CN103617561A - System and method for evaluating state of secondary equipment of power grid intelligent substation - Google Patents
System and method for evaluating state of secondary equipment of power grid intelligent substation Download PDFInfo
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Abstract
The invention provides a state evaluation system for secondary equipment of a power grid intelligent substation, which comprises: the system comprises an intelligent substation, a security master station, a full-dimensional management system, a production management system and secondary equipment of a bay level of the intelligent substation; the secondary equipment is connected with the information protection substation equipment of the intelligent substation, the information protection main station obtains online monitoring information of the secondary equipment through a configuration mode of a calling substation of the information protection main station, and the online monitoring information and self-checking data of the online monitoring information are sent to the full-dimensional management system; and the full-dimensional management system adopts different model algorithms to evaluate the state of the secondary equipment. By implementing the invention, the transformer substation secondary equipment monitoring and state evaluation module is established in the full-dimensional management system, and the transformer substation secondary equipment state evaluation based on the information fusion model and method can be realized, so that the investment and maintenance cost can be greatly reduced.
Description
Technical field
The present invention relates to power technology field, relate in particular to a kind of electrical network secondary equipment of intelligent converting station status assessing system and method.
Background technology
The intellectuality of electric system, requires to realize to the management of electrical equipment life cycle management, to the reliability of electrical equipment and operation maintenance, requires more and more higher.
At present, power enterprises practice be take scheduled overhaul and is main overhaul of the equipments system, this maintenance system guarantee human and material resources and fund etc. arrange planned, kept the basicly stable property of power supply.But in fact, the health status of electrical equipment is subject to the impact of running environment, various disturbing factor and individual inherent quality.For the more equipment of defect, often move less than the next repair time, the lower work of just nonserviceabling, even because of the disorderly closedown accident maintenance of having to, and equipment in good condition just may carry out unnecessary maintenance according to schedule.The equipment that scheduled overhaul causes is crossed and is repaiied or in bad repair, has greatly increased undoubtedly the cost of overhaul and the running losses of enterprise, so the service technique of electric power enterprise urgently further improves.
The maintenance of reasonable arrangement electrical equipment, saves recondition expense, reduces the cost of overhaul, guarantees that operation of power networks has higher reliability simultaneously, is an important topic of electric system.Along with the integrated intelligent systems such as sensing technology, microelectronics, computer software and hardware and Digital Signal Processing, fuzzy set theory, artificial neural network, expert system, information fusion technology are applied in monitoring of equipment and state estimation, make the repair based on condition of component research based on equipment condition monitoring and advanced diagnostic techniques and apply developed.
At present, the research of the repair based on condition of component of electric system primary equipment with apply comparative maturity, the repair based on condition of component of the main equipments such as power transformer, isolating switch and genset has successful application.But, the repair based on condition of component of electrical secondary equipment is only in the starting stage, its main cause is that on-line monitoring secondary device own health status means also lack as the state evaluation system of the electrical secondary equipment of the important evidence of repair based on condition of component is sound not enough, method is perfect not.
Denomination of invention is " monitoring system of operation condition of digitalized substation secondary device and method ", publication number is that the patent application of CN101854078A discloses a kind of monitoring method that can realize digitalized substation secondary device, but needs network analyzer corresponding to special configuration and state monitoring apparatus etc.
Denomination of invention is " a kind of monitoring system of the digitalized substation secondary device based on WEB service ", notification number is that the monitoring system of the disclosed secondary device of utility model patent of CN202034826U also must be by means of special hardware device as rear portion expander board and bus backplane, some blocks of data Gather and input plates, some block control signal output boards etc., to realize the monitoring of secondary device; And the critical function of secondary equipment of intelligent converting station is exactly to the monitoring of electric main equipment and control, itself just there is more perfect self check and monitoring and network communicating function, should not add again the monitoring that special equipment or device are realized secondary device.
Denomination of invention is " second power equipment method for evaluating state and system thereof ", publication number be the China application of CN102324067A disclose a kind of to the every maintenance state parameter of secondary device the weight proportion computation model to maintenance state value, for calculating, judge the maintenance state of described secondary device, it has been considered the different weights of every maintenance state parameter but has not been considered ambiguity, probability metastatic of every maintenance state parameter etc., but has not mentioned the acquisition methods of the real-time detected value of secondary device state parameter.
Therefore, prior art is disclosed improves and science not enough to second power equipment state online measuring technique.
Summary of the invention
For solving the problems of the technologies described above, the invention provides a kind of electrical network secondary equipment of intelligent converting station status assessing system, this system comprises:
Intelligent substation, Prudential Master, full dimension management system, production management system, the secondary device of interval between intelligent substation;
The prudential sub-station equipment connection of described secondary device and intelligent substation, described Prudential Master calls the configuration mode of substation to obtain the on-line monitoring information of described secondary device by Prudential Master, together with its self check data, is sent to described full dimension management system;
Described full dimension management system comprises:
Data level processing module, for gathering described secondary device self check and Monitoring Data from described centralized control center Prudential Master, and the running state data and the family's defective data that from described production management system, gather described secondary device;
Operation characteristic level evaluation module, for adopting different model algorithms to carry out state estimation to described secondary device;
Decision level fusion module, for based on information fusion method, the evaluation index of described self check and Monitoring Data, running state data, family's defective data being carried out to belief assignment, according to evaluation criteria and information fusion result, the state of described secondary device is carried out to comprehensive assessment.
Wherein, described operation characteristic level evaluation module comprises:
Fuzzy comprehensive evoluation submodule, for adopting fuzzy comprehensive evaluation method to analyze its state and degree of membership thereof to the self check of described secondary device and Monitoring Data;
Prediction of Markov submodule, adopts Markov method event prediction method to analyze the probability of its future period in predetermined state for the running state data to described secondary device;
Logic association judgement submodule, adopts logic association determining method to analyze the influence degree of family's defect to secondary device state for the family's defective data to described secondary device.
Accordingly, the present invention also provides a kind of electrical network secondary equipment of intelligent converting station state evaluating method, and the method realizes based on aforesaid electrical network secondary equipment of intelligent converting station status assessing system, comprising:
Described Prudential Master calls the configuration mode of substation to obtain the on-line monitoring information of described secondary device by Prudential Master, together with its self check data, is sent to described full dimension management system;
Described full dimension management system gathers described secondary device self check and Monitoring Data from described centralized control center Prudential Master, and the running state data and the family's defective data that from described production management system, gather described secondary device;
Described full dimension management system adopts different model algorithms to carry out state estimation to described secondary device;
Described full dimension management system is carried out belief assignment based on information fusion method to the evaluation index of described self check and Monitoring Data, running state data, family's defective data, according to evaluation criteria and information fusion result, the state of described secondary device is carried out to comprehensive assessment.
Wherein, described full dimension management system adopts different model algorithms to carry out state estimation to described secondary device, comprising:
To the self check of described secondary device and Monitoring Data, adopt fuzzy comprehensive evaluation method to analyze its state and degree of membership thereof;
To the running state data of described secondary device, adopt Markov method event prediction method to analyze the probability of its future period in predetermined state;
To family's defective data of described secondary device, adopt logic association determining method to analyze the influence degree of family's defect to secondary device state.
Wherein, to the self check of described secondary device and Monitoring Data, adopt fuzzy comprehensive evaluation method to analyze its state and degree of membership thereof, comprising:
Self check and the on-line monitoring information of determining described secondary device form factor of evaluation collection;
Adopt analytical hierarchy process to solve the weighted value that described factor of evaluation is concentrated each factor of evaluation;
The health status of described secondary device is divided into four grades, and the form factor of these four grades forms state evaluation collection, and determines that concentrated each factor of evaluation of described factor of evaluation is corresponding to the evaluation criteria of described state evaluation collection;
Obtaining respectively described factor of evaluation concentrates each factor of evaluation corresponding to the degree of membership of each concentrated form factor of described state evaluation;
Build the model of fuzzy synthetic evaluation that adopts weighted mean Fuzzy compose operation, adopt the evaluation principle of fuzzy increasing and index method, the state of described secondary device is comprehensively passed judgment on.
Wherein, to the running state data of described secondary device, adopt Markov method event prediction method to analyze the probability of its future period in predetermined state, comprising:
Build Markov method event prediction model;
Determine that the one of four states in described Markov method event prediction model is normal condition, attention state, abnormality, serious state;
Build state transition probability matrix, according to the initial state probability of described secondary device, predict the probability of described secondary device future period in predetermined state.
Wherein, to family's defective data of described secondary device, adopt logic association determining method to analyze the influence degree of family's defect to secondary device state, comprising:
Build family's defect evaluate formula to analyze the influence degree of family's defect to secondary device state, wherein ，Gai family defect evaluate formula is:
Wherein, F is influence degree; N is the total number of units of family's equipment; M is repeated defects number of units; n
jit is the equipment deficiency scoring of j platform family; W
fjit is j platform equipment family mass defect weight.
Wherein, described full dimension management system is carried out belief assignment based on information fusion method to the evaluation index of described self check and Monitoring Data, running state data, family's defective data, according to evaluation criteria and information fusion result, the state of described secondary device is carried out to comprehensive assessment, comprising:
Component information merges assessment models, and it comprises data Layer, characteristic layer, decision-making level;
At described data Layer, the status information of each secondary device is categorized as to on-line monitoring information, operation information and family's defect information, at described characteristic layer, adopt respectively different model algorithms to carry out the assessment assessment result of state, realize its normal condition, attention state, abnormality, serious shape probability of state and belief assignment;
In decision-making level, by DS synthetic method, obtain the belief assignment under four kinds of different conditions of secondary device after merging;
According to evaluation criteria and information fusion result, realize the state estimation to described secondary device.
Implement the present invention, there is following beneficial effect:
1. at Prudential Master end, create the static model of substation.Consider that protection information system itself has the ability of secondary device modeling; protection information main website (abbreviation Prudential Master) sets up the model of transformer station's wall secondary device by the mode of calling substation configuration; when prudential sub-station response main website calls; protection and oscillograph device in seeing off not only also send substation itself on a device.Prudential Master can obtain the data such as all remote signalling classes, analog quantity, definite value, process, cpu load rate, EMS memory occupation ratio, SOE resolution of the device such as substation secondary device protection, observing and controlling and oscillograph;
2. at full dimension management system FDMS(Full Dimension Management System) in set up substation secondary device monitoring and state estimation module, need to and not safeguard specially at the other erecting device of transformer substation side, at the RTU(Remote Terminal of remote data acquisition and supervisory system and transformer substation side Unit, terminal unit) can normally move, substation secondary device state estimation based on information fusion model and method just can be realized, and can greatly reduce investment and maintenance cost;
3. described in, the assessment of electric grid secondary equipment state is to be based upon in the full dimension management system FDMS of power supply administration system, can read all substation secondary device information of full electric network, comprise equipment on-line monitoring information, operation information and family's defect information etc., therefore can evaluate all substation secondary device states of electrical network, be convenient to the running status that operation maintenance personnel grasp equipment in time, for realizing the repair based on condition of component of electric grid secondary equipment, provide decision-making foundation simultaneously, thereby can improve the safety and reliability of operation of power networks.
Accompanying drawing explanation
In order to be illustrated more clearly in the embodiment of the present invention or technical scheme of the prior art, to the accompanying drawing of required use in embodiment or description of the Prior Art be briefly described below, apparently, accompanying drawing in the following describes is only some embodiments of the present invention, for those of ordinary skills, do not paying under the prerequisite of creative work, can also obtain according to these accompanying drawings other accompanying drawing.
Fig. 1 is the composition schematic diagram of a kind of electrical network secondary equipment of intelligent converting station status assessing system provided by the invention;
Fig. 2 is the network diagram of a kind of electrical network secondary equipment of intelligent converting station status assessing system provided by the invention;
Fig. 3 is the composition schematic diagram of the full dimension management system in a kind of electrical network secondary equipment of intelligent converting station status assessing system provided by the invention;
Fig. 4 also provides the schematic flow sheet of a kind of electrical network secondary equipment of intelligent converting station state evaluating method embodiment mono-for the present invention;
Fig. 5 also provides the schematic flow sheet of a kind of electrical network secondary equipment of intelligent converting station state evaluating method embodiment bis-for the present invention;
Fig. 6 also provides the schematic flow sheet of a kind of electrical network secondary equipment of intelligent converting station state evaluating method embodiment tri-for the present invention;
Fig. 7 also provides the schematic flow sheet of a kind of electrical network secondary equipment of intelligent converting station state evaluating method embodiment tetra-for the present invention;
Fig. 8 also provides electric grid secondary equipment state space diagram in a kind of electrical network secondary equipment of intelligent converting station state evaluating method for the present invention;
Fig. 9 also provides the schematic flow sheet of a kind of electrical network secondary equipment of intelligent converting station state evaluating method embodiment five for the present invention;
Figure 10 also provides the schematic flow sheet of a kind of electrical network secondary equipment of intelligent converting station state evaluating method embodiment six for the present invention.
Embodiment
The present invention proposes self check and monitoring function and the networking characteristic by secondary equipment of intelligent converting station self, by being based upon the network platform of guarantor's communication system of centralized control center-intelligent substation, only need to set up respectively special software function module at guarantor's communication system and the full dimension management system of power supply administration, just can obtain self check and the monitoring information of secondary device, not need to set up in addition hardware unit; The present invention simultaneously proposes that the state parameter of secondary device is divided into self check and monitoring, service data, family's defective data philosophy adopt fuzzy evaluation, state probability transfer, three kinds of models of logic association weighting to evaluate respectively, then according to DS(Dempster Shafer, evidence theory) three class evaluations are carried out to information fusion and this equipment is carried out to the comprehensive evaluation of state, more scientific and reasonable.
Referring to Fig. 1 and Fig. 2, Fig. 1 is the composition schematic diagram of a kind of electrical network secondary equipment of intelligent converting station status assessing system provided by the invention, and Fig. 2 is network diagram, and this system comprises:
Described secondary device 5 is connected with the prudential sub-station equipment 10 of intelligent substation 1, described Prudential Master 2 calls the configuration mode of substation to obtain the on-line monitoring information of described secondary device 5 by Prudential Master, together with its self check data, is sent to described full dimension management system 3.
Referring to Fig. 3, described full dimension management system 3 comprises:
Data level processing module 30, for gathering described secondary device self check and Monitoring Data from described centralized control center Prudential Master, and the running state data and the family's defective data that from described production management system, gather described secondary device;
Operation characteristic level evaluation module 31, for adopting different model algorithms to carry out state estimation to described secondary device;
Decision level fusion module 32, for based on information fusion method, the evaluation index of described self check and Monitoring Data, running state data, family's defective data being carried out to belief assignment, according to evaluation criteria and information fusion result, the state of described secondary device is carried out to comprehensive assessment.
Wherein, described operation characteristic level evaluation module 31 comprises:
Fuzzy comprehensive evoluation submodule 310, for adopting fuzzy comprehensive evaluation method to analyze its state and degree of membership thereof to the self check of described secondary device and Monitoring Data;
Prediction of Markov submodule 311, adopts Markov method event prediction method to analyze the probability of its future period in predetermined state for the running state data to described secondary device;
Logic association judgement submodule 312, adopts logic association determining method to analyze the influence degree of family's defect to secondary device state for the family's defective data to described secondary device.
Accordingly, the present invention also provides a kind of electrical network secondary equipment of intelligent converting station state evaluating method, and the method realizes based on aforesaid electrical network secondary equipment of intelligent converting station status assessing system, flow process shown in Figure 4, and it specifically comprises:
Referring to Fig. 5, described full dimension management system adopts different model algorithms described secondary device to be carried out to the method step of state estimation, specifically comprises:
Referring to Fig. 6, to the self check of described secondary device and Monitoring Data, adopt fuzzy comprehensive evaluation method to analyze the method step of its state and degree of membership thereof, specifically comprise:
Step 300, determines that the self check of described secondary device and on-line monitoring information form factor of evaluation collection;
Concrete, determining that the self check of electric grid secondary equipment and on-line monitoring information form factor of evaluation collection U, U is that each quantity of state of reflection secondary device state is the set that element forms, i.e. U={u
1, u
2, Λ, u
n, in formula, u
1, u
2, L, u
n, i.e. each quantity of state of secondary device, this quantity of state is determined according to the self check of the different secondary equipment that can obtain by Prudential Master and substation in FDMS and on-line monitoring information.
Step 301, adopts analytical hierarchy process to solve the weighted value that described factor of evaluation is concentrated each factor of evaluation;
The evaluation result of minute pairing electric grid secondary equipment state of each factor weight plays vital effect, and its general expression-form is A={a
1, a
2, Λ, a
n.A
irepresent i the weighted value that factor is corresponding.
In the present invention, adopt analytical hierarchy process to solve weighted value vector.
First, Judgement Matricies M, wherein u
ijrepresent that factor of evaluation concentrates u
ito u
jrelative importance numerical value.
According to M judgment matrix, obtain the corresponding proper vector of maximum characteristic root again, required proper vector is weighted value Vector Groups.
Step 302, is divided into four grades by the health status of described secondary device, and the form factor of these four grades forms state evaluation collection, and determines that concentrated each factor of evaluation of described factor of evaluation is corresponding to the evaluation criteria of described state evaluation collection;
The present invention mainly assesses the state of electric grid secondary equipment by the mode of scoring.Concrete, the health status of electric grid secondary equipment is divided into 4 grades, i.e. state evaluation collection V={ normal condition, attention state, abnormality, serious state }, and determine the evaluation criteria corresponding with state evaluation collection V according to equipment state with scoring recommendation tables.
Step 303, obtains respectively described factor of evaluation and concentrates each factor of evaluation corresponding to the degree of membership of each concentrated form factor of described state evaluation;
The present invention is to represent by degree of membership when describing secondary device and the concentrated evaluation result of state evaluation and be related to, wherein degree of membership is asked for by membership function.
Concrete, the degree of membership r of electric grid secondary equipment state assessment
ijrepresent in factor of evaluation collection U the degree of membership of i factor value to j grade in state evaluation collection V.Concrete, obtain respectively i factor value in factor of evaluation collection U, corresponding to evaluating the degree of membership of V1, V2, V3, V4, V5 in state evaluation collection V, be degree of membership matrix.
Step 304, builds the model of fuzzy synthetic evaluation that adopts weighted mean Fuzzy compose operation, adopts the evaluation principle of fuzzy increasing and index method, and the state of described secondary device is comprehensively passed judgment on.
Wherein, the model of fuzzy synthetic evaluation of structure is:
B=AoR={b
1,b
2,b
3,b
4,b
5} （2）
In formula "." expression fuzzy composition operator.
In order to retain whole useful informations, described model of fuzzy synthetic evaluation is selected " weighted mean type " fuzzy composition computing, evaluates principle and adopts fuzzy comprehensive index, and fuzzy overall evaluation index is:
In formula, S
tfor classification standard vector.
Referring to Fig. 7, to the running state data of described secondary device, adopt Markov method event prediction method to analyze the step of the probability of its future period in predetermined state, specifically comprise:
Concrete, according to rules, secondary device is divided into normal condition, attention state, abnormality and serious state four classes, set up Prediction of Markov model, universal law according to the deteriorated development of equipment state, think that the equipment of normal condition should only may be deteriorated gradually to attention state, abnormality and serious state successively, determine the transfer relationship between each state.Note μ
ijfor the rate of transform to state j by state i, set up the electric grid secondary equipment state space diagram based on Prediction of Markov method, as shown in Figure 8.
In specific implementation, first, according to the rate of transform between each state in electric grid secondary equipment state space diagram, set up state transition probability matrix K.
Note secondary device current state is i, the state probability P of next stage i+1 equipment
i+1for:
P
i+1=P
i·K （8）
And the long-term state probability P of secondary device
mcan be tried to achieve by following formula:
Referring to Fig. 9, to family's defective data of described secondary device, adopt logic association determining method to analyze the step of family's defect to the influence degree of secondary device state, specifically comprise:
Step 500, builds family's defect evaluate formula to analyze the influence degree of family's defect to secondary device state, and wherein ，Gai family defect evaluate formula is:
Wherein, F is influence degree; N is the total number of units of family's equipment; M is repeated defects number of units; n
jit is the equipment deficiency scoring of j platform family; W
fjit is j platform equipment family mass defect weight.
It should be noted that, " family " in family's defect is and other equipment of three types that are evaluated secondary device and belong to the same same model ,Huo Tong of manufacturer manufacturer's different model or the different manufacturers of same model; It is generally acknowledged the homology due to family's equipment design, manufacture and structure aspects, the defect of family's equipment is reacted the health status that (association) is evaluated the state of equipment to a certain extent, and correlation degree and family device type, the defect order of severity are relevant.
Step 501, relatively draws W according to the type in family's equipment and Defect Correlation degree between two by each object
fjweight.
Concrete, W
fjweight is divided into " 2,4,6,8 " four grades and is designated as a
ij, corresponding judgement is " slightly relevant, some is relevant, very relevant, extremely relevant ", certainly also can insert the sub-grades such as 1,3,5,7.Form numerical value judgment matrix A=[a
ij];
Calculate the long-pending M of each row element of judgment matrix A
i:
Calculate each row M
in power root:
In formula, n is matrix exponent number.
By vector
normalization, is calculated as follows:
W
ibe the weight of each required index.
Referring to Figure 10, described full dimension management system is carried out belief assignment based on information fusion method to the evaluation index of described self check and Monitoring Data, running state data, family's defective data, according to evaluation criteria and information fusion result, the state of described secondary device is carried out to the step of comprehensive assessment, specifically comprises:
In specific implementation, information fusion assessment models is that the general framework of fusion treatment is three-decker: data Layer, characteristic layer and decision-making level, model as shown in Figure 3.Its framework can well treatment facility self check and monitoring information, operation information, defect information, the information fusion that is conducive to three class different characteristics is carried out state estimation.Data Layer is mainly the raw data of fusion treatment multiple information sources input; Characteristic layer is to adopt various analytical approachs to extract the feature of data Layer fusion results; Decision-making level carrys out the information characteristics of Classification and Identification different aforementioned sources based on priori, thereby draws final fusion results.
In specific implementation, establish Bel
1and Bel
2two belief functions on same identification framework U, while m
1and m
2its corresponding basic probability assignment function, if
and m (A) >0, claims that A is burnt unit; Burnt unit is respectively A
1, A
2..., A
nand B
1, B
2..., B
n, and hypothesis
More than two belief function Bel
1and Bel
2compositional rule, be designated as Bel
1⊕ Bel
2.If belief function to be synthesized, more than 2, can synthesize the synthetic result of back and next belief function with same algorithm, until all belief functions are synthetic complete.The hypothesis with maximum confidence and likelihood score is the evaluation result of this equipment state model.
Implement the present invention, there is following beneficial effect:
1. at Prudential Master end, create the static model of substation.Consider that protection information system itself has the ability of secondary device modeling; protection information main website (abbreviation Prudential Master) sets up the model of transformer station's wall secondary device by the mode of calling substation configuration; when prudential sub-station response main website calls; protection and oscillograph device in seeing off not only also send substation itself on a device.Prudential Master can obtain the data such as all remote signalling classes, analog quantity, definite value, process, cpu load rate, EMS memory occupation ratio, SOE resolution of the device such as substation secondary device protection, observing and controlling and oscillograph;
2. in full dimension management system FDMS, set up substation secondary device monitoring and state estimation module, need to and not safeguard specially at the other erecting device of transformer substation side, at the RTU(Remote Terminal of remote data acquisition and supervisory system and transformer substation side Unit, terminal unit) can normally move, substation secondary device state estimation based on information fusion model and method just can be realized, and can greatly reduce investment and maintenance cost;
3. described in, the assessment of electric grid secondary equipment state is to be based upon in the full dimension management system FDMS of power supply administration system, can read all substation secondary device information of full electric network, comprise equipment on-line monitoring information, operation information and family's defect information etc., therefore can evaluate all substation secondary device states of electrical network, be convenient to the running status that operation maintenance personnel grasp equipment in time, for realizing the repair based on condition of component of electric grid secondary equipment, provide decision-making foundation simultaneously, thereby can improve the safety and reliability of operation of power networks.
One of ordinary skill in the art will appreciate that all or part of flow process realizing in above-described embodiment method, to come the hardware that instruction is relevant to complete by computer program, described program can be stored in a computer read/write memory medium, this program, when carrying out, can comprise as the flow process of the embodiment of above-mentioned each side method.Wherein, described storage medium can be magnetic disc, CD, read-only store-memory body (Read-Only Memory, ROM) or random store-memory body (Random Access Memory, RAM) etc.
Above content is in conjunction with concrete preferred implementation further description made for the present invention, can not assert that specific embodiment of the invention is confined to these explanations.For general technical staff of the technical field of the invention, without departing from the inventive concept of the premise, can also make some simple deduction or replace, all should be considered as belonging to protection scope of the present invention.
Claims (8)
1. an electrical network secondary equipment of intelligent converting station status assessing system, is characterized in that, this system comprises:
Intelligent substation, Prudential Master, full dimension management system, production management system, the secondary device of interval between intelligent substation;
The prudential sub-station equipment connection of described secondary device and intelligent substation, described Prudential Master calls the configuration mode of substation to obtain the on-line monitoring information of described secondary device by Prudential Master, together with its self check data, is sent to described full dimension management system;
Described full dimension management system comprises:
Data level processing module, for gathering described secondary device self check and Monitoring Data from described centralized control center Prudential Master, and the running state data and the family's defective data that from described production management system, gather described secondary device;
Operation characteristic level evaluation module, for adopting different model algorithms to carry out state estimation to described secondary device;
Decision level fusion module, for based on information fusion method, the evaluation index of described self check and Monitoring Data, running state data, family's defective data being carried out to belief assignment, according to evaluation criteria and information fusion result, the state of described secondary device is carried out to comprehensive assessment.
2. electrical network secondary equipment of intelligent converting station status assessing system as claimed in claim 1, is characterized in that, described operation characteristic level evaluation module comprises:
Fuzzy comprehensive evoluation submodule, for adopting fuzzy comprehensive evaluation method to analyze its state and degree of membership thereof to the self check of described secondary device and Monitoring Data;
Prediction of Markov submodule, adopts Markov method event prediction method to analyze the probability of its future period in predetermined state for the running state data to described secondary device;
Logic association judgement submodule, adopts logic association determining method to analyze the influence degree of family's defect to secondary device state for the family's defective data to described secondary device.
3. an electrical network secondary equipment of intelligent converting station state evaluating method, is characterized in that, the electrical network secondary equipment of intelligent converting station status assessing system of the method based on described in any one in claim 1 to 2 realized, and comprising:
Described Prudential Master calls the configuration mode of substation to obtain the on-line monitoring information of described secondary device by Prudential Master, together with its self check data, is sent to described full dimension management system;
Described full dimension management system gathers described secondary device self check and Monitoring Data from described centralized control center Prudential Master, and the running state data and the family's defective data that from described production management system, gather described secondary device;
Described full dimension management system adopts different model algorithms to carry out state estimation to described secondary device;
Described full dimension management system is carried out belief assignment based on information fusion method to the evaluation index of described self check and Monitoring Data, running state data, family's defective data, according to evaluation criteria and information fusion result, the state of described secondary device is carried out to comprehensive assessment.
4. electrical network secondary equipment of intelligent converting station state evaluating method as claimed in claim 3, is characterized in that, described full dimension management system adopts different model algorithms to carry out state estimation to described secondary device, comprising:
To the self check of described secondary device and Monitoring Data, adopt fuzzy comprehensive evaluation method to analyze its state and degree of membership thereof;
To the running state data of described secondary device, adopt Markov method event prediction method to analyze the probability of its future period in predetermined state;
To family's defective data of described secondary device, adopt logic association determining method to analyze the influence degree of family's defect to secondary device state.
5. electrical network secondary equipment of intelligent converting station state evaluating method as claimed in claim 4, is characterized in that, to the self check of described secondary device and Monitoring Data, adopts fuzzy comprehensive evaluation method to analyze its state and degree of membership thereof, comprising:
Self check and the on-line monitoring information of determining described secondary device form factor of evaluation collection;
Adopt analytical hierarchy process to solve the weighted value that described factor of evaluation is concentrated each factor of evaluation;
The health status of described secondary device is divided into four grades, and the form factor of these four grades forms state evaluation collection, and determines that concentrated each factor of evaluation of described factor of evaluation is corresponding to the evaluation criteria of described state evaluation collection;
Obtaining respectively described factor of evaluation concentrates each factor of evaluation corresponding to the degree of membership of each concentrated form factor of described state evaluation;
Build the model of fuzzy synthetic evaluation that adopts weighted mean Fuzzy compose operation, adopt the evaluation principle of fuzzy increasing and index method, the state of described secondary device is comprehensively passed judgment on.
6. electrical network secondary equipment of intelligent converting station state evaluating method as claimed in claim 5, is characterized in that, to the running state data of described secondary device, adopts Markov method event prediction method to analyze the probability of its future period in predetermined state, comprising:
Build Markov method event prediction model;
Determine that the one of four states in described Markov method event prediction model is normal condition, attention state, abnormality, serious state;
Build state transition probability matrix, according to the initial state probability of described secondary device, predict the probability of described secondary device future period in predetermined state.
7. electrical network secondary equipment of intelligent converting station state evaluating method as claimed in claim 6, is characterized in that, to family's defective data of described secondary device, adopts logic association determining method to analyze the influence degree of family's defect to secondary device state, comprising:
Build family's defect evaluate formula to analyze the influence degree of family's defect to secondary device state, wherein ，Gai family defect evaluate formula is:
Wherein, F is influence degree; N is the total number of units of family's equipment; M is repeated defects number of units; n
jit is the equipment deficiency scoring of j platform family; W
fjit is j platform equipment family mass defect weight.
8. electrical network secondary equipment of intelligent converting station state evaluating method as claimed in claim 7, it is characterized in that, described full dimension management system is carried out belief assignment based on information fusion method to the evaluation index of described self check and Monitoring Data, running state data, family's defective data, according to evaluation criteria and information fusion result, the state of described secondary device is carried out to comprehensive assessment, comprising:
Component information merges assessment models, and it comprises data Layer, characteristic layer, decision-making level;
At described data Layer, the status information of each secondary device is categorized as to on-line monitoring information, operation information and family's defect information, at described characteristic layer, adopt respectively different model algorithms to carry out the assessment assessment result of state, realize its normal condition, attention state, abnormality, serious shape probability of state and belief assignment;
In decision-making level, by evidence theory synthetic method, obtain the belief assignment under four kinds of different conditions of secondary device after merging;
According to evaluation criteria and information fusion result, realize the state estimation to described secondary device.
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