Hydraulic variable pitch control method and system under complex wind conditions

Abstract

The embodiment of the invention provides a hydraulic variable pitch control method and system under a complex wind condition, and the method comprises the steps: obtaining the pressure data and piston displacement data of a plurality of oil cylinders in real time, and synchronously collecting the real-time wind speed data of an area where a unit is located; calculating pressure fluctuation intensity and wind speed fluctuation intensity of each oil cylinder in a plurality of continuous time windows based on the pressure data and the wind speed real-time data, and determining the number of turbulence early warning events in each time window based on a fluctuation threshold value; based on each piece of pressure data and each piece of piston displacement data, generating a load early warning mark of each blade in each time window; and in the continuous monitoring time period, the total occurrence frequency of the turbulence early warning mark and the load early warning mark is accumulated, when the total occurrence frequency reaches the set frequency, the output power of the unit is reduced to an adjustment value, and the adjustment value is obtained through calculation according to the average power in the monitoring time period. The blade load state can be analyzed in real time, and active safety protection is achieved under the complex wind condition.

Description

Technical Field

[0001] The present application belongs to the field of wind power generation technology, and specifically relates to a hydraulic pitch control method and system under complex wind conditions. Background Art

[0002] In complex operating environments such as mountainous terrain and offshore, wind turbines often face the challenges of complex wind conditions. These impacts on the turbines in multiple dimensions, including unstable power generation, unstable mechanical component structures, poor control decision-making accuracy, and threats to grid security. Specific reasons include frequent fluctuations in wind speed and direction, leading to unstable output power. Strong gusts or excessive turbulence require turbine power throttling to ensure safety, resulting in power loss. Non-uniform aerodynamic forces subject blades to alternating stresses, inducing fatigue cracks or even fractures. Fluctuations in rotor speed and torque accelerate wear in the transmission system. Tower vibrations can induce resonance, impacting structural stability. The complexity and uncertainty of wind conditions complicate control algorithm design, making sensors susceptible to interference and errors, reducing decision-making accuracy. Power fluctuations lead to output voltage instability, exceeding the grid's tolerance range. Power electronic equipment generates harmonic currents, causing voltage waveform distortion and threatening grid security.

[0003] Currently, complex wind condition detection relies primarily on the following methods: Anemometers / wind vanes are installed on the hub or tower top to measure wind speed and direction in real time, but the equipment lacks stability and accuracy, making it difficult to meet control requirements. LiDAR is used to monitor wind conditions at different heights and provide early warnings, but this is expensive and requires a separate system configuration. Acoustic radar is suitable for complex terrain and offshore environments, acquiring three-dimensional wind field data and optimizing unit layout. Meteorological satellites are used to assess wind energy resources at a macro level, but this lacks timeliness and accuracy, making it impossible to support precise control. Wind conditions are indirectly inferred using parameters such as power and speed, but timeliness and accuracy are difficult to guarantee. Summary of the Invention

[0004] The present application proposes a hydraulic pitch control method and system under complex wind conditions to address the above-mentioned defects of the prior art.

[0005] According to a first aspect of an embodiment of the present application, a method for controlling a hydraulic pitch in complex wind conditions is provided, comprising:

[0006] Acquire the pressure data and piston displacement data of multiple oil cylinders in real time, and simultaneously collect the real-time wind speed data in the area where the unit is located;

[0007] Based on the pressure data and the real-time wind speed data, calculating the pressure fluctuation intensity and wind speed fluctuation intensity of each cylinder in a plurality of consecutive time windows, and determining the number of turbulence warning events in each time window based on a fluctuation threshold;

[0008] generating a load warning mark for each blade within each time window based on each pressure data and each piston displacement data;

[0009] During the continuous monitoring period, the total number of occurrences of the turbulence warning mark and the load warning mark is accumulated. When the total number of occurrences reaches the set number, the unit output power is reduced to an adjustment value, and the adjustment value is calculated based on the average power during the monitoring period.

[0010] In some embodiments, determining the number of turbulence warning events within each time window based on the fluctuation threshold includes:

[0011] When the fluctuation intensity of the oil cylinder pressure in the same time window exceeds the pressure fluctuation threshold, and the wind speed fluctuation intensity in the time window exceeds the second threshold, it is marked as the turbulence warning event.

[0012] In some embodiments, generating a load warning mark for each blade in each time window based on each pressure data and each piston displacement data includes:

[0013] generating an actual driving torque value of a corresponding blade based on the pressure data and the piston displacement data of each cylinder;

[0014] Counting the first number of times that the actual driving torque value of each blade exceeds a load intensity threshold within each time window;

[0015] When any of the first times exceeds a proportion threshold, a load warning mark is generated.

[0016] In some embodiments, calculating the pressure fluctuation intensity of each cylinder in a plurality of consecutive time windows includes:

[0017] calculating the standard deviation of the pressure of each of the oil cylinders within a plurality of consecutive time windows;

[0018] The pressure fluctuation intensity is obtained based on the standard deviation of the pressure.

[0019] In some embodiments, the standard deviation of the pressure is calculated by the following formula:

[0020]

[0021] Where S represents the standard deviation of the pressure, n represents the sample size, and x i represents the value of the i-th pressure data, represents the sample mean.

[0022] In some embodiments, calculating the wind speed fluctuation intensity of each oil cylinder within a plurality of consecutive time windows includes:

[0023] Calculating the standard deviation of each of the real-time wind speed data in a plurality of consecutive time windows;

[0024] The wind speed fluctuation intensity is obtained based on the standard deviation of the real-time wind speed data.

[0025] In some embodiments, the standard deviation of the real-time wind speed data is calculated by the following formula:

[0026]

[0027] Wherein, Tur represents the wind speed fluctuation intensity, V i Represents the real-time data of wind speed, V m represents the average wind speed, and 3000 is the number of sampling points.

[0028] In some embodiments, generating the actual driving torque value of the corresponding blade based on the pressure data and the piston displacement data of each cylinder includes:

[0029] Determining a lever arm length of the corresponding blade based on the piston displacement data;

[0030] The actual driving torque value of the corresponding blade is generated based on the product of the pressure data and the lever arm length.

[0031] In some embodiments, the duration of each time window is 1 minute; and / or

[0032] The continuous monitoring time is 10 minutes; and / or

[0033] The set number of times is 3 times.

[0034] According to a second aspect of an embodiment of the present application, a hydraulic pitch control system for complex wind conditions is provided, comprising:

[0035] The data acquisition module is used to obtain real-time pressure data and piston displacement data of multiple cylinders, and simultaneously collect real-time wind speed data in the area where the unit is located;

[0036] a turbulence warning module, configured to calculate, based on the pressure data and the real-time wind speed data, the pressure fluctuation intensity and the wind speed fluctuation intensity of each cylinder in a plurality of consecutive time windows, and determine, based on a fluctuation threshold, the number of turbulence warning events in each of the time windows;

[0037] A load warning module, configured to generate a load warning mark for each blade within each of the time windows based on each of the pressure data and each of the piston displacement data;

[0038] The control execution module is used to accumulate the total number of occurrences of the turbulence warning mark and the load warning mark during a continuous monitoring period. When the total number of occurrences reaches a set number, the unit output power is reduced to an adjustment value, and the adjustment value is calculated based on the average power during the monitoring period.

[0039] According to a third aspect of an embodiment of the present application, a computer-readable storage medium is provided, on which a computer program is stored, characterized in that when the program is executed by a processor, the above-mentioned hydraulic pitch control method under complex wind conditions is implemented.

[0040] The beneficial effects of the hydraulic pitch control method and system under complex wind conditions of the embodiments of the present application include at least:

[0041] The embodiment of the present application establishes millisecond-level dynamic monitoring capabilities by synchronously collecting cylinder pressure, piston displacement and wind speed data, eliminates sensor delay differences, provides a consistent data foundation for accurate analysis, and realizes real-time multi-source data synchronous perception; calculates the pressure fluctuation intensity and wind speed fluctuation intensity of continuous time windows, and combines them with preset thresholds for dual verification to significantly improve the reliability of complex wind condition identification, reduce the risk of single data misjudgment, and realize dual fluctuation threshold joint judgment; generates each blade driving torque based on the physical relationship between pressure and displacement, and independently marks load warnings after counting the over-limit ratio, realizing accurate fault location of the three blades, supporting targeted maintenance, and realizing independent diagnosis of blade-level load risks; by accumulating the total number of turbulence and load warnings, dynamically adjusts the output according to the average power of the monitoring period after reaching the set value, taking into account safety protection and power generation efficiency, and realizing cumulative warning triggering dynamic power reduction; also uses the accumulation mechanism to avoid instantaneous fluctuation malfunction and realize adaptive optimization of power adjustment value according to actual working conditions. The present application monitors the cylinder pressure and driving torque changes of the hydraulic pitch system, analyzes the blade load status in real time, and realizes active safety protection under complex wind conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 This is a flow chart of a hydraulic pitch control method under complex wind conditions according to an embodiment of the present application;

[0043] Figure 2 This is a schematic structural diagram of a hydraulic pitch control system under complex wind conditions according to an embodiment of the present application. DETAILED DESCRIPTION

[0044] In order to enable those skilled in the art to better understand the technical solution of the present application, the present application is further described in detail below with reference to the accompanying drawings and specific implementation methods.

[0045] The following detailed description of the embodiments of the present application is provided in conjunction with the accompanying drawings and examples. The following detailed description of the embodiments and the accompanying drawings are used to illustrate the principles of the present application, but are not intended to limit the scope of the present application, that is, the present application is not limited to the described embodiments.

[0046] Refer to the attached Figure 1 As shown, the embodiment of the present application discloses specific implementation steps of a hydraulic pitch control method under complex wind conditions. The method is implemented by a hydraulic pitch control system under complex wind conditions. The hydraulic pitch control system under complex wind conditions includes a readable storage medium to ensure that those skilled in the art can implement the technical solution of the present application accordingly. The method specifically includes the following steps 110-150.

[0047] Step 110 , obtaining the pressure data and piston displacement data of multiple cylinders in real time, and synchronously collecting the real-time wind speed data of the area where the unit is located.

[0048] In some embodiments, the data collection and processing of this step can be carried out through the pitch system controller of the wind turbine generator set (such as a programmable logic controller, PLC for short) and the main control system PLC, to collect key operating data of the hydraulic pitch system and the main control system in real time, and the sampling interval can be, for example, 20ms.

[0049] In some embodiments, the collected key operating data is processed as follows: data extraction, displacement conversion and filtering. The data extraction may include extracting the pressure data of multiple cylinders (e.g., the cylinder pressure data P1, P2, P3 of three pitch cylinders), piston displacement data (e.g., the linear displacement data L1, L2, L3 of three pitch cylinders), proportional valve control parameters (K p , K i ), unit power measurement value (P) and real-time wind speed data in the area where the unit is located. Displacement transfer can include linear displacement L j (j = 1, 2, 3, representing the piston displacement data of the three pitch cylinders respectively) is converted into the corresponding pitch angle. Filtering can use a low-pass filter to remove sudden interference caused by equipment start-up and shutdown, ensuring the accuracy of subsequent algorithm judgments.

[0050] Step 120 , based on the pressure data and the real-time wind speed data, calculate the pressure fluctuation intensity and wind speed fluctuation intensity of each cylinder in multiple consecutive time windows, and determine the number of turbulence warning events in each time window based on the fluctuation threshold.

[0051] Among them, turbulence warning is mainly manifested as frequent fluctuations in the pressure of the three variable pitch drive cylinders due to severe fluctuations. The change in cylinder pressure over a certain period of time is used to judge whether complex weather and wind conditions will occur.

[0052] In some embodiments, based on the fluctuation threshold, determining the number of turbulence warning events in each time window includes: when the fluctuation intensity of each cylinder pressure in the same time window exceeds the pressure fluctuation threshold, and the wind speed fluctuation intensity in the time window exceeds the second threshold, it is marked as a turbulence warning event.

[0053] In some embodiments, calculating the pressure fluctuation intensity of each oil cylinder in a plurality of consecutive time windows includes: calculating the standard deviation of the pressure of each oil cylinder in a plurality of consecutive time windows; and obtaining the pressure fluctuation intensity based on the standard deviation of the pressure.

[0054] In some embodiments, the duration of each time window is 1 minute.

[0055] For example, the pressure data and wind speed real-time data processed in step 110 can be segmented into 1-minute windows, and then the standard deviation of the three cylinder pressures for each minute can be calculated. The standard deviation of the pressure can be calculated using the following formula:

[0056]

[0057] Where S represents the standard deviation of pressure, n represents the sample size, and x i Indicates the value of the i-th pressure data, The number of sampling points per minute is 60000ms / 20ms = 3000 points. In addition, Sp1, Sp2, and Sp3 represent the standard deviation of the pressures of the three cylinders, respectively.

[0058] In some embodiments, calculating the wind speed fluctuation intensity of each oil cylinder in multiple consecutive time windows includes: calculating the standard deviation of each wind speed real-time data in multiple consecutive time windows; and obtaining the wind speed fluctuation intensity based on the standard deviation of the wind speed real-time data.

[0059] For example, when the current window is one minute, the standard deviation of the real-time wind speed data within the window can be calculated using the following formula:

[0060]

[0061] Among them, V m =average(V1+V2+…+V3000);

[0062] Among them, Tur represents the wind speed fluctuation intensity, V i Indicates real-time wind speed data, V m represents the average wind speed, 3000 is the number of sampling points, and average represents the averaging function. In addition, Tur1, Tur2, and Tur3 represent the wind speed fluctuation intensity of the three pitch control units, respectively.

[0063] In addition, the pressure fluctuation threshold (expressed as FZp) is used to characterize the pressure tolerance of the cylinder pressure fluctuation risk under complex wind conditions. The second threshold can be understood as the wind speed turbulence threshold (expressed as FZtur), which is used to determine the tolerance of the turbulence intensity of the external wind environment. For example, if Sp1>FZp, Sp2>FZp, and Sp3>FZp occur for three consecutive minutes, and Tur1>FZtur, Tur2>FZtur, and Tur3>FZtur occur at the same time, it is considered that complex wind conditions with high turbulence have occurred, and a turbulence warning event is marked.

[0064] Step 130 : generating a load warning mark for each blade in each time window based on each pressure data and each piston displacement data.

[0065] Among them, the load warning mark is used to indicate a sudden increase in the actual driving torque and a warning that exceeds the load limit, which can also indicate that a sudden increase in wind speed causes the ultimate load to exceed the limit; the load intensity threshold can also be understood as the load excess abnormality threshold (expressed as FZt), which is used to indicate the driving torque excess tolerance capacity.

[0066] In some embodiments, generating a load warning mark for each blade in each time window based on each pressure data and each piston displacement data includes: generating an actual driving torque value for the corresponding blade based on the pressure data and piston displacement data of each cylinder; counting the first number of times that the actual driving torque value of each blade in each time window exceeds a load intensity threshold; and generating a load warning mark when any first number exceeds a percentage threshold.

[0067] In some embodiments, generating the actual driving torque value of the corresponding blade based on the pressure data and piston displacement data of each cylinder includes: determining the lever arm length of the corresponding blade based on the piston displacement data; and generating the actual driving torque value of the corresponding blade based on the product of the pressure data and the lever arm length.

[0068] For example, the data processed in step 110 is stored in the PLC cache and divided into a time window of 1 minute for processing; the actual driving torque values ​​of the three variable pitches at each sampling point are calculated (the calculation method can be the product of length L and pressure P), and recorded as Trq1, Trq2 and Trq3 respectively; then the proportion of Trq1 exceeding FZt in each 1-minute time window is calculated. If the excess ratio reaches K or more within 1 minute (K is usually set to a value of about 10%), it is considered that the limit load exceeds the limit, and a load warning mark is generated. Similarly, it can also be used to calculate the excess ratio of Trq2 and Trq3. Among them, if any of Trq1, Trq2 and Trq3 exceeds the limit, a load excess warning is reported.

[0069] Step 140: During the continuous monitoring period, the total number of occurrences of the turbulence warning mark and the load warning mark is accumulated. When the total number of occurrences reaches the set number, the unit output power is reduced to an adjustment value. The adjustment value is calculated based on the average power during the monitoring period.

[0070] In some embodiments, the continuous monitoring time is 10 minutes; and / or the set number of times is 3 times.

[0071] For example, during the continuous monitoring period, warning information is continuously recorded. If more than three cumulative warnings occur within 10 minutes, the power limit is reduced to the adjustment value. The adjustment value can be understood as the active power target value, and the calculation method of the adjustment value can be expressed as follows:

[0072] Ptarget=Kp*Pavg.

[0073] Wherein, Ptarget is the adjustment value, Pavg is the actual average power in the previous 10 minutes, and KP is the power reduction coefficient (a value less than 1).

[0074] In addition, during the reduced power operation, if there is no alarm information after half an hour, normal operation will be restored.

[0075] The embodiment of the present application establishes millisecond-level dynamic monitoring capabilities by synchronously collecting cylinder pressure, piston displacement and wind speed data, eliminates sensor delay differences, provides a consistent data foundation for accurate analysis, and realizes real-time multi-source data synchronous perception; calculates the pressure fluctuation intensity and wind speed fluctuation intensity of continuous time windows, and combines them with preset thresholds for dual verification to significantly improve the reliability of complex wind condition identification, reduce the risk of single data misjudgment, and realize dual fluctuation threshold joint judgment; generates each blade driving torque based on the physical relationship between pressure and displacement, and independently marks load warnings after counting the over-limit ratio, realizing accurate fault location of the three blades, supporting targeted maintenance, and realizing independent diagnosis of blade-level load risks; by accumulating the total number of turbulence and load warnings, dynamically adjusts the output according to the average power of the monitoring period after reaching the set value, taking into account safety protection and power generation efficiency, and realizing cumulative warning triggering dynamic power reduction; also uses the accumulation mechanism to avoid instantaneous fluctuation malfunction and realize adaptive optimization of power adjustment value according to actual working conditions. The present application monitors the cylinder pressure and driving torque changes of the hydraulic pitch system, analyzes the blade load status in real time, and realizes active safety protection under complex wind conditions.

[0076] Refer to the attached Figure 2 As shown, an embodiment of the present application further provides a hydraulic pitch control system under complex wind conditions, including: a data acquisition module 210 , a turbulence warning module 220 , a load warning module 230 and a control execution module 240 .

[0077] The data acquisition module 210 is used to obtain the pressure data and piston displacement data of multiple cylinders in real time, and simultaneously collect the real-time wind speed data of the area where the unit is located.

[0078] The turbulence warning module 220 is used to calculate the pressure fluctuation intensity and wind speed fluctuation intensity of each cylinder in multiple consecutive time windows based on the pressure data and real-time wind speed data, and determine the number of turbulence warning events in each time window based on the fluctuation threshold.

[0079] The load warning module 230 is configured to generate a load warning mark for each blade in each time window based on each pressure data and each piston displacement data.

[0080] The control execution module 240 is used to accumulate the total number of occurrences of turbulence warning marks and load warning marks during the continuous monitoring period. When the total number of occurrences reaches a set number, the unit output power is reduced to an adjustment value. The adjustment value is calculated based on the average power during the monitoring period.

[0081] The embodiments of the present application accurately identify the turbulence risk caused by drastic changes in wind speed based on the intensity of cylinder pressure fluctuations in continuous time periods; when the fluctuation frequency exceeds the threshold and accumulates to a set number of times, it actively triggers power reduction control to reduce the mechanical load of the unit and realize turbulence warning in complex wind conditions; through the driving torque converted from cylinder pressure and displacement, it detects load surge and over-limit events in real time; when the over-limit ratio exceeds the standard cumulatively, it starts power limiting to avoid damage to the blade structure and realize extreme load over-limit protection; it directly uses the cylinder pressure sensor built into the hydraulic pitch system to feedback load changes, without the need for additional blade load monitoring equipment, significantly reducing implementation costs and improving system reliability, and realizing low-cost and high-reliability monitoring; for wind turbines equipped with blade load sensors, the power limiting control logic triggered by load changes is also applicable to the protection scope of this application, enhancing technical compatibility, and this application has a universal extension of the technical solution.

[0082] The present application also provides a computer-readable storage medium having a computer program stored thereon, wherein when the program is executed by a processor, the program implements the aforementioned method for controlling hydraulic pitch in complex wind conditions. For example, the method for controlling hydraulic pitch in complex wind conditions of the present application can be implemented via computer program instructions, and the relevant code can be stored in a computer-readable storage medium (such as a hard disk, SSD, or cloud server).

[0083] It is understood that the above embodiments are merely exemplary embodiments for illustrating the principles of the present application, and the present application is not limited thereto. Those skilled in the art may make various modifications and improvements without departing from the spirit and substance of the present application, and such modifications and improvements are also considered to be within the scope of protection of the present application.

Claims

1. A hydraulic pitch control method under complex wind conditions, characterized in that: include: Acquire the pressure data and piston displacement data of multiple oil cylinders in real time, and simultaneously collect the real-time wind speed data in the area where the unit is located; Based on the pressure data and the real-time wind speed data, calculating the pressure fluctuation intensity and wind speed fluctuation intensity of each cylinder in a plurality of consecutive time windows, and determining the number of turbulence warning events in each time window based on a fluctuation threshold; generating a load warning mark for each blade within each time window based on each pressure data and each piston displacement data; During the continuous monitoring period, the total number of occurrences of the turbulence warning mark and the load warning mark is accumulated. When the total number of occurrences reaches the set number, the unit output power is reduced to an adjustment value, and the adjustment value is calculated based on the average power during the monitoring period.

2. The method according to claim 1, characterized in that Determining the number of turbulence warning events within each time window based on the fluctuation threshold comprises: When the fluctuation intensity of the oil cylinder pressure in the same time window exceeds the pressure fluctuation threshold, and the wind speed fluctuation intensity in the time window exceeds the second threshold, it is marked as the turbulence warning event.

3. The method according to claim 1, characterized in that The generating of the load warning mark of each blade in each time window based on each pressure data and each piston displacement data includes: generating an actual driving torque value of a corresponding blade based on the pressure data and the piston displacement data of each cylinder; Counting the first number of times that the actual driving torque value of each blade exceeds a load intensity threshold within each time window; When any of the first times exceeds a proportion threshold, a load warning mark is generated.

4. The method according to claim 1, wherein Calculating the pressure fluctuation intensity of each oil cylinder in a plurality of consecutive time windows includes: calculating the standard deviation of the pressure of each of the oil cylinders within a plurality of consecutive time windows; The pressure fluctuation intensity is obtained based on the standard deviation of the pressure.

5. The method according to claim 4, characterized in that The standard deviation of the pressure is calculated by the following formula: Where S represents the standard deviation of the pressure, n represents the sample size, and x i represents the value of the i-th pressure data, represents the sample mean.

6. The method according to claim 1, characterized in that Calculating the wind speed fluctuation intensity of each oil cylinder in a plurality of consecutive time windows includes: Calculating the standard deviation of each of the real-time wind speed data in a plurality of consecutive time windows; The wind speed fluctuation intensity is obtained based on the standard deviation of the real-time wind speed data.

7. The method according to claim 6, characterized in that The standard deviation of the real-time wind speed data is calculated by the following formula: Wherein, Tur represents the wind speed fluctuation intensity, V i Represents the real-time data of wind speed, V m represents the average wind speed, and 3000 is the number of sampling points.

8. The method according to claim 3, characterized in that Generating the actual driving torque value of the corresponding blade based on the pressure data and the piston displacement data of each cylinder includes: Determining a lever arm length of the corresponding blade based on the piston displacement data; The actual driving torque value of the corresponding blade is generated based on the product of the pressure data and the lever arm length.

9. The method according to claim 1, characterized in that The duration of each time window is 1 minute; and / or The continuous monitoring time is 10 minutes; and / or The set number of times is 3 times.

10. A hydraulic pitch control system under complex wind conditions, characterized in that: include: The data acquisition module is used to obtain real-time pressure data and piston displacement data of multiple cylinders, and simultaneously collect real-time wind speed data in the area where the unit is located; a turbulence warning module, configured to calculate, based on the pressure data and the real-time wind speed data, the pressure fluctuation intensity and the wind speed fluctuation intensity of each cylinder in a plurality of consecutive time windows, and determine, based on a fluctuation threshold, the number of turbulence warning events in each of the time windows; A load warning module, configured to generate a load warning mark for each blade within each of the time windows based on each of the pressure data and each of the piston displacement data; The control execution module is used to accumulate the total number of occurrences of the turbulence warning mark and the load warning mark during a continuous monitoring period. When the total number of occurrences reaches a set number, the unit output power is reduced to an adjustment value, and the adjustment value is calculated based on the average power during the monitoring period.

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