Wave energy device intervention post-marine area wave height prediction method and related device

Abstract

The application discloses a wave energy device intervention post-sea area wave surface height prediction method and related device, relates to the marine energy utilization field, and comprises the following steps: based on the wave energy device main body size, establishing a numerical tank and setting boundary conditions and other parameters, comparing and analyzing an ideal wave numerical tank with a theoretical wave sine curve, obtaining an ideal wave numerical tank numerical model after verification, importing the wave energy device after modeling, setting a dynamic region, a static region and a boundary layer grid, calculating the conversion efficiency of the wave energy device, comparing the conversion efficiency of the device obtained through experiments, until the relative error range is met, based on the wave tank numerical model containing the device after the final verification, obtaining wave surface average change data within a period, adopting a fitting method to determine a wave surface height distribution function variable factor, obtaining a wave surface change function before and after the device, and then the wave surface height before and after the device can be quickly obtained. The application can quickly calculate the wave height change of the surrounding sea area after the wave energy device is arranged.

Description

TECHNICAL FIELD

[0001] The application relates to the technical field of ocean energy utilization, in particular to a method for predicting wave height in a sea area after intervention of a wave energy device and a related device. BACKGROUND

[0002] After the wave energy device is intervened in the sea area, the energy in the sea area is extracted, and the original wave power propagation process is changed. The wave height is lifted in front of the device, and attenuation occurs behind the device, that is, the "tail wave" phenomenon occurs, and the input energy of the rear device changes. With large-scale deployment of wave energy devices in the sea area, the overall wave field of the sea area changes compared to the original state, which will sharply affect the overall wave energy resource distribution. However, the existing wave energy resource evaluation methods do not consider the changes in the wave field caused by the large-scale deployment of wave energy devices, and the changes in resources caused by the changes in the wave surface are not considered. At the same time, since the wave surface propagation is always changing with the period, how to establish a model to convert the instantaneous changes at each time into a unified average change is also a challenge. If the traditional numerical simulation method is used, complete modeling of all devices is required, which not only consumes a large amount of computing resources, but also takes too long to calculate, making it difficult to obtain the wave field height changes in time, and unable to quickly obtain the changes in the overall wave energy resources, and also limiting the rapid optimization ability of the device array arrangement.

[0003] In summary, there is an urgent need to develop a method for predicting the wave surface and the tail wave surface after the wave energy device is intervened in the sea area. SUMMARY

[0004] The purpose of the present application is to provide a method for predicting the wave height in the sea area after intervention of a wave energy device, which can quickly calculate the wave height changes around the wave energy device.

[0005] To achieve the above-mentioned purpose, the present application provides the following solutions.

[0006] In a first aspect, the present application provides a method for predicting the wave height in the sea area after intervention of a wave energy device, which comprises the following steps.

[0007] Based on the main size of the wave energy device, a numerical tank is established and boundary conditions and numerical tank parameters are set to obtain an ideal wave numerical tank.

[0008] The ideal wave numerical tank is compared and analyzed with a theoretical wave sine curve to obtain a verified ideal wave tank numerical model.

[0009] After modeling the wave energy device, the ideal wave pool numerical model is imported, the dynamic domain, static domain and boundary layer grid are set, the conversion efficiency of the wave energy device is calculated, and the conversion efficiency of the device obtained by the test is compared until the relative error range is met, and the final verified wave pool numerical model containing the device is obtained.

[0010] Based on the final verified wave pool numerical model containing the device, a period is divided into several equidistant time points, the wave surface change position at each time point is counted and averaged, and the average change data of the wave surface in front of the device and the wave surface behind the device in a period is obtained.

[0011] Based on the average change data of the wave surface in front of the device and the wave surface behind the device in a period, the least square fitting method is used to determine the wave surface height distribution function variable factor, that is, the wave height distribution function in front of the device based on the natural exponential type and the tail wave height distribution function behind the device based on the oscillation attenuation are obtained.

[0012] Based on the wave height distribution function in front of the device based on the natural exponential type and the tail wave height distribution function behind the device based on the oscillation attenuation, the wave surface height in front of and behind the wave energy device is calculated.

[0013] In a second aspect, the present application provides a computer device, comprising: a memory, a processor, and a computer program stored on the memory and capable of running on the processor, and the processor executes the computer program to realize the wave energy device intervention sea area wave surface height prediction method of the first aspect.

[0014] In a third aspect, the present application provides a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to realize the wave energy device intervention sea area wave surface height prediction method of the first aspect.

[0015] According to the specific embodiments provided by the present application, the following technical effects are disclosed.

[0016] The present application provides a wave energy device intervention sea area wave surface height prediction method and related device, which comprises: based on the main size of the wave energy device, a numerical wave pool is established, boundary conditions and numerical wave pool parameters are set, an ideal wave numerical wave pool is obtained, and the initial conditions are matched with the water flow in and out, boundary constraints and other conditions in the actual wave environment.

[0017] The ideal wave numerical tank is compared with the theoretical wave sine curve, and the verified ideal wave tank numerical model is obtained. Through this comparison, it can be effectively tested whether the previously set numerical tank parameters and boundary condition settings are reasonable. If the two are highly consistent, it means that the ideal wave numerical tank is reliable, and then the verified ideal wave tank numerical model is obtained, ensuring the accuracy of the subsequent simulation of wave energy device conversion efficiency and wave surface changes.

[0018] After modeling the wave energy device and importing it into the ideal wave tank numerical model, the dynamic domain, static domain, and boundary layer grid are set, and the wave energy device conversion efficiency is calculated. The device conversion efficiency obtained by the test is compared until the relative error range is met, and the final verified wave tank numerical model containing the device is obtained. This can distinguish different properties in the simulation, accurately simulate the motion state of the wave energy device under the action of waves in the dynamic domain, and simulate the normal wave propagation without interference from the device motion in the static domain, providing a reasonable and effective model basis for further analysis of the interaction between the wave energy device and the wave. By continuously optimizing the grid settings and boundary conditions of these key areas until the preset conversion efficiency or the relative error range is met, the model can more accurately simulate the interaction between the wave energy device and the wave, providing a reliable model basis for subsequent prediction of wave height.

[0019] Based on the final verified wave tank numerical model containing the device, a period is divided into several equidistant time points, the wave surface change position at each time point is counted and averaged, and the average change data of the wave surface in front of and behind the device in a period is obtained. This approach can effectively eliminate the randomness and contingency of wave surface changes at a single time point, and obtain a more representative result that reflects the overall trend of wave surface changes, providing a stable and reliable data basis for subsequent fitting of wave surface change functions.

[0020] Based on the average change data of the wave surface in front of and behind the device in a period, the least square fitting method is used to determine the wave height distribution function variable factor, i.e., the wave height distribution function in front of the device based on the natural exponential type and the tail wave height distribution function behind the device based on the oscillation decay are obtained. The function can succinctly and accurately describe the change law of the wave surface with time and space in the form of mathematical expression, and convert the complex process of wave surface changes into an analyzable and calculable mathematical model, providing a mathematical tool for calculating the wave height in front of and behind the wave energy device, and greatly improving the accuracy and efficiency of predicting the wave height.

[0021] Based on the natural exponential-based wave height distribution function before the device and the oscillation attenuation-based tail wave height distribution function after the device, the wave surface height before and after the wave energy device is calculated. These specific wave surface height data intuitively and accurately reflect the actual state of the wave surface after the wave energy device is intervened, and the precise prediction of the wave surface height after the wave energy device is intervened is realized, thereby providing strong data support for accurate assessment of wave energy resources and optimization of wave energy device array.

[0022] In summary, the method provides important support and guarantee for wave energy resource assessment and array optimization research. By accurately predicting the wave surface height after the wave energy device is intervened, the prediction accuracy of wave energy resources and power generation can be improved, providing strong support for wave energy device array optimization and development and utilization, and helping wave energy to become a more reliable clean energy. At the same time, it can help designers fully consider the influence of waves when designing wave energy devices, optimize structural design, and improve the reliability and safety of wave energy devices. BRIEF DESCRIPTION OF DRAWINGS

[0023] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed in the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0024] Figure 1 The flowchart of a wave surface height prediction method after a wave energy device is intervened according to an embodiment of the present application is shown.

[0025] Figure 2 The overall framework diagram of a wave surface height prediction method after a wave energy device is intervened according to an embodiment of the present application is shown.

[0026] Figure 3 The flowchart of a least squares fitting method according to an embodiment of the present application is shown.

[0027] Figure 4 The structure diagram of a wave energy device according to an embodiment of the present application is shown.

[0028] Figure 5 The ideal wave numerical tank diagram according to an embodiment of the present application is shown.

[0029] Figure 6 The diagram for comparison between the extracted wave surface position and the theoretical wave sine curve according to an embodiment of the present application is shown.

[0030] Figure 7 The overall diagram of numerical tank grid division according to an embodiment of the present application is shown.

[0031] Figure 8 A numerical pool initial position diagram provided by an embodiment of the present application.

[0032] Figure 9 A boundary layer setting diagram provided by an embodiment of the present application.

[0033] Figure 10 A power conversion efficiency verification result diagram provided by an embodiment of the present application.

[0034] Figure 11 A wave surface diagram of an initial state provided by an embodiment of the present application.

[0035] Figure 12 A T / 2 moment simulation curve and a theoretical wave height comparison diagram provided by an embodiment of the present application.

[0036] Figure 13 A T / 2 moment wave surface relative change diagram in front of the device provided by an embodiment of the present application.

[0037] Figure 14 A T / 2 moment wave surface relative change diagram behind the device provided by an embodiment of the present application.

[0038] Figure 15 A wave surface change diagram in front of the device after period averaging provided by an embodiment of the present application.

[0039] Figure 16 A wave surface change diagram behind the device after period averaging provided by an embodiment of the present application.

[0040] Figure 17 A wave surface distribution function diagram in front of the device provided by an embodiment of the present application.

[0041] Figure 18 A wave surface distribution function diagram behind the device provided by an embodiment of the present application.

[0042] Figure 19 A structure diagram of a computer device provided by an embodiment of the present application. DETAILED DESCRIPTION

[0043] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative work fall within the protection scope of the present application.

[0044] The application can quickly and accurately predict the wave height change and influence range of the wave field after the single wave device is intervened, thereby achieving the rapid prediction of the wave field change after the wave energy device is arranged in a large scale, improving the accuracy of wave energy resource assessment and total power generation calculation of the wave energy array field, supporting the optimization of wave energy device arrangement array, and reasonably arranging to improve the total power generation.

[0045] In order to make the above-mentioned purposes, features and advantages of the application more obvious and easy to understand, the application will be further described in detail below in combination with the drawings and specific embodiments.

[0046] In one exemplary embodiment, as shown in Figure 1 and Figure 2 , a wave energy device intervention sea area wave height prediction method is provided, which comprises the following steps.

[0047] S1: Based on the main size of the wave energy device, a numerical tank is established and boundary conditions and numerical tank parameters are set to obtain an ideal wave numerical tank; the main size includes height, length and width; the boundary conditions are that the left side of the tank is defined as an inlet Inlet, which is set as a velocity inlet (Velocity Inlet), the upper and lower sides are defined as Up and Down respectively, which are set as velocity inlets (Velocity Inlet) and no-slip walls (No slip Wall) respectively, and the right side outlet Outlet is defined as a pressure outlet (Pressure Outlet); the numerical tank parameters include turbulence model, multiphase flow, wave, gravity effect and time solving method; the ideal wave numerical tank is a tank established based on a Cartesian coordinate system.

[0048] S2: Comparing the ideal wave numerical tank with the theoretical wave sine curve, an ideal wave tank numerical model after verification is obtained.

[0049] S3: After modeling the wave energy device, it is introduced into the ideal wave tank numerical model, the dynamic domain, static domain and boundary layer grid are set, the wave energy device conversion efficiency is calculated, compared with the device conversion efficiency obtained by experiment, until the relative error range is met, and the final verified wave tank numerical model containing the device is obtained.

[0050] S4: Based on the final verified wave tank numerical model containing the device, a period is divided into several equidistant time points, the wave surface change position at each time point is counted and averaged to obtain the average change data of the wave surface before and after the device in a period.

[0051] S5: Based on the average change data of the wave surface in front of the device and the wave surface behind the device in one period, the least square fitting method is used to determine the variable factor of the wave height distribution function, that is, the natural exponential type based on the wave height distribution function in front of the device and the oscillation attenuation based on the tail wave height distribution function behind the device.

[0052] S6: Based on the natural exponential type based on the wave height distribution function in front of the device and the oscillation attenuation based on the tail wave height distribution function behind the device, the wave height in front of and behind the wave energy device is calculated.

[0053] Implementing the above steps S1 to S6, based on the numerical simulation method, by constructing an ideal wave numerical tank, reasonably setting the boundary conditions and numerical tank parameters, modeling the wave energy device in the ideal wave numerical tank, verifying with the regular theoretical wave surface, and comparing with the regular theoretical wave surface change, the wave height change around the wave energy device can be quickly calculated.

[0054] The overall scheme of the present application is as follows.

[0055] I. First, an ideal wave tank is established.

[0056] First, the size of the wave energy device to be modeled is obtained, mainly the height, length and width. An ideal wave numerical tank matching the device is established in the numerical model, and the tank is established based on the Cartesian coordinate system. The positive direction of the vertical direction Z points downward, X the positive direction points to the right, Y the direction should follow the right-hand rule.

[0057] Set reasonable boundary conditions, the left side of the tank is defined as Inlet, set as velocity inlet, the top and bottom are defined as Up and Down, respectively, set as velocity inlet and no-slip wall, and the right side outlet Outlet is defined as pressure outlet.

[0058] Use hexahedral structured grid to establish an ideal wave numerical tank without device, and encrypt the grid at the water-air interface. The turbulent flow model of the wave numerical tank adopts Reynolds time-averaged turbulent flow model, and the multi-phase flow adopts VOF multi-phase flow setting. For other specific settings, refer to Table 1.

[0059] Table 1 Numerical tank parameters and setting types

[0060]

[0061] The Reynolds time-averaged turbulent flow model can select k-e or SST k-w model, the wave uses Fifth Order VOF wave, and the simulated wave height and wave period are set at the same time.

[0062] II. Verify the numerical wave tank simulation effect.

[0063] The simulated wave tank is compared with the theoretical wave sine curve to verify the model, and then the ideal wave tank numerical model after verification is obtained.

[0064] III. Model the wave energy device.

[0065] The wave energy device is modeled in three-dimensional modeling software, and the model is appropriately simplified to retain the main part of the energy harvesting structure. The moment of inertia, mass, center of gravity, and other parameters are obtained. The device is imported into the numerical model, and the grid is encrypted at the water-air interface. At the same time, the boundary layer encryption method is used at the edge of the device to perform grid encryption.

[0066] IV. Verify the numerical model.

[0067] The wave energy device is set as a 6-degree-of-freedom (6DOF) motion model, and the moment of inertia, center of gravity, and other parameters of the wave energy device are set. The calculation domain is divided into static and dynamic domains. The numerical model is verified by calculating the conversion efficiency of the wave energy device.

[0068] V. Wave surface change analysis.

[0069] After the numerical model is verified, the liquid surface change caused by the wave energy device is analyzed. The theoretical height generated by the theoretical wave surface sine function is compared with the wave surface after the device is involved, and the period is divided into M equidistant time points. The change of the wave surface at each time point is calculated, and the average change is calculated. According to this, the period-averaged wave surface height change can be obtained.

[0070] VI. Fit the wave surface height change function.

[0071] The wave surface change is divided into two parts before and after the device, and the least squares method is used for fitting to obtain the wave height distribution function before and after the device. According to this, the wave surface change before and after the device can be quickly calculated.

[0072] As an optional implementation, in step S1, the ideal wave numerical tank size is determined. First, the height and length of the wave energy device to be modeled are obtained. An ideal wave numerical tank is established, and the overall height of the tank is at least 5 times the height of the device, and the width is at least 5 times the width of the device.

[0073] .

[0074] .

[0075] wherein, height of the ideal wave numerical tank; width of the ideal wave numerical tank; height of the wave energy device; width of the wave energy device.

[0076] In terms of length, the overall length is at least 31 times the length of the device: at least 10 times the length in front of the device and at least 20 times the length behind the device.

[0077] .

[0078] .

[0079] .

[0080] wherein, length of the ideal wave numerical tank; length in front of the wave energy device; length behind the wave energy device; length of the wave energy device.

[0081] According to the above dimensions, an ideal wave numerical tank is established. First, the coordinate system is based on the Cartesian coordinate system, and the vertical direction Z is in the positive direction, pointing downward, X the positive direction points to the right, Y the direction should follow the right-hand rule. X = 0 is set as the origin of the wave energy device to be placed.

[0082] Boundary conditions are set, the left side of the tank is defined as Inlet, which is set as a velocity inlet, the top and bottom are defined as Up and Down, respectively, which are set as velocity inlets and no-slip walls, respectively, and the right side outlet Outlet is defined as a pressure outlet, as shown in Table 2.

[0083] Table 2 Boundary and setting type

[0084]

[0085] The numerical model (ideal wave numerical tank) is meshed using hexahedral structured mesh, and the overall mesh size should be selected as 0.1 times the smaller value of the device height or length. First, determine which one is smaller, the height or the length, and the overall mesh size of the tank should be based on: 0.1 times the smaller value.

[0086] .

[0087] .

[0088] wherein, is the smaller value between the height and length of the wave energy device; is the overall grid size of the ideal wave numerical tank.

[0089] and the water-air interface is encrypted, the minimum grid size is shown as follows.

[0090] .

[0091] wherein, is the minimum grid size of the ideal wave numerical tank.

[0092] The numerical model is set for the turbulence model, multiphase flow, wave and time solving method, as shown in Table 1; the turbulence model selects the Reynolds time-averaged turbulence model, the multiphase flow adopts the VOF multiphase flow model, the wave adopts the fifth-order wave model, the gravity effect is considered, and the time calculation format selects the implicit unsteady calculation format.

[0093] The wave model is set to Fifth Order VOF Wave, and the specific theory of the wave model can be referred to the paper“A Fifth-Order Stokes Theory For Steady Waves”by Fenton J D, Journal of Waterway Port Coastal and Ocean Engineering, 1985, 111(2): 216-234; which will not be repeated here.

[0094] The Reynolds time-averaged turbulence model can select k-e model, k-w model, or SST k-w model, and in terms of waterline, at least 3.5 height is the reference position of the water-air interface (waterline).

[0095] The wave height of the regular wave is set to H=0.2 , the wave period is T, and the minimum calculation time step is set to T / 1000; after the model is calculated for 10T, it is considered that the model is stable. The wave surface position at =0 is extracted after 10T, and the wave surface fluctuation is continuously extracted for 5T time. The waterline position is set to x , the amplitude A=0.5 H; the position of the liquid surface at a certain moment is , then the relative change of the liquid surface is obtained by subtracting the reference waterline position from the lifting of the water surface and dividing by the amplitude; that is, , the change range is [-1, 1].

[0096] ​As an optional implementation, in step S2, the ideal wave numerical tank is compared with the theoretical wave sine curve, and the ideal wave tank numerical model after verification is obtained, specifically including the following steps.

[0097] S21: set the wave height, wave period and minimum calculation time step of the regular wave.

[0098] S22: extract the wave surface position at =0 after the preset wave period x , continuously extract several wave periods, and carry out dimensionless processing on the wave surface fluctuation.

[0099] S23: compare the extracted wave surface position with the theoretical wave sine curve, and obtain the difference between the theoretical value and the actual value.

[0100] S24: judge whether the difference exceeds the preset threshold.

[0101] S25: if yes, the ideal wave numerical tank fails the verification, and the numerical tank parameters are reset.

[0102] S26: if no, the ideal wave numerical tank passes the verification, and the ideal wave tank numerical model after verification is obtained.

[0103] In step S2, the extracted wave surface position is compared with the theoretical sine value, and the difference between the theoretical value and the actual value can be obtained; the theoretical sine value can be generated according to the following formula.

[0104] .

[0105] wherein, A is the amplitude, m; is the angular frequency, rad / s; ; is the initial phase offset, rad; t is the time, s; T is the wave period of the current working condition.

[0106] According to the comparison result, the model boundary condition and the like can be adjusted to obtain the numerical tank (ideal wave tank numerical model after verification) best matching the theoretical value.

[0107] As an optional implementation, in step S3, wave energy device three-dimensional modeling simplification is performed, Solidworks or other three-dimensional modeling software is used to appropriately simplify the wave energy device, the main structure is retained, and the moment of inertia, mass, center of gravity and other parameters of the device are obtained.

[0108] The simplified model is imported into the ideal wave pool numerical model, the surrounding of the wave energy device is set as a dynamic region, the remaining area is set as a static region, and the wave energy device motion model is set as a 6 degree of freedom (6DOF) motion mode. The moment of inertia, mass, center of gravity and other parameters of the wave energy device are input into the model. The remaining waterline position, boundary condition and foundation grid division are consistent with the verified ideal wave pool.

[0109] As an optional implementation, in step S3, the wave energy device is modeled and imported into the ideal wave pool numerical model, the dynamic region, static region and boundary layer grid are set, and the wave energy device conversion efficiency is calculated. The device conversion efficiency obtained by the test is compared, and the relative error range is satisfied to obtain the final verified wave pool numerical model containing the device, which specifically includes the following steps.

[0110] S31: The wave energy device is modeled and imported into the ideal wave pool numerical model, wherein the surrounding of the wave energy device is set as a dynamic region, and the other areas are set as a static region.

[0111] S32: The dynamic region is encrypted, and the boundary layer grid is set around the wave energy device to calculate the first layer boundary layer grid height.

[0112] S33: Based on the first layer boundary layer grid height, the boundary layer thickness and growth rate are set to obtain the final grid division numerical pool.

[0113] S34: Based on the final grid division numerical pool, the wave energy device conversion efficiency is calculated.

[0114] S35: When the calculated wave energy device conversion efficiency and the conversion efficiency obtained by the test cannot satisfy the error requirement, the boundary layer grid or boundary condition parameter of the dynamic region and the surrounding area of the device is adjusted until the relative error range is satisfied, that is, the final verified wave pool numerical model containing the device is obtained.

[0115] Specifically, the surrounding water area of the wave energy device is encrypted, prism grid is used, and boundary layer grid is set around the device to capture the complex wave changes around the device. The first layer boundary layer grid height calculation method is as follows.

[0116] 1) First, calculate the Reynolds number.

[0117] .

[0118] wherein, is the Reynolds number; is the reference velocity; is the reference length; is the hydrodynamic viscosity.

[0119] The hydrodynamic viscosity is: For the wave energy device, in the usual sea environment, the reference velocity The value can be taken as follows.

[0120] .

[0121] Wherein, A is the amplitude, 0.5 H , is the frequency, ; the reference length can be taken as the device length value.

[0122] 2) Then calculate the friction coefficient: the friction coefficient can be estimated by an empirical formula.

[0123] .

[0124] Wherein, is the friction coefficient.

[0125] 3) Then calculate the friction velocity: the friction velocity estimation method is as follows.

[0126] .

[0127] Wherein, is the friction velocity.

[0128] 4) Finally, solve the first layer boundary layer grid height.

[0129] .

[0130] Wherein, is the first layer boundary layer grid height; is the wall dimensionless distance. According to the calculation requirement, the wall dimensionless distance value can be taken as 1~20; finally, the first layer grid height of the boundary layer .

[0131] As an optional implementation, the boundary layer thickness and growth rate are set, which can be generally set to 5~20 layers, and the growth rate can be set to 1.1~1.3.

[0132] As an optional implementation, through the model output result, first calculate the device time-averaged output power, and finally verify the model according to the wave energy device conversion efficiency calculation result.

[0133] The device time-averaged output power calculation formula is as follows.

[0134] .

[0135] in, The average hourly output power of the device is expressed in kW. The area enclosed by the device's output power duration curve and the time axis is kW·s; t is the total calculation time.

[0136] The conversion efficiency of a wave energy device is the ratio of the power acquired by the device to the wave input power. The wave input power can be calculated from the incident power of the regular wave. The incident power of the regular wave can be obtained by multiplying the regular wave power density by the width of the device facing the wave.

[0137] The expression for calculating the power density of a regular wave is shown below.

[0138] .

[0139] in, J The power density is for regular waves, in kW / m. The density of seawater, ; g It is the acceleration due to gravity. ; H For regular wave height, m, T Let be the wave period, s.

[0140] The formula for calculating the incident power of a regular wave is shown below.

[0141] .

[0142] in, Let be the incident power of the regular wave, in kW; B The width facing the waves is measured in meters (m).

[0143] Finally, the formula for calculating the conversion efficiency of wave energy devices is shown below.

[0144] .

[0145] in, The conversion efficiency of wave energy devices.

[0146] As an alternative implementation, if the conversion efficiency verification is not satisfactory (for example, the threshold can be set to within 15% relative error), the grid division method around the device needs to be adjusted until the verification is satisfactory.

[0147] As an optional implementation, in step S4, after verifying the accurate numerical model, the wave surface changes around the wave energy device can be analyzed. To better analyze the periodic changes of the wave surface, one period is divided into M time periods (M≥6), and the wave surface position at each time period is denoted as... , x Distance in the X direction ，tM is the moment in a period.

[0148] The wave surface change is divided into before and after the device, and the wave surface change is converted into the change of the relative theoretical value. The specific method is as follows.

[0149] First, the wave surface of the theoretical value at each moment is obtained, and the theoretical liquid surface at each position at each moment is , and the wave surface relative position is calculated according to the following formula.

[0150] .

[0151] When is negative, it means that the wave surface height after the device is lower than the theoretical value; when is positive, it means that the wave surface height after the device is higher than the theoretical value.

[0152] The water surface change is converted into the relative change, and the wave surface change at each moment is extracted, and finally the changes of M moments (M≥6) are averaged, and then the average change of the wave surface in a period can be obtained.

[0153] According to the regular wave power density formula, the wave energy density is proportional to the square of the wave height, that is, the larger the wave height, the more energy is contained and transmitted in the water body at this moment.

[0154] Therefore, the wave surface change needs to be weighted and averaged. When the wave height is high, the wave energy contained in the water body is larger, and the interaction between the device and the wave is most intense, so the wave surface change when the energy is large needs to be considered.

[0155] The following spatial change-based weighted average method is used to calculate the weight of each position x at each moment. The theoretical wave height at this position is as follows.

[0156] .

[0157] The above formula shows that is X = x the theoretical wave height at moment, and the square reflects the proportional relationship between energy and wave height. The absolute value is used to make the weight always positive, and the wave crest and the wave trough have equal importance.

[0158] This method can reflect the different contributions of different spatial positions to the average wave surface change due to different wave phases during wave propagation, and especially emphasizes the disturbance effect of high-energy areas (wave crest / wave trough).

[0159] Finally, the weights corresponding to the M time points are summed to equal 1, that is... .

[0160] Then, the weighted average wavefront change is calculated: the wavefront change after periodic averaging, for each position. x The weighted average is calculated using its specific weights.

[0161] .

[0162] in, This represents the average change data of the wavefront before and after the device within one cycle. for time x The relative position of the wavefront at the location; for time x Weight at position; M For the total time.

[0163] Optionally, the wavefront variation can be averaged using an average function, i.e., the ordinary averaging method can be used instead of the weighted averaging method.

[0164] .

[0165] Based on the formula above, the relative change of the wavefront in front of the device can be obtained. The relative change of the wavefront behind the device .

[0166] As an optional implementation, in step S5, in order to further obtain the wavefront change functions before and after the device, the least squares fitting method (with a threshold of at least 75% for the coefficient of determination) is used to determine the variable factors of the wavefront change functions before and after the device (the fitting process is as follows). Figure 3 (as shown)

[0167] When waves propagate to the device, reflection and energy accumulation occur, both of which cause the wavefront to rise. Furthermore, this phenomenon intensifies as the wave approaches the device, exhibiting an exponential growth pattern.

[0168] Therefore, the wave height distribution function based on the natural exponential type in front of the device can be obtained.

[0169] .

[0170] in, The wave height distribution function in front of the device is based on the natural exponential type. Amplitude factor; It is the stacking factor; C This is the wave-offset factor; x for XDirectional distance. This function can reflect the wave height rise in front of the device, and in the far distance away from the device, the relative change of wave surface tends to zero, that is, close to the theoretical wave surface.

[0171] The least square fitting method is used to determine , and C , and the incident wave height distribution function can be obtained.

[0172] The wave energy device extracts energy from the sea, and the total energy decays, and the wave surface behind the device has a phenomenon of wave height reduction. According to the principle of energy conservation, and because the wave energy density is proportional to the square of the wave height ( E ∝ ), the reduction of energy will inevitably lead to the reduction of transmitted wave height. The change of wave surface behind the device can be expressed as a function of oscillation decay with propagation distance.

[0173] Therefore, the tail wave height distribution function behind the device based on oscillation decay can be obtained.

[0174] .

[0175] Among them, is the tail wave height distribution function behind the device based on oscillation decay; is the tail wave amplitude factor; is the frequency, ; is the phase shift factor, is the tail wave shift factor; is the tail wave decay factor. This function can indicate that the wave surface decays behind the device, and slowly approaches the theoretical wave surface in the position away from the device.

[0176] The least square fitting method is used to determine , , and , and the tail wave height distribution function can be obtained.

[0177] .

[0178] Among them, is the relative change function of the wave surface in front of the device and the wave surface behind the device.

[0179] Finally, in step S6, the prediction expression of the wave surface height in front of and behind the device can be uniformly expressed as follows.

[0180] .

[0181] Among them, is the wave surface height in front of and behind the wave energy device; is the theoretical wave surface height.

[0182] Through the method, the wave surface height distribution at any position around the wave energy device can be quickly calculated without re-performing numerical simulation, thereby providing quantitative basis for array layout optimization and device interference analysis.

[0183] The method realizes the rapid prediction of the wave surface height before and after the wave energy device by converting the complex instantaneous wave surface change into periodic average change and further fitting into a continuous function. Compared with the traditional numerical simulation method, the method has the advantages of high calculation efficiency, strong applicability, and easy engineering application, and is especially suitable for wave field interference analysis, resource assessment and array optimization after the array layout of the wave energy device.

[0184] The application will be described below using specific embodiments.

[0185] The wave energy device to be studied is shown in Figure 4 , with a height of 5 m, a width of 7 m, and a length of 1 m; an ideal numerical tank is established according to the above dimensions (as shown in Figure 5 ): the boundary conditions and other parameters are set according to the description above, the regular wave height is set to 1 m, and the wave period is set to 4 s. The calculation step is set to 0.004 s.

[0186] The water surface change at the position X =0 for 5 consecutive periods is extracted and compared with the ideal wave sine curve: the ideal sine curve is , in order to facilitate comparison, the period is dimensionless; the comparison result is shown in Figure 6 .

[0187] The correlation coefficient reaches 98.5% for 5 consecutive periods, proving the feasibility of the numerical model. After verifying the ideal wave tank, the wave energy device is introduced into the numerical model, and the overall grid division diagram of the numerical tank is obtained, as shown in Figure 7 ; the initial position of the numerical tank is shown in Figure 8 ; the boundary layer setting is shown in Figure 9 ; and the conversion efficiency verification result is shown in Figure 10 .

[0188] The relative error of the highest point conversion efficiency is 5.71%, and the overall trend is close, so it is considered that the numerical model is verified, and the simulation result is reliable.

[0189] Now start the wave surface analysis, which is divided into 6 time points. Figure 11 is the initial state of the wave surface: (asterisk represents the position of the wave energy device); Figure 12 is the comparison between the simulation curve and the theoretical wave height at T / 2; Figure 13 is the relative change of the wave surface in front of the device at T / 2; Figure 14The relative change of the wave surface behind the device at T / 2.

[0190] The wave surface change at 6 time points is averaged to obtain the wave surface change in front of the device after period averaging as shown in Figure 15 The wave surface change behind the device after period averaging is shown in Figure 16 .

[0191] The variable factors of the wave surface height distribution functions in front of and behind the device are determined by using the least square method, and then the wave surface height distribution functions in front of and behind the device are obtained as shown below.

[0192] .

[0193] .

[0194] The schematic diagram of the wave height distribution function in front of the device is shown in Figure 17 , and the schematic diagram of the tail wave height distribution function behind the device is shown in Figure 18 . The results show that the wave surface function is very consistent with the wave surface value of the numerical simulation result, the root mean square error RMSE is 0.0063, the determination coefficient is 84.4%, the root mean square error RMSE is 0.00283, and the determination coefficient is 76.6%.

[0195] The relative change functions of the wave surface in front of and behind the device can be expressed as the following formula.

[0196] .

[0197] Finally, the prediction expression of the wave height in front of and behind the device can be expressed as the following formula.

[0198] .

[0199] In an exemplary embodiment, a computer device is provided, which can be a server or a terminal, and the internal structure diagram thereof can be as shown in Figure 19As shown in the figure. The computer device includes a processor, a memory, an Input / Output (I / O) interface and a communication interface. Among them, the processor, the memory and the input / output interface are connected through the system bus, and the communication interface is connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capability. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store the main size of the wave energy device. The input / output interface of the computer device is used to exchange information between the processor and the external device. The communication interface of the computer device is used to communicate with the terminal outside through the network connection. The computer program is executed by the processor to realize a wave energy device intervention post-sea wave height prediction method.

[0200] Those skilled in the art can understand that, Figure 19 The structure shown in the figure is only a block diagram of part of the structure related to the scheme of the present application, and does not constitute a limitation on the computer device to which the scheme of the present application is applied. The specific computer device can include more or fewer components than those shown in the figure, or combine certain components, or have a different component arrangement.

[0201] In one exemplary embodiment, a computer device is also provided, including a memory and a processor, the memory storing a computer program, and the processor executing the computer program to realize the above-mentioned method embodiments.

[0202] In one exemplary embodiment, a computer readable storage medium is provided, storing a computer program, which is executed by a processor to realize the above-mentioned method embodiments.

[0203] The technical features of the above embodiments can be combined in any way. In order to make the description concise, not all possible combinations of the technical features in the above embodiments are described, but as long as the combination of the technical features does not exist contradictory, it should be considered as the scope of the present application.

[0204] The principles and implementation modes of the present application are described by applying specific examples herein, and the above embodiment descriptions are only used to help understand the method and its core idea of the present application; at the same time, for those skilled in the art, according to the idea of the present application, the specific implementation mode and application range will be changed. In view of the above, the content of the present application should not be understood as a limitation.

Claims

1. A method for predicting sea surface height after the intervention of a wave energy device, characterized in that, include: Based on the main dimensions of the wave energy device, a numerical water tank is established and boundary conditions and numerical water tank parameters are set to obtain an ideal wave numerical water tank. By comparing and analyzing the ideal wave numerical pool with the theoretical wave sine curve, the verified ideal wave numerical pool model is obtained. After modeling the wave energy device, import it into the numerical model of an ideal wave pool. Set the dynamic domain, static domain and boundary layer mesh, calculate the conversion efficiency of the wave energy device, and compare it with the conversion efficiency of the device obtained from the experiment until the relative error range is met, and finally obtain the numerical model of the wave pool containing the device after verification. Based on the final verified numerical model of the wave pool containing the device, one cycle is divided into several equidistant moments. The position of wave surface change at each moment is statistically analyzed and averaged to obtain the average change data of the wave surface before and after the device within one cycle. Based on the average change data of the wavefront before and after the device within one cycle, the wavefront height distribution function variable factors are determined by the least squares fitting method, and the wavefront height distribution function based on the natural exponential type before the device and the wake height distribution function based on oscillation decay after the device can be obtained. Based on the natural exponential wave height distribution function in front of the device and the oscillating decay-based wake height distribution function behind the device, the wave surface heights before and after the wave energy device are calculated.

2. The method for predicting sea surface height after the intervention of a wave energy device according to claim 1, characterized in that, By comparing and analyzing the ideal wave numerical tank with the theoretical wave sine curve, a validated ideal wave numerical tank model is obtained, which specifically includes: Set the wave height, wave period, and minimum calculation time step for the regular wave; After extracting the preset wave period x The wavefront position at =0 is continuously sampled for several wave periods, and the wavefront undulations are made dimensionless. By comparing the extracted wavefront positions with the theoretical wave sine curve, the difference between the theoretical and actual values ​​can be obtained. Determine whether the difference exceeds a preset threshold; If so, the ideal wave numerical pool has failed the verification; reset the numerical pool parameters. If not, the ideal wave numerical pool is verified, and the verified ideal wave numerical pool model is obtained.

3. The method for predicting sea surface height after the intervention of a wave energy device according to claim 1, characterized in that, After modeling the wave energy device, it is imported into an ideal wave pool numerical model. Dynamic, static, and boundary layer meshes are set, and the wave energy conversion efficiency is calculated. This efficiency is compared with the experimentally obtained conversion efficiency until the relative error range is met, resulting in the final verified wave pool numerical model containing the device. Specifically, this includes: After modeling the wave energy device, import it into the numerical model of an ideal wave pool. The area around the wave energy device is set as the dynamic domain, and other areas are set as the static domain. The dynamic domain is densified, and a boundary layer mesh is set around the wave energy device. The height of the first boundary layer mesh is calculated. Based on the height of the first boundary layer mesh, the boundary layer thickness and growth rate are set to obtain the final meshed numerical water tank. Based on the final meshed numerical pool, the wave energy conversion efficiency was calculated. When the calculated conversion efficiency of the wave energy device cannot meet the error requirements compared with the experimental conversion efficiency, the boundary layer mesh or boundary condition parameters of the dynamic domain and the area surrounding the device are adjusted until the relative error range is met, and the final verified numerical model of the wave pool containing the device can be obtained.

4. The method for predicting sea surface height after the intervention of a wave energy device according to claim 1, characterized in that, The formula for calculating the conversion efficiency of the wave energy device is as follows: ； ； ； ； in, The conversion efficiency of wave energy devices; The average output power of the device; The incident power of the regular wave; B For the width facing the waves; J For regular wave power density; The density of seawater; g It is the acceleration due to gravity; H For regular wave height, T For wave period; The area enclosed by the device's output power duration curve and the time axis; t This represents the total calculation time.

5. The method for predicting sea surface height after the intervention of a wave energy device according to claim 1, characterized in that, The formula for calculating the average change data of the wavefront before and after the device within one cycle is as follows: or ; in, This represents the average change data of the wavefront before and after the device within one cycle. for time x The relative position of the wavefront at the location; for time x Weight at position; M For the total time.

6. The method for predicting sea surface height after the intervention of a wave energy device according to claim 1, characterized in that, The expression for the wave height distribution function based on the natural exponential type in front of the device is: ； in, The wave height distribution function in front of the device is based on the natural exponential type. Amplitude factor; It is the stacking factor; C This is the wave-offset factor; x for X Directional distance.

7. The method for predicting sea surface height after the intervention of a wave energy device according to claim 1, characterized in that, The expression for the wake height distribution function based on oscillation attenuation after the device is as follows: ； in, The height distribution function of the tailwave after the device is based on oscillation attenuation; This is the wake amplitude factor; For frequency; For phase shift factor, This is the wake offset factor; This is the wake attenuation factor; x for X Directional distance.

8. The method for predicting sea surface height after the intervention of a wave energy device according to claim 1, characterized in that, The formula for calculating the height of the wave surface before and after the wave energy device is as follows: ； ； in, The height of the wave surface before and after the wave energy device; The theoretical wavefront height; This includes the relative change function of the wavefront before and after the device; The wave height distribution function in front of the device is based on the natural exponential type. The height distribution function of the wake wave based on oscillation attenuation is given after the device.

9. A computer device, comprising: A memory, a processor, and a computer program stored in the memory and capable of running on the processor, characterized in that the processor executes the computer program to implement the method for predicting sea surface height after the intervention of a wave energy device as described in any one of claims 1-8.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program implements the method for predicting sea surface height after the intervention of a wave energy device as described in any one of claims 1-8.

Images