Method and device for determining mechanical parameters of fan system simulation model

Abstract

The present application discloses a method and device for determining the mechanical parameters of a wind turbine system simulation model. It relates to the field of power systems. The method comprises: establishing an initial simulation model, generating a simulation model under each operating environment, obtaining Q first simulation models, sequentially adding each group of second initial values ​​to the first simulation model, obtaining Q groups of second simulation models; sequentially substituting H groups of first initial values ​​into each second simulation model, obtaining T groups of simulation results, determining the concentration distribution diagram of each mechanical parameter according to the accuracy of each group of simulation results, determining the target operating environment corresponding to each mechanical parameter according to the concentration distribution diagram; obtaining the target concentration distribution diagram under the target operating environment, and determining the target parameter value of each mechanical parameter according to the target concentration distribution diagram. Through the present application, the problem of low accuracy of the simulation results of the wind turbine model caused by setting mechanical parameters in the wind turbine model by preset values ​​in the related art is solved.

Description

Technical Field

[0001] The present application relates to the field of power systems, and in particular, to a method and device for determining mechanical parameters of a wind turbine system simulation model. Background Art

[0002] In the field of wind power generation, doubly-fed wind turbines have become one of the most popular wind turbines because they can operate in a wide range of rotor speeds. Before a wind turbine is put into operation, an accurate wind turbine model must be generated, and a large-scale wind power grid-connected system must be studied through the wind turbine model to ensure the normal operation and grid connection of the doubly-fed wind turbine after it is put into operation.

[0003] However, when generating a wind turbine model, preset values ​​(such as values ​​specified by the manufacturer or values ​​obtained based on experience) are usually used to specify the mechanical parameters in the wind turbine model. However, using the above method will lead to inaccurate simulation models of wind turbines, which in turn affects the simulation results obtained through the simulation model, thereby causing abnormalities in the operation of the wind turbine.

[0004] Currently, no effective solution has been proposed to solve the problem that the mechanical parameters in the wind turbine model are set by preset values ​​in the related art, resulting in low accuracy of the simulation results of the wind turbine model. Summary of the invention

[0005] The present application provides a method and device for determining mechanical parameters of a wind turbine system simulation model, so as to solve the problem in the related art that mechanical parameters in a wind turbine model are set by preset values, resulting in low accuracy of simulation results of the wind turbine model.

[0006] According to one aspect of the present application, a method for determining mechanical parameters of a fan system simulation model is provided. The method comprises: establishing an initial simulation model of a transmission shaft of the fan system, and generating H groups of first initial values ​​and P groups of second initial values, wherein the simulation model comprises M mechanical parameters and N non-mechanical parameters, each group of first initial values ​​comprises a first initial value of each mechanical parameter, and each group of second initial values ​​comprises a second initial value of each non-mechanical parameter, M, N, H, and P are positive integers; the operating environment that the initial simulation model needs to simulate is obtained to obtain Q operating environments, and a simulation model under each operating environment is generated to obtain Q first simulation models, and each group of second initial values ​​is added to the first simulation model under each operating environment in turn to obtain Q groups of second simulation models, wherein each group of second simulation models includes P second simulation models, each second simulation model includes a group of second initial values, and Q is a positive integer; the H groups of first initial values ​​are substituted into each second simulation model in turn to obtain T groups of simulation results, and the concentration distribution diagram of each mechanical parameter under each operating environment is determined according to the accuracy of each group of simulation results to obtain K concentration distribution diagrams, and the target operating environment corresponding to each mechanical parameter is determined according to the K concentration distribution diagrams, wherein T is the product of P and Q, K is the product of M and Q, each group of simulation results includes H simulation results, and P, K, and T are positive integers; the target concentration distribution diagram under the target operating environment corresponding to each mechanical parameter is obtained, and the target parameter value of each mechanical parameter is determined according to the target concentration distribution diagram.

[0007] Optionally, generating H groups of first initial values ​​includes: obtaining mechanical parameters in the initial simulation model to obtain M mechanical parameters, and obtaining a preset true value of each mechanical parameter to obtain M preset true values; setting a value range of each mechanical parameter according to the preset true value of each mechanical parameter, and setting a fixed step size; adjusting the preset true value of each mechanical parameter according to the fixed step size to obtain H first initial values ​​of each mechanical parameter, wherein the H first initial values ​​include the preset true value; randomly grouping the H first initial values ​​of the M mechanical parameters to obtain H groups of first initial values, wherein each group of first initial values ​​includes M mechanical parameters, and each group of first initial values ​​includes a first initial value of each mechanical parameter.

[0008] Optionally, substituting H groups of first initial values ​​into each second simulation model in turn to obtain T groups of simulation results includes: obtaining the second simulation model corresponding to each group of second initial values ​​under each operating environment to obtain T second simulation models; for each second simulation model, adding each group of first initial values ​​in the H groups of first initial values ​​to the second simulation model in turn to obtain H third simulation models; running the H third simulation models to obtain a generator rotor speed simulation curve output by each third simulation model, and using the H simulation curves to determine a simulation result to obtain H simulation results; determining the H simulation results as a group of simulation results to obtain a group of simulation results for the second simulation model.

[0009] Optionally, a concentration distribution diagram of each mechanical parameter under each operating environment is determined according to the accuracy of each group of simulation results, and K concentration distribution diagrams are obtained, including: for any group of target simulation results in P groups of simulation results under each operating environment, a measurement curve of the generator rotor speed is obtained, and multiple sampling points are set; in any group of target simulation results, the difference in speed value between each target simulation curve and the measurement curve at each sampling point is obtained to obtain H groups of speed difference values, and the error value between the measurement curve and the simulation curve is calculated according to multiple speed difference values ​​in each group of speed difference values ​​to obtain H error values; the minimum error value among the H error values ​​is obtained, and a group of first initial values ​​corresponding to the minimum error value is determined to obtain the target initial value; a group of target initial values ​​corresponding to each simulation result is obtained to obtain P groups of target initial values, and the first initial value corresponding to each mechanical parameter in the P groups of target initial values ​​is extracted to obtain M sets of first initial value sets; the number of occurrences of each first initial value in each set of first initial value sets is obtained, and a distribution diagram of each set of first initial value sets is generated according to the number of occurrences to obtain a concentration distribution diagram of each mechanical parameter under each operating environment.

[0010] Optionally, the error value between the measurement curve and the simulation curve is calculated according to multiple speed difference values ​​in each group of speed difference values ​​to obtain H error values, including: calculating the ratio between each speed difference value in each group of speed difference values ​​and the corresponding measurement value to obtain multiple ratios; calculating the average value of the multiple ratios, and determining the average value as the error value of each group of speed difference values ​​to obtain H error values.

[0011] Optionally, determining the target operating environment corresponding to each mechanical parameter based on K concentration distribution graphs includes: obtaining the concentration of the concentration distribution graph of each mechanical parameter in each operating environment to obtain Q concentrations; and determining the operating environment to which the concentration distribution graph with the largest concentration belongs as the target operating environment corresponding to the mechanical parameter.

[0012] Optionally, obtaining a target concentration distribution diagram under a target operating environment corresponding to each mechanical parameter, and determining a target parameter value of each mechanical parameter based on the target concentration distribution diagram includes: for each mechanical parameter, obtaining the concentration of the target concentration distribution diagram under the target operating environment, and determining whether the concentration is greater than or equal to a preset concentration; when the concentration is greater than or equal to the preset concentration, obtaining the first initial value that appears most frequently in the target concentration distribution diagram, and determining the first initial value that appears most frequently as the target parameter value of the mechanical parameter; when the concentration is less than the preset concentration, obtaining the first initial value that appears most frequently in the target concentration distribution diagram, and obtaining a value interval of the first initial value whose number of occurrences is greater than 0 from the target concentration distribution diagram to obtain a target value interval; adjusting the first initial value according to the target value interval to obtain the target parameter value of the mechanical parameter.

[0013] According to another aspect of the present application, a device for determining the mechanical parameters of a simulation model of a fan system is provided. The device includes: a generating unit, which is used to establish an initial simulation model of the transmission shaft of the fan system, and generate H groups of first initial values ​​and P groups of second initial values, wherein the simulation model includes M mechanical parameters and N non-mechanical parameters, each group of first initial values ​​includes a first initial value for each mechanical parameter, and each group of second initial values ​​includes a second initial value for each non-mechanical parameter, and M, N, H, and P are positive integers; an adding unit, which is used to obtain the operating environment that the initial simulation model needs to simulate, obtain Q operating environments, and generate a simulation model under each operating environment to obtain Q first simulation models, and sequentially add each group of second initial values ​​to the first simulation model under each operating environment to obtain Q groups of second simulation models, wherein each group of second simulation models includes P second simulation models, and each second simulation model includes a group of second initial values, and Q is a positive integer; a first determining unit, which is used to sequentially substitute the H groups of first initial values ​​into each second simulation model, T groups of simulation results are obtained, and a concentration distribution diagram of each mechanical parameter in each operating environment is determined according to the accuracy of each group of simulation results, K concentration distribution diagrams are obtained, and a target operating environment corresponding to each mechanical parameter is determined according to the K concentration distribution diagrams, wherein T is the product of P and Q, K is the product of M and Q, each group of simulation results includes H simulation results, and P, K, and T are positive integers; a second determination unit is used to obtain a target concentration distribution diagram under the target operating environment corresponding to each mechanical parameter, and determine a target parameter value of each mechanical parameter according to the target concentration distribution diagram.

[0014] According to another aspect of the present invention, a computer program product is provided, including a computer program, wherein when the computer program is executed by a processor, the method for determining mechanical parameters of a fan system simulation model in the present application is implemented.

[0015] According to another aspect of the present invention, there is also provided an electronic device comprising one or more processors and a memory; the memory stores computer-readable instructions, and the processor is used to run the computer-readable instructions, wherein when the computer-readable instructions are run, a method for determining mechanical parameters of a fan system simulation model is executed.

[0016] Through the present application, the following steps are adopted: establishing an initial simulation model of the transmission shaft of the fan system, and generating H groups of first initial values ​​and P groups of second initial values, wherein the simulation model includes M mechanical parameters and N non-mechanical parameters, each group of first initial values ​​includes a first initial value of each mechanical parameter, and each group of second initial values ​​includes a second initial value of each non-mechanical parameter, M, N, H, and P are positive integers; the operating environment that the initial simulation model needs to simulate is obtained to obtain Q operating environments, and a simulation model under each operating environment is generated to obtain Q first simulation models, and each group of second initial values ​​is added to the first simulation model under each operating environment in turn to obtain Q groups of second simulation models, wherein each group of second simulation models includes P second simulation models, each second simulation model includes a group of second initial values, and Q is a positive integer; the H groups of first initial values ​​are substituted into each second simulation model in turn to obtain T groups of simulation results, and the concentration distribution diagram of each mechanical parameter under each operating environment is determined according to the accuracy of each group of simulation results to obtain K concentration distribution diagrams, and the target operating environment corresponding to each mechanical parameter is determined according to the K concentration distribution diagrams, wherein T is the product of P and Q, K is the product of M and Q, each group of simulation results includes H simulation results, and P, K, and T are positive integers; the target concentration distribution diagram under the target operating environment corresponding to each mechanical parameter is obtained, and the target parameter value of each mechanical parameter is determined according to the target concentration distribution diagram. The problem that the mechanical parameters in the wind turbine model are set by preset values ​​in the related art, resulting in low accuracy of the simulation results of the wind turbine model, is solved. By establishing an initial simulation model of the transmission shaft of the wind turbine system, setting the initial values ​​of various parameters, and performing simulations under different operating environments according to different permutations and combinations of the initial values ​​of different parameters, a concentration distribution diagram of different mechanical parameter values ​​is obtained, and then the operating environment with the highest concentration of each mechanical parameter value is determined according to the concentration distribution diagram, and the parameter with the highest accuracy is obtained under the operating environment as the value of the mechanical parameter, thereby achieving the effect of improving the accuracy of obtaining the value of the mechanical parameter in the simulation model. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The drawings constituting a part of the present application are used to provide a further understanding of the present application. The illustrative embodiments and descriptions of the present application are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0018] Figure 1is a flow chart of a method for determining mechanical parameters of a fan system simulation model provided in an embodiment of the present application;

[0019] Figure 2 is a schematic diagram of an optional grid-connected structure of a doubly-fed wind turbine system provided according to an embodiment of the present application;

[0020] Figure 3 It is an optional generator rotor speed signal waveform diagram for calculating the generator inertia time constant and the generator damping coefficient provided in an embodiment of the present application;

[0021] Figure 4 is an optional wind speed disturbance signal waveform diagram provided according to an embodiment of the present application;

[0022] Figure 5 is an optional two-rotor speed disturbance signal waveform diagram provided according to an embodiment of the present application;

[0023] Figure 6 is an optional concentration distribution diagram of mechanical parameters under wind speed disturbance provided according to an embodiment of the present application;

[0024] Figure 7 It is an optional concentration distribution diagram of mechanical parameters under rotor speed broken line disturbance provided according to an embodiment of the present application;

[0025] Figure 8 is an optional concentration distribution diagram of mechanical parameters under a step-type disturbance of rotor speed provided in accordance with an embodiment of the present application;

[0026] Fig. 9 is a schematic diagram of a device for determining mechanical parameters of a fan system simulation model provided in an embodiment of the present application;

[0027] Fig.10 It is a schematic diagram of an electronic device provided according to an embodiment of the present application. DETAILED DESCRIPTION

[0028] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0029] 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.

[0030] 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 sequential order. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present application described here. 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.

[0031] It should be noted that the method and device for determining the mechanical parameters of the wind turbine system simulation model determined in the present disclosure can be used in the field of power systems, and can also be used in any field other than the field of power systems. The application field of the method and device for determining the mechanical parameters of the wind turbine system simulation model determined in the present disclosure is not limited.

[0032] It should be noted that the collected information, user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) used in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, storage, use, processing, transmission, provision, disclosure and application of relevant data are in compliance with the relevant laws, regulations and standards of the relevant regions, necessary confidentiality measures are taken, and public order and good customs are not violated. Corresponding operation portals are provided for users to choose to authorize or refuse to use. For example, an interface is set up between this system and relevant users or organizations. Before obtaining relevant information, it is necessary to send an acquisition request to the aforementioned user or organization through the interface, and obtain relevant information after receiving the consent information fed back by the aforementioned user or organization.

[0033] For the convenience of description, some nouns or terms involved in the embodiments of the present application are explained below:

[0034] Doubly-fed wind turbine system is a design scheme of wind turbine generator set, mainly composed of doubly-fed induction generator, rotor, doubly-fed converter and power grid. In this system, the rotor of wind turbine generator can be driven by the power provided by the power grid or by the power generated by the wind turbine rotor, so it is called doubly-fed system.

[0035] DFIG: Doubly Fed Induction Generator is a type of generator commonly used in wind turbines. It can control the power flow between the rotor and the grid through electronic devices on the rotor, thereby improving the efficiency and flexibility of wind turbines. Compared with traditional fixed-speed generators, DFIG has a higher variable speed adjustment range and better grid adaptability.

[0036] According to an embodiment of the present application, a method for determining mechanical parameters of a fan system simulation model is provided.

[0037] Figure 1 FIG. 1 is a flow chart of a method for determining mechanical parameters of a fan system simulation model according to an embodiment of the present application. Figure 1 As shown, the method comprises the following steps:

[0038] Step S101, establish an initial simulation model of the drive shaft of the fan system, and generate H groups of first initial values ​​and P groups of second initial values, wherein the simulation model includes M mechanical parameters and N non-mechanical parameters, each group of first initial values ​​includes a first initial value for each mechanical parameter, each group of second initial values ​​includes a second initial value for each non-mechanical parameter, and M, N, H, and P are positive integers.

[0039] It should be noted that the wind turbine system can be a double-fed wind turbine system. Figure 2 is a schematic diagram of an optional grid-connected structure of a doubly-fed wind turbine system provided according to an embodiment of the present application, such as Figure 2 As shown, an initial simulation model of the drive shaft of the wind turbine system can be first built in the simulation software, wherein the initial model can include components of the doubly fed wind turbine system, but does not include model parameters, and the components can use the simulation module carried by the simulation software.

[0040] Specifically, in order to obtain accurate mechanical parameters, it is first necessary to build an initial simulation model of the drive shaft of the fan system in a simulation environment, and set H groups of first initial values ​​and P groups of second initial values. For example, 21 groups of first initial values ​​and 100 groups of second initial values ​​can be set, wherein the first initial value is the parameter value corresponding to the mechanical parameter, and the second initial value is the parameter value corresponding to the non-mechanical parameter. The second initial value of each non-mechanical parameter can be selected in its respective value range. In order to ensure the accuracy of the obtained mechanical parameters, it is necessary to set H groups of first initial values, so as to determine the optimal value of each mechanical parameter in the H groups of first initial values.

[0041] It should be noted that since the non-mechanical parameters in the model may change, in order to ensure that the optimal mechanical parameter value can still be selected when the non-mechanical parameters change, it is also necessary to set the second initial value of group P to simulate the doubly fed wind turbine system under different non-mechanical parameters, thereby ensuring the accuracy of the mechanical parameters.

[0042] For example, the simulation model may include 6 mechanical parameters, and 21 groups of first initial values ​​(ie, H=21) may be set. Each group of first initial values ​​includes parameter values ​​of each mechanical parameter, and the parameter values ​​corresponding to the same mechanical parameters in different groups are different. Similarly, the simulation model may include 15 non-mechanical parameters (ie, N=15), and 100 groups of second initial values ​​(ie, P=100) may be set. Each group of second initial values ​​includes parameter values ​​of each non-mechanical parameter, and the parameter values ​​corresponding to the same mechanical parameters in different groups may be the same or different. However, the set mechanical parameters and non-mechanical parameters cannot exceed their respective value ranges. Table 1 shows the true values ​​and value ranges of the parameters of each part of the doubly fed wind turbine generator set, and the value ranges can be obtained from Table 1.

[0043] Table 1

[0044]

[0045] It should be noted that the transmission shaft model of the doubly-fed wind turbine system can be represented by the following mathematical model, as shown in Formula 1 to Formula 4:

[0046] (1)

[0047] (2)

[0048] (3)

[0049] (4)

[0050] Among them, H w and H g are the inertia time constants of wind turbine and generator rotors respectively; K sh is the transmission shaft stiffness coefficient; D sh is the mutual damping between the two masses; D w and D g is the damping coefficient of the wind turbine and generator; T w 、T e 、T sh They are the mechanical torque of the wind turbine, the electromagnetic torque of the generator, and the mechanical torque transmitted by the shaft system; ω w and ω g are the wind turbine speed and generator rotor speed respectively; ω sis the basic value of the speed, usually 1; θ sh is the relative angular displacement between the two masses. There are 6 mechanical parameters of the doubly fed wind turbine system: H w , H g , K sh , D w , D g and D sh .

[0051] Furthermore, in order to simplify the calculation, the order of the transmission shaft mathematical model can be reduced by deriving the following formula, as shown in Formula 5 and Formula 6, where:

[0052] In the mathematical equation of the drive shaft model, when ω w and ω g When the first-order derivative of is zero, we can get:

[0053] (5)

[0054] Among them, D Σ Yes D w and D g The sum of the values ​​can therefore be obtained by using Formula 5 and D w Calculate and get D g .

[0055] Furthermore, when ω w =ω g And dω w / d t =dω g / d t When , we can get:

[0056] (6)

[0057] Among them, H Σ Yes H w and H g The sum of the values ​​can be obtained by using Formula 6 and H w Calculate and get H g Then, if the above conditions are met, D can be calculated by formula 5 and formula 6. g and H g , thus reducing the mechanical parameters to be obtained in the simulation model of the doubly fed wind turbine system to 4, namely H w , K sh , D w and D sh . Figure 3 is an optional generator rotor speed signal waveform diagram for calculating the generator inertia time constant and the generator damping coefficient according to an embodiment of the present application, wherein Figure 3The moment indicated by the black dot, dω w / d t and dω g / d t are all zero, Figure 3 In the period indicated by the solid line, ω w =ω g And dω w / d t =dω g / d t , so H can be calculated from the data at the solid line moment g , calculate D at the time indicated by the black dot position g , thereby simplifying the six mechanical parameters that need to be calculated to four, thereby improving the calculation efficiency of the model.

[0058] Step S102, obtain the operating environment that the initial simulation model needs to simulate, obtain Q operating environments, and generate a simulation model under each operating environment to obtain Q first simulation models, and add each group of second initial values ​​to the first simulation model under each operating environment in turn to obtain Q groups of second simulation models, wherein each group of second simulation models contains P second simulation models, each second simulation model contains a group of second initial values, and Q is a positive integer.

[0059] Specifically, since disturbances may occur in the doubly-fed wind turbine system during operation, in order to ensure that the mechanical parameters can still maintain accuracy under different disturbances, when obtaining the mechanical parameters, it is necessary to set a simulation model for different disturbance conditions, that is, each operating environment corresponds to a disturbance, and each disturbance corresponds to a simulation model, so as to obtain Q first simulation models.

[0060] Figure 4 is an optional wind speed disturbance signal waveform diagram provided according to an embodiment of the present application, Figure 5 is an optional two-rotor speed disturbance signal waveform diagram provided according to an embodiment of the present application, such as Figure 4 and Figure 5 As shown, Figure 4 and Figure 5 Three different disturbance situations are shown, so Q in the present application can be 3, that is, simulation models corresponding to the three disturbance situations in the figure are obtained, and three first simulation models are obtained.

[0061] Furthermore, after obtaining Q first simulation models, since there are no parameters in the first simulation model, it is necessary to add each group of second initial values ​​to the first simulation model under each operating environment respectively, so as to obtain Q groups of second simulation models, wherein, since there are P groups of second initial values, each group of second simulation models contains P second simulation models with different non-mechanical parameters, thereby completing the preliminary construction of the simulation model.

[0062] It should be noted that when obtaining the second initial value, since the second initial value is the parameter value of the non-mechanical parameter, the 15 non-mechanical parameters of the generator and the controller can be randomly combined, and random values ​​can be taken within their value ranges to form sufficient samples (such as 100 groups) of random value combinations of generator and controller parameters to obtain P groups of second initial values.

[0063] Step S103, substituting H groups of first initial values ​​into each second simulation model in turn to obtain T groups of simulation results, and determining the concentration distribution diagram of each mechanical parameter in each operating environment according to the accuracy of each group of simulation results, obtaining K concentration distribution diagrams, and determining the target operating environment corresponding to each mechanical parameter according to the K concentration distribution diagrams, wherein T is the product of P and Q, K is the product of M and Q, each group of simulation results contains H simulation results, and P, K, and T are positive integers.

[0064] Specifically, after obtaining Q groups of second simulation models, since each group of second simulation models includes P second simulation models, there are a total of T second simulation models. At this time, it is necessary to substitute the H groups of first initial values ​​into each second simulation model to obtain T groups of third simulation models, and obtain T groups of simulation results based on the T groups of third simulation models, wherein the simulation result can be the generator rotor speed ω output by the simulation model g , due to ω g Since it is a value that can be directly measured, it can be obtained by ω g Determine if the mechanical parameters are accurate.

[0065] Furthermore, after obtaining T groups of simulation results, since each group of simulation results contains H simulation results, it is necessary to select the simulation result that is closest to the actual measurement result from the H simulation results, and obtain a set of mechanical parameters corresponding to the simulation result, and then obtain P groups of mechanical parameters from P second simulation models, and determine the occurrence probability of P parameter values ​​of each mechanical parameter in the P groups of mechanical parameters, and statistically analyze the occurrence probability of the parameter value of each mechanical parameter to obtain a concentration distribution diagram of each mechanical parameter in each operating environment, and then compare the three concentration distribution diagrams of the mechanical parameters to obtain the optimal concentration distribution diagram, so as to determine the target operating environment corresponding to the optimal concentration distribution diagram of each mechanical parameter.

[0066] For example, P is 100, H is 21, and each of the 100 second simulation models contains 21 simulation results. A set of mechanical parameters corresponding to the optimal simulation result among the 21 simulation results is obtained to obtain 100 sets of mechanical parameters under the operating environment. Since there are repeated values ​​in the 100 parameter values ​​corresponding to each mechanical parameter in the 100 sets of mechanical parameters, the number of occurrences of the 100 parameter values ​​corresponding to each mechanical parameter can be counted to obtain a concentration distribution diagram of each mechanical parameter under each operating environment.

[0067] Step S104, obtaining a target concentration distribution diagram under a target operating environment corresponding to each mechanical parameter, and determining a target parameter value of each mechanical parameter according to the target concentration distribution diagram.

[0068] Specifically, after obtaining the target operating environment corresponding to each mechanical parameter, it is necessary to obtain a concentration distribution diagram under the target operating environment obtained in step S103, that is, a target concentration distribution diagram, and after obtaining the target concentration distribution diagram, the parameter value with the largest number of appearances in the target concentration distribution diagram can be obtained as the target parameter value of the mechanical parameter, thereby obtaining the optimal mechanical parameter value of the mechanical parameter under different operating environments and different non-mechanical parameters, thereby improving the accuracy of obtaining the parameter value of the mechanical parameter.

[0069] The method for determining the mechanical parameters of the fan system simulation model provided in the embodiment of the present application establishes an initial simulation model of the transmission shaft of the fan system and generates H groups of first initial values ​​and P groups of second initial values, wherein the simulation model includes M mechanical parameters and N non-mechanical parameters, each group of first initial values ​​includes a first initial value of each mechanical parameter, and each group of second initial values ​​includes a second initial value of each non-mechanical parameter. M, N, H, and P are positive integers; the operating environment that the initial simulation model needs to simulate is obtained to obtain Q operating environments, and a simulation model under each operating environment is generated to obtain Q first simulation models, and each group of second initial values ​​is added to the first simulation model under each operating environment in turn to obtain Q groups of second simulation models, wherein each group of second simulation models includes P second simulation models, each second simulation model includes a group of second initial values, and Q is a positive integer; the H groups of first initial values ​​are substituted into each second simulation model in turn to obtain T groups of simulation results, and the concentration distribution diagram of each mechanical parameter under each operating environment is determined according to the accuracy of each group of simulation results to obtain K concentration distribution diagrams, and the target operating environment corresponding to each mechanical parameter is determined according to the K concentration distribution diagrams, wherein T is the product of P and Q, K is the product of M and Q, each group of simulation results includes H simulation results, and P, K, and T are positive integers; the target concentration distribution diagram under the target operating environment corresponding to each mechanical parameter is obtained, and the target parameter value of each mechanical parameter is determined according to the target concentration distribution diagram. The problem that the mechanical parameters in the wind turbine model are set by preset values ​​in the related art, resulting in low accuracy of the simulation results of the wind turbine model, is solved. By establishing an initial simulation model of the transmission shaft of the wind turbine system, setting the initial values ​​of various parameters, and performing simulations under different operating environments according to different permutations and combinations of the initial values ​​of different parameters, a concentration distribution diagram of different mechanical parameter values ​​is obtained, and then the operating environment with the highest concentration of each mechanical parameter value is determined according to the concentration distribution diagram, and the parameter with the highest accuracy is obtained under the operating environment as the value of the mechanical parameter, thereby achieving the effect of improving the accuracy of obtaining the value of the mechanical parameter in the simulation model.

[0070] In order to ensure the accuracy of the first initial value, optionally, in the method for determining the mechanical parameters of the fan system simulation model provided in the embodiment of the present application, generating H groups of first initial values ​​includes: obtaining the mechanical parameters in the initial simulation model to obtain M mechanical parameters, and obtaining the preset true value of each mechanical parameter to obtain M preset true values; setting the value range of each mechanical parameter according to the preset true value of each mechanical parameter, and setting a fixed step size; adjusting the preset true value of each mechanical parameter according to the fixed step size to obtain H first initial values ​​of each mechanical parameter, wherein the H first initial values ​​include the preset true value; randomly grouping the H first initial values ​​of the M mechanical parameters to obtain H groups of first initial values, wherein each group of first initial values ​​includes M mechanical parameters, and each group of first initial values ​​includes a first initial value of each mechanical parameter.

[0071] Specifically, when generating the first initial value, it is necessary to first obtain the mechanical parameters that need to be determined in the initial simulation model, that is, H w , K sh , D w and D sh . Afterwards, it is necessary to obtain the preset true value of each mechanical parameter, wherein the preset true value may be a preset value carried in the model, or a preset value determined based on experience, and set the value range of each mechanical parameter according to the preset true value of each mechanical parameter, and set a fixed step size, wherein the value range may be the range of the preset true value [-50%, +50%], and the fixed step size may be 5%, so that 21 first initial values ​​including the preset true value may be obtained.

[0072] Furthermore, after obtaining 21 first initial values ​​of each mechanical parameter, the 21 first initial values ​​of each mechanical parameter need to be shuffled and reorganized to obtain 21 groups of first initial values, wherein each group of first initial values ​​includes a first initial value of each mechanical parameter, thereby obtaining H groups of first initial values.

[0073] In this embodiment, by setting the first initial value according to the preset true value, the number of first initial values ​​can be increased while ensuring that the mechanical parameter can be located in a relatively accurate value range, thereby ensuring the accuracy of the first initial value of the mechanical parameter.

[0074] Optionally, in the method for determining the mechanical parameters of the fan system simulation model provided in an embodiment of the present application, H groups of first initial values ​​are substituted into each second simulation model in turn to obtain T groups of simulation results, including: obtaining the second simulation model corresponding to each group of second initial values ​​under each operating environment to obtain T second simulation models; for each second simulation model, adding each group of first initial values ​​in the H groups of first initial values ​​to the second simulation model in turn to obtain H third simulation models; running the H third simulation models to obtain a generator rotor speed simulation curve output by each third simulation model, and using the H simulation curves to determine a simulation result to obtain H simulation results; determining the H simulation results as a group of simulation results to obtain a group of simulation results for the second simulation model.

[0075] Specifically, when obtaining the simulation result, since the second simulation model has been generated, the H groups of first initial values ​​are substituted into each second simulation model respectively to obtain P groups of third simulation models, wherein each group of third simulation models includes H third simulation models, and each third simulation model has complete operating parameters. Therefore, the third simulation model can be run according to the parameters in the third simulation model to obtain the simulation result, wherein the simulation result can be the generator rotor speed ω that can be directly measured. g .

[0076] Further, after the simulation results are obtained, a group of simulation results obtained by the third simulation model corresponding to each second simulation model may be determined as a group of simulation results, thereby obtaining P groups of simulation results.

[0077] It should be noted that each simulation result may be a generator rotor speed simulation curve within the measurement time, so that the generator rotor speed simulation curve and the actual measured generator rotor speed measurement curve can be compared to determine the optimal mechanical parameters.

[0078] Optionally, in the method for determining the mechanical parameters of the wind turbine system simulation model provided in the embodiment of the present application, a concentration distribution diagram of each mechanical parameter under each operating environment is determined according to the accuracy of each group of simulation results, and K concentration distribution diagrams are obtained, including: for any group of target simulation results in P groups of simulation results under each operating environment, a measurement curve of the generator rotor speed is obtained, and a plurality of sampling points are set; in any group of target simulation results, the difference between the speed values ​​of each target simulation curve and the measurement curve at each sampling point is obtained to obtain H groups of speed differences, and a plurality of speed differences in each group of speed differences are calculated. The error value between the measurement curve and the simulation curve is obtained to obtain H error values; the minimum error value among the H error values ​​is obtained, and a group of first initial values ​​corresponding to the minimum error value is determined to obtain the target initial value; a group of target initial values ​​corresponding to each simulation result is obtained to obtain P groups of target initial values, and the first initial value corresponding to each mechanical parameter in the P groups of target initial values ​​is extracted to obtain M sets of first initial values; the number of occurrences of each first initial value in each set of first initial values ​​is obtained, and a distribution diagram of each set of first initial values ​​is generated according to the number of occurrences to obtain a concentration distribution diagram of each mechanical parameter under each operating environment.

[0079] Specifically, when obtaining the concentration distribution diagram, it is first necessary to determine the operating environment and obtain P groups of simulation results under each operating environment, wherein each group of simulation results includes H generator rotor speed simulation curves.

[0080] Furthermore, after obtaining P groups of simulation results, since the second simulation model of each group of simulation results is different, it is necessary to obtain the measurement curve of the generator rotor speed corresponding to each group of simulation results, and set multiple sampling points, and obtain the speed value on the measurement curve of the generator rotor speed at each sampling point corresponding to each group of second simulation models, as well as the speed value on each generator rotor speed simulation curve, and calculate the speed value on each generator rotor speed simulation curve with the speed value on the measurement curve of the generator rotor speed to obtain an average error value, and then determine a group of first initial values ​​with the smallest error based on the average error value to obtain the target initial value corresponding to each second simulation model.

[0081] Further, after obtaining a set of target initial values ​​corresponding to each second simulation model, the P sets of target initial values ​​can be classified according to the mechanical parameters to obtain M first initial value sets, wherein each first initial value set includes P initial values ​​belonging to the same mechanical parameter. After obtaining the M first initial value sets, since the same first initial value exists in each initial value set, a distribution diagram of each first initial value set can be generated according to the number of occurrences, that is, the quantity, of each first initial value in the set, thereby obtaining a concentration distribution diagram of the mechanical parameter to which each first initial value set belongs.

[0082] Figure 6 is an optional concentration distribution diagram of mechanical parameters under wind speed disturbance provided in an embodiment of the present application, Figure 7 is an optional concentration distribution diagram of mechanical parameters under rotor speed broken line disturbance provided according to an embodiment of the present application, Figure 8 is an optional concentration distribution diagram of mechanical parameters under a step-type disturbance of rotor speed provided in an embodiment of the present application, such as Figures 6 to 8 As shown, the distribution of different first initial values ​​of different mechanical parameters under different operating environments can be observed respectively, and then the optimal first initial value can be determined according to the distribution.

[0083] For example, the mechanical parameter D of the doubly fed wind turbine system sh As an example, the 15 parameters of the generator and controller of the doubly fed wind turbine system are fixed to a random combination of 100 groups of samples, and the parameters D sh Then, from small to large, we increase the parameter D sh Fixed to 21 different preset values, and calculated the parameter D sh The error indicator ARE value at different preset values ​​is plotted into an ARE curve, and then the parameter preset value corresponding to the lowest point of the ARE curve is selected. Then, the parameter D is calculated in the same way. sh The ARE curves of all other generators and controllers under random value samples are selected, and the parameter preset values ​​corresponding to the lowest points of all ARE curves are selected, and the statistical parameter D sh The number of times it falls on 21 preset values; finally, calculate the parameter D sh The probability of falling into 21 preset values ​​is plotted to show the parameter D sh The concentration distribution diagram of Figure 6-8 shown.

[0084] Optionally, in the method for determining the mechanical parameters of the fan system simulation model provided in an embodiment of the present application, the error value between the measurement curve and the simulation curve is calculated according to multiple speed difference values ​​in each group of speed difference values, and H error values ​​are obtained, including: calculating the ratio between each speed difference value in each group of speed difference values ​​and the corresponding measurement value to obtain multiple ratios; calculating the average value of the multiple ratios, and determining the average value as the error value of each group of speed difference values, to obtain H error values.

[0085] Specifically, when determining the error value, it can be calculated by the following formula 7:

[0086] (7)

[0087] Among them, ARE is the average error value, is the speed value of the i-th sampling point on the generator rotor speed simulation curve, is the speed value of the i-th sampling point of the measurement curve of the generator rotor speed, and C is the number of sampling points.

[0088] Optionally, in the method for determining the mechanical parameters of the fan system simulation model provided in the embodiment of the present application, determining the target operating environment corresponding to each mechanical parameter based on K concentration distribution diagrams includes: obtaining the concentration of the concentration distribution diagram of each mechanical parameter in each operating environment to obtain Q concentrations; and determining the operating environment to which the concentration distribution diagram with the largest concentration belongs as the target operating environment corresponding to the mechanical parameter.

[0089] Specifically, after obtaining the concentration distribution diagram of each mechanical parameter in each operating environment, the concentration of the concentration distribution diagram at multiple positions on the curve can be obtained, and the maximum concentration in the concentration distribution diagram can be obtained. The three maximum concentrations corresponding to the same mechanical parameter are compared, and the operating environment to which the concentration distribution diagram to which the maximum value of the three maximum concentrations belongs belongs is determined as the target operating environment.

[0090] For example, Figures 6 to 8 As shown, the mechanical parameter D sh For example, through analysis, we can see that Figure 8 The curve concentration in is the largest. Figure 6 Minimum, therefore, Figure 8 The corresponding rotor speed step disturbance environment is the target operating environment.

[0091] For example, with D sh For example, from Figure 6-8 Medium mechanical parameters D sh It can be seen from the concentration distribution diagram that when the generator and controller parameters are uncertain, the mechanical parameter D sh Only under the condition of broken line or step rotor speed disturbance, the concentration is high; but under the condition of wind speed disturbance, the mechanical parameter D sh Affected by the parameters of the generator and controller, the distribution is very scattered. Figure 8 Medium mechanical parameters D sh From the probability distribution diagram, we can see that the mechanical parameter D sh Under the step-type rotor speed disturbance, the influence of the uncertainty of the generator and controller parameters is the smallest, and the parameter distribution is the most concentrated. Therefore, this disturbance is most suitable for determining the mechanical parameter D sh .from Figure 6 Medium mechanical parameters D sh From the probability distribution diagram, we can see that the mechanical parameter D sh Under wind speed disturbance, the uncertainty of the generator and controller parameters has a great influence on the parameter distribution, so the mechanical parameter D is very dispersed.sh Cannot be accurately determined using concentration distribution graphs.

[0092] It should be noted that after the target operating environment corresponding to each mechanical parameter is determined, the parameter value of each mechanical parameter may be determined in sequence by changing the environment.

[0093] For example, when the second initial value is 100 groups of random value combinations, the wind speed disturbance is used as the model input excitation, and the mechanical parameter D is determined by the model. w Then, under the second initial value of 100 random value combinations, the rotor speed zigzag disturbance is used as the input excitation to determine the mechanical parameter K sh and H w Then, based on the three determined mechanical parameters, the final system mechanical parameter D is determined with the rotor speed step disturbance as input excitation under the second initial value of 100 random value combinations. sh , thereby completing the operation of determining the parameter values ​​of the mechanical parameters.

[0094] Optionally, in the method for determining the mechanical parameters of the fan system simulation model provided in the embodiment of the present application, a target concentration distribution diagram under the target operating environment corresponding to each mechanical parameter is obtained, and the target parameter value of each mechanical parameter is determined according to the target concentration distribution diagram, including: for each mechanical parameter, obtaining the concentration of the target concentration distribution diagram under the target operating environment, and judging whether the concentration is greater than or equal to a preset concentration; when the concentration is greater than or equal to the preset concentration, obtaining the first initial value that appears most frequently in the target concentration distribution diagram, and determining the first initial value that appears most frequently as the target parameter value of the mechanical parameter; when the concentration is less than the preset concentration, obtaining the first initial value that appears most frequently in the target concentration distribution diagram, and obtaining the value interval of the first initial value with a number of occurrences greater than 0 from the target concentration distribution diagram to obtain the target value interval; adjusting the first initial value according to the target value interval to obtain the target parameter value of the mechanical parameter.

[0095] Specifically, after obtaining the target concentration distribution map, the concentration of each target concentration distribution map can be obtained, and it can be determined whether it is greater than the preset concentration, wherein the concentration can be calculated by the proportion of parameters that have no probability value (that is, the number of times is 0) in the total description. When the concentration is greater than or equal to the preset concentration, the first initial value that appears the most times in the target concentration distribution map can be directly obtained, and the first initial value that appears the most times can be determined as the target parameter value of the mechanical parameter.

[0096] Furthermore, when the concentration is less than the preset concentration, the first initial value that appears most frequently in the target concentration distribution map is obtained, and the value interval of the first initial value that appears more than 0 frequently is obtained from the target concentration distribution map to obtain the target value interval; the first initial value is adjusted according to the target value interval to obtain the target parameter value of the mechanical parameter, which can be calculated by Formula 8:

[0097] (8)

[0098] in, is the first initial value of the mechanical parameters before adjustment, is the first initial value of the adjusted mechanical parameter, a and b are the upper and lower limits of the target value range of the parameter, respectively. sh For example, from Figure 8 It can be seen that the parameter D sh The target value range can be [-20%, -5%], then a=-20%, b=-5%, thereby completing the adjustment of the parameter values ​​of the mechanical parameters and improving the accuracy of the parameters.

[0099] It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and that, although a logical order is shown in the flowcharts, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0100] The embodiment of the present application also provides a device for determining the mechanical parameters of a fan system simulation model. It should be noted that the device for determining the mechanical parameters of a fan system simulation model in the embodiment of the present application can be used to execute the method for determining the mechanical parameters of a fan system simulation model provided in the embodiment of the present application. The device for determining the mechanical parameters of a fan system simulation model provided in the embodiment of the present application is introduced below.

[0101] Fig. 9 Schematic diagram of a device for determining mechanical parameters of a fan system simulation model according to an embodiment of the present application. Fig. 9 As shown, the device includes: a generating unit 91, an adding unit 92, a first determining unit 93, and a second determining unit 94.

[0102] A generation unit 91 is used to establish an initial simulation model of the drive shaft of the fan system, and generate H groups of first initial values ​​and P groups of second initial values, wherein the simulation model includes M mechanical parameters and N non-mechanical parameters, each group of first initial values ​​includes a first initial value for each mechanical parameter, and each group of second initial values ​​includes a second initial value for each non-mechanical parameter, and M, N, H, and P are positive integers.

[0103] An adding unit 92 is used to obtain the operating environment in which the initial simulation model needs to be simulated, obtain Q operating environments, and generate a simulation model under each operating environment to obtain Q first simulation models, and add each group of second initial values ​​to the first simulation model under each operating environment in turn to obtain Q groups of second simulation models, wherein each group of second simulation models includes P second simulation models, each second simulation model includes a group of second initial values, and Q is a positive integer.

[0104] The first determination unit 93 is used to substitute the H groups of first initial values ​​into each second simulation model in turn to obtain T groups of simulation results, and determine the concentration distribution diagram of each mechanical parameter in each operating environment according to the accuracy of each group of simulation results to obtain K concentration distribution diagrams, and determine the target operating environment corresponding to each mechanical parameter according to the K concentration distribution diagrams, wherein T is the product of P and Q, K is the product of M and Q, each group of simulation results includes H simulation results, and P, K, and T are positive integers.

[0105] The second determination unit 94 is configured to obtain a target concentration distribution diagram under a target operating environment corresponding to each mechanical parameter, and determine a target parameter value of each mechanical parameter according to the target concentration distribution diagram.

[0106] The device for determining the mechanical parameters of the simulation model of the fan system provided in the embodiment of the present application establishes an initial simulation model of the transmission shaft of the fan system through a generating unit 91, and generates H groups of first initial values ​​and P groups of second initial values, wherein the simulation model includes M mechanical parameters and N non-mechanical parameters, each group of first initial values ​​includes a first initial value for each mechanical parameter, each group of second initial values ​​includes a second initial value for each non-mechanical parameter, and M, N, H, and P are positive integers; an adding unit 92 obtains the operating environment that the initial simulation model needs to simulate, obtains Q operating environments, and generates a simulation model under each operating environment to obtain Q first simulation models, and adds each group of second initial values ​​to the first simulation model under each operating environment in turn to obtain Q groups of second simulation models, wherein each group of second simulation models includes P second simulation models, each second simulation model includes a group of second initial values, and Q is a positive integer; a first determining unit 93 substitutes the H groups of first initial values ​​into each second simulation model in turn, to obtain T groups of simulation results are obtained, and a concentration distribution diagram of each mechanical parameter in each operating environment is determined according to the accuracy of each group of simulation results, K concentration distribution diagrams are obtained, and a target operating environment corresponding to each mechanical parameter is determined according to the K concentration distribution diagrams, wherein T is the product of P and Q, K is the product of M and Q, each group of simulation results includes H simulation results, and P, K, and T are positive integers; the second determination unit 94 obtains a target concentration distribution diagram in the target operating environment corresponding to each mechanical parameter, and determines a target parameter value of each mechanical parameter according to the target concentration distribution diagram. The problem in the related art that mechanical parameters in a wind turbine model are set by preset values, resulting in low accuracy of simulation results of the wind turbine model, is solved. An initial simulation model of a transmission shaft of a wind turbine system is established, and initial values ​​of various parameters are set. Simulations are performed under different operating environments according to different permutations and combinations of initial values ​​of different parameters to obtain concentration distribution diagrams of different mechanical parameter values. Then, the operating environment in which the concentration of each mechanical parameter value is the highest is determined based on the concentration distribution diagram, and the parameter with the highest accuracy is obtained under the operating environment as the numerical value of the mechanical parameter, thereby achieving the effect of improving the accuracy of obtaining the numerical values ​​of the mechanical parameters in the simulation model.

[0107] Optionally, in the device for determining the mechanical parameters of the fan system simulation model provided in the embodiment of the present application, the generation unit 91 includes: a first acquisition module, used to acquire the mechanical parameters in the initial simulation model to obtain M mechanical parameters, and acquire the preset true value of each mechanical parameter to obtain M preset true values; a setting module, used to set the value range of each mechanical parameter according to the preset true value of each mechanical parameter, and set a fixed step size; a first adjustment module, used to adjust the preset true value of each mechanical parameter according to the fixed step size to obtain H first initial values ​​of each mechanical parameter, wherein the H first initial values ​​include the preset true value; a grouping module, used to randomly group the H first initial values ​​of the M mechanical parameters to obtain H groups of first initial values, wherein each group of first initial values ​​contains M mechanical parameters, and each group of first initial values ​​includes a first initial value of each mechanical parameter.

[0108] Optionally, in the device for determining the mechanical parameters of the fan system simulation model provided in the embodiment of the present application, the first determination unit 93 includes: a second acquisition module, used to obtain the second simulation model corresponding to each group of second initial values ​​under each operating environment, and obtain T second simulation models; an adding module, used to add each group of first initial values ​​in H groups of first initial values ​​to the second simulation model in turn for each second simulation model, and obtain H third simulation models; a first determination module, used to run the H third simulation models, obtain the generator rotor speed simulation curve output by each third simulation model, and use the H simulation curves to determine a simulation result, and obtain H simulation results; a second determination module, used to determine the H simulation results as a group of simulation results, and obtain a group of simulation results of the second simulation model.

[0109] Optionally, in the device for determining the mechanical parameters of the fan system simulation model provided in the embodiment of the present application, the first determination unit 93 includes: a third acquisition module, which is used to obtain the measurement curve of the generator rotor speed for any group of target simulation results in the P groups of simulation results under each operating environment, and set multiple sampling points; a fourth acquisition module, which is used to obtain the difference between the speed values ​​of each target simulation curve and the measurement curve at each sampling point in any group of target simulation results, obtain H groups of speed differences, and calculate the error value between the measurement curve and the simulation curve according to the multiple speed differences in each group of speed differences, to obtain H error values. ; A fifth acquisition module is used to obtain the minimum error value among H error values, and determine a group of first initial values ​​corresponding to the minimum error value to obtain a target initial value; a sixth acquisition module is used to obtain a group of target initial values ​​corresponding to each simulation result, obtain P groups of target initial values, and extract the first initial value corresponding to each mechanical parameter in the P groups of target initial values ​​to obtain M first initial value sets; a seventh acquisition module is used to obtain the number of occurrences of each first initial value in each first initial value set, and generate a distribution diagram of each first initial value set according to the number of occurrences to obtain a concentration distribution diagram of each mechanical parameter under each operating environment.

[0110] Optionally, in the device for determining the mechanical parameters of the fan system simulation model provided in the embodiment of the present application, the fourth acquisition module includes: a first calculation submodule, used to calculate the ratio between each speed difference value and the corresponding measurement value in each group of speed difference values, to obtain multiple ratios; a second calculation submodule, used to calculate the average value of the multiple ratios, and determine the average value as the error value of each group of speed difference values, to obtain H error values.

[0111] Optionally, in the device for determining the mechanical parameters of the fan system simulation model provided in the embodiment of the present application, the first determination unit 93 includes: an eighth acquisition module, used to obtain the concentration of the concentration distribution diagram of each mechanical parameter in each operating environment, and obtain Q concentrations; a third determination module, used to determine the operating environment to which the concentration distribution diagram with the largest concentration belongs as the target operating environment corresponding to the mechanical parameter.

[0112] Optionally, in the device for determining the mechanical parameters of the fan system simulation model provided in the embodiment of the present application, the second determination unit 94 includes: a judgment module, used to obtain the concentration of the target concentration distribution diagram under the target operating environment for each mechanical parameter, and determine whether the concentration is greater than or equal to the preset concentration; a fourth determination module, used to obtain the first initial value that appears most frequently in the target concentration distribution diagram when the concentration is greater than or equal to the preset concentration, and determine the first initial value that appears most frequently as the target parameter value of the mechanical parameter; a ninth acquisition module, used to obtain the first initial value that appears most frequently in the target concentration distribution diagram when the concentration is less than the preset concentration, and obtain the value interval of the first initial value whose occurrence frequency is greater than 0 from the target concentration distribution diagram to obtain the target value interval; a second adjustment module, used to adjust the first initial value according to the target value interval to obtain the target parameter value of the mechanical parameter.

[0113] The device for determining the mechanical parameters of the above-mentioned fan system simulation model includes a processor and a memory. The above-mentioned generation unit 91, addition unit 92, first determination unit 93, second determination unit 94, etc. are all stored in the memory as program units, and the processor executes the above-mentioned program units stored in the memory to realize corresponding functions.

[0114] The processor includes a kernel, and the kernel retrieves the corresponding program unit from the memory. One or more kernels can be set, and the problem of low accuracy of simulation results of the wind turbine model caused by setting mechanical parameters in the wind turbine model by preset values ​​in the related art is solved by adjusting kernel parameters.

[0115] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM, and the memory includes at least one memory chip.

[0116] An embodiment of the present invention provides a computer-readable storage medium on which a program is stored. When the program is executed by a processor, the method for determining the mechanical parameters of the fan system simulation model is implemented.

[0117] An embodiment of the present invention provides a processor, which is used to run a program, wherein the program executes a method for determining mechanical parameters of the fan system simulation model when the program is running.

[0118] Fig.10 is a schematic diagram of an electronic device provided according to an embodiment of the present application, such as Fig.10As shown, an embodiment of the present invention provides an electronic device, the electronic device 100 includes a processor, a memory, and a program stored in the memory and executable on the processor, and the processor implements the steps of the method for determining the mechanical parameters of the fan system simulation model when executing the program. The device in this article can be a server, a PC, a PAD, a mobile phone, etc.

[0119] The present application also provides a computer program product, which, when executed on a data processing device, is suitable for executing a program that initializes the steps of the method for determining mechanical parameters of the above-mentioned fan system simulation model.

[0120] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0121] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0122] These computer program instructions may also be stored in a computer readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0123] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0124] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0125] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0126] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0127] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0128] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included within the scope of the claims of the present application.

Claims

1. A method for determining mechanical parameters of a fan system simulation model, characterized in that: include: Establishing an initial simulation model of the drive shaft of the fan system, and generating H groups of first initial values ​​and P groups of second initial values, wherein the simulation model includes M mechanical parameters and N non-mechanical parameters, each group of first initial values ​​includes a first initial value of each mechanical parameter, each group of second initial values ​​includes a second initial value of each non-mechanical parameter, and M, N, H, and P are positive integers; Obtain the operating environment that the initial simulation model needs to simulate, obtain Q operating environments, and generate a simulation model under each operating environment to obtain Q first simulation models, and add each group of second initial values ​​to the first simulation model under each operating environment in turn to obtain Q groups of second simulation models, wherein each group of second simulation models includes P second simulation models, each second simulation model includes a group of second initial values, and Q is a positive integer; Substituting the H groups of first initial values ​​into each second simulation model in turn to obtain T groups of simulation results, and determining a concentration distribution diagram of each mechanical parameter in each operating environment according to the accuracy of each group of simulation results to obtain K concentration distribution diagrams, and determining a target operating environment corresponding to each mechanical parameter according to the K concentration distribution diagrams, wherein T is the product of P and Q, K is the product of M and Q, each group of simulation results includes H simulation results, and P, K, and T are positive integers; A target concentration distribution diagram under a target operating environment corresponding to each mechanical parameter is obtained, and a target parameter value of each mechanical parameter is determined according to the target concentration distribution diagram.

2. The method according to claim 1, characterized in that Generating the first initial value of group H includes: Acquire mechanical parameters in the initial simulation model to obtain M mechanical parameters, and acquire a preset true value of each mechanical parameter to obtain M preset true values; The value range of each mechanical parameter is set according to the preset true value of each mechanical parameter, and a fixed step size is set; Adjusting the preset true value of each mechanical parameter according to the fixed step length to obtain H first initial values ​​of each mechanical parameter, wherein the H first initial values ​​include the preset true value; The H first initial values ​​of the M mechanical parameters are randomly grouped to obtain the H groups of first initial values, wherein each group of first initial values ​​includes M mechanical parameters, and each group of first initial values ​​includes a first initial value of each mechanical parameter.

3. The method according to claim 1, characterized in that Substituting the H groups of first initial values ​​into each second simulation model in turn, the T groups of simulation results obtained include: Obtain a second simulation model corresponding to each group of second initial values ​​in each operating environment to obtain T second simulation models; For each second simulation model, sequentially add each group of first initial values ​​in the H groups of first initial values ​​to the second simulation model to obtain H third simulation models; Running the H third simulation models to obtain a generator rotor speed simulation curve output by each third simulation model, and using the H simulation curves to determine a simulation result to obtain H simulation results; The H simulation results are determined as a group of simulation results to obtain a group of simulation results of the second simulation model.

4. The method according to claim 3, characterized in that According to the accuracy of each group of simulation results, the concentration distribution diagram of each mechanical parameter in each operating environment is determined, and K concentration distribution diagrams are obtained, including: For any set of target simulation results in the P sets of simulation results under each operating environment, a measurement curve of the generator rotor speed is obtained, and a plurality of sampling points are set; Obtaining the difference between the speed value of each target simulation curve and the measured curve at each sampling point in any one group of target simulation results to obtain H groups of speed difference values, and calculating the error value between the measured curve and the simulation curve according to multiple speed difference values ​​in each group of speed difference values ​​to obtain H error values; Obtaining a minimum error value among the H error values, and determining a set of first initial values ​​corresponding to the minimum error value, to obtain a target initial value; Obtaining a set of target initial values ​​corresponding to each simulation result to obtain P sets of target initial values, and extracting the first initial value corresponding to each mechanical parameter in the P sets of target initial values ​​to obtain M sets of first initial values; The number of occurrences of each first initial value in each first initial value set is obtained, and a distribution diagram of each first initial value set is generated according to the number of occurrences to obtain a concentration distribution diagram of each mechanical parameter in each operating environment.

5. The method according to claim 4, characterized in that The error value between the measurement curve and the simulation curve is calculated according to the multiple speed difference values ​​in each group of speed difference values, and the H error values ​​obtained include: Calculating the ratio between each speed difference value and the corresponding measured value in each group of speed difference values ​​to obtain multiple ratios; An average value of the multiple ratios is calculated, and the average value is determined as the error value of each group of rotation speed difference values ​​to obtain the H error values.

6. The method according to claim 1, characterized in that Determining the target operating environment corresponding to each mechanical parameter according to the K concentration distribution diagrams includes: Obtain the concentration of the concentration distribution diagram of each mechanical parameter under each operating environment to obtain Q concentrations; The operating environment to which the concentration distribution diagram with the largest concentration belongs is determined as the target operating environment corresponding to the mechanical parameter.

7. The method according to claim 1, characterized in that Obtaining a target concentration distribution diagram under a target operating environment corresponding to each mechanical parameter, and determining a target parameter value of each mechanical parameter according to the target concentration distribution diagram includes: For each mechanical parameter, obtaining a concentration of a target concentration distribution diagram under the target operating environment, and determining whether the concentration is greater than or equal to a preset concentration; When the concentration is greater than or equal to the preset concentration, obtaining a first initial value that appears most frequently in the target concentration distribution graph, and determining the first initial value that appears most frequently as a target parameter value of the mechanical parameter; In the case where the concentration is less than the preset concentration, obtaining the first initial value that appears most frequently in the target concentration distribution map, and obtaining a value interval of the first initial value whose number of occurrences is greater than 0 from the target concentration distribution map to obtain a target value interval; The first initial value is adjusted according to the target value interval to obtain a target parameter value of the mechanical parameter.

8. A device for determining mechanical parameters of a fan system simulation model, characterized in that: include: A generating unit, used to establish an initial simulation model of a transmission shaft of a fan system, and generate H groups of first initial values ​​and P groups of second initial values, wherein the simulation model includes M mechanical parameters and N non-mechanical parameters, each group of first initial values ​​includes a first initial value of each mechanical parameter, each group of second initial values ​​includes a second initial value of each non-mechanical parameter, and M, N, H, and P are positive integers; An adding unit is used to obtain the operating environment that the initial simulation model needs to simulate, obtain Q operating environments, and generate a simulation model under each operating environment to obtain Q first simulation models, and sequentially add each group of second initial values ​​to the first simulation model under each operating environment to obtain Q groups of second simulation models, wherein each group of second simulation models includes P second simulation models, each second simulation model includes a group of second initial values, and Q is a positive integer; A first determination unit is used to sequentially substitute the H groups of first initial values ​​into each second simulation model to obtain T groups of simulation results, and determine a concentration distribution diagram of each mechanical parameter in each operating environment according to the accuracy of each group of simulation results to obtain K concentration distribution diagrams, and determine a target operating environment corresponding to each mechanical parameter according to the K concentration distribution diagrams, wherein T is the product of P and Q, K is the product of M and Q, each group of simulation results includes H simulation results, and P, K, and T are positive integers; The second determination unit is used to obtain a target concentration distribution diagram under a target operating environment corresponding to each mechanical parameter, and determine a target parameter value of each mechanical parameter according to the target concentration distribution diagram.

9. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the method for determining the mechanical parameters of the fan system simulation model according to any one of claims 1 to 7 is implemented.

10. An electronic device, characterized in that: It includes one or more processors and a memory, wherein the memory is used to store one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the method for determining the mechanical parameters of the fan system simulation model as described in any one of claims 1 to 7.

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