CN112560331A - Energy-saving and material-saving optimization design system and method for amorphous alloy dry type transformer - Google Patents
Energy-saving and material-saving optimization design system and method for amorphous alloy dry type transformer Download PDFInfo
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Abstract
The invention discloses an energy-saving and material-saving optimization design system and method for an amorphous alloy dry-type transformer, wherein the system comprises an amorphous alloy dry-type transformer optimization design system main interface parameter setting module, an amorphous alloy dry-type transformer optimization design system product operation parameter input module, an amorphous alloy dry-type transformer optimization design system improved NSGA-II optimization algorithm parameter and optimization variable parameter upper limit and lower limit setting module, an amorphous alloy dry-type transformer optimization design system improved NSGA-II algorithm optimization processing module and an amorphous alloy dry-type transformer optimization design system output optimization result module; the method comprises the following steps: acquiring an initial design scheme of the amorphous alloy dry-type transformer through manual design; compared with the traditional transformer design method, the optimization system is simple to operate, high in automation degree and short in design period, can effectively reduce the manufacturing cost of the amorphous alloy dry-type transformer, remarkably improves the loss performance of the amorphous alloy dry-type transformer, and has important significance for popularization of the amorphous alloy dry-type transformer.
Description
Technical Field
The invention relates to the technical field of amorphous alloy transformer optimization design, in particular to an energy-saving and material-saving optimization design system and method for an amorphous alloy dry type transformer.
Background
The demand of new capital construction on electric power is continuously increased, and in the process of electric power production, a large amount of pollutants such as greenhouse gas and dust are often accompanied, so that the environment is greatly polluted. In the electric energy loss of China, the electric energy loss in a power distribution network accounts for about 70% of the total network loss. In power distribution networks, there are long-term lightly loaded or unloaded distribution transformers whose no-load losses account for a large portion of the losses in the distribution network. Therefore, the reduction of the no-load loss of the transformer can bring huge energy-saving and environmental-protection benefits.
With the popularization of energy conservation and emission reduction and green environmental protection concepts, amorphous alloy iron core transformers with low no-load loss are paid more and more attention and are applied. Compared with the traditional iron core transformer made of silicon steel sheets, the amorphous alloy iron core transformer has great advantages in energy conservation. Compared with a silicon steel sheet iron core transformer, the no-load loss of the amorphous alloy iron core transformer is reduced by 70-80%, and the no-load current is reduced by about 80%, so that the amorphous alloy iron core transformer is a distribution transformer with ideal energy-saving effect at present. However, compared with the conventional silicon steel sheet iron core, the amorphous alloy iron core is more difficult to manufacture and uses more materials, so that the price of the amorphous alloy iron core transformer is higher than that of the conventional silicon steel sheet iron core transformer. Therefore, the amorphous alloy transformer needs to be optimally designed.
At present, the deficiency and shortage of related amorphous alloy transformer optimization design tool software cause a great deal of waste of raw materials of products and insufficient quality stability. In addition, the traditional transformer design method has low automation degree, large design workload and long design period, and an optimal design scheme is difficult to obtain. Therefore, in the optimization problem of multi-objective, multi-variable, multi-constraint, discrete and non-linear transformer optimization design, how to reduce the manufacturing cost of the amorphous alloy transformer, improve the loss performance of the transformer and accelerate the design cycle of the transformer becomes a critical task in the amorphous alloy transformer design industry.
Disclosure of Invention
The invention aims to provide an energy-saving and material-saving optimization design method and system for an amorphous alloy dry type transformer; the optimization design method disclosed by the invention can effectively reduce the manufacturing cost of the amorphous alloy transformer and improve the loss performance of the transformer; in addition, the optimization design system disclosed by the invention can solve the problems of low automation degree, large design workload and long design period of the traditional transformer design method.
In order to solve the technical problems, the technical scheme adopted by the invention is as follows:
the energy-saving and material-saving optimization design system for the amorphous alloy dry type transformer comprises a main interface parameter setting module of the amorphous alloy dry type transformer optimization design system, an amorphous alloy dry type transformer optimization design system product operation parameter input module, an NSGA-II optimization algorithm parameter and optimization variable parameter upper limit and lower limit setting module improved by the amorphous alloy dry type transformer optimization design system, an NSGA-II algorithm optimization processing module improved by the amorphous alloy dry type transformer optimization design system and an amorphous alloy dry type transformer optimization design system output optimization result module;
wherein;
the amorphous alloy dry-type transformer optimization design system main interface parameter setting module is used for determining rated capacity, iron core form, iron core material, coupling group and insulation grade operation parameters of an optimized object;
the amorphous alloy dry-type transformer optimization design system product operation parameter input module is used for inputting transformer optimization calculation operation parameters, and the transformer optimization calculation operation parameters comprise rated parameters, structural parameters, insulation distance, determination coefficients, line mode margin, performance tolerance, air passage type and material unit price parameters;
the optimized design system of the amorphous alloy dry-type transformer is characterized in that an improved NSGA-II optimized algorithm parameter and optimized variable parameter upper bound and lower bound setting module is used for setting the coding length, the population size, the genetic algebra, the selection probability, the cross probability and the variation probability of an optimized algorithm, and setting the value upper bound and lower bound of an iron core stack thickness, the number of low-voltage layers, the high-voltage line width, the high-voltage line thickness, the low-voltage line width and the low-voltage line thickness optimized variable;
the optimized design system of the amorphous alloy dry-type transformer is characterized in that an improved NSGA-II algorithm optimized processing module is used for establishing a transformer optimized model, and the economic index and the loss index of the amorphous alloy dry-type transformer are optimized and solved by adopting an NSGA-II algorithm under the condition that the constraint conditions of electrical performance, material performance and material specification are met;
the output optimization result module of the amorphous alloy dry type transformer optimization design system is used for outputting a plurality of optimization schemes which are obtained by an improved NSGA-II algorithm and meet performance requirements, and selecting an optimal high-efficiency energy-saving low-cost optimization design scheme according to different requirements of customers.
The rated parameters in the operation parameter input module of the amorphous alloy dry-type transformer optimization design system are specifically used for setting parameters of the product model specification, the product rated capacity, the high-voltage rated voltage, the low-voltage rated voltage, the working frequency, the load loss, the no-load loss, the impedance voltage, the no-load current and the temperature rise limit value of the high-low voltage winding.
The structural parameters in the operation parameter input module of the amorphous alloy dry-type transformer optimization design system are specifically used for setting the material and shape of high-voltage and low-voltage windings, the winding and parallel winding form of high-voltage wires, the number of iron core stacks and parallel, the number of high-voltage winding sections, the thickness of an upper clamping piece, the thickness of a lower clamping piece and the thickness of an end clamping piece.
The insulation distance in the operation parameter input module of the amorphous alloy dry-type transformer optimization design system is specifically used for setting parameters of iron core gaps, small window gaps, thicknesses of epoxy cylinders or paperboards, thicknesses of reinforcing plates in the middle of the epoxy cylinders, air flue thicknesses, high-voltage lead insulation thicknesses, low-voltage outer layer thicknesses, main air flue thicknesses, high-voltage inner layer thicknesses, high-voltage outer layer thicknesses, end insulation, high-voltage lead interlayer insulation thicknesses and low-voltage lead interlayer insulation thicknesses.
The determined coefficients in the operation parameter input module of the amorphous alloy dry type transformer optimization design system are specifically used for setting parameters of an iron core lamination coefficient, an iron core loss coefficient, an iron core lap joint coefficient, a low-voltage winding overlapping thickness coefficient, a high-voltage winding overlapping thickness coefficient, a load loss coefficient, a high-voltage winding temperature rise coefficient, a low-voltage winding temperature rise coefficient and a copper foil coefficient;
the performance tolerance in the operation parameter input module of the amorphous alloy dry-type transformer optimization design system is used for setting an allowable upper limit and a lower limit of impedance voltage, a no-load loss tolerance value and a load loss tolerance value;
the line mode margin in the operation parameter input module is used for setting a line mode width margin and a line mode length margin;
the air channel type in the operation parameter input module is used for setting the high-pressure side air channel type and the low-pressure side air channel type.
Further optimizing, wherein the material unit price in the operation parameter input module of the amorphous alloy dry-type transformer optimization design system is specifically used for setting amorphous alloy unit price, high-voltage aluminum flat wire unit price, high-voltage copper round wire unit price, low-voltage copper foil unit price, low-voltage aluminum foil unit price, clamping piece unit price and accessory unit price parameters;
based on the setting of the upper and lower bounds of the optimization algorithm parameters and the optimization variable parameters, an improved NSGA-II algorithm optimization processing module in the amorphous alloy dry type transformer optimization design system is used for carrying out program internal optimization calculation on the established transformer optimization model;
the output optimization result module of the amorphous alloy dry-type transformer optimization design system is specifically used for displaying various feasible optimization results and outputting main transformer parameter values in an optimization scheme by selecting one of the optimization results;
the obtained optimization scheme can be output and stored in 3 forms, namely in the form of Txt text; secondly, outputting and storing in the form of an Excel calculation sheet; and thirdly, outputting and storing in the form of an Access database.
The energy-saving and material-saving optimization design method for the amorphous alloy dry type transformer comprises the following steps:
step 1:
determining optimization variables and constraint conditions in an improved NSGA-II optimization model according to an optimization target of the amorphous alloy dry-type transformer; the optimization variables comprise iron core stack thickness, low-voltage layer number, a high-voltage wire gauge and a low-voltage wire gauge; the constraint conditions comprise electrical property constraint, material property constraint and process constraint;
step 2:
acquiring an initial design scheme of the amorphous alloy dry-type transformer by manual design, and determining the upper and lower value limits of the optimized variables;
and step 3:
determining the number and the length of genes contained in a single individual of a population in the NSGA-II algorithm according to the number of optimized variables, coding the genes of the population individual by setting the size of the population and the upper and lower value limits of each gene in a real number coding and integer coding mode, and generating an initial population by a chaotic mapping mode so as to enhance the diversity of the population; wherein the initial population comprises an inner population P and an outer population PeThe internal population participates in genetic evolution, is continuously initialized and updated in a chaotic mapping mode and participates in the selection operation of the population; the number of genes contained in the population individual is determined by the optimization variable;
and 4, step 4:
calculating an objective function value of each individual in the current-generation population by the optimized objective function, and performing rapid non-dominated sorting operation on the objective function values by comparing the objective function values of each individual to obtain sorted population individuals;
and 5:
performing virtual fitness calculation, namely congestion distance calculation, on the sorted population individuals of each domination level, and obtaining a offspring population Q after performing selection, crossing and variation operations on the population individuals;
step 6:
combining the parent population and the offspring population into a new population R, firstly carrying out variation operation on the individuals with dense repetition in the combined population and calculating the objective function value of the individuals, then carrying out rapid non-dominated sorting operation on the combined population, and selecting the first N excellent individuals as the new parent population;
and 7:
carrying out initialization updating operation on an external population by adopting a chaotic mapping mode, and carrying out non-branch updating operation on the new parent populationThe matching sequence number is 1 (F)1) Storing the individuals into the updated external population, and if the population genetic algebra does not reach the maximum iteration times, returning the new parent population and the updated external population to execute the steps 3-6 to perform the next genetic operation;
and 8:
and if the population genetic algebra reaches the maximum iteration times, selecting an optimal design scheme with high efficiency, energy conservation and low manufacturing cost according to different requirements of customers according to a plurality of groups of feasible amorphous alloy dry-type transformers output in the population.
Further optimizing, the optimization target comprises an economic index (main material cost) and a loss index (total loss), wherein the economic index is the main material cost, and the loss index is the total loss:
wherein APC (X) is the cost of the main material; NLL (X) is the no-load loss; LL (X) is load loss; x ═ X1,X2,...,Xn]To optimize variable parameters;
wherein the main material cost f1(X) and total loss f2(X) is respectively:
f1(X)＝min(Ccore×Wcore+Clow×Wlow+Chigh×Whigh)
f2(X)＝min(K×Vcore×ρcore×fα×Bm β+k1×Ihigh 2×Rhigh+k2×Ilow 2×Rlow)
wherein the content of the first and second substances,
Ccore、Clow、Chighthe unit price of the amorphous alloy iron core, the low-voltage winding and the high-voltage winding is respectively;
Wcore、Wlow、Whighthe weights of the amorphous alloy iron core, the low-voltage winding and the high-voltage winding are respectively set;
K. alpha and beta are the material coefficients of the iron core;
Vcoreis the volume of the iron core;
ρcoreis the amorphous alloy density;
f, the working frequency of the transformer;
Bmis the core flux density;
k1、k2the loss coefficients of the high-voltage winding and the low-voltage winding are respectively;
Ihigh、Ilowhigh and low voltage winding phase currents, respectively;
Rhigh、Rlowrespectively high and low voltage winding resistances.
Further optimization, the electrical property constraint, the material property constraint and the material specification constraint are as follows:
1) the electrical performance constraints are as follows:
a. no-load loss: p0<kP0×P0r；
b. Load loss: pk<kPk×Pkr；
c. No-load current: i is0<I0r；
d. Short-circuit impedance: u shapek min<Uk<Uk max；
e. Efficiency: eta>ηr；
2) The material property constraints are as follows:
a. core magnetic flux density: b ism min<Bm<Bm max；
b. Current density of low-voltage wire: j. the design is a squarel<Jl max；
c. Current density of the high-voltage wire: j. the design is a squareh<Jh max；
d. Temperature rise of the low-voltage winding: t isl<Tl max；
e. Temperature rise of the high-voltage winding: t ish<Th max；
3) The material specification constraints are as follows:
a. iron core lamination thickness: dmin<Dt<Dmax；
b. The number of layers of the low-voltage winding is as follows: n is a radical ofc min<Nc<Nc max；
c. High-voltage wire width: wh min<Wh<Wh max；
d. And (3) thickness of the high-voltage wire: dh min<Dh<Dh max；
e. Low-voltage conductor width: wl min<Wl<Wl max；
f. And (3) thickness of a low-voltage wire: dl min<Dl<Dl max。
Wherein the content of the first and second substances,
P0、P0rrespectively representing the actual value and the rated value of no-load loss;
kP0is the no-load loss coefficient;
Pk、Pkrrespectively representing the actual value and the rated value of the load loss;
kPkis the load loss factor;
I0、I0rrespectively an actual value and a rated value of the no-load current;
Ukfor actual value of short-circuit impedance, Uk max、Uk minThe short circuit impedance values are respectively an upper bound and a lower bound;
η、ηractual efficiency and rated efficiency respectively;
Bm max、Bm minan upper limit and a lower limit of the magnetic flux density of the iron core are respectively set;
Jl、Jhactual values of current density of high and low voltage wires, Jl max、Jh maxThe maximum limiting values of the current density of the high-voltage wire and the low-voltage wire are respectively set;
Tl、Ththe actual values of the temperature rise of the high-voltage winding and the low-voltage winding are respectively,Tl max、Th maxrespectively setting the maximum limit values of the temperature rise of the high-voltage winding and the low-voltage winding;
Dmax、Dminrespectively taking an upper bound and a lower bound for the iron core lamination thickness;
Nc max、Nc minrespectively taking an upper bound and a lower bound for the layer number of the low-voltage winding;
Wh max、Wh minthe width of the high-voltage wire is respectively taken as an upper bound and a lower bound;
Dh min、Dh maxrespectively taking a lower bound and an upper bound for the thickness of the high-voltage wire;
Wl max、Wl minthe width of the low-voltage wire is respectively taken as an upper bound and a lower bound;
Dl min、Dl maxthe low voltage wire thickness values are the lower and upper bounds, respectively.
10. The energy-saving and material-saving optimization design method for the amorphous alloy dry type transformer according to claim 9, characterized in that: the mode of generating the initial population by the chaotic mapping mode comprises the following steps:
Li+1,j＝γLi,j+(1-Li,j)
wherein the content of the first and second substances,
Li,jis the j dimension chaotic variable of the ith individual;
gamma is a chaos factor, and gamma belongs to (0, 4);
when gamma is 4, the chaotic variable is in a complete chaotic state;
Xi,ja j dimension variable parameter of the ith individual; xj min,Xj maxRespectively the lower bound and the upper bound of the variable parameter of the j dimension of the population individual;
wherein the content of the first and second substances,
the calculation method of the virtual fitness (crowding distance) of the population individuals is as follows:
wherein the content of the first and second substances,
Corwd_disti 1(X) is a first objective function f of the ith individual1(X) degree of crowding;
Corwd_disti 2(X) is the ith individual second objective function f2(X) degree of crowding;
Corwd_disti(X) is the virtual fitness (crowding distance) of the ith population individual;
pre_f1(X)、next_f1(X) first objective function values for the (i-1) th individual and the (i + 1) th individual, respectively; f. of1 max、f1 minRespectively the maximum value and the minimum value of the first objective function;
pre_f2(X)、next_f2(X) second objective function values for the (i-1) th individual and the (i + 1) th individual, respectively;
f2 max、f2 minrespectively the maximum value and the minimum value of the second objective function;
in each domination level population individual, sorting according to the sizes of the first objective function value and the second objective function value respectively, and taking the crowdedness of the first individual and the last individual as infinity;
the selection, crossing and variation of population individuals generate offspring populations, and the genetic operations of the offspring populations respectively adopt a championship selection operation, a simulated binary crossing operation and a polynomial variation operation.
Compared with the prior art, the invention has the following beneficial effects:
the method adopts the NSGA-II multi-objective optimization algorithm improved under the constraint condition to optimize the cost and the total loss of the main material of the amorphous alloy transformer, and can obtain a plurality of feasible optimization schemes to the maximum extent for the selection of designers. Compared with manual design, the obtained optimization scheme can effectively reduce the manufacturing cost of the amorphous alloy transformer and improve the loss performance of the transformer. In addition, based on an improved NSGA-II optimization algorithm, the invention also provides an energy-saving and material-saving optimization design system for the amorphous alloy dry-type transformer, the system has reasonable design flow, accurate optimization calculation result and high calculation speed, and the problems of low automation degree, large design workload and long design period of the traditional transformer design method are effectively solved.
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In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are required to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.
FIG. 1 is a flow chart of the operation of the energy-saving and material-saving optimization design system of the dry type transformer based on the improved NSGA-II amorphous alloy.
FIG. 2 is a structural design diagram of an energy-saving and material-saving optimization design system of the amorphous alloy dry type transformer.
FIG. 3 is an operation flow chart of the energy-saving and material-saving optimization design system of the amorphous alloy dry type transformer.
FIG. 4 is a main interface of the energy-saving and material-saving optimized design system of the amorphous alloy dry type transformer.
FIG. 5 is a product parameter setting interface of the energy-saving and material-saving optimization design system of the amorphous alloy dry type transformer.
FIG. 6 is a view showing the interface between the operation parameters of the NSGA-II algorithm and the parameters of the optimized variables set by the energy-saving and material-saving optimization design system of the amorphous alloy dry type transformer.
FIG. 7 is an interface of the optimized result output by the optimized energy-saving material-saving design system of the amorphous alloy dry-type transformer of the present invention.
FIG. 8 is an optimization result distribution curve of the energy-saving and material-saving optimization design system of the amorphous alloy dry type transformer based on the NSGA-II algorithm.
FIG. 9 is a distribution curve of the energy-saving and material-saving optimization design system of the amorphous alloy dry type transformer based on the improved NSGA-II algorithm.
Detailed Description
The present invention will be further described with reference to the following examples, which are intended to illustrate only some, but not all, of the embodiments of the present invention. Based on the embodiments of the present invention, other embodiments used by those skilled in the art without any creative effort belong to the protection scope of the present invention.
Example one
The invention discloses an energy-saving and material-saving optimization design system for an amorphous alloy dry-type transformer, which comprises an amorphous alloy dry-type transformer optimization design system main interface parameter setting module, an amorphous alloy dry-type transformer optimization design system product operation parameter input module, an amorphous alloy dry-type transformer optimization design system improved NSGA-II optimization algorithm parameter and optimization variable parameter upper limit and lower limit setting module, an amorphous alloy dry-type transformer optimization design system improved NSGA-II algorithm optimization processing module and an amorphous alloy dry-type transformer optimization design system output optimization result module;
wherein;
the amorphous alloy dry-type transformer optimization design system main interface parameter setting module is used for determining rated capacity, iron core form, iron core material, coupling group and insulation grade operation parameters of an optimized object;
the amorphous alloy dry-type transformer optimization design system product operation parameter input module is used for inputting transformer optimization calculation operation parameters, and the transformer optimization calculation operation parameters comprise rated parameters, structural parameters, insulation distance, determination coefficients, line mode margin, performance tolerance, air passage type and material unit price parameters;
the optimized design system of the amorphous alloy dry-type transformer is characterized in that an improved NSGA-II optimized algorithm parameter and optimized variable parameter upper bound and lower bound setting module is used for setting the coding length, the population size, the genetic algebra, the selection probability, the cross probability and the variation probability of an optimized algorithm, and setting the value upper bound and lower bound of an iron core stack thickness, the number of low-voltage layers, the high-voltage line width, the high-voltage line thickness, the low-voltage line width and the low-voltage line thickness optimized variable;
the optimized design system of the amorphous alloy dry-type transformer is characterized in that an improved NSGA-II algorithm optimized processing module is used for establishing a transformer optimized model, and the economic index and the loss index of the amorphous alloy dry-type transformer are optimized and solved by adopting an NSGA-II algorithm under the condition that the constraint conditions of electrical performance, material performance and material specification are met;
the output optimization result module of the amorphous alloy dry type transformer optimization design system is used for outputting a plurality of optimization schemes which are obtained by an improved NSGA-II algorithm and meet performance requirements, and selecting an optimal high-efficiency energy-saving low-cost optimization design scheme according to different requirements of customers.
The rated parameters in the operation parameter input module of the amorphous alloy dry-type transformer optimization design system are specifically used for setting parameters of the product model specification, the product rated capacity, the high-voltage rated voltage, the low-voltage rated voltage, the working frequency, the load loss, the no-load loss, the impedance voltage, the no-load current and the temperature rise limit value of the high-low voltage winding.
The structural parameters in the operation parameter input module of the amorphous alloy dry-type transformer optimization design system are specifically used for setting the material and shape of high-voltage and low-voltage windings, the winding and parallel winding form of high-voltage wires, the number of iron core stacks and parallel, the number of high-voltage winding sections, the thickness of an upper clamping piece, the thickness of a lower clamping piece and the thickness of an end clamping piece.
The insulation distance in the operation parameter input module of the amorphous alloy dry-type transformer optimization design system is specifically used for setting parameters of iron core gaps, small window gaps, thicknesses of epoxy cylinders or paperboards, thicknesses of reinforcing plates in the middle of the epoxy cylinders, air flue thicknesses, high-voltage lead insulation thicknesses, low-voltage outer layer thicknesses, main air flue thicknesses, high-voltage inner layer thicknesses, high-voltage outer layer thicknesses, end insulation, high-voltage lead interlayer insulation thicknesses and low-voltage lead interlayer insulation thicknesses.
The determined coefficients in the operation parameter input module of the amorphous alloy dry type transformer optimization design system are specifically used for setting parameters of an iron core lamination coefficient, an iron core loss coefficient, an iron core lap joint coefficient, a low-voltage winding overlapping thickness coefficient, a high-voltage winding overlapping thickness coefficient, a load loss coefficient, a high-voltage winding temperature rise coefficient, a low-voltage winding temperature rise coefficient and a copper foil coefficient;
the performance tolerance in the operation parameter input module of the amorphous alloy dry-type transformer optimization design system is used for setting an allowable upper limit and a lower limit of impedance voltage, a no-load loss tolerance value and a load loss tolerance value;
the line mode margin in the operation parameter input module is used for setting a line mode width margin and a line mode length margin;
the air channel type in the operation parameter input module is used for setting the high-pressure side air channel type and the low-pressure side air channel type.
Further optimizing, wherein the material unit price in the operation parameter input module of the amorphous alloy dry-type transformer optimization design system is specifically used for setting amorphous alloy unit price, high-voltage aluminum flat wire unit price, high-voltage copper round wire unit price, low-voltage copper foil unit price, low-voltage aluminum foil unit price, clamping piece unit price and accessory unit price parameters;
based on the setting of the upper and lower bounds of the optimization algorithm parameters and the optimization variable parameters, an improved NSGA-II algorithm optimization processing module in the amorphous alloy dry type transformer optimization design system is used for carrying out program internal optimization calculation on the established transformer optimization model;
the output optimization result module of the amorphous alloy dry-type transformer optimization design system is specifically used for displaying various feasible optimization results and outputting main transformer parameter values in an optimization scheme by selecting one of the optimization results;
the obtained optimization scheme can be output and stored in 3 forms, namely in the form of Txt text; secondly, outputting and storing in the form of an Excel calculation sheet; and thirdly, outputting and storing in the form of an Access database.
The energy-saving and material-saving optimization design method for the amorphous alloy dry type transformer comprises the following steps:
step 1:
determining optimization variables and constraint conditions in an improved NSGA-II optimization model according to an optimization target of the amorphous alloy dry-type transformer; the optimization variables comprise iron core stack thickness, low-voltage layer number, a high-voltage wire gauge and a low-voltage wire gauge; the constraint conditions comprise electrical property constraint, material property constraint and process constraint;
step 2:
acquiring an initial design scheme of the amorphous alloy dry-type transformer by manual design, and determining the upper and lower value limits of the optimized variables;
and step 3:
determining the number and the length of genes contained in a single individual of a population in the NSGA-II algorithm according to the number of optimized variables, coding the genes of the population individual by setting the size of the population and the upper and lower value limits of each gene in a real number coding and integer coding mode, and generating an initial population by a chaotic mapping mode so as to enhance the diversity of the population; wherein the initial population comprises an inner population P and an outer population PeThe internal population participates in genetic evolution, is continuously initialized and updated in a chaotic mapping mode and participates in the selection operation of the population; the number of genes contained in the population individual is determined by the optimization variable;
and 4, step 4:
calculating an objective function value of each individual in the current-generation population by the optimized objective function, and performing rapid non-dominated sorting operation on the objective function values by comparing the objective function values of each individual to obtain sorted population individuals;
and 5:
performing virtual fitness calculation, namely congestion distance calculation, on the sorted population individuals of each domination level, and obtaining a offspring population Q after performing selection, crossing and variation operations on the population individuals;
step 6:
combining the parent population and the offspring population into a new population R, firstly carrying out variation operation on the individuals with dense repetition in the combined population and calculating the objective function value of the individuals, then carrying out rapid non-dominated sorting operation on the combined population, and selecting the first N excellent individuals as the new parent population;
and 7:
carrying out initialization updating operation on an external population by adopting a chaotic mapping mode, and setting the non-dominated sequencing sequence number in the new parent population as1(F1) Storing the individuals into the updated external population, and if the population genetic algebra does not reach the maximum iteration times, returning the new parent population and the updated external population to execute the steps 3-6 to perform the next genetic operation;
and 8:
and if the population genetic algebra reaches the maximum iteration times, selecting an optimal design scheme with high efficiency, energy conservation and low manufacturing cost according to different requirements of customers according to a plurality of groups of feasible amorphous alloy dry-type transformers output in the population.
Further optimizing, the optimization target comprises an economic index (main material cost) and a loss index (total loss), wherein the economic index is the main material cost, and the loss index is the total loss:
wherein APC (X) is the cost of the main material; NLL (X) is the no-load loss; LL (X) is load loss; x ═ X1,X2,...,Xn]To optimize variable parameters;
wherein the main material cost f1(X) and total loss f2(X) is respectively:
f1(X)＝min(Ccore×Wcore+Clow×Wlow+Chigh×Whigh)
f2(X)＝min(K×Vcore×ρcore×fα×Bm β+k1×Ihigh 2×Rhigh+k2×Ilow 2×Rlow)
wherein the content of the first and second substances,
Ccore、Clow、Chighthe unit price of the amorphous alloy iron core, the low-voltage winding and the high-voltage winding is respectively;
Wcore、Wlow、Whighthe weights of the amorphous alloy iron core, the low-voltage winding and the high-voltage winding are respectively set;
K. alpha and beta are the material coefficients of the iron core;
Vcoreis the volume of the iron core;
ρcoreis the amorphous alloy density;
f, the working frequency of the transformer;
Bmis the core flux density;
k1、k2the loss coefficients of the high-voltage winding and the low-voltage winding are respectively;
Ihigh、Ilowhigh and low voltage winding phase currents, respectively;
Rhigh、Rlowrespectively high and low voltage winding resistances.
Further optimization, the electrical property constraint, the material property constraint and the material specification constraint are as follows:
1) the electrical performance constraints are as follows:
a. no-load loss: p0<kP0×P0r；
b. Load loss: pk<kPk×Pkr；
c. No-load current: i is0<I0r；
d. Short-circuit impedance: u shapek min<Uk<Uk max；
e. Efficiency: eta>ηr；
2) The material property constraints are as follows:
a. core magnetic flux density: b ism min<Bm<Bm max；
b. Current density of low-voltage wire: j. the design is a squarel<Jl max；
c. Current density of the high-voltage wire: j. the design is a squareh<Jh max；
d. Temperature rise of the low-voltage winding: t isl<Tl max；
e. Temperature rise of the high-voltage winding: t ish<Th max；
3) The material specification constraints are as follows:
a. iron core lamination thickness: dmin<Dt<Dmax；
b. The number of layers of the low-voltage winding is as follows: n is a radical ofc min<Nc<Nc max；
c. High-voltage wire width: wh min<Wh<Wh max；
d. And (3) thickness of the high-voltage wire: dh min<Dh<Dh max；
e. Low-voltage conductor width: wl min<Wl<Wl max；
f. And (3) thickness of a low-voltage wire: dl min<Dl<Dl max。
Wherein the content of the first and second substances,
P0、P0rrespectively representing the actual value and the rated value of no-load loss;
kP0is the no-load loss coefficient;
Pk、Pkrrespectively representing the actual value and the rated value of the load loss;
kPkis the load loss factor;
I0、I0rrespectively an actual value and a rated value of the no-load current;
Ukfor actual value of short-circuit impedance, Uk max、Uk minThe short circuit impedance values are respectively an upper bound and a lower bound;
η、ηractual efficiency and rated efficiency respectively;
Bm max、Bm minan upper limit and a lower limit of the magnetic flux density of the iron core are respectively set;
Jl、Jhactual values of current density of high and low voltage wires, Jl max、Jh maxThe maximum limiting values of the current density of the high-voltage wire and the low-voltage wire are respectively set;
Tl、Ththe actual values of temperature rise, T, of the high-voltage winding and the low-voltage winding respectivelyl max、Th maxRespectively setting the maximum limit values of the temperature rise of the high-voltage winding and the low-voltage winding;
Dmax、Dminrespectively taking an upper bound and a lower bound for the iron core lamination thickness;
Nc max、Nc minrespectively taking an upper bound and a lower bound for the layer number of the low-voltage winding;
Wh max、Wh minthe width of the high-voltage wire is respectively taken as an upper bound and a lower bound;
Dh min、Dh maxrespectively taking a lower bound and an upper bound for the thickness of the high-voltage wire;
Wl max、Wl minthe width of the low-voltage wire is respectively taken as an upper bound and a lower bound;
Dl min、Dl maxthe low voltage wire thickness values are the lower and upper bounds, respectively.
10. The energy-saving and material-saving optimization design method for the amorphous alloy dry type transformer according to claim 9, characterized in that: the mode of generating the initial population by the chaotic mapping mode comprises the following steps:
Li+1,j＝γLi,j+(1-Li,j)
wherein the content of the first and second substances,
Li,jis the j dimension chaotic variable of the ith individual;
gamma is a chaos factor, and gamma belongs to (0, 4);
when gamma is 4, the chaotic variable is in a complete chaotic state;
Xi,ja j dimension variable parameter of the ith individual; xj min,Xj maxRespectively the lower bound and the upper bound of the variable parameter of the j dimension of the population individual;
wherein the content of the first and second substances,
the calculation method of the virtual fitness (crowding distance) of the population individuals is as follows:
wherein the content of the first and second substances,
Corwd_disti 1(X) is a first objective function f of the ith individual1(X) degree of crowding;
Corwd_disti 2(X) is the ith individual second objective function f2(X) degree of crowding;
Corwd_disti(X) is the virtual fitness (crowding distance) of the ith population individual;
pre_f1(X)、next_f1(X) first objective function values for the (i-1) th individual and the (i + 1) th individual, respectively; f. of1 max、f1 minRespectively the maximum value and the minimum value of the first objective function;
pre_f2(X)、next_f2(X) second objective function values for the (i-1) th individual and the (i + 1) th individual, respectively;
f2 max、f2 minrespectively the maximum value and the minimum value of the second objective function;
in each domination level population individual, sorting according to the sizes of the first objective function value and the second objective function value respectively, and taking the crowdedness of the first individual and the last individual as infinity;
the selection, crossing and variation of population individuals generate offspring populations, and the genetic operations of the offspring populations respectively adopt a championship selection operation, a simulated binary crossing operation and a polynomial variation operation.
To further facilitate a more intuitive understanding of the present invention to those skilled in the art, the present invention is further described below in terms of specific embodiments.
An energy-saving and material-saving optimization design method for an amorphous alloy dry type transformer (see figure 1) adopts an improved NSGA-II optimization algorithm and carries out optimization design on amorphous alloy through an operable optimization system.
The specific operation process is as follows:
the first step is as follows: setting the main interface parameters (see fig. 4): and determining the rated capacity, the iron core form, the iron core material, the coupling group, the insulation grade and other operation parameters of the optimized object, and selecting the optimized design.
The embodiment of the invention takes an amorphous alloy dry-type transformer of SCLBH15-315/10 as an example, the rated capacity is 315kVA, the iron core is in a three-phase five-column type, the iron core is made of amorphous alloy, the coupling group is Dyn11, and the insulation grade is F grade.
The second step is that: set product run parameters (see fig. 5): and determining rated parameters, structural parameters, insulation distance, determination coefficient, line mode margin, performance tolerance, air channel type and unit price of materials of the product.
The third step: setting improved NSGA-II algorithm operation parameters and optimization variable parameters (see FIG. 6): setting the coding length, the population size, the genetic algebra, the selection probability, the cross probability and the variation probability of an optimization algorithm; setting the upper and lower value limits of optimized variables such as the iron core stack thickness, the low-voltage layer number, the high-voltage line width, the high-voltage line thickness, the low-voltage line width and the low-voltage line thickness;
the improved NSGA-II algorithm of the embodiment of the invention adopts a real number coding and integer coding mode to code the optimized variable, and adopts a chaos mapping mode to generate an initial population. The optimized variable parameter coding length is set to be 6, the population sizes of both the internal population and the external population in the initial population are set to be N equal to 100, the population genetic algebra is 200, the selection probability is 0.8, and the mutation probability is 1/6.
Setting an optimized variable value interval [ Xj min,Xj max]Wherein the value interval of the lamination thickness of the iron core is set as [50,100 ]]The value interval of the low-voltage layer number is set to be [15,25 ]]The high-voltage line width value interval is set to be [2,16 ]]The value interval of the high-voltage line thickness is set to be 0.8,5.6]The low-voltage line width value interval is set as [20,1400 ]]The value interval of the low-voltage line thickness is set to be [0.2,2.5 ]]。
And fourthly, calling a modified NSGA-II algorithm to carry out optimization calculation on the amorphous alloy dry-type transformer of SCLBH 15-315/10.
Firstly, generating an initial population in a set optimization variable value interval by adopting a chaotic mapping mode, wherein the initial population comprises an internal population P and an external population Pe。
Calculating an objective function f of each individual in the contemporary population1(X) and f2(X), performing rapid non-dominated sorting operation on each individual by comparing the objective function value of each individual to obtain sorted population individuals;
performing virtual fitness (crowding distance, Corwd _ dist) on the sorted population individuals of each domination leveli(X)) calculating. Obtaining a progeny population Q after selecting, crossing and mutating population individuals;
secondly, merging the parent population P and the child population Q into a new population R, firstly carrying out variation operation on the individuals with dense repetition in the merged population and calculating the objective function value of the individuals, then carrying out rapid non-dominant sorting operation on the merged population, and selecting the first N excellent individuals as the new parent population;
initializing and updating the external population by chaotic mapping, and setting the non-dominated sequencing sequence number in the new parent population to be 1 (F)1) Storing the individuals into the updated external population, and if the population genetic algebra does not reach the maximum genetic algebra of 200, returning the new parent population and the updated external population to execute the steps (3) to (6) to perform the next genetic operation;
finally, if the population genetic algebra reaches the maximum genetic algebra of 200, selecting an optimal design scheme with high efficiency, energy saving and low manufacturing cost according to different requirements of customers according to a plurality of groups of feasible amorphous alloy dry-type transformers output from the population;
and fourthly, outputting a plurality of optimization schemes which are acquired by the improved NSGA-II algorithm and meet the performance requirements, wherein the optimization schemes are as follows (in the table, the unit is mm):
| serial number | Stack thickness of iron core | Low-voltage layer number | High voltage linewidth | Thickness of high-voltage line | Low voltage line width | Low line thickness | f1(X) | f2(X) |
| 1 | 78 | 21 | 4.25 | 2.50 | 600 | 0.6 | 28054 | 3775 |
| 2 | 78 | 21 | 3.75 | 3.00 | 605 | 0.6 | 28196 | 3654 |
| 3 | 74 | 22 | 3.55 | 3.35 | 665 | 0.6 | 28489 | 3555 |
| 4 | 78 | 21 | 5.30 | 2.24 | 610 | 0.6 | 28662 | 3535 |
| 5 | 78 | 21 | 4.75 | 2.24 | 620 | 0.7 | 28867 | 3427 |
| 6 | 81 | 20 | 4.50 | 2.65 | 565 | 0.7 | 29196 | 3347 |
| 7 | 78 | 21 | 5.60 | 2.12 | 630 | 0.7 | 29429 | 3284 |
| 8 | 78 | 21 | 5.00 | 2.50 | 630 | 0.7 | 29526 | 3253 |
| 9 | 78 | 21 | 5.00 | 2.50 | 635 | 0.7 | 29679 | 3213 |
| 10 | 82 | 20 | 4.25 | 3.00 | 575 | 0.7 | 29786 | 3205 |
And selecting an optimal efficient energy-saving low-manufacturing-cost design scheme from the table according to different requirements of customers, wherein specific parameters of the optimal scheme are displayed on an output product optimization result interface (see fig. 7).
In the embodiment, an amorphous alloy dry-type transformer of SCLBH15-315/10 is taken as an example, and the optimization design is carried out by respectively adopting an NSGA-II algorithm and an improved NSGA-II algorithm. As can be seen from fig. 8 and 9, the improved NSGA-II algorithm enhances the diversity of the population, effectively improves the phenomenon that denser individuals repeatedly appear in the population, makes the obtained Pareto solutions more uniformly distributed, and provides more feasible design solutions for designers. In this embodiment, the optimized variable parameter values and the objective function values of the original design of the amorphous alloy dry-type transformer of SCLBH15-315/10 are as follows: iron core stack thickness (X)1) 83mm, low pressure layer number (X)2) Is 20 layers, high voltage line width (X)3) 4.75mm, high voltage line thickness (X)4) 1.9mm, low voltage line width (X)5) 600mm, low voltage line thickness (X)6) 0.7mm, the main material cost f1(X) is 29590 yuan, total loss f2(X) is 3745W. From the above table, on the premise of meeting the performance requirements of the amorphous alloy dry-type transformer, compared with the original design, the 2 nd to 8 th optimization schemes obtained by adopting the improved NSGA-II algorithm can effectively reduce the manufacturing cost of the transformer and improve the loss of the transformer. In addition, the optimization design system for the amorphous alloy dry-type transformer is simple to operate, the optimization calculation time of the embodiment is within 1 minute each time, the design period is greatly shortened, and the design process is accelerated.
While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all such alterations and modifications as fall within the scope of the invention. The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, it should be noted that any modifications, equivalents and improvements made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (10)
1. A be used for energy-conserving material-saving optimal design system of metallic glass dry-type transformer, its characterized in that:
the system comprises an amorphous alloy dry-type transformer optimization design system main interface parameter setting module, an amorphous alloy dry-type transformer optimization design system product operation parameter input module, an amorphous alloy dry-type transformer optimization design system improved NSGA-II optimization algorithm parameter and optimization variable parameter upper limit and lower limit setting module, an amorphous alloy dry-type transformer optimization design system improved NSGA-II algorithm optimization processing module and an amorphous alloy dry-type transformer optimization design system output optimization result module;
wherein the content of the first and second substances,
the amorphous alloy dry-type transformer optimization design system main interface parameter setting module is used for determining rated capacity, iron core form, iron core material, coupling group and insulation grade operation parameters of an optimized object;
the amorphous alloy dry-type transformer optimization design system product operation parameter input module is used for inputting transformer optimization calculation operation parameters, and the transformer optimization calculation operation parameters comprise rated parameters, structural parameters, insulation distance, determination coefficients, line mode margin, performance tolerance, air passage type and material unit price parameters;
the optimized design system of the amorphous alloy dry-type transformer comprises an optimized design system, an optimized design system and an optimized design system, wherein the optimized design system comprises an optimized design system of an amorphous alloy dry-type transformer, an optimized design system of the amorphous alloy;
the optimized design system of the amorphous alloy dry-type transformer is characterized in that an improved NSGA-II algorithm optimized processing module is used for establishing a transformer optimized model, and the economic index and the loss index of the amorphous alloy dry-type transformer are optimized and solved by adopting an NSGA-II algorithm under the condition that the constraint conditions of electrical performance, material performance and material specification are met;
the output optimization result module of the amorphous alloy dry type transformer optimization design system is used for outputting a plurality of optimization schemes which are obtained by an improved NSGA-II algorithm and meet performance requirements, and selecting an optimal high-efficiency energy-saving low-cost optimization design scheme according to different requirements of customers.
2. The energy-saving and material-saving optimization design system for the amorphous alloy dry type transformer according to claim 1, characterized in that: the rated parameters in the operation parameter input module of the amorphous alloy dry type transformer optimization design system are specifically used for setting parameters of the product model specification, the product rated capacity, the high-voltage rated voltage, the low-voltage rated voltage, the working frequency, the load loss, the no-load loss, the impedance voltage, the no-load current and the temperature rise limit value of the high-low voltage winding.
3. The energy-saving and material-saving optimization design system for the amorphous alloy dry type transformer according to claim 1, characterized in that: the structural parameters in the operation parameter input module of the amorphous alloy dry type transformer optimization design system are specifically used for setting the material and the shape of a high-voltage winding and a low-voltage winding, the winding and parallel form of a high-voltage lead, the number of the iron core, the number of the sections of the high-voltage winding, the thickness of an upper clamping piece, the thickness of a lower clamping piece and the thickness of an end clamping piece.
4. The energy-saving and material-saving optimization design system for the amorphous alloy dry type transformer according to claim 1, characterized in that: the insulation distance in the amorphous alloy dry-type transformer optimization design system operation parameter input module is specifically used for setting iron core gap, small window gap, epoxy cylinder or paperboard thickness, epoxy cylinder middle reinforcing plate thickness, air channel thickness, high-voltage lead insulation thickness, low-voltage outer layer thickness, main air channel thickness, high-voltage inner layer thickness, high-voltage outer layer thickness, end insulation, high-voltage lead interlayer insulation thickness and low-voltage lead interlayer insulation thickness parameters.
5. The energy-saving and material-saving optimization design system for the amorphous alloy dry type transformer according to claim 1, characterized in that: the determined coefficients in the operation parameter input module of the amorphous alloy dry type transformer optimization design system are specifically used for setting parameters of an iron core lamination coefficient, an iron core loss coefficient, an iron core lap joint coefficient, a low-voltage winding overlapping thickness coefficient, a high-voltage winding overlapping thickness coefficient, a load loss coefficient, a high-voltage winding temperature rise coefficient, a low-voltage winding temperature rise coefficient and a copper foil coefficient;
the performance tolerance in the operation parameter input module of the amorphous alloy dry-type transformer optimization design system is used for setting an allowable upper limit and a lower limit of impedance voltage, a no-load loss tolerance value and a load loss tolerance value;
the line mode margin in the operation parameter input module is used for setting a line mode width margin and a line mode length margin;
the air channel type in the operation parameter input module is used for setting the high-pressure side air channel type and the low-pressure side air channel type.
6. The energy-saving and material-saving optimization design system for the amorphous alloy dry type transformer according to claim 1, characterized in that: the material unit price in the amorphous alloy dry-type transformer optimization design system operation parameter input module is specifically used for setting amorphous alloy unit price, high-voltage aluminum flat wire unit price, high-voltage copper round wire unit price, low-voltage copper foil unit price, low-voltage aluminum foil unit price, clamping piece unit price and accessory unit price parameters;
based on the setting of the upper and lower bounds of the optimization algorithm parameters and the optimization variable parameters, an improved NSGA-II algorithm optimization processing module in the amorphous alloy dry type transformer optimization design system is used for carrying out program internal optimization calculation on the established transformer optimization model;
the output optimization result module of the amorphous alloy dry-type transformer optimization design system is specifically used for displaying various feasible optimization results and outputting main transformer parameter values in an optimization scheme by selecting one of the optimization results;
the obtained optimization scheme can be output and stored in 3 forms, namely in the form of Txt text; secondly, outputting and storing in the form of an Excel calculation sheet; and thirdly, outputting and storing in the form of an Access database.
7. The energy-saving and material-saving optimization design method for the amorphous alloy dry type transformer is characterized by comprising the following steps of:
step 1:
determining optimization variables and constraint conditions in an improved NSGA-II optimization model according to an optimization target of the amorphous alloy dry-type transformer; the optimization variables comprise iron core stack thickness, low-voltage layer number, a high-voltage wire gauge and a low-voltage wire gauge; the constraint conditions comprise electrical property constraint, material property constraint and process constraint;
step 2:
acquiring an initial design scheme of the amorphous alloy dry-type transformer by manual design, and determining the upper and lower value limits of the optimized variables;
and step 3:
determining the number and the length of genes contained in a single individual of a population in the NSGA-II algorithm according to the number of optimized variables, coding the genes of the population individual by setting the size of the population and the upper and lower value limits of each gene in a real number coding and integer coding mode, and generating an initial population by a chaotic mapping mode so as to enhance the diversity of the population; wherein the initial population comprises an inner population P and an outer population PeThe internal population participates in genetic evolution, is continuously initialized and updated in a chaotic mapping mode and participates in the selection operation of the population; the number of genes contained in the population individual is determined by the optimization variable;
and 4, step 4:
calculating an objective function value of each individual in the current-generation population by the optimized objective function, and performing rapid non-dominated sorting operation on the objective function values by comparing the objective function values of each individual to obtain sorted population individuals;
and 5:
performing virtual fitness calculation, namely congestion distance calculation, on the sorted population individuals of each domination level, and obtaining a offspring population Q after performing selection, crossing and variation operations on the population individuals;
step 6:
combining the parent population and the offspring population into a new population R, firstly carrying out variation operation on the individuals with dense repetition in the combined population and calculating the objective function value of the individuals, then carrying out rapid non-dominated sorting operation on the combined population, and selecting the first N excellent individuals as the new parent population;
and 7:
performing initialization updating operation on the external population by adopting a chaotic mapping mode, and setting the non-dominated sorting sequence number in the new parent population to be 1 (F)1) Storing the individuals into the updated external population, and if the population genetic algebra does not reach the maximum iteration times, returning the new parent population and the updated external population to execute the steps 3-6 to perform the next genetic operation;
and 8:
and if the population genetic algebra reaches the maximum iteration times, selecting an optimal design scheme with high efficiency, energy conservation and low manufacturing cost according to different requirements of customers according to a plurality of groups of feasible amorphous alloy dry-type transformers output in the population.
8. The energy-saving and material-saving optimization design method for the amorphous alloy dry type transformer according to claim 7, characterized in that:
the optimization target comprises an economic index and a loss index, wherein the economic index is the main material cost, and the loss index is the total loss:
wherein APC (X) is the cost of the main material; NLL (X) is the no-load loss; LL (X) is load loss; x ═ X1,X2,...,Xn]To optimize variablesA parameter;
wherein the main material cost f1(X) and total loss f2(X) is respectively:
f1(X)＝min(Ccore×Wcore+Clow×Wlow+Chigh×Whigh)
f2(X)＝min(K×Vcore×ρcore×fα×Bm β+k1×Ihigh 2×Rhigh+k2×Ilow 2×Rlow)
wherein the content of the first and second substances,
Ccore、Clow、Chighthe unit price of the amorphous alloy iron core, the low-voltage winding and the high-voltage winding is respectively;
Wcore、Wlow、Whighthe weights of the amorphous alloy iron core, the low-voltage winding and the high-voltage winding are respectively set;
K. alpha and beta are the material coefficients of the iron core;
Vcoreis the volume of the iron core;
ρcoreis the amorphous alloy density;
f, the working frequency of the transformer;
Bmis the core flux density;
k1、k2the loss coefficients of the high-voltage winding and the low-voltage winding are respectively;
Ihigh、Ilowhigh and low voltage winding phase currents, respectively;
Rhigh、Rlowrespectively high and low voltage winding resistances.
9. The energy-saving and material-saving optimization design method for the amorphous alloy dry type transformer according to claim 7 or 8, wherein the method comprises the following steps: the electrical property constraint, the material property constraint and the material specification constraint are as follows:
1) the electrical performance constraints are as follows:
a. no-load loss: p0<kP0×P0r；
b. Load loss: pk<kPk×Pkr；
c. No-load current: i is0<I0r；
d. Short-circuit impedance: u shapek min<Uk<Uk max；
e. Efficiency: eta>ηr；
2) The material property constraints are as follows:
a. core magnetic flux density: b ism min<Bm<Bm max；
b. Current density of low-voltage wire: j. the design is a squarel<Jl max；
c. Current density of the high-voltage wire: j. the design is a squareh<Jh max；
d. Temperature rise of the low-voltage winding: t isl<Tl max；
e. Temperature rise of the high-voltage winding: t ish<Th max；
3) The material specification constraints are as follows:
a. iron core lamination thickness: dmin<Dt<Dmax；
b. The number of layers of the low-voltage winding is as follows: n is a radical ofc min<Nc<Nc max；
c. High-voltage wire width: wh min<Wh<Wh max；
d. And (3) thickness of the high-voltage wire: dh min<Dh<Dh max；
e. Low-voltage conductor width: wl min<Wl<Wl max；
f. And (3) thickness of a low-voltage wire: dl min<Dl<Dl max。
Wherein the content of the first and second substances,
P0、P0rrespectively representing the actual value and the rated value of no-load loss;
kP0is the no-load loss coefficient;
Pk、Pkrrespectively representing the actual value and the rated value of the load loss;
kPkis the load loss factor;
I0、I0rrespectively an actual value and a rated value of the no-load current;
Ukfor actual value of short-circuit impedance, Uk max、Uk minThe short circuit impedance values are respectively an upper bound and a lower bound;
η、ηractual efficiency and rated efficiency respectively;
Bm max、Bm minan upper limit and a lower limit of the magnetic flux density of the iron core are respectively set;
Jl、Jhactual values of current density of high and low voltage wires, Jl max、Jh maxThe maximum limiting values of the current density of the high-voltage wire and the low-voltage wire are respectively set;
Tl、Ththe actual values of temperature rise, T, of the high-voltage winding and the low-voltage winding respectivelyl max、Th maxRespectively setting the maximum limit values of the temperature rise of the high-voltage winding and the low-voltage winding;
Dmax、Dminrespectively taking an upper bound and a lower bound for the iron core lamination thickness;
Nc max、Nc minrespectively taking an upper bound and a lower bound for the layer number of the low-voltage winding;
Wh max、Wh minthe width of the high-voltage wire is respectively taken as an upper bound and a lower bound;
Dh min、Dh maxrespectively taking a lower bound and an upper bound for the thickness of the high-voltage wire;
Wl max、Wl minthe width of the low-voltage wire is respectively taken as an upper bound and a lower bound;
Dl min、Dl maxthe low voltage wire thickness values are the lower and upper bounds, respectively.
10. The energy-saving and material-saving optimization design method for the amorphous alloy dry type transformer according to claim 9, characterized in that: the mode of generating the initial population by the chaotic mapping mode comprises the following steps:
Li+1,j＝γLi,j+(1-Li,j)
wherein the content of the first and second substances,
Li,jis the j dimension chaotic variable of the ith individual;
gamma is a chaos factor, and gamma belongs to (0, 4);
when gamma is 4, the chaotic variable is in a complete chaotic state;
Xi,ja j dimension variable parameter of the ith individual; xj min,Xj maxRespectively the lower bound and the upper bound of the variable parameter of the j dimension of the population individual;
wherein the content of the first and second substances,
the calculation method of the virtual fitness (crowding distance) of the population individuals is as follows:
wherein the content of the first and second substances,
Corwd_disti 1(X) is a first objective function f of the ith individual1(X) degree of crowding;
Corwd_disti 2(X) is the ith individual second objective function f2(X) degree of crowding;
Corwd_disti(X) is the virtual fitness of the ith population individual;
pre_f1(X)、next_f1(X) first objective function values for the (i-1) th individual and the (i + 1) th individual, respectively; f. of1 max、f1 minRespectively the maximum value and the minimum value of the first objective function;
pre_f2(X)、next_f2(X) is the (i-1) th individual and the (X) th individualA second objective function value for i +1 individuals;
f2 max、f2 minrespectively the maximum value and the minimum value of the second objective function;
in each domination level population individual, sorting according to the sizes of the first objective function value and the second objective function value respectively, and taking the crowdedness of the first individual and the last individual as infinity;
the selection, crossing and variation of population individuals generate offspring populations, and the genetic operations of the offspring populations respectively adopt a championship selection operation, a simulated binary crossing operation and a polynomial variation operation.
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| CN115310353B (en) * | 2022-07-26 | 2024-02-20 | 明珠电气股份有限公司 | Power transformer design method based on rapid multi-objective optimization |
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