Deicing method and device of wind turbine generator, storage medium and electronic device

Abstract

The invention discloses a deicing method and device for a wind turbine generator set, a storage medium and an electronic device, and the method comprises the steps: in response to a deicing instruction generated according to the ice coating state of a blade of the wind turbine generator set, calculating first predicted loss energy of the wind turbine generator set for deicing operation in a deicing period by using a deicing system simulation model; determining second predicted loss energy generated by shutdown of the wind turbine generator in the deicing period; target period loss energy with the minimum value is determined from multiple pieces of period loss energy corresponding to the duration needed by deicing, the duration needed by deicing comprises multiple deicing periods, and the period loss energy of each deicing period is the sum of the first predicted loss energy and the second predicted loss energy; and controlling the wind turbine generator to deice according to the deicing parameter corresponding to the target period loss energy. By the adoption of the technical scheme, the technical problem that the energy loss is high in the deicing period of the wind turbine generator is solved.

Description

Technical Field

[0001] The present application relates to the field of de - icing of wind turbines, and more particularly, to a de - icing method and device for a wind turbine, a storage medium, and an electronic device. Background Art

[0002] As a clean energy source, wind power generation has an expanding application scope. However, wind turbines for wind power generation are often designed outdoors and can have their blade surfaces iced due to environmental factors such as freezing weather, which affects normal operation and may even cause faults in the entire wind turbine.

[0003] To solve this problem, currently in the industry, heating elements such as resistance wires or electric heating films are installed on wind turbines. After being powered on, they generate heat to melt the ice layer. However, in actual operation, blade icing can also cause the wind turbine to malfunction, resulting in shutdown. This not only reduces the power generation time but also increases the maintenance cost. The current de - icing methods only focus on the thermal energy control of the de - icing system itself to control the de - icing intensity and ignore the energy loss caused by the shutdown of the wind turbine due to blade icing. Therefore, in related technologies, there is a technical problem of high energy loss during the de - icing of wind turbines.

[0004] In view of the technical problem of high energy loss during the de - icing of wind turbines in related technologies, no effective solution has been proposed yet.

[0005] Therefore, it is necessary to improve related technologies to overcome the defects in related technologies. Summary of the Invention

[0006] Embodiments of the present application provide a de - icing method and device for a wind turbine, a storage medium, and an electronic device, so as to at least solve the technical problem of high energy loss during the de - icing of wind turbines.

[0007] According to an aspect of the embodiments of the present application, a de - icing method for a wind turbine is provided, including: in response to a de - icing instruction generated according to the icing state of the blades of the wind turbine, using a de - icing system simulation model to calculate a first predicted loss energy of the wind turbine during de - icing operation in a de - icing cycle; determining a second predicted loss energy of the wind turbine due to shutdown during the de - icing cycle; determining a target cycle loss energy with the minimum value from multiple cycle loss energies corresponding to the required de - icing duration, where the required de - icing duration includes multiple de - icing cycles, and the cycle loss energy of each de - icing cycle is the sum of the first predicted loss energy and the second predicted loss energy; and controlling the wind turbine to perform de - icing according to the de - icing parameters corresponding to the target cycle loss energy.

[0008] In an exemplary embodiment, before calculating, by using an ice removal system simulation model, a first predicted lost energy of the wind turbine during an ice removal period in response to an ice removal instruction generated according to an ice covering state of blades of the wind turbine, the method further includes: generating the ice removal instruction according to the ice covering state of the blades of the wind turbine, including: determining a proportion of an ice covered area corresponding to the ice covering state, where the proportion of the ice covered area represents a ratio of an ice covered area of the blades of the wind turbine to an outer surface area of the blades of the wind turbine; and generating a first ice removal instruction when it is determined that the proportion of the ice covered area is greater than a preset ratio.

[0009] In an exemplary embodiment, calculating, by using an ice removal system simulation model, the first predicted lost energy of the wind turbine during the ice removal period includes: obtaining working environment parameters of the wind turbine, where the working environment parameters include at least one of the following: working temperature, working humidity, and an ice covering thickness of the blades of the wind turbine; inputting the working temperature, the working humidity, and the ice covering thickness of the blades of the wind turbine into the ice removal system simulation model to obtain a predicted heating relationship output by the ice removal system simulation model, where the predicted heating relationship represents a corresponding relationship between a predicted heating power and a predicted heating time; obtaining a target heating power and a target heating time of the wind turbine during the ice removal period from the predicted heating relationship; and determining the first predicted lost energy according to the target heating time and the target heating power.

[0010] In an exemplary embodiment, determining the first predicted lost energy according to the target heating time and the target heating power indicated by the target heating parameter corresponding relationship includes: obtaining a comparison result between the target heating power and a heating power threshold; when it is determined that the comparison result indicates that the target heating power is greater than the heating power threshold, obtaining a default heating time corresponding to the heating power threshold; and determining a product of the heating power threshold and the default heating time as the first predicted lost energy.

[0011] In an exemplary embodiment, determining a second predicted lost energy generated by the wind turbine due to shutdown during the ice removal period includes: determining a current working power of the wind turbine at the time of shutdown, and determining a target predicted working power of the wind turbine according to a wind power prediction result of the current working power; and calculating the second predicted lost energy based on the following formula:

[0012]

[0013] where W P2 represents the second predicted lost energy, and P irepresents the target predicted working power, Δt is the calculation interval time, t is the de-icing period, and L j is the duration required for de-icing.

[0014] In an exemplary embodiment, before controlling the wind turbine to perform de-icing according to the de-icing parameters corresponding to the target periodic loss energy, the method further includes: determining a first target predicted loss energy and a second target predicted loss energy corresponding to the target periodic loss energy; obtaining a first power used for calculating the first target predicted loss energy and a second power used for calculating the second target predicted loss energy, and determining the first power, the second power, and the target de-icing period corresponding to the target periodic loss energy as the de-icing parameters.

[0015] According to another aspect of the embodiments of the present application, there is also provided a de-icing device for a wind turbine, including: a calculation module, configured to, in response to a de-icing instruction generated according to the icing state of the blades of the wind turbine, calculate a first predicted loss energy of the wind turbine during de-icing operation within a de-icing period by using a de-icing system simulation model; a first determination module, configured to determine a second predicted loss energy generated by the wind turbine due to shutdown during the de-icing period; a second determination module, configured to determine a target periodic loss energy with a minimum value from multiple periodic loss energies corresponding to the de-icing required duration, where the de-icing required duration includes multiple de-icing periods, and the periodic loss energy of each de-icing period is the sum of the first predicted loss energy and the second predicted loss energy; and a control module, configured to control the wind turbine to perform de-icing according to the de-icing parameters corresponding to the target periodic loss energy.

[0016] According to yet another aspect of the embodiments of the present application, there is also provided a computer-readable storage medium, in which a computer program is stored, and the computer program is configured to execute the above-mentioned de-icing method of the wind turbine when running.

[0017] According to yet another aspect of the embodiments of the present application, there is also provided an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, where the above-mentioned processor executes the above-mentioned de-icing method of the wind turbine through the computer program.

[0018] According to yet another aspect of the present application, there is also provided a computer program product, including a computer program, and the steps in any one of the above-mentioned method embodiments are implemented when the computer program is executed by a processor.

[0019] Through this application, in response to a de-icing instruction generated according to the icing state of the unit blades of a wind turbine, a first predicted loss energy of the wind turbine during de-icing operation within a de-icing period is calculated using a de-icing system simulation model; a second predicted loss energy of the wind turbine due to shutdown during the de-icing period is determined; a target period loss energy with the minimum value is determined from multiple period loss energies corresponding to the required de-icing duration, wherein the required de-icing duration includes multiple de-icing periods, and the period loss energy of each de-icing period is the sum of the first predicted loss energy and the second predicted loss energy; the wind turbine is controlled to perform de-icing according to the de-icing parameters corresponding to the target period loss energy. This application comprehensively considers the energy loss of the de-icing system and the energy loss caused by blade icing shutdown, realizes the efficient and stable operation of the wind turbine in freezing weather, improves the energy utilization efficiency, and further solves the technical problem of high energy loss during the de-icing of the wind turbine, increases the power generation of the wind turbine, and reduces the energy loss during the de-icing of the wind turbine. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The accompanying drawings herein are incorporated into the specification and form a part of the specification, showing embodiments consistent with the present application, and are used together with the specification to explain the principles of the present application.

[0021] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the accompanying drawings required for use in the description of the embodiments or the prior art. Obviously, for those of ordinary skill in the art, other drawings can also be obtained based on these drawings without creative efforts.

[0022] Figure 1 It is a hardware structure block diagram of a mobile terminal for a de-icing method of a wind turbine according to an embodiment of the present application;

[0023] Figure 2 It is a flowchart of a de-icing method of a wind turbine according to an embodiment of the present application;

[0024] Figure 3 It is a schematic flowchart of a de-icing method of a wind turbine according to an embodiment of the present application;

[0025] Figure 4 It is a schematic diagram of heating power and de-icing time according to an embodiment of the present application;

[0026] Figure 5 It is a structure block diagram of a de-icing device of a wind turbine according to an embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0027] To enable those skilled in the art to better understand the solution of this application, the technical solutions in the embodiments of this application will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of this application. Obviously, the described embodiments are only a part of the embodiments of this application, rather than all the embodiments. Based on the embodiments in this application, all other embodiments obtained by those of ordinary skill in the art without making creative efforts shall fall within the scope of protection of this application.

[0028] It should be noted that the terms "first", "second", etc. in the specification and claims of this application and the above-mentioned drawings are used to distinguish similar objects, and do not necessarily need to describe a specific order or sequence. It should be understood that such used data can be interchanged under appropriate circumstances so that the embodiments of this application described here can be implemented in an order different from those illustrated or described here. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products, or devices.

[0029] The method embodiments provided in the embodiments of this application can be executed on a mobile terminal, a computer terminal, or a similar computing device. Taking the operation on a mobile terminal as an example, Figure 1 is a hardware structure block diagram of a mobile terminal for an ice removal method of a wind turbine in the embodiments of this application. As Figure 1 shown, the mobile terminal may include one or more ( Figure 1 only one is shown in the figure) processors 102 (the processor 102 may include, but is not limited to, a processing device such as a microprocessor (Central Processing Unit, MCU) or a field programmable gate array (Field Programmable Gate Array, FPGA)) and a memory 104 for storing data. Among them, the above-mentioned mobile terminal may further include a transmission device 106 for communication functions and an input / output device 108. Those of ordinary skill in the art can understand that Figure 1 the structure shown is only schematic and does not limit the structure of the above-mentioned mobile terminal. For example, the mobile terminal may further include more or fewer components than those shown in Figure 1 the figure, or have a different configuration from that shown in Figure 1 the figure.

[0030] The memory 104 can be used to store computer programs, such as software programs and modules of application software, like the computer program corresponding to the ice removal method of the wind turbine in the embodiments of the present application. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, that is, implements the above method. The memory 104 may include a high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memories. In some instances, the memory 104 may further include a memory remotely disposed relative to the processor 102, and these remote memories can be connected to the mobile terminal through a network. Examples of the above network include but are not limited to the Internet, intranet, local area network, mobile communication network, and combinations thereof.

[0031] The transmission device 106 is used to receive or send data via a network. Specific examples of the above network may include a wireless network provided by the communication provider of the mobile terminal. In one instance, the transmission device 106 includes a network adapter (Network Interface Controller, abbreviated as NIC), which can be connected to other network devices through a base station and thus communicate with the Internet. In one instance, the transmission device 106 can be a Radio Frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0032] In this embodiment, an ice removal method for a wind turbine is provided. Figure 2 is a flowchart of an ice removal method for a wind turbine according to an embodiment of the present application, as Figure 2 shown, and the process includes the following steps:

[0033] Step S202: In response to an ice removal instruction generated according to the ice-covered state of the blades of the wind turbine, use the ice removal system simulation model to calculate the first predicted loss energy of the wind turbine during the ice removal operation in the ice removal cycle;

[0034] It should be noted that the efficiency of blade ice removal is closely related to the power of the heating system. Within a certain range, the greater the heating power, the shorter the required ice removal time. Therefore, in the design of the air heating or electric heating ice removal system, the relationship between the heating power and the heating time can be determined through the ice removal system simulation model corresponding to the blade. For example, by multiplying the heating power by the heating time, the energy loss during the entire ice removal process can be obtained.

[0035] Step S204: Determine the second predicted loss energy of the wind turbine due to shutdown during the ice removal cycle;

[0036] Step S206: Determine the target cycle loss energy with the minimum value from multiple cycle loss energies corresponding to the ice removal required duration, where the ice removal required duration includes multiple ice removal cycles, and the cycle loss energy of each ice removal cycle is the sum of the first predicted loss energy and the second predicted loss energy;

[0037] Among them, the ice removal required duration can be determined according to the predicted heating relationship provided by the ice removal system simulation model. After the ice removal system simulation model obtains the predicted heating relationship between the predicted heating power and the predicted heating time based on the input working environment parameters such as the working temperature, working humidity, and the ice thickness on the blades of the wind turbine generator set, the ice removal required duration can be determined according to the predicted heating time. It should be noted that in this application, the predicted heating time is used as the reference standard to determine the ice removal required duration. The ice removal required duration can be appropriately extended or shortened according to actual needs.

[0038] Step S208: Control the wind turbine generator set to perform ice removal according to the ice removal parameters corresponding to the target cycle loss energy.

[0039] It can be understood that the above ice removal parameters can include parameters for ice removal operations such as power and ice removal cycle.

[0040] Through the above steps, by responding to the ice removal instruction generated according to the ice covering state of the blades of the wind turbine generator set, using the ice removal system simulation model to calculate the first predicted loss energy of the wind turbine generator set during the ice removal cycle; determining the second predicted loss energy generated by the wind turbine generator set due to shutdown during the ice removal cycle; determining the target cycle loss energy with the minimum value from multiple cycle loss energies corresponding to the ice removal required duration, where the ice removal required duration includes multiple ice removal cycles, and the cycle loss energy of each ice removal cycle is the sum of the first predicted loss energy and the second predicted loss energy; controlling the wind turbine generator set to perform ice removal according to the ice removal parameters corresponding to the target cycle loss energy. This application comprehensively considers the energy loss of the ice removal system and the energy loss caused by the blade icing shutdown, realizes the efficient and stable operation of the wind turbine generator set in freezing weather, improves the energy utilization efficiency, and further solves the technical problem of high energy loss during the ice removal period of the wind turbine generator set, increases the power generation of the wind turbine generator set, and reduces the energy loss during the ice removal period of the wind turbine generator set.

[0041] In an exemplary embodiment, before calculating the first predicted lost energy of the wind turbine during the de-icing period by using the de-icing system simulation model in response to a de-icing instruction generated according to the icing state of the turbine blades of the wind turbine, further, a technical solution for generating the de-icing instruction according to the icing state of the turbine blades of the wind turbine can be implemented, specifically including: determining the proportion of the ice-covered area corresponding to the icing state of the turbine blades, where the proportion of the ice-covered area represents the ratio of the ice-covered area of the blades of the wind turbine to the outer surface area of the blades of the wind turbine; and generating a first de-icing instruction when it is determined that the proportion of the ice-covered area is greater than a preset ratio. In this embodiment, the severity of blade icing is specifically judged according to the proportion of the ice-covered area, and the de-icing instruction can be generated from the perspective of the severity of blade icing.

[0042] Alternatively, in other embodiments, the ice thickness corresponding to the icing state of the turbine blades can also be determined; and a second de-icing instruction is generated when it is determined that the ice thickness is greater than a preset thickness. In this embodiment, the severity of blade icing is specifically judged according to the ice thickness, and the de-icing instruction can be generated from the perspective of the severity of blade icing.

[0043] Alternatively, in other embodiments, a third de-icing instruction is generated when it is determined that the proportion of the ice-covered area is greater than a preset ratio and the ice thickness is greater than a preset thickness. In this embodiment, the severity of blade icing is specifically judged according to the proportion of the ice-covered area and the ice thickness, and the de-icing instruction can be generated from the perspective of the severity of blade icing.

[0044] Further, in this embodiment, the de-icing intensity (specifically, the power or the de-icing period) can also be adjusted in combination with the severity of blade icing to improve the de-icing efficiency.

[0045] In an exemplary embodiment, for the process of calculating the first predicted lost energy of the wind turbine during the de-icing period by using the de-icing system simulation model, it can include: obtaining the working environment parameters of the wind turbine, where the working environment parameters at least include one of the following: working temperature, working humidity, and the ice thickness of the blades of the wind turbine; inputting the working temperature, the working humidity, and the ice thickness of the blades of the wind turbine into the de-icing system simulation model to obtain the target heating parameters output by the de-icing system simulation model, where the target heating parameters include the target heating power and the target heating time of the wind turbine during the de-icing period; and determining the first predicted lost energy according to the target heating time and the target heating power.

[0046] Among them, the de-icing system simulation model is trained with historical working environment parameters as input samples and the historical heating parameters of the wind turbine as output samples.

[0047] Among them, the target heating time is not greater than the time corresponding to the de-icing cycle.

[0048] Further, the first predicted loss energy can be calculated by the following formula:

[0049] W P1 =P j *t j .

[0050] Among them, W P1 represents the first predicted loss energy, P j is the target heating power, tj is P j corresponding target heating time.

[0051] It can be understood that for the de-icing energy loss corresponding to the duration required for de-icing, it can be obtained according to the product of the target heating power and the duration required for de-icing.

[0052] Optionally, in an exemplary embodiment, for the process of calculating the first predicted loss energy of the wind turbine during the de-icing cycle using the de-icing system simulation model, it may further include: obtaining the de-icing equipment on the wind turbine, the de-icing equipment is equipped with heating tools, wherein the heating tools have different heating types; determining the first de-icing amount corresponding to the ice-covered state of the turbine blades, and determining the second de-icing amount consistent with the first de-icing amount from the preset de-icing strategies; determining the target heating power supported by the heating tool from the multiple heating powers corresponding to the second de-icing amount; determining the target heating parameter correspondence to which the target heating power belongs from the heating parameter correspondences provided by the de-icing system simulation model, wherein the heating parameter correspondence represents the relationship between the heating power and the heating time; determining the first predicted loss energy according to the target heating time indicated by the target heating parameter correspondence and the target heating power. This embodiment provides a data basis for subsequent determination of the power and cycle required for de-icing based on the first predicted loss energy, facilitating the efficient and stable operation of the wind turbine in freezing weather and improving the energy utilization efficiency.

[0053] In this embodiment, the de-icing equipment is, for example, a heating equipment, and the corresponding heating tools may include a gas heating tool, an electric heating tool, and a tool combining gas heating and electric heating. Among them, the gas heating tool melts the ice layer by delivering hot air to the blade surface, while the electric heating tool uses a resistance heating element to generate heat to achieve de-icing. The tool combining gas heating and electric heating combines these two methods in order to achieve a higher de-icing effect. Among them, the gas heating tool and the electric heating tool can precisely and smoothly control the heating power.

[0054] Optionally, in one embodiment, it is also possible to determine the power and cycle required for the de-icing system simulation model calculation. The following is the curve relationship between the heating power and the heating time obtained from the de-icing system simulation model, as well as the general process of calculating the energy loss required for de-icing using the de-icing system simulation model:

[0055] 1. Establish a simulation model: First, a simulation model needs to be established. The established simulation model can simulate the icing conditions of aircraft wings, wind turbine blades, or other similar structures under different temperature and humidity conditions.

[0056] 2. Simulate the icing process: Use simulation software to simulate the icing process of the blade under specific environmental conditions. Record the temperature, humidity, icing thickness, distribution, and time. The physical parameters required for the icing simulation model include the thermal conductivity, specific heat capacity, density, etc. of the blade material.

[0057] 3. Determine the heating strategy: Based on the simulation results, determine the strategy for heating the blade to remove the ice layer. The specific strategy can include selecting the position of the heating element, heating power, and heating time.

[0058] 4. Simulate the heating process: Apply the heating strategy in the model to simulate the heating process. Observe how the ice layer melts and record the required heating power and time.

[0059] 5. Plot the curve of heating power vs. heating time: Based on the simulation results, plot the relationship curve between the heating power and the heating time. This curve can help understand how long it takes to completely remove the ice layer under different heating powers.

[0060] 6. Calculate the energy loss: The energy loss can be calculated by multiplying the heating power by the heating time.

[0061] 7. Optimize the de-icing strategy: Analyze the curve to find the combination of heating power and time with the minimum energy loss. This may involve adjusting the heating power or heating time to achieve more effective de-icing.

[0062] 8. Verify and test: Conduct tests on the actual blade to verify the accuracy of the simulation model. Adjust the model parameters according to the test results to improve the prediction ability of the model.

[0063] 9. Implement the de-icing system: Design and implement an actual de-icing system based on the simulation and test results. Ensure that the system can work effectively under different environmental conditions.

[0064] Through the above embodiments, the design process of the de-icing system simulation model can be realized, and then the energy loss of the wind turbine during the de-icing operation within the de-icing cycle can be determined, which is convenient for adjusting the equipment power according to the energy loss, and then improving the safety and operation efficiency of the equipment under harsh weather conditions.

[0065] In an exemplary embodiment, for the technical solution of determining the first predicted loss energy according to the target heating time and the target heating power indicated by the target heating parameter correspondence, the specific steps include: obtaining a comparison result between the target heating power and a heating power threshold; in the case where it is determined that the comparison result indicates that the target heating power is greater than the heating power threshold, obtaining a default heating time corresponding to the heating power threshold; and determining the product of the heating power threshold and the default heating time as the first predicted loss energy. Considering that the heating power and heating duration of the de-icing system are non-linear within a certain range, that is, when the heating power of the de-icing system reaches a certain value, even if the power is increased further, the heating time will not decrease significantly. In this embodiment, heating strategies are formulated respectively for the heating power and heating time under the linear relationship and the non-linear relationship, so as to improve the heating efficiency of the wind turbine and reduce unnecessary energy loss.

[0066] Optionally, in an embodiment, in the case where it is determined that the comparison result indicates that the target heating power is less than the heating power threshold, the product of the target heating power and the target heating time may be determined as the first predicted loss energy.

[0067] In an exemplary embodiment, the second predicted loss energy generated by the wind turbine due to shutdown during the de-icing period may be determined through the following steps: determining the current working power of the wind turbine at the time of shutdown, and determining the target predicted working power of the wind turbine according to the wind power prediction result of the current working power; calculating the second predicted loss energy based on the following formula:

[0068]

[0069] where W P2 represents the second predicted loss energy, P i represents the target predicted working power, Δt is the calculation interval time, t is the de-icing period, and L j is the duration required for de-icing.

[0070] Optionally, in an exemplary embodiment, the second predicted lost energy generated by the wind turbine due to shutdown during the de-icing period may also be determined through the following steps, which specifically include: obtaining the current operating power of the wind turbine during shutdown; in the case where it is determined that the current operating power is less than the preset operating power, determining the second predicted lost energy by multiplying the current operating power by the de-icing period; in the case where it is determined that the current operating power is greater than the preset operating power, determining the second predicted lost energy by multiplying the current operating power by the de-icing period. Through this embodiment, the heating power and heating duration can be effectively controlled to achieve the purpose of minimizing the overall energy loss.

[0071] Alternatively, for the case where power compensation is required for the wind turbine, obtain the current operating power and the current ambient wind speed of the wind turbine during shutdown; in the case where it is determined that the current operating power is less than the preset operating power, determine the first predicted operating power of the wind turbine during shutdown according to the current ambient wind speed and the current operating power, obtain the sum value of the first predicted operating power and the compensation operating power of the wind turbine, and determine the second predicted lost energy by multiplying the sum value by the de-icing period.

[0072] Further, in the case where it is determined that the current operating power is greater than the preset operating power, determine the second predicted operating power of the wind turbine during shutdown according to the current ambient wind speed and the current operating power, and determine the second predicted lost energy by multiplying the second predicted operating power by the de-icing period.

[0073] Alternatively, determine the third predicted operating power of the wind turbine during shutdown according to the current ambient wind speed, and determine the second predicted lost energy by multiplying the third predicted operating power by the de-icing period.

[0074] It should be noted that the above predicted operating power can be realized, for example, according to the wind power prediction method. For the wind power prediction methods commonly used in this field, this application will not elaborate here.

[0075] Through the above embodiments, when the wind turbine shuts down due to icing, according to the ultra-short-term wind power prediction results, if it is predicted that the wind turbine has high power during shutdown and is in a strong wind period (which will accelerate the heat dissipation of the wind turbine, increase the energy loss, and affect the de-icing effect), the heating power of the de-icing system needs to be increased to remove the ice as soon as possible and resume normal operation, thereby reducing the energy loss during the entire de-icing process; if it is predicted that the wind turbine has high power during shutdown and is in a light wind period or a windless period, the heating power of the de-icing system can be reduced to de-ice slowly. Finally, the energy loss during the entire de-icing process is optimized.

[0076] In an exemplary embodiment, before controlling the wind turbine to de-ice according to the de-icing parameters corresponding to the target cycle loss energy, the de-icing parameters can be further determined by the following process: determining the first target predicted loss energy and the second target predicted loss energy corresponding to the target cycle loss energy; obtaining the first power used to calculate the first target predicted loss energy and the second power used to calculate the second target predicted loss energy, and determining the target de-icing cycle corresponding to the first power, the second power and the target cycle loss energy as the de-icing parameters. The de-icing parameters are determined by this embodiment, and then the de-icing parameters are used to control de-icing.

[0077] Optionally, the present application also provides other de-icing methods, such as using ultrasonic vibration to break and remove the ice layer. Alternatively, special chemicals are coated on the surface of the blade, which can reduce the adhesion of ice and make it easier to fall off.

[0078] Furthermore, during the de-icing process, the status of the blades can be continuously monitored to ensure that the ice layer is effectively removed. If necessary, the system will automatically adjust the de-icing intensity. Once the ice layer is completely removed, the de-icing operation is stopped and the blade status is continuously monitored to prevent re-icing. At the same time, the de-icing system needs to be regularly inspected and maintained to ensure its normal operation, which improves the operating efficiency of wind turbines in severe weather conditions and reduces downtime and maintenance costs caused by icing.

[0079] Obviously, the embodiments described above are only some embodiments of the present application, not all embodiments. In order to better understand the above method, the above process is described below in conjunction with the embodiments, but it is not intended to limit the technical solutions of the embodiments of the present application, specifically:

[0080] In an optional embodiment, the present application combines Figure 3 The specific steps are as follows:

[0081] Step 1: Perform frequency conversion on the gas heating and electric heating deicing systems so that their heating power can be accurately and smoothly controlled.

[0082] Step 2: Obtain the current wind turbine temperature, humidity, blade ice thickness and other parameters, and obtain the heating power P according to the de-icing system simulation model. j And heating time L j (corresponding to the time required for deicing mentioned above).

[0083] Step 3: According to the heating power P j And heating time L j The relationship curve (corresponding to the above predicted heating relationship) is, for example, expressed as:

[0084] W1 = P j * L j / 60。

[0085] Then, every 15 min (i.e., the above calculated interval time), determine the corresponding heating power according to the relationship curve, and calculate the energy loss of the de-icing system.

[0086] Step 4: Obtain the prediction results of the ultra-short-term wind power within 15 min - 240 min (i.e., 4 h) of the wind farm (i.e., the above predicted working power).

[0087] Step 5: During the heating duration, every 15 min, calculate the expected energy loss caused by icing shutdown:

[0088]

[0089] Wherein, the unit of W2 is W / s or kW / s.

[0090] Step 6: Every 15 min, calculate the total energy loss at each point:

[0091] W 总 = W1 + W2.

[0092] Step 7: Obtain the minimum value of the total energy loss.

[0093] Step 8: Obtain the parameters such as the heating power and heating duration corresponding to the minimum value of the total energy loss.

[0094] Furthermore, according to the current icing state, considering the maximum power limit of the de-icing system, there will be a maximum heating power and the corresponding shortest heating time constraint.

[0095] As Figure 4 shown, for example, the maximum heating power is 300 kW and the shortest heating time is 60 min. At this state point, W1 = 300 kW * 60 min / 60. At this time, it is necessary to calculate the sum of the losses at 4 points (denoted as p1, p2, p3, p4) within 60 min to obtain the wind power prediction energy loss W2, and then use W1 and W2 to calculate the total W 60min 。

[0096] W2 = p1 * 15 min / 60 min + p2 * 15 min / 60 min + p3 * 15 min / 60 min + p4 * 15 min / 60 min.

[0097] Among them, the maximum heating power of 300 kW represents the above first power.

[0098] Taking the start point calculated with a cycle of [300 kW, 60 min], continue to calculate the heating power when the heating time is 75 min. For example, if it is 260 kW, then W1 at this state point is obtained as W1 = 260 kW * 75 min / 60. Then calculate the sum of losses at a total of 5 points (denoted as p1, p2, p3, p4, and p5) within the heating time range to obtain W2, and then calculate the total W using W1 and W2 75min .

[0099] W2 = p1 * 15 min / 60 min + p2 * 15 min / 60 min + p3 * 15 min / 60 min + p4 * 15 min / 60 min + p5 * 15 min / 60 min.

[0100] And so on until the heating power when the heating time is 240 min is obtained, and calculate the total W at this time according to the method 240min . Then obtain the minimum value among the W60min to W240min values, and set the heating power corresponding to the minimum value as the target control power Pset of the de-icing system, that is, the above-mentioned second power.

[0101] Step 9: Control the frequency converter of the de-icing system to heat according to the above parameters.

[0102] When the wind turbine generator stops due to icing, according to the ultra-short-term wind power prediction results, if it is predicted that the wind turbine generator has high power during the shutdown period and is in a high-wind period (which will accelerate the heat dissipation of the wind turbine generator and affect the de-icing effect), then it is necessary to increase the heating power of the de-icing system to remove the ice as soon as possible and resume normal operation, thereby reducing the energy loss during the entire de-icing process; if it is predicted that the wind turbine generator has high power during the shutdown period and is in a low-wind period or a windless period, then the heating power of the de-icing system can be reduced to de-ice slowly. The ultimate goal is to optimize the energy loss during the entire de-icing process. Optimization is a complex problem. Through the above steps, this application optimizes through multiple aspects such as the selection of de-icing strategies, the adjustment of heating power, and the control of shutdown time, so as to achieve the efficient and stable operation of the wind turbine generator in freezing weather and improve the energy utilization efficiency.

[0103] Through the description of the above embodiments, those skilled in the art can clearly understand that the method according to the above embodiments can be implemented by means of software plus a necessary general hardware platform. Of course, it can also be implemented by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of this application, in essence, or the part 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 disc), and includes several instructions to enable a terminal device (which can be a mobile phone, computer, server, or network device, etc.) to execute the methods of various embodiments of this application.

[0104] In this embodiment, an ice removal device for a wind turbine is further provided. This device is used to implement the above-mentioned embodiments and preferred implementation manners, and those that have been described will not be repeated. As used hereinafter, the term "module" can be a combination of software and / or hardware that can achieve a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, implementation in hardware, or a combination of software and hardware is also possible and contemplated.

[0105] Figure 5 is a structural block diagram of an ice removal device for a wind turbine according to an embodiment of the present application. The device includes:

[0106] A calculation module 42, configured to respond to an ice removal instruction generated according to the ice-covered state of the blades of the wind turbine, and calculate a first predicted loss energy of the wind turbine during an ice removal operation within an ice removal cycle using an ice removal system simulation model;

[0107] A first determination module 44, configured to determine a second predicted loss energy generated by the wind turbine due to shutdown during the ice removal cycle;

[0108] A second determination module 46, configured to determine a target cycle loss energy with a minimum value from multiple cycle loss energies corresponding to the required ice removal duration, where the required ice removal duration includes multiple ice removal cycles, and the cycle loss energy of each ice removal cycle is the sum of the first predicted loss energy and the second predicted loss energy;

[0109] A control module 48, configured to control the wind turbine to perform ice removal according to the ice removal parameters corresponding to the target cycle loss energy.

[0110] Through the above device, by responding to an ice removal instruction generated according to the ice-covered state of the blades of the wind turbine, calculating a first predicted loss energy of the wind turbine during an ice removal operation within an ice removal cycle using an ice removal system simulation model; determining a second predicted loss energy generated by the wind turbine due to shutdown during the ice removal cycle; determining a target cycle loss energy with a minimum value from multiple cycle loss energies corresponding to the required ice removal duration, where the required ice removal duration includes multiple ice removal cycles, and the cycle loss energy of each ice removal cycle is the sum of the first predicted loss energy and the second predicted loss energy; controlling the wind turbine to perform ice removal according to the ice removal parameters corresponding to the target cycle loss energy. The present application comprehensively considers the energy loss of the ice removal system and the energy loss caused by blade icing and shutdown, realizes the efficient and stable operation of the wind turbine in freezing weather, improves the energy utilization efficiency, and further solves the technical problem of high energy loss during the ice removal of the wind turbine, increases the power generation of the wind turbine, and reduces the energy loss during the ice removal of the wind turbine.

[0111] In an exemplary embodiment, the calculation module 42 is further configured to: before calculating, using the de-icing system simulation model, the first predicted lost energy of the wind turbine during the de-icing period in response to a de-icing instruction generated according to the icing state of the blades of the wind turbine, generate the de-icing instruction according to the icing state of the blades of the wind turbine, including: determining the proportion of the ice-covered area corresponding to the icing state, where the proportion of the ice-covered area represents the ratio of the ice-covered area of the blades of the wind turbine to the outer surface area of the blades of the wind turbine; and generating a first de-icing instruction when it is determined that the proportion of the ice-covered area is greater than a preset ratio.

[0112] In an exemplary embodiment, the calculation module 42 is further configured to: obtain the working environment parameters of the wind turbine, where the working environment parameters at least include one of the following: working temperature, working humidity, and the ice thickness of the blades of the wind turbine; input the working temperature, the working humidity, and the ice thickness of the blades of the wind turbine into the de-icing system simulation model to obtain a predicted heating relationship output by the de-icing system simulation model, where the predicted heating relationship represents the corresponding relationship between the predicted heating power and the predicted heating time; obtain the target heating power and the target heating time of the wind turbine during the de-icing period from the predicted heating relationship; and determine the first predicted lost energy according to the target heating time and the target heating power.

[0113] In an exemplary embodiment, the calculation module 42 is further configured to: obtain the comparison result between the target heating power and the heating power threshold; when it is determined that the comparison result indicates that the target heating power is greater than the heating power threshold, obtain the default heating time corresponding to the heating power threshold; and determine the product of the heating power threshold and the default heating time as the first predicted lost energy.

[0114] In an exemplary embodiment, the first determination module 44 is further configured to: determine the current working power of the wind turbine when it is shut down, and determine the target predicted working power of the wind turbine according to the wind power prediction result of the current working power; calculate the second predicted lost energy based on the following formula:

[0115]

[0116] where, W P2 represents the second predicted lost energy, P i represents the target predicted working power, Δt is the calculation interval time, t is the de-icing period, and L j is the duration required for de-icing.

[0117] In an exemplary embodiment, the control module 48 is further configured to determine a first target predicted loss energy and a second target predicted loss energy corresponding to the target cycle loss energy before controlling the wind turbine to perform de-icing according to the de-icing parameters corresponding to the target cycle loss energy; obtain a first power used for calculating the first target predicted loss energy and a second power used for calculating the second target predicted loss energy, and determine the first power, the second power, and a target de-icing cycle corresponding to the target cycle loss energy as the de-icing parameters.

[0118] An embodiment of the present application further provides a computer-readable storage medium, in which a computer program is stored, and the computer program is configured to execute the steps in any one of the above method embodiments when running.

[0119] Optionally, in this embodiment, the above storage medium may be configured to store a computer program for executing the following steps:

[0120] S1. In response to a de-icing instruction generated according to the icing state of the blades of the wind turbine, use a de-icing system simulation model to calculate a first predicted loss energy of the wind turbine during the de-icing operation within the de-icing cycle;

[0121] S2. Determine a second predicted loss energy generated by the wind turbine due to shutdown during the de-icing cycle;

[0122] S3. Determine a target cycle loss energy with the minimum value from multiple cycle loss energies corresponding to the de-icing required duration, where the de-icing required duration includes multiple de-icing cycles, and the cycle loss energy of each de-icing cycle is the sum of the first predicted loss energy and the second predicted loss energy;

[0123] S4. Control the wind turbine to perform de-icing according to the de-icing parameters corresponding to the target cycle loss energy.

[0124] In an exemplary embodiment, the above computer-readable storage medium may include, but is not limited to: various media such as a USB flash drive, a read-only memory (ROM for short), a random access memory (RAM for short), a mobile hard disk, a magnetic disk, or an optical disc that can store a computer program.

[0125] Specific examples in this embodiment may refer to the examples described in the above embodiments and exemplary embodiments, and will not be repeated here.

[0126] An embodiment of the present application further provides an electronic device, including a memory and a processor. A computer program is stored in the memory, and the processor is configured to run the computer program to execute the steps in any one of the above method embodiments.

[0127] Optionally, in this embodiment, the above processor may be configured to execute the following steps through a computer program:

[0128] S1, in response to a de-icing instruction generated according to the icing state of the turbine blades of a wind turbine, use a de-icing system simulation model to calculate a first predicted loss energy of the wind turbine during de-icing operations within a de-icing period;

[0129] S2, determine a second predicted loss energy generated by the wind turbine due to shutdown during the de-icing period;

[0130] S3, determine a target cycle loss energy with the minimum value from multiple cycle loss energies corresponding to the required de-icing duration, where the required de-icing duration includes multiple de-icing periods, and the cycle loss energy of each de-icing period is the sum of the first predicted loss energy and the second predicted loss energy;

[0131] S4, control the wind turbine to perform de-icing according to the de-icing parameters corresponding to the target cycle loss energy.

[0132] In an exemplary embodiment, the above electronic device may further include a transmission device and an input / output device. The transmission device is connected to the above processor, and the input / output device is connected to the above processor.

[0133] An embodiment of the present application further provides a computer program product. The computer program product includes a computer program, and when the computer program is executed by a processor, it implements the steps in any one of the above method embodiments.

[0134] An embodiment of the present application further provides another computer program product, including a non-volatile computer-readable storage medium. The non-volatile computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, it implements the steps in any one of the above method embodiments.

[0135] An embodiment of the present application further provides a computer program. The computer program includes computer instructions, and the computer instructions are stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes the steps in any one of the above method embodiments.

[0136] Specific examples in this embodiment may refer to the examples described in the above embodiments and exemplary embodiments, and will not be elaborated herein.

[0137] Obviously, those skilled in the art should understand that the various modules or steps of the present application described above can be implemented by a general-purpose computing device. They can be concentrated on a single computing device or distributed over a network composed of multiple computing devices. They can be implemented by program codes executable by the computing device. Thus, they can be stored in a storage device and executed by the computing device. And in some cases, the steps shown or described can be executed in a different order than here, or they can be separately fabricated into individual integrated circuit modules, or multiple modules or steps among them can be fabricated into a single integrated circuit module for implementation. In this way, the present application is not limited to any specific combination of hardware and software.

[0138] The above are only the preferred embodiments of the present application. It should be noted that for those of ordinary skill in the art, without departing from the principle of the present application, several improvements and modifications can be made, and these improvements and modifications should also be regarded as the protection scope of the present application.

Claims

1. A deicing method for a wind turbine generator set, characterized in that: include: In response to a deicing instruction generated according to the ice-covered state of the blades of the wind turbine generator set, a first predicted loss energy of the wind turbine generator set performing a deicing operation during a deicing cycle is calculated using a deicing system simulation model; and a second predicted loss energy of the wind turbine generator set caused by shutdown during the deicing cycle is determined; Determining a target cycle loss energy with a minimum value from a plurality of cycle loss energies corresponding to the required deicing time, wherein the required deicing time includes a plurality of deicing cycles, and the cycle loss energy of each deicing cycle is the sum of the first predicted loss energy and the second predicted loss energy; The wind turbine generator set is controlled to perform de-icing according to the de-icing parameters corresponding to the target periodic energy loss.

2. The method according to claim 1, characterized in that Before calculating the first predicted energy loss of the wind turbine generator set in a deicing cycle using a deicing system simulation model in response to a deicing instruction generated according to the icing state of the wind turbine generator set blades, the method further includes: Generating the deicing instruction according to the ice-covered state of the blades of the wind turbine generator set includes: Determine an ice-covered area ratio corresponding to an ice-covered state of the blades of the wind turbine generator set, wherein the ice-covered area ratio represents a ratio of an ice-covered area of ​​the blades of the wind turbine generator set to an outer surface area of ​​the blades of the wind turbine generator set; When it is determined that the ice-covered area accounts for a greater than a preset proportion, a first de-icing instruction is generated.

3. The method according to claim 1, characterized in that Calculating a first predicted energy loss of the wind turbine generator set during a deicing cycle using a deicing system simulation model includes: Acquire the working environment parameters of the wind turbine generator set, wherein the working environment parameters include at least one of the following: working temperature, working humidity, and ice thickness of blades of the wind turbine generator set; Inputting the operating temperature, the operating humidity and the ice thickness of the blades of the wind turbine into the deicing system simulation model to obtain a predicted heating relationship output by the deicing system simulation model, wherein the predicted heating relationship represents a corresponding relationship between a predicted heating power and a predicted heating time; Obtaining a target heating power and a target heating time of the wind turbine generator set in the deicing cycle from the predicted heating relationship; The first predicted loss energy is determined according to the target heating time and the target heating power.

4. The method according to claim 3, characterized in that Determining the first predicted energy loss according to the target heating time and the target heating power indicated by the target heating parameter correspondence relationship includes: Obtaining a comparison result between the target heating power and a heating power threshold; When it is determined that the comparison result indicates that the target heating power is greater than a heating power threshold, obtaining a default heating time corresponding to the heating power threshold; The product of the heating power threshold and the default heating time is determined as the first predicted loss energy.

5. The method according to claim 1, characterized in that Determining a second predicted energy loss of the wind turbine generator set due to shutdown during the deicing cycle includes: Determining the current operating power of the wind turbine generator set when it is shut down, and determining the target predicted operating power of the wind turbine generator set according to the wind power prediction result of the current operating power; The second predicted loss energy is calculated based on the following formula: Among them, W P2 represents the second predicted loss energy, P i represents the target predicted working power, Δt is the calculation interval time, t is the deicing cycle, L j The time required for the de-icing.

6. The method according to claim 1, characterized in that Before controlling the wind turbine generator set to de-ice according to the de-icing parameters corresponding to the target periodic energy loss, the method further includes: Determine a first target predicted loss energy and a second target predicted loss energy corresponding to the target periodic loss energy; A first power used to calculate the first target predicted energy loss and a second power used to calculate the second target predicted energy loss are obtained, and a target deicing cycle corresponding to the first power, the second power and the target cycle energy loss is determined as the deicing parameter.

7. A deicing device for a wind turbine generator set, characterized in that: include: A calculation module, configured to calculate, in response to a deicing instruction generated according to an ice-covered state of blades of the wind turbine generator set, a first predicted loss energy of the wind turbine generator set during a deicing operation in a deicing cycle using a deicing system simulation model; A first determination module, configured to determine a second predicted energy loss caused by shutdown of the wind turbine generator set during the deicing cycle; a second determination module, configured to determine a target cycle loss energy with a minimum value from a plurality of cycle loss energies corresponding to a required deicing time, wherein the required deicing time includes a plurality of deicing cycles, and the cycle loss energy of each deicing cycle is the sum of the first predicted loss energy and the second predicted loss energy; A control module is used to control the wind turbine to de-ice according to the de-icing parameters corresponding to the target periodic energy loss.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored program, wherein the program executes the method according to any one of claims 1 to 6 when executed.

9. An electronic device comprising a memory and a processor, characterized in that: A computer program is stored in the memory, and the processor is configured to execute the method according to any one of claims 1 to 6 through the computer program.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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