Wind farm noise control methods, devices and electronic equipment

Abstract

This application discloses a method, apparatus, and electronic device for wind farm noise control. The wind farm noise control method includes: acquiring preset noise measurement values ​​for sensitive areas of the wind farm; if the noise measurement value of any sensitive area exceeds a preset noise threshold, then using the constraint that the calculated noise value of the sensitive area does not exceed the preset noise threshold, and taking the maximization of power generation by wind turbines within the wind farm as the optimization objective, calculating control parameters for the wind turbines within the wind farm based on wind turbine operating data, ambient temperature and humidity data, and a preset noise propagation model; and controlling the wind turbines within the wind farm using the calculated control parameters. According to the embodiments of this application, the technical problem of balancing wind farm power generation and noise in sensitive areas in related technologies can be solved.

Description

Technical Field

[0001] This application belongs to the field of wind power technology, and in particular relates to a method, device and electronic equipment for wind farm noise control. Background Technology

[0002] Current wind farm noise control technology primarily involves establishing a wind farm noise propagation model to calculate the noise level in sensitive areas. If the noise exceeds the limit, the control parameters of the wind turbines are adjusted. The noise level in the sensitive area after parameter adjustments is a simulation value obtained from the wind farm noise propagation model, which deviates from the actual noise value and cannot definitively determine whether the sensitive area meets the standard. While excessively restricting wind turbine power generation within the wind farm may increase the likelihood of noise compliance in sensitive areas, it also limits the wind farm's overall power generation, resulting in power loss. Summary of the Invention

[0003] This application provides a wind farm noise control method, device, and electronic equipment, which can solve the technical problem in related technologies that it is difficult to balance wind farm power generation and noise in sensitive areas.

[0004] In a first aspect, embodiments of this application provide a wind farm noise control method, the method comprising:

[0005] Obtain noise measurement values ​​for the preset sensitive areas of the wind farm;

[0006] If the noise measurement value of any sensitive area exceeds the preset noise threshold, then the calculated noise value of the sensitive area does not exceed the preset noise threshold as a constraint, and the power generation of the wind turbines in the wind farm is maximized as the optimization objective. Based on the wind turbine operation data, ambient temperature and humidity data and preset noise propagation model, the control parameters of the wind turbines in the wind farm are calculated.

[0007] The wind turbines in the wind farm are controlled by the calculated control parameters.

[0008] Optionally, after controlling the wind turbines in the wind farm using the calculated control parameters, the method may further include repeatedly performing the following steps until the current noise measurement value in the sensitive area is lower than or equal to a preset noise threshold:

[0009] After a preset time period, the updated noise measurement value of the sensitive area is acquired again;

[0010] If the updated noise measurement value exceeds the preset noise threshold, the model parameters of the preset noise propagation model will be adjusted.

[0011] Based on the constraints and optimization objectives, the control parameters are recalculated using the wind turbine operation data, ambient temperature and humidity data, and a preset noise propagation model within the wind farm.

[0012] The wind turbines in the wind farm are controlled by recalculated control parameters.

[0013] Optionally, calculating the control parameters of wind turbines within a wind farm may include:

[0014] Within the available speed range of wind turbines in a wind farm, calculate the noise level in the sensitive area and the power of the wind turbines in the wind farm when the wind turbines operate at different speeds.

[0015] Within the available speed range, determine the target speed for each wind turbine generator set that ensures the calculated noise value does not exceed the preset noise threshold and maximizes power.

[0016] The target speed of each wind turbine generator set is taken as the upper limit of the speed of the corresponding unit, and the maximum output power corresponding to the target speed of each wind turbine generator set is taken as the upper limit of the output power of the corresponding unit.

[0017] The control parameters include the upper limit of the rotational speed and the upper limit of the output power of each wind turbine generator set.

[0018] Optionally, the method may further include:

[0019] Calculate the optimal pitch angle for each wind turbine to output maximum power at the corresponding target speed; the control parameters for each wind turbine also include the optimal pitch angle.

[0020] Optionally, calculating the control parameters of wind turbines within a wind farm may include:

[0021] Obtain the objective function for calculating the power generation of wind turbines in a wind farm based on the control parameters of the wind turbines in the wind farm.

[0022] With the constraint that the calculated noise value in the sensitive area does not exceed the preset noise threshold, the objective function is iteratively calculated until convergence based on the optimization algorithm to maximize the power generation of the wind turbines in the wind farm.

[0023] Determine the control parameters of the wind turbines in the wind farm that make the objective function converge.

[0024] Secondly, embodiments of this application provide a wind farm noise control device, the device comprising:

[0025] Acquisition unit, used to acquire noise measurement values ​​of a preset sensitive area of ​​a wind farm;

[0026] The first calculation unit is used to calculate the control parameters of the wind turbines in the wind farm based on the wind turbine operation data, environmental temperature and humidity data and the preset noise propagation model, if the noise measurement value of any sensitive area exceeds the preset noise threshold. The constraint is that the calculated noise value of the sensitive area does not exceed the preset noise threshold. The optimization objective is to maximize the power generation of the wind turbines in the wind farm.

[0027] The control unit is used to control the wind turbines in the wind farm using calculated control parameters.

[0028] Optionally, the device can be installed in the controller of the wind farm.

[0029] Optionally, the device may further include a cyclic execution unit for repeatedly executing the following steps after controlling the wind turbines in the wind farm with calculated control parameters, until the current noise measurement value in the sensitive area is lower than or equal to a preset noise threshold:

[0030] After a preset time period, the updated noise measurement value of the sensitive area is acquired again;

[0031] If the updated noise measurement value exceeds the preset noise threshold, the model parameters of the preset noise propagation model will be adjusted.

[0032] Based on the constraints and optimization objectives, the control parameters are recalculated using the wind turbine operation data, ambient temperature and humidity data, and a preset noise propagation model within the wind farm.

[0033] The wind turbines in the wind farm are controlled by recalculated control parameters.

[0034] Optionally, the first computing unit may include:

[0035] The first calculation subunit is used to calculate the noise value of the sensitive area and the power of the wind turbines in the wind farm when the wind turbines are running at different speed values ​​within the available speed range of the wind turbines in the wind farm.

[0036] The first determining subunit is used to determine the target speed of each wind turbine generator set within the available speed range, so that the calculated noise value does not exceed the preset noise threshold and the power is maximized.

[0037] The second determining subunit is used to take the target speed of each wind turbine generator set as the upper limit of the speed of the corresponding unit, and take the maximum output power corresponding to the target speed of each wind turbine generator set as the upper limit of the output power of the corresponding unit.

[0038] The control parameters include the upper limit of the rotational speed and the upper limit of the output power of each wind turbine generator set.

[0039] Optionally, the device may further include:

[0040] The second calculation unit is used to calculate the optimal pitch angle of each wind turbine when it outputs the maximum output power at the corresponding target speed; the control parameters of each wind turbine also include the optimal pitch angle.

[0041] Optionally, the first computing unit may include:

[0042] The sub-unit is used to obtain the objective function for calculating the power generation of wind turbines in the wind farm based on the control parameters of the wind turbines in the wind farm.

[0043] The second calculation subunit is used to iteratively calculate the objective function until convergence based on the optimization algorithm, with the constraint that the calculated noise value of the sensitive area does not exceed the preset noise threshold, so as to maximize the power generation of the wind turbine units in the wind farm.

[0044] The third determining sub-unit is used to determine the control parameters of the wind turbines in the wind farm that make the objective function converge.

[0045] Thirdly, embodiments of this application provide an electronic device, which includes: a processor and a memory storing program instructions; when the processor executes the program instructions, it implements the wind farm noise control method as described in the first aspect.

[0046] Optionally, the electronic device can be installed in the controller of the wind farm.

[0047] Fourthly, embodiments of this application provide a readable storage medium storing program instructions that, when executed by a processor, implement the wind farm noise control method as described in the first aspect.

[0048] Fifthly, embodiments of this application provide a program product in which instructions, when executed by a processor of an electronic device, enable the electronic device to perform the wind farm noise control method as described in the first aspect.

[0049] In a sixth aspect, embodiments of this application provide a wind farm controller, which may include the wind farm noise control device provided in the second aspect of embodiments of this application, or the electronic device provided in the third aspect of embodiments of this application.

[0050] The wind farm noise control method, apparatus, electronic device, readable storage medium, and program product of this application acquire preset noise measurement values ​​of sensitive areas of the wind farm. When the noise measurement value of any sensitive area exceeds a preset noise threshold, the calculated noise value of the sensitive area does not exceed the preset noise threshold as a constraint. The optimization objective is to maximize the power generation of the wind turbines in the wind farm. Based on the operating data of the wind turbines in the wind farm, the ambient temperature and humidity data, and a preset noise propagation model, the control parameters of the wind turbines in the wind farm are calculated. The wind turbines in the wind farm are controlled by the calculated control parameters. This solves the technical problem in related technologies that it is difficult to balance the power generation of the wind farm and the noise in sensitive areas. It increases the power generation of the wind farm while ensuring that the noise in sensitive areas does not exceed the limit. Attached Figure Description

[0051] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments of this application will be briefly introduced below. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0052] Figure 1 This is a schematic diagram illustrating the correlation between temperature, humidity, and noise measurements;

[0053] Figure 2 This is a flowchart illustrating a wind farm noise control method provided in one embodiment of this application;

[0054] Figure 3 This is a schematic diagram illustrating an application scenario of a wind farm noise control method provided in one embodiment of this application;

[0055] Figure 4 This is a flowchart illustrating a wind farm noise control method provided in another embodiment of this application;

[0056] Figure 5 This is a flowchart illustrating a wind farm noise control method provided in another embodiment of this application;

[0057] Figure 6 This is a schematic diagram of the structure of a wind farm noise control device provided in another embodiment of this application;

[0058] Figure 7 This is a schematic diagram of the structure of an electronic device provided in another embodiment of this application. Detailed Implementation

[0059] The features and exemplary embodiments of various aspects of this application will be described in detail below. To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain this application and not to limit it. For those skilled in the art, this application can be implemented without some of these specific details. The following description of the embodiments is merely to provide a better understanding of this application by illustrating examples.

[0060] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that 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. Without further limitations, an element defined by the phrase "comprising..." does not exclude the presence of additional identical elements in the process, method, article, or apparatus that includes said element.

[0061] As the installed density of wind turbines continues to increase, wind turbines are being placed closer and closer to residential areas. To prevent the spread of wind turbine noise from affecting residents' normal activities, wind farm noise control technology is receiving increasing attention. Related technologies offer solutions including switching noise modes based on wind conditions and time of day; using sound power management software to optimize wind turbine control settings based on real-time wind conditions to achieve wind farm noise control; or employing a noise control system to adjust the pitch angle or reduce the rotational speed based on time and wind direction changes to achieve noise reduction and maximum output.

[0062] However, the main solution for wind farm noise control in related technologies is to establish a wind farm noise propagation model to calculate the noise level at sensitive points (also called sensitive buildings, referring to buildings that need to remain quiet, such as hospitals, schools, government offices, research institutions, and residences; in this application embodiment, they are also referred to as sensitive areas). If the noise exceeds the limit, the control parameters of the wind turbine are changed to reduce the calculated noise in the sensitive area. Since the controlled noise level in the sensitive area is also a simulation calculation value, it deviates somewhat from the actual measured noise value, making it impossible to determine whether the sensitive area meets the environmental impact assessment standards, thus posing a certain risk.

[0063] Furthermore, the relevant technologies only considered the influence of wind conditions and did not take into account the impact of ambient temperature and humidity on the propagation of wind farm noise. The applicant's research has found that ambient temperature and humidity have a significant impact on noise propagation, and changes in ambient temperature and humidity also cause changes in measured noise values ​​in sensitive areas, see [reference needed]. Figure 1 As shown, changes in ambient temperature and humidity can affect the measured noise levels in sensitive areas. If control is based solely on simulation results, the actual measured noise levels in sensitive areas may be significantly higher than the simulated values, leading to noise pollution. Alternatively, limiting the simulated noise levels in sensitive areas of the wind farm to excessively low limits would cause wind turbines to operate at even lower power levels, resulting in substantial power generation losses. This makes it difficult to balance the power generation of the wind farm with the noise levels in sensitive areas.

[0064] To address the problems of the prior art, embodiments of this application provide a wind farm noise control method, apparatus, device, and readable storage medium. The wind farm noise control method provided in this application embodiment will be described first below.

[0065] Figure 2 A flowchart illustrating a wind farm noise control method according to an embodiment of this application is shown. Figure 2 As shown, the method includes the following steps:

[0066] Step 101: Obtain noise measurement values ​​for the preset sensitive areas of the wind farm.

[0067] The wind farm noise control method provided in this application embodiment can be applied to a noise control system. Addressing the issue of inaccurate noise control at sensitive points, this method can measure the noise level in the sensitive area requiring noise control in real time using a noise monitoring device and return the noise measurement data to the noise control system, forming a closed-loop control. Optionally, the noise monitoring device can be a noise monitoring microphone used to monitor noise in the sensitive area, collecting and transmitting noise data from the sensitive area (within or around it). Alternatively, a portable noise testing device can be used to measure the noise in the sensitive area.

[0068] Optionally, the noise measurement value can be obtained by analyzing the noise data of the sensitive area collected, filtering out abnormal noise, and then correcting the background noise, which can be obtained through measurement.

[0069] Step 102: If the noise measurement value of any sensitive area exceeds the preset noise threshold, then the calculated noise value of the sensitive area does not exceed the preset noise threshold as a constraint, and the power generation of the wind turbines in the wind farm is maximized as the optimization objective. Based on the wind turbine operation data, ambient temperature and humidity data and preset noise propagation model, the control parameters of the wind turbines in the wind farm are calculated.

[0070] The preset noise threshold is a pre-defined threshold. Optionally, to more accurately control noise in sensitive areas, the preset noise threshold can be adjusted based on changes in different environmental factors. For example, since changes in ambient temperature and humidity affect the noise propagation distance, the corresponding preset noise threshold can be found in real time based on the monitored ambient temperature and humidity, and the preset noise threshold can be dynamically adjusted in real time. Optionally, it is also possible to automatically switch between different limits (preset noise thresholds) for noise around sensitive areas during the day and night (or other different time periods) based on time conditions.

[0071] When the noise measurement value of any sensitive area exceeds the preset noise threshold, step 102 is triggered to calculate the control parameters of the wind turbines in the wind farm. Optionally, the noise measurement value of the sensitive area is judged to see if it exceeds the preset noise threshold at preset time intervals.

[0072] When calculating the control parameters of wind turbines in a wind farm, the constraint is that the calculated noise value in the sensitive area does not exceed the preset noise threshold.

[0073] The noise calculation value can be calculated based on the wind turbine operation data, ambient temperature and humidity data, and the preset noise propagation model in the wind farm.

[0074] The input parameters for the preset noise propagation model include wind turbine operating data and ambient temperature and humidity data within the wind farm. These data can be monitored using appropriate sensors.

[0075] In one example, this can be obtained from the wind farm controller (WFC). The WFC is the hardware carrier for the wind farm cluster control system to make cluster control decisions on the wind turbines at the wind farm side. It consists of two parts: a real-time core part and a non-real-time core part. The WFC can be used to execute control of the wind turbines within the wind farm.

[0076] Based on the above input parameters, the preset noise propagation model can calculate the noise value in the sensitive area. The noise calculation value can be regarded as a theoretical simulation calculation value.

[0077] Wind turbine operating data can include wind conditions within the wind farm and various operating parameters of the wind turbine. Addressing the issue of incomplete consideration of noise influencing factors in related technologies, this application considers environmental factors in addition to operating data, specifically including ambient temperature and humidity. In this embodiment, ambient temperature and humidity values ​​can be measured using an ambient temperature and humidity meter installed on the turbine. Since the difference in ambient temperature and humidity within a wind farm at the same time is small, the average value can be taken. Optionally, factors such as noise absorption / blocking / reflection can also be included to achieve precise noise control in sensitive areas. The wind farm noise control method provided in this embodiment can achieve more precise control of noise levels in sensitive areas while avoiding unnecessary power generation losses due to excessive control.

[0078] Since the operating data of wind turbines includes controllable parameters such as pitch angle, maximum speed, and maximum power, noise calculations can be performed by iterating through the selectable range of wind turbine control parameters. This allows us to obtain wind turbine control parameters that ensure the noise calculations do not exceed a preset noise threshold (constraint) and maximize power generation (specifically, the sum of the power of all wind turbines in the wind farm) (optimization objective).

[0079] In one optional implementation, calculating the control parameters of wind turbines within a wind farm may include the following steps:

[0080] Step 1021: Obtain the objective function for calculating the power generation of the wind turbines in the wind farm based on the control parameters of the wind turbines in the wind farm.

[0081] The objective function is established based on the formula for calculating power generation. The independent variables of the objective function include the control parameters of the wind turbine, while the dependent variable is power generation. The objective is to maximize the objective function.

[0082] Step 1022: With the noise calculation value of the sensitive area not exceeding the preset noise threshold as a constraint, the objective function is iteratively calculated until convergence based on the optimization algorithm, so as to maximize the power generation of the wind turbine units in the wind farm.

[0083] Alternatively, the optimization algorithm can be the OpenMDAO optimization algorithm.

[0084] Once the objective function converges during iterative calculation, the maximum power generation achievable by the wind turbine control parameters within the selectable range can be obtained.

[0085] Step 1023: Determine the control parameters of the wind turbines in the wind farm that enable the objective function to converge.

[0086] When the objective function converges, the control parameters of the wind turbines in the wind farm are the final output control parameters used to control the wind turbines in the wind farm. Here, in addition to ensuring the convergence of the objective function, it is also necessary to satisfy the constraint condition, that is, to ensure that the noise calculated based on the control parameters of the wind turbines (the wind turbine operating data includes the wind turbine control parameters) does not exceed the preset noise threshold.

[0087] Step 103: Control the wind turbines in the wind farm using the calculated control parameters.

[0088] After the control parameters are calculated in step 102, the wind turbines in the wind farm are controlled using the calculated control parameters.

[0089] Optionally, since there may be some error between the theoretical calculation results of the preset noise propagation model and the actual measurement data, after controlling the wind turbines in the wind farm through the calculated control parameters, closed-loop control can also be performed. The model parameters in the preset noise propagation model can be repeatedly adjusted by using feedback such as whether the noise measurement value obtained by real-time monitoring in the sensitive area exceeds the preset noise threshold, so that the preset noise propagation model can better match the actual propagation situation.

[0090] Specifically, controlling wind turbines within a wind farm using calculated control parameters can include cyclically executing the following steps until the current noise measurement value in the sensitive area is lower than or equal to a preset noise threshold:

[0091] Step 1041: After a preset time period, acquire the updated noise measurement value of the sensitive area again.

[0092] The preset duration is the adjustment cycle. After one cycle, updated noise measurements from the monitoring of the sensitive area are acquired again.

[0093] Step 1042: If the updated noise measurement value exceeds the preset noise threshold, then adjust the model parameters of the preset noise propagation model.

[0094] Here, if the monitored updated noise measurement value exceeds the preset noise threshold, it indicates that the preset noise propagation model may have errors compared to the actual propagation situation. In order to more accurately simulate the noise and obtain a noise calculation value that better matches the actual measured noise, the model parameters of the preset noise propagation model can be adjusted. Adjusting the model parameters can employ feedback algorithms from related technologies, such as loss functions, etc., and this application embodiment does not limit this approach.

[0095] Step 1043: Based on the constraints and optimization objectives, calculate the control parameters again according to the wind turbine operation data in the wind farm, the ambient temperature and humidity data, and the adjusted preset noise propagation model.

[0096] After updating the preset noise propagation model, the preset noise model used in the constraints is the updated and adjusted preset noise propagation model. That is, the objective function remains unchanged, and the control parameters are calculated to make the objective function optimal, and the noise calculated by the adjusted preset noise propagation model does not exceed the preset noise threshold.

[0097] Step 1044: Control the wind turbines in the wind farm by recalculating the control parameters.

[0098] In one optional implementation, the control parameters may include the upper limit of the rotational speed and the upper limit of the output power of each wind turbine generator. When calculating the control parameters of the wind turbine generators in the wind farm, the noise level in the sensitive area and the power of the wind turbine generators in the wind farm can be calculated within the available rotational speed range of the wind turbine generators in the wind farm at different rotational speeds (the control parameters of the wind turbine generators include rotational speed).

[0099] Furthermore, within the available speed range, the target speed of each wind turbine generator set is determined such that the calculated noise value does not exceed the preset noise threshold and the power is maximized. The target speed of each wind turbine generator set is taken as the upper limit of the speed of the corresponding unit, and the maximum output power corresponding to the target speed of each wind turbine generator set is taken as the upper limit of the output power of the corresponding unit.

[0100] The control parameters for each wind turbine can be the same, or they can be fine-tuned based on the different conditions of each wind turbine. For example, when the distance between the wind turbine and the grid connection point varies, there will be some power transmission loss, and the control parameters can be adjusted based on the distance.

[0101] Optionally, when calculating the optimal pitch angle at the corresponding target speed for each wind turbine generator set, the optimal pitch angle at which the maximum output power is achieved can be output. That is, the control parameters of each wind turbine generator set can also include the optimal pitch angle, and the wind turbine generator set can be controlled by the optimal pitch angle.

[0102] The wind farm noise control method provided in this application can achieve real-time dynamic optimization control based on noise measurement values ​​of one or more sensitive areas of the wind farm. In some optional embodiments, the model parameters of a preset noise propagation model can also be optimized based on the feedback results after control. The control range can cover any type and number of wind turbine generators within the wind farm.

[0103] The wind farm noise control method of this application embodiment obtains the noise measurement values ​​of the sensitive areas of the wind farm in a preset manner. When the noise measurement value of any sensitive area exceeds the preset noise threshold, the method uses the constraint that the calculated noise value of the sensitive area does not exceed the preset noise threshold. The optimization objective is to maximize the power generation of the wind turbines in the wind farm. Based on the operating data of the wind turbines in the wind farm, the ambient temperature and humidity data, and the preset noise propagation model, the method calculates the control parameters of the wind turbines in the wind farm. The wind turbines in the wind farm are then controlled by the calculated control parameters. This method can solve the technical problem in related technologies that it is difficult to balance the power generation of the wind farm and the noise in the sensitive areas. It can improve the power generation of the wind farm while ensuring that the noise in the sensitive areas does not exceed the limit.

[0104] A schematic diagram of an optional application scenario for the wind farm noise control method provided in this application embodiment is shown below. Figure 3 As shown, wind farm noise control methods can be derived from... Figure 3 The Wind Farm Controller (WFC) shown is the hardware carrier for the wind farm control system to make cluster control decisions on the wind turbine units at the wind farm side. It consists of two parts: a real-time core part and a non-real-time core part. The WFC can be used to control the wind turbine units in the wind farm.

[0105] Figure 3 The paper also provides a wind farm noise control system, which may include the following devices:

[0106] The user terminal can be used to set preset noise thresholds for sensitive areas, configure information about wind turbines and sensitive areas within the wind farm, enable / disable the wind farm noise control function provided by the wind farm noise control method provided in this application embodiment, and view wind farm noise control logs, etc.

[0107] The Wind Farm Controller (WFC) is used to store data, interpret codes, run programs, and perform noise test data analysis. It is the core device of the wind farm noise control system.

[0108] The data interface is a unit used to acquire wind turbine operating data and environmental data of sensitive areas, and can send unit control commands to noise monitoring equipment in sensitive areas;

[0109] A noise monitoring microphone is a noise monitoring device installed in a sensitive area to measure the noise level in or around the sensitive area and transmit the measured noise values ​​to the WFC via a data interface.

[0110] like Figure 4 The image shows a model based on... Figure 3An optional implementation of a wind farm noise control method for a provided wind farm noise control system is provided. In this implementation, the wind farm noise control method can be periodically triggered. After the noise control function of the wind farm noise control method is enabled, the control program is executed once every periodic time T (step 204). The program execution method may include the following flow:

[0111] Step 201: Before carrying out wind farm noise control, configure the information of the controlled wind turbines and the sensitive areas of the wind farm, establish a preset noise propagation model for the wind farm, and set the preset noise threshold for the sensitive areas.

[0112] Step 202: After the wind farm noise control function is enabled, acquire wind turbine operation data, ambient temperature and humidity data, acquire noise measurement data of sensitive areas, filter abnormal noise, and obtain noise measurement values ​​of sensitive areas.

[0113] Step 203: Determine whether at least one sensitive area has a noise measurement value greater than a preset noise threshold.

[0114] If step 203 determines that it is yes, then step 205 is executed. Based on the wind turbine operating data, ambient temperature and humidity data, wind farm noise propagation model and noise optimization algorithm, the wind turbine control parameters that satisfy the preset noise threshold and maximize the power generation of the wind farm are calculated.

[0115] Next, step 206 is executed, and control parameters are sent to each unit. After executing step 206, step 207 is executed, and each unit executes the control parameter instructions. Furthermore, step 208 is executed, and noise measurement data of sensitive areas is acquired again. Abnormal noise is filtered to obtain the noise measurement values ​​of sensitive areas, and it is determined whether at least one sensitive area noise measurement value is greater than a preset noise threshold.

[0116] If the result of step 209 is yes, then step 210 is executed to correct the coefficients of the wind farm noise propagation model, resulting in the corrected wind farm noise propagation model. Steps 205 to 209 are then repeated until the result of step 209 is no, and the generator set continues to operate according to the latest set of control parameters.

[0117] If step 203 is negative, it means that the noise measurement value of no sensitive area exceeds the preset noise threshold. Then, step 209 is executed, and the wind turbine continues to execute according to the current control parameters until the condition of step 204 is met, and the next cycle begins.

[0118] During step 209, while maintaining the current control parameters, changes in yaw position affecting noise directivity or environmental temperature and humidity affecting noise propagation may cause variations in noise measurements in sensitive areas. Therefore, optimization can be performed periodically (t) to calculate the unit's control parameters, achieving real-time dynamic control of noise at sensitive points. The above optional implementation forms a closed loop for noise control at sensitive points in the wind farm, ensuring that noise measurements in sensitive areas remain within the required threshold range.

[0119] In each cycle, when executing step 205: calculating the optimal control parameters for the unit that meet the noise limits based on generator set operating data, ambient temperature and humidity data, wind farm noise propagation model, and noise optimization algorithm, an optional implementation method can be as follows: Figure 5 The implementation method shown is executed.

[0120] Specifically, refer to Figure 5 If step 203 determines that it is yes, then step 2051 is executed to obtain real-time wind turbine operation data, ambient temperature and humidity data, and preset noise thresholds, and then step 2052 is executed to calculate the noise calculation value of the sensitive area using the preset noise propagation model of the wind farm.

[0121] Then, step 2053 is executed. The OpenMDAO optimization algorithm is used to set the constraint condition that the noise calculation value does not exceed the preset noise threshold. The optimization independent variable of the wind turbine (the optimization independent variable can be included in the control parameters, for example, it can be the speed) traverses the entire available value range of the speed and finds the speed at which the power sum is the maximum as the target speed, that is, the target variable.

[0122] Next, step 2054 is executed. In each iteration of the above optimization algorithm, the noise value of the sensitive area and the power of the wind turbine are calculated until the power sum function (objective function) converges, and the following optimization results are obtained:

[0123] The noise calculation value when the objective function of the sensitive area is optimal and the noise calculation value does not exceed the preset noise threshold.

[0124] The upper limit of the rotational speed of each wind turbine when the constraints are met and the objective function is optimal, i.e., the optimized rotational speed mode;

[0125] Maximum power and optimal pitch angle under optimized speed operating mode;

[0126] The power corresponding to the current wind speed in the optimized rotation speed operation mode.

[0127] Among them, the upper limit of rotational speed, the upper limit of power, and the optimal pitch angle are the optimal control parameters of the wind turbine at the current moment (step 2055). Finally, step 206 is executed to send the control parameters to each turbine. As mentioned above, the control parameters obtained by the optimization algorithm are the optimal control parameters that can meet the preset noise threshold requirements and maximize power generation.

[0128] In the wind farm noise control method provided in this application embodiment, the main variables affecting the optimization results may include the nacelle yaw position, ambient temperature, and relative humidity. Therefore, these variables can also be treated as a variable group, and the control parameters under different variable group conditions can be calculated in advance and stored in WFC. When wind farm noise control is required, WFC queries the control parameters corresponding to the variable group based on the current nacelle position and ambient temperature and humidity obtained from the data interface, and then sends them to each wind turbine. This can save the time of calculating control parameters.

[0129] Optionally, the WFC in the above-mentioned wind farm noise control system can not only integrate noise control functions, but also be combined with other farm group control functions, such as wind correction, icing protection, and wake control, to achieve intelligent wind farm and maximize benefits.

[0130] The wind farm noise control method provided in this application embodiment may further include control parameters for blade accessories such as serrated trailing edges, brushes, and VG blades, thereby achieving noise control through a combination of hardware and software.

[0131] To compensate for the power generation loss under noise control, the wind farm noise control method provided in this application embodiment can also be combined with the noise reduction control strategy of a single wind turbine. That is, in low speed mode, the pitch is adjusted in advance and the speed increases with the wind speed to obtain higher power and maximize power generation.

[0132] Figure 6 A schematic diagram of a wind farm noise control device according to an embodiment of this application is shown. The wind farm noise control device provided in this embodiment can be used to execute the wind farm noise control method provided in this embodiment. For parts not described in detail in the embodiments of the wind farm noise control device provided in this embodiment, please refer to the descriptions in the embodiments of the wind farm noise control method provided in this embodiment.

[0133] like Figure 6 As shown, the wind farm noise control device provided in this application embodiment includes an acquisition unit 11, a first calculation unit 12, and a control unit 13.

[0134] The acquisition unit 11 is used to acquire noise measurement values ​​of a preset sensitive area of ​​the wind farm;

[0135] The first calculation unit 12 is used to calculate the control parameters of the wind turbines in the wind farm based on the wind turbine operation data, ambient temperature and humidity data and the preset noise propagation model if the noise measurement value of any sensitive area exceeds the preset noise threshold. The first calculation unit 12 is used to calculate the control parameters of the wind turbines in the wind farm based on the wind turbine operation data, ambient temperature and humidity data and the preset noise propagation model if the noise measurement value of any sensitive area exceeds the preset noise threshold.

[0136] The control unit 13 is used to control the wind turbines in the wind farm using calculated control parameters.

[0137] Optionally, the device may further include a cyclic execution unit for repeatedly executing the following steps after controlling the wind turbines in the wind farm with calculated control parameters, until the current noise measurement value in the sensitive area is lower than or equal to a preset noise threshold:

[0138] After a preset time period, the updated noise measurement value of the sensitive area is acquired again;

[0139] If the updated noise measurement value exceeds the preset noise threshold, the model parameters of the preset noise propagation model will be adjusted.

[0140] Based on the constraints and optimization objectives, the control parameters are recalculated using the wind turbine operation data, ambient temperature and humidity data, and a preset noise propagation model within the wind farm.

[0141] The wind turbines in the wind farm are controlled by recalculated control parameters.

[0142] Optionally, the first computing unit 12 may include:

[0143] The first calculation subunit is used to calculate the noise value of the sensitive area and the power of the wind turbines in the wind farm when the wind turbines are running at different speed values ​​within the available speed range of the wind turbines in the wind farm.

[0144] The first determining subunit is used to determine the target speed of each wind turbine generator set within the available speed range, so that the calculated noise value does not exceed the preset noise threshold and the power is maximized.

[0145] The second determining subunit is used to take the target speed of each wind turbine generator set as the upper limit of the speed of the corresponding unit, and take the maximum output power corresponding to the target speed of each wind turbine generator set as the upper limit of the output power of the corresponding unit.

[0146] The control parameters include the upper limit of the rotational speed and the upper limit of the output power of each wind turbine generator set.

[0147] Optionally, the device may further include:

[0148] The second calculation unit is used to calculate the optimal pitch angle of each wind turbine when it outputs the maximum output power at the corresponding target speed; the control parameters of each wind turbine also include the optimal pitch angle.

[0149] Optionally, the first computing unit 12 may include:

[0150] The sub-unit is used to obtain the objective function for calculating the power generation of wind turbines in the wind farm based on the control parameters of the wind turbines in the wind farm.

[0151] The second calculation subunit is used to iteratively calculate the objective function until convergence based on the optimization algorithm, with the constraint that the calculated noise value of the sensitive area does not exceed the preset noise threshold, so as to maximize the power generation of the wind turbine units in the wind farm.

[0152] The third determining sub-unit is used to determine the control parameters of the wind turbines in the wind farm that make the objective function converge.

[0153] The wind farm noise control device of this application embodiment acquires the noise measurement values ​​of the sensitive areas of the wind farm in a preset manner. When the noise measurement value of any sensitive area exceeds the preset noise threshold, the device uses the constraint that the calculated noise value of the sensitive area does not exceed the preset noise threshold and takes the maximization of the power generation of the wind turbines in the wind farm as the optimization objective. Based on the operating data of the wind turbines in the wind farm, the ambient temperature and humidity data, and the preset noise propagation model, the device calculates the control parameters of the wind turbines in the wind farm. The device controls the wind turbines in the wind farm by using the calculated control parameters. This solves the technical problem in related technologies that it is difficult to balance the power generation of the wind farm and the noise in the sensitive areas. It increases the power generation of the wind farm while ensuring that the noise in the sensitive areas does not exceed the limit.

[0154] Optionally, the wind farm noise control device provided in this application embodiment can be installed in the wind farm controller (WFC).

[0155] Figure 7 A schematic diagram of the hardware structure of the electronic device provided in an embodiment of this application is shown.

[0156] The electronic device may include a processor 301 and a memory 302 storing program instructions.

[0157] Specifically, the processor 301 may include a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits that can be configured to implement the embodiments of this application.

[0158] Memory 302 may include mass storage for data or instructions. For example, and not limitingly, memory 302 may include a hard disk drive (HDD), floppy disk drive, flash memory, optical disk, magneto-optical disk, magnetic tape, or Universal Serial Bus (USB) drive, or a combination of two or more of these. Where appropriate, memory 302 may include removable or non-removable (or fixed) media. Where appropriate, memory 302 may be internal or external to the integrated gateway disaster recovery device. In a particular embodiment, memory 302 is non-volatile solid-state memory.

[0159] In a particular embodiment, memory 302 includes read-only memory (ROM). Where appropriate, the ROM may be a mask-programmed ROM, a programmable ROM (PROM), an erasable PROM (EPROM), an electrically erasable PROM (EEPROM), an electrically rewritable ROM (EAROM), or flash memory, or a combination of two or more of these.

[0160] Memory may include read-only memory (ROM), random access memory (RAM), disk storage media devices, optical storage media devices, flash memory devices, and electrical, optical, or other physical / tangible memory storage devices. Therefore, typically, memory includes one or more tangible (non-transitory) readable storage media (e.g., memory devices) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described with reference to the method according to one aspect of this application.

[0161] The processor 301 reads and executes the program instructions stored in the memory 302 to implement any of the wind farm noise control methods in the above embodiments.

[0162] In one example, the electronic device may also include a communication interface 303 and a bus 310. For example, Figure 7 As shown, the processor 301, memory 302, and communication interface 303 are connected through bus 310 and complete communication with each other.

[0163] The communication interface 303 is mainly used to realize communication between various modules, devices, units and / or equipment in the embodiments of this application.

[0164] Bus 310 includes hardware, software, or both, that couples components of an electronic device together. For example, and not limitingly, the bus may include an Accelerated Graphics Port (AGP) or other graphics bus, an Enhanced Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), HyperTransport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an Infinite Bandwidth Interconnect, a Low Pin Count (LPC) bus, a memory bus, a Microchannel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local (VLB) bus, or other suitable buses, or combinations of two or more of these. Where appropriate, bus 310 may include one or more buses. Although specific buses are described and illustrated in embodiments of this application, this application contemplates any suitable bus or interconnect.

[0165] Optionally, the aforementioned electronic equipment can be installed in the controller of the wind farm.

[0166] This application also provides a wind farm controller, which may include the wind farm noise control device or electronic device provided in the above-described embodiments of this application. An optional application scenario diagram of the wind farm controller can be shown as follows: Figure 3 As shown, the specific connection methods between the wind farm controller (WFC) and other equipment can be found in the documentation. Figure 3 The explanation will not be repeated here.

[0167] In conjunction with the wind farm noise control methods in the above embodiments, this application embodiment can provide a readable storage medium for implementation. The readable storage medium stores program instructions; when these program instructions are executed by a processor, they implement any of the wind farm noise control methods in the above embodiments.

[0168] It should be clarified that this application is not limited to the specific configurations and processes described above and shown in the figures. For the sake of brevity, detailed descriptions of known methods are omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of this application is not limited to the specific steps described and shown. Those skilled in the art can make various changes, modifications, and additions, or change the order of steps, after understanding the spirit of this application.

[0169] The functional blocks shown in the above-described structural diagram can be implemented as hardware, software, firmware, or a combination thereof. When implemented in hardware, they can be, for example, electronic circuits, application-specific integrated circuits (ASICs), appropriate firmware, plug-ins, function cards, etc. When implemented in software, the elements of this application are programs or code segments used to perform the required tasks. Programs or code segments can be stored on a machine-readable medium or transmitted over a transmission medium or communication link via data signals carried on a carrier wave. "Machine-readable medium" can include any medium capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, fiber optic media, radio frequency (RF) links, etc. Code segments can be downloaded via computer networks such as the Internet, intranets, etc.

[0170] It should also be noted that the exemplary embodiments mentioned in this application describe methods or systems based on a series of steps or apparatus. However, this application is not limited to the order of the above steps; that is, the steps can be performed in the order mentioned in the embodiments, or in a different order, or several steps can be performed simultaneously.

[0171] The aspects of this application have been described above with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and program products according to embodiments of this application. It should be understood that each block in the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by program instructions. These program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to create a machine such that these instructions, executable via the processor of the computer or other programmable data processing apparatus, enable the implementation of the functions / actions specified in one or more blocks of the flowchart illustrations and / or block diagrams. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor, or a field-programmable logic circuit. It is also understood that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can also be implemented by special-purpose hardware performing the specified functions or actions, or can be implemented by a combination of special-purpose hardware and computer instructions.

[0172] The above description is merely a specific implementation of this application. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, modules, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here. It should be understood that the protection scope of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the protection scope of this application.

Claims

1. A method for controlling noise in a wind farm, characterized in that, include: Obtain noise measurement values ​​for the preset sensitive areas of the wind farm; If the noise measurement value of any sensitive area exceeds the preset noise threshold, then the control parameters of the wind turbines in the wind farm are calculated based on the wind turbine operation data, environmental temperature and humidity data, and a preset noise propagation model, with the constraint that the calculated noise value of the sensitive area does not exceed the preset noise threshold, and with the optimization objective of maximizing the power generation of the wind turbines in the wind farm. The preset noise threshold varies according to changes in the monitored environmental temperature and humidity data. The wind turbines in the wind farm are controlled by the calculated control parameters. After controlling the wind turbines in the wind farm using the calculated control parameters, the method further includes repeatedly executing the following steps until the current noise measurement value of the sensitive area is lower than or equal to the preset noise threshold: After a preset time period, the updated noise measurement value of the sensitive area is obtained again; If the updated noise measurement value exceeds the preset noise threshold, then the model parameters of the preset noise propagation model are adjusted. The control parameters are recalculated based on the constraints and optimization objectives, according to the wind turbine operation data, ambient temperature and humidity data, and a preset noise propagation model within the wind farm. The wind turbines in the wind farm are controlled by the recalculated control parameters.

2. The method according to claim 1, characterized in that, The calculation of the control parameters of the wind turbines in the wind farm includes: Within the available speed range of the wind turbine generators in the wind farm, calculate the noise level of the sensitive area and the power of the wind turbine generators in the wind farm when the wind turbine generators operate at different speeds. Within the available speed range, target speeds are determined for each wind turbine generator set that maximizes the power output while ensuring that the calculated noise value does not exceed the preset noise threshold. The target speed of each wind turbine generator set is taken as the upper limit of the speed of the corresponding unit, and the maximum output power corresponding to the target speed of each wind turbine generator set is taken as the upper limit of the output power of the corresponding unit. The control parameters include the upper limit of the rotational speed and the upper limit of the output power of each wind turbine generator set.

3. The method according to claim 2, characterized in that, Also includes: Calculate the optimal pitch angle for each wind turbine to output maximum power at the corresponding target speed; the control parameters for each wind turbine also include the optimal pitch angle.

4. The method according to claim 1, characterized in that, The calculation of the control parameters of the wind turbines in the wind farm includes: Obtain the objective function for calculating the power generation of the wind turbines in the wind farm based on the control parameters of the wind turbines in the wind farm; With the constraint that the calculated noise value of the sensitive area does not exceed the preset noise threshold, the objective function is iteratively calculated until convergence based on the optimization algorithm, so as to maximize the power generation of the wind turbines in the wind farm. Determine the control parameters of the wind turbines in the wind farm that enable the objective function to converge.

5. A wind farm noise control device, characterized in that, The device includes: Acquisition unit, used to acquire noise measurement values ​​of a preset sensitive area of ​​a wind farm; The first calculation unit is used to calculate the control parameters of the wind turbines in the wind farm based on the wind turbine operation data, environmental temperature and humidity data, and a preset noise propagation model, if the noise measurement value of any sensitive area exceeds a preset noise threshold. This is done under the constraint that the calculated noise value of the sensitive area does not exceed the preset noise threshold, and with the optimization objective of maximizing the power generation of the wind turbines in the wind farm. The preset noise threshold varies according to changes in the monitored environmental temperature and humidity data. A control unit is used to control the wind turbines in the wind farm using calculated control parameters. The device further includes: A cyclic execution unit is configured to, after the control unit controls the wind turbines in the wind farm using calculated control parameters, cyclically execute the following steps until the current noise measurement value of the sensitive area is lower than or equal to the preset noise threshold: After a preset time period, the updated noise measurement value of the sensitive area is obtained again; If the updated noise measurement value exceeds the preset noise threshold, then the model parameters of the preset noise propagation model are adjusted. The control parameters are recalculated based on the constraints and optimization objectives, according to the wind turbine operation data, ambient temperature and humidity data, and a preset noise propagation model within the wind farm. The wind turbines in the wind farm are controlled by the recalculated control parameters.

6. The apparatus according to claim 5, characterized in that, The device is installed in the controller of the wind farm.

7. An electronic device, characterized in that, The electronic device includes: a processor and a memory storing program instructions; When the processor executes the program instructions, it implements the wind farm noise control method as described in any one of claims 1-4.

8. The electronic device according to claim 7, characterized in that, The electronic equipment is installed in the controller of the wind farm.

9. A readable storage medium, characterized in that, The readable storage medium stores program instructions that, when executed by a processor, implement the wind farm noise control method as described in any one of claims 1-4.

10. A program product, characterized in that, When the instructions in the program product are executed by the processor of the electronic device, the electronic device performs the wind farm noise control method as described in any one of claims 1-4.

11. A wind farm controller, characterized in that, This includes the wind farm noise control device as described in claim 5 or 6, or the electronic device as described in claim 7 or 8.

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