CN112964960A - Multi-source data fusion power grid fault diagnosis method based on scheduling fault fingerprint database - Google Patents
Multi-source data fusion power grid fault diagnosis method based on scheduling fault fingerprint database Download PDFInfo
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Abstract
The invention relates to a power grid fault diagnosis method based on multi-source data fusion of a scheduling fault fingerprint library, which comprises the following steps of: step 1: acquiring data of a plurality of systems from a scheduling end; step 2: and establishing a fault local characteristic fingerprint database by using the transformer substation interval remote signaling data, and establishing a fault overall characteristic fingerprint database by using the power grid element. And step 3: matching the local characteristic fingerprint database and the overall characteristic fingerprint database by using a matching search algorithm, searching for similar or matched values of the power grid fault remote signaling data received by the dispatching terminal and the data in the fingerprint database, and outputting corresponding fault identity information as a final output result of fault diagnosis. Compared with the prior art, the method has the advantages of comprehensive and rapid fault diagnosis and the like.
Description
Technical Field
The invention relates to a power grid fault diagnosis method, in particular to a power grid fault diagnosis method based on multi-source data fusion of a scheduling fault fingerprint database.
Background
The fusion method of the dispatching end fault recording system, the PMU system, the language image system and the meteorological system comprises the following steps: combining a radial basis function neural network and an information fusion technology, fusing electrical quantity, PMU (phasor measurement unit) and SCADA (supervisory control and data acquisition) system data, and realizing second-level diagnosis of cascading faults; a diagnosis method based on fuzzy integral information fusion and a power grid fault diagnosis method combining power flow of a power grid and remote signaling information; the method of combining the time sequence information and the multi-source information is utilized to solve the fault equipment and the fault time sequence, and the fault tolerance of fault diagnosis is improved; the application scene of multidimensional information including information sources such as SCADA, WAMS and FIS in power system fault diagnosis is fully excavated, and the power grid fault diagnosis method based on multi-source information time sequence matching is provided. The above method has certain limitations for the rapid identification of faults and the fusion of multiple systems and the interpretation of grid faults.
The fault diagnosis method using remote signaling and fault recording fusion comprises a D-S evidence theory fusion method, an artificial intelligence method and a reasoning model method: a multi-data source information fusion fault diagnosis method based on an improved D-S evidence theory; constructing a new wavelet neural network fault identification model by utilizing the lifting wavelet and the PNN network; an algorithm for fault diagnosis by using a quantum neural network is used for improving fault diagnosis fault tolerance; an intelligent power transmission network fault diagnosis method based on knowledge grid technology; a method for diagnosing the failure of electric network features use of multi-agent technique and cooperative expert system. The research on the inference model is mainly as follows: the subjective Bayes method is put forward to play the advantages of the Bayes network in the aspect of reasoning; establishing a power grid fault diagnosis model based on a colored Petri network; a time Petri network fault diagnosis model considering a topological structure and a power system fault diagnosis method based on forward and reverse reasoning give out fault equipment or a fault range. The method can only fuse the information of the electrical quantity and the switching value, and is difficult to display the fault information of the power grid in a panoramic way.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provide a power grid fault diagnosis method based on multi-source data fusion of a scheduling fault fingerprint database.
The purpose of the invention can be realized by the following technical scheme:
a multi-source data fusion power grid fault diagnosis method based on a dispatching fault fingerprint library comprises the following steps:
step 1: acquiring data of a plurality of systems from a scheduling end;
step 2: establishing a fault local characteristic fingerprint database by using the transformer substation interval remote signaling data, and establishing a fault overall characteristic fingerprint database by using the power grid element;
and step 3: matching the local characteristic fingerprint database and the overall characteristic fingerprint database by using a matching search algorithm, searching for similar or matched values of the power grid fault remote signaling data received by the dispatching terminal and the data in the fingerprint database, and outputting corresponding fault identity information as a final output result of fault diagnosis.
Further, the data of the systems in step 1 include SCADA, fault recording and PMU system data related to power grid operation and control; PMS, OMS system data related to production management; video monitoring, dispatch telephony voice system data related to operations and incident handling.
Further, the process of establishing the fault local feature fingerprint database in step 2 specifically includes: dividing and coding the remote signaling data field, then mapping to a multi-dimensional data space according to a mapping transformation relation, and converting the problem of fault diagnosis of remote signaling displacement data into a classification problem of sample data in the multi-dimensional space.
Further, the mapping transformation relationship is described by the formula:
in the formula, A1...AnFor remote signalling binary data matrices after n faults, c1...cnFor n fault-coded data after passing coding, f1...fnFor n fault codesAnd the code mapping function, the code mode of the remote signaling binary data matrix after the fault and the code mode of the fault code mapping function adopt a two-dimensional code mode and a one-dimensional code mode.
Further, the process of establishing the fault global characteristic fingerprint database in step 2 specifically includes: logic multiplication and logic addition are defined, and protection and circuit breaker expected remote signaling values are formed according to protection logics of element faults, main protection, backup protection and failure protection and serve as data in a fault fingerprint overall characteristic fingerprint library.
Further, the data in the fault fingerprint overall characteristic fingerprint database is described by the formula:
in the formula (d)kIn order to be a faulty component,
the desired telecommand value for the primary protection of the failed element,
for desired telemetry values for near backup protection of the failed element,
is the non-operational value of the primary protection of the failed element,
desired telecommand value, Z (r), for far back-up protection of a faulty elementks,dk) Far backup protection range d for fault elementkSet of adjacent elements, p (r)ks,dx) For installation from far backup protection of faulty component to component d along supply pathxIn the collection of all the circuit breakers,
for the non-operational value of the t-th breaker in the set of all breakers,
for non-operational values of the near backup protection of the failed component,
for circuit breaker cjThe desired remote signaling value of the fail-safe,
for circuit breaker cjIs not a value of R (c)j) For all the energy-actuated circuit breakers cjTrip protection set of riTo drive the circuit breaker cjThe ith trip protection in the set of trip protections of (1),
for circuit breaker cjDesired telecommand value of.
Further, the process of matching the local feature fingerprint database by using the matching search algorithm in step 3 includes: after the power grid fails, collecting remote signaling data in intervals, mapping the remote signaling data to a three-dimensional space in a block coding mode, finding out fingerprint data with the shortest spatial distance and the least binary remote signaling data mismatching digits in a local characteristic fingerprint database through a matching strategy, wherein the corresponding description formula is as follows:
in the formula, A (a, B, c) is three-dimensional data formed by encoding and mapping power grid fault interval remote signaling, and BkAnd (x, Y, z) is interval remote signaling coding mapping data in the kth local fingerprint library, Y' is fault interval remote signaling data, and Y (k) is binary data which is not coded in the local fingerprint library.
Further, the process of matching the global feature fingerprint database by using the matching search algorithm in step 3 includes: carrying out bitwise XOR operation on corresponding element remote signaling data in the overall characteristic fingerprint database by using remote signaling data triggered by a failed element after failure, and searching fingerprint data with the least number of different binary bits, wherein the corresponding description formula is as follows:
where r' (k) is remote signaling data of suspected faulty elements in the blackout area after the grid fault, and r*(k) And E is a matching result, and k and N are both natural numbers.
Further, the compiling of the fault identity in the step 3 includes preset fault fingerprint identity information and identity dynamic information, wherein the preset fault fingerprint identity information is fault information which can be determined in advance in a logic operation mode according to a matching mode between protection of a relay protection principle and trip logic after relay protection action after the power grid fault occurs, and the identity dynamic information is result information which is output after analysis and calculation according to data of each system collected by each fault after the power grid fault occurs.
Compared with the prior art, the invention has the following advantages:
(1) the method forms a scheduling big data system by fusing a plurality of system data of the scheduling end, can judge and correct the validity of each system data by using the advantages of the big data system, can identify bad data, diagnoses the faults and defects of equipment and secondary circuits in each system, and finds hidden dangers in the automatic system.
(2) The method can also deeply use the data of each system, and display the panoramic information of the fault to accelerate the processing and recovery of the fault. Compared with the traditional fault diagnosis method, the method has the advantages of being capable of achieving rapid and comprehensive diagnosis of the fault under the advantage of a large amount of data fused by multiple systems.
(3) The method searches out the similar or matched value of the power grid fault remote signaling data received by the dispatching end and the data in the fingerprint library through matching the local fingerprint library and the global fingerprint library, outputs corresponding fault identity information as the final output result of fault diagnosis, can fully utilize the advantages of big data under the increasingly deep construction of a large data regulation and control platform, and has good application prospect in the fault diagnosis of the power grid.
(4) The method comprises the steps of constructing a dispatching fault fingerprint system of the power grid according to interval remote signaling, power grid elements and protected action remote signaling, establishing fault identity information serving as a diagnosis result of a fault fingerprint database in a multi-system fusion mode, establishing a matching strategy of the fault fingerprint database, matching and searching the fault fingerprint database, determining the fault identity of the power grid fault and performing panoramic display on the fault.
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FIG. 1 is an architectural diagram of a fault fingerprint diagnosis provided by the present invention;
FIG. 2 is a grid fault wiring diagram provided by the present invention;
FIG. 3 is a diagram of a diagnostic process utilizing a dispatch failure fingerprint library provided by the present invention;
fig. 4 is a diagram illustrating a structure of an IEEE39 node system according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, not all, embodiments of the present invention. All other embodiments, which can be obtained by a person skilled in the art without any inventive step based on the embodiments of the present invention, shall fall within the scope of protection of the present invention.
With the deep construction of a large data system at a dispatching end, aiming at the problems of fusion of multi-system data, deep use of data, rapid diagnosis and processing of multiple complex faults of a power grid and the like, the invention provides a dispatching fault fingerprint identification system constructed to realize the fusion of the multi-system data and the rapid diagnosis of the complex faults. The method comprises the steps of constructing a scheduling data local characteristic fault fingerprint database by utilizing interval remote signaling data in a transformer substation, constructing a scheduling data overall characteristic fingerprint database by utilizing primary equipment of a power grid, related protection and automation devices and breaker remote signaling, and providing a matching search algorithm of the local characteristic fault fingerprint database and the overall characteristic fingerprint database of fault fingerprints. And the fault data of each system is fused in a fault identity mode, and the power grid fault identity is rapidly determined through the rapid matching of a fault fingerprint database. The effectiveness of the diagnosis method provided by the method is illustrated by taking an IEEE39 node system as an example.
As shown in fig. 1, the grid fault diagnosis method based on multi-source data fusion of the scheduling fault fingerprint database includes the following steps:
1) acquiring data of a plurality of systems from a scheduling end, such as SCADA (supervisory control and data acquisition), fault recording and PMU (phasor measurement unit) system data related to power grid operation and control; production management related systems such as PMS and OMS systems, operation and accident handling related systems such as video surveillance and dispatch telephone voice systems, and operation environment related systems such as lightning and weather systems.
2) And establishing a fault local characteristic fingerprint database by using the transformer substation interval remote signaling data, and establishing a fault overall characteristic fingerprint database by using the power grid element.
3) And by matching the local fingerprint library and the global fingerprint library, finding out the similarity or matching value of the power grid fault remote signaling data received by the dispatching terminal and the data in the fingerprint library, and outputting corresponding fault identity information as a final output result of fault diagnosis.
In the steps of the method, step 1), the establishment of the system architecture for the fault fingerprint diagnosis of the dispatching system needs the establishment of a local fingerprint feature library of each interval in the transformer substation and a total fingerprint feature library of the power grid element. And determining the operation mode of the transformer substation and the operation mode of the power grid, determining the fingerprint characteristic library, namely determining the evaluation space of the fault mode of the power grid, wherein each fault mode of the power grid is a fingerprint characteristic in the fingerprint characteristic library, and solving a reorganization characteristic value, namely a fault diagnosis result.
In the step 2) and the step 3), a fault local characteristic fingerprint database is established by using the transformer substation interval remote signaling data, a fault overall characteristic fingerprint database is established by using the power grid element, and the two fingerprint databases respectively use different establishing algorithms.
Establishing a coding mapping function from remote signaling data to a fault space; logic multiplication and logic addition are defined and respectively expressed, and expected remote signaling values of the protection and the breaker are formed according to protection logics such as element failure, main protection, backup protection and failure protection and the like and are used as data in a failure fingerprint general characteristic library.
The establishment of the local characteristic fingerprint database is mainly aimed at all equipment in a substation, and the local characteristic fingerprint database is divided into a main network local characteristic fingerprint database of 220kV or more and a distribution network local characteristic fingerprint database of 110kV or less according to different voltage grades; according to different fault types, the dispatching fault fingerprint database global feature fingerprint database may need to perform logic operation on equipment elements and remote signaling data of a plurality of substations to form data in the fingerprint database; the data in the global fingerprint database are binary numbers, the interrelation between elements among faults and the interrelation between protection actions and circuit breaker tripping under the condition of single and complex faults are reflected, and the global condition of a power grid is reflected.
The specific implementation mode is as follows:
firstly, the method comprises the following steps: system architecture for fault fingerprint diagnosis
1. Integral framework of fault fingerprint
The establishment of a system architecture for fault fingerprint diagnosis of a dispatching system requires the establishment of a local fingerprint feature library of each interval in a transformer substation and an overall fingerprint feature library of power grid elements. And determining the operation mode of the transformer substation and the operation mode of the power grid, determining the fingerprint characteristic library, namely determining the evaluation space of the fault mode of the power grid, wherein each fault mode of the power grid is a fingerprint characteristic in the fingerprint characteristic library, and solving a reorganization characteristic value, namely a fault diagnosis result.
With the construction of a large data regulation platform, a dispatching end can obtain data of a plurality of systems, SCADA (supervisory control and data acquisition), fault recording and PMU (phasor measurement unit) system data related to the operation and control of a power grid, PMS (system management system) and OMS (operation management system) systems related to production management, video monitoring and dispatching telephone voice systems related to operation and accident handling, thunder and weather systems related to an operation environment and the like. Fault data in each system can be incorporated into a fault fingerprint diagnosis framework by constructing fault identities to serve as output information displayed in a fault panorama mode.
In order to quickly search and match the fault fingerprint value with the highest similarity, a local feature matching algorithm and an overall feature recognition algorithm are respectively set, and after the power grid fails, the whole fingerprint database is searched and the fault identity is output.
2. Method for establishing remote signaling data fault fingerprint database
(1) Establishment of fault fingerprint local characteristics
Dividing and coding the remote signaling data field, then mapping to a multidimensional data space, and mapping and transforming to:
in the formula, A1...AnFor remote signalling binary data matrices after n faults, c1...cnFor n fault-coded data after passing coding, f1...fnAnd the coding modes of the remote signaling binary data matrix and the fault coding mapping function after the fault adopt a two-dimensional coding mode and a one-dimensional coding mode for the n fault coding mapping functions.
By the above equation, the remote signaling of binary number to n-dimensional coding space (c) is practically completed1,...,cn) So, the fault diagnosis problem using the remote signaling displacement data is converted into the sample data in the multidimensional spaceThe classification problem of (1). For mapping to an n-dimensional coding space, a remote signaling binary data matrix A must be determinediAnd a fault code mapping function fiNamely, the coding mode of the remote signaling binary number is determined. Determination of Ai、fiThere are two encoding methods: two-dimensional coding and one-dimensional coding.
(2) Establishment of fault fingerprint overall characteristics
After the elements in the power grid are in fault, relevant relay protection acts, and corresponding circuit breakers are triggered to act to remove the fault elements. Therefore, different relay protection action remote signaling and breaker tripping remote signaling can be triggered after different elements fail. The fault fingerprint general characteristic is mainly that a general characteristic data space of remote signaling data of all element faults, trigger protection and circuit breakers in a power grid is established, and a group of data closest to the fault elements in the data space is found out to serve as a diagnosis result according to matching of the fault elements in a stop area, the triggered remote signaling data and the data in the general characteristic data space. The method for establishing the fault fingerprint overall characteristic library comprises the following steps:
definition of
And
and respectively representing logical multiplication and logical addition, and forming expected remote signaling values of protection and a breaker as data in a fault fingerprint general characteristic library according to protection logics such as element fault, main protection, backup protection, failure protection and the like. As shown in the following formula:
in the formula (d)kIn order to be a faulty component,
the desired telecommand value for the primary protection of the failed element,
for desired telemetry values for near backup protection of the failed element,
is the non-operational value of the primary protection of the failed element,
desired telecommand value, Z (r), for far back-up protection of a faulty elementks,dk) Far backup protection range d for fault elementkSet of adjacent elements, p (r)ks,dx) For installation from far backup protection of faulty component to component d along supply pathxIn the collection of all the circuit breakers,
for the non-operational value of the t-th breaker in the set of all breakers,
for non-operational values of the near backup protection of the failed component,
for circuit breaker cjThe desired remote signaling value of the fail-safe,
for circuit breaker cjIs not a value of R (c)j) For all the energy-actuated circuit breakers cjTrip protection set of riTo drive the circuit breaker cjThe ith trip protection in the set of trip protections of (1),
for circuit breaker cjDesired telecommand value of.
(3) Establishment of power grid fault fingerprint database
And scheduling the fault fingerprint database, the local characteristic fingerprint database and the global characteristic fingerprint database. The establishment of the local characteristic fingerprint database mainly aims at all devices in the substation. The method is divided into a main network local characteristic fingerprint library of 220kV or more and a distribution network local characteristic fingerprint library of 110kV or less according to different voltage grades. The system comprises a bus, a transformer, a line, a capacitor, a spare power automatic switching device and other elements, wherein each equipment element forms a sub-library of a local characteristic fingerprint library, and each sub-library comprises codes of various types of fault remote signaling data. For example, the sub-base of the transmission line contains remote signaling data such as main protection, backup protection, remote tripping, reclosing, PT disconnection and the like, and 159 fields of codes are formed for a fault process, protection action details and fault types.
The dispatching fault fingerprint database global feature fingerprint database may need to perform logical operation on equipment elements and remote signaling data of a plurality of substations according to different fault types to form data in the fingerprint database. For example, the single-stage circuit breaker failure fault may involve binary data such as equipment in two substations and circuit breaker failure remote signaling, and the data in the local feature fingerprint library is formed through logic operation. Therefore, the data in the global fingerprint database are binary numbers, the relationship between elements among faults and the interrelation between protection actions and circuit breaker tripping under the condition of single and complex faults are reflected, and the global condition of the power grid is reflected.
3. Establishment of fault identity information
The fault identity is the output result of the diagnosis of the fault fingerprint. And by matching the local fingerprint library and the global fingerprint library, finding out the similarity or matching value of the power grid fault remote signaling data received by the dispatching terminal and the data in the fingerprint library, and outputting corresponding fault identity information as a final output result of fault diagnosis. The fault identity integrates the original data and the analysis result data related to the fault diagnosis of the system such as the SCADA, the PMU, the fault recording, the protection subsystem, the PMS and the like. And simultaneously, the fault identity further comprises: accident voice information of dispatching telephones, image information of transformer substation equipment sites, meteorological data information and the like.
The matching of the fault fingerprints mainly comprises the steps of searching the fault identity information of the fault, outputting and displaying. The compiling of the fault identity comprises the following steps:
(1) presetting failure fingerprint identity information
The preset fault fingerprint identity information refers to fault information which can be determined in advance in a logic operation mode according to a matching mode between protection of a relay protection principle and a tripping strategy after relay protection action after a power grid fault. For example, the types of the devices include faults of a transformer, a bus and a line, the types of the faults include single phase, interphase and three phase, the protection action process includes the relation of whether reclosure exists, main backup protection action and the like, and the types of cascading faults and the like.
(2) Dynamic information of identity
The preset fault fingerprint identity information refers to a result which cannot be determined in advance in a logic operation mode after the power grid has faults and is output after analysis and calculation according to data of each system collected during each fault. For example, the fault distance of a PMU measurement system, the failure probability of historical maintenance data and fault data of a circuit breaker in the PMS, the analysis and calculation of real-time data of load flow transfer, the calculation of the occurrence probability of grid cascading faults and the like are calculated. The data of the identity dynamic information can change according to different historical data and real-time fault data, and the data is filled in real time according to the calculated value of the data after the fault.
4. Matching strategy of fault fingerprint database
The matching strategy of the fault fingerprint database is to find the fault fingerprint of the current power grid fault in the fingerprint local characteristic database and the global characteristic database and determine the fault identity.
Remote signaling data of protection, reclosing and circuit breakers in a single interval are grouped according to action and tripping logic of relay protection, are coded and mapped to a multi-bit data space to form a local characteristic fingerprint database. Matching of the fingerprint local feature library is to find out the closest group of fingerprint data in the fingerprint library under the condition that the remote signaling of the power grid fault is possible to be wrong. Taking the power transmission line as an example, the remote signaling data of the equipment in the interval is divided into: the three groups of the fault process word, the protection action word and the fault type word are mapped into a three-dimensional space through coding, and the matching strategy is as follows:
in the formula, A (a, B, c) is three-dimensional data formed by encoding and mapping power grid fault interval remote signaling, and Bk(x, Y, z) is interval remote signaling coding mapping data in the kth local fingerprint library, Y' is fault interval remote signaling data, Y (k) is uncoded binary data in the local fingerprint library,
representing a logical exclusive or operation.
According to the formula, after the power grid fails, remote signaling data in intervals are collected, block codes are mapped to a three-dimensional space, and the group of fingerprint data with the closest spatial distance and the smallest number of unmatched binary remote signaling data bits is found out in a local fingerprint database through a matching strategy.
From the foregoing, it can be seen that the overall characteristic fingerprint database is a combination of multiple remote signaling data according to protection actions and trip strategy logic, assuming that a power grid element is in fault. The matching strategy of the overall characteristic fingerprints is to find out the closest group of combination modes in the fingerprint database as the overall characteristic fingerprints of the fault remote signaling according to the fault remote signaling. The matching formula is as follows:
where r' (k) is remote signaling data of suspected faulty elements in the blackout area after the grid fault, and r*(k) And E is a matching result, and k and N are both natural numbers.
The formula carries out bitwise XOR operation on the remote signaling data of the corresponding elements in the fingerprint database by using the remote signaling data triggered by the failed element after the failure, and searches the group of fingerprint data with the least number of different binary bits.
Therefore, the identity of the power grid fault can be determined by searching the matching algorithm of the local feature library and the global feature library, and the result is output.
Second, practical case
The method for diagnosing the power grid fault by using the dispatching fingerprint library is illustrated by a power grid wiring diagram shown in FIG. 2. In fig. 2, when the L1 power transmission line has fault line protection action, the B3 breaker fails to cause the M1 failure protection action, and the B2 and B1 trip-out breakers remove the fault.
The diagnosis method using the dispatching fault fingerprint is shown in fig. 3, all fault remote signaling data of the current fault and remote signaling data of a tripped substation after the fault are captured, and then power failure area searching is performed by using the remote signaling data and the remote signaling data after the fault. A trip breaker with voltage on one side and no voltage on one side is defined as a boundary breaker. In the power grid topological diagram, a region including the element and the closing breaker and surrounded by the boundary breaker is a power failure region.
In the power failure area searching process, the boundary breaker is used as a searching starting point to search, in a topological wiring diagram, the boundary breaker is searched in a certain direction, namely, the boundary breaker is stopped, then other directions are searched until the boundary breaker is searched in all directions, and finally, a boundary breaker and suspected fault element list is formed. And forming a local fault characteristic fingerprint database by all remote signaling data of the boundary circuit breaker at intervals, matching in the local characteristic database, matching fingerprints formed by suspected fault elements in the overall fault fingerprint database, finally determining the fault identity, and outputting fault identity information fused by multiple systems.
The matching mode of the fault fingerprint system is divided into a partial characteristic fingerprint matching mode and an overall fingerprint matching mode, the partial characteristic fingerprint matching mode mainly aims at the fingerprint matching of the boundary circuit breaker intervals, and the overall fingerprint matching mode mainly aims at the fingerprint matching of equipment among multiple intervals and the fingerprint matching of protection and circuit breakers.
Third, simulation verification result
To further verify the versatility and effectiveness of the methods herein, an example simulation analysis was performed using the IEEE39 node system shown in fig. 4. For convenience of analysis, lines, breakers and protections are all marked according to bus numbers, for example, a line connecting buses B18 and B17 is marked as L1817, a breaker on the side of B18 is marked as CB1817, the opposite side is CB1718, line main protections on both sides are respectively marked as L1817m and L1718m, and a main protection of a bus B18 is marked as RB18 m. The failure fingerprint diagnosis results are shown in table 1 in consideration of the situations of various failure types such as the error of alarm information, the failure and misoperation of protection and circuit breakers. Each telecommunications data is represented by 2-dimensional data, such as (R0203s,6) for L0203 line protection far back-up protection action, SOE time scale 6 ms.
For two complex faults in an IEEE39 node power grid system, simulation analysis is respectively carried out on the two faults by using the fault fingerprint identification system fusing multi-system analysis data, and the analysis data are shown in table 1. The failure 1 is: the B03 bus has two-phase grounding fault, and the circuit breaker fails, so that the far backup actions of L0318, L0304 and L0302 are finally removed. The failure 2 is: b03 and B14 buses are failed, CB0318 refuses to act, and the failure is removed by L0318 far backup action.
The matching mode of the fault fingerprint system is divided into a partial characteristic fingerprint matching mode and an overall fingerprint matching mode, the partial characteristic fingerprint matching mode mainly aims at the fingerprint matching of the boundary circuit breaker intervals, and the overall fingerprint matching mode mainly aims at the fingerprint matching of equipment among multiple intervals and the fingerprint matching of protection and circuit breakers. In the simulation process, an outage area search algorithm is used for finding out an edge breaker and a suspected fault element, a local characteristic fingerprint and an overall characteristic fingerprint are formed through encoding, then a matching algorithm is used for matching a fault fingerprint database, all matching values E of a fault 1 are 0, complete matching is achieved, and in a fault 2, except for the situation that the overall characteristic fingerprint is matched with 1, other parameters are 0. The global feature matching algorithm finds a set of unequal but closest fingerprint encoding values. And finally, outputting the fused fault identity values of all the systems, wherein detailed analysis results are shown in a table 1.
Therefore, the corresponding fault identity can be found through the dispatching fault fingerprint identification system, the analysis contents of other systems are fused, and the panoramic fault analysis data is displayed on the dispatching side.
Table 1: scheduling fault fingerprint diagnosis results
While the invention has been described with reference to specific embodiments, the invention is not limited thereto, and various equivalent modifications and substitutions can be easily made by those skilled in the art within the technical scope of the invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (9)
1. A multi-source data fusion power grid fault diagnosis method based on a dispatching fault fingerprint library is characterized by comprising the following steps:
step 1: acquiring data of a plurality of systems from a scheduling end;
step 2: establishing a fault local characteristic fingerprint database by using the transformer substation interval remote signaling data, and establishing a fault overall characteristic fingerprint database by using the power grid element;
and step 3: matching the local characteristic fingerprint database and the overall characteristic fingerprint database by using a matching search algorithm, searching for similar or matched values of the power grid fault remote signaling data received by the dispatching terminal and the data in the fingerprint database, and outputting corresponding fault identity information as a final output result of fault diagnosis.
2. The grid fault diagnosis method based on the multi-source data fusion of the dispatching fault fingerprint library according to claim 1, wherein the data of the systems in the step 1 comprise SCADA, fault recording and PMU system data related to grid operation and control; PMS, OMS system data related to production management; video monitoring, dispatch telephony voice system data related to operations and incident handling.
3. The grid fault diagnosis method based on the multi-source data fusion of the scheduling fault fingerprint library according to claim 1, wherein the process of establishing the fault local feature fingerprint library in the step 2 specifically comprises: dividing and coding the remote signaling data field, then mapping to a multi-dimensional data space according to a mapping transformation relation, and converting the problem of fault diagnosis of remote signaling displacement data into a classification problem of sample data in the multi-dimensional space.
4. The grid fault diagnosis method based on the multi-source data fusion of the dispatching fault fingerprint library according to claim 3, wherein the mapping transformation relation is described by a formula:
in the formula, A1...AnFor remote signalling binary data matrices after n faults, c1...cnFor n fault-coded data after passing coding, f1...fnAnd the coding modes of the remote signaling binary data matrix and the fault coding mapping function after the fault adopt a two-dimensional coding mode and a one-dimensional coding mode for the n fault coding mapping functions.
5. The grid fault diagnosis method based on the multi-source data fusion of the scheduling fault fingerprint library according to claim 1, wherein the process of establishing the fault overall characteristic fingerprint library in the step 2 specifically comprises: logic multiplication and logic addition are defined, and protection and circuit breaker expected remote signaling values are formed according to protection logics of element faults, main protection, backup protection and failure protection and serve as data in a fault fingerprint overall characteristic fingerprint library.
6. The grid fault diagnosis method based on multi-source data fusion of the dispatching fault fingerprint library according to claim 5, wherein the data in the fault fingerprint general characteristic fingerprint library is described by a formula:
in the formula (d)kIn order to be a faulty component,
the desired telecommand value for the primary protection of the failed element,
for desired telemetry values for near backup protection of the failed element,
is the non-operational value of the primary protection of the failed element,
desired telecommand value, Z (r), for far back-up protection of a faulty elementks,dk) Far backup protection range d for fault elementkSet of adjacent elements, p (r)ks,dx) For installation from far backup protection of faulty component to component d along supply pathxIn the collection of all the circuit breakers,
for the non-operational value of the t-th breaker in the set of all breakers,
for non-operational values of the near backup protection of the failed component,
for circuit breaker cjThe desired remote signaling value of the fail-safe,
for circuit breaker cjIs not a value of R (c)j) For all the energy-actuated circuit breakers cjTrip protection set of riTo drive the circuit breaker cjThe ith trip protection in the set of trip protections of (1),
for circuit breaker cjDesired telecommand value of.
7. The method for grid fault diagnosis based on multi-source data fusion of the dispatching fault fingerprint library according to claim 1, wherein the matching process of the local feature fingerprint library by using the matching search algorithm in the step 3 comprises: after the power grid fails, collecting remote signaling data in intervals, mapping the remote signaling data to a three-dimensional space in a block coding mode, finding out fingerprint data with the shortest spatial distance and the least binary remote signaling data mismatching digits in a local characteristic fingerprint database through a matching strategy, wherein the corresponding description formula is as follows:
in the formula, A (a, B, c) is three-dimensional data formed by encoding and mapping power grid fault interval remote signaling, and BkAnd (x, Y, z) is interval remote signaling coding mapping data in the kth local fingerprint library, Y' is fault interval remote signaling data, and Y (k) is binary data which is not coded in the local fingerprint library.
8. The method for grid fault diagnosis based on multi-source data fusion of the dispatching fault fingerprint library according to claim 1, wherein the matching process of the overall characteristic fingerprint library by using the matching search algorithm in the step 3 comprises: carrying out bitwise XOR operation on corresponding element remote signaling data in the overall characteristic fingerprint database by using remote signaling data triggered by a failed element after failure, and searching fingerprint data with the least number of different binary bits, wherein the corresponding description formula is as follows:
where r' (k) is remote signaling data of suspected faulty elements in the blackout area after the grid fault, and r*(k) And E is a matching result, and k and N are both natural numbers.
9. The grid fault diagnosis method based on the multisource data fusion of the dispatching fault fingerprint library according to claim 1, wherein the compiling of the fault identity in the step 3 comprises preset fault fingerprint identity information and identity dynamic information, wherein after the preset fault fingerprint identity information is a grid fault, fault information which can be determined in advance in a logic operation mode according to a matching mode between protection of a relay protection principle and trip logic after relay protection action is obtained, and after the identity dynamic information is the grid fault, result information which is output after analysis and calculation is obtained according to data of each system collected by each fault.
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