A single-unit equivalent modeling method for new energy power stations

Abstract

The present invention provides a single-machine equivalent modeling method for a new energy power station. The single-machine equivalent modeling method for a photovoltaic power station is a model that simplifies the entire photovoltaic power station into an equivalent single unit, so as to be used in power system simulation research. The control strategies of photovoltaic converters mainly include the following three types: maximum power point tracking control, active and reactive power control, and grid adaptive control. According to the connection mode of photovoltaic modules, they can be divided into centralized and distributed topological structures. Different topological structures will affect the electrical characteristics and control strategies of the power station. The output power of photovoltaic modules is closely related to the solar irradiance, and the irradiance may be different at different locations in the power station. The ambient temperature affects the efficiency of photovoltaic modules and the performance of converters. The temperature distribution in the power station area may be uneven.

Description

Technical Field

[0001] The present invention relates to the technical field of photovoltaic power stations, and in particular to a single-machine equivalent modeling method for a new energy power station. Background Art

[0002] According to the connection method of photovoltaic modules, there are two topological structures: centralized and distributed. Different topological structures will affect the electrical characteristics and control strategies of the power station. The output power of photovoltaic modules is closely related to the solar irradiance, which may vary at different locations of the power station. The ambient temperature affects the efficiency of photovoltaic modules and the performance of the converter. The temperature distribution in the power station area may be uneven. Centralized photovoltaic power stations are mainly built in desert areas. Deserts have sufficient sunlight, drought and little rain. The construction sites of photovoltaic power stations are almost free of trees or other buildings. The electricity generated by photovoltaic power stations is transmitted to the public power grid and connected to the high-voltage transmission system to supply long-distance loads.

[0003] In the process of establishing a single-machine equivalent model, an equivalent circuit model needs to be established. By establishing equivalent circuit models of photovoltaic modules and photovoltaic converters, the complex physical process is converted into a simplified mathematical model. Then, according to the characteristics of the actual photovoltaic modules and photovoltaic converters, the parameters in the equivalent circuit model are determined. By comparing with the operating data of the applied power station, the accuracy and reliability of the single-machine equivalent model are verified. Select appropriate electromagnetic transient simulation software, import the established single-machine equivalent model into the simulation platform, and set the parameters.

[0004] However, in the actual power generation process, there is a problem: the desert area is dry and rainless, with high dust content and many birds. Dust, dirt or bird excrement will accumulate on the surface of the photovoltaic modules, affecting the power generation of the photovoltaic power station. Manual cleaning is required, which is very inconvenient. Therefore, it is very necessary to reduce manual cleaning of photovoltaic modules and ensure the normal operation of photovoltaic power stations. Summary of the invention

[0005] Therefore, the present invention provides a single-machine equivalent modeling method for a new energy power station, wherein the photovoltaic power station includes an operation and maintenance center, and the operation and maintenance center is provided with a drone and a cleaning robot, and the modeling method includes: building a photovoltaic power station model, wherein the photovoltaic power station model is an equivalent model of the photovoltaic power station, and the photovoltaic power station model has multiple photovoltaic modules; selecting an origin photovoltaic module according to the position of the photovoltaic module, and establishing a position coordinate system; setting a first inspection route of the drone according to the position coordinate system, and controlling the drone to operate according to the first inspection route, controlling the drone to obtain the transmittance of the photovoltaic module and photos of the photovoltaic module; and feeding back to the operation and maintenance center; controlling the operation and maintenance center to determine whether the photovoltaic module is dirty and the corresponding type of dirt according to the transmittance and photos; controlling the cleaning robot to execute the corresponding cleaning mode according to the type of dirt; generating a target range of dirty photovoltaic modules when the photovoltaic modules are dirty; setting a second inspection route of the drone according to the target range; and controlling the drone to operate according to the second inspection route; wherein the target range is a set of position coordinates of dirty photovoltaic modules.

[0006] Compared with the prior art, the technical effect achieved by adopting the technical solution is as follows: first, a photovoltaic power station model is built based on a photovoltaic power station. The photovoltaic power station model has multiple photovoltaic modules. One of the photovoltaic modules is selected as the origin photovoltaic module. According to the origin photovoltaic module, a position coordinate system is established so that each photovoltaic module has corresponding coordinates. The photovoltaic power station is inspected by a drone. Therefore, according to the position coordinate system, a first inspection route of the drone is set. According to the first inspection route, the drone performs the first inspection. In the process of performing the first inspection, the drone obtains the transmittance and photos of the photovoltaic modules, and feeds the photos and transmittance back to the operation and maintenance center. After obtaining the photos and transmittance of each photovoltaic module, the operation and maintenance center analyzes them one by one to determine whether the photovoltaic module is dirty and the corresponding type of dirt. According to the type of dirt of the photovoltaic module, the cleaning mode that the cleaning robot needs to execute is determined to generate a target range. The target range includes the position coordinates of the dirty photovoltaic modules. According to the target range, a second inspection route is set. After the cleaning robot cleans, the drone inspects again to check the cleaning effect of the cleaning robot, thereby ensuring the normal operation of the photovoltaic power station.

[0007] Furthermore, according to the position coordinate system, a first inspection route of the UAV is set, specifically including: taking the origin photovoltaic module as the starting point of the first inspection route, wherein the first inspection route is "S" shaped.

[0008] Compared with the existing technology, the technical effect achieved by adopting this technical solution is as follows: according to the position coordinate system, the first inspection route is set, and the origin photovoltaic module is used as the starting point of the first inspection route. The first inspection route is "S" shaped, so that the first inspection route can cover all photovoltaic modules, avoid missed inspections, and reduce the time of drone inspections.

[0009] Furthermore, the drone is provided with a detection device and a photographing device, which controls the drone to obtain the transmittance of the photovoltaic module and take photos of the photovoltaic module, specifically including: controlling the detection device to detect the transmittance of the photovoltaic module, and controlling the photographing device to take photos of the photovoltaic module.

[0010] Compared with the prior art, the technical effect achieved by adopting this technical solution is as follows: the drone is provided with a detection device and a shooting device. The detection device can emit light to the photovoltaic module, and then collect the light reflected back by the photovoltaic module to obtain the transmittance of the photovoltaic module. In addition, the detection device detects different positions of the photovoltaic module to determine whether the dust on the surface of the photovoltaic module will affect the power generation of the photovoltaic module. The shooting device can take pictures of the photovoltaic module to facilitate the judgment of whether there is bird excrement on the surface of the photovoltaic module.

[0011] Furthermore, controlling the detection device to detect the transmittance of the photovoltaic module specifically includes: controlling the detection device to detect the transmittance of the photovoltaic module multiple times to obtain multiple transmittances; comparing the multiple transmittances to obtain a minimum value among the multiple transmittances; and feeding back the minimum value to the operation and maintenance center.

[0012] Compared with the prior art, the technical effect achieved by adopting this technical solution is as follows: the smaller the transmittance value is, the more dust there is on the surface of the photovoltaic module. Therefore, after the detection device obtains multiple transmittances, the minimum value of the multiple transmittances is fed back to the operation and maintenance center to prevent the operation and maintenance center from making misjudgments. The operation and maintenance center determines whether the dust on the surface of the photovoltaic module affects the power generation of the photovoltaic module based on the minimum value.

[0013] Furthermore, the type of dirt on the photovoltaic module is determined based on the transmittance and the photograph, specifically including: judging based on the photograph whether there are irregular spots on the surface of the photovoltaic module, and judging whether the minimum value meets the transmittance range to obtain a judgment result; judging the type of dirt on the photovoltaic module based on the judgment result; wherein the transmittance range is the transmittance range of the photovoltaic module surface that can meet the requirements of photovoltaic power generation.

[0014] Compared with the prior art, the technical effect achieved by adopting this technical solution is as follows: the photo can show whether the surface of the photovoltaic module has any irregular spots. Therefore, the photo can be used to intuitively judge whether there is bird excrement on the surface of the photovoltaic module, and whether the minimum value falls within the light transmittance range. If the minimum value falls within the light transmittance range, it can be explained that the dust on the surface of the photovoltaic module will not affect the power generation of the photovoltaic module. If the minimum value does not meet the light transmittance range, it can be explained that the dust on the surface of the photovoltaic module will affect the power generation of the photovoltaic module, and therefore, it needs to be cleaned in time.

[0015] Furthermore, based on the judgment result, the type of dirtiness of the photovoltaic module is judged, specifically including: when there are irregular spots on the surface of the photovoltaic module and the minimum value satisfies the light transmission range, the photovoltaic module is of the first type of dirtiness; when there are irregular spots on the surface of the photovoltaic module and the minimum value does not satisfy the light transmission range, the photovoltaic module is of the second type of dirtiness; when there are no irregular spots on the surface of the photovoltaic module and the minimum value does not satisfy the light transmission range, the photovoltaic module is of the third type of dirtiness; wherein, the first type of dirtiness is that the surface of the photovoltaic module has bird excrement or dirt, the second type of dirtiness is that the surface of the photovoltaic module has bird excrement and dust, and the third type of dirtiness is that the surface of the photovoltaic module has dust.

[0016] Compared with the prior art, the technical effect achieved by adopting this technical solution is as follows: based on the judgment result, the dirt is distinguished, and when there are no irregular spots on the surface of the photovoltaic module and the minimum value does not meet the light transmittance range, the photovoltaic module is of the third dirt type; wherein, the first dirt type is that the surface of the photovoltaic module has bird excrement or dirt, the second dirt type is that the surface of the photovoltaic module has bird excrement and dust, and the third dirt type is that the surface of the photovoltaic module has dust. The dirt type is related to the cleaning mode of the cleaning robot. Therefore, the dirt type is clearly distinguished, which is convenient for selecting the cleaning mode for the cleaning robot.

[0017] Further, according to the target range, the second inspection route of the UAV is set, which specifically includes: selecting the target starting point k according to the target range n ; According to the target starting point k n , get the target starting point k n The straight-line distance between the target position and the target range; through the straight-line distance, determine the starting point k n The next target position k n+1 ; where n is the order of the target position.

[0018] Compared with the prior art, the technical effect achieved by adopting this technical solution is: the target range is a set of position coordinates of dirty photovoltaic coordinates, and the target starting point k is selected within the target range. n, obtain the straight-line distance between the target positions within the target range, and select the next target position k according to the straight-line distance n+1 , continue to take the next target position as the target starting point k n , select the next target position k n+1 , thereby completing the setting of the second inspection route. Through this setting method, the inspection time of the drone can be reduced and the inspection efficiency can be improved.

[0019] Furthermore, by using the straight-line distance, the starting point k is determined n The next target position k n+1 After that, the modeling method further includes: clearing the starting position k n .

[0020] Compared with the prior art, the technical effect achieved by adopting this technical solution is: after determining the next target position k n+1 After that, the last starting point position has been inspected by the drone. Therefore, in order to avoid repeated inspections, the last starting point position is cleared after the next target position is determined.

[0021] After adopting the technical solution of the present invention, the following technical effects can be achieved:

[0022] (1) Based on the photovoltaic power station, a photovoltaic power station model is built. The photovoltaic power station model has multiple photovoltaic modules. One of the photovoltaic modules is selected as the origin photovoltaic module. According to the origin photovoltaic module, a position coordinate system is established so that each photovoltaic module has a corresponding coordinate. The photovoltaic power station is inspected by a drone. Therefore, according to the position coordinate system, the first inspection route of the drone is set. The drone performs the first inspection according to the first inspection route. During the first inspection, the drone obtains the transmittance and photos of the photovoltaic modules, and feeds the photos and transmittance to the operation and maintenance center. After obtaining the photos and transmittance of each photovoltaic module, the operation and maintenance center analyzes them one by one to determine whether the photovoltaic module is dirty and the corresponding type of dirt. According to the type of dirt of the photovoltaic module, the cleaning mode that the cleaning robot needs to execute is determined, and a target range is generated. The target range includes the position coordinates of the dirty photovoltaic modules. According to the target range, the second inspection route is set. After the cleaning robot cleans, the drone conducts another inspection to verify the cleaning effect of the cleaning robot, thereby ensuring the normal operation of the photovoltaic power station;

[0023] (2) According to the position coordinate system, the first inspection route is set, and the origin photovoltaic module is used as the starting point of the first inspection route. The first inspection route is "S" shaped, so that the first inspection route can cover all photovoltaic modules, avoid missed inspections, and reduce the time of drone inspections;

[0024] (3) The drone is equipped with a detection device and a shooting device. The detection device can emit light to the photovoltaic module and then collect the light reflected by the photovoltaic module to obtain the transmittance of the photovoltaic module. In addition, the detection device detects different positions of the photovoltaic module to determine whether the dust on the surface of the photovoltaic module will affect the power generation of the photovoltaic module. The shooting device can take pictures of the photovoltaic module to facilitate the determination of whether there is bird excrement on the surface of the photovoltaic module. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 A flowchart of a single-machine equivalent modeling solution for a photovoltaic power station provided by an embodiment of the present invention;

[0026] Figure 2 is a schematic diagram of the position coordinate system of the photovoltaic module;

[0027] Figure 3 It is a schematic diagram of the structure of a photovoltaic module;

[0028] Figure 4 This is a schematic diagram of the second inspection route. DETAILED DESCRIPTION

[0029] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0030] The embodiment of the present invention provides a single-machine equivalent modeling method for a new energy power station. The photovoltaic power station includes an operation and maintenance center, which is equipped with a drone and a cleaning robot. The modeling method is as shown in the attached figure. Figure 1 As shown:

[0031] S100, building a photovoltaic power station model;

[0032] S200, selecting an origin photovoltaic module according to the position of the photovoltaic module, and establishing a position coordinate system;

[0033] S300, setting a first inspection route of the drone according to the position coordinate system, and controlling the drone to run according to the first inspection route;

[0034] S400, controls the drone to obtain the transmittance of the photovoltaic modules and photos of the photovoltaic modules, and feeds back to the operation and maintenance center;

[0035] S500, the control operation and maintenance center determines whether the photovoltaic module is dirty and the corresponding dirt type according to the light transmittance and the photo;

[0036] S600, controlling the cleaning robot to execute a corresponding cleaning mode according to the type of dirt;

[0037] S700, when the photovoltaic modules are dirty, generating a target range of the dirty photovoltaic modules;

[0038] S800, setting a second inspection route for the UAV according to the target range, and controlling the UAV to operate according to the second inspection route;

[0039] Specifically, first, a photovoltaic power station model is built based on the photovoltaic power station. The photovoltaic power station model has multiple photovoltaic modules. One of the photovoltaic modules is selected as the origin photovoltaic module. According to the origin photovoltaic module, a position coordinate system is established so that each photovoltaic module has corresponding coordinates. The photovoltaic power station is inspected by a drone. Therefore, according to the position coordinate system, a first inspection route of the drone is set. The drone performs the first inspection according to the first inspection route. During the first inspection, the drone obtains the transmittance and photos of the photovoltaic modules, and feeds the photos and transmittance to the operation and maintenance center. After obtaining the photos and transmittance of each photovoltaic module, the operation and maintenance center analyzes them one by one to determine whether the photovoltaic module is dirty and the corresponding type of dirt. According to the type of dirt of the photovoltaic module, the cleaning mode that the cleaning robot needs to execute is determined to generate a target range. The target range includes the position coordinates of the dirty photovoltaic modules. According to the target range, a second inspection route is set. After the cleaning robot cleans, the drone inspects again to verify the cleaning effect of the cleaning robot, thereby ensuring the normal operation of the photovoltaic power station.

[0040] Specifically, according to the position coordinate system, the first inspection route of the drone is set, which specifically includes: taking the origin photovoltaic module as the starting point of the first inspection route, wherein the first inspection route is "S" shaped.

[0041] Specifically, the display of photovoltaic modules is as follows: Figure 2 As shown, according to the position coordinate system, the first inspection route is set, and the origin photovoltaic module is used as the starting point of the first inspection route. The first inspection route is "S" shaped, so that the first inspection route can cover all photovoltaic modules, avoid missed inspections, and reduce the time of drone inspections.

[0042] Specifically, the drone is provided with a detection device and a shooting device, and controlling the drone to obtain the transmittance of the photovoltaic module and take photos of the photovoltaic module specifically includes: controlling the detection device to detect the transmittance of the photovoltaic module, and controlling the shooting device to take photos of the photovoltaic module.

[0043] Specifically, the drone is equipped with a detection device and a shooting device. The detection device can emit light to the photovoltaic module, and then collect the light reflected back by the photovoltaic module to obtain the transmittance of the photovoltaic module. In addition, the detection device detects different positions of the photovoltaic module to determine whether the dust on the surface of the photovoltaic module will affect the power generation of the photovoltaic module. The shooting device can take pictures of the photovoltaic module to facilitate the judgment of whether there is bird excrement on the surface of the photovoltaic module.

[0044] For example, controlling the detection device to detect the transmittance of the photovoltaic module specifically includes: controlling the detection device to detect the transmittance of the photovoltaic module multiple times to obtain multiple transmittances; comparing the multiple transmittances to obtain a minimum value among the multiple transmittances; and feeding back the minimum value to the operation and maintenance center.

[0045] For example, as shown in the attached Figure 3 As shown in the figure, the detection device performs multi-point detection on the surface of the photovoltaic module, and the position of each detection is different. The number of detections is adjusted according to the actual situation. Figure 3 The dots in the figure are the positions of the photovoltaic modules detected by the detection device. The detection device can emit light to the photovoltaic modules and then collect the light reflected by the photovoltaic modules to obtain the light transmittance of the photovoltaic modules. In addition, the detection device detects different positions of the photovoltaic modules to determine whether the dust on the surface of the photovoltaic modules will affect the power generation of the photovoltaic modules. The shooting device can take pictures of the photovoltaic modules to determine whether there is bird excrement on the surface of the photovoltaic modules.

[0046] For example, judging the type of dirt on the photovoltaic module based on the transmittance and the photograph, specifically including: judging whether there are irregular spots on the surface of the photovoltaic module based on the photograph, and judging whether the minimum value meets the transmittance range to obtain a judgment result; judging the type of dirt on the photovoltaic module based on the judgment result; wherein the transmittance range is the transmittance range of the photovoltaic module surface that can meet the requirements of photovoltaic power generation.

[0047] For example, the smaller the transmittance value is, the more dust there is on the surface of the photovoltaic module. Therefore, after the detection device obtains multiple transmittances, the minimum value of the multiple transmittances is fed back to the operation and maintenance center to prevent the operation and maintenance center from misjudgment. The operation and maintenance center determines whether the dust on the surface of the photovoltaic module affects the power generation of the photovoltaic module based on the minimum value.

[0048] Specifically, the type of dirtiness of the photovoltaic module is determined according to the judgment result, specifically including: when there are irregular spots on the surface of the photovoltaic module and the minimum value satisfies the light transmission range, the photovoltaic module is of the first type of dirtiness; when there are irregular spots on the surface of the photovoltaic module and the minimum value does not satisfy the light transmission range, the photovoltaic module is of the second type of dirtiness; when there are no irregular spots on the surface of the photovoltaic module and the minimum value does not satisfy the light transmission range, the photovoltaic module is of the third type of dirtiness; wherein, the first type of dirtiness is that the surface of the photovoltaic module has bird excrement or dirt, the second type of dirtiness is that the surface of the photovoltaic module has bird excrement and dust, and the third type of dirtiness is that the surface of the photovoltaic module has dust.

[0049] Specifically, the dirt is differentiated according to the judgment results. When there are no irregular spots on the surface of the photovoltaic module and the minimum value does not meet the light transmittance range, the photovoltaic module is of the third dirt type; among them, the first dirt type is that the surface of the photovoltaic module has bird excrement or dirt, the second dirt type is that the surface of the photovoltaic module has bird excrement and dust, and the third dirt type is that the surface of the photovoltaic module has dust. The dirt type is related to the cleaning mode of the cleaning robot. Therefore, the dirt type is clearly distinguished to facilitate the selection of the cleaning mode for the cleaning robot.

[0050] For example, according to the target range, the second inspection route of the drone is set, specifically including: selecting the target starting point k according to the target range n ; According to the target starting point k n , get the target starting point k n The straight-line distance between the target position and the target range; through the straight-line distance, determine the starting point k n The next target position k n+1 ; where n is the order of the target position.

[0051] For example, the target range is the set of position coordinates of the dirty photovoltaic coordinates, and the target starting point k is selected within the target range. n , obtain the straight-line distance between the target positions within the target range, and select the next target position k according to the straight-line distance n+1 , continue to take the next target position as the target starting point k n , select the next target position k n+1 , thereby completing the setting of the second inspection route. Through this setting method, the inspection time of the drone can be reduced and the inspection efficiency can be improved.

[0052] Supplementary note: The straight-line distance between target positions within the target range is the distance between the center points of the PV modules. Figure 2As shown, in the X-axis direction, the X-axis coordinate of the first photovoltaic module is 1, the X-axis coordinate of the second photovoltaic module is 2, and so on, the X-axis coordinate of the n-th photovoltaic module is n; in the Y-axis direction, the Y-axis coordinate of the first photovoltaic module is 1, the Y-axis coordinate of the second photovoltaic module is 2, and so on, the Y-axis coordinate of the n-th photovoltaic module is n. The coordinates of the X-axis and Y-axis together constitute the position coordinates of a photovoltaic module, and the coordinates of the origin photovoltaic module are (1, 1).

[0053] For example, as shown in the attached Figure 4 As shown, attached Figure 4 Only one method for determining the second inspection route is shown. Figure 4 The PV modules marked in the target range are dirty, so the target range is the set of PV modules marked. The origin PV module is used as the target starting point of the second inspection route, and the straight-line distance between other PV modules in the target range and the target starting point is identified. The straight-line distance between the PV module with coordinates (1, 2) and the target starting point is the shortest. Therefore, the next target position can be determined. After determining the next target position, clear the previous target starting point, that is, the next target starting point. Figure 4 The origin PV module with coordinates (1, 1) is removed from the target range.

[0054] Then, the next target position is taken as the target starting point, and the next target position is determined by the straight-line distance. The above steps are repeated to complete the setting of the second inspection route.

[0055] Supplementary explanation: when selecting the next target position, if two points with the same distance appear, the X-axis coordinates of the two points are compared, and the point with the larger X-axis coordinate is preferably selected as the next target position.

[0056] Specifically, by using the straight-line distance, determine the starting point k n The next target position k n+1 After that, the modeling method further includes: clearing the starting position k n .

[0057] Specifically, after determining the next target position k n+1 After that, the last starting point position has been inspected by the drone. Therefore, in order to avoid repeated inspections, the last starting point position is cleared after the next target position is determined.

[0058] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A single-machine equivalent modeling method for a new energy power station, characterized in that: The equivalent modeling method is used to control a photovoltaic power station, wherein the photovoltaic power station includes an operation and maintenance center, wherein the operation and maintenance center is provided with a drone and a cleaning robot, and the modeling method includes: Building a photovoltaic power station model, wherein the photovoltaic power station model is an equivalent model of the photovoltaic power station, and the photovoltaic power station model has a plurality of photovoltaic modules; According to the position of the photovoltaic module, an origin photovoltaic module is selected, and a position coordinate system is established so that each photovoltaic module has a corresponding coordinate; According to the position coordinate system, a first inspection route of the drone is set, and the drone is controlled to run according to the first inspection route, with the origin photovoltaic component as the starting point of the first inspection route; wherein the origin photovoltaic component is the photovoltaic component at the origin of the position coordinate system, and the first inspection route is "S" shaped; The drone is provided with a detection device and a photographing device, and controlling the drone to obtain the light transmittance of the photovoltaic module and the photo of the photovoltaic module specifically includes: controlling the detection device to detect the light transmittance of the photovoltaic module, and controlling the photographing device to take the photo of the photovoltaic module; Controlling the drone to obtain the light transmittance of the photovoltaic module and photos of the photovoltaic module, and feeding back the results to the operation and maintenance center; Controlling the operation and maintenance center to determine whether the photovoltaic module is dirty and the corresponding dirt type according to the light transmittance and the photo; According to the dirt type, controlling the cleaning robot to execute a corresponding cleaning mode; In the case where the photovoltaic assembly is dirty, generating a target range of the photovoltaic assembly that is dirty; According to the target range, setting a second inspection route for the drone, and controlling the drone to operate according to the second inspection route; The target range is a set of position coordinates of the photovoltaic components that are dirty.

2. The equivalent modeling method according to claim 1, characterized in that: The controlling the detection device to detect the light transmittance of the photovoltaic module specifically includes: Controlling the detection device to detect the light transmittance of the photovoltaic module multiple times to obtain multiple light transmittances; Comparing the plurality of light transmittances to obtain a minimum value among the plurality of light transmittances; The minimum value is fed back to the operation and maintenance center.

3. The equivalent modeling method according to claim 2, characterized in that: The determining the type of dirt on the photovoltaic module according to the light transmittance and the photo specifically includes: According to the photo, judging whether there are irregular spots on the surface of the photovoltaic module, and judging whether the minimum value meets the light transmission range, and obtaining a judgment result; According to the determination result, determining the type of dirt on the photovoltaic module; The light transmittance range is the light transmittance range of the photovoltaic module surface that can meet the requirements of photovoltaic power generation.

4. The equivalent modeling method according to claim 3, characterized in that: The determining, according to the determination result, the type of dirt on the photovoltaic module specifically includes: When the irregular spots exist on the surface of the photovoltaic component and the minimum value satisfies the light transmission range, the photovoltaic component is of the first dirt type; When the irregular spots exist on the surface of the photovoltaic component and the minimum value does not satisfy the light transmission range, the photovoltaic component is of the second dirt type; When the irregular spots do not exist on the surface of the photovoltaic component and the minimum value does not satisfy the light transmission range, the photovoltaic component is of the third dirt type; Among them, the first dirt type is that the surface of the photovoltaic component has bird excrement or dirt, the second dirt type is that the surface of the photovoltaic component has bird excrement and dust, and the third dirt type is that the surface of the photovoltaic component has dust.

5. The equivalent modeling method according to claim 4, characterized in that: The cleaning robot has an absorption device and a scrubbing device, and according to the dirt type, the cleaning robot is controlled to execute a corresponding cleaning mode, specifically including: When the photovoltaic assembly is of a first dirty type, controlling the cleaning robot to execute a first cleaning mode; When the photovoltaic assembly is of a second dirty type, controlling the cleaning robot to execute a second cleaning mode; When the photovoltaic assembly is of a third type of dirt, controlling the cleaning robot to execute a third cleaning mode; The first cleaning mode is to start the scrubbing device, the second cleaning mode is to start the scrubbing device and the absorbing device, and the third cleaning mode is to start the absorbing device.

6. The equivalent modeling method according to claim 1, characterized in that: The step of setting a second inspection route of the drone according to the target range specifically includes: According to the target range, select the target starting point k n ; According to the target starting point k n , get the target starting point k n The straight-line distance from the target location within the target range; Determine the starting point k by the straight-line distance n The next target position k n+1 ; Wherein, n is the order of the target position.

7. The equivalent modeling method according to claim 6, characterized in that: After passing the straight line distance, determine the starting point position k n The next target position k n+1 Afterwards, the modeling method further comprises: Clear the starting position k n .

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