Wind turbine control method, device, equipment and computer readable storage medium

Abstract

This invention relates to the field of wind power generation technology, and more particularly to a wind turbine control method, device, equipment, and computer-readable storage medium. The method includes: acquiring the power consumption of electrical equipment in the wind turbine based on power line carrier communication; performing power consumption analysis on the electrical equipment based on the power consumption to obtain a power consumption analysis result, wherein the power consumption analysis result indicates high power consumption or normal power consumption; and adjusting the equipment parameters of the electrical equipment when the power consumption analysis result indicates high power consumption. This invention improves the efficiency of wind turbine power consumption management by automatically managing the self-power consumption of electrical equipment by adjusting the operating state of the electrical equipment when it is consuming high power.

Description

Technical Field

[0001] This invention relates to the field of wind power generation technology, and in particular to a wind turbine control method, device, equipment, and computer-readable storage medium. Background Technology

[0002] Wind power generation is a process that converts the kinetic energy of wind into mechanical kinetic energy, and then into electrical energy, through wind turbine generators. Each system within a wind turbine generator consumes electrical energy during operation; that is, wind turbines have self-consumption of electricity. In recent years, with the increasing demand for wind power generation, the installed capacity of wind turbine generators has gradually increased, leading to a continuous increase in the self-consumption of wind turbine generators. This self-consumption directly affects the power generation efficiency of wind turbines.

[0003] Currently, the main method for addressing the self-consumption problem of wind turbine generators is to install monitoring modules in the wind turbine generators to monitor the self-consumption of electrical equipment, and then have maintenance personnel identify and modify electrical equipment with high self-consumption. However, this method requires manual management of the wind turbine generator's electrical equipment, resulting in low management efficiency. Summary of the Invention

[0004] The main objective of this invention is to provide a wind turbine control method, device, equipment, and computer-readable storage medium. By adjusting the electrical equipment when it is consuming a lot of power, the self-consumption of the electrical equipment can be automatically managed, thereby improving the management efficiency of wind turbine self-consumption management.

[0005] To achieve the above objectives, the present invention provides a wind turbine control method, the wind turbine control method comprising the following steps:

[0006] Power consumption of electrical equipment in wind turbine generators is obtained using power line carrier communication.

[0007] Based on the power consumption of the equipment, a power consumption analysis is performed on the electrical equipment to obtain the power consumption analysis result of the electrical equipment, wherein the power consumption analysis result is either high power consumption or normal power consumption;

[0008] If the power consumption analysis results indicate high power consumption, the equipment parameters of the electrical equipment are adjusted.

[0009] Optionally, the step of performing a power consumption analysis on the electrical equipment based on the power consumption of the equipment to obtain the power consumption analysis results of the electrical equipment includes:

[0010] The current power consumption data of the electrical equipment is determined based on the power consumption of the equipment, and the current operating status of the electrical equipment is determined based on the current power consumption data;

[0011] Based on the power generation of the wind turbine and the meteorological data of the external environment where the wind turbine is located, the theoretical working state of the electrical equipment is determined.

[0012] If the current working state is inconsistent with the theoretical working state, then the power consumption analysis result of the electrical equipment is determined to be high power consumption;

[0013] If the current working state is consistent with the theoretical working state, then the power consumption analysis result is determined to be normal power consumption.

[0014] Optionally, the step of adjusting the equipment parameters of the electrical equipment when the power consumption analysis result indicates high power consumption includes:

[0015] If the power consumption analysis result indicates high power consumption, detect whether the electrical equipment has malfunctioned;

[0016] If the electrical equipment is not faulty, adjust the equipment parameters of the electrical equipment to bring it to the theoretical working state.

[0017] Optionally, the step of determining the current power consumption data of the electrical equipment based on the power consumption of the equipment includes:

[0018] Determine the excess power consumption exceeding the preset power threshold from the power consumption of the device within the preset detection period prior to the current moment;

[0019] Based on each of the above-limit electricity consumptions and the time corresponding to each of the above-limit electricity consumptions, the duration of the above-limit electricity consumption of the electrical equipment is calculated.

[0020] The excess power consumption and the excess power consumption duration are used as the current power consumption data of the electrical equipment.

[0021] Optionally, the step of determining the theoretical operating state of the electrical equipment based on the power generation of the wind turbine and meteorological data of the external environment where the wind turbine is located includes:

[0022] Based on the power generation of the wind turbine and the meteorological data of the external environment where the wind turbine is located, the theoretical operating parameters of the electrical equipment are determined.

[0023] The theoretical operating state of the electrical equipment is determined based on the theoretical operating parameters.

[0024] Optionally, the step of determining the theoretical operating state of the electrical equipment based on the power generation of the wind turbine and meteorological data of the external environment where the wind turbine is located includes:

[0025] The power generation of the wind turbine and the meteorological data of the external environment where the wind turbine is located are input into the trained target network model to obtain the theoretical operating parameters of the electrical equipment.

[0026] Optionally, the wind turbine control method further includes:

[0027] The power generation of the wind turbine and the meteorological data of the external environment where the wind turbine is located are obtained as training sample data, and the operating parameters of the electrical equipment are used as training labels. The target network model is obtained by training the model based on the training sample data and the training labels.

[0028] To achieve the above objectives, the present invention also provides a wind turbine control device, the wind turbine control device comprising:

[0029] The acquisition module is used to acquire the power consumption of electrical equipment in the wind turbine based on power line carrier communication.

[0030] The analysis module performs power consumption analysis on the electrical equipment based on the power consumption of the equipment, and obtains the power consumption analysis result of the electrical equipment, wherein the power consumption analysis result is either high power consumption or normal power consumption;

[0031] The adjustment module adjusts the equipment parameters of the electrical equipment when the power consumption analysis result indicates high power consumption.

[0032] To achieve the above objectives, the present invention also provides a wind turbine control device, the wind turbine control device comprising: a memory, a processor, and a wind turbine control program stored in the memory and executable on the processor, wherein the wind turbine control program, when executed by the processor, implements the steps of the wind turbine control method as described above.

[0033] In addition, to achieve the above objectives, the present invention also proposes a computer-readable storage medium storing a wind turbine control program, which, when executed by a processor, implements the steps of the wind turbine control method described above.

[0034] In this invention, the power consumption of electrical equipment in a wind turbine is acquired using power line carrier communication. Based on this power consumption, a power consumption analysis is performed on the electrical equipment to obtain a power consumption analysis result, which can be either high power consumption or normal power consumption. If the power consumption analysis result indicates high power consumption, the equipment parameters of the electrical equipment are adjusted. This invention achieves automatic management of the self-consumption of electrical equipment by adjusting the equipment when it is consuming high power. Compared to manual optimization and modification of electrical equipment, this invention improves the management efficiency of self-consumption management, thereby improving the overall management efficiency of wind turbine self-consumption management. Attached Figure Description

[0035] Figure 1 This is a schematic diagram of the hardware operating environment involved in the embodiments of the present invention;

[0036] Figure 2 This is a flowchart illustrating the first embodiment of the wind turbine control method of the present invention;

[0037] Figure 3 This is a schematic diagram of a wind turbine system designed according to one embodiment of the wind turbine control method of the present invention;

[0038] Figure 4 This is a flowchart illustrating the second embodiment of the wind turbine control method of the present invention;

[0039] Figure 5 This is a flowchart illustrating the third embodiment of the wind turbine control method of the present invention;

[0040] Figure 6 This is a schematic diagram of the functional modules of a preferred embodiment of the wind turbine control device of the present invention.

[0041] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0042] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0043] like Figure 1 As shown, Figure 1 This is a schematic diagram of the device structure of the hardware operating environment involved in the embodiments of the present invention.

[0044] It should be noted that the wind turbine control device in the embodiments of the present invention can be a controller of the wind turbine or a device that establishes a communication connection with the controller of the wind turbine, such as a personal computer, a smartphone, a server, etc., and no specific limitation is made here.

[0045] like Figure 1 As shown, the wind turbine control device may include: a processor 1001, such as a CPU; a network interface 1004; a user interface 1003; a memory 1005; and a communication bus 1002. The communication bus 1002 is used to enable communication between these components. The user interface 1003 may include a display screen and an input unit such as a keyboard; optionally, the user interface 1003 may also include a standard wired interface or a wireless interface. The network interface 1004 may optionally include a standard wired interface or a wireless interface (such as a Wi-Fi interface). The memory 1005 may be high-speed RAM or stable non-volatile memory, such as a disk storage device. Optionally, the memory 1005 may also be a storage device independent of the aforementioned processor 1001.

[0046] Those skilled in the art will understand that Figure 1 The equipment structure shown does not constitute a limitation on the wind turbine control equipment, and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0047] like Figure 1 As shown, the memory 1005, serving as a computer storage medium, may include an operating system, a network communication module, a user interface module, and a wind turbine control program. The operating system is a program that manages and controls the hardware and software resources of the equipment, supporting the operation of the wind turbine control program and other software or programs. Figure 1 In the device shown, the user interface 1003 is mainly used for data communication with the client; the network interface 1004 is mainly used for establishing a communication connection with the server; and the processor 1001 can be used to call the wind turbine control program stored in the memory 1005 and perform the following operations:

[0048] Power consumption of electrical equipment in wind turbine generators is obtained using power line carrier communication.

[0049] Based on the power consumption of the equipment, a power consumption analysis is performed on the electrical equipment to obtain the power consumption analysis result of the electrical equipment, wherein the power consumption analysis result is either high power consumption or normal power consumption;

[0050] If the power consumption analysis results indicate high power consumption, the equipment parameters of the electrical equipment are adjusted.

[0051] Furthermore, the step of performing a power consumption analysis on the electrical equipment based on the power consumption of the equipment to obtain the power consumption analysis results of the electrical equipment includes:

[0052] The current power consumption data of the electrical equipment is determined based on the power consumption of the equipment, and the current operating status of the electrical equipment is determined based on the current power consumption data;

[0053] Based on the power generation of the wind turbine and the meteorological data of the external environment where the wind turbine is located, the theoretical working state of the electrical equipment is determined.

[0054] If the current working state is inconsistent with the theoretical working state, then the power consumption analysis result of the electrical equipment is determined to be high power consumption;

[0055] If the current working state is consistent with the theoretical working state, then the power consumption analysis result is determined to be normal power consumption.

[0056] Furthermore, the step of adjusting the equipment parameters of the electrical equipment when the power consumption analysis result indicates high power consumption includes:

[0057] If the power consumption analysis result indicates high power consumption, detect whether the electrical equipment has malfunctioned;

[0058] If the electrical equipment is not faulty, adjust the equipment parameters of the electrical equipment to bring it to the theoretical working state.

[0059] Further, the step of determining the current power consumption data of the electrical equipment based on the power consumption of the equipment includes:

[0060] Determine the excess power consumption exceeding the preset power threshold from the power consumption of the device within the preset detection period prior to the current moment;

[0061] Based on each of the above-limit electricity consumptions and the time corresponding to each of the above-limit electricity consumptions, the duration of the above-limit electricity consumption of the electrical equipment is calculated.

[0062] The excess power consumption and the excess power consumption duration are used as the current power consumption data of the electrical equipment.

[0063] Furthermore, the step of determining the theoretical operating state of the electrical equipment based on the power generation of the wind turbine and meteorological data of the external environment where the wind turbine is located includes:

[0064] Based on the power generation of the wind turbine and the meteorological data of the external environment where the wind turbine is located, the theoretical operating parameters of the electrical equipment are determined.

[0065] The theoretical operating state of the electrical equipment is determined based on the theoretical operating parameters.

[0066] Furthermore, the step of determining the theoretical operating state of the electrical equipment based on the power generation of the wind turbine and meteorological data of the external environment where the wind turbine is located includes:

[0067] The power generation of the wind turbine and the meteorological data of the external environment where the wind turbine is located are input into the trained target network model to obtain the theoretical operating parameters of the electrical equipment.

[0068] Furthermore, the processor 1001 can be used to call the wind turbine control program stored in the memory 1005 and perform the following operations:

[0069] The power generation of the wind turbine and the meteorological data of the external environment where the wind turbine is located are obtained as training sample data, and the operating parameters of the electrical equipment are used as training labels. The target network model is obtained by training the model based on the training sample data and the training labels.

[0070] Based on the above structure, various embodiments of the wind turbine control method are proposed.

[0071] Reference Figure 2 , Figure 2 This is a flowchart illustrating the first embodiment of the wind turbine control method of the present invention.

[0072] This invention provides an embodiment of a wind turbine control method. It should be noted that although the logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order. In this embodiment, the executing entity of the wind turbine control method can be the control device of the wind turbine. The control device can be the controller of the wind turbine, or a device that establishes a communication connection with the controller of the wind turbine, such as a personal computer, smartphone, or server. This embodiment does not impose any limitations. For ease of description, the execution entity is omitted from the description of each embodiment. In this embodiment, the wind turbine control method includes:

[0073] Step S10: Obtain the power consumption of electrical equipment in the wind turbine generator set based on power line carrier communication.

[0074] The power loss of a wind turbine refers to the power loss generated during the conversion of wind energy into electrical energy. This power loss primarily affects the power consumption of the system equipment and can be divided into two main parts: generation and transmission losses, and auxiliary power supply system losses. Generation and transmission losses occur during the generation, conversion, and transmission of electrical energy, mainly in the generator set, frequency converter, and tower power cables. Auxiliary power supply system losses primarily involve electrical equipment, including gearboxes, pitch systems, yaw systems, temperature control systems, and heaters. The power loss of electrical equipment is usually related to its operating status. For example, the gearbox experiences significant internal temperature fluctuations during operation, requiring the activation of lubrication and cooling systems and heating systems to stabilize the temperature, thus generating power loss. Similarly, pitch motors, by controlling the blade angle to control the effective windward area and ensure the wind turbine's output power, can experience additional power loss if the control strategy is not properly configured, leading to frequent pitch angle adjustments before the wind turbine reaches its rated power.

[0075] Based on the above, this embodiment proposes a method for efficient and accurate management of the self-consumption of wind turbine generators. Specifically, in this embodiment, power monitoring devices are installed at each electrical equipment node, and the power monitoring devices transmit the monitored power to the control equipment via power line carrier communication. For example, in one embodiment, referring to... Figure 3 Power monitoring devices can be installed at the electrical equipment nodes of the wind turbine system. Figure 3 The electrical equipment in the wind turbine shown includes the generator fan, yaw motor, and pitch system (i.e., ... Figure 3 The pitch control shown includes the pitch control, slip rings, water cooling system, and converter system (i.e.,...). Figure 3 The water-cooled, converter system, transformer, and generator shown are shown in the diagram. Figure 3 G shown), switch cabinet (i.e. Figure 3 K is shown in the figure.

[0076] In this embodiment, the power consumption of electrical equipment in a wind turbine is obtained based on power line carrier communication. The specific process of power line carrier communication is as follows: the power monitoring device processes and encodes analog or digital signals to convert the monitored power consumption into a modulated signal, which is then sent to the control equipment as a power line carrier signal. During the modulation process, different methods such as amplitude modulation, frequency modulation, and phase modulation can be used to control the signal transmission characteristics. The modulated signal is then transmitted to the control equipment through the circuitry of the wind turbine. The control equipment needs to demodulate, amplify, and filter the power line carrier signal to obtain the power consumption.

[0077] This embodiment uses power line carrier for information transmission, which can reduce the layout of communication buses in wind turbines, reduce line power loss, thereby reducing the self-consumption of wind turbines and improving the grid connection efficiency of wind turbines.

[0078] Step S20: Perform power consumption analysis on the electrical equipment based on the power consumption of the equipment to obtain the power consumption analysis result of the electrical equipment, wherein the power consumption analysis result is either high power consumption or normal power consumption;

[0079] In this embodiment, after obtaining the power consumption of the equipment, the power consumption analysis of the electrical equipment can be performed based on the power consumption of the equipment to obtain the power consumption analysis results of the electrical equipment.

[0080] In specific implementations, the power consumption analysis results of electrical equipment can be determined by threshold judgment; alternatively, the current operating state of electrical equipment can be determined by other feasible methods, such as deep learning, without limitation. For example, in one feasible implementation, it can be detected whether the power consumption of the equipment at each moment exceeds a preset threshold; if the power consumption of the equipment at each moment exceeds the preset threshold, the power consumption analysis result of the electrical equipment is determined to be a high power consumption state. Further, in one feasible implementation, the power consumption analysis result of the electrical equipment can also be determined to be a high power consumption state when the detected power consumption exceeds the preset time threshold for consecutive moments.

[0081] Step S30: If the power consumption analysis result indicates high power consumption, adjust the equipment parameters of the electrical equipment.

[0082] In this embodiment, when the power consumption analysis results indicate high power consumption, the equipment parameters of the electrical equipment are adjusted. Furthermore, in another feasible embodiment, the selection of the electrical equipment can also be adjusted; this is not limited and can be set according to actual needs.

[0083] In this embodiment, the power consumption of electrical equipment in the wind turbine is acquired using power line carrier communication. Power consumption analysis is then performed on the electrical equipment based on this power consumption, yielding the analysis results. When the analysis indicates high power consumption, the equipment parameters are adjusted. This embodiment achieves automatic management of the self-consumption of electrical equipment by adjusting the equipment when it is consuming high power. Compared to manual optimization and modification of the equipment, this embodiment improves the management efficiency of self-consumption management, thereby enhancing the overall management efficiency of wind turbine self-consumption. Furthermore, by adjusting the equipment when it is consuming high power, this embodiment can control the self-consumption of electrical equipment, improve the grid connection efficiency of the wind turbine, and reduce the self-consumption of the wind turbine.

[0084] Furthermore, based on the first embodiment described above, a second embodiment of the wind turbine control method of the present invention is proposed, referring to... Figure 4 In this embodiment, step S20 includes:

[0085] Step S201: Determine the current power consumption data of the electrical equipment based on the power consumption of the equipment, and determine the current working status of the electrical equipment based on the current power consumption data;

[0086] In this embodiment, when the power consumption analysis instruction is triggered, the current power consumption data of the electrical equipment is determined based on the power consumption of the equipment, so as to evaluate the working status of the electrical equipment (hereinafter referred to as the current working status for distinction).

[0087] In this embodiment, the current working state of the electrical equipment is: the actual working state of the electrical equipment at the current moment. The current working state can be a high power consumption state or a normal high power consumption state. In a specific implementation, the current working state of the electrical equipment can be determined by a threshold judgment method; or it can be determined by other feasible methods, such as deep learning, etc., which are not limited here.

[0088] Step S202: Based on the power generation of the wind turbine and the meteorological data of the external environment where the wind turbine is located, determine the theoretical working state of the electrical equipment;

[0089] In this embodiment, when it is determined that the wind turbine has triggered an instruction to adjust the working state of the electrical equipment, the power generation of the wind turbine and the meteorological data of the external environment where the wind turbine is located are also acquired. Then, based on the power generation of the wind turbine and the meteorological data of the external environment where the wind turbine is located, the theoretical working state of the electrical equipment is determined.

[0090] In this embodiment, the theoretical operating state of the electrical equipment is defined as the operating state of the electrical equipment when matched with the power generation of the wind turbine and the meteorological data of the external environment. The theoretical operating state can also be a high-power-consumption state or a low-power-consumption state. In one feasible implementation, the theoretical operating parameters of the electrical equipment can be determined based on the power generation of the wind turbine and the meteorological data of the external environment where the wind turbine is located, and then the theoretical operating state of the electrical equipment can be determined based on the theoretical operating parameters. In another feasible implementation, the power generation and meteorological data can be directly input into a pre-trained deep learning model to obtain the theoretical operating state. There is no limitation here, and the specific settings can be made according to actual needs.

[0091] Step S203: If the current working state is inconsistent with the theoretical working state, then the power consumption analysis result of the electrical equipment is determined to be high power consumption;

[0092] In this embodiment, after determining the current working state and the theoretical working state, it is detected whether the current working state and the theoretical working state are consistent. If the current working state and the theoretical working state are inconsistent, it is determined that the power consumption of the electrical equipment matches the actual power generation of the wind turbine. Therefore, the power consumption analysis result of the electrical equipment is determined to be high power consumption.

[0093] If the current working state is inconsistent with the theoretical working state, it may be that the current working state of the electrical equipment is a high power consumption state, while the theoretical working state is not a high power consumption state. In this case, it is determined that there is power loss outside of production. It may be due to unreasonable control parameter settings of the electrical equipment. For example, it may be due to the electrical equipment operating too frequently. In this case, the power consumption analysis result of the electrical equipment is determined to be high power consumption.

[0094] Furthermore, in some scenarios, due to discrepancies between the actual selection of electrical equipment and the selection recorded by the control equipment, there may be a situation where the current operating state is not a high-power-consumption state, but the theoretical operating state is a high-power-consumption state. To distinguish between these two situations where the current operating state and the theoretical operating state are inconsistent, when it is determined that the current operating state is inconsistent with the theoretical operating state, it can be checked whether the current operating state is a high-power-consumption state. If the current operating state is a high-power-consumption state, then the power consumption analysis result of the electrical equipment is determined to be high-power-consumption; if the current operating state is not a high-power-consumption state, then the record of the control equipment is adjusted, or the equipment selection is changed. Compared to not processing when the current operating state is not a high-power-consumption state, this implementation method can reduce the energy consumption of the electrical equipment itself and reduce the self-power consumption of the wind turbine.

[0095] Step S204: If the current working state is consistent with the theoretical working state, then the power consumption analysis result is determined to be normal power consumption.

[0096] If the current working state is consistent with the theoretical working state, then the power consumption of the electrical equipment is determined to match the actual power generation of the wind turbine. In this case, the power consumption analysis result is determined to be normal power consumption.

[0097] Furthermore, in one feasible implementation, step S30 includes:

[0098] Step S301: If the power consumption analysis result indicates high power consumption, detect whether the electrical equipment has malfunctioned;

[0099] Since electrical equipment may also experience high power consumption due to malfunctions, such as aging of parts, this embodiment aims to reduce ineffective management of electrical equipment and improve the accuracy of electrical equipment management. When it is determined that the wind turbine has triggered an instruction to adjust the working status of the electrical equipment, the system first checks whether the electrical equipment has malfunctioned. If it is determined that the electrical equipment is not malfunctioning, the system then adjusts the electrical equipment.

[0100] Step S302: If the electrical equipment has not malfunctioned, adjust the equipment parameters of the electrical equipment to bring it to the theoretical working state.

[0101] In this embodiment, if the electrical equipment does not malfunction, it is determined that the high power consumption of the electrical equipment is not caused by the malfunction of the electrical equipment. At this time, the electrical equipment can be adjusted. Specifically, in this embodiment, the equipment parameters of the electrical equipment are adjusted to adjust the electrical equipment to the theoretical working state.

[0102] Furthermore, in one feasible implementation, if an electrical equipment malfunctions, maintenance personnel are alerted to replace the equipment to ensure the safe operation of the wind turbine.

[0103] In this embodiment, by adjusting the equipment parameters of the electrical equipment, the electrical equipment is adjusted to its theoretical working state. Compared with adjusting the selection of electrical equipment, this embodiment can improve the adjustment efficiency and reduce the cost of the wind turbine generator set while controlling the self-consumption of the electrical equipment.

[0104] In this embodiment, the current power consumption data of the electrical equipment is determined based on the equipment's power consumption, and the current operating status of the electrical equipment is determined based on the current power consumption data. The theoretical operating status of the electrical equipment is determined based on the power generation of the wind turbine and the meteorological data of the external environment where the wind turbine is located. If the current operating status is inconsistent with the theoretical operating status, the power consumption analysis result of the electrical equipment is determined to be high power consumption; if the current operating status is consistent with the theoretical operating status, the power consumption analysis result is determined to be normal power consumption. This embodiment determines whether the electrical equipment is in a high power consumption state by comparing the current operating status with the theoretical operating status to see if the operating power consumption of the electrical equipment matches the actual power generation of the wind turbine. Compared with power consumption analysis based on threshold judgment, this embodiment can improve the accuracy of power consumption analysis results, thereby improving the management accuracy of wind turbine self-power consumption management. Compared with power consumption analysis using deep learning, this embodiment can reduce analysis steps and improve power consumption analysis efficiency, thereby improving the management efficiency of wind turbine self-power consumption management.

[0105] Furthermore, based on the first and / or second embodiments described above, a third embodiment of the wind turbine control method of the present invention is proposed, referring to... Figure 5In this embodiment, step S201 includes:

[0106] Step S2011: Determine the excess power consumption exceeding the preset power consumption threshold from the power consumption of the device within the preset detection period before the current time;

[0107] In this embodiment, the excess power consumption exceeding a preset power threshold is determined from the device's power consumption within a preset detection period prior to the current time. The preset detection period can be set according to actual needs and is not limited here.

[0108] Step S2012: Based on each of the excess power consumption and the time corresponding to each of the excess power consumption, calculate the excess power consumption duration of the electrical equipment;

[0109] Based on each excess power consumption and the corresponding time, the duration of excess power consumption for electrical equipment is calculated.

[0110] Step S2013: The reference power consumption and the power consumption duration are used as the current power consumption data of the electrical equipment.

[0111] The excessive power consumption and duration of each excess power consumption are used as the current power consumption data of the electrical equipment. In this embodiment, using the excessive power consumption and duration of each excess power consumption as the current power consumption data of the electrical equipment, compared to using only the power consumption as the current power consumption data, allows for a more accurate determination of the current operating status, thereby improving the accuracy of wind turbine management.

[0112] Furthermore, in one feasible implementation, step S202 includes;

[0113] Step S2021: Based on the power generation of the wind turbine and the meteorological data of the external environment where the wind turbine is located, determine the theoretical operating parameters of the electrical equipment.

[0114] In this embodiment, after obtaining the power generation of the wind turbine and the meteorological data of the external environment, the equipment parameters of the electrical equipment in this scenario are determined based on the power generation and meteorological data. These are referred to as theoretical operating parameters for distinction.

[0115] In one feasible implementation, power generation and meteorological data can be input into the trained target network model to obtain the theoretical operating parameters of the electrical equipment. The target network model is trained using the operating parameters of the electrical equipment as training labels and the power generation of the wind turbine and the meteorological data of the external environment as input data.

[0116] In another feasible implementation, a device characteristic curve can be constructed for each electrical device based on device parameters, power generation, and meteorological data. In this implementation, the corresponding device parameters are found in the device characteristic curve of the electrical device based on power generation and meteorological data as theoretical operating parameters. In this embodiment, the equipment parameters in the characteristic curves of different electrical devices are different. The specific equipment parameters can be determined based on the parameters that affect the self-consumption of the electrical devices. For example, the internal temperature of the gearbox fluctuates greatly during operation, requiring the activation of the lubrication and cooling system and the heating system to stabilize the temperature, which results in power loss. Therefore, the equipment parameters corresponding to the gearbox, temperature control system, and heating system can be the temperature fluctuation range. The power loss of the pitch system depends on the wind direction change. The pitch motor needs to control the effective windward area by controlling the blade angle to ensure the output power of the wind turbine. If the control strategy is not set reasonably, it is easy to generate additional power loss due to frequent adjustment of the pitch angle before the wind turbine reaches the rated power. Therefore, the equipment parameter corresponding to the pitch system can be the blade angle. When there is no wind or the wind speed does not reach the cut-in wind speed, frequent wind advances of the yaw system will increase unnecessary power loss. Therefore, the equipment parameter corresponding to the yaw system can be the number of wind advances. In addition, it can also include other electrical devices and their corresponding equipment parameters, which are not limited here.

[0117] Step S2022: Determine the theoretical operating state of the electrical equipment based on the theoretical operating parameters.

[0118] In this embodiment, the theoretical operating state of the electrical equipment is determined based on theoretical operating parameters. In one feasible implementation, a mapping relationship between theoretical operating parameters and theoretical operating states can be established, and the theoretical operating state corresponding to the theoretical operating parameters can be determined according to the mapping relationship. In another feasible implementation, a neural network model can be trained using operating parameters and electrical equipment as input data and operating states as training labels to determine the theoretical operating state of the electrical equipment based on the theoretical operating parameters. The specific training process and neural network structure are not limited here.

[0119] In this embodiment, the theoretical operating parameters of the electrical equipment are determined based on the power generation of the wind turbine and meteorological data of the external environment where the wind turbine is located; the theoretical operating state of the electrical equipment is then determined based on these theoretical operating parameters. This embodiment realizes the adjustment of the actual operating state of the electrical equipment based on the theoretical operating state, achieving automatic management of the self-consumption of the electrical equipment. Compared with manual optimization and modification of the electrical equipment, this invention can improve the management efficiency and accuracy of wind turbine self-consumption management.

[0120] Further, in one feasible implementation, step S2021 includes:

[0121] Step S20211: Input the power generation of the wind turbine and the meteorological data of the external environment where the wind turbine is located into the trained target network model to obtain the theoretical operating parameters of the electrical equipment.

[0122] In this embodiment, theoretical operating parameters are determined based on a neural network model. Compared with determining theoretical operating parameters through characteristic curves, the theoretical operating parameters obtained in this embodiment are more accurate, thereby making the control of electrical equipment more precise and improving the control accuracy of wind turbine units.

[0123] Specifically, in this embodiment, the power generation of the wind turbine and the meteorological data of the external environment where the wind turbine is located are input into the trained target network model to obtain the theoretical operating parameters of the electrical equipment. The target network model is trained using the operating parameters of the electrical equipment as training labels and the power generation of the wind turbine and the meteorological data of the external environment as input data.

[0124] Furthermore, in one feasible embodiment, the wind turbine control method further includes:

[0125] Step S40: Obtain the power generation of the wind turbine and the meteorological data of the external environment where the wind turbine is located as training sample data, and use the operating parameters of the electrical equipment as training labels, so as to train the model according to the training sample data and the training labels to obtain the target network model.

[0126] In this embodiment, the power generation of the wind turbine and meteorological data of the external environment where the wind turbine is located are obtained as training sample data, and the operating parameters of the electrical equipment are used as training labels. A target network model is obtained by training the model based on the training sample data and the training labels. The theoretical operating parameters of the electrical equipment are then determined through the target network model.

[0127] This implementation does not limit the specific structure and training process of the target network model. For example, in one feasible implementation, the target network model may include convolutional blocks, attention mechanism layers, and fully connected layers. In this implementation, the process of inputting the power generation of the wind turbine and the meteorological data of the external environment where the wind turbine is located into the trained target network model to obtain the theoretical operating parameters of the electrical equipment can be as follows: inputting the power generation and meteorological data into cascaded convolutional blocks to obtain features, wherein the input data of the first cascaded convolutional block is the power generation and meteorological data, and the input data of each convolutional block other than the first convolutional block is the output data of the previous level convolutional block; inputting the features into the attention mechanism layer, and weighting the features through the attention mechanism layer to obtain weighted features; fusing the features and weighted features to obtain fused features, and inputting the fused features into the fully connected layer to obtain the theoretical operating parameters.

[0128] In this embodiment, by using the excess power consumption and excess power consumption duration as the current power consumption data of electrical equipment, compared with only using the power consumption as the current power consumption data, this implementation method can obtain a more accurate current working status, thereby improving the accuracy of wind turbine management.

[0129] Furthermore, embodiments of the present invention also propose a wind turbine control device, referring to... Figure 6 The wind turbine control device includes:

[0130] The acquisition module 10 is used to acquire the power consumption of electrical equipment in the wind turbine based on power line carrier communication.

[0131] Analysis module 20 performs power consumption analysis on the electrical equipment based on the power consumption of the equipment, and obtains the power consumption analysis result of the electrical equipment, wherein the power consumption analysis result is either high power consumption or normal power consumption;

[0132] The adjustment module 30 adjusts the equipment parameters of the electrical equipment when the power consumption analysis result indicates high power consumption.

[0133] Furthermore, the analysis module 20 is also used for:

[0134] The current power consumption data of the electrical equipment is determined based on the power consumption of the equipment, and the current operating status of the electrical equipment is determined based on the current power consumption data;

[0135] Based on the power generation of the wind turbine and the meteorological data of the external environment where the wind turbine is located, the theoretical working state of the electrical equipment is determined.

[0136] If the current working state is inconsistent with the theoretical working state, then the power consumption analysis result of the electrical equipment is determined to be high power consumption;

[0137] If the current working state is consistent with the theoretical working state, then the power consumption analysis result is determined to be normal power consumption.

[0138] Furthermore, the adjustment module 30 is also used for:

[0139] If the power consumption analysis result indicates high power consumption, detect whether the electrical equipment has malfunctioned;

[0140] If the electrical equipment is not faulty, adjust the equipment parameters of the electrical equipment to bring it to the theoretical working state.

[0141] Furthermore, the analysis module 20 is also used for:

[0142] Determine the excess power consumption exceeding the preset power threshold from the power consumption of the device within the preset detection period prior to the current moment;

[0143] Based on each of the above-limit electricity consumptions and the time corresponding to each of the above-limit electricity consumptions, the duration of the above-limit electricity consumption of the electrical equipment is calculated.

[0144] The excess power consumption and the excess power consumption duration are used as the current power consumption data of the electrical equipment.

[0145] Furthermore, the analysis module 20 is also used for:

[0146] Based on the power generation of the wind turbine and the meteorological data of the external environment where the wind turbine is located, the theoretical operating parameters of the electrical equipment are determined.

[0147] The theoretical operating state of the electrical equipment is determined based on the theoretical operating parameters.

[0148] Furthermore, the analysis module 20 is also used for:

[0149] The power generation of the wind turbine and the meteorological data of the external environment where the wind turbine is located are input into the trained target network model to obtain the theoretical operating parameters of the electrical equipment.

[0150] Furthermore, the wind turbine control device also includes a model training module, used for:

[0151] The power generation of the wind turbine and the meteorological data of the external environment where the wind turbine is located are obtained as training sample data, and the operating parameters of the electrical equipment are used as training labels. The target network model is obtained by training the model based on the training sample data and the training labels.

[0152] All embodiments of the wind turbine control device of the present invention can refer to the various embodiments of the wind turbine control method of the present invention, and will not be repeated here.

[0153] Furthermore, this embodiment of the invention also proposes a computer-readable storage medium storing a wind turbine control program, which, when executed by a processor, implements the steps of the wind turbine control method described below.

[0154] The various embodiments of the wind turbine control device and computer-readable storage medium of the present invention can be referred to the various embodiments of the wind turbine control method of the present invention, and will not be repeated here.

[0155] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0156] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0157] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, or the area that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in the various embodiments of the present invention.

[0158] The above are merely preferred embodiments of the present invention and do not limit the scope of the patent. Any equivalent structural or procedural transformations made based on the description and drawings of the present invention, or direct or indirect applications in other related technical fields, are similarly included within the scope of patent protection of the present invention.

Claims

1. A wind turbine control method, characterized in that, The wind turbine control method includes the following steps: Power consumption of electrical equipment in wind turbine generators is obtained using power line carrier communication. Based on the power consumption of the equipment, a power consumption analysis of the electrical equipment is performed to obtain the power consumption analysis results of the electrical equipment. If the power consumption analysis result indicates high power consumption, detect whether the electrical equipment has malfunctioned; If the electrical equipment is not faulty, adjust the equipment parameters of the electrical equipment to bring it to its theoretical working state; The step of performing power consumption analysis on the electrical equipment based on the power consumption of the equipment to obtain the power consumption analysis results of the electrical equipment includes: The current power consumption data of the electrical equipment is determined based on the power consumption of the equipment, and the current working state of the electrical equipment is determined based on the current power consumption data, wherein the current working state is a high power consumption state or a non-high power consumption state; Based on the power generation of the wind turbine and the meteorological data of the external environment where the wind turbine is located, the theoretical operating state of the electrical equipment is determined, wherein the theoretical operating state is either a high power consumption state or a non-high power consumption state. If the current working state is inconsistent with the theoretical working state, then if the current working state is high power consumption, the power consumption analysis result is determined to be high power consumption.

2. A wind turbine control method according to claim 1, wherein, The step of determining the current power consumption data of the electrical equipment based on the power consumption of the equipment includes: Determine the excess power consumption exceeding the preset power threshold from the power consumption of the device within the preset detection period prior to the current moment; Based on each of the above-limit electricity consumptions and the time corresponding to each of the above-limit electricity consumptions, the duration of the above-limit electricity consumption of the electrical equipment is calculated. The excess power consumption and the excess power consumption duration are used as the current power consumption data of the electrical equipment.

3. The wind turbine control method of claim 1, wherein, The step of determining the theoretical operating state of the electrical equipment based on the power generation of the wind turbine and meteorological data of the external environment where the wind turbine is located includes: Based on the power generation of the wind turbine and the meteorological data of the external environment where the wind turbine is located, the theoretical operating parameters of the electrical equipment are determined. The theoretical operating state of the electrical equipment is determined based on the theoretical operating parameters.

4. A wind turbine control method according to claim 3, wherein, The step of determining the theoretical operating state of the electrical equipment based on the power generation of the wind turbine and meteorological data of the external environment where the wind turbine is located includes: The power generation of the wind turbine and the meteorological data of the external environment where the wind turbine is located are input into the trained target network model to obtain the theoretical operating parameters of the electrical equipment.

5. A wind turbine control method according to claim 3, wherein, The wind turbine control method also includes: The power generation of the wind turbine and the meteorological data of the external environment where the wind turbine is located are obtained as training sample data, and the operating parameters of the electrical equipment are used as training labels. The target network model is obtained by training the model based on the training sample data and the training labels.

6. A wind turbine control device, characterized in that, The wind turbine control device includes: The acquisition module is used to acquire the power consumption of electrical equipment in the wind turbine based on power line carrier communication. An analysis module is used to perform power consumption analysis on the electrical equipment based on the power consumption of the equipment, and obtain the power consumption analysis result of the electrical equipment, wherein the power consumption analysis result is either high power consumption or normal power consumption; The adjustment module is used to detect whether the electrical equipment has malfunctioned when the power consumption analysis result indicates high power consumption; The adjustment module is used to adjust the equipment parameters of the electrical equipment to bring it to its theoretical working state if the electrical equipment does not malfunction. The analysis module is configured to determine the current power consumption data of the electrical equipment based on the power consumption of the equipment, and determine the current operating state of the electrical equipment based on the current power consumption data, wherein the current operating state is a high power consumption state or a non-high power consumption state; based on the power generation of the wind turbine and the meteorological data of the external environment where the wind turbine is located, determine the theoretical operating state of the electrical equipment, wherein the theoretical operating state is a high power consumption state or a non-high power consumption state; if the current operating state is inconsistent with the theoretical operating state, then if the current operating state is a high power consumption state, the power consumption analysis result is determined to be high power consumption.

7. A wind turbine generator control device characterized by comprising: The wind turbine control device includes: a memory, a processor, and a wind turbine control program stored in the memory and executable on the processor. When the wind turbine control program is executed by the processor, it implements the steps of the wind turbine control method as described in any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a wind turbine control program, which, when executed by a processor, implements the steps of the wind turbine control method as described in any one of claims 1 to 5.

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