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

Abstract

The invention 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 electronic equipment. The method comprises the following steps: carrying out coordinate transformation on the whole unit; determining an upstream unit in a plurality of units before the target unit according to the wake radius in the wake model; upstream units of all the target units are determined; screening the target units with the upstream units to obtain a unit list containing all the target units with the upstream units and the corresponding upstream units; calculating an equivalent inflow velocity; the sum of the total power of all the upstream units and the downstream units is calculated; and on the basis of a differential evolution algorithm, the optimal yaw angle of each upstream unit is determined. According to the method, the complex fan arrangement mode of the actual wind power plant is considered, the optimal yaw angle matrix of the unit is obtained based on the wake flow model and in combination with the differential evolution algorithm with the maximum whole-plant power as the target, and yaw angle calculation of the wind power plant under the conditions of all wind speeds and all wind directions is achieved.

Description

Technical Field

[0001] The present invention belongs to the technical field of wind turbine yaw control, and in particular, relates to a yaw matrix optimization method, device and electronic equipment based on a differential evolution algorithm. Background Art

[0002] The capacity of wind power units has increased year by year, the scale of wind farms has also expanded, and the wake impact between wind turbines has increased. The study of the wake characteristics of wind turbines has become an increasingly important topic.

[0003] There are three methods for calculating the wake of a wind turbine: simulation calculation, wind tunnel experiment, and analytical wake model. The simulation calculation method has deviations, 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, the Reynolds number has large deviations, and the number of wind tunnel tests is too many to reflect the actual situation; the existing analytical wake model method has the problems of complex wake model structure, slow calculation speed, and cannot reflect the actual situation of the flow.

[0004] At the yaw optimization level, based on the Boolean control yaw angle strategy, the yaw angle of the wind rotor is defined as a Boolean value, that is, the yaw angle is pre-defined, and then the unit needs to yaw to determine whether it needs to yaw and then control the unit yaw operation. In the simulation experiment, the use of this strategy obtains less optimized power than the gradient optimizer. The existing technology only uses small rectangular simulated wind farms to study the application of genetic algorithms in optimizing the yaw angle of the unit, but has not conducted research on actual large wind farms. The wake steering control method uses a gradient ascent search algorithm to maximize the power analytical function. The application of this wake deflection control increases the annual average wind speed and the power generation under the average wind direction. Moreover, this method is only a study of small wind farms with a single row arrangement, and does not consider large wind farms with complex unit arrangements. Summary of the invention

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

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

[0007] The wind direction of the wind tower is used as the incoming wind direction of the whole field, and the wind speed of the wind tower is used as the incoming wind speed of the whole field. According to the change of wind direction in the horizontal direction, the coordinates of the units in the whole field are transformed to obtain the unit list after the coordinate transformation;

[0008] Sort all the units in the field, select the target unit, obtain the relative distance between each unit and the target unit, and determine the upstream unit among the first several units of the target unit according to the wake radius in the wake model; the upstream unit is defined as the unit that has a wake impact on the downstream unit within the wake radius range in the wake model;

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

[0010] Filter the target units with upstream units, remove duplicates from all target units with upstream units and corresponding upstream units, sort them by coordinate size, and obtain a unit list including all target units with upstream units and corresponding upstream units;

[0011] According to the incoming wind speed of each upstream unit and the yaw angle of each upstream unit, the equivalent inflow velocity of the downstream unit corresponding to each upstream unit is calculated;

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

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

[0014] In a second aspect, the present invention provides a yaw matrix optimization device based on a differential evolution algorithm, comprising 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] A coordinate transformation unit is used to use the wind direction of the wind tower as the incoming wind direction of the entire field, and the wind speed of the wind tower as the incoming wind speed of the entire field. According to the change of the wind direction in the horizontal direction, coordinate transformation is performed on the units of the entire field 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 unit among the first several units of the target unit according to the wake radius in the wake model; the upstream unit is defined as the unit that has a wake impact on the downstream unit within the wake radius range in the wake model;

[0017] An input unit, used for inputting the next target unit until the upstream units of all target units are determined;

[0018] The second processing unit is used to screen the target units with upstream units, remove duplicates from all target units with upstream units and corresponding upstream units, sort them according to the size of coordinates, and obtain a unit list including all target units with upstream units and corresponding upstream units;

[0019] A third processing unit is used to calculate the equivalent inflow velocity of the downstream unit corresponding to each upstream unit according to the incoming wind velocity of each upstream unit and the yaw angle of each upstream unit;

[0020] a fourth processing unit, configured to calculate the sum of the total powers of all upstream units and downstream units according to the equivalent inflow speeds and yaw angles of all upstream units and the equivalent inflow speeds and yaw angles of all downstream units;

[0021] The fifth processing unit is used 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 the objective function.

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

[0023] Processor and memory;

[0024] The memory is used to store computer operation instructions;

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

[0026] Based on the above technical solution, the present invention can also be improved as follows.

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

[0028] Among the first several units of the target unit, the unit whose relative distance to the target unit is less than the wake radius in the wake model is the upstream unit of the target unit; the relative distance between the unit and the target unit in the x direction is less than the 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;

[0029] 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.

[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 rotor diameter, r z is the wake radius of the wake in the vertical direction, r y is the wake radius of the wake in the horizontal direction, then:

[0031]

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

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

[0034] Furthermore, let w represent the change angle of the incoming wind direction, counterclockwise is positive, 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 ordinate 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 ordinate value after coordinate transformation, then the formula of coordinate transformation is:

[0035]

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

[0037] Furthermore, based on the differential evolution algorithm, the sum of the total power of all upstream units 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 processing, calculation of objective function and output of optimal yaw angle;

[0038] Crossover: The degree of difference between the new population individuals and the current population individuals is controlled by the crossover probability. Whether to use mutation operation to generate new individuals is determined based on the randomly generated value and the crossover probability. If the randomly generated value is less than the crossover probability, mutation operation is used to generate new individuals; otherwise, the new individuals are the same as the target individuals.

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

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

[0041] Let ρ be the airflow density, A be the rotor area, Cp is the wind power coefficient, η is the empirical coefficient, β is the yaw angle, P e is the rated power, U is the incoming wind speed, and the fan power is P, then:

[0042]

[0043]

[0044] Let P ph represents the power after yaw, P() represents the corresponding unyawed power under 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() is the wake model function, U ue is the equivalent inflow velocity of the upstream unit, β u is the yaw angle of the upstream unit corresponding to 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 total power of all upstream and downstream units, including: Let n be the number of wind turbines, i be the number of wind turbines, U i is the incoming wind speed of the i-th unit, P i is the yaw power of the i-th wind turbine, and the value of the objective function is P g ,but:

[0050]

[0051] After the set number of iterations, the optimal yaw angle is output.

[0052] The beneficial effects of the present invention are as follows: after the coordinate transformation of the unit according to the wind direction, the present invention arranges the order of the units according to the wind direction, uses the wake model to determine the wake area of ​​the upstream wind turbine closest to the target unit, and forms a list of upstream and downstream units, and then uses the yaw angle of the upstream unit as an independent variable and the total power as the objective function to input into the differential evolution algorithm to obtain the optimal yaw angle. Finally, through data reorganization, a list of yaw angles for each wind speed under each wind direction of the entire field is obtained; the present invention realizes the yaw matrix calculation under three-dimensional coordinate conditions with the help of the wake model, which improves the calculation accuracy compared to the two-dimensional calculation, and improves the calculation efficiency by determining the wake area; the present invention takes into account the complex wind turbine arrangement method of the actual wind farm, based on the wake model, combined with the differential evolution algorithm, with the maximum whole field power as the goal, to obtain the optimal yaw angle matrix of the unit, and realizes the yaw angle calculation under each wind speed and wind direction of the wind farm. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 A schematic diagram of a yaw matrix optimization method based on a differential evolution algorithm provided in Example 1 of the present invention;

[0054] Figure 2 This is the flow chart of differential evolution algorithm;

[0055] Figure 3 A schematic diagram of a yaw matrix optimization device based on a differential evolution algorithm provided in Example 2 of the present invention;

[0056] Figure 4 This is a schematic diagram of an electronic device provided in Example 3 of the present invention.

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

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

[0059] Example 1

[0060] As an example, Figure 1 As shown, in order to solve the above technical problems, this embodiment provides a yaw matrix optimization method based on a differential evolution algorithm, including:

[0061] The wind direction of the wind tower is used as the incoming wind direction of the whole field, and the wind speed of the wind tower is used as the incoming wind speed of the whole field. According to the change of wind direction in the horizontal direction, the coordinates of the units in the whole field are transformed to obtain the unit list after the coordinate transformation;

[0062] Sort all the units in the field, select the target unit, obtain the relative distance between each unit and the target unit, and determine the upstream unit among the first several units of the target unit according to the wake radius in the wake model; the upstream unit is defined as the unit that has a wake impact on the downstream unit within the wake radius range in the wake model;

[0063] Enter the next target unit until the upstream units of all target units are determined;

[0064] Filter the target units with upstream units, remove duplicates from all target units with upstream units and corresponding upstream units, sort them by coordinate size, and obtain a unit list including all target units with upstream units and corresponding upstream units;

[0065] According to the incoming wind speed of each upstream unit and the yaw angle of each upstream unit, the equivalent inflow velocity of the downstream unit corresponding to each upstream unit is calculated;

[0066] Calculate the sum of the total power of all upstream units and downstream units based on 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 used as the objective function to determine the optimal yaw angle of each upstream unit.

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

[0069] Among the first several units of the target unit, the unit whose relative distance to the target unit is less than the wake radius in the wake model is the upstream unit of the target unit; the relative distance between the unit and the target unit in the x direction is less than the 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, let z hub is the height of the hub center, uhub 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 rotor diameter, r z is the wake radius of the wake in the vertical direction, r y is the wake radius of the wake 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 an expression of the wake velocity obtained based on the operating status of the wind turbine. It can accurately describe the three-dimensional distribution characteristics of the wake area while considering the yaw angle.

[0076] Optionally, let w represent the change angle of the incoming wind direction, counterclockwise is positive, 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 ordinate 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 ordinate value after coordinate transformation, then the formula of coordinate transformation is:

[0077]

[0078] Optionally, the wind speed at the hub center is regarded as the equivalent inflow velocity of the wind turbine.

[0079] Optional, as attached Figure 2 As shown, based on the differential evolution algorithm, the sum of the total power of all upstream units 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 processing, calculation of objective function and output of optimal yaw angle;

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

[0081] Boundary processing: set the boundary value of the yaw angle;

[0082] Calculate the objective function, including calculating the wind turbine power and the yaw power, and calculate the objective function according to the yaw power;

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

[0084]

[0085]

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

[0087] P ph =P(U e )cos η β;

[0088] 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() is the wake model function, U ue is the equivalent inflow velocity of the upstream unit, β u is the yaw angle of 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 total power of all upstream and downstream units, including: Let n be the number of wind turbines, i be the number of wind turbines, U i is the incoming wind speed of the i-th unit, P i is the yaw power of the i-th wind turbine, and the value of the objective function is P g ,but:

[0092]

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

[0094] Differential Evolution Algorithm (DE algorithm) is an optimization algorithm based on modern intelligent theory. It forms swarm intelligence through the cooperation and competition among individuals within the swarm to guide the direction of the optimization search. Its basic idea is to start from a randomly generated initial population and generate new individuals by calculating the vector difference between any two individuals and summing it 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. New individuals are generated by using the mutation operation. 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. A higher crossover probability will lead to more differences, while a lower crossover probability is more conducive to retaining more characteristics of the original individuals.

[0098] Let CR be the crossover probability, the population be X, X old be the unmutated population, and the individuals in the population be β i , be the (g + 1)-th new individual. if rand(0, 1) < CR means that if the random number taken between (0, 1) is less than the crossover probability CR, then The individuals in the population include the yaw angles of all upstream units output in the wake influence judgment. Generally speaking, the yaw angle generally does not exceed the interval [-30, 30]. Therefore, the upper and lower limits of each β are set to [-30, 30].

[0099]

[0100] Compare the new individual 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. By continuously evolving, retaining excellent individuals and eliminating inferior individuals, the search is guided to gradually approach the optimal solution.

[0101] In order to calculate the equivalent incoming flow wind speed of each unit, it is necessary to know the incoming flow wind speed and yaw angle of the upstream units. The yaw angle is given by the population individuals. The determination of the upstream incoming flow wind speed is as follows:

[0102] The units are divided into units affected by wake and units not affected by wake. The units not affected by wake regard the incoming wind speed as the incoming wind speed of the entire field. The units affected by wake are based on the upstream and downstream relationship list and the function U about the yaw angle of the upstream unit. e Calculate the equivalent inflow velocity. After the coordinate transformation, the upstream and downstream relationships are initially determined by sorting the units by the size of the X coordinates. Based on this, the units in the selected unit list are sorted based on the sorted list of the entire field unit, and the calculation starts from the unit with the smallest X coordinate value to obtain the corresponding upstream wind turbine number. This can effectively avoid the problem of requiring the inflow velocity of the upstream wind turbine but not calculating it first. The obtained upstream unit numbers increase in X coordinate from top to bottom, corresponding to the yaw angle of each upstream unit in the population, so that the equivalent inflow velocity of each wind turbine is calculated in turn according to the wake model.

[0103] The present invention transforms the coordinates of the units according to the wind direction, arranges the order of the units according to the wind direction, uses the wake model to determine the wake area of ​​the upstream wind turbine of the target unit, and forms a list of upstream and downstream units. The yaw angle of the upstream unit is used as the independent variable and the total power is used as the objective function to input into the differential evolution algorithm to obtain the optimal yaw angle. Finally, through data reorganization, a list of yaw angles for each wind speed under each wind direction in the entire field is obtained. The present invention realizes the yaw matrix calculation under three-dimensional coordinate conditions with the help of the wake model, which improves the calculation accuracy compared to two-dimensional calculation, and improves the calculation efficiency by determining the wake area.

[0104] The present invention takes into account the complex wind turbine layout in actual wind farms, based on the wake model and combined with the differential evolution algorithm, takes the maximum overall power as the goal, obtains the optimal yaw angle matrix of the unit, and realizes the yaw angle calculation under various wind speed and wind direction conditions in the wind farm.

[0105] Example 2

[0106] Based on the same principle as the method shown in Example 1 of the present invention, as shown in the attached Figure 3 As shown, an embodiment of the present invention further provides a yaw matrix optimization device based on a differential evolution algorithm, comprising 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] A coordinate transformation unit is used to use the wind direction of the wind tower as the incoming wind direction of the entire field, and the wind speed of the wind tower as the incoming wind speed of the entire field. According to the change of the wind direction in the horizontal direction, coordinate transformation is performed on the units of the entire field to obtain a list of units after coordinate transformation;

[0108] 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 unit among the first several units of the target unit according to the wake radius in the wake model; the upstream unit is defined as the unit that has a wake impact on the downstream unit within the wake radius range in the wake model;

[0109] An input unit, used for inputting the next target unit until the upstream units of all target units are determined;

[0110] The second processing unit is used to screen the target units with upstream units, remove duplicates from all target units with upstream units and corresponding upstream units, sort them according to the size of coordinates, and obtain a unit list including all target units with upstream units and corresponding upstream units;

[0111] A third processing unit is used to calculate the equivalent inflow velocity of the downstream unit corresponding to each upstream unit according to the incoming wind velocity of each upstream unit and the yaw angle of each upstream unit;

[0112] a fourth processing unit, configured to calculate the sum of the total powers of all upstream units and downstream units according to the equivalent inflow speeds and yaw angles of all upstream units and the equivalent inflow speeds and yaw angles of all downstream units;

[0113] The fifth processing unit is used 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 the objective function.

[0114] Optionally, let z hub is 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 rotor diameter, r z is the wake radius of the wake in the vertical direction, r y is the wake radius of the wake in the horizontal direction, then:

[0115]

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

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

[0118] Optionally, let w represent the change angle of the incoming wind direction, counterclockwise is positive, the initial angle of the incoming wind direction is the horizontal axis direction, xold is the horizontal coordinate value of the target unit before coordinate transformation, y old is the ordinate 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 ordinate value after coordinate transformation, then the formula of coordinate transformation is:

[0119]

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

[0121] Optionally, the wind speed at the hub center is regarded as the equivalent inflow velocity of the wind turbine, the target unit is selected, and 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 for the nearest upstream unit within the set range in the reverse x direction, and determine whether the unit will have a wake impact on the target unit.

[0122] All units after the whole field is sorted are regarded as search targets. In order to ensure that the wind speed of the upstream unit in the subsequent calculation is obtained before the downstream unit, the selected unit is sorted based on all the units after the whole field is sorted, and the reverse search is performed (the selected unit starts from the beginning, the whole field starts from the corresponding selected unit, and the upstream unit is searched in reverse order). In order to ensure the speed of calculation, the wind speed at the center of the hub is regarded as the equivalent inflow speed U of the wind turbine. e , using the relationship between the wake radius and the relative distance x of the wind turbine in the Y-3DJGF wake model, starting from the target unit, search the nearest upstream unit within 10D in the reverse x direction, and determine whether the unit will have a wake impact on the target unit. If so, record its number and relative position.

[0123] Optionally, based on a differential evolution algorithm, the sum of the total power of all upstream units and downstream units is used as an 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;

[0124] Crossover: The degree of difference between the new population individuals and the current population individuals is controlled by the crossover probability. Whether to use mutation operation to generate new individuals is determined based on the randomly generated value and the crossover probability. If the randomly generated value is less than the crossover probability, mutation operation is used to generate new individuals; otherwise, the new individuals are the same as the target individuals.

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

[0126] Calculate the objective function, including calculating the wind turbine power and the yaw power, and calculate the objective function according to the yaw power;

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

[0128]

[0129]

[0130] Let P ph represents the power after yaw, P() represents the corresponding unyawed power under the incoming wind speed, U e 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() is the wake model function, U ue is the equivalent inflow velocity of the upstream unit, β u is the yaw angle of the upstream unit corresponding to 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 total power of all upstream and downstream units, including: Let n be the number of wind turbines, i be the number of wind turbines, U i is the incoming wind speed of the i-th unit, P i is the yaw power of the i-th wind turbine, and the value of the objective function is P g ,but:

[0136]

[0137] After the set number of iterations, the optimal yaw angle is output.

[0138] Example 3

[0139] Based on the same principle as the method shown in the embodiment of the present invention, an electronic device is also provided in the embodiment of the present invention, as shown in the attached Figure 4 As shown, the electronic device may 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 embodiment of the present invention by calling the computer program.

[0140] In an optional embodiment, an electronic device is provided. Figure 4 The electronic device 40 shown includes: a processor 410 and a memory 430. The processor 410 and the memory 430 are connected, for example, via a bus 420.

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

[0142] Processor 410 may be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array) or other programmable logic devices, transistor logic devices, hardware components or any combination thereof. It may implement or execute various exemplary logic blocks, modules and circuits described in conjunction with the disclosure of the present invention. Processor 410 may also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, etc.

[0143] The bus 420 may include a path to transmit information between the above components. The bus 420 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus. The bus 420 may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 4 Only one thick line is used in the diagram, but this 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 types of static storage devices that can store static information and instructions, a RAM (Random Access Memory) or other types of dynamic storage devices that can store information and instructions, or an EEPROM (Electrically Erasable Programmable Read Only Memory), a CD-ROM (Compact Disc Read Only Memory) or other optical disk storage, optical disk storage (including compressed optical disk, laser disk, optical disk, digital versatile disk, Blu-ray disk, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited to these.

[0145] The memory 430 is used to store application code (computer program) for executing the solution of the present invention, and is controlled to be executed by the processor 410. The processor 410 is used to execute the application code stored in the memory 430 to implement the contents shown in the above method embodiment.

[0146] The above are only preferred embodiments of the present invention and are not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A yaw matrix optimization method based on differential evolution algorithm, characterized in that: include: The wind direction of the wind tower is used as the incoming wind direction of the whole field, and the wind speed of the wind tower is used as the incoming wind speed of the whole field. According to the change of wind direction in the horizontal direction, the coordinates of the units in the whole field are transformed to obtain the unit list after the coordinate transformation; Sort all the units in the field, select the target unit, obtain the relative distance between each unit and the target unit, and determine the upstream unit among the first several units of the target unit according to the wake radius in the wake model; the upstream unit is defined as the unit that has a wake impact on the downstream unit within the wake radius range in the wake model; Enter the next target unit until the upstream units of all target units are determined; Filter the target units with upstream units, remove duplicates from all target units with upstream units and corresponding upstream units, sort them by coordinate size, and obtain a unit list including all target units with upstream units and corresponding upstream units; According to the incoming wind speed of each upstream unit and the yaw angle of each upstream unit, the equivalent inflow velocity of the downstream unit corresponding to each upstream unit is calculated; Calculate the sum of the total power of all upstream units and downstream units based on the equivalent inflow speed and yaw angle of all upstream units and the equivalent inflow speed and yaw angle of all downstream units; Based on the differential evolution algorithm, the sum of the total power of all upstream units and downstream units is used as the objective function to determine the optimal yaw angle of each upstream unit.

2. The yaw matrix optimization method based on differential evolution algorithm according to claim 1 is characterized in that: Obtain the relative distance between each unit and the target unit, and determine the upstream units among the first several units of the target unit according to the wake radius in the wake model, including: Among the first several units of the target unit, the unit whose relative distance to the target unit is less than the wake radius in the wake model is the upstream unit of the target unit; the relative distance between the unit and the target unit in the x direction is less than the 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; 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.

3. The yaw matrix optimization method based on differential evolution algorithm according to claim 1, characterized in that: Assume z hub is 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 rotor diameter, r z is the wake radius of the wake in the vertical direction, r y is the wake radius of the wake in the horizontal direction, then: r y =k y x+r0; r z =k z x+r0。 4. According to the yaw matrix optimization method based on differential evolution algorithm in claim 1, it is characterized in that w represents the change angle of the incoming wind direction, counterclockwise is positive, 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 ordinate 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 ordinate value after coordinate transformation, then the formula of 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 hub center is regarded as the equivalent inflow velocity of the wind turbine.

6. The yaw matrix optimization method based on differential evolution algorithm according to claim 1, characterized in that: Based on the differential evolution algorithm, the sum of the total power of all upstream units 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 processing, calculation of objective function and output of optimal yaw angle; Crossover: The degree of difference between the new population individuals and the current population individuals is controlled by the crossover probability. Whether to use mutation operation to generate new individuals is determined based on the randomly generated value and the crossover probability. If the randomly generated value is less than the crossover probability, mutation operation is used to generate new individuals; otherwise, the new individuals are the same as the target individuals. Boundary processing: set the boundary value of the yaw angle; Calculate the objective function, including calculating the wind turbine power and the yaw power, and calculate the objective function according to the yaw power; Let ρ be the airflow density, A be the rotor area, C p is the wind power coefficient, η is the empirical coefficient, β is the yaw angle, P e is the rated power, U is the incoming wind speed, and the fan power is P, then: Let P ph represents the power after yaw, P() represents the corresponding unyawed power under the incoming wind speed, U e is a function of the upstream unit yaw angle, then: Pph=P(Ue)cos η b; 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() is the wake model function, U ue is the equivalent inflow velocity of the upstream unit, β u is the yaw angle of the upstream unit corresponding to the target unit, then: HER e =Y3DJGF(U ue ,X,Y,Z,β u ): P ph =P(Y3DJGF(U ue ,X,Y,Z,β u ))cos η β: Calculate 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, U i is the incoming wind speed of the i-th unit, P i is the yaw power of the i-th wind turbine, and the value of the objective function is P g ,but: After the set number of iterations, the optimal yaw angle is output.

7. A yaw matrix optimization device based on a 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; A coordinate transformation unit is used to use the wind direction of the wind tower as the incoming wind direction of the entire field, and the wind speed of the wind tower as the incoming wind speed of the entire field. According to the change of the wind direction in the horizontal direction, coordinate transformation is performed on the units of the entire field 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 unit among the first several units of the target unit according to the wake radius in the wake model; the upstream unit is defined as the unit that has a wake impact on the downstream unit within the wake radius range in the wake model; An input unit, used for inputting the next target unit until the upstream units of all target units are determined; The second processing unit is used to screen the target units with upstream units, remove duplicates from all target units with upstream units and corresponding upstream units, sort them according to the size of coordinates, and obtain a unit list including all target units with upstream units and corresponding upstream units; A third processing unit is used to calculate the equivalent inflow velocity of the downstream unit corresponding to each upstream unit according to the incoming wind velocity of each upstream unit and the yaw angle of each upstream unit; a fourth processing unit, configured to calculate the sum of the total powers of all upstream units and downstream units according to the equivalent inflow speeds and yaw angles of all upstream units and the equivalent inflow speeds and yaw angles 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, taking the sum of the total power of all upstream units and downstream units as the objective function.

8. An electronic device, characterized in that: include: Processor and memory; The memory is used to store computer operation instructions; The processor is used to execute the yaw matrix optimization method based on the differential evolution algorithm according to any one of claims 1 to 6 by calling the computer operation instruction.

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