Wind power plant fan power distribution method and device and computing equipment

Abstract

The invention relates to the technical field of wind driven generators, in particular to a wind power plant fan power distribution method and device, computing equipment and a computer readable storage medium. The method comprises the following steps: acquiring operation data of a fan, load data of a component and a material SN curve of the component; according to the load data and the material SN curve of the part, the accumulated fatigue damage and the residual life of the part are obtained; according to the operation data of the draught fan and the accumulated fatigue damage and the residual life of the parts, the accumulated fatigue damage, the residual life and the unit fatigue damage power of the draught fan are obtained on the basis of a preset weight value; and based on the current power target of the wind power plant, performing power distribution on the fans of the wind power plant according to the accumulated fatigue damage of the fans, the residual life of the fans and the unit fatigue damage power of the fans. The power distribution of the fans in the wind power plant is carried out based on the unit fatigue damage power, and the unit fatigue damage power is comprehensively considered, so that the service life balance of all the fans and the maximization of the generating capacity of the wind power plant are realized.

Description

Technical Field

[0001] The present invention relates to the technical field of wind turbines, and in particular to a method, device, computing equipment and computer-readable storage medium for allocating wind turbine power in a wind farm. Background Art

[0002] A wind farm consists of multiple wind turbines. The energy management and distribution methods of wind turbines in traditional wind farms are mostly aimed at maximizing the power generation of the entire farm, with less consideration given to the health of the wind turbines themselves and the impact on their lifespan. How to achieve life balance for all wind turbines and maximize the power generation of the wind farm under power restrictions or free power generation in the wind farm is a technical problem that needs to be solved urgently. Summary of the invention

[0003] In view of the above problems in the prior art, the present application provides a method and device for allocating wind turbine power in a wind farm, which can:

[0004] To achieve the above-mentioned object, the present application provides a first aspect of a wind farm wind turbine power distribution method, comprising:

[0005] Obtaining operation data of the fan, load data of components and material SN curves of the components;

[0006] Obtaining the accumulated fatigue damage and the remaining life of the component according to the load data and the material SN curve of the component;

[0007] According to the operation data of the fan, the accumulated fatigue damage and the remaining life of the components, the accumulated fatigue damage of the fan, the remaining life of the fan and the unit fatigue damage power of the fan are obtained based on the preset weight values ​​of the components;

[0008] Based on the current power target of the wind farm, the power of the wind turbines in the wind farm is allocated according to the accumulated fatigue damage of the wind turbines, the remaining life of the wind turbines and the unit fatigue damage power of the wind turbines.

[0009] In this embodiment, the power of wind turbines in the wind farm is allocated based on the unit fatigue damage power, and the unit fatigue damage power is comprehensively considered to achieve life balance of all wind turbines and maximization of wind farm power generation.

[0010] As a possible implementation of the first aspect, obtaining the accumulated fatigue damage and the remaining life of the wind turbine component includes:

[0011] Performing rain flow counting analysis on the load data and material SN curve of the fan component to obtain a Markov matrix of the fan component;

[0012] The accumulated fatigue damage and the remaining life of the fan component are calculated based on the Markov matrix and the SN curve of the material.

[0013] As a possible implementation of the first aspect, after obtaining the accumulated fatigue damage and the remaining life of the wind turbine component, the method further includes:

[0014] Obtaining operating data and life cycle operating characteristic curves of the fan components;

[0015] Analyze the operating data and life cycle operating characteristic curve of the fan component to obtain a correction coefficient;

[0016] The accumulated fatigue damage and the remaining life are corrected by the correction coefficient.

[0017] As a possible implementation of the first aspect, the wind turbine unit fatigue damage power includes:

[0018] Determining fatigue damage data of the fan at different powers according to the operating data of the fan;

[0019] According to the fatigue damage data of the fan at different powers, the unit fatigue damage power ΔFd of the fan is obtained: power change / fan fatigue damage change.

[0020] As a possible implementation of the first aspect, the power allocation for the wind turbines in the wind farm based on the current power target of the wind farm and according to the accumulated fatigue damage of the wind turbines, the remaining life of the wind turbines and the unit fatigue damage power of the wind turbines includes:

[0021] Power allocation is performed when the wind farm is generating power at a limited power level, including:

[0022] Determine the difference △P between the current fan power and the power limit value;

[0023] According to the difference between the current wind turbine power and the power limit value and the unit fatigue damage power △Fd, Power allocation is performed; where △P is the difference between the current wind turbine power and the power limit value, △Fd is the unit fatigue damage power, and n is the number of wind turbines in the wind farm.

[0024] As a possible implementation of the first aspect, the power allocation for the wind turbines in the wind farm based on the current power target of the wind farm and according to the accumulated fatigue damage of the wind turbines, the remaining life of the wind turbines and the unit fatigue damage power of the wind turbines includes:

[0025] Power allocation during free generation of wind farms, including:

[0026] Determine the average value avg of the remaining fatigue life of the fan (DMRL i ) selected ;

[0027] Determine the power change of the fan - unit fatigue damage power (ΔP / ΔFd) i changes;

[0028] According to the average value of the remaining fatigue life, (ΔP / ΔFd) i To regulate the variable, power distribution is performed on the fans.

[0029] As a possible implementation of the first aspect, according to the average value of the remaining fatigue life, the (ΔP / ΔFd) i To adjust the variable, the wind turbine is allocated power, including:

[0030] Power limitation is applied to wind turbines whose average remaining fatigue life is lower than a preset threshold;

[0031] Over-fatigue is performed on wind turbines whose average remaining fatigue life is higher than a preset threshold.

[0032] A second aspect of the present application provides a wind farm power distribution device, comprising:

[0033] A data acquisition module, used to acquire the operation data of the fan, the load data of the components and the material SN curve of the components;

[0034] A calculation module, used for obtaining the accumulated fatigue damage and the remaining life of the component according to the load data and the SN curve of the material of the component;

[0035] The calculation module is further used to obtain the cumulative fatigue damage of the fan, the remaining life of the fan and the unit fatigue damage power of the fan based on the preset weight values ​​of the components according to the operation data of the fan, the cumulative fatigue damage and the remaining life of the components;

[0036] The power allocation module is used to allocate power to the wind turbines in the wind farm based on the current power target of the wind farm, the accumulated fatigue damage of the wind turbines, the remaining life of the wind turbines and the unit fatigue damage power of the wind turbines.

[0037] A third aspect of the present application provides a computing device, including:

[0038] processor, and

[0039] A memory having program instructions stored therein, wherein when the program instructions are executed by the processor, the processor executes the wind farm power allocation method as described above.

[0040] A fourth aspect of the present application provides a computer-readable storage medium having program instructions stored thereon, and when the program instructions are executed by a computer, the computer executes the wind farm power allocation method as described above.

[0041] These and other aspects of the invention will become apparent from the following description of the embodiment(s). BRIEF DESCRIPTION OF THE DRAWINGS

[0042] The following further illustrates the various features of the present invention and the relationship between the various features with reference to the accompanying drawings. The accompanying drawings are all exemplary, some features are not shown in actual proportion, and some drawings may omit the conventional features in the field involved in the present application and are not necessary for the present application, or additionally show the features that are not necessary for the present application. The combination of the various features shown in the accompanying drawings is not intended to limit the present application. In addition, throughout this specification, the same figure numerals refer to the same content. The specific description of the drawings is as follows:

[0043] Figure 1 It is a schematic diagram of a flow chart of a method for allocating wind turbine power in a wind farm provided by an embodiment of the present application;

[0044] Figure 2 It is a structural schematic diagram of a wind farm wind turbine power distribution device 200 provided in an embodiment of the present application;

[0045] Figure 3 It is a structural schematic diagram of a computing device 900 provided in an embodiment of the present application. DETAILED DESCRIPTION

[0046] The technical solution provided by the present application is further described below with reference to the accompanying drawings and examples. It should be understood that the system structure and business scenarios provided in the examples of the present application are mainly to illustrate the possible implementation methods of the technical solution of the present application and should not be interpreted as the only limitation on the technical solution of the present application. It is known to those of ordinary skill in the art that with the evolution of the system structure and the emergence of new business scenarios, the technical solution provided by the present application is also applicable to similar technical problems.

[0047] It should be understood that the wind farm wind turbine power allocation scheme provided in the embodiments of the present application includes a wind farm wind turbine power allocation method, device, computing device, and computer-readable storage medium, etc. Since the principles of solving the problems in these technical solutions are the same or similar, some repetitive parts may not be repeated in the introduction of the following specific embodiments, but it should be regarded as that these specific embodiments have been referenced to each other and can be combined with each other.

[0048] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art of the present application. In case of any inconsistency, the meaning described in this specification or the meaning derived from the contents recorded in this specification shall prevail. In addition, the terms used herein are only for the purpose of describing the embodiments of the present application and are not intended to limit the present application.

[0049] A wind farm is composed of multiple wind turbines. The energy management and distribution methods of wind turbines in traditional wind farms are mostly to maximize the power generation of the entire field, and less consideration is given to the health of the wind turbines themselves and the degree of impact on their lifespan. How to achieve wind turbine power distribution while taking into account the most efficient power generation and lifespan of the wind farm under the conditions of power restriction or free power generation in the wind farm is a problem that needs to be balanced. This application distributes the power of wind turbines in a wind farm based on "unit fatigue damage power". When the power of a wind farm is limited, the unit fatigue damage power is comprehensively considered, and more power is allocated to units with large unit fatigue damage power. In the case of free power generation in a wind farm, the balanced development of the lifespan of wind turbines in the wind farm is the main consideration. First, the units with problems are excluded, and the average remaining lifespan of the remaining units is used as the benchmark value. The unit fatigue damage power defined in this application is used as the control quantity to achieve over-generation of some units within a controllable range, and strategic power limitation of some units, thereby achieving life balance of all wind turbines and maximization of wind farm power generation.

[0050] Figure 1 FIG. 1 is a flow chart of a method for allocating wind turbine power in a wind farm provided by the present application. Figure 1 As shown, the wind farm wind turbine power allocation method provided in this embodiment includes the following steps:

[0051] S101: Determine fatigue damage and remaining life of wind turbine components.

[0052] Calculate the accumulated fatigue damage and remaining life of the blade:

[0053] The blade root load data is obtained, and then the load data is processed using the rain flow counting method to obtain the number and amplitude of the load cycle. Then, the Markov matrix can be constructed using these load cycle number and amplitude data.

[0054] The Markov matrix describes the probability of a system transitioning between different states. Here, states can refer to different load amplitude ranges or load cycle number ranges. By calculating and analyzing the Markov matrix, the transition probability between different states can be obtained.

[0055] Combined with the SN curve of the material, the load under different conditions can be converted into equivalent stress amplitude. The SN curve describes the fatigue life of the material under different stress amplitudes. By converting the load into the equivalent stress amplitude, the cumulative fatigue damage of the blade can be calculated.

[0056] The cumulative fatigue damage of the blade can be calculated using fatigue damage accumulation theories, such as linear cumulative damage theory or Palmgren-Miner criterion. These theories weighted sum the fatigue damage of different load cycles to obtain the cumulative fatigue damage of the blade.

[0057] The remaining life can be estimated by comparing the accumulated fatigue damage with the known fatigue life of the material. If the accumulated fatigue damage exceeds the fatigue life of the material, then the blade can be considered to have reached its life limit and needs to be repaired or replaced.

[0058] Calculate the accumulated fatigue damage and remaining life of components such as the spindle:

[0059] The load characteristics of components such as the main shaft can be obtained through state observation technology, and the accumulated fatigue damage and remaining life of components such as the main shaft can be calculated in the same way as the accumulated fatigue damage and remaining life of the blade in step S101.

[0060] Among them, state observation techniques refer to a method of estimating the internal state of a system by measuring and processing the input and output signals of the system. In practical applications, it is sometimes impossible to directly measure the internal state of the system, and the internal state of the system can only be inferred by measuring the input and output signals of the system. Commonly used state observation techniques include: Kalman Filtering, Extended Kalman Filtering, Particle Filtering, and Extended Particle Filtering, etc.

[0061] In some embodiments, the method further includes correcting the accumulated fatigue damage and the remaining life of each component.

[0062] The data of the condition detection system is obtained and used, combined with the operating characteristic curve of the component life cycle obtained by the test, and the fatigue damage change, cumulative fatigue damage and remaining life calculation calculated by the above load are corrected using the weighted method.

[0063] Specifically, the data of the vibration and other status detection system may include:

[0064] Vibration data: including parameters such as vibration velocity, vibration displacement, and vibration acceleration of each component of the fan; these parameters can be used to evaluate the vibration of each component of the fan and determine whether there is abnormal vibration. Spectral analysis data: by performing spectral analysis on the vibration signal, the energy distribution of the vibration signal at different frequencies can be obtained; these data can be used to determine whether there is a vibration problem of a specific frequency, such as resonance. Temperature data: the temperature data of each component of the fan can be used to evaluate the working condition and fatigue damage of the component; high temperature may cause accelerated fatigue of the component material, while low temperature may cause embrittlement and deformation of the component. Pressure data: the pressure data of each component of the fan can be used to evaluate the stress condition and fatigue damage degree of the component; excessive pressure may cause deformation and fatigue damage of the component. Current data: the current data of the fan motor can be used to evaluate the working condition and fatigue damage of the motor; excessive current may indicate that the motor load is too large and there is a risk of fatigue damage. Acceleration data: the acceleration data of each component of the fan can be used to evaluate the stress condition and vibration state of the component; excessive acceleration may cause fatigue damage of the component.

[0065] By collecting, analyzing and monitoring the data from the above-mentioned status detection system, the working status and fatigue damage of each component of the wind turbine can be monitored in real time, and its remaining life can be evaluated.

[0066] The operating characteristic curve of the component life cycle obtained by testing is a curve obtained by testing each component: the performance, status or reliability index of the component changes over time. Specific operating characteristic curves may include:

[0067] Performance curve: This curve describes how the performance of a component changes over time; for example, the output power of a fan may gradually decrease as the operating time increases due to blade wear or reduction in blade surface area. Failure curve: This curve describes how the failure rate of a component changes over time; typically, the failure rate of a component is low when it is first used, and then gradually increases until it reaches a steady state; this curve can help predict the risk of component failure. Reliability curve: This curve describes how the reliability of a component changes over time; reliability refers to the probability that a component will work properly with specified requirements within a given period of time; reliability curves are usually decreasing because reliability decreases over time due to wear and aging of the component. Maintenance curve: This curve describes how the maintenance rate of a component changes over time; the maintenance rate refers to the frequency with which a component needs to be repaired or replaced within a given period of time; maintenance curves are usually increasing because over time, the wear and failure rate of the component increases, requiring more frequent maintenance.

[0068] Finally, the accumulated fatigue damage and remaining life of each component are corrected using a weighted method, which may include:

[0069] 1) Determine weights: weights can be set for the data of the condition detection system and the operating characteristic curve of the component life cycle obtained from the test according to the work manual, specific circumstances or actual data, and expert experience; weights can be assigned according to their importance to fatigue damage and remaining life assessment. In some embodiments, if the data of the condition detection system is more important for assessing fatigue damage, it can be given a higher weight.

[0070] 2) According to the set weights, the data of each state detection system are weighted averaged to obtain a comprehensive state evaluation value.

[0071] For the various parameters of the component life cycle operation characteristic curve obtained from the data test of the vibration and other status detection systems, there may be different dimensions and ranges; in order to compare and weight them, the data needs to be normalized, etc.

[0072] 3) Weighted calculation: Based on the set weights and normalized data, weighted calculation is performed on the data of the detection system and the operating characteristic curve of the component life cycle obtained from the test; the weighted value can be calculated using weighted average, that is, the value of each parameter is multiplied by the corresponding weight, and then all weighted values ​​are added together.

[0073] 4) Correction of fatigue damage and remaining life calculation: Based on the results obtained by weighted calculation, they can be applied to fatigue damage change, cumulative fatigue damage and remaining life calculation to correct the original calculation results. The corrected results will more accurately reflect the actual fatigue damage degree and remaining life of the components.

[0074] For example, for the blades and the main shaft, the status of the blades and the main shaft is monitored by the vibration state detection system and the temperature sensor. Assume that the blades are very important for the operation of the entire wind turbine, while the main shaft has a relatively small impact on the overall operation. When setting the weight, according to the importance of the blades and the main shaft, the vibration state detection system (representing the blade status) is given a higher weight, such as 0.7, while the temperature sensor (representing the main shaft status) is given a weight of 0.3.

[0075] Then, the data of the vibration and other state detection system and the temperature sensor are weighted averaged according to the weights. Assuming that the data of the vibration and other state detection system is 0.8 and the data of the temperature sensor is 0.6, the comprehensive state evaluation value is:

[0076] (0.7*0.8)+(0.3*0.6)=0.74

[0077] Cumulative fatigue damage correction: Use the comprehensive state assessment value of 0.74 to correct the calculation of cumulative fatigue damage. Assume that the fatigue damage model used is the SN curve method, where S represents stress and N represents the number of cycles. According to the fatigue damage model, the comprehensive state assessment value of 0.74 can be used as a correction factor in the fatigue damage calculation formula.

[0078] Corrected cumulative fatigue damage = correction factor * original cumulative fatigue damage.

[0079] Remaining life calculation: First, obtain the strength parameters of the material, such as tensile strength, yield strength, etc. Detect the stress of the object: It can include axial, shear, bending, etc. Calculate the strength ratio: Divide the stress of the object by the strength parameter of the material to get the strength ratio. If the strength ratio is less than 1, it means that the strength of the object has not exceeded the strength of the material and still has a reliable life. Estimate the remaining life: According to the relationship between the strength ratio and the service life, use the residual strength factor method to estimate the remaining life of the object. This relationship can be obtained through experiments or empirical formulas.

[0080] In addition, in addition to the residual strength factor method cited in the implementation of this application, there are other applicable methods to calculate the remaining life, such as fatigue life method, reliability analysis method, etc. The specific steps and principles of these methods may be different, but the basic idea is to estimate the remaining life by quantitatively analyzing the stress and material performance of the object. The specific method to be selected should be determined according to the specific situation and application field, and this application does not limit it.

[0081] S102: Determine the remaining life of the fan.

[0082] Based on the probability of fan component failure and the downtime caused (for example, blade damage causes a long failure time and a small number of failures, while inverter damage causes a long failure time and a large number of failures), weights are set to comprehensively calculate the fan fatigue damage change, cumulative fatigue damage, and remaining life of the fan.

[0083] For example:

[0084] First, the failure probability and downtime of each component need to be determined. In practical applications, this can be obtained through historical data, reliability data provided by manufacturers, or experience knowledge in professional fields.

[0085] Assume that the probability of blade failure is 0.05, that is, each fan blade has a 5% probability of failure after one use. The average downtime of the blade is 10 hours, that is, it takes an average of 10 hours of downtime for repair or replacement after a blade failure. The probability of inverter failure is 0.1, and each fan inverter has a 10% probability of failure after one use. The average downtime of the inverter is 2 hours, that is, it takes an average of 2 hours to repair or replace the inverter after a inverter failure.

[0086] Then, we set weights to comprehensively consider the failure of blades and inverters. Since the probability of blade failure is low, but the downtime is long, we can set the weight of blades to 0.7 and the weight of inverters to 0.3, indicating that the failure of blades has a greater impact on the life of the whole machine.

[0087] Finally, the fatigue damage model (fatigue life curve) and the remaining life calculation method can be used to calculate the fatigue damage change of the fan, the cumulative fatigue damage of the fan and the remaining life of the whole machine. Among them, the fatigue damage change can be described by Miner's linear cumulative damage method, assuming that the damage contribution of each cyclic stress is linearly superimposed. In some embodiments, the fatigue damage change calculation method is as follows:

[0088] Determine the stress amplitude Δσ and the number of cycles N for each cyclic stress.

[0089] The damage per stress cycle is calculated as D = Δσ / σf, where σf is the fatigue limit of the material.

[0090] According to Miner's criterion, the damage ratio D of each cyclic stress is divided by the number of cycles N of the cyclic stress, and then the results of all cycles are added together to obtain the cumulative damage ratio S.

[0091] The change of fatigue damage can be expressed by the SN curve, which describes the growth of fatigue damage with the number of cycles.

[0092] Remaining life of the whole machine DMRL i It can be calculated by comparing the accumulated fatigue damage with the fatigue life curve of the material. The fatigue life curve describes the life of the material under different force amplitudes. Based on the fatigue life curve and the cumulative damage ratio S, the remaining life DMRL of the wind turbine can be estimated. i .

[0093] S103: Determine the corresponding relationship between the power change and the fatigue damage change of the wind turbine.

[0094] The present application defines unit fatigue damage power as change in power / change in fatigue damage, expressed as ΔP / ΔFd.

[0095] Obtain the operating data of the wind turbine under extreme and normal working conditions, and analyze the acquired data to obtain the relationship between fatigue damage changes and working conditions and power changes, that is, to obtain the working condition (wind speed, wind direction, turbulence, etc.)-power-fatigue damage correlation model, and then obtain the working condition-unit fatigue damage power model (ΔP / ΔFd) i .

[0096] S104: Allocate power to wind turbines according to the power generation requirements of the wind farm.

[0097] The power generation requirements of a wind farm may include limited power generation of the wind farm and free power generation of the wind farm.

[0098] In the case of power-limited generation at a wind farm, that is, the output of the wind farm is limited by scheduling or other reasons, that is, the power that can be generated by the wind farm exceeds the power limit value of the wind farm, the wind farm needs to reduce or increase power (if the power that can be generated by the wind turbine is not exceeded, the scheduling power is increased), and the difference between the current power and the power limit value (for example, the current power is greater than the power limit value) is taken as the influencing factor, and the model ΔP / ΔFd of the working condition-unit fatigue damage power of each wind turbine is used. The power is weightedly allocated in a manner so that the total damage to all wind turbines in the wind farm is minimized while the power limit value is met.

[0099] In the case of free power generation in the wind farm, the wind turbine remaining life balance method is used to distribute the power generation, combined with the remaining life DMRL of a single wind turbine. i And the operating condition of a single wind turbine - unit fatigue damage power model (ΔP / ΔFd) i First, the distribution curve of the remaining fatigue life of all wind turbines is analyzed. Generally speaking, it should conform to the characteristics of normal distribution. The middle section of the normal distribution is taken (such as meeting the probability of 80%. This parameter can be adjusted in combination with different wind farms and wind turbine types). Next, the average value avg (DMRL) of the remaining fatigue life of the selected wind turbine is calculated. i ) selected . Take avg(DMRL i ) selected As a target, (ΔP / ΔFd) i As a control variable, the power allocation of each wind turbine is carried out. As a result, some wind turbines can be strategically and actively limited in power to reduce fatigue damage, such as the average value of the remaining fatigue life avg (DMRL i ) seThe wind turbines with lower lected can have their information power limited, while the wind turbines with higher average remaining fatigue life can be appropriately over-generated within the range allowed by the control system, so as to achieve life balance of wind farm wind turbines while maximizing the power generation of the wind farm.

[0100] In the above implementation of the present application, the power generation efficiency of the wind farm is maximized by comprehensively considering the correlation between fatigue damage and power of wind turbine components and the entire machine, and the balance strategy between wind farm power generation and wind turbine life.

[0101] Based on an inventive concept, the present application also provides a wind farm wind turbine power distribution device, such as Figure 2 As shown, Figure 2 2 is a schematic diagram of the structure of the wind farm wind turbine power distribution device 200 provided in the embodiment of the present application. The wind farm wind turbine power distribution device 200 of this embodiment is specifically used to perform the above steps S101 to S104 and any optional examples therein. For details, please refer to the detailed description in the method embodiment, which is briefly described as follows:

[0102] The wind farm power distribution device 200 comprises:

[0103] The data acquisition module 201 is used to acquire the operation data of the wind turbine, the load data of the components and the material SN curve of the components;

[0104] A calculation module 202, configured to obtain the accumulated fatigue damage and the remaining life of the component according to the load data and the SN curve of the material of the component;

[0105] The calculation module 202 is further used to obtain the cumulative fatigue damage of the fan, the remaining life of the fan and the unit fatigue damage power of the fan based on the preset weight values ​​of the components according to the operation data of the fan, the cumulative fatigue damage and the remaining life of the components;

[0106] The power allocation module 203 is used to allocate power to the wind turbines in the wind farm based on the current power target of the wind farm, the accumulated fatigue damage of the wind turbines, the remaining life of the wind turbines and the unit fatigue damage power of the wind turbines.

[0107] Figure 3 900 is a schematic structural diagram of a computing device 900 provided in an embodiment of the present application. The computing device can be used as a wind farm wind turbine power distribution device to execute the optional embodiments of the wind farm wind turbine power distribution method described above. The computing device can be a terminal or a chip or chip system inside the terminal. Figure 3 As shown, the computing device 900 includes: a processor 910 , a memory 920 , and a communication interface 930 .

[0108] It should be understood that Figure 3 The communication interface 930 in the computing device 900 shown may be used to communicate with other devices, and may specifically include one or more transceiver circuits or interface circuits.

[0109] The processor 910 may be connected to a memory 920. The memory 920 may be used to store the program code and data. Therefore, the memory 920 may be a storage unit inside the processor 910, or an external storage unit independent of the processor 910, or a component including a storage unit inside the processor 910 and an external storage unit independent of the processor 910.

[0110] Optionally, the computing device 900 may further include a bus. The memory 920 and the communication interface 930 may be connected to the processor 910 via the bus. The bus may be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 3 A line without an arrow is used to represent the bus, but this does not mean that there is only one bus or one type of bus.

[0111] It should be understood that in the embodiment of the present application, the processor 910 can adopt a central processing unit (CPU). The processor can also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor, etc. Or the processor 910 adopts one or more integrated circuits to execute related programs to implement the technical solutions provided in the embodiment of the present application.

[0112] The memory 920 may include a read-only memory and a random access memory, and provides instructions and data to the processor 910. A portion of the processor 910 may also include a nonvolatile random access memory. For example, the processor 910 may also store information on the device type.

[0113] When the computing device 900 is running, the processor 910 executes the computer-executable instructions in the memory 920 to perform any operation step of the above method and any optional embodiment thereof.

[0114] It should be understood that the computing device 900 according to the embodiment of the present application can correspond to the corresponding subjects in the methods according to the embodiments of the present application, and the above-mentioned and other operations and / or functions of each module in the computing device 900 are respectively for implementing the corresponding processes of each method of the present embodiment. For the sake of brevity, they will not be repeated here.

[0115] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0116] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0117] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0118] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0119] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0120] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0121] An embodiment of the present application also provides a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, it is used to execute the above method, which includes at least one of the solutions described in the above embodiments.

[0122] The computer storage medium of the embodiment of the present application can adopt any combination of one or more computer-readable media. Computer-readable media can be computer-readable signal media or computer-readable storage media. Computer-readable storage media can be, for example, but not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or devices, or any combination of the above. More specific examples (non-exhaustive lists) of computer-readable storage media include: electrical connections with one or more wires, portable computer disks, hard disks, random access memories (RAM), read-only memories (ROM), erasable programmable read-only memories (EPROM or flash memory), optical fibers, portable compact disk read-only memories (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the above. In this document, computer-readable storage media can be any tangible medium containing or storing programs, which can be used by instruction execution systems, devices or devices or used in combination with them.

[0123] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, which carry computer-readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0124] The program code embodied on the computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

[0125] The computer program code for performing the operation of the present application can be written in one or more programming languages ​​or a combination thereof, and the programming language includes an object-oriented programming language, such as Java, Small tale, C++, and also includes a conventional procedural programming language, such as "C" language or similar programming language. The program code can be executed completely on the user's computer, partially on the user's computer, as an independent software package, partially on the user's computer, partially on the remote computer, or completely on the remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computer (for example, using an Internet service provider to connect through the Internet). In addition, the words "first, second, third, etc." or similar terms such as module A, module B, module C in the specification and claims are only used to distinguish similar objects, and do not represent a specific order for the object. It can be understood that the specific order or sequence can be interchanged when allowed, so that the embodiment of the present application described here can be implemented in an order other than that illustrated or described here.

[0126] In the above description, the numbers representing the steps, such as S110, S120, etc., do not necessarily mean that the steps will be executed in this manner. If permitted, the order of the steps can be interchanged or they can be executed simultaneously.

[0127] The term "comprising" as used in the description and claims should not be interpreted as being limited to what is listed thereafter; it does not exclude other elements or steps. Therefore, it should be interpreted as specifying the presence of the features, integers, steps or components mentioned, but does not exclude the presence or addition of one or more other features, integers, steps or components and groups thereof. Therefore, the expression "a device comprising means A and B" should not be limited to a device consisting of components A and B only.

[0128] References to "one embodiment" or "an embodiment" in this specification mean that a particular feature, structure, or characteristic described in conjunction with the embodiment is included in at least one embodiment of the present application. Therefore, the phrases "in one embodiment" or "in an embodiment" appearing in various places in this specification do not necessarily refer to the same embodiment, but may refer to the same embodiment. In addition, in one or more embodiments, the particular features, structures, or characteristics can be combined in any appropriate manner, as would be apparent to one of ordinary skill in the art from this disclosure.

[0129] Note that the above are only preferred embodiments of the present application and the technical principles used. Those skilled in the art will understand that the present application is not limited to the specific embodiments described herein, and that various obvious changes, readjustments and substitutions can be made by those skilled in the art without departing from the scope of protection of the present application. Therefore, although the present application is described in more detail through the above embodiments, the present application is not limited to the above embodiments, and may also include more other equivalent embodiments without departing from the concept of the present application, all of which belong to the scope of protection of the present application.

Claims

1. A wind farm power allocation method, characterized in that: include: Obtaining operation data of the fan, load data of components and material SN curves of the components; Obtaining the accumulated fatigue damage and the remaining life of the component according to the load data and the material SN curve of the component; According to the operation data of the fan, the accumulated fatigue damage and the remaining life of the components, the accumulated fatigue damage of the fan, the remaining life of the fan and the unit fatigue damage power of the fan are obtained based on the preset weight values ​​of the components; Based on the current power target of the wind farm, the power of the wind turbines in the wind farm is allocated according to the accumulated fatigue damage of the wind turbines, the remaining life of the wind turbines and the unit fatigue damage power of the wind turbines.

2. The method according to claim 1, characterized in that Obtaining the accumulated fatigue damage and remaining life of the fan components, including: Performing rain flow counting analysis on the load data and material SN curve of the fan component to obtain a Markov matrix of the fan component; The accumulated fatigue damage and the remaining life of the fan component are calculated based on the Markov matrix and the SN curve of the material.

3. The method according to claim 1, characterized in that: After obtaining the accumulated fatigue damage and the remaining life of the fan components, the method further includes: Obtaining operating data and life cycle operating characteristic curves of the fan components; Analyze the operating data and life cycle operating characteristic curve of the fan component to obtain a correction coefficient; The accumulated fatigue damage and the remaining life are corrected by the correction coefficient.

4. The method according to claim 1, characterized in that: The unit fatigue damage power of the fan includes: Determining fatigue damage data of the fan at different powers according to the operating data of the fan; According to the fatigue damage data of the fan at different powers, the unit fatigue damage power ΔFd of the fan is obtained: power change / fan fatigue damage change.

5. The method according to claim 1, characterized in that The method of allocating power to the wind turbines in the wind farm based on the current power target of the wind farm and according to the accumulated fatigue damage of the wind turbines, the remaining life of the wind turbines and the unit fatigue damage power of the wind turbines comprises: Power allocation is performed when the wind farm is generating power at a limited power level, including: Determine the difference △P between the current fan power and the power limit value; According to the difference between the current wind turbine power and the power limit value and the unit fatigue damage power △Fd, according to (ΔP / ΔFd) i / ∑ n i＝1 (ΔP / ΔFd) i Power allocation is performed; where △P is the difference between the current wind turbine power and the power limit value, △Fd is the unit fatigue damage power, and n is the number of wind turbines in the wind farm.

6. The method according to claim 1, characterized in that The method of allocating power to the wind turbines in the wind farm based on the current power target of the wind farm and according to the accumulated fatigue damage of the wind turbines, the remaining life of the wind turbines and the unit fatigue damage power of the wind turbines comprises: Power allocation during free generation of wind farms, including: Determine the average value avg of the remaining fatigue life of the fan (DMRL i ) selected ; Determine the power change of the fan - unit fatigue damage power (ΔP / ΔFd) i changes; According to the average value of the remaining fatigue life, (ΔP / ΔFd) i To regulate the variable, power distribution is performed on the fans.

7. The method according to claim 6, characterized in that According to the average value of the remaining fatigue life, (ΔP / ΔFd) i To adjust the variable, the wind turbine is allocated power, including: Power limitation is applied to wind turbines whose average remaining fatigue life is lower than a preset threshold; Over-fatigue is performed on wind turbines whose average remaining fatigue life is higher than a preset threshold.

8. A wind farm power distribution device, characterized in that: include: A data acquisition module, used to acquire the operation data of the fan, the load data of the components and the material SN curve of the components; A calculation module, used for obtaining the accumulated fatigue damage and the remaining life of the component according to the load data and the SN curve of the material of the component; The calculation module is further used to obtain the cumulative fatigue damage of the fan, the remaining life of the fan and the unit fatigue damage power of the fan based on the preset weight values ​​of the components according to the operation data of the fan, the cumulative fatigue damage and the remaining life of the components; The power allocation module is used to allocate power to the wind turbines in the wind farm based on the current power target of the wind farm, the accumulated fatigue damage of the wind turbines, the remaining life of the wind turbines and the unit fatigue damage power of the wind turbines.

9. A computing device, characterized in that include: processor, and A memory having program instructions stored thereon, wherein when the program instructions are executed by the processor, the processor executes the wind farm power allocation method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: Program instructions are stored thereon, and when the program instructions are executed by a computer, the computer is enabled to execute the wind farm power allocation method according to any one of claims 1 to 7.

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