Method and device for determining dead band parameters of a wind turbine, equipment and medium

Abstract

The application provides a wind turbine dead zone parameter determination method and device, equipment and medium, and relates to the technical field of wind turbine control. In the application, first, a prediction wind speed sequence of a prediction time window, a wind speed dead zone characteristic function, a time dead zone characteristic function and an optimization objective function are obtained; second, an index actual value of a wind speed characteristic index is determined based on the prediction wind speed sequence; then, based on the index actual value, the index actual value of the wind speed characteristic index and the index actual value of a relationship characteristic index in the wind speed dead zone characteristic function and the time dead zone characteristic function are determined by taking minimizing power generation loss as the target; finally, based on the index actual value of the wind speed characteristic index and the index actual value of the relationship characteristic index, the actual value of the wind speed dead zone and the actual value of the time dead zone are respectively determined according to the wind speed dead zone characteristic function and the time dead zone characteristic function. Based on the above, the problem of strong data experience dependence and weak scene adaptability in the existing dead zone parameter determination technology can be improved.

Description

Technical Field

[0001] This application relates to the field of wind turbine generator control technology, and more specifically, to a method, apparatus, equipment, and medium for determining the dead zone parameters of a wind turbine generator. Background Technology

[0002] High wind speeds exhibit significant variations, leading to frequent shedding and re-in of wind turbines during such conditions. This increases the turbine's failure rate and raises maintenance costs. Offshore wind farms, in particular, are vulnerable to extreme weather events such as strong tropical storms and typhoons. During typhoons, the mechanical load on wind turbines increases significantly, seriously threatening their safety and reliability. To avoid exceeding design wind loads under strong wind conditions, wind turbines are equipped with a shedding wind speed (typically 25 m / s). When the detected wind speed exceeds the shedding speed, the turbine brakes and stops. When the wind speed fluctuates around the shedding speed, the turbine will frequently start and stop, potentially significantly increasing the probability of failure. Extensive operational and statistical data indicate that gearbox failure is a major cause of downtime for both onshore and offshore wind turbines. Gearboxes are installed in the confined space at the top of wind turbine towers, making repairs difficult once a fault occurs. The average repair time for gearboxes in onshore wind turbines is 256.7 hours, while the average repair time for gearboxes in offshore wind turbines is as high as 360 hours. Gearbox failures account for 50% of the downtime of offshore wind turbines. Frequent switching in and out of the turbine increases the risk of gearbox failure. Furthermore, frequent operation of circuit breakers or switches during off-grid and grid-connected operation can lead to significant temperature increases, resulting in circuit breaker or switch failures. Dead zone, as a control method to avoid frequent reciprocating movements of the controlled object, is widely used in the automatic control and power system industries. The wind speed dead zone is the set re-entry wind speed, and the time dead zone is the additional downtime after the turbine is cut off. To avoid frequent start-ups and shutdowns of wind turbines under strong wind conditions, wind turbine manufacturers have begun to introduce wind speed dead zones in recent years. This means that after a wind turbine is cut off due to strong winds, a re-entry wind speed lower than the cut-off wind speed (usually 23 m / s) is set. The turbine will only restart and connect to the grid when the wind speed falls below this threshold. However, because typhoon wind speeds vary significantly, a wind speed dead zone threshold of 23 m / s may not be effective in preventing repeated start-ups and shutdowns.

[0003] It should be noted that while cut-in and cut-out wind speeds and time dead zones reduce the number of times wind turbines re-cut in, they also reduce the power generation of wind farms. Wider wind speeds and time dead zones can, on the one hand, reduce the number of cut-outs and improve reliability, indirectly reducing maintenance costs and power losses due to downtime. On the other hand, they extend downtime before and after typhoons, when power generation is close to full capacity, directly reducing power generation. However, in existing technologies, using fixed dead zone parameters suffers from strong reliance on data experience and weak adaptability to different scenarios (requiring statistical analysis of large amounts of historical data for different scenarios). Summary of the Invention

[0004] In view of this, the purpose of this application is to provide a method, apparatus, equipment and medium for determining the dead zone parameters of wind turbine generator sets, so as to improve the problems of strong reliance on data experience and weak adaptability to scenarios in the existing dead zone parameter determination technology.

[0005] To achieve the above objectives, this application adopts the following technical solution: A method for determining the dead zone parameters of a wind turbine generator set, comprising: Obtain the predicted wind speed sequence corresponding to the prediction time window, and obtain the pre-determined wind speed dead zone characterization function, time dead zone characterization function and optimization objective function, wherein the prediction time window includes multiple time points, and the predicted wind speed sequence includes multiple predicted wind speeds corresponding to the multiple time points; Based on the predicted wind speed sequence, at least one wind speed characterization index is determined to have an actual value. The wind speed dead zone characterization function is used to reflect the mapping relationship between at least one wind speed characterization index and the wind speed dead zone. The time dead zone characterization function is used to reflect the mapping relationship between at least one wind speed characterization index and the time dead zone. The optimization objective function is used to reflect the mapping relationship between the wind speed dead zone, the time dead zone and the power generation loss. Based on the actual values ​​of the at least one wind speed characterization index, with the goal of minimizing power generation loss, the actual values ​​of the relationship characterization indexes used to reflect the corresponding mapping relationships in the wind speed dead zone characterization function and the time dead zone characterization function are determined. Based on the actual values ​​of the at least one wind speed characterization index and the actual values ​​of the relationship characterization index, the actual values ​​of the wind speed dead zone and the actual values ​​of the time dead zone are determined according to the wind speed dead zone characterization function and the time dead zone characterization function, respectively.

[0006] In a preferred embodiment of this application, in the above-described method for determining the dead zone parameter of a wind turbine generator, the step of determining the actual value of at least one wind speed characterization index based on the predicted wind speed sequence includes: Based on the predicted wind speed sequence and the predetermined standard deviation calculation formula, the actual value of the standard deviation index of the wind speed prediction sequence is determined. Based on the predicted wind speed sequence and the predetermined gradient calculation formula, the actual value of the instantaneous wind speed gradient index is determined. Based on the predicted wind speed sequence and the pre-determined frequency component calculation formula, the actual value of the dominant frequency component index is determined.

[0007] In a preferred embodiment of this application, the standard deviation calculation formula in the above-mentioned method for determining the dead zone parameter of a wind turbine generator includes: ; in, The standard deviation of the wind speed forecast sequence is denoted by n, where n is the number of time points. To predict wind speed, This is the average wind speed. The standard time interval is t, where t is the first time point; The gradient calculation formula includes: ; in, This is an index of instantaneous wind speed gradient; The formula for calculating the frequency components includes: , =0,1,2,...,n; in, The dominant frequency component index.

[0008] In a preferred embodiment of this application, the wind speed dead zone characterization function in the above-mentioned method for determining the dead zone parameters of a wind turbine generator includes: ; in, This is a wind speed dead zone. This is the base value for the wind speed dead zone. The standard deviation of the wind speed forecast sequence serves as a measure of wind speed. As an instantaneous wind speed gradient index, it serves as a characterization indicator of wind speed. and These are two relational indexes used in the wind speed dead zone characterization function to reflect the corresponding mapping relationship; The time dead zone representation function includes: ; in, For time dead zone, This is the base value for the time dead zone. As the dominant frequency component index, and as a wind speed characterization index, This is the reference value for the wind speed component. This is a relational representation index used in the time dead zone representation function to reflect the corresponding mapping relationship.

[0009] In a preferred embodiment of this application, the optimization objective function in the above-mentioned method for determining the dead zone parameters of a wind turbine generator includes: ; in, For power generation losses, and These are hysteresis power loss and the number of state transitions, respectively. It is the grid-connected electricity price of wind farms. This is a metric indicating that the change in state leads to an increase in the operation and maintenance costs of wind turbines; ; ; ; ; =0; ; in, To obtain the wind speed-power conversion coefficient corresponding to the wind speed, Let wind speed loss function be used. and These are the cut-out air velocity before and after adjustment, respectively. and These are the cut-in wind speed before and after adjustment, respectively. The standard time interval is defined as t, where t is the first time point and n is the number of time points. The wind speed dead zone and the wind speed dead zone at the previous moment; When the wind speed is greater than the adjusted cut-out wind speed, the wind speed after cut-out does not reach the adjusted cut-in wind speed, or the cut-out time is less than the time dead zone. In other cases 0; When the wind speed is less than the adjusted cut-in wind speed or the wind speed after cutting in does not reach the adjusted cut-out wind speed. In other cases 0.

[0010] In a preferred embodiment of this application, in the above-described method for determining the dead zone parameters of a wind turbine generator, the step of determining the actual value of the wind speed dead zone and the actual value of the time dead zone based on the actual values ​​of the at least one wind speed characterization index and the actual values ​​of the relationship characterization index, according to the wind speed dead zone characterization function and the time dead zone characterization function, respectively, includes: Based on the actual values ​​of the at least one wind speed characterization index and the actual values ​​of the relationship characterization index, the initial actual values ​​of the wind speed dead zone and the initial actual values ​​of the time dead zone are determined according to the wind speed dead zone characterization function and the time dead zone characterization function, respectively. Determine whether the wind speed at the current moment meets the turbulence condition. Meeting the turbulence condition means that the turbulence intensity corresponding to the wind speed at the current moment is greater than the preset intensity. If the turbulence condition is not met, the initial actual value of the wind speed dead zone and the initial actual value of the time dead zone are taken as the target actual value of the wind speed dead zone and the target actual value of the time dead zone, respectively. If the turbulence condition is met, the initial actual values ​​of the wind speed dead zone and the time dead zone are updated to form the target actual values ​​of the wind speed dead zone and the time dead zone.

[0011] In a preferred embodiment of this application, in the above-mentioned method for determining the dead zone parameters of a wind turbine generator, the step of updating the initial actual values ​​of the wind speed dead zone and the initial actual values ​​of the time dead zone to form the target actual values ​​of the wind speed dead zone and the time dead zone if the turbulence condition is met includes: If the turbulence condition is met, the initial actual value of the wind speed dead zone is expanded based on the turbulence intensity corresponding to the wind speed at the current moment to form the target actual value of the wind speed dead zone. Based on the covariance between the predicted wind speed sequence and the actual wind speed at each moment in the predicted wind speed sequence, the initial actual value of the time dead zone is extended to form the target actual value of the time dead zone.

[0012] This application also provides a device for determining the dead zone parameters of a wind turbine generator set, including: The data acquisition module is used to acquire the predicted wind speed sequence corresponding to the prediction time window, and to acquire the pre-determined wind speed dead zone characterization function, time dead zone characterization function and optimization objective function. The prediction time window includes multiple time points, and the predicted wind speed sequence includes multiple predicted wind speeds corresponding to the multiple time points. The first indicator determination module is used to determine the actual value of at least one wind speed characterization indicator based on the predicted wind speed sequence. The wind speed dead zone characterization function is used to reflect the mapping relationship between at least one wind speed characterization indicator and the wind speed dead zone. The time dead zone characterization function is used to reflect the mapping relationship between at least one wind speed characterization indicator and the time dead zone. The optimization objective function is used to reflect the mapping relationship between the wind speed dead zone and the time dead zone and the power generation loss. The second indicator determination module is used to determine the actual values ​​of the relationship indicators that reflect the corresponding mapping relationship in the wind speed dead zone characterization function and the time dead zone characterization function, based on the actual values ​​of the at least one wind speed characterization indicator, with the goal of minimizing power generation loss. The dead zone value determination module is used to determine the actual value of the wind speed dead zone and the actual value of the time dead zone based on the actual value of the at least one wind speed characterization index and the actual value of the relationship characterization index, according to the wind speed dead zone characterization function and the time dead zone characterization function, respectively.

[0013] Based on the above, this application also provides an electronic device, including: Memory, used to store computer programs; A processor connected to the memory is used to execute the computer program stored in the memory to implement the above-described method for determining the dead zone parameters of a wind turbine generator.

[0014] Based on the above, this application also provides a computer-readable storage medium storing a computer program that, when executed, performs the various steps of the above-described method for determining the dead zone parameters of a wind turbine generator set.

[0015] The method, apparatus, equipment, and medium for determining the dead zone parameters of wind turbine generators provided in this application firstly acquire the predicted wind speed sequence, wind speed dead zone characterization function, time dead zone characterization function, and optimization objective function for the predicted time window; secondly, determine the actual values ​​of the wind speed characterization indicators based on the predicted wind speed sequence; then, based on the actual values ​​of the indicators, with the objective of minimizing power generation losses, determine the actual values ​​of the relational characterization indicators in the wind speed dead zone characterization function and the time dead zone characterization function; finally, based on the actual values ​​of the wind speed characterization indicators and the relational characterization indicators, determine the actual values ​​of the wind speed dead zone and the time dead zone respectively according to the wind speed dead zone characterization function and the time dead zone characterization function. Based on the above, since the wind speed dead zone and time dead zone can be dynamically confirmed by predicting wind speed sequences, that is, the corresponding wind speed dead zone and time dead zone can be determined based on the predicted wind speed sequences at different times, so that the actual values ​​of the determined wind speed dead zone and time dead zone match the actual wind speed state, it is easier to control power generation losses. In other words, since it no longer relies on the statistical analysis of a large amount of historical data under different scenarios, it can improve the problems of strong data experience dependence and weak scenario adaptability in the existing dead zone parameter determination technology. Attached Figure Description

[0016] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings.

[0017] Figure 1 A structural block diagram of an electronic device provided in an embodiment of this application.

[0018] Figure 2 A flowchart illustrating the method for determining the dead zone parameters of a wind turbine generator set provided in this application embodiment.

[0019] Figure 3 A block diagram of a device for determining the dead zone parameters of a wind turbine generator set provided in an embodiment of this application. Detailed Implementation

[0020] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, 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. The components of the embodiments of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0021] Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of the application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0022] like Figure 1 As shown in the figure, this application provides an electronic device. The electronic device may include a memory, a processor, and a device for determining the dead-zone parameters of a wind turbine generator.

[0023] In detail, the memory and the processor are electrically connected directly or indirectly to enable data transmission or interaction. For example, the memory and the processor can be electrically connected via one or more communication buses or signal lines. The dead-zone parameter determination device for the wind turbine generator set includes at least one software functional module stored in the memory in the form of software or firmware. The processor is used to execute executable computer programs stored in the memory, such as the software functional modules and computer programs included in the dead-zone parameter determination device for the wind turbine generator set, to implement the dead-zone parameter determination method for the wind turbine generator set provided in the embodiments of this application.

[0024] Optionally, the memory may be, but is not limited to, random access memory (RAM), read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), etc.

[0025] Optionally, the processor may be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), a system on chip (SoC), etc.; it may also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0026] Understandable. Figure 1The structure shown is for illustrative purposes only; the electronic device may also include components that are more advanced than those shown. Figure 1 The more or fewer components shown, or having the same Figure 1 The different configurations shown may include, for example, a communication unit for exchanging information with other devices.

[0027] Combination Figure 2 This application also provides a method for determining the dead-zone parameters of a wind turbine generator set that can be applied to the aforementioned electronic equipment. The method steps defined in the process related to determining the dead-zone parameters of the wind turbine generator set can be implemented by the electronic equipment.

[0028] The following will be about Figure 2 The specific process shown will be explained in detail.

[0029] Step S110: Obtain the predicted wind speed sequence corresponding to the prediction time window, and obtain the pre-determined wind speed dead zone characterization function, time dead zone characterization function, and optimization objective function.

[0030] In this embodiment, the electronic device can acquire a predicted wind speed sequence corresponding to a predicted time window, and acquire a pre-determined wind speed dead zone representation function, a time dead zone representation function, and an optimization objective function. The predicted time window includes multiple time points, and the predicted wind speed sequence includes multiple predicted wind speeds corresponding to the multiple time points. For example, the predicted time window can be... The predicted wind speed sequence , , The standard time interval is defined as follows. It should be noted that the specific prediction method for wind speed (not the focus of this application) is not limited and existing wind speed prediction technologies can be used. Furthermore, the wind speed dead zone characterization function reflects the mapping relationship between at least one of the wind speed characterization indicators and the wind speed dead zone; the time dead zone characterization function reflects the mapping relationship between at least one of the wind speed characterization indicators and the time dead zone; and the optimization objective function reflects the mapping relationship between the wind speed dead zone, the time dead zone, and power generation losses.

[0031] Step S120: Determine the actual value of at least one wind speed characterization index based on the predicted wind speed sequence.

[0032] In this embodiment, after obtaining the predicted wind speed sequence, the electronic device can determine the actual value of at least one wind speed characterization index based on the predicted wind speed sequence. The wind speed characterization index refers to an index related to the distribution of predicted wind speeds in the predicted wind speed sequence, i.e., it reflects the distribution of predicted wind speeds. Thus, in subsequent processing, determining the actual values ​​of the wind speed dead zone and the time dead zone based on the actual values ​​of the wind speed characterization index allows for adaptation to the current wind speed, thereby improving reliability.

[0033] Step S130: Based on the actual values ​​of the at least one wind speed characterization index, with the goal of minimizing power generation loss, determine the actual values ​​of the relationship characterization indexes in the wind speed dead zone characterization function and the time dead zone characterization function that reflect the corresponding mapping relationship.

[0034] In this embodiment, after determining the actual value of the at least one wind speed characterization index, the electronic device can, based on the actual value of the at least one wind speed characterization index, determine the actual value of the relationship characterization index used to reflect the corresponding mapping relationship in the wind speed dead zone characterization function and the time dead zone characterization function, with the goal of minimizing power generation loss. That is, in the wind speed dead zone characterization function and the time dead zone characterization function, the wind speed dead zone, the time dead zone, and the corresponding mapping relationship's relationship characterization index are unknown, while the wind speed characterization index is known. In the optimization objective function, the wind speed dead zone, the time dead zone, and the power generation loss are unknown, while the corresponding mapping relationship's relationship characterization index is known. Thus, with the goal of minimizing power generation loss, by jointly solving the three functions, the actual value of the relationship characterization index used to reflect the corresponding mapping relationship in the wind speed dead zone characterization function and the time dead zone characterization function can be determined.

[0035] Step S140: Based on the actual values ​​of the at least one wind speed characterization index and the actual values ​​of the relationship characterization index, the actual values ​​of the wind speed dead zone and the actual values ​​of the time dead zone are determined according to the wind speed dead zone characterization function and the time dead zone characterization function, respectively.

[0036] In this embodiment, after determining the actual value of the relationship characterization index, the electronic device can determine the actual value of the wind speed dead zone and the actual value of the time dead zone based on the actual values ​​of the at least one wind speed characterization index and the relationship characterization index, according to the wind speed dead zone characterization function and the time dead zone characterization function, respectively. After determining the actual value of the relationship characterization index, in the wind speed dead zone characterization function, only the wind speed dead zone is an unknown value, therefore, it can be directly solved. Similarly, in the time dead zone characterization function, only the time dead zone is an unknown value, therefore, it can be directly solved.

[0037] Based on the above, since the wind speed dead zone and time dead zone can be dynamically confirmed by predicting wind speed sequences, that is, the corresponding wind speed dead zone and time dead zone can be determined based on the predicted wind speed sequences at different times, so that the actual values ​​of the determined wind speed dead zone and time dead zone match the actual wind speed state, it is easier to control power generation losses. In other words, since it no longer relies on the statistical analysis of a large amount of historical data under different scenarios, it can improve the problems of strong data experience dependence and weak scenario adaptability in the existing dead zone parameter determination technology.

[0038] Firstly, regarding step S110, it should be noted that the specific composition of the wind speed dead zone characterization function, the time dead zone characterization function, and the optimization objective function is not limited, and can be selected and configured according to actual needs.

[0039] For example, in an alternative implementation, to account for both long-term and short-term variations in wind speed, the wind speed dead-zone characterization function may include the following: ; in, This is a wind speed dead zone. This is the baseline value for the wind speed dead zone (e.g., 1.5 m / s). The standard deviation of the wind speed forecast sequence (i.e., the long-term variation of wind speed) serves as a characterization indicator of wind speed. The instantaneous gradient of wind speed (i.e., the change in wind speed over a short period of time) serves as a characterization indicator of wind speed. and These are two relational indicators used in the wind speed dead zone characterization function to reflect the corresponding mapping relationship. In other words, and This refers to the relational representation index that needs to be determined to reflect the corresponding mapping relationship. That is, the actual value of the corresponding index needs to be determined first. In this way, the actual value of the wind speed dead zone can be determined based on the above formula.

[0040] For example, in an alternative implementation, to account for the dominant frequency component of wind speed, the time dead-zone characterization function may include the following: ; in, For time dead zone, This is the base value for the time dead zone (e.g., 30 minutes). As the dominant frequency component index, and as a wind speed characterization index, This is the reference value for the wind speed component. This is a relational representation index used in the time dead zone representation function to reflect the corresponding mapping relationship. In other words, The relational representation index that needs to be determined to reflect the corresponding mapping relationship is the one that needs to be determined first. In this way, the actual value of the corresponding index can be determined based on the above formula.

[0041] For example, in an alternative implementation, in order to consider power generation losses from multiple perspectives, the optimization objective function may include the following: ; in, For power generation losses, and These are hysteresis power loss and the number of state transitions, respectively. This is the grid-connected electricity price for wind farms (unit: yuan / kWh). This is a metric for the increased wind turbine operation and maintenance costs resulting from state switching (unit: yuan / time); where: ; ; ; ; =0; ; in, To obtain the wind speed-power conversion coefficient corresponding to the wind speed, Let wind speed loss function be used. and These are the cut-out air velocity before and after adjustment, respectively. and These are the cut-in wind speed before and after adjustment, respectively. The standard time interval is defined as t, where t is the first time point and n is the number of time points. The wind speed dead zone and the wind speed dead zone at the previous moment; Furthermore, when the wind speed is greater than the adjusted cut-out wind speed, the wind speed after cut-out does not reach the adjusted cut-in wind speed, or the cut-out time is less than the time dead zone, In other cases 0; When the wind speed is less than the adjusted cut-in wind speed or the wind speed after cutting in does not reach the adjusted cut-out wind speed, In other cases 0. In other words, the cut-in / cut-out 01 flag of the wind turbine generator set will only change when the wind turbine generator set is cut in or cut out. Therefore, the above formula can be used to count the number of cut-in / cut-out times of the wind turbine generator set over a period of time.

[0042] Based on the above, it should be noted that the dynamic adjustment of the wind speed dead zone is determined by the fluctuation of wind speed over a period of time and the instantaneous change of wind speed at a given moment, thus taking into account both short-term and long-term environmental changes. The time dead zone, on the other hand, is determined based on the dominant wind speed frequency component over a period of time. When the wind speed component is greater than the reference value, the wind speed is highly likely to increase in the next moment, and the dead zone needs to be increased to adapt to the wind speed change. When the wind speed component is less than the reference value, the wind speed is highly likely to decrease in the next moment, and the dead zone needs to be decreased to adapt to the wind speed change. The greater the difference from the reference value, the larger the adjustment of the time dead zone. When the dominant wind speed frequency component is close to the reference value, the wind speed change is not significant, and the time dead zone only needs minor adjustments. In other words, the above algorithm adopts a non-linear adjustment strategy to cope with sudden wind speed changes, which, compared to a linear adjustment strategy, can better adapt to environmental changes.

[0043] Secondly, regarding step S120, it should be noted that the specific method for determining the actual value of at least one wind speed characterization index based on the predicted wind speed sequence is not limited and can be selected according to actual needs.

[0044] For example, in an alternative implementation, in order to better cope with sudden wind speed changes and ensure that the actual values ​​of the determined wind speed dead zone and time dead zone better adapt to environmental changes, step S120 above may include the following: On one hand, the actual value of the standard deviation index of the wind speed prediction sequence can be determined based on the predicted wind speed sequence and the predetermined standard deviation calculation formula. On one hand, the actual value of the instantaneous gradient index of wind speed can be determined based on the predicted wind speed sequence and the predetermined gradient calculation formula. On one hand, the actual value of the dominant frequency component index can be determined based on the predicted wind speed sequence and the predetermined frequency component calculation formula.

[0045] It is understood that the specific content of the standard deviation calculation formula in step S120 above is not limited. For example, in an alternative implementation, the standard deviation calculation formula includes: ; in, The standard deviation of the wind speed forecast sequence is denoted by n, where n is the number of time points. To predict wind speed, This is the average wind speed. The standard time interval is t, where t is the first moment.

[0046] It is understood that the specific content of the gradient calculation formula in step S120 above is not limited. For example, in an alternative implementation, the gradient calculation formula includes: ; in, This is an index of instantaneous wind speed gradient.

[0047] It is understood that the specific content of the frequency component calculation formula in step S120 above is not limited. For example, in an alternative embodiment, the frequency component calculation formula includes: , =0,1,2,...,n; in, The dominant frequency component index is determined by Fourier transform.

[0048] Thirdly, regarding step S130, it should be noted that the specific method for determining the actual value of the relational representation index used to reflect the corresponding mapping relationship in the wind speed dead zone representation function and the time dead zone representation function is not limited and can be selected according to actual needs.

[0049] For example, in an alternative implementation, based on the actual values ​​of the at least one wind speed characterization index, with the goal of minimizing power generation losses, a heuristic algorithm is used to determine the actual values ​​of the relation characterization indices used to reflect the corresponding mapping relationships in the wind speed dead zone characterization function and the time dead zone characterization function.

[0050] Fourthly, regarding step S140, it should be noted that the specific methods for determining the actual values ​​of the wind speed dead zone and the time dead zone are not restricted and can be selected according to actual needs.

[0051] For example, in an alternative implementation, to improve the efficiency of determining the actual value, step S140 above may include the following: Based on the actual values ​​of the at least one wind speed characterization index and the actual values ​​of the relationship characterization index, the initial actual values ​​of the wind speed dead zone and the initial actual values ​​of the time dead zone are determined according to the wind speed dead zone characterization function and the time dead zone characterization function, respectively. The initial actual values ​​of the wind speed dead zone and the initial actual values ​​of the time dead zone are used as the target actual values ​​of the wind speed dead zone and the time dead zone, respectively.

[0052] For example, in another alternative implementation, in order to further improve the reliability of the determined actual value, the above step S140 may further include steps S141, S142, S143 and S144, the specific contents of each step are as follows.

[0053] Step S141: Based on the actual values ​​of the at least one wind speed characterization index and the actual values ​​of the relationship characterization index, determine the initial actual values ​​of the wind speed dead zone and the time dead zone according to the wind speed dead zone characterization function and the time dead zone characterization function, respectively.

[0054] In this embodiment of the application, based on the actual values ​​of the at least one wind speed characterization index and the actual values ​​of the relationship characterization index, the initial actual values ​​of the wind speed dead zone and the time dead zone are determined according to the wind speed dead zone characterization function and the time dead zone characterization function, respectively. That is, the initial actual value of the wind speed dead zone is determined based on the wind speed dead zone characterization function, and the initial actual value of the time dead zone is determined based on the time dead zone characterization function.

[0055] Step S142: Determine whether the wind speed at the current moment meets the turbulence condition.

[0056] In this embodiment, when turbulence is generated by a rapid change in wind speed over a short period, the dead zone parameter needs to be fine-tuned on a smaller time scale based on the turbulence intensity to better cope with the rapid changes in meteorological conditions. Thus, after determining the initial actual value, it can also be determined whether the wind speed at the current moment meets the turbulence condition. Meeting the turbulence condition means that the turbulence intensity corresponding to the wind speed at the current moment is greater than a preset intensity (e.g., 0.15).

[0057] Step S143: If the turbulence condition is not met, the initial actual value of the wind speed dead zone and the initial actual value of the time dead zone are taken as the target actual value of the wind speed dead zone and the target actual value of the time dead zone, respectively.

[0058] In the embodiments of this application, when it is determined that the turbulence condition is not met, that is, the turbulence intensity is relatively low, the initial actual value of the wind speed dead zone and the initial actual value of the time dead zone can be used as the target actual value of the wind speed dead zone and the target actual value of the time dead zone, respectively.

[0059] Step S144: If the turbulence condition is met, update the initial actual value of the wind speed dead zone and the initial actual value of the time dead zone to form the target actual value of the wind speed dead zone and the target actual value of the time dead zone.

[0060] In this embodiment, when the turbulence condition is met (i.e., the turbulence intensity is relatively high), the initial actual values ​​of the wind speed dead zone and the time dead zone can be updated to form target actual values ​​for the wind speed dead zone and the time dead zone, thus adapting to short-term, drastic changes in meteorological conditions. As mentioned earlier, there is a standard time interval between two adjacent moments. Therefore, if a situation with relatively high turbulence intensity occurs, using the determined initial actual values ​​throughout this standard time interval (e.g., 5 minutes) may not be suitable for situations with rapid short-term changes in wind speed. Therefore, it is necessary to update the initial actual values ​​accordingly.

[0061] It is understood that in step S144 above, the specific method of updating the initial actual value of the wind speed dead zone and the initial actual value of the time dead zone is not limited. For example, in an alternative implementation, step S144 above may include the following: If the turbulence condition is met, the initial actual value of the wind speed dead zone is expanded based on the turbulence intensity corresponding to the wind speed at the current moment to form the target actual value of the wind speed dead zone. Furthermore, the initial actual value of the time dead zone can be extended based on the covariance between the predicted wind speed sequence and the actual wind speed at each moment in the predicted wind speed sequence, to form the target actual value of the time dead zone.

[0062] For example, in one specific implementation, the initial actual value of the wind speed dead zone is expanded to form the target actual value of the wind speed dead zone, which can be achieved by the following formula: = × (1 + 0.5·TI); in, This represents the actual target value for the wind speed dead zone. TI represents the initial actual value of the wind speed dead zone, and TI represents the turbulence intensity corresponding to the wind speed at the current moment.

[0063] For example, in one specific implementation, extending the initial actual value of the time dead zone to form the target actual value of the time dead zone can be achieved using the following formula: = × (1 + 3· ); in, The actual value of the target for the time dead zone. This is the initial actual value of the time dead zone. For covariance, the above-mentioned prediction time window is used as... Taking this as an example, the current time is Therefore, it is necessary to The covariance of the predicted wind speed and the actual wind speed at each time point is calculated to obtain the... The actual value of the target within the time dead zone at the corresponding moment.

[0064] Combination Figure 3 This application also provides a dead-zone parameter determination device for wind turbine generator sets applicable to the aforementioned electronic equipment. The dead-zone parameter determination device for wind turbine generator sets may include a data acquisition module, a first index determination module, a second index determination module, and a dead-zone value determination module.

[0065] The data acquisition module is used to acquire the predicted wind speed sequence corresponding to the prediction time window, and to acquire a pre-determined wind speed dead zone characterization function, time dead zone characterization function, and optimization objective function. The prediction time window includes multiple time points, and the predicted wind speed sequence includes multiple predicted wind speeds corresponding to the multiple time points. In this embodiment, the data acquisition module can be used to execute... Figure 2 The relevant content regarding the data acquisition module in step S110 shown can be found in the preceding description of step S110.

[0066] The first index determination module is used to determine the actual value of at least one wind speed characterization index based on the predicted wind speed sequence. The wind speed dead zone characterization function reflects the mapping relationship between at least one wind speed characterization index and the wind speed dead zone; the time dead zone characterization function reflects the mapping relationship between at least one wind speed characterization index and the time dead zone; and the optimization objective function reflects the mapping relationship between the wind speed dead zone, the time dead zone, and power generation loss. In this embodiment, the first index determination module can be used to execute... Figure 2 The relevant content regarding the first indicator determination module in step S120 shown can be found in the previous description of step S120.

[0067] The second indicator determination module is used to determine, based on the actual values ​​of the at least one wind speed characterization indicator, the actual values ​​of the relation characterization indicators reflecting the corresponding mapping relationships in the wind speed dead zone characterization function and the time dead zone characterization function, with the objective of minimizing power generation losses. In this embodiment, the second indicator determination module can be used to perform... Figure 2The relevant content regarding the second indicator determination module in step S130 shown can be found in the previous description of step S130.

[0068] The dead zone value determination module is used to determine the actual value of the wind speed dead zone and the actual value of the time dead zone based on the actual values ​​of the at least one wind speed characterization index and the actual values ​​of the relationship characterization index, according to the wind speed dead zone characterization function and the time dead zone characterization function, respectively. In this embodiment of the application, the dead zone value determination module can be used to perform... Figure 2 The relevant content regarding the dead zone value determination module in step S140 shown can be found in the previous description of step S140.

[0069] In this embodiment of the application, corresponding to the above-described method for determining the dead zone parameters of a wind turbine generator set applied to the electronic device, a computer-readable storage medium is also provided, which stores a computer program that executes the various steps of the method for determining the dead zone parameters of a wind turbine generator set when the computer program is run.

[0070] The steps executed by the aforementioned computer program during runtime will not be described in detail here, but can be found in the explanation of the method for determining the dead zone parameters of the wind turbine generator set mentioned above.

[0071] In summary, the method, apparatus, equipment, and medium for determining the dead zone parameters of wind turbine generators provided in this application firstly acquire the predicted wind speed sequence, wind speed dead zone characterization function, time dead zone characterization function, and optimization objective function for the predicted time window; secondly, determine the actual values ​​of the wind speed characterization indicators based on the predicted wind speed sequence; then, based on the actual values ​​of the indicators, with the objective of minimizing power generation losses, determine the actual values ​​of the relational characterization indicators in the wind speed dead zone characterization function and the time dead zone characterization function; finally, based on the actual values ​​of the wind speed characterization indicators and the relational characterization indicators, determine the actual values ​​of the wind speed dead zone and the time dead zone respectively according to the wind speed dead zone characterization function and the time dead zone characterization function. Based on the above, since the wind speed dead zone and time dead zone can be dynamically confirmed by predicting wind speed sequences, that is, the corresponding wind speed dead zone and time dead zone can be determined based on the predicted wind speed sequences at different times, so that the actual values ​​of the determined wind speed dead zone and time dead zone match the actual wind speed state, it is easier to control power generation losses. In other words, since it no longer relies on the statistical analysis of a large amount of historical data under different scenarios, it can improve the problems of strong data experience dependence and weak scenario adaptability in the existing dead zone parameter determination technology.

[0072] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can also be implemented in other ways. The apparatus and method embodiments described above are merely illustrative. For example, the flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than those marked in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram and / or flowchart, and combinations of blocks in block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0073] In addition, the functional modules in the various embodiments of this application can be integrated together to form an independent part, or each module can exist independently, or two or more modules can be integrated to form an independent part.

[0074] If the aforementioned functions are implemented as software functional modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, electronic device, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes 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. It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. In the absence of further restrictions, an element defined by the phrase "comprising a..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0075] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A method for determining the dead zone parameters of a wind turbine generator set, characterized in that, include: Obtain the predicted wind speed sequence corresponding to the prediction time window, and obtain the pre-determined wind speed dead zone characterization function, time dead zone characterization function and optimization objective function, wherein the prediction time window includes multiple time points, and the predicted wind speed sequence includes multiple predicted wind speeds corresponding to the multiple time points; Based on the predicted wind speed sequence, at least one wind speed characterization index is determined to have an actual value. The wind speed dead zone characterization function reflects the mapping relationship between at least one wind speed characterization index and the wind speed dead zone. The time dead zone characterization function reflects the mapping relationship between at least one wind speed characterization index and the time dead zone. The optimization objective function reflects the mapping relationship between the wind speed dead zone, the time dead zone, and power generation loss. The wind speed dead zone characterization function includes: ;in, This is a wind speed dead zone. This is the base value for the wind speed dead zone. The standard deviation of the wind speed forecast sequence serves as a measure of wind speed. As an instantaneous gradient index of wind speed, it serves as a characterization indicator of wind speed. and These are two relational indicators used in the wind speed dead zone characterization function to reflect the corresponding mapping relationship; the time dead zone characterization function includes: ;in, For time dead zone, This is the base value for the time dead zone. As the dominant frequency component index, and as a wind speed characterization index, This is the reference value for the wind speed component. This is a relational representation index used in the time dead zone representation function to reflect the corresponding mapping relationship; Based on the actual values ​​of the at least one wind speed characterization index, with the goal of minimizing power generation loss, the actual values ​​of the relationship characterization indexes used to reflect the corresponding mapping relationships in the wind speed dead zone characterization function and the time dead zone characterization function are determined. Based on the actual values ​​of the at least one wind speed characterization index and the actual values ​​of the relationship characterization index, the actual values ​​of the wind speed dead zone and the actual values ​​of the time dead zone are determined according to the wind speed dead zone characterization function and the time dead zone characterization function, respectively.

2. The method for determining the dead zone parameters of a wind turbine generator set according to claim 1, characterized in that, The step of determining the actual value of at least one wind speed characterization index based on the predicted wind speed sequence includes: Based on the predicted wind speed sequence and the predetermined standard deviation calculation formula, the actual value of the standard deviation index of the wind speed prediction sequence is determined. Based on the predicted wind speed sequence and the predetermined gradient calculation formula, the actual value of the instantaneous wind speed gradient index is determined. Based on the predicted wind speed sequence and the pre-determined frequency component calculation formula, the actual value of the dominant frequency component index is determined.

3. The method for determining the dead zone parameters of a wind turbine generator set according to claim 2, characterized in that, The formula for calculating the standard deviation includes: ； in, The standard deviation of the wind speed forecast sequence is denoted by n, where n is the number of time points. To predict wind speed, This is the average wind speed. The standard time interval is t, where t is the first time point; The gradient calculation formula includes: ； in, This is an index of instantaneous wind speed gradient; The formula for calculating the frequency components includes: ， =0,1,2,...,n； in, The dominant frequency component index.

4. The method for determining the dead zone parameters of a wind turbine generator set according to claim 1, characterized in that, The optimization objective function includes: ； in, For power generation losses, and These are hysteresis power loss and the number of state transitions, respectively. It is the grid-connected electricity price of wind farms. This is a metric indicating that the change in state leads to an increase in the operation and maintenance costs of wind turbines; ； ； ； ； =0； ； in, To obtain the wind speed-power conversion coefficient corresponding to the wind speed, Let wind speed be the loss function. and These are the cut-out air velocity before and after adjustment, respectively. and These are the cut-in wind speed before and after adjustment, respectively. The standard time interval is defined as t, where t is the first time point and n is the number of time points. The wind speed dead zone and the wind speed dead zone at the previous moment; When the wind speed is greater than the adjusted cut-out wind speed, the wind speed after cut-out does not reach the adjusted cut-in wind speed, or the cut-out time is less than the time dead zone. In other cases 0; When the wind speed is less than the adjusted cut-in wind speed or the wind speed after cutting in does not reach the adjusted cut-out wind speed. In other cases 0.

5. The method for determining the dead zone parameters of a wind turbine generator set according to any one of claims 1-4, characterized in that, The step of determining the actual values ​​of the wind speed dead zone and the time dead zone based on the actual values ​​of the at least one wind speed characterization index and the actual values ​​of the relationship characterization index, according to the wind speed dead zone characterization function and the time dead zone characterization function, respectively, includes: Based on the actual values ​​of the at least one wind speed characterization index and the actual values ​​of the relationship characterization index, the initial actual values ​​of the wind speed dead zone and the initial actual values ​​of the time dead zone are determined according to the wind speed dead zone characterization function and the time dead zone characterization function, respectively. Determine whether the wind speed at the current moment meets the turbulence condition. Meeting the turbulence condition means that the turbulence intensity corresponding to the wind speed at the current moment is greater than the preset intensity. If the turbulence condition is not met, the initial actual value of the wind speed dead zone and the initial actual value of the time dead zone are taken as the target actual value of the wind speed dead zone and the target actual value of the time dead zone, respectively. If the turbulence condition is met, the initial actual values ​​of the wind speed dead zone and the time dead zone are updated to form the target actual values ​​of the wind speed dead zone and the time dead zone.

6. The method for determining the dead zone parameters of a wind turbine generator set according to claim 5, characterized in that, The step of updating the initial actual values ​​of the wind speed dead zone and the time dead zone to form the target actual values ​​of the wind speed dead zone and the time dead zone if the turbulence condition is met includes: If the turbulence condition is met, the initial actual value of the wind speed dead zone is expanded based on the turbulence intensity corresponding to the wind speed at the current moment to form the target actual value of the wind speed dead zone. Based on the covariance between the predicted wind speed sequence and the actual wind speed at each moment in the predicted wind speed sequence, the initial actual value of the time dead zone is extended to form the target actual value of the time dead zone.

7. A device for determining the dead zone parameters of a wind turbine generator set, characterized in that, include: The data acquisition module is used to acquire the predicted wind speed sequence corresponding to the prediction time window, and to acquire the pre-determined wind speed dead zone characterization function, time dead zone characterization function and optimization objective function. The prediction time window includes multiple time points, and the predicted wind speed sequence includes multiple predicted wind speeds corresponding to the multiple time points. The first indicator determination module is used to determine the actual value of at least one wind speed characterization indicator based on the predicted wind speed sequence. The wind speed dead zone characterization function reflects the mapping relationship between at least one wind speed characterization indicator and the wind speed dead zone; the time dead zone characterization function reflects the mapping relationship between at least one wind speed characterization indicator and the time dead zone; and the optimization objective function reflects the mapping relationship between the wind speed dead zone, the time dead zone, and power generation loss. The wind speed dead zone characterization function includes: ;in, This is a wind speed dead zone. This is the base value for the wind speed dead zone. The standard deviation of the wind speed forecast sequence serves as a measure of wind speed. As an instantaneous gradient index of wind speed, it serves as a characterization indicator of wind speed. and These are two relational indicators used in the wind speed dead zone characterization function to reflect the corresponding mapping relationship; the time dead zone characterization function includes: ;in, For time dead zone, This is the base value for the time dead zone. As the dominant frequency component index, and as a wind speed characterization index, This is the reference value for the wind speed component. This is a relational representation index used in the time dead zone representation function to reflect the corresponding mapping relationship; The second indicator determination module is used to determine the actual values ​​of the relationship indicators that reflect the corresponding mapping relationship in the wind speed dead zone characterization function and the time dead zone characterization function, based on the actual values ​​of the at least one wind speed characterization indicator, with the goal of minimizing power generation loss. The dead zone value determination module is used to determine the actual value of the wind speed dead zone and the actual value of the time dead zone based on the actual value of the at least one wind speed characterization index and the actual value of the relationship characterization index, according to the wind speed dead zone characterization function and the time dead zone characterization function, respectively.

8. An electronic device, characterized in that, include: Memory, used to store computer programs; A processor connected to the memory is used to execute the computer program stored in the memory to implement the dead zone parameter determination method for wind turbine generator sets as described in any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium contains a computer program that, when executed, performs the dead zone parameter determination method for wind turbine generator sets as described in any one of claims 1-6.

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