Parameter optimization method for shunt reactor with mixed iron core cake structure and reactor

Abstract

The invention discloses a parallel reactor parameter optimization method of a mixed iron core cake structure and a reactor, and relates to the technical field of reactors. Comprising the following steps that an optimization target and optimization variables are determined, and the optimization variables comprise the non-oriented silicon steel sheet proportion, the iron core diameter, the iron yoke height, the air gap height and the air gap number; after electromagnetic characteristic parameters are obtained, a finite element simulation model is established based on the parameters and optimization variables, and simulation values under different variable combinations are analyzed. A sensitivity index is generated through a sensitivity analysis method, the correlation degree of an optimization variable and a target is judged, and the correlation degree is divided into two levels. After environment parameters are obtained, a simulation value is corrected, and a fitness function and a constraint condition function are generated; and the optimal solution of the optimization variable is obtained by adopting a multi-target genetic algorithm, so that the parameter optimization of the reactor is completed, meanwhile, the requirements of the extra-high voltage shunt reactor on relatively small vibration and loss are met, and the method can be widely applied to actual power grid engineering.

Description

Technical Field

[0001] The present invention relates to the technical field of reactors, and in particular to a method for optimizing parameters of a shunt reactor with a hybrid iron core cake structure and a reactor. Background Art

[0002] UHV shunt reactors are used to compensate for capacitive current in the line, suppress the rise in power frequency voltage and operating overvoltage at the end of the line caused by capacitive reactive power under light load conditions, and are important reactive compensation equipment to ensure the safety and stability of the power system. The high voltage level and large capacity of UHV shunt reactors make temperature rise and vibration problems increasingly serious. Therefore, achieving multi-objective optimization while meeting the performance and technical parameter requirements of iron core reactors such as electromagnetic, temperature rise and vibration has become an engineering requirement.

[0003] The core of the reactor is made of stacked silicon steel sheets. The core column is composed of multiple core cakes stacked and divided into uniform small sections by air gaps. The air gaps are separated by epoxy laminated glass cloth plates to prevent the air gap from changing during the operation of the reactor. Silicon steel sheets are divided into oriented silicon steel sheets and non-oriented silicon steel sheets. According to the research of domestic and foreign scholars, for the core stacked with oriented silicon steel sheets, the magnetostrictive effect and Maxwell force will promote each other under the action of the magnetic field. The core vibrates significantly during operation, but the loss is relatively low. For the core stacked with non-oriented silicon steel sheets, the magnetostrictive effect and Maxwell force offset each other, but the loss is relatively large.

[0004] At present, the design of reactor cores generally adopts oriented silicon steel sheets, which vibrate significantly during operation. There is a lack of multi-objective optimization design methods that consider both reducing vibration and reducing losses.

[0005] In the prior art, the publication number CN106229995B discloses a method for optimizing the parameters of the backup power supply shunt reactor based on the typhoon-resistant operation mode of the wind farm, and the optimization method includes the following process: first, the system in the typhoon-resistant operation is modeled as a whole, and the system model includes the backup power supply, the backup power supply shunt reactor, the backup power supply transformer, the direct buried cable and the equivalent model of multiple multi-way wind turbines; then, the power loss of the system components in the model is calculated respectively; finally, the parameters of the reactor that needs to be connected in parallel are determined according to the system power factor before optimization and the power factor to be achieved after optimization. However, this optimization method only mentions determining the parameters of the shunt reactor according to the power factor, and lacks consideration of multi-objective optimization. At the same time, the data are all obtained under ideal conditions. When quoted in the actual environment, there may be large errors, and the constraints in the optimization process are not clearly listed. Therefore, the accuracy and effectiveness of the optimization results are reduced.

[0006] The above information disclosed in this Background section is only for enhancement of understanding of the background of the present disclosure and therefore it may contain information that does not constitute the prior art that is already known to one of ordinary skill in the art. Summary of the invention

[0007] The object of the present invention is to provide a method for optimizing parameters of a shunt reactor of a hybrid iron core cake structure and a reactor, so as to solve the problems raised in the above background technology.

[0008] To achieve the above object, the present invention provides the following technical solutions: A method for optimizing parameters of a shunt reactor of a hybrid core disk structure, the specific steps comprising: Determine the optimization target and optimization variables of the hybrid core cake structure ultra-high voltage shunt reactor, wherein the hybrid core cake structure is specifically formed by stacking oriented silicon steel sheets and non-oriented silicon steel sheets at the same time, the optimization target includes the maximum vibration displacement of the ultra-high voltage shunt reactor, the amount of core metal and the core loss, and the optimization variables include the proportion of non-oriented silicon steel sheets, the core diameter, the iron yoke height, the air gap height and the number of air gaps; Obtaining electromagnetic characteristic parameters of the UHV shunt reactor, establishing a finite element simulation model of the UHV shunt reactor based on the electromagnetic characteristic parameters and optimization variables of the UHV shunt reactor, and analyzing the simulation values ​​of each optimization target under different combinations of optimization variables through the finite element simulation model, wherein the electromagnetic characteristic parameters include the number of turns of the core winding, the radial cross-sectional area of ​​the core column, the elastic modulus of the core material, and the working power supply voltage and frequency; According to different combinations of optimization variables, the simulation values ​​of each optimization target are obtained. Combined with the sensitivity analysis method, the sensitivity index of each optimization target and the optimization variable is generated. The correlation between the optimization variable and the optimization target is judged by the sensitivity index. According to the correlation, the design variables and the optimization target are divided into two levels, among which the maximum vibration displacement and core loss of the UHV shunt reactor are the optimization targets of the first level, the proportion of non-oriented silicon steel sheets and the number of air gaps are the optimization variables of the first level, and the rest are classified as the second level. The environmental parameters of the working place of the UHV shunt reactor are obtained, and the simulation values ​​of each optimization target under different optimization variable combinations are corrected based on the obtained environmental parameters to obtain the actual correction value of each optimization target. According to the actual correction value of each optimization target, two levels of fitness functions are generated in combination with electromagnetic characteristic parameters. At the same time, constraint condition functions are established through electromagnetic characteristic parameters. Based on the fitness function and constraint condition function of the corresponding levels, a multi-objective genetic algorithm is used to obtain the optimal solution of the corresponding optimization variable, and complete the parameter optimization of the UHV shunt reactor with a hybrid iron core disk structure.

[0009] Furthermore, a finite element simulation model of the UHV shunt reactor is established based on the electromagnetic characteristic parameters and optimization variables of the UHV shunt reactor, wherein the specific method for establishing the finite element simulation model is as follows: a geometric model of the reactor is established in the selected finite element software, a 3D model of the core and winding is created according to the acquired electromagnetic characteristic parameters and optimization variables, the conductivity and permeability characteristics of the core and winding are defined respectively, a voltage source or a current source is applied, the operating frequency is determined, the mesh type is selected, a finite element analysis is performed on the model, and the corresponding optimization target value is obtained by changing the combination of optimization variables.

[0010] Furthermore, according to different combinations of optimization variables, the simulation values ​​of each optimization target are obtained, and the sensitivity index of each optimization target and optimization variable is generated by combining the sensitivity analysis method. The specific formula for calculating the sensitivity index of each optimization target and optimization variable is as follows: ; In the formula, is the sensitivity index between the i-th optimization variable and the j-th optimization objective, For the i-th optimization variable For the jth optimization goal The unconditional variance of is the jth optimization objective The unconditional variance of Represents a given optimization variable Under the condition of The conditional probability of , where i is the index of the optimization variable and j is the index of the optimization target.

[0011] Furthermore, the environmental parameters of the working place of the UHV shunt reactor are obtained, and the simulation values ​​of each optimization target under different optimization variable combinations are corrected based on the obtained environmental parameters to obtain the actual correction value of each optimization target, wherein the actual correction value of each optimization target is calculated based on the formula: ; In the formula, is the actual correction value of core loss, is the core loss simulation value obtained through the finite element analysis model, is the actual correction value of the maximum vibration displacement, is the maximum vibration displacement simulation value obtained through the finite element analysis model, is the actual correction value of the core metal usage, is the simulation value of the core metal content obtained through the finite element analysis model, is the daily average temperature at the working place of the UHV shunt reactor, is the daily average humidity at the working place of the UHV shunt reactor, and are the reference temperature and reference humidity respectively, where and is the temperature and humidity influence constant, where and Both are greater than 0.

[0012] Furthermore, according to the actual correction value of each optimization target, two levels of fitness functions are generated in combination with the electromagnetic characteristic parameters, wherein the formula for the specific calculation of the first level fitness function is as follows: ; In the formula, is the fitness function value of the first level, represents the optimization variable combination of the first level, is the core stiffness, and is the actual correction value of the maximum vibration displacement and the weight coefficient of the core stiffness, where , ,and and All are greater than 0; ; In the formula, is the second level fitness function value, Represents the second-level optimization variable combination.

[0013] Furthermore, a group of optimization variable combinations is taken as an individual, and the optimization variables in the combination are taken as genes. The specific logic is: all the data of the optimization variables in the combination are encoded as corresponding genes, and the target parameters of the same type are alleles to each other, that is, there are 2 genes corresponding to the optimization variable combination of the first level, including the proportion of non-oriented silicon steel sheets and the number of air gaps. All optimization variable combinations are encoded to obtain a total of several individuals, namely ; Based on all the individuals obtained, the initial population is constructed and the initial population is marked as ,and , represents the index of different individuals in the initial population, and u=1,2, , D, where each individual There are two genes in each case, and the two genes correspond to a certain parameter value of the proportion of non-oriented silicon steel sheets and the number of air gaps respectively; The second level of optimization variable combination individuals and populations are established in the same way as the first level, except that each individual There are three corresponding genes, including core diameter, iron yoke height and air gap height.

[0014] Furthermore, a constraint condition function is established by using electromagnetic characteristic parameters, wherein the constraint condition function is specifically based on the formula: ; In the formula, is the actual value of the inductance of the UHV shunt reactor, is the target inductance value of the UHV shunt reactor, is the core magnetic flux density, is the core saturation flux density, is the working power supply voltage, is the working power frequency, is the radial cross-sectional area of ​​the core column; The multi-objective genetic algorithm is used to obtain the optimal solution of the corresponding optimization variable. The specific logic is as follows: the initial population is cyclically selected, crossed and mutated, and the individual with the highest fitness in the previous population is placed in the next iteration population to generate an iteration population containing multiple new individuals. It is determined whether the maximum number of iterations has been reached. When it is greater than the maximum number of iterations, the individual with the highest fitness function value in the current population is selected as the optimal optimization parameter combination. Otherwise, the generated iteration population is used as the initial population for iteration until the iteration termination condition is met. The optimization process parameter combination with the largest fitness value that appears during the iteration process is selected as the optimal target parameter combination, wherein the iteration termination condition is the set maximum number of iterations, and the mutation operation needs to set the mutation rate. The specific formula for dynamic adjustment of the mutation rate is: ; In the formula, is the dynamically adjusted mutation rate, is the initial mutation rate set, is the standard deviation of the fitness of the current iteration population.

[0015] The present invention also provides a shunt reactor with a hybrid iron core cake structure, which is used to construct the reactor in the above-mentioned shunt reactor parameter optimization method with a hybrid iron core cake structure. The shunt reactor with a hybrid iron core cake structure is composed of an iron core and a winding coil as a whole. The iron core is divided into two parts: an iron core column and an iron yoke. The iron core column is composed of a discus and an air gap. The coil is fitted with the iron core column and fixed by end pads. The iron core column is fixed into a whole by screws and upper and lower iron yoke clamps. The coil of the iron core reactor is wound by enameled flat copper wire and arranged tightly and evenly. The iron core is stacked by silicon steel sheets, and the air gap is made of epoxy resin material.

[0016] Compared with the prior art, the present invention has the following beneficial effects: Firstly, a shunt reactor with a hybrid core cake structure is proposed. The core cake is made of oriented silicon steel sheets and non-oriented silicon steel sheets, which makes the vibration and loss small at the same time. By clarifying the optimization objectives and optimization variables, the influence of different design schemes on the performance of the reactor can be systematically evaluated. The optimization objectives include maximum vibration displacement, core metal usage and core loss, which are directly related to the economy and operation safety of the reactor. The hybrid structure design of oriented silicon steel sheets and non-oriented silicon steel sheets can not only effectively reduce the core loss, but also optimize the use of materials, improve the mechanical strength, and thus reduce the vibration displacement. This design strategy ensures the reliability and durability of the reactor under high-voltage working conditions. Secondly, after considering the influence of environmental parameters, the simulation values ​​under different optimization variable combinations are corrected, so that the final optimization results can be more in line with the actual operating conditions. This consideration of environmental adaptability ensures that the reactor can maintain excellent performance in practical applications and avoid performance degradation caused by environmental changes. Based on the multi-physics field simulation calculation method, the hierarchical optimization method is used to obtain the optimal structural parameters through a multi-objective genetic algorithm, which can simultaneously meet the requirements of low vibration and loss of UHV shunt reactors and can be widely used in actual power grid projects. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 It is a schematic diagram of the overall method flow of the present invention; Figure 2 This is a topological schematic diagram of the UHV shunt reactor of the present invention; Figure 3 This is a structural diagram of the hybrid iron core cake of the ultra-high voltage shunt reactor of the present invention. DETAILED DESCRIPTION

[0018] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with specific embodiments.

[0019] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the present invention should be understood by people with ordinary skills in the field to which the present invention belongs. The words "first", "second" and similar words used in the present invention do not indicate any order, quantity or importance, but are only used to distinguish different components. "Include" or "comprise" and similar words mean that the elements or objects appearing before the word include the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0020] Example: See also Figure 1-Figure 3 , the present invention provides a technical solution: A method for optimizing parameters of a shunt reactor of a hybrid core disk structure, the specific steps comprising: Step 1: Determine the optimization objectives and optimization variables of the hybrid core cake structure ultra-high voltage shunt reactor, wherein the hybrid core cake structure is specifically formed by stacking oriented silicon steel sheets and non-oriented silicon steel sheets at the same time, the optimization objectives include the maximum vibration displacement of the ultra-high voltage shunt reactor, the core metal usage and the core loss, and the optimization variables include the proportion of non-oriented silicon steel sheets, the core diameter, the iron yoke height, the air gap height and the number of air gaps.

[0021] In order to solve the problem that UHV shunt reactors cannot meet the requirements of low vibration and low loss at the same time, a UHV shunt reactor topology is designed in which the core cakes are made of oriented silicon steel sheets and non-oriented silicon steel sheets. After a large number of experimental tests, it is known that the magnetostriction curve of non-oriented silicon steel sheets mainly shows elongation deformation of silicon steel sheets, while the magnetostriction curve of oriented silicon steel sheets mainly shows contraction deformation. According to the research of domestic and foreign scholars, when the power frequency current is passed through the winding, magnetic poles will be induced between the core cakes of the UHV shunt reactor, causing the core cakes to attract each other. Therefore, the magnetostriction elongation effect of the core made of non-oriented silicon steel sheets and the mutually attractive Maxwell force offset each other, and the vibration is smaller than that of the core made of oriented silicon steel sheets.

[0022] At the same time, oriented silicon steel sheets have superior magnetic properties in a certain direction. When the current flows along the oriented grains, it can significantly reduce magnetic losses and improve the overall efficiency of the UHV shunt reactor. Therefore, a combination of oriented silicon steel sheets and non-oriented silicon steel sheets is used, in which the non-oriented silicon steel sheets are higher, so that the magnetostrictive elongation effect of the core cake and the mutually attractive Maxwell force are offset, and the overall vibration and loss of the UHV shunt reactor are small.

[0023] Step 2: Obtain the electromagnetic characteristic parameters of the UHV shunt reactor, establish a finite element simulation model of the UHV shunt reactor based on the electromagnetic characteristic parameters and optimization variables of the UHV shunt reactor, and analyze the simulation values ​​of each optimization target under different combinations of optimization variables through the finite element simulation model. The electromagnetic characteristic parameters include the number of turns of the core winding, the radial cross-sectional area of ​​the core column, the elastic modulus of the core material, and the working power supply voltage and frequency.

[0024] A finite element simulation model of an ultra-high voltage shunt reactor is established based on the electromagnetic characteristic parameters and optimization variables of the ultra-high voltage shunt reactor. The specific method for establishing the finite element simulation model is as follows: a geometric model of the reactor is established in the selected finite element software, a 3D model of the core and winding is created according to the obtained electromagnetic characteristic parameters and optimization variables, the conductivity and permeability characteristics of the core and winding are defined respectively, a voltage source or a current source is applied, the operating frequency is determined, the mesh type is selected, a finite element analysis is performed on the model, and the corresponding optimization target value is obtained by changing the combination of optimization variables.

[0025] In the reactor design stage, according to the rated power, frequency and working environment of the reactor, the appropriate core material and structure are selected, and the required column radial cross-sectional area is calculated using geometric relationships. The number of core winding turns can be obtained by consulting the material supplier or referring to the relevant material data manual. The elastic modulus of the selected core material is determined by laboratory testing. Common methods include tensile tests or compression tests, which can provide the strain characteristics of the material under different stress conditions; or by consulting relevant material databases or standards (such as ASTM, ISO, etc.), according to the type of material (such as oriented silicon steel, non-oriented silicon steel, etc.) to obtain the standard value of the elastic modulus. Determine the voltage and frequency of the working power supply according to the design requirements and operating conditions of the power system. Usually this is closely related to the standard frequency (such as 50Hz or 60Hz) and voltage level of the power system, or based on monitoring in the actual operating environment, record the voltage and frequency required by the equipment when working to ensure that it is within the design range.

[0026] Step 3: Under different combinations of optimization variables, the simulation values ​​of each optimization target are obtained. Combined with the sensitivity analysis method, the sensitivity index of each optimization target and the optimization variable is generated. The correlation between the optimization variable and the optimization target is judged by the sensitivity index. According to the correlation, the design variables and optimization targets are divided into two levels, among which the maximum vibration displacement and core loss of UHV shunt reactor are the optimization targets of the first level, the proportion of non-oriented silicon steel sheets and the number of air gaps are the optimization variables of the first level, and the rest are classified as the second level.

[0027] According to different combinations of optimization variables, the simulation values ​​of each optimization target are obtained. Combined with the sensitivity analysis method, the sensitivity index of each optimization target and optimization variable is generated. The specific formula for calculating the sensitivity index of each optimization target and optimization variable is as follows: ; In the formula, is the sensitivity index between the i-th optimization variable and the j-th optimization objective, For the i-th optimization variable For the jth optimization goal The unconditional variance of is the jth optimization objective The unconditional variance of Represents a given optimization variable Under the condition of The conditional probability of , where i is the index of the optimization variable and j is the index of the optimization target.

[0028] The sensitivity index calculation formula can be used to quantitatively obtain the influence of the optimization variables of the UHV shunt reactor on the physical field characteristic indicators, that is, the sensitivity. The greater the sensitivity, the greater the influence on the optimization target. When the sensitivity is positive, the optimization target is positively correlated with the optimization variable; when the sensitivity is negative, the optimization target is negatively correlated with the optimization variable. The unconditional variance and conditional probability calculation formulas are common technical means and will not be elaborated here.

[0029] According to the results of sensitivity analysis, the vibration displacement and core loss, which have extremely significant effects, are taken as the first-level optimization targets, the proportion of non-oriented silicon steel sheets and the number of air gaps are taken as the first-level optimization variables, the core amount is taken as the second-level optimization target, and the core diameter, iron yoke height 3 and air gap height are taken as the second-level optimization variables.

[0030] Step 4: Obtain the environmental parameters of the working place of the UHV shunt reactor, and based on the obtained environmental parameters, correct the simulation values ​​of each optimization target under different optimization variable combinations to obtain the actual correction value of each optimization target. According to the actual correction value of each optimization target, two levels of fitness functions are generated in combination with electromagnetic characteristic parameters. At the same time, constraint conditions functions are established through electromagnetic characteristic parameters. Based on the fitness functions and constraint conditions functions of the corresponding levels, a multi-objective genetic algorithm is used to obtain the optimal solution of the corresponding optimization variables, and complete the parameter optimization of the UHV shunt reactor with a hybrid iron core cake structure.

[0031] The environmental parameters of the working place of the UHV shunt reactor are obtained, and the simulation values ​​of each optimization target under different optimization variable combinations are corrected based on the obtained environmental parameters to obtain the actual correction value of each optimization target. The formula for calculating the actual correction value of each optimization target is: ; In the formula, is the actual correction value of core loss, is the core loss simulation value obtained through the finite element analysis model, is the actual correction value of the maximum vibration displacement, is the maximum vibration displacement simulation value obtained through the finite element analysis model, is the actual correction value of the core metal usage, is the simulation value of the core metal content obtained through the finite element analysis model, is the daily average temperature at the working place of the UHV shunt reactor, is the daily average humidity at the working place of the UHV shunt reactor, and are the reference temperature and reference humidity respectively, where and is the temperature and humidity influence constant, where and Both are greater than 0.

[0032] It should be noted that when humidity increases, the moisture in the air will cause a layer of water film to form on the surface of the core material, which may increase local conductivity and increase eddy current loss. In a high humidity environment, the resistivity of the core may decrease, resulting in higher eddy current loss. Humidity may also affect the magnetic properties of the core material, such as reducing the magnetic permeability of the material, resulting in increased hysteresis loss. Therefore, the daily average humidity at the working place of the UHV shunt reactor is proportional to the actual correction value of the core loss, which can be expressed through an exponential function. In a high humidity environment, the increase in losses will significantly affect the efficiency of the reactor. As the temperature rises, the magnetic permeability of the core material may change. Generally, the magnetic permeability of the material decreases with increasing temperature. This will lead to changes in hysteresis losses. Therefore, the daily average temperature at the working point of the UHV shunt reactor is proportional to the actual correction value of the core loss. Through the logarithmic function It means that temperature changes (especially when exceeding the reference temperature) will affect the resistivity of the core material, resulting in increased losses, but as the temperature gradually increases, the impact on core losses gradually decreases.

[0033] The increase in humidity may cause the physical properties of the core material (such as elastic modulus and density) to change, thus affecting the stiffness and vibration characteristics of the core. After the material absorbs moisture, its stiffness may decrease and the vibration displacement may increase. Therefore, the daily average humidity at the working place of the UHV shunt reactor is proportional to the actual correction value of the maximum vibration displacement. The proportional relationship is expressed in the form of . When the humidity decreases, the hygroscopicity of the core material decreases, and the moisture inside the material decreases, which may cause the physical properties of the material (such as elastic modulus) to increase. This increases the stiffness of the material, thereby enhancing its resistance to external vibrations. Due to the increase in stiffness, the core material will be more sensitive to vibrations, and the overall vibration characteristics will become more stable, which may reduce the maximum vibration displacement. Temperature changes may cause thermal expansion of the material, especially the difference in thermal expansion coefficients between different materials, which will cause changes in mechanical stress and displacement, thereby affecting the vibration characteristics. High temperature may cause the structure to loosen, thereby causing an increase in vibration displacement, which in turn affects the operating stability and reliability of the reactor. Through the square form Indicates the significant effect of temperature on vibration displacement.

[0034] Although the amount of metal may not change directly due to humidity changes, in order to ensure the normal operation of the reactor in a humid environment, it may be necessary to increase the amount of insulating material, which will indirectly affect the use of metal in the design. In a high humidity environment, it may be necessary to select metal materials with added anti-corrosion properties (such as stainless steel or galvanized materials), which will affect the overall metal usage. Therefore, the daily average humidity at the working place of the UHV shunt reactor is proportional to the actual correction value of the core metal usage, which can be calculated in the form of logarithm and square root. It means that the direct effect of humidity on the amount of metal used is relatively small, but there is also some indirect relationship. If the working environment temperature of the reactor is high, the design may consider using thicker metal materials or selecting materials with better high temperature performance, which will increase the amount of metal used. Represents the nonlinear effect of temperature on metal usage.

[0035] in is the daily average temperature at the working place of the UHV shunt reactor, The daily average humidity of the UHV shunt reactor working place is obtained by collecting the daily working environment parameters of the UHV shunt reactor within one month before the current date, including temperature and humidity, and calculating the average value based on the obtained working environment parameters. This average value is used as the daily average temperature and daily average humidity of the UHV shunt reactor working place. and It is the temperature and humidity influence constant, which can be set according to expert experience and generally ranges from 0 to 1.

[0036] According to the actual correction value of each optimization target, two levels of fitness function are generated in combination with the electromagnetic characteristic parameters. The formula for the specific calculation of the first level fitness function is as follows: ; In the formula, is the fitness function value of the first level, represents the optimization variable combination of the first level, is the core stiffness. The core stiffness characterizes the compressive strength of the core during vibration and can reflect the change of the maximum vibration displacement. Therefore, the displacement is characterized by the core stiffness and the actual correction value of the maximum vibration displacement, thus avoiding the error of a single data parameter. and is the actual correction value of the maximum vibration displacement and the weight coefficient of the core stiffness, where , ,and and All are greater than 0; ; In the formula, is the second level fitness function value, Represents the second-level optimization variable combination.

[0037] The core stiffness is calculated by the elastic modulus of the core material, the effective cross-sectional area of ​​the core and the effective length of the core. The specific formula is: ; In the formula, is the elastic modulus of the core material, is the effective cross-sectional area of ​​the core, is the effective length of the core. At the same time, since the actual correction value of the maximum vibration displacement is obtained by simulating the physical field, and the core stiffness only indirectly characterizes the vibration displacement, it is set , ,and and Both are greater than 0.

[0038] The fitness functions are all set with the goal of minimizing the maximum vibration displacement, core metal usage and core loss of the UHV shunt reactor. Minimizing the optimization target can improve the working quality and energy consumption of the reactor.

[0039] A group of optimization variable combinations is regarded as an individual, and the optimization variables in the combination are regarded as genes. The specific logic is: all the data of the optimization variables in the combination are encoded as corresponding genes, and the target parameters of the same type are alleles to each other, that is, there are 2 genes corresponding to the optimization variable combination of the first level, including the proportion of non-oriented silicon steel sheets and the number of air gaps. All optimization variable combinations are encoded to obtain a total of several individuals, namely ; Based on all the individuals obtained, the initial population is constructed and the initial population is marked as ,and , represents the index of different individuals in the initial population, and u=1,2, , D, where each individual There are two genes, and the two genes correspond to a certain parameter value of the proportion of non-oriented silicon steel sheets and the number of air gaps respectively; the parameter value corresponding to the proportion of non-oriented silicon steel sheets and the number of air gaps cannot exceed its value range, and the method for obtaining the value range of each optimization variable includes: determining the typical range of the optimization variable by referring to theoretical research, standards and specifications and literature in related fields, and making adjustments with reference to the industry standards or experimental specifications of UHV shunt reactors.

[0040] The second level of optimization variable combination individuals and populations are established in the same way as the first level, except that each individual There are three corresponding genes, including core diameter, iron yoke height and air gap height.

[0041] At the same time, the constraint condition function is established through the electromagnetic characteristic parameters, and the specific formula of the constraint condition function is: ; In the formula, is the actual value of the inductance of the UHV shunt reactor, is the target inductance value of the UHV shunt reactor, is the core magnetic flux density, is the core saturation flux density, is the working power supply voltage, is the working power frequency, is the radial cross-sectional area of ​​the core column; the target value of the inductance of the UHV shunt reactor is Set it according to the actual work needs. Consult the relevant material data manual or the technical information provided by the manufacturer. Many core materials (such as different types of silicon steel) will list the saturation flux density in their technical parameters. , or in the academic literature in the relevant electrical engineering and materials science fields, there are often studies on the magnetic properties of various core materials, and specific saturation flux density data can be found.

[0042] The multi-objective genetic algorithm is used to obtain the optimal solution of the corresponding optimization variables. The specific logic is as follows: the initial population is cyclically selected, crossed and mutated, and the individual with the highest fitness in the previous population is placed in the next iterative population to generate an iterative population containing multiple new individuals. It is judged whether the maximum number of iterations has been reached. When it is greater than the maximum number of iterations, the individual with the highest fitness function value in the current population is selected as the optimal optimization parameter combination. Otherwise, the generated iterative population is used as the initial population for iterative operation until the iteration termination condition is met. The optimization process parameter combination with the largest fitness value that appears during the iteration process is selected as the optimal target parameter combination.

[0043] The initial population is cycled through selection, crossover and mutation operations, where the logic of the selection operation is: select individuals in the population according to the fitness in the sequence, and select two individuals from the current sequence. The formula for calculating the probability of being selected is: ; In the formula, represents the first individual in the initial population The fitness of each individual, For the The probability of an individual being selected is ,and is a positive integer, and the roulette method is used to select individuals. The system randomly generates a A random number in the interval is distributed in the selection interval of the corresponding individual to determine the individual to be selected in this round according to the generated probability of being selected; The logic of performing the crossover operation is: performing the crossover operation on two selected individuals, exchanging the two selected individuals from a certain gene position and the chromosome fragment after the gene position, and obtaining two crossed individuals, wherein the crossover operation is performed on the two selected individuals, and the logic based on which the crossover operation is performed is: using a single-point crossover method to perform the crossover operation.

[0044] The logic of mutation operation is: the mutation operation is performed on the two new individuals generated by the crossover operation, and the mutation probability is set. The selected gene is mutated into one of its alleles, and the gene at the gene position is replaced with the mutated gene, thereby obtaining a new individual.

[0045] The iteration termination condition is the set maximum number of iterations, and the mutation operation needs to set the mutation rate. The formula for dynamic adjustment of the mutation rate is as follows: ; In the formula, is the dynamically adjusted mutation rate, is the initial mutation rate set, is the standard deviation of the fitness of the current iteration population. It should be noted that the standard deviation of the population fitness reflects the diversity of the population. A larger standard deviation indicates a high population diversity. A lower standard deviation indicates a poor population diversity and may fall into a local optimal solution. To avoid premature convergence, the mutation rate should be increased. The smaller the standard deviation, the lower the mutation rate, which encourages the exploration of a wider search space. Therefore, the standard deviation of the fitness of the current iteration population is inversely proportional to the dynamically adjusted mutation rate. Through the exponential function Indicates the significant effect of the fitness standard deviation on the mutation rate.

[0046] The iteration termination condition is a set maximum number of iterations, wherein the maximum number of iterations is generally set between 200 and 500.

[0047] See also Figure 2-Figure 3The present invention also provides a shunt reactor of a hybrid iron core cake structure, which is used to construct the reactor in the above-mentioned shunt reactor parameter optimization method of a hybrid iron core cake structure. The shunt reactor of the hybrid iron core cake structure is composed of an iron core and a winding coil as a whole. The iron core is divided into two parts: an iron core column and an iron yoke. The iron core column is composed of a discus and an air gap. The coil is fitted with the iron core column and fixed by end pads. The iron core column is fixed into a whole by screws and upper and lower iron yoke clamps. The coil of the iron core reactor is wound by enameled flat copper wire and arranged tightly and evenly. The iron core is stacked by silicon steel sheets, and the air gap is made of epoxy resin material.

[0048] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0049] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination thereof. When implemented by software, the above embodiments may be implemented in whole or in part in the form of a computer program product. Those skilled in the art may appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein may be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed by hardware or software methods depends on the specific application and design constraints of the technical solution.

[0050] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, and may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0051] The above description is only a specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application.

Claims

1. A method for optimizing parameters of a shunt reactor with a hybrid core cake structure, characterized in that: The specific steps include: Determine the optimization target and optimization variables of the hybrid core cake structure ultra-high voltage shunt reactor, wherein the hybrid core cake structure is specifically formed by stacking oriented silicon steel sheets and non-oriented silicon steel sheets at the same time, the optimization target includes the maximum vibration displacement of the ultra-high voltage shunt reactor, the amount of core metal and the core loss, and the optimization variables include the proportion of non-oriented silicon steel sheets, the core diameter, the iron yoke height, the air gap height and the number of air gaps; Obtaining electromagnetic characteristic parameters of the UHV shunt reactor, establishing a finite element simulation model of the UHV shunt reactor based on the electromagnetic characteristic parameters and optimization variables of the UHV shunt reactor, and analyzing the simulation values ​​of each optimization target under different combinations of optimization variables through the finite element simulation model, wherein the electromagnetic characteristic parameters include the number of turns of the core winding, the radial cross-sectional area of ​​the core column, the elastic modulus of the core material, and the working power supply voltage and frequency; According to different combinations of optimization variables, the simulation values ​​of each optimization target are obtained. Combined with the sensitivity analysis method, the sensitivity index of each optimization target and the optimization variable is generated. The correlation between the optimization variable and the optimization target is judged by the sensitivity index. According to the correlation, the design variables and the optimization target are divided into two levels, among which the maximum vibration displacement and core loss of the UHV shunt reactor are the optimization targets of the first level, the proportion of non-oriented silicon steel sheets and the number of air gaps are the optimization variables of the first level, and the rest are classified as the second level. The environmental parameters of the working place of the UHV shunt reactor are obtained, and the simulation values ​​of each optimization target under different optimization variable combinations are corrected based on the obtained environmental parameters to obtain the actual correction value of each optimization target. According to the actual correction value of each optimization target, two levels of fitness functions are generated in combination with electromagnetic characteristic parameters. At the same time, constraint condition functions are established through electromagnetic characteristic parameters. Based on the fitness function and constraint condition function of the corresponding levels, a multi-objective genetic algorithm is used to obtain the optimal solution of the corresponding optimization variable, and complete the parameter optimization of the UHV shunt reactor with a hybrid iron core disk structure.

2. The method for optimizing parameters of a shunt reactor of a hybrid core disk structure according to claim 1, characterized in that: A finite element simulation model of an ultra-high voltage shunt reactor is established based on the electromagnetic characteristic parameters and optimization variables of the ultra-high voltage shunt reactor. The specific method for establishing the finite element simulation model is as follows: a geometric model of the reactor is established in the selected finite element software, a 3D model of the core and winding is created according to the obtained electromagnetic characteristic parameters and optimization variables, the conductivity and permeability characteristics of the core and winding are defined respectively, a voltage source or a current source is applied, the operating frequency is determined, the mesh type is selected, a finite element analysis is performed on the model, and the corresponding optimization target value is obtained by changing the combination of optimization variables.

3. The method for optimizing parameters of a shunt reactor of a hybrid core disk structure according to claim 2, characterized in that: According to different combinations of optimization variables, the simulation values ​​of each optimization target are obtained. Combined with the sensitivity analysis method, the sensitivity index of each optimization target and optimization variable is generated. The specific formula for calculating the sensitivity index of each optimization target and optimization variable is as follows: ； In the formula, is the sensitivity index between the i-th optimization variable and the j-th optimization objective, For the i-th optimization variable For the jth optimization goal The unconditional variance of is the jth optimization objective The unconditional variance of Represents a given optimization variable Under the condition of The conditional probability of , where i is the index of the optimization variable and j is the index of the optimization target.

4. The method for optimizing parameters of a shunt reactor of a hybrid core disk structure according to claim 1, characterized in that: The environmental parameters of the working place of the UHV shunt reactor are obtained, and the simulation values ​​of each optimization target under different optimization variable combinations are corrected based on the obtained environmental parameters to obtain the actual correction value of each optimization target. The formula for calculating the actual correction value of each optimization target is: ； In the formula, is the actual correction value of core loss, is the core loss simulation value obtained through the finite element analysis model, is the actual correction value of the maximum vibration displacement, is the maximum vibration displacement simulation value obtained through the finite element analysis model, is the actual correction value of the core metal usage, is the simulation value of the core metal content obtained through the finite element analysis model, is the daily average temperature at the working place of the UHV shunt reactor, is the daily average humidity at the working place of the UHV shunt reactor, and are the reference temperature and reference humidity respectively, where and is the temperature and humidity influence constant, where and Both are greater than 0.

5. The method for optimizing parameters of a shunt reactor of a hybrid core disk structure according to claim 4, characterized in that: According to the actual correction value of each optimization target, two levels of fitness function are generated in combination with the electromagnetic characteristic parameters. The formula for the specific calculation of the first level fitness function is as follows: ； In the formula, is the fitness function value of the first level, represents the optimization variable combination of the first level, is the core stiffness, and is the actual correction value of the maximum vibration displacement and the weight coefficient of the core stiffness, where , ,and and All are greater than 0; ； In the formula, is the second level fitness function value, Represents the second-level optimization variable combination.

6. The method for optimizing parameters of a shunt reactor of a hybrid core disk structure according to claim 5, characterized in that: A group of optimization variable combinations is regarded as an individual, and the optimization variables in the combination are regarded as genes. The specific logic is: all the data of the optimization variables in the combination are encoded as corresponding genes, and the target parameters of the same type are alleles to each other, that is, there are 2 genes corresponding to the optimization variable combination of the first level, including the proportion of non-oriented silicon steel sheets and the number of air gaps. All optimization variable combinations are encoded to obtain a total of several individuals, namely ; Based on all the individuals obtained, the initial population is constructed and the initial population is marked as ,and , represents the index of different individuals in the initial population, and u=1,2, , D, where each individual There are two genes in each case, and the two genes correspond to a certain parameter value of the proportion of non-oriented silicon steel sheets and the number of air gaps respectively; The second level of optimization variable combination individuals and populations are established in the same way as the first level, except that each individual There are three corresponding genes, including core diameter, iron yoke height and air gap height.

7. The method for optimizing parameters of a shunt reactor of a hybrid core disk structure according to claim 5, characterized in that: At the same time, the constraint condition function is established through the electromagnetic characteristic parameters, and the specific formula of the constraint condition function is: ； In the formula, is the actual value of the inductance of the UHV shunt reactor, is the target inductance value of the UHV shunt reactor, is the core magnetic flux density, is the core saturation flux density, is the working power supply voltage, is the working power frequency, is the radial cross-sectional area of ​​the core column; The multi-objective genetic algorithm is used to obtain the optimal solution of the corresponding optimization variable. The specific logic is as follows: the initial population is cyclically selected, crossed and mutated, and the individual with the highest fitness in the previous population is placed in the next iteration population to generate an iteration population containing multiple new individuals. It is determined whether the maximum number of iterations has been reached. When it is greater than the maximum number of iterations, the individual with the highest fitness function value in the current population is selected as the optimal optimization parameter combination. Otherwise, the generated iteration population is used as the initial population for iteration until the iteration termination condition is met. The optimization process parameter combination with the largest fitness value that appears during the iteration process is selected as the optimal target parameter combination, wherein the iteration termination condition is the set maximum number of iterations, and the mutation operation needs to set the mutation rate. The specific formula for dynamic adjustment of the mutation rate is: ； In the formula, is the dynamically adjusted mutation rate, is the initial mutation rate set, is the standard deviation of the fitness of the current iteration population.

8. A shunt reactor with a hybrid iron core structure, characterized in that: The hybrid iron core cake structure shunt reactor is used to construct the reactor in the hybrid iron core cake structure shunt reactor parameter optimization method described in any one of claims 1 to 7, including: the hybrid iron core cake structure shunt reactor is composed of an iron core and a winding coil as a whole, the iron core is divided into two parts: an iron core column and an iron yoke, the iron core column is composed of a disc and an air gap, the coil is fitted with the iron core column and fixed by end pads, the iron core column is fixed into a whole by screws and upper and lower iron yoke clamps, the coil of the iron core reactor is wound by enameled flat copper wire and arranged tightly and evenly, the iron core is stacked by silicon steel sheets, and the air gap is made of epoxy resin material.

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