CN110095661A - A kind of distribution transformer high-pressure side open-phase fault emergency repair method - Google Patents

A kind of distribution transformer high-pressure side open-phase fault emergency repair method Download PDF

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Publication number
CN110095661A
CN110095661A CN201910286431.1A CN201910286431A CN110095661A CN 110095661 A CN110095661 A CN 110095661A CN 201910286431 A CN201910286431 A CN 201910286431A CN 110095661 A CN110095661 A CN 110095661A
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China
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matrix
data
fault
phase
index
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CN201910286431.1A
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Inventor
韩翊
钱忠敏
陈琳
葛晓军
聂峥
魏明林
张国成
蒋立志
毛亚明
邵丹璐
林秋佳
马凌
何琴琴
刘玉俊
吕骁男
裘枭敏
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STATE GRID ZHEJIANG WENLING POWER SUPPLY Co Ltd
Zhejiang Huayun Information Technology Co Ltd
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STATE GRID ZHEJIANG WENLING POWER SUPPLY Co Ltd
Zhejiang Huayun Information Technology Co Ltd
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Priority to CN201910286431.1A priority Critical patent/CN110095661A/en
Publication of CN110095661A publication Critical patent/CN110095661A/en
Pending legal-status Critical Current

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Abstract

The invention discloses a kind of distribution transformer high-pressure side open-phase fault emergency repair methods, are related to phase shortage judgment method.Currently, phase shortage judgement there is a problem of lacking real-time and intelligence degree is not deep enough.The present invention includes that step obtains data, data matrix, high dimensional feature extraction, multiple features fusion, fault source tracing, high voltage phase loss fault diagnosis;Spectrum analysis based on MP-Law and the average spectral radius index based on Ring-Law further establish LES system for statistical indices and its visualization, and then construct phase shortage criterion index;Power distribution network operation and environmental information are merged, failure influence factor is analyzed, equipment state evolution process is modeled by time series, index of correlation is formed with random matrix and the state of power network line is assessed, provide guidance for power distribution network service arrangement.The technical program rationally to all types of distribution respective resources, realizes the reasonable disposition of maintenance resource;Optimize power distribution network and overhaul resource distribution, so that emergency first-aid repair is more accurate.

Description

A kind of distribution transformer high-pressure side open-phase fault emergency repair method
Technical field
The present invention relates to phase shortage judgment method more particularly to a kind of distribution transformer high-pressure side open-phase fault emergency repair methods.
Background technique
In the normal course of operation of transformer, the foreign matter of environment fall or overload etc. due to, lead to height Press a certain phase line in side to disconnect or fuse blows, further will cause other biphase currents increase suddenly, transformer coil Temperature increases, and easily transformer is caused to burn out, causes some unsafe accidents, can all caused to resident and factory user great Personnel and economic loss.It is most of by manually patrolling since automation degree of equipment is low in most traditional transformer O&M Look into, the mode of manual report checks problem, efficiency is extremely low.It is general with automatically-monitored equipment and cloud computing in recent years And monitoring terminal periodic on send the monitoring data such as real-time voltage to cloud main website, main website passes through the analysis continuous 2-3 period Monitoring data carry out problem analysis, due to communication flows limitation and mitigate Cloud Server burden, above the period is sent at least to limit It is scheduled on 15 minutes, therefore, the time of fault discovery is at least half an hour, is not able to satisfy wanting for power grid O&M and power supply reliability It asks.
Currently, being related generally in the application of low-voltage distribution network to the emergency repair method of distribution transformer high-pressure side open-phase fault To intelligent distribution transformer terminals (referred to as: distribution transformer terminals), the public change monitoring system of intelligence (referred to as: main station system) and it is three artificial in terms of, And include from process: given in intelligent distribution transformer terminals timing, the public change monitoring system timing judgement of intelligence, manual analysis and publication and Artificial treatment four processes, detailed process are as shown in Figure 1.
Firstly, the three-phase voltage of the intelligent distribution transformer terminals real-time measurement distribution transformer low-pressure side mounted in scene, and with 15 Minute is the mission profile in period, gives the data to intelligence public affairs change monitoring system in timing remotely;Then, intelligence is public becomes monitoring system System judges high-pressure side phase shortage using the data (that is: sending the period at least two) continuously received three times, and then forms alarm thing Part information, while alarm event information is sent to related personnel in the form of short message;Finally, according to short message content, artificial point The information such as equipment involved in the alarm event, user are precipitated, to make a report on corresponding outage information and be issued, simultaneously also Work of sending someone is to in-situ processing.The process has the following disadvantages:
One, lack real-time.Send a data to intelligence public affairs change monitoring system on intelligent distribution transformer terminals 15 minutes are just long-range, And the public change monitoring system of intelligence needs at least 30 minutes (sending the period on two) could judge high-pressure side phase shortage, is next connected For artificial link in time there is also very big uncertainty, whole flow process is far from satisfying requirement in real-time;
Two, intelligence degree is not deep enough.In whole flow process, the content for needing manually to participate in is more, for example analysis is accused Alert event information content, publication outage information, worksheet processing maintenance etc., intelligence employed in process, information system can not be right The treatment process of the problem carries out all-the-way tracking and monitoring.
Summary of the invention
The technical problem to be solved in the present invention and the technical assignment of proposition are to be improved and improved to prior art, A kind of distribution transformer high-pressure side open-phase fault emergency repair method is provided, to achieve the purpose that improve emergency first-aid repair accuracy.For this purpose, The present invention takes following technical scheme.
A kind of distribution transformer high-pressure side open-phase fault emergency repair method, comprising the following steps:
1) data are obtained:
High Dimensional Data Set is obtained using existing communication mechanism, the data collection of the relevant sensor of fault detection in intelligence Energy distribution transformer terminals, transfer to edge from cloud;
2) data matrix:
Sampled data forms random matrix by stochastic matrix models;Stochastic matrix models are based on time series to equipment shape The modeling of state evolution process converts random matrix problem analysis for electric network state cognition by stochastic matrix models;To split only The part area data that need to be handled;
3) high dimensional feature extracts
High dimensional feature is extracted to pretreated random matrix based on Ring-Law and MP-Law, obtains average spectral radius MSR, linear statistical characteristic value LES, and visualization processing is carried out, it is united by the higher-dimension that spectrum analysis figure intuitively embodies fault data collection Metering;
4) multiple features fusion
It is that time reference quantity progress multiple features melt with electrical special reason amount and general statistic with higher-dimension statistic for main reference quantity It closes, constructs phase shortage criterion;
5) fault source tracing
By splicing matrix disposal, trace to the source failure, positioning failure phase;Index is recalculated through data splicing and is led to The situation of change for crossing New Set judges the influence of spliced data to event, analyzes the statistical property of criterion, according to setting Fixed criterion threshold value carries out high voltage phase loss breakdown judge;Statistical property includes convergence, confidence level;The criterion threshold value set up includes Omission factor threshold value, false alarm rate threshold value;
Since network system state depends on multiple influence factors, it is assumed that the state of certain power grid is the change of a N-dimensional parameter It measures and has K potential influence factors, by certain time period tiThe measurement of (i=1,2 ..., T), the N-dimensional of the state of power grid Vector can form basic status matrix naturallyAnd each influence factor can also obtain the value of the period, constitute because Plain vector
Two matrixes (vector) with equal length can form a new matrix by concatenation;By basic status Matrix B and factor vector cjIt is spliced into composite matrix Aj
For the ease of analyzing its impact factor to the influence power of basic status, need to amplify the influence power of impact factor;Choosing Determine factor vector cj, replicating the factor vector K times by certain mode, (K can use 0.4 × N) forms one and state matrix rule The matched matrix D of mouldj, as shown in formula (4):
In DjMiddle introducing white noise is to eliminate interdependency, as shown in formula (5):
Cj=DjjR (j=1,2 ..., m) (5)
In formula (5), R is standard gaussian random matrix, ηjWith signal-to-noise ratio (SNR, signal-to-noise ratio) ρ phase It closes:
Concurrently to each factor vector cjComposite matrix A is spliced to form by matrixj:
Compare each AjStatistical indicator LES can find out different data, that is, influence the sensible factor of state;
6) high voltage phase loss fault diagnosis
Fault source tracing is obtained as a result, obtaining high voltage phase loss fault diagnosis result, arranges corresponding maintenance to appoint by diagnostic result Business.
MSR and LES essence is the statistic of the random matrix of matrix, and when system is abnormal, which can significant changes. It may make using distributed algorithm and distribution global behavior assessed by the statistic in each region, i.e., lacked to what be whether there is in distribution Mutually make a response.
The technical program lacks high pressure using data in edge calculations and region by redesigning local communication mechanism Mutually " edge " (the intelligent distribution transforming transferred to from " cloud " (power distribution automation main station system of new generation) closer to the source of trouble is studied and judged in alarm Terminal), the real-time of high voltage phase loss breakdown repair is substantially increased, is increased in one minute from least half an hour before.? In function decentralization process, it is based on overall condition initial setting criterion, is based further on localization historical data edge feelings with arround Condition revises criterion.In conjunction with existing big data platform, " alarm event large data center " is deployed beyond the clouds, is passed through Big data intellectual analysis is automatically performed the process from equipment fault detailed analysis to auto form delivering.Finally, automatic receive live people The feedback result of work processing enriches the intelligence degree of entire repairing process.The technical program is for distribution transformer high pressure Open-phase fault repairing in side is of great significance, and effectively improves the power supply reliability of power distribution network.
Meanwhile the technical program optimization power distribution network overhauls resource distribution;So that emergency first-aid repair is more accurate.Merge power distribution network fortune Capable and environmental information analyzes failure influence factor, is modeled by time series to equipment state evolution process, with random matrix shape It is assessed at state of the index of correlation to power network line, provides guidance for power distribution network service arrangement.Index and visual image, The state of route is assessed, and then provides guidance for line maintenance arrangement.Distribution network line is divided into distribution network Good segments, easily the hair types such as section and faulty section realize the reasonable disposition of maintenance resource rationally to all types of distribution respective resources.
As optimization technique means: it further include data prediction step, pre-treatment step carries out before high dimensional feature extracts, Data prediction includes:
Data are translated certain periods to restore nonsynchronous data by translation;
And/or reinforce, a certain column data is replicated, the influence with the selective analysis time to system integrality;
And/or augmentation, abnormal inducement is excavated, to conveniently realize parallel computation;
And/or random wave, normalization, matrix mark is changed to the statistics premise so that its satisfaction.
Different observing matrixes can be set up by different pretreatment modes for analysis.
As optimization technique means: the average spectral radius MSR index is higher-dimension statistical indicator, passes through comparative observation Value and desired value carry out hypothesis testing.
As optimization technique means: the number that the linear statistical characteristic value LES index system passes through Random Matrices Theory It is obtained according to processing method, value has statistical nature.
The utility model has the advantages that
1, the technical program is by redesigning local communication mechanism, using data in edge calculations and region, high pressure Phase shortage alarm, which is studied and judged from " cloud ", transfers to " edge " closer to the source of trouble, substantially increases the real-time of high voltage phase loss breakdown repair Property, it is increased in one minute from least half an hour before.In function decentralization process, it is automatically performed from equipment fault and divides in detail Analyse the process of auto form delivering.Finally, the automatic feedback result for receiving live artificial treatment, enriches the intelligence of entire repairing process Degree can be changed.The technical program is of great significance for the repairing of distribution transformer high-pressure side open-phase fault, effectively improves distribution The power supply reliability of net.
2, the technical program optimization power distribution network overhauls resource distribution;So that emergency first-aid repair is more accurate.Merge power distribution network operation And environmental information, failure influence factor is analyzed, equipment state evolution process is modeled by time series, is formed with random matrix Index of correlation assesses the state of power network line, provides guidance for power distribution network service arrangement.Index and visual image, it is right The state of route is assessed, and then provides guidance for line maintenance arrangement.Distribution network line is divided into distribution network good Good section, easily the hair types such as section and faulty section realize the reasonable disposition of maintenance resource rationally to all types of distribution respective resources.
Detailed description of the invention
Fig. 1 is existing procedure figure.
Fig. 2 is flow chart of the invention.
Fig. 3 is Ring Law, MP Law, MSR/LES hypothesis testing effect picture of the invention.
Fig. 4 is fault source tracing partial process view of the invention.
Specific embodiment
Technical solution of the present invention is described in further detail below in conjunction with Figure of description.
As shown in Fig. 2, the present invention the following steps are included:
Step 1: obtaining data
High Dimensional Data Set is obtained using existing communication mechanism, is exactly the data collection the relevant sensor of fault detection In intelligent distribution transformer terminals, edge is transferred to from cloud.
Step 2: establishing data model for the high dimensional data collected
Using Random Matrices Theory method, based on it, Random Matrices Theory is constructed.Random matrix models its advantage and exists In the space-time associative correlation (higher-dimension statistical information) for being contemplated that Data In High-dimensional Spaces (data set) itself.The model built can Contain certain statistical information (depending on actual scene and data cases), further, data matrix can be pre-processed with side Just high dimensional feature (MSR, LES) extracts;Index of correlation is formed with random matrix to assess the state of power network line, is distribution The diagnosis of net phase shortage provides guidance.Stochastic matrix models RMM is established based on sampled data, row N represents sampling dimension, column T is represented Sampling.Random matrix problem analysis is converted by electric network state cognition by RMM.Due to the spy that character matrix is detachable, merges Property, the detachable data for only handling regional area of the modeling method.
Step 3: extracting its higher-dimension statistic using specific parser for the high dimensional data collected
MSR and LES is extracted based on Ring-Law and MP-Law, and why can put forward this feature and this feature energy Being used as criterion is because there is Random Matrices Theory ensureing, the conclusion of spectrum analysis has a statistical property, and these Property can be obtained a priori, as shown in figure 3, the higher-dimension statistic as fault data collection.
Step 4: multiple features fusion
Using higher-dimension statistic as Primary Reference, phase shortage criterion is constructed based on multiple features fusion technology, detects whether that event occurs Barrier.
Step 5: fault source tracing
By further splicing the processing of matrix, trace to the source failure, i.e. the phase of positioning failure, to the statistics of criterion Matter (convergence, confidence level) etc. is further analyzed, and sets up criterion threshold value according to engineering demand (omission factor, false alarm rate).
As shown in figure 4, since network system state depends on multiple influence factors, it is assumed that the state of certain power grid is a N It ties up the variable of parameter and has K potential influence factors, by certain time period tiThe measurement of (i=1,2 ..., T), power grid The N-dimensional vector of state can form basic status matrix naturallyAnd each influence factor can also obtain the period Value, constituent element vector
Two matrixes (vector) with equal length can form a new matrix by concatenation;By basic status Matrix B and factor vector cjIt is spliced into composite matrix Aj
For the ease of analyzing its impact factor to the influence power of basic status, need to amplify the influence power of impact factor;Choosing Determine factor vector cj, replicating the factor vector K times by certain mode, (K can use 0.4 × N) forms one and state matrix rule The matched matrix D of mouldj, as shown in formula (4):
In DjMiddle introducing white noise is to eliminate interdependency, as shown in formula (5):
Cj=DjjR (j=1,2 ..., m) (5)
In formula (5), R is standard gaussian random matrix, ηjWith signal-to-noise ratio (SNR, signal-to-noise ratio) ρ phase It closes:
Concurrently to each factor vector cjComposite matrix A is spliced to form by matrixj:
Compare each AjStatistical indicator LES can find out different data, that is, influence the sensible factor of state.
Step 6: high voltage phase loss fault diagnosis and repairing
High voltage phase loss fault diagnosis result is obtained by fault detection and fault source tracing, is arranged according to diagnostic result corresponding Maintenance plan.
To set up different observing matrixes for analysis, and accuracy is improved, it can be into before extracting its higher-dimension statistic Row pretreatment.Following basic function: 1. translations is set up in pretreatment --- data are translated into certain periods to restore nonsynchronous Data;2. reinforcing --- a certain column data is replicated into the influence with the selective analysis time to system integrality;3. increasing Extensively --- exception inducement can be achieved and excavate, can easily realize parallel computation;4. random wave, normalization --- by matrix mark Change certain statistics premise so that its satisfaction.
A kind of distribution transformer high-pressure side open-phase fault emergency repair method shown in figure 2 above is specific implementation of the invention Example, has embodied substantive distinguishing features of the present invention and progress, can be under the inspiration of the present invention, right according to actual using needs Its equivalent modifications for carrying out shape, structure etc., the column in the protection scope of this programme.

Claims (4)

1. a kind of distribution transformer high-pressure side open-phase fault emergency repair method, it is characterised in that the following steps are included:
1) data are obtained:
High Dimensional Data Set is obtained using existing communication mechanism, the data collection of the relevant sensor of fault detection is matched intelligently Transformer terminals transfer to edge from cloud;
2) data matrix:
Sampled data forms random matrix by stochastic matrix models;Stochastic matrix models are based on time series and drill equipment state Become process model building, converts random matrix problem analysis for electric network state cognition by stochastic matrix models;It only needs to locate to split The part area data of reason;
3) high dimensional feature extracts
High dimensional feature is extracted to pretreated random matrix based on Ring-Law and MP-Law, obtains average spectral radius MSR, line Property statistical characteristics LES, and visualization processing is carried out, the higher-dimension statistic of fault data collection is intuitively embodied by spectrum analysis figure;
4) multiple features fusion
It is that time reference quantity carries out multiple features fusion with electrical special reason amount and general statistic with higher-dimension statistic for main reference quantity, Phase shortage criterion is constructed, general statistic includes mean value, variance, low-dimensional transformation index;
5) fault source tracing
By splicing matrix disposal, trace to the source failure, positioning failure phase;Index is recalculated through data splicing and by new The situation of change of index judges influence of the spliced data to event, analyzes the statistical property of criterion, according to setting Criterion threshold value carries out high voltage phase loss breakdown judge;Statistical property includes convergence, confidence level;The criterion threshold value set up includes missing inspection Rate threshold value, false alarm rate threshold value;
Since network system state depends on multiple influence factors, it is assumed that the state of certain power grid be the variable of a N-dimensional parameter and There are K potential influence factors, by certain time period tiThe measurement of (i=1,2 ..., T), the N-dimensional vector of the state of power grid Basic status matrix can be formed naturallyAnd each influence factor can also obtain the value of the period, constituent element to Amount
Two matrixes with equal length form a new matrix by concatenation;By basic status matrix B and factor Vector cjIt is spliced into composite matrix Aj
For the ease of analyzing its impact factor to the influence power of basic status, amplify the influence power of impact factor;Selected Factors to Measure cj, replicate the factor vector K times matrix D for forming one with state matrix Size Matchj, it is shown below:
In DjMiddle introducing white noise is shown below with eliminating interdependency:
Cj=DjjR (j=1,2 ..., m) (5)
In formula, R is standard gaussian random matrix, ηjIt is related with signal-to-noise ratio (SNR, signal-to-noise ratio) ρ:
Concurrently to each factor vector cjComposite matrix A is spliced to form by matrixj:
Compare each AjStatistical indicator LES can find out different data, that is, influence the sensible factor of state;
6) high voltage phase loss fault diagnosis
Fault source tracing is obtained as a result, obtaining high voltage phase loss fault diagnosis result, arranges corresponding maintenance task by diagnostic result.
2. a kind of distribution transformer high-pressure side open-phase fault emergency repair method according to claim 1, it is characterised in that: also wrap Data prediction step is included, pre-treatment step carries out before high dimensional feature extracts, and data prediction includes:
Data are translated certain periods to restore nonsynchronous data by translation;
And/or reinforce, a certain column data is replicated, the influence with the selective analysis time to system integrality;
And/or augmentation, abnormal inducement is excavated, to conveniently realize parallel computation;
And/or random wave, normalization, matrix mark is changed to the statistics premise so that its satisfaction.
3. a kind of distribution transformer high-pressure side open-phase fault emergency repair method according to claim 2, it is characterised in that: described Average spectral radius MSR index be higher-dimension statistical indicator, hypothesis testing is carried out by comparative observation value and desired value.
4. a kind of distribution transformer high-pressure side open-phase fault emergency repair method according to claim 3, it is characterised in that: described Linear statistical characteristic value LES index system obtained by the data processing method of Random Matrices Theory, value has statistics special Sign.
CN201910286431.1A 2019-04-10 2019-04-10 A kind of distribution transformer high-pressure side open-phase fault emergency repair method Pending CN110095661A (en)

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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110568275A (en) * 2019-09-17 2019-12-13 国网福建省电力有限公司安溪县供电公司 open-phase fault studying and judging method and system based on public and private power distribution network variable data
CN111196201A (en) * 2019-12-31 2020-05-26 国网北京市电力公司 Mobile box transformer substation vehicle

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101964548A (en) * 2010-11-12 2011-02-02 国电南瑞科技股份有限公司 Comprehensive intelligent assembly of power transformer
CN105071536A (en) * 2015-08-19 2015-11-18 江苏省电力公司扬州供电公司 Intelligent distribution transformer area system
CN106571626A (en) * 2016-08-29 2017-04-19 上海交通大学 Power system cognitive method based on random moment theory
CN108152675A (en) * 2017-12-21 2018-06-12 华中科技大学 It is determined and fault zone localization method based on the fault moment of Random Matrices Theory
CN108828405A (en) * 2018-06-06 2018-11-16 西南交通大学 A kind of electric transmission line fault detection method based on random matrix

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101964548A (en) * 2010-11-12 2011-02-02 国电南瑞科技股份有限公司 Comprehensive intelligent assembly of power transformer
CN105071536A (en) * 2015-08-19 2015-11-18 江苏省电力公司扬州供电公司 Intelligent distribution transformer area system
CN106571626A (en) * 2016-08-29 2017-04-19 上海交通大学 Power system cognitive method based on random moment theory
CN108152675A (en) * 2017-12-21 2018-06-12 华中科技大学 It is determined and fault zone localization method based on the fault moment of Random Matrices Theory
CN108828405A (en) * 2018-06-06 2018-11-16 西南交通大学 A kind of electric transmission line fault detection method based on random matrix

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
徐心怡 等: "基于随机矩阵理论的配电网运行状态相关性分析方法", 《电网技术》 *
贺兴 等: "随机矩阵理论在电力系统认知中的应用初探", 《电网技术》 *

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110568275A (en) * 2019-09-17 2019-12-13 国网福建省电力有限公司安溪县供电公司 open-phase fault studying and judging method and system based on public and private power distribution network variable data
CN111196201A (en) * 2019-12-31 2020-05-26 国网北京市电力公司 Mobile box transformer substation vehicle

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