CN113325267A - Power distribution network fault diagnosis system and method and computer program product - Google Patents
Power distribution network fault diagnosis system and method and computer program product Download PDFInfo
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Abstract
The invention belongs to the technical field of power distribution network fault diagnosis, and discloses a power distribution network fault diagnosis system and method based on topology knowledge, and a computer program product, wherein the power distribution network fault diagnosis system based on the topology knowledge comprises the following steps: the system comprises a data acquisition module, a data preprocessing module, a fault feature extraction module, a data fusion module, a central control module, a model construction module, a fault diagnosis module, a diagnosis evaluation module, a data storage module and an update display module. According to the invention, the fault characteristics of the power distribution network based on the time sequence can be obtained through the fault characteristic extraction module; the central control module is used for PID control, integral regulation is put into when an error signal is large, the response speed of the system is accelerated, the control precision is high, and the control performance is good; the fault diagnosis module is used for diagnosing the faults of the power distribution network by utilizing the constructed fault diagnosis model of the power distribution network, so that the faults of the power distribution network can be simply, conveniently and accurately positioned, and the fault diagnosis accuracy is high, and the generalization capability and robustness are good.
Description
Technical Field
The invention belongs to the technical field of power distribution network fault diagnosis, and particularly relates to a power distribution network fault diagnosis system and method based on topology knowledge.
Background
At present, with the permeability of the distributed power supply in the power distribution network becoming higher and higher, the operational reliability of the power distribution network becomes more and more important. If the active power distribution network fails to diagnose the line fault in time, the normal life of residents is affected, and the failure and paralysis of the whole system and the huge loss of personnel and production can be caused.
The normal operation of the power distribution network has important significance for ensuring the power consumption quality of power consumers. With the development of energy and power systems, the grid connection of renewable energy sources, the access of electric equipment and the network topology structure of a power distribution network are more and more complex, and the difficulty is brought to fault diagnosis. When the power distribution network has faults, how to realize fault location and fault type identification in time and ensure that the faults are eliminated in time, power supply and utilization are recovered rapidly, and the power distribution network operates normally, so that the method has important practical significance for accurately diagnosing the faults of the active power distribution network.
However, the conventional power distribution network fault diagnosis system has various types, lacks of unified standards and is sensitive to input data, so that the fault diagnosis lacks of simplicity and accuracy, and the fault diagnosis effect is poor. Therefore, a new power distribution network fault diagnosis system is needed.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides a power distribution network fault diagnosis system and method based on topology knowledge.
The invention is realized in such a way, a power distribution network fault diagnosis system based on topology knowledge comprises:
the system comprises a data acquisition module, a data preprocessing module, a fault feature extraction module, a data fusion module, a central control module, a model construction module, a fault diagnosis module, a diagnosis evaluation module, a data storage module and an update display module.
The data acquisition module is connected with the central control module and used for acquiring data information of key nodes of the power distribution network through data acquisition equipment; wherein the data information comprises electrical operating parameters and identification information;
the data preprocessing module is connected with the central control module and used for preprocessing the acquired data information of the key nodes of the power distribution network through a data preprocessing program;
the fault feature extraction module is connected with the central control module and used for carrying out feature extraction on the preprocessed data information of the key nodes of the power distribution network through a feature extraction program to obtain power distribution network fault features based on a time sequence;
the data fusion module is connected with the central control module and used for carrying out fusion processing on the acquired power distribution network fault characteristics based on the time sequence through a data fusion program to obtain a power distribution network fault characteristic set;
the central control module is connected with the data acquisition module, the data preprocessing module, the fault feature extraction module, the data fusion module, the model construction module, the fault diagnosis module, the diagnosis evaluation module, the data storage module and the update display module and is used for coordinating and controlling the normal operation of each module of the power distribution network fault diagnosis system based on the topology knowledge through the central processing unit;
the model building module is connected with the central control module and used for building a power distribution network fault diagnosis model according to the power distribution network fault feature set through a model building program;
the fault diagnosis module is connected with the central control module and used for diagnosing the faults of the power distribution network by utilizing the power distribution network fault diagnosis model through a fault diagnosis program and generating a fault diagnosis result;
the diagnosis evaluation module is connected with the central control module and used for evaluating the power distribution network fault diagnosis result through a diagnosis evaluation program and generating a final power distribution network fault diagnosis report;
the data storage module is connected with the central control module and used for storing the acquired data information of the key nodes of the power distribution network, data preprocessing results, power distribution network fault characteristics based on time sequences, a power distribution network fault characteristic set, a power distribution network fault diagnosis model, fault diagnosis results and final power distribution network fault diagnosis reports through the memory;
and the updating display module is connected with the central control module and is used for updating and displaying the acquired data information of the key nodes of the power distribution network, the data preprocessing result, the power distribution network fault characteristics based on the time sequence, the power distribution network fault characteristic set, the power distribution network fault diagnosis model, the fault diagnosis result and the final real-time data of the power distribution network fault diagnosis report through the display.
The invention also provides a power distribution network fault diagnosis method based on topology knowledge, which comprises the following steps:
s101, acquiring data information of key nodes of the power distribution network by using data acquisition equipment through a data acquisition module; wherein the data information comprises electrical operating parameters and identification information;
s102, preprocessing the acquired data information of the key nodes of the power distribution network by using a data preprocessing program through a data preprocessing module;
s103, performing feature extraction on the preprocessed data information of the key nodes of the power distribution network by using a feature extraction program through a fault feature extraction module to obtain power distribution network fault features based on a time sequence;
s104, fusing the acquired power distribution network fault characteristics based on the time sequence by using a data fusion program through a data fusion module to obtain a power distribution network fault characteristic set;
s105, coordinating and controlling normal operation of each module of the power distribution network fault diagnosis system based on topology knowledge by using a central processing unit through a central control module;
s106, constructing a power distribution network fault diagnosis model according to the power distribution network fault feature set by using a model construction module and a model construction program;
s107, diagnosing the power distribution network fault by using a fault diagnosis program and a power distribution network fault diagnosis model through a fault diagnosis module, and generating a fault diagnosis result;
s108, evaluating the power distribution network fault diagnosis result by using a diagnosis evaluation module and a diagnosis evaluation program to generate a final power distribution network fault diagnosis report;
s109, the data storage module stores the acquired data information of the key nodes of the power distribution network, data preprocessing results, power distribution network fault characteristics based on time sequences, a power distribution network fault characteristic set, a power distribution network fault diagnosis model, fault diagnosis results and final power distribution network fault diagnosis reports by using the memory;
and S110, updating and displaying the acquired data information of the key nodes of the power distribution network, the data preprocessing result, the power distribution network fault characteristics based on the time sequence, the power distribution network fault characteristic set, the power distribution network fault diagnosis model, the fault diagnosis result and the real-time data of the final power distribution network fault diagnosis report by using the display through the updating and displaying module.
Further, in the data acquisition module, the data information includes electrical operation parameters and identification information; the electrical operating parameters include three phase currents, zero sequence currents, negative sequence currents and zero sequence active and reactive power.
Further, in the data preprocessing module, the preprocessing of the acquired data information of the key node of the power distribution network by the data preprocessing program includes: selecting fault characteristic quantity, constructing a network incidence matrix and carrying out regional differentiation processing.
Further, in the fault feature extraction module, the feature extraction of the preprocessed data information of the key nodes of the power distribution network is performed through a feature extraction program, so as to obtain the power distribution network fault features based on the time sequence, and the method includes:
(1) extracting zero sequence current signals of each line in a power distribution network fault area;
(2) obtaining an IMF component of the zero sequence current of the line in the fault area of the power distribution network through variational modal decomposition;
(3) and screening IMF components with characteristic information reaching a specific quantity, and performing Hilbert-Huang transform processing on the screened IMF components to obtain the power distribution network fault characteristics based on the time sequence.
Further, in the central control module, the normal operation of each module of the power distribution network fault diagnosis system based on topology knowledge is coordinately controlled by the central processing unit, and the method includes:
(1) the method comprises the steps of obtaining an error signal by making a difference between an input signal and an output signal of a controlled object;
(2) judging whether the error signal is larger than a preset error threshold value or not;
(3) and outputting the total control quantity to the controlled object so as to adjust the output signal of the controlled object.
Further, in the model building module, the power distribution network fault diagnosis model comprises an input layer, a hidden layer and an output layer, wherein the hidden layer comprises a convolution layer, a pooling layer and a full-connection layer;
where the convolutional layer is defined by a set of small filters through which the input data is convolved in the forward channel, the convolutional layer output is as follows:
wherein h isj(x) Is the spatial position x ═ x1，x2) The jth inactive output feature map of (g)ijIs hjAnd the ith input channel fiA core in between; c represents the total input channel number, b represents the deviation;
the operator is a two-dimensional convolution defined as follows:
where m × n represents the kernel size.
Further, in the fault diagnosis module, the diagnosing of the power distribution network fault by the fault diagnosis program using the power distribution network fault diagnosis model includes:
(1) acquiring a power distribution network fault characteristic set based on a time sequence;
(2) the power distribution network fault feature set based on the time sequence is used as an input signal and is input to the power distribution network fault diagnosis model;
(3) and diagnosing the power distribution network fault by using the power distribution network fault diagnosis model.
It is a further object of the present invention to provide a computer program product stored on a computer readable medium, comprising a computer readable program for providing a user input interface for applying said topology knowledge based power distribution network fault diagnosis system or for performing a topology knowledge based power distribution network fault diagnosis method, when executed on an electronic device.
Another object of the present invention is to provide a computer-readable storage medium storing instructions that, when executed on a computer, cause the computer to apply the topology knowledge-based power distribution network fault diagnosis system or perform the topology knowledge-based power distribution network fault diagnosis method.
By combining all the technical schemes, the invention has the advantages and positive effects that: according to the power distribution network fault diagnosis system based on topology knowledge, the power distribution network fault characteristics based on the time sequence can be obtained through the fault characteristic extraction module; the central control module is used for PID control, integral regulation is put into when an error signal is large, the response speed of the system is effectively accelerated, the control precision is high, and the control performance is good; the fault diagnosis module is used for diagnosing the faults of the power distribution network by utilizing the constructed fault diagnosis model of the power distribution network, so that the faults of the power distribution network can be simply, conveniently and accurately positioned, and the fault diagnosis accuracy is high, and the generalization capability and robustness are good.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments of the present invention will be briefly described below, and it is obvious that the drawings described below are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a structural block diagram of a power distribution network fault diagnosis system based on topology knowledge according to an embodiment of the present invention;
in the figure: 1. a data acquisition module; 2. a data preprocessing module; 3. a fault feature extraction module; 4. a data fusion module; 5. a central control module; 6. a model building module; 7. a fault diagnosis module; 8. a diagnostic evaluation module; 9. a data storage module; 10. and updating the display module.
Fig. 2 is a flowchart of a method for diagnosing a fault of a power distribution network based on topology knowledge according to an embodiment of the present invention.
Fig. 3 is a flowchart of a method for obtaining power distribution network fault characteristics based on a time sequence by performing characteristic extraction on data information of a preprocessed power distribution network key node through a fault characteristic extraction module by using a characteristic extraction program according to an embodiment of the present invention.
Fig. 4 is a flowchart of a method for coordinating and controlling normal operation of each module of the topology-knowledge-based power distribution network fault diagnosis system through a central control module by using a central processor according to an embodiment of the present invention.
Fig. 5 is a flowchart of a method for diagnosing a power distribution network fault by using a fault diagnosis program and a power distribution network fault diagnosis model through a fault diagnosis module according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail with reference to the following embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
In order to solve the problems in the prior art, the invention provides a power distribution network fault diagnosis system and method based on topology knowledge, and the invention is described in detail below with reference to the accompanying drawings.
As shown in fig. 1, a power distribution network fault diagnosis system based on topology knowledge provided in an embodiment of the present invention includes: the system comprises a data acquisition module 1, a data preprocessing module 2, a fault feature extraction module 3, a data fusion module 4, a central control module 5, a model construction module 6, a fault diagnosis module 7, a diagnosis evaluation module 8, a data storage module 9 and an update display module 10.
The data acquisition module 1 is in communication connection with the central control module 5 and is used for acquiring data information of key nodes of the power distribution network through data acquisition equipment; wherein the data information comprises electrical operating parameters and identification information;
the data preprocessing module 2 is in communication connection with the central control module 5, is connected with the data acquisition module 1, and is used for preprocessing the data information of the key nodes of the power distribution network acquired by the data acquisition module 1 through a data preprocessing program;
the fault feature extraction module 3 is in communication connection with the central control module 5, is connected with the data preprocessing module 2, and is used for performing feature extraction on the preprocessed data information of the key nodes of the power distribution network through a feature extraction program to obtain power distribution network fault features based on a time sequence;
the data fusion module 4 is connected with the central control module 5, connected with the fault feature extraction module 3 and used for carrying out fusion processing on the acquired power distribution network fault features based on the time sequence through a data fusion program to obtain a power distribution network fault feature set;
the central control module 5 is in communication connection with the data acquisition module 1, the data preprocessing module 2, the fault feature extraction module 3, the data fusion module 4, the model construction module 6, the fault diagnosis module 7, the diagnosis evaluation module 8, the data storage module 9 and the update display module 10, and is used for coordinating and controlling the normal operation of each module of the power distribution network fault diagnosis system based on topology knowledge through a central processing unit;
the model building module 6 is connected with the central control module 5 and used for building a power distribution network fault diagnosis model according to the power distribution network fault feature set through a model building program;
the fault diagnosis module 7 is in communication connection with the central control module 5, is connected with the model construction module 6, and is used for diagnosing the power distribution network faults by utilizing the power distribution network fault diagnosis model through a fault diagnosis program and generating a fault diagnosis result;
the diagnosis and evaluation module 8 is in communication connection with the central control module 5, is connected with the fault diagnosis module 7 and is used for evaluating the power distribution network fault diagnosis result through a diagnosis and evaluation program and generating a final power distribution network fault diagnosis report;
the data storage module 9 is in communication connection with the central control module 5 and is used for storing the acquired data information of the key nodes of the power distribution network, data preprocessing results, power distribution network fault characteristics based on time sequences, a power distribution network fault characteristic set, a power distribution network fault diagnosis model, fault diagnosis results and final power distribution network fault diagnosis reports through a memory;
and the updating display module 10 is in communication connection with the central control module 5, is connected with the data storage module 9, and is used for updating and displaying the acquired data information of the key nodes of the power distribution network, the data preprocessing result, the power distribution network fault characteristics based on the time sequence, the power distribution network fault characteristic set, the power distribution network fault diagnosis model, the fault diagnosis result and the real-time data of the final power distribution network fault diagnosis report through a display.
As shown in fig. 2, the method for diagnosing a fault of a power distribution network based on topology knowledge according to an embodiment of the present invention includes the following steps:
s101, acquiring data information of key nodes of the power distribution network by using data acquisition equipment through a data acquisition module; wherein the data information comprises electrical operating parameters and identification information;
s102, preprocessing the acquired data information of the key nodes of the power distribution network by using a data preprocessing program through a data preprocessing module;
s103, performing feature extraction on the preprocessed data information of the key nodes of the power distribution network by using a feature extraction program through a fault feature extraction module to obtain power distribution network fault features based on a time sequence;
s104, fusing the acquired power distribution network fault characteristics based on the time sequence by using a data fusion program through a data fusion module to obtain a power distribution network fault characteristic set;
s105, coordinating and controlling normal operation of each module of the power distribution network fault diagnosis system based on topology knowledge by using a central processing unit through a central control module;
s106, constructing a power distribution network fault diagnosis model according to the power distribution network fault feature set by using a model construction module and a model construction program;
s107, diagnosing the power distribution network fault by using a fault diagnosis program and a power distribution network fault diagnosis model through a fault diagnosis module, and generating a fault diagnosis result;
s108, evaluating the power distribution network fault diagnosis result by using a diagnosis evaluation module and a diagnosis evaluation program to generate a final power distribution network fault diagnosis report;
s109, the data storage module stores the acquired data information of the key nodes of the power distribution network, data preprocessing results, power distribution network fault characteristics based on time sequences, a power distribution network fault characteristic set, a power distribution network fault diagnosis model, fault diagnosis results and final power distribution network fault diagnosis reports by using the memory;
and S110, updating and displaying the acquired data information of the key nodes of the power distribution network, the data preprocessing result, the power distribution network fault characteristics based on the time sequence, the power distribution network fault characteristic set, the power distribution network fault diagnosis model, the fault diagnosis result and the real-time data of the final power distribution network fault diagnosis report by using the display through the updating and displaying module.
In step S101 provided in the embodiment of the present invention, the electric operating parameters include three-phase current, zero-sequence current, negative-sequence current, and zero-sequence active and reactive power.
In step S102 provided in the embodiment of the present invention, the preprocessing, performed by the data preprocessing program, on the acquired data information of the key node of the power distribution network includes: selecting fault characteristic quantity, constructing a network incidence matrix and carrying out regional differentiation processing.
As shown in fig. 3, in step S103 provided in the embodiment of the present invention, the performing, by a fault feature extraction module, feature extraction on the data information of the preprocessed power distribution network key node by using a feature extraction program to obtain a power distribution network fault feature based on a time sequence includes:
s201, extracting zero sequence current signals of each line in a power distribution network fault area;
s202, obtaining an IMF component of the zero sequence current of the line in the fault area of the power distribution network through variational modal decomposition;
s203, screening IMF components with characteristic information reaching a specific amount, and performing Hilbert-Huang transform processing on the screened IMF components to obtain power distribution network fault characteristics based on a time sequence.
In step S202 provided in the embodiment of the present invention, obtaining an IMF component of the zero-sequence current of the line in the fault area of the power distribution network through variational modal decomposition includes:
wherein u iskIs the k-th modal component, wkIs the center frequency of the kth mode, f is the input signal, δ (t) is the dirac function; introducing a penalty factor alpha and a Lagrange multiplier lambda to obtain:
wherein L ({ u (k) }, { w (k) }, λ) is an extended Lagrange expression obtained by converting the constraint variation problem into the non-constraint variation problem.
Through multiple iterations, the modal component and the center frequency in the iteration process are respectively represented as:
wherein,
and
are respectively as
f(t)，uk(t) and λ (t) are the results obtained by fourier transform.
In the case of the modal component,
is the center frequency. As shown in fig. 4, in step S105 provided in the embodiment of the present invention, the coordinating and controlling, by the central control module and the central processing unit, normal operation of each module of the power distribution network fault diagnosis system based on topology knowledge includes:
s301, obtaining an error signal by making a difference between an input signal and an output signal of a controlled object;
s302, judging whether the error signal is larger than a preset error threshold value;
and S303, outputting the total control quantity to the controlled object so as to adjust the output signal of the controlled object.
In step S302 provided in the embodiment of the present invention, the determining whether the error signal is greater than a preset error threshold includes:
if so, calculating a first PID control quantity by adopting a first PID control algorithm with integral regulation so as to serve as a total control quantity;
if not, calculating a second PID control quantity by adopting a second PID control algorithm for canceling integral regulation, calculating a compensation control quantity by adopting a preset compensation algorithm, and taking the sum of the second PID control quantity and the compensation control quantity as the total control quantity.
In step S302 provided in the embodiment of the present invention, the preset error threshold is:
ef＝k1r(t)；
wherein e isfSetting the preset error threshold value; k is a radical of1Is a preset error threshold coefficient k1∈[0,0.2](ii) a r (t) is the input signal.
In step S106 provided in the embodiment of the present invention, the power distribution network fault diagnosis model includes an input layer, a hidden layer, and an output layer, where the hidden layer includes a convolution layer, a pooling layer, and a full connection layer.
Where the convolutional layer is defined by a set of small filters through which the input data is convolved in the forward channel, the convolutional layer output is as follows:
wherein h isj(x) Is the spatial position x ═ x1，x2) The jth inactive output feature map of (g)ijIs hjAnd the ith input channel fiA core in between; c represents the total input channel number, b represents the deviation;
the operator is a two-dimensional convolution defined as follows:
where m × n represents the kernel size.
As shown in fig. 5, in step S107 provided in the embodiment of the present invention, the diagnosing, by the fault diagnosing module, the power distribution network fault by using the fault diagnosing program and using the power distribution network fault diagnosing model includes:
s401, acquiring a power distribution network fault characteristic set based on a time sequence;
s402, inputting the power distribution network fault feature set based on the time sequence into the power distribution network fault diagnosis model as an input signal;
and S403, diagnosing the power distribution network fault by using the power distribution network fault diagnosis model.
In the description of the present invention, "a plurality" means two or more unless otherwise specified; the terms "upper", "lower", "left", "right", "inner", "outer", "front", "rear", "head", "tail", and the like, indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, are only for convenience in describing and simplifying the description, and do not indicate or imply that the device or element referred to must have a particular orientation, be constructed in a particular orientation, and be operated, and thus, should not be construed as limiting the invention. Furthermore, the terms "first," "second," "third," and the like are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
In the above embodiments, the implementation may be wholly or partially realized by software, hardware, firmware, or any combination thereof. When used in whole or in part, can be implemented in a computer program product that includes one or more computer instructions. When loaded or executed on a computer, cause the flow or functions according to embodiments of the invention to occur, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored in a computer readable storage medium or transmitted from one computer readable storage medium to another, for example, the computer instructions may be transmitted from one website site, computer, server, or data center to another website site, computer, server, or data center via wire (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL), or wireless (e.g., infrared, wireless, microwave, etc.)). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device, such as a server, a data center, etc., that includes one or more of the available media. The usable medium may be a magnetic medium (e.g., floppy Disk, hard Disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., Solid State Disk (SSD)), among others.
The above description is only for the purpose of illustrating the present invention and the appended claims are not to be construed as limiting the scope of the invention, which is intended to cover all modifications, equivalents and improvements that are within the spirit and scope of the invention as defined by the appended claims.
Claims (10)
1. A power distribution network fault diagnosis system based on topology knowledge is characterized by comprising:
the system comprises a data acquisition module, a data preprocessing module, a fault feature extraction module, a data fusion module, a central control module, a model construction module, a fault diagnosis module, a diagnosis evaluation module, a data storage module and an update display module;
the data acquisition module acquires data information of key nodes of the power distribution network through data acquisition equipment;
the data preprocessing module is connected with the data acquisition module and used for preprocessing the data information of the key nodes of the power distribution network acquired by the data acquisition module through a data preprocessing program;
the fault feature extraction module is connected with the data preprocessing module and used for carrying out feature extraction on the preprocessed data information of the key nodes of the power distribution network through a feature extraction program to obtain power distribution network fault features based on a time sequence;
the data fusion module is connected with the fault feature extraction module and used for carrying out fusion processing on the acquired power distribution network fault features based on the time sequence through a data fusion program to obtain a power distribution network fault feature set;
the central control module is in communication connection with the data acquisition module, the data preprocessing module, the fault feature extraction module, the data fusion module, the model construction module, the fault diagnosis module, the diagnosis evaluation module, the data storage module and the update display module and is used for coordinating and controlling the normal operation of each module of the power distribution network fault diagnosis system based on the topology knowledge through the central processing unit;
the model building module is used for building a power distribution network fault diagnosis model according to the power distribution network fault feature set through a model building program;
the fault diagnosis module is connected with the model construction module and used for diagnosing the power distribution network faults by utilizing the power distribution network fault diagnosis model through a fault diagnosis program and generating a fault diagnosis result;
the diagnosis and evaluation module is connected with the fault diagnosis module and used for evaluating the power distribution network fault diagnosis result through a diagnosis and evaluation program and generating a final power distribution network fault diagnosis report;
the data storage module is used for storing the acquired data information of the key nodes of the power distribution network, data preprocessing results, power distribution network fault characteristics based on time sequences, a power distribution network fault characteristic set, a power distribution network fault diagnosis model, fault diagnosis results and final power distribution network fault diagnosis reports through the memory;
and the updating display module is used for updating and displaying the acquired data information of the key nodes of the power distribution network, the data preprocessing result, the power distribution network fault characteristics based on the time sequence, the power distribution network fault characteristic set, the power distribution network fault diagnosis model, the fault diagnosis result and the final real-time data of the power distribution network fault diagnosis report through the display.
2. The topology knowledge based power distribution network fault diagnosis system of claim 1, wherein in the data acquisition module, the data information comprises electrical operating parameters and identification information; the electrical operating parameters include three phase currents, zero sequence currents, negative sequence currents and zero sequence active and reactive power.
3. The topology knowledge-based power distribution network fault diagnosis system according to claim 2, wherein in the data preprocessing module, the preprocessing of the acquired data information of the key nodes of the power distribution network by the data preprocessing program includes: selecting fault characteristic quantity, constructing a network incidence matrix and carrying out regional differentiation processing.
4. The system according to claim 3, wherein in the fault feature extraction module, the feature extraction of the preprocessed data information of the key nodes of the power distribution network by the feature extraction program to obtain the fault features of the power distribution network based on the time series includes:
(1) extracting zero sequence current signals of each line in a power distribution network fault area;
(2) obtaining an IMF component of the zero sequence current of the line in the fault area of the power distribution network through variational modal decomposition;
(3) and screening IMF components with characteristic information reaching a specific quantity, and performing Hilbert-Huang transform processing on the screened IMF components to obtain the power distribution network fault characteristics based on the time sequence.
5. The topology knowledge based power distribution network fault diagnosis system according to claim 4, wherein in the central control module, the coordinating and controlling the normal operation of each module of the topology knowledge based power distribution network fault diagnosis system through the central processor comprises:
(1) the method comprises the steps of obtaining an error signal by making a difference between an input signal and an output signal of a controlled object;
(2) judging whether the error signal is larger than a preset error threshold value or not;
(3) and outputting the total control quantity to the controlled object so as to adjust the output signal of the controlled object.
6. The topology knowledge based power distribution network fault diagnosis system of claim 5, wherein in the model building module, the power distribution network fault diagnosis model comprises an input layer, a hidden layer and an output layer, wherein the hidden layer comprises a convolutional layer, a pooling layer and a full connection layer;
where the convolutional layer is defined by a set of small filters through which the input data is convolved in the forward channel, the convolutional layer output is as follows:
wherein h isj(x) Is the spatial position x ═ x1，x2) The jth inactive output feature map of (g)ijIs hjAnd the ith input channel fiA core in between; c represents the total input channel number, b represents the deviation;
the operator is a two-dimensional convolution defined as follows:
where m × n represents the kernel size.
7. The topology knowledge-based power distribution network fault diagnosis system of claim 6, wherein the diagnosing of the power distribution network fault by the fault diagnosis program using the power distribution network fault diagnosis model comprises:
(1) acquiring a power distribution network fault characteristic set based on a time sequence;
(2) the power distribution network fault feature set based on the time sequence is used as an input signal and is input to the power distribution network fault diagnosis model;
(3) and diagnosing the power distribution network fault by using the power distribution network fault diagnosis model.
8. A power distribution network fault diagnosis method based on topology knowledge is characterized by comprising the following steps:
s101, acquiring data information of key nodes of the power distribution network by using data acquisition equipment through a data acquisition module; wherein the data information comprises electrical operating parameters and identification information;
s102, preprocessing the acquired data information of the key nodes of the power distribution network by using a data preprocessing program through a data preprocessing module;
s103, performing feature extraction on the preprocessed data information of the key nodes of the power distribution network by using a feature extraction program through a fault feature extraction module to obtain power distribution network fault features based on a time sequence;
s104, fusing the acquired power distribution network fault characteristics based on the time sequence by using a data fusion program through a data fusion module to obtain a power distribution network fault characteristic set;
s105, coordinating and controlling normal operation of each module of the power distribution network fault diagnosis system based on topology knowledge by using a central processing unit through a central control module;
s106, constructing a power distribution network fault diagnosis model according to the power distribution network fault feature set by using a model construction module and a model construction program;
s107, diagnosing the power distribution network fault by using a fault diagnosis program and a power distribution network fault diagnosis model through a fault diagnosis module, and generating a fault diagnosis result;
s108, evaluating the power distribution network fault diagnosis result by using a diagnosis evaluation module and a diagnosis evaluation program to generate a final power distribution network fault diagnosis report;
s109, the data storage module stores the acquired data information of the key nodes of the power distribution network, data preprocessing results, power distribution network fault characteristics based on time sequences, a power distribution network fault characteristic set, a power distribution network fault diagnosis model, fault diagnosis results and final power distribution network fault diagnosis reports by using the memory;
and S110, updating and displaying the acquired data information of the key nodes of the power distribution network, the data preprocessing result, the power distribution network fault characteristics based on the time sequence, the power distribution network fault characteristic set, the power distribution network fault diagnosis model, the fault diagnosis result and the real-time data of the final power distribution network fault diagnosis report by using the display through the updating and displaying module.
9. A computer program product stored on a computer readable medium, comprising a computer readable program for providing a user input interface for applying the topology knowledge based power distribution network fault diagnosis system according to any one of claims 1 to 8 or for performing the topology knowledge based power distribution network fault diagnosis method according to any one of claim 9 when executed on an electronic device.
10. A computer-readable storage medium storing instructions that, when executed on a computer, cause the computer to apply the topology knowledge based power distribution network fault diagnosis system according to any one of claims 1 to 8 or to perform the topology knowledge based power distribution network fault diagnosis method according to any one of claim 9.
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