Snow removal control method and related device

Abstract

The invention provides a snow removal control method and a related device, and relates to the technical field of photovoltaic power stations. After snowfall is stopped, real-time irradiation data and real-time power generation power of a photovoltaic sub-region in a target photovoltaic region are obtained, reference power generation power corresponding to the real-time irradiation data of the photovoltaic sub-region is determined, a snow removal mode of the photovoltaic sub-region is determined based on the real-time power generation power and the reference power generation power, and snow is removed according to the snow removal mode. And snow removal operation is carried out on the photovoltaic subareas. According to the method and the device, after snowfall, accumulated snow can influence the power generation power of the photovoltaic sub-region, so that the snow removal mode is determined according to the influence degree of the accumulated snow on the power generation power, namely based on the relative magnitude of the real-time power generation power and the reference power generation power, so that the snow removal mode is matched with the snow accumulation condition of the photovoltaic sub-region; therefore, snow removal operation of the photovoltaic subarea can be accurately carried out, and the snow removal accuracy is improved.

Description

Technical Field

[0001] This application relates to the field of photovoltaic power plant technology, and in particular to a snow removal control method and related device. Background Technology

[0002] When photovoltaic power plants operate in snowy areas, snow covering the photovoltaic panels can lead to a significant decrease in power generation efficiency and even cause structural damage.

[0003] Currently, snow removal operations at photovoltaic power stations can be carried out by heating and melting snow. However, this method has the problem of low snow removal accuracy, and it is easy for some snow-covered areas to not be completely cleared. Summary of the Invention

[0004] In view of the above problems, this application provides a snow removal control method and related device to improve snow removal accuracy. The specific solution is as follows:

[0005] The first aspect of this application provides a snow removal control method, comprising:

[0006] After snowfall ceases in the target photovoltaic area, real-time irradiance data and real-time power generation of the photovoltaic sub-regions within the target photovoltaic area are acquired.

[0007] Determine the reference power generation corresponding to the real-time irradiance data of the photovoltaic sub-region; the reference power generation is the power generation when the snow accumulation in the photovoltaic sub-region is lower than the preset snow accumulation.

[0008] Based on the real-time power generation and the reference power generation, the snow removal method for the photovoltaic sub-region is determined;

[0009] Snow removal operations are performed on the photovoltaic sub-area according to the described snow removal method.

[0010] In one possible implementation, the snow removal method for the photovoltaic sub-region is determined based on the real-time power generation and the reference power generation, including:

[0011] Calculate the ratio of the real-time power generation to the reference power generation;

[0012] If the ratio is less than a preset threshold, the snow removal method for the photovoltaic sub-region is determined based on the ratio; wherein, if the ratio is greater than or equal to the preset threshold, the snow removal operation for the photovoltaic sub-region is stopped.

[0013] In one possible implementation, determining the snow removal method for the photovoltaic sub-region based on the ratio includes:

[0014] Determine the first target rotation angle of the support actuator in the photovoltaic sub-region corresponding to the ratio, wherein the ratio is negatively correlated with the first target rotation angle of the support actuator;

[0015] The snow removal method for the photovoltaic sub-area is determined as follows: the support actuator is controlled to rotate according to the first target rotation angle until the next detection time of the real-time irradiance data and the real-time power generation is reached;

[0016] Alternatively, the snow accumulation level of the photovoltaic sub-region can be obtained, and the ratio and the second target rotation angle of the support actuator of the photovoltaic sub-region corresponding to the snow accumulation level can be determined; wherein, the ratio is negatively correlated with the second target rotation angle of the support actuator, and the snow accumulation level is positively correlated with the second target rotation angle of the support actuator.

[0017] The snow removal method for the photovoltaic sub-area is determined as follows: the support actuator is controlled to rotate according to the second target rotation angle until the next detection time of the real-time irradiance data and the real-time power generation is reached, at which point the rotation stops.

[0018] In one possible implementation, determining the snow removal method for the photovoltaic sub-region based on the ratio includes:

[0019] Get the current ambient temperature;

[0020] The current ambient temperature, the real-time irradiance data, and the ratio are processed using a data processing model to obtain the snow removal method for the photovoltaic sub-region.

[0021] The data processing model is obtained by training using sample data; the sample data includes:

[0022] The reference photovoltaic sub-region is defined as the photovoltaic sub-region whose real-time power generation ratio is greater than the reference power generation ratio after snow removal operation.

[0023] In one possible implementation, snow removal operations are performed on the photovoltaic sub-region according to the described snow removal method, including:

[0024] The snow removal method is sent to the tracking control unit in the photovoltaic sub-area, so that the tracking control unit controls the corresponding support actuator to rotate according to the snow removal method to perform snow removal operation on the photovoltaic sub-area.

[0025] In one possible implementation, before acquiring real-time irradiance data and real-time power generation of photovoltaic sub-regions within the target photovoltaic region, the method further includes:

[0026] Detect the snow accumulation level in the photovoltaic sub-regions within the target photovoltaic region;

[0027] Identify the target photovoltaic sub-region where the snow accumulation is greater than the preset snow accumulation level;

[0028] Control the support actuator in the target photovoltaic sub-region to perform a preset rotation operation.

[0029] In one possible implementation, determining the reference power generation corresponding to the real-time irradiance data of the photovoltaic sub-region includes:

[0030] Obtain the correspondence between irradiation data and power generation; wherein the correspondence is obtained by statistical analysis of historical irradiation data and historical power generation in historical power generation data;

[0031] The reference power generation corresponding to the real-time irradiance data of the photovoltaic sub-region can be obtained from the correspondence.

[0032] In one possible implementation, if snowfall does not cease in the target photovoltaic area, the snow removal control method further includes:

[0033] Obtain wind speed and direction data;

[0034] Based on the wind speed and direction data, the rotation angle of the support actuator in the photovoltaic sub-region of the target photovoltaic region is adjusted.

[0035] A second aspect of this application provides a snow removal control device, comprising:

[0036] The acquisition module is used to acquire real-time irradiance data and real-time power generation of the photovoltaic sub-regions in the target photovoltaic area after snowfall stops in the target photovoltaic area;

[0037] The power determination module is used to determine the reference power generation corresponding to the real-time irradiance data of the photovoltaic sub-region; the reference power generation is the power generation when the snow accumulation in the photovoltaic sub-region is lower than the preset snow accumulation.

[0038] The snow removal method determination module is used to determine the snow removal method of the photovoltaic sub-region based on the real-time power generation and the reference power generation;

[0039] The snow removal module is used to perform snow removal operations on the photovoltaic sub-area according to the snow removal method.

[0040] A third aspect of this application provides an electronic device, comprising at least one processor and a memory connected to the processor, wherein:

[0041] The memory is used to store computer programs;

[0042] The processor is used to execute the computer program so that the electronic device can implement the snow removal control method described above.

[0043] A fourth aspect of this application provides a snow removal control system, including the aforementioned electronic equipment;

[0044] The electronic device communicates with the tracking control unit in the photovoltaic sub-area through the communication box to send the snow removal method to the tracking control unit, and the tracking control unit controls the corresponding support actuator to rotate according to the snow removal method.

[0045] By employing the above technical solution, this application provides a snow removal control method and related apparatus. In this application, after snowfall ceases in the target photovoltaic area, real-time irradiance data and real-time power generation of a photovoltaic sub-region within the target photovoltaic area are acquired. A reference power generation corresponding to the real-time irradiance data of the photovoltaic sub-region is determined. The reference power generation is the power generation when the snow accumulation in the photovoltaic sub-region is lower than a preset snow accumulation level. Based on the real-time power generation and the reference power generation, a snow removal method for the photovoltaic sub-region is determined, and snow removal operations are performed on the photovoltaic sub-region according to the determined snow removal method. That is, in this application, after snowfall, snow accumulation affects the power generation of the photovoltaic sub-region. Therefore, the snow removal method is determined based on the degree of influence of snow accumulation on power generation, i.e., based on the relative magnitude of the real-time power generation and the reference power generation, so that the snow removal method matches the snow accumulation situation of the photovoltaic sub-region, thereby enabling accurate snow removal operations in the photovoltaic sub-region and improving snow removal accuracy. Attached Figure Description

[0046] The above and other features, advantages, and aspects of the embodiments of this disclosure will become more apparent from the accompanying drawings and the following detailed description. Throughout the drawings, the same or similar reference numerals denote the same or similar elements. It should be understood that the drawings are schematic, and the originals and elements are not necessarily drawn to scale.

[0047] Figure 1 A flowchart of a snow removal control method provided in this application;

[0048] Figure 2 A flowchart of a method for determining a snow removal method provided in this application;

[0049] Figure 3 A flowchart of another snow removal control method provided in this application;

[0050] Figure 4 This is a schematic diagram of a snow removal control device provided in this application. Detailed Implementation

[0051] The embodiments of this application are described below with reference to the accompanying drawings. The terminology used in the implementation section of this application is for explaining specific embodiments only and is not intended to limit the scope of this application.

[0052] The embodiments of this application will now be described with reference to the accompanying drawings. Those skilled in the art will recognize that, with technological advancements and the emergence of new scenarios, the technical solutions provided in the embodiments of this application are equally applicable to similar technical problems.

[0053] The terms "first," "second," etc., used in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such terms are interchangeable where appropriate; this is merely a way of distinguishing objects with the same attributes in the embodiments of this application. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion, so that a process, method, system, product, or apparatus that comprises a series of elements is not necessarily limited to those elements, but may include other elements not explicitly listed or inherent to those processes, methods, products, or apparatuses.

[0054] When photovoltaic power plants operate in snowy areas, snow covering the photovoltaic panels can lead to a significant decrease in power generation efficiency and even cause structural damage.

[0055] Currently, manual snow removal is possible, but it is inefficient. To improve efficiency, heating and melting methods can be used for snow removal at photovoltaic power plants. However, this method suffers from low accuracy, often leaving some areas with incomplete snow removal, high energy consumption, and poor adaptability.

[0056] To address the problems associated with manual snow removal and heat-based snow melting methods, snow removal operations can be performed using rotating support structures. While this method controls the movement of the entire power station support structure via unified commands, it doesn't account for differences in snow accumulation across different areas, potentially leading to over-snow removal or incomplete removal in some areas. Furthermore, the timing of snow removal completion often relies on experience or fixed time settings, lacking precise judgment and potentially resulting in untimely or premature cessation of snow removal. Therefore, a snow removal control method that can accurately sense snow accumulation and adaptively adjust snow removal strategies is urgently needed.

[0057] Therefore, in this embodiment, after snowfall stops in the target photovoltaic area, real-time irradiance data and real-time power generation of the photovoltaic sub-regions within the target photovoltaic area are acquired. A reference power generation corresponding to the real-time irradiance data of the photovoltaic sub-region is determined. The reference power generation is the power generation when the snow accumulation in the photovoltaic sub-region is lower than a preset snow accumulation level. Based on the real-time power generation and the reference power generation, a snow removal method for the photovoltaic sub-region is determined, and snow removal operations are performed on the photovoltaic sub-region according to the snow removal method. That is, in this application, after snowfall, snow accumulation will affect the power generation of the photovoltaic sub-region. Therefore, the snow removal method is determined based on the degree of influence of snow accumulation on power generation, i.e., based on the relative magnitude of the real-time power generation and the reference power generation, so that the snow removal method matches the snow accumulation situation of the photovoltaic sub-region, thereby enabling accurate snow removal operations in the photovoltaic sub-region and improving snow removal accuracy.

[0058] Based on the above, one embodiment of this application provides a snow removal control method, wherein the executing entity can be an electronic device, which can be a central algorithm platform or a TCU (Tracking Control Unit).

[0059] In real-world scenarios, each row of photovoltaic panels in a photovoltaic power station is independently equipped with a TCU (Transmission Control Unit). The TCU integrates a power detection circuit to collect real-time power generation data from that row of panels. If this electronic device is a central algorithm platform, the TCU reports the collected power generation data to the central algorithm platform and receives snow removal commands from it. This drives the tracking bracket's actuator to perform a rotational shaking motion. The tracking bracket's actuator supports angle adjustment, driven by a motor controlled by the TCU, enabling rapid reciprocating oscillation within a ±60° range. Furthermore, the TCU can also receive instructions from the central algorithm platform, such as global trigger signals for the start / end of snowfall.

[0060] The TCU and the central algorithm platform communicate bidirectionally via a communication box (which can be an NCU (Network Control Unit)). The communication box can receive snow removal strategies from the central algorithm platform and distribute them to the corresponding TCU. Upon receiving the instructions from the communication box, the TCU executes the snow removal rotation and jitter strategy. Additionally, the communication box can also receive snow removal stop strategies from the central algorithm platform and distribute them to the corresponding TCU. After receiving the instructions from the communication box, the TCU executes the snow removal stop strategy and performs normal standby, tracking, and other strategies.

[0061] It should be noted that if the electronic device is a TCU (Transmission Control Unit), then there is no need to configure the aforementioned central algorithm platform and communication box. The TCU directly determines the snow removal method and performs the corresponding snow removal operations based on the power generation data it collects. In this embodiment, the following explanation will use an electronic device as the central algorithm platform.

[0062] Reference Figure 1 A snow removal control method may include:

[0063] S11. After snowfall stops in the target photovoltaic area, acquire real-time irradiance data and real-time power generation of the photovoltaic sub-regions within the target photovoltaic area.

[0064] In this embodiment, the target photovoltaic area can be an area in a photovoltaic power station equipped with photovoltaic panels, and the photovoltaic sub-area within the target photovoltaic area can be each row of photovoltaic panels. In actual scenarios, there are multiple photovoltaic sub-areas within the target photovoltaic area.

[0065] During snowfall, the snow accumulation on the photovoltaic panels in the target photovoltaic area will increase. If strong winds accompany the snowfall, in order to protect the tracking bracket, one approach is to acquire wind speed and direction data while the snowfall in the target photovoltaic area continues, and adjust the rotation angle of the bracket actuator in the photovoltaic sub-area of ​​the target photovoltaic area based on the wind speed and direction data.

[0066] In practical implementation, when monitoring whether snowfall has occurred in the target photovoltaic area, snow sensors, such as snow depth gauges and weighing rain and snow gauges, can be installed to determine whether snowfall has occurred. Additionally, video surveillance equipment can be installed, and image analysis algorithms can be used to determine whether snowfall is currently occurring by collecting video footage from the equipment.

[0067] If the target photovoltaic area is experiencing snowfall, the tracking bracket can be adjusted to a suitable angle by taking into account wind speed and direction and adjusting the rotation angle of the bracket actuator in the photovoltaic sub-area within the target photovoltaic area. This protects the bracket and allows for continuous monitoring of the snowfall situation.

[0068] In practice, under light wind and snowfall conditions, the impact of snowfall on the tracking bracket is minimal, allowing it to be rotated to a larger angle. Under moderate wind and snowfall conditions, the impact is moderate, allowing it to be rotated to a centered angle. Under heavy wind and snowfall conditions, the impact is significant, requiring the tracking bracket to be laid flat at 0°.

[0069] After snowfall ceases in the target photovoltaic (PV) area, real-time irradiance data of the PV sub-regions within the target PV area can be obtained using irradiance instruments (such as spectroradiometers or photoelectric irradiometers) installed in the PV sub-regions or the target PV area itself. This real-time irradiance data can be irradiance. In practical scenarios, if the irradiance received by each PV sub-region is the same, only one irradiance instrument can be configured in the target PV area, and the irradiance data collected by this instrument will be the irradiance data for each PV sub-region in the target PV area. If the irradiance received by each PV sub-region is different, such as when rows of PV panels are located in different areas on a hillside and are subject to shading, then one irradiance instrument can be configured in each PV sub-region of the target PV area, and the irradiance data collected by this instrument will be the irradiance data for the corresponding PV sub-region.

[0070] In addition to obtaining real-time irradiance data for the photovoltaic sub-region, it is also necessary to obtain the real-time power generation of the photovoltaic sub-region. This real-time power generation data can be acquired in real time by the power detection circuit integrated into the TCU, which can collect the real-time power generation data of the photovoltaic panels in the photovoltaic sub-region.

[0071] In real-world scenarios, different photovoltaic sub-regions may block each other, or be blocked by other objects such as trees, or the snow may fall due to gravity, resulting in different levels of snow accumulation in different photovoltaic sub-regions. Consequently, the power generation of different photovoltaic sub-regions is affected differently by the snow accumulation. Therefore, in the embodiments of this application, the real-time power generation of different photovoltaic sub-regions is different.

[0072] S12. Determine the reference power generation corresponding to the real-time irradiance data of the photovoltaic sub-region.

[0073] The reference power generation is the power generation of the photovoltaic sub-region when the snow accumulation is lower than the preset snow accumulation level. In a real-world scenario, the preset snow accumulation level can be a preset snow thickness, such as 0.1mm or 0.5mm, which does not affect the power generation of the photovoltaic panels. If the snow accumulation in the photovoltaic sub-region is lower than the preset snow accumulation level, it means that the current snow accumulation in that photovoltaic sub-region is very small, almost non-existent, or completely absent.

[0074] To analyze whether the power generation of the photovoltaic sub-region is affected by snow accumulation, this embodiment obtains the theoretical power generation when the snow accumulation in the photovoltaic sub-region is very small, almost non-existent, or completely absent. This theoretical power generation is referred to as the reference power generation in this embodiment. The reference power generation is affected by real-time irradiance data; generally, the higher the real-time irradiance, the higher the reference power generation, and vice versa. Therefore, in this embodiment, the reference power generation corresponding to the real-time irradiance data of the photovoltaic sub-region can be determined.

[0075] In one implementation, the correspondence between irradiation data and power generation can be obtained, and the reference power generation corresponding to the real-time irradiation data of the photovoltaic sub-region can be retrieved from the correspondence.

[0076] The correspondence is obtained through statistical analysis of historical irradiance data and historical power generation from historical power generation data. In specific implementation, to achieve adaptive snow removal cycles for each row of photovoltaic panels, the system can periodically (e.g., quarterly or annually) update the historical irradiance data and historical power generation from the historical power generation data. A historical power spectrum is established based on this historical irradiance data and historical power generation. This historical power spectrum can be a "historical power-irradiance" mapping model. Instead of using a uniform "historical power-irradiance" mapping model, a separate "historical power-irradiance" mapping model is established for each row of photovoltaic panels. This model serves as the benchmark for determining whether the current power of that row of photovoltaic panels has returned to normal (i.e., the snow has been cleared). The "historical power-irradiance" mapping model contains the correspondence between irradiance data and power generation, including power generation under different irradiance levels. This allows the theoretical power generation to be determined based on the current real-time irradiance. Since this power generation is determined based on real-time irradiance, instead of using a uniform theoretical value, the accuracy of determining whether the snow has been cleared is improved.

[0077] Establishing historical power spectra is an ongoing process, which can automatically adapt to the slow performance decline of photovoltaic modules due to natural aging, ensuring that the judgment benchmark is always effective. This reflects the long-term adaptability and intelligence of the technology, achieving the purpose of self-learning and self-adaptation.

[0078] Once the correspondence between irradiance data and power generation is known, the reference power generation corresponding to the real-time irradiance data of the photovoltaic sub-region can be retrieved from the correspondence. This reference power generation is the theoretical power generation under the condition that the photovoltaic sub-region has very little snow, or almost no snow, or no snow at all.

[0079] S13. Determine the snow removal method for the photovoltaic sub-region based on real-time power generation and reference power generation.

[0080] In practical scenarios, the power recovery rate after snowfall can be analyzed based on the relative magnitudes of real-time and reference power generation. A higher power recovery rate indicates that the power generation of the photovoltaic sub-region is less affected by snow accumulation, allowing for snow removal operations using a smaller rotation angle of the support mechanism. Conversely, a lower power recovery rate indicates that the power generation of the photovoltaic sub-region is significantly affected by snow accumulation, requiring a larger rotation angle of the support mechanism. Furthermore, the rotation time of the support mechanism can be adjusted based on the power recovery rate to better adapt to the current snow conditions. Additionally, the total number of rotations of the support mechanism can be determined based on the power recovery rate to match the current snow accumulation level. Moreover, other snow removal methods can be configured according to actual circumstances.

[0081] In this embodiment, power generation is used as a direct indicator of snow removal, enabling accurate judgment of power-driven snow removal operations. Compared with timed or uniform angle adjustment snow removal methods, this approach is more adaptable to the differences in snow accumulation in different areas.

[0082] S14. Perform snow removal operations on the photovoltaic sub-area according to the snow removal method.

[0083] In this embodiment, once the snow removal method is known, the TCU can be used to control the rotation of the support actuator to achieve the purpose of snow removal.

[0084] In one implementation, if the electronic device executing the snow removal control method is a central algorithm platform, the central algorithm platform sends the snow removal method to the tracking control unit in the photovoltaic sub-area through the communication box, so that the tracking control unit controls the corresponding support actuator to rotate according to the snow removal method to perform snow removal operation on the photovoltaic sub-area.

[0085] In one implementation, if the electronic device executing the snow removal control method is a TCU, the TCU directly controls the corresponding support actuator to rotate according to the snow removal method in order to perform snow removal operation on the photovoltaic sub-area.

[0086] In this embodiment, after snowfall ceases in the target photovoltaic area, real-time irradiance data and real-time power generation of the photovoltaic sub-regions within the target photovoltaic area are acquired. A reference power generation corresponding to the real-time irradiance data of the photovoltaic sub-region is determined. The reference power generation is the power generation when the snow accumulation in the photovoltaic sub-region is lower than a preset snow accumulation level. Based on the real-time power generation and the reference power generation, a snow removal method for the photovoltaic sub-region is determined, and snow removal operations are performed on the photovoltaic sub-region according to the snow removal method. That is, in this application, after snowfall, snow accumulation will affect the power generation of the photovoltaic sub-region. Therefore, the snow removal method is determined based on the degree of influence of snow accumulation on power generation, i.e., based on the relative magnitude of the real-time power generation and the reference power generation, so that the snow removal method matches the snow accumulation situation of the photovoltaic sub-region, thereby enabling accurate snow removal operations in the photovoltaic sub-region and improving snow removal accuracy.

[0087] Furthermore, this embodiment enables point-to-point control, avoiding energy waste: snow removal is only initiated on the row of photovoltaic panels truly covered by snow. Equipment in areas without snow or with light snow remains stationary, significantly reducing unnecessary mechanical movements, saving power required for the drive motor, reducing mechanical wear and fatigue damage to the equipment, and extending the service life of the support system.

[0088] Furthermore, this embodiment enables rapid restoration of power generation, minimizing revenue loss: due to precise snow removal assessment and efficient operation, snow can be cleared as quickly as possible. Photovoltaic panels can then be exposed to sunlight as soon as possible to resume power generation, minimizing power generation loss caused by snow accumulation. Especially during sunny periods after snowfall, this can help power plant owners recover considerable economic benefits.

[0089] In addition, this embodiment can reduce reliance on manual labor and operation and maintenance costs: the whole process is automated, eliminating the need for operation and maintenance personnel to carry out high-risk and low-efficiency manual cleaning in the wind and snow, and eliminating the need to deploy high-energy-consuming heating and snow melting systems, which significantly reduces the long-term operation and maintenance costs of the power plant.

[0090] Furthermore, this embodiment can handle complex terrain and microclimates: for large mountain power plants, coastal power plants, etc., the microclimates and terrains of different areas can lead to huge differences in snow thickness and melting rate. The point-to-point snow removal control logic in this embodiment can adapt to this unevenness, ensuring that each "hilltop" or "valley" receives the most appropriate treatment.

[0091] Furthermore, this embodiment boasts strong fault tolerance: even if several TCUs or sensors within the photovoltaic power station malfunction, it will largely not affect snow removal operations in other normally functioning units. This distributed architecture avoids the risk of a "single point of failure" causing the entire system to collapse, as is common in traditional centralized control systems, thus improving the overall reliability of the system.

[0092] Based on any of the above embodiments, refer to Figure 2 , based on the real-time power generation and the reference power generation, determining the snow removal method for the photovoltaic sub-region may include:

[0093] S21. Calculate the ratio of the real-time power generation to the reference power generation.

[0094] In this embodiment, the real-time power generation is represented by P_current, the reference power generation is represented by P_expected, and the ratio of the real-time power generation to the reference power generation is represented by R, that is:

[0095] R = (P_current / P_expected) × 100%.

[0096] In this embodiment, the calculated R can be used as the above-mentioned power recovery rate. R can directly and accurately reflect the snow coverage. If R is larger, it means that the power generation of this photovoltaic sub-region is less affected by snow, and it also means that there is less snow currently. If R is smaller, it means that the power generation of this photovoltaic sub-region is more affected by snow, and it also means that there is more snow currently.

[0097] S22. When the ratio is less than the preset threshold, determine the snow removal method for the photovoltaic sub-region based on the ratio.

[0098] In this embodiment, the preset threshold can be represented by N%. When the ratio is greater than or equal to the preset threshold (i.e., R ≥ N%), it indicates that the power generation performance of this row of photovoltaic panels has recovered to more than N% of its normal level, the snow removal effect has reached the expected value, and the snow impact is acceptable. At this time, the TCU immediately stops the snow removal operation of the photovoltaic sub-region and instead executes normal control strategies such as tracking and standby.

[0099] When the ratio is less than the preset threshold (i.e., R < N%), it indicates that the snow still significantly affects power generation. At this time, the TCU needs to perform a snow removal operation on this photovoltaic sub-region. The snow removal method used in the specific snow removal operation is determined according to this ratio, that is, R. The smaller R is, the more snow there is currently, and at this time, a stronger snow removal method is needed. The larger R is, the less snow there is currently, and at this time, a weaker snow removal method is needed.

[0100] In this embodiment, when determining the snow removal method for the photovoltaic sub-region based on the ratio, there are multiple implementation methods, which are introduced separately below.

[0101] In one implementation method, determine the first target rotation angle of the support actuator of the photovoltaic sub-region corresponding to the ratio, and then determine the snow removal method for the photovoltaic sub-region as: control the support actuator to rotate according to the first target rotation angle until it stops at the next detection time of the real-time irradiance data and the real-time power generation.

[0102] The ratio is negatively correlated with the first target rotation angle of the support actuator. In practice, the dynamic rotation angle can be determined based on R. First, a maximum rotation angle is set for each support actuator controlled by the TCU. Within this maximum rotation angle, the lower R is, the thicker the snow accumulation, and the greater the required snow removal force. In this case, a larger rotation angle (e.g., ±60°) should be used to effectively break the snow's adhesion using gravitational acceleration. Conversely, when R is higher, only small angle adjustments (e.g., ±15°) are needed to shake off residual snow. When R is in the middle, the TCU can control the support actuator to perform a single rotational shaking motion (e.g., reciprocating motion within ±25°) to attempt to shake off the snow.

[0103] In real-world scenarios, a pre-established correspondence between the ratio and the first target rotation angle of the support actuator in the photovoltaic sub-region can be established. In this correspondence, the ratio is negatively correlated with the first target rotation angle of the support actuator, as illustrated in the examples above.

[0104] Then, after knowing R, we can query the correspondence to obtain the first target rotation angle of the support actuator of the photovoltaic sub-region corresponding to R. Then, the snow removal method of the photovoltaic sub-region is set to: control the support actuator to rotate according to the first target rotation angle until the next detection time of real-time irradiance data and real-time power generation is reached and then stop.

[0105] In practical scenarios, real-time irradiance data and real-time power generation can be detected according to a fixed data detection cycle (e.g., 30 seconds). If the TCU needs to control the support actuator to rotate according to a first target rotation angle within a single detection period, the support actuator can be controlled to rotate according to this first target angle during the current data detection cycle. During the rotation and shaking process, the support actuator can effectively break the adhesion of the snow using gravitational acceleration, thereby causing the snow to fall. At the start of the next data detection cycle, the rotation of the support actuator is stopped, and the real-time irradiance data and real-time power generation are measured again, and the above cyclic operation begins again.

[0106] It should be noted that since the snow accumulation level varies in each photovoltaic sub-region, the corresponding R and snow removal method can be calculated and configured independently for each photovoltaic sub-region. Each row of TCUs makes independent decisions, avoiding a "one-size-fits-all" approach. This allows each photovoltaic sub-region to perform the above-mentioned snow removal operation independently, achieving point-to-point adaptive snow removal control, reducing energy consumption while improving snow removal efficiency, and ensuring that no snow removal area is missed.

[0107] Additionally, when setting the data detection cycle as described above, when R is low, a shorter data detection cycle (e.g., 30 seconds) can be set after the snow removal action, meaning the next power detection and snow removal action will be performed after 30 seconds. When R is high, a longer data detection cycle (e.g., 30 seconds) can be set after the snow removal action to allow time for the snow to slide off naturally.

[0108] In addition, a maximum number of rotations is set for each support actuator controlled by the TCU to prevent the support actuator from getting stuck in a rotation dead loop due to excessive rotation, thus protecting the safety of the tracking support structure. For example, a total upper limit for each snow removal cycle is set (e.g., 10 times). Once the upper limit is reached, the system will be forcibly stopped even if the snow is not completely cleared, and a "snow removal anomaly" status will be reported to prompt maintenance personnel to check.

[0109] In another implementation, when determining the snow removal method for the photovoltaic sub-region based on the ratio, the snow accumulation degree of the photovoltaic sub-region is obtained, the ratio and the second target rotation angle of the support actuator corresponding to the snow accumulation degree of the photovoltaic sub-region are determined, and the snow removal method of the photovoltaic sub-region is determined as follows: the support actuator is controlled to rotate according to the second target rotation angle until the next detection time of real-time irradiance data and real-time power generation is reached and then stopped.

[0110] The ratio is negatively correlated with the second target rotation angle of the support actuator, while the degree of snow accumulation is positively correlated with the second target rotation angle of the support actuator. Specifically, the lower the R value, the thicker and more severe the snow accumulation, and the greater the snow removal effort required. In this case, a larger rotation angle (e.g., ±60°) should be used to effectively break the adhesion of the snow by utilizing gravitational acceleration. Conversely, when R is higher, the snow accumulation is thinner and less severe, and only small angle adjustments (e.g., ±15°) are needed to shake off the remaining snow.

[0111] In this embodiment, the degree of snow accumulation can be detected using the snow sensor described above. It can be the thickness of the snow accumulation or the weight of the snow accumulation, etc. This degree of snow accumulation can reflect the real-time snow accumulation situation of the photovoltaic panel.

[0112] Compared to the previous embodiment, which only used a ratio to determine the first target rotation angle, this embodiment uses both the ratio and the degree of snow accumulation to determine the second target rotation angle of the support actuator in the photovoltaic sub-region. By considering both power recovery and snow accumulation, the determination of the rotation angle is more comprehensive, resulting in a more accurate second target rotation angle. In practical scenarios, a pre-established correspondence between the ratio, snow accumulation, and the second target rotation angle can still be established. In this correspondence, the ratio is negatively correlated with the second target rotation angle of the support actuator, while the degree of snow accumulation is positively correlated with the second target rotation angle of the support actuator.

[0113] Then, after knowing R and the degree of snow accumulation, the correspondence can be queried to obtain the second target rotation angle of the support actuator of the photovoltaic sub-region corresponding to R. Then, the snow removal method of the photovoltaic sub-region is determined to be: control the support actuator to rotate according to the second target rotation angle until the next detection time of real-time irradiance data and real-time power generation is reached and then stop. The specific implementation is the same as the explanation in the previous embodiment.

[0114] In another implementation, when determining the snow removal method for the photovoltaic sub-region based on the ratio, a data processing model can be used. Specifically, the current ambient temperature can be obtained, and the data processing model can be used to process the current ambient temperature, real-time irradiance data, and ratio to obtain the snow removal method for the photovoltaic sub-region.

[0115] The data processing model can incorporate algorithms such as case-based reasoning, reinforcement learning, and supervised learning, and supports dynamic adjustment of policy parameters.

[0116] In one implementation, the data processing model is obtained by training using sample data; the sample data includes:

[0117] The reference snow removal method is based on the ambient temperature and irradiance data of the photovoltaic sub-region.

[0118] The reference photovoltaic sub-region is the photovoltaic sub-region where the ratio of real-time power generation to reference power generation is greater than a preset reference value after snow removal operations.

[0119] In real-world scenarios, during historical snow removal processes, a data chain can be recorded of the complete snow removal operation performed by the TCU. This data chain can include the following:

[0120] 1. Initial stage of snow removal: snow thickness level, initial power recovery rate, ambient temperature, and irradiance before snow removal.

[0121] 2: Snow Removal Execution Phase: When the support actuator in the photovoltaic sub-region rotates, the angle, frequency, direction of rotation (clockwise, counterclockwise), and total number of cycles are recorded for each rotation.

[0122] 3: Final snow removal effect: Power recovery rate and total time when snow removal is successful.

[0123] Meaningful features (such as temperature range, snow thickness level, etc.) are extracted from the complete data chain. Data chains of successful snow removal cases (such as final power recovery rate (the ratio of real-time power generation after snow removal to reference power generation) ≥ preset reference value, such as 85%) are stored in the successful case library. These photovoltaic sub-regions with a final power recovery rate ≥ 85% are the reference photovoltaic sub-regions in the embodiments of this application.

[0124] For a reference photovoltaic sub-region, a reference snow removal method corresponding to the ambient temperature and irradiance data of the reference photovoltaic sub-region is obtained. Specifically, the reference snow removal method refers to the angle, frequency, direction of rotation (clockwise or counterclockwise), and total number of cycles for each rotation. Using the reference snow removal method corresponding to the ambient temperature and irradiance data of the reference photovoltaic sub-region as sample data, a mapping relationship is established from the initial snow removal state (specifically, ambient temperature, irradiance data, and initial power recovery rate) to the optimal snow removal strategy (specifically, the reference snow removal method). Algorithms such as case-based reasoning, reinforcement learning, and supervised learning are employed to dynamically adjust the policy parameters in the data processing model to achieve model training.

[0125] When a new snow removal task begins, the system matches the optimal strategy from the model based on the current ambient temperature, real-time irradiance data, and ratio. After the snow removal operation is executed, the confidence level of the strategy is updated based on the snow removal effect, and new cases are recorded to achieve closed-loop optimization. Subsequently, the system can record each successful snow removal process (e.g., the angle and number of passes required to restore 85%), and optimize the snow removal strategy under different initial states through algorithms to achieve continuous improvement and realize the goal of adaptive learning.

[0126] It should be noted that, in this embodiment, after the snow removal method is determined using the data processing model, the support actuator can be controlled to rotate according to the determined angle, frequency, direction (clockwise, counterclockwise) and total number of cycles for each rotation until the next data detection cycle for irradiation and power detection is reached.

[0127] In addition to using models to determine snow removal methods, corresponding snow removal methods can also be matched from the case library based on the current ambient temperature, real-time irradiance data, and ratio. In this case, the data processing model can be omitted.

[0128] This embodiment provides multiple implementation schemes for determining the snow removal method. In actual scenarios, the appropriate method can be selected according to the requirements to determine the snow removal method and then carry out subsequent snow removal operations.

[0129] Furthermore, the swing amplitude and frequency are dynamically adjusted based on power feedback to achieve a dynamic shaking strategy, balancing snow removal effectiveness with mechanical wear. The tracking algorithm automatically resumes after snow removal is complete, requiring no manual intervention and achieving seamless integration with the tracking system.

[0130] Based on any of the above embodiments, in one implementation, before performing adaptive snow removal operations according to the power recovery rate for each photovoltaic sub-region, a unified snow removal operation can also be performed on the target photovoltaic sub-region with a large snow accumulation. Specifically, before obtaining the real-time irradiance data and real-time power generation of the photovoltaic sub-regions in the target photovoltaic region, refer to... Figure 3 Snow control methods also include:

[0131] S31. Detect the snow accumulation level in the photovoltaic sub-regions within the target photovoltaic region.

[0132] In this embodiment, please refer to the corresponding description above for the specific implementation of detecting the degree of snow accumulation.

[0133] S32. Identify the target photovoltaic sub-region where the snow accumulation is greater than the preset snow accumulation.

[0134] In this embodiment, a preset snow accumulation level can be configured. Taking snow accumulation level as an example, the preset snow accumulation level can be a thickness value that represents a relatively thick snow accumulation. For each photovoltaic sub-region in the target photovoltaic region, its snow accumulation level is detected, and photovoltaic sub-regions with a snow accumulation level greater than the preset snow accumulation level are selected as target photovoltaic sub-regions.

[0135] S33. Control the bracket actuator in the target photovoltaic sub-region to perform a preset rotation operation.

[0136] In this embodiment, a rotation strategy for the support actuator can be pre-configured for the target photovoltaic sub-region, such as the angle, frequency, rotation direction (clockwise, counterclockwise) and total number of cycles for each rotation. Then, according to the rotation strategy of the support actuator, the TCU controls the support actuator in the target photovoltaic sub-region to perform a preset rotation operation to uniformly eliminate snow accumulation in multiple photovoltaic sub-regions. Subsequently, for each photovoltaic sub-region, an adaptive snow removal operation is performed according to the above-mentioned utilization power recovery rate to carry out personalized snow removal operation.

[0137] The above describes a snow removal control method provided by an embodiment of this application. The following describes the apparatus for performing the above snow removal control method.

[0138] Please see Figure 4 , Figure 4 This is a schematic diagram of a snow removal control device provided in an embodiment of this application. Figure 4 As shown, the snow removal control device includes:

[0139] The acquisition module 101 is used to acquire real-time irradiance data and real-time power generation of the photovoltaic sub-regions in the target photovoltaic area after the snowfall stops in the target photovoltaic area;

[0140] The power determination module 102 is used to determine the reference power generation corresponding to the real-time irradiance data of the photovoltaic sub-region; the reference power generation is the power generation when the snow accumulation in the photovoltaic sub-region is lower than the preset snow accumulation.

[0141] The snow removal method determination module 103 is used to determine the snow removal method for the photovoltaic sub-region based on the real-time power generation and the reference power generation.

[0142] Snow removal module 104 is used to perform snow removal operations on the photovoltaic sub-area according to the snow removal method.

[0143] In one possible implementation, the snow removal method determination module 103 includes:

[0144] The ratio calculation submodule is used to calculate the ratio between real-time power generation and reference power generation.

[0145] The snow removal method determination submodule is used to determine the snow removal method for the photovoltaic sub-region based on the ratio when the ratio is less than a preset threshold; wherein, when the ratio is greater than or equal to the preset threshold, the snow removal operation of the photovoltaic sub-region is stopped.

[0146] In one possible implementation, the snow removal method determination submodule includes:

[0147] The first determining unit is used to determine the first target rotation angle of the support actuator of the photovoltaic sub-region corresponding to the ratio, wherein the ratio is negatively correlated with the first target rotation angle of the support actuator; the snow removal method of the photovoltaic sub-region is determined as follows: the support actuator is controlled to rotate according to the first target rotation angle until the next detection time of real-time irradiance data and real-time power generation is reached and then stopped.

[0148] The second determining unit is used to obtain the snow accumulation level of the photovoltaic sub-region, determine the ratio and the second target rotation angle of the support actuator of the photovoltaic sub-region corresponding to the snow accumulation level; wherein, the ratio is negatively correlated with the second target rotation angle of the support actuator, and the snow accumulation level is positively correlated with the second target rotation angle of the support actuator; the snow removal method of the photovoltaic sub-region is determined as follows: the support actuator is controlled to rotate according to the second target rotation angle until the next detection time of real-time irradiance data and real-time power generation is reached and then stopped.

[0149] In one possible implementation, the snow removal method determination submodule includes:

[0150] The third determining unit is used to obtain the current ambient temperature, process the current ambient temperature, real-time irradiance data and ratio using a data processing model, and obtain the snow removal method for the photovoltaic sub-region.

[0151] The data processing model was trained using sample data; the sample data included:

[0152] The reference snow removal method is based on the ambient temperature and irradiance data of the reference photovoltaic sub-region; the reference photovoltaic sub-region is the photovoltaic sub-region where the ratio of real-time power generation to reference power generation is greater than the preset reference value after snow removal operation.

[0153] In one possible implementation, the snow removal module 104 is specifically used for:

[0154] The snow removal method is sent to the tracking control unit in the photovoltaic sub-area, so that the tracking control unit controls the corresponding support actuator to rotate according to the snow removal method to carry out snow removal operation in the photovoltaic sub-area.

[0155] One possible implementation also includes:

[0156] The detection module is used to detect the snow accumulation level in the photovoltaic sub-regions within the target photovoltaic area;

[0157] The region determination module is used to identify target photovoltaic sub-regions where the snow accumulation is greater than a preset snow accumulation level;

[0158] The unified snow removal module is used to control the support actuators in the target photovoltaic sub-region to perform preset rotation operations.

[0159] In one possible implementation, the power determination module 102 is specifically used for:

[0160] Obtain the correspondence between irradiance data and power generation; the correspondence is obtained by statistical analysis of historical irradiance data and historical power generation in historical power generation data; the reference power generation corresponding to the real-time irradiance data of the photovoltaic sub-region is obtained from the correspondence.

[0161] One possible implementation also includes:

[0162] The rotation control module is used to acquire wind speed and direction data when snowfall continues in the target photovoltaic area, and adjust the rotation angle of the support actuator in the photovoltaic sub-area within the target photovoltaic area based on the wind speed and direction data.

[0163] In this embodiment, after snowfall ceases in the target photovoltaic area, real-time irradiance data and real-time power generation of the photovoltaic sub-regions within the target photovoltaic area are acquired. A reference power generation corresponding to the real-time irradiance data of the photovoltaic sub-region is determined. The reference power generation is the power generation when the snow accumulation in the photovoltaic sub-region is lower than a preset snow accumulation level. Based on the real-time power generation and the reference power generation, a snow removal method for the photovoltaic sub-region is determined, and snow removal operations are performed on the photovoltaic sub-region according to the snow removal method. That is, in this application, after snowfall, snow accumulation will affect the power generation of the photovoltaic sub-region. Therefore, the snow removal method is determined based on the degree of influence of snow accumulation on power generation, i.e., based on the relative magnitude of the real-time power generation and the reference power generation, so that the snow removal method matches the snow accumulation situation of the photovoltaic sub-region, thereby enabling accurate snow removal operations in the photovoltaic sub-region and improving snow removal accuracy.

[0164] It should be noted that the working process of each module, submodule and unit in this embodiment is described in the corresponding description in the above embodiment, and will not be repeated here.

[0165] This application also provides an electronic device, including at least one processor and a memory connected to the processor, wherein:

[0166] Memory is used to store computer programs;

[0167] The processor is used to execute computer programs so that the electronic equipment can implement the snow removal control method described above.

[0168] This application also provides a snow removal control system, including the aforementioned electronic equipment.

[0169] The electronic equipment communicates with the tracking control unit (TCU) in the photovoltaic sub-area through the communication box to send the snow removal method to the tracking control unit. The tracking control unit then controls the corresponding support actuator to rotate according to the snow removal method.

[0170] This application also provides a computer program product including computer-readable instructions, which, when executed on an electronic device, cause the electronic device to implement any of the snow removal control methods provided in this application.

[0171] This application also provides a computer-readable storage medium that carries one or more computer programs. When the one or more computer programs are executed by an electronic device, the electronic device can implement any of the snow removal control methods provided in this application.

[0172] It should also be noted that the device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. In addition, in the accompanying drawings of the device embodiments provided in this application, the connection relationship between modules indicates that they have a communication connection, which can be implemented as one or more communication buses or signal lines.

[0173] Through the above description of the embodiments, those skilled in the art can clearly understand that this application can be implemented by means of software plus necessary general-purpose hardware, or it can be implemented by special-purpose hardware including application-specific integrated circuits, special-purpose CPUs, special-purpose memory, special-purpose components, etc. Generally, any function performed by a computer program can be easily implemented by corresponding hardware, and the specific hardware structure used to implement the same function can also be diverse, such as analog circuits, digital circuits, or special-purpose circuits. However, for this application, software program implementation is more often the preferred implementation method. Based on this 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 readable storage medium, such as a computer floppy disk, USB flash drive, mobile hard disk, ROM, RAM, magnetic disk, or optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, training equipment, or network device, etc.) to execute the methods of the various embodiments of this application.

[0174] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, as a computer program product.

[0175] A computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the flow or function according to the embodiments of this application is generated. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, computer instructions may be transmitted from one website, computer, training device, or data center to another website, computer, training device, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium may be any available medium that a computer can store or a data storage device such as a training device or data center that integrates one or more available media. The available media may be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., DVDs), or semiconductor media (e.g., solid-state drives (SSDs)).

Claims

1. A snow removal control method, characterized in that, include: After snowfall ceases in the target photovoltaic area, real-time irradiance data and real-time power generation of the photovoltaic sub-regions within the target photovoltaic area are acquired. Determine the reference power generation corresponding to the real-time irradiance data of the photovoltaic sub-region; the reference power generation is the power generation when the snow accumulation in the photovoltaic sub-region is lower than the preset snow accumulation. Based on the real-time power generation and the reference power generation, the snow removal method for the photovoltaic sub-region is determined; Snow removal operations are performed on the photovoltaic sub-area according to the described snow removal method.

2. The snow removal control method according to claim 1, characterized in that, Based on the real-time power generation and the reference power generation, the snow removal method for the photovoltaic sub-region is determined, including: Calculate the ratio of the real-time power generation to the reference power generation; If the ratio is less than a preset threshold, the snow removal method for the photovoltaic sub-region is determined based on the ratio; wherein, if the ratio is greater than or equal to the preset threshold, the snow removal operation for the photovoltaic sub-region is stopped.

3. The snow removal control method according to claim 2, characterized in that, Determining the snow removal method for the photovoltaic sub-region based on the ratio includes: Determine the first target rotation angle of the support actuator in the photovoltaic sub-region corresponding to the ratio, wherein the ratio is negatively correlated with the first target rotation angle of the support actuator; The snow removal method for the photovoltaic sub-area is determined as follows: the support actuator is controlled to rotate according to the first target rotation angle until the next detection time of the real-time irradiance data and the real-time power generation is reached; Alternatively, the snow accumulation level of the photovoltaic sub-region can be obtained, and the ratio and the second target rotation angle of the support actuator of the photovoltaic sub-region corresponding to the snow accumulation level can be determined; wherein, the ratio is negatively correlated with the second target rotation angle of the support actuator, and the snow accumulation level is positively correlated with the second target rotation angle of the support actuator. The snow removal method for the photovoltaic sub-area is determined as follows: the support actuator is controlled to rotate according to the second target rotation angle until the next detection time of the real-time irradiance data and the real-time power generation is reached, at which point the rotation stops.

4. The snow removal control method according to claim 2, characterized in that, Determining the snow removal method for the photovoltaic sub-region based on the ratio includes: Get the current ambient temperature; The current ambient temperature, the real-time irradiance data, and the ratio are processed using a data processing model to obtain the snow removal method for the photovoltaic sub-region. The data processing model is obtained by training using sample data; the sample data includes: The reference photovoltaic sub-region is defined as the photovoltaic sub-region whose real-time power generation ratio is greater than the reference power generation ratio after snow removal operation.

5. The snow removal control method according to claim 1, characterized in that, According to the snow removal method described above, snow removal operations are performed on the photovoltaic sub-area, including: The snow removal method is sent to the tracking control unit in the photovoltaic sub-area, so that the tracking control unit controls the corresponding support actuator to rotate according to the snow removal method to perform snow removal operation on the photovoltaic sub-area.

6. The snow removal control method according to claim 1, characterized in that, Before acquiring real-time irradiance data and real-time power generation of the photovoltaic sub-regions within the target photovoltaic region, the process also includes: Detect the snow accumulation level in the photovoltaic sub-regions within the target photovoltaic region; Identify the target photovoltaic sub-region where the snow accumulation is greater than the preset snow accumulation level; Control the support actuator in the target photovoltaic sub-region to perform a preset rotation operation.

7. The snow removal control method according to claim 1, characterized in that, Determining the reference power generation corresponding to the real-time irradiance data of the photovoltaic sub-region includes: Obtain the correspondence between irradiation data and power generation; wherein the correspondence is obtained by statistical analysis of historical irradiation data and historical power generation in historical power generation data; The reference power generation corresponding to the real-time irradiance data of the photovoltaic sub-region can be obtained from the correspondence.

8. The snow removal control method according to claim 1, characterized in that, If snowfall continues in the target photovoltaic area, the snow removal control method further includes: Obtain wind speed and direction data; Based on the wind speed and direction data, the rotation angle of the support actuator in the photovoltaic sub-region of the target photovoltaic region is adjusted.

9. A snow removal control device, characterized in that, include: The acquisition module is used to acquire real-time irradiance data and real-time power generation of the photovoltaic sub-regions in the target photovoltaic area after snowfall stops in the target photovoltaic area; The power determination module is used to determine the reference power generation corresponding to the real-time irradiance data of the photovoltaic sub-region; the reference power generation is the power generation when the snow accumulation in the photovoltaic sub-region is lower than the preset snow accumulation. The snow removal method determination module is used to determine the snow removal method of the photovoltaic sub-region based on the real-time power generation and the reference power generation; The snow removal module is used to perform snow removal operations on the photovoltaic sub-area according to the snow removal method.

10. An electronic device, characterized in that, It includes at least one processor and a memory connected to the processor, wherein: The memory is used to store computer programs; The processor is used to execute the computer program to enable the electronic device to implement the snow removal control method as described in any one of claims 1 to 8.

11. A snow removal control system, characterized in that, Including the electronic device as described in claim 10; The electronic device communicates with the tracking control unit in the photovoltaic sub-area through the communication box to send the snow removal method to the tracking control unit, and the tracking control unit controls the corresponding support actuator to rotate according to the snow removal method.

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