CN117131990A - Power grid infrastructure information management method and device, electronic equipment and storage medium - Google Patents
Power grid infrastructure information management method and device, electronic equipment and storage medium Download PDFInfo
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Abstract
The invention discloses a method and a device for managing power grid infrastructure information, electronic equipment and a storage medium. The method comprises the following steps: acquiring historical grid infrastructure information, and screening the historical grid infrastructure information to obtain a screening result corresponding to the historical grid infrastructure information; analyzing and processing the data screening result corresponding to the historical grid infrastructure information to obtain a data analysis result corresponding to the historical grid infrastructure information; training the neural network model according to the data analysis result corresponding to the historical power grid infrastructure information to obtain a power grid infrastructure prediction model; and acquiring real-time power grid infrastructure information, and inputting the real-time power grid infrastructure information into a power grid infrastructure prediction model to obtain a infrastructure prediction result corresponding to the real-time power grid infrastructure information. According to the technical scheme, accurate and reliable training sample data is obtained by screening and analyzing the power grid infrastructure information, model training is further carried out, prediction is carried out, and accurate prediction of the power grid infrastructure information is achieved.
Description
Technical Field
The present invention relates to the field of power grid information management technologies, and in particular, to a method, an apparatus, an electronic device, and a storage medium for managing power grid infrastructure information.
Background
With the rapid development of the power industry, smart grids are becoming the main trend of future power development as the key research direction of the current power industry.
In the process of implementing the present invention, the inventor finds that at least the following technical problems exist in the prior art: the existing power grid infrastructure information management method only analyzes and displays the existing power grid infrastructure information, and cannot predict future power grid infrastructure information, so that a user cannot manage and control the power grid infrastructure in advance, and the safety of power grid infrastructure management is reduced.
Disclosure of Invention
The invention provides a power grid infrastructure information management method, a device, electronic equipment and a storage medium, so as to realize the prediction of the power grid infrastructure information, enable a user to manage and control the power grid infrastructure according to the predicted power grid infrastructure information, and improve the safety of power grid infrastructure management.
According to an aspect of the present invention, there is provided a power grid infrastructure information management method, including:
acquiring historical grid infrastructure information, and screening the historical grid infrastructure information to obtain a screening result corresponding to the historical grid infrastructure information;
analyzing and processing the data screening result corresponding to the historical grid infrastructure information to obtain a data analysis result corresponding to the historical grid infrastructure information;
training a neural network model according to a data analysis result corresponding to the historical power grid infrastructure information to obtain a power grid infrastructure prediction model;
and acquiring real-time power grid infrastructure information, and inputting the real-time power grid infrastructure information into the power grid infrastructure prediction model to obtain a infrastructure prediction result corresponding to the real-time power grid infrastructure information.
According to another aspect of the present invention, there is provided a power grid infrastructure information management apparatus, comprising:
the system comprises a basic construction information screening module, a power grid information processing module and a power grid information processing module, wherein the basic construction information screening module is used for acquiring historical power grid basic construction information and screening the historical power grid basic construction information to obtain a screening result corresponding to the historical power grid basic construction information;
the construction information analysis module is used for analyzing and processing the data screening results corresponding to the historical power grid construction information to obtain data analysis results corresponding to the historical power grid construction information;
the building model training module is used for training the neural network model according to the data analysis result corresponding to the historical power grid building information to obtain a power grid building prediction model;
the system comprises a foundation construction result prediction module, a power grid construction model and a power grid construction model, wherein the foundation construction result prediction module is used for acquiring real-time power grid foundation construction information, inputting the real-time power grid foundation construction information into the power grid foundation construction prediction model and obtaining a foundation construction prediction result corresponding to the real-time power grid foundation construction information.
According to another aspect of the present invention, there is provided an electronic apparatus including:
at least one processor;
and a memory communicatively coupled to the at least one processor;
the memory stores a computer program executable by the at least one processor, so that the at least one processor can execute the grid infrastructure information management method according to any embodiment of the invention.
According to another aspect of the present invention, there is provided a computer readable storage medium storing computer instructions for causing a processor to implement the grid-infrastructure information management method according to any of the embodiments of the present invention when executed.
According to the technical scheme, accurate and reliable training sample data are obtained through screening and analysis processing of the historical grid infrastructure information, model training is further conducted, prediction is conducted, accurate prediction of the real-time grid infrastructure information is achieved, a user can manage and control the grid infrastructure according to the infrastructure prediction result corresponding to the real-time grid infrastructure information, and safety of grid infrastructure management is improved.
It should be understood that the description in this section is not intended to identify key or critical features of the embodiments of the invention or to delineate the scope of the invention. Other features of the present invention will become apparent from the description that follows.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic structural diagram of a power grid infrastructure information management system according to an embodiment of the present invention;
fig. 2 is a flowchart of a method for managing information of a power grid infrastructure according to a first embodiment of the present invention;
fig. 3 is a flowchart of a method for managing information of a power grid infrastructure according to a second embodiment of the present invention;
fig. 4 is a flowchart of a method for managing information of a power grid infrastructure according to a third embodiment of the present invention;
fig. 5 is a schematic structural diagram of a power grid infrastructure information management device according to a fourth embodiment of the present invention;
fig. 6 is a schematic structural diagram of an electronic device implementing the method for managing grid-infrastructure information according to an embodiment of the present invention.
Detailed Description
In order that those skilled in the art will better understand the present invention, a technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, shall fall within the scope of the present invention.
It should be noted that the terms "first," "second," and the like in the description and the claims of the present invention and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the invention described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
Before describing the specific embodiment, an application scenario of the grid infrastructure information management method is described. Fig. 1 is a schematic structural diagram of a power grid infrastructure information management system according to an embodiment of the present invention, specifically, a power grid infrastructure information management method may be executed by the power grid infrastructure information management system, where the power grid infrastructure information management system includes a smart power grid integrated management center, a cloud computing platform, a cloud computing server, distributed control nodes and sensors, where the sensors are used to collect power grid infrastructure information, the distributed control nodes are respectively in communication connection with the sensors and the cloud computing server, and are used to transmit the collected power grid infrastructure information to the cloud computing server, the cloud computing server is in communication connection with the smart power grid integrated management center, and the cloud computing platform is respectively connected with the smart power grid integrated management center and the cloud computing server.
Example 1
Fig. 2 is a flowchart of a method for managing grid-infrastructure information according to a first embodiment of the present invention, where the method may be performed by a grid-infrastructure information management device, and the grid-infrastructure information management device may be implemented in hardware and/or software, and the grid-infrastructure information management device may be configured in a cloud computing platform. As shown in fig. 2, the method includes:
s110, acquiring historical grid infrastructure information, and screening the historical grid infrastructure information to obtain a screening result corresponding to the historical grid infrastructure information.
In this embodiment, the historical grid infrastructure information refers to grid infrastructure information collected in the past. Optionally, the historical grid infrastructure information includes one or more of the following: the method comprises the steps of resistance of grid infrastructure equipment, reactance of the grid infrastructure equipment, conductivity of the grid infrastructure equipment, susceptance of the grid infrastructure equipment, short-circuit loss of the grid infrastructure equipment, short-circuit voltage percentage of the grid infrastructure equipment, no-load loss of the grid infrastructure equipment and no-load current percentage of the grid infrastructure equipment. The power grid infrastructure equipment refers to power grid equipment which completes infrastructure or is being built.
Specifically, historical grid infrastructure information can be read from a preset data storage path of the electronic device; or acquiring historical grid infrastructure information through sensors connected with the distributed control nodes.
In some alternative embodiments, the screening of the historical grid infrastructure information includes one or more of the following: processing the historical grid infrastructure information to remove abnormal data; processing the data filling the gap of the historical grid infrastructure information; the historical grid infrastructure information is subjected to data deduplication treatment, and a specific screening mode is not limited herein.
And S120, analyzing and processing the data screening result corresponding to the historical grid infrastructure information to obtain a data analysis result corresponding to the historical grid infrastructure information.
In some alternative embodiments, the analyzing and processing the data screening result corresponding to the historical grid infrastructure information includes one or more of the following steps: performing cluster analysis on data screening results corresponding to the historical grid infrastructure information; carrying out correlation analysis on data screening results corresponding to historical grid infrastructure information; and carrying out anomaly detection on the data screening result corresponding to the historical grid infrastructure information, wherein the specific analysis mode is not limited.
It is to be noted that, through screening and analysis processing of historical grid infrastructure information, accurate and reliable training sample data is obtained, and a reliable data base is laid for model training.
And S130, training the neural network model according to the data analysis result corresponding to the historical grid infrastructure information to obtain a grid infrastructure prediction model.
In this embodiment, the neural network model may be a neural network model of any network architecture, such as a convolutional neural network, a long-term and short-term memory artificial neural network, and the like, which is not limited herein. Specifically, after the data analysis result corresponding to the historical grid infrastructure information is obtained, a training set and a testing set can be generated according to the data analysis result corresponding to the historical grid infrastructure information for model training and testing, so that a trained grid infrastructure prediction model is obtained.
In some alternative embodiments, training the neural network model according to the data analysis result corresponding to the historical grid infrastructure information to obtain a grid infrastructure prediction model, including: inputting the data analysis results corresponding to the historical grid construction information into a neural network model, and performing feature extraction on the data analysis results corresponding to the historical grid construction information by the neural network model to obtain feature information corresponding to the data analysis results; and determining a power grid infrastructure prediction result based on the characteristic information corresponding to the data analysis result, determining loss between the power grid infrastructure prediction result and the data analysis result label, and adjusting parameters of the neural network model based on the loss between the power grid infrastructure prediction result and the data analysis result label until the model stopping training requirement is met, so as to obtain a trained power grid infrastructure prediction model.
In some alternative embodiments, training a decision tree or a support vector machine according to the data analysis result corresponding to the historical grid infrastructure information to obtain a grid infrastructure prediction model
And S140, acquiring real-time power grid infrastructure information, and inputting the real-time power grid infrastructure information into the power grid infrastructure prediction model to obtain a infrastructure prediction result corresponding to the real-time power grid infrastructure information.
In this embodiment, the prediction result of the infrastructure may be a failure rate, a power generation amount, or a power load of the power grid device, in other words, the trained power grid infrastructure prediction model may be used to predict the failure rate, the power generation amount, or the power load of the power grid device according to real-time power grid infrastructure information.
According to the technical scheme, accurate and reliable training sample data are obtained through screening and analysis processing of the historical grid infrastructure information, model training is further conducted, prediction is conducted, accurate prediction of the real-time grid infrastructure information is achieved, a user can manage and control the grid infrastructure according to the infrastructure prediction result corresponding to the real-time grid infrastructure information, and safety of grid infrastructure management is improved.
Example two
Fig. 3 is a flowchart of a method for managing power grid infrastructure information according to a second embodiment of the present invention, where the method of this embodiment may be combined with each of the alternatives in the method for managing power grid infrastructure information provided in the foregoing embodiment. The power grid infrastructure information management method provided by the embodiment further refines the screening processing step and the analysis processing step.
As shown in fig. 3, the method includes:
s210, acquiring historical grid infrastructure information, and performing abnormal data removal processing, vacancy filling data processing and data deduplication processing on the historical grid infrastructure information to obtain screening results corresponding to the historical grid infrastructure information.
In this embodiment, by performing three processing operations of removing abnormal data processing, filling up blank data processing and performing data deduplication processing on the historical grid infrastructure information, the quality of the historical grid infrastructure information is improved, so that the historical grid infrastructure information is normalized and standardized, and statistical analysis is performed on the historical grid infrastructure information.
S220, performing cluster analysis, correlation analysis and anomaly detection on the data screening result corresponding to the historical grid infrastructure information to obtain a data analysis result corresponding to the historical grid infrastructure information.
In this embodiment, three analysis operations, namely cluster analysis, correlation analysis and anomaly detection, are performed on the data screening result corresponding to the historical grid infrastructure information, so that data mining on the historical grid infrastructure information is realized, and rules among the historical grid infrastructure information are found.
And S230, training the neural network model according to the data analysis result corresponding to the historical grid infrastructure information to obtain a grid infrastructure prediction model.
S240, acquiring real-time power grid infrastructure information, and inputting the real-time power grid infrastructure information into the power grid infrastructure prediction model to obtain a infrastructure prediction result corresponding to the real-time power grid infrastructure information.
According to the technical scheme, the quality of the historical grid infrastructure information is improved by screening the historical grid infrastructure information, so that the historical grid infrastructure information is normalized and standardized, and statistical analysis is conducted on the historical grid infrastructure information; and further, the screened historical grid infrastructure information is analyzed, so that the data mining of the historical grid infrastructure information is realized, and the rules among the historical grid infrastructure information are found.
Example III
Fig. 4 is a flowchart of a method for managing power grid infrastructure information according to a third embodiment of the present invention, where the method of this embodiment may be combined with each of the alternatives in the method for managing power grid infrastructure information provided in the foregoing embodiment. The power grid infrastructure information management method provided by the embodiment is further optimized. Optionally, after obtaining the infrastructure prediction result corresponding to the real-time power grid infrastructure information, the method further includes: the construction prediction result corresponding to the real-time power grid construction information is differenced with the actual construction result, and a construction result difference value is obtained; and adjusting model parameters of the power grid infrastructure prediction model based on the infrastructure result difference value to obtain a corrected power grid infrastructure prediction model.
As shown in fig. 4, the method includes:
s310, acquiring historical grid infrastructure information, and screening the historical grid infrastructure information to obtain a screening result corresponding to the historical grid infrastructure information.
S320, analyzing and processing the data screening result corresponding to the historical grid infrastructure information to obtain a data analysis result corresponding to the historical grid infrastructure information.
And S330, training the neural network model according to the data analysis result corresponding to the historical grid infrastructure information to obtain a grid infrastructure prediction model.
The data analysis results comprise, for example, the resistance of the grid infrastructure equipment, the reactance of the grid infrastructure equipment, the conductance of the grid infrastructure equipment, the susceptance of the grid infrastructure equipment, the short-circuit loss of the grid infrastructure equipment, the short-circuit voltage percentage of the grid infrastructure equipment, the no-load loss of the grid infrastructure equipment and the no-load current percentage of the grid infrastructure equipment; and inputting the data analysis result into a long-short-period memory artificial neural network model, extracting the characteristics of the data analysis result by the long-short-period memory artificial neural network to obtain characteristic information corresponding to the data analysis result, determining the predicted power grid equipment power utilization load based on the characteristic information corresponding to the data analysis result, determining the loss between the predicted power grid equipment power utilization load and the actual power utilization load, and adjusting parameters of the long-short-period memory artificial neural network based on the loss between the predicted power grid equipment power utilization load and the actual power utilization load until the model training stopping requirement is met, so as to obtain a power grid infrastructure prediction model capable of realizing power utilization load prediction.
S340, acquiring real-time power grid infrastructure information, and inputting the real-time power grid infrastructure information into the power grid infrastructure prediction model to obtain a infrastructure prediction result corresponding to the real-time power grid infrastructure information.
And S350, the construction prediction result corresponding to the real-time power grid construction information is differenced from the actual construction result, and a construction result difference value is obtained.
And S360, adjusting model parameters of the power grid infrastructure prediction model based on the infrastructure result difference value to obtain a corrected power grid infrastructure prediction model.
The prediction result of the foundation may be a predicted electricity load of the power grid device, the actual foundation result may be an actual electricity load of the power grid device, the difference value of the foundation result is a difference value between the predicted electricity load and the actual electricity load, and after the difference value between the predicted electricity load and the actual electricity load is obtained, model parameters of a power grid foundation prediction model may be adjusted according to the difference value between the predicted electricity load and the actual electricity load, so as to improve prediction accuracy of the power grid foundation prediction model.
According to the technical scheme, the basic construction result corresponding to the real-time power grid basic construction information is differenced from the actual basic construction result to obtain the basic construction result difference value, and further, the model parameters of the power grid basic construction prediction model are corrected according to the basic construction result difference value, so that the prediction precision of the power grid basic construction prediction model is improved.
Example IV
Fig. 5 is a schematic structural diagram of a power grid infrastructure information management device according to a fourth embodiment of the present invention. As shown in fig. 5, the apparatus includes:
the building information screening module 410 is configured to obtain historical grid building information, and perform screening processing on the historical grid building information to obtain a screening result corresponding to the historical grid building information;
the infrastructure information analysis module 420 is configured to analyze and process a data screening result corresponding to the historical grid infrastructure information to obtain a data analysis result corresponding to the historical grid infrastructure information;
the infrastructure model training module 430 is configured to train the neural network model according to the data analysis result corresponding to the historical grid infrastructure information, so as to obtain a grid infrastructure prediction model;
the infrastructure result prediction module 440 is configured to obtain real-time power grid infrastructure information, input the real-time power grid infrastructure information to the power grid infrastructure prediction model, and obtain a infrastructure prediction result corresponding to the real-time power grid infrastructure information.
According to the technical scheme, accurate and reliable training sample data are obtained through screening and analysis processing of the historical grid infrastructure information, model training is further conducted, prediction is conducted, accurate prediction of the real-time grid infrastructure information is achieved, a user can manage and control the grid infrastructure according to the infrastructure prediction result corresponding to the real-time grid infrastructure information, and safety of grid infrastructure management is improved.
In some alternative embodiments, the infrastructure information screening module 410 is further configured to:
reading historical grid infrastructure information from a preset data storage path;
or acquiring historical grid infrastructure information through sensors connected with the distributed control nodes.
In some alternative embodiments, the historical grid infrastructure information includes one or more of the following:
the method comprises the steps of resistance of grid infrastructure equipment, reactance of the grid infrastructure equipment, conductivity of the grid infrastructure equipment, susceptance of the grid infrastructure equipment, short-circuit loss of the grid infrastructure equipment, short-circuit voltage percentage of the grid infrastructure equipment, no-load loss of the grid infrastructure equipment and no-load current percentage of the grid infrastructure equipment.
In some alternative embodiments, the screening the historical grid infrastructure information includes one or more of:
processing the historical grid infrastructure information to remove abnormal data;
processing the data filling the gap of the historical grid infrastructure information;
and carrying out data deduplication processing on the historical grid infrastructure information.
In some optional embodiments, the analyzing the data screening result corresponding to the historical grid infrastructure information includes one or more of the following steps:
performing cluster analysis on data screening results corresponding to the historical grid infrastructure information;
carrying out correlation analysis on data screening results corresponding to the historical grid infrastructure information;
and carrying out anomaly detection on the data screening result corresponding to the historical grid infrastructure information.
In some alternative embodiments, the infrastructure model training module 430 may be further specifically configured to:
inputting the data analysis result corresponding to the historical grid construction information into a neural network model, and performing feature extraction on the data analysis result corresponding to the historical grid construction information by the neural network model to obtain feature information corresponding to the data analysis result;
and determining a power grid infrastructure prediction result based on the characteristic information corresponding to the data analysis result, determining loss between the power grid infrastructure prediction result and the data analysis result label, and adjusting parameters of a neural network model based on the loss between the power grid infrastructure prediction result and the data analysis result label until the model stopping training requirement is met, so as to obtain a trained power grid infrastructure prediction model.
In some alternative embodiments, the grid infrastructure information management apparatus further includes:
the foundation construction result difference value determining module is used for making a difference between a foundation construction prediction result corresponding to the real-time power grid foundation construction information and an actual foundation construction result to obtain a foundation construction result difference value;
and the foundation prediction model correction module is used for adjusting the model parameters of the power grid foundation prediction model based on the foundation result difference value to obtain a corrected power grid foundation prediction model.
The power grid infrastructure information management device provided by the embodiment of the invention can execute the power grid infrastructure information management method provided by any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the execution method.
Example five
Fig. 6 shows a schematic diagram of the structure of an electronic device 10 that may be used to implement an embodiment of the invention. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. Electronic equipment may also represent various forms of mobile devices, such as personal digital assistants, cellular telephones, smartphones, wearable devices (e.g., helmets, eyeglasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the inventions described and/or claimed herein.
As shown in fig. 6, the electronic device 10 includes at least one processor 11, and a memory, such as a Read Only Memory (ROM) 12, a Random Access Memory (RAM) 13, etc., communicatively connected to the at least one processor 11, in which the memory stores a computer program executable by the at least one processor, and the processor 11 may perform various appropriate actions and processes according to the computer program stored in the Read Only Memory (ROM) 12 or the computer program loaded from the storage unit 18 into the Random Access Memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 may also be stored. The processor 11, the ROM 12 and the RAM 13 are connected to each other via a bus 14. An I/O interface 15 is also connected to bus 14.
Various components in the electronic device 10 are connected to the I/O interface 15, including: an input unit 16 such as a keyboard, a mouse, etc.; an output unit 17 such as various types of displays, speakers, and the like; a storage unit 18 such as a magnetic disk, an optical disk, or the like; and a communication unit 19 such as a network card, modem, wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information/data with other devices via a computer network, such as the internet, and/or various telecommunication networks.
The processor 11 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various specialized Artificial Intelligence (AI) computing chips, various processors running machine learning model algorithms, digital Signal Processors (DSPs), and any suitable processor, controller, microcontroller, etc. The processor 11 performs the various methods and processes described above, such as a grid infrastructure information management method, which includes:
acquiring historical grid infrastructure information, and screening the historical grid infrastructure information to obtain a screening result corresponding to the historical grid infrastructure information;
analyzing and processing the data screening result corresponding to the historical grid infrastructure information to obtain a data analysis result corresponding to the historical grid infrastructure information;
training a neural network model according to a data analysis result corresponding to the historical power grid infrastructure information to obtain a power grid infrastructure prediction model;
and acquiring real-time power grid infrastructure information, and inputting the real-time power grid infrastructure information into the power grid infrastructure prediction model to obtain a infrastructure prediction result corresponding to the real-time power grid infrastructure information.
In some embodiments, the grid-infrastructure information management method may be implemented as a computer program tangibly embodied on a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and/or installed onto the electronic device 10 via the ROM 12 and/or the communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the grid-infrastructure information management method described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to perform the grid-infrastructure information management method in any other suitable way (e.g., by means of firmware).
Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuit systems, field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), systems On Chip (SOCs), complex Programmable Logic Devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs, the one or more computer programs may be executed and/or interpreted on a programmable system including at least one programmable processor, which may be a special purpose or general-purpose programmable processor, that may receive data and instructions from, and transmit data and instructions to, a storage system, at least one input device, and at least one output device.
A computer program for carrying out methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the computer programs, when executed by the processor, cause the functions/acts specified in the flowchart and/or block diagram block or blocks to be implemented. The computer program may execute entirely on the machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server.
In the context of the present invention, a computer-readable storage medium may be a tangible medium that can contain, or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. The computer readable storage medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. Alternatively, the computer readable storage medium may be a machine readable signal medium. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
To provide for interaction with a user, the systems and techniques described here can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) through which a user can provide input to the electronic device. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic input, speech input, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a background component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such background, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), wide Area Networks (WANs), blockchain networks, and the internet.
The computing system may include clients and servers. The client and server are typically remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, also called a cloud computing server or a cloud host, and is a host product in a cloud computing service system, so that the defects of high management difficulty and weak service expansibility in the traditional physical hosts and VPS service are overcome.
It should be appreciated that various forms of the flows shown above may be used to reorder, add, or delete steps. For example, the steps described in the present invention may be performed in parallel, sequentially, or in a different order, so long as the desired results of the technical solution of the present invention are achieved, and the present invention is not limited herein.
The above embodiments do not limit the scope of the present invention. It will be apparent to those skilled in the art that various modifications, combinations, sub-combinations and alternatives are possible, depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the scope of the present invention.
Claims (10)
1. A method for managing information of a power grid infrastructure, comprising:
acquiring historical grid infrastructure information, and screening the historical grid infrastructure information to obtain a screening result corresponding to the historical grid infrastructure information;
analyzing and processing the data screening result corresponding to the historical grid infrastructure information to obtain a data analysis result corresponding to the historical grid infrastructure information;
training a neural network model according to a data analysis result corresponding to the historical power grid infrastructure information to obtain a power grid infrastructure prediction model;
and acquiring real-time power grid infrastructure information, and inputting the real-time power grid infrastructure information into the power grid infrastructure prediction model to obtain a infrastructure prediction result corresponding to the real-time power grid infrastructure information.
2. The method of claim 1, wherein the obtaining historical grid infrastructure information comprises:
reading historical grid infrastructure information from a preset data storage path;
or acquiring historical grid infrastructure information through sensors connected with the distributed control nodes.
3. The method of claim 1 or 2, wherein the historical grid infrastructure information comprises one or more of the following:
the method comprises the steps of resistance of grid infrastructure equipment, reactance of the grid infrastructure equipment, conductivity of the grid infrastructure equipment, susceptance of the grid infrastructure equipment, short-circuit loss of the grid infrastructure equipment, short-circuit voltage percentage of the grid infrastructure equipment, no-load loss of the grid infrastructure equipment and no-load current percentage of the grid infrastructure equipment.
4. The method of claim 1, wherein the screening the historical grid infrastructure information comprises one or more of:
processing the historical grid infrastructure information to remove abnormal data;
processing the data filling the gap of the historical grid infrastructure information;
and carrying out data deduplication processing on the historical grid infrastructure information.
5. The method of claim 1, wherein the analyzing the data screening results corresponding to the historical grid-infrastructure information comprises one or more of:
performing cluster analysis on data screening results corresponding to the historical grid infrastructure information;
carrying out correlation analysis on data screening results corresponding to the historical grid infrastructure information;
and carrying out anomaly detection on the data screening result corresponding to the historical grid infrastructure information.
6. The method according to claim 1, wherein training the neural network model according to the data analysis result corresponding to the historical grid infrastructure information to obtain the grid infrastructure prediction model comprises:
inputting the data analysis result corresponding to the historical grid construction information into a neural network model, and performing feature extraction on the data analysis result corresponding to the historical grid construction information by the neural network model to obtain feature information corresponding to the data analysis result;
and determining a power grid infrastructure prediction result based on the characteristic information corresponding to the data analysis result, determining loss between the power grid infrastructure prediction result and the data analysis result label, and adjusting parameters of a neural network model based on the loss between the power grid infrastructure prediction result and the data analysis result label until the model stopping training requirement is met, so as to obtain a trained power grid infrastructure prediction model.
7. The method according to any one of claims 1-6, wherein after obtaining the infrastructure prediction result corresponding to the real-time grid infrastructure information, the method further comprises:
the construction prediction result corresponding to the real-time power grid construction information is differenced with the actual construction result, and a construction result difference value is obtained;
and adjusting model parameters of the power grid infrastructure prediction model based on the infrastructure result difference value to obtain a corrected power grid infrastructure prediction model.
8. A power grid infrastructure information management apparatus, comprising:
the system comprises a basic construction information screening module, a power grid information processing module and a power grid information processing module, wherein the basic construction information screening module is used for acquiring historical power grid basic construction information and screening the historical power grid basic construction information to obtain a screening result corresponding to the historical power grid basic construction information;
the construction information analysis module is used for analyzing and processing the data screening results corresponding to the historical power grid construction information to obtain data analysis results corresponding to the historical power grid construction information;
the building model training module is used for training the neural network model according to the data analysis result corresponding to the historical power grid building information to obtain a power grid building prediction model;
the system comprises a foundation construction result prediction module, a power grid construction model and a power grid construction model, wherein the foundation construction result prediction module is used for acquiring real-time power grid foundation construction information, inputting the real-time power grid foundation construction information into the power grid foundation construction prediction model and obtaining a foundation construction prediction result corresponding to the real-time power grid foundation construction information.
9. An electronic device, the electronic device comprising:
at least one processor;
and a memory communicatively coupled to the at least one processor;
wherein the memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the grid-infrastructure information management method of any of claims 1-7.
10. A computer readable storage medium, characterized in that the computer readable storage medium stores computer instructions for causing a processor to implement the grid infrastructure information management method of any of claims 1 to 7 when executed.
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| CN202311129729.4A CN117131990A (en) | 2023-08-31 | 2023-08-31 | Power grid infrastructure information management method and device, electronic equipment and storage medium |
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