CN-122020010-A - Power distribution network bearing performance evaluation method, system, equipment and medium based on multi-source data analysis

CN122020010ACN 122020010 ACN122020010 ACN 122020010ACN-122020010-A

Abstract

The invention relates to the technical field of power grid performance evaluation and discloses a method, a system, equipment and a medium for evaluating the load bearing performance of a power distribution network based on multi-source data analysis, which comprise the steps of acquiring an edge execution set, and periodically determining an optimization execution set for executing the optimization analysis of the set according to an execution evaluation coefficient; the method comprises the steps of determining whether to perform allocation optimization or training optimization based on a resource execution evaluation index and an execution target duty ratio index, determining an allocation optimization target according to a resource execution correlation index when performing allocation optimization, determining an execution prediction correlation index according to a reference resource correlation index or a correlation resource coincidence index when performing training optimization, determining whether to perform deviation correlation analysis or concurrent correlation analysis according to the execution prediction correlation index, and determining optimization execution data based on a deviation correlation coverage index or a deviation time sequence correlation index. The invention improves the processing quality of the monitoring data of the power distribution network and the load bearing performance evaluation efficiency of the power distribution network.

Inventors

WU CHUNJI
GUO HUIFANG
ZHENG DING
ZHANG NA
Lin Yunxuan
CAO LU
DONG YUNZHOU
LIN SHIZHE
Zhu Mingsi
XING BOXIANG
QI MINGLU

Assignees

海南电网有限责任公司信息通信分公司

Dates

Publication Date: 20260512
Application Date: 20251203

Claims (10)

1. The utility model provides a distribution network bearing performance evaluation method based on multisource data analysis, which is characterized by comprising the following steps: determining an edge execution set based on the resource association index, and periodically determining an optimized execution set for performing set execution optimization analysis according to the execution evaluation coefficient; Determining an execution demand state of each optimized execution set based on the resource execution evaluation index and the execution target duty ratio index, and determining whether to execute allocation optimization or training optimization for each optimized execution set based on the execution demand state; When performing execution allocation optimization, determining an allocation optimization target of an optimization execution set according to the resource execution correlation index so as to ensure the resource utilization efficiency of the optimization execution set in a class of execution demand states; When the execution training optimization is carried out, an execution prediction association index of each optimization execution set is determined according to the reference resource correlation index or the related resource coincidence index, whether deviation association analysis or concurrence association analysis is carried out on each optimization execution set is determined according to the execution prediction association index, and the optimization execution data for extraction optimization is determined based on the deviation correlation coverage index or the deviation time sequence correlation index.
2. The method for evaluating the load bearing performance of the power distribution network based on multi-source data analysis according to claim 1, wherein the optimized execution set is an edge execution set with an execution evaluation coefficient larger than a preset execution evaluation coefficient; the execution evaluation coefficient of any edge execution set is determined according to the analysis execution index of each access analysis target in the corresponding edge execution set, and the analysis execution index is determined according to the deviation evaluation index and the processing evaluation index of the access analysis target. The edge execution sets are sets of a plurality of access analysis targets, and the resource association index of any edge execution set is larger than a preset resource association index.
3. The method for evaluating the load bearing performance of a power distribution network based on multi-source data analysis according to claim 2, wherein the execution demand states include a class of execution demand states and a class of execution demand states; The optimized execution set in the execution demand state is an optimized execution set with a resource execution evaluation index larger than a preset resource execution evaluation index or an execution target duty ratio index larger than a preset execution target duty ratio index; The optimized execution set in the second-class execution demand state is an optimized execution set with a resource execution evaluation index smaller than or equal to a preset resource execution evaluation index and an execution target duty ratio index smaller than or equal to a preset execution target duty ratio index.
4. A method of evaluating load bearing performance of a power distribution network based on multi-source data analysis according to claim 3, wherein the distribution optimization is performed for an optimized execution set in a class of execution demand states, wherein: Detecting the resource execution correlation indexes of the corresponding optimization execution sets aiming at each access analysis target to determine the allocation optimization targets of the corresponding optimization execution sets; the resource execution correlation index is determined according to the category of analysis execution data of each access analysis target in the optimization execution set; performing allocation optimization for allocation optimization targets of an optimization execution set in a class of execution demand states, wherein: Determining an allocation execution set of each allocation optimization target according to the resource execution correlation index and the deviation execution correlation index; The allocation optimization target is an access analysis target with a resource execution correlation index of the corresponding optimization execution set smaller than or equal to a preset resource execution correlation index.
5. The method for evaluating the load bearing performance of a power distribution network based on multi-source data analysis according to claim 4, wherein the process of performing training optimization for the optimal execution set in the second class of execution demand state or completed execution allocation optimization to determine the optimized execution data for extraction optimization, and performing training optimization comprises: an execution prediction association index for the corresponding optimization execution set, and a setting mode of optimizing execution data for extraction optimization is determined based on the execution prediction association index; and the setting mode of the execution prediction association index is determined according to the deviation target duty ratio index of the optimized execution set and the execution target duty ratio index.
6. The method for evaluating the load bearing performance of the power distribution network based on the multi-source data analysis according to claim 5, wherein the execution prediction association index of the optimized execution set with the deviation target duty ratio index larger than the preset deviation target duty ratio index or the execution target duty ratio index larger than the preset execution target duty ratio index is determined based on the reference resource correlation index; And determining an execution prediction association index of the optimized execution set, wherein the deviation target duty ratio index is smaller than or equal to a preset deviation target duty ratio index and the execution target duty ratio index is smaller than or equal to the preset execution target duty ratio index, based on the related resource superposition index.
7. The method for evaluating the load bearing performance of a power distribution network based on multi-source data analysis according to claim 6, wherein the deviation association analysis is performed on an optimized execution set with an execution prediction association index greater than a preset execution prediction association index to determine optimized execution data for data processing optimization and an associated optimized data set; the optimized execution data are analysis execution data with the deviation related coverage index being larger than a preset deviation related coverage index; The determined correlation time sequence difference index of any correlation optimization data set is smaller than or equal to a preset correlation time sequence difference index; Carrying out concurrent association analysis on an optimized execution set with the execution prediction association index smaller than or equal to a preset execution prediction association index, wherein: detecting deviation time sequence correlation indexes of analysis execution data of the corresponding optimization execution set to determine the optimization execution data of the optimization execution set; the optimization execution data are analysis execution data with deviation time sequence correlation indexes larger than preset deviation time sequence correlation indexes, and the deviation time sequence correlation indexes are determined according to judgment moments corresponding to deviation analysis targets of all analysis execution data in a predictive analysis process.
8. A power distribution network load bearing performance evaluation system based on multi-source data analysis, applying the method according to any one of claims 1-7, comprising: the first determining module is used for determining an edge execution set based on the resource association index and periodically determining an optimized execution set for performing set execution optimization analysis according to the execution evaluation coefficient; the second determining module is used for determining an execution demand state of each optimized execution set based on the resource execution evaluation index and the execution target duty ratio index, and determining whether to execute allocation optimization or training optimization for each optimized execution set based on the execution demand state; the allocation optimization module is used for determining an allocation optimization target of the optimization execution set according to the resource execution correlation index when the execution allocation optimization is carried out so as to ensure the resource utilization efficiency of the optimization execution set in a class of execution demand state; The training optimization module is used for determining an execution prediction association index of each optimization execution set according to the reference resource correlation index or the related resource coincidence index when performing training optimization, determining whether deviation association analysis or concurrence association analysis is performed on each optimization execution set according to the execution prediction association index, and determining optimization execution data for extraction optimization based on the deviation correlation coverage index or the deviation time sequence correlation index.
9. A computer device, comprising: A memory and a processor; The memory is configured to store computer executable instructions, and the processor is configured to execute the computer executable instructions, which when executed by the processor, implement the steps of a method for evaluating load bearing performance of a power distribution network based on multi-source data analysis according to any one of claims 1 to 7.
10. A computer readable storage medium, characterized in that it stores computer executable instructions, which when executed by a processor, implement the steps of a method for evaluating load bearing performance of a power distribution network based on multi-source data analysis according to any one of claims 1 to 7.

Description

Power distribution network bearing performance evaluation method, system, equipment and medium based on multi-source data analysis Technical Field The invention relates to the technical field of power grid performance evaluation, in particular to a power distribution network load bearing performance evaluation method, system, equipment and medium based on multi-source data analysis. Background With the continuous development of new energy technology, the access scale of the distributed photovoltaic in the power distribution network is gradually increased, but the actual access scale of the actual distributed energy can influence the safe and stable running state of the power distribution network, and the load bearing evaluation of the power distribution network on the access scale of the distributed photovoltaic has important significance for the actual running management of the power distribution network. In the process of carrying performance evaluation of the power distribution network facing to high-proportion distributed energy sources, the data amount of multi-source data to be processed is more, the influence on the actual evaluation efficiency is easily caused by data transmission and centralized analysis, the edge computing nodes are arranged to conduct predictive analysis on the distributed energy sources accessed by the power distribution network, so that the processing of a large amount of acquired multi-source data and the resource consumption caused by the transmission process are avoided, but the suitability of a fixed analysis scheme caused by the change of the operation states of the power distribution network and the distributed energy sources in the actual operation process is not considered in the existing analysis process, the evaluation efficiency and quality of the carrying performance of the power distribution network are influenced, and therefore, how to conduct targeted processing on the acquired multi-source data to ensure the data analysis efficiency in the actual evaluation process is a problem to be solved urgently by technicians in the field. The China application publication No. CN117634923A discloses a power distribution network bearing capacity assessment method of distributed energy equipment, which comprises the steps of assessing the performance requirements of the power distribution network according to the distributed energy equipment, establishing a power distribution network bearing capacity assessment index system, constructing a decision model of the power distribution network bearing capacity according to the assessment index system, calculating subjective weights of the assessment index system through the decision model, constructing an initial data matrix of power data of the power distribution network based on the assessment indexes and calculating objective weights of the initial data matrix, calculating basic weights of the assessment index system through the subjective weights and the objective weights, constructing an optimization model through the basic weights and calculating comprehensive weights of all indexes, and making a comprehensive assessment scheme of the power distribution network bearing capacity based on the comprehensive weights to comprehensively assess the power distribution network bearing capacity of the distributed energy equipment. However, the scheme has the defect that the data analysis efficiency of the power distribution network load performance assessment process is poor due to the fact that the scheme cannot carry out targeted processing on multi-source data for assessing the power distribution network load performance in combination with practical situations. Disclosure of Invention The present invention has been made in view of the above-described problems occurring in the prior art. Therefore, the invention provides a method and a system for evaluating the load-bearing performance of a power distribution network based on multi-source data analysis, which solve the problem that the data analysis efficiency of the load-bearing performance evaluation process of the power distribution network is poor because the current situation that multi-source data for evaluating the load-bearing performance of the power distribution network cannot be processed in a targeted manner is not combined. In order to solve the technical problems, the invention provides the following technical scheme: In a first aspect, the invention provides a method for evaluating the load-bearing performance of a power distribution network based on multi-source data analysis, which comprises the steps of determining an edge execution set based on a resource association index, and periodically determining an optimized execution set for performing set execution optimization analysis according to an execution evaluation coefficient; Determining an execution demand state of each optimized execution set based on the resource execution evaluation index and the execution t