CN110189010A - A kind of high altitude localities converter power transformer differentiation O&M method and system based on genetic algorithm - Google Patents
A kind of high altitude localities converter power transformer differentiation O&M method and system based on genetic algorithm Download PDFInfo
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Abstract
The high altitude localities converter power transformer differentiation O&M method based on genetic algorithm that the invention discloses a kind of, it is characterised in that: be specifically implemented according to the following steps: S1: initialization of population is carried out, the set b of an individual is selectedi, the number of element is n in set, and 30 < n < 160, setting maximum number of iterations is T；S2: it indicates needing the problem of solving to be converted into chromosome, and carries out binary coding；S3: select the objective function of Optimized model as adaptation value function f (bi), and calculate adaptive value；S4: genetic manipulation is carried out；S5: convergence judgement: if the number of iterations reaches T, terminate and export the maximum individual of adaptive value；Otherwise S3 is returned；The present invention can satisfy the distribution of O&M resource and workload.
Description
Technical field
The present invention relates to a kind of differentiation O&M method and system of transformer, specifically a kind of height based on genetic algorithm
Altitude Regions converter power transformer differentiation O&M method and system.
Background technique
The dimension of high altitude localities converter power transformer O&M planning model is big, discrete and non-linear, to ensure High aititude
Under the premise of regional converter power transformer O&M meets various constraint conditions, economy reaches best, and can scientifically and rationally pacify
O&M exact date and the workload of O&M project are arranged, differentiation O&M must be carried out.
At present often with differentiation O&M method include integer programming method, linear programming technique and heuristics etc., but
It is that optimal solution theoretically can be obtained in integer programming method, but lacks to uncertainty and consider, is difficult to realize when design size is larger
It calculates；Linear programming technique calculating is easy, rapid, but faces the transformer equipment O&M plan of discrete nature, must do more complex change
Changing linearizes its objective function and constraint condition, and the precision of solving result is difficult to ensure；Not having to consideration in heuristic is
The no conditions such as linear, discrete, convenient, big and discrete suitable for the dimension O&M Plan Problem of the introducing of each constraint condition, but its
Optimal solution is only found in a certain range, is many times difficult to characterize the degree of correlation for obtaining solution with optimal solution, not can guarantee and obtain
Optimal solution is obtained, or even not can guarantee feasibility.
Summary of the invention
The present invention mainly solves the problems, such as of the existing technology, provides a kind of high altitude localities based on genetic algorithm and changes
Convertor transformer differentiation O&M method and system, being capable of reasonable distribution O&M resource and workload.
The present invention is achieved through technology:
A kind of high altitude localities converter power transformer differentiation O&M method based on genetic algorithm, it is characterised in that: specific
It follows the steps below to implement:
S1: initialization of population is carried out, the set b of an individual is selectedi, the method for selection is to be randomly generated, first in set
The number of element is n, 30 < n < 160；Setting maximum number of iterations is T；
S2: high altitude localities converter power transformer differentiation O&M problem, which is converted into chromosome, to be indicated, and carries out binary system
Coding；
S3: select the objective function of Optimized model as adaptation value function f (bi), and calculate each individual in per generation population
Adaptive value；The minimum for solving objective function is actually to seek the maximum for adapting to value function, the big expression breeding of adaptive value
The next generation it is more, the small population number of adaptive value can tail off, and individual may be eliminated disappearance；
S4: genetic manipulation is carried out；
S5: convergence judgement: if the number of iterations reaches T, terminate and export the maximum individual of adaptive value；Otherwise S3 is returned.
Further, the specific steps of the S4 include:
S401: adaptive value is set as selection criteria, to biIn individual selected；In the lesser choosing of algorithm initial setting
Selecting pressure enables search space to extend, and selection pressure is improved in the later period and is convenient for seeking and being optimal solution；
S402: to biPopulation intersected, mutation operation；Crossover probability is 0.25-0.75, and probability crosses conference and destroys Gao Shi
It should be worth, it is too small to increase search difficulty；Mutation probability is 0.01-0.2, and probability crosses the randomness that conference increases search, it is too small then
It is difficult to generate new individual.
A kind of high altitude localities converter power transformer differentiation operational system based on genetic algorithm, includes: input module, number
According to processing module, output module, display module and print module；It is characterized by: the input module and data processing module
Input terminal be electrically connected；The output end and output module of the data processing module are electrically connected；The output module difference
It is electrically connected with display module and print module；Genetic algorithm module built in the data processing module.
Further, the operational system further includes data memory module, the data memory module and output module electricity
Property connection.
Further, the input quantity in the input module is the state grade of transformer, risk class and relevant
The essential informations such as O&M expense.
Further, the output quantity in the output module is differentiation O&M result, O&M cost and fitness function
Value etc..
This system inputs essential information by input module, and initial monthly O&M plan is mapped as just by data processing module
Beginningization matrix；The O&M period of every equipment is mapped as chromosome coding；Differentiation O&M is carried out by genetic manipulation, and
Determine to calculate with convergence criterion and whether terminate；Finally by output module output results to data storage module, display module and
Print module.
The beneficial effects of the present invention are:
1, genetic algorithm, reasonable distribution O&M resource and workload are utilized；
2, O&M cost is reduced, the reliability of O&M is improved.
Detailed description of the invention
Fig. 1 is flow chart of the invention.
Fig. 2 is system block diagram of the invention.
Fig. 3 is genetic algorithm solution procedure figure of the invention.
Fig. 4 is comprehensive maintenance work amoun distribution of each O&M period in a specific embodiment of the invention.
Fig. 5 is the comprehensive tour O&M meter patrolled after dimension plan and optimization comprehensively original in a specific embodiment of the invention
The comparison diagram drawn.
Appended drawing reference meaning: 1, input module；2, data processing module；3, output module；4, display module；5, impression block
Block；6, genetic algorithm module；7, data memory module.
Specific embodiment
With reference to the accompanying drawings and examples, technical solution of the present invention is further explained.
As shown in Figure 1, a kind of high altitude localities converter power transformer differentiation O&M method based on genetic algorithm, is specifically pressed
Implement according to following steps:
S1: one matrix of initialization represents the initial monthly O&M planning chart of equipment；16 equipment are chosen as matrix
Ranks；52 periods were divided by 1 year, using 52 periods as the O&M period；Element in matrix is the O&M shape of equipment
State, if equipment k is in period t O&M, xkt=1, it is at this time O&M state；xkt=0 Shi Weiwei O&M state；N=50, T are set
=500；
The O&M period of S2: every equipment is chosen in (1,52) section, and O&M period maximum number is 52, every equipment fortune
Tie up the period binary coding be 6, equipment totally 16, thus chromosome length be 96；Since each O&M period only has 5
Working day, therefore need to only guarantee the equipment without 5 or more while be assigned to the same period；Two that binary string is represented
System number turns to decimal number；
S3: select the objective function of Optimized model as adaptation value function f (bi), then input the constraint item of O&M plan
Part, and calculate the adaptive value of each individual in per generation population；
S4: genetic manipulation is carried out:
S401: adaptive value is set as selection criteria, to biIn individual selected；
S402: to biPopulation intersected, mutation operation；Crossover probability is 0.5；Mutation probability is 0.08；
S5: convergence judgement: if the number of iterations reaches 500, terminating and export the maximum individual of adaptive value, as selected
Optimal sample.
As shown in Fig. 2, a kind of high altitude localities converter power transformer differentiation operational system based on genetic algorithm, comprising:
Input module 1, data processing module 2, output module 3, display module 4 and print module 5；Input module 1 and data processing mould
The input terminal of block 2 is electrically connected；The output end and output module 3 of data processing module 2 are electrically connected；Output module 3 respectively with
Display module 4 and print module 5 are electrically connected；Genetic algorithm module 6 built in data processing module 2.
Operational system further includes data memory module 7, and data memory module 7 and output module 3 are electrically connected.
Input quantity in input module 1 is the bases such as state grade, risk class and the relevant O&M expense of transformer
This information.
Output quantity in output module 3 is differentiation O&M result, O&M cost and fitness function value etc..
Essential information is inputted by input module 1, initial monthly O&M plan is mapped as initializing by data processing module 2
Matrix；The O&M period of every equipment is mapped as chromosome coding；By genetic manipulation carry out differentiation O&M, and with receipts
It holds back criterion and determines whether calculating terminates；Data storage module 7, display module 4 are outputted results to finally by output module 3 and are beaten
Impression block 5.
Mainly include the wage of operation maintenance personnel, the oil consumption of vehicle to the considerations of O&M expense in the present embodiment and lose expense,
If the wage of operation maintenance personnel every month is 3300 yuan, month 22 working days, i.e. the manpower expense of every workday is 150
Member, by one group of every 2 people, every group can make an inspection tour 2 high altitude localities converter power transformers for one day, then 1 High aititude of tour in everyone one day
Regional converter power transformer, the usage charges of O&M instrument tool etc. are 100 yuan every time, between the converter power transformer of high altitude localities away from
From 18 kilometers of average out to, 100 kilometers of fuel oils of vehicle are about 7-8 liter or so, and oil price is 7.5 yuan every liter, i.e. vehicle oil consumption takes every public affairs
In 0.6 yuan, vehicle by 100,000 yuan of car purchase fees of each car can with 10 years convert, the vehicle of every kilometer of equipment lose expense be 1 yuan, it is comprehensive
Upper analysis, comprehensive tour O&M expense of every high altitude localities converter power transformer are 278.8 yuan.
As shown in figure 3, the line of middle partial below indicates adaptive optimal control value, the line of side on the upper side indicates adaptive value mean value, Cong Tuzhong
It can be seen that in iteration initial stage adaptive optimal control value and adaptive value mean value all rapid decreases, represent unfeasible in the initial period
Solution, to 50 generations or so, the decrease speed of curve slows down, after the number of iterations increase backward, adaptive optimal control value and actual
The interval of adaptive value mean value is smaller and smaller, and actual value is more and more closer from optimal solution, after the number of iterations is more to certain, adaptive optimal control value
Hardly change with the increase of the number of iterations, finally tends to restrain, illustrate that the algorithm used herein is feasible and reasonable
, it should be noted that adaptive value mean value is as there is also certain fluctuations for the increase of the number of iterations, this is because a certain when reaching
After feasible optimal solution, genetic algorithm does not stop immediately and is to continue with and searches in feasible solution range, once occur more
It is optimal solution that excellent target, which just takes this value, avoids and falls into local optimum.
As can be seen from Figure 3 the adaptation value function of original O&M plan is about 235000, the adaptation value function after optimization
It is 186000, about reduces 20.9%, the equipment differentiation O&M planning optimization model for showing that the present invention establishes is effective.
Optimum results be 16 rows 52 column matrix, 16 indicate number of devices be 16,52 indicate every equipment O&M when
Section, the element in matrix is the O&M state of equipment, if equipment k is in period t O&M, xkt=1, it is at this time O&M state；xkt
=0 Shi Weiwei O&M state.
According to result above, the comprehensive O&M number for counting 52 O&M periods is shown in Fig. 4-5, from can in Fig. 4-5
O&M resource and workload allocations have been better meet out most reasonably to constrain.
Simply to illustrate that technical concepts and features of the invention, its purpose is allows in the art above-described embodiment
Those of ordinary skill cans understand the content of the present invention and implement it accordingly, and it is not intended to limit the scope of the present invention；It is all
It is the equivalent changes or modifications that the essence of content according to the present invention is made, should be covered by the scope of protection of the present invention.
Claims (4)
1. a kind of high altitude localities converter power transformer differentiation O&M method based on genetic algorithm, it is characterised in that: specifically press
Implement according to following steps:
S1: initialization of population is carried out, the set b of an individual is selectedi, the number of element is n in set, and 30 < n < 160, setting is most
Big the number of iterations is T；
S2: the problem of solving will be needed to be converted into chromosome expression, and carry out binary coding；
S3: select the objective function of Optimized model as adaptation value function f (bi), and calculate each individual in per generation population fit
It should be worth；
S4: genetic manipulation is carried out；
S5: convergence judgement: if the number of iterations reaches T, terminate and export the maximum individual of adaptive value；Otherwise S3 is returned.
2. the high altitude localities converter power transformer differentiation O&M method based on genetic algorithm as described in claim 1, special
Sign is: the specific steps of the S4 include:
S401: adaptive value is set as selection criteria, to biIn individual selected；
S402: to biPopulation intersected, mutation operation；Crossover probability is 0.25-0.75；Mutation probability is 0.01-0.2.
3. a kind of high altitude localities converter power transformer differentiation operational system based on genetic algorithm, includes: input module, data
Processing module, output module, display module and print module；It is characterized by: the input module and data processing module
Input terminal is electrically connected；The output end and output module of the data processing module are electrically connected；The output module respectively with
Display module and print module are electrically connected；Genetic algorithm module built in the data processing module.
4. the high altitude localities converter power transformer differentiation operational system based on genetic algorithm as claimed in claim 3, special
Sign is: the operational system further includes data memory module, and the data memory module and output module are electrically connected.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN111160607A (en) * | 2019-11-28 | 2020-05-15 | 泰康保险集团股份有限公司 | Medical maintenance institution scheduling method, system, equipment and medium based on evolutionary algorithm |
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| CN106405271A (en) * | 2016-08-23 | 2017-02-15 | 上海局放软件技术有限公司 | Monitoring data-based transformer state expert diagnosis method |
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| CN210244417U (en) * | 2019-05-22 | 2020-04-03 | 中国南方电网有限责任公司超高压输电公司大理局 | Differentiation operation and maintenance system for converter transformer in high altitude area |
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| CN105574589A (en) * | 2016-01-07 | 2016-05-11 | 西安工程大学 | Transformer oil chromatogram fault diagnosis method based on ecological niche genetic algorithm |
| CN106405271A (en) * | 2016-08-23 | 2017-02-15 | 上海局放软件技术有限公司 | Monitoring data-based transformer state expert diagnosis method |
| CN107977740A (en) * | 2017-11-23 | 2018-05-01 | 海南电网有限责任公司 | A kind of scene O＆M intelligent dispatching method |
| CN210244417U (en) * | 2019-05-22 | 2020-04-03 | 中国南方电网有限责任公司超高压输电公司大理局 | Differentiation operation and maintenance system for converter transformer in high altitude area |
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