Fan control method, device and equipment and computer readable storage medium

Abstract

The invention discloses a draught fan control method, device and equipment and a computer readable storage medium, and relates to the technical field of draught fan control, and the draught fan control method comprises the steps that current operation energy of a current operation cycle of a draught fan and historical operation energy of multiple historical operation cycles before the current operation cycle are obtained; determining historical operation energy of each historical operation cycle and an energy lag coefficient corresponding to the current operation cycle; according to the historical operation energy of each historical operation cycle and the energy lag coefficient corresponding to each historical operation energy, lag energy transmitted to the current operation cycle by each historical operation cycle is calculated; and according to the lagging energy and the current operation energy, the accumulated operation energy of the current operation period is determined, and according to the accumulated operation energy, the fan is controlled to operate. The control accuracy of the fan can be improved, so that the power generation efficiency and the power generation uniformity of the fan are ensured.

Description

Technical Field

[0001] This application relates to the field of wind turbine control technology, and in particular to a wind turbine control method, device, equipment, and computer-readable storage medium. Background Technology

[0002] Currently, wind turbine operation is typically controlled using the wind speed or wind energy measured at the current moment. However, a wind turbine is a dynamic system with a huge moment of inertia, and its operating state (such as speed, torque, and power) exhibits a lag effect. This means that the control strategy determined by the wind speed or wind energy measured at the current moment cannot accurately match the actual operating state of the wind turbine, which can easily lead to power fluctuations, increased load, and reduced power generation efficiency. This not only affects power generation efficiency but also the uniformity of power generation. Summary of the Invention

[0003] The main objective of this application is to provide a wind turbine control method, device, equipment, and computer-readable storage medium, which aims to improve the accuracy of wind turbine control to ensure the power generation efficiency and uniformity of the wind turbine.

[0004] This application provides a method for controlling a wind turbine, the method comprising: Obtain the current operating energy of the wind turbine in the current operating cycle, as well as the historical operating energy of multiple historical operating cycles prior to the current operating cycle; Determine the historical operating energy for each of the aforementioned historical operating cycles, and the energy lag coefficient corresponding to the current operating cycle; Based on the historical operating energy of each historical operating cycle and the energy lag coefficient corresponding to each historical operating energy, the lag energy transmitted from each historical operating cycle to the current operating cycle is calculated; Based on the lag energy and the current operating energy, the cumulative operating energy of the current operating cycle is determined, and the operation of the wind turbine is controlled according to the cumulative operating energy.

[0005] In one embodiment, the step of determining the historical operating energy of each of the historical operating cycles, and the energy lag coefficient corresponding to the current operating cycle, includes: Determine the time interval between each of the historical operating cycles and the current operating cycle; Based on the time intervals corresponding to each of the historical operating cycles, the energy lag coefficient corresponding to each of the historical operating energies is determined.

[0006] In one embodiment, the step of determining the energy lag coefficient corresponding to each of the historical operating energies based on the time intervals corresponding to each of the historical operating cycles includes: For any of the aforementioned historical operating cycles, the energy lag coefficient corresponding to the time interval is searched in the preset energy lag coefficient table using the time interval corresponding to the historical operating cycle as an index. If an energy lag coefficient corresponding to the time interval exists in the energy lag coefficient table, then the energy lag coefficient recorded in the energy lag coefficient table corresponding to the time interval shall be used as the energy lag coefficient corresponding to the historical operating energy. If there is no energy lag coefficient corresponding to the time interval in the energy lag coefficient table, then interpolation calculation is performed in the energy lag coefficient table based on the time interval to obtain the energy lag coefficient corresponding to the historical operating energy.

[0007] In one embodiment, the step of interpolating the energy lag coefficients corresponding to the historical operating energy based on the time interval in the energy lag coefficient table includes: Obtain the lower limit time interval and upper limit time interval adjacent to the time interval in the energy lag coefficient table, as well as the energy lag coefficient corresponding to the lower limit time interval and the energy lag coefficient corresponding to the upper limit time interval; Calculate the difference between the time interval and the lower limit time interval to obtain a first time difference, and calculate the difference between the upper limit time interval and the lower limit time interval to obtain a second time difference; Calculate the ratio between the first time difference and the second time difference to obtain the time ratio, and calculate the difference between the energy lag coefficient corresponding to the upper limit time interval and the energy lag coefficient corresponding to the lower limit time interval to obtain the coefficient difference; The sum of the product of the time ratio and the coefficient difference, and the energy lag coefficient corresponding to the lower limit time interval, is used to obtain the energy lag coefficient corresponding to the historical operating energy.

[0008] In one embodiment, the step of determining the historical operating energy of each of the historical operating cycles, and the energy lag coefficient corresponding to the current operating cycle, includes: Determine the time interval between each of the historical operating cycles and the current operating cycle, and obtain the historical operating parameters of the wind turbine in each of the historical operating cycles; Based on the time interval and historical operating parameters corresponding to each of the historical operating cycles, the energy lag coefficient corresponding to each of the historical operating energies is determined.

[0009] In one embodiment, the step of determining the cumulative operating energy of the current operating cycle based on each of the hysteresis energies and the current operating energy includes: Obtain the energy lag coefficient corresponding to the current operating cycle; Calculate the product of the current operating energy and the energy lag coefficient corresponding to the current operating cycle to obtain the target operating energy transferred from the current operating energy to the current operating cycle; The sum of the lag energy and the target operating energy is calculated to obtain the cumulative operating energy of the current operating cycle.

[0010] In one embodiment, the step of controlling the operation of the wind turbine based on the accumulated operating energy includes: Based on the preset mapping relationship between operating energy and operating target parameters, the operating target parameters corresponding to the accumulated operating energy are obtained; The operation of the wind turbine is controlled based on the target operating parameters corresponding to the accumulated operating energy.

[0011] Furthermore, to achieve the above objectives, this application also provides a control device for a fan, the control device comprising: The operating energy acquisition module is used to acquire the current operating energy of the wind turbine in the current operating cycle, as well as the historical operating energy of multiple historical operating cycles prior to the current operating cycle. An inertia coefficient determination module is used to determine the historical operating energy of each of the historical operating cycles, and the energy lag coefficient corresponding to the current operating cycle. The lag energy determination module is used to calculate the lag energy transferred from each of the historical operating cycles to the current operating cycle based on the historical operating energy of each of the historical operating cycles and the energy lag coefficient corresponding to each of the historical operating energies. The control module is used to determine the cumulative operating energy of the current operating cycle based on the hysteresis energy and the current operating energy, and to control the operation of the wind turbine based on the cumulative operating energy.

[0012] In addition, to achieve the above objectives, this application also provides a control device, the control device comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the fan control method as described above.

[0013] In addition, to achieve the above objectives, this application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the fan control method described above.

[0014] In addition, to achieve the above objectives, this application also provides a computer program product, which includes a computer program that, when executed by a processor, implements the steps of the fan control method described above.

[0015] This application provides a method for controlling a wind turbine, comprising: acquiring the current operating energy of the wind turbine in the current operating cycle, and the historical operating energy of multiple historical operating cycles prior to the current operating cycle; determining the energy lag coefficient corresponding to the historical operating energy of each historical operating cycle in the current operating cycle; calculating the lag energy transferred from each historical operating cycle to the current operating cycle based on the historical operating energy of each historical operating cycle and the corresponding energy lag coefficient; determining the cumulative operating energy of the current operating cycle based on the lag energy and the current operating energy, and controlling the wind turbine operation based on the cumulative operating energy.

[0016] Therefore, the technical solution provided in this application, when controlling the operation of the wind turbine, not only considers the current operating energy of the current operating cycle, but also the lag energy transferred from the historical operating energy of multiple historical operating cycles before the current operating cycle to the current operating cycle. This helps to eliminate the impact of energy lag effect on the control accuracy of the wind turbine, thereby effectively improving the accuracy of wind turbine control and ensuring the power generation efficiency and uniformity of the wind turbine. Attached Figure Description

[0017] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0018] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 A schematic flowchart illustrating the fan control method provided in the first embodiment of this application; Figure 2 A schematic flowchart illustrating the fan control method provided in the second embodiment of this application; Figure 3 A flowchart illustrating the fan control method provided in the third embodiment of this application; Figure 4 This is a schematic diagram of the module structure of the control device for the fan provided in the embodiments of this application; Figure 5 This is a schematic diagram of the hardware operating environment involved in the embodiments of this application.

[0020] The purpose, features, and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0021] It should be understood that the specific embodiments described herein are merely illustrative of the technical solutions of this application and are not intended to limit this application.

[0022] To better understand the technical solution of this application, a detailed description will be provided below in conjunction with the accompanying drawings and specific implementation methods.

[0023] Currently, wind turbine operation is typically controlled using the wind speed or wind energy measured at the current moment. However, a wind turbine is a dynamic system with a huge moment of inertia, and its operating state (such as speed, torque, and power) exhibits a lag effect. This means that the control strategy determined by the wind speed or wind energy measured at the current moment cannot accurately match the actual operating state of the wind turbine, which can easily lead to power fluctuations, increased load, and reduced power generation efficiency. This not only affects power generation efficiency but also the uniformity of power generation.

[0024] Based on this, this application provides a wind turbine control method, comprising: acquiring the current operating energy of the wind turbine in the current operating cycle, and the historical operating energy of multiple historical operating cycles prior to the current operating cycle; determining the energy lag coefficient corresponding to the historical operating energy of each historical operating cycle in the current operating cycle; calculating the lag energy transferred from each historical operating cycle to the current operating cycle based on the historical operating energy of each historical operating cycle and the energy lag coefficient corresponding to each historical operating energy; determining the cumulative operating energy of the current operating cycle based on the lag energy and the current operating energy, and controlling the wind turbine operation based on the cumulative operating energy.

[0025] Therefore, the technical solution provided in this application, when controlling the operation of the wind turbine, not only considers the current operating energy of the current operating cycle, but also the lag energy transferred from the historical operating energy of multiple historical operating cycles before the current operating cycle to the current operating cycle. This helps to eliminate the impact of energy lag effect on the control accuracy of the wind turbine, thereby effectively improving the accuracy of wind turbine control and ensuring the power generation efficiency and uniformity of the wind turbine.

[0026] The execution subject of the wind turbine control method of this application can be a control device with data processing, network communication and program operation functions, or a control system, control circuit, etc. that can realize the above functions, or a wind turbine blade defect detection system. This embodiment does not specifically limit it.

[0027] The following description uses a control device as the execution subject to illustrate the various embodiments.

[0028] This application presents a fan control method according to a first embodiment. Please refer to [link / reference]. Figure 1 The control method for the fan may include steps S10 to S40: Step S10: Obtain the current operating energy of the wind turbine in the current operating cycle, as well as the historical operating energy of multiple historical operating cycles prior to the current operating cycle; It should be noted that the current operating cycle refers to the operating cycle in which the wind turbine is currently operating; the current operating energy refers to the theoretical operating energy of the wind turbine in the current operating cycle; and the historical operating energy refers to the theoretical operating energy of the wind turbine in historical operating cycles. Theoretical operating energy refers to the ideal energy state value of the wind turbine in the corresponding operating cycle, directly calculated or mapped from the wind speed or wind energy measured during that cycle. It characterizes the instantaneous energy state of the wind turbine corresponding to the current wind energy or wind speed under the condition of no historical inertia. Operating energy can be the wind turbine's power, equivalent kinetic energy, etc., and this embodiment does not specifically limit this. The operating cycle refers to the fixed time interval for the control equipment to collect data, process data, and issue control commands.

[0029] Step S20: Determine the historical operating energy of each historical operating cycle and the energy lag coefficient corresponding to the current operating cycle; It should be noted that the energy lag coefficient is a weighting coefficient between 0 and 1. It is used to quantify the proportion of historical operating energy that is delayed in fully manifesting its impact until the current operating cycle due to factors such as the mechanical inertia of the wind turbine system and control response time delay. For example, if the energy lag coefficient corresponding to a historical operating cycle is 0.3, it means that 30% of the operating energy of the wind turbine in that historical operating cycle has lagged behind to the current operating cycle.

[0030] Step S30: Calculate the lag energy transferred from each historical operating cycle to the current operating cycle based on the historical operating energy of each historical operating cycle and the energy lag coefficient corresponding to each historical operating energy. It should be noted that the lag energy transferred from each historical operating cycle to the current operating cycle can be obtained by multiplying the historical operating energy of each historical operating cycle with the energy lag coefficient corresponding to each historical operating energy.

[0031] Step S40: Determine the cumulative operating energy of the current operating cycle based on each lag energy and the current operating energy, and control the operation of the fan based on the cumulative operating energy.

[0032] It should be noted that cumulative operating energy refers to the combined value of current operating energy and all lagging energy, which is used to reflect the actual operating energy of the wind turbine system in the current operating cycle.

[0033] When determining the cumulative operating energy of the current operating cycle based on each lag energy and the current operating energy, in one feasible implementation, the sum of each lag energy and the current operating energy can be directly used as the cumulative operating energy of the current operating cycle. In another feasible implementation, the implementation process shown in steps S41 to S43 can also be used to determine the cumulative operating energy of the current operating cycle; this embodiment does not specifically limit this approach.

[0034] Step S41: Obtain the energy lag coefficient corresponding to the current operating cycle; It should be noted that the energy lag coefficient corresponding to the current operating cycle is the energy lag coefficient when the time interval is zero. When obtaining the energy lag coefficient corresponding to the current operating cycle, the default energy lag coefficient (e.g., 0.9) can be used as the energy lag coefficient corresponding to the current operating cycle; alternatively, it can be flexibly determined according to the operating conditions of the wind turbine in the current operating cycle (e.g., current wind speed and wind intensity). This embodiment does not impose specific limitations on this.

[0035] Step S42: Calculate the product of the current operating energy and the energy lag coefficient corresponding to the current operating cycle to obtain the target operating energy transferred from the current operating energy to the current operating cycle; Step S43: Calculate the sum of each delayed energy and the target operating energy to obtain the cumulative operating energy of the current operating cycle.

[0036] Understandably, the current operating energy in the current operating cycle is often not fully utilized due to factors such as the mechanical inertia of the wind turbine system and control response time delays. Therefore, when determining the cumulative operating energy for the current operating cycle based on the lagged energies and the current operating energy, we can first use the energy lag coefficient corresponding to the current operating cycle to determine the target operating energy transferred from the current operating energy to the current operating cycle—that is, to determine the portion of the current operating energy that can be utilized in the current operating cycle. Then, we calculate the sum of the lagged energies and the target operating energy to obtain the cumulative operating energy for the current operating cycle. This allows us to accurately determine the actual operating energy of the wind turbine in the current operating cycle, enabling the subsequently determined control strategy to precisely match the actual operating state of the wind turbine in the current operating cycle. This further improves the accuracy of wind turbine control, thereby ensuring the power generation efficiency and uniformity of the wind turbine.

[0037] In one feasible implementation, the step of controlling the operation of the wind turbine based on the accumulated operating energy may include steps S401-S402: Step S401: Based on the preset mapping relationship between operating energy and operating target parameters, obtain the operating target parameters corresponding to the accumulated operating energy; It should be noted that the target operating parameters refer to the target parameter values ​​that the wind turbine needs to achieve in order to reach its optimal operating performance (such as maximum efficiency, minimum load, or specific power) under corresponding operating energy conditions. These may include, but are not limited to, target generator torque, target impeller speed, and / or target output power, etc., and this embodiment does not impose specific limitations on them. The mapping relationship between operating energy and target operating parameters can be recorded in the form of relational tables, relational functions, etc., and this embodiment does not impose specific limitations on them.

[0038] For example, assuming the wind turbine needs to achieve maximum efficiency, the greater the operating energy, the greater the target generator torque and the target impeller speed need to be. That is, when the wind turbine needs to achieve maximum efficiency, the mapping relationship between operating energy and target generator torque and target impeller speed is positively correlated.

[0039] Step S402: Control the operation of the fan based on the target operating parameters corresponding to the accumulated operating energy.

[0040] When controlling the operation of a wind turbine based on the target operating parameters corresponding to the accumulated operating energy, a control strategy for the wind turbine can be constructed first using these target parameters, and then the wind turbine can be controlled using this control strategy. Specifically, the target operating parameter (such as the target rotational speed) can be used as the setpoint for the wind turbine controller, and the actual operating parameters of the wind turbine (such as the actual rotational speed) corresponding to the target operating parameter can be used as the feedback value for the wind turbine controller. This allows the wind turbine controller to output a control command based on the deviation between the setpoint and the feedback value, which is used to eliminate the deviation. This control command is then used to control the wind turbine operation. Alternatively, a combination of feedforward and feedback methods can be used to generate control commands to control the wind turbine operation; this embodiment does not specifically limit this approach.

[0041] As can be seen from the above, the technical solution provided in this embodiment, when controlling the operation of the wind turbine, not only considers the current operating energy of the current operating cycle, but also the lag energy transferred from the historical operating energy of multiple previous historical operating cycles to the current operating cycle. This helps to eliminate the impact of energy lag effect on the control accuracy of the wind turbine, thereby effectively improving the accuracy of wind turbine control and ensuring the power generation efficiency and uniformity of the wind turbine.

[0042] Based on the first embodiment described above, a second embodiment of the fan control method of this application is proposed. For the second embodiment, please refer to... Figure 2 Step S20 may include steps S21 to S22: Step S21: Determine the time interval between each historical operating cycle and the current operating cycle; It should be noted that the time interval between each historical operating cycle and the current operating cycle is the absolute value of the time difference between each historical operating cycle and the current operating cycle.

[0043] Step S22: Determine the energy lag coefficient corresponding to each historical operating energy based on the time interval corresponding to each historical operating cycle.

[0044] It should be noted that when determining the energy lag coefficient corresponding to each historical operating energy based on the time interval corresponding to each historical operating cycle, the energy lag coefficient that has a mapping relationship with the time interval corresponding to each historical operating cycle can be obtained based on the preset mapping relationship between the time interval and the energy lag coefficient, and used as the energy lag coefficient corresponding to each historical operating energy.

[0045] The mapping relationship between the time interval and the energy lag coefficient can be recorded in the form of a relation table (i.e., the energy lag coefficient table below), a relation function, or key-value pairs, etc. This embodiment does not make specific limitations on this.

[0046] In one feasible implementation, when using a relational table to record the mapping relationship between time intervals and energy hysteresis coefficients, step S22 may include steps S221-S223: Step S221: For any historical operating cycle, use the time interval corresponding to the historical operating cycle as an index to find the energy lag coefficient corresponding to that time interval in the preset energy lag coefficient table. Step S222: If there is an energy lag coefficient corresponding to the time interval in the energy lag coefficient table, then the energy lag coefficient recorded in the energy lag coefficient table corresponding to the time interval is used as the energy lag coefficient corresponding to the historical operating energy. Step S223: If there is no energy lag coefficient corresponding to the time interval in the energy lag coefficient table, then interpolation calculation is performed in the energy lag coefficient table based on the time interval to obtain the energy lag coefficient corresponding to the historical operating energy.

[0047] This implementation method determines the energy lag coefficient corresponding to historical operating energy by combining table lookup and interpolation calculation. Therefore, for time intervals pre-stored in the energy lag coefficient table, the accurate energy lag coefficient can be directly obtained by table lookup, ensuring both efficiency and accuracy in determining the energy lag coefficient. For time intervals not directly stored in the energy lag coefficient table, the accurate energy lag coefficient can be estimated based on data from nearby reference time intervals through interpolation calculation.

[0048] Further, in a feasible implementation, step S223 may include: obtaining the lower and upper time intervals adjacent to the time interval in the energy lag coefficient table, as well as the energy lag coefficients corresponding to the lower and upper time intervals; calculating the difference between the time interval and the lower time interval to obtain a first time difference, and calculating the difference between the upper and lower time intervals to obtain a second time difference; calculating the ratio between the first and second time differences to obtain a time ratio, and calculating the difference between the energy lag coefficients corresponding to the upper and lower time intervals to obtain a coefficient difference; calculating the sum of the product of the time ratio and the coefficient difference and the energy lag coefficient corresponding to the lower time interval to obtain the energy lag coefficient corresponding to the historical operating energy. Specifically, the above interpolation calculation process can be expressed as the following formula 1.

[0049] Formula 1; Where R0 is the energy lag coefficient corresponding to the historical operating energy, and T is the time interval between the historical operating cycle and the current operating cycle. The upper limit of the time interval. R1 is the lower limit time interval, R2 is the energy lag coefficient corresponding to the lower limit time interval, and R2 is the energy lag coefficient corresponding to the upper limit time interval.

[0050] It should be noted that the lower limit time interval is the reference time interval that is smaller than and closest to the time interval between the historical operating cycle and the current operating cycle among all the time intervals recorded in the energy lag coefficient table; the upper limit time interval is the reference time interval that is larger than and closest to the time interval between the historical operating cycle and the current operating cycle among all the time intervals recorded in the energy lag coefficient table.

[0051] In another feasible implementation, when using a relational function to record the mapping relationship between time intervals and energy lag coefficients, step S22 may include: substituting the time interval between each historical operating cycle and the current operating cycle into the relational function to calculate the energy lag coefficient corresponding to each time interval, which is then used as the energy lag coefficient corresponding to each historical operating energy.

[0052] The above are only two feasible implementation methods of step S22 provided in this embodiment. This embodiment does not specifically limit the specific implementation method of step S22.

[0053] Understandably, since time intervals reflect the natural decay characteristics of historical operating energy during transmission, the longer the time interval, the weaker the residual effect. Therefore, in this embodiment, the energy lag coefficient corresponding to each historical operating energy is determined by utilizing the time interval between each historical operating cycle and the current operating cycle. This ensures that the weight assigned to each historical operating energy matches the physical laws governing its actual effect, thereby ensuring that the subsequently calculated lag energy can accurately quantify the true residual effect at different historical moments, effectively improving the accuracy of wind turbine control.

[0054] Based on the first embodiment described above, a third embodiment of the fan control method of this application is proposed. In the third embodiment, please refer to... Figure 3 Step S20 may include steps S23-S24: Step S23: Determine the time interval between each historical operating cycle and the current operating cycle, and obtain the historical operating parameters of the wind turbine in each historical operating cycle; It should be noted that historical operating parameters refer to physical parameters used to characterize the operating status of the wind turbine in the historical operating cycle. These parameters may include, but are not limited to, historical output power, historical generator speed, historical wind turbine speed and / or historical pitch angle. This embodiment does not make specific limitations on these parameters.

[0055] Step S24: Determine the energy lag coefficient corresponding to each historical operating energy based on the time interval and historical operating parameters corresponding to each historical operating cycle.

[0056] It should be noted that when determining the energy lag coefficient corresponding to each historical operating energy based on the time interval and historical operating parameters corresponding to each historical operating cycle, the energy lag coefficient that has a common mapping relationship with the time interval and historical operating parameters corresponding to each historical operating cycle can be obtained based on the preset mapping relationship between the time interval, operating parameters and energy lag coefficient, and used as the energy lag coefficient corresponding to each historical operating energy.

[0057] The mapping relationship between time interval, operating parameters and energy lag coefficient can be recorded in the form of relational table, relational function or key-value pair, and this embodiment does not make specific limitations on this.

[0058] In one feasible implementation, when using a relational table to record the mapping relationship between time intervals, operating parameters, and energy lag coefficients, step S24 may include: for any historical operating cycle, using the time interval and historical operating parameters corresponding to the historical operating cycle as indexes, searching in a preset relational table for the energy lag coefficient that commonly corresponds to the time interval and the historical operating parameters; if there is an energy lag coefficient that commonly corresponds to the time interval and the historical operating parameters in the relational table, then the energy lag coefficient recorded in the relational table that commonly corresponds to the time interval and the historical operating parameters is used as the energy lag coefficient corresponding to the historical operating energy; if there is no energy lag coefficient that commonly corresponds to the time interval and the historical operating parameters in the relational table, then interpolation calculation is performed in the relational table based on the time interval and the historical operating parameters to obtain the energy lag coefficient corresponding to the historical operating energy.

[0059] When calculating the energy lag coefficient corresponding to the historical operating energy by interpolation in the relation table based on the time interval and historical operating parameters, we can first obtain the lower and upper time intervals adjacent to the current time interval, as well as the lower and upper operating parameters adjacent to the historical operating parameters in the relation table, and obtain the energy lag coefficients corresponding to the four vertices determined by these four values ​​(i.e., including the energy lag coefficients corresponding to the lower time interval and lower operating parameters, the lower time interval and upper operating parameters, the upper time interval and lower operating parameters, and the upper time interval and upper operating parameters); then calculate the energy lag coefficients corresponding to the current time interval and the historical operating parameters. The difference between the lower limit time intervals is used to obtain the first time difference, and the difference between the upper limit time interval and the lower limit time interval is used to obtain the second time difference. Then, the ratio between the first time difference and the second time difference is calculated to obtain the time ratio. Next, the difference between the historical operating parameters and the lower limit operating parameters is calculated to obtain the first operating parameter difference, and the difference between the upper limit operating parameters and the lower limit operating parameters is calculated to obtain the second operating parameter difference. Then, the ratio between the first operating parameter difference and the second operating parameter difference is calculated to obtain the operating parameter ratio. After that, based on the time ratio, the operating parameter ratio, and the energy lag coefficients of the four vertices, bilinear interpolation is performed to obtain the energy lag coefficients corresponding to the historical operating energy. The specific calculation process can be expressed as the following formula 2.

[0060] Formula 2; Where R0 is the energy lag coefficient corresponding to the historical operating energy, rx is the time ratio, ry is the operating parameter ratio, V11 is the energy lag coefficient corresponding to the lower limit time interval and the lower limit operating parameters, V12 is the energy lag coefficient corresponding to the lower limit time interval and the upper limit operating parameters, V21 is the energy lag coefficient corresponding to the upper limit time interval and the lower limit operating parameters, and V22 is the energy lag coefficient corresponding to the upper limit time interval and the upper limit operating parameters.

[0061] It should be noted that the lower limit operating parameter is the reference operating parameter that is less than and closest to the historical operating parameter among all operating parameters recorded in the relation table; the upper limit operating parameter is the reference operating parameter that is greater than and closest to the historical operating parameter among all operating parameters recorded in the relation table.

[0062] This implementation method determines the energy lag coefficient corresponding to historical operating energy by combining table lookup and interpolation calculation. Therefore, for time intervals and historical operating parameters pre-stored in the relationship table, the accurate energy lag coefficient can be directly obtained by table lookup, ensuring both efficiency and accuracy in determining the energy lag coefficient. For time intervals and historical operating parameters not directly stored in the relationship table, the accurate energy lag coefficient can be estimated by interpolation calculation based on data from nearby reference time intervals and reference operating parameters.

[0063] In another feasible implementation, when using a relational function to record the mapping relationship between time intervals, operating parameters and energy lag coefficients, step S24 may include: substituting the time intervals and historical operating parameters corresponding to each historical operating cycle into the relational function to calculate the energy lag coefficient corresponding to each historical operating energy.

[0064] The above are only two feasible implementations of step S24 provided in this embodiment. This embodiment does not specifically limit the specific implementation of step S24.

[0065] Understandably, since the time interval reflects the natural decay trend of historical operating energy during transmission, and historical operating parameters reflect the specific dynamic characteristics of the wind turbine at historical moments (such as inertial load, response speed, etc.), this implementation, when determining the energy lag coefficient corresponding to each historical operating energy, considers not only the time interval between the historical operating cycle and the current operating cycle, but also the historical operating parameters of the wind turbine during its historical operating cycle. This ensures that the determined energy lag coefficient can adapt to the actual operating conditions at historical moments (for example, for the same time interval, if the wind turbine is in a high wind speed and high rotational speed state during the historical operating cycle, its system inertia is greater, and the coefficient decays more slowly; conversely, under low load conditions, the coefficient decays faster). This ensures that the subsequently calculated lag energy can better match the actual physical decay law of the wind turbine during the historical operating cycle, thereby further improving the accuracy of wind turbine control.

[0066] Based on the second and / or third embodiments described above, a fourth embodiment of the wind turbine control method of this application is proposed. In the fourth embodiment, when determining the energy lag coefficients corresponding to each historical operating cycle and the current operating cycle, the operating conditions of adjacent wind turbines (especially upstream wind turbines) in the wind farm can be further considered. Thus, the operating data of adjacent wind turbines in the wind farm (such as real-time power, yaw angle, yaw angle, etc.) can be obtained. Then, based on the operating data of adjacent wind turbines and the relative positions between wind turbines, a wake influence factor is calculated using a pre-trained wake model (such as the Jensen model). This wake influence factor is used to characterize the degree of influence and delay time of the wake of adjacent wind turbines on the wind speed turbulence intensity at the wind turbine. Next, the energy lag coefficients corresponding to each historical operating cycle and the current operating cycle can be determined based on the preset mapping relationship between the wake influence factor, time interval, and energy lag coefficient, or based on the preset mapping relationship between the wake influence factor, time interval, operating parameters, and energy lag coefficient.

[0067] The mapping relationships between wake influence factors, time intervals, and energy lag coefficients, as well as the mapping relationships between wake influence factors, time intervals, and energy lag coefficients, can all be recorded in the form of relational tables. Similarly, during the table lookup process, for data not directly stored in the table, the accurate energy lag coefficients can be estimated through interpolation.

[0068] For example, for the same time interval, when the adjacent wind turbine is an upstream turbine, if the wake influence factor indicates that the turbine is in a strong wake region and the influence has a delay of several seconds, the energy lag coefficient of the turbine will decay more slowly compared to the case without the wake influence of an upstream turbine.

[0069] In this embodiment, the impact of wake effects on the energy transfer process is quantified and introduced to anticipate and compensate for the spatiotemporally delayed coupling effects caused by the operation of adjacent wind turbines. This not only further improves the accuracy of wind turbine control but also effectively enhances the operational economy and grid friendliness of the entire wind farm while ensuring the performance of individual wind turbines.

[0070] This application also provides a control device for a fan; please refer to... Figure 4 The control device for the fan includes: The operating energy acquisition module 10 is used to acquire the current operating energy of the wind turbine in the current operating cycle, as well as the historical operating energy of multiple historical operating cycles prior to the current operating cycle. The inertia coefficient determination module 20 is used to determine the historical operating energy of each historical operating cycle and the energy lag coefficient corresponding to the current operating cycle. The lag energy determination module 30 is used to calculate the lag energy transferred from each historical operating cycle to the current operating cycle based on the historical operating energy of each historical operating cycle and the energy lag coefficient corresponding to each historical operating energy. The control module 40 is used to determine the cumulative operating energy of the current operating cycle based on the lag energy and the current operating energy, and to control the operation of the fan based on the cumulative operating energy.

[0071] In one embodiment, the inertia coefficient determination module 20 is further configured to: Determine the time interval between each historical operating cycle and the current operating cycle; Based on the time intervals corresponding to each historical operating cycle, determine the energy lag coefficient corresponding to each historical operating energy.

[0072] In one embodiment, the inertia coefficient determination module 20 is further configured to: For any historical operating cycle, the energy lag coefficient corresponding to the time interval is searched in the preset energy lag coefficient table, using the time interval corresponding to the historical operating cycle as the index. If an energy lag coefficient corresponding to a time interval exists in the energy lag coefficient table, then the energy lag coefficient corresponding to the time interval recorded in the energy lag coefficient table shall be used as the energy lag coefficient corresponding to the historical operating energy. If there is no energy lag coefficient corresponding to the time interval in the energy lag coefficient table, then interpolation is performed in the energy lag coefficient table based on the time interval to obtain the energy lag coefficient corresponding to the historical operating energy.

[0073] In one embodiment, the inertia coefficient determination module 20 is further configured to: Obtain the lower and upper time intervals adjacent to the time interval from the energy lag coefficient table, as well as the energy lag coefficients corresponding to the lower and upper time intervals; Calculate the difference between the time interval and the lower limit time interval to obtain the first time difference, and calculate the difference between the upper limit time interval and the lower limit time interval to obtain the second time difference; Calculate the ratio between the first time difference and the second time difference to obtain the time ratio, and calculate the difference between the energy lag coefficient corresponding to the upper limit time interval and the energy lag coefficient corresponding to the lower limit time interval to obtain the coefficient difference; The sum of the product of the time ratio and the coefficient difference, and the energy lag coefficient corresponding to the lower limit time interval, yields the energy lag coefficient corresponding to the historical operating energy.

[0074] In one embodiment, the inertia coefficient determination module 20 is further configured to: Determine the time interval between each historical operating cycle and the current operating cycle, and obtain the historical operating parameters of the wind turbine in each historical operating cycle; Based on the time intervals and historical operating parameters corresponding to each historical operating cycle, the energy lag coefficient corresponding to each historical operating energy is determined.

[0075] In one embodiment, the control module 40 is further configured to: Obtain the energy lag coefficient corresponding to the current operating cycle; Calculate the product of the current operating energy and the energy lag coefficient corresponding to the current operating cycle to obtain the target operating energy transferred from the current operating energy to the current operating cycle; Calculate the sum of each delayed energy and the target operating energy to obtain the cumulative operating energy of the current operating cycle.

[0076] In one embodiment, the control module 40 is further configured to: Based on the preset mapping relationship between operating energy and operating target parameters, obtain the operating target parameters corresponding to the accumulated operating energy; The operation of the fan is controlled based on the target parameters corresponding to the accumulated operating energy.

[0077] The wind turbine control device provided in this application adopts the wind turbine control method in the above embodiments, which can improve the accuracy of wind turbine control, thereby ensuring the power generation efficiency and uniformity of the wind turbine. Compared with the prior art, the beneficial effects of the wind turbine control device provided in this application are the same as those of the wind turbine control method provided in the above embodiments, and other technical features in the wind turbine control device are the same as those disclosed in the methods of the above embodiments, and will not be repeated here.

[0078] This application also provides a control device, which may include: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform the fan control method in the above embodiments.

[0079] The following is for reference. Figure 5 It shows a schematic diagram of the structure of a control device suitable for implementing the embodiments of this application. Figure 5 The control device shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of this application.

[0080] like Figure 5 As shown, the control device may include a processing unit 101 (e.g., a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to a program stored in read-only memory 102 or a program loaded from storage device 103 into random access memory 104. Random access memory 104 also stores various programs and data required for the operation of the control device. The processing unit 101, read-only memory 102, and random access memory 104 are interconnected via bus 105. Input / output interface 106 is also connected to bus 105. Typically, the following systems can be connected to input / output interface 106: input devices 107 including, for example, touch screens, touchpads, keyboards, mice, image sensors, microphones, accelerometers, gyroscopes, etc.; output devices 108 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 103 including, for example, magnetic tapes, hard disks, etc.; and communication devices 109. Communication device 109 allows the control device to communicate wirelessly or wiredly with other devices to exchange data. Although the diagram shows control equipment with various systems, it should be understood that it is not required to implement or have all of the systems shown. More or fewer systems may be implemented alternatively.

[0081] In particular, according to embodiments of this disclosure, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of this disclosure include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device, or installed from storage device 103, or installed from read-only memory 102. When the computer program is executed by processing device 101, it performs the functions defined in the methods of the embodiments of this application.

[0082] The control device provided in this application, employing the wind turbine control method described in the above embodiments, can improve the accuracy of wind turbine control, thereby ensuring the power generation efficiency and uniformity of the wind turbine. Compared with the prior art, the beneficial effects of the control device provided in this application are the same as those of the wind turbine control method provided in the above embodiments, and other technical features in the control device are the same as those disclosed in the methods of the above embodiments, and will not be repeated here.

[0083] It should be understood that various parts of the embodiments of this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any suitable manner in one or more embodiments or examples.

[0084] The above description is merely a specific implementation of the embodiments of this application, but the protection scope of the embodiments of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the protection scope of the embodiments of this application. Therefore, the protection scope of the embodiments of this application should be determined by the protection scope of the above claims.

[0085] This application also provides a computer-readable storage medium storing a computer program that can run on a processor. The computer program is used to execute the fan control method in the above embodiments.

[0086] The computer-readable storage medium provided in this application embodiment may be, for example, a USB flash drive, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems or devices, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections with one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, system, or device. The program code contained on the computer-readable storage medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination thereof.

[0087] The aforementioned computer-readable storage medium may be included in the control device; or it may exist independently and not assembled into the control device.

[0088] The aforementioned computer-readable storage medium carries one or more programs. When the aforementioned one or more programs are executed by the control device, the control device causes the control device to: acquire the current operating energy of the wind turbine in the current operating cycle, and the historical operating energy of multiple historical operating cycles prior to the current operating cycle; determine the energy lag coefficient corresponding to the historical operating energy of each historical operating cycle in the current operating cycle; calculate the lag energy transferred from each historical operating cycle to the current operating cycle based on the historical operating energy of each historical operating cycle and the corresponding energy lag coefficient; determine the cumulative operating energy of the current operating cycle based on the lag energy and the current operating energy, and control the wind turbine operation based on the cumulative operating energy.

[0089] Computer program code for performing the operations of this disclosure can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0090] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, 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 indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated 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 the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0091] The modules described in the embodiments of this application can be implemented in software or hardware. The names of the modules do not necessarily limit the functionality of the unit itself.

[0092] The computer-readable storage medium provided in this application embodiment stores computer-readable program instructions for executing the wind turbine control method described above, which can improve the accuracy of wind turbine control and ensure the power generation efficiency and uniformity of the wind turbine. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this application embodiment are the same as the beneficial effects of the wind turbine control method provided in the above embodiments, and will not be repeated here.

[0093] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the wind turbine control method described above.

[0094] The computer program product provided in this application can improve the accuracy of wind turbine control, thereby ensuring the power generation efficiency and uniformity of the wind turbine. Compared with the prior art, the beneficial effects of the computer program product provided in this application are the same as those of the wind turbine control method provided in the above embodiments, and will not be repeated here.

[0095] The above are merely preferred embodiments of this application and do not limit the patent scope of this application. Any equivalent structural or procedural transformations made using the content of this application's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent scope of this application.

Claims

1. A method for controlling a fan, characterized in that, The method includes: Obtain the current operating energy of the wind turbine in the current operating cycle, as well as the historical operating energy of multiple historical operating cycles prior to the current operating cycle; Determine the historical operating energy for each of the aforementioned historical operating cycles, and the energy lag coefficient corresponding to the current operating cycle; Based on the historical operating energy of each historical operating cycle and the energy lag coefficient corresponding to each historical operating energy, the lag energy transmitted from each historical operating cycle to the current operating cycle is calculated; Based on the lag energy and the current operating energy, the cumulative operating energy of the current operating cycle is determined, and the operation of the wind turbine is controlled according to the cumulative operating energy.

2. The method as described in claim 1, characterized in that, The step of determining the historical operating energy of each of the historical operating cycles, and the energy lag coefficient corresponding to the current operating cycle, includes: Determine the time interval between each of the historical operating cycles and the current operating cycle; Based on the time intervals corresponding to each of the historical operating cycles, the energy lag coefficient corresponding to each of the historical operating energies is determined.

3. The method as described in claim 2, characterized in that, The step of determining the energy lag coefficient corresponding to each of the historical operating energies based on the time intervals corresponding to each of the historical operating cycles includes: For any of the aforementioned historical operating cycles, the energy lag coefficient corresponding to the time interval is searched in the preset energy lag coefficient table using the time interval corresponding to the historical operating cycle as an index. If an energy lag coefficient corresponding to the time interval exists in the energy lag coefficient table, then the energy lag coefficient recorded in the energy lag coefficient table corresponding to the time interval shall be used as the energy lag coefficient corresponding to the historical operating energy. If there is no energy lag coefficient corresponding to the time interval in the energy lag coefficient table, then interpolation calculation is performed in the energy lag coefficient table based on the time interval to obtain the energy lag coefficient corresponding to the historical operating energy.

4. The method as described in claim 3, characterized in that, The step of interpolating and calculating the energy lag coefficient corresponding to the historical operating energy based on the time interval in the energy lag coefficient table includes: Obtain the lower limit time interval and upper limit time interval adjacent to the time interval in the energy lag coefficient table, as well as the energy lag coefficient corresponding to the lower limit time interval and the energy lag coefficient corresponding to the upper limit time interval; Calculate the difference between the time interval and the lower limit time interval to obtain a first time difference, and calculate the difference between the upper limit time interval and the lower limit time interval to obtain a second time difference; Calculate the ratio between the first time difference and the second time difference to obtain the time ratio, and calculate the difference between the energy lag coefficient corresponding to the upper limit time interval and the energy lag coefficient corresponding to the lower limit time interval to obtain the coefficient difference; The sum of the product of the time ratio and the coefficient difference, and the energy lag coefficient corresponding to the lower limit time interval, is used to obtain the energy lag coefficient corresponding to the historical operating energy.

5. The method as described in claim 1, characterized in that, The step of determining the historical operating energy of each of the historical operating cycles, and the energy lag coefficient corresponding to the current operating cycle, includes: Determine the time interval between each of the historical operating cycles and the current operating cycle, and obtain the historical operating parameters of the wind turbine in each of the historical operating cycles; Based on the time interval and historical operating parameters corresponding to each of the historical operating cycles, the energy lag coefficient corresponding to each of the historical operating energies is determined.

6. The method according to any one of claims 1 to 5, characterized in that, The step of determining the cumulative operating energy of the current operating cycle based on the respective hysteresis energy and the current operating energy includes: Obtain the energy lag coefficient corresponding to the current operating cycle; Calculate the product of the current operating energy and the energy lag coefficient corresponding to the current operating cycle to obtain the target operating energy transferred from the current operating energy to the current operating cycle; The sum of the lag energy and the target operating energy is calculated to obtain the cumulative operating energy of the current operating cycle.

7. The method according to any one of claims 1 to 5, characterized in that, The step of controlling the operation of the wind turbine based on the accumulated operating energy includes: Based on the preset mapping relationship between operating energy and operating target parameters, the operating target parameters corresponding to the accumulated operating energy are obtained; The operation of the wind turbine is controlled based on the target operating parameters corresponding to the accumulated operating energy.

8. A control device for a fan, characterized in that, The control device for the fan includes: The operating energy acquisition module is used to acquire the current operating energy of the wind turbine in the current operating cycle, as well as the historical operating energy of multiple historical operating cycles prior to the current operating cycle. An inertia coefficient determination module is used to determine the historical operating energy of each of the historical operating cycles, and the energy lag coefficient corresponding to the current operating cycle. The lag energy determination module is used to calculate the lag energy transferred from each of the historical operating cycles to the current operating cycle based on the historical operating energy of each of the historical operating cycles and the energy lag coefficient corresponding to each of the historical operating energies. The control module is used to determine the cumulative operating energy of the current operating cycle based on the hysteresis energy and the current operating energy, and to control the operation of the wind turbine based on the cumulative operating energy.

9. A control device, characterized in that, The control device includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the wind turbine control method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the steps of the wind turbine control method as described in any one of claims 1 to 7.

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