CN106570567A - Main network maintenance multi-constraint multi-target evaluation expert system and optimization method - Google Patents
Main network maintenance multi-constraint multi-target evaluation expert system and optimization method Download PDFInfo
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- CN106570567A CN106570567A CN201610947806.0A CN201610947806A CN106570567A CN 106570567 A CN106570567 A CN 106570567A CN 201610947806 A CN201610947806 A CN 201610947806A CN 106570567 A CN106570567 A CN 106570567A
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- 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
- G06Q10/20—Administration of product repair or maintenance
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- 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—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
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Abstract
The invention discloses a main network maintenance multi-constraint multi-target evaluation expert system and an optimization method. The system mainly comprises a data integration module, an integrated power grid maintenance plan evaluation module, a safety evaluation module, an economic performance evaluation module, a reliability evaluation module, a historical database, an index model database, a maintenance capability evaluation module, an intelligent algorithm program and an intelligent man-machine interface. Through the system, problems that changeable work requirements can not be satisfied by standard state maintenance in the prior art, the real-time monitoring and analysis diagnosis technology is not mature, and maintenance decision complexity further greatly increases even though acquisition of more information and improvement of decision accuracy are realized through state maintenance development are solved.
Description
Technical field
The present invention relates to grid maintenance technical field, in particular it relates to a kind of maintenance multi-restriction Multi-Objective assessment of major network is special
Family's system and optimization method.
Background technology
The establishment of grid power blackout repair schedule is an annual important process of Utilities Electric Co..The main purpose of maintenance is to ensure
Electric network security, economy and reliability.With the development of power industry, grid maintenance pattern also experienced transition, in development
Initial stage, overhaul management is based on trouble shooting pattern.Twentieth century middle and late stage is arrived, then based on periodic inspection.But enter
It is after 21 century, the drawbacks of this maintenance model and not enough more and more obvious, on the one hand, with the development of power technology, electric power
The workmanship of equipment is increasingly improved, and all kinds of detection techniques and means are gradually improved；On the other hand, it is rapid due to electrical network scale
Expand, continue to continue to use periodic plan maintenance model, as maintenance is for Xiang Buqiang, not only cause part to overhaul the waste of resource,
Again as maintainer is not enough, and cause the in bad repair of equipment component.Electric power enterprise actively develops Maintenance Mode at present.State
Maintenance be enterprise based on safety, economy, reliability, by equipment state evaluation, risk assessment, maintenance decision, reach
To a kind of rational Strategies of Maintenance of the cost of overhaul safe and reliable to operation.
With the progress of electric power overhaul technology, new model also brings new problem.On the one hand, standardized repair based on condition of component without
Method meets changeable job requirement, and on the other hand, real-time monitoring and analyzing and diagnosing technology are also immature.Although repair based on condition of component is carried out
More than ever before information is obtained, the correctness of decision-making is which raises, but while is also greatly increased maintenance decision complexity.For
This needs to carry out overall merit repair schedule reasonability using new approaches, new technology and method.
The content of the invention
It is an object of the present invention to be directed to the problems referred to above, a kind of major network maintenance multi-restriction Multi-Objective assessment experts system is proposed
System and optimization method, to realize to being capable of achieving the prediction to major network repair schedule reliability effect；Simultaneously according to national economy shadow
Ringing affects to make inferences and inquiry on major network fault outage, is calculated using the intelligence of major network repair schedule comprehensive appraisal expert system
Method, can search out the prioritization scheme of major network overhauling project priority, the reasonable duration of each scheduled overhaul and human input demand, and then
Realize the advantage of the global optimization of safe operation of electric network, economy and reliability.
For achieving the above object, the technical solution used in the present invention is：A kind of major network maintenance multi-restriction Multi-Objective assessment is special
Family's system, mainly includes：
For obtaining power transformating and supplying facility account parameter, power transformating and supplying facility running state information, power transmission and transformation system loop account parameter
With the data integration module of power transmission and transformation system operation information；
For the electric network security evaluation module of the safety of analysis and evaluation operation of power networks；
For the economic power system evaluation module of the economy of analysis and evaluation operation of power networks；
For the system adequacy evaluation module of the reliability of analysis and evaluation operation of power networks；
For the rational maintenance scheduling for power systems overall merit module of overall merit operation of power networks repair schedule；
For according to all kinds of breakdown repair data and all kinds of scheduled overhaul data are actually occurred, finding in repair schedule model library
The service ability evaluation module of immediate ripe case；
For storing electrical network history scheduled overhaul situation, fault outage situation, and the historical data of correspondence other modules records
Historical data base；
For configuration and query argument input and monitor in real time or the service end data statisticss mould of the output for collecting history report
Block；
The intelligent human/computer interface communicated by PORT COM with service end data statistics module；
With the index model storehouse of the analysis model evaluated including multiple multidimensional major network repair schedules.
Further, also include to be affected according to electric network fault rate, facility reliability and power failure national economy, described
The reasoning by cases module of immediate ripe case is found in net repair schedule overall merit module and most to connect according to
Near ripe case constraint control parameter, searching reach the inspection for overhauling reasonable man-hour parameter that certain class overhauls the parameter in reasonable man-hour
Repair man-hour evaluation module.
Further, the reasoning by cases module includes approximate case query unit and optimal solution case storage unit, institute
Approximate case query unit is stated to according to electric network fault rate value up to standard, maintenance and failure inverse ratio correlation coefficient and its people Jing that has a power failure
Ji affects data, and the maintenance model in the index model storehouse finds immediate ripe case, and the optimal solution case is protected
Under memory cell is to preserve with maximum failure rate limit, the new case obtained after economy and reliability are adjusted simultaneously should
New case is used as maintenance model.
The optimization method of multi-restriction Multi-Objective assessment experts system is overhauled based on major network, including：
Step 1：Data integration module obtains power transformating and supplying facility account data, power transformating and supplying facility event data, power transmission and transformation loop board
Account data, power transmission and transformation loop event data and repair schedule task derived data；
Step 2：All data is activations that data integration module in step 1 is obtained are to service end data statistics module, service end
Data statistics module is processed to data, then the parameter of renewal is sent to security assessment module, economic evaluation mould
Fast and reliability assessment module；
Step 3：Parameter initialization, by being contrasted with historical data optimum working condition, if approximate history, is then configured
Parameter is transmitted to maintenance scheduling for power systems PLAN Overall evaluation module, and stores historical data, terminates maintenance, if nothing is approximately gone through
History, then inquired about to index model storehouse and reasoning by reasoning by cases module, finds immediate ripe case, and by inspection
Repairing man-hour searches out the parameter for overhauling reasonable man-hour, exports configuration parameter；
Step 4：After output configuration parameter, configuration parameter is transmitted to maintenance scheduling for power systems overall merit module, by input results,
The precomputation result of all kinds of control type indexs is analyzed, optimal solution is stored, terminates maintenance
Further, in step 2, the safety evaluation carries out reduced value-at-risk by assessing repair schedule, embodies
The safety improved by this repair schedule, risk value calculating method：Value-at-risk（D）=probability index（P）× frequency index（F）
× the order of severity（S）；The economic evaluation is concretely comprised the following steps：It is first depending on 3 years consumption ratios of certain type of work history to calculate
Go out the economic index value of such work in meansigma methodss（α）And standard deviation（β）If the economic index value of certain plan exists（α±
β）Interior, then acquiescence judges qualified；If the economic index value of certain plan exists（α±2β）It is interior, then identify automatically the plan needs
Explanation is enumerated in subdivision；
During the reliability assessment, overall control is carried out with annual index, that is, require to consider early stage service work situation, current maintenance
Projected conditions and later stage projected conditions to be scheduled, reliability and electric load all have season undulatory property, therefore reliability evaluation
Using the undulatory property of moving average as the dynamic fundamentals of management.
A kind of major network maintenance multi-restriction Multi-Objective assessment experts system of various embodiments of the present invention and optimization method, due to master
Including：Data integration module, maintenance scheduling for power systems overall merit module, security assessment module, economic evaluation module, can
By property evaluation module, historical data base, index model storehouse, service ability evaluation module, intelligent algorithm program and the man-machine boundary of intelligence
Face；Repair based on condition of component such that it is able to overcome prior art Plays cannot meet changeable job requirement, real-time monitoring and point
Analysis diagnostic techniquess are also immature, although repair based on condition of component development obtains more than ever before information, which raises the correct of decision-making
Property, but while also greatly increase maintenance decision complexity.
Other features and advantages of the present invention will be illustrated in the following description, also, partly be become from description
Obtain it is clear that or being understood by implementing the present invention.
Below by drawings and Examples, technical scheme is described in further detail.
Description of the drawings
Accompanying drawing is used for providing a further understanding of the present invention, and constitutes a part for description, the reality with the present invention
Applying example is used for explaining the present invention together, is not construed as limiting the invention.In the accompanying drawings：
Fig. 1 is that the composition of the major network maintenance multi-restriction Multi-Objective assessment experts system described in the specific embodiment of the invention is illustrated
Figure；
Fig. 2 is the optimization side that multi-restriction Multi-Objective assessment experts system is overhauled based on major network described in the specific embodiment of the invention
The Optimizing Flow figure started from data integration in method；
Fig. 3 is the optimization side that multi-restriction Multi-Objective assessment experts system is overhauled based on major network described in the specific embodiment of the invention
The Optimizing Flow figure that the Maintenance Schedule Optimization system of method/man machine interface starts.
Specific embodiment
The preferred embodiments of the present invention are illustrated below in conjunction with accompanying drawing, it will be appreciated that preferred reality described herein
Apply example and be merely to illustrate and explain the present invention, be not intended to limit the present invention.
Specifically, a kind of major network overhauls multi-restriction Multi-Objective assessment experts system, mainly includes：
For obtaining power transformating and supplying facility account parameter, power transformating and supplying facility running state information, power transmission and transformation system loop account parameter
With the data integration module of power transmission and transformation system operation information；
For the electric network security evaluation module of the safety of analysis and evaluation operation of power networks；
For the economic power system evaluation module of the economy of analysis and evaluation operation of power networks；
For the system adequacy evaluation module of the reliability of analysis and evaluation operation of power networks；
For the rational maintenance scheduling for power systems overall merit module of overall merit operation of power networks repair schedule；
For according to all kinds of breakdown repair data and all kinds of scheduled overhaul data are actually occurred, finding in repair schedule model library
The service ability evaluation module of immediate ripe case；
For storing electrical network history scheduled overhaul situation, fault outage situation, and the historical data of correspondence other modules records
Historical data base；
For configuration and query argument input and monitor in real time or the service end data statisticss mould of the output for collecting history report
Block；
The intelligent human/computer interface communicated by PORT COM with service end data statistics module；
With the index model storehouse of the analysis model evaluated including multiple multidimensional major network repair schedules.
Also include to be affected according to electric network fault rate, facility reliability and power failure national economy, in the net maintenance meter
The reasoning by cases module of immediate ripe case is found and to according to the immediate maturation in drawing overall merit module
Case constrains control parameter, and searching reaches the check man's news commentary for overhauling reasonable man-hour parameter that certain class overhauls the parameter in reasonable man-hour
Valency module.
The reasoning by cases module includes approximate case query unit and optimal solution case storage unit, the approximate case
Query unit is to affect number according to electric network fault rate value up to standard, maintenance and failure inverse ratio correlation coefficient and power failure national economy
According to the maintenance model in the index model storehouse finds immediate ripe case, and the optimal solution case storage unit is used
Under preserving with maximum failure rate limit, the new case that obtains after economy and reliability are adjusted by the new case
As maintenance model.
The optimization method of multi-restriction Multi-Objective assessment experts system is overhauled based on major network, including：
Step 1：Data integration module obtains power transformating and supplying facility account data, power transformating and supplying facility event data, power transmission and transformation loop board
Account data, power transmission and transformation loop event data and repair schedule task derived data；
Step 2：All data is activations that data integration module in step 1 is obtained are to service end data statistics module, service end
Data statistics module is processed to data, then the parameter of renewal is sent to security assessment module, economic evaluation mould
Fast and reliability assessment module；
Step 3：Parameter initialization, by being contrasted with historical data optimum working condition, if approximate history, is then configured
Parameter is transmitted to maintenance scheduling for power systems PLAN Overall evaluation module, and stores historical data, terminates maintenance, if nothing is approximately gone through
History, then inquired about to index model storehouse and reasoning by reasoning by cases module, finds immediate ripe case, and by inspection
Repairing man-hour searches out the parameter for overhauling reasonable man-hour, exports configuration parameter；
Step 4：After output configuration parameter, configuration parameter is transmitted to maintenance scheduling for power systems overall merit module, by input results,
The precomputation result of all kinds of control type indexs is analyzed, optimal solution is stored, terminates maintenance
In step 2, safety evaluation carries out reduced value-at-risk by assessing repair schedule, embodies this repair schedule institute
The safety of raising, risk value calculating method：Value-at-risk（D）=probability index（P）× frequency index（F）× the order of severity（S）；
The economic evaluation is concretely comprised the following steps：It is first depending on 3 years consumption ratios of certain type of work history and calculates the Jing of such work
Ji property desired value is in meansigma methodss（α）And standard deviation（β）If the economic index value of certain plan exists（α±β）Interior, then acquiescence is sentenced
It is fixed qualified；If the economic index value of certain plan exists（α±2β）Interior, then identifying automatically the plan needs subdivision to enumerate explanation；
During the reliability assessment, overall control is carried out with annual index, that is, require to consider early stage service work situation, current maintenance
Projected conditions and later stage projected conditions to be scheduled, reliability and electric load all have season undulatory property, therefore reliability evaluation
Using the undulatory property of moving average as the dynamic fundamentals of management.
With reference to Fig. 1, present invention is disclosed a kind of major network repair schedule multi-restriction Multi-Objective Optimal Expert System, to optimize
The safety of major network repair schedule, economy and reliability；Which includes：Data integration module, maintenance scheduling for power systems overall merit
Module, security assessment module, economic evaluation module, reliability assessment module, historical data base, index model storehouse, maintenance
Merit rating module, intelligent algorithm program and intelligent human/computer interface.Each module is introduced in detail below.
Data integration module, returns for obtaining power transformating and supplying facility account parameter, facility operation status information, power transmission and transformation system
Road account parameter and power transmission and transformation system operation information；
Electric network security evaluation module, for the safety of analysis and evaluation operation of power networks；
Economic power system evaluation module, for the economy of analysis and evaluation operation of power networks；
System adequacy evaluation module, for the reliability of analysis and evaluation operation of power networks；
Maintenance scheduling for power systems overall merit module, for the reasonability of overall merit operation of power networks repair schedule；
Service ability evaluation module, for according to all kinds of breakdown repair data and all kinds of scheduled overhaul data are actually occurred, in inspection
Immediate ripe case is found in repairing planning model storehouse；
Historical data base, for storing electrical network history scheduled overhaul situation, fault outage situation, and corresponds to other modules records
Historical data；
Index model storehouse, including the analysis model that some multidimensional major network repair schedules are evaluated；
Data statistics module, input and the monitor in real time for parameter configuration collect the/output of history report.
Service ability evaluation module, actually occurs all kinds of breakdown repair data and all kinds of scheduled overhaul data for basis,
Immediate ripe case is found in repair schedule model library；
Historical data base, for storing electrical network history scheduled overhaul situation, fault outage situation, and corresponds to other modules records
Historical data；
Index model storehouse, including the analysis model that some multidimensional major network repair schedules are evaluated；
Data statistics module, input and the monitor in real time for parameter configuration collect the/output of history report.
Used as a preferred embodiment of the present invention, the Multi objective optimization system includes：
Reasoning by cases module, to be affected according to electric network fault rate, facility reliability and power failure national economy, examines in the major network
Repair during PLAN Overall evaluates storehouse and find immediate ripe case；
Evaluation module during check man, to constrain control parameter according to above-mentioned immediate ripe case, searching reaches certain class and examines
Parameter during backfit science and engineering.
Used as a preferred embodiment of the present invention, the reasoning by cases module includes：
Approximate case query unit, to according to electric network fault rate value up to standard, maintenance and failure inverse ratio correlation coefficient and power failure state
People's economic impact data, the maintenance model in the index model storehouse find immediate ripe case；
Optimal solution case storage unit, under preserving with maximum failure rate limit, after economy and reliability are adjusted
The new case for arriving is used as maintenance model.
The Multi objective optimization system includes security assessment module, economic evaluation module, reliability assessment and electrical network
Repair schedule overall merit module.When case carries out multiple-objection optimization, if safety evaluation is not up to standard, the plan is by a ticket
Rejection, safety evaluation are to carry out reduced value-at-risk by assessing repair schedule, embody this repair schedule and are improved
Safety.Risk value calculating method：Value-at-risk（D）=probability index（P）× frequency index（F）× the order of severity（S）.
During economic evaluation, it is first depending on 3 years efficiency-cost ratios of certain type of work history and calculates the economy of such work referring to
The meansigma methodss of scale value（α）And standard deviation（β）.If the economic index value of certain plan exists in case study on implementation（α±β）It is interior, then
It is qualified that acquiescence judges；Otherwise similar case is searched in the time-consuming history of maintenance, if the planned economy desired value is in similar case
In example value is interval, then regarding as economic evaluation can pass through；If not being similar to case, the requirements of plan submits additional materials to
Carry out manual review.The plan when manual review passes through is brought in case library.
During reliability assessment, overall control is carried out with annual index, that is, require to consider early stage service work situation, current maintenance
Projected conditions and later stage projected conditions to be scheduled.Reliability and electric load all have season undulatory property, are this present case reliability
Property evaluate using the undulatory property of moving average as the dynamic fundamentals of management.
During reliability assessment, from terms of angle of statistics, it is desirable to annual interior network system reliability season undulatory property and history
Value is essentially identical, and current reliability actual value should be in the controlled area of prediction curve.
Multi objective optimization system is according to the target component for arranging, control plan initial time and planning work duration, and divides
Analysis closes on repair schedule and merges the impact to index.When the potential safety hazard risk of certain wanted defect elimination of plan is larger, then manpower is preferential
It is preferential with sequential；When same certain plan is arranged, if resource requirement exceeds limit, maintenance time-out may be produced and turn the first kind
Unplanned outage, now needs to carry out repair schedule balance, adjustment maintenance sequential.
The data integration module, gathered data include power transformating and supplying facility account parameter, power transformating and supplying facility running status letter
Breath, power transmission and transformation system loop account parameter, power transmission and transformation system operation information, major network interruption maintenance application information and major network overhaul skill
Change annual plan information etc..Power transformating and supplying facility machine account parameter is mainly used in obtaining the equipment letter for needing first year to put into operation routine inspection
Breath.Power transformating and supplying facility running state information is mainly used in the operating time for obtaining historical failure repairing or scheduled overhaul.Power transmission and transformation
For dividing, equipment is same to stop with the spacer units for sending system circuit account information.Power transmission and transformation system operation information is used for assessment system
The index situation such as safety and reliability.Major network interruption maintenance application information and major network overhaul technological transformation annual plan information are needs
It is optimized adjustment original scheme data.
With reference to Fig. 2 to Fig. 3, methods described comprises the steps：
Serve end program carries out preliminary treatment to the data that Monitoring Data integration module is obtained, then update parameter send to
The major network repair schedule complex optimum module of Multi objective optimization system；
Multi objective optimization system is by the integrated Monitoring Data for collecting or active inquiry major network Maintenance Schedule Optimization system, index
The information of model library, the execution parameter set of the historical data optimum repair schedule built-in with system are contrasted, and check maintenance meter
Draw and whether be in optimum state；
Multi objective optimization system is based on historical data base and index model storehouse, by stopping to integrated data machine account parameter set and equipment
Electrical quantity collection is analyzed with the functional relationship of service ability index, and multiple constraints of equipment are integrally considered, finally
Obtain the configuration parameter of repair schedule total optimization；
More specifically it is described as：Major network operating state monitoring system, repair schedule analysis module obtain power failure planning data, equipment
History examining and analyzing data, device history accident analysis data, equipment close relative's historical failure analytical data, and send data to
Platform PORT COM；
Serve end program carries out preliminary treatment to the data that Monitoring Data collecting unit is obtained, then update parameter send to
The adjustment module of Multi objective optimization system；
Multi objective optimization system, is by sample division, the constraint of sample event data, power system security, economy constraint
With the data such as reliability constraint, to set up the purpose of computer aided decision making.System be based on Principle of Statistics, by with history number
Contrasted according to optimum working condition, checked whether repair schedule belongs to optimum state；
Index model storehouse exports configuration parameter according to model, and transmits it to grid maintenance overall merit module；
Grid maintenance overall merit module, by input results, analyzes the precomputation result of all kinds of control type indexs, and is used for
Plan is further adjusted.
Used as a preferred embodiment of the present invention, the Multi objective optimization system includes：
Reasoning by cases module, to be affected according to electric network fault rate, facility reliability and power failure national economy, examines in the major network
Repair during PLAN Overall evaluates storehouse and find immediate ripe case；
Evaluation module during check man, to constrain control parameter according to above-mentioned immediate ripe case, searching reaches certain class and examines
Parameter during backfit science and engineering.
Used as a preferred embodiment of the present invention, the reasoning by cases module includes：
Approximate case query unit, to according to electric network fault rate value up to standard, maintenance and failure inverse ratio correlation coefficient and power failure state
People's economic impact data, the maintenance model in the index model storehouse find immediate ripe case；
Optimal solution case storage unit, under preserving with maximum failure rate limit, after economy and reliability are adjusted
The new case for arriving is used as maintenance model.
In sum, a kind of major network maintenance multi-restriction Multi-Objective assessment experts system proposed by the present invention and optimization method,
It is capable of achieving to affect reliability index to be predicted major network repair schedule；Overall merit is carried out according to index model storehouse simultaneously and is pushed away
Reason, using the intelligent algorithm of Maintenance Schedule Optimization specialist system, can find the optimal repair schedule sequential under constraints and arrange
Scheme, and then management and control is implemented by repair schedule, realize the global optimization of multi-restriction Multi-Objective.
Following beneficial effect can at least be reached：Major network repair schedule multi-restriction Multi-Objective proposed by the present invention optimizes expert
System and its optimization method, are capable of achieving the prediction to major network repair schedule reliability effect；Affect right according to national economy simultaneously
Major network fault outage affects to make inferences and inquiry, using the intelligent algorithm of major network repair schedule comprehensive appraisal expert system, can
The prioritization scheme of major network overhauling project priority, the reasonable duration of each scheduled overhaul and human input demand is searched out, and then is realized
The global optimization of safe operation of electric network, economy and reliability.
Finally it should be noted that：The preferred embodiments of the present invention are the foregoing is only, the present invention is not limited to,
Although being described in detail to the present invention with reference to the foregoing embodiments, for a person skilled in the art, which still may be used
To modify to the technical scheme described in foregoing embodiments, or equivalent is carried out to which part technical characteristic.
All any modification, equivalent substitution and improvements within the spirit and principles in the present invention, made etc., should be included in the present invention's
Within protection domain.
Claims (5)
1. a kind of major network overhauls multi-restriction Multi-Objective assessment experts system, it is characterised in that include：
For obtaining power transformating and supplying facility account parameter, power transformating and supplying facility running state information, power transmission and transformation system loop account parameter
With the data integration module of power transmission and transformation system operation information；
For the electric network security evaluation module of the safety of analysis and evaluation operation of power networks；
For the economic power system evaluation module of the economy of analysis and evaluation operation of power networks；
For the system adequacy evaluation module of the reliability of analysis and evaluation operation of power networks；
For the rational maintenance scheduling for power systems overall merit module of overall merit operation of power networks repair schedule；
For according to all kinds of breakdown repair data and all kinds of scheduled overhaul data are actually occurred, finding in repair schedule model library
The service ability evaluation module of immediate ripe case；
For storing electrical network history scheduled overhaul situation, fault outage situation, and the historical data of correspondence other modules records
Historical data base；
For configuration and query argument input and monitor in real time or the service end data statisticss mould of the output for collecting history report
Block；
The intelligent human/computer interface communicated by PORT COM with service end data statistics module；
With the index model storehouse of the analysis model evaluated including multiple multidimensional major network repair schedules.
2. major network according to claim 1 overhauls multi-restriction Multi-Objective assessment experts system, it is characterised in that also include using
To be affected according to electric network fault rate, facility reliability and power failure national economy, in the net repair schedule overall merit module
Find the reasoning by cases module of immediate ripe case and control parameter is constrained according to the immediate ripe case,
Searching reaches evaluation module when certain class overhauls the check man of reasonable man-hour parameter.
3. major network according to claim 2 overhauls multi-restriction Multi-Objective assessment experts system, it is characterised in that the case
Reasoning module includes approximate case query unit and optimal solution case storage unit, and the approximate case query unit is to basis
Electric network fault rate value up to standard, maintenance and failure inverse ratio correlation coefficient and power failure national economy affect data, in the index model
Maintenance model in storehouse finds immediate ripe case, and the optimal solution case storage unit is to preserve with maximum failure rate
Under limit, the new case that obtains after economy and reliability are adjusted and using the new case as maintenance model.
4. the optimization method of multi-restriction Multi-Objective assessment experts system is overhauled based on the major network described in claim 3, and its feature exists
In, including：
Step 1：Data integration module obtains power transformating and supplying facility account data, power transformating and supplying facility event data, power transmission and transformation loop board
Account data, power transmission and transformation loop event data and repair schedule task derived data；
Step 2：All data is activations that data integration module in step 1 is obtained are to service end data statistics module, service end
Data statistics module is processed to data, then the parameter of renewal is sent to security assessment module, economic evaluation mould
Fast and reliability assessment module；
Step 3：Parameter initialization, by being contrasted with historical data optimum working condition, if approximate history, is then configured
Parameter is transmitted to maintenance scheduling for power systems PLAN Overall evaluation module, and stores historical data, terminates maintenance scheduling evaluation, if nothing
Approximate history, then inquired about to index model storehouse and reasoning by reasoning by cases module, finds immediate ripe case, and
The parameter for overhauling reasonable man-hour is searched out during by check man, configuration parameter is exported；
Step 4：After output configuration parameter, configuration parameter is transmitted to maintenance scheduling for power systems overall merit module, by input results,
The precomputation result of all kinds of control type indexs is analyzed, optimal solution is stored, terminates maintenance scheduling evaluation.
5. major network according to claim 4 overhauls the optimization method of multi-restriction Multi-Objective assessment experts system, and its feature exists
In in step 2, the safety evaluation carries out reduced value-at-risk by assessing repair schedule, embodies this maintenance meter
Draw improved safety, risk value calculating method：Value-at-risk（D）=probability index（P）× frequency index（F）× the order of severity
（S）；The economic evaluation is concretely comprised the following steps：It is first depending on 3 years consumption ratios of certain type of work history and calculates such work
Economic index value in meansigma methodss（α）And standard deviation（β）If the economic index value of certain plan exists（α±β）It is interior, then write from memory
Recognize judgement qualified；If the economic index value of certain plan exists（α±2β）Interior, then identifying automatically the plan needs subdivision to enumerate
It is bright；
During the reliability assessment, overall control is carried out with annual index, that is, require to consider early stage service work situation, current maintenance
Projected conditions and later stage projected conditions to be scheduled, reliability and electric load all have season undulatory property, therefore reliability evaluation
Using the undulatory property of moving average as the dynamic fundamentals of management.
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Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107938474A (en) * | 2018-01-09 | 2018-04-20 | 福建船政交通职业学院 | Based on driver's cabin double-amplitude than compactness on-line measuring device system |
| CN109919406A (en) * | 2018-12-18 | 2019-06-21 | 国网浙江桐乡市供电有限公司 | The intelligent housekeeping arrangement method of the power distribution network method of operation |
| CN111126726A (en) * | 2018-10-30 | 2020-05-08 | 北京同方软件有限公司 | Intelligent decision multi-target analysis method based on heterogeneous fusion data |
| CN111651496A (en) * | 2020-04-27 | 2020-09-11 | 国网河南省电力公司商丘供电公司 | Repeated power failure analysis decision system and method based on artificial intelligence mode |
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| CN112613179A (en) * | 2020-12-28 | 2021-04-06 | 国网天津市电力公司电力科学研究院 | Method for evaluating influence of live overhaul of power transmission and transformation on power grid |
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Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107938474A (en) * | 2018-01-09 | 2018-04-20 | 福建船政交通职业学院 | Based on driver's cabin double-amplitude than compactness on-line measuring device system |
| CN107938474B (en) * | 2018-01-09 | 2023-09-01 | 福建船政交通职业学院 | Compactness on-line measuring device system based on two amplitude ratios in driver's cabin |
| CN111126726A (en) * | 2018-10-30 | 2020-05-08 | 北京同方软件有限公司 | Intelligent decision multi-target analysis method based on heterogeneous fusion data |
| CN109919406A (en) * | 2018-12-18 | 2019-06-21 | 国网浙江桐乡市供电有限公司 | The intelligent housekeeping arrangement method of the power distribution network method of operation |
| CN111651496A (en) * | 2020-04-27 | 2020-09-11 | 国网河南省电力公司商丘供电公司 | Repeated power failure analysis decision system and method based on artificial intelligence mode |
| CN112183896A (en) * | 2020-10-31 | 2021-01-05 | 国网河南省电力公司漯河供电公司 | Intelligent identification and auxiliary compilation method for regional power grid maintenance plan |
| CN112183896B (en) * | 2020-10-31 | 2022-08-09 | 国网河南省电力公司漯河供电公司 | Intelligent identification and auxiliary compilation method for regional power grid maintenance plan |
| CN112348374A (en) * | 2020-11-12 | 2021-02-09 | 深圳供电局有限公司 | Intelligent arrangement system for distribution network maintenance plan |
| CN112613179A (en) * | 2020-12-28 | 2021-04-06 | 国网天津市电力公司电力科学研究院 | Method for evaluating influence of live overhaul of power transmission and transformation on power grid |
| CN112613179B (en) * | 2020-12-28 | 2022-11-08 | 国网天津市电力公司电力科学研究院 | Method for evaluating influence of live overhaul of power transmission and transformation on power grid |
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