CN-121984221-A - Electric power monitoring optimization method and related device based on situation awareness and intelligent diagnosis

CN121984221ACN 121984221 ACN121984221 ACN 121984221ACN-121984221-A

Abstract

The application provides a power monitoring optimization method and a related device based on situation awareness and intelligent diagnosis, wherein the method comprises the steps of acquiring multisource real-time operation data and a power monitoring system corresponding to a target power system; the power monitoring system is used for monitoring and adjusting the real-time running state of the target power system, performing situation awareness analysis on the multi-source real-time running data to obtain situation assessment results, performing intelligent diagnosis analysis on the situation assessment results to obtain fault diagnosis results, generating a monitoring optimization strategy according to the fault diagnosis results, and generating a plurality of target instruction sets according to the monitoring optimization strategy. Through deep fusion situation awareness and intelligent diagnosis technology, the power monitoring parameters are optimized, and therefore accuracy and adaptability of the power monitoring system are improved.

Inventors

WANG HU
DAI YONG
WANG JIANAN
TIAN XIN

Assignees

云南电力试验研究院(集团)有限公司

Dates

Publication Date: 20260505
Application Date: 20251229

Claims (10)

1. The utility model provides a power monitoring optimization method based on situation awareness and intelligent diagnosis, which is characterized in that the method comprises the following steps: The power monitoring system is used for monitoring and adjusting the real-time running state of the target power system; performing situation awareness analysis on the multisource real-time operation data to obtain situation assessment results; performing intelligent diagnosis and analysis on the situation assessment result to obtain a fault diagnosis result; Generating a monitoring optimization strategy according to the fault diagnosis result; and generating a plurality of target instruction sets according to the monitoring optimization strategy, wherein the target instruction sets are used for dynamically adjusting the monitoring parameters of the power monitoring system aiming at the equipment in the target power system.
2. The method of claim 1, wherein the multi-source real-time operation data comprises voltage deviation data, current fluctuation data and frequency offset data, the situation assessment result comprises a system stability level and a risk early warning sign, and the situation awareness analysis is performed on the multi-source real-time operation data to obtain the situation assessment result, which comprises: performing space-time alignment and preprocessing on the voltage deviation data, the current fluctuation data and the frequency offset data to obtain first characteristic data, second characteristic data and third characteristic data; Performing fusion processing on the first feature data, the second feature data and the third feature data to obtain a fusion feature data set; and inputting the fusion characteristic data set into a preset situation assessment model to obtain the system stability grade and the risk early warning sign.
3. The method of claim 2, wherein the fault diagnosis result includes a fault type and a fault probability, and the performing intelligent diagnosis analysis on the situation assessment result to obtain the fault diagnosis result includes: Acquiring a data subset corresponding to the risk early warning sign in the fusion characteristic data set to obtain a reference data subset; determining the current risk type corresponding to the risk early warning mark; Acquiring a historical fault case matched with the current risk type from a preset historical fault case library to obtain a reference fault case set; constructing a diagnosis triplet according to the reference data subset, the reference fault case set and the system stability level; And inputting the diagnosis triplet into a preset fault diagnosis model to obtain the fault type and the fault probability.
4. The method of claim 3, wherein the subset of reference data comprises a plurality of reference data records, the inputting the diagnostic triplet into a pre-set fault diagnosis model to obtain the fault type and the fault probability comprises: Acquiring a global topological structure diagram corresponding to the target power system; Acquiring a reference node identifier corresponding to each reference data record in the plurality of reference data records to obtain a plurality of reference node identifiers; acquiring a plurality of reference node identifiers corresponding to a plurality of reference nodes in the global topology structure chart; in the global topology structure diagram, taking each reference node in the plurality of reference nodes as a center, acquiring all associated nodes which have an electrical connection relationship with the reference nodes in a preset adjacent range, and obtaining a plurality of associated node sets; determining a sub-topology structure diagram according to the plurality of reference nodes and the plurality of associated node sets; And analyzing the diagnosis triples and the sub-topology structure diagram according to the fault diagnosis model to obtain the fault type and the fault probability.
5. The method of claim 4, wherein the fault type includes fault location information and fault property information, and wherein generating a monitoring optimization strategy based on the fault diagnosis results comprises: analyzing the fault property information to obtain a fault type identifier; Determining a fault confidence score according to the fault probability; obtaining a fault influence level corresponding to the fault type identifier in a preset strategy knowledge base; Determining a monitoring frequency adjustment value according to the fault confidence score, the fault influence level and the system stability level; Obtaining target nodes corresponding to the fault locating information in the sub-topology structure diagram to obtain a plurality of target nodes; Acquiring all state quantity of each target node in the plurality of target nodes to obtain a plurality of state quantity sets, wherein each state quantity set corresponds to one target node; Determining a plurality of target data acquisition sequences according to the plurality of state quantity sets; and generating the monitoring optimization strategy according to the monitoring frequency adjustment value and the plurality of target data acquisition sequences.
6. The method of claim 5, wherein said determining a plurality of target data acquisition sequences from said plurality of state quantity sets comprises: Determining causal association strength of each state quantity in a first state quantity set and the fault type according to the strategy knowledge base to obtain a plurality of causal association strengths; Determining a risk urgency level corresponding to the risk early warning sign; determining a plurality of data acquisition priorities according to a preset resource scheduling coefficient, the risk urgency level and each causal association strength of the plurality of causal association strengths; sequencing the data acquisition priorities from high priority to low priority to obtain a first priority sequence; and determining a target data acquisition sequence corresponding to the first state quantity set in the plurality of target data acquisition sequences according to the first priority sequence.
7. The method of claim 5 or 6, wherein the generating a plurality of target instruction sets according to the monitoring optimization strategy comprises: Determining a plurality of target node identifiers corresponding to the plurality of target nodes according to the sub-topology structure diagram; acquiring a plurality of initial sampling frequencies corresponding to the plurality of target nodes; adjusting the plurality of initial sampling frequencies according to the monitoring frequency adjustment value to obtain a plurality of target sampling frequencies; And generating the target instruction sets according to the target node identifications, the target sampling frequencies and the target data acquisition sequences.
8. The utility model provides a power monitoring optimizing apparatus based on situation awareness and intelligent diagnosis which characterized in that, the device includes acquisition module, first analysis module, second analysis module, first generation module, second generation module, wherein: The system comprises an acquisition module, a power monitoring system, a control module and a control module, wherein the acquisition module is used for acquiring multi-source real-time operation data corresponding to a target power system and the power monitoring system; The first analysis module is used for carrying out situation awareness analysis on the multi-source real-time operation data to obtain a situation assessment result; the second analysis module is used for performing intelligent diagnosis and analysis on the situation assessment result to obtain a fault diagnosis result; the first generation module is used for generating a monitoring optimization strategy according to the fault diagnosis result; The second generation module is used for generating a plurality of target instruction sets according to the monitoring optimization strategy, and the target instruction sets are used for dynamically adjusting the monitoring parameters of the power monitoring system aiming at the equipment in the target power system.
9. An electronic device comprising a processor, a memory, a communication interface, and one or more programs stored in the memory and configured to be executed by the processor, the programs comprising instructions for performing the steps in the method of any of claims 1-7.
10. A computer readable storage medium, characterized in that the computer readable storage medium stores a computer program comprising program instructions which, when executed by a processor, cause the processor to perform the method of any of claims 1-7.

Description

Electric power monitoring optimization method and related device based on situation awareness and intelligent diagnosis Technical Field The application relates to the technical field of power monitoring, in particular to a power monitoring optimization method and a related device based on situation awareness and intelligent diagnosis. Background Under the background of rapid development of a power system, the system running state is more complex and changeable due to large-scale access of new energy and rapid increase of power equipment, and the real-time performance, the accuracy and the self-adaption of the traditional power monitoring system face serious challenges. The monitoring parameters such as sampling frequency, data transmission rule and the like of the traditional power monitoring system are usually preconfigured and static fixed. This results in the possible waste of resources during normal operation of the power system, but when a fault occurs or an abnormal trend occurs, key information cannot be captured in time due to insufficient monitoring density, and it is difficult to meet the safety requirement of dynamic change. Therefore, how to improve the accuracy and the adaptability of the power monitoring system is needed to be solved. Disclosure of Invention The embodiment of the application provides a power monitoring optimization method and a related device based on situation awareness and intelligent diagnosis, which are used for converting monitoring parameters from static preset to dynamic adjustment based on real-time fault diagnosis results through a deep fusion situation awareness and intelligent diagnosis technology, so that the accurate focusing of a high-risk area and the optimal configuration of resources are realized, and the accuracy and the adaptability of a power monitoring system are finally improved. In a first aspect, an embodiment of the present application provides a method for optimizing power monitoring based on situational awareness and intelligent diagnosis, where the method includes: The power monitoring system is used for monitoring and adjusting the real-time running state of the target power system; performing situation awareness analysis on the multisource real-time operation data to obtain situation assessment results; performing intelligent diagnosis and analysis on the situation assessment result to obtain a fault diagnosis result; Generating a monitoring optimization strategy according to the fault diagnosis result; and generating a plurality of target instruction sets according to the monitoring optimization strategy, wherein the target instruction sets are used for dynamically adjusting the monitoring parameters of the power monitoring system aiming at the equipment in the target power system. In a second aspect, an embodiment of the present application provides a power monitoring optimization device based on situation awareness and intelligent diagnosis, where the device includes an acquisition module, a first analysis module, a second analysis module, a first generation module, and a second generation module, where: The system comprises an acquisition module, a power monitoring system, a control module and a control module, wherein the acquisition module is used for acquiring multi-source real-time operation data corresponding to a target power system and the power monitoring system; The first analysis module is used for carrying out situation awareness analysis on the multi-source real-time operation data to obtain a situation assessment result; the second analysis module is used for performing intelligent diagnosis and analysis on the situation assessment result to obtain a fault diagnosis result; the first generation module is used for generating a monitoring optimization strategy according to the fault diagnosis result; The second generation module is used for generating a plurality of target instruction sets according to the monitoring optimization strategy, and the target instruction sets are used for dynamically adjusting the monitoring parameters of the power monitoring system aiming at the equipment in the target power system. In a third aspect, an embodiment of the present application provides an electronic device, including a processor, a memory, a communication interface, and one or more programs, where the one or more programs are stored in the memory and configured to be executed by the processor, the programs including instructions for performing steps in any of the methods of the first aspect of the embodiments of the present application. In a fourth aspect, embodiments of the present application provide a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program for electronic data exchange, wherein the computer program causes a computer to perform part or all of the steps as described in any of the methods of the first aspect of the embodiments of the present application. In a fifth aspect, e