CN116308082A - Accurate storage and allocation management method and system for electric power emergency materials - Google Patents
Accurate storage and allocation management method and system for electric power emergency materials Download PDFInfo
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Abstract
The invention provides a precise reserve and allocation management method and system for electric power emergency materials, which relate to the technical field of intelligent management, and the method comprises the following steps: the method comprises the steps of acquiring basic information of the electric power equipment, acquiring weather state information and geographical environment information in a future preset time zone according to geographical coordinate parameters of the electric power equipment, generating disaster type information and disaster grade information, carrying out fault prediction based on equipment operation state parameters to generate a fault event prediction result, and carrying out allocation management on a first emergency material reserve if the first emergency material reserve does not meet the matched event-related element type information and event-related element quantity information.
Description
Technical Field
The invention relates to the technical field of intelligent management, in particular to a precise storage and allocation management system for electric power emergency materials.
Background
With the rapid development of Chinese economy, the requirements of people on living standard and quality are continuously improved, and the power supply is an important guarantee for sustainable development of national economy as an important basic industry and public utility related to national life, so that the emergency material supply capability is required to be continuously improved for realizing timely, stable and reliable power resource supply, the power failure of a power grid caused by severe natural disasters and the shutdown of a power station are prevented, and the timely supply of power grid repair equipment, materials, tools, disaster relief materials, emergency relief equipment and the like required for short-time power restoration is met. Coordination of distribution, allocation and supply of materials for critical project construction such as peaked summer, industry expansion matching, new energy construction, municipal engineering, electric iron matching and the like ensures timely and smooth production and operation of engineering projects. Therefore, the allocation and management of the electric power emergency materials are emphasized, and the improvement of allocation quality and allocation efficiency is significant through a scientific and reasonable mode.
In the prior art, the reserve and allocation of the electric power emergency materials are insufficient in advance, so that the final electric power emergency materials cannot be reserved and allocated in time.
Disclosure of Invention
The application provides a precise storage and allocation management method of electric power emergency materials, which is used for solving the technical problems that the storage and allocation of the electric power emergency materials in the prior art are insufficient in advance, so that the final electric power emergency materials cannot be stored and allocated in time.
In view of the above problems, the present application provides a method and a system for accurate storage and allocation management of electric power emergency materials.
In a first aspect, the present application provides a method for accurate storage and allocation management of electric power emergency materials, the method comprising: acquiring basic information of the power equipment, wherein the basic information of the power equipment comprises operation state parameters of the power equipment and geographic coordinate parameters of the power equipment; acquiring weather state information and geographical environment information of a future preset time zone according to the geographical coordinate parameters of the power equipment; performing disaster analysis according to the meteorological state information and the geographic environment information to generate disaster type information and disaster grade information; according to the disaster type information and the disaster grade information, performing fault prediction based on the equipment running state parameters, and generating a fault event prediction result; matching event-related element type information and event-related element quantity information according to the fault event prediction result; judging whether a first emergency material reserve library meets the event-related element type information and the event-related element quantity information; and if the first emergency material reserve is not satisfied, performing allocation management on the first emergency material reserve.
In a second aspect, the present application provides a precision reserve and transfer management system for electrical emergency supplies, the system comprising: the system comprises a basic information acquisition module, a control module and a control module, wherein the information acquisition module is used for acquiring basic information of the power equipment, and the basic information of the power equipment comprises operation state parameters of the power equipment and geographic coordinate parameters of the power equipment; the information acquisition module is used for acquiring weather state information and geographic environment information of a future preset time zone according to the geographic coordinate parameters of the power equipment; the disaster analysis module is used for carrying out disaster analysis according to the meteorological state information and the geographic environment information to generate disaster type information and disaster grade information; the fault prediction module is used for performing fault prediction based on the equipment running state parameters according to the disaster type information and the disaster grade information to generate a fault event prediction result; the matching module is used for matching event-related element type information and event-related element quantity information according to the fault event prediction result; the judging module is used for judging whether the first emergency material reserve library meets the event-related element type information and the event-related element quantity information; and the management module is used for allocating and managing the first emergency material reserve warehouse if the first emergency material reserve warehouse is not satisfied.
One or more technical solutions provided in the present application have at least the following technical effects or advantages:
the application provides a precise reserve and transfer management method of electric power emergency materials, relates to intelligent management technical field, has solved the advance of reserve and transfer to electric power emergency materials among the prior art not enough for final electric power emergency materials can't in time carry out the technical problem of reserve and transfer, has realized the rationalization accurate management and control to the reserve and the transfer of electric power emergency materials, and then accurate reserve and the transfer of electric power emergency materials.
Drawings
Fig. 1 is a schematic flow chart of a method for accurately storing and allocating and managing electric power emergency materials;
fig. 2 is a schematic diagram of a disaster type information setting flow in a method for accurately storing and allocating and managing electric power emergency materials;
fig. 3 is a schematic diagram of a process for obtaining a fault event prediction result in a method for accurately storing and allocating and managing electric power emergency materials;
fig. 4 is a schematic diagram of a process for obtaining type information of event-related elements and quantity information of event-related elements in a method for accurately storing and allocating and managing electric power emergency materials;
Fig. 5 is a schematic structural diagram of a precise storage and allocation management system for electric emergency materials.
Reference numerals illustrate: the system comprises a basic information acquisition module 1, an information acquisition module 2, a disaster analysis module 3, a fault prediction module 4, a matching module 5, a judgment module 6 and a management module 7.
Detailed Description
The utility model provides a through providing an accurate deposit and transfer management method of emergent material of electric power for solve among the prior art to the deposit of emergent material of electric power and the advance nature of transferring not enough for final emergent material of electric power can't in time carry out the technical problem of deposit and transferring.
Example 1
As shown in fig. 1, an embodiment of the present application provides a method for accurately storing and allocating and managing electric power emergency materials, which includes:
step S100: acquiring basic information of the power equipment, wherein the basic information of the power equipment comprises operation state parameters of the power equipment and geographic coordinate parameters of the power equipment;
specifically, when the electric power emergency materials are accurately reserved and allocated and managed, all basic information of the electric power emergency materials is required to be collected, electric power equipment contained in the electric power materials can be divided into two main types, namely power station boilers, steam turbines, gas turbines, water turbines, generators, transformers and the like, the electric power equipment mainly comprises power transmission lines, transformers, contactors and the like with various voltage levels, the basic information of the electric power equipment mainly comprises operation state parameters of the electric power equipment and geographic coordinate parameters of the electric power equipment, the operation state parameters of the electric power equipment are in closing positions by isolating switches and breakers of the electric power equipment, a circuit from a power supply to a power receiving end of the electric power equipment is connected into the operation state of the electric power equipment, and the geographic coordinate parameters of the electric power equipment refer to spherical coordinates of corresponding electric power equipment points represented by longitude and latitude, so that the allocation and management of the electric power emergency materials are realized in the later stage as important reference basis.
Step S200: acquiring weather state information and geographical environment information of a future preset time zone according to the geographical coordinate parameters of the power equipment;
specifically, based on the geographical coordinate parameters of the electric power equipment contained in the basic information of the electric power equipment, a future time zone is preset, namely, the time after the current moment can be divided into time nodes taking hours as a unit, and the meteorological states and the geographical environments in the geographical coordinates of the current electric power equipment are collected and extracted on the geographical coordinates of the electric power equipment in the divided time nodes, wherein the meteorological states can be precipitation, ground condensation, thunder and lightning, and the like, and the geographical environments refer to the sum of geographical elements comprising various conditions of the earth surface, including natural environments and artificial environments, so that the meteorological state information and the geographical environment information corresponding to the preset time zone are extracted, and further, the adjustment management of electric power emergency materials is guaranteed.
Step S300: performing disaster analysis according to the meteorological state information and the geographic environment information to generate disaster type information and disaster grade information;
specifically, disaster analysis is performed on the weather states and the geographical environment states contained in the divided preset time zones on the basis of geographical coordinates of the power equipment, first, power disaster feature extraction is performed on the weather state information, environment feature extraction is performed on the geographical environment information, accordingly, the weather types of disasters and the continuous time of disaster weather of different disaster types are correspondingly obtained, the corresponding environment geological features, the altitude of the environment according to the current geology and the like, the disaster weather types and the continuous time of the disasters are further classified on the basis of the influence on the power equipment, namely, the disaster grades corresponding to the larger the influence on the power equipment are, so that disaster grade information is obtained, then the disaster weather types and the continuous time of the disaster weather corresponding to the disaster grade information are set as disaster type information, and disaster grade information and disaster type information corresponding to the disaster grade information are obtained, so that the power emergency ramming management basis is realized for follow-up implementation.
Step S400: according to the disaster type information and the disaster grade information, performing fault prediction based on the equipment running state parameters, and generating a fault event prediction result;
specifically, the accurate position of the power equipment is obtained according to the geographical coordinate parameters of the current power equipment, the meteorological state and the geographical environment of the position of the power equipment, accordingly, according to disaster type information, disaster grade information and the power equipment operation state parameters in basic information of the power equipment corresponding to the current power equipment, fault prediction is carried out on the operation state of the power equipment according to the operation parameters of the power equipment, a fault threshold is set on the operation state of the power equipment, if the operation state of the power equipment is in the threshold, the current power equipment is judged to be the fault state, a value when the operation state of the power equipment approaches the threshold is set to be a dangerous interval, the fault event type meeting the threshold and the correlation degree of the fault event meeting the threshold are further obtained, the fault event type meeting the threshold is ordered according to the correlation degree of the fault event meeting the threshold, finally, the fault event prediction result is correspondingly obtained, and the effect of transferring and managing the power emergency materials is promoted.
Step S500: matching event-related element type information and event-related element quantity information according to the fault event prediction result;
specifically, on the basis of the fault event prediction result generated by performing fault prediction according to the equipment operation state parameters, traversing the obtained fault event prediction result, namely sequentially accessing each node in the fault event prediction result, and on the basis, matching the event-related element type and the corresponding event-related element number of the power equipment, wherein the event-related element type and the event-related element number can be the element type matched when the power equipment fails and the element number corresponding to one element type, so that the element inventory which can be used in the current emergency material reserve can be better known, further acquiring the fault element type record data and the corresponding fault element number record data of the power equipment in the fault prediction result of the power equipment, and then correspondingly adding the fault element type record data and the corresponding fault element number record data to the event-related element type information and the event-related element number information, thereby obtaining final event-related element type information and event-related element number information, and having a profound influence on the allocation management of the power emergency material.
Step S600: judging whether a first emergency material reserve library meets the event-related element type information and the event-related element quantity information;
the method comprises the steps that a current emergency material reserve is set as a first emergency material reserve, whether the first emergency material reserve meets event-related element type information and event-related element quantity information or not is judged, namely, when the current first emergency material reserve is used for carrying out emergency treatment on electric power materials in emergency, the first emergency material reserve can be timely scheduled, therefore, the element type of time-related elements in the first emergency material reserve and the element replacement quantity corresponding to the element quantity are required to be ensured to be larger than the element replacement quantity when electric power equipment fails, if the first emergency material reserve meets the event-related element type information and the event-related element quantity information, the fact that the element type of time-related elements in the first emergency material reserve and the element replacement quantity corresponding to the element quantity are larger than the element replacement quantity when electric power equipment fails is confirmed, namely, when the first emergency material reserve does not meet the event-related element type information and the event-related element quantity information, the fact that the element type of time-related elements in the first emergency material reserve and the element quantity corresponding to the element quantity are required to be smaller than the element replacement quantity when the electric power equipment fails is confirmed, and emergency material reserve can be timely scheduled according to the emergency material reserve, and accordingly, emergency material reserve management can be judged.
Step S700: and if the first emergency material reserve is not satisfied, performing allocation management on the first emergency material reserve.
Specifically, if the first emergency material reserve pool does not meet the event-related element type information and the event-related element quantity information, it is proved that the element type and the corresponding element quantity reserve quantity of the time-related element in the first emergency material reserve pool are smaller than the element replacement quantity when the power equipment fails, that is, the reserve quantity of the first emergency material reserve pool is insufficient, the current first emergency material reserve pool needs to be allocated and managed, that is, the element type and the corresponding element quantity reserve quantity of the time-related element in the first emergency material reserve pool need to be timely supplemented according to the element replacement quantity when the power equipment fails, so that the accurate management and control of the reserve and allocation of the power emergency material are realized, and the power emergency material reserve and allocation are better.
Further, as shown in fig. 2, step S300 of the present application further includes:
step S310: extracting electric power disaster characteristics of the meteorological state information to obtain disaster meteorological information, wherein the disaster meteorological information comprises disaster meteorological types and disaster meteorological duration;
Step S320: extracting environmental characteristics from the geographic environmental information to obtain environmental geological characteristics and environmental elevation characteristics;
step S330: carrying out disaster log loading by taking the environmental geological features and the environmental elevation features as scene constraint parameters to obtain electric disaster record data;
step S340: carrying out relevance analysis on the electric power disaster record data according to the disaster weather type and the disaster weather duration to obtain a fault event relevance;
step S350: grading the disaster weather type and the disaster weather duration according to the fault event association degree to acquire the disaster grade information;
step S360: and setting the disaster weather type and the disaster weather duration corresponding to the disaster grade information as the disaster type information.
Specifically, according to the weather state information and the geographical environment information of the future preset time zone obtained by the geographical coordinate parameters of the power equipment, firstly, the weather state information in the future preset time zone is extracted to obtain disaster weather information including ice disasters, high temperatures, thunder and the like, the disaster weather information also comprises different disaster weather types and disaster weather duration corresponding to different types of disaster weather, then the geographical environment information is extracted to obtain the environmental geologic features and the environmental altitude features along with the shadows, the environmental geologic features comprise basins, soil environments, plains and the like, so that whether the water accumulation, the geological hardness and the like exist at the current position of the power equipment is determined, the environmental features can be used for determining the influence of the temperature on the power equipment, further taking the obtained environmental geological features and environmental elevation features as environmental scene constraint parameters of the current power equipment, loading a disaster log, namely recording disaster parameters generated at the position of the power equipment, and correspondingly constraining the obtained environmental geological features and the obtained environmental elevation features by the scene constraint parameters to obtain corresponding power disaster record data, further carrying out relevance analysis on the power disaster record data according to the disaster weather type and the disaster weather duration, namely respectively independently measuring the disaster weather type and the disaster weather duration, leading the disaster weather type and the disaster weather duration to be subjected to normal distribution, simultaneously extracting relevance of influences of the disaster weather type and the disaster weather duration on the power equipment, thereby obtaining the relevance of fault events, and dividing disaster grades according to the disaster weather type and the disaster weather duration, wherein the disaster grades are the disaster grades corresponding to the larger the influence degree on the power equipment is, the higher the disaster grades are, the lower the disaster grades are, the disaster weather type and the disaster weather duration corresponding to the disaster grade information are finally set as disaster type information, and finally the technical effect of providing reference for allocating and managing the power emergency materials is achieved through the obtained disaster grade information and the set disaster type information.
Further, step S340 of the present application includes:
step S341: acquiring the m type disaster weather according to the disaster weather type;
step S342: taking the m type disaster weather as a quantification, taking the duration of the disaster weather as a variable, and carrying out relevance analysis on the electric power disaster record data to obtain a first subset of relevance of fault events;
step S343: taking the m type disaster weather as a variable and the duration of the disaster weather as a quantification, carrying out relevance analysis on the electric power disaster record data to obtain a second subset of the relevance of the fault event;
step S344: and adding the first subset of the fault event relevancy and the second subset of the fault event relevancy into the fault event relevancy.
Specifically, the disaster weather types can include multiple types of acid rain, storm rain, waterlogging, drought, high temperature, tropical cyclone, cold injury, freezing rain, snow disaster, hail disaster, wind injury, tornado, thunderbolt, continuous overcast and the like, so that the type of the needed disaster weather is set as m, meanwhile, the m-th type of disaster weather is correspondingly obtained, further, the m-th type of disaster weather is taken as a quantification, the continuous time of the disaster weather is taken as a variable, the power disaster record data is subjected to relevance analysis, namely the m-th type of disaster weather is input according to the power disaster record data, the continuous time of the disaster weather record data and the power failure event record data are screened, the failure event triggering frequency parameter, the failure event influence range parameter and the failure event damage element parameter contained in the power failure event record data are normalized, the failure event triggering frequency association coefficient, the failure event influence range association coefficient and the failure event damage element association coefficient are obtained, the failure event trigger frequency association coefficient, the failure event influence range association coefficient and the failure event damage element association coefficient are correspondingly obtained, the m-th type of the disaster weather is correspondingly set and weighted, the continuous time of the disaster weather duration is taken as a variable, the power disaster weather duration is correspondingly, the average value is calculated, the result is calculated, and the failure duration is finally is calculated, and the result is obtained.
And then, taking the m type disaster weather as a variable and taking the duration of the disaster weather as a quantity, carrying out relevance analysis on the power disaster record data to obtain a second subset of the relevance of the fault event, wherein the process of obtaining the second subset of the relevance of the fault event is the same as that of the first subset of the relevance of the fault event, and the obtained first subset of the relevance of the fault event and the obtained second subset of the relevance of the fault event are added into the relevance of the fault event finally without redundant description so as to ensure the high efficiency when the power emergency materials are allocated and managed.
Further, step S341 of the present application includes:
step S3421: inputting the m type disaster weather into the power disaster record data, and screening disaster weather duration record data and power failure event record data, wherein the power failure event record data comprises a failure event trigger frequency parameter, a failure event influence range parameter and a failure event damage element parameter;
step S3422: normalizing the fault event triggering frequency parameter, the fault event influence range parameter and the fault event damage element parameter to obtain a first association coefficient, a second association coefficient and a third association coefficient;
Step S3423: setting a first weight for the first association coefficient, a second weight for the second association coefficient, and a third weight for the third association coefficient;
step S3424: summing the first association coefficient, the second association coefficient and the third association coefficient according to the first weight, the second weight and the third weight to obtain an initial association degree set;
step S3425: performing cluster analysis on the initial association degree set according to the disaster weather duration record data to obtain a plurality of groups of association degree calculation results;
step S3426: and traversing the multiple groups of relevance calculation results to perform mean value calculation, and obtaining the first subset of the relevance of the fault event.
Specifically, the acquired m-th type disaster weather is input into electric power disaster record data, meanwhile, disaster weather duration record data and electric power failure event record data are screened, wherein the electric power failure event record data refer to that failure records of electric power equipment at different positions are corresponding different failure events, the electric power failure event record data comprise failure event triggering frequency parameters, failure event influence range parameters and failure event damage element parameters, further, normalization processing is carried out on the failure event triggering frequency parameters, the failure event influence range parameters and the failure event damage element parameters, so that absolute values of physical system numerical values of the failure event triggering frequency parameters, the failure event influence range parameters and the failure event damage element parameters become relative value relations, the purposes of simplifying calculation and reducing the numerical values are achieved, a first association coefficient, a second association coefficient and a third association coefficient corresponding to the failure event triggering frequency parameters, the failure event influence range parameters and the failure event damage element parameters are obtained, the first association coefficient, the second association coefficient is set with a third weight, the third association coefficient is set, the first association coefficient is further set with the first association coefficient, the second association coefficient is set with the third association coefficient, the first association coefficient is further set with the first association coefficient is larger than the first association coefficient, the first association coefficient is further obtained, the first association coefficient is further clustered according to the set with the corresponding relation coefficient is larger than the initial association coefficient, the initial association coefficient is obtained, and the cluster value is further analyzed according to the initial association coefficient is obtained, the clustering analysis is to group the initial association degree sets based on the disaster weather duration record data, divide the initial association degree sets into a plurality of classes composed of similar association degrees, integrate the association degree calculation results of each group and obtain a plurality of groups of association degree calculation results, access and traverse the association degree calculation results of each group in the plurality of groups of association degree calculation results finally, then perform mean value calculation, namely add and divide the association degree calculation results of each group by the number of groups, obtain a first subset of the association degree of the fault event on the basis, and finally achieve the technical effect of allocating and managing the electric emergency materials.
Further, step S350 of the present application includes:
step S351: acquiring a fault event association threshold;
step S352: inputting the disaster weather type and the disaster weather duration into the fault event association degree to extract fault events meeting the fault event association degree threshold, and obtaining the number of fault events meeting a threshold and the sum of the fault event association degrees meeting the threshold;
step S353: and grading the disaster weather type and the disaster weather duration according to the sum of the number of the fault events meeting the threshold and the association degree of the fault events meeting the threshold, and obtaining the disaster grade information.
Specifically, relevant technicians set a fault event association degree threshold according to the fault event and the disaster weather type and the disaster weather duration of the power equipment, further, the disaster weather type and the disaster weather duration are input into the preset fault event association degree to uniformly extract the fault events meeting the fault event association degree threshold, so that the total sum of the number of the fault events meeting the fault event association degree threshold and the fault event association degree meeting the fault event association degree threshold is obtained, disaster grades corresponding to the number of different fault events and the size of the different fault event association degrees are further set in advance, the disaster weather type and the disaster weather duration are correspondingly graded, and finally, the graded disaster grade information is obtained, so that the technical effect of providing important basis for realizing the allocation management of electric emergency materials in the later period is achieved.
Further, as shown in fig. 3, step S400 of the present application further includes:
step S410: acquiring a type of a fault event meeting a threshold value and a degree of association of the fault event meeting the threshold value;
step S420: and carrying out serialization adjustment on the fault event type meeting the threshold according to the relevance of the fault event meeting the threshold, and obtaining the fault event prediction result.
Specifically, a fault threshold is correspondingly set for the running state of the power equipment, the fault threshold is preset by related technicians according to fault parameter data of the power equipment, if the running state of the power equipment is in the threshold, the current power equipment is judged to be in the fault state, a value when the running state of the power equipment approaches to the threshold is set as a dangerous interval, the fault event type conforming to the threshold and the correlation degree of the fault event conforming to the threshold are further acquired, the fault event type conforming to the threshold is the correlation degree of the fault event, the disaster type and the disaster level of the current power equipment in the fault threshold, the correlation degree of the fault event conforming to the threshold is further subjected to sequential adjustment by the correlation degree of the fault event conforming to the threshold, namely the correlation degree acquired from large to small, and finally the fault event prediction result is correspondingly acquired, so that the technical effect of allocating and managing the power emergency materials is achieved.
Further, as shown in fig. 4, step S500 of the present application further includes:
step S510: traversing the fault event prediction result, and collecting first maintenance record data, wherein the first maintenance record data comprises damage element type record data and damage element number record data;
step S520: acquiring the number of triggering records of the type of the broken element according to the type record data of the broken element;
step S530: according to the number of the triggering record of the type of the broken element and the number of the first maintenance record data, calculating the supporting degree of the type of the broken element;
step S540: and when the support degree of the broken element type meets a support degree threshold, adding the broken element type record data and the broken element quantity record data into the event-related element type information and the event-related element quantity information.
Specifically, traversing the fault event prediction result, namely performing node access on each fault event in the fault event prediction result, so as to acquire fault events of corresponding types, wherein the fault positions, the fault quantity and the acquired maintenance records of the power equipment are used as first maintenance record data, the first maintenance record data comprise damage element type record data and damage element quantity record data, further correspondingly acquiring the triggering times of the damage element types in the power equipment according to the damage element type record data, summarizing and integrating the triggering times to obtain the number of damage element type trigger record bars, calculating the damage element type support according to the number of damage element type trigger record bars and the first maintenance record data bar, namely dividing the number of damage element type trigger record bars by the number of damage element type trigger record bars, further, when the damage element type support degree meets a support degree threshold, presetting the support degree threshold by related technicians according to the data parameters of the damage element type support degree in the power equipment, finally adding the damage element type record data and the damage element quantity record data into the related element type information and emergency element type information, and finally performing adjustment value adjustment to realize final adjustment of the power management, thereby realizing adjustment of the final material.
Example two
Based on the same inventive concept as the precise storage and allocation management method of electric power emergency materials in the foregoing embodiments, as shown in fig. 5, the present application provides a precise storage and allocation management system of electric power emergency materials, the system includes:
the system comprises a basic information acquisition module 1, wherein the information acquisition module 1 is used for acquiring basic information of power equipment, and the basic information of the power equipment comprises operation state parameters of the power equipment and geographic coordinate parameters of the power equipment;
the information acquisition module 2 is used for acquiring weather state information and geographical environment information of a future preset time zone according to the geographical coordinate parameters of the power equipment;
the disaster analysis module 3 is used for performing disaster analysis according to the meteorological state information and the geographic environment information to generate disaster type information and disaster grade information;
the fault prediction module 4 is used for performing fault prediction based on the equipment running state parameters according to the disaster type information and the disaster grade information, and generating a fault event prediction result;
the matching module 5 is used for matching event-related element type information and event-related element quantity information according to the fault event prediction result;
The judging module 6 is used for judging whether the first emergency material reserve pool meets the event-related element type information and the event-related element quantity information or not;
and the management module 7 is used for allocating and managing the first emergency material reserve if the first emergency material reserve is not met.
Further, the system further comprises:
the disaster feature extraction module is used for carrying out electric power disaster feature extraction on the meteorological state information to obtain disaster meteorological information, wherein the disaster meteorological information comprises a disaster meteorological type and a disaster meteorological duration;
the environment feature extraction module is used for extracting environment features of the geographic environment information to obtain environment geological features and environment elevation features;
the disaster log loading module is used for loading the disaster log by taking the environmental geological features and the environmental elevation features as scene constraint parameters to acquire electric disaster record data;
the correlation analysis module is used for carrying out correlation analysis on the power disaster record data according to the disaster weather type and the disaster weather duration to obtain a fault event correlation degree;
The first grading module is used for grading the disaster weather type and the disaster weather duration according to the fault event association degree to acquire the disaster grade information;
the corresponding module is used for setting the disaster weather type and the disaster weather duration corresponding to the disaster grade information as the disaster type information.
Further, the system further comprises:
the disaster type acquisition module is used for acquiring the m type disaster weather according to the disaster weather type;
the first relevance analysis module is used for carrying out relevance analysis on the power disaster record data by taking the m type disaster weather as a quantification and the duration of the disaster weather as a variable to obtain a first subset of the relevance of the fault event;
the second relevance analysis module is used for carrying out relevance analysis on the power disaster record data by taking the m type disaster weather as a variable and taking the duration of the disaster weather as a quantification to obtain a second subset of the relevance of the fault event;
the adding module is used for adding the first subset of the fault event association degree and the second subset of the fault event association degree into the fault event association degree.
Further, the system further comprises:
the input module is used for inputting the m type disaster weather into the power disaster record data, screening disaster weather duration record data and power failure event record data, wherein the power failure event record data comprises failure event trigger frequency parameters, failure event influence range parameters and failure event damage element parameters;
the normalization processing module is used for carrying out normalization processing on the fault event triggering frequency parameter, the fault event influence range parameter and the fault event damage element parameter to obtain a first association coefficient, a second association coefficient and a third association coefficient;
the weight setting module is used for setting a first weight for the first association coefficient, a second weight for the second association coefficient and a third weight for the third association coefficient;
the summing module is used for summing the first association coefficient, the second association coefficient and the third association coefficient according to the first weight, the second weight and the third weight to obtain an initial association degree set;
The cluster analysis module is used for carrying out cluster analysis on the initial association degree set according to the disaster weather duration record data to obtain a plurality of groups of association degree calculation results;
and the average calculation module is used for traversing the multiple groups of relevance calculation results to perform average calculation and acquire the first subset of the relevance of the fault event.
Further, the system further comprises:
the association degree threshold value acquisition module is used for acquiring the association degree threshold value of the fault event;
the extraction module is used for inputting the disaster weather type and the disaster weather duration into the fault event association degree to extract fault events meeting the fault event association degree threshold value, and obtaining the number of fault events meeting the threshold value and the sum of the fault event association degrees meeting the threshold value;
and the second grading module is used for grading the disaster weather type and the disaster weather duration according to the sum of the number of the fault events meeting the threshold and the association degree of the fault events meeting the threshold, and acquiring the disaster grade information.
Further, the system further comprises:
the association degree module is used for acquiring the types of fault events meeting the threshold and the association degree of the fault events meeting the threshold;
And the serialization adjustment module is used for carrying out serialization adjustment on the type of the fault event conforming to the threshold according to the correlation degree of the fault event conforming to the threshold, and obtaining the prediction result of the fault event.
Further, the system further comprises:
the record data acquisition module is used for traversing the fault event prediction result and acquiring first maintenance record data, wherein the first maintenance record data comprises damage element type record data and damage element number record data;
the record number acquisition module is used for acquiring the trigger record number of the type of the broken element according to the record data of the type of the broken element;
the calculation module is used for calculating the support degree of the type of the broken element according to the number of the triggering records of the type of the broken element and the number of the first maintenance records;
and the second adding module is used for adding the broken element type record data and the broken element quantity record data into the event-related element type information and the event-related element quantity information when the broken element type support degree meets a support degree threshold value.
Through the foregoing detailed description of the method for accurately storing and allocating and managing electric power emergency materials, those skilled in the art can clearly know the method and the system for accurately storing and allocating and managing electric power emergency materials in the embodiment, and for the device disclosed in the embodiment, the description is relatively simple because the device corresponds to the method disclosed in the embodiment, and relevant places refer to the description of the method section.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (8)
1. The utility model provides a accurate deposit and transfer management method of emergent material of electric power which characterized in that includes:
acquiring basic information of the power equipment, wherein the basic information of the power equipment comprises operation state parameters of the power equipment and geographic coordinate parameters of the power equipment;
Acquiring weather state information and geographical environment information of a future preset time zone according to the geographical coordinate parameters of the power equipment;
performing disaster analysis according to the meteorological state information and the geographic environment information to generate disaster type information and disaster grade information;
according to the disaster type information and the disaster grade information, performing fault prediction based on the equipment running state parameters, and generating a fault event prediction result;
matching event-related element type information and event-related element quantity information according to the fault event prediction result;
judging whether a first emergency material reserve library meets the event-related element type information and the event-related element quantity information;
and if the first emergency material reserve is not satisfied, performing allocation management on the first emergency material reserve.
2. The method of claim 1, wherein the performing disaster analysis based on the weather status information and the geographical environment information to generate disaster type information and disaster level information comprises:
extracting electric power disaster characteristics of the meteorological state information to obtain disaster meteorological information, wherein the disaster meteorological information comprises disaster meteorological types and disaster meteorological duration;
Extracting environmental characteristics from the geographic environmental information to obtain environmental geological characteristics and environmental elevation characteristics;
carrying out disaster log loading by taking the environmental geological features and the environmental elevation features as scene constraint parameters to obtain electric disaster record data;
carrying out relevance analysis on the electric power disaster record data according to the disaster weather type and the disaster weather duration to obtain a fault event relevance;
grading the disaster weather type and the disaster weather duration according to the fault event association degree to acquire the disaster grade information;
and setting the disaster weather type and the disaster weather duration corresponding to the disaster grade information as the disaster type information.
3. The method of claim 2, wherein said performing a correlation analysis on said power disaster record data based on said disaster weather type and said disaster weather duration to obtain a fault event correlation comprises:
acquiring the m type disaster weather according to the disaster weather type;
taking the m type disaster weather as a quantification, taking the duration of the disaster weather as a variable, and carrying out relevance analysis on the electric power disaster record data to obtain a first subset of relevance of fault events;
Taking the m type disaster weather as a variable and the duration of the disaster weather as a quantification, carrying out relevance analysis on the electric power disaster record data to obtain a second subset of the relevance of the fault event;
and adding the first subset of the fault event relevancy and the second subset of the fault event relevancy into the fault event relevancy.
4. The method of claim 3, wherein said correlating the power disaster record data with the m-th type disaster weather as a quantification and the disaster weather duration as a variable to obtain a first subset of failure event correlations comprises:
inputting the m type disaster weather into the power disaster record data, and screening disaster weather duration record data and power failure event record data, wherein the power failure event record data comprises a failure event trigger frequency parameter, a failure event influence range parameter and a failure event damage element parameter;
normalizing the fault event triggering frequency parameter, the fault event influence range parameter and the fault event damage element parameter to obtain a first association coefficient, a second association coefficient and a third association coefficient;
Setting a first weight for the first association coefficient, a second weight for the second association coefficient, and a third weight for the third association coefficient;
summing the first association coefficient, the second association coefficient and the third association coefficient according to the first weight, the second weight and the third weight to obtain an initial association degree set;
performing cluster analysis on the initial association degree set according to the disaster weather duration record data to obtain a plurality of groups of association degree calculation results;
and traversing the multiple groups of relevance calculation results to perform mean value calculation, and obtaining the first subset of the relevance of the fault event.
5. The method of claim 2, wherein the grading the disaster weather type and the disaster weather duration according to the fault event correlation degree, obtaining the disaster grade information, comprises:
acquiring a fault event association threshold;
inputting the disaster weather type and the disaster weather duration into the fault event association degree to extract fault events meeting the fault event association degree threshold, and obtaining the number of fault events meeting a threshold and the sum of the fault event association degrees meeting the threshold;
And grading the disaster weather type and the disaster weather duration according to the sum of the number of the fault events meeting the threshold and the association degree of the fault events meeting the threshold, and obtaining the disaster grade information.
6. The method of claim 5, wherein said performing a fault prediction based on said equipment operational status parameters based on said disaster type information and said disaster level information, generating a fault event prediction result, comprises:
acquiring a type of a fault event meeting a threshold value and a degree of association of the fault event meeting the threshold value;
and carrying out serialization adjustment on the fault event type meeting the threshold according to the relevance of the fault event meeting the threshold, and obtaining the fault event prediction result.
7. The method of claim 1, wherein said matching event-related element type information with event-related element number information based on said failure event prediction result comprises:
traversing the fault event prediction result, and collecting first maintenance record data, wherein the first maintenance record data comprises damage element type record data and damage element number record data;
acquiring the number of triggering records of the type of the broken element according to the type record data of the broken element;
According to the number of the triggering record of the type of the broken element and the number of the first maintenance record data, calculating the supporting degree of the type of the broken element;
and when the support degree of the broken element type meets a support degree threshold, adding the broken element type record data and the broken element quantity record data into the event-related element type information and the event-related element quantity information.
8. An accurate reserve and transfer management system of emergent goods and materials of electric power, characterized in that includes:
the system comprises a basic information acquisition module, a control module and a control module, wherein the information acquisition module is used for acquiring basic information of the power equipment, and the basic information of the power equipment comprises operation state parameters of the power equipment and geographic coordinate parameters of the power equipment;
the information acquisition module is used for acquiring weather state information and geographic environment information of a future preset time zone according to the geographic coordinate parameters of the power equipment;
the disaster analysis module is used for carrying out disaster analysis according to the meteorological state information and the geographic environment information to generate disaster type information and disaster grade information;
the fault prediction module is used for performing fault prediction based on the equipment running state parameters according to the disaster type information and the disaster grade information to generate a fault event prediction result;
The matching module is used for matching event-related element type information and event-related element quantity information according to the fault event prediction result;
the judging module is used for judging whether the first emergency material reserve library meets the event-related element type information and the event-related element quantity information;
and the management module is used for allocating and managing the first emergency material reserve warehouse if the first emergency material reserve warehouse is not satisfied.
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