CN117145709A - Wind turbine generator control method, device, equipment and computer readable storage medium - Google Patents
Wind turbine generator control method, device, equipment and computer readable storage medium Download PDFInfo
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- CN117145709A CN117145709A CN202311133670.6A CN202311133670A CN117145709A CN 117145709 A CN117145709 A CN 117145709A CN 202311133670 A CN202311133670 A CN 202311133670A CN 117145709 A CN117145709 A CN 117145709A
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- 238000012549 training Methods 0.000 claims description 42
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F03—MACHINES OR ENGINES FOR LIQUIDS; WIND, SPRING, OR WEIGHT MOTORS; PRODUCING MECHANICAL POWER OR A REACTIVE PROPULSIVE THRUST, NOT OTHERWISE PROVIDED FOR
- F03D—WIND MOTORS
- F03D17/00—Monitoring or testing of wind motors, e.g. diagnostics
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F03—MACHINES OR ENGINES FOR LIQUIDS; WIND, SPRING, OR WEIGHT MOTORS; PRODUCING MECHANICAL POWER OR A REACTIVE PROPULSIVE THRUST, NOT OTHERWISE PROVIDED FOR
- F03D—WIND MOTORS
- F03D7/00—Controlling wind motors
- F03D7/02—Controlling wind motors the wind motors having rotation axis substantially parallel to the air flow entering the rotor
- F03D7/04—Automatic control; Regulation
- F03D7/042—Automatic control; Regulation by means of an electrical or electronic controller
- F03D7/048—Automatic control; Regulation by means of an electrical or electronic controller controlling wind farms
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F03—MACHINES OR ENGINES FOR LIQUIDS; WIND, SPRING, OR WEIGHT MOTORS; PRODUCING MECHANICAL POWER OR A REACTIVE PROPULSIVE THRUST, NOT OTHERWISE PROVIDED FOR
- F03D—WIND MOTORS
- F03D80/00—Details, components or accessories not provided for in groups F03D1/00 - F03D17/00
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Abstract
The invention relates to the technical field of wind power generation, in particular to a wind turbine generator control method, a device, equipment and a computer readable storage medium, wherein the method comprises the following steps: acquiring the equipment power consumption of the electrical equipment in the wind turbine generator based on the power carrier mode; performing power consumption analysis on the electrical equipment based on the equipment power consumption to obtain a power consumption analysis result of the electrical equipment, wherein the power consumption analysis result is high power consumption or normal power consumption; and when the power consumption analysis result is high power consumption, adjusting the equipment parameters of the electrical equipment. According to the invention, the self-consumption of the electrical equipment is automatically managed by adjusting the working state of the electrical equipment when the electrical equipment consumes high power, and the management efficiency of the self-consumption management of the electrical equipment is improved, so that the management efficiency of the self-consumption management of the wind turbine generator is improved.
Description
Technical Field
The present invention relates to the field of wind power generation technologies, and in particular, to a method, an apparatus, a device, and a computer readable storage medium for controlling a wind turbine generator.
Background
The wind power generation is a power generation process of converting wind kinetic energy into mechanical kinetic energy through a wind generating set and then converting the mechanical kinetic energy into electric kinetic energy, and each system device of the wind generating set needs to consume electric energy in the operation process, namely, the wind generating set has self-power consumption. In recent years, with the continuous improvement of the power generation requirement of wind generators, the installed capacity of the wind generator is gradually increased, so that the self-consumption of the wind generator is also continuously increased, and the self-consumption of the wind generator directly influences the power generation efficiency of the wind generator.
At present, aiming at the problem of self-consumption of a wind generating set, the method mainly adopted is as follows: and a monitoring module is arranged in the wind turbine generator to monitor the self-consumption of the electrical equipment in the wind turbine generator, and then maintenance personnel can check and reform the electrical equipment with higher self-consumption. However, the electrical equipment of the wind turbine generator needs to be managed manually, and management efficiency is low.
Disclosure of Invention
The invention mainly aims to provide a control method, a device, equipment and a computer readable storage medium for a wind turbine generator, which are used for automatically managing the self-power consumption of electrical equipment by adjusting the electrical equipment when the electrical equipment consumes high power, so that the management efficiency of the self-power consumption management of the wind turbine generator is improved.
In order to achieve the above purpose, the invention provides a wind turbine control method, which comprises the following steps:
acquiring the equipment power consumption of the electrical equipment in the wind turbine generator based on the power carrier mode;
performing power consumption analysis on the electrical equipment based on the equipment power consumption to obtain a power consumption analysis result of the electrical equipment, wherein the power consumption analysis result is high power consumption or normal power consumption;
and when the power consumption analysis result is high power consumption, adjusting the equipment parameters of the electrical equipment.
Optionally, the step of performing power consumption analysis on the electrical device based on the device power consumption to obtain a power consumption analysis result of the electrical device includes:
determining current electricity consumption data of the electrical equipment based on the equipment electricity consumption, and determining the current working state of the electrical equipment according to the current electricity consumption data;
determining a theoretical working state of the electrical equipment based on the generated energy of the wind turbine and meteorological data of the external environment where the wind turbine is located;
if the current working state is inconsistent with the theoretical working state, determining that the power consumption analysis result of the electrical equipment is high power consumption;
And if the current working state is consistent with the theoretical working state, determining that the power consumption analysis result is normal power consumption.
Optionally, the step of adjusting the device parameter of the electrical device when the power consumption analysis result is high power consumption includes:
detecting whether the electrical equipment fails or not under the condition that the power consumption analysis result is high power consumption;
and if the electrical equipment does not fail, adjusting equipment parameters of the electrical equipment to adjust the electrical equipment to the theoretical working state.
Optionally, the step of determining current electricity consumption data of the electrical device based on the device electricity consumption amount includes:
determining out-of-limit electricity consumption exceeding a preset electricity consumption threshold from the electricity consumption of the equipment in a preset detection time before the current moment;
calculating out-of-limit electricity consumption time of the electrical equipment based on the out-of-limit electricity consumption and the corresponding time of the out-of-limit electricity consumption;
and taking the over-limit electricity consumption and the over-limit electricity consumption time as current electricity consumption data of the electrical equipment.
Optionally, the step of determining the theoretical working state of the electrical device based on the generated energy of the wind turbine and weather data of an external environment where the wind turbine is located includes:
Determining theoretical working parameters of the electrical equipment based on the generated energy of the wind turbine and meteorological data of the external environment of the wind turbine;
and determining a theoretical working state of the electrical equipment based on the theoretical working parameter.
Optionally, the step of determining the theoretical working state of the electrical device based on the generated energy of the wind turbine and weather data of an external environment where the wind turbine is located includes:
and inputting the generated energy of the wind turbine and the meteorological data of the external environment of the wind turbine into a target network model after training is completed, and obtaining theoretical working parameters of the electrical equipment.
Optionally, the wind turbine generator control method further includes:
and acquiring the generated energy of the wind turbine and the meteorological data of the external environment where the wind turbine is located as training sample data, and taking the working parameters of the electrical equipment as training labels, so as to perform model training according to the training sample data and the training labels to obtain a target network model.
In order to achieve the above object, the present invention further provides a wind turbine control device, including:
The acquisition module is used for acquiring the equipment power consumption of the electrical equipment in the wind turbine generator based on the mode of the power carrier;
the analysis module is used for carrying out power consumption analysis on the electrical equipment based on the equipment power consumption to obtain a power consumption analysis result of the electrical equipment, wherein the power consumption analysis result is high power consumption or normal power consumption;
and the adjusting module is used for adjusting the equipment parameters of the electrical equipment when the power consumption analysis result is high power consumption.
In order to achieve the above object, the present invention further provides a wind turbine control apparatus, including: the wind turbine control system comprises a memory, a processor and a wind turbine control program which is stored in the memory and can run on the processor, wherein the wind turbine control program realizes the steps of the wind turbine control method when being executed by the processor.
In addition, in order to achieve the above object, the present invention also proposes a computer readable storage medium, on which a wind turbine control program is stored, which when executed by a processor, implements the steps of the wind turbine control method as described above.
According to the method, the device power consumption of the electrical devices in the wind turbine generator is obtained in a mode based on the power carrier; performing power consumption analysis on the electrical equipment based on the equipment power consumption to obtain a power consumption analysis result of the electrical equipment, wherein the power consumption analysis result is high power consumption or normal power consumption; and when the power consumption analysis result is high power consumption, adjusting the equipment parameters of the electrical equipment. According to the invention, the self-power consumption of the electrical equipment is automatically managed by adjusting the electrical equipment when the electrical equipment consumes high power, and compared with the method for optimizing and modifying the electrical equipment manually, the method can improve the management efficiency of the self-power consumption management of the electrical equipment, thereby improving the management efficiency of the self-power consumption management of the wind turbine generator.
Drawings
FIG. 1 is a schematic diagram of a hardware operating environment according to an embodiment of the present invention;
FIG. 2 is a flowchart of a first embodiment of a wind turbine control method according to the present invention;
FIG. 3 is a schematic diagram of a wind turbine system according to an embodiment of the wind turbine control method of the present invention;
FIG. 4 is a flowchart of a second embodiment of a wind turbine control method according to the present invention;
FIG. 5 is a flowchart of a third embodiment of a wind turbine control method according to the present invention;
FIG. 6 is a functional block diagram of a wind turbine control system according to a preferred embodiment of the present invention.
The achievement of the objects, functional features and advantages of the present invention will be further described with reference to the accompanying drawings, in conjunction with the embodiments.
Detailed Description
It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
Referring to fig. 1, fig. 1 is a schematic device structure of a hardware running environment according to an embodiment of the present invention.
It should be noted that, in the wind turbine generator control device according to the embodiment of the present invention, the wind turbine generator control device may be a controller of a wind turbine generator, or may be a device that establishes communication connection with a controller of a wind turbine generator, for example, a device such as a personal computer, a smart phone, a server, etc., which is not limited herein.
As shown in fig. 1, the wind turbine control apparatus may include: a processor 1001, such as a CPU, a network interface 1004, a user interface 1003, a memory 1005, a communication bus 1002. Wherein the communication bus 1002 is used to enable connected communication between these components. The user interface 1003 may include a Display, an input unit such as a Keyboard (Keyboard), and the optional user interface 1003 may further include a standard wired interface, a wireless interface. The network interface 1004 may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface). The memory 1005 may be a high-speed RAM memory or a stable memory (non-volatile memory), such as a disk memory. The memory 1005 may also optionally be a storage device separate from the processor 1001 described above.
It will be appreciated by those skilled in the art that the arrangement shown in FIG. 1 is not limiting of a wind turbine control device and may include more or fewer components than shown, or may be combined with certain components, or a different arrangement of components.
As shown in fig. 1, an operating system, a network communication module, a user interface module, and a wind turbine control program may be included in a memory 1005, which is a type of computer storage medium. The operating system is a program that manages and controls the hardware and software resources of the device, supporting the operation of the wind turbine control program and other software or programs. In the device shown in fig. 1, the user interface 1003 is mainly used for data communication with the client; the network interface 1004 is mainly used for establishing communication connection with a server; and the processor 1001 may be configured to call a wind turbine control program stored in the memory 1005, and perform the following operations:
acquiring the equipment power consumption of the electrical equipment in the wind turbine generator based on the power carrier mode;
performing power consumption analysis on the electrical equipment based on the equipment power consumption to obtain a power consumption analysis result of the electrical equipment, wherein the power consumption analysis result is high power consumption or normal power consumption;
And when the power consumption analysis result is high power consumption, adjusting the equipment parameters of the electrical equipment.
Further, the step of performing power consumption analysis on the electrical device based on the device power consumption to obtain a power consumption analysis result of the electrical device includes:
determining current electricity consumption data of the electrical equipment based on the equipment electricity consumption, and determining the current working state of the electrical equipment according to the current electricity consumption data;
determining a theoretical working state of the electrical equipment based on the generated energy of the wind turbine and meteorological data of the external environment where the wind turbine is located;
if the current working state is inconsistent with the theoretical working state, determining that the power consumption analysis result of the electrical equipment is high power consumption;
and if the current working state is consistent with the theoretical working state, determining that the power consumption analysis result is normal power consumption.
Further, the step of adjusting the device parameter of the electrical device when the power consumption analysis result is high power consumption includes:
detecting whether the electrical equipment fails or not under the condition that the power consumption analysis result is high power consumption;
And if the electrical equipment does not fail, adjusting equipment parameters of the electrical equipment to adjust the electrical equipment to the theoretical working state.
Further, the step of determining current electricity consumption data of the electrical device based on the device electricity consumption amount includes:
determining out-of-limit electricity consumption exceeding a preset electricity consumption threshold from the electricity consumption of the equipment in a preset detection time before the current moment;
calculating out-of-limit electricity consumption time of the electrical equipment based on the out-of-limit electricity consumption and the corresponding time of the out-of-limit electricity consumption;
and taking the over-limit electricity consumption and the over-limit electricity consumption time as current electricity consumption data of the electrical equipment.
Further, the step of determining the theoretical working state of the electrical equipment based on the generated energy of the wind turbine and the meteorological data of the external environment where the wind turbine is located includes:
determining theoretical working parameters of the electrical equipment based on the generated energy of the wind turbine and meteorological data of the external environment of the wind turbine;
and determining a theoretical working state of the electrical equipment based on the theoretical working parameter.
Further, the step of determining the theoretical working state of the electrical equipment based on the generated energy of the wind turbine and the meteorological data of the external environment where the wind turbine is located includes:
and inputting the generated energy of the wind turbine and the meteorological data of the external environment of the wind turbine into a target network model after training is completed, and obtaining theoretical working parameters of the electrical equipment.
Further, the processor 1001 may be configured to call a wind turbine control program stored in the memory 1005, and perform the following operations:
and acquiring the generated energy of the wind turbine and the meteorological data of the external environment where the wind turbine is located as training sample data, and taking the working parameters of the electrical equipment as training labels, so as to perform model training according to the training sample data and the training labels to obtain a target network model.
Based on the structure, various embodiments of a wind turbine control method are provided.
Referring to fig. 2, fig. 2 is a schematic flow chart of a first embodiment of a wind turbine control method according to the present invention.
The embodiments of the present invention provide embodiments of a method of controlling a wind turbine, and it should be noted that although a logic sequence is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than that shown or described herein. In this embodiment, the execution main body of the wind turbine control method may be a control device of a wind turbine, and the control device of the wind turbine may be a controller of the wind turbine, or may be a device that establishes communication connection with the controller of the wind turbine, for example, a personal computer, a smart phone, a server, etc., which is not limited in this embodiment, and for convenience of description, explanation of each embodiment by the execution main body is omitted. In this embodiment, the method for controlling a wind turbine includes:
Step S10, acquiring the equipment power consumption of the electrical equipment in the wind turbine based on the power carrier mode;
the electric energy loss of the wind turbine generator refers to the electric energy loss generated in the process of converting wind energy into electric energy of the wind turbine generator, and the electric energy loss of the wind turbine generator is mainly the production electricity consumption of system equipment and can be mainly divided into two parts of power generation and transmission loss and auxiliary power supply system electric energy loss. The power generation and transmission loss, namely the loss of electric energy in the processes of generation, conversion and transmission, is mainly the electric energy loss of a generator set, a frequency converter, a tower cylinder power cable and the like. The electric energy loss of the auxiliary power supply system is mainly the electric energy loss of electric equipment, including the electric energy loss of the electric equipment such as a gear box, a pitch system, a yaw system, a temperature control system, a heater and the like. The electrical energy loss of the electrical equipment is usually related to the operation state of the electrical equipment, for example, the internal temperature of the gearbox fluctuates greatly when the gearbox works, and the lubrication cooling system and the heating system need to be started for temperature maintenance, so that the electrical energy loss can be generated; for another example, in order to control the effective windward area by controlling the angle of the fan blade, the pitch angle of the variable-pitch motor is easy to be frequently adjusted to generate additional electric energy loss before the rated power of the wind turbine is not reached if the control strategy is set unreasonably.
Based on the above, the present embodiment provides a method for efficiently and accurately managing the power consumption of a wind turbine generator. Specifically, in this embodiment, an electrical device node is provided with an electrical device monitoring device, and the electrical device monitoring device sends the monitored electrical quantity to the control device by means of a power carrier. For example, in an embodiment, referring to fig. 3, an electrical device node of a wind turbine system may be provided with an electrical device monitoring device, where the electrical device in the wind turbine shown in fig. 3 includes a generator fan, a yaw motor, a pitch system (i.e., pitch shown in fig. 3), a slip ring, a water cooling system, a current transformation system (i.e., water cooling, current transformation system shown in fig. 3), a transformer, a generator (i.e., G shown in fig. 3), and a switchgear (i.e., K shown in fig. 3).
In this embodiment, based on a power carrier mode, device power consumption of electrical devices in the wind turbine generator is obtained. The specific process of the power carrier wave is as follows: the electric quantity monitoring device converts the monitored electric quantity into a modulation signal through processing and encoding of an analog signal or a digital signal, and sends the modulation signal to the control equipment as a power carrier signal, and in the modulation process, different modes such as amplitude modulation, frequency modulation, phase modulation and the like can be used for controlling the transmission characteristics of the signal; transmitting the modulation signal to control equipment through a circuit of the wind turbine generator; the control device needs to demodulate, amplify, filter and the like the power carrier signal to obtain the electric quantity.
According to the embodiment, the information transmission is carried out through the power carrier, so that the arrangement of a communication bus in the wind turbine can be reduced, the electric energy loss of a circuit is reduced, the self-power consumption of the wind turbine is reduced, and the power networking efficiency of the wind turbine is improved.
Step S20, carrying out power consumption analysis on the electrical equipment based on the equipment power consumption to obtain a power consumption analysis result of the electrical equipment, wherein the power consumption analysis result is high power consumption or normal power consumption;
in this embodiment, after the electricity consumption of the device is obtained, the electricity consumption analysis of the electrical device may be performed according to the electricity consumption of the device, so as to obtain the electricity consumption analysis result of the electrical device.
In a specific embodiment, the power consumption analysis result of the electrical equipment may be determined by a threshold value judgment mode; the current operating state of the electrical device may also be determined by other possible means, for example by means of deep learning, etc., and is not limited in particular here. For example, in a possible implementation, it may be detected whether the device power consumption at each moment exceeds a preset threshold; if the power consumption of the device at each moment exceeds the preset threshold, determining that the power consumption analysis result of the electrical device is in a high power consumption state, and further, in a feasible implementation manner, determining that the power consumption analysis result of the electrical device is in a high power consumption state when the continuous moment when the power consumption of the device exceeds the threshold exceeds the preset moment threshold is detected.
And step S30, adjusting the equipment parameters of the electric equipment when the power consumption analysis result is high power consumption.
In this embodiment, when the power consumption analysis result is high power consumption, the device parameters of the electrical device are adjusted. Further, in another possible implementation manner, the type of the electrical device may be adjusted, which is not limited herein, and may be set according to actual requirements.
In the embodiment, the equipment power consumption of the electrical equipment in the wind turbine generator is obtained in a mode based on the power carrier; carrying out power consumption analysis on the electrical equipment based on the equipment power consumption to obtain a power consumption analysis result of the electrical equipment; when the power consumption analysis result is high power consumption, the device parameters of the electrical device are adjusted. According to the embodiment, the self-power consumption of the electrical equipment is automatically managed by adjusting the electrical equipment when the electrical equipment consumes high power, and compared with the method that the electrical equipment is optimized and modified manually, the self-power consumption management efficiency of the electrical equipment can be improved, so that the self-power consumption management efficiency of the wind turbine generator is improved. In addition, the embodiment can control the self-power consumption of the electrical equipment by adjusting the electrical equipment when the electrical equipment consumes high power, improve the networking efficiency of the fan power unit and reduce the self-power consumption of the fan power unit.
Further, based on the above first embodiment, a second embodiment of the wind turbine generator control method according to the present invention is provided, and referring to fig. 4, in this embodiment, step S20 includes:
step S201, determining current electricity utilization data of the electrical equipment based on the equipment electricity utilization amount, and determining the current working state of the electrical equipment according to the current electricity utilization data;
in the present embodiment, when an instruction for power consumption analysis is triggered, current power consumption data of the electrical device is determined based on the device power consumption amount to evaluate the operating state of the electrical device from the power consumption data (hereinafter referred to as current operating state to show distinction).
In this embodiment, the current working state of the electrical device is: the actual working state of the electrical equipment at the current moment can be a high power consumption state or a normal high power consumption state, and in a specific embodiment, the current working state of the electrical equipment can be determined in a threshold judgment mode; the current operating state of the electrical device may also be determined by other possible means, for example by means of deep learning, etc., and is not limited in particular here.
Step S202, determining a theoretical working state of the electrical equipment based on the generated energy of the wind turbine and weather data of the external environment where the wind turbine is located;
In this embodiment, when it is determined that the wind turbine generator triggers an instruction for adjusting the working state of the electrical device, the generated energy of the wind turbine generator and weather data of an external environment where the wind turbine generator is located are also obtained, and then the theoretical working state of the electrical device is determined according to the generated energy of the wind turbine generator and the weather data of the external environment where the wind turbine generator is located.
In this embodiment, the theoretical operating states of the electrical device are: when the working state of the electric equipment is matched with the generated energy of the wind turbine generator and the meteorological data of the external environment, the theoretical working state can be a high power consumption state or a non-high power consumption state. In a possible implementation manner, the theoretical working parameters of the electrical equipment can be determined based on the generated energy of the wind turbine and the meteorological data of the external environment where the wind turbine is located, and then the theoretical working state of the electrical equipment is determined based on the theoretical working parameters; in another possible implementation manner, the power generation and meteorological data can also be directly input into a pre-trained deep learning model through a deep learning mode to obtain a theoretical working state, and the theoretical working state is not limited herein, and can be specifically set according to actual requirements.
Step S203, if the current working state is inconsistent with the theoretical working state, determining that the power consumption analysis result of the electrical device is high power consumption;
In this embodiment, after determining the current working state and the theoretical working state, whether the current working state is consistent with the theoretical working state is detected, and if the current working state is inconsistent with the theoretical working state, it is determined that the working power consumption of the electrical device is matched with the actual power generation of the wind turbine generator, so that it is determined that the power consumption analysis result of the electrical device is high power consumption.
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 in a high power consumption state, and the theoretical working state is not in a high power consumption state, at this time, it is determined that the electrical equipment has power loss beyond production, which may be caused by unreasonable control parameter setting of the electrical equipment, for example, may be caused by too frequent equipment working of the electrical equipment, and at this time, it is determined that the power consumption analysis result of the electrical equipment is high power consumption.
Further, in some scenarios, when the actual model of the electrical device is inconsistent with the model of the electrical device recorded by the control device, there may be: the current operating state is not a high power consumption state, but the theoretical operating state is a high power consumption state. In order to distinguish the situation that the two current working states are inconsistent with the theoretical working state, when the current working state is determined to be inconsistent with the theoretical working state, whether the current working state is in a high power consumption state or not can be detected; if the current working state is a high power consumption state, determining that the power consumption analysis result of the electrical equipment is high power consumption; if the current working state is not the high power consumption state, the record of the control device is adjusted, or the device is replaced to select the type, compared with the mode that the current working state is not the high power consumption state and is not processed, the embodiment can reduce the energy consumption of the electrical device and reduce the self power consumption of the wind turbine generator.
Step S204, if the current working state is consistent with the theoretical working state, determining that the power consumption analysis result is normal power consumption.
If the current working state is consistent with the theoretical working state, the working power consumption of the electrical equipment is determined to be matched with the actual power generation of the wind turbine generator, and at the moment, the power consumption analysis result is determined to be normal power consumption.
Further, in a possible embodiment, step S30 includes:
step S301, detecting whether the electrical equipment is in fault or not when the power consumption analysis result is high power consumption;
since high power consumption may occur when the electrical equipment is faulty, for example, high power consumption may occur in the electrical equipment due to aging of parts or the like, in order to reduce invalid management of the electrical equipment and improve management accuracy of the electrical equipment, when determining that the wind turbine generator triggers an instruction for adjusting the working state of the electrical equipment, the embodiment detects whether the electrical equipment is faulty or not, and adjusts the electrical equipment when determining that the electrical equipment is faulty.
And step S302, if the electrical equipment does not fail, adjusting equipment parameters of the electrical equipment to adjust the electrical equipment to the theoretical working state.
In this embodiment, if the electrical device does not fail, it is determined that the high power consumption of the electrical device is not due to the failure of the electrical device, and at this time, the electrical device may be adjusted, specifically, in this embodiment, the device parameters of the electrical device are adjusted so as to adjust the electrical device to the theoretical operating state.
Further, in a possible implementation manner, if the electrical equipment fails, a maintainer is reminded of replacing the equipment so as to ensure safe operation of the wind turbine.
In the present embodiment, by adjusting the device parameters of the electrical device to adjust the electrical device to the theoretical operating state, compared with the mode selection of adjusting the electrical device, the present embodiment can improve the adjustment efficiency, control the self-power consumption of the electrical device, and reduce the cost of the fan power unit.
In the embodiment, 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 according to the current power consumption data; determining a theoretical working state of the electrical equipment based on the generated energy of the wind turbine and meteorological data of the external environment where the wind turbine is located; if the current working state is inconsistent with the theoretical working state, determining that the power consumption analysis result of the electrical equipment is high power consumption; and if the current working state is consistent with the theoretical working state, determining that the power consumption analysis result is normal power consumption. According to the embodiment, by comparing the current working state with the theoretical working state, whether the working power consumption of the electrical equipment is matched with the actual power generation of the wind turbine generator is determined, so that whether the electrical equipment is in a high power consumption state or not is determined, and compared with the power consumption analysis performed through threshold judgment, the accuracy of a power consumption analysis result can be improved, and therefore the management accuracy of the self-power consumption management of the wind turbine generator is improved; compared with the power consumption analysis by the deep learning mode, the method and the device can reduce analysis steps and improve the power consumption analysis efficiency, so that the management efficiency of the self-power consumption management of the wind turbine generator is improved.
Further, based on the first and/or second embodiments, a third embodiment of the wind turbine control method according to the present invention is provided, and referring to fig. 5, in this embodiment, step S201 includes:
step 2011, determining an overrun electricity consumption exceeding a preset electricity consumption threshold from the electricity consumption of the equipment in a preset detection time before the current moment;
in this embodiment, the excess electricity consumption exceeding the preset electricity consumption threshold is determined from the electricity consumption of the device within the preset detection period before the current time. The preset detection duration can be set according to actual requirements, and is not limited herein.
Step S2012, calculating an overrun electricity consumption duration of the electrical device based on each overrun electricity consumption and a time corresponding to each overrun electricity consumption;
and calculating out the overrun electricity consumption time length of the electrical equipment based on each overrun electricity consumption and the corresponding time of each overrun electricity consumption.
And step S2013, taking the reference electricity consumption and the electricity consumption duration as current electricity consumption data of the electrical equipment.
And taking the over-limit electricity consumption and the over-limit electricity consumption time as current electricity consumption data of the electrical equipment. In this embodiment, the power consumption exceeding and the power consumption exceeding duration are used as the current power consumption data of the electrical device, and compared with the power consumption only used as the current power consumption data, the current working state obtained by the method and the device can be more accurate, so that the accuracy of wind turbine generator set management is improved.
Further, in a possible embodiment, step S202 includes;
step S2021, determining theoretical working parameters of the electrical equipment based on the generated energy of the wind turbine and meteorological data of the external environment of the wind turbine;
in this embodiment, after the generated energy of the wind turbine generator and the weather data of the external environment where the generated energy and the weather data are located are obtained, the equipment parameters of the electrical equipment in the scene are determined based on the generated energy and the weather data, and are hereinafter referred to as theoretical working parameters to show distinction.
In a possible implementation manner, the generated energy and the meteorological data can be input into a target network model after training to obtain theoretical working parameters of the electrical equipment, wherein the target network model is obtained by training by taking the working parameters of the electrical equipment as training labels and taking the generated energy of the wind turbine and the meteorological data of the external environment as input data.
In another possible embodiment, the device characteristic curves may be constructed for each electrical device by using the device parameters, the power generation amount and the meteorological data, and in this embodiment, the corresponding device parameters are found in the device characteristic curves of the electrical devices based on the power generation amount and the meteorological data, and the corresponding device parameters are obtained as theoretical working parameters. In this embodiment, the device parameters in the characteristic curves corresponding to different electrical devices are different, and the specific device parameters may be determined according to the parameters affecting the self-power consumption of the electrical devices, for example, when the gearbox works, the internal temperature fluctuation is large, and the lubrication cooling system and the heating system need to be started to perform temperature maintenance, so that electric energy loss may be generated, and therefore, the device parameters corresponding to the gearbox, the temperature control system and the heating system may be the temperature fluctuation range; the electric energy loss of the pitch system depends on the change of wind direction, the pitch motor needs to control the effective windward area by controlling the angle of the blades so as to ensure the output power of the wind turbine, if the control strategy is set unreasonably, the extra electric energy loss is easily generated by frequently adjusting the pitch angle before the wind turbine reaches the rated power, so that the equipment parameters corresponding to the pitch system can be the angle of the blades; when the wind speed does not reach the cut-in wind speed, unnecessary electric energy loss is increased if frequent wind facing is performed on the yaw system, so that the equipment parameters corresponding to the yaw system can be the wind facing times, and specifically, other electric equipment and corresponding equipment parameters can also be included, and the yaw system is not limited.
Step S2022 determines a theoretical operating state of the electrical device based on the theoretical operating parameter.
In this embodiment, the theoretical operating state of the electrical device is determined based on the theoretical operating parameter. In a possible implementation manner, a mapping relationship between theoretical working parameters and theoretical working states can be established, and the theoretical working states corresponding to the theoretical working parameters are determined according to the mapping relationship; in another possible implementation manner, the working parameters and the electrical equipment are used as input data, the working states are used as training labels, a neural network model is trained, the theoretical working states of the electrical equipment are determined according to the theoretical working parameters, and the specific training process and the neural network structure are not limited herein.
In the embodiment, theoretical working parameters of the electrical equipment are determined based on the generated energy of the wind turbine and meteorological data of the external environment where the wind turbine is located; a theoretical operating state of the electrical device is determined based on the theoretical operating parameter. According to the embodiment, the actual working state of the electrical equipment is adjusted based on the theoretical working state, the self-power consumption of the electrical equipment is automatically managed, and compared with the method for optimizing and modifying the electrical equipment manually, the method and the device can improve the management efficiency and the management accuracy of the self-power consumption management of the wind turbine.
Further, in a possible embodiment, step S2021 includes:
and step S20211, inputting the generated energy of the wind turbine and the meteorological data of the external environment of the wind turbine into a target network model after training is completed, and obtaining theoretical working parameters of the electrical equipment.
In the embodiment, the theoretical working parameters are determined based on the neural network model, and compared with the theoretical working parameters determined through the characteristic curve, the theoretical working parameters obtained in the embodiment are more accurate, so that the control of the electrical equipment is more accurate, and the control accuracy of the control of the wind turbine generator is improved.
Specifically, in this embodiment, the generated energy of the wind turbine and the meteorological data of the external environment where the wind turbine is located are input into a trained target network model to obtain theoretical working parameters of the electrical equipment, where the target network model uses the working parameters of the electrical equipment as training labels, and uses the generated energy of the wind turbine and the meteorological data of the external environment as input data to train.
Further, in a possible implementation manner, the wind turbine control method further includes:
and S40, acquiring the generated energy of the wind turbine and the meteorological data of the external environment where the wind turbine is located as training sample data, and taking the working parameters of the electrical equipment as training labels, so as to perform model training according to the training sample data and the training labels to obtain a target network model.
In this embodiment, the generated energy of the wind turbine generator and the weather data of the external environment where the wind turbine generator is located are obtained as training sample data, and the working parameters of the electrical equipment are used as training labels, so that model training is performed according to the training sample data and the training labels to obtain a target network model. To determine theoretical operating parameters of the electrical device via the target network model.
In this embodiment, the process of inputting the generated energy of the wind turbine and the meteorological data of the external environment where the wind turbine is located into the trained target network model may be: inputting generated energy and meteorological data into cascaded convolution blocks to obtain characteristics, wherein the input data of a first convolution block in the cascade are generated energy and meteorological data, and the input data of all convolution blocks except the first convolution block are output data of a previous convolution block; inputting the features into an attention mechanism layer, and weighting the features through the attention mechanism layer to obtain weighted features; and the fusion characteristics and the weighting characteristics are obtained, and the fusion characteristics are input into a full-connection layer to obtain theoretical working parameters.
In this embodiment, by using each of the excess electricity consumption and the excess electricity consumption time length as current electricity consumption data of the electrical device, compared with using only the electricity consumption as current electricity consumption data, the present working state obtained by the present working state obtaining method is more accurate, so that accuracy of wind turbine generator set management is improved.
In addition, an embodiment of the present invention further provides a wind turbine generator control device, referring to fig. 6, where the wind turbine generator control device includes:
the acquisition module 10 is used for acquiring the equipment power consumption of the electrical equipment in the wind turbine generator based on the power carrier mode;
the analysis module 20 is used for carrying out power consumption analysis on the electrical equipment based on the equipment power consumption to obtain a power consumption analysis result of the electrical equipment, wherein the power consumption analysis result is high power consumption or normal power consumption;
the adjustment module 30 adjusts the device parameters of the electrical device when the power consumption analysis result is high power consumption.
Further, the analysis module 20 is further configured to:
determining current electricity consumption data of the electrical equipment based on the equipment electricity consumption, and determining the current working state of the electrical equipment according to the current electricity consumption data;
Determining a theoretical working state of the electrical equipment based on the generated energy of the wind turbine and meteorological data of the external environment where the wind turbine is located;
if the current working state is inconsistent with the theoretical working state, determining that the power consumption analysis result of the electrical equipment is high power consumption;
and if the current working state is consistent with the theoretical working state, determining that the power consumption analysis result is normal power consumption.
Further, the adjusting module 30 is further configured to:
detecting whether the electrical equipment fails or not under the condition that the power consumption analysis result is high power consumption;
and if the electrical equipment does not fail, adjusting equipment parameters of the electrical equipment to adjust the electrical equipment to the theoretical working state.
Further, the analysis module 20 is further configured to:
determining out-of-limit electricity consumption exceeding a preset electricity consumption threshold from the electricity consumption of the equipment in a preset detection time before the current moment;
calculating out-of-limit electricity consumption time of the electrical equipment based on the out-of-limit electricity consumption and the corresponding time of the out-of-limit electricity consumption;
and taking the over-limit electricity consumption and the over-limit electricity consumption time as current electricity consumption data of the electrical equipment.
Further, the analysis module 20 is further configured to:
determining theoretical working parameters of the electrical equipment based on the generated energy of the wind turbine and meteorological data of the external environment of the wind turbine;
and determining a theoretical working state of the electrical equipment based on the theoretical working parameter.
Further, the analysis module 20 is further configured to:
and inputting the generated energy of the wind turbine and the meteorological data of the external environment of the wind turbine into a target network model after training is completed, and obtaining theoretical working parameters of the electrical equipment.
Further, the wind turbine generator control device further comprises a model training module for:
and acquiring the generated energy of the wind turbine and the meteorological data of the external environment where the wind turbine is located as training sample data, and taking the working parameters of the electrical equipment as training labels, so as to perform model training according to the training sample data and the training labels to obtain a target network model.
Embodiments of the wind turbine generator control device of the present invention may refer to embodiments of the wind turbine generator control method of the present invention, and will not be described herein.
In addition, the embodiment of the invention also provides a computer readable storage medium, wherein a wind turbine control program is stored on the storage medium, and the wind turbine control program realizes the steps of a wind turbine control method when being executed by a processor.
Embodiments of the wind turbine control apparatus and the computer readable storage medium of the present invention may refer to embodiments of the wind turbine control method of the present invention, and are not described herein.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The foregoing embodiment numbers of the present invention are merely for the purpose of description, and do not represent the advantages or disadvantages of the embodiments.
From the above description of the embodiments, it will be clear to those skilled in the art that the above-described embodiment method may be implemented by means of software plus a necessary general hardware platform, but of course may also be implemented by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present invention may be embodied essentially or in an area contributing to the prior art in the form of a software product stored in a storage medium (e.g. ROM/RAM, magnetic disk, optical disk) comprising instructions for causing a terminal device (which may be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to perform the method according to the embodiments of the present invention.
The foregoing description is only of the preferred embodiments of the present invention, and is not intended to limit the scope of the invention, but rather is intended to cover any equivalents of the structures or equivalent processes disclosed herein or in the alternative, which may be employed directly or indirectly in other related arts.
Claims (10)
1. The wind turbine generator control method is characterized by comprising the following steps of:
acquiring the equipment power consumption of the electrical equipment in the wind turbine generator based on the power carrier mode;
performing power consumption analysis on the electrical equipment based on the equipment power consumption to obtain a power consumption analysis result of the electrical equipment;
and when the power consumption analysis result is high power consumption, adjusting the equipment parameters of the electrical equipment.
2. The wind turbine control method according to claim 1, wherein the step of performing power consumption analysis on the electrical device based on the device power consumption to obtain a power consumption analysis result of the electrical device includes:
determining current electricity consumption data of the electrical equipment based on the equipment electricity consumption, and determining the current working state of the electrical equipment according to the current electricity consumption data;
Determining a theoretical working state of the electrical equipment based on the generated energy of the wind turbine and meteorological data of the external environment where the wind turbine is located;
if the current working state is inconsistent with the theoretical working state, determining that the power consumption analysis result of the electrical equipment is high power consumption;
and if the current working state is consistent with the theoretical working state, determining that the power consumption analysis result is normal power consumption.
3. The wind turbine control method according to claim 2, wherein the step of adjusting the device parameter of the electrical device when the power consumption analysis result is high power consumption includes:
detecting whether the electrical equipment fails or not under the condition that the power consumption analysis result is high power consumption;
and if the electrical equipment does not fail, adjusting equipment parameters of the electrical equipment to adjust the electrical equipment to the theoretical working state.
4. The wind turbine control method of claim 2, wherein the step of determining current electricity usage data of the electrical device based on the device electricity usage amount comprises:
determining out-of-limit electricity consumption exceeding a preset electricity consumption threshold from the electricity consumption of the equipment in a preset detection time before the current moment;
Calculating out-of-limit electricity consumption time of the electrical equipment based on the out-of-limit electricity consumption and the corresponding time of the out-of-limit electricity consumption;
and taking the over-limit electricity consumption and the over-limit electricity consumption time as current electricity consumption data of the electrical equipment.
5. The wind turbine control method of claim 2, wherein the step of determining the theoretical operating state of the electrical device based on the power generation amount of the wind turbine and weather data of an external environment in which the wind turbine is located comprises:
determining theoretical working parameters of the electrical equipment based on the generated energy of the wind turbine and meteorological data of the external environment of the wind turbine;
and determining a theoretical working state of the electrical equipment based on the theoretical working parameter.
6. The wind turbine control method of claim 5, wherein determining the theoretical operating state of the electrical device based on the power generation of the wind turbine and weather data of an external environment in which the wind turbine is located comprises:
and inputting the generated energy of the wind turbine and the meteorological data of the external environment of the wind turbine into a target network model after training is completed, and obtaining theoretical working parameters of the electrical equipment.
7. The wind turbine control method of claim 5, further comprising:
and acquiring the generated energy of the wind turbine and the meteorological data of the external environment where the wind turbine is located as training sample data, and taking the working parameters of the electrical equipment as training labels, so as to perform model training according to the training sample data and the training labels to obtain a target network model.
8. A wind turbine generator control device, characterized in that the wind turbine generator control device comprises:
the acquisition module is used for acquiring the equipment power consumption of the electrical equipment in the wind turbine generator based on the mode of the power carrier;
the analysis module is used for carrying out power consumption analysis on the electrical equipment based on the equipment power consumption to obtain a power consumption analysis result of the electrical equipment, wherein the power consumption analysis result is high power consumption or normal power consumption;
and the adjusting module is used for adjusting the equipment parameters of the electrical equipment when the power consumption analysis result is high power consumption.
9. A wind turbine control apparatus, the wind turbine control apparatus comprising: a memory, a processor and a wind turbine control program stored on the memory and operable on the processor, which when executed by the processor, implements the steps of the wind turbine control method of any one of claims 1 to 7.
10. A computer readable storage medium, characterized in that the computer readable storage medium has stored thereon a wind turbine control program, which when executed by a processor, implements the steps of the wind turbine control method according to any of claims 1 to 7.
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