Position determination method and device, storage medium, electronic device and computer program product
By determining the monitoring point with the minimum error value on the wind speed instrument as the placement position of the temperature and humidity sensor, the problem of being easily frozen in the cold tide weather in the cold wave, which improves the efficiency and safety of wind power.
Patent Information
- Application Number
- CN202411637842.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-11-15
- Publication Date
- 2025-01-21
Smart Images
Figure CN119335216A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the technical field of wind power generation, and in particular to a method and device for determining a position, a storage medium, an electronic device, and a computer program product. Background Art
[0002] The anemometer of a wind turbine is the only wind measuring device of a wind turbine. Its working state is particularly important for the overall control of the wind turbine. At present, the mainstream wind speed and direction sensors used on wind turbines are mechanical anemometers. Mechanical anemometers are low-cost and easy to use, and the speed and wind speed are basically linear. However, the mechanical structure of a mechanical anemometer will be affected by bad weather. It is easy to freeze and frost in cold weather. When the mechanical anemometer freezes and frosts, it will have a serious impact on the control system of the wind turbine.
[0003] In order to prevent the mechanical anemometer from freezing in cold weather, it is necessary to install a temperature and humidity sensing device on the anemometer. The temperature and humidity sensing device is mainly a temperature and humidity sensor, so as to determine the appropriate time to start the corresponding mechanical anemometer deicing device. However, the measuring part of the anemometer is generally composed of three hemispherical or parabolic hollow cup shells, which are approximately spherical as a whole. The temperature and humidity measured at each position on the anemometer will be affected by the environmental factors at that position, so it is necessary to confirm an optimal monitoring position that is least affected by environmental factors to place the temperature and humidity sensor. However, in the relevant technology, there is a lack of methods to determine this position.
[0004] With regard to the problem in the related art that it is impossible to determine the position on the anemometer that is least affected by environmental factors, no effective solution has been proposed yet.
[0005] Therefore, it is necessary to improve the related technology to overcome the above-mentioned defects in the related technology. Summary of the invention
[0006] The embodiments of the present application provide a position determination method and device, a storage medium, an electronic device, and a computer program product to at least solve the problem of being unable to determine the position on the anemometer that is least affected by environmental factors.
[0007] According to one aspect of an embodiment of the present application, a position determination method is provided, including: determining M error values of M monitoring points on an anemometer of a wind turbine, wherein an i-th error value among the M error values is an error value between a first temperature value and a second temperature value corresponding to an i-th monitoring point among the M monitoring points, and the first temperature value corresponding to the i-th monitoring point is correlated with the relative humidity and wind speed corresponding to the i-th monitoring point; the second temperature value corresponding to the i-th monitoring point is not correlated with the relative humidity and wind speed corresponding to the i-th monitoring point; M is an integer greater than or equal to 2, and i is a positive integer less than or equal to M; and the position of the monitoring point with the smallest error value among the M monitoring points is determined as the target position, wherein the target position is the position where the temperature and humidity sensor is placed.
[0008] In an exemplary embodiment, determining M error values of M monitoring points on an anemometer of a wind turbine includes: determining the ith error value in the following manner to determine the M error values: determining a first temperature value corresponding to the ith monitoring point according to the monitored temperature of the ith monitoring point, the relative humidity and wind speed corresponding to the ith monitoring point; determining a second temperature value corresponding to the ith monitoring point according to the monitored temperature of the ith monitoring point and the monitored temperature of the ith reference point among M reference points, wherein the M reference points are reference points corresponding to the M monitoring points, the ith reference point is symmetrical with the ith monitoring point with the central axis of the anemometer as the axis of symmetry, and the anemometer is spherical; and determining the absolute value of the difference between the first temperature value and the second temperature value corresponding to the ith monitoring point as the ith error value.
[0009] In an exemplary embodiment, determining a first temperature value corresponding to the ith monitoring point according to the monitored temperature of the ith monitoring point, the relative humidity and the wind speed corresponding to the ith monitoring point, includes: determining the first temperature value corresponding to the ith monitoring point according to the monitored temperature of the ith monitoring point, the relative humidity and the wind speed corresponding to the ith monitoring point by the following formula: Among them, ET is the first temperature value corresponding to the i-th monitoring point, T is the monitoring temperature of the i-th monitoring point, RH is the relative humidity corresponding to the i-th monitoring point, and V is the wind speed corresponding to the i-th monitoring point.
[0010] In an exemplary embodiment, determining the second temperature value corresponding to the ith monitoring point based on the monitored temperature of the ith monitoring point and the monitored temperature of the ith reference point among M reference points includes: when the monitored temperature of the ith monitoring point includes N first target temperatures at N moments and the monitored temperature of the ith reference point includes N second target temperatures at the N moments, determining the average value of the N first target temperatures to obtain a first temperature average value, and determining the average value of the N second target temperatures to obtain a second temperature average value, wherein N is a positive integer; determining the standard deviation of the N first target temperatures based on the first temperature average value to obtain a first standard deviation; and determining the standard error of the N second target temperatures based on the second temperature average value to obtain a second standard deviation; determining the second temperature value corresponding to the ith monitoring point based on the first temperature average value, the second temperature average value, the first standard deviation and the second standard deviation.
[0011] In an exemplary embodiment, determining the standard deviation of the N first target temperatures according to the first temperature average value to obtain the first standard deviation includes: calculating the first standard deviation using the following formula: in, is the first standard deviation, is the pth first target temperature among the N first target temperatures, is the first temperature average value, and p is a positive integer less than or equal to N; determining the standard errors of the N second target temperatures according to the second temperature average value to obtain a second standard deviation includes: calculating the second standard deviation by the following formula: in, is the second standard deviation, is the pth second target temperature among the N second target temperatures, is the second temperature average value.
[0012] In an exemplary embodiment, determining the second temperature value corresponding to the i-th monitoring point according to the first temperature average value, the second temperature average value, the first standard deviation, and the second standard deviation includes: determining the second temperature value corresponding to the i-th monitoring point by the following formula: in, is the first standard deviation, is the second standard deviation, is the first temperature average value, is the second average temperature, is the second temperature value corresponding to the i-th monitoring point.
[0013] In an exemplary embodiment, after determining the position of the monitoring point with the smallest error value among the M monitoring points as the target position, the method also includes: obtaining the target temperature and / or target humidity detected by the temperature and humidity sensor located at the target position; when the target temperature is lower than a first preset threshold and / or the target humidity is lower than a second preset threshold, performing a de-icing operation on the anemometer.
[0014] According to another aspect of an embodiment of the present application, a position determination device is also provided, including: a first determination module, used to determine M error values of M monitoring points on the anemometer of a wind turbine, wherein the i-th error value among the M error values is the error value of a first temperature value and a second temperature value corresponding to the i-th monitoring point among the M monitoring points, and the first temperature value corresponding to the i-th monitoring point is associated with the relative humidity and wind speed corresponding to the i-th monitoring point; the second temperature value corresponding to the i-th monitoring point is not associated with the relative humidity and wind speed corresponding to the i-th monitoring point; M is an integer greater than or equal to 2, and i is a positive integer less than or equal to M; a second determination module, used to determine the position of the monitoring point with the smallest error value among the M monitoring points as the target position, wherein the target position is the position where the temperature and humidity sensor is placed.
[0015] According to another aspect of the embodiments of the present application, a computer-readable storage medium is provided, wherein the computer-readable storage medium includes a stored program, wherein the program is configured to execute the above-mentioned position determination method when running.
[0016] According to another aspect of the embodiments of the present application, there is also provided an electronic device, including a memory and a processor, wherein the memory stores a computer program, wherein the processor is configured to execute the above-mentioned position determination method through the computer program.
[0017] According to another aspect of the embodiments of the present application, a computer program product is provided, including a computer program, and the computer program performs the above-mentioned position determination method when executed by a processor.
[0018] The present application determines the error values of multiple monitoring points on the anemometer, and then selects the location of the monitoring point with the smallest error value as the target location. Since the influence of the relative humidity and wind speed corresponding to each monitoring point on the temperature measurement of each monitoring point is taken into account when calculating the error value, the problem of being unable to determine the location on the anemometer that is least affected by environmental factors is solved. In addition, since the best location for placing the temperature and humidity sensor is determined, the temperature and humidity of the anemometer can be monitored more accurately, the icing problem of the anemometer can be discovered and handled in time, and the efficiency and safety of wind power generation are improved. BRIEF DESCRIPTION OF THE DRAWINGS
[0019] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.
[0020] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.
[0021] Figure 1 It is a hardware structure block diagram of a mobile terminal for determining a position according to an embodiment of the present application;
[0022] Figure 2 is a flow chart of position determination according to an embodiment of the present application;
[0023] Figure 3 is a schematic diagram of an optional process of position determination according to an embodiment of the present application;
[0024] Figure 4 It is a structural block diagram of a position determination device according to an embodiment of the present application. DETAILED DESCRIPTION
[0025] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present application.
[0026] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.
[0027] The method embodiments provided in the embodiments of the present application can be executed in a mobile terminal, a computer terminal or a similar computing device. Taking running on a mobile terminal as an example, Figure 1 is a hardware structure block diagram of a mobile terminal for determining a position according to an embodiment of the present application. Figure 1 As shown, the mobile terminal may include one or more ( Figure 1 Only one is shown in the figure) a processor 102 (the processor 102 may include but is not limited to a processing device such as a microprocessor (MP) or a programmable logic device (FPGA)) and a memory 104 for storing data, wherein the mobile terminal may also include a transmission device 106 and an input / output device 108 for communication functions. It can be understood by those skilled in the art that Figure 1 The structure shown is only for illustration and does not limit the structure of the mobile terminal. Figure 1 More or fewer components as shown, or with Figure 1 Different configurations are shown.
[0028] The memory 104 can be used to store computer programs, for example, software programs and modules of application software, such as the computer program corresponding to the position determination in the embodiment of the present application. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, that is, to implement the above method. The memory 104 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 104 may further include a memory remotely arranged relative to the processor 102, and these remote memories may be connected to the mobile terminal via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.
[0029] The transmission device 106 is used to receive or send data via a network. The specific example of the above network may include a wireless network provided by a communication provider of the mobile terminal. In one example, the transmission device 106 includes a network adapter (Network Interface Controller, referred to as NIC), which can be connected to other network devices through a base station so as to communicate with the Internet. In one example, the transmission device 106 can be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.
[0030] In order to solve the above problem, this embodiment provides a location determination method, including but not limited to being applied to the above mobile terminal. Figure 2 is a flow chart of position determination according to an embodiment of the present application, such as Figure 2 As shown, the process includes the following steps S202-S204:
[0031] Step S202: determining M error values of M monitoring points on the anemometer of the wind turbine, wherein the i-th error value among the M error values is an error value of a first temperature value and a second temperature value corresponding to the i-th monitoring point among the M monitoring points, the first temperature value corresponding to the i-th monitoring point is associated with the relative humidity and the wind speed corresponding to the i-th monitoring point; the second temperature value corresponding to the i-th monitoring point is not associated with the relative humidity and the wind speed corresponding to the i-th monitoring point; M is an integer greater than or equal to 2, and i is a positive integer less than or equal to M;
[0032] Optionally, the heights and horizontal positions of the M monitoring points on the anemometer of the wind turbine are different from each other.
[0033] Optionally, the first temperature value is a temperature value obtained by taking into account the influence of relative humidity and wind speed, reflecting the correlation between environmental factors (including relative humidity and wind speed) and temperature measurement; the second temperature value is a temperature value obtained by assuming that environmental factors have no effect on temperature measurement.
[0034] Step S204: Determine the position of the monitoring point with the smallest error value among the M monitoring points as the target position, wherein the target position is the position where the temperature and humidity sensor is placed.
[0035] It should be noted that after obtaining the error values of M monitoring points, the monitoring point with the smallest error can be determined by analyzing the size of the M error values. This monitoring point is least affected by environmental factors when measuring temperature, that is, its measurement value is closer to the actual temperature, so the position of the monitoring point with the smallest error value is determined as the optimal placement position for the temperature and humidity sensor, that is, the target position. At the target position, the readings of the temperature and humidity sensor are least affected by wind speed and relative humidity, and can provide more accurate temperature and humidity data.
[0036] Through the above steps, the optimal location of the temperature and humidity sensor can be scientifically determined, thereby improving the accuracy and reliability of the temperature and humidity control system, and further ensuring the normal operation and measurement accuracy of the anemometer under severe weather conditions.
[0037] In the above steps, by determining the error values of multiple monitoring points on the anemometer, the position of the monitoring point with the smallest error value is selected as the target position. Since the influence of the relative humidity and wind speed corresponding to each monitoring point on the temperature measurement of each monitoring point is taken into account when calculating the error value, the problem of being unable to determine the position on the anemometer that is least affected by environmental factors is solved. In addition, since the best position for placing the temperature and humidity sensor is determined, the temperature and humidity of the anemometer can be monitored more accurately, the icing problem of the anemometer can be discovered and dealt with in time, and the efficiency and safety of wind power generation are improved.
[0038] In an exemplary embodiment, determining the M error values of the M monitoring points on the anemometer of the wind turbine can be achieved by the following steps: determining the i-th error value by the following steps S11-S13 to determine the M error values:
[0039] Step S11: determining a first temperature value corresponding to the ith monitoring point according to the monitored temperature of the ith monitoring point, the relative humidity and the wind speed corresponding to the ith monitoring point;
[0040] Optionally, a temperature and humidity sensor installed at the i-th monitoring point on the anemometer is used to obtain temperature, relative humidity and wind speed data of the i-th monitoring point in real time.
[0041] Optionally, the monitored temperature of the i-th monitoring point includes the temperature monitored at the middle moment of N moments within a period of time, that is, assuming that the temperature of the i-th monitoring point is obtained at five moments respectively, then the monitored temperature of the i-th monitoring point is the temperature monitored at the third moment among the five moments.
[0042] Step S12: determining a second temperature value corresponding to the ith monitoring point according to the monitoring temperature of the ith monitoring point and the monitoring temperature of the ith reference point among the M reference points, wherein the M reference points are reference points corresponding to the M monitoring points, the ith reference point is symmetrical with the ith monitoring point with the central axis of the anemometer as the symmetry axis, and the anemometer is spherical in shape;
[0043] Optionally, a temperature and humidity sensor installed at the i-th reference point on the anemometer is used to obtain the temperature of the i-th reference point in real time.
[0044] It should be noted that, in addition to the monitoring points, M reference points are set on the anemometer. The i-th reference point among the M reference points and the i-th monitoring point among the M monitoring points are symmetrical with the central axis of the anemometer as the axis of symmetry. The temperature value obtained at the i-th reference point and the temperature value obtained at the i-th monitoring point are affected by basically the same environmental factors, that is, the difference between the temperature values obtained at the i-th reference point and the i-th monitoring point is less than the preset difference and is within the allowable range.
[0045] Step S13: determining the absolute value of the difference between the first temperature value and the second temperature value corresponding to the i-th monitoring point as the i-th error value.
[0046] It should be noted that, through the above steps, an error value can be calculated for each monitoring point (eg, the i-th monitoring point), and the error value reflects the degree to which the relative humidity and wind speed affect the temperature measurement of the monitoring point.
[0047] In an exemplary embodiment, determining the first temperature value corresponding to the i-th monitoring point according to the monitored temperature of the i-th monitoring point, the relative humidity and the wind speed corresponding to the i-th monitoring point can be achieved by the following steps: determining the first temperature value corresponding to the i-th monitoring point according to the monitored temperature of the i-th monitoring point, the relative humidity and the wind speed corresponding to the i-th monitoring point by the following formula:
[0048]
[0049] Among them, ET is the first temperature value corresponding to the i-th monitoring point, T is the monitoring temperature of the i-th monitoring point, RH is the relative humidity corresponding to the i-th monitoring point, and V is the wind speed corresponding to the i-th monitoring point.
[0050] It should be noted that by applying a formula that comprehensively considers wind speed, relative humidity and monitoring temperature, the temperature status of the monitoring point can be evaluated more accurately, especially the temperature status under severe weather conditions. Under severe conditions such as cold waves, traditional temperature measurements may be affected by factors such as icing and humidity changes, resulting in errors in the measurement results. Using a formula that takes environmental factors into account can help predict and compensate for these errors and enhance the environmental adaptability of the system.
[0051] In an exemplary embodiment, determining the second temperature value corresponding to the i-th monitoring point according to the monitored temperature of the i-th monitoring point and the monitored temperature of the i-th reference point among the M reference points can be implemented by the following steps S21-S23:
[0052] Step S21: when the monitored temperature at the i-th monitoring point includes N first target temperatures at N moments, and the monitored temperature at the i-th reference point includes N second target temperatures at the N moments, determining an average value of the N first target temperatures to obtain a first temperature average value, and determining an average value of the N second target temperatures to obtain a second temperature average value, wherein N is a positive integer;
[0053] Optionally, the temperature values of the i-th monitoring point at five moments, ie, five first target temperatures, are obtained, and five second target temperature values at the same five moments are collected at the i-th reference point.
[0054] Optionally, based on the five first target temperatures, the first temperature average value is obtained by the following formula:
[0055]
[0056] in, is the pth first target temperature among the five first target temperatures, is the first temperature average value.
[0057] Optionally, based on the five second target temperatures, the second temperature average value is obtained by the following formula:
[0058]
[0059] in, is the pth second target temperature among the five second target temperatures, is the second temperature average value.
[0060] Step S22: determining the standard deviation of the N first target temperatures according to the first temperature average value to obtain a first standard deviation; and determining the standard error of the N second target temperatures according to the second temperature average value to obtain a second standard deviation;
[0061] Step S23: determining a second temperature value corresponding to the i-th monitoring point according to the first temperature average value, the second temperature average value, the first standard deviation, and the second standard deviation.
[0062] It should be noted that the above steps, by obtaining the temperature average and fluctuation degree of the ith monitoring point and the ith reference point within N moments, can obtain a temperature value under the assumption that environmental factors have no effect on temperature measurement, which helps to more accurately analyze the actual temperature state of the monitoring point and provides basic data for subsequent error analysis and sensor location optimization. By comparing the first temperature value (actual temperature considering environmental factors) and the second temperature value (expected temperature ignoring environmental factors) of the monitoring point, the environmental adaptability and data accuracy of the sensor at the monitoring point can be further evaluated.
[0063] In an exemplary embodiment, determining the standard deviation of the N first target temperatures according to the first temperature average value to obtain the first standard deviation can be achieved by the following steps: calculating the first standard deviation by the following formula:
[0064]
[0065] in, is the first standard deviation, is the pth first target temperature among the N first target temperatures, is the first temperature average value, and p is a positive integer less than or equal to N;
[0066] Optionally, the five first target temperatures are The first temperature average is 3 degrees Celsius ((1+2+3+4+5) / 5=3), then the first standard deviation 2.5 degrees Celsius
[0067]
[0068] In an exemplary embodiment, determining the standard errors of the N second target temperatures according to the second temperature average value to obtain the second standard deviation can be achieved by the following steps: calculating the second standard deviation by the following formula:
[0069]
[0070] in, is the second standard deviation, is the pth second target temperature among the N second target temperatures, is the second temperature average value.
[0071] Optionally, the five second target temperatures are The second temperature average is 4 degrees Celsius ((2+3+4+5+6) / 5=4), then the second standard deviation 3.75 degrees Celsius
[0072]
[0073] It should be noted that analyzing the standard deviation helps find the target position so that the temperature and humidity sensor can maintain high measurement accuracy and stability in severe weather, thereby optimizing the startup and shutdown timing of the de-icing system and reducing energy consumption and maintenance costs.
[0074] In an exemplary embodiment, determining the second temperature value corresponding to the i-th monitoring point according to the first temperature average value, the second temperature average value, the first standard deviation, and the second standard deviation can be achieved by the following steps: determining the second temperature value corresponding to the i-th monitoring point by the following formula:
[0075]
[0076] in, is the first standard deviation, is the second standard deviation, is the first temperature average value, is the second average temperature, is the second temperature value corresponding to the i-th monitoring point.
[0077] Optionally, at the first temperature average The second average temperature is 3 degrees Celsius The first standard deviation is 4 degrees Celsius The second standard deviation is 2.5 degrees Celsius When the temperature is 3.75 degrees Celsius, the second temperature value 3.3 degrees Celsius
[0078] It should be noted that by combining the temperature data of the reference point and the monitoring point, and quantitatively analyzing the temperature volatility and comparing it with the first temperature value, it is helpful to identify which monitoring points' temperature data are less affected by environmental factors, thereby providing a basis for optimizing the layout of temperature and humidity sensors and ensuring that the system can obtain information from the most stable data source.
[0079] Through the above steps, the impact of environmental factors on the anemometer temperature measurement can be effectively evaluated, the performance and reliability of the temperature and humidity control system in the wind turbine can be improved, and accurate temperature monitoring and control can be ensured even in severe weather conditions.
[0080] In an exemplary embodiment, after determining the position of the monitoring point with the smallest error value among the M monitoring points as the target position, the method further includes the following steps S31-S32:
[0081] Step S31: acquiring a target temperature and / or a target humidity detected by the temperature and humidity sensor located at the target location;
[0082] Optionally, after determining the monitoring point with the smallest error value among the M monitoring points as the target position, the temperature and humidity sensor installed at this position will provide the most reliable and accurate environmental temperature and humidity data, and the system will continuously monitor and collect the real-time target temperature and / or target humidity value detected by the temperature and humidity sensor at the target position. These data will directly reflect the temperature and humidity conditions of the environment where the anemometer is located, providing a decision-making basis for subsequent deicing operations.
[0083] Step S32: when the target temperature is lower than a first preset threshold value and / or the target humidity is lower than a second preset threshold value, de-icing the anemometer.
[0084] Optionally, the system will automatically determine whether it is necessary to start the de-icing procedure based on the real-time temperature and humidity data provided by the target position sensor. The specific operations are as follows: Threshold setting: pre-set the first preset threshold and the second preset threshold, the first preset threshold and the second preset threshold respectively correspond to the minimum temperature and humidity conditions for starting the de-icing operation, for example, the first preset threshold is 0 degrees Celsius, and the second preset threshold may be set at a specific high humidity point to ensure timely response when there is a risk of icing; De-icing decision: when the target temperature detected by the target position sensor is lower than the first preset threshold and / or the target humidity is lower than the second preset threshold, the system will determine that the anemometer may face the risk of icing, and automatically perform de-icing operations (such as starting the de-icing device) to maintain the normal operation of the anemometer.
[0085] Obviously, the above-described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. In order to better understand the above method, the above process is described below in conjunction with the embodiments, but it is not intended to limit the technical solutions of the embodiments of the present invention. Figure 3 The overall flow chart of a position determination of an embodiment of the application is shown, specifically:
[0086] First, this application uses computational fluid dynamics simulation method (Computational Fluid Dynamics, referred to as CFD) to process the temperature field and humidity field data of the mechanical anemometer. By extracting the temperature and humidity data at each point of the mechanical anemometer, the fusion temperature of each point temperature (i.e., the above-mentioned second temperature value) is calculated using the mean recursive fusion algorithm. The effective temperature (i.e., the above-mentioned first temperature value) calculated by fusing various physical quantities is used as the true value of the mechanical anemometer, and the effective temperature of each measuring point is compared with the fusion temperature to obtain the monitoring point with the smallest deviation from the true value of the environment, i.e., the theoretical optimal monitoring point. This method can provide a basis for the layout of the temperature and humidity sensors before debugging.
[0087] This application is aimed at the temperature and humidity control of a mechanical anemometer. It uses CFD simulation technology to process the wind speed, temperature, and humidity monitoring values of the mechanical anemometer at different heights and positions, and combines the "effective temperature theory" and "mean recursive fusion algorithm" to analyze the theoretical optimal temperature and humidity sensor layout positions of the anemometer, thereby achieving precise control of the temperature and humidity of the anemometer.
[0088] 1. Data collection:
[0089] The collected status parameters can be mainly divided into natural environment data, equipment status data, etc. Natural environment data mainly includes mechanical anemometer wind speed, wind direction absolute value, atmospheric pressure, anemometer ambient temperature and ambient humidity. Usually, wind speed and direction information is collected through anemometers and wind vanes, and temperature and weather condition information is collected through thermometers, hygrometers or meteorological systems.
[0090] 2. Comprehensive correlation analysis:
[0091] Calculate the effective temperature (ET) of a monitoring point, that is, the first temperature value. The calculation formula used is as follows:
[0092]
[0093] Among them, ET is the effective temperature, T is the monitoring temperature of the monitoring point, RH is the relative humidity, and V is the wind speed. The effective temperature comprehensively considers the influence of the three physical quantities of temperature, relative humidity and wind speed on the anemometer monitoring point. The ET indicator formula has the characteristics of simple calculation, easy data acquisition, and can truly reflect environmental parameters. For the selected best monitoring anemometer environmental parameter sensor point, this indicator can be used as a coupling value to judge the accuracy of the three physical quantities of the anemometer measured at the monitoring point.
[0094] Since the environment at the top of the wind turbine is a complex distributed parameter system with characteristics such as nonlinear time variation, strong multivariate correlation, and large delay, the change of one parameter will affect the change of multiple environmental parameters. In addition, the environmental parameters at different locations on the top of the cabin vary greatly, and it is necessary to combine the environmental parameters at different locations for measurement. Therefore, in order to improve the accuracy and comprehensiveness of the anemometer environmental information and improve the reliability of the temperature and humidity control system, this application proposes to use a mean recursive fusion algorithm to integrate the monitoring information of each measuring point of the mechanical anemometer to obtain an environmental value that can represent the anemometer (i.e., the fused temperature value, i.e., the second temperature value mentioned above).
[0095] The mean recursive fusion algorithm is a data fusion algorithm that combines the arithmetic mean and the estimation algorithm. It can obtain reliable initial measurement values in real time, eliminate uncertainty in measurement, improve the accuracy and repeatability of measurement results, and obtain reliable real-time measurement results. This method has the advantages of small computational complexity and easy computer programming. It is suitable for slow-moving variable detection systems and matches the characteristics of temperature and humidity control systems. For the measurement series obtained by the temperature and humidity sensors, the consistency measurement data is first obtained, and then divided into two groups according to the principle of symmetry. The average value of the two groups of measurement data uses a batch estimation algorithm to estimate a fusion value close to the true value of the effective temperature, thereby obtaining an accurate measurement result of the effective temperature and eliminating uncertainty in the measurement process. Divide the data into two groups, and take the arithmetic mean of the data in each group:
[0096]
[0097] The corresponding standard error is:
[0098]
[0099] The arithmetic mean of the two groups was calculated Standard error According to batch estimation theory, the data fusion value after batching is:
[0100]
[0101] When the calculation results converge, open the post-processing module of the CFD fluid simulation software. Based on the simulation results of the CFD simulation, select multiple data monitoring points in the numerical model, and compare the gap between each monitoring point and the true value through numerical fusion, and select the monitoring point with the smallest difference from the true value as the theoretical optimal monitoring point.
[0102] 3. Install the temperature and humidity sensor:
[0103] Select the corresponding temperature and humidity sensors, install them at the monitoring points determined above, transmit the signals to the signal processing control cabinet installed on the cabin, set the temperature and humidity limits, and start the corresponding mechanical anemometer de-icing device when the humidity and temperature exceed the judgment conditions.
[0104] It should be noted that the present application also has the following advantages: (1) Analyzing the correlation between the parameters of different sampling points of the same mechanical anemometer and the parameters between the equipment operation parameters and the external environment, fully exploring the characteristic state parameters related to temperature and humidity during the operation of the fan and the state parameters unrelated to temperature and humidity; (2) Using comprehensive related indicators and mean recursive fusion algorithm to analyze temperature and humidity parameters and natural environment parameters, processing and analyzing the data, obtaining accurate measurement results of the effective temperature, and eliminating the uncertainty in the measurement process; (3) Selecting CFD fluid simulation software can not only reduce the computing cost but also improve the authenticity of the monitoring point selection, which is of great significance.
[0105] Through the description of the above implementation methods, those skilled in the art can clearly understand that the method according to the above embodiment can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes a number of instructions for a terminal device (which can be a mobile phone, computer, server, or network device, etc.) to execute the methods of each embodiment of the present application.
[0106] In this embodiment, a position determination device is also provided, which is used to implement the above-mentioned embodiments and preferred implementation modes, and the descriptions that have been made will not be repeated. As used below, the term "module" can implement a combination of software and / or hardware of a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceivable.
[0107] Figure 4 is a structural block diagram of a position determination device according to an embodiment of the present application, the device comprising:
[0108] The first determination module 402 is used to determine M error values of M monitoring points on the anemometer of the wind turbine, wherein the i-th error value among the M error values is an error value of a first temperature value and a second temperature value corresponding to the i-th monitoring point among the M monitoring points, and the first temperature value corresponding to the i-th monitoring point has a correlation with the relative humidity and the wind speed corresponding to the i-th monitoring point; the second temperature value corresponding to the i-th monitoring point has no correlation with the relative humidity and the wind speed corresponding to the i-th monitoring point; M is an integer greater than or equal to 2, and i is a positive integer less than or equal to M;
[0109] The second determination module 404 is used to determine the position of the monitoring point with the smallest error value among the M monitoring points as the target position, wherein the target position is the position where the temperature and humidity sensor is placed.
[0110] The above device determines the error values of multiple monitoring points on the anemometer, and thus selects the position of the monitoring point with the smallest error value as the target position. Since the influence of the relative humidity and wind speed corresponding to each monitoring point on the temperature measurement of each monitoring point is taken into account when calculating the error value, the problem of being unable to determine the position on the anemometer that is least affected by environmental factors is solved. In addition, since the best position for placing the temperature and humidity sensor is determined, the temperature and humidity of the anemometer can be monitored more accurately, the icing problem of the anemometer can be discovered and handled in time, and the efficiency and safety of wind power generation are improved.
[0111] In an exemplary embodiment, the first determination module 402 is also used to determine the i-th error value in the following manner to determine the M error values: determine the first temperature value corresponding to the i-th monitoring point according to the monitored temperature of the i-th monitoring point, the relative humidity and wind speed corresponding to the i-th monitoring point; determine the second temperature value corresponding to the i-th monitoring point according to the monitored temperature of the i-th monitoring point and the monitored temperature of the i-th reference point among M reference points, wherein the M reference points are reference points corresponding to the M monitoring points, the i-th reference point is symmetrical with the i-th monitoring point with the central axis of the anemometer as the symmetry axis, and the anemometer is spherical; and determine the absolute value of the difference between the first temperature value and the second temperature value corresponding to the i-th monitoring point as the i-th error value.
[0112] In an exemplary embodiment, the first determination module 402 is further configured to determine a first temperature value corresponding to the ith monitoring point according to the monitored temperature of the ith monitoring point, the relative humidity and the wind speed corresponding to the ith monitoring point by using the following formula: Among them, ET is the first temperature value corresponding to the i-th monitoring point, T is the monitoring temperature of the i-th monitoring point, RH is the relative humidity corresponding to the i-th monitoring point, and V is the wind speed corresponding to the i-th monitoring point.
[0113] In an exemplary embodiment, the first determination module 402 is also used to determine the average value of the N first target temperatures to obtain a first temperature average value, and determine the average value of the N second target temperatures to obtain a second temperature average value, when the monitored temperature of the i-th monitoring point includes N first target temperatures at N moments and the monitored temperature of the i-th reference point includes N second target temperatures at the N moments, wherein N is a positive integer; determine the standard deviation of the N first target temperatures based on the first temperature average value to obtain a first standard deviation; and determine the standard error of the N second target temperatures based on the second temperature average value to obtain a second standard deviation; determine the second temperature value corresponding to the i-th monitoring point based on the first temperature average value, the second temperature average value, the first standard deviation and the second standard deviation.
[0114] In an exemplary embodiment, the first determination module 402 is further configured to determine the standard deviation of the N first target temperatures according to the first temperature average value to obtain the first standard deviation, including: calculating the first standard deviation by the following formula: in, is the first standard deviation, is the pth first target temperature among the N first target temperatures, is the first temperature average value, and p is a positive integer less than or equal to N; determining the standard errors of the N second target temperatures according to the second temperature average value to obtain a second standard deviation includes: calculating the second standard deviation by the following formula: in, is the second standard deviation, is the pth second target temperature among the N second target temperatures, is the second temperature average value.
[0115] In an exemplary embodiment, the first determining module 402 is further configured to determine the second temperature value corresponding to the i-th monitoring point by using the following formula: in, is the first standard deviation, is the second standard deviation, is the first temperature average value, is the second average temperature, is the second temperature value corresponding to the i-th monitoring point.
[0116] In an exemplary embodiment, the above-mentioned device also includes: an acquisition module, which is used to obtain the target temperature and / or target humidity detected by the temperature and humidity sensor located at the target position after determining the position of the monitoring point with the smallest error value among the M monitoring points as the target position; a processing module, which is used to perform de-icing operation on the anemometer when the target temperature is lower than a first preset threshold value and / or the target humidity is lower than a second preset threshold value.
[0117] An embodiment of the present application further provides a computer-readable storage medium, in which a computer program is stored, wherein the computer program is configured to execute the steps of any of the above method embodiments when running.
[0118] Optionally, in this embodiment, the storage medium may be configured to store a computer program for performing the following steps:
[0119] S1, determining M error values of M monitoring points on the anemometer of the wind turbine, wherein the i-th error value among the M error values is an error value of a first temperature value and a second temperature value corresponding to the i-th monitoring point among the M monitoring points, and the first temperature value corresponding to the i-th monitoring point has a correlation with the relative humidity and the wind speed corresponding to the i-th monitoring point; the second temperature value corresponding to the i-th monitoring point has no correlation with the relative humidity and the wind speed corresponding to the i-th monitoring point; M is an integer greater than or equal to 2, and i is a positive integer less than or equal to M;
[0120] S2, determining the position of the monitoring point with the smallest error value among the M monitoring points as the target position, wherein the target position is the position where the temperature and humidity sensor is placed.
[0121] In an exemplary embodiment, the computer-readable storage medium may include, but is not limited to, various media that can store computer programs, such as a USB flash drive, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk or an optical disk.
[0122] For specific examples in this embodiment, reference may be made to the examples described in the above embodiments and exemplary implementation modes, and this embodiment will not be described in detail herein.
[0123] An embodiment of the present application further provides a computer program product, including a computer program, and when the computer program is executed by a processor, the steps in any one of the above method embodiments are performed.
[0124] An embodiment of the present application further provides an electronic device, including a memory and a processor, wherein a computer program is stored in the memory, and the processor is configured to run the computer program to execute the steps in any one of the above method embodiments.
[0125] Optionally, in this embodiment, the processor may be configured to perform the following steps through a computer program:
[0126] S1, determining M error values of M monitoring points on the anemometer of the wind turbine, wherein the i-th error value among the M error values is an error value of a first temperature value and a second temperature value corresponding to the i-th monitoring point among the M monitoring points, and the first temperature value corresponding to the i-th monitoring point has a correlation with the relative humidity and the wind speed corresponding to the i-th monitoring point; the second temperature value corresponding to the i-th monitoring point has no correlation with the relative humidity and the wind speed corresponding to the i-th monitoring point; M is an integer greater than or equal to 2, and i is a positive integer less than or equal to M;
[0127] S2, determining the position of the monitoring point with the smallest error value among the M monitoring points as the target position, wherein the target position is the position where the temperature and humidity sensor is placed.
[0128] In an exemplary embodiment, the electronic device may further include a transmission device and an input / output device, wherein the transmission device is connected to the processor, and the input / output device is connected to the processor.
[0129] For specific examples in this embodiment, reference may be made to the examples described in the above embodiments and exemplary implementation modes, and this embodiment will not be described in detail herein.
[0130] Obviously, those skilled in the art should understand that the above modules or steps of the present application can be implemented by a general computing device, they can be concentrated on a single computing device, or distributed on a network composed of multiple computing devices, they can be implemented by a program code executable by a computing device, so that they can be stored in a storage device and executed by the computing device, and in some cases, the steps shown or described can be executed in a different order from that herein, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. Thus, the present application is not limited to any specific combination of hardware and software.
[0131] The above is only a preferred implementation of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.
Claims
1. A method for determining a position, characterized in that: include: Determine M error values of M monitoring points on the anemometer of the wind turbine, wherein the i-th error value among the M error values is an error value of a first temperature value and a second temperature value corresponding to the i-th monitoring point among the M monitoring points, and the first temperature value corresponding to the i-th monitoring point has a correlation with the relative humidity and the wind speed corresponding to the i-th monitoring point; the second temperature value corresponding to the i-th monitoring point has no correlation with the relative humidity and the wind speed corresponding to the i-th monitoring point; M is an integer greater than or equal to 2, and i is a positive integer less than or equal to M; The position of the monitoring point with the smallest error value among the M monitoring points is determined as the target position, wherein the target position is the position where the temperature and humidity sensor is placed.
2. The method according to claim 1, characterized in that Determine M error values of M monitoring points on the anemometer of the wind turbine, including: The i-th error value is determined by the following method to determine the M error values: Determine a first temperature value corresponding to the ith monitoring point according to the monitored temperature of the ith monitoring point, the relative humidity and the wind speed corresponding to the ith monitoring point; Determine a second temperature value corresponding to the ith monitoring point according to the monitored temperature of the ith monitoring point and the monitored temperature of the ith reference point among M reference points, wherein the M reference points are reference points corresponding to the M monitoring points, the ith reference point is symmetrical with the ith monitoring point with the central axis of the anemometer as the symmetry axis, and the anemometer is spherical in shape; The absolute value of the difference between the first temperature value and the second temperature value corresponding to the i-th monitoring point is determined as the i-th error value.
3. The method according to claim 2, characterized in that Determining a first temperature value corresponding to the ith monitoring point according to the monitored temperature of the ith monitoring point, the relative humidity and the wind speed corresponding to the ith monitoring point, comprising: The first temperature value corresponding to the ith monitoring point is determined according to the monitored temperature of the ith monitoring point, the relative humidity and the wind speed corresponding to the ith monitoring point by the following formula: Among them, ET is the first temperature value corresponding to the i-th monitoring point, T is the monitoring temperature of the i-th monitoring point, RH is the relative humidity corresponding to the i-th monitoring point, and V is the wind speed corresponding to the i-th monitoring point.
4. The method according to claim 2, characterized in that: Determining a second temperature value corresponding to the ith monitoring point according to the monitored temperature of the ith monitoring point and the monitored temperature of the ith reference point among the M reference points includes: In a case where the monitored temperature of the i-th monitoring point includes N first target temperatures at N moments, and the monitored temperature of the i-th reference point includes N second target temperatures at the N moments, determining an average value of the N first target temperatures to obtain a first temperature average value, and determining an average value of the N second target temperatures to obtain a second temperature average value, wherein N is a positive integer; Determine the standard deviation of the N first target temperatures according to the first temperature average value to obtain a first standard deviation; and determine the standard error of the N second target temperatures according to the second temperature average value to obtain a second standard deviation; A second temperature value corresponding to the i-th monitoring point is determined according to the first temperature average value, the second temperature average value, the first standard deviation, and the second standard deviation.
5. The method according to claim 4, characterized in that Determining the standard deviation of the N first target temperatures according to the first temperature average value to obtain a first standard deviation includes: calculating the first standard deviation using the following formula: in, is the first standard deviation, is the pth first target temperature among the N first target temperatures, is the first temperature average value, and p is a positive integer less than or equal to N; Determining the standard errors of the N second target temperatures according to the second temperature average value to obtain a second standard deviation includes: calculating the second standard deviation using the following formula: in, is the second standard deviation, is the pth second target temperature among the N second target temperatures, is the second temperature average value.
6. The method according to claim 4, characterized in that Determining a second temperature value corresponding to the i-th monitoring point according to the first temperature average value, the second temperature average value, the first standard deviation, and the second standard deviation includes: The second temperature value corresponding to the i-th monitoring point is determined by the following formula: in, is the first standard deviation, is the second standard deviation, is the first temperature average value, is the second average temperature, is the second temperature value corresponding to the i-th monitoring point.
7. The method according to claim 1, characterized in that After determining the position of the monitoring point with the smallest error value among the M monitoring points as the target position, the method further includes: Acquiring a target temperature and / or a target humidity detected by the temperature and humidity sensor located at the target location; When the target temperature is lower than a first preset threshold and / or the target humidity is lower than a second preset threshold, a deicing operation is performed on the anemometer.
8. A position determination device, characterized in that: include: A first determination module is used to determine M error values of M monitoring points on the anemometer of the wind turbine, wherein the i-th error value among the M error values is an error value of a first temperature value and a second temperature value corresponding to the i-th monitoring point among the M monitoring points, and the first temperature value corresponding to the i-th monitoring point has a correlation with the relative humidity and the wind speed corresponding to the i-th monitoring point; the second temperature value corresponding to the i-th monitoring point has no correlation with the relative humidity and the wind speed corresponding to the i-th monitoring point; M is an integer greater than or equal to 2, and i is a positive integer less than or equal to M; The second determination module is used to determine the position of the monitoring point with the smallest error value among the M monitoring points as the target position, wherein the target position is the position where the temperature and humidity sensor is placed.
9. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored program, wherein the program executes the method according to any one of claims 1 to 7 when executed.
10. An electronic device comprising a memory and a processor, characterized in that: A computer program is stored in the memory, and the processor is configured to execute the method according to any one of claims 1 to 7 through the computer program.
11. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.