CN105761001B - Distribution network equipment state evaluation method fusing multi-source information - Google Patents
Distribution network equipment state evaluation method fusing multi-source information Download PDFInfo
- Publication number
- CN105761001B CN105761001B CN201610091916.1A CN201610091916A CN105761001B CN 105761001 B CN105761001 B CN 105761001B CN 201610091916 A CN201610091916 A CN 201610091916A CN 105761001 B CN105761001 B CN 105761001B
- Authority
- CN
- China
- Prior art keywords
- state evaluation
- information
- equipment
- weight
- regular
- 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.)
- Active
Links
- 238000011156 evaluation Methods 0.000 title claims abstract description 85
- 238000000034 method Methods 0.000 claims abstract description 20
- 230000000737 periodic effect Effects 0.000 claims abstract description 14
- 230000032683 aging Effects 0.000 claims description 14
- 230000007547 defect Effects 0.000 claims description 14
- 238000012937 correction Methods 0.000 claims description 9
- 230000008859 change Effects 0.000 claims description 6
- 238000012544 monitoring process Methods 0.000 claims description 6
- 230000003862 health status Effects 0.000 claims description 4
- 238000007689 inspection Methods 0.000 claims description 4
- 238000001514 detection method Methods 0.000 claims description 3
- 238000012360 testing method Methods 0.000 claims description 3
- 238000012423 maintenance Methods 0.000 abstract description 21
- 230000036541 health Effects 0.000 description 7
- 239000011159 matrix material Substances 0.000 description 7
- 238000011161 development Methods 0.000 description 6
- 230000018109 developmental process Effects 0.000 description 6
- 230000000694 effects Effects 0.000 description 3
- 230000015556 catabolic process Effects 0.000 description 2
- 238000006731 degradation reaction Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 230000007613 environmental effect Effects 0.000 description 2
- 230000008569 process Effects 0.000 description 2
- 230000002159 abnormal effect Effects 0.000 description 1
- 230000015572 biosynthetic process Effects 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 230000006866 deterioration Effects 0.000 description 1
- 230000008030 elimination Effects 0.000 description 1
- 238000003379 elimination reaction Methods 0.000 description 1
- 238000009472 formulation Methods 0.000 description 1
- 230000004927 fusion Effects 0.000 description 1
- 238000009434 installation Methods 0.000 description 1
- 238000009413 insulation Methods 0.000 description 1
- 230000010354 integration Effects 0.000 description 1
- 239000000203 mixture Substances 0.000 description 1
- 238000011158 quantitative evaluation Methods 0.000 description 1
- 230000008439 repair process Effects 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 238000007789 sealing Methods 0.000 description 1
- 238000003786 synthesis reaction Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0637—Strategic management or analysis, e.g. setting a goal or target of an organisation; Planning actions based on goals; Analysis or evaluation of effectiveness of goals
- G06Q10/06375—Prediction of business process outcome or impact based on a proposed change
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
- G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/06—Energy or water supply
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E40/00—Technologies for an efficient electrical power generation, transmission or distribution
- Y02E40/70—Smart grids as climate change mitigation technology in the energy generation sector
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S10/00—Systems supporting electrical power generation, transmission or distribution
- Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
Landscapes
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Engineering & Computer Science (AREA)
- Economics (AREA)
- Strategic Management (AREA)
- Educational Administration (AREA)
- Entrepreneurship & Innovation (AREA)
- General Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- Marketing (AREA)
- Theoretical Computer Science (AREA)
- Development Economics (AREA)
- Tourism & Hospitality (AREA)
- Physics & Mathematics (AREA)
- Quality & Reliability (AREA)
- Game Theory and Decision Science (AREA)
- Operations Research (AREA)
- Health & Medical Sciences (AREA)
- Public Health (AREA)
- Water Supply & Treatment (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention discloses a distribution network equipment state evaluation method fusing multi-source informationA method, comprising: step (1): the current state evaluation result S based on the periodic operation information is knownregularAnd a state evaluation result S based on the real-time operation informationrealtimeAnd a state evaluation result S based on the historical operation informationhistoryObtaining initial subjective weights of the three types of evaluation results by adopting a proportional scaling method in an importance comparison mode, and respectively recording the initial subjective weights as
And
step (2): the initial weight is corrected by adopting a variable weight formula, so that the corrected weight can be obtained:
and (3): calculating the final weight of the three types of information according to the following formula; and (4): according to the formula S ═ Sregularwregular+Srealtimewrealtime+ShistorywhistoryAnd calculating the final score S of the state evaluation of the distribution network equipment fused with the multi-source information. The method calculates and obtains the total score of the state evaluation of the distribution network equipment fused with the multi-source information, so that the state evaluation result is more comprehensive, and the actual operation and maintenance requirements of the power grid can be met.
Description
Technical Field
The invention belongs to the technical field of electric power, and particularly relates to a distribution network equipment state evaluation method fusing multi-source information.
Background
At present, the power distribution network in China enters a new development stage: the quantity of power distribution equipment is increased day by day, the quality is improved continuously, and the failure rate of the equipment tends to be reduced; the association relation among the devices is increasingly complex, the society has higher and higher requirements on power supply reliability, and the arrangement of power failure maintenance is increasingly difficult; the requirement of a power enterprise on the cost performance of maintenance is improved, so that the development space of maintenance resources is limited, and therefore, the regular maintenance mode is more and more difficult to adapt to the development of a power grid.
The condition maintenance is a maintenance mode which judges the degradation condition of the equipment by monitoring the change trend of the condition parameters of the equipment and carries out maintenance after the degradation condition of the equipment is obvious. Obviously, the condition maintenance is compared in the periodic maintenance, can prolong the economic life of equipment, can guarantee the electric wire netting safe and reliable operation again, makes validity, the economic nature of maintenance very improve, therefore the maintenance mode of distribution network must follow the periodic maintenance and gradually change to the condition maintenance.
The condition inspection is a repair performed after the equipment has been significantly deteriorated, and the state deterioration is reflected by a change in the condition parameters of the monitored equipment. The state parameters of the equipment are various and composed of different types of indexes, and can be acquired only by acquiring, analyzing and judging through certain economic and technical means, so that state evaluation technology is needed for state maintenance.
The state evaluation is to select a certain amount of operation information to obtain a series of state quantities reflecting the states of the equipment, and to perform quantitative evaluation and qualitative classification on the states of the equipment, so as to provide a basis for risk evaluation and maintenance strategy formulation.
At present, electric power enterprises accumulate massive equipment data, including real-time operation information, periodic live-line detection, inspection and power failure test information, environmental factors such as operation years, family defects, working environment and load conditions, historical maintenance (such as defect elimination and maintenance) information and defect fault information. The data without additional acquisition cost is fully utilized, valuable information and knowledge are mined, and the equipment can be guided to carry out comprehensive and objective state evaluation.
Disclosure of Invention
The invention provides a distribution network equipment state evaluation method fusing multi-source information state evaluation results aiming at the problems of insufficient timeliness and comprehensiveness of the conventional distribution network equipment periodic state evaluation technology.
In order to solve the technical problems, the invention adopts the following technical scheme: a distribution network equipment state evaluation method fusing multi-source information comprises the following steps:
step (1): the current state evaluation result S based on the periodic operation information is knownregularAnd a state evaluation result S based on the real-time operation informationrealtimeAnd a state evaluation result S based on the historical operation informationhistoryObtaining initial subjective weights of the three types of evaluation results by adopting a proportional scaling method in an importance comparison mode, and respectively recording the initial subjective weights as
And
step (2): the initial weight is corrected by adopting a variable weight formula, so that the corrected weight can be obtained:
and (3): the final weights for the three types of information are calculated according to the following formula:
wherein, wregular、wrealtime、whistoryFinal weight of the three types of evaluation results; b is the aging index of the apparatus, betaiObtaining a correction coefficient by considering equipment environment factors or equipment self factors, wherein i is 1-4, and t is the current service life of the equipment; and (4): according to the formula S ═ Sregularwregular+Srealtimewrealtime+ShistorywhistoryAnd calculating the final score S of the state evaluation of the distribution network equipment fused with the multi-source information.
Preferably, step (1) uses a 11-step base ratio scale as shown in the following table:
the 3 decision indices based on the evaluation of regular, real-time, historical operating information are c ═ (c ═ c)1,c2,c3) The following decision matrix P is constructed from the 11-level basic scale above:
wherein: p is a radical ofiIndicating index ciAnd ci+1And (3) comparing the importance degrees of the two, namely i is 1-3.
Preferably, the weight-varying formula in step (2) is
Wherein alpha is an equalization factor, 0< a ≦ 1, and is used for adjusting the variable weight.
Furthermore, when the balance problem of each index is not considered much, the alpha is more than 1/2; when serious defects of certain indexes cannot be tolerated, taking alpha < 1/2; when α is 1, it is equivalent to a constant weight mode.
Preferably, the aging index B in step (3) is estimated by the following formula:
Further, in the case where the data amount is sufficient, SN、S0And TNThe three parameters are all valued by calculating the average value of the equipment parameters in a certain area, and under the condition of insufficient data quantity, the values of the three parameters are obtained through empirical estimation or curve fitting.
Preferably, in step (3), the specific correction factor considering the environment of the device is as follows:
preferably, in the step (3), the specific correction coefficient considering the number of the defect failures of the device itself is as follows:
according to the technical scheme, the existing state evaluation result based on the periodic information is fused with the evaluation result based on the real-time running information and the historical running information, and the state evaluation result obtained by the method can make up for the problem that the existing state evaluation result is insufficient in timeliness and comprehensiveness. The state evaluation result obtained by the method comprehensively reflects the state evaluation result based on the regular operation information, the real-time operation information and the historical operation information, and considers the calculation and correction of the evaluator opinions, the short board effect, the equipment aging coefficient and other factors to the weight distribution, and finally calculates the distribution network equipment state evaluation total score integrating the multi-source information, so that the state evaluation result is more comprehensive, and the actual operation and maintenance requirements of a power grid can be met.
Detailed Description
The technical solution of the present invention is further specifically described below by means of specific examples and attached tables.
According to the difference of information sources, acquisition modes and acquisition frequencies, the operation information of the existing distribution network equipment can be divided into three types of regular operation information, real-time operation information and historical operation information. The multi-source information of the invention refers to the integration of the three types of information.
The regularly acquired operation information mainly comprises inspection information, live detection, power failure test and other information. Because the reliability of the power equipment is relatively high, the state evaluation based on the periodic information is generally performed once a year and is used for monitoring the development trend of the operation performance of the distribution network equipment. The state evaluation method based on the periodic information is mature, and the current state maintenance guide rules of each power grid enterprise can be referred to specifically. The state evaluation method used at present is an evaluation method based on periodic operation information, and has the defects of insufficient timeliness and comprehensiveness.
The real-time operation information mainly comes from a real-time online monitoring system of each device, and data is generally acquired in units of minutes, hours and days. The method is used for reflecting the instant operation parameter change of the equipment so as to pay attention to the abnormal operation state of the equipment. With the development of an online monitoring system, the state characteristic quantity of a large number of distribution network devices can be measured online. Therefore, when the equipment is evaluated, the equipment does not need to be stopped, and the power supply reliability can be greatly improved. The state evaluation method based on real-time operation information has already applied for invention patent.
The historical operation information is mainly derived from historical defects or fault records of the equipment, is used for checking familial defects of the equipment, and is convenient for finding out fault-prone parts or equipment for focusing. In an electric power system, a large amount of unstructured data is distributed in the whole life cycle links of design, installation, operation, overhaul, retirement and the like, and mainly comprises texts, audios, images and the like. The state evaluation result based on the historical record information has no obvious time law, and the state evaluation method is also patented.
The state evaluation results based on the different types of operation information reflect the operation state of the apparatus from different sides, at different time frequencies and depths. The invention carries out fusion research on the state evaluation results of the distribution network equipment formed based on the various information, provides the state evaluation method of the distribution network equipment based on the multi-source information, and realizes the aims of comprehensively utilizing the data of the distribution equipment and scientifically reflecting the health state of the equipment.
The invention provides a distribution network equipment state evaluation method fusing multi-source information, which comprises the following steps:
step (1): the current state evaluation result S based on the periodic operation information is knownregularAnd a state evaluation result S based on the real-time operation informationrealtime(obtaining method another patent application), State evaluation result S based on historical operating informationhistory(obtaining method another patent application). Obtaining initial subjective weights of the three types of evaluation results by a proportional scaling method in an importance comparison mode, and respectively recording the initial subjective weights as
And
the method comprises the following steps:
due to the fact that overhaul resources of different power grid enterprises are different from monitoring equipment, and state information which can be obtained by power equipment in the actual engineering situation is different, the attention degrees of different equipment to the state evaluation result based on the regular operation information, the state evaluation result based on the real-time operation information and the state evaluation result based on the historical operation information are different. Therefore, an evaluator is required to assign subjective initial weights to the three types of evaluation results by an importance comparison mode by adopting an analytic hierarchy process.
The key of the analytic hierarchy process is to construct a judgment matrix, and the judgment matrix constructed according to the most common 1-9 scales cannot pass consistency check. Therefore, a judgment matrix of a scale-scale construction is adopted here because such a judgment matrix naturally satisfies consistency. Typically, an 11-step base scale is used as shown in the following table:
in the invention, only 3 decision indexes are evaluated based on regular, real-time and historical operation information respectively and are marked as c ═ c (c)1,c2,c3) From the 11-level scale above, the following decision matrix P can be constructed:
wherein: p is a radical ofiIndicating index ciAnd ci+1And the scale value is used for comparing the importance degrees of the two. If p isi1 denotes an index ciAnd ci+1Equally important; if p isi1.2, denotes index ciPhase comparison index ci+1Is of slight importance; if p isi1.5 denotes index ciAnd index ci+1The importance degree of (A) is between more important and important in comparison; and so on. When the index ciImportance ratio index ci+1Low, then expressed in reciprocal, e.g. pi1/1.8 denotes index ci+1Ratio index ciThe importance is much greater. Here, i is 1 to 3.
The initial subjective weight of the state evaluation score based on the three types of operation information can be obtained by calculating by using a judgment matrix constructed by a proportional scaling method and is recorded as
Andlet p be1And p2Are respectively SregularAnd Srealtime、SrealtimeAnd ShistoryScale of importance degree in between, then
And
the expression is as follows:
step (2): considering the "short plate effect", when the score of a certain evaluation is low, the weight of the evaluation is increased correspondingly, and importance is attached to the evaluation result and the state of the device based on the information. The method comprises the following steps:
the state evaluation of the power distribution equipment needs to follow the short board principle, and the serious defects of any index need to be focused. In the normal weight evaluation mode, the parameters with serious deviation may be evaluated normally due to their small weight, and may not reflect the real state of the power equipment. Therefore, in the present invention, the weight-varying synthesis theory is adopted.
The specific weight-changing formula is as follows:
wherein x isiThe value of the ith evaluation index is shown, and m is the number of the evaluation indexes. In the present invention, m is 3, x1、x2、x3Are respectively Sregular、Srealtime、Shistory。wiIs a variable weight of the i-th factor,is a constant weight of the ith factor.
The variable weight can achieve the effect of changing the weight according to the value of the evaluation index, and specifically, the lower the score of the health state is, the higher the corresponding weight will be.
In order to improve the universality of the model, an equalization function is introduced into the variable weight, and the formula is as follows:
wherein, α is an equalization factor for adjusting the variable weight. In general, when the balance problem of each index is not considered much, the alpha is more than 1/2; when serious defects of certain indexes cannot be tolerated, taking alpha < 1/2; when α is 1, it is equivalent to a constant weight mode.
The initial weight obtained in the step 1 is corrected by adopting the variable weight formula, and the corrected weight is obtained as follows:
and (3): considering that the state evaluation result based on the periodic operation information has a problem of timeliness, the weight thereof is corrected by using the equipment aging coefficient. The method comprises the following steps:
since the state evaluation based on the periodic operation information is usually performed once a year, the health state of the equipment can be accurately and effectively reflected within a period of time immediately after the evaluation, but the equipment can age to a certain extent with the passage of time, so that the timeliness of the part of the evaluation is reduced. In this case, the weight of the partial evaluation needs to be appropriately reduced, and the weight of the real-time evaluation needs to be appropriately increased to reflect the health status of the equipment more accurately.
In order to quantify the degree of weight adjustment, an aging index parameter is introduced to measure the aging degree of equipment, and further the change degree of the state evaluation based on the regular operation information and the evaluation weight based on the real-time operation information is judged. It should be noted that, since the information recorded in the history fault or defect text of the equipment has no special time regularity and timeliness characteristics, the weight adjustment performed in this step does not involve the weight of the part evaluated based on the history operation information state, i.e., the part of the weight follows the result in step 2.
The estimation formula of the equipment aging index is as follows:
in the formula, SNAnd S0Respectively representing health status scores, T, during decommissioning and commissioning of the equipmentNRepresenting the actual service life of the equipment when out of service. Under the condition of sufficient data quantity, the three parameters can be evaluated by calculating the average value of the equipment parameters in a certain area. In the case of insufficient data volume, the values of the three parameters can be obtained by empirical estimation or curve fitting.
Besides the statistical or fitting device aging index, some environmental factors or device factors may also affect the aging degree of the device, and these factors need to be refined to further correct the above weights. The invention introduces a correction coefficient betaiI is 1 to 4, and the correction is performed in each of the following two cases.
(1) The equipment environment is as follows: the equipment is located indoors or outdoors, which affects the operating temperature, humidity and other conditions of the equipment, and further affects the aging of components such as equipment insulation and sealing elements.
(2) The defect failure frequency is as follows: the more past defects and failure times of the equipment are, the faster the equipment aging speed is correspondingly, and the more easily the health state of the equipment is changed.
After considering the above correction factors, the final weights of the evaluations are:
wherein, wregular、wrealtime、whistoryFinal weight of the three types of evaluation results; b is the aging index of the apparatus, betaiTo correct the factor, t is the current working age of the appliance.
And (4): according to the formula S ═ Sregularwregular+Srealtimewrealtime+ShistorywhistoryAnd calculating the total evaluation score S of the state of the distribution network equipment fused with the multi-source information.
The method and the device make up the problem of insufficient timeliness of the evaluation of the current state, enrich the evaluation content by utilizing the real-time information and the historical information, and enable the evaluation result to reflect the health state of the distribution network equipment more comprehensively. The evaluation result obtained by the invention integrates the state evaluation results based on the regular state maintenance information (equivalent to the results of annual physical examination), the real-time operation information (equivalent to the results of real-time observation) and the historical operation information (equivalent to the past history), has comprehensiveness and timeliness in reflecting the health condition of the equipment, and can scientifically reflect the health state and the development trend of the equipment.
Claims (3)
1. A distribution network equipment state evaluation method fusing multi-source information is characterized by comprising the following steps:
step (1): the current state evaluation result S based on the periodic operation information is knownregularAnd a state evaluation result S based on the real-time operation informationrealtimeAnd a state evaluation result S based on the historical operation informationhistoryObtaining initial subjective weights of the three types of evaluation results by adopting a proportional scaling method in an importance comparison mode, and respectively recording the initial subjective weights as
And
the regular operation information comprises routing inspection information, live detection information and power failure test information, the real-time operation information is from a real-time online monitoring system of each device and reflects the real-time operation parameter change of the device, and the historical operation information is from the historical defect or fault record of the device;
let p be1And p2Are respectively SregularAnd Srealtime、SrealtimeAnd ShistoryScale of importance degree in between, thenAnd
the expression is as follows:
step (2): the initial weight is corrected by adopting a variable weight formula, so that the corrected weight can be obtained:
the weight-variable formula is
Wherein alpha is an equalization factor, 0< a is less than or equal to 1 and is used for adjusting the variable weight;
and (3): the final weights for the three types of information are calculated according to the following formula:
wherein, wregular、wrealtime、whistoryFinal weight of the three types of evaluation results; b is the aging index of the apparatus, betaiFor correcting the coefficient, the factor is obtained by considering equipment environment factors or equipment self factors, i is 1-4, t is the current service life of the equipment, and the estimation formula of the aging index B is as follows:
in the formula, SNAnd S0Respectively representing health status scores, T, during decommissioning and commissioning of the equipmentNRepresenting the actual service life of the equipment when retired;
and (4): according to the formula S ═ Sregularwregular+Srealtimewrealtime+ShistorywhistoryAnd calculating the final score S of the state evaluation of the distribution network equipment fused with the multi-source information.
2. The method for evaluating the state of the distribution network equipment integrating the multi-source information, according to claim 1, is characterized in that: in step (3), the specific correction coefficient considering the environment of the device is as follows:
3. the method for evaluating the state of the distribution network equipment integrating the multi-source information, according to claim 1, is characterized in that: in the step (3), the specific correction coefficient considering the number of the self-defect faults of the equipment is as follows:
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610091916.1A CN105761001B (en) | 2016-02-19 | 2016-02-19 | Distribution network equipment state evaluation method fusing multi-source information |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610091916.1A CN105761001B (en) | 2016-02-19 | 2016-02-19 | Distribution network equipment state evaluation method fusing multi-source information |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN105761001A CN105761001A (en) | 2016-07-13 |
| CN105761001B true CN105761001B (en) | 2020-01-14 |
Family
ID=56330122
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201610091916.1A Active CN105761001B (en) | 2016-02-19 | 2016-02-19 | Distribution network equipment state evaluation method fusing multi-source information |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN105761001B (en) |
Families Citing this family (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106571627A (en) * | 2016-10-12 | 2017-04-19 | 中国南方电网有限责任公司 | Secondary device health state evaluation method based on on-line monitoring information |
| CN106651731B (en) * | 2016-12-25 | 2020-10-09 | 杭州博烁晟斐智能科技有限公司 | Communication tower to-be-solved problem set generation method and system based on historical data |
| CN107025514A (en) * | 2016-12-27 | 2017-08-08 | 贵州电网有限责任公司电力科学研究院 | The evaluation method and power transmission and transforming equipment of a kind of dynamic evaluation transformer equipment state |
| CN110619413A (en) * | 2018-06-20 | 2019-12-27 | 北京金风慧能技术有限公司 | Method and device for evaluating health degree of wind generating set |
| CN109544399B (en) * | 2018-11-29 | 2021-03-16 | 广东电网有限责任公司 | Power transmission equipment state evaluation method and device based on multi-source heterogeneous data |
| CN109902334B (en) * | 2019-01-09 | 2023-04-11 | 中国电子产品可靠性与环境试验研究所（（工业和信息化部电子第五研究所）（中国赛宝实验室）） | Method and device for predicting service life of precision speed reducer for robot and computer equipment |
| CN110247975B (en) * | 2019-06-19 | 2022-01-07 | 公安部第一研究所 | Internet of things multi-device cooperative service construction method based on improved D-S evidence |
| CN110929986A (en) * | 2019-10-25 | 2020-03-27 | 贵州电网有限责任公司 | Power distribution equipment state evaluation method based on standing book, real-time and historical information |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104318482A (en) * | 2014-08-22 | 2015-01-28 | 国家电网公司 | Comprehensive assessment system and method of smart distribution network |
| CN105205590A (en) * | 2015-09-01 | 2015-12-30 | 深圳供电局有限公司 | Transformer health state analysis method and system |
-
2016
- 2016-02-19 CN CN201610091916.1A patent/CN105761001B/en active Active
Also Published As
| Publication number | Publication date |
|---|---|
| CN105761001A (en) | 2016-07-13 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN105761001B (en) | Distribution network equipment state evaluation method fusing multi-source information | |
| CN108375476B (en) | Hydroelectric generating set health assessment method | |
| CN104268678B (en) | A kind of petrochemical equipment preventative maintenance method based on dynamic reliability | |
| KR101683256B1 (en) | Asset management system and method for electric power apparatus | |
| CN109359894B (en) | RPN-based risk evaluation method and device for electric power metering equipment | |
| CN110929986A (en) | Power distribution equipment state evaluation method based on standing book, real-time and historical information | |
| CN104316803B (en) | A kind of Power Transformer Condition evaluation method and system based on live detection | |
| CN110309981A (en) | A kind of power station Decision-making of Condition-based Maintenance system based on industrial big data | |
| CN110375787A (en) | A kind of measuring instrument operating status on-line evaluation method | |
| CN107239876B (en) | Management method and system for aging life cycle of I & C equipment of nuclear power plant | |
| CN109636110A (en) | A kind of method and device obtaining protective relaying device operating status | |
| CN117421687A (en) | Method for monitoring running state of digital power ring main unit | |
| Srinivasan et al. | Effects of environmental factors in transformer’s insulation life | |
| CN115905474A (en) | Power equipment state evaluation method and device based on historical defect text information | |
| CN106325258B (en) | Relay protection device state evaluation method based on online monitoring information | |
| CN115809805A (en) | Power grid multi-source data processing method based on edge calculation | |
| CN112766657B (en) | Single equipment quality evaluation method based on fault probability and equipment state | |
| Rui et al. | Failure risk assessment method of electric energy meter based on state evaluation | |
| Ma et al. | Electric Energy Meter State Management System Based on Index Analysis System | |
| CN107346008B (en) | Electric energy meter state inspection optimization method based on actual load condition | |
| Xu et al. | Comprehensive Method for Determining Transformer Decommissioning Life Considering Economic Life and Physical Life | |
| Goretti et al. | Evaluation of wind energy forecasts: The undervalued importance of data preparation | |
| CN117808456B (en) | Equipment fault early warning method and device based on intelligent operation management | |
| CN114154848B (en) | Terminal equipment power supply dynamic risk assessment method, system, equipment and medium | |
| Hao et al. | Power equipment reliability evaluation based on data mining |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |