CN110599060A - Method, device and equipment for determining operation efficiency of power distribution network - Google Patents

Method, device and equipment for determining operation efficiency of power distribution network Download PDF

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Publication number
CN110599060A
CN110599060A CN201910894871.5A CN201910894871A CN110599060A CN 110599060 A CN110599060 A CN 110599060A CN 201910894871 A CN201910894871 A CN 201910894871A CN 110599060 A CN110599060 A CN 110599060A
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data
distribution network
efficiency
power distribution
equipment
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CN110599060B (en
Inventor
白浩
于力
梁朔
袁智勇
姜臻
史训涛
张斌
黄彦璐
徐全
郭志诚
陈光侵
陈柔伊
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China Southern Power Grid Co Ltd
Research Institute of Southern Power Grid Co Ltd
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China Southern Power Grid Co Ltd
Research Institute of Southern Power Grid Co Ltd
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
    • G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
    • G06Q50/06—Electricity, gas or water supply
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E40/00—Technologies for an efficient electrical power generation, transmission or distribution
    • Y02E40/70—Smart grids as climate change mitigation technology in the energy generation sector
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
    • Y04S10/00—Systems supporting electrical power generation, transmission or distribution
    • Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications

Abstract

The invention discloses a method for determining the operation efficiency of a power distribution network, which comprises the steps of collecting operation data of each device in the power distribution network, and correcting abnormal conditions in the operation data to eliminate the abnormal conditions; performing efficiency operation according to the operation data to obtain the equipment operation efficiency and the system operation efficiency of the power distribution network; and storing and displaying the equipment operation efficiency and the system operation efficiency based on the visualization tool. According to the method and the device, the operation data of each device in the whole power distribution network are collected in real time, and the operation data are corrected, so that the usability of the operation data is guaranteed; and the equipment operation efficiency and the system operation efficiency of the whole power distribution network are obtained on the basis, the operation condition of the power distribution network can be visually displayed for a user in real time, the accuracy of the operation efficiency is ensured, and convenience is provided for the user to know and manage the operation condition of the power distribution network. The application also provides a device and equipment for determining the operating efficiency of the power distribution network, and the device and equipment have the beneficial effects.

Description

Method, device and equipment for determining operation efficiency of power distribution network
Technical Field
The invention relates to the technical field of power distribution networks, in particular to a method, a device and equipment for determining the operating efficiency of a power distribution network.
Background
Traditional analysis and management of the operating conditions of the power distribution network focus more on the analysis of the utilization rate of equipment in the power distribution network. However, in order to maintain the normal operation of the power distribution network, a large number of necessary redundant devices are often configured in the power distribution network; therefore, when the utilization rate of the equipment in the power distribution network is analyzed, the low utilization rate of the equipment is inevitably caused, and the running condition of the equipment in the power distribution network cannot be accurately reflected. With the comprehensive implementation of lean management, the development of the power distribution network gradually changes from paying attention to the operation quantity and quality of equipment into paying attention to efficiency and benefit, and the operation efficiency and quality are focused.
Therefore, at present, the analysis of the operation condition of the power distribution network is more and more biased to analyze the operation efficiency of the power distribution network. However, at present, an electric power system operator mainly derives load data and network architecture data of a certain time period, a geographical area and a device type from each data platform or database of an electric power system, and finally obtains operation efficiency according to the data.
Disclosure of Invention
The invention aims to provide a method, a device and equipment for determining the operating efficiency of a power distribution network, solves the problems of low analysis efficiency, time and labor consumption and poor accuracy of the operating efficiency of the power distribution network, and provides convenience for users to know and manage the operating conditions of the power distribution network.
In order to solve the technical problem, the invention provides a method for determining the operating efficiency of a power distribution network, which comprises the following steps:
receiving operation data of each device in the power distribution network in real time through each data service interface, wherein the operation data at least comprises line data, transformer load data, rated capacity data and device asset data;
judging whether the operation data has abnormal conditions or not, if so, correcting the operation data to eliminate the abnormal conditions;
carrying out efficiency operation on the operation data without abnormal conditions to obtain the equipment operation efficiency and the system operation efficiency of the power distribution network;
and storing the equipment operating efficiency and the system operating efficiency, and displaying the equipment operating efficiency and the system operating efficiency based on a visualization tool.
Optionally, the determining whether the running data has an abnormal condition includes:
performing position sequencing on the operation data according to a fitting time sequence model by taking acquisition time as a sequence;
performing positive-too correction on the sequenced operation data by using a fitting residual error algorithm;
and judging whether the running data after being corrected too much has data loss and/or data abnormity.
Optionally, the correcting the operation data includes:
when the running data has data missing, recording position coordinates of the data missing;
according to the position coordinates of the data missing, 2m running data with the acquisition time closest to the acquisition time corresponding to the position of the data missing are obtained and serve as interpolation cardinality, wherein m is a positive integer;
obtaining a plurality of complementary deficiency values by adopting at least three interpolation methods;
and taking the average value of a plurality of supplementary missing values as the data of the missing data position.
Optionally, the correcting the operation data includes:
when the running data has data abnormality, recording the position coordinates of the abnormal data;
acquiring 2n running data with the acquisition time closest to the acquisition time corresponding to the position of the abnormal data as an adjacent node data set according to the position coordinates of the abnormal data, wherein n is a positive integer;
obtaining correction data by adopting a solution deviation algorithm according to the operating data in the adjacent node data set;
and replacing the abnormal data with the corrected data.
Optionally, the performing efficiency operation on the operation data without the abnormal condition to obtain the equipment operation efficiency of the power distribution network and the operation efficiency of the power distribution network system includes:
acquiring equipment load values and equipment reference load values of each equipment in the power distribution network according to the operation data;
obtaining the equipment operation efficiency according to the equipment load value and the equipment reference load value;
according to the equipment operation efficiency, obtaining the system operation efficiency as follows:wherein eta isiFor operation of apparatus iEfficiency; n is the total number of the equipment; vuiThe value of the warehousing asset of the equipment i; alpha is alphaiThe monthly depreciation rate for device i; moiThe number of operating months of the device i.
Optionally, the method further comprises:
monitoring the load data volume of each data service interface;
and carrying out balanced migration according to the load data volume.
Optionally, the monitoring the load data amount of each data service interface includes:
acquiring the utilization rate of a processor, the memory occupancy rate, the disk utilization rate, the disk read-write rate and the load data volume when each data service interface receives the operation data according to a preset period;
obtaining load indexes of the data service interfaces according to the processor utilization rate, the memory occupancy rate, the disk utilization rate, the disk read-write rate and the load data volume;
obtaining a load variance factor of each service interface according to each load index;
and judging whether the load variance factor is larger than a preset balance threshold value or not.
Optionally, the performing balanced migration according to the load data amount includes:
when the load variance factor is larger than the preset balance threshold, slicing the load data volume according to the unit data volume to obtain a data volume slice;
establishing a balance optimal function of the load data volume of each data service interface according to the number of data volume slices of each data service interface, the utilization rate of the processor, the memory occupancy rate, the utilization rate of the disk and the read-write rate of the disk;
and obtaining the data load migration volume of each data service interface according to the balance optimal function.
The application also provides a distribution network operating efficiency determination device, includes:
the data receiving module is used for receiving operation data of each device in the power distribution network through each data service interface, wherein the operation data at least comprises line data, transformer load data and rated capacity data;
the data correction module is used for judging whether the operating data have abnormal conditions or not, and if so, correcting the operating data to eliminate the abnormal conditions;
the efficiency operation module is used for performing efficiency operation on the operation data without abnormal conditions to obtain the equipment operation efficiency and the system operation efficiency of the power distribution network;
and the storage display module is used for storing the equipment operating efficiency and the system operating efficiency and displaying the equipment operating efficiency and the system operating efficiency based on a visualization tool.
The application also provides a distribution network operating efficiency confirms equipment, includes:
a memory for storing a computer program;
a processor for executing the computer program to implement the steps of the method for determining the operating efficiency of a power distribution network as described in any one of the above.
The method for determining the operation efficiency of the power distribution network comprises the following steps: receiving operation data of each device in the power distribution network in real time through each data service interface, wherein the operation data at least comprises line data, transformer load data and rated capacity data of each device; judging whether the operation data has abnormal conditions or not, if so, correcting the operation data to eliminate the abnormal conditions; performing efficiency operation according to the operation data without abnormal conditions to obtain the equipment operation efficiency and the system operation efficiency of the power distribution network; and displaying the equipment operating efficiency and the system operating efficiency based on the visualization tool.
According to the method and the device, the operation data of each device in the whole power distribution network are collected in real time, and the operation data are corrected, so that the usability of the operation data is guaranteed; the equipment operation efficiency and the system operation efficiency of the whole power distribution network are obtained on the basis, the operation condition of the power distribution network can be visually displayed for a user in real time, excessive complex operation is not required to be performed under a manual line, and the accuracy of the operation efficiency is ensured; in addition, the obtained operation efficiency is stored, so that the subsequent checking and comparison of the user are facilitated, the checking of the operation efficiency is more convenient and visual, and convenience is provided for the user to know and manage the operation condition of the power distribution network.
The application also provides a device and equipment for determining the operating efficiency of the power distribution network, and the device and equipment have the beneficial effects.
Drawings
In order to more clearly illustrate the embodiments or technical solutions of the present invention, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained based on these drawings without creative efforts.
Fig. 1 is a schematic flow chart of a method for detecting and analyzing operation efficiency of a power distribution network according to an embodiment of the present invention;
FIG. 2 is a flow chart illustrating a process for correcting missing data according to an embodiment of the present invention;
FIG. 3 is a flow chart illustrating a process for correcting data anomalies according to an embodiment of the present invention;
FIG. 4 is a schematic flow chart of obtaining operating efficiency according to an embodiment of the present invention;
fig. 5 is a schematic process diagram for monitoring the load data amount of each data service interface according to the embodiment of the present invention;
fig. 6 is a block diagram of a power distribution network operation efficiency determination apparatus according to an embodiment of the present invention.
Detailed Description
In order that those skilled in the art will better understand the disclosure, the invention will be described in further detail with reference to the accompanying drawings and specific embodiments. It is to be understood that the described embodiments are merely exemplary of the invention, and not restrictive of the full scope of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As shown in fig. 1, fig. 1 is a schematic flow chart of a method for detecting and analyzing operation efficiency of a power distribution network according to an embodiment of the present invention, where the method may include:
step S11: and receiving the operation data of each device in the power distribution network in real time through each data service interface.
Wherein the operational data includes at least line data, transformer load data, rated capacity data, and equipment asset data.
The operation data mainly provides basic data for operation efficiency analysis by adopting a standard ECIM data model interface; the operation data comprises data provided by a power distribution and utilization big data analysis platform, a data integration platform, a mass quasi-real-time platform and the like, for example, the power distribution and utilization big data analysis platform acquires customer file information, equipment file information and a grid structure through the data integration platform; acquiring real-time measurement data of equipment such as lines, transformer areas and the like through a mass quasi-real-time platform, and acquiring related meteorological data and other operation data; further, the equipment asset data is a cost price of the equipment itself, and is important data for analyzing a relationship between the use efficiency of the equipment and the equipment value.
According to the method and the device, the running data in the whole power distribution network are comprehensively and automatically collected through the plurality of data service interfaces, and preparation is made for analyzing the running conditions of all devices in the power distribution network subsequently.
Step S12: and judging whether the operation data has abnormal conditions, if so, entering the step S13, and if not, entering the step S14.
In order to ensure the accuracy of the operation data, the operation data can be corrected after the operation data is collected so as to ensure the accuracy and reliability of the operation data.
Step S13: the operational data is corrected to eliminate the abnormal situation.
Step S14: and carrying out efficiency operation on the operation data without abnormal conditions to obtain the equipment operation efficiency and the system operation efficiency of the power distribution network.
Specifically, after the operation data is collected, the operation efficiency in the whole power distribution network is automatically calculated. Because the operation data is collected in real time, the equipment operation efficiency and the system operation efficiency in the power distribution network can be correspondingly solved in real time, so that a user can know the operation condition of the power distribution network in time.
Step S15: and displaying the equipment operating efficiency and the system operating efficiency based on the visualization tool.
Specifically, after obtaining the device operating efficiency and the system operating efficiency, the data may be stored in a corresponding database, so that a subsequent worker may call to view the historical data.
In addition, a visualization display tool based on Echarts, Java and the like can be adopted, and the load monitoring and the operation efficiency monitoring of the power distribution network system and the main equipment can be realized in the form of a multi-dimensional chart and list, wherein the monitoring comprises the multi-dimensional operation efficiency monitoring, the operation efficiency abnormal characteristics, the abnormal condition tracing correlation factor display and the operation efficiency overall trend.
At present, an electric power system operator mainly adopts an offline manual mode to analyze the operation efficiency. Load data and network architecture data of a certain time period, a geographical area, equipment types are derived from each data platform or database of the power system. And checking and filtering the manual data according to the working experience, eliminating abnormal data to supplement vacant data, inputting an operating efficiency calculation formula to complete calculation, and displaying an operating efficiency result in a curve form. The method relies on manual calculation, data errors are easy to occur, interaction and calculation of mass data are difficult to support, the data analysis function is weak, and multi-dimensional analysis and practicability cannot be flexibly developed; in addition, in the prior art, analysis of the operation condition in the power system is more focused on analysis of the operation efficiency of a single device, and when the operation efficiency of the single device and the operation efficiency of the system are known, which device has the largest influence on the operation efficiency of the system can be analyzed, comparison among different regional systems, aggregation analysis of a plurality of regional systems and the like are performed, so that the analysis method has a stronger analysis function.
According to the method and the device, the operation data of each device in the whole power distribution network are collected in real time, and the operation data are corrected, so that the usability of the operation data is guaranteed; the equipment operation efficiency and the system operation efficiency of the whole power distribution network are obtained on the basis, the operation condition of the power distribution network can be visually displayed for a user in real time, excessive complex operation is not required to be performed under a manual line, and the accuracy of the operation efficiency is ensured; in addition, the obtained operation efficiency is stored, so that the subsequent checking and comparison of the user are facilitated, the checking of the operation efficiency is more convenient and visual, and convenience is provided for the user to know and manage the operation condition of the power distribution network. Therefore, the monitoring and analyzing method for the operation efficiency of the power distribution network, provided by the application, realizes a monitoring and analyzing system for the operation efficiency of the power distribution network, which is used for integrating, monitoring, butting, analyzing and processing mass data of the power distribution network in real time and displaying the mass data intelligently, helps a power distribution network to operate and maintain, and a planning and designing person to analyze the operation data of power distribution network equipment more intuitively, efficiently and comprehensively, accurately grasp the operation condition of the equipment, timely and effectively operate control measures, and provides technical support for the power distribution network from planning to operation.
Based on the above embodiment, in step S12, it is considered that errors and anomalies may exist in the collected operation data, and therefore, before performing efficiency operation, the received operation data needs to be cleaned, repaired and correlated, the error data and the anomaly data are eliminated, standardization and formatting of the data are realized, and basic data with strong business relevance is coupled and correlated to provide application data satisfying strong operation efficiency calculation analysis; the specific processing method can comprise the following steps:
performing position sequencing on the operation data according to a fitting time sequence model by taking acquisition time as a sequence;
and performing positive correction on the sorted running data by using a fitting residual error algorithm.
And judging whether the running data which is corrected too much has data missing or data abnormity.
Specifically, the abnormal data identification is performed on the service data, that is, the operation data, based on the Grubbs (Grubbs) and the service specification. The method comprises the steps of sequencing multi-source operation data, specifically sequencing the positions of the operation data in sequence of time for acquiring the operation data according to a fitting time sequence ARIMA model, and performing positive correction on the sequenced operation data by using a fitting residual error algorithm. The abnormal condition of the operation data comprises two conditions of data loss or data abnormity.
For data missing and data abnormality of the operating data, different modes can be adopted for correction respectively.
Optionally, as shown in fig. 2, fig. 2 is a schematic flow chart of a data missing correction process according to an embodiment of the present invention. The process of correcting the data missing may include:
step S21: and when the running data has data missing, recording the position coordinates of the data missing.
Step S22: and acquiring 2m running data with the acquisition time closest to the acquisition time corresponding to the data missing position as an interpolation base number according to the position coordinates of the data missing.
Wherein m is a positive integer.
The operation data are collected in real time or according to a preset time interval in the power distribution network, so that the change of the operation data in a short time is not obvious, the operation data in an adjacent time period do not change too much, namely the operation data in the adjacent time period have strong relevance, and the operation data collected in the adjacent time period is used for correcting the correction base number of missing data, so that more accurate operation data can be obtained.
Step S23: and obtaining a plurality of supplementary missing values by adopting at least three interpolation methods.
Step S24: and taking the average value of the plurality of supplementary missing values as data corresponding to the missing data position.
Specifically, a data missing value may be recorded as xtThe interpolation radix is accordingly Ω ═ xt-m,...,xt-1,xt+1,...,xt+m]Wherein x ist-mTo xt+mAre respectively in time sequenceAnd acquiring the value of the same type of operation data.
Based on interpolation technology, q interpolation methods, such as Newton interpolation method, Lagrange function and cubic spline function, are adopted to calculate the numerical value of the missing point as a supplement missing valueTaking the average value of a plurality of supplementary missing values as a data missing value
The correction method adopted in the embodiment can analyze the distribution condition of time sequence data, and improves the accuracy by adopting the calculation of missing value data and adjacent data; the value of the m value can be selected according to the accuracy and the computing resource, and the size of the adjacent range has flexibility.
Optionally, as shown in fig. 3, fig. 3 is a schematic flow chart of a process of correcting a data anomaly according to an embodiment of the present invention. The process of correcting the data anomaly may include:
step S31: and when the running data has data abnormality, recording the position coordinates of the abnormal data.
Step S32: acquiring 2n running data with the acquisition time closest to the acquisition time corresponding to the abnormal data as an adjacent node data set according to the position coordinates of the abnormal data;
wherein n is a positive integer.
Step S33: and obtaining correction data by adopting a solution deviation algorithm according to the operating data in the adjacent node data set.
Step S34: replacing the abnormal data with corrected data.
In particular, the anomalous data may be labeled xrReading nearby 2n running data as a set of adjacent nodes Z ═ xr-n,xr-1,xr+1,,xr+n]And solving the deviation beta of the data in the set, for the average of all elements in the set, δxAll element variances are aggregated.
Setting a deviation threshold epsilon and screening betaiOperating data x corresponding to ≧ epsiloniForming a running data set gamma, and taking the average value of the maximum running data and the minimum running data in the set as abnormal data
In the embodiment, the corrected data candidate set is determined according to the analysis result of variance of the abnormal data and the adjacent data, so that the deviation between the abnormal data and the surrounding data can be accurately analyzed; then, selecting the average value of the maximum value and the minimum value of the corrected data candidate set, and comprehensively considering the possible upper bound and the lower bound of abnormal data by the method, thereby obtaining more reasonable data and ensuring the reliability of the operating data; and the value of n can be selected according to the precision and the computing resource, and the size of the adjacent range has flexibility.
Based on the embodiment, on the basis of obtaining more accurate operation data, the invention further provides a specific embodiment for obtaining the equipment operation efficiency and the power distribution network system operation efficiency. As shown in fig. 4, fig. 4 is a schematic flowchart of obtaining operation efficiency according to an embodiment of the present invention, where the process may include:
step S41: and obtaining the equipment load value and the equipment reference load value of each equipment in the power distribution network according to the operation data.
For line equipment and transformers, the equipment load value is the transmission active power of the line and the transformers, and the equipment reference load value is the rated capacity.
Step S42: and obtaining the equipment operation efficiency according to the equipment load value and the equipment reference load value.
Step S43: according to the equipment operation efficiency, the obtained system operation efficiency is as follows:
wherein eta isiThe operating efficiency of the equipment i; n is the total number of the equipment; vuiThe value of the warehousing asset of the equipment i; alpha is alphaiThe monthly depreciation rate for device i; moiThe number of operating months of the device i.
In particular, equipment operating efficiency in a power distribution network may be based onObtaining wherein p isiA device load value (actual load value) representing a device i;is the reference load value of the device i; etaiThe operating efficiency of the equipment i; from which the individual device operating efficiencies can be calculated. The system operation efficiency can be obtained through the equipment operation efficiency.
As described above, in the present application, a large amount of operation data needs to be received through the interface server, but when a business application needs transmission and calculation of a large amount of data, load pressure of a data service interface is increased, which results in a reduction in service quality, and therefore, in another embodiment of the present invention, the method may further include:
monitoring the load data volume of each data service interface; and carrying out balanced migration according to the load data volume.
Specifically, when the load pressure of the data service interfaces increases, service balance expansion is automatically performed, so that the data volume of the operation data collected by each data service interface is migrated, the pressure of the operation data collected by each data service interface is reduced, and the service quality of the data service interfaces is not reduced.
Specifically, as shown in fig. 5, fig. 5 is a schematic diagram of a process for monitoring load data amount of each data service interface according to an embodiment of the present invention, where the process may include:
step S51: and acquiring the utilization rate of a processor, the memory occupancy rate, the disk utilization rate, the disk read-write rate and the load data volume when each data service interface receives the operating data according to a preset period.
Step S52: and obtaining the load index of each data service interface according to the utilization rate of the processor, the memory occupancy rate, the utilization rate of the disk, the read-write rate of the disk and the load data volume.
Step S53: and obtaining the load variance factor of each service interface according to each load index.
Specifically, the processor utilization may be set to LcThe memory occupancy rate is LrAnd the disk usage rate is LsThe disk read-write rate is LtAnd load data amount is LD; whereby the load index of each of said data service interfaces is Lci＝LDici，Lri＝LDiri，Lsi＝LDi(ii) S; wherein i represents a serial number of a data service interface, and c is a processor operation amount of a unit data amount; r is the memory occupation amount per unit data volume; and S is the size of the disk space.
According to the load index, the load variance factor is obtained as follows:wherein the content of the first and second substances,Di＝λ1Lci+λ2Lri+λ3Lsi，λ1、λ2、λ3the weighting coefficients are constant coefficients, and N represents the number of data service interfaces.
The load variance factor reflects the load pressure of the data service interface, so that the load variance factor is an important basis for judging whether each data service interface needs to perform data balanced migration.
Step S54: and when the load variance factor is larger than a preset balance threshold, slicing the load data volume according to the unit data volume to obtain a data volume slice.
The data volume of the operation data required to be received by each data service interface is different, and if the data volume corresponding to a certain data service interface is too large, the data volume of the data service interface needs to be migrated, so that the data volume of the operation data required to be received by each data service interface is uniformly distributed as much as possible, and the service pressure of each data service interface is uniform.
The load variance factor is a parameter for measuring the pressure balance of each data service interface, and if the load variance factor is larger, the difference between the load pressures of the data service interfaces is larger, so that a specific preset balance threshold value can be set, and the data size can be migrated only when the load variance factor is larger than the preset balance threshold value.
When migrating the load data volume of the data service interfaces, the data volume of each data service interface may be counted, and the total load of all the data service interfaces may be sliced by a unit data volume.
Step S55: and establishing a balanced optimal function of the load data volume of each data service interface according to the number of data volume slices of each data service interface, the utilization rate of a processor, the memory occupancy rate, the utilization rate of a disk and the read-write rate of the disk.
The processor utilization rate, the memory occupancy rate, the disk utilization rate and the disk read-write rate of each data service interface are the embodiment of the capacity of the data service interface for processing the load data volume.
To obtain an equalization optimization function:the constraint conditions of the equalization optimization function are as follows:
where M is the number of slices, Δ LD is the amount of load data in each slice, and t is the time taken for data migration. m isiNumber of slices, m, representing the ith data service interface to be migratediTo positively indicate immigration by other data service interfaces, miNegative means immigration to other data service interfaces; l istiAnd the disk read-write speed of the ith data service interface.
For example: there are three data service interfaces A, B, C;
a, the utilization rate of a processor is 50 percent, and the memory occupancy rate is 80 percent; the utilization rate of the disk is 40%;
b, the utilization rate of the processor is 80 percent, and the memory occupancy rate is 20 percent; the utilization rate of the disk is 30%;
c: the processor utilization rate is 20%, and the memory occupancy rate is 60%; the utilization rate of the disk is 60%;
the difference of the three indexes of the three data service interfaces requires that the amount of the received data tasks is balanced among A, B, C, so that the index deviation among A, B, C is minimum, namely the load variance factor in the balanced optimal function is minimum.
Meanwhile, the disk read-write speeds of ABC are different, and when the task amount is transferred, the read-write time is the shortest, namely the read-write time in the balanced optimal function is the smallest.
For the equalization optimization function, an optimal solution needs to be found under a constraint condition, and there may be a variety of specific methods for finding the optimal solution, such as a genetic algorithm, a traversal method, and the like, which are not listed here.
Step S56: and obtaining the data load migration volume of each data service interface according to the balance optimal function.
In this embodiment, when efficiency analysis operation is performed, a large amount of operation data needs to be collected in statistics, so that the load pressure of each data service interface is large, and the operation efficiency analysis result is more timeliness for ensuring, the capability of the data service interface for collecting the operation data needs to be ensured, therefore, in this embodiment, the load of the data service interface is monitored in real time, the load balance of each data service interface is ensured to the maximum extent, so that the whole data service interface is ensured to have stronger capability of receiving and collecting the operation data, and the timeliness of the operation efficiency analysis is improved.
In the following, the power distribution network operation efficiency determination device provided by the embodiment of the present invention is introduced, and the power distribution network operation efficiency determination device described below and the power distribution network operation efficiency determination method described above may be referred to in a corresponding manner.
Fig. 6 is a block diagram of a power distribution network operation efficiency determining device according to an embodiment of the present invention, where, referring to fig. 6, the power distribution network operation efficiency determining device may include:
the data receiving module 100 is configured to receive operation data of each device in the power distribution network through each data service interface, where the operation data at least includes line data, transformer load data, rated capacity data, and device asset data;
the data correction module 200 is configured to determine whether the operating data has an abnormal condition, and if so, correct the operating data to eliminate the abnormal condition;
the efficiency operation module 300 is configured to perform efficiency operation on operation data without abnormal conditions, so as to obtain the equipment operation efficiency and the system operation efficiency of the power distribution network;
and a storage and display module 400, configured to store the device operating efficiency and the system operating efficiency, and display the device operating efficiency and the system operating efficiency based on a visualization tool.
Optionally, in another specific embodiment of the present invention, the data correction module 200 is specifically configured to perform position sorting on the operation data according to a fitted time series model by using the collection time as a sequence; performing positive-too correction on the sequenced operation data by using a fitting residual error algorithm; and judging whether the running data after being corrected too much has data loss and/or data abnormity.
Optionally, in another embodiment of the present invention, the data correction module 200 is specifically configured to, when there is data missing in the operation data, record a position coordinate of the data missing; according to the position coordinates of the data missing, 2m running data with the acquisition time closest to the acquisition time corresponding to the position of the data missing are obtained and serve as interpolation cardinality, wherein m is a positive integer; obtaining a plurality of complementary deficiency values by adopting at least three interpolation methods; and taking the average value of the plurality of supplementary missing values as the data corresponding to the data missing position.
Optionally, in another specific embodiment of the present invention, the data correction module 200 is specifically configured to, when there is data abnormality in the operation data, record a position coordinate of the abnormal data; acquiring 2n running data with the acquisition time closest to the acquisition time corresponding to the abnormal data position as an adjacent node data set according to the position coordinates of the abnormal data, wherein n is a positive integer; obtaining the correction data by adopting a solution deviation algorithm according to the operating data in the adjacent node data set; and replacing the abnormal data with the corrected data.
Optionally, in another specific embodiment of the present invention, the efficiency calculation module 300 is specifically configured to calculate and obtain an equipment load value and an equipment reference load value of each equipment in the power distribution network according to the operation data; calculating to obtain the equipment operation efficiency according to the equipment load value and the equipment reference load value; according to the equipment operation efficiency, obtaining the system operation efficiency as follows:wherein eta isiThe efficiency of the equipment operation; n is the total number of the equipment; vuiIs the value of the warehousing asset of the equipment; alpha is alphaiThe monthly depreciation rate; moiIs the number of months of operation.
Optionally, in another specific embodiment of the present invention, the system further includes a balance migration module, configured to monitor a load data volume of each data service interface; and carrying out balanced migration according to the load data volume.
Optionally, in another specific embodiment of the present invention, the balance migration module is specifically configured to collect, according to a preset period, a utilization rate of the processor, a memory occupancy rate, a utilization rate of a disk, a read-write rate of the disk, and a load data volume when each data service interface receives the operation data; obtaining load indexes of the data service interfaces according to the processor utilization rate, the memory occupancy rate, the disk utilization rate, the disk read-write rate and the load data volume; obtaining a load variance factor of each service interface according to each load index; and judging whether the load variance factor is larger than a preset balance threshold value or not.
Optionally, in another specific embodiment of the present invention, the balance migration module is specifically configured to, when the load variance factor is greater than the preset balance threshold, slice the load data amount according to a unit data amount to obtain a data amount slice; establishing a balance optimal function of the load data volume of each data service interface according to the number of data volume slices of each data service interface, the utilization rate of the processor, the memory occupancy rate, the utilization rate of the disk and the read-write rate of the disk; and obtaining the data load migration volume of each data service interface according to the balance optimal function.
The distribution network operation efficiency determining apparatus of this embodiment is used to implement the foregoing distribution network operation efficiency determining method, and therefore specific embodiments of the distribution network operation efficiency determining apparatus can be seen in the foregoing embodiments of the distribution network operation efficiency determining method, for example, the data receiving module 100, the data correcting module 200, the efficiency calculating module 300, and the storage and display module 400 are respectively used to implement steps S11, S12, S13, and S14 in the foregoing distribution network operation efficiency determining method, so that specific embodiments thereof may refer to descriptions of corresponding partial embodiments, and are not described herein again.
The application also provides a distribution network operating efficiency confirms equipment, includes:
a memory for storing a computer program;
a processor configured to execute the computer program to implement the steps of the method for determining the operating efficiency of the power distribution network according to any of the above embodiments.
In particular, the memory may be Random Access Memory (RAM), memory, Read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.
Those of skill would further appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the various illustrative components and steps have been described above generally in terms of their functionality in order to clearly illustrate this interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
The embodiments are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same or similar parts among the embodiments are referred to each other. The device disclosed by the embodiment corresponds to the method disclosed by the embodiment, so that the description is simple, and the relevant points can be referred to the method part for description.

Claims (10)

1. A method for determining the operating efficiency of a power distribution network is characterized by comprising the following steps:
receiving operation data of each device in the power distribution network in real time through each data service interface, wherein the operation data at least comprises line data, transformer load data, rated capacity data and device asset data;
judging whether the operation data has abnormal conditions or not, if so, correcting the operation data to eliminate the abnormal conditions;
carrying out efficiency operation on the operation data without abnormal conditions to obtain the equipment operation efficiency and the system operation efficiency of the power distribution network;
and storing the equipment operating efficiency and the system operating efficiency, and displaying the equipment operating efficiency and the system operating efficiency based on a visualization tool.
2. The method for determining the operating efficiency of the power distribution network according to claim 1, wherein the determining whether the operating data has an abnormal condition comprises:
performing position sequencing on the operation data according to a fitting time sequence model by taking acquisition time as a sequence;
performing positive-too correction on the sequenced operation data by using a fitting residual error algorithm;
and judging whether the running data after being corrected too much has data loss and/or data abnormity.
3. The method of determining the operational efficiency of a power distribution network of claim 2, wherein said correcting said operational data comprises:
when the running data has data missing, recording position coordinates of the data missing;
according to the position coordinates of the data missing, 2m running data with the acquisition time closest to the acquisition time corresponding to the position of the data missing are obtained and serve as interpolation cardinality, wherein m is a positive integer;
obtaining a plurality of complementary deficiency values by adopting at least three interpolation methods;
and taking the average value of the plurality of supplementary missing values as the data corresponding to the data missing position.
4. The method of determining the operational efficiency of a power distribution network of claim 2, wherein said correcting said operational data comprises:
when the running data has data abnormality, recording the position coordinates of the abnormal data;
acquiring 2n running data with the acquisition time closest to the acquisition time corresponding to the position of the abnormal data as an adjacent node data set according to the position coordinates of the abnormal data, wherein n is a positive integer;
obtaining correction data by adopting a solution deviation algorithm according to the operating data in the adjacent node data set;
and replacing the abnormal data with the corrected data.
5. The method for determining the operation efficiency of the power distribution network according to claim 1, wherein the performing the efficiency operation on the operation data without the abnormal condition to obtain the equipment operation efficiency of the power distribution network and the operation efficiency of the power distribution network system comprises:
acquiring equipment load values and equipment reference load values of each equipment in the power distribution network according to the operation data;
obtaining the equipment operation efficiency according to the equipment load value and the equipment reference load value;
according to the equipment operation efficiency, obtaining the system operation efficiency as follows:wherein eta isiThe operating efficiency of the equipment i; n is the total number of the equipment; vuiThe value of the warehousing asset of the equipment i; alpha is alphaiThe monthly depreciation rate for device i; moiThe number of operating months of the device i.
6. The method for determining the operating efficiency of a power distribution network according to any one of claims 1 to 5, further comprising:
monitoring the load data volume of each data service interface;
and carrying out balanced migration according to the load data volume.
7. The method for determining the operating efficiency of the power distribution network according to claim 6, wherein the monitoring of the load data amount of each of the data service interfaces comprises:
acquiring the processor utilization rate, the memory occupancy rate, the disk utilization rate, the disk read-write rate and the load data volume when each data service interface receives the operating data according to a preset period;
obtaining load indexes of the data service interfaces according to the processor utilization rate, the memory occupancy rate, the disk utilization rate, the disk read-write rate and the load data volume;
obtaining a load variance factor of each service interface according to each load index;
and judging whether the load variance factor is larger than a preset balance threshold value or not.
8. The method for determining the operation efficiency of the power distribution network according to claim 7, wherein the performing balanced migration according to the load data amount comprises:
when the load variance factor is larger than the preset balance threshold, slicing the load data volume according to the unit data volume to obtain a data volume slice;
establishing a balance optimal function of the load data volume of each data service interface according to the number of data volume slices of each data service interface, the utilization rate of the processor, the memory occupancy rate, the utilization rate of the disk and the read-write rate of the disk;
and obtaining the data load migration volume of each data service interface according to the balance optimal function.
9. An apparatus for determining operating efficiency of a power distribution network, comprising:
the data receiving module is used for receiving operation data of each device in the power distribution network through each data service interface, wherein the operation data at least comprises line data, transformer load data and rated capacity data;
the data correction module is used for judging whether the operating data have abnormal conditions or not, and if so, correcting the operating data to eliminate the abnormal conditions;
the efficiency operation module is used for performing efficiency operation on the operation data without abnormal conditions to obtain the equipment operation efficiency and the system operation efficiency of the power distribution network;
and the storage display module is used for storing the equipment operating efficiency and the system operating efficiency and displaying the equipment operating efficiency and the system operating efficiency based on a visualization tool.
10. An apparatus for determining operating efficiency of a power distribution network, comprising:
a memory for storing a computer program;
a processor for executing said computer program to carry out the steps of the method of determining the operating efficiency of an electric distribution network according to any one of claims 1 to 8.
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