Extreme coherent gust determination method and device, controller, medium and product
Patent Information
- Application Number
- CN202310922140.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2023-07-26
- Publication Date
- 2025-01-28
AI Technical Summary
When determining whether the gust is an extreme coherent gust, the prior art fails to fully consider the geographical differences in the wind turbine unit, resulting in inaccurate determination of the extreme coherent gust.
By obtaining the wind status parameters and sampling frequencies in the preset historical period of the wind farm, set the gusts period to determine the wind speed and wind proportion factors, the gust -style energy fit parameter, and combine the Gumbel extreme distribution algorithm and the DIR function to identify the target gusts continuously The wind speed direction within the period is extreme coherent gusts.
Improve the identification accuracy of extreme coherent gusts, and ensure the accuracy of load analysis in the design of the wind generator set.
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Figure CN119375979A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the technical field of wind power generation, and in particular to an extreme coherent gust determination method, device, controller, medium and product. Background Art
[0002] Coherent gusts are gusts in which wind speed and wind direction continue to change monotonically within a certain period of time. Extreme coherent gusts are extreme cases of coherent gusts that occur within a specific recurrence period. Since extreme coherent gusts have the characteristics of large changes in wind direction, fast changes in wind speed, and uncertain duration, this wind condition is used as a load design condition in the IEC61400-1:2019 standard, the GL IV-1-4:2010 standard, and the EC61400-3:2019 standard. It can be seen that in the design of wind turbines, the impact of extreme coherent gusts on the load of the unit is crucial.
[0003] In the prior art, when determining whether a gust is an extreme coherent gust, the parameter values of the characteristic parameters of the extreme coherent gusts in the design standards of the wind turbine generator set (IEC61400-1:2019, GL IV-1-4:2010, EC61400-3:2019) are used to determine whether the gust is an extreme coherent gust. However, the parameter values of the above characteristic parameters do not take into account the influence caused by the regional differences of the wind turbine generator set, which leads to inaccurate determination of the extreme coherent gusts. Summary of the invention
[0004] The purpose of the embodiments of the present application is to provide a method, device, controller, medium and product for determining extreme coherent gusts, so as to accurately determine extreme coherent gusts.
[0005] The technical solution of this application is as follows:
[0006] In a first aspect, a method for determining an extreme coherent gust is provided, wherein the method comprises:
[0007] Obtaining wind condition parameters within a preset historical time period of the wind farm and the sampling frequency of the wind condition parameters; wherein the wind condition parameters include: wind speed amplitude and wind direction amplitude;
[0008] Based on the sampling frequency, setting a gust duration period;
[0009] Based on the wind speed amplitude and the wind direction amplitude, determine the wind speed and wind direction proportional factor within the preset historical time period, the wind speed and wind direction proportional parameter corresponding to each gust duration period within the preset historical time period, and the gust energy fitting parameter; the wind speed and wind direction proportional factor is used to characterize the ratio of the maximum wind speed change amplitude and the maximum wind direction change amplitude within the gust duration period within the preset historical time period, and the wind speed and wind direction proportional parameter is used to characterize the ratio of the wind speed change amplitude and the wind direction change amplitude within the same gust duration period;
[0010] When it is determined that the wind speed and direction proportional factor and the wind speed and direction proportional parameter within the target gust duration period satisfy a preset corresponding relationship, and the gust energy fitting parameter within the target gust duration period satisfies a preset condition, it is determined that the wind speed and direction within the target gust duration period is an extreme coherent gust, wherein the target gust duration period is at least one of different gust duration periods.
[0011] In one example, the preset corresponding relationship is: the wind speed and wind direction proportional parameter within the target gust duration period is equal to the wind speed and wind direction proportional factor;
[0012] The preset condition is that the gust energy fitting parameter within the target gust duration period is the maximum value of the gust energy fitting parameters within a plurality of different gust duration periods.
[0013] In one example, the target gust duration period is multiple, and after determining that the wind speed and wind direction within the target gust duration period is an extreme coherent gust, the method further includes:
[0014] Using a Gumbel extreme value distribution algorithm to fit the wind speed amplitudes within a plurality of target gust duration periods, a distribution parameter of a Gumbel extreme value distribution function for characterizing the relationship between time and the wind speed amplitude is obtained, so as to obtain a Gumbel extreme value distribution function for characterizing the relationship between time and the wind speed amplitude;
[0015] Fitting the wind speed amplitude and the wind direction amplitude within a plurality of target gust duration periods to obtain a second corresponding relationship between the wind speed amplitude and the wind direction amplitude;
[0016] Based on the Gumbel extreme value distribution function and the second corresponding relationship, target wind speed amplitudes and target wind direction amplitudes of extreme coherent gusts with different gust duration periods within a target recurrence period are obtained.
[0017] In one example, fitting the wind speed amplitudes and the wind direction amplitudes within the target gust duration periods to obtain a second corresponding relationship between the wind speed amplitudes and the wind direction amplitudes includes:
[0018] The wind speed amplitude and the wind direction amplitude within a plurality of the target gust duration periods are fitted using the least squares method to obtain function parameters of a Dir function for characterizing the relationship between the wind speed amplitude and the wind direction amplitude, so as to obtain a Dir function for describing the relationship between the wind speed amplitude and the wind direction amplitude.
[0019] In one example, obtaining target wind speed amplitudes and target wind direction amplitudes of extreme coherent gusts with different gust duration periods within a target recurrence period based on the Gumbel extreme value distribution function and the second corresponding relationship includes:
[0020] Based on the Gumbel extreme value distribution function, target wind speed amplitudes of extreme coherent gusts with different gust durations within a target return period are obtained;
[0021] Based on the target wind speed amplitude and the second corresponding relationship, the target wind direction amplitude of the extreme coherent gusts with different gust duration periods within the target recurrence period is obtained.
[0022] In one example, determining the gust energy fitting parameter corresponding to each gust duration period in the preset historical time period based on the wind speed amplitude and the wind direction amplitude includes:
[0023] Based on the wind speed amplitude and the wind direction amplitude, the gust energy fitting parameter corresponding to each gust duration period in the preset historical time period is determined according to the following formula:
[0024]
[0025] Among them, V(t i +Δt) is (t i +Δt) time, V(t i ) is (t i ) moment, D(t i +Δt) is (t i +Δt), D(t i ) is (t i ) wind direction amplitude at time i = 1, 2, 3..., 0 < t i is less than T, T is the preset historical time period, and EN(i) is the gust energy fitting parameter corresponding to the i-th gust duration period in the preset historical time period.
[0026] In a second aspect, a device for determining an extreme coherent gust is provided, wherein the method comprises:
[0027] An acquisition module is used to acquire wind condition parameters and a sampling frequency of the wind condition parameters within a preset historical time period of the wind farm; wherein the wind condition parameters include: wind speed amplitude and wind direction amplitude;
[0028] A setting module, used for setting a gust duration period based on the sampling frequency;
[0029] A first determination module is used to determine the wind speed and wind direction proportional factor within the preset historical time period, the wind speed and wind direction proportional parameter corresponding to each gust duration period within the preset historical time period, and the gust energy fitting parameter based on the wind speed amplitude and the wind direction amplitude; the wind speed and wind direction proportional factor is used to characterize the ratio of the maximum wind speed change amplitude and the maximum wind direction change amplitude within the gust duration period within the preset historical time period, and the wind speed and wind direction proportional parameter is used to characterize the ratio of the wind speed change amplitude and the wind direction change amplitude within the same gust duration period;
[0030] The second determination module is used to determine that the wind speed and direction within the target gust duration period are extreme coherent gusts when it is determined that the wind speed and direction proportional factor and the wind speed and direction proportional parameter within the target gust duration period satisfy a preset corresponding relationship, and the gust energy fitting parameter within the target gust duration period satisfies a preset condition, wherein the target gust duration period is at least one of different gust duration periods.
[0031] In a third aspect, an embodiment of the present application provides an extreme coherent gust determination controller, which includes a processor, a memory, and a program or instruction stored in the memory and executable on the processor, wherein the program or instruction, when executed by the processor, implements the steps of the extreme coherent gust determination method described in any one of the embodiments of the present application.
[0032] In a fourth aspect, an embodiment of the present application provides a readable storage medium, on which a program or instruction is stored. When the program or instruction is executed by a processor, the steps of the method for determining extreme coherent gusts described in any one of the embodiments of the present application are implemented.
[0033] In a fifth aspect, an embodiment of the present application provides a computer program product. When instructions in the computer program product are executed by a processor of an electronic device, the electronic device is able to perform the steps of the extreme coherent gust determination method described in any one of the embodiments of the present application.
[0034] The technical solution provided by the embodiments of the present application brings at least the following beneficial effects:
[0035] In an embodiment of the present application, wind condition parameters and a sampling frequency of the wind condition parameters within a preset historical time period of a wind farm are obtained, and then a gust duration period is set based on the sampling frequency. Based on the wind speed amplitude and the wind direction amplitude, a wind speed and direction proportional factor within the preset historical time period, a wind speed and direction proportional parameter corresponding to each gust duration period within the preset historical time period, and a gust energy fitting parameter are determined. When it is determined that the wind speed and direction proportional factor and the wind speed and direction proportional parameter within the target gust duration period satisfy a preset corresponding relationship, and the gust energy fitting parameter within the target gust duration period satisfies a preset condition, it is determined that the wind speed and direction within the target gust duration period are extreme coherent gusts. Since the acquired wind condition parameters and the sampling frequency of the wind condition parameters are the actual wind condition parameters within the preset historical time period of the wind farm, and when identifying extreme coherent gusts, a gust energy fitting parameter is proposed, and the gust energy is used as one of the identification criteria, and combined with the wind speed and direction proportional factor to identify extreme coherent gusts, the identification accuracy of extreme coherent gusts is improved.
[0036] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS
[0037] The drawings herein are incorporated into the specification and constitute a part of the specification, illustrate embodiments consistent with the present application, and together with the specification are used to explain the principles of the present application, and do not constitute an improper limitation on the present application.
[0038] Figure 1 It is one of the flow charts of a method for determining an extreme coherent gust provided in an embodiment of the first aspect of the present application;
[0039] Figure 2 This is a second flow chart of a method for determining an extreme coherent gust provided in an embodiment of the first aspect of the present application;
[0040] Figure 3 It is a structural schematic diagram of an extreme coherent gust determination device provided by an embodiment of the second aspect of the present application;
[0041] Figure 4 It is a structural schematic diagram of an extreme coherent gust determination controller provided in an embodiment of the third aspect of the present application. DETAILED DESCRIPTION
[0042] In order to make those of ordinary skill in the art better understand the technical scheme of the present application, the technical scheme in the embodiments of the present application will be clearly and completely described below in conjunction with the accompanying drawings. It should be understood that the specific embodiments described herein are only intended to explain the present application, rather than to limit the present application. For those skilled in the art, the present application can be implemented without the need for some of these specific details. The following description of the embodiments is only to provide a better understanding of the present application by illustrating the examples of the present application.
[0043] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present application described here can be implemented in an order other than those illustrated or described here. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. On the contrary, they are only examples consistent with some aspects of the present application as detailed in the attached claims.
[0044] As described in the background technology section, there is a problem of inaccurate determination of extreme coherent gusts in the prior art. In order to solve the above problem, the embodiments of the present application provide a method, device, controller, medium and product for determining extreme coherent gusts, by obtaining wind condition parameters and the sampling frequency of wind condition parameters in a preset historical time period of the wind farm, and then setting the gust duration period based on the sampling frequency, and determining the wind speed and wind direction proportional factor in the preset historical time period, the wind speed and wind direction proportional parameters corresponding to each gust duration period in the preset historical time period, and the gust energy fitting parameters based on the wind speed amplitude and the wind direction amplitude, and then determining the wind speed and wind direction. When the proportional factor and the proportional parameter of wind speed and direction in the target gust duration period satisfy the preset corresponding relationship, and the gust energy fitting parameter in the target gust duration period satisfies the preset conditions, the wind speed and direction in the target gust duration period is determined to be an extreme coherent gust. Since the acquired wind condition parameters and the sampling frequency of the wind condition parameters are the actual wind condition parameters in the preset historical time period of the wind farm, and when identifying extreme coherent gusts, the gust energy fitting parameter is proposed, the gust energy is used as one of the identification criteria, and combined with the wind speed and direction proportional factor to identify extreme coherent gusts, the identification accuracy of extreme coherent gusts is improved.
[0045] The following describes in detail the method for determining extreme coherent gusts provided in the embodiment of the present application through specific embodiments and application scenarios in conjunction with the accompanying drawings.
[0046] Figure 1 FIG. 1 is a flow chart of an extremely coherent gust determination method provided in an embodiment of the present application. The execution subject of the extremely coherent gust determination method may be a server. Figure 1 As shown, the extreme coherent gust determination method provided in the embodiment of the present application may include steps 110 to 140.
[0047] Step 110: Obtain wind condition parameters and a sampling frequency of the wind condition parameters within a preset historical time period of the wind farm; wherein the wind condition parameters include: wind speed amplitude and wind direction amplitude.
[0048] The preset historical time period may be a period before the current time. The wind condition parameters may be parameters used to describe the wind conditions in the preset historical time period of the wind farm, and may specifically include wind speed amplitude and wind direction amplitude.
[0049] In some embodiments of the present application, the wind condition parameters and the sampling frequency of the wind condition parameters within a preset historical time period of the wind farm may be obtained from the historical records of the wind farm.
[0050] Step 120: Set the gust duration period based on the sampling frequency.
[0051] In some embodiments of the present application, according to the sampling frequency, the gust duration can be obtained based on the following formula (1):
[0052] Δt=nt0 (1)
[0053] Wherein, Δt is the set gust duration period, n=2,3,4,…; t0=1 / f, f is the sampling frequency.
[0054] It should be noted that in the embodiment of the present application, f is preferably greater than or equal to 1 Hz.
[0055] Step 130: Based on the wind speed amplitude and the wind direction amplitude, determine the wind speed and wind direction proportional factor within a preset historical time period, the wind speed and wind direction proportional parameter corresponding to each gust duration period within the preset historical time period, and the gust energy fitting parameter.
[0056] The wind speed and wind direction proportional factor is used to characterize the ratio of the maximum wind speed change amplitude to the maximum wind direction change amplitude during the gust duration period within a preset historical time period.
[0057] The wind speed and wind direction ratio parameter is used to characterize the ratio of the wind speed change amplitude to the wind direction change amplitude within the same gust duration period.
[0058] In some embodiments of the present application, based on the wind speed amplitude and the wind direction amplitude, the wind speed and wind direction proportional factor within a preset historical time period can be determined according to the following formula (2):
[0059]
[0060] Wherein, SF is the wind speed and direction proportional factor, |V(t+Δt)-V(t)| is the wind speed change amplitude within the gust duration period within the preset historical time period, max|V(t+Δt)-V(t)| is the maximum wind speed change amplitude within the gust duration period within the preset historical time period, |D(t+Δt)-D(t)| is the wind direction change amplitude within the gust duration period within the preset historical time period, and max|D(t+Δt)-D(t)| is the maximum wind direction change amplitude within the gust duration period within the preset historical time period.
[0061] In some embodiments of the present application, based on the wind speed amplitude and the wind direction amplitude, the wind speed and wind direction proportional parameter corresponding to each gust duration period in the preset historical time period can be determined according to the following formula (3):
[0062]
[0063] Among them, k i is the wind speed and direction proportional parameter corresponding to the duration of the ith gust in the preset historical time period, |V(t i +Δt)-V(t i )| is the wind speed change amplitude during the duration of the i-th gust in the preset historical time period, |D(t i +Δt)-D(t i )| is the wind direction change amplitude during the duration of the i-th gust within the preset historical time period.
[0064] In some embodiments of the present application, determining the gust energy fitting parameter corresponding to each gust duration period in a preset historical time period based on the wind speed amplitude and the wind direction amplitude may specifically include:
[0065] Based on the wind speed amplitude and wind direction amplitude, the gust energy fitting parameter corresponding to each gust duration period in the preset historical time period can be determined according to the following formula (4):
[0066]
[0067] Among them, V(t i +Δt) is (t i +Δt) time, V(t i ) is (t i ) moment, D(t i +Δt) is (t i +Δt), D(t i ) is (t i ) wind direction amplitude at time i = 1, 2, 3..., 0 < t iis less than T, T is the preset historical period, and EN(i) is the gust energy fitting parameter corresponding to the i-th gust duration period in the preset historical time period.
[0068] In the embodiment of the present application, the above formulas (2)-(4) can be used to accurately determine the wind speed and wind direction proportional factor within a preset historical time period, the wind speed and wind direction proportional parameter corresponding to each gust duration period within the preset historical time period, and the gust energy fitting parameter based on the wind speed amplitude and wind direction amplitude.
[0069] Step 140: When it is determined that the wind speed and direction proportional factor and the wind speed and direction proportional parameter within the target gust duration period satisfy a preset corresponding relationship, and the gust energy fitting parameter within the target gust duration period satisfies a preset condition, it is determined that the wind speed and direction within the target gust duration period is an extreme coherent gust.
[0070] The target gust duration period may be at least one of different gust duration periods.
[0071] The preset corresponding relationship can be a preset setting. If it is to be determined that the wind speed and direction within the target gust duration period is an extreme coherent gust, then the wind speed and direction proportional factor and the wind speed and direction proportional parameter within the target gust duration period must satisfy the corresponding relationship. The specific preset corresponding relationship can be that the wind speed and direction proportional parameter within the target gust duration period is equal to the wind speed and direction proportional factor.
[0072] The preset condition may be a preset condition that the gust energy fitting parameter within the target gust duration period must satisfy if the wind speed and wind direction within the target gust duration period is to be determined as an extreme coherent gust. The specific preset condition may be that the gust energy fitting parameter within the target gust duration period is the maximum value of the gust energy fitting parameters within multiple different gust duration periods.
[0073] In some embodiments of the present application, when determining k i =SF, and EN(i)=ENmax, it is determined that the wind speed and direction during the i-th gust duration period are extreme coherent gusts.
[0074] In some embodiments of the present application, after the extreme coherent gusts are determined, the wind speed amplitudes and wind direction amplitudes of the extreme coherent gusts for different gust durations within different recurrence periods can be obtained according to the wind speed amplitudes and wind direction amplitudes of the extreme coherent gusts within a preset historical time period. The specific implementation method is as follows:
[0075] In some embodiments of the present application, there may be multiple target gust duration periods. After step 140, the above method may further include:
[0076] The wind speed amplitudes in multiple target gust duration periods are fitted using the Gumbel extreme value distribution algorithm to obtain the distribution parameters of the Gumbel extreme value distribution function used to characterize the relationship between time and wind speed amplitude, so as to obtain the Gumbel extreme value distribution function used to characterize the relationship between time and wind speed amplitude;
[0077] Fitting the wind speed amplitude and wind direction amplitude within a plurality of target gust duration periods to obtain a second corresponding relationship between the wind speed amplitude and the wind direction amplitude;
[0078] Based on the Gumbel extreme value distribution function and the second corresponding relationship, the target wind speed amplitude and target wind direction amplitude of extreme coherent gusts with different gust duration periods within the target recurrence period are obtained.
[0079] The second corresponding relationship may be used to characterize the corresponding relationship between the wind speed amplitude and the wind direction amplitude.
[0080] The target recurrence period can be any recurrence period desired by the user, and the specific period can be selected according to the user's needs, and is not limited here.
[0081] The target wind speed amplitude may be the wind speed amplitude of the extreme coherent gusts corresponding to the extreme coherent gusts that last for different gust duration periods within the target recurrence period.
[0082] The target wind direction amplitude may be the wind direction amplitude corresponding to the extreme coherent gusts that last for different gust duration periods within the target recurrence period.
[0083] In some embodiments of the present application, the Gumbel extreme value distribution algorithm can be used to fit the wind speed amplitudes within multiple target gust duration periods to obtain distribution parameters α and β of the Gumbel extreme value distribution function used to characterize the relationship between time and wind speed amplitude, so as to obtain the Gumbel extreme value distribution function F(x) = exp(-exp(-α(x-β)) used to characterize the relationship between time and wind speed amplitude.
[0084] Then, the wind speed amplitude and wind direction amplitude within multiple target gust duration periods are fitted to obtain the second corresponding relationship between the wind speed amplitude and the wind direction amplitude. Then, based on the Gumbel extreme value distribution function and the second corresponding relationship, the target wind speed amplitude and target wind direction amplitude of extreme coherent gusts with different gust duration periods within the target recurrence period can be obtained.
[0085] In an embodiment of the present application, the wind speed amplitudes within multiple target gust duration periods are fitted by using the Gumbel extreme value distribution algorithm to obtain distribution parameters of the Gumbel extreme value distribution function for characterizing the relationship between time and wind speed amplitude, so as to obtain the Gumbel extreme value distribution function for characterizing the relationship between time and wind speed amplitude, and then the wind speed amplitudes and wind direction amplitudes within multiple target gust duration periods are fitted to obtain a second corresponding relationship between the wind speed amplitude and the wind direction amplitude, and then based on the Gumbel extreme value distribution function and the second corresponding relationship, the target wind speed amplitude and target wind direction amplitude of extreme coherent gusts for different gust duration periods within the target recurrence period can be obtained.
[0086] In some embodiments of the present application, in order to further accurately obtain the target wind speed amplitude and target wind direction amplitude of the extreme coherent gusts that last for different gust durations within the target recurrence period, the wind speed amplitude and wind direction amplitude within multiple target gust duration periods are fitted to obtain the second corresponding relationship between the wind speed amplitude and the wind direction amplitude, which may specifically include:
[0087] The least squares method is used to fit the wind speed amplitude and wind direction amplitude in multiple target gust duration periods to obtain the function parameters of the Dir function used to characterize the relationship between the wind speed amplitude and the wind direction amplitude, so as to obtain the Dir function used to describe the relationship between the wind speed amplitude and the wind direction amplitude.
[0088] In some embodiments of the present application, the least squares method can be used to fit the wind speed amplitude and wind direction amplitude within multiple target gust duration periods to obtain function parameters a and b of the Dir function used to characterize the relationship between the wind speed amplitude and the wind direction amplitude, and then obtain the Dir function Dcg=a*Vcg+b used to describe the relationship between the wind speed amplitude and the wind direction amplitude, where Dcg is the wind direction amplitude and Vcg is the wind speed amplitude.
[0089] In an embodiment of the present application, by using the least squares method to fit the wind speed amplitude and wind direction amplitude within multiple target gust duration periods, the function parameters of the Dir function used to characterize the relationship between the wind speed amplitude and the wind direction amplitude can be obtained, and then the Dir function used to describe the relationship between the wind speed amplitude and the wind direction amplitude can be obtained. In this way, based on the Dir function, the target wind speed amplitude and target wind direction amplitude of extreme coherent gusts for different gust duration periods within the target recurrence period can be obtained.
[0090] In some embodiments of the present application, in order to accurately obtain the target wind speed amplitude and target wind direction amplitude of the extreme coherent gusts that continue for different gust durations within the target recurrence period, the target wind speed amplitude and target wind direction amplitude of the extreme coherent gusts that continue for different gust durations within the target recurrence period based on the Gumbel extreme value distribution function and the second corresponding relationship may specifically include:
[0091] Based on the Gumbel extreme value distribution function, the target wind speed amplitude of extreme coherent gusts with different gust durations within the target return period is obtained;
[0092] Based on the target wind speed amplitude and the second corresponding relationship, the target wind direction amplitude of the extreme coherent gusts with different gust duration periods within the target recurrence period is obtained.
[0093] In some embodiments of the present application, after obtaining the Gumbel extreme value distribution function and the second corresponding relationship, the target wind speed amplitude of extreme coherent gusts that continue for different gust durations within the target recurrence period can be obtained based on the Gumbel extreme value distribution function, and then the target wind direction amplitude of extreme coherent gusts that continue for different gust durations within the target recurrence period can be obtained based on the target wind speed amplitude and the second corresponding relationship.
[0094] In an embodiment of the present application, after determining the Gumbel extreme value distribution function, the target wind speed amplitude of the extreme coherent gusts corresponding to a certain duration within a certain recurrence period can be obtained, and then the target wind direction amplitude of the extreme coherent gusts corresponding to the duration within the recurrence period can be determined based on the target wind speed amplitude and the second corresponding relationship. In this way, the target wind speed amplitude and target wind direction amplitude of the extreme coherent gusts corresponding to any duration within any recurrence period can be obtained, and the target wind speed amplitude and target wind direction amplitude of the extreme coherent gusts corresponding to any duration within any recurrence period can be obtained. The target wind speed amplitude and target wind direction amplitude of the extreme coherent gusts in the non-gust duration periods within different recurrence periods of all wind farms are not defined according to the standard, which improves the accuracy of the evaluation of the target wind speed amplitude and target wind direction amplitude of the extreme coherent gusts in the non-gust duration periods within different recurrence periods of the wind farm.
[0095] In order to better understand the technical solution of the present application, the technical solution of the present application is described in detail with reference to a specific scenario. Figure 2 , Figure 2 FIG. 1 is a flow chart of another method for determining extremely coherent gusts provided in an embodiment of the present application. Figure 2 As shown, the method for determining extreme coherent gusts provided in the embodiment of the present application may include the following steps:
[0096] Step 210: Obtain wind condition parameters and a sampling frequency of the wind condition parameters within a preset historical time period of the wind farm.
[0097] Step 210 here is consistent with step 110 in the above embodiment and will not be described again.
[0098] Step 220: based on the sampling frequency, set the gust duration period; based on the wind speed amplitude and the wind direction amplitude, determine the wind speed and direction proportional factor within the preset historical time period, the wind speed and direction proportional parameter corresponding to each gust duration period within the preset historical time period, and the gust energy fitting parameter; when it is determined that the wind speed and direction proportional factor and the wind speed and direction proportional parameter within the target gust duration period satisfy a preset corresponding relationship, and the gust energy fitting parameter within the target gust duration period satisfies a preset condition, determine that the wind speed and direction within the target gust duration period is an extreme coherent gust.
[0099] Step 220 here is consistent with step 120 to step 140 in the above embodiment, and will not be repeated here.
[0100] Step 230, using the Gumbel extreme value distribution algorithm to fit the wind speed amplitudes within multiple target gust duration periods to obtain the Gumbel extreme value distribution function; fitting the wind speed amplitudes and wind direction amplitudes within multiple target gust duration periods to obtain a second corresponding relationship between the wind speed amplitude and the wind direction amplitude; and calculating the target wind speed amplitude and target wind direction amplitude of extreme coherent gusts that last for different gust duration periods within the target recurrence period.
[0101] Step 230 here is consistent with the process of fitting the wind speed amplitudes within multiple target gust duration periods using the Gumbel extreme value distribution algorithm in the above embodiment to obtain the distribution parameters of the Gumbel extreme value distribution function used to characterize the relationship between time and wind speed amplitude, so as to obtain the Gumbel extreme value distribution function used to characterize the relationship between time and wind speed amplitude; fitting the wind speed amplitudes and wind direction amplitudes within multiple target gust duration periods to obtain the second corresponding relationship between the wind speed amplitude and the wind direction amplitude; and obtaining the target wind speed amplitude and target wind direction amplitude of extreme coherent gusts of different gust duration periods within the target recurrence period based on the Gumbel extreme value distribution function and the second corresponding relationship, which will not be repeated here.
[0102] In the embodiment of the present application, based on the actual wind field measurement data, the coherent gusts can be identified from the perspective of gust energy and in combination with the characteristics of the coherent gusts, and the wind speed amplitude set and wind direction amplitude set corresponding to different durations can be obtained (i.e., the target wind speed amplitude set and the target wind direction amplitude set of extreme coherent gusts in different gust duration periods within different recurrence periods), and the evaluation of the duration, wind speed amplitude and wind direction amplitude of the extreme coherent gusts can be realized, which is of great significance for the identification of the characteristic parameters of the extreme coherent gusts in the wind farm site. The scheme of the embodiment of the present application is crucial to identifying dangerous loads and improving the economy, reliability and safety of wind turbine design.
[0103] It should be noted that the extreme coherent gust determination method provided in the embodiment of the present application may be executed by an extreme coherent gust determination device, or a control module in the extreme coherent gust determination device for executing the extreme coherent gust determination method.
[0104] Based on the same inventive concept as the above-mentioned method for determining extreme coherent gusts, the present application also provides a device for determining extreme coherent gusts. Figure 3 The extreme coherent gust determination device provided in the embodiment of the present application is described in detail.
[0105] Figure 3 It is a schematic structural diagram of an extreme coherent gust determination device according to an exemplary embodiment.
[0106] like Figure 3 As shown, the extreme coherent gust determining device 300 may include:
[0107] The acquisition module 310 is used to acquire wind condition parameters and the sampling frequency of the wind condition parameters within a preset historical time period of the wind farm; wherein the wind condition parameters include: wind speed amplitude and wind direction amplitude;
[0108] A setting module 320, configured to set a gust duration period based on the sampling frequency;
[0109] A first determination module 330 is used to determine the wind speed and wind direction proportional factor within the preset historical time period, the wind speed and wind direction proportional parameter corresponding to each gust duration period within the preset historical time period, and the gust energy fitting parameter based on the wind speed amplitude and the wind direction amplitude; the wind speed and wind direction proportional factor is used to characterize the ratio of the maximum wind speed change amplitude and the maximum wind direction change amplitude within the gust duration period within the preset historical time period, and the wind speed and wind direction proportional parameter is used to characterize the ratio of the wind speed change amplitude and the wind direction change amplitude within the same gust duration period;
[0110] The second determination module 340 is used to determine that the wind speed and direction within the target gust duration period are extreme coherent gusts when it is determined that the wind speed and direction proportional factor and the wind speed and direction proportional parameter within the target gust duration period satisfy a preset corresponding relationship, and the gust energy fitting parameter within the target gust duration period satisfies a preset condition, wherein the target gust duration period is at least one of different gust duration periods.
[0111] In an embodiment of the present application, wind condition parameters and a sampling frequency of the wind condition parameters within a preset historical time period of a wind farm are obtained, and then a gust duration period is set based on the sampling frequency. Based on the wind speed amplitude and the wind direction amplitude, a wind speed and direction proportional factor within the preset historical time period, a wind speed and direction proportional parameter corresponding to each gust duration period within the preset historical time period, and a gust energy fitting parameter are determined. When it is determined that the wind speed and direction proportional factor and the wind speed and direction proportional parameter within the target gust duration period satisfy a preset corresponding relationship, and the gust energy fitting parameter within the target gust duration period satisfies a preset condition, it is determined that the wind speed and direction within the target gust duration period are extreme coherent gusts. Since the acquired wind condition parameters and the sampling frequency of the wind condition parameters are the actual wind condition parameters within the preset historical time period of the wind farm, and when identifying extreme coherent gusts, a gust energy fitting parameter is proposed, and the gust energy is used as one of the identification criteria, and combined with the wind speed and direction proportional factor to identify extreme coherent gusts, the identification accuracy of extreme coherent gusts is improved.
[0112] In some embodiments of the present application, the preset corresponding relationship is: the wind speed and wind direction proportional parameter within the target gust duration period is equal to the wind speed and wind direction proportional factor; the preset condition is that the gust energy fitting parameter within the target gust duration period is the maximum value of the gust energy fitting parameters within multiple different gust duration periods.
[0113] In some embodiments of the present application, the target gust duration period is multiple, and the above-mentioned device may further include:
[0114] A first fitting module is used to fit the wind speed amplitudes within the target gust duration periods using a Gumbel extreme value distribution algorithm to obtain distribution parameters of a Gumbel extreme value distribution function for characterizing the relationship between time and the wind speed amplitude, so as to obtain a Gumbel extreme value distribution function for characterizing the relationship between time and the wind speed amplitude;
[0115] A second fitting module is used to fit the wind speed amplitude and the wind direction amplitude within a plurality of target gust duration periods to obtain a second corresponding relationship between the wind speed amplitude and the wind direction amplitude;
[0116] The third determination module is used to obtain the target wind speed amplitude and target wind direction amplitude of extreme coherent gusts with different gust duration periods within the target recurrence period based on the Gumbel extreme value distribution function and the second corresponding relationship.
[0117] In some embodiments of the present application, the second fitting module may be specifically used for:
[0118] The wind speed amplitude and the wind direction amplitude within a plurality of the target gust duration periods are fitted using the least squares method to obtain function parameters of a Dir function for characterizing the relationship between the wind speed amplitude and the wind direction amplitude, so as to obtain a Dir function for describing the relationship between the wind speed amplitude and the wind direction amplitude.
[0119] In some embodiments of the present application, the third determination module may be specifically used to:
[0120] Based on the Gumbel extreme value distribution function, target wind speed amplitudes of extreme coherent gusts with different gust durations within a target return period are obtained;
[0121] Based on the target wind speed amplitude and the second corresponding relationship, the target wind direction amplitude of the extreme coherent gusts with different gust duration periods within the target recurrence period is obtained.
[0122] In some embodiments of the present application, the first determination module 330 may be specifically used to:
[0123] Based on the wind speed amplitude and the wind direction amplitude, the gust energy fitting parameter corresponding to each gust duration period in the preset historical time period is determined according to the following formula:
[0124]
[0125] Among them, V(t i +Δt) is (t i +Δt) time, V(t i ) is (t i ) moment, D(t i +Δt) is (t i +Δt), D(t i ) is (t i ) wind direction amplitude at time i = 1, 2, 3..., 0 < t i is less than T, T is the preset historical time period, and EN(i) is the gust energy fitting parameter corresponding to the i-th gust duration period in the preset historical time period.
[0126] The extreme coherent gust determination device provided in the embodiment of the present application can be used to execute the extreme coherent gust determination method provided in the above-mentioned method embodiments. Its implementation principle and technical effect are similar, and for the sake of brief introduction, they will not be repeated here.
[0127] Based on the same inventive concept, an embodiment of the present application also provides an extreme coherent gust determination controller.
[0128] Figure 4is a schematic diagram of the structure of an extreme coherent gust determination controller provided in an embodiment of the present application. Figure 4 As shown, the extreme coherent gust determination controller may include a processor 401 and a memory 402 storing computer programs or instructions.
[0129] Specifically, the processor 401 may include a central processing unit (CPU), or an application specific integrated circuit (ASIC), or may be configured to implement one or more integrated circuits of the embodiment of the present invention.
[0130] The memory 402 may include a large capacity memory for data or instructions. For example, but not limitation, the memory 402 may include a hard disk drive (HDD), a floppy disk drive, a flash memory, an optical disk, a magneto-optical disk, a magnetic tape or a universal serial bus (USB) drive or a combination of two or more of these. In appropriate cases, the memory 402 may include a removable or non-removable (or fixed) medium. In appropriate cases, the memory 402 may be inside or outside the integrated gateway disaster recovery device. In a specific embodiment, the memory 402 is a non-volatile solid-state memory. The memory may include a read-only memory (ROM), a random access memory (RAM), a disk storage medium device, an optical storage medium device, a flash memory device, an electrical, optical or other physical / tangible memory storage device. Therefore, generally, the memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., memory devices) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described in the extreme coherent gust determination method provided in the above embodiments.
[0131] The processor 401 implements any one of the extreme coherent gust determination methods in the above embodiments by reading and executing computer program instructions stored in the memory 402 .
[0132] In one example, the extreme coherent gust determination controller may further include a communication interface 403 and a bus 410. Figure 4 As shown, the processor 401, the memory 402, and the communication interface 403 are connected via a bus 410 and communicate with each other.
[0133] The communication interface 403 is mainly used to implement the communication between the modules, devices, units and / or devices in the embodiment of the present invention.
[0134] Bus 410 includes hardware, software or both, and the parts of electronic equipment are coupled to each other. For example, but not limitation, bus may include accelerated graphics port (AGP) or other graphics bus, enhanced industrial standard architecture (EISA) bus, front side bus (FSB), hypertransport (HT) interconnection, industrial standard architecture (ISA) bus, infinite bandwidth interconnection, low pin count (LPC) bus, memory bus, micro channel architecture (MCA) bus, peripheral component interconnection (PCI) bus, PCI-Express (PCI-X) bus, serial advanced technology attachment (SATA) bus, video electronics standard association local (VLB) bus or other suitable bus or two or more of these combinations. In appropriate cases, bus 410 may include one or more buses. Although the embodiment of the present invention describes and shows a specific bus, the present invention considers any suitable bus or interconnection.
[0135] The extreme coherent gust determination controller can execute the extreme coherent gust determination method in the embodiment of the present invention, thereby achieving Figure 1 and Figure 2 A method for determining extremely coherent gusts is described.
[0136] In addition, in combination with the extreme coherent gust determination method in the above embodiment, the embodiment of the present invention can provide a readable storage medium for implementation. The readable storage medium stores program instructions; when the program instructions are executed by a processor, any one of the extreme coherent gust determination methods in the above embodiment is implemented.
[0137] In addition, in combination with the extreme coherent gust determination method in the above-mentioned embodiment, an embodiment of the present invention may provide a computer program product. When the instructions in the computer program product are executed by the processor of the extreme coherent gust determination controller, the extreme coherent gust determination controller executes any one of the extreme coherent gust determination methods in the above-mentioned embodiment.
[0138] It should be clear that the present invention is not limited to the specific configuration and processing described above and shown in the figures. For the sake of simplicity, a detailed description of the known method is omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of the present invention is not limited to the specific steps described and shown, and those skilled in the art can make various changes, modifications and additions, or change the order between the steps after understanding the spirit of the present invention.
[0139] The functional blocks shown in the above-described block diagram can be implemented as hardware, software, firmware or a combination thereof. When implemented in hardware, it can be, for example, an electronic circuit, an application specific integrated circuit (ASIC), appropriate firmware, a plug-in, a function card, etc. When implemented in software, the elements of the present invention are programs or code segments that are used to perform the required tasks. The program or code segment can be stored in a machine-readable medium, or transmitted on a transmission medium or a communication link by a data signal carried in a carrier wave. "Machine-readable medium" can include any medium capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, optical fiber media, radio frequency (RF) links, etc. The code segment can be downloaded via a computer network such as the Internet, an intranet, etc.
[0140] It should also be noted that the exemplary embodiments mentioned in the present invention describe some methods or systems based on a series of steps or devices. However, the present invention is not limited to the order of the above steps, that is, the steps can be performed in the order mentioned in the embodiments, or in a different order from the embodiments, or several steps can be performed simultaneously.
[0141] The above reference is according to the method of the embodiment of the present application, the flow chart of the device (system) and the computer program product and / or the block diagram described various aspects of the present application.It should be understood that each square box in the flow chart and / or the block diagram and the combination of each square box in the flow chart and / or the block diagram can be realized by computer program instructions.These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer or other programmable data processing device to produce a machine so that these instructions executed by the processor of the computer or other programmable data processing device enable the realization of the function / action specified in one or more square boxes of the flow chart and / or the block diagram.Such a processor can be but is not limited to a general-purpose processor, a special-purpose processor, a special application processor or a field programmable logic circuit.It can also be understood that each square box in the block diagram and / or the flow chart and the combination of the square boxes in the block diagram and / or the flow chart can also be realized by the dedicated hardware that performs the specified function or action, or can be realized by the combination of dedicated hardware and computer instructions.
[0142] The above is only a specific implementation of the present invention. Those skilled in the art can clearly understand that for the convenience and simplicity of description, the specific working process of the system, module and unit described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here. It should be understood that the protection scope of the present invention is not limited to this. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed by the present invention, and these modifications or replacements should be covered within the protection scope of the present invention.
Claims
1. A method for determining extremely coherent gusts, characterized in that: The method comprises: Obtaining wind condition parameters within a preset historical time period of the wind farm and the sampling frequency of the wind condition parameters; wherein the wind condition parameters include: wind speed amplitude and wind direction amplitude; Based on the sampling frequency, setting a gust duration period; Based on the wind speed amplitude and the wind direction amplitude, determine the wind speed and wind direction proportional factor within the preset historical time period, the wind speed and wind direction proportional parameter corresponding to each gust duration period within the preset historical time period, and the gust energy fitting parameter; the wind speed and wind direction proportional factor is used to characterize the ratio of the maximum wind speed change amplitude and the maximum wind direction change amplitude within the gust duration period within the preset historical time period, and the wind speed and wind direction proportional parameter is used to characterize the ratio of the wind speed change amplitude and the wind direction change amplitude within the same gust duration period; When it is determined that the wind speed and direction proportional factor and the wind speed and direction proportional parameter within the target gust duration period satisfy a preset corresponding relationship, and the gust energy fitting parameter within the target gust duration period satisfies a preset condition, it is determined that the wind speed and direction within the target gust duration period is an extreme coherent gust, wherein the target gust duration period is at least one of different gust duration periods.
2. The method according to claim 1, characterized in that The preset corresponding relationship is: the wind speed and wind direction proportional parameter within the target gust duration period is equal to the wind speed and wind direction proportional factor; The preset condition is that the gust energy fitting parameter within the target gust duration period is the maximum value of the gust energy fitting parameters within a plurality of different gust duration periods.
3. The method according to claim 1, characterized in that: The target gust duration period is multiple, and after determining that the wind speed and wind direction within the target gust duration period are extreme coherent gusts, the method further includes: Using a Gumbel extreme value distribution algorithm to fit the wind speed amplitudes within a plurality of target gust duration periods, a distribution parameter of a Gumbel extreme value distribution function for characterizing the relationship between time and the wind speed amplitude is obtained, so as to obtain a Gumbel extreme value distribution function for characterizing the relationship between time and the wind speed amplitude; Fitting the wind speed amplitude and the wind direction amplitude within a plurality of target gust duration periods to obtain a second corresponding relationship between the wind speed amplitude and the wind direction amplitude; Based on the Gumbel extreme value distribution function and the second corresponding relationship, target wind speed amplitudes and target wind direction amplitudes of extreme coherent gusts with different gust duration periods within a target recurrence period are obtained.
4. The method according to claim 3, characterized in that: The step of fitting the wind speed amplitudes and the wind direction amplitudes within a plurality of target gust duration periods to obtain a second corresponding relationship between the wind speed amplitudes and the wind direction amplitudes includes: The wind speed amplitude and the wind direction amplitude within a plurality of the target gust duration periods are fitted using the least squares method to obtain function parameters of a Dir function for characterizing the relationship between the wind speed amplitude and the wind direction amplitude, so as to obtain a Dir function for describing the relationship between the wind speed amplitude and the wind direction amplitude.
5. The method according to claim 3, characterized in that: The method of obtaining target wind speed amplitudes and target wind direction amplitudes of extreme coherent gusts with different gust duration periods within a target recurrence period based on the Gumbel extreme value distribution function and the second corresponding relationship includes: Based on the Gumbel extreme value distribution function, target wind speed amplitudes of extreme coherent gusts with different gust durations within a target return period are obtained; Based on the target wind speed amplitude and the second corresponding relationship, the target wind direction amplitude of the extreme coherent gusts with different gust duration periods within the target recurrence period is obtained.
6. The method according to claim 1, characterized in that Determining the gust energy fitting parameter corresponding to each gust duration period in the preset historical time period based on the wind speed amplitude and the wind direction amplitude includes: Based on the wind speed amplitude and the wind direction amplitude, the gust energy fitting parameter corresponding to each gust duration period in the preset historical time period is determined according to the following formula: Among them, V(t i +Δt) is (t i +Δt) time, V(t i ) is (t i ) moment, D(t i +Δt) is (t i +Δt), D(t i ) is (t i ) wind direction amplitude at time i = 1, 2, 3..., 0 < t i is less than T, T is the preset historical time period, and EN(i) is the gust energy fitting parameter corresponding to the i-th gust duration period in the preset historical time period.
7. An extremely coherent gust determination device, characterized in that: The method comprises: An acquisition module is used to acquire wind condition parameters and a sampling frequency of the wind condition parameters within a preset historical time period of the wind farm; wherein the wind condition parameters include: wind speed amplitude and wind direction amplitude; A setting module, used for setting a gust duration period based on the sampling frequency; A first determination module is used to determine the wind speed and wind direction proportional factor within the preset historical time period, the wind speed and wind direction proportional parameter corresponding to each gust duration period within the preset historical time period, and the gust energy fitting parameter based on the wind speed amplitude and the wind direction amplitude; the wind speed and wind direction proportional factor is used to characterize the ratio of the maximum wind speed change amplitude and the maximum wind direction change amplitude within the gust duration period within the preset historical time period, and the wind speed and wind direction proportional parameter is used to characterize the ratio of the wind speed change amplitude and the wind direction change amplitude within the same gust duration period; The second determination module is used to determine that the wind speed and direction within the target gust duration period are extreme coherent gusts when it is determined that the wind speed and direction proportional factor and the wind speed and direction proportional parameter within the target gust duration period satisfy a preset corresponding relationship, and the gust energy fitting parameter within the target gust duration period satisfies a preset condition, wherein the target gust duration period is at least one of different gust duration periods.
8. An extreme coherence gust determination controller, characterized in that: The extreme coherent gust parameter determination controller comprises: a processor and a memory storing computer program instructions; when the processor executes the computer program instructions, the extreme coherent gust determination method according to any one of claims 1 to 6 is implemented.
9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer program instructions, and when the computer program instructions are executed by a processor, the method for determining extreme coherent gusts according to any one of claims 1 to 6 is implemented.
10. A computer program product, characterized in that When the instructions in the computer program product are executed by a processor of an extreme coherent gust determination controller, the extreme coherent gust determination controller is caused to perform the extreme coherent gust determination method according to any one of claims 1 to 6.