CN106844851A - A kind of on-line monitoring and diagnosis model adaptation algorithm for transformer station - Google Patents

A kind of on-line monitoring and diagnosis model adaptation algorithm for transformer station Download PDF

Info

Publication number
CN106844851A
CN106844851A CN201611173979.8A CN201611173979A CN106844851A CN 106844851 A CN106844851 A CN 106844851A CN 201611173979 A CN201611173979 A CN 201611173979A CN 106844851 A CN106844851 A CN 106844851A
Authority
CN
China
Prior art keywords
model
line monitoring
configuration file
xml configuration
dynamic link
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN201611173979.8A
Other languages
Chinese (zh)
Inventor
杨楠
杨隽
郑博文
李邦源
杨承辰
唐伟
崔勇
禹海斌
李芳方
田庆生
梁仕斌
王磊
昌明
刘涛
杜景琦
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Yuxi Power Supply Bureau of Yunnan Power Grid Co Ltd
Yunnan Electric Power Test and Research Institute Group Co Ltd
Original Assignee
Yuxi Power Supply Bureau of Yunnan Power Grid Co Ltd
Yunnan Electric Power Test and Research Institute Group Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Yuxi Power Supply Bureau of Yunnan Power Grid Co Ltd, Yunnan Electric Power Test and Research Institute Group Co Ltd filed Critical Yuxi Power Supply Bureau of Yunnan Power Grid Co Ltd
Priority to CN201611173979.8A priority Critical patent/CN106844851A/en
Publication of CN106844851A publication Critical patent/CN106844851A/en
Pending legal-status Critical Current

Links

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00Computer-aided design [CAD]
    • G06F30/20Design optimisation, verification or simulation
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01RMEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • YGENERAL 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
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02EREDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E60/00Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation

Landscapes

  • Physics & Mathematics (AREA)
  • Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Computer Hardware Design (AREA)
  • Evolutionary Computation (AREA)
  • Geometry (AREA)
  • General Engineering & Computer Science (AREA)
  • Testing And Monitoring For Control Systems (AREA)
  • Testing Electric Properties And Detecting Electric Faults (AREA)

Abstract

A kind of on-line monitoring and diagnosis model adaptation algorithm for transformer station, monitors self adaptation and the optimization of all kinds of diagnostic models on-line for transformer station.The dynamic link library of model containing on-line monitoring and diagnosis, XML configuration file and adaptive algorithm.It is the form that dynamic link library will be compiled into for the diagnostic model of transformer station's on-line monitoring, it is copied directly to above the memory space of on-line monitoring equipment or diagnostic device, coordinate corresponding XML configuration file and adaptive algorithm again realize all kinds of diagnostic models use whether, the requirement of priority level and model interface, so as to realize voluntarily matching and the self adaptation of the other on-line monitoring and diagnosis model of variety classes.A kind of on-line monitoring and diagnosis model adaptation algorithm for transformer station of the invention can realize the self-adapted call of all kinds of variety classeses, the diagnostic model of classification according to algorithm, solve various diagnostic models and be unable to self adaptation, the Embarrassing borders that can only be used alone, algorithm is easy to use, it is easy to use, it is high using the degree of accuracy.

Description

A kind of on-line monitoring and diagnosis model adaptation algorithm for transformer station
Technical field
The present invention relates to converting equipment on-line monitoring technique field, in particular, it is related to a kind of exist for transformer station Line monitoring, diagnosing model adaptation algorithm.
Background technology
With the fast development of power automation technology, Power Electronic Technique and computer network communication technology, in the market Various intelligent automatic devices are emerged, these devices are widely used in transformer station's on-line monitoring field, so as to promote The development of power transformation on-line monitoring technique, respective producer combines the demand of transformer station, and exploitation is devised to be supervised online for transformer The various models of diagnosis, breaker on-line monitoring, capacitive apparatus on-line monitoring and sleeve pipe on-line monitoring and diagnosis are surveyed to converting equipment Carry out monitoring fault diagnosis and prediction on-line, so that all kinds of diagnosis of different manufacturers, forecast model are more and more, but these are not The diagnostic model of same type is all single use, or when changing the use of these models when needing to use by system Machine, does not have a kind of algorithm to be directed to different types of on-line monitoring and diagnosis model adaptation so that different types of diagnosis mould Type can be used simultaneously.
The content of the invention
The purpose of the present invention is to propose to a kind of on-line monitoring and diagnosis model adaptation algorithm for transformer station, can be compatible With the different types of diagnostic model of self adaptation.
To realize above technical purpose, the present invention proposes a kind of on-line monitoring and diagnosis model adaptation for transformer station Algorithm, including on-line monitoring and diagnosis model dynamic link library, XML configuration file and adaptive algorithm.
The purpose of the present invention is achieved by the following technical solution.
A kind of on-line monitoring and diagnosis model adaptation algorithm for transformer station, the invention is characterised in that, including online prison Survey diagnostic model dynamic link library, XML configuration file and adaptive algorithm;Wherein:
The on-line monitoring and diagnosis model dynamic link library includes that transformer online monitoring diagnostic model, breaker are supervised online Survey diagnostic model, 4 kinds of model dynamic link libraries of capacitive apparatus on-line monitoring and diagnosis model and sleeve pipe on-line monitoring and diagnosis model;
The XML configuration file include dynamic link library name, classification, mark, priority level, whether immediately using, make With state, dynamic link library call function title, mode input parameter type, mode input number of parameters, model output parameters Type, model output parameters number;
Described dynamic link library name be stored in above the memory space of on-line monitoring equipment or diagnostic device On-line monitoring and diagnosis model name is identical;
Classification in described XML configuration file includes:Transformer online monitoring diagnostic model classification, breaker are supervised online Survey diagnostic model, 4 kinds of models of capacitive apparatus on-line monitoring and diagnosis model and sleeve pipe on-line monitoring and diagnosis model, respectively with " 0 ", " 1 ", " 2 ", " 3 " represent;
Mark in XML configuration file of the present invention includes:Oil chromatography, iron core grounding current in transformer online monitoring, Wei Shui, micro- gas, are represented with " a ", " b ", " c ", " d " respectively;Mechanical property parameter, electrical characteristic in breaker on-line monitoring Parameter, state of insulation parameter, are represented with " e ", " f ", " g " respectively;Reactor, capacitor voltage in capacitive apparatus on-line monitoring Transformer, current transformer, disconnecting switch, insulator, arc suppression coil, arrester, respectively with " h ", " i ", " j ", " k ", " l ", " m " " n " is represented;C2H2 contents, H2 contents, capacitance, dielectric loss, end shield earth resistance in sleeve pipe on-line monitoring, use respectively " o ", " p ", " q ", " r ", " s " are represented;
Priority level in described XML configuration file represents the height of the preferential executive level of dynamic link library, including Highest executive level, secondary executive level, three kinds of minimum executive level, are represented with " 1 ", " 2 ", " 3 " respectively;
In described XML configuration file whether be immediately performed including be with it is no, respectively with " t ", " f " represent;
Use state in described XML configuration file includes being currently in use and not using two states, uses respectively " T ", " F " are represented;
Dynamic link library call function title representation program in described XML configuration file is used when calling the model library Function name;
When mode input parameter type in described XML configuration file represents the function of the routine call model, transmission Parameter type, including the type of bool, int, string, float tetra-;
Mode input number of parameters representation program in described XML configuration file calls what is transmitted during the function of the model Number of parameters;
When model output parameters type in described XML configuration file represents the function of the routine call model, transmission Parameter type, including the type of bool, int, string, float tetra-;
Model output parameters number representation program in described XML configuration file calls what is transmitted during the function of the model Number of parameters.
Adaptive algorithm of the present invention needs that diagnostic model dynamic link library is first copied to on-line monitoring equipment before performing Or above the memory space of diagnostic device, and set up XML configuration file;Wherein XML configuration file is calculated after completion is configured Method model starts to be performed according to following steps:
Step 1:Content → detection XML that program starts to perform → load dynamic link library → reading XML configuration file matches somebody with somebody Put file format whether standard, "Yes" perform step 2, "No" program perform terminate, return to step 1;
Step 2:Set up title → reading MAP that XML configuration file MAP maps → obtained from store path dynamic link library Dynamic link library name in mapping → compare whether title is identical, "Yes" performs step 3, and "No" program is performed and terminated, returns Step 1;
Step 3:Read classification → acquisition transformer online monitoring diagnostic model classification (0), the open circuit respectively in MAP mappings Device on-line monitoring and diagnosis model (1), capacitive apparatus on-line monitoring and diagnosis model (2) and sleeve pipe on-line monitoring and diagnosis model (3), hold Row step 4;
Step 4:Transformer online monitoring diagnostic model classification (0) gets the oil chromatography in transformer online monitoring respectively (a), iron core grounding current (b), micro- water (c), micro- gas (d);Breaker on-line monitoring and diagnosis model (1) obtain mechanical spy respectively Property parameter (e), electrical characteristic parameter (f), state of insulation parameter (g);Capacitive apparatus on-line monitoring and diagnosis model (2) are obtained respectively Reactor (h), capacitance type potential transformer (i), current transformer (j), disconnecting switch (k), insulator (l), arc suppression coil (m), arrester (n);Sleeve pipe on-line monitoring and diagnosis model (3) obtain respectively C2H2 contents (o), H2 contents (p), capacitance (q), Dielectric loss (r), end shield earth resistance (s), perform step 5 afterwards;
Step 5:Judge preferential executive level → judge whether to be immediately performed → judge use state → reading call function Title → reading call function |input paramete type → reading call function |input paramete number → reading call function output ginseng Several classes of type → reading call function output parameter number → self-adapting program is performed and terminated;By 5 execution of step, self adaptation Algorithm routine finally confirm program operation preferential executive level, whether be immediately performed, use state, afterwards again by calling Function input parameters type, call function |input paramete number, call function output parameter type and call function output parameter Number is determined and preferentially call which program is performed, so as to realize the self adaptation of on-line monitoring and diagnosis model.
The beneficial effects of the invention are as follows with a kind of on-line monitoring and diagnosis model adaptation algorithm use letter for transformer station Single, convenience, as long as setting parameters according to configuration requirement, just can simultaneously use all kinds of different classes of diagnostic models, high What is imitated makes all kinds of diagnostic model self adaptations.
The present invention is further explained with specific embodiment below in conjunction with the accompanying drawings.
Brief description of the drawings
Accompanying drawing 1 is a kind of flow of embodiment of on-line monitoring and diagnosis model adaptation algorithm one for transformer station of the invention Block diagram.
Specific embodiment
As shown in figure 1, a kind of on-line monitoring and diagnosis model adaptation algorithm for transformer station, the invention is characterised in that, Including on-line monitoring and diagnosis model dynamic link library, XML configuration file and adaptive algorithm;Wherein:
The on-line monitoring and diagnosis model dynamic link library includes that transformer online monitoring diagnostic model, breaker are supervised online Survey diagnostic model, 4 kinds of model dynamic link libraries of capacitive apparatus on-line monitoring and diagnosis model and sleeve pipe on-line monitoring and diagnosis model;
The XML configuration file include dynamic link library name, classification, mark, priority level, whether immediately using, make With state, dynamic link library call function title, mode input parameter type, mode input number of parameters, model output parameters Type, model output parameters number;
Described dynamic link library name be stored in above the memory space of on-line monitoring equipment or diagnostic device On-line monitoring and diagnosis model name is identical;
Classification in described XML configuration file includes:Transformer online monitoring diagnostic model classification, breaker are supervised online Survey diagnostic model, 4 kinds of models of capacitive apparatus on-line monitoring and diagnosis model and sleeve pipe on-line monitoring and diagnosis model, respectively with " 0 ", " 1 ", " 2 ", " 3 " represent;
Mark in XML configuration file of the present invention includes:Oil chromatography, iron core grounding current in transformer online monitoring, Wei Shui, micro- gas, are represented with " a ", " b ", " c ", " d " respectively;Mechanical property parameter, electrical characteristic in breaker on-line monitoring Parameter, state of insulation parameter, are represented with " e ", " f ", " g " respectively;Reactor, capacitor voltage in capacitive apparatus on-line monitoring Transformer, current transformer, disconnecting switch, insulator, arc suppression coil, arrester, respectively with " h ", " i ", " j ", " k ", " l ", " m " " n " is represented;C2H2 contents, H2 contents, capacitance, dielectric loss, end shield earth resistance in sleeve pipe on-line monitoring, use respectively " o ", " p ", " q ", " r ", " s " are represented;
Priority level in described XML configuration file represents the height of the preferential executive level of dynamic link library, including Highest executive level, secondary executive level, three kinds of minimum executive level, are represented with " 1 ", " 2 ", " 3 " respectively;
In described XML configuration file whether be immediately performed including be with it is no, respectively with " t ", " f " represent;
Use state in described XML configuration file includes being currently in use and not using two states, uses respectively " T ", " F " are represented;
Dynamic link library call function title representation program in described XML configuration file is used when calling the model library Function name;
When mode input parameter type in described XML configuration file represents the function of the routine call model, transmission Parameter type, including the type of bool, int, string, float tetra-;
Mode input number of parameters representation program in described XML configuration file calls what is transmitted during the function of the model Number of parameters;
When model output parameters type in described XML configuration file represents the function of the routine call model, transmission Parameter type, including the type of bool, int, string, float tetra-;
Model output parameters number representation program in described XML configuration file calls what is transmitted during the function of the model Number of parameters.
Adaptive algorithm of the present invention needs that diagnostic model dynamic link library is first copied to on-line monitoring equipment before performing Or above the memory space of diagnostic device, and set up XML configuration file;Wherein XML configuration file is calculated after completion is configured Method model starts to be performed according to following steps:
Step 1:Content → detection XML that program starts to perform → load dynamic link library → reading XML configuration file matches somebody with somebody Put file format whether standard, "Yes" perform step 2, "No" program perform terminate, return to step 1;
Step 2:Set up title → reading MAP that XML configuration file MAP maps → obtained from store path dynamic link library Dynamic link library name in mapping → compare whether title is identical, "Yes" performs step 3, and "No" program is performed and terminated, returns Step 1;
Step 3:Read classification → acquisition transformer online monitoring diagnostic model classification (0), the open circuit respectively in MAP mappings Device on-line monitoring and diagnosis model (1), capacitive apparatus on-line monitoring and diagnosis model (2) and sleeve pipe on-line monitoring and diagnosis model (3), hold Row step 4;
Step 4:Transformer online monitoring diagnostic model classification (0) gets the oil chromatography in transformer online monitoring respectively (a), iron core grounding current (b), micro- water (c), micro- gas (d);Breaker on-line monitoring and diagnosis model (1) obtain mechanical spy respectively Property parameter (e), electrical characteristic parameter (f), state of insulation parameter (g);Capacitive apparatus on-line monitoring and diagnosis model (2) are obtained respectively Reactor (h), capacitance type potential transformer (i), current transformer (j), disconnecting switch (k), insulator (l), arc suppression coil (m), arrester (n);Sleeve pipe on-line monitoring and diagnosis model (3) obtain respectively C2H2 contents (o), H2 contents (p), capacitance (q), Dielectric loss (r), end shield earth resistance (s), perform step 5 afterwards;
Step 5:Judge preferential executive level → judge whether to be immediately performed → judge use state → reading call function Title → reading call function |input paramete type → reading call function |input paramete number → reading call function output ginseng Several classes of type → reading call function output parameter number → self-adapting program is performed and terminated;By 5 execution of step, self adaptation Algorithm routine finally confirm program operation preferential executive level, whether be immediately performed, use state, afterwards again by calling Function input parameters type, call function |input paramete number, call function output parameter type and call function output parameter Number is determined and preferentially call which program is performed, so as to realize the self adaptation of on-line monitoring and diagnosis model.
The adaptive algorithm flow is as shown in Figure 1.Adaptive algorithm needs first diagnostic model dynamic chain before performing Connect storehouse to copy to above the memory space of on-line monitoring equipment or diagnostic device, and set up XML configuration accessories.Wherein XML matches somebody with somebody Putting file needs to be described in detail and configure according to the configuration content shown in claims 2.
A. specific algorithm flow implementation process is:Program starts to perform → depositing from on-line monitoring equipment or diagnostic device Storage space above load dynamic link library → reading XML configuration file content → detection XML configuration file form whether standard, Standard then performs b, nonstandard, goes to a;
B. the title that XML configuration file MAP maps → obtained from store path dynamic link library is set up, MAP mappings are read In dynamic link library name → compare title it is whether identical, it is identical, perform c, differ, program is performed and terminated, and is returned to a;
C. the classification in MAP mappings is read, if " 0 ", then d is performed;If " 1 ", then e is performed;If " 2 ", Then perform f;If " 3 ", then g is performed;If " other ", program is performed and terminated, and returns to a;
D. " a ", " b ", " c ", " d " respectively indication transformer on-line monitoring in oil chromatography, iron core grounding current, Wei Shui, Micro- gas, if other then program perform terminate;
E. " e ", " f ", " g " represent mechanical property parameter, electrical characteristic parameter, the insulation in breaker on-line monitoring respectively State parameter, if other then program perform terminate;
F. " h ", " i ", " j ", " k ", " l ", " m " " n " represent reactor, the condenser type in capacitive apparatus on-line monitoring respectively Voltage transformer, current transformer, disconnecting switch, insulator, arc suppression coil, arrester, if other then program perform terminate;
G. " o ", " p ", " q ", " r ", " s " represent respectively sleeve pipe on-line monitoring in C2H2 contents, H2 contents, capacitance, Dielectric loss, end shield earth resistance, if other then program perform terminate;
H. preferential executive level → judge whether to be immediately performed → judge use state → reading call function title is judged → read call function |input paramete type → reading call function |input paramete number → reading call function output parameter class Type → reading call function output parameter number → self-adapting program is performed and terminated.
Priority level in described XML configuration file represents the height of the preferential executive level of dynamic link library, including Highest executive level, secondary executive level, three kinds of minimum executive level, are represented with " 1 ", " 2 ", " 3 " respectively;
Wherein, in described XML configuration file whether be immediately performed including be with it is no, respectively with " t ", " f " represent;
Wherein, the use state in described XML configuration file includes being currently in use and not using two states, respectively Represented with " T ", " F ";
Wherein, the dynamic link library call function title representation program in described XML configuration file calls the model library When the function name that uses;
Wherein, when the mode input parameter type in described XML configuration file represents the function of the routine call model, The parameter type of transmission, including the type of bool, int, string, float tetra-;
Wherein, when the mode input number of parameters representation program in described XML configuration file calls the function of the model The number of parameters of transmission;
Wherein, when the model output parameters type in described XML configuration file represents the function of the routine call model, The parameter type of transmission, including the type of bool, int, string, float tetra-;
Wherein, when the model output parameters number representation program in described XML configuration file calls the function of the model The number of parameters of transmission.

Claims (3)

1. a kind of on-line monitoring and diagnosis model adaptation algorithm for transformer station, it is characterised in that including on-line monitoring and diagnosis Model dynamic link library, XML configuration file and adaptive algorithm;Wherein:
The on-line monitoring and diagnosis model dynamic link library includes that transformer online monitoring diagnostic model, breaker on-line monitoring are examined Disconnected model, 4 kinds of model dynamic link libraries of capacitive apparatus on-line monitoring and diagnosis model and sleeve pipe on-line monitoring and diagnosis model;
The XML configuration file include dynamic link library name, classification, mark, priority level, whether immediately use, use shape State, dynamic link library call function title, mode input parameter type, mode input number of parameters, model output parameters type, Model output parameters number;
Described dynamic link library name be stored in it is online above the memory space of on-line monitoring equipment or diagnostic device Monitoring, diagnosing model name is identical;
Classification in described XML configuration file includes:Transformer online monitoring diagnostic model classification, breaker on-line monitoring are examined Disconnected model, 4 kinds of models of capacitive apparatus on-line monitoring and diagnosis model and sleeve pipe on-line monitoring and diagnosis model, respectively with " 0 ", " 1 ", " 2 ", " 3 " represent.
2. a kind of on-line monitoring and diagnosis model adaptation algorithm for transformer station according to claim 1, its feature exists In:Mark in XML configuration file includes:Oil chromatography, iron core grounding current, Wei Shui in transformer online monitoring, micro- gas, Represented with " a ", " b ", " c ", " d " respectively;Mechanical property parameter, electrical characteristic parameter, insulation shape in breaker on-line monitoring State parameter, is represented with " e ", " f ", " g " respectively;Reactor, capacitance type potential transformer, electric current in capacitive apparatus on-line monitoring Transformer, disconnecting switch, insulator, arc suppression coil, arrester, are represented with " h ", " i ", " j ", " k ", " l ", " m " " n " respectively; Sleeve pipe on-line monitoring in C2H2 contents, H2 contents, capacitance, dielectric loss, end shield earth resistance, respectively with " o ", " p ", " q ", " r ", " s " are represented;
Priority level in described XML configuration file represents the height of the preferential executive level of dynamic link library, including highest Level executive level, secondary executive level, three kinds of minimum executive level, are represented with " 1 ", " 2 ", " 3 " respectively;
In described XML configuration file whether be immediately performed including be with it is no, respectively with " t ", " f " represent;
Use state in described XML configuration file includes being currently in use and not using two states, respectively with " T ", " F " Represent;
Dynamic link library call function title representation program in described XML configuration file calls the letter used during the model library Several titles;
When mode input parameter type in described XML configuration file represents the function of the routine call model, the ginseng of transmission Several classes of type, including the type of bool, int, string, float tetra-;
Mode input number of parameters representation program in described XML configuration file calls the parameter transmitted during the function of the model Number;
When model output parameters type in described XML configuration file represents the function of the routine call model, the ginseng of transmission Several classes of type, including the type of bool, int, string, float tetra-;
Model output parameters number representation program in described XML configuration file calls the parameter transmitted during the function of the model Number.
3. a kind of on-line monitoring and diagnosis model adaptation algorithm for transformer station according to claim 1 and 2, its feature It is:Adaptive algorithm needs that diagnostic model dynamic link library is first copied to on-line monitoring equipment before performing or diagnosis sets Above standby memory space, and set up XML configuration file;Wherein XML configuration file algorithm model after completion is configured starts Performed according to following steps:
Step 1:Program starts to perform → load content → detection XML configuration texts of dynamic link library → reading XML configuration file Part form whether standard, "Yes" perform step 2, "No" program perform terminate, return to step 1;
Step 2:Set up title → reading MAP mappings that XML configuration file MAP maps → obtained from store path dynamic link library In dynamic link library name → compare title it is whether identical, "Yes" performs step 3, and "No" program is performed and terminated, return to step 1;
Step 3:Read the classification → respectively in MAP mappings and obtain transformer online monitoring diagnostic model classification (0), breaker and exist Line monitoring, diagnosing model (1), capacitive apparatus on-line monitoring and diagnosis model (2) and sleeve pipe on-line monitoring and diagnosis model (3), perform step Rapid 4;
Step 4:Transformer online monitoring diagnostic model classification (0) get respectively oil chromatography (a) in transformer online monitoring, Iron core grounding current (b), micro- water (c), micro- gas (d);Breaker on-line monitoring and diagnosis model (1) obtain mechanical property ginseng respectively Number (e), electrical characteristic parameter (f), state of insulation parameter (g);Capacitive apparatus on-line monitoring and diagnosis model (2) obtain reactance respectively Device (h), capacitance type potential transformer (i), current transformer (j), disconnecting switch (k), insulator (l), arc suppression coil (m), keep away Thunder device (n);Sleeve pipe on-line monitoring and diagnosis model (3) obtain C2H2 contents (o), H2 contents (p), capacitance (q), dielectric loss respectively R (), end shield earth resistance (s), performs step 5 afterwards;
Step 5:Judge preferential executive level → judge whether to be immediately performed → judge use state → reading call function title → read call function |input paramete type → reading call function |input paramete number → reading call function output parameter class Type → reading call function output parameter number → self-adapting program is performed and terminated;By 5 execution of step, adaptive algorithm Program finally confirm program operation preferential executive level, whether be immediately performed, use state, afterwards again pass through call function |input paramete type, call function |input paramete number, call function output parameter type and call function output parameter number Determine and preferentially call which program is performed, so as to realize the self adaptation of on-line monitoring and diagnosis model.
CN201611173979.8A 2016-12-16 2016-12-16 A kind of on-line monitoring and diagnosis model adaptation algorithm for transformer station Pending CN106844851A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201611173979.8A CN106844851A (en) 2016-12-16 2016-12-16 A kind of on-line monitoring and diagnosis model adaptation algorithm for transformer station

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201611173979.8A CN106844851A (en) 2016-12-16 2016-12-16 A kind of on-line monitoring and diagnosis model adaptation algorithm for transformer station

Publications (1)

Publication Number Publication Date
CN106844851A true CN106844851A (en) 2017-06-13

Family

ID=59140231

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201611173979.8A Pending CN106844851A (en) 2016-12-16 2016-12-16 A kind of on-line monitoring and diagnosis model adaptation algorithm for transformer station

Country Status (1)

Country Link
CN (1) CN106844851A (en)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111208385A (en) * 2019-12-19 2020-05-29 云南电网有限责任公司玉溪供电局 Online fault layered diagnosis method for power grid

Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103336213A (en) * 2013-07-06 2013-10-02 云南电力试验研究院(集团)有限公司电力研究院 In-situ diagnostic method and device used for on-line monitoring of transformer substation
CN105652137A (en) * 2015-12-28 2016-06-08 云南电网有限责任公司电力科学研究院 Transformer substation online monitoring and diagnosis model identification method and device

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103336213A (en) * 2013-07-06 2013-10-02 云南电力试验研究院(集团)有限公司电力研究院 In-situ diagnostic method and device used for on-line monitoring of transformer substation
CN105652137A (en) * 2015-12-28 2016-06-08 云南电网有限责任公司电力科学研究院 Transformer substation online monitoring and diagnosis model identification method and device

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111208385A (en) * 2019-12-19 2020-05-29 云南电网有限责任公司玉溪供电局 Online fault layered diagnosis method for power grid

Similar Documents

Publication Publication Date Title
CN104133146B (en) A kind of feeder automation fault handling logic on-the-spot test method
CN101821750A (en) Method of automatically generating an SSD file
CN102967780A (en) Modeling method for substation intelligent alarm
CN107657019B (en) Network topology structure obtaining method and system of power grid system
CN105335342A (en) Method for automatic examination of wiring correctness of intelligent substation SCD configuration file virtual terminator
CN103500249A (en) Visual relay protection setting calculation system and method
CN105445585B (en) The method for diagnosing faults and system of power grid primary circuit
CN110852023B (en) Automatic generation method and device for primary main wiring diagram of intelligent substation
CN108733928A (en) A kind of SCD file void circuit automatic Verification method based on mid-module file
CN105652137B (en) A kind of substation's on-line monitoring and diagnosis method of model identification and device
CN112733430B (en) Intelligent line selection and section positioning method and device for power distribution network faults
CN106292576B (en) A kind of mapping method of SCL models and CIM model
CN108490282B (en) Method and system for presetting alarm test data of intelligent substation
CN105574291A (en) Automatic power supply loop configuration method and system
CN113300356A (en) Low-voltage distribution area topology identification method
CN106844851A (en) A kind of on-line monitoring and diagnosis model adaptation algorithm for transformer station
US20130211610A1 (en) Configuring of a field device in an arragement for distribution of electric energy
Poudel et al. Admittance matrix validation for power distribution system models using a networked equipment model framework
CN104463699A (en) Intelligent substation control layer information extraction method and device
CN110032389B (en) Method and system for configuring process layer communication
CN115293073A (en) Method and device for converting BPA electromechanical transient model into ADPSS electromagnetic transient model
CN108242028A (en) Substation Bus Arrangement figure and intelligent alarm test case visualization automatic correlation method
CN103217192A (en) Intelligent assembly
CN105956107A (en) Data quality detection method based on IEC61968
CN113359656A (en) Test system, test cabinet and test method for generator set control box

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
RJ01 Rejection of invention patent application after publication

Application publication date: 20170613

RJ01 Rejection of invention patent application after publication