Tidal unit control method, device, electronic equipment, storage medium and unit

Abstract

The present application discloses a method, device, electronic device, storage medium and unit for regulating a tidal unit. A plurality of control parameters of the unit at a predetermined time are obtained, wherein each control parameter group includes a rotational speed and a unit flow rate at a predetermined time; each control parameter group is input into a prediction model respectively, and the unit efficiency corresponding to each control parameter group is determined respectively through the target correspondence between the control parameters pre-constructed in the prediction model and the unit efficiency; a group of control parameters corresponding to the highest unit efficiency is determined as the target control parameters; and the operation of the unit at a predetermined time is regulated according to the rotational speed in the target control parameters. The present application can realize the use of the candidate control parameters corresponding to the highest efficiency at every moment to control the rotational speed of the tidal unit, thereby avoiding the problem of poor stability of the efficiency and power generation of the tidal unit and low power generation efficiency caused by a constant rotational speed.

Description

Technical Field

[0001] The present application belongs to the technical field of tidal energy development, and in particular relates to a control method, device, electronic equipment, storage medium and unit of a tidal unit. Background Art

[0002] In the process of generating electricity using a tidal turbine, a constant rotation speed is usually set for the tidal turbine.

[0003] However, in the operating environment of tidal turbines, due to the fluctuations of tidal water levels and reservoir water levels, the operating head will change frequently and drastically. If the tidal turbines use a constant speed to operate under different operating environments, the efficiency of the tidal turbines will not be the same, making it impossible for the tidal turbines to maintain the highest efficiency in real time, resulting in low efficiency of the tidal turbines and low power generation. Summary of the Invention

[0004] The embodiments of the present application provide a control method, device, electronic device, storage medium and unit for a tidal generator set, which can control the rotation speed of the tidal generator set using the target control parameters corresponding to the highest efficiency at every time.

[0005] In a first aspect, an embodiment of the present application provides a method for controlling a tidal generator set, the method comprising:

[0006] Acquire multiple sets of control parameters of the unit at a predetermined time, wherein each set of control parameters includes a rotational speed and a flow rate of the unit at a predetermined time;

[0007] Each set of control parameters is input into the prediction model respectively, and the unit efficiency corresponding to each set of control parameters is determined respectively through the target correspondence between the control parameters and the unit efficiency pre-built in the prediction model;

[0008] Determine a set of control parameters corresponding to the highest unit efficiency as target control parameters;

[0009] The speed of the unit is regulated to run at the scheduled time according to the target control parameters.

[0010] The acquisition of multiple control parameters of the unit at a predetermined time includes:

[0011] Taking the predetermined speed as the center, multiple speeds are selected within the speed optimization range;

[0012] The flow rate of the unit at the predetermined time is obtained, and the flow rate of the unit is combined with the speed to obtain multiple groups of control parameters of the unit at the predetermined time.

[0013] Furthermore, before inputting each set of control parameters into the prediction model, the method further includes:

[0014] Obtain multiple sets of historical control parameters at different speeds under the same unit flow rate, as well as the corresponding survey unit efficiency in each set of historical control parameters, where each set of historical control parameters includes historical unit flow rate and speed;

[0015] Input each set of historical control parameters into the initial prediction model respectively;

[0016] By comparing the correspondence between different rotational speeds and the surveyed unit efficiency under the same historical unit flow rate, the correspondence between the historical control parameters and the corresponding surveyed unit efficiency is associated in the initial prediction model to obtain a first prediction model containing the initial correspondence between the control parameters and the unit efficiency;

[0017] Using the initial correspondence between the control parameters and the corresponding unit efficiencies in the first prediction model, each group of historical control parameters is predicted to obtain the corresponding predicted unit efficiencies;

[0018] When the difference between the highest predicted unit efficiency and the highest surveyed unit efficiency is less than or equal to a preset convergence threshold, a second prediction model containing a target correspondence relationship between control parameters and unit efficiency is obtained;

[0019] Using a simulation system to simulate the unit according to historical control parameters corresponding to the highest predicted unit efficiency, to obtain the corresponding simulation efficiency;

[0020] Determine whether the simulation efficiency is greater than or equal to the corresponding highest survey unit efficiency;

[0021] When the simulation efficiency is greater than or equal to the corresponding highest survey unit efficiency, the second prediction model containing the target corresponding relationship between the control parameters and the unit efficiency is determined as the prediction model.

[0022] Furthermore, after predicting each set of historical control parameters using the initial correspondence between the control parameters and the corresponding unit efficiencies in the first prediction model to obtain the corresponding predicted unit efficiencies, the method further includes:

[0023] When the difference between the highest predicted unit efficiency and the highest surveyed unit efficiency is greater than a preset convergence threshold, adjusting the model parameters of the first prediction model containing the initial corresponding relationship;

[0024] The initial correspondence between the control parameters and the corresponding unit efficiencies in the adjusted first prediction model is used to predict each group of historical control parameters until the difference between the highest predicted unit efficiency and the highest surveyed unit efficiency is less than or equal to the convergence threshold, thereby obtaining a second prediction model containing the target correspondence between the control parameters and the unit efficiencies.

[0025] Furthermore, after determining whether the simulation efficiency is greater than or equal to the corresponding highest survey unit efficiency, the method further includes:

[0026] When the simulation efficiency is less than the corresponding highest survey unit efficiency, adjusting the model parameters of the second prediction model containing the target corresponding relationship between the control parameters and the unit efficiency;

[0027] The target correspondence between the control parameters and the unit efficiency in the adjusted second prediction model is used to predict the predicted unit efficiency corresponding to each group of historical control parameters, and the historical control parameter group corresponding to the highest predicted unit efficiency is simulated and executed until the obtained simulation efficiency is greater than or equal to the corresponding highest survey unit efficiency. The second prediction model containing the target correspondence between the control parameters and the survey unit efficiency is determined to be the prediction model.

[0028] The multiple groups of historical control parameters include multiple groups of first historical control parameters during reverse operation and multiple groups of second historical control parameters during forward operation.

[0029] Furthermore, when the difference between the highest predicted unit efficiency and the highest surveyed unit efficiency is less than or equal to a preset convergence threshold, a second prediction model containing a target correspondence between control parameters and unit efficiency is obtained, including:

[0030] If the difference between the highest predicted unit efficiency among the predicted unit efficiencies corresponding to the first historical control parameter and the corresponding highest surveyed unit efficiency is less than or equal to the convergence threshold, determining whether the difference between the highest predicted unit efficiency and the highest surveyed unit efficiency among the predicted unit efficiencies corresponding to the second historical control parameter is less than or equal to the convergence threshold;

[0031] When the difference between the highest predicted unit efficiency among the predicted unit efficiencies corresponding to the second historical control parameter and the corresponding highest survey unit efficiency is less than or equal to the convergence threshold, a second prediction model including a target correspondence relationship between the control parameter and the survey unit efficiency is obtained;

[0032] Wherein, when the simulation efficiency is greater than or equal to the corresponding highest survey unit efficiency, determining the second prediction model containing the target corresponding relationship between the control parameter and the unit efficiency as the prediction model includes:

[0033] If the simulation efficiency corresponding to the first historical control parameter is greater than or equal to the corresponding highest survey unit efficiency, determining whether the simulation efficiency corresponding to the second historical control parameter is greater than or equal to the corresponding highest survey unit efficiency;

[0034] When the simulation efficiency corresponding to the second historical control parameter is greater than or equal to the corresponding highest survey unit efficiency, the second prediction model containing the target corresponding relationship between the control parameter and the unit efficiency is determined as the prediction model.

[0035] In a second aspect, an embodiment of the present application provides a control device for a tidal generator set, the device comprising:

[0036] An acquisition module, configured to acquire multiple sets of control parameters of the unit at a predetermined time, wherein each set of control parameters includes a rotational speed and a flow rate of the unit at a predetermined time;

[0037] The unit efficiency determination module is used to input each set of control parameters into the prediction model, and determine the unit efficiency corresponding to each set of control parameters based on the target correspondence between the control parameters and the unit efficiency pre-established in the prediction model;

[0038] a control parameter determination module, configured to determine a set of control parameters corresponding to the highest unit efficiency as target control parameters;

[0039] The control module is used to control the operation of the unit at a predetermined time according to the speed in the target control parameter.

[0040] In a third aspect, an embodiment of the present application provides an electronic device, the device comprising:

[0041] a processor and a memory storing computer program instructions;

[0042] When the processor executes the computer program instructions, it implements the control method of the tidal turbine as described in any of the above items.

[0043] In a fourth aspect, an embodiment of the present application provides a computer storage medium, on which computer program instructions are stored. When the computer program instructions are executed by a processor, a control method for a tidal generator set as described in any of the above items is implemented.

[0044] In a fifth aspect, an embodiment of the present application provides a computer program product in which, when instructions in the computer program product are executed by a processor of an electronic device, the electronic device executes a method for controlling a tidal generator set as described in any of the preceding items.

[0045] In a sixth aspect, an embodiment of the present application further provides a tidal generator set, comprising an electronic device, which executes any one of the above methods for controlling the tidal generator set.

[0046] The control method, device, electronic device, storage medium and unit of the tidal unit of the embodiment of the present application can predict the unit efficiency of multiple groups of control parameters by optimizing the target correspondence between the control parameters and the unit efficiency constructed in the model when controlling the operation of the tidal unit at each time, so as to select the target control parameters corresponding to the highest unit efficiency, and then realize the use of the target control parameters corresponding to the highest unit efficiency to control the speed of the tidal unit at each time, avoiding the problems of poor stability of tidal unit efficiency and power generation and low power generation efficiency caused by constant speed. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0048] Figure 1 This is a flow chart of a method for controlling a tidal turbine provided in an embodiment of the present application;

[0049] Figure 2 is a schematic diagram of a reservoir capacity-water level curve provided in an embodiment of the present application;

[0050] Figure 3 is a schematic diagram of an operating water level curve provided in an embodiment of the present application;

[0051] Figure 4 is a schematic diagram of a characteristic curve of a first unit provided in an embodiment of the present application;

[0052] Figure 5 is a schematic diagram of a second unit characteristic curve provided in an embodiment of the present application;

[0053] Figure 6 Schematic diagram of the process of optimizing and verifying the prediction model provided in the embodiment of the present application;

[0054] Figure 7 This is a schematic structural diagram of a control device for a tidal generator set provided in an embodiment of the present application;

[0055] Figure 8 This is a structural diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0056] The features and exemplary embodiments of various aspects of the present application will be described in detail below. In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain the present application, rather than to limit the present application. For those skilled in the art, the present application can be implemented without the need for some of these specific details. The following description of the embodiments is merely to provide a better understanding of the present application by illustrating the examples of the present application.

[0057] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article, or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or device. In the absence of further limitations, the elements defined by the phrase "comprising..." do not exclude the presence of other identical elements in the process, method, article, or device comprising the elements.

[0058] As described in the background technology section, the control technology of related tidal turbines is still difficult to meet the needs of actual work.

[0059] In the process of generating electricity by using a tidal turbine, a constant rotation speed is usually set for the tidal turbine, and the tidal turbine operates at the constant rotation speed.

[0060] However, in the operating environment of the tidal unit, due to the fluctuations of the tidal water level and the reservoir water level, the operating head and unit flow of the tidal unit will change frequently and drastically. If the tidal unit is operated at a constant speed under different operating heads and unit flow environments, the unit efficiency of the tidal unit will not be the same, making it impossible for the tidal unit to maintain the highest unit efficiency in real time, resulting in low unit efficiency and low power generation.

[0061] In order to solve the problems of the prior art, the embodiments of the present application provide a control method, device, electronic equipment, storage medium and unit of a tidal unit.

[0062] The following is a detailed description of the control method of the tidal generator set provided in the embodiment of the present application with reference to the accompanying drawings.

[0063] Figure 1 A flow chart of a method for controlling a tidal generator set provided in one embodiment of the present application is shown.

[0064] refer to Figure 1 A method for controlling a tidal generator set according to an embodiment of the present application includes the following steps 101-104.

[0065] S101. Acquire multiple sets of control parameters of a unit at a predetermined time, wherein each set of control parameters includes a rotational speed and a flow rate of the unit at the predetermined time.

[0066] In this embodiment, for a tidal turbine that will operate at a predetermined time, in order to determine the target control parameters of the tidal turbine at the predetermined time, multiple sets of control parameters may be obtained, and then the target control parameters may be selected from the multiple sets of control parameters through a prediction model.

[0067] Each of the multiple groups of control parameters may specifically include a selected rotational speed and a unit flow rate within a predetermined time, and the rotational speeds of the control parameters of each group are different.

[0068] In this step, when obtaining the unit flow rate at the predetermined time, the unit flow rate at the predetermined time can be obtained based on the operating water level at the predetermined time.

[0069] The operating water level at the predetermined time is the difference between the tidal water level and the reservoir water level at the predetermined time.

[0070] Among them, the tidal water level and the reservoir water level are the water levels on both sides of the tidal unit respectively. One side of the tidal unit is a water area with tides, such as seawater, and the water level on this side is the tidal water level of the water area; the other side is a reservoir water area, and the water level on this side is the reservoir water level.

[0071] In a specific example, when obtaining the tidal water level and reservoir water level at a predetermined time, the periodic change data of the tidal water level in history can be obtained, and a tidal water level change curve covering the predetermined time can be determined based on this to represent the change of the tidal water level over time; the periodic change data of the reservoir water level in history can be obtained, and a reservoir water level change curve covering the predetermined time can be determined based on this to represent the change of the reservoir water level over time.

[0072] In another specific example, when obtaining the reservoir water level at a predetermined time, the reservoir water level at the predetermined time may be obtained by querying a preset reservoir capacity-water level curve based on the predetermined reservoir capacity at the predetermined time.

[0073] The preset operating storage capacity-water level curve may specifically represent the numerical relationship between the storage capacity of the reservoir and the water level of the reservoir.

[0074] Figure 2 A specific example of a reservoir capacity-water level curve is shown, where: Figure 2The horizontal axis is the reservoir water level and the vertical axis is the reservoir capacity. Based on this, the reservoir water level can be determined by querying the reservoir capacity-water level curve based on the reservoir capacity at a predetermined time.

[0075] Based on this, when determining the operating water level at the scheduled time, the operating water level and tidal water level at any time including the scheduled time can be determined through the tidal water level change curve and the reservoir water level change curve, and the difference between the tidal water level and the operating water level at the scheduled time can be determined as the operating water level at the scheduled time.

[0076] In one example, when determining the operating water level at a predetermined time, an operating water level curve may be determined by using a tidal water level variation curve and a reservoir water level variation curve, and the operating water level at the predetermined time may be determined by using the operating water level curve.

[0077] The operating water level curve is specifically used to represent the operating water level at each time.

[0078] Figure 3 The figure shows a specific schematic diagram of the operating water level curve, where: Figure 3 The horizontal axis is time, and the vertical axis is the operating water level. The curve represents the operating water level changing with time. H1, H2, H3 and H4 represent the operating water levels at four different times respectively.

[0079] Accordingly, based on the scheduled time, the operating water level corresponding to the scheduled time can be determined by querying the operating water level curve.

[0080] In this embodiment, when determining the unit flow rate at a predetermined time, it can be obtained by querying a preset operating water level-unit flow rate curve based on the operating water level at the predetermined time.

[0081] The preset operating water level-unit flow curve may specifically represent the numerical relationship between different operating water levels and unit flow of the tidal unit at various times.

[0082] In this step, the speed selected from each set of control parameters may be selected from a predetermined speed optimization range, or may be set based on historical experience.

[0083] In some examples, each set of control parameters may include, in addition to the selected rotational speed and unit flow at a predetermined time, for example, operating water level, guide vane angle, and blade angle, among which the operating water level, guide vane angle, and blade angle at a predetermined time can be regarded as operating parameters that characterize the operating environment of the tidal unit, which can affect the unit efficiency of the tidal unit, but are not parameters to be adjusted in this embodiment.

[0084] S102 , inputting each set of control parameters into the prediction model respectively, and determining the unit efficiency corresponding to each set of control parameters respectively through the target correspondence between the control parameters and the unit efficiency pre-constructed in the prediction model.

[0085] In this embodiment, in order to enable the tidal cycle to operate at the highest unit efficiency at the predetermined time, the unit efficiency of each group of control parameters can be predicted by a preset prediction model, so that the target control parameters can be selected from multiple groups of control parameters according to the unit efficiency corresponding to each group of control parameters, so that the tidal unit controlled by the target control parameters has the highest unit efficiency when running at the predetermined time.

[0086] In this step, in order to predict the unit efficiency corresponding to each set of control parameters, based on the multiple sets of control parameters obtained in the previous steps, each set of control parameters can be input into the prediction model to predict the unit efficiency corresponding to each set of control parameters.

[0087] Among them, in the prediction model for predicting unit efficiency, a target correspondence between control parameters and unit efficiency is pre-constructed. The target correspondence can specifically point to the unit efficiency of the tidal unit when it operates with the set of control parameters at a predetermined time based on the control parameters.

[0088] Based on this, after each set of control parameters is input into the prediction model, the prediction model can predict the unit efficiency corresponding to each set of control parameters according to the pre-constructed target correspondence relationship.

[0089] S103: Determine a set of control parameters corresponding to the highest unit efficiency as target control parameters.

[0090] In this embodiment, when determining the target control parameters, based on the unit efficiencies predicted for each set of control parameters in the aforementioned steps, the unit efficiencies corresponding to each set of control parameters can be compared, and the highest unit efficiency can be selected from the unit efficiencies.

[0091] Furthermore, based on the selected highest unit efficiency, a corresponding set of control parameters can be used as target control parameters.

[0092] S104: regulating the operation of the unit within a predetermined time according to the rotational speed in the target control parameter.

[0093] In this embodiment, based on the target control parameters determined in the aforementioned steps, the operation of the tidal generator set can be controlled at a predetermined time using the rotational speed in the set of target control parameters, so that the efficiency of the tidal generator set operating at the predetermined time is higher than that of the generator set operating with other control parameters.

[0094] Based on this, in this embodiment, when the tidal unit is running at each time, the target correspondence between the control parameters and the unit efficiency constructed in the optimization model is used to predict the unit efficiency of multiple groups of control parameters, so that the target control parameters corresponding to the highest unit efficiency can be selected, and then the target control parameters corresponding to the highest efficiency are used to control the speed of the tidal unit at each time, so that the unit efficiency and power generation of the tidal unit are kept at the highest at each implementation, avoiding the problems of poor stability of the tidal unit efficiency and power generation and low power generation efficiency caused by constant speed.

[0095] In another embodiment of the present application, when obtaining each set of control parameters, a speed optimization range can be constructed with a predetermined speed as the center, so that multiple speeds can be selected from the speed optimization range, and the unit flow rate can be combined with each selected speed to obtain multiple sets of control parameters.

[0096] The predetermined rotation speed may be, for example, a unit rotation speed of the tidal turbine, or may be, for example, a constant rotation speed normally used by the tidal turbine.

[0097] In this embodiment, when constructing the rotation speed optimization range, the rotation speed floating range can be set with the predetermined rotation speed as the center.

[0098] For example, the predetermined rotation speed n can be taken as the center, and 20% can be used as the rotation speed floating range, so that the rotation speed optimization range is 80%n to 120%n.

[0099] Furthermore, when selecting multiple rotational speeds, multiple rotational speeds may be selected within the determined rotational speed optimization range according to a preset step size.

[0100] For example, with a step size of 1%, 40 speeds are selected from the speed optimization range of 80%n to 120%n.

[0101] Furthermore, when obtaining multiple sets of control parameters, the unit flow rate at a predetermined time may be combined with the 40 selected rotational speeds to obtain 40 sets of control parameters.

[0102] In some examples, when the control parameters include not only the selected speed and the unit flow at a predetermined time, but also the operating water level, the guide vane angle, and the blade angle, the unit flow, the operating water level, the guide vane angle, and the blade angle can be regarded as a group of operating parameters.

[0103] Furthermore, the group of operating parameters is combined with the selected multiple rotational speeds respectively, thereby obtaining multiple groups of control parameters.

[0104] Based on this, in this embodiment, based on the predetermined speed, when constructing a speed optimization range with it as the center to select multiple speeds, the selected multiple speeds can be made not to differ too much from the predetermined speed, thereby avoiding the inclusion of unreasonable speeds in the control parameters and avoiding the predicted unit efficiency being too low.

[0105] In another embodiment of the present application, before each set of control parameters is input into the prediction model for prediction, in order to obtain a prediction model containing a target correspondence between the control parameters and the unit efficiency, multiple sets of historical control parameters can be obtained, and the correspondence between the historical control parameters and the corresponding survey unit efficiency can be associated in a preset initial prediction model to obtain a first prediction model. By training with the model parameters in the first prediction model, a second prediction model containing a target correspondence between the control parameters and the unit efficiency is obtained, and the second prediction model is verified through simulation. After the second prediction model passes the verification, the second prediction model is determined as a prediction model containing a target correspondence between the control parameters and the unit efficiency.

[0106] Among them, each set of historical control parameters can specifically include unit flow and speed. The unit flow of each set of historical control parameters is the same but the speed is different, so that the correspondence between different speeds and the survey unit efficiency of the tidal unit during unit operation under the same operating environment can be accurately constructed.

[0107] In some examples, each set of historical control parameters may also include a guide vane angle and a blade angle, as well as an operating water level corresponding to the flow rate of the unit.

[0108] In this embodiment, when obtaining each set of historical control parameters, it is also necessary to simultaneously obtain the survey unit efficiency corresponding to each set of historical control parameters, so that the highest survey unit efficiency among the survey unit efficiencies can be used to optimize the first prediction model and the second prediction model.

[0109] When obtaining the survey unit efficiency corresponding to each set of historical control parameters, the corresponding survey unit efficiency can be determined by querying a preset unit characteristic curve based on the rotational speed and unit flow.

[0110] The unit characteristic curve specifically represents the numerical relationship between the speed, unit flow and survey unit efficiency. In some examples, the unit characteristic curve can also represent the numerical relationship between a set of operating parameters including the speed, unit flow, blade angle and guide vane angle and the speed.

[0111] When determining the efficiency of the survey unit using the unit characteristic curve, the corresponding unit characteristic curve can be selected according to the unit operating conditions corresponding to the historical control parameters.

[0112] Among them, the unit operating conditions can be divided into reverse operating conditions during the high tide cycle and forward operating conditions during the low tide cycle.

[0113] In a specific example, Figure 4 The figure shows the first unit characteristic curve corresponding to the reverse operation condition during the high tide cycle when the tidal unit is running at a predetermined speed. Figure 5 The figure shows a schematic diagram of the second unit characteristic curve corresponding to the tidal turbine operating at a predetermined speed under the forward operating condition during the ebb tide cycle.

[0114] Figure 4 The horizontal axis Q of the first unit characteristic curve 11 Indicates unit flow, vertical axis n 11 represents the unit speed, the dotted line 1 represents the unit speed corresponding to the predetermined speed, β represents the blade angle, and the red curve represents the equivalent survey unit efficiency, and represents the survey unit efficiency from 68% to 78% respectively.

[0115] Among them, there is a numerical correspondence between the rotational speed and the unit rotational speed, and there is a numerical correspondence between the unit flow rate and the unit flow rate. The equivalent survey unit efficiency is used to represent: when the tidal unit operates at a speed corresponding to the unit speed represented by the dotted line 1, the corresponding survey unit efficiency under different unit flow rates and blade angles.

[0116] The numerical correspondence between unit flow and unit flow is expressed as the following formula (1):

[0117]

[0118] Wherein, Q represents the flow rate of the unit, D represents the runner diameter of the bidirectional tidal unit, and H represents the operating head.

[0119] The numerical correspondence between the unit speed and the speed is expressed as the following formula (2):

[0120]

[0121] Where n represents the rotational speed.

[0122] Based on the above formula (1), there is a corresponding relationship between the unit flow rate and the unit flow rate, and based on the above formula (2), there is a corresponding relationship between the unit speed and the speed. Figure 4 In the above, based on the determined unit flow and blade angle, the corresponding survey unit efficiency can be determined for the selected speed.

[0123] Figure 5 The horizontal axis Q of the second unit characteristic curve 11 Indicates unit flow, vertical axis n 11represents the unit speed, the dotted line 3 represents the unit speed corresponding to the predetermined speed, β represents the blade angle, α represents the guide vane angle, and the red curve represents the equivalent survey unit efficiency, and represents the survey unit efficiency from 78% to 86% respectively.

[0124] The equivalent survey unit efficiency is used to represent: when the tidal turbine is operating at a speed corresponding to a unit speed represented by a dotted line 3, the survey unit efficiency corresponding to different unit flow rates, blade angles and guide vane angles.

[0125] Accordingly, from Figure 5 In the present invention, based on the determined unit flow, blade angle and guide vane angle, the corresponding survey unit efficiency can be determined for the selected speed.

[0126] Based on this, when using the unit characteristic curve to determine the survey unit efficiency, the unit characteristic curve corresponding to each speed can be used according to the selected multiple speeds, and the corresponding survey unit efficiency can be queried based on the determined flow rate, blade angle and guide vane angle.

[0127] In this embodiment, based on the multiple groups of historical control parameters and their corresponding survey unit efficiencies determined above, they can be output to a preset initial prediction model, so that the initial correspondence between the control parameters and the unit efficiency can be constructed using each group of historical control parameters and the corresponding survey unit efficiency.

[0128] Specifically, after each set of historical control parameters and their corresponding unit efficiencies are input into the initial prediction model, since the unit characteristic curve represents the correspondence between the historical control parameters and the survey unit efficiencies, the correspondence between the historical control parameters guaranteed by each unit characteristic curve and the corresponding survey unit efficiency can be associated in the initial prediction model based on the unit characteristic curve of each historical control parameter.

[0129] The corresponding relationship between the historical control parameter and the corresponding survey unit efficiency specifically indicates that: based on the determined historical control parameter, it is used as a data feature, and the data feature points to the corresponding survey unit efficiency.

[0130] Based on this, after constructing the correspondence between the historical control parameters and the corresponding survey unit efficiency, a first prediction model can be obtained. The first prediction model contains the initial correspondence between the control parameters and the unit efficiency. Since the model parameters of the first prediction model have not been optimized and verified, it is necessary to optimize and verify the first prediction model before determining the prediction model containing the target correspondence between the control parameters and the unit efficiency.

[0131] Furthermore, when optimizing the model parameters of the first prediction model, the initial correspondence between the control parameters and the unit efficiency constructed in the first prediction model can be used to predict the corresponding predicted unit efficiency for each set of input historical control parameters.

[0132] Furthermore, based on the predicted unit efficiencies, in order to train the model parameters of the first prediction model, the highest predicted unit efficiency can be determined from the predicted unit efficiencies, and the highest survey unit efficiency can be determined from the survey unit efficiencies corresponding to each set of historical control parameters.

[0133] Accordingly, when optimizing the model parameters of the first prediction model, the difference between the highest predicted unit efficiency and the highest surveyed unit efficiency can be calculated, and a convergence threshold can be set in advance. If the difference is greater than the convergence threshold, it is considered that the difference between the highest predicted unit efficiency and the highest surveyed unit efficiency is too large, and it is considered that due to the error in the model parameters, the difference between the speed corresponding to the highest predicted unit efficiency and the speed corresponding to the highest surveyed unit efficiency is too large. Therefore, it is necessary to adjust the model parameters of the first prediction model with an initial correspondence between the control parameters and the unit efficiency.

[0134] Furthermore, the first prediction model after parameter adjustment is used to predict each historical control parameter based on the initial correspondence between the control parameters and the unit efficiency, to obtain the corresponding predicted unit efficiency, and to calculate the difference between the highest predicted unit efficiency and the highest surveyed unit efficiency.

[0135] Furthermore, if the difference between the highest predicted unit efficiency and the highest surveyed unit efficiency is less than or equal to the convergence threshold, it is considered reasonable that the highest predicted unit efficiency is less than the difference between the highest surveyed unit efficiency and the highest predicted unit efficiency, and it is considered that since the error of the model parameters is within a reasonable range, the difference between the speed corresponding to the highest predicted unit efficiency and the speed corresponding to the highest surveyed unit efficiency is also within a reasonable range. Therefore, the model parameters of the first prediction model have been optimized, and the first prediction model at this time is determined as the second prediction model containing the target correspondence between the control parameters and the unit efficiency.

[0136] In this embodiment, based on the determined second prediction model containing the target correspondence between the control parameters and the unit efficiency, whether the second prediction model containing the target correspondence between the control parameters and the unit efficiency is valid can be verified through simulation, and when the second prediction model is valid, it is determined as the prediction model containing the target correspondence between the control parameters and the unit efficiency.

[0137] Specifically, when verifying the second prediction model, a group of historical control parameters corresponding to the highest predicted unit efficiency may be determined based on the highest predicted unit efficiency obtained when the second prediction model predicts each group of historical control parameters.

[0138] Furthermore, a preset simulation system can be used to simulate the operation of the tidal turbine at a predetermined time with a set of historical control parameters corresponding to the highest predicted turbine efficiency, so as to output the simulation efficiency corresponding to the set of historical control parameters at the predetermined time.

[0139] Based on this, the second prediction model can be verified using the simulation efficiency and the highest survey unit efficiency among the survey unit efficiencies corresponding to each set of historical control parameters.

[0140] Specifically, if the predicted unit efficiency predicted by the second prediction model for each group of historical control parameters is accurate, then the survey unit efficiency corresponding to the group of historical control parameters with the highest predicted unit efficiency should be the highest survey unit efficiency among the survey unit efficiencies of each group of historical control parameters.

[0141] Therefore, it can be judged whether the simulation efficiency is greater than or equal to the highest survey unit efficiency. If the simulation efficiency is greater than or equal to the highest survey unit efficiency, it is considered that the predicted unit efficiency predicted by the second prediction model is accurate, and the speed corresponding to the highest predicted unit efficiency determined based on this is accurate, and it can simulate a simulation efficiency that is not less than the highest survey unit efficiency at this speed. It is also considered that the second prediction model containing the target correspondence between the control parameters and the unit efficiency is verified to be valid, and it can be determined as a prediction model containing the target correspondence between the control parameters and the unit efficiency.

[0142] If the simulation efficiency is less than the highest survey unit efficiency, it is considered that the predicted unit efficiency predicted by the second prediction model is inaccurate, and it is considered that due to the error in the model parameters, the speed corresponding to the highest predicted unit efficiency predicted by the second prediction model is inaccurate, and it is difficult to simulate a simulation efficiency that is not less than the highest survey unit efficiency at this speed. Therefore, it is necessary to adjust the model parameters of the second prediction model with a target correspondence between the control parameters and the unit efficiency.

[0143] Furthermore, using the second prediction model after parameter adjustment, each historical control parameter is predicted based on the target correspondence between the control parameters and the unit efficiency to obtain the corresponding predicted unit efficiency, and a set of historical control parameters corresponding to the highest predicted unit efficiency is used for simulation to obtain the corresponding simulation efficiency, and it is determined whether the simulation efficiency is greater than or equal to the highest survey unit efficiency.

[0144] Based on this, in this embodiment, by associating the correspondence between each group of historical control data in the unit characteristic curve and the survey unit efficiency with the initial prediction model, an initial correspondence between the control parameters and the unit efficiency is achieved in the first prediction model. In order to optimize and verify the model parameters in the first prediction model with the initial correspondence so that the initial correspondence can become the target correspondence, in this embodiment, the parameters are adjusted based on the difference between the highest predicted unit efficiency predicted by the first prediction model and the highest survey unit efficiency, thereby obtaining a second prediction model containing the target correspondence, and the second prediction model is verified through simulation, so that the prediction model containing the target correspondence is obtained after verification.

[0145] Figure 4 The dashed line 2 in the figure shows the corresponding speed that can achieve the highest unit efficiency after simulation under different unit flow rates and blade angles during reverse operation; Figure 5 The dotted line 4 in the figure shows the corresponding speed that can achieve the highest unit efficiency after simulation under different unit flow rates, guide vane angles and blade angles during forward operation.

[0146] Figure 4 The dashed line 2 in Figure 5 The dotted line 4 in the figure is the same as the speed in the target control parameter obtained by prediction and comparison of the prediction model of the target correspondence between the control parameter and the unit efficiency obtained by adopting this embodiment. Therefore, the prediction model of the target correspondence between the control parameter and the unit efficiency obtained in this embodiment can determine the target control parameter with the highest unit efficiency at a predetermined time.

[0147] In another embodiment of the present application, in the process of obtaining an effective prediction model, since the operating conditions of the tidal unit include forward operating conditions and reverse operating conditions, after constructing the first prediction model, the first prediction model can be optimized with the historical control parameters corresponding to one of the operating conditions, and the optimized second prediction model can be verified through simulation. After verification, the first prediction model can be optimized with the historical control parameters corresponding to another operating condition, and the optimized second prediction model can be verified through simulation, so as to obtain an effective prediction model.

[0148] Wherein, based on the historical control parameters obtained in the aforementioned embodiment, the historical control parameters corresponding to the reverse operating condition may be used as the first historical control parameters, and the historical control parameters corresponding to the forward operating condition may be used as the second historical control parameters.

[0149] When planning the order of using the first historical control parameter and the second historical control parameter, based on the number of parameters involved in the first historical control parameter and the second historical control parameter, the historical control parameter with a smaller number of parameters can be used for optimization and verification first, and then the other historical control parameter can be used for optimization and verification.

[0150] Specifically, when comparing the number of parameters involved in the first historical control parameter and the second historical control parameter, by comparing Figure 4 The first unit characteristic curve corresponding to the tidal turbine operating at a predetermined speed under the reverse operating condition during the high tide cycle is shown, and Figure 5 Under the forward operating conditions during the low tide cycle shown, the corresponding second unit characteristic curve when the tidal unit operates at a predetermined speed can be determined. The first historical control parameters involve three parameters including speed, unit flow and blade angle, and the second historical control parameters involve four parameters including speed, unit flow, guide vane angle and blade angle.

[0151] Therefore, the first historical control parameters include more parameters than the second historical control parameters. The first historical control parameters can be used for optimization and verification first, and then the second historical control parameters can be used for optimization and verification.

[0152] In a specific example of this embodiment, Figure 6 A schematic diagram of a specific process of optimizing the first historical control parameter and the second historical control parameter to obtain an effective prediction model is shown, including steps 601-610.

[0153] like Figure 6 As shown, when obtaining the unit flow and speed in the historical control parameters, you can execute Figure 6 S601, determine the unit flow rate and S602, select the speed.

[0154] Specifically, when executing S601 , the unit flow rate may be determined based on the operating water level and the operating water level-unit flow rate curve.

[0155] Furthermore, when executing S602 , a speed may be selected from a preset speed optimization curve.

[0156] like Figure 6 As shown, based on S601 and S602, after combining the guide vane angle and the blade angle, the historical control parameters can be obtained, and S603 is further executed to construct the first prediction model.

[0157] Specifically, based on the acquired historical control parameters, the correspondence between different rotational speeds under the same historical unit flow conditions and the surveyed unit efficiency can be associated in a preset initial prediction model, thereby obtaining a first prediction model containing the initial correspondence between the control parameters and the unit efficiency.

[0158] like Figure 6 As shown, based on S603, S604 can be further executed to select historical control parameters for reverse operation.

[0159] Specifically, when selecting the order of the first historical control parameters and the second historical control parameters, based on the comparison of the number of parameters, since the number of parameters included in the first historical control parameters of the reverse operating condition is smaller, it is easier to use the first historical control parameters for optimization and verification than to use the second historical control parameters for optimization and verification.

[0160] Therefore, in S604, firstly, a first historical control parameter corresponding to the tidal turbine operating at a predetermined speed under the reverse operating condition during the high tide cycle is selected from each group of historical control parameters.

[0161] like Figure 6 As shown, based on S604, S605 can be further performed to optimize the first prediction model.

[0162] Specifically, when optimizing the model parameters of the first prediction model, the initial correspondence between the control parameters and the unit efficiency constructed in the first prediction model can be used to predict the corresponding predicted unit efficiency for each set of input first historical control parameters.

[0163] Furthermore, based on the predicted unit efficiencies corresponding to the predicted groups of first historical control parameters, the highest predicted unit efficiency can be determined from the predicted unit efficiencies, and the corresponding highest survey unit efficiency can be determined from the survey unit efficiencies corresponding to the first historical control parameters.

[0164] Based on this, the difference between the highest predicted unit efficiency and the corresponding highest survey unit efficiency corresponding to each group of first historical control parameters can be calculated. If the difference is greater than the convergence threshold, the model parameters of the first prediction model with the initial corresponding relationship between the control parameters and the unit efficiency are adjusted.

[0165] Furthermore, using the first prediction model after parameter adjustment, based on the initial correspondence between the control parameters and the unit efficiency, each group of first historical control parameters is predicted to obtain the corresponding predicted unit efficiency, and the difference between the highest predicted unit efficiency and the highest survey unit efficiency is calculated.

[0166] If the difference between the highest predicted unit efficiency and the highest surveyed unit efficiency corresponding to each group of first historical control parameters is less than or equal to the convergence threshold, the first prediction model at this time is determined as the second prediction model containing the target correspondence between the control parameters and the unit efficiency.

[0167] like Figure 6 As shown, based on S605, S606 can be further executed to perform simulation.

[0168] Specifically, based on the determined second prediction model containing the target correspondence between control parameters and unit efficiency, the highest predicted unit efficiency obtained when predicting each group of first historical control parameters based on the second prediction model can be used to determine a group of first historical control parameters corresponding to the highest predicted unit efficiency.

[0169] Furthermore, a preset simulation system can be used to simulate the operation of the tidal unit at a predetermined time with a set of first historical control parameters corresponding to the highest predicted unit efficiency, so as to output the simulation efficiency corresponding to the set of first historical control parameters at the predetermined time.

[0170] Based on this, we can further perform Figure 3 S607 in the process, determining whether the verification is passed.

[0171] Specifically, it is determined whether the corresponding simulation efficiency is greater than or equal to the highest survey unit efficiency corresponding to each group of first historical control parameters. If the simulation efficiency is less than the highest survey unit efficiency, the judgment result of S607 is no, and S608 is further executed to adjust parameters and make predictions.

[0172] Specifically, in S608 , the model parameters of the second prediction model having the target corresponding relationship between the control parameters and the unit efficiency are adjusted.

[0173] Furthermore, the second prediction model after parameter adjustment is used to predict each group of first historical control parameters according to the target correspondence between the control parameters and the unit efficiency, so as to obtain the corresponding predicted unit efficiency.

[0174] Furthermore, S606 is executed again to perform simulation using a set of first historical control parameters corresponding to the highest predicted unit efficiency to obtain corresponding simulation efficiency.

[0175] If the simulation efficiency is greater than or equal to the highest survey unit efficiency, the judgment result of S607 is yes, and further execution can be performed. Figure 6 In step S609, the historical control parameters for the forward operation are selected to execute S605 to S608 again using the second historical control parameters in each group of historical control parameters.

[0176] Specifically, a second historical control parameter corresponding to the tidal turbine operating at a predetermined rotational speed under a forward operating condition during a low tide period is selected from each group of historical control parameters.

[0177] like Figure 6 As shown, based on S609, S605 can be executed again to optimize the first prediction model.

[0178] Specifically, when optimizing the model parameters of the first prediction model again, the initial correspondence between the control parameters and the unit efficiency constructed in the first prediction model can be used to predict the corresponding predicted unit efficiency for each set of second historical control parameters input.

[0179] Furthermore, based on the predicted unit efficiencies corresponding to the predicted sets of second historical control parameters, the highest predicted unit efficiency can be determined from the predicted unit efficiencies, and the corresponding highest survey unit efficiency can be determined from the survey unit efficiencies corresponding to the predicted sets of second historical control parameters.

[0180] Based on this, the difference between the highest predicted unit efficiency and the corresponding highest survey unit efficiency corresponding to each group of second historical control parameters can be calculated. If the difference is greater than the convergence threshold, the model parameters of the first prediction model with the initial corresponding relationship between the control parameters and the unit efficiency are adjusted.

[0181] Furthermore, using the first prediction model after parameter adjustment, based on the initial correspondence between the control parameters and the unit efficiency, each group of second historical control parameters is predicted to obtain the corresponding predicted unit efficiency, and the difference between the highest predicted unit efficiency and the highest survey unit efficiency is calculated.

[0182] If the difference between the highest predicted unit efficiency and the highest surveyed unit efficiency corresponding to each group of second historical control parameters is less than or equal to the convergence threshold, the first prediction model at this time is determined as the second prediction model containing the target correspondence between the control parameters and the unit efficiency.

[0183] like Figure 6 As shown, based on S605, S606 can be further executed to perform simulation.

[0184] Specifically, based on the determined second prediction model containing the target correspondence between control parameters and unit efficiency, the highest predicted unit efficiency obtained when predicting each group of second historical control parameters based on the second prediction model can be used to determine a group of second historical control parameters corresponding to the highest predicted unit efficiency.

[0185] Furthermore, a preset simulation system can be used to simulate the operation of the tidal unit at a predetermined time with a set of second historical control parameters corresponding to the highest predicted unit efficiency, so as to output the simulation efficiency corresponding to the set of second historical control parameters at the predetermined time.

[0186] Based on this, we can further perform Figure 3 S607 in the process, determining whether the verification is passed.

[0187] Specifically, it is determined whether the corresponding simulation efficiency is greater than or equal to the highest survey unit efficiency corresponding to each group of second historical control parameters. If the simulation efficiency is less than the highest survey unit efficiency, the judgment result of S607 is no, and S608 is further executed to adjust parameters and make predictions.

[0188] Specifically, in S608 , the model parameters of the second prediction model having the target corresponding relationship between the control parameters and the unit efficiency are adjusted.

[0189] Furthermore, the second prediction model after parameter adjustment is used to predict each group of second historical control parameters according to the target correspondence between the control parameters and the unit efficiency, so as to obtain the corresponding predicted unit efficiency.

[0190] Furthermore, S606 is executed again to perform simulation using a set of first historical control parameters corresponding to the highest predicted unit efficiency to obtain corresponding simulation efficiency.

[0191] If the simulation efficiency is greater than or equal to the highest survey unit efficiency, then the judgment result of S607 is yes, and it can be determined that the second prediction model is a prediction model containing a target correspondence relationship between control parameters and unit efficiency, that is, Figure 6 In S610, an effective prediction model is obtained.

[0192] In another specific example of this embodiment, when the first historical control parameter and the second historical control parameter are respectively used for optimization, the first historical control parameter may be used to optimize the model parameters of the first prediction model, that is, to perform Figure 6 S605 in.

[0193] Furthermore, after completing S605, the model parameters of the first prediction model are optimized using the second historical control parameters, that is, the second historical control parameters are used to perform the optimization again. Figure 6 S605 in.

[0194] After completing S605 again, a second prediction model containing the target correspondence between the control parameters and the unit efficiency is obtained, and the first historical control parameters are used for simulation to verify whether the second prediction model is effective, that is, to execute Figure 6S606 to S608 in.

[0195] Furthermore, after completing S606 to S608, the second historical control parameters are used to perform simulation and verify whether the second prediction model is effective, that is, the second historical control parameters are used to perform simulation again. Figure 6 S606 to S608 in.

[0196] After completing S606 to S608 again, a prediction model containing the target correspondence between the control parameters and the unit efficiency is obtained.

[0197] Based on this, in this embodiment, based on the forward operating conditions and reverse operating conditions of the tidal unit, the first historical control parameters corresponding to the forward operating conditions and the second historical control parameters corresponding to the reverse operating conditions are respectively determined, so that the historical control parameters of the two different conditions can be used respectively to optimize the first prediction model and verify the second prediction model. Since the historical control parameters corresponding to different operating conditions are used respectively in the optimization and verification process, the optimization and verification process is faster and more accurate, avoiding the problem of using historical control parameters with too large differences under different operating conditions during optimization and verification, resulting in slow optimization and verification and low accuracy.

[0198] Based on the same inventive concept, corresponding to any of the above-mentioned embodiments and methods, an embodiment of the present application further provides a control device for a tidal generator set.

[0199] refer to Figure 7 The control device of the tidal turbine unit includes:

[0200] An acquisition module 701 is used to acquire multiple sets of control parameters of the unit at a predetermined time, wherein each set of control parameters includes a rotational speed and a unit flow rate at a predetermined time;

[0201] The unit efficiency determination module 702 is used to input each set of control parameters into the prediction model and determine the unit efficiency corresponding to each set of control parameters based on the target correspondence between the control parameters and the unit efficiency pre-established in the prediction model;

[0202] A control parameter determination module 703 is configured to determine a set of control parameters corresponding to the highest unit efficiency as target control parameters;

[0203] The control module 704 is used to control the operation of the unit within a predetermined time according to the speed in the target control parameter.

[0204] In one embodiment, the acquisition module 701 is specifically configured to:

[0205] Taking the predetermined speed as the center, multiple speeds are selected within the speed optimization range;

[0206] The flow rate of the unit at the predetermined time is obtained, and the flow rate of the unit is combined with the speed to obtain multiple groups of control parameters of the unit at the predetermined time.

[0207] In one embodiment, the unit efficiency determination module 702 is specifically configured to:

[0208] Before inputting each set of control parameters into the prediction model, the unit efficiency determination module 702 performs:

[0209] Obtain multiple sets of historical control parameters at different speeds under the same unit flow rate, as well as the corresponding survey unit efficiency in each set of historical control parameters, where each set of historical control parameters includes historical unit flow rate and speed;

[0210] Input each set of historical control parameters into the initial prediction model respectively;

[0211] By comparing the correspondence between different rotational speeds and the surveyed unit efficiency under the same historical unit flow rate, the correspondence between the historical control parameters and the corresponding surveyed unit efficiency is associated in the initial prediction model to obtain a first prediction model containing the initial correspondence between the control parameters and the unit efficiency;

[0212] Using the initial correspondence between the control parameters and the corresponding unit efficiencies in the first prediction model, each group of historical control parameters is predicted to obtain the corresponding predicted unit efficiencies;

[0213] When the difference between the highest predicted unit efficiency and the highest surveyed unit efficiency is less than or equal to a preset convergence threshold, a second prediction model containing a target correspondence relationship between control parameters and unit efficiency is obtained;

[0214] Using a simulation system to simulate the unit according to historical control parameters corresponding to the highest predicted unit efficiency, to obtain the corresponding simulation efficiency;

[0215] Determine whether the simulation efficiency is greater than or equal to the corresponding highest survey unit efficiency;

[0216] When the simulation efficiency is greater than or equal to the corresponding highest survey unit efficiency, the second prediction model containing the target corresponding relationship between the control parameters and the unit efficiency is determined as the prediction model.

[0217] After predicting each set of historical control parameters using the initial correspondence between the control parameters and the corresponding unit efficiencies in the first prediction model and obtaining the corresponding predicted unit efficiencies, the unit efficiency determination module 702 executes:

[0218] When the difference between the highest predicted unit efficiency and the highest surveyed unit efficiency is greater than a preset convergence threshold, adjusting the model parameters of the first prediction model containing the initial corresponding relationship;

[0219] The initial correspondence between the control parameters and the corresponding unit efficiencies in the adjusted first prediction model is used to predict each group of historical control parameters until the difference between the highest predicted unit efficiency and the highest surveyed unit efficiency is less than or equal to the convergence threshold, thereby obtaining a second prediction model containing the target correspondence between the control parameters and the unit efficiencies.

[0220] After determining whether the simulation efficiency is greater than or equal to the corresponding highest survey unit efficiency, the unit efficiency determination module 702 further performs:

[0221] When the simulation efficiency is less than the corresponding highest survey unit efficiency, adjusting the model parameters of the second prediction model containing the target corresponding relationship between the control parameters and the unit efficiency;

[0222] The target correspondence between the control parameters and the unit efficiency in the adjusted second prediction model is used to predict the predicted unit efficiency corresponding to each group of historical control parameters, and the historical control parameter group corresponding to the highest predicted unit efficiency is simulated and executed until the obtained simulation efficiency is greater than or equal to the corresponding highest survey unit efficiency. The second prediction model containing the target correspondence between the control parameters and the survey unit efficiency is determined to be the prediction model.

[0223] The multiple groups of historical control parameters include multiple groups of first historical control parameters during reverse operation and multiple groups of second historical control parameters during forward operation.

[0224] Wherein, when the difference between the highest predicted unit efficiency and the highest surveyed unit efficiency is less than or equal to a preset convergence threshold, a second prediction model containing a target correspondence relationship between control parameters and unit efficiency is obtained, including:

[0225] If the difference between the highest predicted unit efficiency among the predicted unit efficiencies corresponding to the first historical control parameter and the corresponding highest surveyed unit efficiency is less than or equal to the convergence threshold, the unit efficiency determination module 702 determines whether the difference between the highest predicted unit efficiency among the predicted unit efficiencies corresponding to the second historical control parameter and the highest surveyed unit efficiency is less than or equal to the convergence threshold.

[0226] When the difference between the highest predicted unit efficiency among the predicted unit efficiencies corresponding to the second historical control parameter and the corresponding highest surveyed unit efficiency is less than or equal to the convergence threshold, the unit efficiency determination module 702 obtains a second prediction model containing a target correspondence relationship between the control parameter and the surveyed unit efficiency;

[0227] When the simulation efficiency is greater than or equal to the corresponding highest survey unit efficiency, determining the second prediction model containing the target corresponding relationship between the control parameter and the unit efficiency as the prediction model includes:

[0228] If the simulation efficiency corresponding to the first historical control parameter is greater than or equal to the corresponding highest survey unit efficiency, the unit efficiency determination module 702 determines whether the simulation efficiency corresponding to the second historical control parameter is greater than or equal to the corresponding highest survey unit efficiency.

[0229] When the simulation efficiency corresponding to the second historical control parameter is greater than or equal to the corresponding highest survey unit efficiency, the unit efficiency determination module 702 determines the second prediction model containing the target correspondence relationship between the control parameter and the unit efficiency as the prediction model.

[0230] For the convenience of description, the above devices are described as being divided into various modules according to their functions. Of course, when implementing the embodiments of the present application, the functions of each module can be implemented in the same or multiple software and / or hardware.

[0231] The device of the above embodiment is used to implement the control method of the corresponding tidal unit in any of the above embodiments, and has the beneficial effects of the corresponding method embodiment, which will not be repeated here.

[0232] Based on the same inventive concept, corresponding to any of the above-mentioned embodiments and methods, an embodiment of the present application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and runnable on the processor, wherein when the processor executes the program, the control method of the tidal generator set of any of the above embodiments is implemented.

[0233] Figure 8 A schematic diagram of the hardware structure of an electronic device provided in an embodiment of the present application is shown.

[0234] The electronic device may include a processor 801 and a memory 802 storing computer program instructions.

[0235] Specifically, the processor 801 may include a central processing unit (CPU), or an application-specific integrated circuit (ASIC), or may be configured to implement one or more integrated circuits of the embodiments of the present application.

[0236] The memory 802 may include a large capacity memory for data or instructions. By way of example and not limitation, the memory 802 may include a hard disk drive (HDD), a floppy disk drive, a flash memory, an optical disk, a magneto-optical disk, a magnetic tape, or a universal serial bus (USB) drive, or a combination of two or more of these. Where appropriate, the memory 802 may include removable or non-removable (or fixed) media. Where appropriate, the memory 802 may be internal or external to the electronic device. In a particular embodiment, the memory 802 is a non-volatile solid-state memory.

[0237] The memory 802 may include a read-only memory (ROM), a random access memory (RAM), a magnetic disk storage medium device, an optical storage medium device, a flash memory device, an electrical, optical, or other physical / tangible memory storage device. Thus, generally, the memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., a memory device) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described with reference to the method according to an aspect of the present disclosure.

[0238] The processor 801 reads and executes the computer program instructions stored in the memory 802 to implement any one of the tidal turbine control methods in the above embodiments.

[0239] In one example, the electronic device may further include a communication interface 803 and a bus 810. Figure 8 As shown, the processor 801, the memory 802, and the communication interface 803 are connected via a bus 810 and communicate with each other.

[0240] The communication interface 803 is mainly used to implement communication between various modules, devices, units and / or equipment in the embodiments of the present application.

[0241] Bus 810 includes hardware, software or both, couples the parts of electronic equipment to each other.For example, but not limitation, bus may include Accelerated Graphics Port (AGP) or other graphics buses, Enhanced Industry Standard Architecture (EISA) bus, Front Side Bus (FSB), Hyper Transport (HT) interconnection, Industry Standard Architecture (ISA) bus, InfiniBand interconnection, Low Pin Count (LPC) bus, memory bus, Micro Channel Architecture (MCA) bus, Peripheral Component Interconnect (PCI) bus, PCI-Express (PCI-X) bus, Serial Advanced Technology Attachment (SATA) bus, Video Electronics Standards Association local (VLB) bus or other suitable bus or two or more of these combinations. In appropriate cases, bus 810 may include one or more buses. Although the present application embodiment describes and shows specific bus, the application considers any suitable bus or interconnection.

[0242] The electronic device can execute the control method of the tidal unit in the embodiment of the present application based on the target correspondence relationship pre-built in the prediction model, thereby realizing the combination Figure 1 The control method of the tidal turbine is described.

[0243] In addition, in conjunction with the control method of the tidal turbine in the above embodiments, embodiments of the present application may provide a computer storage medium for implementation. The computer storage medium stores computer program instructions; when the computer program instructions are executed by a processor, any of the control methods of the tidal turbine in the above embodiments is implemented.

[0244] An embodiment of the present application also provides a computer program product, including a computer program, which, when processed and executed, implements any one of the tidal generator control methods in the above embodiments.

[0245] It should be understood that the present application is not limited to the specific configurations and processes described above and illustrated in the figures. For the sake of brevity, a detailed description of known methods is omitted here. In the above embodiments, several specific steps are described and illustrated as examples. However, the method process of the present application is not limited to the specific steps described and illustrated. Those skilled in the art can make various changes, modifications, and additions, or change the order of the steps after understanding the spirit of the present application.

[0246] The functional blocks shown in the above-described block diagram can be implemented as hardware, software, firmware or a combination thereof. When implemented in hardware, they can be, for example, electronic circuits, application specific integrated circuits (ASICs), appropriate firmware, plug-ins, function cards, etc. When implemented in software, the elements of the present application are programs or code segments that are used to perform the required tasks. The program or code segment can be stored in a machine-readable medium, or transmitted on a transmission medium or a communication link by a data signal carried in a carrier wave. "Machine-readable medium" can include any medium that can store or transmit information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROMs, flash memories, erasable ROMs (EROMs), floppy disks, CD-ROMs, optical disks, hard disks, optical fiber media, radio frequency (RF) links, etc. The code segment can be downloaded via a computer network such as the Internet, an intranet, etc.

[0247] Based on the same inventive concept, corresponding to any of the above-mentioned embodiments and methods, the present application also provides a tidal turbine unit, which includes a control device and / or electronic device of the tidal turbine unit of any of the above-mentioned embodiments, and the electronic device executes the control method of the tidal turbine unit as any of the above-mentioned embodiments.

[0248] It should also be noted that the exemplary embodiments mentioned in this application describe some methods or systems based on a series of steps or devices. However, this application is not limited to the order of the above steps. In other words, the steps can be performed in the order mentioned in the embodiments, or in a different order, or several steps can be performed simultaneously.

[0249] Aspects of the present disclosure have been described above 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 disclosure. It should be understood that each box in the flowchart and / or block diagram and the combination of each box 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 or other programmable data processing device to produce a machine so that these instructions executed by the processor of the computer or other programmable data processing device enable the implementation of the function / action specified in one or more boxes of the flowchart and / or block diagram. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor or a field programmable logic circuit. It is also understood that each box in the block diagram and / or flowchart and the combination of the boxes in the block diagram and / or flowchart can also be implemented by dedicated hardware that performs the specified function or action, or can be implemented by a combination of dedicated hardware and computer instructions.

[0250] The above description is only a specific embodiment of the present application. Those skilled in the art will clearly understand that for the convenience and brevity of description, the specific working processes of the systems, modules and units described above can refer to the corresponding processes in the aforementioned method embodiments, and will not be repeated here. It should be understood that the scope of protection of the present application is not limited thereto. Any person skilled in the art can easily think of various equivalent modifications or replacements within the technical scope disclosed in the present application, and these modifications or replacements should be included in the scope of protection of the present application.

Claims

1. A method for controlling a tidal turbine, characterized in that: include: Acquiring multiple sets of control parameters of the unit at a predetermined time, wherein each set of control parameters includes a rotational speed and a flow rate of the unit at the predetermined time; Obtain multiple sets of historical control parameters at different speeds under the same unit flow rate, as well as the corresponding survey unit efficiency in each set of historical control parameters, where each set of historical control parameters includes historical unit flow rate and speed; Input each set of historical control parameters into the initial prediction model respectively; By comparing the correspondence between different rotational speeds and the surveyed unit efficiency under the same historical unit flow rate, the correspondence between the historical control parameters and the corresponding surveyed unit efficiency is associated in the initial prediction model to obtain a first prediction model containing the initial correspondence between the control parameters and the unit efficiency; Using the initial correspondence between the control parameters and the corresponding unit efficiencies in the first prediction model, each group of historical control parameters is predicted to obtain the corresponding predicted unit efficiencies; When the difference between the highest predicted unit efficiency and the highest surveyed unit efficiency is less than or equal to a preset convergence threshold, a second prediction model containing a target correspondence relationship between control parameters and unit efficiency is obtained; Using a simulation system to simulate the unit according to historical control parameters corresponding to the highest predicted unit efficiency, to obtain the corresponding simulation efficiency; Determining whether the simulation efficiency is greater than or equal to the corresponding highest survey unit efficiency; In the case where the simulation efficiency is greater than or equal to the corresponding highest survey unit efficiency, determining the second prediction model containing the target corresponding relationship between the control parameter and the unit efficiency as the prediction model; Inputting each set of control parameters into the prediction model, and determining the unit efficiency corresponding to each set of control parameters based on the target correspondence between the control parameters and the unit efficiency pre-established in the prediction model; Determine a set of control parameters corresponding to the highest unit efficiency as target control parameters; The operation of the unit at a predetermined time is regulated according to the rotational speed in the target control parameter.

2. The control method of a tidal turbine according to claim 1, characterized in that: The obtaining of multiple sets of control parameters of the unit at a predetermined time includes: Taking the predetermined speed as the center, multiple speeds are selected within the speed optimization range; The flow rate of the unit at a predetermined time is obtained, and the flow rate of the unit is respectively combined with the rotational speed to obtain the multiple groups of control parameters of the unit at the predetermined time.

3. The control method of a tidal turbine according to claim 1, characterized in that: After predicting each set of historical control parameters using the initial correspondence between the control parameters and the corresponding unit efficiencies in the first prediction model to obtain the corresponding predicted unit efficiencies, the method further includes: When the difference between the highest predicted unit efficiency and the highest surveyed unit efficiency is greater than a preset convergence threshold, adjusting the model parameters of the first prediction model containing the initial corresponding relationship; Each group of historical control parameters is predicted respectively using the initial correspondence between the control parameters and the corresponding unit efficiencies in the adjusted first prediction model until the difference between the highest predicted unit efficiency and the highest surveyed unit efficiency is less than or equal to the convergence threshold, thereby obtaining a second prediction model containing the target correspondence between the control parameters and the unit efficiencies.

4. The control method of a tidal turbine according to claim 1, characterized in that: After determining whether the simulation efficiency is greater than or equal to the corresponding highest survey unit efficiency, the method further includes: When the simulation efficiency is less than the corresponding highest survey unit efficiency, adjusting the model parameters of the second prediction model containing the target correspondence relationship between the control parameters and the unit efficiency; The target correspondence between the control parameters and the unit efficiency in the adjusted second prediction model is used to predict the predicted unit efficiency corresponding to each group of historical control parameters, and the historical control parameter group corresponding to the highest predicted unit efficiency is simulated and executed until the obtained simulation efficiency is greater than or equal to the corresponding highest survey unit efficiency. The second prediction model containing the target correspondence between the control parameters and the survey unit efficiency is determined to be the prediction model.

5. The control method of a tidal turbine according to claim 1, characterized in that: The multiple sets of historical control parameters include multiple sets of first historical control parameters during reverse operation and multiple sets of second historical control parameters during forward operation. When the difference between the highest predicted unit efficiency and the highest surveyed unit efficiency is less than or equal to a preset convergence threshold, obtaining a second prediction model containing a target correspondence between the control parameters and the unit efficiency includes: If the difference between the highest predicted unit efficiency among the predicted unit efficiencies corresponding to the first historical control parameter and the corresponding highest surveyed unit efficiency is less than or equal to the convergence threshold, determining whether the difference between the highest predicted unit efficiency and the highest surveyed unit efficiency among the predicted unit efficiencies corresponding to the second historical control parameter is less than or equal to the convergence threshold; When the difference between the highest predicted unit efficiency among the predicted unit efficiencies corresponding to the second historical control parameter and the corresponding highest survey unit efficiency is less than or equal to the convergence threshold, obtaining a second prediction model containing a target correspondence relationship between the control parameter and the survey unit efficiency; When the simulation efficiency is greater than or equal to the corresponding highest survey unit efficiency, determining the second prediction model containing the target corresponding relationship between the control parameter and the unit efficiency as the prediction model includes: If the simulation efficiency corresponding to the first historical control parameter is greater than or equal to the corresponding highest survey unit efficiency, determining whether the simulation efficiency corresponding to the second historical control parameter is greater than or equal to the corresponding highest survey unit efficiency; When the simulation efficiency corresponding to the second historical control parameter is greater than or equal to the corresponding highest survey unit efficiency, a second prediction model containing a target corresponding relationship between the control parameter and the unit efficiency is determined as the prediction model.

6. A control device for a tidal generator, characterized in that: The device comprises: an acquisition module, configured to acquire a plurality of control parameters of the unit at a predetermined time, wherein each control parameter includes a rotational speed and a flow rate of the unit at the predetermined time; The unit efficiency determination module is used to obtain multiple sets of historical control parameters at different speeds under the same unit flow rate, and the corresponding survey unit efficiency in each set of historical control parameters. Each set of historical control parameters includes historical unit flow rate and speed; Input each set of historical control parameters into the initial prediction model respectively; By comparing the correspondence between different rotational speeds and the surveyed unit efficiency under the same historical unit flow rate, the correspondence between the historical control parameters and the corresponding surveyed unit efficiency is associated in the initial prediction model to obtain a first prediction model containing the initial correspondence between the control parameters and the unit efficiency; Using the initial correspondence between the control parameters and the corresponding unit efficiencies in the first prediction model, each group of historical control parameters is predicted to obtain the corresponding predicted unit efficiencies; When the difference between the highest predicted unit efficiency and the highest surveyed unit efficiency is less than or equal to a preset convergence threshold, a second prediction model containing a target correspondence relationship between control parameters and unit efficiency is obtained; Using a simulation system to simulate the unit according to historical control parameters corresponding to the highest predicted unit efficiency, to obtain the corresponding simulation efficiency; Determining whether the simulation efficiency is greater than or equal to the corresponding highest survey unit efficiency; In the case where the simulation efficiency is greater than or equal to the corresponding highest survey unit efficiency, determining the second prediction model containing the target corresponding relationship between the control parameter and the unit efficiency as the prediction model; The unit efficiency determination module is further configured to input each set of control parameters into the prediction model, and determine the unit efficiency corresponding to each set of control parameters based on the target correspondence between the control parameters and the unit efficiency pre-established in the prediction model; a control parameter determination module, configured to determine a set of control parameters corresponding to the highest unit efficiency as target control parameters; A control module is used to control the operation of the unit at a predetermined time according to the speed in the target control parameter.

7. An electronic device, characterized in that: The device includes: a processor and a memory storing computer program instructions; When the processor executes the computer program instructions, the control method of the tidal generator set according to any one of claims 1 to 5 is implemented.

8. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer program instructions, which, when executed by a processor, implement the method for controlling a tidal generator set according to any one of claims 1 to 5.

9. A tidal generator set, characterized in that: It comprises the electronic device as claimed in claim 7, and the electronic device is used to execute the control method of the tidal generator set as claimed in any one of claims 1-5.

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