CN105243239A - Method for composite insulator electric field optimization of power transmission line - Google Patents
Method for composite insulator electric field optimization of power transmission line Download PDFInfo
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- CN105243239A CN105243239A CN201510759768.1A CN201510759768A CN105243239A CN 105243239 A CN105243239 A CN 105243239A CN 201510759768 A CN201510759768 A CN 201510759768A CN 105243239 A CN105243239 A CN 105243239A
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Abstract
The invention discloses a method for composite insulator electric field optimization of a power transmission line. The method comprises the following steps of 1) carrying out numerical calculation on composite insulator electric field intensity in Maxwell software; 2) calling a genetic algorithm toolbox (GATBX) module of MATLAB software in Maxwell visual basic script (VBS); 3) optimizing umbrella skirt radius by using a single target genetic algorithm in the MATLAB software; and 4) obtaining optimized composite insulator electric field distribution by taking large radius, medium radius and small radius of an umbrella skirt as optimization variables. According to the method, the large radius, the medium radius and the small radius of the umbrella skirt of a composite insulator are optimized respectively by taking minimum field intensity Range-E and minimum field intensity maximum of gradients Max-Grad as single optimization targets, so that the composite insulator electric field distribution is more uniform.
Description
Technical field
The present invention relates to a kind of method of transmission line composite insulator electric Field Optimization, belong to composite insulator Electric Field Distribution optimisation technique field.
Background technology
In recent years, due to be combined into insulator have antifouling property good, light, be convenient to the advantages such as maintenance and be widely used in the electric system of China.And composite insulator is due to the low conductivity of its profile feature, hardware fitting structure and silastic material, make Potential distribution rapid decay from high-pressure side, such Potential distribution makes to create higher electric field at contiguous high-pressure side and earth terminal place.If surface electric field of insulator has exceeded corona inception field strength (0.45kV/mm), corona discharge will be produced.The chance that highfield causes insulator chain and gold utensil surface to produce corona discharge increases, and can run cause serious threat to electric power safety.For UHV (ultra-high voltage) and extra high voltage line, its electric pressure is high, electric field intensity is large, composite insulator Electric Field Distribution is more uneven compared with conventional line, therefore improves the gordian technique that composite insulator Electric Field Distribution is the development of ultra-high/extra-high voltage engineering external insulation equipment and safe operation thereof.
At present, the method for research composite insulator Electric Field Distribution optimization has a lot, such as: be optimized calculating by the distance of raising of the ring footpath to grading ring, caliber and ring, make rod insulator insulator electric field homogenising.But by optimizing umbrella skirt construction, the document in the hope of insulator electric field homogenising is but very few, therefore, the present invention relates to one and exist
maxwellin call the composite insulator umbrella skirt radius of matlab Sheffield genetic algorithm module (GATBX) to the Optimization Software of Electric Field Distribution, intend by optimizing full skirt radius, to obtain more uniform field strength distribution.
Summary of the invention
Technical matters to be solved by this invention is to provide a kind of method of transmission line composite insulator electric Field Optimization, minimum minimum as single optimization aim with magnetic field gradient maximal value Max_GradE using field intensity extreme difference Range_E respectively, the large, medium and small full skirt radius of composite insulator is optimized, makes composite insulator Electric Field Distribution more even.
For solving the problems of the technologies described above, the invention discloses a kind of method of transmission line composite insulator electric Field Optimization, it is characterized in that, comprise the following steps:
1) exist
maxwellin software, numerical evaluation is carried out to composite insulator electric field intensity, namely based on finite element theory, numerical evaluation is carried out to insulator electric field;
2) exist
maxwellcall in VBS
mATLABthe GATBX module of software;
3) exist
mATLABin software, single objective genetic algorithm is adopted to be optimized full skirt radius;
4) with large, medium and small three radiuses of full skirt for optimized variable, draw the composite insulator Electric Field Distribution of optimization.
In described step 2) in,
maxwellcall in VBS
mATLABthe GATBX module of software, specifically comprises the following steps:
21) initialization calculates.
Concrete finger initialization AnalysisData.xlsx computing parameter value (regular expression), write input variable information, i.e. variable name, unit and original value.
22) flow process turns
mATLAB, according to genetic algorithm iteration once, generate new population;
23) the new value of one group of variable is taken out;
24) composite characters string, covers
maxwellvariate-value;
25) (Analyzeall) is analyzed;
26) take out the value of output variable, separation unit, transfers numeral (regular expression) to;
27) input, output variable value write AnalysisData.xlsx;
28) judge whether population data circulation terminates, if do not terminate, proceeds to step 23);
29) judge whether population number iteration terminates, if do not terminate, proceed to step 22);
210) call flow terminates.
In described step 3), adopt single objective genetic algorithm to be optimized full skirt radius, specifically comprise the following steps:
31) initialization calculates;
32) fitness value is distributed;
33) select, intersect, make a variation, change;
34) calculate filial generation target fitness value, data are imported into
mATLAB;
35) in heavy intron generation, is to parent;
36) obtain often for optimum solution and sequence number;
37)
mATLABvoice message " kth completes for population iteration ";
38) judge whether population number iteration terminates, if do not terminate, proceed to step 32);
39) draw the evolution graph separated, preserve optimum solution and image.
Described step 31) in, initialization calculates and comprises the following steps:
311):
mATLABobject initialization;
312) optimum configurations;
313) optimizing result initial value is defined, defined range describer;
314) initial population creates;
315) calculate initial population fitness value, data are imported into
mATLAB;
316) voice message " initialization of population completes ".
The beneficial effect that the present invention reaches:
maxwellextraordinary finite element software insulator being carried out to Electric Field Numerical Calculation, although software inhouse with Parametric Analysis optimize module, optimize module single, the optimization task of complex condition cannot be adapted to, and map data and display mode limited.In order to overcome this shortcoming, herein for adopting
mATLABoptimization module powerful in software.
mATLABas current classic computational science software, in algorithm development, data visualization, data analysis, numerical evaluation etc., have original performance, the encapsulation scale of its algoritic module, diversity and extensibility are that other programming languages are difficult to reach.Therefore, for optimizing full skirt size further, to obtain more excellent field strength distribution, this software application is outside
mATLABsheffield genetic algorithm module (GATBX) in software is to eliminate
maxwellthe limitation of internal module.The core of genetic algorithm optimization is the setting of fitness function, and fitness to use
mATLABsimulation, must pass through
maxwellcalculate, the present invention passes through
maxwellin call
mATLABsheffield genetic algorithm module (GATBX) achieves the optimization of genetic algorithm to insulator umbrella radius.Because all external algorithm realize all using
mATLABand the module of maturation, therefore ensure that the correctness of software, decrease the scramble time.
The present invention with large, medium and small three radiuses of full skirt for optimized variable, minimum minimum as single optimization aim with magnetic field gradient maximal value Max_GradE using composite insulator electric field intensity extreme difference Range_E respectively, ask for the full skirt radius optimum solution that insulator electric field is more evenly distributed.
Accompanying drawing explanation
Fig. 1 system chart of the present invention;
Fig. 2 interface routine process flow diagram;
Fig. 3 GATBX realizes the population iterative process figure of full skirt;
Fig. 4 population iteration initialization process flow diagram.
Fig. 5 carries out field strength distribution corresponding to optimized parameter that GATBX optimized Genetic Algorithm iteration obtains to Range_E.
Fig. 6 carries out field strength distribution corresponding to optimized parameter that GATBX optimized Genetic Algorithm iteration obtains to Max_GradE.
Embodiment
Below in conjunction with accompanying drawing, the present invention is further described.
System chart of the present invention as shown in Figure 1.The method of a kind of transmission line composite insulator electric Field Optimization of the present invention comprises altogether four major parts:
maxwellin software, numerical evaluation is carried out to composite insulator electric field intensity; ?
maxwellcall in VBS
mATLABthe GATBX module of software; ?
mATLABin software, single objective genetic algorithm is adopted to be optimized full skirt radius; With large, medium and small three radiuses of full skirt for optimized variable, draw the composite insulator Electric Field Distribution of optimization.
Step 1 exists
maxwellin software, numerical evaluation is carried out to composite insulator electric field intensity, namely based on finite element theory, numerical evaluation is carried out to insulator electric field
Step 2 exists
maxwellcall in VBS
mATLABthe GATBX module of software.As shown in Figure 2, ten steps are specifically divided into:
1) initialization calculates;
Concrete finger initialization AnalysisData.xlsx computing parameter value (regular expression), write input variable information, i.e. variable name, unit and original value.
2) flow process turns
mATLAB, according to genetic algorithm iteration once, generate new population;
3) the new value of one group of variable is taken out;
4) composite characters string, covers
maxwellvariate-value;
5) (Analyzeall) is analyzed;
6) take out the value of output variable, separation unit, transfers numeral (regular expression) to;
7) input, output variable value write AnalysisData.xlsx;
8) judge whether population data circulation terminates, if do not terminate, proceeds to step 3);
9) judge whether population number iteration terminates, if do not terminate, proceed to step 2);
10) call flow terminates.
Step 3 exists
mATLABin software, single objective genetic algorithm is adopted to be optimized full skirt radius.As shown in Figure 3, nine steps are specifically divided into:
1) initialization calculates.
2) fitness value is distributed;
3) select, intersect, make a variation, change;
4) calculate filial generation target fitness value, data are imported into
mATLAB;
5) in heavy intron generation, is to parent;
6) obtain often for optimum solution and sequence number;
7)
mATLABvoice message " kth completes for population iteration ";
8) judge whether population number iteration terminates, if do not terminate, proceed to step 2);
9) draw the evolution graph separated, preserve optimum solution and image.
Initialization in step 3 calculates, and as shown in Figure 4, is specifically divided into six steps:
1)
mATLABobject initialization;
2) optimum configurations.
3) optimizing result initial value is defined, defined range describer.
4) initial population creates.
5) calculate initial population fitness value, data are imported into
mATLAB;
6) voice message " initialization of population completes ".
Step 4 for optimized variable, draws the composite insulator Electric Field Distribution of optimization with large, medium and small three radiuses of full skirt.
embodiment:
University of Sheffield genetic algorithm module GATBX uses M language compilation, for the user using genetic algorithm to deal with problems provides extensively various utility function, when genetic algorithm function is encoded, employ senior selection opertor, senior recombination operator and Discrete mutation operator.The executive mode of several operators that the present invention mainly uses comprises selection opertor select, crossover operator recombin, mutation operator mut, heavy update reins.
In order to enable user understand in the long operational process of algorithm and control calculating progress, use voice message to be necessary, the present invention uses Microsoft voice com component SAPI(TheMicrosoftSpeechAPI) realize.
Arranging population quantity is 10, and iterations was 200 generations, carries out full skirt optimizing to field intensity extreme difference Range_E, and optimum full skirt parameter is: it is rice that large, medium and small full skirt variate-value is respectively 0.0927,0.1011,0.0456(unit).The arrangement of this group full skirt is " middle size is large " from top to bottom.Optimum solution appears in the 92nd generation population, and corresponding optimum field intensity extreme difference value is 2.4 × 10
7, compared with the initial value in table 1, single objective genetic algorithm makes field intensity extreme difference value optimize 24.1%.Field strength distribution is drawn as shown in Figure 5 with the optimum full skirt parameter of this group.
The target function value of front and back 1/4th simplified models optimized by table 1
| Max_GradE | Range_E | |
| Under initial parameter | 34289038360 | 31638868 |
| After GATBX optimizes | 2.4×10 7 | 1.93×10 10 |
Again with magnetic field gradient maximal value Max_GradE for objective function, carry out full skirt optimizing.Optimum full skirt parameter is: it is rice that large, medium and small full skirt variate-value is respectively 0.0884,0.0696,0.0541(unit).Optimum solution appears in the 174th generation population, and corresponding optimum field intensity extreme difference value is 1.93 × 10
10, compared with the initial value in table 1, single objective genetic algorithm makes field intensity extreme difference value optimize 43.7%.Field strength distribution is drawn as shown in Figure 6 with the optimum full skirt parameter of this group.
Claims (5)
1. a method for transmission line composite insulator electric Field Optimization, comprises the following steps:
(1), exist
maxwellin software, carry out numerical evaluation to composite insulator electric field intensity, described numerical evaluation is based on finite element theory;
(2), exist
maxwellcall in VBS
mATLABthe GATBX module of software;
(3), exist
mATLABin software, single objective genetic algorithm is adopted to be optimized full skirt radius;
(4), with large, medium and small three radiuses of full skirt for optimized variable, the composite insulator Electric Field Distribution of optimization is drawn.
2. the method for a kind of transmission line composite insulator electric Field Optimization according to claim 1, is characterized in that: in described step (2)
maxwellcall in VBS
mATLABthe GATBX module of software, concrete steps refer to:
(2a), initialization calculates;
(2b), flow process turns
mATLAB, according to genetic algorithm iteration once, generate new population;
(2c) the new value of one group of variable, is taken out;
(2d), composite characters string, cover
maxwellvariate-value;
(2e), analyze;
(2f), take out the value of output variable, separation unit, transfers numeral to;
(2g), input, output variable value write AnalysisData.xlsx;
(2h), judge whether population data circulation terminates, if do not terminate, proceeds to step (2c);
(2i), judge whether population number iteration terminates, if do not terminate, proceed to (step 2b);
(2j), call flow terminates.
3. the method for a kind of transmission line composite insulator electric Field Optimization according to claim 2, it is characterized in that: the initialization of described step (2a) calculates, specifically refer to initialization AnalysisData.xlsx computing parameter value, write input variable information, i.e. variable name, unit and original value.
4. the method for a kind of transmission line composite insulator electric Field Optimization according to claim 1, is characterized in that: in described step (3)
mATLABin software, the step adopting single objective genetic algorithm to be optimized full skirt radius is as follows:
(4a), initialization calculates;
(4b), fitness value is distributed;
(4c), select, intersect, make a variation, change;
(4d), calculate filial generation target fitness value, data are imported into
mATLAB;
(4e), in heavy intron generation, is to parent;
(4f), obtain often for optimum solution and sequence number;
(4g),
mATLABvoice message " kth completes for population iteration ";
(4h), judge whether population number iteration terminates, if do not terminate, proceed to step (4b);
(4i), draw the evolution graph separated, preserve optimum solution and image.
5. the method for a kind of transmission line composite insulator electric Field Optimization according to claim 4, is characterized in that: described step (4a) initialization calculates, and concrete steps refer to:
(5a),
mATLABobject initialization;
(5b), optimum configurations;
(5c), optimizing result initial value is defined, defined range describer;
(5d), initial population creates;
(5e), calculate initial population fitness value, data are imported into
mATLAB;
(5f), voice message " initialization of population completes ".
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105912812A (en) * | 2016-04-29 | 2016-08-31 | 南方电网科学研究院有限责任公司 | Method and apparatus for determining umbrella skirt parameters of support insulator |
| CN108875225A (en) * | 2018-06-25 | 2018-11-23 | 西安交通大学 | Regulation method for insulator and its surface field in GIS/GIL |
| CN109101716A (en) * | 2018-08-06 | 2018-12-28 | 南方电网科学研究院有限责任公司 | A kind of the influence emulation mode and device of bushing shell for transformer external insulation electric field |
| CN109494029A (en) * | 2018-12-29 | 2019-03-19 | 天津大学 | A kind of superconduction GIL insulator electric field homogenization process based on surface graded conductance |
| CN114005628A (en) * | 2021-09-29 | 2022-02-01 | 云南电网有限责任公司电力科学研究院 | Preparation method of gradient insulating part |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103411970A (en) * | 2013-07-17 | 2013-11-27 | 同济大学 | Alternating current transmission line insulator contamination condition detection method based on infrared thermography |
| CN104166761A (en) * | 2014-08-13 | 2014-11-26 | 南京理工大学 | Transmission line mechanical deicing sequence optimizing method based on genetic algorithm |
| CN105005675A (en) * | 2015-08-11 | 2015-10-28 | 河海大学常州校区 | Composite insulator electric field optimization method based on multi-target genetic algorithm |
-
2015
- 2015-11-10 CN CN201510759768.1A patent/CN105243239A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103411970A (en) * | 2013-07-17 | 2013-11-27 | 同济大学 | Alternating current transmission line insulator contamination condition detection method based on infrared thermography |
| CN104166761A (en) * | 2014-08-13 | 2014-11-26 | 南京理工大学 | Transmission line mechanical deicing sequence optimizing method based on genetic algorithm |
| CN105005675A (en) * | 2015-08-11 | 2015-10-28 | 河海大学常州校区 | Composite insulator electric field optimization method based on multi-target genetic algorithm |
Non-Patent Citations (3)
| Title |
|---|
| F.MUÑOZ: "An intelligent computing technique to estimate the magnetic field generated by overhead transmission lines using a hybrid GA-Sx algorithm", 《ELECTRICALPOWERANDENERGYSYSTEMS》 * |
| 张林俊: "UHV复合绝缘子均压环结构优化设计算法分析", 《重庆市电机工程学会》 * |
| 苗红霞: "采用多目标遗传算法优化复合绝缘子伞裙半径", 《电子测试》 * |
Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105912812A (en) * | 2016-04-29 | 2016-08-31 | 南方电网科学研究院有限责任公司 | Method and apparatus for determining umbrella skirt parameters of support insulator |
| CN105912812B (en) * | 2016-04-29 | 2019-04-23 | 南方电网科学研究院有限责任公司 | A kind of method and apparatus of the full skirt parameter of determining support insulator |
| CN108875225A (en) * | 2018-06-25 | 2018-11-23 | 西安交通大学 | Regulation method for insulator and its surface field in GIS/GIL |
| CN109101716A (en) * | 2018-08-06 | 2018-12-28 | 南方电网科学研究院有限责任公司 | A kind of the influence emulation mode and device of bushing shell for transformer external insulation electric field |
| CN109101716B (en) * | 2018-08-06 | 2021-07-30 | 南方电网科学研究院有限责任公司 | Method and device for simulating influence of external insulation electric field of transformer bushing |
| CN109494029A (en) * | 2018-12-29 | 2019-03-19 | 天津大学 | A kind of superconduction GIL insulator electric field homogenization process based on surface graded conductance |
| CN109494029B (en) * | 2018-12-29 | 2020-04-28 | 天津大学 | Superconducting GIL insulator electric field homogenization method based on surface gradient conductance |
| CN114005628A (en) * | 2021-09-29 | 2022-02-01 | 云南电网有限责任公司电力科学研究院 | Preparation method of gradient insulating part |
| CN114005628B (en) * | 2021-09-29 | 2022-09-16 | 云南电网有限责任公司电力科学研究院 | Preparation method of gradient insulating part |
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