, equipment and medium. Background Art

[0002] As modern society becomes increasingly dependent on electricity supply, grid power supply reliability has become a key indicator that is of particular concern in the power system field.

[0003] Currently, common methods for evaluating power grid reliability indices mainly rely on historical data statistics. These methods, based on historical power outage data, record information such as the number of power outages experienced by users within a certain time period and the total duration of the outages to reflect the numerical value of power grid reliability. However, historical data statistics can only reflect past power outages and make it difficult to effectively estimate potential failure risks that have not yet occurred. Due to the large number of various components in the power grid, their different characteristics, and the complex coupling relationships between them, relying solely on historical power outage data cannot fully grasp the impact of different component failure combinations on power supply reliability. Furthermore, modern power grids are facing an increasing number of external environmental interference factors, such as extreme weather and external damage. However, traditional methods have significant shortcomings in considering the impact of complex and changing environmental factors on power supply reliability. They are unable to accurately simulate possible failure scenarios under different environmental interference conditions, as well as the corresponding power outage impact range and duration. This makes it difficult to accurately conduct forward-looking assessments and planning of power grid reliability, hindering the development of effective preventive measures and emergency plans to ensure power supply quality. Summary of the Invention

[0004] In view of the above-mentioned problems, the present invention is proposed.

[0005] Therefore, the technical problem solved by the present invention is: how to provide a power grid service quality index evaluation system, method, equipment and medium to solve the problem that the existing methods are difficult to guide accurate decision-making and ensure power supply quality, so as to achieve an all-round improvement in the power grid's ability to respond to faults and ensure the reliability and stability of power supply.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions: a power grid service quality index evaluation system, comprising: a power grid service middle station, a component classification module, a model construction module, a scenario generation module, an anomaly analysis module and an index evaluation module; the power grid service middle station is respectively connected to the component classification module, the model construction module, the scenario generation module, the anomaly analysis module and the index evaluation module to manage each module; the component classification module is used to classify each component in the target power grid according to the power grid component characteristic information to obtain a component set of different component types; the model construction module is used to perform association mapping and assign component category attributes to the corresponding power grid elements in the topology structure based on the component set to construct a power grid topology structure model; the The topology structure is constructed with the power equipment in the target power grid as node elements and the transmission lines of the power equipment as connecting elements; the scenario generation module is used to determine the coupling relationship information between the various components in the target power grid based on the power grid topology structure model, and generate multiple fault scenarios based on the coupling relationship information and environmental interference factor information; the abnormality analysis module is used to determine the affected component set and the corresponding fault occurrence probability under each fault scenario, and determine the power interruption time for each type of user under each fault scenario based on the power grid topology structure model; the index evaluation module is used to determine the power supply reliability index of the target power grid based on the fault occurrence probability and power interruption time under each fault scenario, and perform service quality index evaluation based on the power supply reliability index.

[0007] Another object of the present invention is to provide a method for evaluating power grid service quality indicators.

[0008] In order to solve the above technical problems, the present invention provides the following technical solutions: a method for evaluating power grid service quality indicators, which comprises the following steps:

[0009] According to the grid element characteristic information, each element in the target grid is classified to obtain a component set of different element types; based on the component set, the corresponding grid elements in the topology structure are associated and mapped and the component category attributes are assigned to construct a grid topology model; the topology structure is constructed with the power equipment in the target grid as the node element and the transmission line of the power equipment as the connection element; based on the grid topology model, the coupling relationship information between the various elements in the target grid is determined, and based on the coupling relationship information and the environmental interference factor information, a variety of fault scenarios are generated; the affected component set and the corresponding fault probability under each fault scenario are determined, and the power interruption time of each fault scenario for each type of user is determined based on the grid topology model; the power supply reliability index of the target grid is determined based on the fault probability and the power interruption time under each fault scenario, and the service quality index is evaluated based on the power supply reliability index.

[0010] As a preferred solution of the power grid service quality index evaluation method described in the present invention, wherein: the power supply reliability index of the target power grid is determined based on the fault probability and power interruption time under each fault scenario, and the service quality index evaluation is performed based on the power supply reliability index, including: determining the user's expected power outage time under each fault scenario based on the fault probability and power interruption time under each fault scenario; determining the power supply reliability index based on the user's expected power outage time, and determining the user satisfaction index value, the power service availability index value and the power quality compliance rate index value based on the power supply reliability index; and performing service quality index evaluation based on the user satisfaction index value, the power service availability index value and the power quality compliance rate index value.

[0011] As a preferred solution of the power grid service quality index evaluation method described in the present invention, wherein: determining the coupling relationship information between the components in the target power grid based on the power grid topology model includes: obtaining a first component and a second component with a connection relationship, and a target transmission line of the first component and the second component based on the power grid topology model; determining an electrical coupling coefficient between the first component and the second component based on a line current flowing through the target transmission line, a line voltage difference between the two ends of the target transmission line, and the shortest electrical distance between the first component and the second component in the topology structure; determining an electromagnetic coupling coefficient between the first component and the second component based on a first current flowing through the first component, a second current flowing through the second component, and the spatial distance between the first component and the second component; determining a coupling relationship coefficient between the first component and the second component based on the electrical coupling coefficient and the electromagnetic coupling coefficient; and constructing coupling relationship information between the components with a connection relationship in the target power grid based on the coupling relationship coefficient between the first component and the second component.

[0012] As a preferred solution of the power grid service quality index evaluation method described in the present invention, wherein: based on the coupling relationship information and the environmental interference factor information, multiple fault scenarios are generated, including: quantizing the environmental interference factor information to obtain the quantized value of the environmental factor; determining the fault trigger condition based on the coupling relationship coefficient between the components and the quantized value of the environmental factor; traversing all component combinations based on the fault trigger condition to obtain the target component combination that meets the fault trigger condition, and determining the fault type according to the position of the target component combination in the topological structure and the component functional characteristics of the target component combination; generating multiple fault scenarios based on each fault type and the corresponding fault result.

[0013] As a preferred solution of the power grid service quality index evaluation method described in the present invention, the determining of the affected component set and the corresponding fault occurrence probability under each fault scenario includes: performing a fault propagation analysis on each fault scenario based on the power grid topology model, and determining the affected component set under each fault scenario in combination with the coupling relationship coefficient between the components; and determining the fault occurrence probability under each fault scenario based on the failure incidence rate, aging coefficient and environmental sensitivity of each component in the affected component set under each fault scenario.

[0014] As a preferred solution of the power grid service quality index evaluation method described in the present invention, wherein: based on the power grid topology model, the power supply interruption time of each fault scenario to each type of user is determined, including: classifying each type of user in the target power grid to obtain a user set of different categories, and analyzing the power supply path of each user in the user set based on the power grid topology model to obtain a power supply path set for each user in the user set; analyzing the impact of each fault scenario on the power supply path of each user, and determining the number of components on the power supply path of each user affected by the fault; based on the number of components, the fault repair time of each component, and the spare capacity and power transfer capability of the target power grid, determining the power supply interruption time of each fault scenario to each type of user.

[0015] As a preferred embodiment of the method for evaluating power grid service quality indicators described in the present invention, the power grid element characteristic information includes functional attributes, fault probability distribution characteristics, importance levels, and the degree of power supply impact on different user types; the classification of each element in the target power grid according to the power grid element characteristic information to obtain element sets of different element types includes: creating a first number of empty element type sets, using a first target element in the target power grid as the initial cluster center of each empty element type set, and using the remaining elements in the target power grid other than the first target element as elements to be classified; for any second target element among the elements to be classified, obtaining a target empty element type set based on the first element characteristic indicator of the second target element; The similarity index between the second component characteristic index of the initial cluster center of the target empty component type set and the first component characteristic index is the maximum value; the component characteristic index is obtained by quantifying the functional attributes, the fault probability distribution characteristics, the importance level and the power supply impact degree; the second target component is classified into the target empty component type set, and the initial component type set of the target empty component type set is updated; based on the first component characteristic index and the second component characteristic index, the updated cluster center of the initial component type set is determined until the updated cluster center converges to obtain the target component type set corresponding to the initial component type set; component sets of different component types are obtained based on all target component type sets.

[0016] The present invention provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, wherein: when the processor executes the computer program, the steps of the power grid service quality index evaluation system are implemented.

[0017] The present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program is executed by a processor, the steps of the power grid service quality index evaluation system are implemented.

[0018] Beneficial effects of the present invention: The present invention constructs a power grid topology model by mapping a set of components with different component characteristics into a topology structure, thereby being able to clearly present the connection relationship between each component and the category to which it belongs, and generates fault scenarios under the combined action of different component coupling relationships and various external environmental interferences through the power grid topology model. According to the fault probability and power outage time under each fault scenario, the power supply reliability index is obtained and the service quality index evaluation is performed, so that the evaluation of the power supply reliability index is no longer simply based on historical and relatively rough statistics, and the specific component failure possibility and the precise power outage impact duration under different fault scenarios are comprehensively considered, thereby being able to more truly reflect the power supply capacity of the power grid under various working conditions; through more accurate evaluation of the power supply reliability index, power companies can more specifically formulate power grid operation and maintenance strategies, optimize power grid planning and layout, and reasonably arrange emergency plans, effectively improve service quality, thereby comprehensively improving the power grid's ability to cope with faults and ensuring the reliability and stability of power supply. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0020] Figure 1 This is a structural diagram of the power grid service quality indicator evaluation system in Example 1.

[0021] Figure 2 This is a flow chart of the method for evaluating power grid service quality indicators in Example 2.

[0022] Figure 3 This is an example diagram of the electronic device in Example 3.

[0023] Figure 4 This is an example diagram of the computer-readable storage medium in Example 3. DETAILED DESCRIPTION

[0024] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0025] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0026] Secondly, the term "one embodiment" or "embodiment" herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in various places throughout this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive of other embodiments.

[0027] Example 1, with reference to Figure 1 , which is the first embodiment of the present invention, provides a power grid service quality indicator evaluation system.

[0028] The existing power grid power supply reliability index assessment methods mainly have the following problems: on the one hand, historical data statistics can only reflect power outages that have occurred in the past, and it is difficult to effectively estimate potential failure risks that have not yet occurred. Due to the large number of various components in the power grid, their different characteristics and complex coupling relationships, it is difficult to fully grasp the impact of different component failure combinations on power supply reliability by relying solely on historical power outage data; on the other hand, modern power grids are facing an increasing number of external environmental interference factors, such as extreme weather and external force damage, but traditional methods have obvious deficiencies in considering the impact of complex and changeable environmental factors on power supply reliability. They cannot accurately simulate the possible failure scenarios under different environmental interferences and the corresponding power outage impact range and duration, making it difficult to accurately conduct forward-looking assessments and planning of power grid power supply reliability, which is not conducive to formulating effective preventive measures and emergency plans in advance to ensure power supply quality.

[0029] The present invention provides a method for effectively solving the above-mentioned problems. Next, multiple embodiments will be combined to explain in detail how to implement the power grid service quality index evaluation system.

[0030] Figure 1 The schematic diagram of the power grid service quality index evaluation system is shown, including:

[0031] Power grid business middle platform, component classification module, model construction module, scenario generation module, anomaly analysis module and indicator evaluation module.

[0032] In an embodiment of the present invention, the power grid business middle platform is respectively connected to the component classification module, the model construction module, the scenario generation module, the abnormality analysis module and the indicator evaluation module to manage each module.

[0033] In the embodiment of the present invention, the component classification module classifies each component in the target power grid according to the characteristic information of the power grid components to obtain a component set of different component types.

[0034] In an optional embodiment, the grid element characteristic information includes functional attributes, fault probability distribution characteristics, importance level, and power supply impact on different types of users.

[0035] Therefore, the component classification module classifies each component in the target power grid according to functional attributes, fault probability distribution characteristics, importance level and power supply impact degree, and obtains a component set of different component types, where different component types are such as busbar, power station or substation.

[0036] In an embodiment of the present invention, the model construction module is used to perform association mapping and assign component category attributes to corresponding power grid elements in the topology structure based on the component set, thereby constructing a power grid topology model; the topology structure is constructed with the power equipment in the target power grid as the node element and the transmission line of the power equipment as the connection element.

[0037] In an optional embodiment, the model building module obtains the power equipment in the target power grid and the transmission lines between the power equipment, wherein the power equipment is such as a bus, a power station or a substation, and a topological structure is constructed with the power equipment in the target power grid as the node elements and the transmission lines of the power equipment as the connection elements.

[0038] In the embodiment of the present invention, the scenario generation module determines the coupling relationship coefficients between the components in the target power grid according to the power grid topology model, and obtains coupling relationship information according to the coupling relationship.

[0039] Furthermore, the scenario generation module obtains environmental interference factor information, wherein the environmental interference factor information includes meteorological factors and geographical factors, and quantifies the meteorological factors and geographical factors to obtain quantified values ​​of the environmental factors.

[0040] Furthermore, the scenario generation module generates multiple fault scenarios based on the coupling relationship information and the quantitative values ​​of environmental factors.

[0041] In an optional embodiment, the anomaly analysis module determines the affected component set and the corresponding fault occurrence probability under each fault scenario, and determines the power outage time for each type of user under each fault scenario based on the power grid topology model.

[0042] In an optional embodiment, the index evaluation module determines the power supply reliability index based on the failure probability and power outage time under each failure scenario, and determines the user satisfaction index value, the power service availability index value and the power quality compliance rate index value based on the power supply reliability index to evaluate the business quality index.

[0043] In summary, the present invention constructs a power grid topology model by mapping a set of components with different component characteristics into a topology structure, so that the connection relationship between each component and the category to which it belongs can be clearly presented. The power grid topology model generates fault scenarios under the combined action of different component coupling relationships and various external environmental interferences. According to the fault probability and power outage time under each fault scenario, the power supply reliability index is obtained and the service quality index evaluation is performed, so that the evaluation of the power supply reliability index is no longer simply based on historical and relatively rough statistics, and the specific component failure possibility and the precise power outage impact duration under different fault scenarios are comprehensively considered, so as to more truly reflect the power supply capacity of the power grid under various working conditions; through more accurate evaluation of the power supply reliability index, power companies can formulate power grid operation and maintenance strategies, optimize power grid planning and layout, and reasonably arrange emergency plans in a more targeted manner, effectively improve service quality, thereby comprehensively improving the power grid's ability to cope with faults and ensuring the reliability and stability of power supply.

[0044] Example 2, reference Figure 2 , which is a second embodiment of the present invention, provides a method for evaluating power grid service quality indicators, including:

[0045] S1: Classify each component in the target power grid according to the grid component characteristic information to obtain a component set of different component types.

[0046] In the embodiment of the present invention, the grid element characteristic information includes functional attributes, fault probability distribution characteristics, importance levels, and the degree of impact on power supply to different types of users.

[0047] Furthermore, obtaining a component set of different component types includes the following steps: obtaining a component characteristic index of each component according to the functional attributes, fault probability distribution characteristics, importance level and power supply impact degree of each component.

[0048] The components in the target power grid are classified according to the component characteristic index of each component to obtain a component set of different component types, where the different component types include busbars, power stations or substations, as shown in steps S1.1 to S1.5.

[0049] Exemplarily, classifying the components in the target power grid according to the grid component characteristic information to obtain a component set of different component types includes the following steps:

[0050] S1.1: Create a first number of empty component type sets, use the first target component in the target power grid as the initial cluster center of each empty component type set, and use the remaining components in the target power grid except the first target component as components to be classified.

[0051] In an optional embodiment, all elements in the target power grid are formed into a total element set U = {u1, u2, ..., u N}, where N is the total number of components, and a first number of empty component type sets are created, where the first number is determined based on empirical estimation, and the first number of empty component type sets created are Type = {C1, C2, ..., C M}, M is the first quantity.

[0052] Furthermore, the initial cluster center of each empty component type set is initialized, that is, a first number of first target components are selected from the total component set U, and the first target components are used as the initial cluster center of each empty component type set, so C1, C2, ..., C M The initial cluster centers are center1, center2, ..., center M At the same time, the remaining elements in the target power grid except the first target element are taken as the elements to be classified, and the elements to be classified are classified into different element type sets.

[0053] S1.2: For any second target component among the components to be classified, obtain a target empty component type set based on the first component characteristic index of the second target component.

[0054] In an optional embodiment, the component characteristic index is obtained by quantifying the functional attributes, fault probability distribution characteristics, importance level and power supply impact, including the following steps: the functional attribute quantification step, the power grid components in the embodiment of the present invention have n different functional categories, with F i Represents the i-th function category, i = 1, 2, ..., n, and for each component j, its function attribute vector can be expressed as If component j has functional category i, then f ji =1, otherwise f ji =0.

[0055] The fault probability distribution characteristic quantification step, in the embodiment of the present invention, the fault probability distribution characteristic is described by the probability density function P(x) as the probability of component failure changes with the influencing factor x (operating time, environmental parameters). For component j, its fault probability distribution characteristic function is P j (x), and obtain the comprehensive failure probability index by integrating it in the time interval [T1, T2] The calculation formula is

[0056] Importance level quantification step, the importance level of the embodiment of the present invention includes m levels, with I kIndicates the kth importance level, k = 1, 2, ..., m, and assigns importance level value I to component j j , the value range is 1 to m, and the larger the value, the higher the importance.

[0057] The power supply impact degree quantification step includes p different user types in the embodiment of the present invention. For component j, its power supply impact degree on the lth user type is represented by E jl (This can be determined by statistical analysis of historical power outage data, simulation of relevant indicators of user impact after power outage, etc.), and constructing a power supply impact degree vector Calculate comprehensive power supply impact index Among them, the weight corresponding to each user type is The calculation formula is

[0058] Furthermore, for any second target element u in the components to be classified i ∈{u1,u2,...,u N-M}, calculate the similarity between the first component characteristic index of the second target component and the second component characteristic index of the initial cluster center of each empty component type set, and obtain the second target component u i with each empty element of type set C c The similarity index Sim(u i ,center c ), c=1,2,...,M, and the second target element u i Divide into the target empty component type set corresponding to the initial cluster center with the largest similarity index, that is, if Then the second target element u i The target empty element type set is set C c Therefore, the similarity index between the second component characteristic index and the first component characteristic index of the initial cluster center of the target empty component type set is the maximum value.

[0059] In the embodiment of the present invention, the comprehensive classification index vector of element j is The specific formula is as follows:

[0060]

[0061] Among them, S j1 、S j2 、S j3 and S j4 Represents the comprehensive classification index vector of component j The 1st, 2nd, 3rd and 4th elements in f ji Represents a functional attribute vector Indicates whether component j has functional category i; n indicates the functional category; Represents the comprehensive failure probability index; I j represents the importance level value of component j; m represents the importance level; Indicates the comprehensive power supply impact index.

[0062] Furthermore, for the similarity index Sim(j,k) between two components j and k, the specific formula is as follows:

[0063]

[0064] Among them, S jr Represents the comprehensive classification index vector of component j The rth element in S kr Represents the comprehensive classification index vector of component k The rth element in ; α represents the adjustment parameter.

[0065] S1.3: Classify the second target component into the target empty component type set, and update the initial component type set of the target empty component type set.

[0066] In the embodiment of the present invention, the second target component is classified into the target empty component type set, and the target empty component type set C is updated. c The initial component type set

[0067] S1.4: Determine updated cluster centers of the initial component type set based on the first component characteristic index and the second component characteristic index until the updated cluster centers converge to obtain a target component type set corresponding to the initial component type set.

[0068] In the embodiment of the present invention, according to each initial component type set The first component characteristic index and the second component characteristic index determine the initial component type set The updated cluster center is The calculation formula for each dimension value of is as follows (taking the rth dimension as an example):

[0069]

[0070] in, Represents the initial component type set The number of components in .

[0071] Furthermore, by judging whether the cluster center converges, that is, calculating whether the sum of the difference between the two cluster centers in each dimension is less than the preset threshold ∈, if For all c *=1,2,...,M holds true, then convergence stops iteration, otherwise update the cluster center The next round of iterative classification is continued until the updated cluster centers converge, and the target component type set corresponding to the initial component type set is obtained.

[0072] S1.5: Obtain component sets of different component types based on all target component type sets.

[0073] In an embodiment of the present invention, all target component type sets are aggregated and integrated to obtain component sets of different component types.

[0074] It should be noted that the present invention classifies all elements in the target power grid into element sets of different element types, so that element sets with different element characteristics can be mapped into the topology structure to construct a power grid topology model, thereby clearly presenting the connection relationship between each element and the category to which they belong.

[0075] S2: Based on the component set, the corresponding power grid elements in the topology structure are associated and mapped and the component category attributes are assigned to construct the power grid topology model.

[0076] In the embodiment of the present invention, the topology structure is constructed with the power equipment in the target power grid as node elements and the transmission lines of the power equipment as connection elements.

[0077] In an optional embodiment, the present invention obtains power equipment in a target power grid and transmission lines between the power equipment, wherein the power equipment includes a busbar, a power station, or a substation.

[0078] In an optional embodiment, constructing a power grid topology model includes the following steps: a node determination step, wherein the collected buses, substations, and power stations are used as node elements in the topology structure; for example, the bus set is B = {b1, b2, ..., b z1}, where z1 represents the dimension of the busbar in the busbar set, and the substation set is S = {s1,s2,...,s z2}, where z2 represents the dimension of the substation in the substation set, and the power station set is G = {g1, g2, ..., g z3}, where z3 represents the dimension of the power station in the power station set, then the total node set in the topological structure is N point =B∪S∪G.

[0079] In the edge determination step, the transmission line is used as the connection element. If the total node set N point There is a transmission line L between node i and node j. ijIf the transmission lines are connected, an edge is added between the corresponding nodes i and j in the topology structure. All transmission lines constitute the edge set E={L ij |i,j∈N point}.

[0080] Through the above operations, a topological structure represented by a node set and an edge set is preliminarily constructed. The topological structure presents the physical connection relationship between power equipment.

[0081] In this embodiment of the present invention, the component category attribute set is H = {h1, h2, h3}, where h1 represents busbar attributes, h2 represents substation attributes, and h3 represents power station attributes. Therefore, for each node element, an association mapping is performed based on its type (busbar, substation, or power station) and the corresponding component category attribute is assigned.

[0082] For example, in this embodiment of the present invention, for node b i ∈B, through the mapping function f(b i )=h1, the busbar node b i Assign the component category attribute h1; for node s k ∈S, through the mapping function f(s k )=h2, the substation node s k Assign the component category attribute h2; for node g l ∈G, through the mapping function f(g l )=h3, the power station node g l Assign the component category attribute h3 and build a power grid topology model.

[0083] Furthermore, in constructing the power grid topology model, the specific formula for evaluating node importance is as follows:

[0084]

[0085] Where I(i) represents the importance index of node i; D(i) represents the degree of node i (i.e., the number of edges connected to node i); |N point | represents the node set N point The total number of nodes in d ij represents the shortest path length between node i and node j; E represents the edge set in the topological structure; C ij Indicates the transmission line L ij The transport capacity of C max represents the maximum transmission capacity of all transmission lines; α1, β1, γ1 represent the preset weight coefficients.

[0086] Furthermore, the specific formula for evaluating topological connectivity is as follows:

[0087]

[0088] Among them, LN represents the connectivity index; N point represents a node set; δ ij Represents a binary function. When there is a path connection between node i and node j (i.e., node j can be reached from node i through several transmission lines), δ ij =1; if there is no connected path, then δ ij =0.

[0089] Furthermore, the specific formula for transmission efficiency evaluation based on component category attributes is as follows:

[0090]

[0091] Where TN represents the transmission efficiency index; E represents the edge set in the topological structure; η ij represents the transmission efficiency of the transmission line; w ij represents the weight coefficient; Indicates the input power of the transmission line; Represents output power; θ i and θ j represents the correction coefficient related to the component category attributes of nodes i and j. For example, if node i is a power station (i.e., the component category attribute is h3), then θ i =1.2, if node θ j For a substation (component category attribute is h2), then θ j =0.9; l ij Indicates the transmission line L ij Length; C ij Indicates the transmission line L ij The transport capacity of C max It represents the maximum transmission capacity of all transmission lines.

[0092] S3: Determine the coupling relationship information between the components in the target power grid based on the power grid topology model, and generate multiple fault scenarios based on the coupling relationship information and environmental interference factor information.

[0093] In an embodiment of the present invention, multiple fault scenarios are generated, including the following steps: determining the coupling relationship between the components in the target power grid based on the power grid topology model, and obtaining coupling relationship information according to the coupling relationship, as specifically shown in steps S3.1 to S3.5.

[0094] Acquire environmental interference factor information, wherein the environmental interference factor information includes meteorological factors and geographical factors, and quantify the meteorological factors and geographical factors to obtain quantified values ​​of the environmental factors.

[0095] Based on the coupling relationship information and the quantitative values ​​of environmental factors, multiple fault scenarios are generated, as shown in steps S3.6 to S3.9.

[0096] Exemplarily, determining the coupling relationship between components in the target power grid based on the power grid topology model and obtaining coupling relationship information according to the coupling relationship includes the following steps:

[0097] S3.1: Acquire a first component and a second component having a connection relationship, and a target transmission line of the first component and the second component based on a power grid topology model.

[0098] In an embodiment of the present invention, by analyzing the power grid topology model, a first element and a second element having a connection relationship in the power grid topology model are obtained, and a target transmission line connecting the first element and the second element is determined.

[0099] For example, the first element A and the second element B are connected via a transmission line L. AB connected, the output current of the first element A will pass through the transmission line L AB When it flows into the second component B, its voltage change will also be transmitted along the line and affect the voltage condition of the second component B.

[0100] S3.2: Determine an electrical coupling coefficient between the first element and the second element based on a line current flowing through the target transmission line, a line voltage difference between two ends of the target transmission line, and a shortest electrical distance between the first element and the second element in the topology.

[0101] In an embodiment of the present invention, by obtaining the line current flowing through the target transmission line and the line voltage difference between the two ends of the target transmission line, the shortest electrical distance between the first element and the second element in the topological structure is simultaneously obtained, wherein the shortest electrical distance can be measured by calculating the number of connections passing through the least lines, and the distance is increased by 1 for each line passed.

[0102] Furthermore, the electrical coupling coefficient between the first component and the second component is calculated based on the line current, the line voltage difference, and the shortest electrical distance. The specific formula is as follows:

[0103]

[0104] Among them, C elec (A, B) represents the electrical coupling coefficient between the first element A and the second element B; I AB Indicates the power flowing through the target transmission line L AB Line current; U AB Indicates the target transmission line L AB The line voltage difference between the two ends; I max Indicates the maximum current allowed to pass through the transmission line in the target power grid; Umax Indicates the highest rated voltage in the target power grid; d AB Indicates the shortest electrical distance between the first component A and the second component B in the topology.

[0105] S3.3: Determine an electromagnetic coupling coefficient between the first element and the second element based on a first current flowing through the first element, a second current flowing through the second element, and a spatial distance between the first element and the second element.

[0106] In an embodiment of the present invention, a first current flowing through a first element, a second current flowing through a second element, and a spatial distance between the first element and the second element are obtained, where the spatial distance can be calculated using information such as coordinates of the first element and the second element.

[0107] Furthermore, the electromagnetic coupling coefficient between the first element and the second element is calculated according to the first current, the second current and the spatial distance. The calculation formula of the electromagnetic coupling coefficient is as follows:

[0108]

[0109] Among them, C em (A, B) represents the electromagnetic coupling coefficient between the first element A and the second element B; I A represents the first current flowing through the first element A; I B represents the second current flowing through the second element B; r AB k represents the spatial distance between the first element A and the second element B; A k represents the electromagnetic characteristic coefficient of the first element A itself; B represents the electromagnetic characteristic coefficient of the second element B itself.

[0110] S3.4: Determine a coupling relationship coefficient between the first element and the second element based on the electrical coupling coefficient and the electromagnetic coupling coefficient.

[0111] In the embodiment of the present invention, the coupling relationship coefficient between the first element and the second element is calculated based on the electrical coupling coefficient and the electromagnetic coupling coefficient of the first element and the second element. The specific formula is as follows:

[0112] C(A,B)=w elec *C elec (A,B)+w em *C em (A,B),w elec +w em =1.

[0113] Wherein, C(A,B) represents the coupling coefficient between the first element A and the second element B; w elec represents the electrical coupling weight coefficient; w emrepresents the electromagnetic coupling weight coefficient.

[0114] S3.5: Based on the coupling relationship coefficient between the first element and the second element, construct coupling relationship information between the elements that have a connection relationship in the target power grid.

[0115] In an embodiment of the present invention, based on the coupling relationship coefficient between any two connected first elements and second elements in the target power grid, a coupling relationship matrix between the connected elements of the entire target power grid is constructed to present the tightness of the coupling between the elements, and obtain the coupling relationship information between the connected elements in the target power grid.

[0116] It should be noted that the present invention analyzes the coupling relationship information between the various components with connection relationships in the target power grid through the power grid topology model, presents the degree of coupling between the components, and provides a comprehensive reference basis for subsequent power grid fault analysis and emergency response plan formulation, effectively improving business quality, thereby comprehensively improving the power grid's ability to respond to faults and ensuring the reliability and stability of power supply.

[0117] Exemplarily, generating multiple fault scenarios based on coupling relationship information and quantified values ​​of environmental factors includes the following steps:

[0118] S3.6: Quantify the environmental interference factor information to obtain the quantified value of the environmental factor.

[0119] In this embodiment of the present invention, environmental interference factor information includes meteorological and geographical factors. Meteorological factors include weather conditions such as strong winds, heavy rain, lightning strikes, and ice and snow. Different meteorological conditions cause varying degrees of damage to components or affect their performance. For example, lightning strikes may directly strike transmission lines or substation equipment, causing faults such as short circuits. Geographical factors include the vulnerability of grid components near areas prone to geological disasters such as earthquakes, landslides, and mudslides. Furthermore, components exposed to special geographical environments such as high humidity and high salt spray will experience accelerated corrosion and aging, affecting their normal operation.

[0120] Furthermore, meteorological factors and geographical factors are quantified. For example, strong winds among meteorological factors can be graded and quantified according to wind force levels (e.g., 0-12 levels correspond to different quantitative values); earthquakes among geographical factors are graded and quantified according to earthquake intensity to obtain quantitative values ​​of environmental factors.

[0121] S3.7: Determine the fault triggering conditions based on the coupling relationship coefficients between components and the quantified values ​​of environmental factors.

[0122] In the embodiment of the present invention, the fault triggering condition is set according to the coupling relationship coefficients between the various components and the quantized values ​​of the environmental factors.

[0123] For example, for the component combination (A, B), a fault may be triggered when the following conditions are met: C(A, B)*F env (A, B) ≥ θ, where C(A, B) represents the coupling coefficient between the components, and F env (A, B) represents the comprehensive impact function of the environmental interference factors faced by the first component A and the second component B. The calculation method can be to add the quantitative values ​​of various environmental factors according to certain weights. For example, the weight of meteorological factors is 0.4, the weight of geographical factors is 0.3, and the weight of human factors is 0.3. θ represents the pre-set fault trigger threshold, which ranges from 0 to 1.

[0124] S3.8: Traverse all component combinations based on the fault triggering condition to obtain a target component combination that meets the fault triggering condition, and determine the fault type based on the position of the target component combination in the topological structure and the component functional characteristics of the target component combination.

[0125] In an embodiment of the present invention, by traversing all component combinations, it is determined which component combinations are likely to trigger a fault under the current environmental interference factors based on the fault trigger conditions. For the target component combination that meets the fault trigger conditions, the position of the target component combination in the topological structure and the component functional characteristics of the target component combination are analyzed to infer the fault type, which includes short circuit fault, open circuit fault and ground fault.

[0126] For example, it is determined that the busbar A and the transmission line L AB The fault triggering conditions are met, and according to electrical analysis, it is speculated that the transmission line L may be caused by lightning strike. AB A short circuit fault has occurred.

[0127] S3.9: Generate multiple failure scenarios based on each failure type and corresponding failure consequences.

[0128] In an embodiment of the present invention, the fault results corresponding to each fault type are obtained through continuous traversal and analysis, and multiple fault scenarios are generated based on each fault type and the corresponding fault results. Therefore, the fault scenarios cover different component combinations, different environmental interference factors and corresponding various fault types.

[0129] For example, it is determined that the busbar A and the transmission line L AB The fault triggering conditions are met, and according to electrical analysis, it is speculated that the transmission line L may be caused by lightning strike. AB A short circuit fault occurs, affecting the normal power supply of bus A. That is, the fault type is a short circuit fault, and the fault result corresponding to the fault type is affecting the normal power supply of bus A. The generated fault scenario is: "Under the interference of the lightning environment, the transmission line L ABA short circuit fault caused by a lightning strike caused a power outage on the connected bus A, affecting the power supply to downstream substations and users.

[0130] It should be noted that the present invention generates fault scenarios under the combined effects of different component coupling relationships and various external environmental interferences through a power grid topology model, providing a comprehensive reference basis for subsequent power grid fault analysis and emergency response plan formulation, effectively improving service quality, thereby comprehensively improving the power grid's ability to respond to faults and ensuring the reliability and stability of power supply.

[0131] S4: Determine the set of affected components and the corresponding probability of failure under each fault scenario, and determine the power outage time for each type of user under each fault scenario based on the grid topology model.

[0132] In an embodiment of the present invention, determining the affected component set and the corresponding fault occurrence probability under each fault scenario, and determining the power outage duration for each type of user under each fault scenario based on a power grid topology model, includes the following steps:

[0133] S4.1: Perform fault propagation analysis for each fault scenario based on the grid topology model, and determine the set of affected components in each fault scenario based on the coupling relationship coefficients between components.

[0134] In this embodiment of the present invention, for each fault scenario, a breadth-first search is performed based on the grid topology model, starting from the initial fault component (i.e., the component that triggered the fault) and following connections such as transmission lines to identify other components that the fault may propagate to. For example, if a fault originates from a generator at a power station, the fault is traced along the busbar connected to the generator and the transmission lines extending from the busbar to downstream substations, other busbars, and connected user-side components. These components that could be affected by the fault through electrical connections are added to the set of affected components.

[0135] Furthermore, the impact range is further expanded by combining the coupling coefficient C(A, B) between each component. For target components with a large coupling coefficient with the initial component, for example, C(A, B) ≥ 0.5, even if the initial component and the target component are not directly connected in the topology, the target component may still be affected by the failure of the initial component due to the strong coupling. Therefore, these strongly coupled target components are added to the set of affected components.

[0136] Exemplary, failure scenario d i The set of affected components under Where D represents the dimension of the elements in the affected element set, e jIndicates the specific affected components (which can be different types of components such as busbars, substations, transmission lines, etc.).

[0137] S4.2: Determine the probability of failure for each failure scenario based on the failure rate, aging factor, and environmental sensitivity of each component in the set of affected components for each failure scenario.

[0138] In an embodiment of the present invention, the failure occurrence rate, aging coefficient and environmental sensitivity of each component in the affected component set under each failure scenario are obtained, including the following steps: for the failure occurrence rate, for each component e in the affected component set, j ,j=1,2,...,X,X represents the number of affected components and the failure rate Indicates element e j The frequency of failures per unit time can be determined by the component e j The historical fault data is statistically analyzed. For example, component e j In the past Q years, there have been j Second fault, then component e j Failure rate The unit is times / year.

[0139] As for the aging coefficient, since the aging coefficient is used to measure the influence of the aging degree of components due to service life, operation time, etc. on the probability of failure, according to each component e j The actual running time t j (Unit: year) and design service life T(design) j Determine; each element e j The calculation formula of the aging coefficient is The value range is between 0 and 1, where 1 means the component is brand new and not aged, and 0 means the component has reached its designed service life.

[0140] As for environmental sensitivity, since environmental sensitivity characterizes the degree of influence of external environmental factors (such as temperature, humidity, wind and sand, salt spray, etc.) on the probability of failure of a component, we can collect various environmental data through long-term monitoring of the environment in which the component is located, and quantify the degree of influence of environmental factors on component performance to obtain a score value. (The value range is 0 to 1, 0 means that the environment has almost no effect on the component, and 1 means that the environment has a great impact). At the same time, the component's tolerance to the environment is considered. (The value range is 0 to 1, 0 means completely intolerant to the environment, 1 means highly tolerant to the environment), then each element e j The environmental sensitivity calculation formula is:

[0141] Furthermore, the comprehensive impact factor of each component in each fault scenario is calculated based on the failure rate, aging coefficient and environmental sensitivity of each component in the affected component set under each fault scenario. The specific formula is as follows:

[0142]

[0143] in, Indicates element e j Failure rate; Represents each element e j The aging coefficient; Represents each element e j Environmental sensitivity; w fir 、w ac and w es Represent the weight coefficients corresponding to the failure rate, aging coefficient and environmental sensitivity, respectively, and satisfy w fir +w ac +w es =1, and the value range is between 0 and 1.

[0144] Furthermore, the probability of failure in each fault scenario is calculated based on the comprehensive impact factor of each component in each fault scenario.

[0145] For example, for the fault scenario d i , the set of components affected is Consider each component in the failure scenario d i The relative importance of the component is expressed by the importance index I(e j ) indicates that, therefore, the fault scenario fault d i The probability of occurrence The specific formula is as follows:

[0146]

[0147] Where D represents the dimension of the elements in the affected element set; Represents the comprehensive impact factor of each component under each fault scenario.

[0148] It should be noted that the present invention determines the probability of failure under each fault scenario, so that the power supply reliability index can be derived and the service quality index evaluation can be performed based on the failure probability and power outage time under each fault scenario. It comprehensively considers the specific component failure possibility and the precise power outage impact duration under different fault scenarios, thereby more truly reflecting the power supply capacity of the power grid under various working conditions.

[0149] S4.3: Classify various types of users in the target power grid to obtain user sets of different categories, and analyze the power supply path of each user in the user set based on the power grid topology model to obtain a power supply path set for each user in the user set.

[0150] In the embodiment of the present invention, various types of users in the target power grid are classified to obtain user sets of different categories O = {o1, o2, ..., o V}, where V represents the dimension of users in the user set, and user categories include industrial user category, commercial user category, and residential user category.

[0151] Furthermore, based on the grid topology model, the power supply path from the power station to each user is analyzed, that is, the links composed of busbars, substations, transmission lines and other components are used to transmit electricity to the user end, and the power supply path set for each user is determined. Among them, r ks Indicates specific components on the power supply path (such as transmission lines and substations).

[0152] S4.4: Analyze the impact of each fault scenario on the power supply path of each user and determine the number of components on the power supply path of each user affected by the fault.

[0153] In the embodiment of the present invention, for each fault scenario d i , analyze each failure scenario d i Impact on the power supply path of each user; if a component on the power supply path is in fault scenario d i The affected component set The power supply path is affected by the fault, which may cause power outages for users. The number of components on the power supply path affected by the fault for each user is recorded.

[0154] S4.5: Determine the power outage duration for each type of user for each fault scenario based on the number of components, the fault repair time for each component, and the backup capacity and power transfer capability of the target grid.

[0155] In the embodiment of the present invention, the power outage time of the user is calculated by taking into account the fault repair time of different types of components and the backup capacity and power transfer capacity of the power grid.

[0156] For example, element e j The average repair time is T j (Unit: hour, which can be obtained through historical maintenance data statistics), the target power grid targets user o k The reserve capacity factor is β k (Value range 0≤β k≤1, indicating the proportion of backup capacity that can meet the normal power demand of users, which can be determined according to the actual backup power configuration of the power grid), the power transfer capacity coefficient γ k (value range 0≤γ k ≤1, reflecting the ability to transfer power through other power supply paths, which can be determined based on the number and capacity of transferable paths in the power grid topology).

[0157] Furthermore, for user o k In the failure scenario d i The power outage time The specific formula is as follows:

[0158]

[0159] Among them, β k Indicates that the target power grid targets user o k The reserve capacity factor; γ k Indicates the power transfer capability coefficient; Indicates fault scenario d i The set of affected components; represents the power supply path set of each user; T j Indicates element e j Mean time to repair a problem; Indicates the number of components on the power supply path that are affected by the fault for each user.

[0160] It should be noted that the present invention determines the power outage time under each fault scenario, so that the power supply reliability index can be derived and the service quality index evaluation can be performed based on the fault probability and power outage time under each fault scenario. It comprehensively considers the specific component failure possibility and the precise power outage impact duration under different fault scenarios, thereby more truly reflecting the power supply capacity of the power grid under various working conditions.

[0161] S5: Determine the power supply reliability index of the target power grid based on the fault probability and power outage time under each fault scenario, and evaluate the service quality index based on the power supply reliability index.

[0162] In an embodiment of the present invention, the power supply reliability index of the target power grid is determined, and the service quality index is evaluated based on the power supply reliability index, including the following steps: according to the fault probability and power outage time under each fault scenario, the expected power outage time of the user under each fault scenario is determined.

[0163] The power supply reliability index is determined based on the user's expected power outage time under each fault scenario.

[0164] The user satisfaction index value, the power service availability index value and the power quality compliance rate index value are determined based on the power supply reliability index and the service quality index evaluation is performed, as shown in steps S5.1 to S5.3.

[0165] Exemplarily, evaluating the service quality index based on the power supply reliability index includes the following steps:

[0166] S5.1: Determine the expected power outage duration for users under each fault scenario based on the fault probability and power outage duration under each fault scenario.

[0167] In the embodiment of the present invention, for each type of user O={o1, o2, ..., o V}, calculate the expected power outage time under all fault scenarios; for user o k , the set of fault scenarios is d={d1,d2,...,d n}, known failure scenario d i The probability of failure is User o k In the failure scenario d i The power outage time is Therefore, the user's expected power outage time The specific formula is as follows:

[0168]

[0169] Where D represents the dimension of the elements in the affected element set.

[0170] S5.2: Determine the power supply reliability index based on the user's expected power outage time, and determine the user satisfaction index value, power service availability index value and power quality compliance rate index value based on the power supply reliability index.

[0171] In this embodiment of the present invention, the presidential timer is obtained as T total (Unit: hour, for example, the total duration of a year can be 8760 hours). The power supply reliability index (SRI) is calculated based on the user's expected power outage time and the presidential time length. The specific formula of the power supply reliability index (SRI) is as follows:

[0172]

[0173] Among them, V represents the dimension of users in the user set; Indicates the user's expected power outage time.

[0174] Furthermore, the user satisfaction index value, power service availability index value and power quality compliance rate index value are determined based on the power supply reliability index, including:

[0175] For the user satisfaction index value CS, the calculation formula is CS=exp(SRI-3).

[0176] For the power service availability index value PSA, the calculation formula is PSA=log(SRI+1).

[0177] For the power quality compliance rate index value PQCR, the calculation formula is PQCR=1 / (SRI+5).

[0178] S5.3: Evaluate service quality indicators based on user satisfaction index values, power service availability index values, and power quality compliance rate index values.

[0179] In the embodiment of the present invention, the comprehensive service quality index IQ is calculated based on the user satisfaction index value, the power service availability index value, and the power quality compliance rate index value. The specific formula is as follows:

[0180] IQ=w CS *CS+w PSA *PSA+w PQCR *PQCR.

[0181] Among them, w CS 、w PSA and w PQCR represent the weights of user satisfaction, power service availability and power quality compliance rate respectively, and w CS +w PSA +w PQCR =1.

[0182] It should be noted that the larger the value of the comprehensive service quality index IQ, the better the service quality index evaluation is: the target power grid performs in terms of power supply reliability and the quality of various services associated with it; conversely, the service quality index evaluation is: the target power grid needs to improve in terms of power supply reliability and the quality of various services associated with it, so it is necessary to improve and optimize the weak links, such as improving the quality of power grid equipment, optimizing the power grid topology structure, and other measures to improve power supply reliability and thus improve service quality.

[0183] It should be noted that the present invention evaluates the service quality indicators of the target power grid by comprehensively considering the specific component failure possibilities under different fault scenarios and the precise duration of power outage impact, thereby more realistically reflecting the power supply capacity of the power grid under various complex working conditions, effectively improving service quality, and thus comprehensively improving the power grid's ability to respond to faults and ensuring the reliability and stability of power supply.

[0184] Embodiment 3 is the third embodiment of the present invention, which differs from the first two embodiments in that:

[0185] like Figure 3 and Figure 4 As shown, if the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0186] The logic and / or steps represented in the flowcharts or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing the logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (e.g., a computer-based system, a system including a processor, or other system that can fetch and execute instructions from an instruction execution system, apparatus, or device). For purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0187] More specific examples (a non-exhaustive list) of computer-readable media include the following: an electrical connection with one or more wires (electronic devices), a portable computer disk cartridge (magnetic devices), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disc read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering, or processing in another suitable manner as necessary, and then stored in a computer memory.

[0188] It should be understood that various parts of the present invention can be implemented using hardware, software, firmware, or a combination thereof. In the above-described embodiments, multiple steps or methods can be implemented using software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented using hardware, as in another embodiment, any one of the following technologies known in the art or a combination thereof can be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application-specific integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0189] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A power grid service quality index evaluation system, characterized by: include, A power grid business middle platform, a component classification module, a model construction module, a scenario generation module, an anomaly analysis module, and an index evaluation module; the power grid business middle platform is connected to the component classification module, the model construction module, the scenario generation module, the anomaly analysis module, and the index evaluation module respectively to manage each module; The component classification module is used to classify each component in the target power grid according to the power grid component characteristic information to obtain a component set of different component types; The model building module is used to perform association mapping and assign element category attributes to corresponding power grid elements in the topology structure based on the element set, thereby building a power grid topology model; the topology structure is built with power equipment in the target power grid as node elements and power transmission lines of the power equipment as connection elements; The scenario generation module is configured to determine coupling relationship information between components in the target power grid based on the power grid topology model, and generate multiple fault scenarios based on the coupling relationship information and environmental interference factor information; The anomaly analysis module is used to determine the set of affected components and the corresponding probability of failure in each fault scenario, and to determine the power outage duration for each type of user in each fault scenario based on the power grid topology model; The indicator evaluation module is used to determine the power supply reliability index of the target power grid based on the fault probability and power outage time under each fault scenario, and to evaluate the service quality index based on the power supply reliability index.

2. A method for evaluating power grid service quality indicators, using the power grid service quality indicator evaluation system according to claim 1, characterized in that: include, Classify each component in the target power grid according to the characteristic information of the power grid components to obtain a component set of different component types; Based on the element set, association mapping is performed on the corresponding power grid elements in the topological structure and element category attributes are assigned to construct a power grid topological structure model; the topological structure is constructed with the power equipment in the target power grid as node elements and the power transmission lines of the power equipment as connection elements; Determining coupling relationship information between components in the target power grid based on the power grid topology model, and generating multiple fault scenarios based on the coupling relationship information and environmental interference factor information; Determining the set of affected components and the corresponding probability of failure in each fault scenario, and determining the power outage duration for each type of user in each fault scenario based on the grid topology model; The power supply reliability index of the target power grid is determined based on the fault occurrence probability and the power outage time under each fault scenario, and the service quality index is evaluated based on the power supply reliability index.

3. A method for evaluating power grid service quality indicators according to claim 2, characterized in that: The determining of the power supply reliability index of the target power grid based on the fault occurrence probability and the power outage time under each fault scenario, and performing a service quality index evaluation based on the power supply reliability index, includes: Determine the expected power outage duration for users under each fault scenario based on the fault probability and power outage duration under each fault scenario; Determining a power supply reliability index based on the user's expected power outage time, and determining a user satisfaction index value, a power service availability index value, and a power quality compliance rate index value based on the power supply reliability index; A service quality index evaluation is performed based on the user satisfaction index value, the power service availability index value, and the power quality compliance rate index value.

4. A method for evaluating power grid service quality indicators according to claim 3, characterized in that: Determining coupling relationship information between components in the target power grid based on the power grid topology model includes: Acquire, based on the power grid topology model, a first element and a second element having a connection relationship, and a target transmission line of the first element and the second element; determining an electrical coupling coefficient between the first element and the second element based on a line current flowing through the target transmission line, a line voltage difference between two ends of the target transmission line, and a shortest electrical distance between the first element and the second element in a topological structure; determining an electromagnetic coupling coefficient between the first element and the second element based on a first current flowing through the first element, a second current flowing through the second element, and a spatial distance between the first element and the second element; determining a coupling relationship coefficient between the first element and the second element based on the electrical coupling coefficient and the electromagnetic coupling coefficient; Based on the coupling relationship coefficient between the first element and the second element, coupling relationship information between the elements having a connection relationship in the target power grid is constructed.

5. A method for evaluating power grid service quality indicators according to claim 4, characterized in that: Based on the coupling relationship information and environmental interference factor information, multiple fault scenarios are generated, including: quantifying the environmental interference factor information to obtain a quantized value of the environmental factor; Determining a fault triggering condition based on the coupling relationship coefficient between the components and the quantified value of the environmental factor; Traversing all component combinations based on the fault triggering condition to obtain a target component combination that meets the fault triggering condition, and determining the fault type according to the position of the target component combination in the topological structure and the component functional characteristics of the target component combination; Based on each fault type and corresponding fault results, multiple fault scenarios are generated.

6. A method for evaluating power grid service quality indicators according to claim 5, characterized in that: Determining the affected component set and the corresponding failure probability under each fault scenario includes: Performing a fault propagation analysis on each fault scenario based on the grid topology model and determining the set of affected components in each fault scenario in combination with coupling coefficients between components; The failure probability under each fault scenario is determined based on the failure rate, aging coefficient and environmental sensitivity of each component in the set of affected components under each fault scenario.

7. A method for evaluating power grid service quality indicators according to claim 6, characterized in that: Determining the power outage time for each type of user under each fault scenario based on the power grid topology model includes: Classifying various types of users in the target power grid to obtain user sets of different categories, and analyzing the power supply path of each user in the user set based on the power grid topology model to obtain a power supply path set for each user in the user set; Analyze the impact of each fault scenario on the power supply path of each user and determine the number of components on the power supply path affected by the fault for each user; Based on the number of components, the fault repair time of each component, and the spare capacity and power transfer capability of the target power grid, the power outage time for each type of user in each fault scenario is determined.

8. A method for evaluating power grid service quality indicators according to claim 7, characterized in that: The grid component characteristic information includes functional attributes, fault probability distribution characteristics, importance level, and the degree of impact on power supply to different types of users; The components in the target power grid are classified according to the grid component characteristic information to obtain component sets of different component types, including: creating a first number of empty component type sets, using a first target component in the target power grid as an initial cluster center of each empty component type set, and using the remaining components in the target power grid except the first target component as components to be classified; For any second target element among the elements to be classified, obtaining a target empty element type set based on the first element characteristic index of the second target element; a similarity index between the second element characteristic index and the first element characteristic index of the initial cluster center of the target empty element type set is a maximum value; the element characteristic index is obtained by quantifying the functional attributes, the fault probability distribution characteristics, the importance level, and the power supply impact degree; Classifying the second target component into the target empty component type set, and updating the initial component type set of the target empty component type set; determining an updated cluster center of the initial component type set based on the first component characteristic index and the second component characteristic index until the updated cluster centers converge to obtain a target component type set corresponding to the initial component type set; Component sets of different component types are obtained based on all target component type sets.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the power grid service quality indicator evaluation system according to claim 1 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the power grid service quality indicator evaluation system according to claim 1 are implemented.

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