CN111291245A - Case online generation system and method applied to PAS and computer equipment - Google Patents
Case online generation system and method applied to PAS and computer equipment Download PDFInfo
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Abstract
The embodiment of the invention relates to a case online generation system and method applied to PAS and computer equipment. The case online generation system applied to the PAS automatically extracts real-time section case data and power grid parameter tertiary from an electric power dispatching automation real-time system through a data acquisition module, a setting module is adopted to establish an initial case, a reasoning module carries out reasoning analysis on the initial case and the power grid parameter secondary, the initial case is optimized to obtain a PAS evaluation case base, the PAS evaluation case base can better meet different requirements of different electric power dispatching automation systems, the technical problems that different PASs used by the power grid dispatching automation systems of different systems are different, and different results can be obtained by checking and accepting the same data in different PASs are solved.
Description
Technical Field
The invention relates to the technical field of power systems, in particular to a case online generation system and method applied to PAS and computer equipment.
Background
The safe and stable operation of the power grid puts higher and higher requirements on dispatching management. With the further development of the scale of the power grid, powerful power supply reserves can be provided for the local economic development, the safe and stable operation of the power grid needs to be ensured due to the change of the operation mode in the process of power grid transformation construction, and higher requirements are provided for the dispatching operation analysis capability. The safe and stable operation of the existing power grid is realized by adopting a power grid dispatching automation system to carry out dispatching operation analysis, and basic requirements and acceptance rules need to be provided for the basic functions of the power grid dispatching automation system, so that the safe and stable operation of the power grid is ensured.
At present, basic requirements and acceptance rules are provided for basic functions of a power grid dispatching automation system, and the examination of advanced application software (PAS) of the power dispatching automation system is realized by formulating quantitative indexes and carrying out error statistics on results and real-time measurement values (or state estimation values) after actual operation.
Since PASs used by power grid dispatching automation systems of all parts are produced from different manufacturers, a plurality of versions exist, software manufactured by different manufacturers has certain differences in the aspects of models, algorithms and data processing, and different results can be obtained from the same data. The model in PAS is mainly obtained through the traditional teaching plan on the power grid, the traditional teaching plan is mainly obtained through manual editing and debugging in an off-line environment, and for a large power grid, manual debugging is needed, so that the difficulty is high.
Disclosure of Invention
The embodiment of the invention provides a case online generation system, a case online generation method and computer equipment applied to PAS, which are used for solving the technical problem that the same data is checked and accepted in different PASs possibly to obtain different results due to different PASs used by the power grid dispatching automation systems of different systems.
In order to achieve the above object, the embodiments of the present invention provide the following technical solutions:
a case on-line generation system applied to PAS comprises a data acquisition module, a setting module and an inference module;
the data acquisition module is used for acquiring section case data and power grid parameter data from the power dispatching automation system;
the setting module is used for classifying the section case data according to an operation mode, an operation mode and a fault type and establishing an initial case library;
and the reasoning module is used for carrying out fault reasoning on the section case data in the initial case library and the power grid parameter data, and storing the reasoning fault result to obtain the PAS evaluation case library.
Preferably, the data acquisition module comprises a section data acquisition submodule and a power grid parameter acquisition submodule;
the section data acquisition submodule is used for acquiring section case data of a power grid in an operating state from the power dispatching automation system;
and the power grid parameter acquisition submodule is used for acquiring power grid parameter data of a generator set, a line, a transformer and/or a load from the power dispatching automation system.
Preferably, the setting module comprises an operation mode setting submodule, a fault setting submodule and a case library establishing submodule;
the operation mode setting submodule is used for classifying the cases in the section case data according to the operation modes of the normal, accident, overhaul, open-loop mode and closed-loop model of the power grid;
the operation mode setting submodule is used for classifying the cases in the section case data according to the active power and the reactive power of the power grid operation;
the fault setting submodule is used for classifying according to the fault type of the power grid operation;
the case base establishing submodule is used for establishing the cases after the operation mode setting submodule, the operation mode setting submodule and the fault setting submodule are classified into the initial case base.
Preferably, the fault types include line faults, bus faults, transformer faults, permanent faults, instantaneous faults, override trip faults.
Preferably, the reasoning module comprises a phenomenon acquisition sub-module, a fault processing sub-module and a reasoning result sub-module;
the phenomenon acquisition submodule is used for converting the section case data and the power grid parameter data in the initial case library into a phenomenon number and setting the phenomenon number in a dynamic array;
the fault processing submodule is used for carrying out fault processing on the phenomenon number in the dynamic array by adopting an and-or relation and constructing a fault tree model on the processed fault phenomenon number by adopting a deep neural network technology;
and the reasoning result submodule is used for carrying out fault reasoning on the fault tree model by adopting a depth-first search mode or an breadth-first search mode and a stack data structure mode and storing a reasoning result to a two-dimensional dynamic array.
Preferably, the process of fault reasoning comprises:
the top phenomenon number of the fault tree model is used as a first element of the stack data structure, and the first element is used as a search starting bit mark;
searching for the influence factors of the fault according to the phenomenon number in the fault tree model by the search starting bit mark;
if the searched result is the influence-free factor, the top phenomenon number of the fault tree model is used as the final influence factor of the fault, and the final influence factor is stored in the two-dimensional dynamic array;
if the search result influences factors, obtaining each phenomenon number in the fault tree model, sequencing each phenomenon number, and storing each sequenced phenomenon number into a stack array;
and searching the phenomenon number in the stack array again according to the downward movement mode of the stack pointer to obtain the final influence factor with the fault, and storing the search path for obtaining the final influence factor into the two-dimensional dynamic array.
Preferably, the two-dimensional dynamic array comprises at least three columns, wherein the first column is used for storing the phenomenon number, the second column is used for storing the search start bit mark, and the third column is used for storing the search path;
wherein the search path is a phenomenon number.
Preferably, the case online generation system applied to PAS further comprises a conversion module, wherein the conversion module is used for converting the final influence factors in the two-dimensional dynamic array into information for guiding an operator to operate.
The invention also provides an online case generation method applied to PAS, which comprises the following steps:
acquiring section case data and power grid parameter data from a power dispatching automation system;
classifying the section case data according to an operation mode, an operation mode and a fault type, and establishing an initial case library;
and fault reasoning is carried out on the section case data in the initial case library and the power grid parameter data, and the fault result of the reasoning is stored to obtain a PAS evaluation case library.
The invention also provides a computer device comprising a memory and a processor;
the memory is used for storing program codes and transmitting the program codes to the processor;
the processor is used for executing the case online generation method applied to PAS according to the instructions in the program code.
According to the technical scheme, the embodiment of the invention has the following advantages:
1. the case online generation system applied to the PAS automatically extracts real-time section case data and power grid parameter tertiary from an electric power dispatching automation real-time system through a data acquisition module, a setting module is adopted to establish an initial case, a reasoning module carries out reasoning analysis on the initial case and the power grid parameter gentleman, the initial case is optimized to obtain a PAS evaluation case base, the PAS evaluation case base can better meet different requirements of different electric power dispatching automation systems, the technical problem that the PASs used by the power grid dispatching automation systems of different systems are different, and the same data can possibly obtain different results after being accepted in different PASs is solved;
2. the case online generation method applied to PAS obtains section case data and power grid parameter data from a power dispatching automation system; classifying the section case data according to the operation mode, the operation mode and the fault type, and establishing an initial case library; fault reasoning is carried out on the section case data and the power grid parameter data in the initial case library, and the fault result of the reasoning is stored to obtain the PAS evaluation case library. The obtained PAS evaluation case library better meets different requirements of different power dispatching automation systems, and the technical problem that the same data can be checked and accepted in different PASs to obtain different results due to different PASs used by the power grid dispatching automation systems of different systems is solved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without inventive exercise.
Fig. 1 is a block diagram of a case online generation system applied to PAS according to an embodiment of the present invention.
Fig. 2 is a frame diagram of an inference module of a case online generation system applied to PAS according to an embodiment of the present invention.
Fig. 3 is a frame diagram of a fault tree model of a case online generation system applied to PAS according to an embodiment of the present invention.
Fig. 4 is a flowchart illustrating steps of a case on-line generation system fault inference process applied to PAS according to an embodiment of the present invention.
Fig. 5 is a flowchart illustrating steps of a case online generation method applied to PAS according to an embodiment of the present invention.
Detailed Description
In order to make the objects, features and advantages of the present invention more obvious and understandable, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is obvious that the embodiments described below are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Ems (energy Management system) energy Management system has been developed so far, and has been developed from a single-machine system to a network-based distributed multi-machine system, and has been developed from a power system advanced Application software pas (power Application software) which originally has only a simple supervisory control and data acquisition (SCADA). PAS has become the important instrument that supplementary dispatch operation personnel realized operation mode analysis, accident preview. The practical application of PAS makes the dispatch change from empirical mode to analytic mode, has improved the safe and stable and economic operation level of electric wire netting.
For a large-scale power grid, convergent and vivid power flow distribution needs to be manually debugged, and the reasonability of voltage and reactive power flow distribution is difficult to guarantee.
Therefore, the embodiment of the application provides a case online generation system, a case online generation method and a computer device applied to PAS, which can automatically acquire section case data and power grid parameter data from a power dispatching automation system of a power grid, and obtain a case reasoning result and store the case reasoning result in a PAS evaluation case library by configuring information such as an operation mode, a control mode and the like of the section case data and performing fault reasoning, and when an accident occurs to the power grid, a nearest online case before the accident is called from the PAS evaluation case library to realize accident reproduction, so that the case online generation system is convenient for an operator to use, and the case online generation system and the method are used for solving the technical problem that the same data can be checked and accepted in different PASs to obtain different results.
The first embodiment is as follows:
fig. 1 is a block diagram of a case online generation system applied to PAS according to an embodiment of the present invention.
As shown in fig. 1, an embodiment of the present invention provides an online case generation system applied to PAS, which includes a data acquisition module 10, a setting module 20, and an inference module 30;
the data acquisition module 10 is used for acquiring section case data and power grid parameter data from the power dispatching automation system;
the setting module 20 is used for classifying the section case data according to the operation mode, the operation mode and the fault type and establishing an initial case library;
and the reasoning module 30 is used for carrying out fault reasoning on the section case data and the power grid parameter data in the initial case library, and storing the reasoning fault result to obtain the PAS evaluation case library.
In the embodiment of the present invention, the section case data and the power grid parameter data obtained by the data obtaining module 10 are mainly obtained from the power dispatching automation system.
It should be noted that, in the operation process of the power grid, the power dispatching automation system automatically acquires the operation state data of the power grid every other period, and the power dispatching automation system automatically starts a tide forming case; each case of the power dispatching automation system contains power grid parameter data.
In the embodiment of the invention, the setting module 20 mainly classifies the acquired section case data according to different types of power grids, establishes a power grid case library in the power dispatching automation system, improves the accuracy of analyzing and acquiring power grid operation service data by operators, and provides more accurate case data for safe and stable operation of the power grids.
In the embodiment of the present invention, the inference module 30 mainly optimizes the section case data and the power grid parameter data in the initial case library, and performs inference analysis on the case to obtain the inferred fault result of the power grid, so as to facilitate monitoring of the power grid by an operator.
The case online generation system applied to the PAS provided by the invention automatically extracts real-time section case data and power grid parameter tertiary from a power dispatching automation real-time system through the data acquisition module, establishes an initial case by adopting the setting module, carries out inference analysis on the initial case and the power grid parameter gentleman by the inference module, optimizes the initial case to obtain a PAS evaluation case base, enables the PAS evaluation case base to better meet different requirements of different power dispatching automation systems, and solves the technical problem that the same data can possibly obtain different results when the same data is checked and accepted in different PASs due to different PASs used by the power grid dispatching automation systems of different systems.
It should be noted that the case online generation system applied to PAS establishes a PAS evaluation case library by adopting an artificial intelligence method, really realizes scientific and reasonable individual cases, and improves the online case operation analysis capability in the power dispatching automation system.
In an embodiment of the present invention, the data acquisition module 10 includes a section data acquisition submodule 11 and a power grid parameter acquisition submodule 12;
the section data acquisition submodule 11 is used for acquiring section case data of a power grid in an operating state from the power dispatching automation system;
and the power grid parameter acquisition submodule 12 is used for acquiring power grid parameter data of the generator set, the line, the transformer and/or the load from the power dispatching automation system.
It should be noted that the section data obtaining submodule 11 is used for the power dispatching automation system to automatically generate a set of starting power flow for the case system at regular intervals in the state that the power grid operates online, and the starting power flow is used as an online section case and stored in the section case library; the section data acquisition sub-module 11 can select a required section case from the section case library as section case data. The power grid parameter obtaining sub-module 12 mainly obtains power grid equipment operation parameters, wherein the power grid equipment operation parameters include generator sets, lines, transformers, load parameters and the like.
In an embodiment of the present invention, the setting module 20 includes an operation mode setting submodule 21, an operation mode setting submodule 22, a fault setting submodule 23, and a case library establishing submodule 24;
the operation mode setting submodule 21 is used for classifying the cases in the section case data according to the operation modes of the normal, accident, overhaul, open-loop mode and closed-loop model of the power grid;
the operation mode setting submodule 22 is used for classifying the cases in the section case data according to the active power and the reactive power of the power grid operation;
the fault setting submodule 23 is used for classifying according to the fault type of the power grid operation;
and a case base establishing submodule 24 for establishing the cases after the operation mode setting submodule, the operation mode setting submodule and the fault setting submodule are classified into an initial case base.
It should be noted that a specific operation and fault or accident in the power system always correspond to a certain operation mode, and the handling of the accident after the fault or accident occurs also relates to the operation mode. The operation mode setting submodule 21 mainly classifies the cases in the section case data according to operation modes, and the operation modes include a normal operation mode, an accident operation mode, a maintenance operation mode, a maximum operation mode, a minimum operation mode, an open loop mode, a closed loop mode and the like. The operation mode setting submodule 21 classifies the section case data to meet the requirements of different power grid systems on operation modes.
In an electric power system, the main function of normal operation is to set the operation of reactive power control, by which the grid voltage level and the distribution of reactive power are changed, and whether the operation can be performed correctly will directly affect the safe operation of the grid. In order to reduce or even prevent malfunctions, it is necessary to implement correct organizational measures. The operation mode setting submodule 22 selects different operation contents according to the levels and requirements of different voltage reactive power control systems, and automatically adjusts the operation contents and the operation progress. On the basis of the case selected by the section data acquisition submodule 11, aiming at the control requirements of different levels and different levels, the operation can be set to be divided into a primary level, a middle level and a high level from easy to difficult, so that the flexibility and pertinence are improved, and the initial case is more standard and scientific.
When the power grid has a fault, the fault is judged quickly and accurately, and the normal operation of the system is restored as soon as possible, which is a basic requirement for the operation control of the power grid. The fault setting submodule 23 divides the cases selected by the section data obtaining submodule 11 into different fault cases on the basis of the fault types. The fault setting submodule 23 may manually classify fault cases, or may select automatically classified fault cases, and the fault random generator automatically generates fault cases, and may manually modify the generated cases. In this embodiment, the determination of whether a fault occurs in the case selected by the section data acquisition submodule 11 is implemented by using an analysis method of a deep neural network; the analysis method of the deep neural network basically starts from apparent parameters, and logical reasoning is carried out to determine whether a fault occurs.
In the present embodiment, the fault types include line faults, bus faults, transformer faults, permanent faults, instantaneous faults, override trip faults.
The fault is combined with the switch rejection, the protection rejection, and the like to constitute various override trip faults.
Fig. 2 is a frame diagram of an inference module of a case online generation system applied to PAS according to an embodiment of the present invention, and fig. 3 is a frame diagram of a fault tree model of the case online generation system applied to PAS according to an embodiment of the present invention.
As shown in FIG. 2, in one embodiment of the present invention, the inference module 30 includes a phenomenon acquisition sub-module 31, a fault handling sub-module 32, and an inference result sub-module 33;
the phenomenon obtaining submodule 31 is used for converting the section case data and the power grid parameter data in the initial case library into a phenomenon number and setting the phenomenon number in a dynamic array;
the fault processing submodule 32 is used for carrying out fault processing on the phenomenon number in the dynamic array by adopting an and-or relation and constructing a fault tree model on the processed fault phenomenon number by adopting a deep neural network technology;
and the reasoning result submodule 33 is used for performing fault reasoning on the fault tree model by adopting a depth-first search mode or a breadth-first search mode and a stack data structure mode, and storing a reasoning result into a two-dimensional dynamic array.
It should be noted that the fault handling sub-module 32 mainly employs "and relationship" fault handling and "or relationship" fault handling. As shown in FIG. 3, at the top of the fault tree model is the most critical abnormal event number, at the end is the fault number, and at the middle node is the one-level abnormal event number. The tail end fault in the fault tree model can cause the abnormal phenomenon of the upper level, and the abnormal phenomenon of the upper level can cause the abnormal phenomenon of the upper level, so that the abnormal phenomenon of the top end of the tree is finally caused. The fault handling submodule 32 in this embodiment is a process of finding one or more faults causing an abnormal phenomenon at the top of the tree, which are sent from the top of the tree to the end according to the reverse order of fault diagnosis.
In this embodiment, the two-dimensional dynamic array includes at least three columns, the first column is used for storing the phenomenon number, the second column is used for storing the search start bit flag, and the third column is used for storing the search path. Wherein, the search path is a phenomenon number.
Fig. 4 is a flowchart illustrating steps of a case on-line generation system fault inference process applied to PAS according to an embodiment of the present invention.
As shown in fig. 3 and 4, in one embodiment of the present invention, the process of fault inference includes:
s01, a top phenomenon number of a fault tree model is used as a first element of a stack data structure, and the first element is used as a search starting bit mark;
s02, searching for the influence factors of the fault according to the phenomenon number in the fault tree model by the search starting bit mark;
s03, if the searched result is free of influence factors, the top phenomenon number of the fault tree model is used as the final influence factor of the fault, and the final influence factor is stored in the two-dimensional dynamic array;
s04, if the influence factors of the searched result are influenced, obtaining each phenomenon number in the fault tree model, sequencing each phenomenon number, and storing each sequenced phenomenon number into a stack array;
and S05, searching the phenomenon number in the stack array again according to the downward movement mode of the stack pointer to obtain the final influence factor with the fault, and storing the search path for obtaining the final influence factor into the two-dimensional dynamic array.
It should be noted that, in the process of fault inference, traversal search is performed on abnormal phenomena of a fault tree in a fault tree model, and a result obtained by the search is stored in a two-dimensional dynamic array as an inference result.
In an embodiment of the present invention, the case online generation system applied to PAS further includes a conversion module 40, and the conversion module 40 is configured to convert the final influence factors in the two-dimensional dynamic array into information for guiding an operator to operate.
It should be noted that the inference result of the two-dimensional dynamic array is converted into diagnostic information and operation guidance provided for the power grid operator, so that the operator can analyze the operation of the power grid conveniently.
Example two:
fig. 5 is a flowchart illustrating steps of a case online generation method applied to PAS according to an embodiment of the present invention.
As shown in fig. 5, an embodiment of the present invention further provides an online case generation method applied to PAS, including the following steps:
s1, acquiring section case data and power grid parameter data from a power dispatching automation system;
s2, classifying the section case data according to the operation mode, the operation mode and the fault type, and establishing an initial case library;
and S3, fault reasoning is carried out on the section case data and the power grid parameter data in the initial case library, and the fault result of the reasoning is stored to obtain the PAS evaluation case library.
It should be noted that, in the case online generation method applied to PAS, the specific contents of step S1, step S2, and step S3 have been described in the three modules of the data acquisition module 10, the setting module 20, and the inference module 30 in the first embodiment one by one, and therefore are not described in this embodiment one by one.
The invention provides an on-line case generation method applied to PAS, which obtains section case data and power grid parameter data from a power dispatching automation system; classifying the section case data according to the operation mode, the operation mode and the fault type, and establishing an initial case library; fault reasoning is carried out on the section case data and the power grid parameter data in the initial case library, and the fault result of the reasoning is stored to obtain the PAS evaluation case library. The obtained PAS evaluation case library better meets different requirements of different power dispatching automation systems, and the technical problem that the same data can be checked and accepted in different PASs to obtain different results due to different PASs used by the power grid dispatching automation systems of different systems is solved.
Example three:
the embodiment of the invention provides computer equipment, which comprises a memory and a processor;
the memory is used for storing the program codes and transmitting the program codes to the processor;
the processor is used for executing the case online generation method applied to PAS according to the instructions in the program code.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (10)
1. A case on-line generation system applied to PAS is characterized by comprising a data acquisition module, a setting module and an inference module;
the data acquisition module is used for acquiring section case data and power grid parameter data from the power dispatching automation system;
the setting module is used for classifying the section case data according to an operation mode, an operation mode and a fault type and establishing an initial case library;
and the reasoning module is used for carrying out fault reasoning on the section case data in the initial case library and the power grid parameter data, and storing the reasoning fault result to obtain the PAS evaluation case library.
2. The case on-line generation system applied to PAS according to claim 1, wherein the data acquisition module comprises a section data acquisition submodule and a power grid parameter acquisition submodule;
the section data acquisition submodule is used for acquiring section case data of a power grid in an operating state from the power dispatching automation system;
and the power grid parameter acquisition submodule is used for acquiring power grid parameter data of a generator set, a line, a transformer and/or a load from the power dispatching automation system.
3. The case online generation system applied to PAS of claim 1, wherein the setting module comprises an operation mode setting submodule, a fault setting submodule and a case library establishing submodule;
the operation mode setting submodule is used for classifying the cases in the section case data according to the operation modes of the normal, accident, overhaul, open-loop mode and closed-loop model of the power grid;
the operation mode setting submodule is used for classifying the cases in the section case data according to the active power and the reactive power of the power grid operation;
the fault setting submodule is used for classifying according to the fault type of the power grid operation;
the case base establishing submodule is used for establishing the cases after the operation mode setting submodule, the operation mode setting submodule and the fault setting submodule are classified into the initial case base.
4. The case on-line generation system applied to PAS according to claim 3, wherein the fault type includes line fault, bus fault, transformer fault, permanent fault, instantaneous fault, override trip fault.
5. The case on-line generation system applied to PAS of claim 1, wherein the reasoning module comprises a phenomenon obtaining sub-module, a fault processing sub-module and a reasoning result sub-module;
the phenomenon acquisition submodule is used for converting the section case data and the power grid parameter data in the initial case library into a phenomenon number and setting the phenomenon number in a dynamic array;
the fault processing submodule is used for carrying out fault processing on the phenomenon number in the dynamic array by adopting an and-or relation and constructing a fault tree model on the processed fault phenomenon number by adopting a deep neural network technology;
and the reasoning result submodule is used for carrying out fault reasoning on the fault tree model by adopting a depth-first search mode or an breadth-first search mode and a stack data structure mode and storing a reasoning result to a two-dimensional dynamic array.
6. The case on-line generating system applied to PAS according to claim 5, wherein the fault reasoning process comprises:
the top phenomenon number of the fault tree model is used as a first element of the stack data structure, and the first element is used as a search starting bit mark;
searching for the influence factors of the fault according to the phenomenon number in the fault tree model by the search starting bit mark;
if the searched result is the influence-free factor, the top phenomenon number of the fault tree model is used as the final influence factor of the fault, and the final influence factor is stored in the two-dimensional dynamic array;
if the search result influences factors, obtaining each phenomenon number in the fault tree model, sequencing each phenomenon number, and storing each sequenced phenomenon number into a stack array;
and searching the phenomenon number in the stack array again according to the downward movement mode of the stack pointer to obtain the final influence factor with the fault, and storing the search path for obtaining the final influence factor into the two-dimensional dynamic array.
7. The system of claim 5, wherein the two-dimensional dynamic array comprises at least three columns, the first column is for storing a phenomenon number, the second column is for storing a search start bit flag, and the third column is for storing a search path;
wherein the search path is a phenomenon number.
8. The on-line case generation system applied to PAS according to claim 5 or 6, characterized in that, the on-line case generation system applied to PAS further comprises a conversion module for converting the final influence factors in the two-dimensional dynamic array into information for guiding the operation of an operator.
9. A case online generation method applied to PAS is characterized by comprising the following steps:
acquiring section case data and power grid parameter data from a power dispatching automation system;
classifying the section case data according to an operation mode, an operation mode and a fault type, and establishing an initial case library;
and fault reasoning is carried out on the section case data in the initial case library and the power grid parameter data, and the fault result of the reasoning is stored to obtain a PAS evaluation case library.
10. A computer device comprising a memory and a processor;
the memory is used for storing program codes and transmitting the program codes to the processor;
the processor, configured to execute the case online generation method applied to PAS of claim 9 according to instructions in the program code.
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| CN112765133A (en) * | 2020-12-25 | 2021-05-07 | 广东电网有限责任公司电力科学研究院 | Maintenance system and maintenance method for PAS case base |
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