CN113656973B - Wake flow hybrid simulation method, system, device and medium for wind power plant - Google Patents
Wake flow hybrid simulation method, system, device and medium for wind power plant Download PDFInfo
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Abstract
The invention relates to the field of wind power plant control, and particularly provides a wake flow hybrid simulation method, a wake flow hybrid simulation system, a wake flow hybrid simulation device and a wake flow hybrid simulation medium for a wind power plant, which solve the problem that the conventional wake flow simulation method for the wind power plant cannot give consideration to both calculation accuracy and calculation speed. For this purpose, the wake mixed simulation method of the wind power plant obtains the difference value between the actual power and the simulated power of the wind power plant, obtains the interval defining value of the average interval of the wind turbine units in the wind power plant according to the comparison result of the difference value and the power error threshold value, adopts the wake simulation method based on the engineering wake model when the average interval of the wind turbine units in the wind power plant is greater than or equal to the interval defining value, and adopts the wake simulation method based on the RANS model when the average interval is smaller than the interval defining value.
Description
Technical Field
The invention relates to the field of wind power plant control, and particularly provides a wake flow hybrid simulation method, a wake flow hybrid simulation system, a wake flow hybrid simulation device and a wake flow hybrid simulation medium for a wind power plant.
Background
With the development of wind power technology, the development and utilization of wind energy are more and more extensive, and in order to save land resources and construction cost, a plurality of wind power generation sets are installed in the same wind power plant, and the number of the wind power generation sets in the wind power plant is different from dozens of wind power generation sets to hundreds of wind power generation sets. With the increase of the number of the units in the wind power plant, the wake effect becomes one of main factors influencing the overall output power of the wind power plant, the wake effect among the wind power plants is simulated efficiently and accurately, and the method has great significance for micro site selection and optimal control of the wind power plant.
The wake flow simulation method of the wind power plant widely used at present mainly comprises two methods: engineering wake flow model based and computational fluid dynamics based methods. The simulation method based on the engineering wake flow model generally obtains an analytic expression for solving the wake flow velocity distribution of a single wind turbine under some idealized assumptions. The method is simple in form and high in calculation speed, but the accuracy needs to be improved. The computational fluid dynamics method is more advantageous in terms of accuracy, but the computational fluid dynamics method is relatively inefficient because of the large amount of computational resources. The method for calculating fluid mechanics can be divided into a direct simulation method (DNS), a large vortex simulation method (LES), a reynolds time averaging method (RANS), and a separation vortex simulation method (DES) according to different modeling modes for turbulence pulsation. The RANS method, however, is a method that omits many flow details in the calculation, but has lower requirements on computational resources compared to other computational fluid dynamics methods, and can also ensure a certain accuracy. Thus, both engineering wake model-based and computational fluid dynamics-based methods have substantial advantages and disadvantages. The problem that the calculation accuracy and the calculation speed cannot be well balanced by the conventional wake flow simulation method of the wind power plant is solved.
Accordingly, there is a need in the art for a new wake simulation solution for wind farms to address the above-mentioned problems.
Disclosure of Invention
The invention aims to solve the technical problem that the existing wake flow simulation method of the wind power plant cannot give consideration to both calculation precision and calculation speed.
In a first aspect, the present invention provides a wake mixing simulation method for a wind farm, the simulation method comprising the steps of:
acquiring actual power of a preset test wind power plant under a preset inflow working condition, performing wake simulation on the test wind power plant by adopting a wake simulation method based on an engineering wake model to obtain simulated power under the inflow working condition, and acquiring a difference value between the actual power and the simulated power;
determining a spacing defining value of the average spacing of the wind turbines formed by the test wind power plant in the incoming flow direction under the incoming flow working condition according to the comparison result of the difference value and a preset power error threshold value;
judging whether the average distance between the wind turbines formed in the incoming flow direction of the actual wind power plant under the incoming flow working condition is larger than or equal to the distance defining value or not;
if so, carrying out wake flow simulation on the actual wind power plant by adopting a wake flow simulation method based on an engineering wake flow model;
and if not, performing wake flow simulation on the actual wind power plant by adopting a wake flow simulation method based on the RANS model.
In one technical solution of the wake mixed simulation method for the wind farm, the preset inflow conditions include a plurality of different inflow conditions, and the step of determining a distance defining value of an average distance between wind turbines formed by the test wind farm in an inflow direction under the inflow conditions according to a comparison result of the difference value and a preset power error threshold includes:
acquiring an absolute value of the difference value according to the difference value aiming at each incoming flow working condition, comparing the absolute value with the power error threshold value, and acquiring a corresponding average distance when the absolute value is less than or equal to the power error threshold value;
and acquiring the spacing definition value according to the acquired average spacing.
In one technical solution of the wake flow hybrid simulation method for the wind farm, the step of obtaining the spacing defining value according to the obtained average spacing includes:
calculating the average value of the average distance according to the obtained average distance;
and acquiring the spacing defining value according to the average value.
In one embodiment of the wake flow hybrid simulation method for the wind farm, "obtaining the spacing limit value according to the average value" includes:
and acquiring the interval defining value according to the average value and a preset wind direction compensation coefficient.
In a second aspect, the present invention provides a wake mixing simulation system for a wind farm, the simulation system comprising:
the power difference value acquisition module is configured to acquire actual power of a preset test wind power plant under a preset incoming flow working condition, carry out wake flow simulation on the test wind power plant by adopting a wake flow simulation method based on an engineering wake flow model, acquire simulated power under the incoming flow working condition and acquire a difference value between the actual power and the simulated power;
the distance limit value determining module is configured to determine a distance limit value of an average distance between the wind turbines formed by the test wind power plant in the incoming flow direction under the incoming flow working condition according to a comparison result of the difference value and a preset power error threshold value;
the simulation scheme confirming module is configured to judge whether the average distance between the wind turbines formed in the incoming flow direction of the actual wind power plant under the incoming flow working condition is larger than or equal to the distance defining value or not; if so, carrying out wake flow simulation on the actual wind power plant by adopting a wake flow simulation method based on an engineering wake flow model; and if not, performing wake flow simulation on the actual wind power plant by adopting a wake flow simulation method based on the RANS model.
In one technical solution of the wake-flow hybrid simulation system of the wind farm, the preset inflow condition includes a plurality of different inflow conditions, and the interval limit value determining module includes:
the average distance obtaining unit is configured to obtain an absolute value of the difference value according to the difference value and compare the absolute value with the power error threshold value for each incoming flow working condition, and when the absolute value is smaller than or equal to the power error threshold value, obtain a corresponding average distance;
an interval-defining-value acquisition unit configured to acquire the interval defining value according to the acquired average interval.
In one embodiment of the wake flow hybrid simulation system of the wind farm, the distance limit value obtaining unit includes:
a pitch average value obtaining subunit configured to calculate an average value of the average pitches according to the obtained average pitches;
a spacing-defining-value obtaining subunit configured to obtain the spacing defining value from the average value.
In an aspect of the wake mixing simulation system of a wind farm, the distance-defining-value obtaining subunit is further configured to obtain the distance defining value according to the following steps:
and acquiring the interval defining value according to the average value and a preset wind direction compensation coefficient.
In a third aspect, a control device is provided, comprising a processor and a memory device adapted to store a plurality of program codes adapted to be loaded and run by the processor to perform the wake mixing simulation method of a wind farm according to any of the above-mentioned technical aspects of the wake mixing simulation method of a wind farm.
In a fourth aspect, a computer readable storage medium is provided, having stored therein a plurality of program codes adapted to be loaded and run by a processor to perform the wake mixing simulation method of a wind farm according to any of the above-mentioned aspects of the wake mixing simulation method of a wind farm.
Under the condition of adopting the technical scheme, the invention can adopt a wake flow simulation method based on an engineering wake flow model to carry out wake flow simulation on the test wind power plant, obtain the simulation power under the working condition of incoming flow, obtain the difference value between the actual power and the simulation power of the test wind power plant, further determine the interval limit value of the average interval of the wind power plants formed by the test wind power plant in the downstream direction of the working condition of incoming flow according to the comparison result of the difference value and the preset power error threshold value, and select the simulation method for carrying out the wake flow simulation on the actual wind power plant according to the comparison result of the average interval of the wind power plants formed by the actual wind power plant in the incoming flow direction of the working condition of incoming flow and the interval limit value. Through the configuration mode, the wake simulation method for the wind power plant can select the actual wind power plant to perform wake simulation according to the average distance of the wind power plant in the incoming wind direction under the incoming working condition, the advantages of the engineering wake model and the RANS model are combined, the wake simulation method based on the RANS model is adopted to perform wake simulation on the actual wind power plant when the average distance of the wind power plant is small, the wake simulation method based on the engineering wake model is adopted to perform wake simulation on the actual wind power plant when the average distance of the wind power plant is large, the calculation efficiency and the calculation precision in the wake simulation process can be comprehensively considered, and the wake simulation process of the wind power plant is more efficient and accurate.
Drawings
The disclosure of the present invention will become more readily understood with reference to the accompanying drawings. As is readily understood by those skilled in the art: these drawings are for illustrative purposes only and are not intended to constitute a limitation on the scope of the present invention. Wherein:
FIG. 1 is a flow chart illustrating the main steps of a wake mixing simulation method of a wind farm according to one embodiment of the present invention;
FIG. 2 is a main block diagram of a wake hybrid simulation system of a wind farm according to an embodiment of the present invention;
fig. 3 is a schematic diagram of a computational mesh of a wake simulation method based on the RANS model according to an embodiment of the present invention;
FIG. 4 is a schematic illustration of a wind farm layout according to one embodiment of the present invention;
FIG. 5 is a schematic diagram of errors of simulation results and actual measurement results of the wind farm shown in FIG. 4 under different working conditions, according to the embodiment of the present invention.
Detailed Description
Some embodiments of the invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only for explaining the technical principle of the present invention, and are not intended to limit the scope of the present invention.
In the description of the present invention, a "module" or "processor" may include hardware, software, or a combination of both. A module may comprise hardware circuitry, various suitable sensors, communication ports, memory, may comprise software components such as program code, or may be a combination of software and hardware. The processor may be a central processing unit, a microprocessor, a digital signal processor, or any other suitable processor. The processor has data and/or signal processing functionality. The processor may be implemented in software, hardware, or a combination thereof. Non-transitory computer readable storage media include any suitable medium that can store program code, such as magnetic disks, hard disks, optical disks, flash memory, read-only memory, random-access memory, and the like. The term "a and/or B" denotes all possible combinations of a and B, such as a alone, B alone or a and B. The term "at least one A or B" or "at least one of A and B" means similar to "A and/or B" and may include only A, only B, or both A and B. The singular forms "a", "an" and "the" may include the plural forms as well.
The wake flow simulation method of the wind power plant widely used at present mainly comprises two types: the method comprises a wind power plant wake flow simulation method based on an engineering wake flow model and a wind power plant wake flow simulation method based on a fluid mechanics method. In the practical application process, the two methods have advantages and disadvantages of the two methods. The engineering wake flow model is an analytic expression for solving the wake flow speed distribution of a single wind turbine generator based on an idealized assumption, and the model is simple in form, high in calculation speed and poor in calculation accuracy. The computational fluid dynamics method relies on solving Navier-Stokes equations, models turbulent pulsation, and is relatively high in computational accuracy, large in consumed computational resources and low in computational efficiency. In the practical engineering application process, the RANS (Reynolds Average Navier-Stokes) model is used as a form in a computational fluid dynamics method, and on the basis of paying attention to the overall effect of wake flow simulation of a wind power plant, a lot of flowing details are ignored, so that compared with other computational fluid dynamics methods, the requirements on computational resources are relatively low, meanwhile, certain precision can be guaranteed, and the application in the engineering field is relatively wide.
Generally, the wake flow simulation method based on the engineering wake flow model has the advantage of high efficiency in wake flow simulation, but the accuracy needs to be improved; however, the wake flow simulation using the computational fluid dynamics method is more advantageous in accuracy, but relatively inefficient.
Correspondingly, the invention provides a wake mixed simulation method for a wind power plant, which combines the characteristics and advantages of an engineering wake model and a method for calculating fluid mechanics to carry out wake simulation on the wind power plant.
Referring to fig. 1, fig. 1 is a schematic flow chart of main steps of a wake flow simulation method of a wind farm according to an embodiment of the invention. As shown in fig. 1, the wake mixing simulation method for a wind farm in the embodiment of the present invention mainly includes the following steps S101 to S105.
Step S101: the method comprises the steps of obtaining the actual power of a preset test wind power plant under a preset inflow working condition, carrying out wake simulation on the test wind power plant by adopting a wake simulation method based on an engineering wake model, obtaining the simulation power under the inflow working condition, and obtaining the difference value between the actual power and the simulation power.
In this embodiment, the actual power of the preset test wind farm under the preset inflow working condition may be obtained, the wake simulation of the test wind farm may be performed by using a wake simulation method of an engineering wake model, the simulated power under the inflow working condition may be obtained, and the difference between the actual power and the simulated power may be obtained. The inflow condition refers to a combination of a group of wind directions (inflow directions) and inflow wind speeds (inflow wind speeds), for example, the wind direction is 270 degrees, the wind speed is 8m/s, and the combination of the wind direction and the wind speed is the inflow condition.
In one embodiment, the actual power of the test wind farm may be the power obtained from actual measurement data. The simulation power of the wind power plant is tested by obtaining the wind speed at the wind wheel height of the wind turbine generator in the wind power plant through a wake simulation method based on an engineering wake model, finding out the corresponding generator set power according to the obtained wind speed and the wind speed-power curve of the wind turbine generator, and adding the power of all the wind turbine generators in the wind power plant to obtain the simulation power of the wind power plant under the incoming flow working condition. The wind speed-power curve of the wind turbine generator is a curve describing the relation between the wind speed and the power of the wind turbine generator.
Step S102: and determining a distance bound value of the average distance of the wind turbines formed by testing the wind power plant in the incoming flow direction under the incoming flow working condition according to the comparison result of the difference value and the preset power error threshold value.
In this embodiment, the difference between the actual power and the simulated power obtained in step S101 may be compared with a preset power error threshold, and a defined value of the average distance between the wind turbines formed in the wind farm in the incoming flow direction under the incoming flow condition is determined according to the comparison result.
Step S103: and judging whether the average distance between the wind turbines formed in the incoming flow direction of the actual wind power plant under the incoming flow working condition is larger than or equal to a distance limit value or not, if so, skipping to the step S104, and if not, skipping to the step S105.
In this embodiment, it is determined whether the average pitch of the wind turbines formed in the incoming flow direction of the actual wind farm under the incoming flow condition is greater than or equal to a pitch limit value.
Step S104: and carrying out wake flow simulation on the actual wind power plant by adopting a wake flow simulation method based on the engineering wake flow model.
In this embodiment, if the average distance between the wind turbines formed in the incoming flow direction of the actual wind farm under the incoming flow working condition is greater than or equal to the distance defining value, a wake simulation method based on an engineering wake model may be adopted to perform wake simulation on the actual wind farm.
Step S105: and performing wake simulation on the actual wind power plant by adopting a wake simulation method based on the RANS model.
In this embodiment, if the average distance between the wind turbines formed in the incoming flow direction of the wind farm under the incoming flow working condition is smaller than the distance limit value, a wake simulation method based on the RANS model may be adopted to perform wake simulation on the actual wind farm.
Based on the steps S101 to S103, the invention can adopt a wake flow simulation method based on an engineering wake flow model to carry out wake flow simulation on a test wind power plant, obtain the simulation power under the working condition of incoming flow, obtain the difference value between the actual power and the simulation power of the test wind power plant, further determine the interval limit value of the average interval of the wind power plants formed by the test wind power plant in the downstream direction of the working condition of incoming flow according to the comparison result of the difference value and the preset power error threshold value, and select the simulation method for carrying out the wake flow simulation on the actual wind power plant according to the comparison result of the average interval of the wind power plants formed by the actual wind power plant in the incoming flow direction of the working condition of incoming flow and the interval limit value. Through the configuration mode, the wake simulation method for the wind power plant can select the actual wind power plant to perform wake simulation according to the average distance of the wind power plant in the incoming wind direction under the incoming working condition, the advantages of the engineering wake model and the RANS model are combined, the wake simulation method based on the RANS model is adopted to perform wake simulation on the actual wind power plant when the average distance of the wind power plant is small, the wake simulation method based on the engineering wake model is adopted to perform wake simulation on the actual wind power plant when the average distance of the wind power plant is large, the calculation efficiency and the calculation precision in the wake simulation process can be comprehensively considered, and the wake simulation process of the wind power plant is more efficient and accurate.
Step S102 will be further described below.
In an implementation manner of the embodiment of the present invention, the preset inflow condition may include a plurality of different inflow conditions, and step S102 may further include the following steps:
step S1021: and acquiring an absolute value of the difference value according to the difference value aiming at each incoming flow working condition, comparing the absolute value with the power error threshold value, and acquiring a corresponding average distance when the absolute value is less than or equal to the power error threshold value.
In this embodiment, the preset incoming flow operating condition may include a plurality of different incoming flow operating conditions, and for each incoming flow operating condition, an absolute value of the difference may be calculated according to the difference between the actual power and the simulated power obtained in step S101, and the absolute value of the difference is compared with the power error threshold, and when the absolute value is less than or equal to the power error threshold, the average distance between the wind turbine generators formed by the incoming flow wind direction and the windward field under the corresponding incoming flow operating condition may be obtained. The value of the power error threshold can be determined by those skilled in the art according to the requirements of the practical application process.
The average distance between the wind turbine generators formed by the wind power plant in the incoming flow direction under the incoming flow working condition is the average value of the distance between the adjacent upstream wind turbine generator and the adjacent downstream wind turbine generator in the wind power plant in the incoming flow direction under the incoming flow working condition.
Step S1022: and acquiring an interval defining value according to the acquired average interval.
In the present embodiment, the pitch defining value may be acquired from the average pitch acquired in step S1021.
In one implementation manner of the embodiment of the present invention, step S1022 may further include:
step S10221: calculating the average value of the average distance according to the obtained average distance;
step S10222: and obtaining a spacing definition value according to the average value.
In the present embodiment, an average value of the average pitches acquired in step S1021 is calculated, and a pitch limit value can be acquired from the obtained average value.
In one implementation of the embodiment of the invention, the step S10222 further includes:
and obtaining a spacing defining value according to the average value and a preset wind direction compensation coefficient.
In the present embodiment, the distance defining value may be determined from the average value of the average distances acquired in step S10221 and the wind direction compensation coefficient. The wind direction compensation coefficient refers to a deviation value caused by uncertainty of a wind direction, and a person skilled in the art can determine a value of a wind direction compensation system according to an actual situation in an actual application process.
Specifically, assume that the average of the average pitches is
The wind direction compensation coefficient is d, the spacing defined value is
The average distance of wind turbines formed in the downstream direction of an actual wind power plant under the working condition of incoming flow is assumed to be
Then when
Carrying out wake simulation on an actual wind power plant by adopting a wake simulation method based on an engineering wake model; when in use
And carrying out wake flow simulation on the actual wind power plant by adopting a wake flow simulation method based on the RANS model.
In one implementation of the embodiment of the present invention, the engineering wake model of the wind farm is established through the following steps S201 to S204, and the RANS model of the wind farm is established through the following step S205:
step S201: setting boundary conditions of the wind power plant, namely setting parameters such as inflow wind speed, wind direction, wind shear index, turbulence intensity and air density of the wind power plant;
step S202: setting the layout of the wind power plant, namely determining the position of each wind turbine generator according to the position coordinates of the wind turbine generators in the wind power plant;
step S203: and setting parameters of the wind turbine generator, namely setting the height of a hub of the wind turbine generator, the diameter of a wind wheel, a wind speed-power curve and a wind speed-thrust curve.
Step S204: and setting an engineering wake model of the wind power plant. The method comprises the following steps of setting a wake model, a wake turbulence model and a superposition model of the wind power plant:
the wake flow model is:
wherein u is0Is the incoming wind speed of the wind farm uwIs the wind speed in the wake of the wind farm, CTIs the thrust coefficient of the wind turbine, k is the wake expansion rate, x is the distance from the downstream of the wind wheel to the wind wheel of the wind turbine, r0The radius of a wind wheel of the wind turbine generator set;
wake turbulence model:
wherein, Delta ImFor additional turbulence intensity, a is the axial induction factor of the wind turbine generator, I∞The intensity of the environmental turbulence is shown, and D is the diameter of a wind wheel of the wind turbine generator;
and (3) superposition model:
wherein u isiThe wind turbine generator is positioned in a wake flow superposition area of N wind turbine generators at the upstream for the inflow wind speed of a target wind turbine generator ijThe inflow wind speed u of an upstream wind turbine jjiIs the wind speed of the wake zone of the wind turbine j at the position of the wind turbine i.
Specifically, after wind passes through the wind wheel of the wind turbine, the wind wheel absorbs kinetic energy in the wind, so that the wind speed is attenuated. The wind after passing through the rotor is generally called wake flow. As the wake flows backwards in the wind farm, free currents in the surroundings will continuously merge, so that the wake wind speed is restored (wake wind speed increases). The wake flow model is the loss generated by calculating the wind speed after the wind passes through the wind wheel compared with the inflow wind speed. The fluctuation of wind speed and the rotation of the wind wheel can generate turbulence, and the size of the turbulence can influence the speed of wake wind speed recovery. The wake turbulence model is to correct parameters in the wake turbulence model according to the influence of turbulence on wake. Because the wake flow has an expansion effect, and meanwhile, the wake flow of the downstream wind turbine generator is also influenced by the wake flow of the upstream wind turbine generator, the wake flow superposition model calculates the wind speed loss of a superposition area when the defined wake flows of the wind turbine generators are superposed together.
Step S205: setting a RANS model of the wind power plant. The method comprises the steps of setting a computational grid of a wind turbine generator, setting an actuating disc model of the wind power plant, obtaining a volume force source item according to the actuating disc model, and further obtaining an RANS model of the wind power plant:
referring to fig. 3, fig. 3 is a schematic diagram of a computational grid of a wake simulation method based on an RANS model according to an embodiment of the present invention, and as shown in fig. 3, the computational grid is rectangular, a distance between a first exhaust wind turbine generator and an inflow port in a wind farm is 5D, a distance between a last exhaust wind turbine generator and an outlet is 20D to ensure that a wake can be fully developed, and distances between wind turbines on two side edges of the wind farm and a boundary of a computational domain are both 6D. The whole calculation domain is divided by structured orthogonal grids, and the actuation disc with severe physical quantity change and the nearby grids are appropriately encrypted. Wherein the encryption method is to increase the resolution of the grid, the grid after encryption may be 3 mx 3m if the grid without encryption is 6 mx 6 m. By increasing the resolution of the grid, the accuracy of wake solving is improved.
Setting an actuating disc model according to the calculation grid, namely simplifying the wind wheel into a paddle disc, assuming that the airflow static pressure at the front and the rear of the wind wheel is equal, the axial thrust borne by the wind wheel is uniformly distributed along the paddle disc, and if the incoming flow wind speed is u0Then, the axial thrust of the unit area of the wind wheel is as follows:
wherein, TaIs the axial thrust on the unit area of the wind wheel, and rho is the air density.
If the thickness of the actuation disc is Δ x, the force per unit volume experienced by the actuation disc is:
wherein S isuAxial stress per unit volume of fluid within the actuation disc is applied.
Adding the unit volume force borne by the actuating disc to a momentum equation in the RANS method, and solving by adopting a closed Navier-Stokes equation of a standard k-epsilon turbulence model to obtain the RANS model.
Referring to fig. 4, fig. 4 is a schematic diagram of a layout of a wind farm according to an embodiment of the present invention. In one embodiment, the layout of the wind farm is as shown in FIG. 4. According to the wind farm of fig. 4, three inflow conditions are simulated, and errors between the simulation results and the actual measurement results are compared. The incoming flow directions of the three incoming flow working conditions are 270 degrees, 221 degrees and 312 degrees respectively, and the wind speeds are all 8 m/s. According to the incoming flow directions of the three incoming flow conditions, the average distances of the wind generation sets formed in the incoming flow directions are calculated and obtained to be 7D, 9.4D and 10.4D respectively. Referring to fig. 5, fig. 5 is a schematic diagram of errors of simulation results and actual measurement results of the wind farm shown in fig. 4 under different working conditions according to the embodiment of the present invention. Errors of simulation results and actual measurement results of the wind power plant under three incoming flow working conditions are shown in fig. 5, along with the increase of the average distance of the wind turbine generator, the error generated by the wake simulation method based on the engineering wake model is gradually reduced, the difference with the error generated by the wake simulation method based on the RANS model is small, meanwhile, the error generated by the wake simulation method based on the RANS model is also at a relatively low level, and the feasibility of the wake mixed simulation method of the wind power plant is verified.
It should be noted that, although the foregoing embodiments describe each step in a specific sequence, those skilled in the art will understand that, in order to achieve the effect of the present invention, different steps do not necessarily need to be executed in such a sequence, and they may be executed simultaneously (in parallel) or in other sequences, and these changes are all within the protection scope of the present invention.
Further, the invention also provides a wake flow hybrid simulation system of the wind power plant.
Referring to fig. 2, fig. 2 is a main structural block diagram of a wake flow hybrid simulation system of a wind farm according to an embodiment of the present invention. As shown in fig. 2, the wake flow hybrid simulation system of the wind farm in the embodiment of the present invention mainly includes a power difference value obtaining module, a distance defining value determining module, and a simulation scheme confirming module. In this embodiment, the power difference obtaining module may be configured to obtain an actual power of a preset test wind farm under a preset inflow condition, perform wake simulation on the test wind farm by using a wake simulation method based on an engineering wake model, obtain a simulated power under the inflow condition, and obtain a difference between the actual power and the simulated power. The interval definition value determination module may be configured to determine an interval definition value of an average interval of wind turbines formed by the wind farm under the incoming flow condition in the incoming flow direction according to a comparison result of the difference value and a preset power error threshold value. The simulation scheme confirmation module can be configured to judge whether the average distance between the wind turbines formed in the incoming flow direction of the actual wind power plant under the incoming flow working condition is larger than or equal to a distance defining value or not; if so, carrying out wake flow simulation on the actual wind power plant by adopting a wake flow simulation method based on the engineering wake flow model; if not, performing wake flow simulation on the actual wind power plant by using a wake flow simulation method based on the RANS model.
In one embodiment, the preset inflow condition may include a plurality of different inflow conditions, and the interval limit value determining module may include an average interval obtaining unit and an interval limit value obtaining unit. In this embodiment, the average distance acquiring unit may be configured to acquire an absolute value of the difference value according to the difference value for each incoming flow condition, compare the absolute value with the power error threshold, and acquire the corresponding average distance when the absolute value is less than or equal to the power error threshold. The pitch limit value acquisition unit may be configured to acquire the pitch limit value according to the acquired average pitch.
In one embodiment, the interval limit value acquiring unit may include an interval average value acquiring sub-unit and an interval limit value acquiring sub-unit. In the present embodiment, the pitch average value acquiring subunit may be configured to calculate an average value of the average pitches from the acquired average pitches. The pitch limit value obtaining subunit may be configured to obtain the pitch limit value from the average value.
In one embodiment, the pitch limit value obtaining subunit may be further configured to obtain the pitch limit value according to the following steps: and acquiring a spacing defining value according to the average value and a preset wind direction compensation coefficient.
The technical principles, the solved technical problems, and the generated technical effects of the wake mixing simulation method embodiment of the wind farm shown in fig. 1 are similar, and it can be clearly understood by those skilled in the art that, for convenience and simplicity of description, the content described in the wake mixing simulation method embodiment of the wind farm may be referred to for specific working processes and related descriptions of the wake mixing simulation system of the wind farm, and details are not repeated here.
It will be understood by those skilled in the art that all or part of the flow of the method according to the above-described embodiment may be implemented by a computer program, which may be stored in a computer-readable storage medium and used to implement the steps of the above-described embodiments of the method when the computer program is executed by a processor. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying said computer program code, media, usb disk, removable hard disk, magnetic diskette, optical disk, computer memory, read-only memory, random access memory, electrical carrier wave signals, telecommunication signals, software distribution media, etc. It should be noted that the computer readable medium may contain content that is subject to appropriate increase or decrease as required by legislation and patent practice in jurisdictions, for example, in some jurisdictions, computer readable media does not include electrical carrier signals and telecommunications signals as is required by legislation and patent practice.
Furthermore, the invention also provides a control device. In an embodiment of the control device according to the invention, the control device comprises a processor and a memory device, the memory device may be configured to store a program for performing the wake mixing simulation method of the wind farm of the above-described method embodiment, and the processor may be configured to execute a program in the memory device, the program including but not limited to a program for performing the wake mixing simulation method of the wind farm of the above-described method embodiment. For convenience of explanation, only the parts related to the embodiments of the present invention are shown, and details of the specific techniques are not disclosed. The control device may be a control device apparatus formed including various electronic apparatuses.
Further, the invention also provides a computer readable storage medium. In one computer-readable storage medium embodiment according to the present invention, a computer-readable storage medium may be configured to store a program for executing the wake mixing simulation method of a wind farm of the above-described method embodiment, which may be loaded and executed by a processor to implement the wake mixing simulation method of the above-described wind farm. For convenience of explanation, only the parts related to the embodiments of the present invention are shown, and specific technical details are not disclosed. The computer readable storage medium may be a storage device formed by including various electronic devices, and optionally, the computer readable storage medium is a non-transitory computer readable storage medium in the embodiment of the present invention.
Further, it should be understood that, since the configuration of each module is only for explaining the functional units of the apparatus of the present invention, the corresponding physical devices of the modules may be the processor itself, or a part of software, a part of hardware, or a part of a combination of software and hardware in the processor. Thus, the number of individual modules in the figures is merely illustrative.
Those skilled in the art will appreciate that the various modules in the apparatus may be adaptively split or combined. Such splitting or combining of specific modules does not cause the technical solutions to deviate from the principle of the present invention, and therefore, the technical solutions after splitting or combining will fall within the protection scope of the present invention.
So far, the technical solutions of the present invention have been described in connection with the preferred embodiments shown in the drawings, but it is easily understood by those skilled in the art that the scope of the present invention is obviously not limited to these specific embodiments. Equivalent changes or substitutions of related technical features can be made by those skilled in the art without departing from the principle of the invention, and the technical scheme after the changes or substitutions can fall into the protection scope of the invention.
Claims (10)
1. A wake flow hybrid simulation method of a wind power plant is characterized by comprising the following steps:
acquiring actual power of a preset test wind power plant under a preset inflow working condition, performing wake simulation on the test wind power plant by adopting a wake simulation method based on an engineering wake model to obtain simulated power under the inflow working condition, and acquiring a difference value between the actual power and the simulated power;
determining a spacing defining value of the average spacing of the wind turbines formed by the test wind power plant in the incoming flow direction under the incoming flow working condition according to the comparison result of the difference value and a preset power error threshold value;
judging whether the average distance between the wind turbines formed in the incoming flow direction of the actual wind power plant under the incoming flow working condition is larger than or equal to the distance defining value or not;
if so, carrying out wake flow simulation on the actual wind power plant by adopting a wake flow simulation method based on an engineering wake flow model;
and if not, performing wake flow simulation on the actual wind power plant by adopting a wake flow simulation method based on the RANS model.
2. The wake mixing simulation method for a wind farm according to claim 1, wherein the preset inflow conditions include a plurality of different inflow conditions, and the step of determining a distance defining value of an average distance between wind turbines formed by the test wind farm in the inflow direction under the inflow conditions according to a comparison result of the difference value and a preset power error threshold value comprises:
acquiring an absolute value of the difference value according to the difference value aiming at each incoming flow working condition, comparing the absolute value with the power error threshold value, and acquiring a corresponding average distance when the absolute value is less than or equal to the power error threshold value;
and acquiring the spacing definition value according to the acquired average spacing.
3. The wake flow hybrid simulation method for a wind farm according to claim 2, wherein the step of obtaining the spacing defining value according to the obtained average spacing comprises:
calculating the average value of the average distance according to the obtained average distance;
and acquiring the spacing definition value according to the average value.
4. The wake mixing simulation method of a wind farm according to claim 3, characterized in that the step of obtaining the spacing defining value from the mean value comprises:
and acquiring the interval defining value according to the average value and a preset wind direction compensation coefficient.
5. A wake mix simulation system of a wind farm, the simulation system comprising:
the power difference value acquisition module is configured to acquire actual power of a preset test wind power plant under a preset incoming flow working condition, carry out wake flow simulation on the test wind power plant by adopting a wake flow simulation method based on an engineering wake flow model, acquire simulated power under the incoming flow working condition and acquire a difference value between the actual power and the simulated power;
the distance limit value determining module is configured to determine a distance limit value of an average distance between the wind turbines formed by the test wind power plant in the incoming flow direction under the incoming flow working condition according to a comparison result of the difference value and a preset power error threshold value;
the simulation scheme confirmation module is configured to judge whether the average distance between the wind turbines formed in the incoming flow direction of the actual wind power plant under the incoming flow working condition is larger than or equal to the distance limit value or not; if so, carrying out wake flow simulation on the actual wind power plant by adopting a wake flow simulation method based on an engineering wake flow model; and if not, performing wake flow simulation on the actual wind power plant by adopting a wake flow simulation method based on the RANS model.
6. The wake flow hybrid simulation system of a wind farm according to claim 5, wherein the preset inflow conditions include a plurality of different inflow conditions, and the interval definition value determination module comprises:
the average distance obtaining unit is configured to obtain an absolute value of the difference value according to the difference value and compare the absolute value with the power error threshold value for each incoming flow working condition, and when the absolute value is smaller than or equal to the power error threshold value, obtain a corresponding average distance;
an interval-defining-value acquisition unit configured to acquire the interval defining value according to the acquired average interval.
7. The wake flow hybrid simulation system of a wind farm according to claim 6, wherein the pitch limit value obtaining unit includes:
a pitch average value obtaining subunit configured to calculate an average value of the average pitches according to the obtained average pitches;
a spacing-defining-value obtaining subunit configured to obtain the spacing defining value from the average value.
8. The wake mixing simulation system of a wind farm according to claim 7, characterized in that the spacing-defining-value obtaining subunit is further configured to obtain the spacing-defining value according to the following steps:
and acquiring the interval defining value according to the average value and a preset wind direction compensation coefficient.
9. A control device comprising a processor and a memory device adapted to store a plurality of program codes, characterized in that said program codes are adapted to be loaded and run by said processor to perform a wake mixing simulation method of a wind farm according to any of claims 1 to 4.
10. A computer readable storage medium having a plurality of program codes stored therein, characterized in that said program codes are adapted to be loaded and run by a processor to perform a wake mix simulation method of a wind farm according to any of the claims 1 to 4.
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