CN114579638A - Line loss abnormity technical cause analysis method and system - Google Patents

Line loss abnormity technical cause analysis method and system Download PDF

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Publication number
CN114579638A
CN114579638A CN202210229702.1A CN202210229702A CN114579638A CN 114579638 A CN114579638 A CN 114579638A CN 202210229702 A CN202210229702 A CN 202210229702A CN 114579638 A CN114579638 A CN 114579638A
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China
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line loss
parameters
power grid
technical
grid system
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CN202210229702.1A
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Chinese (zh)
Inventor
吴丽贤
罗秀红
伍慧君
黄健
庞伟林
陈冠健
宋才华
关兆雄
林钰杰
杨峰
张小双
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Guangdong Topway Network Co ltd
Foshan Power Supply Bureau of Guangdong Power Grid Corp
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Guangdong Topway Network Co ltd
Foshan Power Supply Bureau of Guangdong Power Grid Corp
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Priority to CN202210229702.1A priority Critical patent/CN114579638A/en
Publication of CN114579638A publication Critical patent/CN114579638A/en
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/24—Querying
    • G06F16/245—Query processing
    • G06F16/2458—Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
    • G06F16/2462—Approximate or statistical queries
    • 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
    • G06Q10/0635—Risk analysis of enterprise or organisation activities
    • 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
    • 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
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
    • H02J13/00002—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by monitoring
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
    • H02J13/00004—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by the power network being locally controlled
    • 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 application discloses a line loss abnormity technical reason analysis method and a system, wherein the method comprises the following steps: acquiring line loss abnormality which occurs historically; acquiring the technical reason of each line loss abnormality which occurs in history; integrating technical reasons corresponding to the line loss abnormality in each history to obtain a reason judgment rule of the line loss abnormality; obtaining parameters of a power grid system, and determining technical causes of line loss abnormity occurring under the parameters according to the parameters in the power grid system and the cause judgment rule, wherein the parameters of the power grid system comprise: current data, voltage data, power factor, three phase imbalance rate, and load data. The method and the device solve the problems that the existing line loss analysis method in the prior art depends on manual operation and is low in efficiency and high in cost, so that the automatic analysis of the line loss abnormal technical reason judgment rules is realized, line loss abnormal technical reason analysis data are automatically generated, and business personnel are assisted to make and execute technical loss reduction measures.

Description

Line loss abnormity technical cause analysis method and system
Technical Field
The application relates to the field of power grids, in particular to a line loss abnormity technical reason analysis method and system.
Background
Along with the improvement of the management level of the power supply enterprise, the refinement degree of the line loss management is correspondingly and continuously improved, and the actual line loss of the power supply enterprise is represented as the difference value of the power supply and power sale amounts, namely the line loss is counted. The influence factors of line loss statistics comprise technical line loss and management line loss, wherein the management line loss is generated by artificial factors such as imperfect regulations and is always taken as a direction of key analysis and management by power supply enterprises, line loss abnormity analysis methods are mostly used for carrying out abnormity investigation and treatment on the management line loss, analysis on the technical reasons of the line loss abnormity is often ignored, and effective technical means and systems are lacked for carrying out line loss abnormity technical reason analysis. The technical line loss comprises fixed loss, namely iron loss of all excitation circuits such as transformers, measuring instruments, secondary circuits and the like; the variable loss is the copper loss of the line, the transformer and the like which is proportional to the square of the current. The line loss of the medium and low voltage distribution network is large due to large power supply radius, small line diameter, insufficient reactive power compensation and the like, so that the technical reasons of line loss abnormity are urgently needed to be analyzed systematically and automatically, and targeted measures are taken to reduce the loss.
The technical line loss relates to a plurality of aspects, such as power transmission and distribution equipment, a power grid structure, an operation mode, load change and the like, and each scene has specific analysis skills and methods. Therefore, for the analysis of the technical line loss data, various operation guidance and analysis methods exist, the method depends too much on the experience of people, a systematic and automatic analysis thought is not formed, and the analysis work efficiency of the abnormal reasons of the technical line loss is low.
Therefore, how to accurately analyze the abnormal reason of the technical line loss and accurately position the abnormal metering point, so as to pertinently make an effective technical loss reduction measure and promote timely and effective processing of the abnormal line loss is a technical problem which needs to be solved in the field.
Most of the methods adopted by the technical line loss analysis work of power supply enterprises at present are as follows: and (4) obtaining the reasons of the abnormal technical line loss and specific users influencing the technical line loss by combining human experience analysis and judgment on the basis of analyzing and comparing the service data according to the power grid operation, history and real-time power utilization data of each service information system by means of manual analysis and judgment. The existing line loss analysis method mainly has the following problems: (1) a large amount of data needs manual collection, analysis and judgment, continuous work cannot be achieved, and the working efficiency is low. (2) The process of line loss analysis is closely related to the skills, emotion, physical strength and the like of workers, belongs to uncontrollable factors, and has great working randomness. (3) Occupies a large amount of human resources and has high labor cost.
Disclosure of Invention
The embodiment of the application provides a line loss abnormal technical reason analysis method and system, and aims to at least solve the problems that the existing technical line loss analysis method depends on manual operation, and is low in efficiency and high in cost.
According to one aspect of the application, a line loss abnormality technical cause analysis method is provided, and the method comprises the following steps: acquiring line loss abnormality which occurs historically; acquiring technical reasons of each historical line loss abnormality, wherein the technical reasons comprise: line loss abnormality caused by power factors, line loss abnormality caused by voltage or current three-phase imbalance, line loss abnormality caused by load extreme values, and line loss abnormality caused by low voltage or high voltage; integrating technical reasons corresponding to the line loss abnormality in each history to obtain a reason judgment rule of the line loss abnormality; acquiring parameters of a power grid system, and determining technical aspects of line loss abnormity occurring under the parameters according to the parameters in the power grid system and the reason judgment rule, wherein the parameters of the power grid system comprise: current data, voltage data, power factor, three phase imbalance rate, and load data.
Further, acquiring the parameter of the power grid system comprises: and regularly crawling the parameters of the power grid system from the functional application of the metering automation system through a preset program, and storing the parameters of the power grid system in a local database.
Further, determining a technical cause of the line loss anomaly that occurred under the parameters includes: and determining the technical cause of the line loss abnormity occurring under the parameters according to a preset time scale.
Further, the predetermined time scale is daily or monthly.
Further, determining the technical cause of the line loss abnormality occurring under the parameters according to the parameters in the power grid system and the cause judgment rule includes: comparing the parameters in the power grid system with a preset threshold value to determine that the parameters of the power grid system are abnormal; and matching the abnormal parameters in the power grid system with the reason judgment rule to determine the technical reason of the line loss abnormality occurring under the parameters.
According to another aspect of the present application, there is also provided a line loss abnormality technical cause analysis system, including: the first acquisition module is used for acquiring line loss abnormity which occurs historically; a second obtaining module, configured to obtain a technical cause of each line loss abnormality that occurs historically, where the technical cause includes: the method comprises the following steps of (1) line loss abnormity caused by power factors, line loss abnormity caused by voltage or current three-phase imbalance, line loss abnormity caused by a load extreme value, and line loss abnormity caused by low voltage or high voltage; the integration module is used for integrating the technical reasons corresponding to the line loss abnormity every time in history to obtain a reason judgment rule of the line loss abnormity; the determining module is configured to acquire parameters of a power grid system, and determine a technical cause of the line loss abnormality occurring under the parameters according to the parameters in the power grid system and the cause determination rule, where the parameters of the power grid system include: current data, voltage data, power factor, three phase imbalance rate, and load data.
Further, the first obtaining module is configured to: and regularly crawling the parameters of the power grid system from the functional application of the metering automation system through a preset program, and storing the parameters of the power grid system in a local database.
Further, the determination module is to: and determining the technical cause of the line loss abnormity occurring under the parameters according to a preset time scale.
Further, the predetermined time scale is daily or monthly.
Further, the determination module is to: comparing the parameters in the power grid system with a preset threshold value to determine that the parameters of the power grid system are abnormal; and matching the abnormal parameters in the power grid system with the reason judgment rule to determine the technical reason of the line loss abnormality occurring under the parameters.
In the embodiment of the application, the method is used for acquiring the historical line loss abnormity; acquiring technical reasons of each historical line loss abnormality, wherein the technical reasons comprise: line loss abnormality caused by power factors, line loss abnormality caused by voltage or current three-phase imbalance, line loss abnormality caused by load extreme values, and line loss abnormality caused by low voltage or high voltage; integrating technical reasons corresponding to the line loss abnormality in each history to obtain a reason judgment rule of the line loss abnormality; acquiring parameters of a power grid system, and determining technical aspects of line loss abnormity occurring under the parameters according to the parameters in the power grid system and the reason judgment rule, wherein the parameters of the power grid system comprise: current data, voltage data, power factor, three phase imbalance rate, and load data. The method and the device solve the problems that the existing line loss analysis method in the prior art depends on manual operation and is low in efficiency and high in cost, so that the automatic analysis of the line loss abnormal technical reason judgment rules is realized, line loss abnormal technical reason analysis data are automatically generated, and business personnel are assisted to make and execute technical loss reduction measures.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this application, illustrate embodiments of the application and, together with the description, serve to explain the application and are not intended to limit the application. In the drawings:
fig. 1 is a flowchart of a line loss anomaly technical cause analysis method according to an embodiment of the present application.
Fig. 2 is a schematic diagram of a reason for analyzing a line loss anomaly according to an embodiment of the present application.
Detailed Description
It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict. The present application will be described in detail below with reference to the embodiments with reference to the attached drawings.
It should be noted that the steps illustrated in the flowcharts of the figures may be performed in a computer system such as a set of computer-executable instructions and that, although a logical order is illustrated in the flowcharts, in some cases, the steps illustrated or described may be performed in an order different than presented herein.
In this embodiment, a method for analyzing a technical cause of a line loss anomaly is provided, and fig. 1 is a flowchart of a method for analyzing a technical cause of a line loss anomaly according to an embodiment of the present application, as shown in fig. 1, the flowchart includes the following steps:
step S102, acquiring line loss abnormality occurred in history;
step S104, obtaining technical causes of each line loss abnormality occurred in the history, where the technical causes include: line loss abnormality caused by power factors, line loss abnormality caused by voltage or current three-phase imbalance, line loss abnormality caused by load extreme values, and line loss abnormality caused by low voltage or high voltage;
step S106, integrating the technical reasons corresponding to the line loss abnormity every time in history to obtain a reason judgment rule of the line loss abnormity;
as an alternative embodiment, the parameter corresponding to each line loss anomaly and the reason corresponding to the line loss anomaly may be used as a set of training data, after a predetermined number of training data are operated, a machine learning model is obtained by using multiple sets of training data for training, and after the machine learning model converges in the training, the parameter of the power grid system is input into the machine learning model in step S108, so as to obtain the technical reason of the line loss anomaly output by the machine learning model.
Step S108, obtaining parameters of a power grid system, and determining technical reasons of line loss abnormity occurring under the parameters according to the parameters in the power grid system and the reason judgment rules, wherein the parameters of the power grid system comprise: current data, voltage data, power factor, three phase imbalance rate, and load data.
The method for acquiring the parameters of the power grid system is various, for example, the parameters of the power grid system can be regularly crawled from functional applications of the metering automation system through a preset program and stored in a local database.
In this step, optionally, determining a technical cause of the line loss abnormality occurring under the parameter includes: and determining the technical cause of the line loss abnormity occurring under the parameters according to a preset time scale. For example, the predetermined time scale is daily or monthly.
The cause can be determined according to the parameter abnormality and the cause judgment rule, and in the optional mode, the parameter in the power grid system is compared with a preset threshold value to determine that the parameter of the power grid system is abnormal; and matching the abnormal parameters in the power grid system with the reason judgment rule to determine the technical reason of the line loss abnormality occurring under the parameters.
The problems that the existing line loss analysis method in the prior art depends on manual operation and is low in efficiency and high in cost are solved through the steps, so that automatic analysis of the line loss abnormal technical reason judgment rules is realized, line loss abnormal technical reason analysis data are automatically generated, and business personnel are assisted in making and executing technical loss reduction measures.
After step S108, the technical reason of the line loss abnormality may also be displayed to the user, and if the user modifies the technical reason of the line loss abnormality, the power grid parameters of the system modified by the user and the modified technical reason are saved and used as a set of new training data, and the machine learning model is incrementally trained when the number of the new training data reaches a predetermined number.
The above-mentioned cause judgment rule is involved in step S106, and several examples of the cause judgment rule will be described below.
As shown in fig. 2, the system analyzes and summarizes the technical causes of the line loss abnormality by integrating the current data, the voltage data, the power factors, the three-phase imbalance rate, the load data and the like of the metering automation system, solidifies the business rules through the information system, combs the results of the abnormality analysis, displays the abnormality data in a visual and friendly manner, and provides business personnel for confirming and processing the technical causes of the line loss abnormality.
The scene of line loss abnormal technical cause analysis comprises the following steps: daily analysis of power factors, daily analysis of current three-phase imbalance rates, daily analysis of voltage three-phase imbalance rates, monthly analysis of load extreme values, monthly analysis of low voltages, daily analysis of high voltages, monthly analysis of high voltages and the like.
(1) Daily analysis of power factor
Acquiring power factors of main electric energy meters collected at 10 morning and 10 evening before a public transformer user and a special transformer user every day, wherein the power factors at two time points are less than 0.85 or more than 1.1, and judging as a power factor problem.
(2) Daily analysis of current three-phase imbalance rate
Acquiring current three-phase imbalance rate data accumulated by a special transformer user every day, and judging that the current three-phase imbalance rate is more than or equal to 40% when the accumulated current three-phase imbalance rate exceeds 8 days in the month for the electric energy meter with a three-phase three-wire connection mode; for the electric energy meter with the wiring mode of three-phase four-wire, the problem of the current three-phase unbalance rate is judged to be 'current three-phase unbalance rate' when the current three-phase unbalance rate is more than or equal to 40% in 15 days in the current month.
(3) Daily analysis of voltage three-phase imbalance rate
And acquiring voltage three-phase imbalance rate data accumulated by all power customers every day, and judging that the voltage three-phase imbalance rate is more than or equal to 30% in 5 consecutive days in the month as the problem of the voltage three-phase imbalance rate.
(4) Load extreme monthly analysis
Monthly load rate data of public and special transformer users are acquired every month, and for a main electric energy meter with the metering point application being a common charging meter, the load rate exceeds 110 percent and is judged as a 'load extreme value' problem.
(5) Low voltage monthly analysis
Monthly voltage data of the special transformer users and the public transformer users are obtained, and the problem of low voltage is judged when the lower limit time of any phase voltage is larger than 1440 minutes.
(6) High voltage daily analysis
And acquiring daily voltage data of the private transformer users and the public transformer users, and judging that the time for any phase voltage to exceed the upper limit is more than 720 minutes as a daily analysis problem of high voltage.
(7) High voltage monthly analysis
And acquiring monthly voltage data of a special transformer user and a public transformer user, and judging that the time for any phase voltage to exceed the upper limit is greater than 7200 minutes as a 'high voltage' monthly analysis problem.
In this embodiment, an electronic device is provided, comprising a memory in which a computer program is stored and a processor configured to run the computer program to perform the method in the above embodiments.
The programs described above may be run on a processor or may also be stored in memory (or referred to as computer-readable media), which includes both non-transitory and non-transitory, removable and non-removable media, that implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.
These computer programs may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks, and corresponding steps may be implemented by different modules.
Such an apparatus or system is provided in this embodiment. The system is called a line loss abnormal technology cause analysis system and comprises: the first acquisition module is used for acquiring historical line loss abnormity; a second obtaining module, configured to obtain a technical cause of each line loss abnormality that occurs historically, where the technical cause includes: line loss abnormality caused by power factors, line loss abnormality caused by voltage or current three-phase imbalance, line loss abnormality caused by load extreme values, and line loss abnormality caused by low voltage or high voltage; the integration module is used for integrating the technical reasons corresponding to the line loss abnormity every time in history to obtain a reason judgment rule of the line loss abnormity; the determining module is configured to acquire parameters of a power grid system, and determine a technical cause of the line loss abnormality occurring under the parameters according to the parameters in the power grid system and the cause determination rule, where the parameters of the power grid system include: current data, voltage data, power factor, three phase imbalance rate, and load data.
The system or the apparatus is configured to implement the functions of the method in the foregoing embodiments, and each module in the system or the apparatus corresponds to each step in the method, which has been already described in the method, and is not described again here.
For example, the first obtaining module is configured to: and regularly crawling the parameters of the power grid system from the functional application of the metering automation system through a preset program, and storing the parameters of the power grid system in a local database.
For another example, the determination module is configured to: and determining the technical cause of the line loss abnormity occurring under the parameters according to a preset time scale. Optionally, the predetermined time scale is daily or monthly.
For another example, the determination module is configured to: comparing the parameters in the power grid system with a preset threshold value to determine that the parameters of the power grid system are abnormal; and matching the abnormal parameters in the power grid system with the reason judgment rule to determine the technical reason of the line loss abnormality occurring under the parameters.
The functions of the modules in the system can also be realized by integrating the following modules:
and the data synchronization module regularly acquires data required by analysis of line loss abnormal technical reasons such as current, voltage and power factors from functional application of the metering automation system by writing small programs such as python and the like, and stores the data in a local database. The data synchronization mechanism realized by the small program mode can reduce the workload of acquiring data by an interface mode, keeps high consistency with the data of the metering automation system, and can realize a concurrent data crawling mode, thereby greatly improving the consistency and efficiency of data synchronization.
The time sequence triggering module triggers modes such as daily analysis and monthly analysis for the measurement automation system data which are successfully put in storage according to the analysis scene of the line loss abnormal technical reason, the daily analysis scene discriminates and classifies the daily analysis scene data such as power factors, current and voltage at regular time every day, and the monthly analysis scene data such as load extreme values and voltage are discriminated and classified at the beginning of each month.
The algorithm triggering mode comprises the steps of constructing a topological relation among a user file, an ammeter file and a measuring point file, enabling measured data such as current and voltage to be associated with a user and an electric energy meter, meanwhile, carrying out algorithm analysis on the preliminarily processed measurement automation data, screening abnormal data exceeding an alarm threshold value or an upper limit value and a lower limit value, and forming an abnormal data result set corresponding to each line loss abnormal technical reason analysis scene.
The embodiment can solve the technical problems of low efficiency and high cost because the existing line loss analysis method depends on manual operation by analyzing, screening and positioning the data acquired by the metering automation system; in addition, the auxiliary analysis of the line loss abnormal technical reasons provides data support and basis for power grid enterprises when planning and formulating technical loss reduction measures, so that the technical loss reduction measure formulation is more pertinent, timeliness and accuracy, the data index and economic benefit of power supply enterprises are improved, and the method plays a positive role in the safe operation of the power grid.
The above are merely examples of the present application and are not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.

Claims (10)

1. A line loss abnormal technical cause analysis method is characterized by comprising the following steps:
acquiring line loss abnormality which occurs historically;
acquiring technical reasons of each historical line loss abnormality, wherein the technical reasons comprise: line loss abnormality caused by power factors, line loss abnormality caused by voltage or current three-phase imbalance, line loss abnormality caused by load extreme values, and line loss abnormality caused by low voltage or high voltage;
integrating technical reasons corresponding to the line loss abnormality in each history to obtain a reason judgment rule of the line loss abnormality;
acquiring parameters of a power grid system, and determining technical aspects of line loss abnormity occurring under the parameters according to the parameters in the power grid system and the reason judgment rule, wherein the parameters of the power grid system comprise: current data, voltage data, power factor, three-phase imbalance rate, and load data.
2. The method of claim 1, wherein obtaining parameters of a power grid system comprises:
and regularly crawling the parameters of the power grid system from the functional application of the metering automation system through a preset program, and storing the parameters of the power grid system in a local database.
3. The method of claim 1, wherein determining a technical cause of the line loss anomaly that occurred under the parameter comprises:
and determining the technical cause of the line loss abnormity occurring under the parameters according to a preset time scale.
4. The method of claim 3, wherein the predetermined time scale is daily or monthly.
5. The method according to any one of claims 1 to 4, wherein determining the technical cause of the line loss abnormality occurring under the parameter according to the parameter in the power grid system and the cause judgment rule comprises:
comparing the parameters in the power grid system with a preset threshold value to determine that the parameters of the power grid system are abnormal;
and matching the abnormal parameters in the power grid system with the reason judgment rule to determine the technical reason of the line loss abnormality occurring under the parameters.
6. A line loss abnormal technical cause analysis system is characterized by comprising:
the first acquisition module is used for acquiring line loss abnormity which occurs historically;
a second obtaining module, configured to obtain a technical cause of each line loss abnormality that occurs historically, where the technical cause includes: line loss abnormality caused by power factors, line loss abnormality caused by voltage or current three-phase imbalance, line loss abnormality caused by load extreme values, and line loss abnormality caused by low voltage or high voltage;
the integration module is used for integrating the technical reasons corresponding to the line loss abnormity every time in history to obtain a reason judgment rule of the line loss abnormity;
the determining module is configured to acquire parameters of a power grid system, and determine a technical cause of the line loss abnormality occurring under the parameters according to the parameters in the power grid system and the cause determination rule, where the parameters of the power grid system include: current data, voltage data, power factor, three phase imbalance rate, and load data.
7. The system of claim 6, wherein the first obtaining module is configured to:
and regularly crawling the parameters of the power grid system from the functional application of the metering automation system through a preset program, and storing the parameters of the power grid system in a local database.
8. The system of claim 6, wherein the determination module is configured to:
and determining the technical cause of the line loss abnormity occurring under the parameters according to a preset time scale.
9. The system of claim 8, wherein the predetermined time scale is daily or monthly.
10. The system of any one of claims 6 to 9, wherein the determination module is configured to:
comparing the parameters in the power grid system with a preset threshold value to determine that the parameters of the power grid system are abnormal;
and matching the abnormal parameters in the power grid system with the reason judgment rule to determine the technical reason of the line loss abnormality occurring under the parameters.
CN202210229702.1A 2022-03-09 2022-03-09 Line loss abnormity technical cause analysis method and system Pending CN114579638A (en)

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