CN117436344B - Wind turbine blade structure optimization design method based on parameterization description - Google Patents

Abstract

The invention discloses a wind turbine blade structure optimization design method based on parameterization description, which is oriented to a main bearing structure of a blade and comprises a main beam, a trailing edge beam, a blade root reinforcing layer and a web plate, and comprises the following implementation steps: 1. designing the layout rule of the spanwise layering thickness distribution and the structural chord direction positioning of the main bearing structural components of the blade; 2. respectively creating mathematical models of the layering thickness distribution and the structural chord direction positioning of the main beam, the trailing edge beam, the blade root reinforcing layer and the web by adopting a parameterized modeling method; 3. taking the minimum total weight of the blade as an optimization target, and adopting an intelligent optimization algorithm to optimally design the blade structure of the wind turbine; 4. and calculating the structural stress of the blade to obtain the optimal structural positioning meeting the optimal design requirement. The invention completes the rapid iteration and strength analysis of blade structure optimization-structure design, improves the blade design efficiency, ensures the safety of the blade structure, has universality and provides a method basis for the large-scale development of the blade.

Description

A wind turbine blade structure optimization design method based on parametric description

Technical Field

The present invention relates to the technical field of wind turbine blades, and in particular to a method for optimizing the structure of wind turbine blades based on parameterized description.

Background technique

Wind turbine blades are key components that convert wind energy into mechanical energy and ultimately drive generators to generate electricity. The structure, quality, and performance of the blades determine whether the entire wind turbine can operate stably for a long time. With the continuous development of wind power generation and the increasing social demand for electricity, the trend of large-scale wind turbines is becoming more and more obvious. As the length of the blades increases, the design difficulty and calculation efficiency risks also increase. The design safety of the blades may not only cause damage to their own operation and reduce the design life, but may also cause the wind turbine to collapse and overturn due to major structural fractures of the blades, causing huge economic losses while increasing safety hazards. Therefore, conducting research on efficient and universal wind turbine blade structural design is of great significance and value to the development and improvement of wind power technology.

At present, the structural layout, geometric positioning, ply thickness distribution, material selection, etc. of the main load-bearing structure of the blade make the blade structure extremely complex. In the optimization design method of wind turbine blades, the research on the parametric definition of each component of the blade structure is insufficient, and it is impossible to effectively describe the distribution law of blade structure positioning and ply thickness distribution in the blade through mathematical expressions at the same time, which leads to low efficiency and accuracy of structural characteristic analysis and structural optimization. Furthermore, wind turbine blade structural optimization is a multi-objective, multi-variable, and multi-constrained design process. Previous studies have not optimized the multiple structural variables involving all the main load-bearing structural performances of the blade, and these variables may have a certain important impact on the structural performance of the blade. In addition, blade structural characteristic analysis, blade structural parametric modeling, and blade structural optimization are independent processes, and there is a lack of an optimization framework that integrates these three processes. Therefore, in order to quickly complete the structural design of the blade and obtain a higher performance wind turbine blade, a blade structural optimization design method based on parametric modeling is proposed, which can alleviate the problems of low blade design efficiency and insufficient safety margin of optimization design to a certain extent, and has great engineering application value for ensuring the large-scale development of blades.

Summary of the invention

The technical problem to be solved by the present invention is to provide a wind turbine blade structure optimization design method based on parameterized description in view of the deficiencies of the above-mentioned prior art.

In order to achieve the above technical objectives, the technical solution adopted by the present invention is:

A wind turbine blade structure optimization design method based on parametric description, the blade structure includes a main beam, a trailing edge beam, a blade root reinforcement layer and a web, and the wind turbine blade structure optimization design method specifically includes the following steps:

Step 1: According to the blade structure design requirements, based on the full-size blade aerodynamic shape and ultimate load, design the spanwise ply thickness distribution and chordwise positioning layout of the blade's main beam, trailing edge beam, root reinforcement layer and web.

Step 2: Use mathematical expressions to parametrically describe the spanwise ply thickness distribution and structural chordwise positioning of the main beam, trailing edge beam, blade root reinforcement layer and web. Define the spanwise ply thickness of the main beam, trailing edge beam, blade root reinforcement layer and web as the number of plies multiplied by the thickness of each ply material. Establish parametric description mathematical models of the thickness distribution of the main beam, the thickness distribution of the trailing edge beam and the thickness distribution of the blade root reinforcement layer along the span of the blade through parametric description. Then, define the parametric description mathematical models of the chordwise positioning of the main beam, trailing edge beam, blade root reinforcement layer and web through the distribution of the chordwise positions of the main beam, trailing edge beam, web and blade root reinforcement layer in the blade section.

Step 3: Based on the parametric mathematical model describing the spanwise ply thickness distribution and chordwise positioning of the main beam, trailing edge beam, blade root reinforcement layer and web, and based on the ultimate load, material properties and ply material distribution data, the thin-walled bar structural mechanics algorithm is used to calculate the blade structural stress to obtain the minimum structural safety factor and strength distribution of the blade section.

Step 4: Establish the optimization variables with the number of main beam plies, the number of trailing edge beam plies, the number of blade root reinforcement layers, and the web position, minimize the total weight of the blade as the optimization goal, and meet the maximum stress criterion as the constraint condition. Use the intelligent optimization algorithm to optimize the wind turbine blade structure, so as to optimize the design of the main beam, trailing edge beam, blade root reinforcement layer, and web structure, and obtain the optimal ply thickness distribution of the main beam, trailing edge beam, and blade root reinforcement layer that meet the optimization design requirements and the optimal structural positioning of the web.

To optimize the above technical solutions, the specific measures taken also include:

In step 1, the load of the wind turbine blade is calculated under different design conditions and wind conditions by using the Bladed software to obtain the load data of each section of the entire wind turbine blade, and then the ultimate load data of the blade is obtained.

In step 2, the specific method of using mathematical expressions to parameterize the chord-wise positioning and span-wise ply thickness distribution of the main beam is as follows: first, the chord-wise positioning of the main beam is based on the center line of the main beam as the reference datum, and the width W ₁ of the main beam is determined by offsetting the center line of the main beam to the leading edge and the trailing edge by W ₁ /2, wherein the position of the center line of the main beam is determined by the distance from the line connecting the vertical angles of the pitch axis on the chord length to the leading edge point, and the percentages of the chord length occupied by the starting point and the ending point of the main beam are defined as γ _spar1 and γ _spar2 , respectively, thereby obtaining the parametric description mathematical model U _s1 = [γ _spar1 γ _spar2 W ₁ ] of the chord-wise positioning of the main beam; secondly, the span-wise ply thickness distribution of the main beam is determined by the number of plies N ₁ of the main beam, the rising angle α ₁ and the falling angle α ₂ of the ply thickness of the main beam, and the span-wise starting and ending positions L ₁ and L 2 of the main beam laying. ₂ , and thus the parametric description mathematical model of the span-wise ply thickness distribution of the main beam is obtained as U _s2 = [N ₁ L ₁ L ₂ α ₁ α ₂ ], where the suction side and pressure side main beams of the blade use the same parametric description mathematical model.

In step 2, the specific method of using mathematical expressions to parameterize the chord-wise positioning and span-wise ply thickness distribution of the trailing edge beam is as follows: first, the chord-wise positioning of the trailing edge beam is referenced by the trailing edge point, and the width W ₂ of the trailing edge beam is obtained after the trailing edge point is offset from the leading edge by a distance of W ₂ , and _the percentage of the chord length occupied by the cutoff point of the trailing edge beam is defined, thereby obtaining the parameterized description mathematical model U _t1 = [γ _TE W ₂ ] of the chord-wise positioning of the trailing edge beam; secondly, the span-wise ply thickness distribution of the trailing edge beam is described by the number of plies N ₂ of the trailing edge beam, the rising angle β ₁ and the falling angle β ₂ of the ply thickness of the trailing edge beam, and the span-wise start and end positions L ₃ and L ₄ of the trailing edge beam laying, thereby obtaining the parameterized description mathematical model U _t2 = [N ₂ L ₃ L ₄ β ₁ β ₂ ] of the span-wise ply thickness distribution of the trailing edge beam, wherein the same parameterized description mathematical model is used for the trailing edge beams on the suction side and the pressure side of the blade.

In step 2, the specific method of using mathematical expressions to parameterize the description of the blade root reinforcement layer is as follows: since the blade root reinforcement layer is fully laid in the chordwise direction along the suction side and the pressure side of the blade, chordwise positioning is not required, and the laying of the blade root reinforcement layer starts at the blade root. Its spanwise laying thickness distribution is described by the number of blade root reinforcement layers N ₃ , the thickness drop angle θ at the spanwise end position of the blade root reinforcement layer, and the spanwise end position L ₅ of the blade root reinforcement layer. The parametric description mathematical model of the spanwise laying thickness of the blade root reinforcement layer is obtained as _Ur = [N ₃ θ L ₅ ].

In step 2, the specific method of using mathematical expressions to parameterize the web is as follows: since the web ply thickness is designed to be uniform along the span direction, there is no need for optimized design of the span direction ply thickness distribution. The parameterization of the web positioning takes the center line of the main beam as the reference datum, and the distances _c1 and _c2 are offset along the center line of the main beam toward the leading edge and the trailing edge, respectively, to obtain the position x _web1 and x _web2 of the web in the chord direction of the blade; the number of web plies N ₄ and the span direction start and end positions L ₆ and L ₇ of the web laying are defined to describe it, thereby obtaining the mathematical model for the parametric description of the web as U _w = [N ₄ L ₆ L ₇ x _web1 x _web2 ].

In step 3, the ply material distribution data includes the blade section ply partition percentage data and ply thickness distribution data of the main beam, trailing edge beam, blade root reinforcement layer and web. The two data are obtained as follows: the structural parameter information in the parametric description mathematical model U _s1 , U _s2 , U _t1 , U _t2 , _Ur , U _w is input into a table through a visual interface, and the blade section ply thickness of the main beam, trailing edge beam, blade root reinforcement layer and web in the table is compared to obtain the blade section ply partition percentage data and ply thickness distribution data of the main beam, trailing edge beam, blade root reinforcement layer and web.

In step 3, based on the ultimate load, material properties and ply material distribution data, the thin-walled rod structural mechanics algorithm is used to calculate the blade structural stress, and the specific method for obtaining the minimum structural safety factor and strength distribution of the blade section is as follows: the thin-walled rod structural mechanics method is used to calculate the tensile stress σ _t and compressive stress σ _c of the blade main beam, trailing edge beam, blade root reinforcement layer and web of the blade structural section under the action of the ultimate load, and compared with the allowable stresses [σ _t ] and [σ _c ] of the main beam material, trailing edge beam material, blade root reinforcement layer material and web material, respectively, to obtain the minimum structural safety factor of the blade section: Ensure that the structural design meets the strength requirements, that is, S _f ≥1.0.

In step 4, the mathematical model expression for optimizing the wind turbine blade structure using the intelligent optimization algorithm is:

Optimization objective function:

Design variables: X = { _xi } (i = 1, 2, 3, 4, 5)

Restrictions:

The minimum total weight of the blade is selected as the optimization objective function, where _mi represents the linear mass of the cross section, _ri represents the spanwise distance of the i-th structural section of the blade from the blade root, the blade span is defined as R, R= _∑ri , and the design variables are: the number of main beam plies _N1 selected from _Us2 , the number of trailing edge beam plies _N2 selected from _Ut2 , the number of blade root reinforcement layers _N3 selected from _Ur , and the positions of the web in the chord direction of the blade _xweb1 and _xweb2 selected from _Uw are defined as _x1 , _x2 , _x3 , _x4 , and _x5 respectively, and the variation of the ply width of each structural component is not considered. The constraint condition is the maximum stress criterion, and the geometric constraints of the number of main beam plies _N1 , the number of trailing edge beam plies _N2 , the number of blade root reinforcement layers _N3 , and the positions of the web in the chord direction of the blade _xweb1 and _xweb2 are:

Where x ^L , x ^U are the lower and upper limits of the design variables.

In step 4, the intelligent optimization algorithm is a genetic algorithm.

The present invention has the following advantages:

The present invention proposes a method for optimizing the design of wind turbine blade structures based on parametric description, and simultaneously completes the parametric description of the structural chord-wise positioning and span-wise ply thickness distribution of important load-bearing components of the blade structure. Furthermore, with the design parameters of the structural components as optimization variables, the minimum total weight of the blade as the optimization goal, and the maximum stress criterion as the constraint, a genetic algorithm is used to optimize the design of the wind turbine blade structure. This method realizes the use of the blade design parameters as optimization variables for blade structure optimization, can complete the rapid iteration of blade structure design-structural optimization, has universality, improves the efficiency of blade design, and ensures the safety of blade operation.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG1 is a flow chart of a method for optimizing the structure of a wind turbine blade based on parameterized description.

Figure 2 shows the chord-wise positioning of the main beam and trailing edge beam of a wind turbine blade.

Figure 3 is a ply thickness distribution model of the main beam of a wind turbine blade.

Figure 4 is a ply thickness distribution model of the trailing edge beam of a wind turbine blade.

Figure 5 is a thickness distribution model of the reinforcement layer at the root of a wind turbine blade.

Figure 6 shows the chord-wise positioning of the web of a wind turbine blade.

FIG. 7 is a schematic diagram of the span direction of the web of a wind turbine blade.

Figure 8 is the blade cross-section coordinate system.

FIG. 9 is a diagram showing the distribution of span-wise cross-sectional distances of a wind turbine blade.

Detailed ways

In order to make the purpose, technical solutions and advantages of the present application clearer, the present application is described and illustrated below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not intended to limit the present application. Based on the embodiments provided in the present application, all other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of the present application.

Obviously, the drawings described below are only some examples or embodiments of the present application. For ordinary technicians in this field, the present application can also be applied to other similar scenarios based on these drawings without creative work. In addition, it can also be understood that although the efforts made in this development process may be complicated and lengthy, for ordinary technicians in this field related to the content disclosed in this application, some changes in design, manufacturing or production based on the technical content disclosed in this application are just conventional technical means, and should not be understood as insufficient content disclosed in this application.

Reference to "embodiments" in this application means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those of ordinary skill in the art that the embodiments described in this application may be combined with other embodiments without conflict.

Unless otherwise defined, the technical terms or scientific terms involved in this application should be understood by people with ordinary skills in the technical field to which this application belongs. The words "one", "a", "a", "the" and the like involved in this application do not indicate a quantitative limitation, and may represent the singular or plural. The terms "include", "comprise", "have" and any of their variations involved in this application are intended to cover non-exclusive inclusions; for example, a process, method, system, product or device that includes a series of steps or units (units) is not limited to the listed steps or units, but may also include steps or units that are not listed, or may also include other steps or units inherent to these processes, methods, products or devices. The words "connect", "connected", "coupled" and the like involved in this application are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. The "multiple"/"several" involved in this application refers to two or more. "And/or" describes the association relationship of associated objects, indicating that there can be three relationships, for example, "A and/or B" can mean: A exists alone, A and B exist at the same time, and B exists alone. The character "/" generally indicates that the objects before and after are in an "or" relationship. The terms "first", "second", "third", etc. involved in this application are only used to distinguish similar objects and do not represent a specific ordering of the objects.

The present invention provides a method for optimizing the structure of a wind turbine blade based on parameterized description, the overall process of which is shown in FIG1 . Specifically, the method comprises the following steps:

Step 1: According to the blade structure design requirements, based on the full-size blade aerodynamic shape and ultimate load, design the main structural components of the blade, including the spanwise ply thickness distribution of the main beam, trailing edge beam, blade root reinforcement layer, web and the layout rules of the chordwise positioning of the structure.

The wind turbine blade data comes from the wind turbine blade manufacturer; the blade load data is calculated using the Bladed software. The large commercial software Bladed is used to calculate the load of the wind turbine blade under different design conditions and wind conditions to obtain the load data of each section of the entire wind turbine blade;

Step 2: Use mathematical expression parametric method to describe each component of the blade structure. This parametric description mainly includes the span-wise ply thickness distribution and structural chord-wise positioning of the blade main beam, trailing edge beam, blade root reinforcement layer, and web, thereby obtaining the structural parameters required for blade structure design and optimization. First, define the ply thickness of each component as the number of plies multiplied by the thickness of each ply material, and establish mathematical models of the main beam thickness distribution, trailing edge beam thickness distribution, and blade root reinforcement layer thickness distribution along the blade span through parametric description. Then, through the distribution of the main beam, trailing edge beam, web, and blade root reinforcement layer in the chord-wise position of the blade section, define the mathematical models of the structural chord-wise positioning.

The parametric description of the main beam in step 2 is divided into the chord-wise positioning of the main beam and the distribution of the ply thickness in the span direction of the main beam. The chord-wise positioning of the main beam is shown in Figure 2. To determine the width of the main beam and the positioning of the start and end positions of the width of the main beam in the chord direction, the position of the center line of the main beam must first be determined. Therefore, the distance from the vertical angle of the pitch axis on the chord length to the leading edge point is used to determine the position of the center line of the main beam.

On this basis, the width W ₁ of the main beam is determined by offsetting the center line of the main beam to the leading edge and the trailing edge by W ₁ /2 respectively, and the positions of the starting point and the ending point of the main beam are determined. Next, the ratio of the distance from the starting point of the main beam to the leading edge point to the chord length γ _spar1 and the ratio of the distance from the ending point of the main beam to the leading edge point to the chord length γ _spar2 are defined, expressed in percentage.

Therefore, the parametric mathematical model for describing the chord-wise positioning of the main beam can be obtained as follows: U _s1 = [γ _spar1 γ _spar2 W ₁ ]

As shown in Figure 3, the spanwise ply thickness of the main beam is determined by the number of ply layers _N1 of the main beam. Since the ply layers of the main beam are laid in different positions in the spanwise direction, the blade main beam needs to be divided into different sections, and the number of ply layers of each section is different. Therefore, the main beam ply thickness rising angle _α1 and falling angle _α2 are used to represent the variation trend of the ply thickness of each section. The spanwise length of the main beam is described by the spanwise starting and ending positions _L1 and _L2 of the main beam, where _L1 is the distance from the starting point of the main beam to the blade root, and _L2 is the distance from the ending point of the main beam to the blade root. Therefore, the parametric description mathematical model of _{the spanwise} ply thickness distribution of the main beam is obtained as _Us2 = _{[N1L1L2α1α2 ] .}

Furthermore, in step 2, the parameterization of the trailing edge beam is described as the chord-wise positioning of the trailing edge beam and the distribution of the ply thickness in the span direction, and the trailing edge beams on the suction side and the pressure side of the blade are designed in the same way. As shown in FIG2 , the chord-wise positioning of the trailing edge beam is based on the edge point as the reference datum, and the width W ₂ of the trailing edge beam is obtained after the distance W ₂ is offset from the trailing edge point to the leading edge direction, and the ratio γ _TE of the distance from the end point of the trailing edge beam to the leading edge point to the chord length is obtained, expressed in percentage form. Thus, the parameterized mathematical model U _t1 = [γ _TE W ₂ ] for describing the chord-wise positioning of the trailing edge beam can be obtained.

As shown in FIG4 , the span-wise ply thickness of the trailing edge beam is determined by the number of ply layers N ₂ of the trailing edge beam. Since the number of ply layers of the trailing edge beam is different at different positions in the span direction, the trailing edge beam also needs to be divided into different sections, and the number of ply layers of each section is different. Therefore, the rising angle β ₁ and the falling angle β ₂ of the ply thickness of the trailing edge beam are used to represent the variation trend of the ply thickness of each section. The span-wise ply length of the trailing edge beam is described by the span-wise starting and ending positions L ₃ and L ₄ of the trailing edge beam, where L ₃ is the distance from the starting point of the trailing edge beam to the blade root, and L ₄ is the distance from the ending point of the trailing edge beam to the blade root. Therefore, the parametric description mathematical model of the span-wise ply thickness distribution of the trailing edge beam is obtained as U _t2 = [N ₂ L ₃ L ₄ β ₁ β ₂ ].

Furthermore, in the parameterized description of the blade root reinforcement layer in step 2, since the blade root reinforcement layer is fully laid along the suction surface and the pressure surface of the blade, chord-wise positioning is not required. According to FIG5 , it can be seen that the laying of the blade root reinforcement layer starts from the blade root, wherein the spanwise laying thickness is represented by the number of blade root reinforcement layer layers N _3. Since the laying thickness of the blade root reinforcement layer is thicker near the blade root and thinner away from the blade root, the thickness drop angle θ at the spanwise end position of the blade root reinforcement layer is used to represent the change in the laying thickness, and the end position L ₅ of the blade root reinforcement layer along the spanwise direction is determined. Therefore, it can be concluded that the parameterized mathematical model of the spanwise laying thickness of the blade root reinforcement layer is _Ur = [N ₃ θ L ₅ ].

Furthermore, in the parametric description of the web in step 2, since the web ply thickness is designed to be uniform along the span direction, there is no need to optimize the ply thickness along the span direction. According to Figure 6, the parameterization of the web positioning takes the center line of the main beam as the reference datum, and the distances c ₁ and c ₂ are offset along the center line of the main beam toward the leading edge and the trailing edge, respectively, so that the position x _web1 and x _{web2 of the} web in the chord direction of the blade can be obtained. Where x _web1 is the percentage of the distance from the center line of the web near the leading edge to the leading edge point in the chord length, and x _web2 is the percentage of the distance from the center line of the web near the trailing edge to the leading edge point in the chord length, where the ply thickness of the web is determined by the number of web ply layers N ₄ .

As shown in Figure 7, the web plate laying distances along the span direction are _L6 and _L7 , where _L6 is the distance from the web plate laying starting point to the blade root, _{and L7} is the distance from the web plate laying ending point _{to the} blade root. It can be concluded that the mathematical model for _{the web plate parameterization description is Uw = [N4L6L7xweb1xweb2 ] .}

Step 3: Design a program based on the mathematical model of the parametric description of the ply thickness distribution and structural positioning of the main structural components of the blade, and obtain the design table of the profile geometric positioning data and ply thickness distribution data of the blade structure design. On the basis of the obtained geometric positioning and ply thickness distribution data, based on the ultimate load, material properties and ply material distribution law, use the thin-walled rod structural mechanics algorithm to calculate the blade structure stress and obtain the minimum structural safety factor and strength distribution of the blade section.

The design table of the wind turbine blade structure section geometric positioning data and ply thickness distribution data adopts a program design method. The structural parameter information of the mathematical model _Us1 , _Us2 , _Ut1 , _Ut2 , _Ur , _Uw of the main components of the blade structure established in step 2 is input through a visual interface to complete the parametric description of the blade structure and obtain the blade section ply partition percentage data and the ply thickness distribution data of each component for the calculation of the positive stress of the blade structure.

In the mechanical property analysis method of the blade structure, the cross-sectional characteristics of the blade structure are calculated based on the ply partition percentage of the blade section and the ply thickness distribution data of each component, and the thin-walled rod structural mechanics method is used, and it is assumed that the linear strain on the blade section conforms to the plane distribution law, that is, the linear strain assumption.

When calculating the normal stress of the wind turbine blade structure, since the load is based on the blade cross-section coordinate system, as shown in Figure 8, the blade structure characteristic calculation is based on XOYs. In order to solve the normal stress of the cross section, it is necessary to first calculate the stiffness, stiffness moment, inertia moment and inertia product of the cross section, and the formula is as follows:

Longitudinal stiffness: EA = ∫ _A EdA, where A is the ply area of the blade section,

The stiffness moment of the blade section about the Y _s axis

The stiffness moment of the blade section about the _Xs axis

Moment of inertia of blade section about _Ys axis

Moment of inertia of blade section about _Xs axis

The moment of inertia of the blade cross section

According to the linear strain hypothesis, the normal stress at any point on the cross section of the wind turbine blade is obtained.

Where E is the elastic modulus of the material, is the linear strain of any point on the blade cross section, _Xs and _Ys are the coordinates of each point on the blade cross section, _ε0 , are unknown coefficients, which are respectively expressed as the elastic strain of the mid-surface of the blade section, the deformation curvature around the Y _s axis and the deformation curvature around the X _s axis, which can be obtained from the static equilibrium condition on the blade section.

By integrating along the entire cross section, the axial force in the cross section can be calculated And the flapping moment _Mf , the swing moment _Me , the formula is as follows:

The above formula can be written as follows:

It can be expressed in matrix form as follows:

The blade section characteristic matrix can be obtained by integrating the blade section. The unknown coefficients ε ₀ , So we can get the stress of a point on the blade cross section With the normal stress, the tensile stress σ _t and compressive stress σ _c of the blade main beam, trailing edge beam, blade root reinforcement layer and web under the action of the ultimate load can be calculated, and compared with the allowable stress [σ _t ] and [σ _c ] of the main beam material, trailing edge beam material, blade root reinforcement layer material and web material respectively, the minimum structural safety factor of the blade section is obtained as Ensure that the structural design meets the strength requirements, that is, S _f ≥1.0.

Step 4: According to the optimization parameter setting and structural strength analysis of steps 2-3, the number of main beam layers, the number of trailing edge beam layers, the number of blade root reinforcement layers, and the web position are selected as design variables from the mathematical model established in step 2. The minimum total weight of the blade is taken as the optimization goal, and the maximum stress criterion is taken as the constraint condition. The wind turbine blade structure is optimized using an intelligent optimization algorithm. In this way, the main beam, trailing edge beam, blade root reinforcement layer, and web structure are optimized to obtain the optimal ply thickness distribution of the main beam, trailing edge beam, and blade root reinforcement layer that meet the optimization design requirements, as well as the optimal structural positioning of the web.

The mathematical model expression of the blade structure intelligent optimization algorithm is:

Optimization objective function:

Design variables: X = { _xi } (i = 1, 2, 3, 4, 5)

Restrictions:

(1) Objective function

Generally speaking, the larger the mass of the blade, the more materials are needed to manufacture, the higher the cost, and the higher the requirements for the tower and the whole machine. Therefore, the smaller the mass of the blade, the better. Therefore, this optimization mathematical model selects the minimum mass of the blade as the objective function, where _mi represents the linear mass of the i-th section, and _ri represents the distance of the i-th section segment, as shown in Figure 9, where _ri = root represents the starting point of the section segment, and _ri = tip represents the ending point of the section segment.

The linear mass of the blade section and the total mass of the blade are calculated using the normal stress equation for free bending of the thin-walled beam mentioned above to obtain the normal stress Then, by combining the given safety factor and intelligent optimization algorithm, the thickness of the main beam, trailing edge beam, blade root reinforcement layer and the position of the web of the key section of the blade can be obtained, _and the linear mass of the section can be obtained after integration. Then, the linear mass of all sections is integrated and then summed to obtain the total weight of the blade.

(2) Design variables

The design variables for blade structure optimization are determined according to the mathematical model established in step 2. The design variables of the mathematical optimization model in the present invention are: the number of main beam plies N ₁ is selected from U _s2 , the number of trailing edge beam plies N ₂ is selected from U _t2 , the number of blade root reinforcement layers N ₃ is selected from U _r , and the positions of the web in the chord direction of the blade x _web1 and x _web2 are selected from U _w as design variables and are defined as x ₁ , x ₂ , x ₃ , x ₄ , x ₅ respectively. And the design variables satisfy the geometric constraints: In the formula, are the lower and upper limits of the design variable.

(3) Constraints

The structural optimization problem of wind turbine blades is a complex constrained optimization problem. In this model, the main constraints are selected to meet the strength conditions. The formula is as follows:

Furthermore, the selected intelligent optimization algorithm is a genetic algorithm, and the basic operation process of the genetic algorithm is as follows:

(a) Initialization: Set the evolutionary generation counter t = 0, set the maximum evolutionary generation T, and randomly generate M individuals as the initial population P(0).

(b) Individual evaluation: Calculate the fitness of each individual in the population P(t).

(c) Selection operation: Apply the selection operator to the population. The purpose of selection is to directly pass on the optimized individuals to the next generation or to generate new individuals through pairing and crossover and then pass on to the next generation. The selection operation is based on the fitness evaluation of individuals in the population.

(d) Crossover operation: Apply the crossover operator to the population. The crossover operator plays a core role in genetic algorithms.

(e) Mutation operation: Apply the mutation operator to the population, that is, change the gene values at certain loci of the individual strings in the population. After the population P(t) undergoes selection, crossover, and mutation operations, the next generation population P(t+1) is obtained.

(f) Termination condition judgment: If t = T, the individual with the maximum fitness obtained in the evolution process is output as the optimal solution and the calculation is terminated.

If the optimization result of the blade meets the strength condition of the blade, the value of the design variable at this time meets the requirements and is brought into the blade ply design to complete the optimization of the blade structure; if the conditions are not met, the blade is iteratively calculated until the constraints are met.

Since the optimization variables in the optimization model are the structural design parameters of the blades in the parametric description, the optimization variables can be adjusted as needed to construct different optimization models; and when the optimal solution after optimization is obtained, the blade structure can be quickly parametrically described and the structural design of the blade can be completed, which greatly reduces the time required for the entire optimization process.

The above are only preferred embodiments of the present invention. The protection scope of the present invention is not limited to the above embodiments. All technical solutions under the concept of the present invention belong to the protection scope of the present invention. It should be pointed out that for ordinary technicians in this technical field, some improvements and modifications without departing from the principle of the present invention should be regarded as the protection scope of the present invention.

Claims (6)

1. A wind turbine blade structure optimization design method based on parametric description, wherein the blade structure includes a main beam, a trailing edge beam, a blade root reinforcement layer and a web, wherein the wind turbine blade structure optimization design method specifically includes the following steps: Step 1: According to the blade structure design requirements, based on the full-size blade aerodynamic shape and ultimate load, design the spanwise ply thickness distribution and chordwise positioning layout of the blade's main beam, trailing edge beam, root reinforcement layer and web. Step 2: Use mathematical expressions to parametrically describe the spanwise ply thickness distribution and structural chordwise positioning of the main beam, trailing edge beam, blade root reinforcement layer and web. Define the spanwise ply thickness of the main beam, trailing edge beam, blade root reinforcement layer and web as the number of plies multiplied by the thickness of each ply material. Establish parametric description mathematical models of the thickness distribution of the main beam, the thickness distribution of the trailing edge beam and the thickness distribution of the blade root reinforcement layer along the span of the blade through parametric description. Then, define the parametric description mathematical models of the chordwise positioning of the main beam, trailing edge beam, blade root reinforcement layer and web through the distribution of the chordwise positions of the main beam, trailing edge beam, web and blade root reinforcement layer in the blade section. Step 3: Based on the parametric mathematical model describing the spanwise ply thickness distribution and chordwise positioning of the main beam, trailing edge beam, blade root reinforcement layer and web, and based on the ultimate load, material properties and ply material distribution data, the thin-walled bar structural mechanics algorithm is used to calculate the blade structural stress to obtain the minimum structural safety factor and strength distribution of the blade section. Step 4: Establish the optimization variables with the number of main beam plies, the number of trailing edge beam plies, the number of blade root reinforcement layers, and the web position, minimize the total weight of the blade as the optimization goal, and meet the maximum stress criterion as the constraint condition. Use the intelligent optimization algorithm to optimize the wind turbine blade structure, so as to optimize the main beam, trailing edge beam, blade root reinforcement layer, and web structure, and obtain the optimal ply thickness distribution of the main beam, trailing edge beam, and blade root reinforcement layer that meet the optimization design requirements, as well as the optimal structural positioning of the web; In step 2, the specific method of using mathematical expressions to parameterize the chord-wise positioning and span-wise ply thickness distribution of the main beam is as follows: first, the chord-wise positioning of the main beam is based on the center line of the main beam as the reference datum, and the width W ₁ of the main beam is determined by offsetting the center line of the main beam to the leading edge and the trailing edge by W ₁ /2, respectively, wherein the position of the center line of the main beam is determined by the distance from the line connecting the vertical angles of the pitch axis on the chord length to the leading edge point, and the percentages of the chord length occupied by the starting point and the ending point of the main beam are defined as γ _spar1 and γ _spar2 , respectively, thereby obtaining the parametric description mathematical model U _s1 = [γ _spar1 γ _spar2 W ₁ ] of the chord-wise positioning of the main beam; secondly, the span-wise ply thickness distribution of the main beam is determined by the number of plies N ₁ of the main beam, the rising angle α ₁ and the falling angle α ₂ of the ply thickness of the main beam, and the span-wise starting and ending positions L ₁ and L 2 of the main beam laying. ₂ , and thus the parametric description mathematical model of the main beam span-wise ply thickness distribution is obtained as U _s2 = [N ₁ L ₁ L ₂ α ₁ α ₂ ], where the blade suction side and pressure side main beams use the same parametric description mathematical model; The specific method of using mathematical expressions to parameterize the chord-wise positioning and span-wise ply thickness distribution of the trailing edge beam is as follows: first, the chord-wise positioning of the trailing edge beam is based on the trailing edge point as the reference datum, and the width W ₂ of the trailing edge beam is obtained after the trailing edge point is offset from the leading edge by a distance of W ₂ , and the _percentage of the chord length occupied by the cutoff point of the trailing edge beam is defined, thereby obtaining the parameterized description mathematical model U _t1 = [γ _TE W ₂ ] of the chord-wise positioning of the trailing edge beam; secondly, the span-wise ply thickness distribution of the trailing edge beam is described by the number of plies N ₂ of the trailing edge beam, the rising angle β ₁ and the falling angle β ₂ of the ply thickness of the trailing edge beam, and the span-wise start and end positions L ₃ and L ₄ of the trailing edge beam laying, thereby obtaining the parameterized description mathematical model U _t2 = [N ₂ L ₃ L ₄ β ₁ β ₂ ] of the span-wise ply thickness distribution of the trailing edge beam, wherein the same parameterized description mathematical model is used for the trailing edge beams on the suction side and the pressure side of the blade; The specific method of using mathematical expressions to parametrically describe the blade root reinforcement layer is as follows: since the blade root reinforcement layer is fully laid along the suction surface and pressure surface of the blade, chord-wise positioning is not required, and the laying of the blade root reinforcement layer starts at the blade root. Its spanwise laying thickness distribution is described by the number of blade root reinforcement layers N ₃ , the thickness drop angle θ at the spanwise end position of the blade root reinforcement layer, and the spanwise end position L ₅ of the blade root reinforcement layer. The parametric description mathematical model of the spanwise laying thickness of the blade root reinforcement layer is obtained as _Ur = [N ₃ θ L ₅ ]; The specific method of using mathematical expressions to parametrically describe the web is as follows: since the web ply thickness is designed to be uniform along the span direction, there is no need for optimized design of the span direction ply thickness distribution. The parameterization of the web positioning takes the center line of the main beam as the reference datum, and the distances _c1 and _c2 are offset along the center line of the main beam toward the leading edge and the trailing edge respectively, thereby obtaining the positions x _web1 and x _web2 of the web in the chord direction of the blade; the number of web plies N ₄ and the span direction start and end positions L ₆ and L ₇ of the web laying are defined to describe it, thereby obtaining the mathematical model of the parametric description of the web as U _w = [N ₄ L ₆ L ₇ x _web1 x _web2 ]. 2. According to the method for optimizing the structure of wind turbine blades based on parametric description in claim 1, the method is characterized in that: in step 1, the load of the wind turbine blades is calculated under different design conditions and wind conditions by using Bladed software to obtain the load data of each cross section of the entire wind turbine blade, and then the ultimate load data of the blades is obtained. 3. A wind turbine blade structure optimization design method based on parametric description according to claim 2, characterized in that: in step 3, the ply material distribution data includes blade section ply partition percentage data and ply thickness distribution data of the main beam, trailing edge beam, blade root reinforcement layer and web, and these two data are obtained by: inputting the structural parameter information in the parametric description mathematical model _Us1 , _Us2 , _Ut1 , _Ut2 , _Ur , _Uw into a table through a visual interface, and comparing the blade section ply thickness of the main beam, trailing edge beam, blade root reinforcement layer and web in the table to obtain the blade section ply partition percentage data and ply thickness distribution data of the main beam, trailing edge beam, blade root reinforcement layer and web. 4. A wind turbine blade structure optimization design method based on parametric description according to claim 3, characterized in that: in step 3, based on the ultimate load, material properties and ply material distribution data, a thin-walled rod structural mechanics algorithm is used to calculate the blade structural stress, and a specific method for obtaining the minimum structural safety factor and strength distribution of the blade section is: the thin-walled rod structural mechanics method is used to calculate the tensile stress σ t and compressive stress σ c of the blade main beam, trailing edge beam, blade root reinforcement layer and web of the blade structural section under the action of the ultimate load, and the tensile stress σ _t and compressive stress σ _c of the blade main beam, trailing edge beam, blade root reinforcement layer and web are respectively compared with the allowable stresses [σ _t ] and [σ _c ] of the main beam material, the trailing edge beam material, the blade root reinforcement layer material and the web material, so as to obtain the minimum structural safety factor of the blade section: Ensure that the structural design meets the strength requirements, that is, S _f ≥1.0. 5. The method for optimizing the structure of a wind turbine blade based on parameterized description according to claim 4 is characterized in that: in step 4, the mathematical model expression for optimizing the structure of a wind turbine blade using an intelligent optimization algorithm is: Optimization objective function: Design variables: X = { _xi } (i = 1, 2, 3, 4, 5) Restrictions: The minimum total weight of the blade is selected as the optimization objective function, where _mi represents the linear mass of the cross section, _ri represents the spanwise distance of the i-th structural section of the blade from the blade root, the blade span is defined as R, R= _∑ri , and the design variables are: the number of main beam plies _N1 selected from _Us2 , the number of trailing edge beam plies _N2 selected from _Ut2 , the number of blade root reinforcement layers _N3 selected from _Ur , and the positions of the web in the chord direction of the blade _xweb1 and _xweb2 selected from _Uw are defined as _x1 , _x2 , _x3 , _x4 , and _x5 respectively, and the variation of the ply width of each structural component is not considered. The constraint condition is the maximum stress criterion, and the geometric constraints of the number of main beam plies _N1 , the number of trailing edge beam plies _N2 , the number of blade root reinforcement layers _N3 , and the positions of the web in the chord direction of the blade _xweb1 and _xweb2 are: Where x ^L , x ^U are the lower and upper limits of the design variables. 6. The method for optimizing the structure of a wind turbine blade based on parameterized description according to claim 1 is characterized in that, in step 4, the intelligent optimization algorithm is a genetic algorithm.