Yaw matrix optimization method and device based on differential evolution algorithm and electronic equipment

Abstract

The application belongs to the technical field of fan yaw control and relates to a yaw matrix optimization method and device based on a differential evolution algorithm and an electronic device. The method comprises the following steps: performing coordinate transformation on the entire set of units; determining the upstream units in the first several units of the target units according to the wake radius in the wake model; determining the upstream units of all target units; screening the target units with upstream units to obtain a unit list containing all target units with upstream units and corresponding upstream units; calculating the equivalent inflow velocity; calculating the sum of the total power of all upstream units and downstream units; and determining the optimal yaw angle of each upstream unit based on the differential evolution algorithm. The application considers the complex fan arrangement mode of an actual wind farm, obtains the optimal yaw angle matrix of the units based on the wake model and the differential evolution algorithm and with the maximum total power of the wind farm as the target, and realizes the yaw angle calculation of the wind farm under the conditions of various wind speeds and wind directions.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of fan yaw control, and in particular relates to a yaw matrix optimization method and device based on a differential evolution algorithm and an electronic device. BACKGROUND

[0002] The single machine capacity of wind power is also increasing year by year, and the scale of wind farms is also expanding, the wake influence between wind turbine generators is increasing, and the wake characteristics of wind turbines are an increasingly important topic.

[0003] There are three methods for wind turbine wake calculation: simulation calculation, wind tunnel experiment and analytical wake model. The simulation calculation method has deviation and sometimes cannot reflect the actual situation, and the calculation speed is slow; the wind tunnel experiment method is affected by the size of the wind tunnel, and there is a large deviation in the Reynolds number, and the wind tunnel test cannot reflect the actual situation; the existing analytical wake model method has the problems of complex wake model structure, slow calculation speed and inability to reflect the true situation of flow.

[0004] In the yaw optimization layer, the strategy based on the Boolean type control yaw angle defines the wind wheel yaw angle as a Boolean value, that is, the yaw angle is defined in advance, and then it is judged whether the unit needs to yaw or not to control the unit yaw operation. In the simulation experiment, the strategy uses less optimized power than the gradient optimizer. The prior art only uses a small rectangular simulation wind farm to study the application of genetic algorithm in optimizing the yaw angle of the unit, but does not expand the research on actual large-scale wind farms. The wake deflection control method uses a gradient ascent search algorithm to maximize the power analytical function, applies this wake deflection control to increase the annual average wind speed and average wind direction power generation, and the method is only for the research of small wind farms arranged in a single row, and does not consider the complex unit arrangement of large wind farms. SUMMARY

[0005] In order to solve the above technical problems, the present application provides a yaw matrix optimization method, device and electronic equipment based on a differential evolution algorithm.

[0006] In a first aspect, the present application provides a yaw matrix optimization method based on a differential evolution algorithm, comprising:

[0007] The wind direction of the wind measurement tower is taken as the inflow wind direction of the whole field, the wind speed of the wind measurement tower is taken as the inflow wind speed of the whole field, the coordinate transformation of the whole unit is carried out according to the change of the wind direction in the horizontal direction, and the unit list after the coordinate transformation is obtained;

[0008] All units in the entire field are sorted, the target unit is selected, the relative distance between each unit and the target unit is obtained, and the upstream units among the first few units of the target unit are determined according to the wake radius in the wake model; the upstream units are defined as units within the wake radius of the wake model that have a wake effect on the downstream units.

[0009] Enter the next target unit until the upstream units of all target units are determined;

[0010] Filter the target units that have upstream units, remove duplicates from all target units that have upstream units and their corresponding upstream units, sort them by coordinate size, and obtain a list of units that includes all target units that have upstream units and their corresponding upstream units;

[0011] Based on the incoming wind speed and yaw angle of each upstream unit, calculate the equivalent inflow velocity of the downstream unit corresponding to each upstream unit;

[0012] Calculate the sum of the total power of all upstream and downstream units based on the equivalent inflow velocity and yaw angle of all upstream units and the equivalent inflow velocity and yaw angle of all downstream units.

[0013] Based on the differential evolution algorithm, the sum of the total power of all upstream and downstream units is used as the objective function to determine the optimal yaw angle of each upstream unit.

[0014] Secondly, the present invention provides a yaw matrix optimization device based on differential evolution algorithm, including a coordinate transformation unit, a first processing unit, an input unit, a second processing unit, a third processing unit, a fourth processing unit and a fifth processing unit;

[0015] The coordinate transformation unit is used to take the wind direction of the meteorological tower as the incoming wind direction of the entire field and the wind speed of the meteorological tower as the incoming wind speed of the entire field. Based on the change of wind direction in the horizontal direction, the coordinate transformation is performed on the entire field of units to obtain a list of units after coordinate transformation.

[0016] The first processing unit is used to sort all the units in the entire field, select the target unit, obtain the relative distance between each unit and the target unit, and determine the upstream units among the first few units of the target unit based on the wake radius in the wake model; the upstream units are defined as units within the wake radius of the wake model that have a wake effect on the downstream units.

[0017] The input unit is used to input the next target unit until the upstream units of all target units are determined;

[0018] The second processing unit is configured to screen target units with upstream units, remove duplicates of all target units with corresponding upstream units, and sort the units according to the coordinate size to obtain a unit list containing all target units with corresponding upstream units.

[0019] The third processing unit is configured to calculate the equivalent inflow velocity of each downstream unit corresponding to each upstream unit according to the incoming flow wind speed of each upstream unit and the yaw angle of each upstream unit.

[0020] The fourth processing unit is configured to calculate the sum of the total power of all upstream units and downstream units according to the equivalent inflow velocity and the yaw angle of all upstream units and the equivalent inflow velocity and the yaw angle of all downstream units.

[0021] The fifth processing unit is configured to determine the optimal yaw angle of each upstream unit based on the differential evolution algorithm, taking the sum of the total power of all upstream units and downstream units as a target function.

[0022] In a third aspect, the present application provides an electronic device, comprising:

[0023] a processor and a memory;

[0024] the memory is configured to store computer operation instructions;

[0025] the processor is configured to execute the yaw matrix optimization method based on the differential evolution algorithm in any one of claims 1 to 6 by calling the computer operation instructions.

[0026] Based on the above technical solutions, the present application can be further improved as follows.

[0027] Further, the relative distance between each unit and the target unit is obtained, and the upstream units in the first several units of the target unit are determined according to the wake radius in the wake model, comprising:

[0028] The units in the first several units of the target unit and the target unit have a relative distance less than the wake radius in the wake model, and the units are upstream units of the target unit; the relative distance between the units and the target unit in the x direction is less than a set value, the relative distance between the units and the target unit in the y direction is less than the wake radius of the target unit in the horizontal direction, and the relative distance between the units and the target unit in the z direction is less than the wake radius of the target unit in the vertical direction.

[0029] If the target unit has at least one upstream unit, the target unit is a downstream unit of the upstream unit; if the target unit has no upstream unit, the next target unit is selected to determine whether there is an upstream unit.

[0030] Further, let z hubis the height of the hub center, u hub is the incoming wind speed at the hub center, z is the vertical height relative to the hub center, a is the axial induction factor, C T is the thrust coefficient, r0 is the initial wake radius, D is the diameter of the wind turbine, r z is the wake radius in the vertical direction, r y is the wake radius in the horizontal direction, then:

[0031]

[0032] r y = k y x + r0;

[0033] r z = k z x + r0.

[0034] Further, let w represent the transformation angle of the incoming wind direction, counterclockwise is positive, and the initial angle of the incoming wind direction is the horizontal axis direction, x old is the horizontal coordinate value of the target unit before coordinate transformation, y old is the vertical coordinate value of the target unit before coordinate transformation, x new is the horizontal coordinate value of the target unit after coordinate transformation, y new is the vertical coordinate value after coordinate transformation, then the formula of coordinate transformation is:

[0035]

[0036] Further, the wind speed at the hub center is regarded as the equivalent inflow speed of the wind turbine.

[0037] Further, based on the differential evolution algorithm, the sum of the total power of all upstream and downstream units is taken as the objective function to determine the optimal yaw angle of each upstream unit, including population initialization, mutation, crossover, boundary processing, calculation of the objective function and output of the optimal yaw angle;

[0038] Crossover: the difference between the new population individuals and the individuals in the current population is controlled by the crossover probability, and whether to generate a new individual by mutation operation is determined according to the randomly generated value and the size of the crossover probability. If the randomly generated value is less than the crossover probability, a new individual is generated by mutation operation; otherwise, the new individual is the same as the target individual;

[0039] Boundary processing: the boundary value of the yaw angle is set;

[0040] The objective function is calculated, including calculating the wind turbine power and the yaw power, and calculating the objective function according to the yaw power;

[0041] Let p be the air flow density, A be the wind wheel area, Cp is the wind power coefficient, η is an empirical coefficient, β is the yaw angle, P e is the rated power, U is the incoming wind speed, and the wind turbine power is P, then:

[0042]

[0043]

[0044] Let P ph represent the power after yawing, P() represent the corresponding unyawed power at the incoming wind speed U e is a function of the upstream unit yaw angle, then:

[0045] P ph = P(U e ) cos η β;

[0046] Let X represent the x coordinate difference between the upstream unit and the downstream unit, Y represent the y coordinate difference between the upstream unit and the downstream unit, Z represent the z coordinate difference between the upstream unit and the downstream unit, Y3DJGF() be the wake model function, U ue be the equivalent incoming flow speed of the upstream unit, β u be the yaw angle of the corresponding upstream unit of the target unit, then:

[0047] U e = Y3DJGF(U ue , X, Y, Z, β u );

[0048] P ph = P(Y3DJGF(U ue , X, Y, Z, β u )) cos η β;

[0049] Calculate the sum of the total power of all upstream units and downstream units, including: Let n be the number of wind turbines, i be the number of wind turbines, U i be the incoming wind speed of the i th unit, P i be the yawed power of the i th wind turbine, and the value of the objective function be P g , then:

[0050]

[0051] After a certain number of iterations, output the optimal yaw angle.

[0052] The beneficial effects of the present application are: the present application carries out coordinate transformation on the unit according to the wind direction, arranges the unit order according to the wind direction, carries out wake area determination on the nearest upstream wind turbine of the target unit by means of the wake model, and forms an upstream and downstream unit list, then inputs the yaw angle of the upstream unit as the independent variable and the total power as the objective function into the differential evolution algorithm to obtain the optimal yaw angle. Finally, the yaw angle list of each wind direction and each wind speed in the whole field is obtained through data reorganization; the present application realizes the yaw matrix calculation under the condition of three-dimensional coordinates by means of the wake model, which improves the calculation accuracy compared with two-dimensional calculation, and improves the calculation efficiency by determining the wake area; the present application considers the complex wind turbine arrangement mode of the actual wind farm, obtains the optimal yaw angle matrix of the unit based on the wake model and combined with the differential evolution algorithm, and realizes the yaw angle calculation under the condition of each wind speed and each wind direction of the wind farm. BRIEF DESCRIPTION OF DRAWINGS

[0053] Figure 1 The principle diagram of the yaw matrix optimization method based on the differential evolution algorithm provided for the embodiment 1 of the present application is shown in the figure.

[0054] Figure 2 The flowchart of the differential evolution algorithm is shown in the figure.

[0055] Figure 3 The principle diagram of the yaw matrix optimization device based on the differential evolution algorithm provided for the embodiment 2 of the present application is shown in the figure.

[0056] Figure 4 The principle diagram of the electronic device provided for the embodiment 3 of the present application is shown in the figure.

[0057] Icon: 40-electronic device; 410-processor; 420-bus; 430-memory; 440-transceiver. DETAILED DESCRIPTION

[0058] In order to make the purpose, technical scheme and advantages of the embodiments of the present application clearer, the technical scheme of the embodiments of the present application will be described clearly and completely below in combination with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all the embodiments. The components of the embodiments of the present application described and shown in the drawings here can be arranged and designed in various different configurations.

[0059] Embodiment 1

[0060] As an embodiment, as shown in the figure, to solve the above technical problems, the embodiment provides a yaw matrix optimization method based on the differential evolution algorithm, which comprises: Figure 1

[0061] ​The wind direction of the wind measurement tower is taken as the whole-field incoming flow direction, the wind speed of the wind measurement tower is taken as the whole-field incoming flow speed, the whole-field unit list after coordinate transformation is obtained by coordinate transformation of the whole-field unit according to the change of the wind direction in the horizontal direction;

[0062] The whole-field units are sorted, a target unit is selected, the relative distances between each unit and the target unit are obtained, the upstream units in the first several units of the target unit are determined according to the wake radius in the wake model; the upstream unit is defined as the unit that has a wake influence on the downstream unit within the wake radius in the wake model;

[0063] The next target unit is input until the upstream units of all target units are determined;

[0064] The target units with upstream units are screened, the target units with upstream units and the corresponding upstream units are removed after duplication, the unit list containing the target units with upstream units and the corresponding upstream units is obtained by sorting according to the coordinate size;

[0065] The equivalent inflow speed of the corresponding downstream unit of each upstream unit is calculated according to the incoming flow speed of each upstream unit and the yaw angle of each upstream unit;

[0066] The sum of the total power of all upstream units and downstream units is calculated according to the equivalent inflow speed and yaw angle of all upstream units and the equivalent inflow speed and yaw angle of all downstream units;

[0067] Based on the differential evolution algorithm, the sum of the total power of all upstream units and downstream units is taken as the objective function to determine the optimal yaw angle of each upstream unit.

[0068] Further, the relative distances between each unit and the target unit are obtained, and the upstream units in the first several units of the target unit are determined according to the wake radius in the wake model, including:

[0069] The units in the first several units of the target unit and the target unit have a relative distance less than the wake radius in the wake model, which are the upstream units of the target unit; the relative distance between the unit and the target unit in the x direction is less than a set value, the relative distance between the unit and the target unit in the y direction is less than the wake radius of the target unit in the horizontal direction, and the relative distance between the unit and the target unit in the z direction is less than the wake radius of the target unit in the vertical direction;

[0070] If the target unit has at least one upstream unit, the target unit is the downstream unit of the upstream unit; if the target unit has no upstream unit, the next target unit is selected to determine whether there is an upstream unit.

[0071] Optionally, z hub is the height of the hub center, uhub is the incoming airflow velocity at the center of the hub, z is the vertical height relative to the center of the hub, and a is the axial induction factor. C T It is the thrust coefficient, r0 is the initial wake radius, D is the rotor diameter, and r z It is the wake radius in the vertical direction, r y Let be the wake radius in the horizontal direction, then:

[0072]

[0073] r y =k y x+r0;

[0074] r z =k z x+r0.

[0075] The wake model is a wake velocity expression obtained from the operating state of the wind turbine, which can accurately describe the three-dimensional distribution characteristics of the wake region when considering the yaw angle.

[0076] Optionally, let w represent the angle of change in the incoming wind direction, with counterclockwise being positive, and the initial angle of the incoming wind direction being the horizontal axis, x old The x-coordinate of the target unit before coordinate transformation is y. old x represents the ordinate of the target unit before coordinate transformation. new Let y be the x-coordinate value of the target unit after coordinate transformation. new Let be the ordinate value after coordinate transformation. Then the formula for coordinate transformation is:

[0077]

[0078] Optionally, the wind speed at the center of the hub can be considered as the equivalent inflow velocity of the wind turbine.

[0079] Optional, as shown in the appendix Figure 2 As shown, based on the differential evolution algorithm, the sum of the total power of all upstream and downstream units is used as the objective function to determine the optimal yaw angle of each upstream unit, including population initialization, mutation, crossover, boundary handling, calculation of the objective function and output of the optimal yaw angle;

[0080] Crossover: The crossover probability controls the degree of difference between individuals in the new population and individuals in the current population. The determination of whether to use mutation to generate new individuals is based on the randomly generated value and the crossover probability. If the randomly generated value is less than the crossover probability, mutation is used to generate new individuals; otherwise, the new individuals are the same as the target individuals.

[0081] Boundary handling: Set boundary values ​​for the yaw angle;

[0082] Calculate the objective function, including calculating the turbine power and yaw power, and calculate the objective function based on the yaw power;

[0083] Let ρ be the airflow density, A be the wind turbine area, and C be the wind turbine area. p η is the wind power coefficient, β is the empirical coefficient, and P is the yaw angle. e Given the rated power, U is the incoming air velocity, and P is the fan power, then:

[0084]

[0085]

[0086] Let P ph P represents the power after yaw, and P() represents the corresponding unyaw power at the incoming wind speed. U e If is a function of the yaw angle of the upstream unit, then:

[0087] P ph =P(U e cos η β;

[0088] Let X represent the x-coordinate difference between the upstream and downstream units, Y represent the y-coordinate difference between the upstream and downstream units, Z represent the z-coordinate difference between the upstream and downstream units, Y3DJGF() be the wake model function, and U ue β is the equivalent inflow velocity of the upstream unit. u Let yaw angle be the upstream unit corresponding to the target unit, then:

[0089] U e =Y3DJGF(U ue X,Y,Z,β u );

[0090] P ph =P(Y3DJGF(U ue X,Y,Z,β u ))cos η β;

[0091] Calculate the sum of the total power of all upstream and downstream units, including: Let n be the number of wind turbines, i be the number of wind turbines, and U i Let P be the incoming air velocity of the i-th unit. i Let P be the yaw power of the i-th wind turbine, and the objective function value be P. g ,but:

[0092]

[0093] After a set number of iterations, the optimal yaw angle is output.

[0094] Differential Evolution (DE) is an optimization algorithm based on modern intelligent theory, which uses the cooperation and competition between individuals in the population to form swarm intelligence to guide the direction of optimization search. The basic idea is to start from a randomly generated initial population, generate new individuals by calculating the vector difference of any two individuals and summing with the third individual.

[0095] Let the first individual be X1, the second individual be X2, the third individual be X3, F be the mutation factor, and the new individual be X new Then:

[0096] X new = X1 + F(X2 - X3).

[0097] The crossover probability controls the degree of difference between the new individual and the individuals in the current population. The mutation operation is used to generate new individuals. Specifically, if the randomly generated value is less than the crossover probability, the mutation operation is used to generate new individuals; otherwise, the mutation operation is not used, and the new individual is used as the target individual. The crossover probability is usually defined in the interval [0, 1], representing the probability of crossover. The higher the crossover probability, the more differences it will cause, while the lower the crossover probability, the more it will help to retain the characteristics of the original individuals.

[0098] Let CR be the crossover probability, the population be X, X old be the unmutated population, and the individual in the population be β i , be the g+1th new individual, and ifrand(0, 1) < CR represent if the random number taken between (0, 1) is less than the crossover probability CR, then The individual in the population contains the yaw angle of all upstream units output in the wake effect judgment. Generally, the yaw angle will not exceed the interval [-30, 30], so the upper and lower limits of each β are set to [-30, 30].

[0099]

[0100] The new individual is compared with the corresponding individual in the current population. If the fitness of the new individual is better than that of the current individual, the new individual replaces the old individual in the next generation; otherwise, the old individual is retained. Through continuous evolution, retention of excellent individuals and elimination of inferior individuals, the search is gradually guided to approach the optimal solution.

[0101] In order to calculate the equivalent inflow wind speed of each unit, the inflow wind speed of the upstream unit and the yaw angle must be known. The yaw angle is given by the population individual, and the upstream inflow wind speed is determined as follows:

[0102] The units are divided into units affected by the wake and units not affected by the wake, the units not affected by the wake are regarded as the whole-field inflow wind speed, and the units affected by the wake are determined according to the upstream and downstream relationship list and the function U related to the yaw angle of the upstream unit e The equivalent inflow velocity is calculated. After the coordinate transformation, the preliminary upstream and downstream relationship is determined by sorting the units according to the X coordinate value, and then the units in the selected unit list are sorted according to the sorted whole-field unit list, and the corresponding upstream wind turbine number is obtained by starting from the unit with the smallest X coordinate value, so that the inflow velocity of the upstream wind turbine which has not been calculated can be effectively avoided. The obtained upstream unit number increases in X coordinate from top to bottom, which respectively corresponds to the yaw angle of each upstream unit in the population, so that the equivalent inflow velocity of each wind turbine is calculated according to the wake model.

[0103] The units are sorted according to the wind direction after the coordinate transformation, the tail flow area of the target unit upstream wind turbine is determined by the tail flow model, and the upstream and downstream unit list is formed, and the yaw angle of the upstream unit is taken as the independent variable and the total power as the target function to input into the differential evolution algorithm to obtain the optimal yaw angle. Finally, the yaw angle list of each wind direction and each wind speed in the whole field is obtained through data reorganization. The yaw matrix calculation under three-dimensional coordinate condition is realized by the tail flow model, which improves the calculation accuracy compared with two-dimensional calculation, and the calculation efficiency is improved by determining the tail flow area.

[0104] The present application considers the complex wind turbine arrangement mode of the actual wind farm, and obtains the optimal yaw angle matrix of the units based on the tail flow model and the differential evolution algorithm, so as to realize the yaw angle calculation under the condition of each wind speed and each wind direction of the wind farm.

[0105] Example 2

[0106] Based on the same principle as the method shown in Example 1 of the present application, as shown in the accompanying Figure 3 The yaw matrix optimization device based on the differential evolution algorithm is also provided in the embodiment of the present application, which includes a coordinate transformation unit, a first processing unit, an input unit, a second processing unit, a third processing unit, a fourth processing unit and a fifth processing unit.

[0107] The coordinate transformation unit is used to take the wind direction of the wind tower as the whole-field inflow wind direction, the wind speed of the wind tower as the whole-field inflow wind speed, and perform coordinate transformation on the whole-field units according to the change of the wind direction in the horizontal direction to obtain the unit list after coordinate transformation.

[0108] The first processing unit is configured to sort all the groups of wind turbines in the whole field, select a target group of wind turbines, obtain relative distances between each group of wind turbines and the target group of wind turbines, and determine upstream groups of wind turbines in front of the target group of wind turbines according to a wake radius in a wake model; the upstream group of wind turbines is defined as a group of wind turbines within the wake radius in the wake model and having a wake influence on a downstream group of wind turbines;

[0109] The input unit is configured to input a next target group of wind turbines until upstream groups of wind turbines of all target groups of wind turbines are determined.

[0110] The second processing unit is configured to filter the target groups of wind turbines having the upstream groups of wind turbines, remove duplicates between all the target groups of wind turbines having the upstream groups of wind turbines and the corresponding upstream groups of wind turbines, sort the target groups of wind turbines and the corresponding upstream groups of wind turbines according to coordinate sizes, and obtain a group list containing the target groups of wind turbines having the upstream groups of wind turbines and the corresponding upstream groups of wind turbines.

[0111] The third processing unit is configured to calculate equivalent inflow velocities of corresponding downstream groups of wind turbines of each upstream group of wind turbines according to a flow wind speed of each upstream group of wind turbines and a yaw angle of each upstream group of wind turbines.

[0112] The fourth processing unit is configured to calculate a sum of total powers of all the upstream groups of wind turbines and the downstream groups of wind turbines according to the equivalent inflow velocities and the yaw angles of all the upstream groups of wind turbines and the equivalent inflow velocities and the yaw angles of all the downstream groups of wind turbines.

[0113] The fifth processing unit is configured to determine optimal yaw angles of the upstream groups of wind turbines based on a differential evolution algorithm, and take the sum of the total powers of all the upstream groups of wind turbines and the downstream groups of wind turbines as a target function.

[0114] Optionally, let z hub be a height of a hub center, u hub be a flow wind speed at the hub center, z be a vertical height relative to the hub center, a be an axial induction factor, C T be a thrust coefficient, r0 be an initial wake radius, D be a diameter of a wind wheel, r z be a wake radius of the wake in a vertical direction, r y be a wake radius of the wake in a horizontal direction, and k be a constant, then:

[0115]

[0116] r y = k y x + r0;

[0117] r z = k z x + r0.

[0118] Optionally, let w represent a transformation angle of a flow wind direction, the counterclockwise being positive, and an initial angle of the flow wind direction being a horizontal axis direction, xold y is the lateral coordinate value of the target machine group before coordinate transformation old x is the longitudinal coordinate value of the target machine group before coordinate transformation new y is the lateral coordinate value of the target machine group after coordinate transformation new x is the longitudinal coordinate value after coordinate transformation, and the formula of coordinate transformation is:

[0119]

[0120] Optionally, the wind speed at the hub center is regarded as the equivalent inflow speed of the wind turbine.

[0121] Optionally, the wind speed at the hub center is regarded as the equivalent inflow speed of the wind turbine, the target machine group is selected, the relationship between the wake radius and the relative distance x of the wind turbine in the Y-3DJGF wake model is used to search the nearest upstream machine group in the set range in the reverse x direction, and it is judged whether the machine group will have a wake effect on the target machine group.

[0122] All the machine groups after sorting of the entire field are regarded as search targets, in order to ensure that the wind speed of the upstream machine group obtained in subsequent calculation is earlier than that of the downstream machine group, the selected machine group is sorted based on all the machine groups after sorting of the entire field, and reverse sequence searching is performed (the selected machine group starts from the head, the entire field machine group starts from the corresponding selected machine group, and the upstream machine group is searched in reverse sequence). In order to ensure the speed of calculation, the wind speed at the hub center is regarded as the equivalent inflow speed U e of the wind turbine, the relationship between the wake radius and the relative distance x of the wind turbine in the Y-3DJGF wake model is used to search the nearest upstream machine group within 10D from the target machine group in the reverse x direction, and it is judged whether the machine group will have a wake effect on the target machine group. If yes, the number and relative position thereof are recorded.

[0123] Optionally, based on the differential evolution algorithm, the sum of the total power of all the upstream and downstream machine groups is taken as a target function to determine the optimal yaw angle of each upstream machine group, including population initialization, mutation, crossover, boundary processing, calculation of the target function and output of the optimal yaw angle;

[0124] Crossover: the difference between the new population individual and the individual in the current population is controlled by the crossover probability, whether the mutation operation is used to generate a new individual is determined according to the randomly generated value and the size of the crossover probability, if the randomly generated value is less than the crossover probability, the mutation operation is used to generate a new individual; otherwise, the new individual is the same as the target individual;

[0125] Boundary processing: the boundary value of the yaw angle is set;

[0126] The target function is calculated, including calculation of the wind turbine power and the yaw power, and calculation of the target function according to the yaw power;

[0127] Let p be the air flow density, A be the rotor area, C p is the wind power coefficient, η is an empirical coefficient, β is the yaw angle, P e is the rated power, U is the incoming wind speed, and the wind turbine power is P, then:

[0128]

[0129]

[0130] Let P ph represent the power after yawing, P() represent the corresponding non-yawing power at the incoming wind speed U e , which is a function of the upstream unit yaw angle, then:

[0131] P ph = P(U e ) cos η β;

[0132] Let X represent the x coordinate difference between the upstream unit and the downstream unit, Y represent the y coordinate difference between the upstream unit and the downstream unit, Z represent the z coordinate difference between the upstream unit and the downstream unit, Y3DJGF() be the wake model function, U ue be the equivalent incoming flow speed of the upstream unit, β u be the yaw angle of the corresponding upstream unit of the target unit, then:

[0133] U e = Y3DJGF(U ue , X, Y, Z, β u );

[0134] P ph = P(Y3DJGF(U ue , X, Y, Z, β u )) cos η β;

[0135] Calculate the sum of the total power of all upstream units and downstream units, including: Let n be the number of wind turbines, i be the number of wind turbines, U i be the incoming wind speed of the i th unit, P i be the yawing power of the i th wind turbine, and the value of the objective function be P g , then:

[0136]

[0137] After a certain number of iterations, output the optimal yaw angle.

[0138] Example 3

[0139] Based on the same principle as the method shown in the embodiments of the present application, an electronic device is also provided in the embodiments of the present application, as shown in the accompanying drawings Figure 4 The electronic device can include but is not limited to a processor and a memory; the memory is used to store a computer program; the processor is used to execute the yaw matrix optimization method based on the differential evolution algorithm shown in the embodiments of the present application by calling the computer program.

[0140] In an optional embodiment, an electronic device is provided, Figure 4 The electronic device 40 shown in the accompanying drawings includes a processor 410 and a memory 430. The processor 410 and the memory 430 are connected, such as through a bus 420.

[0141] Optionally, the electronic device 40 can also include a transceiver 440, which can be used for data interaction between the electronic device and other electronic devices, such as data transmission and / or data reception, etc. It should be noted that the transceiver 440 is not limited to one in actual application, and the structure of the electronic device 40 does not constitute a limitation on the embodiments of the present application.

[0142] The processor 410 can be a CPU (Central Processing Unit, central processor), a general-purpose processor, a DSP (Digital Signal Processor, data signal processor), an ASIC (Application Specific Integrated Circuit, application specific integrated circuit), an FPGA (Field Programmable Gate Array, field programmable gate array) or other programmable logic devices, transistor logic devices, hardware components or any combination thereof. It can realize or execute various exemplary logical blocks, modules and circuits described in combination with the disclosure. The processor 410 can also be a combination of computing functions, such as one or more microprocessor combinations, combinations of DSP and microprocessor, etc.

[0143] The bus 420 can include a channel for transmitting information between the above-mentioned components. The bus 420 can be a PCI (Peripheral Component Interconnect, peripheral component interconnect) bus or an EISA (Extended Industry Standard Architecture, extended industry standard architecture) bus, etc. The bus 420 can be divided into an address bus, a data bus, a control bus, etc. For the sake of representation, Figure 4 In the drawings, only one thick line is used to represent the bus, but it does not mean that there is only one bus or only one type of bus.

[0144] The memory 430 can be a ROM (Read Only Memory) or other type of static storage device that can store static information and instructions, a RAM (Random Access Memory) or other type of dynamic storage device that can store information and instructions, an EEPROM (Electrically Erasable Programmable Read Only Memory), a CD-ROM (Compact Disc Read Only Memory) or other optical disk storage, a magnetic disk storage or other magnetic storage device, or any other medium that can be used to carry or store desired program codes in the form of instructions or data structures and that can be accessed by a computer, but is not limited thereto.

[0145] The memory 430 is used to store application program codes (computer programs) for implementing the schemes of the present application, and is controlled by the processor 410 to perform. The processor 410 is used to execute the application program codes stored in the memory 430 to realize the content shown in the foregoing method embodiments.

[0146] The above merely describes the preferred embodiments of the present application, and is not intended to limit the present application. The present application can have various modifications and changes for those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A yaw matrix optimization method based on differential evolution algorithm, characterized in that, include: The wind direction of the meteorological tower is taken as the incoming wind direction of the entire field, and the wind speed of the meteorological tower is taken as the incoming wind speed of the entire field. Based on the change of wind direction in the horizontal direction, the coordinate transformation of the entire field unit is performed to obtain the unit list after coordinate transformation. All units in the entire field are sorted, the target unit is selected, the relative distance between each unit and the target unit is obtained, and the upstream units among the first few units of the target unit are determined according to the wake radius in the wake model; the upstream units are defined as units within the wake radius of the wake model that have a wake effect on the downstream units. Enter the next target unit until the upstream units of all target units are determined; Filter the target units that have upstream units, remove duplicates from all target units that have upstream units and their corresponding upstream units, sort them by coordinate size, and obtain a list of units that includes all target units that have upstream units and their corresponding upstream units; Based on the incoming wind speed and yaw angle of each upstream unit, calculate the equivalent inflow velocity of the downstream unit corresponding to each upstream unit; Calculate the sum of the total power of all upstream and downstream units based on the equivalent inflow velocity and yaw angle of all upstream units and the equivalent inflow velocity and yaw angle of all downstream units. Based on the differential evolution algorithm, the sum of the total power of all upstream and downstream units is used as the objective function to determine the optimal yaw angle of each upstream unit. This includes population initialization, mutation, crossover, boundary handling, calculation of the objective function, and output of the optimal yaw angle. Crossover: The crossover probability controls the degree of difference between individuals in the new population and individuals in the current population. The determination of whether to use mutation to generate new individuals is based on the randomly generated value and the crossover probability. If the randomly generated value is less than the crossover probability, mutation is used to generate new individuals; otherwise, the new individuals are the same as the target individuals. Boundary handling: Set boundary values ​​for the yaw angle; Calculate the objective function, including calculating the turbine power and yaw power, and calculate the objective function based on the yaw power; set up Where A is the airflow density and A is the wind turbine area. It is the wind power coefficient. It is an empirical coefficient. It's the yaw angle. It is the rated power. The incoming air velocity is [value], and the fan power is [value]. ,but: ； ； set up Represents the power after yaw. This represents the corresponding non-yaw power at the incoming wind speed. If is a function of the yaw angle of the upstream unit, then: ； set up Representing upstream and downstream units The coordinate difference Representing upstream and downstream units The coordinate difference Representing upstream and downstream units The coordinate difference For the wake model function, The equivalent inflow velocity of the upstream unit. Let yaw angle be the upstream unit corresponding to the target unit, then: ； ； Calculate the sum of the total power of all upstream and downstream units, including: assuming Number of wind turbines For the number of wind turbines, For the first Incoming air velocity of the Taiwanese unit For the first The yaw power of a typhoon generator, the objective function value is ,but: ； After a set number of iterations, the optimal yaw angle is output.

2. The yaw matrix optimization method based on differential evolution algorithm according to claim 1, characterized in that, Obtain the relative distances between each unit and the target unit. Based on the wake radius in the wake model, determine the upstream units among the first few units of the target unit, including: Among the preceding units of the target unit, the units whose relative distance to the target unit is smaller than the wake radius in the wake model are considered upstream units of the target unit; the units and the target unit are... The relative distance in the direction is less than the set value, and the generator unit and the target generator unit are in... The relative distance in the direction is less than the wake radius of the target unit in the horizontal direction, and the unit and the target unit are in The relative distance in the direction is less than the wake radius of the target unit in the vertical direction; If the target unit has at least one upstream unit, then the target unit is a downstream unit of the upstream unit; if the target unit has no upstream unit, then the next target unit is selected to determine whether there is an upstream unit.

3. The yaw matrix optimization method based on differential evolution algorithm according to claim 1, characterized in that, set up It is the height of the center of the wheel hub. It refers to the incoming wind speed at the center of the wheel hub. It is the vertical height relative to the center of the wheel hub. It is an axial inducing factor. , It is the thrust coefficient. It is the initial wake radius. It is the diameter of the wind turbine. It is the wake radius in the vertical direction. Let be the wake radius in the horizontal direction, then: ； ； 。 4. The yaw matrix optimization method based on differential evolution algorithm according to claim 1, characterized in that, set up This represents the angle of change in the incoming wind direction, with counterclockwise being positive. The initial angle of the incoming wind direction is the horizontal axis. The x-coordinate value of the target unit before coordinate transformation. The ordinate value of the target unit before coordinate transformation. This represents the x-coordinate value of the target unit after coordinate transformation. Let be the ordinate value after coordinate transformation. Then the formula for coordinate transformation is: 。 5. The yaw matrix optimization method based on differential evolution algorithm according to claim 1, characterized in that, The wind speed at the center of the hub is considered as the equivalent inflow velocity of the wind turbine.

6. A yaw matrix optimization device based on differential evolution algorithm, characterized in that, It includes a coordinate transformation unit, a first processing unit, an input unit, a second processing unit, a third processing unit, a fourth processing unit, and a fifth processing unit; The coordinate transformation unit is used to take the wind direction of the meteorological tower as the incoming wind direction of the entire field and the wind speed of the meteorological tower as the incoming wind speed of the entire field. Based on the change of wind direction in the horizontal direction, the coordinate transformation is performed on the entire field of units to obtain a list of units after coordinate transformation. The first processing unit is used to sort all the units in the entire field, select the target unit, obtain the relative distance between each unit and the target unit, and determine the upstream units among the first few units of the target unit based on the wake radius in the wake model; the upstream units are defined as units within the wake radius of the wake model that have a wake effect on the downstream units. The input unit is used to input the next target unit until the upstream units of all target units are determined; The second processing unit is used to filter target units with upstream units, remove duplicates from all target units with upstream units and their corresponding upstream units, sort them according to coordinate size, and obtain a list of units containing all target units with upstream units and their corresponding upstream units. The third processing unit is used to calculate the equivalent inflow velocity of the downstream unit corresponding to each upstream unit based on the incoming wind speed of each upstream unit and the yaw angle of each upstream unit. The fourth processing unit is used to calculate the sum of the total power of all upstream and downstream units based on the equivalent inflow velocity and yaw angle of all upstream units and the equivalent inflow velocity and yaw angle of all downstream units. The fifth processing unit is used to determine the optimal yaw angle of each upstream unit based on the differential evolution algorithm, using the sum of the total power of all upstream and downstream units as the objective function. This includes population initialization, mutation, crossover, boundary handling, calculation of the objective function, and output of the optimal yaw angle. Crossover: The crossover probability controls the degree of difference between individuals in the new population and individuals in the current population. The determination of whether to use mutation to generate new individuals is based on the randomly generated value and the crossover probability. If the randomly generated value is less than the crossover probability, mutation is used to generate new individuals; otherwise, the new individuals are the same as the target individuals. Boundary handling: Set boundary values ​​for the yaw angle; Calculate the objective function, including calculating the turbine power and yaw power, and calculate the objective function based on the yaw power; set up Where A is the airflow density and A is the wind turbine area. It is the wind power coefficient. It is an empirical coefficient. It's the yaw angle. It is the rated power. The incoming air velocity is [value], and the fan power is [value]. ,but: ； ； set up Represents the power after yaw. This represents the corresponding non-yaw power at the incoming wind speed. If is a function of the yaw angle of the upstream unit, then: ； set up This represents the difference in x-coordinates between the upstream and downstream generating units. Representing upstream and downstream units The coordinate difference Representing upstream and downstream units The coordinate difference For the wake model function, The equivalent inflow velocity of the upstream unit. Let yaw angle be the upstream unit corresponding to the target unit, then: ； ； Calculate the sum of the total power of all upstream and downstream units, including: Let n be the number of wind turbines. For the number of wind turbines, For the first Incoming air velocity of the Taiwanese unit For the first The yaw power of a typhoon generator, the objective function value is ,but: ； After a set number of iterations, the optimal yaw angle is output.

7. An electronic device, characterized in that, include: Processor and memory; The memory is used to store computer operation instructions; The processor is configured to execute the yaw matrix optimization method based on differential evolution algorithm as described in any one of claims 1 to 5 by invoking the computer operation instructions.

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