A data processing method in wind resource assessment directional calculation and related device

Abstract

This application discloses a data processing method, apparatus, equipment, and readable storage medium for directional calculation in wind resource assessment. The method includes: calculating the convergence rate of the current iteration step based on the target physical quantity within the previous first preset iteration step and the previous first preset iteration step from the current iteration step; determining whether it is stable convergence based on the convergence rate within the next second preset iteration step; if not, obtaining the target physical quantity within the tail end and an integer multiple of the change period, and performing spectrum analysis; if the maximum amplitude of the obtained waveform is within a preset range, determining whether it is fluctuating convergence based on the waveform; if so, obtaining the directional calculation result based on the target physical quantity within the change period. The technical solution disclosed in this application uses the target physical quantity for convergence rate calculation and judgment, improving the efficiency and robustness of convergence judgment, and obtaining the directional calculation result based on the target physical quantity within the complete change period under fluctuating convergence, thereby improving the accuracy and stability of the directional result.

Description

Technical Field

[0001] This application relates to the field of wind resource assessment technology, and more specifically, to a data processing method, apparatus, equipment, and readable storage medium for wind resource assessment directional calculation. Background Technology

[0002] Wind resource assessment is a crucial step in wind energy resource development planning and an important means of ensuring the investment benefits of wind farms. Wind resource assessment mainly consists of two parts: directional calculation and comprehensive calculation. Directional calculation is performed based on input topography, roughness, anemometer tower locations, and wind turbine locations. Based on this, comprehensive calculations are performed using the directional calculation results, anemometer tower wind measurement data, and wind turbine power curves to obtain wind speed, wind direction, turbulence, and power generation.

[0003] In recent years, wind resource assessment technology based on CFD (Computational Fluid Dynamics) has received widespread attention due to its advantages such as flexible calculation, short processing time, and high-precision assessment. Among these advantages, the accuracy of CFD directional calculations directly determines the effectiveness of the overall calculation; therefore, CFD directional calculations are crucial for wind resource assessment.

[0004] To obtain accurate CFD directional calculation results, traditional convergence judgment methods typically involve engineers monitoring residual curves, physical quantity change curves, or even observing local flow field changes. This approach heavily relies on engineers' personal experience and often requires specific analysis for each problem. Furthermore, for wind resource assessment directional calculations, dozens of CFD calculations across sectors are usually initiated simultaneously. Manually identifying and determining the output for each sector's residual curve, physical quantity change curve, or flow field characteristics would significantly increase the engineers' workload and severely reduce wind resource assessment efficiency. Currently, some commercial software uses residual-based convergence rates to meet the need for rapid convergence judgment. However, residual-based convergence rates do not always fully reflect the convergence status of CFD calculations. When there are fluctuations in physical quantity values, the residual convergence rate cannot characterize the reliability of the CFD calculation results. Moreover, CFD directional calculations with numerical fluctuations often lead to significant changes in the target physical quantity within just a few dozen iteration steps, resulting in considerable uncertainty in the calculation results. Due to the aforementioned limitations, when numerical fluctuations occur in CFD directional calculations, there will be significant deviations in the accuracy of convergence judgment and directional calculation results, thus affecting the wind resource assessment results.

[0005] In summary, improving the accuracy and efficiency of CFD directional calculation convergence judgment in wind resource assessment, and improving the accuracy of directional calculation to enhance the accuracy of wind resource assessment, is a technical problem that urgently needs to be solved by those skilled in the art. Summary of the Invention

[0006] In view of this, the purpose of this application is to provide a data processing method, apparatus, equipment and readable storage medium for wind resource assessment directional calculation, which can improve the accuracy and efficiency of CFD directional calculation convergence judgment in wind resource assessment, and improve the accuracy of directional calculation, so as to improve the accuracy of wind resource assessment.

[0007] To achieve the above objectives, this application provides the following technical solution:

[0008] A data processing method for directional calculation of wind resource assessment includes:

[0009] Based on the target physical quantity calculated by CFD orientation in the wind resource assessment within the first preset iteration step, and the target physical quantity from the current iteration step to the first preset iteration step, calculate the convergence rate at the current iteration step;

[0010] Based on the convergence rate of the CFD directional calculation within the second preset iteration step, determine whether the CFD directional calculation is a stable convergence.

[0011] If the convergence is not stable, the target physical quantity within an integer multiple of the change period at the tail end of the CFD directional calculation is obtained, and a spectral analysis is performed on the target physical quantity within the integer multiple of the change period; the change period is the change period of the target physical quantity.

[0012] If the maximum amplitude of the waveform obtained by the spectrum analysis is within a preset range, then it is determined whether the CFD directional calculation is fluctuating convergence based on the waveform.

[0013] If the fluctuation converges, the target physical quantity directional calculation result is obtained based on the target physical quantity within the change period.

[0014] Preferably, determining whether the CFD directional calculation is fluctuating convergence based on the waveform includes:

[0015] Noise signals are filtered out from the waveform;

[0016] Determine whether the waveform after filtering out noise signals has multiple dominant frequencies;

[0017] If not, then the CFD directional calculation is determined to be fluctuating convergence.

[0018] Preferably, if the waveform after filtering out noise signals has multiple dominant frequencies, then it further includes:

[0019] Determine that the CFD directional computation has not converged, and output the target physical quantity of the CFD directional computation in the final iteration step.

[0020] Preferably, obtaining the target physical quantity within an integer multiple of the change period at the tail end of the CFD directional calculation includes:

[0021] The target physical quantity is obtained within a preset percentage of the total number of iterations at the tail end of the CFD directional calculation, in order to form a sequence of target physical quantities;

[0022] Peak and valley identification is performed on the target physical quantity sequence;

[0023] If the number of peaks and valleys in the target physical quantity sequence is greater than or equal to 2, then the target physical quantity within the change period that is an integer multiple of the tail end of the CFD directional calculation is obtained according to the iteration step where the peaks and valleys of the target physical quantity sequence are located.

[0024] Preferred options also include:

[0025] If the number of peaks and valleys in the target physical quantity sequence is less than 2, then the CFD directional calculation is determined to be stable and converged, and the target physical quantity of the CFD directional calculation in the final iteration step is output.

[0026] Preferably, the convergence rate at the current iteration step is calculated based on the target physical quantity calculated by CFD directional calculation in the wind resource assessment within the previous first preset iteration step and the target physical quantity from the current iteration step to the previous first preset iteration step, including:

[0027] use Calculate the convergence rate at the Mth iteration step;

[0028] in, Let θ be the convergence rate, n be the first preset iteration step, and θ be the convergence rate. i Let be the target physical quantity in the i-th iteration step. The average value of the target physical quantity within the first preset iteration step prior to the Mth iteration step. It is the average value of the target physical quantity within the first preset iteration step.

[0029] Preferred options also include:

[0030] If the maximum amplitude is less than the minimum value in the preset range, the CFD directional calculation is determined to be stable convergence, and the target physical quantity of the CFD directional calculation in the final iteration step is output.

[0031] If the maximum amplitude is greater than the maximum value in the preset range, it is determined that the CFD directional calculation has not converged, and the target physical quantity of the CFD directional calculation in the final iteration step is output.

[0032] A data processing device for wind resource assessment and directional calculation, comprising:

[0033] The calculation module is used to calculate the convergence rate in the current iteration step based on the target physical quantity in the previous first preset iteration step and the target physical quantity in the previous first preset iteration step from the current iteration step, according to the CFD directional calculation in wind resource assessment.

[0034] The first judgment module is used to determine whether the CFD directional calculation is stable convergence based on the convergence rate of the CFD directional calculation in the second preset iteration step.

[0035] The spectrum analysis module is used to obtain the target physical quantity within an integer multiple of the change period at the tail end of the CFD directional calculation if the convergence is not stable, and to perform spectrum analysis on the target physical quantity within the integer multiple of the change period; the change period is the change period of the target physical quantity.

[0036] The second judgment module is used to determine whether the CFD directional calculation is fluctuating convergence based on the waveform if the maximum amplitude of the waveform obtained by the spectrum analysis is within a preset range.

[0037] The result acquisition module is used to obtain the target physical quantity orientation calculation result based on the target physical quantity within the change period if the fluctuation converges.

[0038] A data processing device for wind resource assessment and directional calculation, comprising:

[0039] Memory, used to store computer programs;

[0040] A processor, configured to execute the computer program to implement the steps of the data processing method in the wind resource assessment directional calculation as described in any of the preceding claims.

[0041] A readable storage medium storing a computer program that, when executed by a processor, implements the steps of the data processing method for wind resource assessment directional calculation as described in any of the preceding claims.

[0042] This application provides a data processing method, apparatus, device, and readable storage medium for wind resource assessment directional calculation. The method includes: calculating the convergence rate in the current iteration step based on the target physical quantity in the previous first preset iteration step and the target physical quantity from the current iteration step to the previous first preset iteration step; determining whether the CFD directional calculation is stable convergence based on the convergence rate in the subsequent second preset iteration step; if it is not stable convergence, obtaining the target physical quantity within an integer multiple of the change period at the end of the CFD directional calculation, and performing spectral analysis on the target physical quantity within the integer multiple of the change period; the change period is the change period of the target physical quantity; if the maximum amplitude of the waveform obtained from the spectral analysis is within a preset range, determining whether the CFD directional calculation is fluctuating convergence based on the waveform; if it is fluctuating convergence, obtaining the target physical quantity directional calculation result based on the target physical quantity within the change period.

[0043] The technical solution disclosed in this application calculates the convergence rate of the current iteration step based on the target physical quantity in the first preset iteration step of CFD directional calculation in wind resource assessment and the target physical quantity in the first preset iteration step prior to the current iteration step. This enables the calculation of the convergence rate for each iteration step from the first preset iteration step onwards using the target physical quantity. Furthermore, it determines whether the CFD directional calculation is stably converged based on the convergence rate in the second preset iteration step. This achieves automatic calculation of the convergence rate and convergence determination using the target physical quantity, thereby enabling rapid and accurate convergence determination for wind resource assessment directional calculation, improving the efficiency and robustness of convergence determination. If the convergence rate in the second preset iteration step determines that the CFD directional calculation is not stably converged, then the target physical quantity within the change period (i.e., the change period of the target physical quantity) that is an integer multiple of the tail end of the CFD directional calculation is obtained, and spectral analysis is performed. If the maximum amplitude of the waveform obtained from the spectrum analysis is within the preset range, then the CFD directional calculation is determined based on the waveform obtained from the spectrum analysis to determine whether it is fluctuating convergence. If it is fluctuating convergence, the target physical quantity directional result is obtained based on the target physical quantity within the change cycle, so as to achieve accurate identification of fluctuating convergence. The target physical quantity directional calculation result is obtained based on the target physical quantity within the complete change cycle under fluctuating convergence, so as to improve the accuracy and stability of the directional calculation result, thereby facilitating the improvement of the effectiveness and accuracy of wind resource assessment. Attached Figure Description

[0044] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of this application. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0045] Figure 1 A flowchart of a data processing method for wind resource assessment directional calculation provided in this application embodiment;

[0046] Figure 2 A flowchart illustrating another data processing method for wind resource assessment directional calculation provided in this application embodiment;

[0047] Figure 3 Wind speed convergence history diagram of a typical fluctuation convergence embodiment provided in this application;

[0048] Figure 4 The frequency domain diagram obtained by spectrum analysis provided in the embodiments of this application;

[0049] Figure 5 This application provides a schematic diagram of the structure of a data processing device for wind resource assessment and directional calculation.

[0050] Figure 6 This is a schematic diagram of the structure of a data processing device for wind resource assessment and directional calculation provided in an embodiment of this application. Detailed Implementation

[0051] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0052] See Figure 1 The diagram illustrates a flowchart of a data processing method for wind resource assessment directional calculation provided in this application embodiment. This data processing method for wind resource assessment directional calculation provided in this application embodiment may include:

[0053] S11: Based on the target physical quantities in the first preset iteration step calculated by CFD in the wind resource assessment, and the target physical quantities in the first preset iteration step from the current iteration step, calculate the convergence rate in the current iteration step.

[0054] When performing CFD-oriented calculations in wind resource assessment, the target physical quantity output at each iteration step of the CFD-oriented calculation can be obtained. Specifically, the target physical quantity mentioned here is wind speed, but it can also be other important physical quantities in wind resource assessment, such as turbulent kinetic energy.

[0055] Furthermore, based on the target physical quantities in the first preset iteration step of the CFD directional calculation (specifically, the target physical quantities in each iteration step of the first preset iteration step) and the target physical quantities in the first preset iteration step before the current iteration step (that is, the target physical quantities in each iteration step included), the convergence rate of the CFD directional calculation in the current iteration step can be calculated. This enables automatic calculation of the convergence rate using the target physical quantities (specifically, the convergence rate is calculated based on the degree of change of the target physical quantities over a period of time), thereby accurately reflecting the convergence status of the target physical quantities and helping users quickly determine the reliability of the CFD directional calculation results for wind resource assessment.

[0056] The size of the first preset iteration step can be set based on experience or actual needs, for example, it can be 100. Additionally, it should be noted that if the current iteration step is less than the first preset iteration step, the convergence rate can be directly set to 0; if the current iteration step is greater than or equal to the first preset iteration step, the convergence rate for the current iteration step can be calculated according to step S11.

[0057] Step S11 yields the convergence rate of CFD directional calculation at each iteration step, which is the convergence rate from the first iteration step to the final iteration step. The convergence rate at each iteration step can be used to construct a convergence history list, which facilitates subsequent determination of the convergence status and allows relevant personnel to obtain the convergence rate and understand the situation.

[0058] S12: Based on the convergence rate of the CFD directional calculation within the second preset iteration step, determine whether the CFD directional calculation is stably converged. If not, proceed to step S13; if yes, determine that it is stably converged and output the target physical quantity of the CFD directional calculation in the final iteration step.

[0059] After calculating the convergence rate of the CFD directional computation at each iteration step using step S11, once the CFD directional computation stops, the convergence rate of the CFD directional computation within the next second preset iteration step can be obtained. That is, starting from the final iteration step of the CFD directional computation, the convergence rate at each of the second preset iteration steps is obtained by backtracking. The second preset iteration step can be set based on experience or actual needs, and it can be the same as the first preset iteration step; this application does not impose any limitations on this.

[0060] Then, the convergence rate of the CFD-directed computation within the second preset iteration step can be used to determine whether the CFD-directed computation is stable. Specifically, it can be determined whether the convergence rate of the CFD-directed computation in each iteration step within the second preset iteration step is greater than a convergence rate limit. If so, the CFD-directed computation is determined to be stable; otherwise, it is determined to be unstable. The convergence rate limit can be determined according to actual needs, and is usually set to 90%. If the CFD-directed computation is determined to be stable, the target physical quantity in the final iteration step can be directly output to participate in the comprehensive calculation of wind resource assessment. If the CFD-directed computation is determined to be unstable, subsequent convergence identification is performed.

[0061] The convergence rate of the obtained CFD directional computation within the second preset iteration step can be expressed as: m represents the number of steps in the second preset iteration step. Let N be the convergence rate at the m-th iteration from the end, and N represent the total number of iterations. This represents the convergence rate at the final iteration step. The above judgment is the determination. Whether it holds true (i.e., whether each convergence rate in the convergence rate sequence is greater than Φ), where Φ represents the convergence rate limit for complete convergence.

[0062] As described above, this application uses the convergence rate over a period of time to determine stable convergence, thereby improving the reliability and accuracy of convergence determination. Furthermore, as shown in steps S11 and S12, this application calculates the convergence rate starting from the target physical quantity, directly reflecting the convergence status of the target physical quantity in CFD directional calculations. This solves the problems of inefficiency, cumbersome procedures, and low reliability and accuracy associated with traditional methods such as observing residual curves or physical quantity change curves.

[0063] S13: Obtain the target physical quantity within an integer multiple of the change period at the tail end of the CFD directional calculation, and perform spectral analysis on the target physical quantity within the integer multiple of the change period; the change period is the change period of the target physical quantity.

[0064] If it is determined in step S12 that the CFD directional computation is not stably converged, then fluctuation identification is performed. Specifically, the target physical quantity within an integer multiple of the variation period at the end of the CFD directional computation can be obtained. This variation period specifically refers to the variation period of the target physical quantity with respect to the iteration step. Furthermore, the integer multiple mentioned here can be one multiple or other multiples. Obtaining the target physical quantity within an integer multiple of the variation period ensures the reliability of subsequent spectral analysis, thereby improving the reliability and accuracy of fluctuation identification.

[0065] Then, spectral analysis is performed on the target physical quantity within an integer multiple of the change period. Specifically, Fourier transform is used to analyze the target physical quantity within an integer multiple of the change period to obtain the corresponding waveform, so as to facilitate feature recognition based on the waveform.

[0066] The Fourier transform is: t represents time, which here signifies the iteration step; f(t) is the target physical quantity corresponding to the iteration step; and ω is the angular frequency. This represents the Fourier transform.

[0067] S14: If the maximum amplitude of the waveform obtained by the spectrum analysis is within the preset range, then determine whether the CFD directional calculation is oscillatory convergence based on the waveform; if so, then execute step S15.

[0068] The maximum amplitude value of the waveform obtained from the spectrum analysis is obtained and compared with a preset range. The minimum value of the preset range can be set according to actual needs, and is typically 10. -5 The maximum value of the preset range can be determined based on the average target physical quantity (i.e., the average value of the target physical quantity over a period of change). It is typically set to 20% of the average target physical quantity. Taking wind speed as an example, the maximum value of the preset range would be 20% * V. ave , where V ave This represents the average wind speed.

[0069] If the maximum amplitude of the waveform is within the preset range, feature recognition is required to determine the waveform characteristics. That is, based on the waveform, it is determined whether the CFD directional calculation is oscillatory convergence. If it is oscillatory convergence, step S15 is executed. If it is not oscillatory convergence, it is determined that the CFD has not converged. At this time, the target physical quantity under the final iteration step can be directly output, and a prompt that the CFD directional calculation has not converged can be issued.

[0070] S15: Obtain the target physical quantity orientation calculation result based on the target physical quantity within the change period.

[0071] If the CFD directional calculation is determined to be fluctuating convergence, the directional calculation result of the target physical quantity can be obtained based on the target physical quantity within the change period. Specifically, the target physical quantity can be averaged over one change period (or several multiples of change periods) to obtain the directional calculation result of the target physical quantity.

[0072] Taking the averaging of the target physical quantity over a period of change as an example, it is: Where θ is the result of the orientation calculation of the target physical quantity, θ i Let T be the target physical quantity in the i-th iteration within a change period, where T is the change period.

[0073] As can be seen from the above, this application uses a fluctuation identification method to effectively analyze the fluctuation characteristics of the target physical quantity, obtain the change period of the target physical quantity, and realize the periodic averaging of the target physical quantity under fluctuation convergence. This solves the defects of large uncertainty and poor reliability of the orientation calculation results when fluctuation converges, which is conducive to improving the accuracy and stability of the orientation results, thereby improving the effectiveness and accuracy of wind resource assessment.

[0074] The technical solution disclosed in this application calculates the convergence rate of the current iteration step based on the target physical quantity in the first preset iteration step of CFD directional calculation in wind resource assessment and the target physical quantity in the first preset iteration step prior to the current iteration step. This enables the calculation of the convergence rate for each iteration step from the first preset iteration step onwards using the target physical quantity. Furthermore, it determines whether the CFD directional calculation is stably converged based on the convergence rate in the second preset iteration step. This achieves automatic calculation of the convergence rate and convergence determination using the target physical quantity, thereby enabling rapid and accurate convergence determination for wind resource assessment directional calculation, improving the efficiency and robustness of convergence determination. If the convergence rate in the second preset iteration step determines that the CFD directional calculation is not stably converged, then the target physical quantity within the change period (i.e., the change period of the target physical quantity) that is an integer multiple of the tail end of the CFD directional calculation is obtained, and spectral analysis is performed. If the maximum amplitude of the waveform obtained from the spectrum analysis is within the preset range, then the CFD directional calculation is determined based on the waveform obtained from the spectrum analysis to determine whether it is fluctuating convergence. If it is fluctuating convergence, the target physical quantity directional result is obtained based on the target physical quantity within the change cycle, so as to achieve accurate identification of fluctuating convergence. The target physical quantity directional calculation result is obtained based on the target physical quantity within the complete change cycle under fluctuating convergence, so as to improve the accuracy and stability of the directional calculation result, thereby facilitating the improvement of the effectiveness and accuracy of wind resource assessment.

[0075] See Figure 2 This document illustrates a flowchart of another data processing method for wind resource assessment directional calculation provided in an embodiment of this application. The data processing method for wind resource assessment directional calculation provided in this application, which determines whether the CFD directional calculation is fluctuating convergence based on the waveform, may include:

[0076] Remove noise signals from the waveform;

[0077] Determine whether the waveform after filtering out noise signals has multiple dominant frequencies;

[0078] If not, then the CFD directional calculation is determined to be wave convergence.

[0079] When determining whether a CFD directional calculation exhibits fluctuating convergence based on the waveform, this application can first filter out noise signals in the waveform based on the maximum amplitude. Specifically, it can first utilize ξ=α·δ max The amplitude limit is obtained, where α represents the allowable amplitude ratio, which can be determined according to actual needs, and is usually taken as 20%, and δ represents the amplitude. max ξ represents the maximum amplitude value, and ξ is the amplitude limit. Then, amplitude values ​​in the waveform that are less than the amplitude limit are filtered out to remove noise signals from the waveform (that is, amplitude values ​​in the waveform that are less than the amplitude limit are filtered out as noise signals), thereby avoiding the impact on the wave convergence identification and improving the accuracy of wave convergence determination.

[0080] After filtering out noise signals from the waveform, it is determined whether the waveform after filtering out noise signals has multiple dominant frequencies (i.e., whether it has multiple amplitudes). If there is only a single dominant frequency corresponding to the largest amplitude, then the CFD directional calculation is determined to be oscillatory convergence.

[0081] The above methods can be used to accurately determine fluctuation convergence, thereby improving the accuracy and robustness of the orientation results, which in turn facilitates the improvement of the accuracy and robustness of wind resource assessment.

[0082] The data processing method for wind resource assessment and directional calculation provided in this application embodiment may further include, if the waveform after filtering out noise signals has multiple dominant frequencies:

[0083] Determine if the CFD directional computation has not converged, and output the target physical quantity of the CFD directional computation in the final iteration step.

[0084] In this application, if it is determined that the waveform after filtering out noise signals not only has a dominant frequency corresponding to the largest amplitude, but also has dominant frequencies corresponding to other amplitudes, that is, if it is determined that the waveform after filtering out noise signals has multiple dominant frequencies, then it is determined that the CFD directional calculation is not oscillatory convergence, but non-convergence. At this time, the target physical quantity under the final iteration step can be output, and a prompt that the CFD directional calculation has not converged can be issued.

[0085] This application provides a data processing method for wind resource assessment directional calculation, which obtains the target physical quantity within an integer multiple of the change period at the tail end of the CFD directional calculation, and may include:

[0086] Obtain the target physical quantities within a preset percentage of the total number of iterations at the tail end of the CFD directional calculation, in order to form a sequence of target physical quantities;

[0087] Peak and valley identification of the target physical quantity sequence;

[0088] If the number of peaks and valleys in the target physical quantity sequence is greater than or equal to 2, then the target physical quantity within the change period that is an integer multiple of the peak and valley of the target physical quantity sequence is obtained from the iteration step at the tail of the CFD directional calculation.

[0089] In this application, the specific process for obtaining the target physical quantity within the change period that is an integer multiple of the tail end of the CFD directional calculation is as follows:

[0090] (1) Obtain the target physical quantity within a preset percentage of the total number of iterations at the end of the CFD directional calculation to form a target physical quantity sequence. The preset percentage can be set according to actual needs, and is usually 20%. If the target physical quantity is wind speed, then it is to obtain the wind speed within a preset percentage of the total number of iterations at the end of the CFD directional calculation to form a wind speed sequence;

[0091] (2) Identify the peaks and valleys (including peaks and valleys) of the target physical quantity sequence using the differential method, and determine the iteration step where the peaks and valleys of the target physical quantity sequence are located:

[0092]

[0093] Where ζ represents the iteration step.

[0094] (3) If the number of peaks and valleys in the target physical quantity sequence is greater than or equal to 2, the target physical quantity sequence can be extracted again based on the identified peaks and valleys (specifically based on the iteration step where the peaks and valleys are located) to obtain the target physical quantity within the change period that is an integer multiple of the tail end of the CFD directional calculation.

[0095] Peak and valley identification can facilitate the accurate capture of target physical quantities within integer multiples of their variation period, thereby improving the reliability of spectral analysis and consequently enhancing the reliability and accuracy of orientation results.

[0096] The data processing method for wind resource assessment directional calculation provided in this application embodiment may further include:

[0097] If the number of peaks and valleys in the target physical quantity sequence is less than 2, then the CFD directional computation is determined to be stable and converged, and the target physical quantity of the CFD directional computation in the final iteration step is output.

[0098] In this application, if the number of peaks and valleys in the target physical quantity sequence is determined to be less than 2 by peak and valley identification, that is, if the target physical quantity sequence is determined to have no peaks and valleys or only one peak or one valley, then in this case, the CFD directional calculation can be considered to be stable and converged, and the target physical quantity under the final iteration can be output to participate in the comprehensive calculation of wind resource assessment.

[0099] This application provides a data processing method for directional calculation in wind resource assessment, which calculates the convergence rate in the current iteration step based on the target physical quantities in the previous first preset iteration step and the target physical quantities from the current iteration step to the previous first preset iteration step. The method may include:

[0100] use Calculate the convergence rate at the Mth iteration step;

[0101] in, Let θ be the convergence rate, n be the first preset iteration step, and θ be the convergence rate. i Let be the target physical quantity in the i-th iteration step. This represents the average value of the target physical quantity within the first preset iteration step preceding the Mth iteration step. It is the average value of the target physical quantity within the first preset iteration step.

[0102] In this application, specific uses can be made This convergence model calculates the convergence rate at the Mth iteration step based on the target physical quantity θ in the first n iterations of the CFD and the target physical quantity θ in the first n iterations from the Mth iteration step. in, θ j The target physical quantity is the j-th iteration within the first preset iteration step.

[0103] The convergence rate model described above can accurately reflect the convergence of the target physical quantity, helping users quickly determine the reliability of CFD directional calculation results for wind resource assessment.

[0104] The data processing method for wind resource assessment directional calculation provided in this application embodiment may further include:

[0105] If the maximum amplitude is less than the minimum value in the preset range, the CFD directional calculation is determined to be stable convergence, and the target physical quantity of the CFD directional calculation in the final iteration step is output.

[0106] If the maximum amplitude is greater than the maximum value in the preset range, it is determined that the CFD directional calculation has not converged, and the target physical quantity of the CFD directional calculation in the final iteration step is output.

[0107] In this application, after performing spectral analysis on the target physical quantity within an integer multiple of the change period, if the maximum amplitude of the waveform obtained from the spectral analysis is less than the minimum value in the preset range, it can be determined that the CFD directional calculation is stably converged. At this time, the target physical quantity of the CFD directional calculation in the final iteration step can be output. If the maximum amplitude of the waveform obtained from the spectral analysis is greater than the maximum value in the preset range, it can be determined that the CFD directional calculation has not converged. At this time, the target physical quantity of the CFD directional calculation in the final iteration step can be output, and a prompt can be given for the non-convergence situation.

[0108] As can be seen from the above process in this application, this application outputs the target physical quantity using different output modes based on different convergence states of CFD directional calculation. Specifically, in cases of stable convergence and non-convergence, the target physical quantity at the final iteration step is directly output; in cases of fluctuating convergence, the target physical quantity at the iteration steps of the complete change cycle is averaged.

[0109]

[0110] As can be seen from the above process in this application, the convergence judgment criteria and result processing method of this application are developed based on the CFD directional calculation of wind resource assessment. Calculating the convergence rate from the perspective of physical quantities directly reflects the convergence status of the target physical quantity in the CFD directional calculation, solving the problems of inefficiency and cumbersome procedures associated with traditional methods such as observing residual curves or physical quantity change curves. Furthermore, the fluctuation identification method can effectively analyze the fluctuation characteristics of physical quantities, thereby determining the convergence type of the directional calculation, and using different output modes to output the target physical quantity for different convergence types, improving the efficiency and robustness of convergence judgment in wind resource assessment directional calculation, and contributing to the improvement of the accuracy and robustness of the directional results. In addition, by obtaining the change period of the target physical quantity through fluctuation identification, the periodic averaging of physical quantities under fluctuation convergence is achieved, solving the defects of large uncertainty and poor reliability of directional calculation results during fluctuation convergence. It can be used for convergence judgment and result processing in wind resource assessment CFD directional calculation, exhibiting excellent robustness.

[0111] To better illustrate this application and facilitate understanding of its technical solutions, typical but non-limiting embodiments of this application are as follows:

[0112] For details, please refer to [link / reference]. Figure 3 The diagram shows the wind speed convergence history of a typical fluctuation convergence embodiment provided in this application. The horizontal axis represents the number of iterations, and the vertical axis represents the wind speed. The total number of iterations is 5000. Since the convergence rate does not meet the requirements for stable convergence, fluctuation identification is performed.

[0113] (1) Extract the last 20% of the convergence history (1000 steps) and perform peak and valley identification to obtain the wind speed sequence (containing 816 steps, i.e., the change period of integer multiples) with a peak and valley number greater than 2;

[0114] (2) Based on this, spectral analysis was performed using the obtained wind speed sequence. Specific results can be found in [reference needed]. Figure 4 The diagram shows a frequency domain graph obtained by spectrum analysis provided in the embodiment of this application. The horizontal axis represents frequency and the vertical axis represents amplitude. The maximum amplitude is 0.32, which is less than 20% of the average wind speed (the average wind speed in this case is 10.14 m / s).

[0115] (3) After filtering out noise with an amplitude less than 20% of the maximum amplitude, only a single dominant frequency exists, which is a wave convergence.

[0116] This allows the orientation result to be averaged over a complete period and output. It is worth noting that... Figure 3 The results show that the difference between the peak (10.53 m / s) and trough (9.85 m / s) of the wind speed sequence is close to 0.7 m / s, which means that even a change in the number of iterations can lead to a significant difference in the power generation obtained from subsequent comprehensive calculations. Therefore, identifying the convergence of fluctuations and averaging physical quantities over a periodic period can effectively improve the stability of the directional calculation results of wind resource assessment CFD. The convergence judgment method in this application shows significant advantages in both convergence judgment efficiency and stability.

[0117] This application also provides a data processing device for wind resource assessment and directional calculation, see [link to relevant documentation]. Figure 5 The diagram illustrates the structure of a data processing device for wind resource assessment directional calculation according to an embodiment of this application, which may include:

[0118] Calculation module 51 is used to calculate the convergence rate in the current iteration step based on the target physical quantity in the previous first preset iteration step and the target physical quantity in the previous first preset iteration step from the current iteration step in the CFD directional calculation of wind resource assessment.

[0119] The first judgment module 52 is used to determine whether the CFD directional calculation is stable convergence based on the convergence rate of the CFD directional calculation in the second preset iteration step.

[0120] The spectrum analysis module 53 is used to obtain the target physical quantity within an integer multiple of the change period at the tail end of the CFD directional calculation if the convergence is not stable, and to perform spectrum analysis on the target physical quantity within the integer multiple of the change period; the change period is the change period of the target physical quantity.

[0121] The second judgment module 54 is used to determine whether the CFD directional calculation is oscillatory convergence based on the waveform if the maximum amplitude of the waveform obtained by the spectrum analysis is within a preset range.

[0122] The result module 55 is used to obtain the target physical quantity directional calculation result based on the target physical quantity within the change period if the fluctuation converges.

[0123] This application provides a data processing device for wind resource assessment and directional calculation, wherein the second judgment module 54 may include:

[0124] The filtering unit is used to filter out noise signals from the waveform.

[0125] The judgment unit is used to determine whether the waveform after filtering out noise signals has multiple main frequencies;

[0126] The first determining unit is used to determine that the CFD directional calculation is oscillatory convergence if it is determined that the waveform after filtering out noise signals does not have multiple dominant frequencies.

[0127] The data processing device for wind resource assessment and directional calculation provided in this application embodiment may further include a second judgment module 54 comprising:

[0128] The second determining unit is used to determine that the CFD directional calculation has not converged if the waveform after filtering out noise signals has multiple dominant frequencies, and to output the target physical quantity of the CFD directional calculation in the final iteration step.

[0129] This application provides a data processing device for wind resource assessment and directional calculation, wherein the spectrum analysis module 53 may include:

[0130] The first acquisition unit is used to acquire the target physical quantity within a preset percentage of the total number of iterations at the end of the CFD directional calculation, so as to form a sequence of target physical quantities.

[0131] The identification unit is used to identify peaks and valleys in the target physical quantity sequence.

[0132] The second acquisition unit is used to acquire the target physical quantity within the change period that is an integer multiple of the tail end of the CFD directional calculation, based on the iteration step where the peaks and valleys of the target physical quantity sequence are located, if the number of peaks and valleys of the target physical quantity sequence is greater than or equal to 2.

[0133] The data processing device for wind resource assessment and directional calculation provided in this application embodiment may further include a spectrum analysis module 53 comprising:

[0134] The third determining unit is used to determine that the CFD directional calculation is stable and convergent if the number of peaks and valleys in the target physical quantity sequence is less than 2, and outputs the target physical quantity of the CFD directional calculation in the final iteration step.

[0135] This application provides a data processing device for wind resource assessment and directional calculation, wherein the calculation module 51 may include:

[0136] Computing unit, used to utilize Calculate the convergence rate at the Mth iteration step; where, Let θ be the convergence rate, n be the first preset iteration step, and θ be the convergence rate. i Let be the target physical quantity in the i-th iteration step. This represents the average value of the target physical quantity within the first preset iteration step preceding the Mth iteration step. It is the average value of the target physical quantity within the first preset iteration step.

[0137] The data processing apparatus for wind resource assessment and directional calculation provided in this application embodiment may further include:

[0138] The first determining module is used to determine that the CFD directional calculation is stable and converged if the maximum amplitude is less than the minimum value in the preset range, and output the target physical quantity of the CFD directional calculation in the final iteration step.

[0139] The second determining module is used to determine that the CFD directional calculation has not converged if the maximum amplitude value is greater than the maximum value in the preset range, and to output the target physical quantity of the CFD directional calculation in the final iteration step.

[0140] This application also provides a data processing device for wind resource assessment and directional calculation, see [link to relevant documentation]. Figure 6 It shows a schematic diagram of the structure of a data processing device for wind resource assessment directional calculation provided in an embodiment of this application, which may include:

[0141] Memory 61 is used to store computer programs;

[0142] When processor 62 executes a computer program stored in memory 61, it can perform the following steps:

[0143] Based on the target physical quantities in the first preset iteration step of the CFD directional calculation in the wind resource assessment, and the target physical quantities in the first preset iteration step prior to the current iteration step, the convergence rate in the current iteration step is calculated. Based on the convergence rate in the second preset iteration step after the CFD directional calculation, it is determined whether the CFD directional calculation is stable convergence. If it is not stable convergence, the target physical quantities within the change period that is an integer multiple of the tail end of the CFD directional calculation are obtained, and the spectrum analysis is performed on the target physical quantities within the integer multiple change period. The change period is the change period of the target physical quantity. If the maximum amplitude of the waveform obtained from the spectrum analysis is within a preset range, it is determined whether the CFD directional calculation is fluctuating convergence based on the waveform. If it is fluctuating convergence, the target physical quantity directional calculation result is obtained based on the target physical quantities within the change period.

[0144] This application embodiment also provides a readable storage medium storing a computer program, which, when executed by a processor, can perform the following steps:

[0145] Based on the target physical quantities in the first preset iteration step of the CFD directional calculation in the wind resource assessment, and the target physical quantities in the first preset iteration step prior to the current iteration step, the convergence rate in the current iteration step is calculated. Based on the convergence rate in the second preset iteration step after the CFD directional calculation, it is determined whether the CFD directional calculation is stable convergence. If it is not stable convergence, the target physical quantities within the change period that is an integer multiple of the tail end of the CFD directional calculation are obtained, and the spectrum analysis is performed on the target physical quantities within the integer multiple change period. The change period is the change period of the target physical quantity. If the maximum amplitude of the waveform obtained from the spectrum analysis is within a preset range, it is determined whether the CFD directional calculation is fluctuating convergence based on the waveform. If it is fluctuating convergence, the target physical quantity directional calculation result is obtained based on the target physical quantities within the change period.

[0146] The readable storage medium may include various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0147] For a description of the relevant parts of the data processing device, equipment and readable storage medium in the wind resource assessment directional calculation provided in this application, please refer to the detailed description of the corresponding part in the data processing method in the wind resource assessment directional calculation provided in the embodiments of this application, and will not be repeated here.

[0148] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that the elements inherent in a process, method, article, or apparatus that includes a list of elements are included. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element. Additionally, portions of the technical solutions provided in the embodiments of this application that are consistent with the implementation principles of corresponding technical solutions in the prior art have not been described in detail to avoid excessive elaboration.

[0149] The above description of the disclosed embodiments enables those skilled in the art to make or use this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for data processing in wind resource assessment directional calculations, characterized by, The method comprises the following steps: calculating the convergence rate at the current iteration step according to the target physical quantity in the first preset iteration step before the CFD directional calculation in the wind resource assessment and the target physical quantity in the first preset iteration step from the current iteration step; judging whether the CFD directional calculation is stable convergence according to the convergence rate in the second preset iteration step after the CFD directional calculation; wherein the convergence rate in the second preset iteration step is the convergence rate at each iteration step in the second preset iteration step from the final iteration step of the CFD directional calculation; if it is not stable convergence, obtaining the target physical quantity in the integer multiple of the change period at the tail end of the CFD directional calculation, and performing frequency spectrum analysis on the target physical quantity in the integer multiple of the change period; the change period is the change period of the target physical quantity; if the maximum amplitude of the waveform obtained by the frequency spectrum analysis is in the preset range, judging whether the CFD directional calculation is fluctuation convergence according to the waveform; if it is fluctuation convergence, obtaining the target physical quantity directional calculation result according to the target physical quantity in the change period.

2. The method of claim 1, wherein, judging whether the CFD directional calculation is fluctuation convergence according to the waveform, comprising: screening out noise signals in the waveform; judging whether the waveform after screening out noise signals has multiple main frequencies; if not, determining that the CFD directional calculation is fluctuation convergence.

3. The method of claim 2, wherein, if the waveform after screening out noise signals has multiple main frequencies, further comprising: determining that the CFD directional calculation has not converged, and outputting the target physical quantity at the final iteration step of the CFD directional calculation.

4. The method of claim 1, wherein, obtaining the target physical quantity in the integer multiple of the change period at the tail end of the CFD directional calculation, comprising: obtaining the target physical quantity in the integer multiple of the change period at the tail end of the CFD directional calculation, comprising: obtaining the target physical quantity in the integer multiple of the change period at the tail end of the CFD directional calculation, comprising: obtaining the target physical quantity in the integer multiple of the change period at the tail end of the CFD directional calculation, comprising:

5. The method of claim 4, wherein, further comprising: if the number of peaks and valleys of the target physical quantity sequence is less than 2, determining that the CFD directional calculation is stable convergence, and outputting the target physical quantity at the final iteration step of the CFD directional calculation.

6. The method of claim 1, wherein, calculating the convergence rate at the current iteration step according to the target physical quantity in the first preset iteration step before the CFD directional calculation in the wind resource assessment and the target physical quantity in the first preset iteration step from the current iteration step, comprising: Utilizing Computing the first Convergence rate at the iteration step; in, Let be the convergence ratio. This is the first preset iteration step. For the first The target physical quantity under the iteration step , For from the first The average value of the target physical quantity within the first preset iteration step forward. , The average value of the target physical quantity within the first preset iteration step. The target physical quantity is defined in the j-th iteration step within the first preset iteration step.

7. The method of claim 1, wherein, further comprising: if the maximum amplitude is less than the minimum value in the preset range, determining that the CFD directional calculation is stable convergence, and outputting the target physical quantity at the final iteration step of the CFD directional calculation. If the maximum amplitude is greater than the maximum value in the preset range, it is determined that the CFD directional calculation does not converge, and the target physical quantity of the CFD directional calculation at the final iteration step is output.

8. A data processing apparatus for wind resource assessment directional calculations, characterized by, The method comprises the steps of: calculating a convergence rate at the current iteration step according to the target physical quantity of the CFD directional calculation in the first preset iteration steps in the wind resource assessment and the target physical quantity from the current iteration step to the first preset iteration steps; wherein the target physical quantity in the first preset iteration steps is the target physical quantity at each iteration step in the first preset iteration steps, and the size of the first preset iteration step is set according to experience or actual needs; a first judging module for judging whether the CFD directional calculation is stable convergence according to the convergence rate of the CFD directional calculation in the second preset iteration steps; wherein the convergence rate in the second preset iteration steps is the convergence rate at each iteration step in the second preset iteration steps starting from the final iteration step of the CFD directional calculation, and the second preset iteration is set according to experience or actual needs; a spectrum analysis module for obtaining the target physical quantity in the change period which is an integer multiple of the tail end of the CFD directional calculation and performing spectrum analysis on the target physical quantity in the integer multiple change period if it is not stable convergence; the change period is the change period of the target physical quantity; a second judging module for judging whether the CFD directional calculation is fluctuation convergence according to the waveform obtained by spectrum analysis if the maximum amplitude of the waveform is in the preset range; a result obtaining module for obtaining the target physical quantity directional calculation result according to the target physical quantity in the change period if it is fluctuation convergence.

9. A data processing device for wind resource assessment directional calculations, characterized by, The method comprises the steps of: a memory for storing a computer program; a processor for executing the computer program to realize the steps of the wind resource assessment directional calculation data processing method according to any one of claims 1 to 7.

10. A readable storage medium, characterized by, The readable storage medium stores a computer program, and the computer program is executed by the processor to realize the steps of the wind resource assessment directional calculation data processing method according to any one of claims 1 to 7.

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