CN-122001820-A - Data transmission quality optimization method and system for intelligent ammeter

CN122001820ACN 122001820 ACN122001820 ACN 122001820ACN-122001820-A

Abstract

The invention relates to the field of data processing, in particular to a data transmission quality optimization method and a system for intelligent electric meters, wherein the method comprises the steps of obtaining historical sensitivity sequences and key update records of each electric meter and constructing transmission sensitivity vectors; the method comprises the steps of clustering electric meter groups, assigning sensitivity levels, dividing a transmission period into a plurality of time slots, establishing corresponding transmission scheduling groups, distributing the electric meters to the groups according to the sensitivity levels to form an initial scheduling scheme, collecting network and computing resource states at the beginning of the current transmission period, computing resource pressure, comparing the resource pressure with a double threshold value, taking the sum of the transmission sensitivity of the electric meters in the groups as a load according to a comparison result, dynamically adjusting the corresponding sequence of the transmission scheduling groups and the transmission time slots according to the load level, and issuing a transmission instruction. According to the invention, through a double-layer scheduling mechanism combining historical behavior classification and real-time resource perception, the peak staggering transmission of the ammeter group is realized, and the processing efficiency of the concentrator is remarkably improved.

Inventors

YOU XIAOBO
YANG LEIYANG
Jin Xiaofu
CHEN JIE
XU LINGXIANG
YU XINWEI
GONG YU
XU WANYIN
HUANG RUI
LI TING

Assignees

杭州百富电子技术有限公司

Dates

Publication Date: 20260508
Application Date: 20260407

Claims (8)

1. A data transmission quality optimization method for a smart meter, comprising: Acquiring a sensitivity sequence formed by the calculated sensitivities of each ammeter in the ammeter group in each historical period, and reporting data to a concentrator according to a preset transmission period based on a key update record obtained by calculating the sensitivities exceeding a preset threshold value; Constructing transmission sensitive vectors for the corresponding electric meters according to the sensitivity sequences and the key update records, clustering the electric meter groups by taking all the transmission sensitive vectors as samples to obtain a plurality of electric meter clusters, and assigning a sensitivity level for each electric meter cluster; Dividing a transmission period into a plurality of transmission time slots, establishing a transmission scheduling group for each transmission time slot, and distributing an ammeter group to the plurality of transmission scheduling groups according to the sensitivity level of each ammeter to form an initial corresponding relation between each transmission scheduling group and the transmission time slot; When the current transmission period starts to transmit, acquiring current network state parameters and computing resource state parameters by the concentrator, and computing the resource pressure when the current transmission period starts to transmit according to all the acquired state parameters; The resource pressure is compared with a first pressure threshold value and a second pressure threshold value which are preset, and according to the comparison result, the sum of the transmission sensitivities of all the electric meters in the transmission scheduling groups is used as a load, and the corresponding sequences of the transmission scheduling groups and the transmission time slots are rearranged according to the load; And when each transmission time slot starts, transmitting a transmission instruction to all the ammeter in the transmission scheduling group corresponding to the transmission time slot.
2. The method for optimizing data transmission quality of a smart meter according to claim 1, wherein the transmission sensitivity vector includes a normalized fluctuation coefficient and a key update frequency; Calculating the ratio of the number of times that the sensitivity exceeds a preset threshold value in a history period to the total transmission number in the history period; Wherein the transmission sensitivity is the product of the normalized fluctuation coefficient and the key update frequency.
3. The method for optimizing data transmission quality of a smart meter according to claim 1, wherein assigning a sensitivity level to each meter cluster comprises: dividing an ammeter group into a plurality of ammeter clusters by taking a transmission sensitivity vector of each ammeter as a sample and adopting a K-means clustering algorithm; calculating a cluster sensitivity index of each ammeter cluster, wherein the cluster sensitivity index is an arithmetic average value of transmission sensitivity of all the ammeter in the ammeter cluster; and marking the sensitivity level for each ammeter cluster in sequence according to the sequence from small cluster sensitivity indexes to large cluster sensitivity indexes.
4. The method for optimizing data transmission quality of smart meters according to claim 1, wherein the assigning the group of meters to the plurality of transmission schedule groups according to the sensitivity level of each meter comprises: Taking the electric meters with the sensitivity level larger than a preset level threshold value as high-sensitivity electric meters, and sequentially and circularly distributing each high-sensitivity electric meter into all transmission scheduling groups by adopting a polling distribution method according to the sequence of the sensitivity level from high to low; taking the electric meters with the sensitivity level smaller than or equal to a preset level threshold value as low-sensitivity electric meters, and sequentially distributing each low-sensitivity electric meter to a transmission scheduling group with the minimum current initial load by adopting a greedy equalization algorithm; wherein the initial load of the transmission scheduling group is the sum of the transmission sensitivities of the allocated meters within the group.
5. The method for optimizing data transmission quality of a smart meter according to claim 4, wherein the greedy equalization algorithm comprises: Creating a null member list for each transmission scheduling group, and initializing the load of each transmission scheduling group to be zero; Selecting any low-sensitivity electric meter to be distributed as a target electric meter, respectively calculating temporary loads of transmission scheduling groups after temporarily adding the target electric meter into each transmission scheduling group, constructing initial loads of all other transmission scheduling groups and the temporary loads of the transmission scheduling groups added into the target electric meter to form a load set, further traversing and distributing the target electric meter to all the transmission scheduling groups to obtain a plurality of load sets; when all the low sensitive meters are allocated, the algorithm is terminated.
6. The method for optimizing data transmission quality of a smart meter according to claim 1, wherein the calculation process of the resource pressure includes: Extracting the bandwidth utilization rate and the packet loss rate in the network state parameter and the CPU utilization rate and the memory occupancy rate in the calculation resource state parameter; Calculating the average value of the products of the bandwidth utilization rate and the packet loss rate of all transmission time slots in the previous transmission period of the current transmission period as a first average value, calculating the average value of the products of the CPU utilization rate and the memory occupancy rate of all transmission time slots in the previous transmission period of the current transmission period as a second average value, dividing the first average value by the sum of the first average value and the second average value to obtain network state weight, and taking the difference value of the 1 and the network state weight as calculation resource state weight; The method comprises the steps of multiplying the network state weight by the product of the bandwidth utilization rate and the packet loss rate of the current transmission period to obtain a first component, multiplying the calculation resource state weight by the product of the CPU utilization rate and the memory occupancy rate of the current transmission period to obtain a second component, and adding the first component and the second component to obtain the resource pressure.
7. The method for optimizing data transmission quality of a smart meter according to claim 1 or 6, wherein the comparison result includes: the first pressure threshold is less than the second pressure threshold; When the resource pressure is smaller than or equal to the first pressure threshold, adjusting the transmission scheduling group with the highest temporary load to a first transmission time slot, and sequentially distributing subsequent transmission time slots by the other transmission scheduling groups from high temporary load to low temporary load; When the resource pressure is greater than the first pressure threshold and less than the second pressure threshold, maintaining the initial correspondence; And when the resource pressure is greater than or equal to the second pressure threshold, adjusting the transmission scheduling group with the lowest current load to a first transmission time slot, and sequentially corresponding the rest transmission scheduling groups to subsequent transmission time slots according to the sequence from low load to high load.
8. A data transmission quality optimization system for a smart meter, comprising a processor and a memory, the memory storing computer program instructions that, when executed by the processor, implement the data transmission quality optimization method for a smart meter according to any one of claims 1-7.

Description

Data transmission quality optimization method and system for intelligent ammeter Technical Field The present invention relates to the field of data processing. More particularly, the invention relates to a data transmission quality optimization method and system for a smart meter. Background The intelligent ammeter is used as key metering equipment of the power system, and data are required to be uploaded to the concentrator periodically. Along with the rapid increase of the number of the electric meters, the concurrent uploading of the multiple electric meters easily causes the problems of network congestion, instantaneous load peak value of a concentrator, rising of transmission delay, increasing of packet loss rate and the like, and seriously influences the real-time performance and reliability of data. In the prior art, for example, a patent authorization document announced as CN120934759B provides an electric energy meter data encryption transmission method and device based on edge calculation, and the electric energy meter data encryption transmission method dynamically decides whether to update an encryption key by performing sensitivity analysis on a single electric meter, so that unnecessary encryption and decryption overhead is reduced while safety is ensured. However, the prior art only optimizes the encryption strategy of a single electric meter, and when a large number of electric meters are transmitted simultaneously, the concentrator still faces the shortage of computing resources and the competition of network bandwidth, so that the overall transmission quality is reduced. Disclosure of Invention In order to solve the technical problem that the prior art only optimizes the encryption strategy of a single ammeter, and when a large number of ammeters are transmitted simultaneously, the concentrator still faces the technical problem that the computing resource is tense and the network bandwidth competes, so that the overall transmission quality is reduced, the invention provides the scheme in the following aspects. In a first aspect, a data transmission quality optimization method for a smart meter includes: Acquiring a sensitivity sequence formed by the calculated sensitivities of each ammeter in the ammeter group in each historical period, and reporting data to a concentrator according to a preset transmission period based on a key update record obtained by calculating the sensitivities exceeding a preset threshold value; Constructing transmission sensitive vectors for the corresponding electric meters according to the sensitivity sequences and the key update records, clustering the electric meter groups by taking all the transmission sensitive vectors as samples to obtain a plurality of electric meter clusters, and assigning a sensitivity level for each electric meter cluster; Dividing a transmission period into a plurality of transmission time slots, establishing a transmission scheduling group for each transmission time slot, and distributing an ammeter group to the plurality of transmission scheduling groups according to the sensitivity level of each ammeter to form an initial corresponding relation between each transmission scheduling group and the transmission time slot; When the current transmission period starts to transmit, acquiring current network state parameters and computing resource state parameters by the concentrator, and computing the resource pressure when the current transmission period starts to transmit according to all the acquired state parameters; The resource pressure is compared with a first pressure threshold value and a second pressure threshold value which are preset, and according to the comparison result, the sum of the transmission sensitivities of all the electric meters in the transmission scheduling groups is used as a load, and the corresponding sequences of the transmission scheduling groups and the transmission time slots are rearranged according to the load; And when each transmission time slot starts, transmitting a transmission instruction to all the ammeter in the transmission scheduling group corresponding to the transmission time slot. Preferably, the transmission sensitivity vector contains a normalized fluctuation coefficient and a key update frequency; Calculating the ratio of the number of times that the sensitivity exceeds a preset threshold value in a history period to the total transmission number in the history period; Wherein the transmission sensitivity is the product of the normalized fluctuation coefficient and the key update frequency. Preferably, said assigning a sensitivity level to each cluster of electricity meters comprises: dividing an ammeter group into a plurality of ammeter clusters by taking a transmission sensitivity vector of each ammeter as a sample and adopting a K-means clustering algorithm; calculating a cluster sensitivity index of each ammeter cluster, wherein the cluster sensitivity index is an arithmetic average val