CN106485596A - A kind of controller switching equipment Strategies of Maintenance optimization method - Google Patents
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Abstract
The invention belongs to the optimization economic load dispatching technical field of the Optimized model of power distribution network Strategies of Maintenance and power distribution network, more particularly to a kind of controller switching equipment Strategies of Maintenance optimization method, comprise the steps：S1, determines the basic parameter of controller switching equipment Strategies of Maintenance Optimized model according to device history data and empirical data；S2, randomly generates the initial solution of the Strategies of Maintenance；S3, evaluates the major overhaul cost of each decision-making of the controller switching equipment under initial solution, obtains the evaluation result of initial solution；S4, applies genetic algorithm, initial population is intersected, made a variation and is selected, obtain new solution；S5, continues new solution described in iteration optimization, until result appraisal result no longer becomes excellent, exports optimal solution.The present invention sets up the Optimized model of power distribution network Strategies of Maintenance under repair based on condition of component background.By can obtaining quantifying including maintenance mode and the Strategies of Maintenance of repair time to the solution of the model.Service work to domestic power distribution network has higher adaptability.
Description
Technical field
The invention belongs to the optimization economic load dispatching technical field of the Optimized model of power distribution network Strategies of Maintenance and power distribution network, especially
It is related to a kind of controller switching equipment Strategies of Maintenance optimization method.
Background technology
With State Grid Corporation of China's formulation in 2011《Distribution net equipment repair based on condition of component directive/guide》Deng issuing for three technology standard
Cloth, controller switching equipment running status prison/detection and analysis and trouble diagnosibility are significantly improved, and Distribution Network Equipment maintenance also will be by
Step is from traditional periodic inspection mode to Mode of condition-oriented overhaul transition.But, existing《Distribution net equipment repair based on condition of component directive/guide》Only
It is qualitatively to give the suggestion which kind of maintenance mode equipment under different health status should take, such as transformer body
Maintenance suggestion under different health status is as shown in table 1.And be to arrange which kind of maintenance actually, actually how long in the range of enter
Row maintenance,《Directive/guide》All do not carry out clearly.Evaluate the disappearance of quantitative criteria so that maintenance decision personnel are big in real work
All decision-making is carried out with personal experience, have impact on popularization and the implementation result of controller switching equipment repair based on condition of component.
Table 1
The current research both at home and abroad to Maintenance Schedule Optimization Model in Distribution Systems has following deficiency：Domestic major part is ground
Study carefully and also rest under " periodic inspection " mode, research is how to pass through under the set time between overhauls(TBO) reasonably to coordinate check man
The time started of work, reduce the cost of overhaul and loss of outage, these Optimized models on the premise of operation of power networks reliability is met
" repair based on condition of component " this new maintenance mode can not be fully met to aspects such as overhaul of the equipments content optimization, maintenance circle optimization
Demand.Also there is part research to take up the formulation problem of Tactial problem under repair based on condition of component, but these are studied or are absorbed in
The coordination problem of the time between overhauls(TBO) of different maintenance modes, or focus on the selection solved in maintenance mode under different health status
Problem, rarely having research answer completely actually should be when using which kind of maintenance mode under different health status.External
Mostly based on the demand of itself, as China's power distribution network development is relatively slow, repair based on condition of component work is at the early-stage, thus external for research
Achievement in research can only play a part of use for reference and inspire, the hand-manipulating of needle need to be entered according to the actual conditions of China's power distribution network service work
Modeling to property.
Content of the invention
For the problems referred to above, the present invention proposes a kind of controller switching equipment Strategies of Maintenance optimization method, comprises the steps：
S1, determines the basic parameter of controller switching equipment Strategies of Maintenance Optimized model according to device history data and empirical data；
S2, randomly generates the initial solution of the Strategies of Maintenance；
S3, evaluates the major overhaul cost of each decision-making of the controller switching equipment under initial solution, obtains initial result appraisal
As a result；
S4, applies genetic algorithm, initial population is intersected, made a variation and is selected, obtain new solution；
S5, continues new solution described in iteration optimization, until result appraisal result no longer becomes excellent, exports optimal solution.
Preferably, the device history data includes device history fault rate, health status evaluating data and device history
Overhaul data.
Preferably, step S1 also includes：Become according to the maintenance that device history overhaul data obtains different maintenance modes
This；Network disaster recovery optimization calculating is carried out, and the power failure load during equipment fault is obtained, and equipment event is obtained based on the data
The loss of outage of barrier；Rule of thumb data, are the service age reduction factor assignment under different maintenance modes.
Preferably, the Strategies of Maintenance includes maintenance mode and repair time.
The beneficial effects of the present invention is：
The present invention sets up the Optimized model of power distribution network Strategies of Maintenance under repair based on condition of component background.By the solution general to the model
The Strategies of Maintenance (including maintenance mode and repair time) for quantifying can be obtained.Service work to domestic power distribution network has higher fitting
Ying Xing.
Description of the drawings
Fig. 1 is the variation diagram of fault rate before and after overhaul of the equipments；
Fig. 2 is that the initial solution to randomly generating carries out evaluation rubric figure.
Specific embodiment
The present invention will set up the Optimized model of power distribution network Strategies of Maintenance under repair based on condition of component background.By the solution to the model
The Strategies of Maintenance (including maintenance mode and repair time) that can will obtain quantifying, as shown in table 2.
Table 2
In table, Mk∈ { A class is overhauled, and B class is overhauled, and C class is overhauled, and is not overhauled }.
Tk∈{Tc, 2Tc……NTc}.Specific equipment and place are needed in view of overhaul of the equipments, when needing certain preparation
Between.It is assumed that TcIt is the most short maintenance time started determined according to real work situation.For example can be by TcIt is set as 1 week.
Below in conjunction with the accompanying drawings, embodiment is elaborated.
(1) Optimized model
Optimization aim：The life cycle management cost of overhaul is expected minimum.
Cj=CM(πj)+CR(πj) (2)
Wherein：L：The total degree of decision-making is carried out in the plant life cycle；After equipment carries out health status evaluation, inspection
The personnel of repairing need to carry out maintenance decision to the equipment.The evaluation cycle of health status is determined by the operating standard of each grid company.
CjFor major overhaul cost during jth time decision-making；
πjFor the Strategies of Maintenance that jth time maintenance is adopted；CM(πj) by executing the cost of overhaul use that the maintenance decision spends, no
The cost of overhaul with maintenance mode is different, can be obtained by carrying out statistics to overhaul of the equipments historical data；CR(πj) for adjacent twice
During decision-making, the breakdown loss risk that device fails are caused.
1) equipment health status prediction during jth time decision-making.
Affected by factors such as aging, abrasions, the fault rate of electrical equipment will be in increase trend with the time.In Reliability Engineering
In, frequent Weibull distribution is shown below describing the fault rate of electrical equipment rule over time：
M, η parameter can apply Marguardt method to be solved by the historical statistical data to electrical equipment.
On the other hand, research shows, there is exponential relationship between the health status of equipment and fault rate, as following formula institute
Show：
λ=KeC*H(4)
Wherein, H is the health status of equipment, and K is proportionality coefficient, and C is coefficient of curvature.Equally, the two parameters of K and C can
Obtained by carrying out data fitting to device history fault rate and health status historical evaluation result.
The relation that can be obtained by two above formula between the health status of equipment and time is as follows：
2) different impacts of the maintenance mode to equipment failure rate.
Overhaul of the equipments work can improve the overall performance of equipment, and its effect is equal to and elapses forward time enlistment age of equipment
A certain amount of, impact of the maintenance to the equipment enlistment age can be characterized by introducing " service age reduction factor α ", so as to can quantify to obtain
The change of fault rate before and after overhaul of the equipments, as shown in Figure 1.
For example overhaul in A point so that equipment enlistment age rollback α T1, then equipment failure rate be reduced to C point from B point.Fault rate
Curve is after C point as shown in curve C D.Different maintenance modes are different to the improvement of equipment performance, thus enlistment age rollback
Factor-alpha value is different.Generally, the value of the back-off factor of A class maintenance～C class maintenance is gradually reduced.And for equipment
Overhaul after fault, simply the fault function of restorer, equipment performance can't be improved, thus back-off factor value is 0.
For example：Certain class maintenance is taken in A point, such corresponding back-off factor of maintenance is α1, α1T1Represent after maintenance,
The enlistment age of equipment can reduce α1T1Year, namely mean after the completion of A point is overhauled, the fault rate of equipment is λ (T1-α1T1).In the same manner,
α2T2Represent that the enlistment age of equipment can reduce α in E point after certain class maintenance2T2Year.
3) equipment fault loss risk assessment.
Twice during decision-making, equipment may break down generation breakdown loss.
Tj：The time of jth time decision-making；
TM：The overhaul of the equipments time；
TE：Equipment health status evaluation cycle.
Twice during decision-making, the probability of device fails.Before and after maintenance
λ (t) is different, adjusts its curve shape by service age reduction factor.
CL：Trouble hunting expense, by obtaining to historical data statistics.
CS：Due to the loss of outage that equipment fault causes.From the angle of grid company, loss of outage includes that sale of electricity is damaged
Become estranged penalty cost two parts, this two parts is all related to power failure load.Can be determined by power distribution network Network Reconfiguration Algorithm should
The power failure load that equipment fault is caused.
(2) calculating process demonstration.
1) determine basic parameter.
Parameter in formula (3)～(5) is obtained according to device history fault rate, health status evaluating data.
The cost of overhaul of different maintenance modes is obtained according to device history overhaul data.
Network disaster recovery optimization calculating is carried out, the power failure load during equipment fault is obtained, and is obtained based on the data
The loss of outage of equipment fault.
Rule of thumb data, are the service age reduction factor assignment under different maintenance modes.
2) initial solution is randomly generated, as shown in table 3.
Table 3
3) solution is evaluated, as shown in Figure 2.
A. initial state：According to formula (3), the Cumulative Failure Rate between T=0 to TE can be obtained.Substitute in formula (6)
Obtain the major overhaul cost of initial state.
B. second decision-making：According to formula (5), the health to equipment during second decision-making is predicted, and according to prediction knot
Fruit determines Strategies of Maintenance.Assume predict the outcome for：Note, then the Strategies of Maintenance that selectes is：Start the maintenance of C class after 1 week.
During then from second decision-making to second decision-making, as centre has inspection operation, so before and after maintenance
The bathtub curve of equipment there occurs change.Assume in maintenance prior fault rate curve such as Fig. 1 shown in E-B, fault rate after maintenance
Curve is as shown in B C.According to this two segment faults rate curve, obtain from T=TETo 2TEBetween Cumulative Failure Rate.Substitute into formula
(6) breakdown loss risk during second decision-making is obtained in.
As second decision-making adopts C class maintenance mode, corresponding cost of overhaul use is to produced.
The major overhaul cost of second decision-making is obtained according to formula (2).
C. by that analogy, the major overhaul cost of each decision-making of the equipment under initial solution is obtained, is substituted in formula (1) and obtains
Evaluation result to initial solution.
4) genetic algorithm is applied, initial population is carried out intersecting, makes a variation and selection operation, obtains new solution.
5) continue iteration optimization, until result appraisal result is not becoming excellent, export optimal solution.
This embodiment is only the present invention preferably specific embodiment, but protection scope of the present invention is not limited thereto,
Any those familiar with the art the invention discloses technical scope in, the change or replacement that can readily occur in,
Should all be included within the scope of the present invention.Therefore, protection scope of the present invention should be with scope of the claims
It is defined.
Claims (4)
1. a kind of controller switching equipment Strategies of Maintenance optimization method, it is characterised in that comprise the steps：
S1, determines the basic parameter of controller switching equipment Strategies of Maintenance Optimized model according to device history data and empirical data；
S2, randomly generates the initial solution of the Strategies of Maintenance；
S3, evaluates the major overhaul cost of each decision-making of the controller switching equipment under initial solution, obtains the evaluation result of initial solution；
S4, applies genetic algorithm, initial population is intersected, made a variation and is selected, obtain new solution；
S5, continues new solution described in iteration optimization, until result appraisal result no longer becomes excellent, exports optimal solution.
2. method according to claim 1, it is characterised in that the device history data includes device history fault rate, strong
Health state evaluation data and device history overhaul data.
3. method according to claim 1, it is characterised in that step S1 also includes：According to device history overhaul data
Obtain the cost of overhaul of different maintenance modes；Network disaster recovery optimization calculating is carried out, power failure when obtaining the equipment fault is born
Lotus, and the loss of outage of equipment fault is obtained based on the data；Rule of thumb data, are the enlistment age rollback under different maintenance modes
Factor assignment.
4. method according to claim 1, it is characterised in that the Strategies of Maintenance includes maintenance mode and repair time.
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Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106647263A (en) * | 2016-12-01 | 2017-05-10 | 贵州电网有限责任公司电力科学研究院 | Power equipment maintenance decision-making method utilizing equal degradation theory and equipment risks |
| CN108182485A (en) * | 2017-12-05 | 2018-06-19 | 中国电力科学研究院有限公司 | A kind of power distribution network maintenance opportunity optimization method and system |
| CN108694447A (en) * | 2018-04-27 | 2018-10-23 | 云南电网有限责任公司 | Device maintenance method based on power scheduling overhaul data and device |
| CN108764494A (en) * | 2018-05-15 | 2018-11-06 | 中山职业技术学院 | Vehicle periodic maintenance manages system and its maintenance measure decision-making technique, computer readable storage medium |
| CN109472384A (en) * | 2018-04-09 | 2019-03-15 | 国网浙江省电力有限公司嘉兴供电公司 | A kind of controller switching equipment Strategies of Maintenance optimization method based on big data |
| CN110705809A (en) * | 2019-11-21 | 2020-01-17 | 国网湖南省电力有限公司 | Power distribution equipment inspection strategy optimization method and device and storage medium |
| CN112418499A (en) * | 2020-11-16 | 2021-02-26 | 广东电网有限责任公司 | Power grid maintenance planning optimization method and device and computer readable storage medium |
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2016
- 2016-09-27 CN CN201610855710.1A patent/CN106485596A/en active Pending
Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106647263A (en) * | 2016-12-01 | 2017-05-10 | 贵州电网有限责任公司电力科学研究院 | Power equipment maintenance decision-making method utilizing equal degradation theory and equipment risks |
| CN106647263B (en) * | 2016-12-01 | 2019-11-26 | 贵州电网有限责任公司电力科学研究院 | A kind of electric power apparatus examination decision-making technique Degradation Theories and equipment Risk such as utilizing |
| CN108182485A (en) * | 2017-12-05 | 2018-06-19 | 中国电力科学研究院有限公司 | A kind of power distribution network maintenance opportunity optimization method and system |
| CN109472384A (en) * | 2018-04-09 | 2019-03-15 | 国网浙江省电力有限公司嘉兴供电公司 | A kind of controller switching equipment Strategies of Maintenance optimization method based on big data |
| CN108694447A (en) * | 2018-04-27 | 2018-10-23 | 云南电网有限责任公司 | Device maintenance method based on power scheduling overhaul data and device |
| CN108694447B (en) * | 2018-04-27 | 2022-08-05 | 云南电网有限责任公司 | Equipment maintenance method and device based on power dispatching maintenance data |
| CN108764494A (en) * | 2018-05-15 | 2018-11-06 | 中山职业技术学院 | Vehicle periodic maintenance manages system and its maintenance measure decision-making technique, computer readable storage medium |
| CN110705809A (en) * | 2019-11-21 | 2020-01-17 | 国网湖南省电力有限公司 | Power distribution equipment inspection strategy optimization method and device and storage medium |
| CN110705809B (en) * | 2019-11-21 | 2022-07-05 | 国网湖南省电力有限公司 | Power distribution equipment inspection strategy optimization method and device and storage medium |
| CN112418499A (en) * | 2020-11-16 | 2021-02-26 | 广东电网有限责任公司 | Power grid maintenance planning optimization method and device and computer readable storage medium |
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Application publication date: 20170308 |