Fault diagnosis method and terminal for action of secondary equipment in dispatching automation system

Abstract

The invention discloses a fault diagnosis method for secondary equipment action in a dispatching automation system and a terminal. Modeling is carried out according to a switch action sequence of a secondary equipment action condition related device in the dispatching automation system and a related device triggered by the secondary equipment action; establishing a fault diagnosis model based on a time sequence constraint network in combination with a modeling result, obtaining a fault diagnosis result through reasoning of the fault diagnosis model, analyzing a time sequence constraint relation between events represented by the fault diagnosis result, and converting the time sequence constraint relation into a linear inequality equation; verifying the fault diagnosis result by judging the compatibility of the linear inequality equation, and if the verification is passed, acquiring device information through an interface of a fault device corresponding to the fault diagnosis result; and performing event analysis according to the device information and the fault diagnosis result to obtain a fault event. In this way, the fault analysis and diagnosis process can be shortened, and the fault handling efficiency can be remarkably improved.

Description

Technical Field

[0001] The present invention relates to the technical field of power grid fault diagnosis, and in particular to a fault diagnosis method and a terminal for secondary equipment action in a dispatching automation system. Background Art

[0002] The fault diagnosis algorithm currently used in the power grid is relatively simple. Its principle is mainly based on the simple correlation analysis of the protection action signal and the switch position signal. In essence, it is still based on the expert system (ES) method, and the logical rigor of the algorithm is difficult to be reliably guaranteed.

[0003] Experts and scholars at home and abroad have done a lot of research in this field and proposed a variety of diagnostic methods, including expert systems (ES), artificial neural networks (ANN), analytical model optimization (Optimization Method), Petri nets, causal networks, fuzzy set theory (FT), Bayesian networks and information theory. These methods have their own advantages and disadvantages. Among them, there are not many methods that can be put into practical application, which are limited to expert systems, Petri networks and other methods.

[0004] Moreover, there are still some deficiencies in the modeling method of the action logic of secondary equipment in the existing dispatching automation system. For example, the large amount of information generated by the existing dispatching automation system after a fault occurs causes congestion in the information transmission link. Due to the defects in the design of the secondary equipment communication link, the problem of missing some key fault information cannot be completely avoided. Moreover, the modeling of secondary equipment in the existing dispatching automation system is more for equipment monitoring or specific applications (such as secondary equipment operation status analysis), and cannot fully and accurately reflect the action logic of secondary equipment. Summary of the invention

[0005] The technical problem to be solved by the present invention is to provide a fault diagnosis method and terminal for secondary equipment action in a dispatching automation system, which can shorten the process of fault analysis and diagnosis and significantly improve the efficiency of fault handling.

[0006] In order to solve the above technical problems, the technical solution adopted by the present invention is:

[0007] A method for diagnosing a fault in a secondary device in a dispatching automation system comprises the following steps:

[0008] S1. Modeling is performed based on the relay protection devices, reclosing devices and standby automatic switching devices related to the secondary equipment action conditions in the dispatching automation system, as well as the switch action sequences of the relay protection devices, reclosing devices and standby automatic switching devices triggered by the secondary equipment actions;

[0009] S2. According to the modeling result of step S1, a fault diagnosis model based on a timing constraint network is established, and fault reasoning is performed through the fault diagnosis model to obtain a fault diagnosis result;

[0010] S3, analyzing the timing constraint relationship between the events represented by the fault diagnosis result, and converting the analysis result into a linear inequality equation, and verifying the fault diagnosis result by judging the compatibility of the linear inequality equation;

[0011] S4. If the fault diagnosis result is verified, obtaining device information through an interface of the fault device corresponding to the fault diagnosis result;

[0012] S5. Perform event analysis based on the device information and the fault diagnosis result to obtain a fault event.

[0013] In order to solve the above technical problems, another technical solution adopted by the present invention is:

[0014] A fault diagnosis terminal for secondary equipment action in a dispatching automation system comprises a memory, a processor and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, each step of the above-mentioned method for fault diagnosis of secondary equipment action in a dispatching automation system is implemented.

[0015] The beneficial effects of the present invention are: modeling is performed according to the relay protection device, reclosing device and standby automatic device related to the action conditions of the secondary equipment in the dispatching automation system, and the switch action sequence of the related devices triggered by the action of the secondary equipment; a fault diagnosis model based on the timing constraint network is established in combination with the modeling results, the fault diagnosis result is obtained by reasoning the fault diagnosis model, the timing constraint relationship between the events represented by the fault diagnosis result is analyzed, and the analysis result is converted into a linear inequality equation, and the fault diagnosis result is verified by judging the compatibility of the linear inequality equation. If the verification is passed, the device information is obtained through the interface of the fault device corresponding to the fault diagnosis result; event analysis is performed according to the device information and the fault diagnosis result to obtain the fault event. In this way, based on the analysis of the fault itself and the related relay protection devices, safety automatic devices and switch action behaviors, an important decision-making basis can be provided for the recovery and disposal of power grid faults, and the safety, correctness and effectiveness of the recovery and disposal plan can be guaranteed; and by improving the secondary equipment model, the problems of large maintenance workload and untimely maintenance caused by the need for a large number of repeated fault diagnosis logic modeling in the previous fault diagnosis method can be solved. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a flow chart of a method for diagnosing a fault of a secondary device action in a dispatching automation system according to an embodiment of the present invention;

[0017] Figure 2 A schematic diagram of a fault diagnosis terminal for secondary equipment actions in a dispatching automation system according to an embodiment of the present invention;

[0018] Figure 3 A schematic diagram of a modeling method for a relay protection device according to an embodiment of the present invention;

[0019] Figure 4 A schematic diagram of a reclosing function modeling method according to an embodiment of the present invention;

[0020] Figure 5 An example diagram of a timing constraint network according to an embodiment of the present invention;

[0021] Figure 6 Schematic diagram of the principle of event-based analysis of fault information according to an embodiment of the present invention.

[0022] Description of labels:

[0023] 1. A fault diagnosis terminal for secondary equipment action in a dispatching automation system; 2. A memory; 3. A processor. DETAILED DESCRIPTION

[0024] In order to explain the technical content, achieved objectives and effects of the present invention in detail, the following is an explanation in combination with the implementation modes and the accompanying drawings.

[0025] Please refer to Figure 1 The embodiment of the present invention provides a method for diagnosing a fault of a secondary device in a scheduling automation system, comprising the steps of:

[0026] S1. Modeling is performed based on the relay protection devices, reclosing devices and standby automatic switching devices related to the secondary equipment action conditions in the dispatching automation system, as well as the switch action sequences of the relay protection devices, reclosing devices and standby automatic switching devices triggered by the secondary equipment actions;

[0027] S2. According to the modeling result of step S1, a fault diagnosis model based on a timing constraint network is established, and fault reasoning is performed through the fault diagnosis model to obtain a fault diagnosis result;

[0028] S3, analyzing the timing constraint relationship between the events represented by the fault diagnosis result, and converting the analysis result into a linear inequality equation, and verifying the fault diagnosis result by judging the compatibility of the linear inequality equation;

[0029] S4. If the fault diagnosis result is verified, obtaining device information through an interface of the fault device corresponding to the fault diagnosis result;

[0030] S5. Perform event analysis based on the device information and the fault diagnosis result to obtain a fault event.

[0031] From the above description, it can be seen that the beneficial effects of the present invention are: modeling is performed according to the relay protection device, reclosing device and standby automatic device related to the action conditions of the secondary equipment in the dispatching automation system, and the switch action sequence of the related devices triggered by the secondary equipment action; a fault diagnosis model based on the timing constraint network is established in combination with the modeling results, the fault diagnosis result is obtained by reasoning the fault diagnosis model, the timing constraint relationship between the events represented by the fault diagnosis result is analyzed, and the analysis result is converted into a linear inequality equation, and the fault diagnosis result is verified by judging the compatibility of the linear inequality equation. If the verification is passed, the device information is obtained through the interface of the fault device corresponding to the fault diagnosis result; event analysis is performed according to the device information and the fault diagnosis result to obtain the fault event. In this way, based on the analysis of the fault itself and the related relay protection devices, safety automatic devices and switch action behaviors, an important decision-making basis can be provided for the recovery and disposal of power grid faults, and the safety, correctness and effectiveness of the recovery and disposal plan can be guaranteed; and by improving the secondary equipment model, the problems of large maintenance workload and untimely maintenance caused by the need for a large number of repeated fault diagnosis logic modeling in the previous fault diagnosis method can be solved.

[0032] Further, step S1 includes:

[0033] Modeling the relay protection device: dividing the relay protection device according to its function, and modeling it in combination with the protection function of the relay protection device, the faults reacted by the protection function, the faults generated after the protection function is actuated, and the switch action sequence triggered after the protection function is actuated;

[0034] Modeling the reclosing device: Modeling the line / switch protection function that initiates the reclosing, the opening switch triggered by the line / switch protection function, and the closing switch triggered by the reclosing action;

[0035] Modeling the standby automatic switching device: Modeling is performed based on the operation mode of the standby automatic switching device and its charging conditions, action conditions and switch action sequence.

[0036] From the above description, it can be seen that the relay protection device provides conditions for the action of the secondary equipment by detecting faults and sending action signals; the reclosing device quickly restores power supply after the fault is eliminated; the backup automatic device automatically switches to the backup power supply when the main power supply disappears to ensure the stable operation of the system. These devices work together to provide a strong guarantee for the safe and stable operation of the power system. Therefore, based on the analysis and modeling of the fault itself and the related relay protection devices, safety automatic devices and switch action behaviors, it can provide an important decision-making basis for the recovery and disposal of power grid faults, and ensure the safety, correctness and effectiveness of the recovery and disposal plan.

[0037] Furthermore, in step S2, according to the modeling result of step S1, establishing a fault diagnosis model based on a timing constraint network includes:

[0038] Acquiring the models established in step S1 for the relay protection device, the reclosing device and the standby automatic switching device, and dynamically correcting and modeling the timing constraint network in combination with the current wiring mode of the power grid of the dispatching automation system;

[0039] The timing constraint network includes a quintuple: G = (V, E, T, C1, C2)

[0040] Where V = {v1,v2,…,v N} represents the node set of the event, which is divided into cause node V C and alarm node V A ; E = { <v i ,v j >|v i ,v j ∈V} represents the set of directed edges in the directed acyclic graph; is the set of time points corresponding to each event in V, Represents event v i The time when it occurred; Indicates time point Constraints; Indicates time point and The time distance constraint between them.

[0041] From the above description, it can be seen that the fault diagnosis model based on the timing constraint network uses the timing constraint network to describe the event logic relationship and time constraint relationship between "primary equipment failure, relay protection / safety automatic device switch, and switch action". The accurate description of the correlation between the primary equipment failure, secondary equipment action and switch action can solve the problems of large maintenance workload and untimely maintenance caused by the previous fault diagnosis methods that require a large amount of repeated fault diagnosis logic modeling.

[0042] Furthermore, in step S2, a fault diagnosis model based on a timing constraint network is established, and fault reasoning is performed through the fault diagnosis model to obtain a fault diagnosis result, which also includes:

[0043] According to the fault information obtained from the modeling results, the state of the alarm node representing the relay protection, safety automatic device and switch action behavior in the timing constraint network is maintained;

[0044] Based on the timing constraint network, reverse timing reasoning is performed on the alarm node at the end to obtain a fault diagnosis result.

[0045] From the above description, it can be seen that by maintaining the status of the alarm nodes that represent the relay protection, safety automatic devices and switch action behaviors in the timing constraint network, and performing reverse timing reasoning on the terminal alarm nodes to obtain the fault diagnosis results, a more reasonable and effective fault diagnosis result can be obtained.

[0046] Furthermore, in step S3, analyzing the timing constraint relationship between the events represented by the fault diagnosis result includes:

[0047] The equation constraint relationship of the fault diagnosis result is obtained according to the timing constraint network subgraph:

[0048] If there is a subgraph The alarm nodes that receive the alarm information are recorded as nodes vk a The accurate time stamp of the event occurrence is the alarm information receiving time stamp and the time stamp error is and There are equality constraints:

[0049]

[0050] For any two connected event nodes v i and v j , there is an equality constraint relationship:

[0051]

[0052] In the formula, and d(v i ,v j ) represent the event v i and v j The exact time distance and the time distance calculated based on the information reception time stamp, δ vi and δ vj Respectively represent the event v i and v j The time scale error.

[0053] Furthermore, analyzing the timing constraint relationship between the events represented by the fault diagnosis result in step S3 also includes:

[0054] According to the timing constraint network subgraph, the inequality constraint relationship of the fault diagnosis result is obtained:

[0055] If the protection r i Action, for p(r i ,d k ), in the fault diagnosis result, the switch does not act or its action time satisfies:

[0056]

[0057] If the fault diagnosis result r i If the protection does not operate, the reason for the protection not operating can be expressed as:

[0058]

[0059] From the above description, it can be seen that the analysis of the timing constraint relationship between the events represented by the fault diagnosis results is the power grid fault diagnosis result reflected by the timing constraint network subgraph, which includes two types of constraint relationships: equality constraints and inequality constraints. By determining the two types of constraint relationships, the accuracy of subsequent fault diagnosis result analysis can be improved.

[0060] Furthermore, in step S3, converting the analysis result into a linear inequality equation includes:

[0061] Converting the inequality constraint relationship of the fault diagnosis result into a linear expression;

[0062] The transformed linear expressions and the linear inequalities determined by the logic modeling of the secondary equipment actions are combined to obtain a group of linear inequalities for uncertain quantities.

[0063] From the above description, it can be seen that through the linear transformation of the expression, the secondary equipment and switch action behavior can be analyzed and evaluated during the occurrence and evolution of the fault, which can provide a basis for the treatment of related equipment defects.

[0064] Furthermore, in step S4, obtaining device information through an interface of the fault device corresponding to the fault diagnosis result includes:

[0065] Through the interface with the wave recording function, online monitoring and analysis function of the standby automatic start-up device, the information required for refined fault analysis and diagnosis is obtained in the form of wave recording briefings and standby automatic start-up device action briefings.

[0066] Further, step S5 includes:

[0067] Restore the process of fault occurrence and evolution based on the fault diagnosis results, describe the fault itself and the relay protection, installation automatic device, and switch action behaviors triggered by it, and evaluate the impact of the fault on the power grid;

[0068] Establish the correlation mapping relationship between fault events, relay protection, installation automatic devices, switch action behaviors and fault information generated by the dispatching automation system, and organize the fault information into events to obtain fault events.

[0069] From the above description, it can be seen that while locating the fault, the original appearance of the fault occurrence and evolution process is intuitively presented to the power grid operation personnel in the form of events, which can significantly reduce the difficulty of fault analysis.

[0070] Please refer to Figure 2 Another embodiment of the present invention provides a fault diagnosis terminal for secondary equipment action in a scheduling automation system, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the processor implements the various steps of the above-mentioned method for fault diagnosis of secondary equipment action in a scheduling automation system.

[0071] The above-mentioned method and terminal for diagnosing the fault of secondary equipment in the dispatching automation system of the present invention are suitable for shortening the process of fault analysis and diagnosis in the dispatching automation system and significantly improving the efficiency of fault handling. The following is an explanation through specific implementation methods:

[0072] Embodiment 1

[0073] Please refer to Figure 1 , a method for diagnosing a fault of a secondary device action in a dispatching automation system, comprising the steps of:

[0074] S1. Model the relay protection devices, reclosing devices and standby automatic switching devices related to the secondary equipment action conditions in the dispatching automation system, as well as the switching action sequences of the relay protection devices, reclosing devices and standby automatic switching devices triggered by the secondary equipment actions.

[0075] S11. Modeling a relay protection device: dividing the relay protection device according to its function, and modeling it in combination with the protection function of the relay protection device, the faults reacted by the protection function, the faults generated after the protection function is actuated, and the switch action sequence triggered after the protection function is actuated.

[0076] Please refer to Figure 3, to model the relay protection device, first, the protection can sense the fault, that is, the changes in electrical quantities such as voltage and current caused by the fault can be sensed by the protection device; second, the fault is within the protection range of the protection device, that is, it meets the protection action conditions, including the set value, fault direction, delay and other action conditions, and it is also necessary to describe the disconnect switch triggered by the action of the secondary equipment.

[0077] Therefore, the specific process of modeling a relay protection device is as follows:

[0078] (1) Classify relay protection equipment according to its function and describe the protection functions included in the device:

[0079] First, divide it according to the protection principle. Taking a 110kV line as an example, it can be divided into overcurrent protection, zero-sequence protection, phase-to-phase distance protection, and ground distance protection; then further divide it according to the action time limit. For example, for the phase-to-phase distance protection of the 110kV line, it can be divided into phase-to-phase distance section I, phase-to-phase distance section II, and phase-to-phase distance section III.

[0080] (2) Describe the fault reflected by the protection function:

[0081] For each specific protection function in the protection device, according to its implementation principle, the faults it can reflect are described, including its approximate protection range, direction and fault category.

[0082] (3) Describe the faults that occur after the protection function is activated:

[0083] The protection action information currently connected to the information control system can be mainly divided into remote signaling information and protection signaling information. Therefore, when modeling the relay protection equipment, the fault information expected to be generated after each specific protection function action should be described.

[0084] (4) Describe the switch action sequence triggered by the protection function:

[0085] The switch action sequence triggered after the protection function is actuated is related to both the configuration of the protection function itself and the current wiring method of the power grid. For protections that require the action switch sequence to be determined in combination with the current wiring method of the power grid, such as main transformer protection, busbar differential protection, longitudinal differential protection, etc., the system should automatically determine the switch action sequence triggered after the protection action according to the current wiring method of the power grid.

[0086] S12. Modeling the reclosing device: Modeling is performed based on the protection function of the line / switch that starts the reclosing, the opening switch triggered by the protection function of the line / switch, and the closing switch triggered after the reclosing action.

[0087] Please refer to Figure 4, modeling the reclosing device, specifically the combination of protection and switching actions and the closing switch triggered by the secondary equipment action.

[0088] S13, modeling the standby automatic switching device: modeling is performed in combination with the operation mode of the standby automatic switching device and its charging conditions, action conditions and switch action sequence.

[0089] Among them, the modeling of the backup automatic switching device is specifically to model the changes in related electrical quantities such as voltage and current caused by the fault and the switch opening and closing sequence triggered by the action of the secondary equipment.

[0090] S2. According to the modeling result of step S1, a fault diagnosis model based on a timing constraint network is established, and fault reasoning is performed through the fault diagnosis model to obtain a fault diagnosis result.

[0091] S21. Obtain the models established in step S1 for the relay protection device, the reclosing device and the standby automatic switching device, and dynamically correct the timing constraint network in combination with the current power grid connection mode of the dispatching automation system.

[0092] In this embodiment, the establishment of the diagnostic model is, on the one hand, to obtain the secondary equipment and its action logic model on the dispatching automation system, and on the other hand, it is necessary to dynamically correct the timing constraint network in combination with the current wiring mode of the power grid.

[0093] Please refer to Figure 5 The fault diagnosis model based on the timing constraint network is established by the timing constraint network to describe the event logic relationship and time constraint relationship between "primary equipment failure-relay protection / safety automatic device switch-switch action". The timing constraint network includes five tuples: G = (V, E, T, C1, C2)

[0094] Where V = {v1, v2, …, v N} represents the node set of the event, which is divided into cause node V C and alarm node V A , where V C ={c1,c2,…,c Nc},V A ={a1,a2,…,a NA}, Timing Constraint Network Applied to Power Grid Fault Diagnosis, V A Can be further divided into protection alarm node V R and switch alarm node V B ; E = { <v i ,v j >|v i ,v j ∈V} represents the set of directed edges in a directed acyclic graph, v i vj The predecessor node, v j v i The successor node of i The occurrence of will trigger the event v j Occurrence of; is the set of time points corresponding to each event in V, Represents event v i The time when it occurred; Indicates time point Constraints; Indicates time point and The time distance constraint between them.

[0095] Among them, define the slave node v i to v j The path is a sequence of events P{u1,u2,u m}:

[0096] ①m≥2;

[0097] ②u1=v i Andu m =v j ;

[0098] ③u1,u2,…,u m ∈V;

[0099] ④

[0100] Let Start(P) and End(P) represent the starting node and ending node of event sequence P respectively. Obviously:

[0101] Start(P)=u1=v i , End(P)=u m =v j ;

[0102] And in the temporal reasoning, the temporal reasoning definition of the timing constraint network defines Forward(v i ) represents the event v i The set of all subsequent events that can be triggered by the occurrence of Backward(v j ) indicates that event v may occur j A set of events that occurred; based on temporal reasoning, Cause[(a j ,t aj )], used to indicate the possibility of causing "at t aj Time event a j ” is a collection of hypotheses about the causes.

[0103] S22. According to the fault information obtained from the modeling results, maintain the status of the alarm node in the timing constraint network that represents the relay protection, safety automatic device and switch action behavior; based on the timing constraint network, perform reverse timing reasoning on the alarm node at the end to obtain the fault diagnosis result.

[0104] Specifically, the program development of the fault diagnosis algorithm involves the state maintenance module of the alarm node. Specifically, through the basic platform of the control system, remote signaling and protection signal fault information is obtained to realize the state maintenance of the alarm nodes that represent the relay protection, safety automatic devices and switch action behaviors in the timing constraint network; it also involves the fault reasoning module. Specifically, based on the timing constraint network, the fault diagnosis results are obtained through reverse timing reasoning of the terminal alarm node.

[0105] In this embodiment, for reverse temporal reasoning, if h(c i ,T(t cj ))∈Cause[(a j ,t aj )], then from c i to a j The number of alarm nodes receiving alarm information on the path reflects the number of alarm nodes caused by the cause event c. i The alarm event a j The credibility of the node should be determined by giving priority to the node that receives the alarm information when performing reverse temporal reasoning.

[0106] In this embodiment, the following node set can be defined:

[0107]

[0108] In the formula, Represents node a 0,j Receiving an alert message; Represents node a 0,j The out-degree of is 0; means Forward(a 0,j ) None of the nodes received the alarm information;

[0109] from Take any node a 0,j , perform breadth-first search on the timing constraint network to obtain the nodes from the cause node to a 0,j All possible paths of

[0110] Define the following sequence of integer variables: α0, α1, …, α k , when k = 0, the sequence is α0; when k = 1, the sequence is α0, α1, and so on.

[0111] Use a sequence of integer variables to mark the nodes, node sets, and the number of nodes in a node set obtained during the search process;

[0112] The node set is denoted as The number of nodes in the set is denoted by The nodes in the set are denoted by Should be The predecessor nodes include the cause nodes and the alarm nodes, wherein the alarm nodes give priority to all nodes that have received the alarm information. If there is no alarm node that meets the conditions, it is composed of all nodes that have not received the alarm information.

[0113] Among them, α k The value of k≥1; when α k When the value of is 1,

[0114] Perform the following search: Let k = 1; Classify the nodes in V C Node, you can get an alarm about a 0,j Hypothesis path of cause:

[0115]

[0116] For those that do not belong to V C , then let k = k + 1, and repeat Until the completion from the cause node to a 0,j A search of all possible paths that constitute a 0,j A set of causal hypothesis paths;

[0117] gather Each alert node in Take any node a 0,j , perform a breadth-first search on the timing constraint network to obtain the nodes from the cause node to a 0,j All possible paths of The set of cause hypothesis paths for each alarm node in;

[0118] Respectively from Select a path from the cause hypothesis path set of each alarm node, then integrate the extracted paths, merge the same nodes, form a subgraph of the original timing constraint network, and form the following subgraph set:

[0119] Generate possible fault hypotheses: Let k = 1; for subgraph G k , let the switch alarm node set in the figure be The protection alarm node set is according to Combined with the grid topology before the fault occurred, check whether the fault has been eliminated;

[0120] If the fault has been removed, then subgraph G k That corresponds to a possible fault hypothesis, continue to execute (let k = k + 1, when k ≤ N S When k , let the switch alarm node set in the figure be The set of protection alarm nodes is according to Combined with the grid topology before the fault occurs, check whether the fault has been cleared); if the fault has not been cleared, it means that G k The switch alarm node that has not received the alarm information is missing, and the execution continues (search for the switch alarm node a that meets the following conditions 0,j );

[0121] Search for switch alarm nodes a that meet the following conditions 0,j :

[0122] a j,b ∈V B and

[0123] If the node set that meets the above conditions is not empty, then according to the principle that the fault can be removed and the number is as small as possible, select the switch alarm node from the node set and add it to G k , get a possible fault hypothesis; otherwise, continue to execute (let k = k + 1, when k ≤ N S When k , let the switch alarm node set in the figure be The protection alarm node set is according to Combined with the grid topology before the fault occurred, check whether the fault has been eliminated);

[0124] By executing (let k = 1) to the subgraph G k , let the switch alarm node set in the figure be The protection alarm node set is according to Combined with the grid topology before the fault occurs, the process of checking whether the fault has been removed is used to generate a set of fault hypotheses for fault diagnosis.

[0125] S3, analyzing the timing constraint relationship between the events represented by the fault diagnosis result, and converting the analysis result into a linear inequality equation, and verifying the fault diagnosis result by judging the compatibility of the linear inequality equation.

[0126] Specifically, it is necessary to analyze the timing constraint relationship between the events represented by the fault diagnosis results;

[0127] The timing constraint relationship between events represented by the fault diagnosis results is converted into a set of mathematical linear inequality equations. By judging the compatibility of the linear inequality group, the validity of the fault hypothesis is verified.

[0128] S31, obtaining the equation constraint relationship of the fault diagnosis result according to the timing constraint network subgraph:

[0129] If there is a subgraph The alarm nodes that receive the alarm information are recorded as nodes vk a The accurate time stamp of the event occurrence is the alarm information receiving time stamp and the time stamp error is and There is a first equality constraint:

[0130]

[0131] For any two connected event nodes v i and v j , there is a second equality constraint:

[0132]

[0133] In the formula, and d(v i ,v j ) represent the event v i and v j The exact time distance and the time distance calculated based on the information reception time stamp, δ vi and δ vj Respectively represent the event v i and v j The time scale error of

[0134] set up The nodes that receive the alarm information are connected, and there is a third equality constraint:

[0135]

[0136] In the formula, I represents The identity matrix of order.

[0137]

[0138] in, There is an undetermined switch action delay in the third equation. If there is N τIf there are two undetermined switch action delays, they are recorded as:

[0139] For any alarm time scale error, there is an error range: The kth a The upper and lower bounds of the time scale error of the alarm nodes are 1≤k τ ≤N τ ;

[0140] Considering the above situation, we can get the following Linear inequalities:

[0141]

[0142] It includes Total N τ +1 uncertainty;

[0143] S32, obtaining the inequality constraint relationship of the fault diagnosis result according to the timing constraint network subgraph:

[0144] Among them, the conditions for protection action after a fault occurs can be: ① the fault is within the protection range; ② the fault can always be sensed during the period from protection start to action exit.

[0145] The reasons why the protection does not operate after a fault occurs may be: ① The fault is not within the protection range; ② The fault is within the protection range, but the protection refuses to operate; ③ The fault is within the protection range and the protection has been activated, but before the expected operation time, other fast protection actions will cut off the fault.

[0146] Assume that in the timing constraint network G, G k To represent the element d k The node causing the failure, a r,i To protect r i The alert node of the action, p(r i ,d k ) indicates protection r i To component d k The associated path, a bj Indicates the switch b on the associated path j The alert node of the action;

[0147] If the protection r i Action, for p(r i ,d k ), in the fault diagnosis result, the switch does not act or its action time satisfies the first inequality:

[0148]

[0149] If the fault diagnosis result r i If the protection does not act, the reason why the protection does not act can be expressed by the second inequality:

[0150]

[0151] S33, converting the inequality constraint relationship of the fault diagnosis result into a linear expression; combining the converted linear expression and the linear inequality determined by the secondary equipment action logic modeling to obtain a linear inequality group of uncertain quantities.

[0152] Specifically, in the first and second inequalities and Obviously, it can also be written The linear expression of

[0153] In summary, the secondary equipment action logic modeling on the joint control system determines Linear inequalities and the linear inequalities determined by the first and second inequalities give us a linear inequality containing Total N τ +1 linear inequality group of uncertain variables. By judging whether the linear inequality group is consistent, it can be judged whether the fault hypothesis is valid;

[0154] The judgment on whether the fault hypothesis is valid is converted into the compatibility judgment of the linear inequality group. The following introduces the method for solving the linear inequality group adopted in this project research;

[0155] The obvious case that a system of linear inequalities is consistent

[0156] The linear inequality group is (I): Yx ≥ Z, let x = (x1, x2, ..., x n ) T

[0157] n=N τ +

[0158]

[0159] Y=(y1,y2,…y m ) T

[0160] y i =(y i 2, …y in ) T , 1≤i≤m

[0161] Z=(z1,z2,…z m ) T

[0162] There are obvious cases like:

[0163] ①Obviously, situation α

[0164] When Y=0, if Then the inequality group is incompatible; on the contrary, if zi≤0, 1≤i≤m, then the inequality group is compatible;

[0165] ②Obviously, the situation β

[0166] like If y1j,y2j,…,ymj are all positive or all negative, then the inequality group is compatible;

[0167] When the linear inequality group satisfies the obvious case α or β above, it will be easy to determine whether the inequality group is compatible;

[0168] Among them, the elimination method solves the linear inequality system, and the steps are as follows:

[0169] ① According to the coefficient of a certain unknown number, the linear inequalities in (I) are divided into three categories: those with positive coefficients are classified into the first category; those with negative coefficients are classified into the second category; those with zero coefficients are classified into the third category. The coefficients of the unknown number in the first and second category inequalities are converted to 1 and -1 respectively. The third category inequality remains unchanged. The linear inequality group (I)' obtained from this is exactly the same as the solution of (I);

[0170] ② Add each inequality of the first type in (I)' to each inequality of the second type, and use the resulting inequalities and the third type inequalities in (I)' to form a new inequality group (I1). It can be proved that the necessary and sufficient condition for (I) to be consistent is that (I1) is consistent;

[0171] ③ Repeat the elimination process of steps ① and ② for (I1), and eventually we can always get a linear inequality group that satisfies the obvious situation described in (the obvious situation of the consistency of the linear inequality group). This inequality group is denoted as (Is). Obviously, the necessary and sufficient condition for the consistency of (I) is that (Is) is consistent. Therefore, it is easy to conclude whether (I) is consistent by judging whether (Is) is consistent.

[0172] S4. If the fault diagnosis result is verified, obtaining device information through an interface of the fault device corresponding to the fault diagnosis result.

[0173] Through the interface with the wave recording function, online monitoring and analysis function of the standby automatic start-up device, the information required for refined fault analysis and diagnosis is obtained in the form of wave recording briefings and standby automatic start-up device action briefings.

[0174] S5. Perform event analysis based on the device information and the fault diagnosis result to obtain a fault event.

[0175] For details, please refer to Figure 6 , restore the process of fault occurrence and evolution according to the fault diagnosis results, describe the fault itself and the actions of relay protection, installation automatic devices, and switches triggered by it, and evaluate the impact of the fault on the power grid;

[0176] Establish the correlation mapping relationship between fault events, relay protection, installation automatic devices, switch action behaviors and fault information generated by the dispatching automation system (including remote signaling, protection signaling, recording briefing, standby automatic transfer action briefing, etc.), and organize the fault information into events to obtain fault events.

[0177] Embodiment 2

[0178] Please refer to Figure 2 A fault diagnosis terminal 1 for secondary equipment action in a dispatching automation system includes a memory 2, a processor 3, and a computer program stored in the memory 2 and executable on the processor 3. When the processor 3 executes the computer program, each step of a fault diagnosis method for secondary equipment action in a dispatching automation system of embodiment 1 is implemented.

[0179] In summary, the present invention provides a method and terminal for fault diagnosis of secondary equipment action in a dispatching automation system. Modeling is performed based on the relay protection device, reclosing device and standby automatic switching device related to the action conditions of the secondary equipment in the dispatching automation system, as well as the switch action sequence of the related devices triggered by the secondary equipment action; a fault diagnosis model based on a timing constraint network is established in combination with the modeling results, the fault diagnosis result is obtained by reasoning the fault diagnosis model, the timing constraint relationship between the events represented by the fault diagnosis result is analyzed, and the analysis result is converted into a linear inequality equation, and the fault diagnosis result is verified by judging the compatibility of the linear inequality equation. If the verification is passed, the device information is obtained through the interface of the fault device corresponding to the fault diagnosis result; event analysis is performed based on the device information and the fault diagnosis result to obtain the fault event. In this way, by improving the secondary equipment model of the dispatching automation system, an accurate description of the correlation between the primary equipment fault, the secondary equipment action and the switch action is achieved, and the problems of large maintenance workload and untimely maintenance caused by the need for a large number of repeated fault diagnosis logic modeling in the previous fault diagnosis method are solved. In addition, the analysis and evaluation of the secondary equipment and switch action behaviors during the occurrence and evolution of the fault can provide a basis for the treatment of related equipment defects. While locating the fault, the original appearance of the fault occurrence and evolution process can be intuitively presented to the power grid operators in the form of events, significantly reducing the difficulty of fault analysis. Furthermore, based on the analysis of the fault itself and the related relay protection devices, safety automatic devices and switch action behaviors, it can provide important decision-making basis for power grid fault recovery and disposal, and ensure the safety, correctness and effectiveness of the recovery and disposal plan.

[0180] The above descriptions are merely embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent transformations made using the contents of the present invention's specification and drawings, or directly or indirectly applied in related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A method for diagnosing faults in secondary equipment actions in a dispatching automation system, characterized in that: Includes steps: S1. Modeling is performed based on the relay protection devices, reclosing devices and standby automatic switching devices related to the secondary equipment action conditions in the dispatching automation system, as well as the switch action sequences of the relay protection devices, reclosing devices and standby automatic switching devices triggered by the secondary equipment actions; S2. According to the modeling result of step S1, a fault diagnosis model based on a timing constraint network is established, and fault reasoning is performed through the fault diagnosis model to obtain a fault diagnosis result; S3, analyzing the timing constraint relationship between the events represented by the fault diagnosis result, and converting the analysis result into a linear inequality equation, and verifying the fault diagnosis result by judging the compatibility of the linear inequality equation; S4. If the fault diagnosis result is verified, obtaining device information through an interface of the fault device corresponding to the fault diagnosis result; S5. Perform event analysis based on the device information and the fault diagnosis result to obtain a fault event.

2. A method for diagnosing faults of secondary equipment in a dispatching automation system according to claim 1, characterized in that: Step S1 includes: Modeling the relay protection device: dividing the relay protection device according to its function, and modeling it in combination with the protection function of the relay protection device, the faults reacted by the protection function, the faults generated after the protection function is actuated, and the switch action sequence triggered after the protection function is actuated; Modeling the reclosing device: Modeling the line / switch protection function that initiates the reclosing, the opening switch triggered by the line / switch protection function, and the closing switch triggered by the reclosing action; Modeling the standby automatic switching device: Modeling is performed based on the operation mode of the standby automatic switching device and its charging conditions, action conditions and switch action sequence.

3. A method for diagnosing faults of secondary equipment in a dispatching automation system according to claim 2, characterized in that: In step S2, according to the modeling result of step S1, a fault diagnosis model based on a timing constraint network is established, including: Acquiring the models established in step S1 for the relay protection device, the reclosing device and the standby automatic switching device, and dynamically correcting and modeling the timing constraint network in combination with the current wiring mode of the power grid of the dispatching automation system; The timing constraint network includes a quintuple: G = (V, E, T, C1, C2) Where V = {v1,v2,…,v N } represents the node set of the event, which is divided into cause node V C and alarm node V A ; E = { <v i ,v j >|v i ,v j ∈V} represents the set of directed edges in the directed acyclic graph; is the set of time points corresponding to each event in V, Represents event v i Time point of occurrence; C1 = Indicates time point Constraints; Indicates time point and The time distance constraint between them.

4. A method for diagnosing faults of secondary equipment in a dispatching automation system according to claim 3, characterized in that: In step S2, a fault diagnosis model based on a timing constraint network is established, and fault reasoning is performed through the fault diagnosis model to obtain a fault diagnosis result, which also includes: According to the fault information obtained from the modeling results, the state of the alarm node representing the relay protection, safety automatic device and switch action behavior in the timing constraint network is maintained; Based on the timing constraint network, reverse timing reasoning is performed on the alarm node at the end to obtain a fault diagnosis result.

5. The method for diagnosing faults of secondary equipment in a dispatching automation system according to claim 3, characterized in that: Analyzing the timing constraint relationship between the events represented by the fault diagnosis result in step S3 includes: The equation constraint relationship of the fault diagnosis result is obtained according to the timing constraint network subgraph: If there is a subgraph The alarm nodes that receive the alarm information are recorded as nodes vk a The accurate time stamp of the event occurrence is the alarm information receiving time stamp and the time stamp error is and There are equality constraints: For any two connected event nodes v i and v j , there is an equality constraint relationship: In the formula, and d(v i ,v j ) represent the event v i and v j The exact time distance and the time distance calculated based on the information reception time stamp, δ vi and δ vj Respectively represent the event v i and v j The time scale error.

6. A method for diagnosing faults of secondary equipment in a dispatching automation system according to claim 5, characterized in that: Analyzing the timing constraint relationship between the events represented by the fault diagnosis result in step S3 also includes: According to the timing constraint network subgraph, the inequality constraint relationship of the fault diagnosis result is obtained: If the protection r i Action, for p(r i ,d k ), in the fault diagnosis result, the switch does not act or its action time satisfies: If the fault diagnosis result r i If the protection does not operate, the reason for the protection not operating can be expressed as:

7. A method for diagnosing faults of secondary equipment in a dispatching automation system according to claim 6, characterized in that: The step S3 converts the analysis result into a linear inequality equation including: Converting the inequality constraint relationship of the fault diagnosis result into a linear expression; The transformed linear expressions and the linear inequalities determined by the logic modeling of the secondary equipment actions are combined to obtain a group of linear inequalities for uncertain quantities.

8. The method for diagnosing faults of secondary equipment in a dispatching automation system according to claim 1, characterized in that: The step S4 of acquiring device information through the interface of the fault device corresponding to the fault diagnosis result includes: Through the interface with the wave recording function, online monitoring and analysis function of the standby automatic start-up device, the information required for refined fault analysis and diagnosis is obtained in the form of wave recording briefings and standby automatic start-up device action briefings.

9. A method for diagnosing faults of secondary equipment in a dispatching automation system according to claim 1, characterized in that: Step S5 includes: Restore the process of fault occurrence and evolution based on the fault diagnosis results, describe the fault itself and the relay protection, installation automatic device, and switch action behaviors triggered by it, and evaluate the impact of the fault on the power grid; Establish the correlation mapping relationship between fault events, relay protection, installation automatic devices, switch action behaviors and fault information generated by the dispatching automation system, and organize the fault information into events to obtain fault events.

10. A fault diagnosis terminal for secondary equipment actions in a dispatching automation system, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, each step of the method for diagnosing a fault of a secondary device in a dispatching automation system according to any one of claims 1 to 9 is implemented.

Images