CN-122022499-A - Electric power material supply chain risk early warning method and device based on digital mirror image

CN122022499ACN 122022499 ACN122022499 ACN 122022499ACN-122022499-A

Abstract

The invention discloses a digital mirror image-based power supply chain risk early warning method and device, which belong to the field of power supply chain management, and specifically comprise the steps of mapping WBS data of a target power engineering task into BOM data based on a power engineering knowledge graph and inquiring a risk threshold value; the supply chain system starts a material circulation operation based on BOM data, updates a digital mirror image according to the generated first logistics data, carries out risk assessment on a target business event generated in the execution process of the material circulation operation based on a risk threshold value, generates and outputs a coping strategy, starts a material transportation operation based on an execution instruction corresponding to the coping strategy, updates the digital mirror image according to the generated second logistics data, compares execution effect data corresponding to the material transportation operation with expected data corresponding to the coping strategy, and generates and outputs an early warning signal. Therefore, by implementing the invention, the accuracy of the risk early warning of the power supply chain can be improved.

Inventors

CHEN TIANMEI
YU CHENXI
YANG KAI
WANG TAO
CHEN YU
JIN YATING
HE XIAOJUN
Bao Jiangxue
MA JUN
SHEN QI
WENG HUIYING
WANG YIJIE
ZHANG GONG
YIN WEIBIN
ZHANG WEILIN
MENG XIAN
ZHANG BING
XIA HONGTAO
ZHAO XIN

Assignees

国网浙江省电力有限公司物资分公司
国网浙江浙电招标咨询有限公司
国网浙江省电力有限公司

Dates

Publication Date: 20260512
Application Date: 20260413

Claims (10)

1. The utility model provides a power supply chain risk early warning method based on digital mirror image which is characterized in that the method comprises the following steps: Acquiring WBS data of a target power engineering task, mapping the WBS data into BOM data based on a pre-constructed power engineering knowledge graph, and inquiring a risk threshold corresponding to the target power engineering task from the power engineering knowledge graph; The BOM data is issued to a supply chain system, so that the supply chain system starts a material circulation operation based on the BOM data, and a pre-constructed digital mirror image is updated according to first logistics data generated in the execution process of the material circulation operation; When a target business event occurs in the execution process of the material circulation operation is monitored, inputting the target business event and the risk threshold value into an updated digital mirror image, so that the digital mirror image carries out risk assessment on the target business event based on the risk threshold value, and generating and outputting a coping strategy according to a risk assessment result; Converting the coping strategy into an execution instruction and issuing the execution instruction to the supply chain system so that the supply chain system starts a material transportation operation based on the execution instruction and updates the digital mirror image according to second stream data generated in the execution process of the material transportation operation; and inputting the execution effect data corresponding to the material transportation operation into the updated digital mirror image so that the digital mirror image compares the execution effect data with the expected data corresponding to the coping strategy, and generating and outputting an early warning signal according to a comparison result.
2. The method for warning risk of power supply chain based on digital mirror image according to claim 1, wherein the obtaining WBS data of a target power engineering task, mapping the WBS data into BOM data based on a pre-constructed power engineering knowledge graph, and querying a risk threshold corresponding to the target power engineering task from the power engineering knowledge graph, comprises: analyzing WBS data of the target power engineering task, and identifying engineering nodes contained in the WBS data; Traversing the power engineering knowledge graph based on WBS-BOM conversion rules, inquiring engineering attribute information matched with each engineering node, and matching corresponding material demand characteristic information according to each engineering attribute information to generate BOM data step by step; and matching corresponding historical risk data from the power engineering knowledge graph according to the engineering type and the material category of the target power engineering task, and generating a risk threshold based on the historical risk data.
3. The method for warning risk of power supply chain based on digital mirror image according to claim 2, wherein before the WBS data of the target power engineering task is obtained, mapping the WBS data into BOM data based on a pre-constructed power engineering knowledge graph, and querying a risk threshold corresponding to the target power engineering task from the power engineering knowledge graph, the method further comprises: and constructing the power engineering knowledge graph, and configuring the WBS-BOM conversion rule by adopting a rule engine.
4. The method for early warning risk of a power supply chain based on digital mirroring according to claim 1, wherein the issuing the BOM data to a supply chain system to enable the supply chain system to start a material circulation operation based on the BOM data, and updating the pre-constructed digital mirroring according to first logistics data generated during the execution of the material circulation operation comprises: The BOM data is issued to the supply chain system, and the supply chain system is triggered to execute purchasing operation and warehousing operation of target materials; based on a preset updating frequency, acquiring material purchasing progress, inventory change data and material delivery state from the supply chain system through a real-time data acquisition interface as first logistics data; and synchronizing the first logistics data to the digital mirror image so as to update the virtual inventory state and the purchasing progress state of the target materials in the digital mirror image.
5. The method of claim 4, wherein before the BOM data is issued to a supply chain system to enable the supply chain system to start a material circulation operation based on the BOM data, and update the pre-constructed digital image according to first logistics data generated during execution of the material circulation operation, the method further comprises: and constructing the digital mirror image, and synchronizing the acquired real-time environment data and the acquired real-time traffic data to the digital mirror image based on the updating frequency.
6. The method for early warning risk of a power supply chain based on digital mirror image according to claim 1, wherein when it is monitored that a target business event occurs during execution of the material circulation operation, the target business event and the risk threshold are input into the updated digital mirror image, so that the digital mirror image performs risk assessment on the target business event based on the risk threshold, and generates and outputs a coping strategy according to a risk assessment result, the method comprises: identifying a target value in the target business event, comparing the target value with the risk threshold, judging that the target business event has risk if the target value is greater than or equal to the risk threshold, and generating a plurality of candidate coping strategies; And carrying out simulation deduction on the candidate coping strategies through a multi-objective optimization algorithm, comparing the simulation deduction results according to preset weights, determining coping strategies according to the comparison results, and outputting the coping strategies.
7. The method of claim 4, wherein converting the coping strategy into an execution instruction and issuing the execution instruction to the supply chain system to enable the supply chain system to start a material transportation operation based on the execution instruction, and updating the digital mirror according to second stream data generated during execution of the material transportation operation, and comprising: converting the coping strategy into an execution instruction and issuing the execution instruction to the supply chain system, and triggering the supply chain system to execute the transportation operation of the target material based on the execution instruction; based on the update frequency, collecting transportation job execution data from the supply chain system through the real-time data collection interface as second stream data; And synchronizing the second stream data to the digital mirror image so as to update the transportation state of the target materials in the digital mirror image.
8. The electric power material supply chain risk early warning device based on the digital mirror image is characterized by comprising a data mapping module, a first digital mirror image updating module, a risk assessment module, a second digital mirror image updating module and a risk early warning module; The data mapping module is used for acquiring WBS data of a target power engineering task, mapping the WBS data into BOM data based on a pre-constructed power engineering knowledge graph, and inquiring a risk threshold corresponding to the target power engineering task from the power engineering knowledge graph; the first digital mirror image updating module is used for sending the BOM data to a supply chain system, so that the supply chain system starts a material circulation operation based on the BOM data, and updates a pre-built digital mirror image according to first logistics data generated in the execution process of the material circulation operation; The risk evaluation module is used for inputting the target business event and the risk threshold value into the updated digital mirror image when the target business event occurs in the execution process of the material circulation operation, so that the digital mirror image carries out risk evaluation on the target business event based on the risk threshold value, and a coping strategy is generated and output according to a risk evaluation result; the second digital image updating module is used for converting the coping strategy into an execution instruction and issuing the execution instruction to the supply chain system so that the supply chain system starts a material transportation operation based on the execution instruction and updates the digital image according to second stream data generated in the execution process of the material transportation operation; The risk early warning module is used for inputting the execution effect data corresponding to the material transportation operation into the updated digital mirror image so that the digital mirror image compares the execution effect data with the expected data corresponding to the coping strategies, and early warning signals are generated and output according to comparison results.
9. A terminal device comprising a processor, a memory and a computer program stored in the memory and configured to be executed by the processor, the processor implementing a digital mirror-based power supply chain risk early warning method according to any one of claims 1-7 when the computer program is executed.
10. A computer readable storage medium comprising a stored computer program, wherein the computer program, when run, controls a device in which the computer readable storage medium resides to perform a digital mirror image based power supply chain risk warning method according to any one of claims 1-7.

Description

Electric power material supply chain risk early warning method and device based on digital mirror image Technical Field The invention relates to the field of power supply chain management, in particular to a power supply chain risk early warning method and device based on digital mirror images. Background In the management task of the power supply chain, the risk early warning timeliness and the decision scientificity directly determine the project progress and the power grid operation quality. The logistics links of large materials such as main transformers are prone to risks such as transportation delay, inventory shortage, abnormal performance of suppliers and the like, and once improper control is conducted, construction period delay, cost increase and even equipment damage are caused. The digital mirror image is used as a core carrier penetrating through the physical world and the digital space of the electric power material supply chain, the core function of the digital mirror image is to realize accurate early warning of risks and scientific optimization of decisions through virtual-real mapping and dynamic deduction, and the digital mirror image is a key for solving the problem of pain point control of the supply chain and pushing the supply chain to change from 'passive response' to 'active service'. However, in the current electric power material management field, a mature digital mirror image application scheme is not formed yet, and the most similar prior art is a "geometric model visualization+static data display" mode, which has the following defects: Firstly, the mode can only visually present static information such as the position and the inventory of electric power materials, risk identification logic and an early warning mechanism are not embedded, and risk cannot be early warned in advance. Secondly, the mode lacks multi-scene simulation deduction and algorithm support, can be used as a simple 'visualization tool', cannot generate optimal coping decisions aiming at risk events, and still depends on manual experience. Thirdly, the mode does not realize linkage of early warning-decision-execution-feedback-optimization, and the self model cannot be optimized by using actual execution data, so that similar risks repeatedly occur. Fourth, the model is a generalized design, and the special functions are designed without combining transportation constraint and technical parameters (such as moisture resistance and load limitation) of large materials such as a main transformer, and the display and deduction results are separated from the reality of an electric material supply chain. Disclosure of Invention The invention provides a power supply chain risk early warning method and device based on digital mirror images, which can improve the accuracy of power supply chain risk early warning. The embodiment of the invention provides a power supply chain risk early warning method based on digital mirror images, which comprises the following steps: Acquiring WBS data of a target power engineering task, mapping the WBS data into BOM data based on a pre-constructed power engineering knowledge graph, and inquiring a risk threshold corresponding to the target power engineering task from the power engineering knowledge graph; The BOM data is issued to a supply chain system, so that the supply chain system starts a material circulation operation based on the BOM data, and a pre-constructed digital mirror image is updated according to first logistics data generated in the execution process of the material circulation operation; When a target business event occurs in the execution process of the material circulation operation is monitored, inputting the target business event and the risk threshold value into an updated digital mirror image, so that the digital mirror image carries out risk assessment on the target business event based on the risk threshold value, and generating and outputting a coping strategy according to a risk assessment result; Converting the coping strategy into an execution instruction and issuing the execution instruction to the supply chain system so that the supply chain system starts a material transportation operation based on the execution instruction and updates the digital mirror image according to second stream data generated in the execution process of the material transportation operation; and inputting the execution effect data corresponding to the material transportation operation into the updated digital mirror image so that the digital mirror image compares the execution effect data with the expected data corresponding to the coping strategy, and generating and outputting an early warning signal according to a comparison result. According to the embodiment of the application, the WBS data of the target power engineering task is obtained and mapped into the BOM data based on the power engineering knowledge graph, a material demand list can be generated according to the inhe