CN103793854A  Multiple combination optimization overhead transmission line operation risk informatization assessment method  Google Patents
Multiple combination optimization overhead transmission line operation risk informatization assessment method Download PDFInfo
 Publication number
 CN103793854A CN103793854A CN201410027736.8A CN201410027736A CN103793854A CN 103793854 A CN103793854 A CN 103793854A CN 201410027736 A CN201410027736 A CN 201410027736A CN 103793854 A CN103793854 A CN 103793854A
 Authority
 CN
 China
 Prior art keywords
 risk
 transmission line
 entropy
 indicator
 value
 Prior art date
Links
 230000005540 biological transmission Effects 0.000 title claims abstract description 71
 238000005457 optimization Methods 0.000 title claims abstract description 11
 238000000034 methods Methods 0.000 claims abstract description 15
 238000004364 calculation methods Methods 0.000 claims description 15
 239000011159 matrix materials Substances 0.000 claims description 10
 238000001921 nucleic acid quantification Methods 0.000 claims description 7
 280000867207 Lambda companies 0.000 claims description 6
 238000007476 Maximum Likelihood Methods 0.000 claims description 3
 230000003449 preventive Effects 0.000 claims description 3
 238000004519 manufacturing process Methods 0.000 claims description 2
 238000004458 analytical methods Methods 0.000 description 8
 230000000694 effects Effects 0.000 description 3
 238000005516 engineering processes Methods 0.000 description 3
 238000010276 construction Methods 0.000 description 2
 238000010586 diagrams Methods 0.000 description 2
 208000008425 Protein Deficiency Diseases 0.000 description 1
 230000000875 corresponding Effects 0.000 description 1
 238000009826 distribution Methods 0.000 description 1
 230000002265 prevention Effects 0.000 description 1
 238000004064 recycling Methods 0.000 description 1
Classifications

 Y02E40/76—

 Y04S10/545—

 Y04S10/60—
Abstract
Description
Technical field
The present invention relates to a kind of Operation of Electric Systems safety technique, be specifically related to a kind of overhead transmission line operation risk informatization evaluation method that Multiple Combination is optimized.
Background technology
The risk assessment of Operation of Electric Systems safety has reflected the process that people deepen continuously to the understanding of power system stability and safe operation.Overhead transmission line is being born the main power transmission mode of power construction, be accompanied by the continuous increase of power grid construction scale, the safety and stablization problem of transmission line of electricity operation is also outstanding gradually, and the impact of electric system is also day by day increased, in the face of thus in order to ensure the healthy and stable operation of circuit, improve safety and the reliability of operation of power networks, the risk assessment of overhead transmission line operation is also just arisen at the historic moment.At present, about the risk assessment of Operation of Electric Systems has become the focus of domestic and international research, along with the concept of Modern Risk Leading assessment is introduced in the system of Power System Security Assessment, risk assessment to overhead transmission line operation also becomes a large focal spot, how to use rationally effective means to assess overhead transmission line operation risk, also become a problem in the urgent need to considering.
In the face of the everincreasing complicacy of transmission line of electricity, uncertainty, failure accident be difficult to expect, often bring heavier and complicated maintenance decision, study overhead transmission line operation risk assessment method, accurately hold the risk status of circuit, for the aid decision making of transmission line of electricity, reasonably optimizing maintenance resource distribution, guarantees circuit stable and high effective operation, has very important directive function.The risk assessment of overhead transmission line operation is exactly to set up risk evaluation system according to the feature of overhead transmission line operation, multiangle, multilevel analytical calculation transmission line of electricity operation integrated risk weights, for followup maintenance and aid decision making provide support, thereby its assess effectiveness and accuracy safeguard that to circuit Decision Making Effect is larger.
At present, can be divided into Deterministic Methods and the large class of uncertain method two for transmission line of electricity security of operation methods of risk assessment.Deterministic Methods is fullfledged, is widely used, and margin of safety is large, and reliability is high, but it has ignored complicacy and the randomness of transmission system operation, and risk is lacked to quantitative test, can cause margin of safety excessive, cannot conscientiously ensure the security of circuit operation.Uncertain method considers that transmission system moves the randomness of each risk accidents and the probability of generation thereof, by all accidents being carried out to the comprehensive assessment realizing total system security of analyzing, but probabilistic analysis method has only been considered randomness and the uncertainty of line fault, do not consider the consequence influence degree that line fault causes, therefore do not consider the safety case of circuit yet.
In the face of nowadays increasingly sophisticated transmission system, traditional system stability analysis and safety evaluation method have showed the deficiency of existence.The present invention is based on the security risk assessment of Modern Risk Leading theory, overcome the deficiency of abovementioned appraisal procedure, a kind of overhead transmission line operation risk informatization evaluation method that Multiple Combination is optimized is disclosed, fully take into account internal factor and the impact of external factor on line security operation of circuit, Multiple Combination, successively reasoning and calculation transmission line of electricity operation integrated risk weights, thereby have more science and practicality, not only improve accuracy and the transmission line of electricity reliability of operation of transmission line of electricity risk assessment, be also conducive to analysis, the management and decision of risk.
The present invention, under National 863 planning item fund (2012AA050209) is subsidized, has proposed " the overhead transmission line operation risk informatization evaluation method that Multiple Combination is optimized ".
Summary of the invention
For above deficiency, the object of this invention is to provide the overhead transmission line operation risk informatization evaluation method that Multiple Combination is optimized, on the basis of tradition stratum fractional analysis, information entropy and analytical hierarchy process are merged, consider risk probability, consequence and risk weight that risk produces, application mutual information quantizes risk sequence severity, recycling levelentropy combined method replaces tradition stratum fractional analysis and calculates weights, and optimize weights by least square method, Multiple Combination, successively reasoning and calculation transmission line of electricity operation integrated risk weights, form a kind of assessment models of autonomous optimization.The present invention overcomes pure subjective analysis thought greatly, accuracy and the transmission line of electricity reliability of operation of transmission line of electricity risk assessment are improved, provide powerful support for for finding that early the risk of loss of the potential risk of circuit operation, the possible risk that reduces circuit operation, the operation of minimizing circuit provides, be conducive to analysis, the management and decision of risk.
For realizing above object, the technical scheme that the present invention has taked is:
The overhead transmission line operation risk informatization evaluation method that Multiple Combination is optimized, it comprises the following steps:
Step 1, risk identification, find out the source of trouble by data acquisition and generate risk accidents collection, and risk accidents collection described in statistical study, determines that transmission line of electricity moves the uncertain factor that may exist, and sets up risk factors collection; And according to uncertain risk factors and the operation characteristic thereof of transmission line of electricity operation, set up Risk Assessment Index System;
Step 2, valueatrisk are determined, build transmission line of electricity operation risk assessment model, utilize multilayer, multiple methods of risk assessment to estimate the valueatrisk of each index of transmission line of electricity, further the integrated risk value of computing electric power line;
Step 3, risk are judged, described integrated risk value is analyzed, and determine risk class, the result of output risk assessment.
The method that generates risk accidents collection described in described step 1 is:
By operation patrol and examine, online monitoring, preventive trial and account obtain the related data of overhead transmission line operation, produces typical risk accidents collection by Enumeration Method, described risk accidents collection comprises tripping operation stoppage in transit risk accidents and system risk accident; Analyze these risk accidents, determine the uncertain factor that causes risk accidents to occur, production risk set of factors, as the index of risk assessment.
Described step 2 comprises:
Step 2.1, the valuation of risk indicator probability;
The quantification of step 2.2, risk consequence;
Step 2.3, valueatrisk are calculated.
Described risk indicator probability is the size of the possibility of circuit risk factors appearance, and according to the property calculation risk indicator probability of risk accidents collection and risk factors collection, its computing method specifically comprise:
(1) according to the historical failure statistics of circuit operation, calculate the average probability of occurrence of each risk factors, as risk probability, be specially:
Wherein, m _{i}for risk factors x in a period of time _{i}cause the number of times of risk accidents, the total degree that N is risk accidents,
(2) adopt Enumeration Method to generate risk accidents collection, the probability that arbitrary risk indicator i occurs is:
Wherein, M is fault element number, and L is normal operation element number, p _{i}for risk probability, μ _{k}for the dependability parameter of element.
The dependability parameter of described element is to obtain the representative value of emergency shutdown coefficient by inquiry related data, or obtains according to the statistical conditions of element idle time in recent years; The method that is obtained the dependability parameter of element by the statistical conditions of the described idle time of element is in recent years: wherein, MTTR be in statistical time range total idle time of element; PRD is the length of statistical time range.
Described step 2.2 risk consequence is that risk factors are while occurring, degree and scope that the impact that risk accidents is occurred or harm may involve, cause the generation of risk accidents can be considered to the minimizing process of risk entropy by risk factors effect, by the information entropy of accident that the statistical study of risk factors is reduced risks, risk information entropy is less think its impact or harm larger, be that mutual information represents measuring of risk consequence with cross entropy.Specifically comprise:
Step 2.2.1, according to the conditional probability between sample training maximumlikelihood method calculation risk factor and risk accidents, described conditional probability is at risk factors x _{i}the probability that lower risk accidents S occurs;
Step 2.2.2, suppose H (x _{i}) represent certain risk factors x _{i}information entropy, H (Sx _{i}) represent certain risk factors x _{i}the conditional entropy of risk accidents S under condition, I (x _{i}, S) and be x _{i}with the mutual information of S, represent the consequence of risk generation with mutual information, and mutual information is quantized, be shown below:
I(x _{i}，S)＝H(S)H(Sx _{i})
Wherein: H (S) represents the information entropy of risk S, E (y) represents the expectation value of parameter y, and from shannon entropy, the information entropy of risk S is:
H(S)＝E(lnp(S))
H (Sx _{i}) expression risk factors x _{i}under condition, the conditional information entropy of risk S is:
H(Sx _{i})＝E(lnp(Sx _{i}))
Thereby determine mutual information I (x _{i}, S) numerical value.
Described step 2.3 risk value adopts levelentropy combined method to calculate, and risk weight is optimized by least square method, specifically comprises the following steps:
Step 2.3.1, determine experience weights; Weights by analytical hierarchy process for calculation risk index, according to risk accidents collection and risk indicator system, set up risk assessment hierarchical structure, size risk indicator being compared between any two with nine grades of scaling laws is carried out scale, set up risk indicator Judgement Matrix, solve maximum characteristic root characteristic of correspondence vector as experience weights, and check consistency;
Step 2.3.2, determine support entropy power; Information entropy is applied to and determines that risk indicator weights are to weigh according to the extremum property of entropy the degree of impact that a certain risk factors produce risk, the degree of support quantification of the possible value that each risk indicator is occurred risk accidents, sets up index and evaluates matrix A=(a _{ij}) _{n × m}; The degree of support of the possible value that risk accidents is occurred quantizes as shown in the table:
Solve described index and evaluate matrix, utilize the extremum property of entropy to carry out standardization, obtain characterizing the entropy of risk indicator importance degree, these weights are defined as to support entropy power, be specially:
Wherein:
W=(w _{1}... w _{m}) ^{t}, 0≤w _{j}≤ 1, w is the support entropy power set of certain risk indicator collection, and m is risk indicator number;
The optimization of step 2.3.3, combination weights; Experience weights and support entropy weights are merged, introduce least square method and optimize the definite comprehensive weights of risk indicator of levelentropy combined method, be specially:
Wherein, F (Ψ) is the Lagrangian function of the comprehensive weights Ψ of risk indicator, for the comprehensive weights of every risk indicator, U _{j}for analytical hierarchy process obtains experience weights, V _{j}for support entropy power, w _{j}the relative Link Importance of the each factor obtaining for analytical hierarchy process, s.t. is constraint condition;
By introducing Lagrangian coefficient lambda, the problems referred to above are reduced to unconstrained optimization problem, solve Lagrangian function and obtain Ψ.
Described step 3 comprises:
The calculating of step 3.1, integrated risk value; Consider risk probability, risk consequence and the comprehensive weights of risk indicator, hierarchically structured successively, the multiple calculating integrated risk of risk indicator value, is specially:
Wherein: P _{i}for risk probability; I (x _{i}, S _{j}) be risk consequence; Ψ _{i}for the comprehensive weights of risk indicator;
The division of step 3.2, risk class; Risk is divided into 5 grades, i.e. " very high, high, medium and low, very low ", according to transmission line of electricity operating experience and actual conditions, sets risk class and divides foundation, determines that risk class judgement is interval;
Step 3.3, risk class are judged; Each Risk Calculation result is carried out to hierarchical classification, judge interval division according to abovementioned different brackets risk, the valueatrisk calculating and risk class are judged to interval matches, determine final risk class.
The present invention, from the influence factor of the various risk accidents of transmission line of electricity operation, in conjunction with the actual conditions of transmission line of electricity operation, has carried out analysis and assessment to overhead transmission line operation risk.Than prior art, beneficial effect of the present invention comprises:
1, all sidedly, at many levels overhead transmission line operation risk is assessed, not only consider randomness and the uncertainty of fault, also considered the consequence influence degree that fault causes, compared the more perfect adequacy that has more of traditional assessment technology;
2, the present invention is the risk assessment technology take probability as core, can take into full account the uncertain factor of circuit operation, to carrying out quantitative test to the uncertainty of various risk factors;
3, the present invention uses the Weighting of Combinatorial Optimization, has greatly overcome dependence and subjectivity to expertise, considers the support of risk indicator itself simultaneously, after subjective and objective combination, optimizes, and obtains more scientific comprehensive weights;
4, the present invention is applied to the theory of information entropy in risk assessment, not only carrys out the severity of measure of risk consequence with mutual information, and solves objective weightvalues with the rule of entropy;
5, according to overhead transmission line operation risk assessment result, operations staff can take corresponding measure to patrol and examine or maintenance etc. targetedly, the transmission line malfunction that prevention may cause, all has important engineering using value for efficient, reliable, the safe operation etc. that ensures circuit operation.
Accompanying drawing explanation
Fig. 1 is the estimation flow schematic block diagram of the overhead transmission line operation risk informatization evaluation method of Multiple Combination optimization of the present invention;
Fig. 2 shows the hierarchical structure of overhead transmission line operation risk assessment.
Embodiment
Below in conjunction with the drawings and specific embodiments, content of the present invention is described in further details.
Embodiment
The overhead transmission line operation risk informatization evaluation method that a kind of Multiple Combination of the present embodiment is optimized, shows its estimation flow schematic block diagram referring to Fig. 1, specifically comprises following 3 stages:
The risk identification stage: two parts of setting up that specifically comprise data acquisition and preservice, Risk Assessment Index System; This stage is also the input stage of risk assessment;
Risk weight is determined the stage: specifically comprise the quantification of risk probability valuation, risk consequence and definite three parts of valueatrisk; Finally carry out calculation risk value according to abovementioned valueatrisk formula;
Risk decision stage: specifically comprise that risk class is divided, risk is sorted out, the output of risk result.
Wherein:
One, the risk identification stage
1. data acquisition and preservice, by operation patrol and examine, online monitoring, preventive trial and account etc. obtain the related data of overhead transmission line operation, adopt Enumeration Method to collect fault data, find out the source of trouble and generate risk accidents collection;
2. set up Risk Assessment Index System;
Statistical study risk accidents collection, determines that transmission line of electricity moves the uncertain factor that may exist, and sets up risk factors collection; According to uncertain risk factors and the operation characteristic thereof of transmission line of electricity operation, set up Risk Assessment Index System.Shown in being listed in the table below:
Two, risk weight is determined the stage
1. risk indicator probability valuation
According to the historical failure statistics of circuit operation, calculate the average probability of occurrence (failure rate) of each risk factors, as the risk probability of risk indicator, be specially:
Wherein, m _{i}for risk factors x in a period of time _{i}cause the number of times of risk accidents, N is the total degree that risk accidents occurs.
The following sheet format of risk indicator probability:
2. the quantification of risk consequence
1) first will be according to the conditional probability between sample training calculated risk factor and risk accidents, at risk factors x _{i}the probability that lower risk S occurs; The method calculation risk conditional probability that adopts maximum likelihood to estimate;
2) suppose H (x _{i}) represent certain risk factors x _{i}information entropy, H (Sx _{i}) represent certain risk factors x _{i}the conditional entropy of risk accidents S under condition, I (x _{i}, S) and be x _{i}with the mutual information of S, represent the consequence of risk generation with mutual information, and mutual information is quantized, be shown below:
I(x _{i}，S)＝H(S)H(Sx _{i})
Wherein:
H (S)the information entropy of risk S, E (y) represents the expectation value of parameter y, from Shannon information entropy, the entropy of risk S is:
H(S)＝E(lnp(S))
H (Sx _{i})risk factors x _{i}under condition, the conditional information entropy of risk S is:
H(Sx _{i})＝E(lnp(Sx _{i}))
Thereby can determine mutual information I (x _{i}, S) numerical value.
3. risk weight
1) determine experience weights; Weights by analytical hierarchy process for calculation risk index, according to risk accidents collection and risk indicator system, set up the hierarchical structure of risk assessment index, and Fig. 2 shows the hierarchical structure of overhead transmission line operation risk assessment index; Size risk indicator being compared between any two by Method of nine marks is carried out scale, sets up risk indicator Judgement Matrix, and solve maximum characteristic root characteristic of correspondence vector, as lower floor, the importance on upper strata is to experience weights, and check consistency;
2) determine support entropy power; Information entropy is applied to and determines that risk indicator weights are to weigh according to the extremum property of entropy the degree of impact that a certain risk factors produce risk.The degree of support quantification of the possible value that each risk indicator is occurred risk accidents, sets up index and evaluates matrix A=(a _{ij}) _{n × m}.Wherein, n represents the possible value mark number of risk indicator degree of support, and m represents risk indicator number.The degree of support of the possible value that risk accidents is occurred quantizes as shown in the table:
The possible value mark of various risks index degree of support
Solve index and evaluate matrix, utilize the extremum property of entropy to carry out standardization, obtain characterizing the entropy of risk indicator importance degree, these weights are defined as to support entropy power; Due to the influence of risk factors, the uncertainty of the relative Link Importance of risk factors j to risk indicator i probable value is measured by following formula:
Wherein:
According to the extremum property of entropy, above formula standardization, obtain characterizing the entropy of risk factors importance degree:
Wherein: 0≤e (a _{j})≤1.
According to the definition of entropy and character, e (a _{j}) value less, the relative Link Importance of risk factors j is just larger.For the ease of comprehensive evaluation, by e (a _{j}) determine the evaluation weights θ of risk factors j _{j}for:
Wherein: Θ=(θ _{1}... θ _{...}) ^{t}, 0≤θ _{j}≤ 1, Θ is the support entropy power set of certain risk indicator collection, and m is risk indicator number;
3) comprehensive weight of supposing every risk factors is use the process of least square method optimization weight as follows:
Wherein, w _{j}the relative Link Importance of the each factor obtaining for analytical hierarchy process.By introducing Lagrangian coefficient lambda, the problems referred to above are reduced to unconstrained optimization problem, obtain Lagrangian function expression formula and be:
By above formula pair ask local derviation with λ and make equation the right equal 0:
In order to solve conveniently, be translated into matrix form:
Wherein:
e _{m}＝(1?1?…?1) ^{T}
Dematrix equation:
4. integrated risk value is calculated
Consider risk probability, risk consequence and valueatrisk, hierarchically structured successively, the multiple calculating integrated risk of risk indicator value, is specially:
Wherein: P _{i}risk probability; C _{i}risk consequence; W _{i}valueatrisk;
Therefore, in sum, being calculated as of a certain subrisk:
Wherein: P _{i}for risk probability; I (x _{i}, S _{j}) be risk consequence; Ψ _{i}for the comprehensive weights of risk indicator.
Three, risk decision stage
1. risk class is divided
For overhead transmission line operation risk is carried out to quantitative test, risk is divided into 5 grades, i.e. " very high, high, medium and low, very low ".According to transmission line of electricity operating experience and actual conditions, set risk class and divide foundation, table specific as follows:
The division of transmission line of electricity operation risk grade
Wherein, the division principle in the judgement interval of risk class is: analyze the result that valueatrisk is calculated, according to the concrete ruuning situation of different circuits and expertise, divide in conjunction with FCM algorithm simultaneously;
2. risk is sorted out and result judgement
According to the division in the judgement interval of abovementioned different brackets risk, by judging that with risk class interval matches after the valueatrisk normalized calculating, determine final risk class.
Abovelisted detailed description is for the illustrating of possible embodiments of the present invention, and this embodiment is not in order to limit the scope of the claims of the present invention, and the equivalence that all the present invention of disengaging do is implemented or changed, and all should be contained in the scope of the claims of this case.
Claims (8)
Priority Applications (1)
Application Number  Priority Date  Filing Date  Title 

CN201410027736.8A CN103793854B (en)  20140121  20140121  The overhead transmission line operation risk informatization evaluation method that Multiple Combination is optimized 
Applications Claiming Priority (1)
Application Number  Priority Date  Filing Date  Title 

CN201410027736.8A CN103793854B (en)  20140121  20140121  The overhead transmission line operation risk informatization evaluation method that Multiple Combination is optimized 
Publications (2)
Publication Number  Publication Date 

CN103793854A true CN103793854A (en)  20140514 
CN103793854B CN103793854B (en)  20150930 
Family
ID=50669485
Family Applications (1)
Application Number  Title  Priority Date  Filing Date 

CN201410027736.8A CN103793854B (en)  20140121  20140121  The overhead transmission line operation risk informatization evaluation method that Multiple Combination is optimized 
Country Status (1)
Country  Link 

CN (1)  CN103793854B (en) 
Cited By (13)
Publication number  Priority date  Publication date  Assignee  Title 

CN104332996A (en) *  20141118  20150204  国家电网公司  Method for estimating power system reliability 
CN104636624A (en) *  20150216  20150520  中国电建集团成都勘测设计研究院有限公司  Risk decision method for water retaining standard of nonoverflow earthrock cofferdam 
CN104992373A (en) *  20150401  20151021  贵州电网公司输电运行检修分公司  Power transmission line natural disaster risk early warning method 
CN105930964A (en) *  20160415  20160907  中国南方电网有限责任公司超高压输电公司检修试验中心  Power transmission line icing risk assessment method based on impact from spacetime factors 
CN106204319A (en) *  20150430  20161207  中国石油天然气股份有限公司  The methods of risk assessment of gas storage ground installation and device 
CN106355343A (en) *  20160906  20170125  深圳供电局有限公司  Comprehensive risk evaluating method of power grid 
CN106354757A (en) *  20160817  20170125  国网四川省电力公司德阳供电公司  GISbased power transmission line risk graphics database management system 
CN106650122A (en) *  20161227  20170510  宝鸡文理学院  Equipment variable working condition operation risk evaluation method 
CN107292497A (en) *  20170605  20171024  国网陕西省电力公司电力科学研究院  The flashover of power transmission circuit caused by windage yaw methods of risk assessment combined based on step analysis entropy weight 
CN107403268A (en) *  20170724  20171128  国网江苏省电力公司电力科学研究院  Transmission line of electricity risk evaluating system 
CN107992962A (en) *  20171123  20180504  海南电网有限责任公司电力科学研究院  A kind of Lightning stroke Protection Measures for OverHead Lines optimum choice method based on entropy assessment 
CN108537367A (en) *  20180320  20180914  广东电网有限责任公司惠州供电局  Power transmission line comprehensive methods of risk assessment under a kind of more meteorological disasters 
CN109583844A (en) *  20181204  20190405  北京诺士诚国际工程项目管理有限公司  A kind of tours of inspection method, apparatus and electronic equipment 
Citations (7)
Publication number  Priority date  Publication date  Assignee  Title 

CN1838161A (en) *  20050323  20060927  大亚湾核电运营管理有限责任公司  Method and apparatus for nuclear power station equipment risk evaluation by computer 
CN101282041A (en) *  20080509  20081008  天津大学  Method for estimating and optimizing dynamic safety risk of power transmission system based on practical dynamic safety field 
CN101800426A (en) *  20100331  20100811  河南电力试验研究院  Safety level evaluation method of power grid 
CN102800029A (en) *  20120620  20121128  南方电网科学研究院有限责任公司  Sametower multiloop transmission circuit risk probability assessment method 
CN103049646A (en) *  20121128  20130417  广东电网公司电力科学研究院  Comprehensive risk assessment method for power grid 500kV terminal substation construction 
CN103337043A (en) *  20130627  20131002  广东电网公司电力调度控制中心  Prewarning method and system for running state of electric power communication equipment 
CN103366096A (en) *  20130722  20131023  广东电网公司电力调度控制中心  Power communications equipment risk assessment method 

2014
 20140121 CN CN201410027736.8A patent/CN103793854B/en active IP Right Grant
Patent Citations (7)
Publication number  Priority date  Publication date  Assignee  Title 

CN1838161A (en) *  20050323  20060927  大亚湾核电运营管理有限责任公司  Method and apparatus for nuclear power station equipment risk evaluation by computer 
CN101282041A (en) *  20080509  20081008  天津大学  Method for estimating and optimizing dynamic safety risk of power transmission system based on practical dynamic safety field 
CN101800426A (en) *  20100331  20100811  河南电力试验研究院  Safety level evaluation method of power grid 
CN102800029A (en) *  20120620  20121128  南方电网科学研究院有限责任公司  Sametower multiloop transmission circuit risk probability assessment method 
CN103049646A (en) *  20121128  20130417  广东电网公司电力科学研究院  Comprehensive risk assessment method for power grid 500kV terminal substation construction 
CN103337043A (en) *  20130627  20131002  广东电网公司电力调度控制中心  Prewarning method and system for running state of electric power communication equipment 
CN103366096A (en) *  20130722  20131023  广东电网公司电力调度控制中心  Power communications equipment risk assessment method 
Cited By (15)
Publication number  Priority date  Publication date  Assignee  Title 

CN104332996A (en) *  20141118  20150204  国家电网公司  Method for estimating power system reliability 
CN104636624A (en) *  20150216  20150520  中国电建集团成都勘测设计研究院有限公司  Risk decision method for water retaining standard of nonoverflow earthrock cofferdam 
CN104992373A (en) *  20150401  20151021  贵州电网公司输电运行检修分公司  Power transmission line natural disaster risk early warning method 
CN104992373B (en) *  20150401  20161221  贵州电网公司输电运行检修分公司  A kind of transmission line of electricity natural hybridized orbit method for early warning 
CN106204319A (en) *  20150430  20161207  中国石油天然气股份有限公司  The methods of risk assessment of gas storage ground installation and device 
CN105930964A (en) *  20160415  20160907  中国南方电网有限责任公司超高压输电公司检修试验中心  Power transmission line icing risk assessment method based on impact from spacetime factors 
CN106354757A (en) *  20160817  20170125  国网四川省电力公司德阳供电公司  GISbased power transmission line risk graphics database management system 
CN106355343A (en) *  20160906  20170125  深圳供电局有限公司  Comprehensive risk evaluating method of power grid 
CN106650122A (en) *  20161227  20170510  宝鸡文理学院  Equipment variable working condition operation risk evaluation method 
CN106650122B (en) *  20161227  20191108  宝鸡文理学院  A kind of equipment variable parameter operation methods of risk assessment 
CN107292497A (en) *  20170605  20171024  国网陕西省电力公司电力科学研究院  The flashover of power transmission circuit caused by windage yaw methods of risk assessment combined based on step analysis entropy weight 
CN107403268A (en) *  20170724  20171128  国网江苏省电力公司电力科学研究院  Transmission line of electricity risk evaluating system 
CN107992962A (en) *  20171123  20180504  海南电网有限责任公司电力科学研究院  A kind of Lightning stroke Protection Measures for OverHead Lines optimum choice method based on entropy assessment 
CN108537367A (en) *  20180320  20180914  广东电网有限责任公司惠州供电局  Power transmission line comprehensive methods of risk assessment under a kind of more meteorological disasters 
CN109583844A (en) *  20181204  20190405  北京诺士诚国际工程项目管理有限公司  A kind of tours of inspection method, apparatus and electronic equipment 
Also Published As
Publication number  Publication date 

CN103793854B (en)  20150930 
Similar Documents
Publication  Publication Date  Title 

Wang et al.  A twostage datadrivenbased prognostic approach for bearing degradation problem  
Wan et al.  Probabilistic forecasting of wind power generation using extreme learning machine  
Mena et al.  A prediction model based on neural networks for the energy consumption of a bioclimatic building  
Zhang et al.  Towards a fuzzy Bayesian network based approach for safety risk analysis of tunnel‐induced pipeline damage  
Su et al.  Performance improvement method of support vector machine‐based model monitoring dam safety  
Nielsen et al.  On riskbased operation and maintenance of offshore wind turbine components  
CN102208028B (en)  Fault predicting and diagnosing method suitable for dynamic complex system  
CN102496069B (en)  Cable multimode safe operation evaluation method based on fuzzy analytic hierarchy process (FAHP)  
Wan et al.  Optimal prediction intervals of wind power generation  
Dong et al.  Combination of evidential sensor reports with distance function and belief entropy in fault diagnosis  
Chen et al.  Project delivery system selection of construction projects in China  
Esmaeili et al.  Attributebased safety risk assessment. II: Predicting safety outcomes using generalized linear models  
CN102289590B (en)  Method for estimating operating state of SF6 highvoltage circuit breaker and intelligent system  
Ševčíková et al.  Assessing uncertainty in urban simulations using Bayesian melding  
CN102520697B (en)  Onsite information preprocessing method of remote cooperative diagnosis  
US8527223B2 (en)  Methods and systems for energy prognosis  
CN102063651B (en)  Urban power grid risk evaluation system based on online data acquisition  
CN103793853B (en)  Condition of Overhead Transmission Lines Based appraisal procedure based on twoway Bayesian network  
AU2001255994B8 (en)  Method of Business Analysis  
Su et al.  Study on an intelligent inference engine in earlywarning system of dam health  
Xue et al.  Fault detection and operation optimization in district heating substations based on data mining techniques  
Sheu  Dynamic reliefdemand management for emergency logistics operations under largescale disasters  
CN104573881B (en)  A kind of military service equipment residual life adaptive forecasting method based on degraded data modeling  
Bhinge et al.  An intelligent machine monitoring system for energy prediction using a Gaussian Process regression  
Freitas et al.  Using degradation data to assess reliability: a case study on train wheel degradation 
Legal Events
Date  Code  Title  Description 

C06  Publication  
PB01  Publication  
C10  Entry into substantive examination  
SE01  Entry into force of request for substantive examination  
C14  Grant of patent or utility model  
GR01  Patent grant 