CN108182485A - A kind of power distribution network maintenance opportunity optimization method and system - Google Patents
A kind of power distribution network maintenance opportunity optimization method and system Download PDFInfo
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Abstract
The present invention relates to a kind of power distribution network maintenance opportunity optimization method and system, the related data generation power distribution network maintenance solutions of acquisition each feeder plant of power distribution network；The power distribution network maintenance solution is set as chromosome, the state of electric distribution network maintenance model pre-established is solved to obtain the optimum maintenance interval of each feed line using genetic algorithm；The related data of each feeder plant of power distribution network includes：Power distribution network respectively presents the health index of built-in unit.Technical solution provided by the invention not only solves the problem of reliability prediction evaluation decision deviation is larger under small time scale, and can instruct, support the state of electric distribution network service work being combined with feeder line, substation or associate device, realization science, quantization, economic service technique rise to.
Description
Technical field
The present invention relates to power distribution network operation and maintenance and asset management technical field, and in particular to a kind of power distribution network overhauls opportunity
Optimization method and system.
Background technology
Power distribution network is directly closed as the final tache being directly connected in electric system with user, the operating status of controller switching equipment
It is to power supply reliability.Controller switching equipment maintenance is to ensure an important measures of its safe and stable operation, rational to arrange maintenance
It can not only ensure power supply reliability to the greatest extent, while also improve itself economic benefit of power grid enterprises.Due to distribution
The maintenance of equipment is needed by equipment self-operating state, load level, ambient weather, maintenance resource, grid structure and reliability
The restriction of factors such as ask；Therefore consider controller switching equipment health status, study the power distribution network using reliability and economy as target and examine
Decision model is repaiied to be of great significance.
The correlative study of state of electric distribution network maintenance decision model at present is with failure risk (reliability) and maintenance risk (warp
Ji property) it is starting point, following three classes can be summarized as：The first kind most preferably overhauls mesh from failure risk with equipment dependability
Mark.Second class is started with from economic index, to overhaul least risk as target.Third class is choosing comprehensively maintenance risk and failure
Risk, i.e., using reliability, economy this conflict equalization point as target.But the research of above-mentioned maintenance model is gone through with equipment
Based on history fault statistics data, the accumulation of one side historical statistical data is insufficient or relies on expertise, can lead to equipment fault
Rate estimation is inaccurate；On the other hand it when the method for operation of equipment changes, is set based on what historical failure data was extrapolated
Standby failure rate has been no longer complies with equipment actual conditions.
Existing controller switching equipment method for evaluating state has continued to use the state evaluation theory and method of power transmission and transforming equipment substantially, exists
Quantity of state collection is difficult, equipment state assessment item is numerous and diverse and is affected by artificial experience.
Invention content
State evaluation theory and the side of power transmission and transforming equipment are continued to use substantially to solve above-mentioned controller switching equipment method for evaluating state
Method, existence amount collects that difficult, equipment state assessment item is numerous and diverse and the problem of being affected by artificial experience, of the invention
Purpose is to provide a kind of power distribution network maintenance opportunity optimization method and system, carries out the change distribution based on equipment and health index
Equipment optimization Strategies of Maintenance is studied, and is reduced power distribution network operation risk, is promoted overall operation level.
The purpose of the present invention is what is realized using following technical proposals：
The present invention provides a kind of power distribution network maintenance opportunity optimization method based on equipment health index, and improvements exist
In：
Acquire the related data generation power distribution network maintenance solution of each feeder plant of power distribution network；
The power distribution network maintenance solution is set as chromosome, the state of electric distribution network pre-established is examined using genetic algorithm
The type of repairing a die is solved to obtain the optimum maintenance interval of each feed line；
The related data of each feeder plant of power distribution network includes：Power distribution network respectively presents the health index of built-in unit.
Further：The health index includes scoring section, and based on scoring by setting on each feeder line of the power distribution network
Standby divided rank and setting maintenance mode；It is described scoring section for (0,5].
Further：It is described that the power distribution network is respectively presented by built-in unit divided rank and setting maintenance mode packet based on scoring
It includes：
When health index is scored at [4,5], each feeder plant of power distribution network is in the normal condition of health；Maintenance mode pair
It should be routine inspection mode；
When health index is scored at [3,4) when, each feeder plant of power distribution network is in sub-health state；Maintenance mode corresponds to
Routine inspection mode；
When health index is scored at [2,3) when, each feeder plant of power distribution network is in the attention state of general defect；Maintenance side
Formula corresponds to light maintenance mode；
When health index is scored at [1,2) when, each feeder plant of power distribution network is in the abnormality of major defect；Maintenance side
Formula corresponds to overhaul mode；
When health index is scored at (0,1), each feeder plant of power distribution network is in the severe conditions of urgent defect；Maintenance side
Formula corresponds to replace DeviceMode.
Further：State of insulation of the health index including each feeder plant of the power distribution network, running environment, maintenance
Record and attachment status.
Further：The state of electric distribution network overhauls model, including：
The health index that built-in unit is respectively presented based on power distribution network establishes power distribution network maintenance object function；
Establish the power distribution network maintenance bound for objective function.
Further：The power distribution network maintenance object function is expressed as：
In formula：M --- the item number of feeder line in research range；N --- the controller switching equipment sum on single feeder line；Pji.m——
Jth item presents the cost of overhaul that built-in unit i is generated in maintenance process based on maintenance mode；λji(tj) --- on j-th strip feeder line
Equipment i is in tjThe probability of malfunction at moment；Pji.f--- economic loss caused by j-th strip feedback built-in unit i failures；μji(tj)——
Indicative function is expressed as：
In formula：Hji(tj) --- j-th strip presents built-in unit i in tjThe health index at moment.
Further：The j-th strip presents the cost of overhaul that built-in unit i is generated in maintenance process based on maintenance mode
Pji.mIt is expressed as：
Pji.m=Δ Tji.m·Cm (2)
In formula：
ΔTji.m--- controller switching equipment i uses the average duration of m classes maintenance on j-th strip feeder line；
Cm--- under m class maintenance modes, the mean unit time cost of overhaul.
Further：The power distribution network maintenance solution is set as chromosome, is matched using genetic algorithm to what is pre-established
Before State-Oriented Maintenance in Power Grid model is solved to obtain the optimum maintenance interval of each feed line, further include：Using modifying factor pair
Parameter in the object function of state of electric distribution network maintenance model is modified, and obtains each feeder plant of power distribution network in life cycle management
The situation of change of health status, the situation of change calculation expression of each feeder plant health status of power distribution network in the life cycle management
Formula is as follows：
In formula, ai(tj) it is health index modifying factor, including tjThe state of insulation of each feeder plant of moment power distribution network, fortune
Row environment, record of examination and attachment status；HIji(tj) it is tjThe health index of equipment i on moment j-th strip distribution feeder；
HIji0Health index for equipment i on initial time j-th strip distribution feeder.
Further：
The Pji.fIt is calculated by following formula：
Pji.f=Δ Tji·ΔLjiloss·Ctariff (5)
In formula：
ΔTji--- j-th strip presents built-in unit i since failure to the time to restore electricity；
ΔLjiloss--- the loss load after j-th strip feedback built-in unit i failures；
Ctariff--- average sale of electricity electricity price；
The λji(tj) be expressed as：
In formula：
Kji(τ), Cji(τ) --- the respectively meter of j-th strip feedback built-in unit i and the proportionality coefficient of enlistment age τ and curvature system
Number.
Further：The power distribution network maintenance bound for objective function includes：
Repair time constrains, and is expressed as：
tj=1,2 ..., 12 (7)
Equipment health index constrains, and is expressed as：
0 ＜ HIji(tj)≤5 (8)
Trend constraint is expressed as：
Sj(tj)≤Sjmax (9)
Feeder line pressure drop constrains, and is expressed as：
Ujmin≤ΔUj(tj)≤Ujmax (10)
Node voltage constrains, and is expressed as：
Ukmax≤Uk(tj)≤Ukmin (11)
It overhauls manpower to constrain with material resources, be expressed as：
In formula,
Sj(tj)、Sjmax--- respectively feeder line j is in tjThe practical trend value and the trend upper limit at moment；
ΔUj(tj)、Ujmax、Ujmin--- it is respectively tjIn the actual voltage-drop at moment feeder line j both ends and the pressure drop allowed,
Lower limit；
Uk(tj)、Ukmax、Ukmin--- respectively nodes k is in tjOn the virtual voltage at moment and the voltage allowed,
Lower limit；
R, R --- service personnel's number and maintenance teams and groups total number of persons respectively；
qi、Qi--- respectively overhaul the spare unit number of the equipment i of needs and the spare unit sum of equipment i.
Further：The power distribution network maintenance solution is set as chromosome, is matched using genetic algorithm to what is pre-established
State-Oriented Maintenance in Power Grid model is solved to obtain the optimum maintenance interval of each feed line, including：
Feedback number of lines in power distribution network maintenance solution binary coding is formed into chromosome, forms chromosome kind
Group；
Calculate the fitness function of each feed line in chromosome population；
Chromosome population is selected successively, is intersected and mutation operation；
Output reaches the optimal maintenance solution of the condition of convergence.
Further：Carry out numeric coding to chromosome, each chromosome represents a network overhaul scheme, in chromosome
Each word string value tjFor the repair time of corresponding feeder line, chromosome length is the feedback number of lines studied in power distribution network.
Further：Inverse of the fitness function for the sum of object function and penalty term, represents as follows：
Wherein, R (tj) --- the power distribution network maintenance object function of state of electric distribution network maintenance model, ωα--- the α distribution
The penalty factor of net maintenance bound for objective function, Tα--- the α power distribution network overhauls bound for objective function
Indicative function takes T when constraint satisfactionα=0；Otherwise it is Tα=1；tjRepresent the moment.
Further：The optimal maintenance solution for reaching the condition of convergence that exports is including exporting several fitness function values most
High or secondary highest chromosome, decoded back export the maintenance risk and failure of each scheme into power distribution network repair time scheme
Risk indicator.
Further：The related data of each feeder plant of power distribution network further includes network topology, load prediction data, inspection
Accomplish this and overhaul of the equipments time.
Further：The controller switching equipment includes：Distribution transformer, overhead transmission line, cable run and switch.
The present invention also provides a kind of power distribution networks to overhaul opportunity optimization system, thes improvement is that：
Acquisition module, for acquiring the related data of each feeder plant of power distribution network generation power distribution network maintenance solution；
Module is solved, for the power distribution network maintenance solution to be set as chromosome, using genetic algorithm to pre-establishing
State of electric distribution network maintenance model solved to obtain the optimum maintenance interval of each feed line；
The related data of each feeder plant of power distribution network includes：Power distribution network respectively presents the health index of built-in unit.
Further：Structure module is further included, the structure module includes：
First construction unit, for establishing power distribution network maintenance object function；
Second construction unit, for establishing power distribution network maintenance bound for objective function.
Further：The solution module, including：
Unit is formed, for the binary coding of the feedback number of lines in the power distribution network maintenance solution to be formed chromosome,
Form chromosome population；
Computing unit, for calculating the fitness function of each feed line in chromosome population；
Genetic manipulation unit, for being selected successively chromosome population, being intersected and mutation operation；
Output unit, for exporting the optimal maintenance solution for reaching the condition of convergence.
Compared with the immediate prior art, technical solution provided by the invention has an advantageous effect in that：
The related data generation power distribution network maintenance solution of present invention acquisition each feeder plant of power distribution network；The power distribution network is examined
Design of scheme is repaiied as chromosome, the state of electric distribution network maintenance model pre-established is solved to obtain every using genetic algorithm
The optimum maintenance interval of feeder line；The related data of each feeder plant of power distribution network includes：Power distribution network respectively presents the strong of built-in unit
Health index carries out the distribution equipment Optimal Maintenance strategy study based on equipment and health index, reduces distribution network operation
Risk promotes overall operation level.
The present invention establishes power distribution network maintenance opportunity Optimized model based on equipment health index, on the one hand solves hour
Between the problem of reliability prediction evaluation decision deviation is larger under scale；On the other hand guidance, support are with feeder line, substation or association
The service work that equipment is combined reduces unnecessary power failure, and Optimal Maintenance improves maintenance benefit, improves utilization rate of equipment and installations, supplies
Electric reliability and operation benefits, realization science, quantization, economic service technique rise to, for power distribution network become more meticulous overhaul management and
Science decision provides theory support, improves power grid overall operation management level.
Power distribution network based on equipment health index maintenance opportunity decision optimization model proposed by the invention, can be according to equipment
Health status neatly arranges the repair time, carries out specific aim maintenance to controller switching equipment, not only increases the reliable of power grid
Property, and power grid O＆M expense can be reduced, economic results in society are notable.
The present invention relies the accuracy calculated in equipment health index, therefore the acquisition of power distribution network operation information is to push away with accumulation
Into repair based on condition of component work basis, therefore state of electric distribution network maintenance implementation process in should as one of major tasks,
And consider how the problems such as reply status information of equipment lacks, information is inaccurate.
Description of the drawings
Fig. 1 is the power distribution network maintenance model solution flow chart provided by the invention based on genetic algorithm；
Fig. 2 is the A stations of specific embodiment provided by the invention, B stations 10kV distribution feeder communication relationship figures；
Fig. 3 is 3# feeder lines yearly peak load curve graph provided by the invention；
Fig. 4 is 5# feeder lines yearly peak load curve graph provided by the invention；
Fig. 5 is 3# feeder lines fitness value iterativecurve figure provided by the invention；
Fig. 6 is 5# fitness values iterativecurve figure provided by the invention；
Fig. 7 is the flow chart of optimization method provided by the invention.
Specific embodiment
The specific embodiment of the present invention is described in further detail below in conjunction with the accompanying drawings.
The following description and drawings fully show specific embodiments of the present invention, to enable those skilled in the art to
Put into practice them.Other embodiments can include structure, logic, it is electrical, process and other change.Embodiment
Only represent possible variation.Unless explicitly requested, otherwise individual component and function are optional, and the sequence operated can be with
Variation.The part of some embodiments and feature can be included in or replace part and the feature of other embodiments.This hair
The range of bright embodiment includes equivalent obtained by the entire scope of claims and all of claims
Object.Herein, these embodiments of the invention can individually or generally be represented that this is only with term " invention "
For convenience, it and if in fact disclosing the invention more than one, is not meant to automatically limit ranging from appointing for the application
What single invention or inventive concept.
The technical term that the present invention is used carries out description below：
First, the computational methods and grading standard of health index
(1) computational methods of health index
After power equipment health index concept originates from last century the eighties Britain power industry privatization, how to drop
Low operation of power networks and electric power apparatus examination expense simultaneously improve equipment operational reliability, how rationally determine equipment time between overhauls(TBO) into
For electric power enterprise focus of attention problem.Controller switching equipment health index is inspired in health physical examination：Controller switching equipment is by multiple
Component forms, and the health status of each component is often codetermined by several quantity of states, therefore the health index of controller switching equipment
It is synthesis result of the multi-part under the influence of multimode amount.
The EA companies of Britain propose the classical aging formula that health index changes with the enlistment age, it is believed that health index obedience refers to
Number attenuation law, the application (such as distribution network planning) being relatively suitble under big time scale.And practical health status and operation ring
The variation in border, the factors such as whether to overhaul closely related.
(2) grading standard of health index
EA companies of Britain health index scoring section is set as (0,10], and equipment state is divided into 4 grades and is provided
Health index is smaller, and equipment state degree is better.Also some scholars are carried out in application process to the evaluation criterion of EA companies
Modification, and provide that health index is smaller, equipment state is poorer.Grading standard is to health index and the no shadow of failure rate research
Ring, therefore present invention selection more meets the scoring of " score value is directly proportional to health status " of compatriots' thinking logic --- (0,
5] divide system, and provide that HI scores are smaller, equipment state is poorer；Vice versa, refers to table 1.The scoring is right《State's household electrical appliances
Net company distribution net equipment state evaluation directive/guide》The 4 kinds of equipment states divided in (Q/GDW 645-2011) carry out corresponding base
On plinth, " inferior health " state is increased, the reason is that finding there is a large amount of " inferior health " equipment in power distribution network by field research；
As can paying close attention in time to the kind equipment, then equipment holistic health level can be improved.
1 health status grading standard of table and maintenance mode
2nd, power distribution network maintenance present situation
According to above-mentioned standard, state of electric distribution network maintenance is divided into A, B, C, and five class of D, E, classification and definition are as shown in table 2.China
Southern Power Grid Company promotes power transmission and transformation equipment state monitoring and repair based on condition of component work since 2009, and is regarded as power grid
Enterprise improves asset operation efficiency and changes the important measure of development model.
2 repair based on condition of component of table is classified and definition
For traditional maintenance model there are many drawbacks such as frequency of power cut is more, overequipment maintenance, working efficiency are low,
And requirement of the user to power supply reliability improves, power distribution network uninterrupted operation service technique is used and is given birth to.By electric power to be repaired
Whether equipment is charged is divided into two kinds by service without power-off operation：The first is livewire work (" maintenance of E classes " i.e. in table 2), you can
Directly to carry out operation on alive circuit or equipment.Second is comprehensive uninterrupted operation, i.e., can not directly to equipment into
During row livewire work, Awaiting Overhaul equipment is isolated from distribution line by using mobile power, bypass equipment etc..It is all kinds of
Livewire work and comprehensive uninterrupted operation are to referring to table 3.
3 uninterrupted operation content of table compares
Embodiment one,
The present invention provides a kind of power distribution network maintenance opportunity optimization method based on equipment health index, flow chart such as Fig. 7 institutes
Show, include the following steps：
Acquire the related data generation power distribution network maintenance solution of each feeder plant of power distribution network；
The power distribution network maintenance solution is set as chromosome, the state of electric distribution network pre-established is examined using genetic algorithm
The type of repairing a die is solved to obtain the optimum maintenance interval of each feed line；
The related data of each feeder plant of power distribution network includes：Power distribution network respectively presents the health index of built-in unit.
The health index includes scoring section, and based on scoring by the equipment divided rank on each feeder line of the power distribution network
With setting maintenance mode；It is described scoring section for (0,5].
It is described that the power distribution network is respectively presented and maintenance mode includes by built-in unit divided rank based on scoring：
When health index is scored at [4,5], each feeder plant of power distribution network is in the normal condition of health；Maintenance mode pair
It should be routine inspection mode；
When health index is scored at [3,4) when, each feeder plant of power distribution network is in sub-health state；Maintenance mode corresponds to
Routine inspection mode；
When health index is scored at [2,3) when, each feeder plant of power distribution network is in the attention state of general defect；Maintenance side
Formula corresponds to light maintenance mode；
When health index is scored at [1,2) when, each feeder plant of power distribution network is in the abnormality of major defect；Maintenance side
Formula corresponds to overhaul mode；
When health index is scored at (0,1), each feeder plant of power distribution network is in the severe conditions of urgent defect；Maintenance side
Formula corresponds to replace DeviceMode.
The state of insulation of the health index including each feeder plant of the power distribution network, running environment, record of examination and attached
Part state.
The state of electric distribution network overhauls model, including：
First, the health index that built-in unit is respectively presented based on power distribution network establishes power distribution network maintenance object function
1st, object function
The purpose of state of electric distribution network maintenance is to reduce the operation risk of power grid enterprises, contains and overhaul risk and failure wind
The contradiction of danger this pair of " shifting ".Wherein, power distribution network maintenance risk refers to the cost of overhaul produced by taking different maintenance modes
Lead to the risk of a part of load of power grid direct losses due to maintenance is exited and exit because of overhaul of the equipments to cause with, controller switching equipment
Other controller switching equipments lose the synthesis of load risk.If using uninterrupted operation technology, load is lost caused by overhaul of the equipments
Loss is negligible, but corresponding maintenance expense and cost can rise.Distribution network failure risk is equipment failure rate and its event
The product of load loss is lost after barrier.Therefore, under limited resource constraints, two kinds of risks mutually restrict reached equalization point and are
The maintenance solution of power distribution network operation risk minimum.
Based on above-mentioned thought, the present invention has considered equipment in different time sections using single feeder line as research object
The factors such as health status, the maintenance mode used and classification, with the minimum target of power distribution network operation risk, are constructed and are set with distribution
Standby repair time (unit：Month) mathematical model of variable in order to control, it can be found under the premise of power distribution network safe operation best
Maintenance opportunity.Its object function is as follows：
(1) in formula,
M --- the item number of feeder line in research range.
N --- the controller switching equipment sum in single feeder line, including distribution transformer, overhead transmission line, cable run and all kinds of
Switch.
Pji.m--- j-th strip present built-in unit i in maintenance process when using different maintenance modes the maintenance that generates into
This, according to Q/GDW644-2011《Distribution Network Equipment overhauls directive/guide》In " Distribution Network Equipment maintenance principle " and " distribution net equipment examine
Repair project and classification " regulation, maintenance mode and repair method that the cost of overhaul is used depending on equipment under different health status and
Fixed (referring to table 4).
μji(tj) --- indicative function, with equipment in tjThe health index value at moment is related (referring to table 4).
Pji.f--- j-th strip presents built-in unit i economic losses caused by due to failure.
λji(tj) --- j-th strip presents built-in unit i in tjThe probability of malfunction at moment.
(1)Pji.m
Pji.m=Δ Tji.m·Cm (2)
(2) in formula,
ΔTji.m--- j-th strip feedback built-in unit i uses the average duration of m classes maintenance；
Cm--- under m class maintenance modes, the mean unit time cost of overhaul.CmValue under different maintenance modes refers to
Table 4.
(2)μji(tj)
(3) in formula,
Hji(tj) --- j-th strip presents built-in unit i in tjThe health index at moment, grading standard and maintenance mode
Refer to table 1.Daily tour and preventative maintenance pertains only to more portable measurement equipment or experimental apparatus, therefore D classes are overhauled
Cost can be ignored.In addition, the replacement of equipment belongs to planning scope, maintenance scope is not belonging to, therefore in this model not
Consider renewal cost.
The equipment health index calculation formula that the EA companies of Britain propose, it is believed that health index obeys exponential damping law,
And practical health status is not only related with insulation ag(e)ing, but also related with running environment, record of examination and attachment status etc..This hair
It is bright that these factors are modified and (refer to formula (4)) using modifying factor, provide the variation of health status in life cycle management
Situation.
In formula (4), ai(tj) for health index modifying factor, respectively tjThe state of insulation of moment equipment, running environment,
Record of examination and attachment status.Among being applied to power distribution network with all kinds of advanced sensors, domestic and international experts and scholars propose
A variety of health index computational methods based on controller switching equipment real-time detector data.
(3)Pji.f
Pji.f=Δ Tji·ΔLjiloss·Ctariff (5)
(5) in formula,
ΔTji--- j-th strip presents built-in unit i since failure to the time to restore electricity.
ΔLjiloss--- the loss load after j-th strip feedback built-in unit i failures can be verified by " N-1 " and be obtained.
Ctariff--- average sale of electricity electricity price.
(4)λji(tj)
(6) in formula,
Kji(τ), Cji(τ) --- the respectively meter of j-th strip feedback built-in unit i and the proportionality coefficient of enlistment age τ and curvature system
Number.Different types of controller switching equipment, proportionality coefficient are different from coefficient of curvature value.
The cost of overhaul of controller switching equipment under the different maintenance modes of table 4
2nd, the power distribution network maintenance bound for objective function is established：
(1) repair time constrains
tj=1,2 ..., 12 (7)
(2) equipment health index constrains：
0 ＜ HIji(tj)≤5 (8)
(3) trend constraint：
Sj(tj)≤Sjmax (9)
In formula (9),
Sj(tj)、Sjmax--- respectively feeder line j is in tjThe practical trend value and the trend upper limit at moment；
(4) feeder line pressure drop constrains：
Ujmin≤ΔUj(tj)≤Ujmax (10)
In formula (10),
ΔUj(tj)、Ujmax、Ujmin--- it is respectively tjIn the actual voltage-drop at moment feeder line j both ends and the pressure drop allowed,
Lower limit, according to DL/T5729-2016《Distribution network planning designing technique directive/guide》, take ± 7%.
(5) node voltage constrains：
Ukmax≤Uk(tj)≤Ukmin (11)
In formula (11),
Uk(tj)、Ukmax、Ukmin--- respectively nodes k is in tjOn the virtual voltage at moment and the voltage allowed,
Lower limit.
(6) maintenance manpower is constrained with material resources：
In formula (12),
R, R --- service personnel's number (generally 2~8 people) and maintenance teams and groups total number of persons respectively.
qi、Qi--- respectively overhaul the spare unit number of the equipment i of needs and the spare unit sum of equipment i.
Before being solved to state of electric distribution network maintenance model, further include：Using modifying factor to state of electric distribution network
The parameter overhauled in the object function of model is modified, and obtains each feeder plant health status of power distribution network in life cycle management
Situation of change, the situation of change calculation expression of each feeder plant health status of power distribution network is as follows in life cycle management：
In formula, ai(tj) for health index modifying factor, respectively tjThe state of insulation of moment distribution feeder equipment i, fortune
Row environment, record of examination and attachment status；HIji(tj) it is tjThe health index of equipment i on moment j-th strip distribution feeder；
HIji0For tjThe health index of equipment i on moment j-th strip distribution feeder；
J-th strip feedback built-in unit i economic loss P caused by due to failureji.fIt is expressed as：
Pji.f=Δ Tji·ΔLjiloss·Ctariff (5)
In formula：
ΔTji--- j-th strip presents built-in unit i since failure to the time to restore electricity；
ΔLjiloss--- the loss load after j-th strip feedback built-in unit i failures；
Ctariff--- average sale of electricity electricity price；
The j-th strip presents built-in unit i in tjThe probability of malfunction λ at momentji(tj) be expressed as：
In formula：
Kji(τ), Cji(τ) --- the respectively meter of j-th strip feedback built-in unit i and the proportionality coefficient of enlistment age τ and curvature system
Number.
2nd, model solution algorithm is overhauled based on genetic algorithm power distribution network
Included based on genetic algorithm power distribution network maintenance model solution step：The construction of parameter coding, initialization group formed,
Fitness function construction, genetic manipulation, control parameter setting etc., algorithm flow is as shown in Figure 1.
(1) data input
Initial data is inputted, including：Network topology, equipment health index, load prediction data, the cost of overhaul, equipment inspection
Time and genetic algorithm parameter are repaiied, such as crossover probability, mutation probability, population scale.
(2) chromosome coding initializes population
Carry out numeric coding to chromosome, each chromosome represents a network overhaul scheme, each word string in chromosome
Value tjRepair time (unit for corresponding feeder line：Month), chromosome length is the feedback number of lines studied in power distribution network.With binary system
Coding is compared, and chromosome length shortens 11 times, greatly improves the iteration speed for improving algorithm.Chromosome initial population scale
Must select size is suitable, for grid maintenance problem, typically no less than 60.
(3) constraints is verified
Load flow calculation is carried out to initial population, whether verification trend, voltage out-of-limit, whether voltage landing meets the requirements and
Whether equipment health index, maintenance resource are out-of-limit.
(4) it determines fitness function, calculates fitness value
Genetic algorithm is judged using fitness function as the selection strategy of " survival of the fittest " by individual adaptation degree letter value
" survival ability " of the individual in solution room.The bigger individual of fitness letter value " existence " chance is bigger；Conversely, fitness is small
Will be eliminated.In view of power distribution network repair schedule with the minimum target of operation risk object function, therefore, the present invention is with mesh
Scalar functions add the inverse of penalty coefficient as fitness function, and fitness function is as follows：
In formula (12),
R(tj) --- power distribution network overhauls object function, ωα--- the penalty factor of the α constraints, Tα--- α
The indicative function of constraints takes T when constraint satisfactionα=0；Otherwise it is Tα=1.
(5) selection operation is carried out to contemporary population
It is alternatively tactful using fitness function value rule of three (roulette wheel method), it chooses S chromosome and is put into mating
In pond or pairing library, mating pond is parents' individual sources for raising up seed.
(6) crossover operation is carried out to chromosome
Realize that the basic step intersected is：
1) parent chromosome is chosen from pairing library.Process is：Procedure below is repeated from i=1 to S：It is generated from [0,1]
Random number riIf ri≤PC(crossover probability), then selective staining body i is that parent is intersected.
2) crosspoint is selected.Crossover operation, which generally comprises, a little intersects, two-point crossover.Present invention selection a little intersects, tool
Gymnastics work is randomly to select a crosspoint in individual is gone here and there, and two individuals carry out part exchange before or after the point, with production
Raw new individual.
(7) mutation operation is carried out to chromosome
Realize that the basic step to make a variation is：
1) parent chromosome is selected from pairing library.According to similar to the process that parent is selected in crossover process.The present invention
Crossover probability P is adaptively adjusted using based on ideal adaptation angle valuecWith mutation probability Pm.When group is absorbed in local optimum,
By improving PcAnd PmThe state that population change is made to stagnate；When group tends to spread out, P can be reducedcAnd Pm。
2) change point is selected.Mutation operation makes a variation including a bit, 2 points of variations and multiple spot variation.The present invention is using some change
It is different, if to tjInto row variation, then t ' after making a variationj=13-tj.It is mainly in view of general Load in Summer peak period (7~September)
Uneasiness, which is listed and indexed, repaiies, and after variation, is just overhauled in spring (4~June).
(8) preservation of excellent chromosome
The preservation number of excellent chromosome is not The more the better.It preserves number and then be easy to cause too much and restrain in advance, hold
Easily it is absorbed in local optimum.Preserve number then influences convergence rate very little.Rule of thumb, the number of excellent chromosome typically constitutes from dyeing
13% or so of body sum.
(9) selection of the condition of convergence
Usually there are two types of methods for the selection of the condition of convergence.One kind is to meet constraints as algorithm stop criterion, the method
It is suitble to use in constraints number and more type.Another kind is fitted using reaching maximum iteration as algorithm stop criterion
For controlling variable less, the more single nonlinear model of constraints type.In maintenance model proposed by the invention only
Containing single control variable, constraints is less and is the constraint such as not, although in the longer chromosome of chromosome length effectively
Gene only accounts for one, thus it is contemplated that convergence rate is very fast, therefore using the latter as the condition of convergence.It is secondary when reaching greatest iteration
After number, stop iteration and be transferred to step (8), be otherwise transferred to step (3).
(10) it decodes and exports optimal maintenance solution
Export several fitness function value highests or secondary highest chromosome, decoded back is into power distribution network repair time side
Case, and the indexs such as maintenance risk and failure risk for exporting each scheme.
Embodiment two,
There are 2 10kV substations in survey region to customer power supply, wherein A stations, B station owner's varying capacities be respectively 3 ×
40MVA、 2×31.5MVA.A stations, B stations 10kV distribution feeder communication relationships are as shown in Figure 2.
Research range chooses A station 3# distribution feeders and B stations 5# distribution feeders in distribution, and wherein 3# feeder lines are overhead line
Road, 5# feeder lines are cable run, determine equipment to be checked according to each equipment health index situation, the equipment for being shown in Table 5 overstrikings；Accordingly
Load prediction curve as shown in Figure 3, Figure 4.
5 each unit type of table and health index score
For convenience of calculating, the maintenance duration of each maintenance mode and each job class takes the average value of its respective bins length；
By overhauling project cost Cj.mUnit from " member/time " conversion be " member/hour ", be shown in Table 6.
To same class distribution equipment malfunction repair time (unit：H) it is averaged, is shown in Table 7.To meeting inspection in research feeder line
The equipment for repairing condition carries out " N-1 criterion " verification, calculates equipment in each time and load is lost because caused by exiting failure.Maintenance
The maximum load of losing of each Awaiting Overhaul equipment " N-1 " is shown in Table 8 in period.
The maintenance duration and cost of 6 each maintenance mode of table
7 distinct device average time for repair of breakdowns of table
8 equipment fault maximum to be repaired of table loses load
In the present embodiment, Population in Genetic Algorithms scale N=100, P during crossover probability calculatesc1=0.9, Pc2=0.7, variation
P in probability calculationm1=0.1, Pm2=0.001.With reference to load prediction curve, 3# distribution feeders and 5# distribution feeders are adopted respectively
With two kinds of different maintenance solutions (being shown in Table 9)：
(1) using scheduled overhaul, according to plan the repair time make 3#, 5# distribution feeder are whole out of service to be examined respectively
It repaiies；
(2) adoption status is overhauled, and is overhauled using uninterrupted operation mode.It solves, obtains by using improved adaptive GA-IAGA
The optimal maintenance solution for going out 3# feeder lines and 5# feeder lines is shown in Table 10, and fitness value curve is shown in Fig. 5 and Fig. 6.As shown in Table 10：
(1) the 3# feeder lines repair based on condition of component time is postponed compared with the scheduled overhaul time.Because 3# feedback built-in unit starting health
State is preferable, and the health status to equipment during the original plan repair time remains to cope with current load level, therefore to maintenance
Plan is suitably delayed.
(2) the 5# feeder lines repair based on condition of component time is shifted to an earlier date compared with the scheduled overhaul time.Because " 115-118 " number electricity in 5# feeder lines
Cable road has been in " major defect " state, cannot be guaranteed safely to run to the scheduled overhaul time, therefore need schedule ahead
Maintenance is to avoid by loss of outage.
(3) repair based on condition of component scheme is compared to scheduled overhaul scheme, 3#, 5# feeder line makes overall risk have dropped 29.15% respectively,
31.83%：1) the 3# feeder lines repair based on condition of component time is delayed compared with the scheduled overhaul time, compared to the fixed year maintenance time of scheduled overhaul
Number, repair based on condition of component can reduce power distribution network year maintenance number when equipment state is preferable, save maintenance resource from the cost of overhaul
On reduce the overall risk of power distribution network；2) 5# feeder lines due to its cable run health status it is poor, the repair time is compared with scheduled overhaul
In advance, it arranges to reduce in this way to carry out the risk lost by serious dead electricity temporarily in load peak, be dropped from failure risk
The low overall risk of power distribution network；3) although the application of service without power-off operation reduces maintenance loss of outage, improves power distribution network
Power supply reliability, but also correspondingly increase the cost of overhaul.
9 repair based on condition of component scheme of table and scheduled overhaul time
The optimal maintenance solution comparison of 10 liang of feeder lines of table
Embodiment three,
Based on same inventive concept, the present invention also provides a kind of power distribution network maintenance opportunity based on equipment health index is excellent
Change system, including：
Acquisition module, for acquiring the related data of each feeder plant of power distribution network generation power distribution network maintenance solution；
Module is solved, for the power distribution network maintenance solution to be set as chromosome, using genetic algorithm to pre-establishing
State of electric distribution network maintenance model solved to obtain the optimum maintenance interval of each feed line；
The related data of each feeder plant of power distribution network includes：Power distribution network respectively presents the health index of built-in unit.
Further：Structure module is further included, the structure module includes：
First construction unit, for establishing power distribution network maintenance object function；
Second construction unit, for establishing power distribution network maintenance bound for objective function.
Further：The solution module, including：
Unit is formed, for the binary coding of the feedback number of lines in the power distribution network maintenance solution to be formed chromosome,
Form chromosome population；
Computing unit, for calculating the fitness function of each feed line in chromosome population；
Genetic manipulation unit, for being selected successively chromosome population, being intersected and mutation operation；
Output unit, for exporting the optimal maintenance solution for reaching the condition of convergence.
Power distribution network maintenance decision the present invention is based on equipment health index is a kind of new method of repair based on condition of component, is not only solved
The problem of reliability prediction evaluation decision deviation is larger under small time scale, and can instruct, support with feeder line, substation or
The service work that associate device is combined, realization science, quantization, economic service technique rise to.
It should be understood by those skilled in the art that, embodiments herein can be provided as method, system or computer program
Product.Therefore, the reality in terms of complete hardware embodiment, complete software embodiment or combination software and hardware can be used in the application
Apply the form of example.Moreover, the computer for wherein including computer usable program code in one or more can be used in the application
The computer program production that usable storage medium is implemented on (including but not limited to magnetic disk storage, CD-ROM, optical memory etc.)
The form of product.
The application is with reference to the flow according to the method for the embodiment of the present application, equipment (system) and computer program product
Figure and/or block diagram describe.It should be understood that it can be realized by computer program instructions each in flowchart and/or the block diagram
The combination of flow and/or box in flow and/or box and flowchart and/or the block diagram.These computers can be provided
Program instruction is to the processor of all-purpose computer, special purpose computer, Embedded Processor or other programmable data processing devices
To generate a machine so that the instruction performed by computer or the processor of other programmable data processing devices generates use
In the dress of function that realization is specified in one flow of flow chart or multiple flows and/or one box of block diagram or multiple boxes
It puts.
These computer program instructions, which may also be stored in, can guide computer or other programmable data processing devices with spy
Determine in the computer-readable memory that mode works so that the instruction generation being stored in the computer-readable memory includes referring to
Enable the manufacture of device, the command device realize in one flow of flow chart or multiple flows and/or one box of block diagram or
The function of being specified in multiple boxes.
These computer program instructions can be also loaded into computer or other programmable data processing devices so that counted
Series of operation steps are performed on calculation machine or other programmable devices to generate computer implemented processing, so as in computer or
The instruction offer performed on other programmable devices is used to implement in one flow of flow chart or multiple flows and/or block diagram one
The step of function of being specified in a box or multiple boxes.
The above embodiments are merely illustrative of the technical scheme of the present invention and are not intended to be limiting thereof, although with reference to above-described embodiment pair
The present invention is described in detail, those of ordinary skill in the art still can to the present invention specific embodiment into
Row modification either equivalent replacement these without departing from any modification of spirit and scope of the invention or equivalent replacement, applying
Within the claims of the pending present invention.
Claims (19)
1. a kind of power distribution network overhauls opportunity optimization method, it is characterised in that：
Acquire the related data generation power distribution network maintenance solution of each feeder plant of power distribution network；
The power distribution network maintenance solution is set as chromosome, mould is overhauled to the state of electric distribution network pre-established using genetic algorithm
Type is solved to obtain the optimum maintenance interval of each feed line；
The related data of each feeder plant of power distribution network includes：Power distribution network respectively presents the health index of built-in unit.
2. power distribution network as described in claim 1 overhauls opportunity optimization method, it is characterised in that：
The health index includes scoring section, and by the equipment divided rank on each feeder line of the power distribution network and is set based on scoring
Determine maintenance mode；It is described scoring section for (0,5].
3. power distribution network as claimed in claim 2 overhauls opportunity optimization method, it is characterised in that：It is described to be matched by described in based on scoring
Power grid respectively presents built-in unit divided rank and setting maintenance mode includes：
When health index is scored at [4,5], each feeder plant of power distribution network is in the normal condition of health；Maintenance mode corresponds to
Routine inspection mode；
When health index is scored at [3,4) when, each feeder plant of power distribution network is in sub-health state；Maintenance mode corresponds to inspection
Mode；
When health index is scored at [2,3) when, each feeder plant of power distribution network is in the attention state of general defect；Maintenance mode pair
It should be light maintenance mode；
When health index is scored at [1,2) when, each feeder plant of power distribution network is in the abnormality of major defect；Maintenance mode pair
It should be overhaul mode；
When health index is scored at (0,1), each feeder plant of power distribution network is in the severe conditions of urgent defect；Maintenance mode pair
It should be replacement DeviceMode.
4. power distribution network as claimed in claim 3 overhauls opportunity optimization method, it is characterised in that：The health index includes described
State of insulation, running environment, record of examination and the attachment status of each feeder plant of power distribution network.
5. power distribution network as described in claim 1 overhauls opportunity optimization method, it is characterised in that：The state of electric distribution network overhauls mould
Type, including：
The health index that built-in unit is respectively presented based on power distribution network establishes power distribution network maintenance object function；
Establish the power distribution network maintenance bound for objective function.
6. power distribution network as claimed in claim 5 overhauls opportunity optimization method, it is characterised in that：The power distribution network overhauls target letter
Number is expressed as：
In formula：M --- the item number of feeder line in research range；N --- the controller switching equipment sum on single feeder line；Pji.m--- j-th strip
Present the cost of overhaul that built-in unit i is generated in maintenance process based on maintenance mode；λji(tj) --- j-th strip feedback built-in unit i
In tjThe probability of malfunction at moment；Pji.f--- economic loss caused by j-th strip feedback built-in unit i failures；μji(tj) --- the property shown letter
Number, is expressed as：
In formula：Hji(tj) --- j-th strip presents built-in unit i in tjThe health index at moment.
7. power distribution network as claimed in claim 6 overhauls opportunity optimization method, it is characterised in that：The j-th strip feedback built-in unit i
The cost of overhaul P generated in maintenance process based on maintenance modeji.mIt is expressed as：
Pji.m=Δ Tji.m·Cm (2)
In formula：
ΔTji.m--- controller switching equipment i uses the average duration of m classes maintenance on j-th strip feeder line；
Cm--- under m class maintenance modes, the mean unit time cost of overhaul.
8. power distribution network as claimed in claim 5 overhauls opportunity optimization method, it is characterised in that：By the power distribution network maintenance solution
It is set as chromosome, the state of electric distribution network maintenance model pre-established is solved to obtain each feed line using genetic algorithm
Before optimum maintenance interval, further include：Using modifying factor to state of electric distribution network maintenance model object function in parameter into
Row is corrected, and is obtained the situation of change of each feeder plant health status of power distribution network in life cycle management, is matched in the life cycle management
The situation of change calculation expression of each feeder plant health status of power grid is as follows：
In formula, ai(tj) it is health index modifying factor, including tjState of insulation, the operation ring of each feeder plant of moment power distribution network
Border, record of examination and attachment status；HIji(tj) it is tjThe health index of equipment i on moment j-th strip distribution feeder；HIji0For
The health index of equipment i on initial time j-th strip distribution feeder.
9. power distribution network as claimed in claim 6 overhauls opportunity optimization method, it is characterised in that：
The Pji.fIt is calculated by following formula：
Pji.f=Δ Tji·ΔLjiloss·Ctariff (5)
In formula：
ΔTji--- j-th strip presents built-in unit i since failure to the time to restore electricity；
ΔLjiloss--- the loss load after j-th strip feedback built-in unit i failures；
Ctariff--- average sale of electricity electricity price；
The λji(tj) be expressed as：
In formula：
Kji(τ), Cji(τ) --- it is respectively the meter of j-th strip feedback built-in unit i and the proportionality coefficient and coefficient of curvature of enlistment age τ.
10. power distribution network as claimed in claim 5 overhauls opportunity optimization method, it is characterised in that：The power distribution network overhauls target
The constraints of function includes：
Repair time constrains, and is expressed as：
tj=1,2 ..., 12 (7)
Equipment health index constrains, and is expressed as：
0 ＜ HIji(tj)≤5 (8)
Trend constraint is expressed as：
Sj(tj)≤Sjmax (9)
Feeder line pressure drop constrains, and is expressed as：
Ujmin≤ΔUj(tj)≤Ujmax (10)
Node voltage constrains, and is expressed as：
Ukmax≤Uk(tj)≤Ukmin (11)
It overhauls manpower to constrain with material resources, be expressed as：
In formula,
Sj(tj)、Sjmax--- respectively feeder line j is in tjThe practical trend value and the trend upper limit at moment；
ΔUj(tj)、Ujmax、Ujmin--- it is respectively tjThe actual voltage-drop at moment feeder line j both ends and the pressure drop upper and lower limit allowed；
Uk(tj)、Ukmax、Ukmin--- respectively nodes k is in tjThe virtual voltage at moment and the voltage upper and lower limit allowed；
R, R --- service personnel's number and maintenance teams and groups total number of persons respectively；
qi、Qi--- respectively overhaul the spare unit number of the equipment i of needs and the spare unit sum of equipment i.
11. power distribution network as described in claim 1 overhauls opportunity optimization method, it is characterised in that：By the power distribution network maintenance side
Case is set as chromosome, and the state of electric distribution network maintenance model pre-established is solved to obtain each feed line using genetic algorithm
Optimum maintenance interval, including：
Feedback number of lines in power distribution network maintenance solution binary coding is formed into chromosome, forms chromosome population；
Calculate the fitness function of each feed line in chromosome population；
Chromosome population is selected successively, is intersected and mutation operation；
Output reaches the optimal maintenance solution of the condition of convergence.
12. power distribution network as claimed in claim 11 overhauls opportunity optimization method, it is characterised in that：Numerical value volume is carried out to chromosome
Code, each chromosome represent a network overhaul scheme, each word string value t in chromosomejFor the repair time of corresponding feeder line, dye
Colour solid length is the feedback number of lines studied in power distribution network.
13. power distribution network as claimed in claim 11 overhauls opportunity optimization method, it is characterised in that：The fitness function is mesh
The inverse of the sum of scalar functions and penalty term represents as follows：
Wherein, R (tj) --- the power distribution network maintenance object function of state of electric distribution network maintenance model, ωα--- the α power distribution network inspection
Repair the penalty factor of bound for objective function, Tα--- the property shown of the α power distribution network maintenance bound for objective function
Function takes T when constraint satisfactionα=0；Otherwise it is Tα=1；tjRepresent the moment.
14. power distribution network as claimed in claim 11 overhauls opportunity optimization method, it is characterised in that：The output reaches convergence item
The optimal maintenance solution of part includes exporting several fitness function value highests or secondary highest chromosome, and decoded back is into power distribution network
Repair time scheme, and export the maintenance risk of each scheme and failure risk index.
15. power distribution network as described in claim 1 overhauls opportunity optimization method, it is characterised in that：Each feeder line of power distribution network is set
Standby related data further includes network topology, load prediction data, the cost of overhaul and overhaul of the equipments time.
16. the power distribution network maintenance opportunity optimization method as described in any one of claim 1-10, it is characterised in that：The distribution
Equipment includes：Distribution transformer, overhead transmission line, cable run and switch.
17. a kind of power distribution network overhauls opportunity optimization system, it is characterised in that：
Acquisition module, for acquiring the related data of each feeder plant of power distribution network generation power distribution network maintenance solution；
Module is solved, for the power distribution network maintenance solution to be set as chromosome, is matched using genetic algorithm to what is pre-established
State-Oriented Maintenance in Power Grid model is solved to obtain the optimum maintenance interval of each feed line；
The related data of each feeder plant of power distribution network includes：Power distribution network respectively presents the health index of built-in unit.
18. power distribution network as claimed in claim 17 overhauls opportunity optimization system, it is characterised in that：Further include structure module, institute
Structure module is stated to include：
First construction unit, for establishing power distribution network maintenance object function；
Second construction unit, for establishing power distribution network maintenance bound for objective function.
19. power distribution network as claimed in claim 17 overhauls opportunity optimization system, it is characterised in that：The solution module, including：
Unit is formed, for the binary coding of the feedback number of lines in the power distribution network maintenance solution to be formed chromosome, is formed
Chromosome population；
Computing unit, for calculating the fitness function of each feed line in chromosome population；
Genetic manipulation unit, for being selected successively chromosome population, being intersected and mutation operation；
Output unit, for exporting the optimal maintenance solution for reaching the condition of convergence.
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| CN112232542A (en) * | 2020-08-19 | 2021-01-15 | 周宁 | Power grid maintenance mode auxiliary generation system based on load prediction |
| CN112149842A (en) * | 2020-09-04 | 2020-12-29 | 深圳供电局有限公司 | Power grid maintenance management method and device |
| CN114970904A (en) * | 2022-07-26 | 2022-08-30 | 中铁电气化勘测设计研究院有限公司 | Digital adjustment method for contact network operation and maintenance resources based on defect processing |
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| CN116109295A (en) * | 2023-04-07 | 2023-05-12 | 华能济南黄台发电有限公司 | Maintenance decision method based on power distribution terminal |
| CN116227759A (en) * | 2023-05-10 | 2023-06-06 | 天宇正清科技有限公司 | Maintenance time prediction method, device and equipment based on multi-equipment information |
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