CN110516359B - Power transformer electrostatic ring structure optimization method based on APDL and response surface method - Google Patents
Power transformer electrostatic ring structure optimization method based on APDL and response surface method Download PDFInfo
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Abstract
The invention discloses a power transformer electrostatic ring structure optimization method based on an APDL and response surface method, which comprises the following steps: establishing a finite element model of the electrostatic ring of the power transformer according to ANSYS parametric modeling language APDL; setting the variation range of parameter variables influencing the maximum electric field strength by taking the reduction of the maximum electric field strength as an optimization target; performing a response surface test by using a central composite design method; the effectiveness of the response surface model is checked, and the fitting degree and the prediction capability of the model are analyzed; and obtaining the optimized parameter variable and the maximum electric field intensity value by adopting a mathematical programming method. The power transformer electrostatic ring structure optimization method based on the APDL and the response surface method provided by the invention avoids the problems of repeated manual modeling, subdivision, solving and optimization of each variable in the optimized structure in the prior art, improves the optimization efficiency, and can perform optimization design on the power transformer electrostatic ring structures of different grades.
Description
Technical Field
The invention relates to the technical field of transformer design, in particular to a power transformer electrostatic ring structure optimization method based on an APDL (active passive display device) and a response surface method.
Background
As the voltage class and capacity of power transformers gradually increase, the problem of electrical insulation of power transformers becomes more severe. The distribution of an insulated electric field is determined by the insulation structure of the power transformer, and how to optimally design the main insulation structure of the power transformer becomes the key for ensuring the safe and stable operation of the power transformer. Therefore, to ensure the rationality and reliability of the main insulation structure of the power transformer, experimental research, analysis and calculation of the electric field distribution in the power transformer are necessary.
At present, the method for optimally designing the structure of the power transformer mainly comprises the following steps: analytical formula method, sensitivity analysis method and intelligent optimization method (such as genetic algorithm and particle swarm algorithm). The analytic formula method is suitable for models with simpler structures, the analytic formula is obtained through theoretical derivation, electric field analysis is conveniently and rapidly carried out, and the analytic formula method cannot be adopted for complex model structures. The sensitivity analysis method comprises a difference method, a half-analysis method and a full-analysis method, the difference method is simple in implementation process, but is poor in precision when the independent variable step length is large, the derivation difficulty of the half-analysis method and the analysis method is large, the derivation process is complex, the calculation time is increased, and the optimization efficiency is low. When the intelligent optimization method is used for processing optimization problems, a large number of modeling, simulation and optimization programs need to be repeatedly called, optimization efficiency is influenced, and if a fitness function is selected improperly, local search capability is poor, and search efficiency is reduced.
Disclosure of Invention
The invention aims to provide a power transformer electrostatic ring structure optimization method based on APDL and a response surface method, which solves the problems of repeated manual modeling, subdivision and solving of an optimized structure and optimization of variables in the prior art, improves optimization efficiency, and can be used for optimally designing electrostatic ring structures of power transformers in different grades.
In order to achieve the purpose, the invention provides the following scheme:
a power transformer electrostatic ring structure optimization method based on APDL and a response surface method comprises the following steps:
step 1: establishing a finite element model of the electrostatic ring of the power transformer according to ANSYS parametric modeling language APDL;
step 2: setting a parameter variation range influencing the maximum electric field strength by taking the reduction of the maximum electric field strength as an optimization target;
and step 3: performing a response surface test by using a central composite design method;
and 4, step 4: checking the effectiveness of the response surface model, and analyzing the fitting degree and the prediction capability of the model;
and 5: and obtaining the optimized variable parameter and the maximum electric field intensity value by adopting a mathematical programming method.
Optionally, in step 1, establishing a finite element model of the transformer electrostatic ring according to ANSYS parameterized modeling language APDL, specifically including:
and compiling an ANSYS parameterized programming command, establishing a finite element model of the electrostatic ring of the power transformer, and automatically carrying out the structure modeling and subdivision of the power transformer, and the calculation of the applied boundary conditions and the electric field intensity.
Optionally, in step 2, with reducing the maximum electric field strength as an optimization target, setting a parameter variation range that affects the maximum electric field strength, specifically including:
according to the structure and size parameter limitation of the electrostatic ring of the power transformer, the curvature radius R1 of the electrostatic ring, the distance h from the upper surface of the electrostatic ring to the first paper board on the electrostatic ring, the thickness s of the insulating layer and the size variation range of the initial position w of the upper section of the electrostatic ring are respectively set.
Optionally, in step 3, the response surface test is performed by using a central composite design method, which specifically includes:
normalizing each parameter variable, then selecting a test point by adopting a central composite design method, designing a combination of each parameter variable with different values, obtaining each test result through mutual calling of ANSYS and MATLAB, establishing an initial response surface model, and generally adopting a form of a second-order polynomial:
wherein y is an objective function, β 0 ，β j ，β jj And beta ij Is a polynomial coefficient, x j Is a parameter variable, and n is the number of the parameter variables.
Optionally, in step 4, the effectiveness of the response surface model is checked, and the fitting degree and the prediction capability of the model are analyzed, which specifically includes:
and (3) adopting Design-Expert10.0 regression analysis software to perform variance analysis, diagnostic analysis and perturbation analysis on the initial response surface model, and eliminating irrelevant factors by checking the significance of each variable and a secondary term to obtain a final response surface model.
Optionally, in step 5, obtaining the optimized parameter and the maximum electric field strength value by using a mathematical programming method specifically includes:
and solving the final response surface model by adopting a mathematical programming method to obtain the maximum electric field intensity optimal value under the mutual matching of all parameter variables, and determining all structural parameters of the power transformer electrostatic ring structure model.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects: according to the power transformer electrostatic ring structure optimization method based on the APDL and the response surface method, the structural model is established through the APDL command stream, the approximate function expression between the objective function and the variable is constructed, the objective function which is originally implicit is shown, meanwhile, the influence of each variable on the optimization target is considered, and the problem that in the prior art, the optimization structure is repeatedly and manually modeled, split and solved, and each variable is optimized is solved, so that the optimization efficiency is improved, and the method can be used for the structural optimization design of the power transformer electrostatic ring with any voltage level.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without inventive exercise.
FIG. 1 is a flow chart of an optimization method for an electrostatic ring structure of a power transformer based on APDL and a response surface method according to the present invention;
FIG. 2 is a schematic diagram of a transformer model according to an embodiment of the present invention;
FIG. 3 is a residual normal probability chart according to an embodiment of the present invention;
FIG. 4 is a comparison graph of the predicted value and the actual value according to the embodiment of the present invention;
FIG. 5 is a perturbation analysis chart of an embodiment of the present invention;
FIG. 6 is a graph of the interaction response curve of the radius of curvature of the electrostatic ring and the thickness of the insulating layer according to an embodiment of the present invention;
FIG. 7 is a graph of the interaction response curve between the distance from the top surface of the electrostatic ring to the first platen above the electrostatic ring and the start of the arc at the top of the electrostatic ring in accordance with an embodiment of the present invention;
figure 8 is a graph of the radius of curvature of the electrostatic ring and the interaction response of the distance from the top surface of the electrostatic ring to the first sheet above the electrostatic ring in accordance with an embodiment of the present invention;
figure 9 is a graph of the radius of curvature of the electrostatic ring interacting with the start of the upper arc of the electrostatic ring in accordance with an embodiment of the present invention;
figure 10 is a graph of the interaction of the distance from the upper surface of the electrostatic ring to the first platen above the electrostatic ring and the thickness of the insulating layer in response to a surface profile of an embodiment of the present invention;
figure 11 is a graph of the thickness of the insulating layer and the initial position of the arc on the upper portion of the electrostatic ring in response to the interaction of the thickness of the insulating layer and the initial position of the arc.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention aims to provide a power transformer electrostatic ring structure optimization method based on APDL and a response surface method, which solves the problems of repeated manual modeling, subdivision and solving of an optimized structure and optimization of variables in the prior art, improves optimization efficiency, and can be used for optimally designing electrostatic ring structures of power transformers in different grades.
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in further detail below.
Fig. 1 is a flowchart of a method for optimizing a structure of an electrostatic ring of a power transformer based on an APDL and response surface method according to the present invention, and as shown in fig. 1, the method for optimizing a structure of an electrostatic ring of a power transformer based on an APDL and response surface method according to the present invention includes the following steps:
step 1: establishing a finite element model of the electrostatic ring of the power transformer according to ANSYS parametric modeling language APDL;
step 2: setting a parameter variation range influencing the maximum electric field strength by taking the reduction of the maximum electric field strength as an optimization target;
and step 3: performing a response surface test by using a central composite design method;
and 4, step 4: the effectiveness of the response surface model is checked, and the fitting degree and the prediction capability of the model are analyzed;
and 5: and obtaining the optimized variable parameter and the maximum electric field intensity value by adopting a mathematical programming method.
In the step 1, establishing a finite element model of the transformer electrostatic ring according to an ANSYS parameterized modeling language APDL, specifically including:
compiling an ANSYS parameterized programming command, establishing a finite element model of an electrostatic ring of the power transformer, and automatically performing the structure modeling, subdivision, boundary condition application and electric field intensity calculation of the power transformer, wherein in the process, an electrostatic field generalized equation is as follows:
when the charge density p =0,
therefore, the side value of the electrostatic field of the power transformer can be obtained:
in step 2, the parameter variation range affecting the maximum electric field strength is set by using the maximum electric field strength reduction as an optimization target, and the method specifically includes:
according to the structural and dimensional parameters of the electrostatic ring of the power transformerRespectively provided with a radius of curvature R of the electrostatic ring 1 The distance h from the upper surface of the electrostatic ring to the first paper board on the electrostatic ring, the thickness s of the insulating layer and the size variation range of the initial position w of the arc of the upper section of the electrostatic ring, and the structural positions corresponding to the parameters are shown in fig. 2.
Due to the limitations of the transformer electrostatic ring structure and size, the variation range of the parameter variables can be set as follows according to experience:
in step 3, the response surface test is performed by using a central composite design method, which specifically includes:
normalizing each parameter variable, then selecting a test point by adopting a central composite design method, designing a combination of each parameter variable with different values, obtaining each test result through mutual calling of ANSYS and MATLAB, establishing an initial response surface model, and generally adopting a form of a second-order polynomial:
wherein y is an objective function, β 0 ，β j ，β jj And beta ij Is a polynomial coefficient, x j Is a parameter variable, and n is the number of the parameter variables.
In step 4, the validity of the response surface model is checked, and the fitting degree and the prediction capability of the model are analyzed, specifically including:
and (3) adopting Design-Expert10.0 regression analysis software to perform variance analysis, diagnostic analysis and perturbation analysis on the initial response surface model, and eliminating irrelevant factors by checking the significance of each variable and a secondary term to obtain a final response surface model.
In step 5, obtaining the optimized parameter and the maximum electric field strength value by using a mathematical programming method specifically includes:
and solving the final response surface model by adopting a mathematical programming method to obtain the maximum electric field intensity optimal value under the mutual matching of all parameter variables, and determining all structural parameters of the power transformer electrostatic ring structure model.
Aiming at the steps 3-5, the specific implementation process comprises the following steps:
firstly, a Design-Expert10.0 software is utilized to carry out electrostatic ring curvature radius R according to a central composite Design method (CCD) 1 The test factors and the level are set according to four factors, namely the distance h from the upper surface of the electrostatic ring to the first paperboard, the thickness s of the insulating layer and the initial position w of the arc at the upper section of the electrostatic ring, and the result is shown in table 1.
TABLE 1 test factors and level settings
Secondly, test points are selected according to the design principle of the central composite design method and the setting of test factors and levels, and the test scheme is shown in table 2.
TABLE 2 test protocol
Thirdly, according to the test scheme, through writing an m file and an APDL command stream, performing ANSYS and MATLAB mutual calling, and automatically extracting each test result. In the second order polynomial response surface model, y is the objective function, beta 0 ，β j ，β jj And beta ij Is a polynomial coefficient, x j Is a parameter variable, n is the number of the parameter variable, and is expressed as:
(4) The formula can be expressed in the form of a matrix as follows:
or
y＝Xβ+ε (6)
And e is an error of y, and the polynomial coefficient is obtained according to the formula (7) by minimizing the sum of squares of the errors by using the least square principle to obtain an initial response surface model:
β＝(X T X) -1 X T y (7)
fourthly, the variance analysis is carried out on the response surface equation, the P value is used for checking the significance of each item, and the smaller the P value is, the higher the significance of the item is. The analysis of variance results (table 3) show that the P value of the model is less than 0.0001, which indicates that the quadratic polynomial model is reasonably selected and the relationship between the response value and the regression equation is very significant. Model correlation coefficient R 2 And after adjustment
0.9918 and 0.9841, respectively, which are comparable and very close to 1, indicate that the model can account for the experimental variation of 98.41%, with less experimental error and better fit.
TABLE 3 ANOVA TABLE
Fifthly, diagnostic analysis and perturbation analysis are carried out by using Design-Expert10.0 software, a residual normal probability graph and a comparison graph of a predicted value and an actual value obtained by the diagnostic analysis are respectively shown in fig. 3 and fig. 4, which show that a response surface model is effective and reasonable and has higher accuracy and prediction quality, and a perturbation analysis graph is shown in fig. 5 and reflects the sensitivity degree of an optimization target to each variable.
Sixth, the response surface map between each two elements obtained by Design-Expert10.0 software reflects the degree of influence of the interaction between the two factors on the response value, as shown in fig. 6 to 11.
And seventhly, removing irrelevant items through analysis in the fifth step to the sixth step to obtain a final response surface equation with higher fitting degree, so that the aim of optimization can be fulfilled, and if the response surface model is insufficient, returning to the step 2 to readjust for testing.
And eighthly, solving the response surface equation by adopting a quadratic programming method in mathematical programming to obtain the maximum electric field intensity optimal value under the mutual matching of all parameter variables, and determining all structural parameters of the power transformer electrostatic ring structure model.
According to the power transformer electrostatic ring structure optimization method based on the APDL and the response surface method, the structural model is established through the APDL command stream, the approximate function expression between the objective function and the variable is constructed, the objective function which is originally implicit is shown, meanwhile, the influence of each variable on the optimization target is considered, and the problems that in the prior art, the optimization structure is repeatedly and manually modeled, split and solved, and each variable is respectively optimized are solved, so that the optimization efficiency is improved, and the method can be used for the structural optimization design of the power transformer electrostatic ring with any voltage level.
The principles and embodiments of the present invention have been described herein using specific examples, which are provided only to help understand the method and the core concept of the present invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, the specific embodiments and the application range may be changed. In view of the above, the present disclosure should not be construed as limiting the invention.
Claims (1)
1. A power transformer electrostatic ring structure optimization method based on APDL and a response surface method is characterized by comprising the following steps:
step 1: establishing a finite element model of the electrostatic ring of the power transformer according to ANSYS parametric modeling language APDL;
step 2: setting the variation range of parameter variables influencing the maximum electric field strength by taking the reduction of the maximum electric field strength as an optimization target;
and step 3: performing a response surface test by using a central composite design method;
and 4, step 4: the effectiveness of the response surface model is checked, and the fitting degree and the prediction capability of the model are analyzed;
and 5: obtaining optimized parameter variables and maximum electric field intensity values by adopting a mathematical programming method;
in the step 1, establishing a finite element model of the transformer electrostatic ring according to an ANSYS parameterized modeling language APDL, specifically including:
compiling an ANSYS parameterization programming command, establishing a finite element model of an electrostatic ring of the power transformer, and automatically carrying out modeling and subdivision on the structure of the power transformer, and calculating applied boundary conditions and electric field intensity;
in the step 2, with the reduction of the maximum electric field strength as an optimization target, a parameter variation range influencing the maximum electric field strength is set, which specifically includes:
respectively setting the curvature radius R of the electrostatic ring according to the limitation of the structure and size parameters of the electrostatic ring of the power transformer 1 The distance h from the upper surface of the electrostatic ring to the first paper board on the electrostatic ring, the thickness s of the insulating layer and the size variation range of the initial position w of the arc at the upper section of the electrostatic ring;
in the step 3, a response surface test is performed by using a central composite design method, which specifically includes:
normalizing each parameter variable, then selecting a test point by adopting a central composite design method, designing the combination of each parameter variable with different values, obtaining the test result of each time through the mutual calling of ANSYS and MATLAB, establishing an initial response surface model, and generally adopting a form of a second-order polynomial:
wherein y is an objective function, β 0 ，β j ，β j And beta ij Is a polynomial coefficient, x j Is a parameter variable, and n is the number of the parameter variables;
in the step 4, the effectiveness of the response surface model is checked, and the fitting degree and the prediction capability of the model are analyzed, which specifically comprises the following steps:
performing variance analysis, diagnostic analysis and perturbation analysis on the initial response surface model by adopting Design-Expert10.0 regression analysis software, and removing irrelevant factors by checking the significance of each variable and a secondary term to obtain a final response surface model;
in the step 5, the optimized parameter variable and the maximum electric field strength value are obtained by a mathematical programming method, which specifically includes:
and solving the final response surface model by adopting a mathematical programming method to obtain the maximum electric field intensity optimal value under the mutual cooperation of parameter variables, and determining each structural parameter of the power transformer electrostatic ring structure model.
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Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102778844A (en) * | 2012-07-30 | 2012-11-14 | 杭州电子科技大学 | Induction heating closed loop simulation method based on finite element model and system identification |
| CN104899375A (en) * | 2015-06-05 | 2015-09-09 | 株洲时代新材料科技股份有限公司 | Main insulating anti-corona structure optimization calculating method used for high-voltage motor |
| CN105224750A (en) * | 2015-10-10 | 2016-01-06 | 北京工业大学 | A kind of new spatial based on response surface can open up single reed structure optimization method in hinge |
| CN106484968A (en) * | 2016-09-23 | 2017-03-08 | 西安交通大学 | A kind of method for quick predicting of the heat exchange Correlations based on response surface |
| CN107404118A (en) * | 2017-09-06 | 2017-11-28 | 河海大学 | Electrical interconnection system probability optimal load flow computational methods based on stochastic response surface |
| CN109543325A (en) * | 2018-11-30 | 2019-03-29 | 湖南固尔邦幕墙装饰股份有限公司 | A kind of door and window is thermally integrated optimum design method with aluminium alloy extrusions power |
| CN109992871A (en) * | 2019-03-26 | 2019-07-09 | 北京工业大学 | A kind of pipe hinge space deployable structure optimum design method considering damage of composite materials |
-
2019
- 2019-08-28 CN CN201910801683.3A patent/CN110516359B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102778844A (en) * | 2012-07-30 | 2012-11-14 | 杭州电子科技大学 | Induction heating closed loop simulation method based on finite element model and system identification |
| CN104899375A (en) * | 2015-06-05 | 2015-09-09 | 株洲时代新材料科技股份有限公司 | Main insulating anti-corona structure optimization calculating method used for high-voltage motor |
| CN105224750A (en) * | 2015-10-10 | 2016-01-06 | 北京工业大学 | A kind of new spatial based on response surface can open up single reed structure optimization method in hinge |
| CN106484968A (en) * | 2016-09-23 | 2017-03-08 | 西安交通大学 | A kind of method for quick predicting of the heat exchange Correlations based on response surface |
| CN107404118A (en) * | 2017-09-06 | 2017-11-28 | 河海大学 | Electrical interconnection system probability optimal load flow computational methods based on stochastic response surface |
| CN109543325A (en) * | 2018-11-30 | 2019-03-29 | 湖南固尔邦幕墙装饰股份有限公司 | A kind of door and window is thermally integrated optimum design method with aluminium alloy extrusions power |
| CN109992871A (en) * | 2019-03-26 | 2019-07-09 | 北京工业大学 | A kind of pipe hinge space deployable structure optimum design method considering damage of composite materials |
Non-Patent Citations (2)
| Title |
|---|
| "A Dynamic Dual-Response-Surface Methodology for Optimal Design of a Permanent-Magnet Motor Using Finite-Element Method";Xiaoyu Liu et al;《IEEE》;20151231;第1-4页 * |
| "电力变压器主绝缘结构的优化及影响因素分析";高有华 等;《变压器》;20091031;第46卷(第10期);第1-5页 * |
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