CN-122026611-A - Power grid monitoring operation dual monitoring and safety verification method and system based on bionic intelligent agent

CN122026611ACN 122026611 ACN122026611 ACN 122026611ACN-122026611-A

Abstract

The invention provides a method and a system for dual monitoring and safety verification of grid monitoring operation based on a bionic intelligent agent, which relate to the technical field of intelligent grid safety, and the method comprises the steps that the bionic intelligent agent analyzes tasks submitted by a manual operator to form a task model; the method comprises the steps of manually monitoring and a bionic agent to independently check operation conditions and safety boundaries and generate permission instructions, synchronously collecting operation data and comparing the operation data with target states to obtain deviation information, enabling the bionic agent to combine historical sample correction rules and calculate safety confidence to generate intelligent judgment results, enabling the manual monitoring to recheck according to field information to form co-decision results, and enabling the bionic agent to verify operation safety closure based on the co-decision results to generate safety verification records. The invention solves the problems of lack of unified whole-process intelligent monitoring mechanism in the power grid monitoring operation, insufficient monitoring continuity, difficult real-time identification of process deviation and incomplete post-safety verification in the prior art.

Inventors

ZENG LINLONG
ZHANG YINGXU
CHEN JUNHUI
He Chenhao
PAN XINGBO
REN XIANG
LIU SISI
YANG ZEYAN
LEI YANG
SONG ZHEXUAN
WANG XIAOYAN

Assignees

国网湖北省电力有限公司襄阳供电公司

Dates

Publication Date: 20260512
Application Date: 20260123

Claims (10)

1. The utility model provides a power grid monitoring operation dual guardianship and safety verification method based on bionical intelligent agent which characterized in that includes: The bionic intelligent agent receives an operation task submitted by a manual operator, and analyzes an operation target, target equipment and operation constraint of the operation task to obtain a task model; The artificial monitoring and bionic intelligent agent respectively carry out independent check on the operation condition, logic consistency and safety boundary of the task model according to a preset safety rule set to obtain a first check result and a second check result; If the first checking result is consistent with the second checking result, generating a starting permission instruction; based on the starting permission instruction, the bionic agent and the manual monitoring collect real-time operation data at the same time, and the collected operation data are compared with a target state in a task model in real time to obtain deviation information; based on the deviation information, the bionic agent performs trend fitting analysis on the current operation characteristics of the power grid system by utilizing a historical task sample and a security event record to obtain an analysis result, and performs parameter updating and local correction on the security rule set by utilizing the analysis result to obtain a correction result; the bionic agent calculates the safety confidence coefficient of the current operation according to the correction result and generates an intelligent safety judgment result; the intelligent safety judgment result is rechecked according to the site information and the operation experience by the manual monitoring to obtain a co-decision result; And the bionic intelligent agent verifies the safety closure of the final running state based on the co-decision result to obtain a safety verification record.
2. The dual monitoring and security verification method for monitoring operation of a power grid based on a bionic intelligent agent according to claim 1, wherein the bionic intelligent agent receives an operation task submitted by a manual operator, analyzes an operation target, a target device and an operation constraint of the operation task, and obtains a task model comprising: The bionic agent receives an operation task instruction input by a manual operator through a monitoring terminal, and extracts an operation type identifier, a target device identifier and an operation parameter in the operation task instruction to obtain initial task information; the bionic agent performs semantic analysis on the initial task information, and identifies an operation target, target equipment and operation constraint conditions of the operation task instruction to obtain an analysis result; converting the analysis result into structured task data; The bionic agent identifies the working state, the electrical topological connection relation and the load characteristic of the equipment related to the operation task instruction based on the real-time operation data of the power grid system, and obtains a current state data set; the bionic agent carries out association matching on the structured task data and the current state data set to obtain a task model; The expression of the task model is as follows: ; Wherein, the A task model generated for the bionic agent; a structured instruction matrix for an operational task; running constraint vectors for the task; Is an environmental state set; the running state matrix is the current equipment running state matrix; A task logic consistency linked list; 、 the first, second, third, fourth and fifth proportionality coefficients are calculated adaptively for the system; Is a nonlinear fusion operator.
3. The dual monitoring and safety verification method for monitoring operation of electric network based on bionic intelligent agent according to claim 1, wherein the method based on starting permission instruction, the bionic intelligent agent and manual monitoring collect real-time operation data at the same time, and compare the collected operation data with the target state in the task model in real time to obtain deviation information, comprises: The bionic intelligent agent and the manual monitoring respectively acquire operation data from the power grid system in real time to obtain a real-time operation data set; The bionic agent compares the real-time operation data set with the corresponding target state in the task model item by item to calculate a difference vector between the actual operation state and the target state; the bionic intelligent agent identifies operation parameters exceeding a safety threshold range based on the difference vector to obtain an intelligent identification result; and carrying out consistency verification on the manual observation result of the manual monitoring and the intelligent identification result to generate deviation information.
4. A dual monitoring and security verification method for monitoring operations of a utility network based on a biomimetic agent as defined in claim 3, wherein the operational data comprises: voltage, current, frequency, load, and switch state.
5. The method for dual monitoring and safety verification of utility grid monitoring operation based on a bionic agent according to claim 3, wherein the bionic agent compares the real-time running dataset with the corresponding target state in the task model item by item to calculate a difference vector between the actual running state and the target state, comprising: the bionic agent searches corresponding real-time measurement parameters in the real-time operation data set according to the equipment identification and the parameter index in the task model, and establishes a parameter corresponding relation table; The bionic intelligent agent calculates the difference between the real-time measured value and the target set value for each group of corresponding parameters according to the parameter corresponding relation table to obtain a parameter difference value set; And the bionic agent arranges the parameter difference value sets according to the logic sequence of the target equipment in the task model to obtain a difference value vector.
6. The dual monitoring and safety verification method for monitoring operation of a power grid based on a bionic agent according to claim 1, wherein the bionic agent performs trend fitting analysis on current operation characteristics of the power grid system by using historical task samples and safety event records based on the deviation information to obtain analysis results, and performs parameter updating and local correction on the safety rule set by using the analysis results to obtain correction results, and the method comprises the following steps: The bionic intelligent agent determines corresponding target equipment and an operation scene according to the deviation information; extracting time sequence characteristic parameters associated with target equipment and an operation scene from a historical task sample and a security event record to form a characteristic data set; based on the characteristic data set, performing trend fitting on the current operation characteristics of the power grid system by using a time sequence algorithm to obtain an analysis result; according to the analysis result, carrying out self-adaptive adjustment on a threshold value, delay time, load limit value and protection action level in the safety rule set, and calculating an update parameter set; Applying the updated parameter set to a local safety rule set corresponding to the current operation situation, and recalculating the rule application range and the trigger condition to form a correction rule set; and generating a correction result comprising parameter variation amplitude, rule application equipment and an update timestamp based on the correction rule set.
7. The method for dual monitoring and security verification of utility monitoring operation based on bionic agent according to claim 6, wherein the step of applying the updated parameter set to the local security rule set corresponding to the current operation situation and recalculating the rule application range and the trigger condition to form a correction rule set comprises the steps of: Identifying a task type, a device type and a risk level corresponding to the current operation situation according to the deviation information and the current operation data, and determining a local safety rule set to be corrected; Respectively embedding a threshold value parameter, a delay parameter and an association coefficient in the updated parameter set into corresponding rule items in the local safety rule set to generate a parameterized rule model; calculating the application range of the rule under the current running situation according to the threshold range and the trigger logic in the parameterized rule model; Reconstructing the relation between the triggering conditions and the priorities of each safety rule set according to the application range, and generating a correction rule item conforming to the current operation characteristics; integrating the correction rule items into a correction rule set; the expression of the parameterized rule model is: ; Wherein, the Is a parameterized rule model; Is a voltage state vector; Is a current distribution matrix; A system frequency and power fluctuation feature set; To operate the electrical parameter sub-module; A record set for fault events; the method comprises the steps of taking the action threshold parameters of the protection device as parameters; is a local rule logic unit set; a rule constraint strategy; is a time sequence characteristic function; is an environmental disturbance index set; Is a space-time correction module; A first proportionality coefficient, a second proportionality coefficient and a third proportionality coefficient which are obtained for self-learning of the system; is a global fusion operator.
8. The dual monitoring and safety verification method for monitoring operation of a power grid based on a bionic intelligent agent according to claim 1, wherein the bionic intelligent agent calculates the safety confidence of the current operation according to the correction result and generates an intelligent safety judgment result, comprising: the bionic agent analyzes the parameter variation amplitude, the rule application range and the rule level weight in the correction result, extracts relevant characteristic variables for confidence calculation, and obtains a confidence evaluation input data set; calculating risk influence factors and comprehensive confidence initial values of all feature variables according to the confidence evaluation input data set; According to the risk influence factors, the priority of the current task model, the importance of the equipment and the real-time deviation amplitude, carrying out dynamic weight adjustment on the comprehensive confidence coefficient initial value to obtain a safety confidence coefficient value of the current operation; the bionic agent compares the calculated safety confidence value with a preset safety confidence threshold value to determine the confidence level of the current operation; The bionic agent generates an intelligent security judgment result based on the confidence level.
9. The dual monitoring and safety verification method for monitoring operation of electric network based on bionic intelligent agent according to claim 1, wherein the manual monitoring rechecks the intelligent safety judgment result according to the field information and the operation experience to obtain a co-decision result, comprising: The manual monitoring obtains the real-time state, environmental parameters and feedback information of operators of the current equipment through a monitoring terminal to form a field information set; The manual monitoring carries out matching analysis on the intelligent safety judgment result according to personal professional experience and power grid operation specification, and identifies judgment items inconsistent with field information to obtain an identification result; Confirming, marking and recording reason information on the difference item according to the identification result, and generating a manual review difference table; and comprehensively judging the result through a preset weight fusion algorithm according to the manual review difference table and the intelligent safety judgment result to obtain a co-decision result.
10. Power grid monitoring operation dual guardianship and safety verification system based on bionical agent, characterized by including: The task analysis module is used for receiving the operation task submitted by the manual operator by the bionic intelligent agent, analyzing the operation target, the target equipment and the operation constraint of the operation task, and obtaining a task model; The rule checking module is used for independently checking the operation conditions, the logic consistency and the safety boundaries of the task model according to a preset safety rule set by the artificial monitoring agent and the bionic agent respectively to obtain a first checking result and a second checking result; The permission judging module is used for generating a starting permission instruction if the first check result is consistent with the second check result; The parallel monitoring module is used for acquiring real-time operation data simultaneously by the bionic agent and the manual monitoring based on the starting permission instruction, and comparing the acquired operation data with a target state in the task model in real time to obtain deviation information; the self-adaptive analysis and rule correction module is used for carrying out trend fitting analysis on the current operation characteristics of the power grid system by utilizing a historical task sample and a safety event record based on the deviation information by the bionic intelligent agent to obtain an analysis result, and carrying out parameter updating and local correction on the safety rule set by utilizing the analysis result to obtain a correction result; the intelligent judging module is used for calculating the safety confidence coefficient of the current operation according to the correction result by the bionic intelligent body and generating an intelligent safety judging result; The manual rechecking module is used for rechecking the intelligent safety judgment result according to the field information and the operation experience in manual monitoring to obtain a co-decision result; and the safety verification module is used for the bionic intelligent agent to verify the safety closure of the final running state based on the co-decision result, and a safety verification record is obtained.

Description

Power grid monitoring operation dual monitoring and safety verification method and system based on bionic intelligent agent Technical Field The invention relates to the technical field of intelligent power grid safety, in particular to a power grid monitoring operation dual monitoring and safety verification method and system based on a bionic intelligent body. Background In the existing power grid operation and monitoring system, the dispatching operation generally depends on electronic operation ticket management and double monitoring systems to ensure safety. The monitoring center usually needs to process data from a dispatching master station, a centralized control system, a protection device, fault recording, dispatching communication and other systems simultaneously. Before operation, the ticket face and the running mode are manually checked, and in the operation process, the manual monitoring picture and the alarm signal are used for realizing verification through manual recording and archiving after the operation is finished. Although some units have developed electronic operation tickets, automatic inspection and standardized misoperation-preventive locking management, most of operation ticket rules are text templates, the operation ticket rules cannot be directly executed by a system, real-time performance and comprehensiveness still have limitations, the process depends on experience judgment, the manual attention burden is heavy, and judgment deviation is easy to occur under the conditions of high-intensity or complex operation. With the development of intelligent scheduling technology, the industry gradually changes to the intelligent direction of rule computability and monitoring. The new generation of power grid operation system requires to realize the prior identification, in-process supervision and post-process traceability of operation behaviors, and the operation tasks are digitally monitored and safety verified by introducing bionic intelligent agents, artificial intelligent algorithms and scene reasoning mechanisms. The system realizes closed-loop management and control from pre-verification to post audit through multi-source state data fusion, dynamic threshold evaluation and condition triggering analysis. The general trend of the power grid operation safety management is to construct a whole process management and control system which is perceivable, analyzable, verifiable and traceable, so that blind areas of human intervention are reduced, and the monitoring accuracy and response speed are improved. However, the prior art still has significant drawbacks in terms of continuity management of the operational whole flow. The current front-end checking, process monitoring and post-check links are mutually independent, lack of uniform logic chain support, and easily cause the problems that the front-end checking is qualified, the rule is deviated in the execution process, the evidence is difficult to reproduce after the fact, and the like. Most of deviation detection in the operation process depends on static trigger logic, and the influence of dynamic change and dependency of an operation mode cannot be recognized in time. The condition of information disconnection, incomplete data and record lag in the post verification link causes difficult definition of responsibility and difficult formation of effective feedback closed loop by experience knowledge Disclosure of Invention In order to overcome the defects of the prior art, the invention aims to provide a dual monitoring and safety verification method and system for grid monitoring operation based on a bionic intelligent body, and solves the problems that the grid monitoring operation in the prior art lacks a unified whole-process intelligent monitoring mechanism, and has insufficient monitoring continuity, difficult real-time identification of process deviation and incomplete post-safety verification. In order to achieve the above object, the present invention provides the following solutions: a dual monitoring and safety verification method for grid monitoring operation based on a bionic agent comprises the steps of enabling the bionic agent to receive an operation task submitted by an artificial operator and analyze the operation target, target equipment and operation constraint of the operation task to obtain a task model, enabling the artificial monitoring agent and the bionic agent to independently check operation conditions, logic consistency and safety boundaries of the task model according to a preset safety rule set to obtain a first check result and a second check result, generating a starting permission instruction if the first check result and the second check result are consistent, enabling the bionic agent to simultaneously acquire real-time operation data based on the starting permission instruction, enabling the acquired operation data to be compared with target states in the task model to obtain deviation information,