A wind farm wake prediction method in a terrain change scene exists

Abstract

The present application provides a kind of wind farm wake prediction method with high calculation precision, good calculation benefit and can adapt to the existence topographic change scene of complex terrain.The method of the present application comprises the following steps: step a, according to the actual engineering situation, determine the evaluation period, determine the site topographic range frame selection, machine position layout and unit basic information;Step b, according to the modeling information of the frame selection area and the given boundary condition, large eddy simulation is carried out, and CFD high-precision background wind field with terrain effect is established;Step c, combined with the background wind field calculated by CFD simulation, the flow field is interpolated and reconstructed, and the wake effect of the wind farm and the total power generation of the wind farm unit are predicted by using the engineering wake model.The present application is applied to the field of wind power technology.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of wind power technology, and in particular to a wind farm wake prediction method in the presence of terrain changes. BACKGROUND

[0002] In actual wind engineering problems, the research on the wake effect of wind turbines generally directly applies existing engineering wake models. Although the engineering wake model has a relatively simple structure and short calculation time, it is suitable for numerical simulation research of wind farms with a large number of wind turbine units. However, since the theory is based on a simplified one-dimensional or two-dimensional flow field and largely depends on empirical parameters, there may be serious deviations from the actual situation in some application scenarios.

[0003] In recent years, with the improvement of computer level, if more accurate flow field simulation results are needed, such as shown in the formula (1), they can be obtained by computational fluid dynamics method (CFD). The most commonly used Reynolds average equation method (RANS) is based on the idea of Reynolds decomposition, which decomposes the physical quantities in the flow field into average and fluctuation parts, and performs time average processing on the NS equation. Although this method has low requirements for calculation conditions, it has problems such as underestimating the wake velocity and delaying the recovery of the wake when solving complex problems such as wind turbine wake. Today, some research institutions can directly numerically solve the NS equation without any form of modeling and simplification using extremely fine grids. This method is also known as direct numerical simulation method (DNS). Although this method can completely analyze the turbulence, it is difficult to be directly applied to actual engineering due to the extremely high cost of DNS method. Figure 1

[0004] Therefore, the large eddy simulation method (LES) gradually rises between the two. LES method is more accurate than Reynolds average equation method, and can be realized on a regular computer, so it is a turbulent numerical calculation method with great development potential. However, LES method has a huge requirement for the number of grids, so the research on wake using LES method is often combined with actuator disk theory, that is, instead of simulating real blades in numerical simulation, a thin circular disc with thrust is used to replace the blades. Although the results obtained by using LES method based on actuator disk for wind farm wake prediction are close to the actual situation, when predicting the wake of wind farms with terrain changes, the atmospheric boundary conditions are more complex, and if the simplified blade model is still divided into grids during the process, the calculation cost is still very high. Therefore, in order to reduce costs and increase benefits, when predicting the wake of wind farms with terrain changes, a method that takes into account the calculation accuracy and calculation efficiency needs to be considered. SUMMARY

[0005] ​The technical problem solved by the present application is to overcome the shortcomings of the prior art, and to provide a wind farm wake prediction method with high calculation accuracy, good calculation efficiency and adaptability to terrain change scenarios.

[0006] The technical solution adopted by the present application is a wind farm wake prediction method in a terrain change scenario, which comprises the following steps:

[0007] Step a, according to the actual engineering situation, determine the evaluation period, determine the site terrain range frame selection, machine position layout and unit foundation information;

[0008] Step b, according to the modeling information of the frame selection area and the given boundary conditions, large eddy simulation is carried out to establish a CFD high-precision background wind field with terrain effect;

[0009] Step c, combine the background wind field calculated by CFD simulation to reconstruct the flow field, and use the engineering wake model to predict the wake effect of the wind farm and the total power generation of the wind farm unit.

[0010] In step a, the site terrain range frame selection is performed according to the following steps:

[0011] Step a1, determine the layout of the wind turbine in the site, and ensure that the frame selection area contains all the units;

[0012] Step a2, determine the change of the main and secondary wind direction, and ensure that there is enough wake development area in the frame selection area;

[0013] Step a3, for the three-dimensional terrain geometric model, use the elevation point cloud fitting to generate, select the spatial resolution of the data set ≤30m, and ensure that the engineering calculation requirements are met;

[0014] Step a4, slope the terrain boundary to make the terrain around the same elevation;

[0015] Step a5, select the frame selection area to ensure that the length and width are close, simplify the calculation and make the grid elements more evenly distributed in space;

[0016] Step a6, divide the structured grid for the selected calculation domain, control the number of grids, and test the grid quality to ensure that the engineering calculation accuracy is met.

[0017] In step b, when performing large eddy simulation, the influence of the wind wheel model is ignored, and only a background wind field with terrain effect is simulated.

[0018] The specific steps of step b are:

[0019] Step b1, export the information and terrain elevation map of the frame selection area, construct the calculation domain, and construct the sub-grid stress model required for large eddy simulation based on the given calculation domain;

[0020] Step b2: Set the inflow boundary conditions, outflow boundary conditions, and sidewall conditions of the simulated atmospheric boundary layer, as well as the viscosity coefficient of the air. Create a grid of appropriate resolution based on the terrain complexity and the expected turbulence scale, and then perform large eddy simulation after setting the solution mode.

[0021] Step b3: When performing large eddy simulation, first perform steady-state calculations. When the residuals reach 10... -4 Then, based on this, large eddy simulation is used to perform unsteady-state calculations to simulate a stable wind field with topographic effects and atmospheric boundary layer characteristics.

[0022] Step b4: Configure the parameters of each wind turbine in the subgrid stress model, use the wind field data obtained through large eddy simulation as input conditions, and solve the problem in combination with the engineering wake model to generate wake effect diagrams of each unit in the wind farm and the power generation of the unit.

[0023] In step b3, the dynamic Smagorinsky-Lilly model is used as the subgrid stress model when performing large eddy simulation. The sidewalls and top surface of the atmospheric boundary layer are symmetrically defined, and the ground surface is defined as a non-slip wall boundary. Combined with the boundary conditions of wind speed and wind direction, a heterogeneous flow probe point is set to simulate a stable wind field with topographic effects and atmospheric boundary layer characteristics, and the wind field simulation results under the selected wind direction are obtained.

[0024] The specific steps of step c are as follows:

[0025] Step c1: Based on the CFD high-precision background wind field with terrain effect established in step b, generate a wind field terrain file, cut the wind field terrain file, the number of cutting steps is the time step of the large eddy simulation calculation, and generate a vtk file of the instantaneous wind field at each step.

[0026] Step c2: Convert the transient wind field data into steady-state data;

[0027] Step c3: Configure wind turbine parameters and set initial solution conditions for the engineering wake model;

[0028] Step c4: Based on the engineering wake model, use the solver to calculate the wake velocity field and the total power of the unit under the condition of heterogeneous inflow.

[0029] The specific steps of step c3 are as follows: configure the wind turbine location information, the solver type is wind turbine mesh, the number of mesh points is 3, set the initial atmospheric conditions of atmospheric density, turbulence intensity, wind speed and wind direction, the wake combination model is Sosfs model, the wake deflection model and velocity deficit model are Gauss model, and the wake turbulence model is Crespo-hernandez model.

[0030] In step c4, the engineering wake model is selected from the Gaussian rotating mixed wake model, and the velocity deficit of the wake is set to follow a Gaussian distribution. The flow velocity u in the flow field after passing through the turbine is... G The parsing expression is as follows:

[0031]

[0032] Where C is the velocity deficit at the wake center, U ∞ δ is the free flow velocity, δ is the wake deflection, δ y It is the wake deflection in the y-direction, δ z This refers to the wake deflection in the z-direction, where y0 is the spanwise position of the wind turbine, y is the calculated component of the wind turbine hub in the y-direction, and z is the calculated component of the wind turbine hub in the z-direction. h It is the hub height of the wind turbine, σ y σ z The wake widths are defined as σ in the y and z directions, respectively. y0 σ z0 These refer to the initial values ​​at the start of the far wake, which depend on the intensity of environmental turbulence and the thrust coefficient C. T This formula accurately describes the spatial distribution of velocity decrease within the wake region.

[0033] The beneficial effects of this invention are as follows: First, the information and terrain elevation map of the selected region are exported to construct a computational domain. Based on the obtained computational domain, a subgrid stress model required for large eddy simulation is constructed. The dynamic Smagorinsky-Lilly model is selected, which has better adaptability than the traditional Smagorinsky model and can automatically adjust the Smagorinsky constant under different flow conditions, better capturing the turbulent characteristics near the wall, thereby improving prediction accuracy. The inflow boundary conditions, outflow boundary conditions, and sidewall conditions of the simulated atmospheric boundary layer, as well as the physical properties such as the air viscosity coefficient, are set. A grid of appropriate resolution is created according to the terrain complexity and the expected turbulence scale. After setting the solution mode, large eddy simulation is performed. To accelerate the convergence speed, steady-state calculations can be performed first. When the residual reaches 10... -4Based on this, large eddy simulation (LES) is then used for unsteady-state calculations to simulate stable wind fields with topographic effects and atmospheric boundary layer characteristics. Parameters such as the position coordinates of each wind turbine in the model are configured, and the wind field data obtained through LES is used as input. The solution is then obtained by combining the engineering wake model to generate wake effect diagrams for each turbine in the wind farm and calculate the turbine's power output. This invention utilizes LES to simulate only the background wind field with topographic effects, and combines it with the engineering wake model to calculate the wind turbine wake, making wake prediction for wind farms with topographic variations more efficient, significantly reducing computational costs while maintaining computational accuracy. Simultaneously, the engineering wake model adopts a Gaussian rotating mixed wake model. Compared to the common Gaussian wake model, the Gaussian rotating mixed wake model (GCH) additionally considers the "secondary deflection of the wake" effect in the superimposed wake. This improvement makes the calculated wake of the wind farm closer to reality, enhancing simulation accuracy. Attached Figure Description

[0034] Figure 1 A flowchart of existing wind farm wake prediction methods;

[0035] Figure 2 This is a flowchart of the method of the present invention;

[0036] Figure 3 A flowchart for high-precision fluid simulation combined with an engineering wake model to predict wakes, provided as an embodiment of the present invention;

[0037] Figure 4 This is a schematic diagram of the wake of each unit in a wind farm provided in an embodiment of the present invention, wherein x, y, and z are three components of a three-dimensional spatial coordinate system, and T1, T2, T3, T4, and T99 are the serial numbers of the wind turbine units. Detailed Implementation

[0038] In this invention, all processes, including modeling and simulation calculations, are implemented on a computer. When predicting the wake effect of wind farms with topographical variations, this invention separates the handling of atmospheric boundary conditions and wind turbine modeling into two modules. Specifically, a high-precision background wind field with only topographical effects is established using large eddy simulation, and this field is then used as input conditions in conjunction with an engineering wake model to achieve wake prediction.

[0039] like Figures 2 to 4 As shown, a method for predicting the wake of a wind farm in a scenario with terrain changes is proposed. The method includes the following steps:

[0040] Step a: Based on the actual engineering situation, determine the assessment time period, and determine the site topographic area selection, turbine layout, and unit foundation information. In step a, the site topographic area selection is carried out according to the following steps:

[0041] Step a1: Determine the wind turbine layout within the site, ensuring that the selected area includes all units. Use GIS to determine the coordinates of the units within the site and extract the latitude and longitude of each unit.

[0042] Step a2: Based on the average wind rose diagram of the local meteorological station at the site, determine the changes in primary and secondary wind directions to ensure that sufficient wake development area is left within the selected area;

[0043] Step a3: For the three-dimensional terrain geometry model, use elevation point cloud fitting to generate the model. Select a dataset with a spatial resolution ≤30m to ensure that it meets the requirements of engineering calculations.

[0044] Step a4: For complex terrain, if "artificial cliffs" are created due to terrain interception and the boundary conditions cannot be determined, the terrain boundary is sloped to make the terrain all around the same elevation.

[0045] Step a5: Select the bounding box area, ensuring that the length and width are close to each other, simplifying the calculation and making the grid cells more evenly distributed in space; Combine the bounding box area after the slope treatment, considering the calculation complexity, try to make the grid cells more evenly distributed in space, and the final bounding box area is a square area. The value of the calculation domain height must be greater than 6 times the maximum terrain elevation difference.

[0046] Step a6: Divide the selected computational domain into a structured mesh, refine the mesh in the area where the wind turbine is located, control the number of meshes, and check the mesh quality based on skewness, twist rate, and overall quality to ensure that the accuracy of engineering calculations is met.

[0047] Step b: Perform large eddy simulation (LES) based on the modeling information of the selected region and the given boundary conditions to establish a high-precision CFD background wind field with topographic effects. During the LES, the influence of the wind turbine model is ignored; only a background wind field with topographic effects is simulated. The specific steps of this step are as follows:

[0048] Step b1: Export the information and terrain elevation map of the selected area, construct the computational domain, and construct the subgrid stress model required for large eddy simulation based on the given computational domain.

[0049] Step b2: Set the inflow boundary conditions, outflow boundary conditions, and sidewall conditions of the simulated atmospheric boundary layer, as well as the viscosity coefficient of the air. Create a grid of appropriate resolution based on the terrain complexity and the expected turbulence scale, and then perform large eddy simulation after setting the solution mode.

[0050] Step b3: When performing large eddy simulation, first perform steady-state calculations. When the residuals reach 10... -4 Then, based on this, large eddy simulation is used to perform unsteady-state calculations to simulate a stable wind field with topographic effects and atmospheric boundary layer characteristics.

[0051] Step b4: Configure the parameters of each wind turbine in the subgrid stress model, use the wind field data obtained through large eddy simulation as input conditions, and solve the problem in combination with the engineering wake model to generate wake effect diagrams of each unit in the wind farm and the power generation of the unit.

[0052] To separate the physical quantities of the flow into solvable scale quantity x and unsolvable scale quantity x', a box filter is chosen, and its filtering function is:

[0053]

[0054] Here, Δ represents the average grid scale; in three dimensions, Δ = (Δ1Δ2Δ3). 1 / 3 Δ1, Δ2, and Δ3 represent the grid scales in the x1, x2, and x3 directions, respectively. When Δ→0, the Large Eddy Simulation (LES) transforms into the Direct Numerical Simulation (DNS). In step b3, subgrid stress is the momentum transport between filtered-out small-scale fluctuations and solvable large-scale fluctuations. A dynamic Smagorinsky-Lilly model is adopted as the subgrid stress model. The dynamic Smagorinsky-Lilly model can overcome the shortcomings of the Smagorinsky-Lilly model, such as excessive dissipation, suppression of transition, and even laminarization of the flow. To meet engineering requirements, the calculation step size of the Large Eddy Simulation is Δt = Δ0 / U. max U max The required free-flow velocity is 1.5 to several times that of the free-flow velocity, and this requirement can be further relaxed in stagnant water areas. The sidewalls and top surface of the atmospheric boundary layer are simulated using symmetrical boundaries, while the ground surface uses a no-slip wall boundary. Combined with boundary conditions such as wind speed and direction, heterogeneous flow probe points are set to simulate a stable wind field with topographic effects and atmospheric boundary layer characteristics, obtaining simulation results for the wind field under the selected wind direction.

[0055] Step c: Reconstruct the flow field by interpolating the background wind field calculated using CFD simulation, and predict the wake effect of the wind farm and the total power generation of the wind farm units using the engineering wake model. The specific steps of this step are as follows:

[0056] Step c1: Based on the CFD high-precision background wind field with terrain effect established in step b, generate a wind field terrain file, cut the wind field terrain file, the number of cutting steps is the time step of the large eddy simulation calculation, and generate a vtk file of the instantaneous wind field at each step.

[0057] Step c2: Convert the transient wind field data into steady-state data;

[0058] Step c3: Configure wind turbine parameters and set initial solution conditions for the engineering wake model;

[0059] Step c4: Based on the engineering wake model, use the solver to calculate the wake velocity field and the total power of the unit under the condition of heterogeneous inflow.

[0060] The specific steps of step c3 are as follows: configure the wind turbine location information, the solver type is wind turbine mesh, the number of mesh points is 3, set the initial atmospheric conditions of atmospheric density, turbulence intensity, wind speed and wind direction, the wake combination model is Sosfs model, the wake deflection model and velocity deficit model are Gauss model, and the wake turbulence model is Crespo-hernandez model.

[0061] In step c4, the engineering wake model is selected from the Gaussian rotating mixture wake model (GCH), and the velocity deficit of the wake is set to follow a Gaussian distribution. The flow velocity u in the flow field after passing through the turbine is... G The parsing expression is as follows:

[0062]

[0063] Where C is the velocity deficit at the wake center, U ∞ δ is the free flow velocity, δ is the wake deflection, δ y It is the wake deflection in the y-direction, δ z This refers to the wake deflection in the z-direction, where y0 is the spanwise position of the wind turbine, y is the calculated component of the wind turbine hub in the y-direction, and z is the calculated component of the wind turbine hub in the z-direction. h It is the hub height of the wind turbine, σ y σ z The wake widths are defined as σ in the y and z directions, respectively. y0 σ z0 These refer to the initial values ​​at the start of the far wake, which depend on the intensity of environmental turbulence and the thrust coefficient C. T This formula accurately describes the spatial distribution of velocity decrease within the wake region.

[0064] This invention aims to solve the problem of wake prediction for wind farms with topographical variations. It utilizes Large Eddy Simulation (LES) to obtain a CFD background wind field with only topographical effects, and combines this with an engineering wake model to predict the wake effect of the wind farm. This method balances computational accuracy and efficiency. This invention can promote the application of CFD numerical simulation technology in practical engineering and is a relatively efficient method for wind farm wake prediction in real-world engineering applications. The method uses a high-precision background wind field to replace the homogeneous wind field, which can significantly improve the accuracy of wind farm wake prediction and reasonably reflect the overlapping effects of wakes from each wind turbine under topographical conditions. It overcomes the limitations of traditional engineering wake models while avoiding the excessive computational resources required for simulating wind farm wakes with topographical variations using traditional CFD methods, thus balancing computational accuracy and efficiency.

[0065] Finally, it should be emphasized that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention can have various changes and modifications. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for predicting the wake of a wind farm in a scenario with terrain changes, characterized in that, The method includes the following steps: Step a: Based on the actual engineering situation, determine the assessment time period, the site topography area selection, the turbine layout, and the basic information of the unit; Step b: Perform large eddy simulation based on the modeling information of the selected area and the given boundary conditions to establish a high-precision CFD background wind field with topographic effects. Step c: Combine the background wind field calculated by CFD simulation, interpolate and reconstruct the flow field, and use the engineering wake model to predict the wake effect of the wind farm and the total power generation of the wind farm units. In step b, when performing large eddy simulation, the influence of the wind turbine model is ignored, and only a background wind field with topographic effects is simulated; the specific steps of step b are as follows: Step b1: Export the information and terrain elevation map of the selected area, construct the computational domain, and construct the subgrid stress model required for large eddy simulation based on the given computational domain. Step b2: Set the inflow boundary conditions, outflow boundary conditions, and sidewall conditions of the simulated atmospheric boundary layer, as well as the viscosity coefficient of the air. Create a grid with an appropriate resolution based on the terrain complexity and the expected turbulence scale. After setting the solution mode, perform large eddy simulation. Step b3: When performing large eddy simulation, first perform steady-state calculations. When the residuals reach 10... -4 Then, based on this, large eddy simulation is used to perform unsteady-state calculations to simulate a stable wind field with topographic effects and atmospheric boundary layer characteristics. Step b4: Configure the parameters of each wind turbine in the subgrid stress model, use the wind field data obtained through large eddy simulation as input conditions, and solve the problem in combination with the engineering wake model to generate wake effect diagrams of each unit in the wind farm and the power generation of the unit.

2. The method for predicting the wake of a wind farm in a scenario with terrain changes according to claim 1, characterized in that, In step a, the site topographic area selection is performed according to the following steps: Step a1: Determine the wind turbine layout within the site, ensuring that the selected area includes all units; Step a2: Determine the changes in primary and secondary wind directions, and ensure that sufficient wake development area is left within the selected area; Step a3: For the three-dimensional terrain geometry model, use elevation point cloud fitting to generate the model. Select a dataset with a spatial resolution ≤30m to ensure that it meets the requirements of engineering calculations. Step a4: Slope the terrain boundary to make the terrain all around the same elevation; Step a5: Select the bounding box area, ensuring that the length and width are similar, which simplifies the calculation and makes the grid cells more evenly distributed in space; Step a6: Divide the selected computational domain into a structured mesh, control the number of meshes, check the mesh quality, and ensure that the accuracy required for engineering calculations is met.

3. The method for predicting the wake of a wind farm in a scenario with terrain changes according to claim 1, characterized in that, In step b3, the dynamic Smagorinsky-Lilly model is used as the subgrid stress model when performing large eddy simulation. The sidewalls and top surface of the atmospheric boundary layer are symmetrically defined, and the ground surface is defined as a non-slip wall boundary. Combined with the boundary conditions of wind speed and wind direction, a heterogeneous flow probe point is set to simulate a stable wind field with topographic effects and atmospheric boundary layer characteristics, and the wind field simulation results under the selected wind direction are obtained.

4. The method for predicting the wake of a wind farm in a scenario with terrain changes according to claim 1, characterized in that, The specific steps of step c are as follows: Step c1: Based on the CFD high-precision background wind field with terrain effect established in step b, generate a wind field terrain file, cut the wind field terrain file, the number of cutting steps is the time step of the large eddy simulation calculation, and generate a vtk file of the instantaneous wind field at each step. Step c2: Convert the transient wind field data into steady-state data; Step c3: Configure wind turbine parameters and set initial solution conditions for the engineering wake model; Step c4: Based on the engineering wake model, use the solver to calculate the wake velocity field and the total power of the unit under the condition of heterogeneous inflow.

5. The method for predicting the wake of a wind farm in a scenario with terrain changes according to claim 4, characterized in that, The specific steps of step c3 are as follows: configure the wind turbine location information, the solver type is wind turbine mesh, the number of mesh points is 3, set the initial atmospheric conditions of atmospheric density, turbulence intensity, wind speed and wind direction, the wake combination model is Sosfs model, the wake deflection model and velocity deficit model are Gauss model, and the wake turbulence model is Crespo-hernandez model.

6. The method for predicting the wake of a wind farm in a scenario with terrain changes according to claim 4, characterized in that, In step c4, the engineering wake model is selected from the Gaussian rotating mixed wake model, and the velocity deficit of the wake is set to follow a Gaussian distribution. The flow velocity in the flow field after passing through the turbine is... u G The parsing expression is as follows: in, C It is the velocity deficit at the wake center. U ∞ It is the free flow velocity. δ It's wake deflection. δ y Is y Wake deflection in direction, δ z Is z Wake deflection in direction, y 0 represents the spanwise position of the wind turbine. y It is the wind turbine hub. y Calculated components in the direction, z It is the wind turbine hub. z Calculated components in the direction, z h It refers to the hub height of the wind turbine. σ y , σ z Defined respectively y direction and z Wake width in the direction, σ y0 , σ z0 These refer to the initial values ​​at the start of the far wake, which depend on the intensity of environmental turbulence and the thrust coefficient. C T The formula accurately describes the spatial distribution of velocity decrease within the wake region.

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