Photovoltaic panel full-automatic mobile cleaning system and method based on timing control

Abstract

The application provides a photovoltaic panel full-automatic mobile cleaning system and method based on timing control, acquires real-time dust thickness, power generation efficiency, weather data and surface image data of the photovoltaic panel through a sensor, combines historical data to predict pollution of the photovoltaic panel in a future period of time, realizes accurate prediction of the photovoltaic panel based on comprehensive data, provides accurate photovoltaic panel conditions for automatic cleaning control, determines a cleaning time point of the photovoltaic panel based on the pollution of the photovoltaic panel in the future period of time and the use condition of the photovoltaic panel, guarantees rationality of the cleaning time, determines a cleaning path of the photovoltaic panel by the cleaning equipment based on arrangement characteristics of the photovoltaic panel, the pollution condition and the cleaning time point, guarantees rationality of the cleaning path, establishes timing control based on the cleaning time point and the cleaning path, automatically cleans the photovoltaic panel by the cleaning equipment, and realizes reduction of energy consumption of photovoltaic panel cleaning while guaranteeing power generation efficiency.

Description

Technical Field

[0001] This invention relates to the field of photovoltaic panel cleaning technology, and in particular to a fully automatic mobile photovoltaic panel cleaning system and method based on timed control. Background Technology

[0002] Currently, photovoltaic panels are often covered with dust due to their outdoor location, which affects their data collection and thus their power generation efficiency. Existing fully automated mobile cleaning equipment can clean the dust from photovoltaic panels and improve their power generation efficiency.

[0003] However, how to optimize the cleaning process to minimize resource consumption, such as water and electricity consumption and equipment wear and tear, while ensuring power generation efficiency when cleaning photovoltaic panels using fully automated mobile cleaning equipment is a problem that needs to be solved in photovoltaic panel cleaning. Summary of the Invention

[0004] This invention provides a fully automatic mobile cleaning system and method for photovoltaic panels based on timed control, in order to solve the problems mentioned in the background art.

[0005] A fully automated mobile cleaning system for photovoltaic panels based on timed control includes:

[0006] The data acquisition module is used to acquire real-time dust thickness, power generation efficiency, weather data, and surface image data of photovoltaic panels through sensors;

[0007] The pollution prediction module is used to predict the pollution level of photovoltaic panels in the future based on dust thickness, power generation efficiency, weather data, and surface image data, combined with historical data.

[0008] The timing module determines the cleaning time for the photovoltaic panels based on their pollution levels and usage over a future period.

[0009] The path determination module is used to determine the cleaning path of the cleaning equipment for the photovoltaic panels based on the arrangement characteristics of the photovoltaic panels, combined with the contamination situation and cleaning time points;

[0010] The cleaning control module is used to establish timed control based on cleaning time points and cleaning paths, and to automatically clean photovoltaic panels using cleaning equipment.

[0011] Preferably, the data acquisition module includes:

[0012] The dust data acquisition unit is used to obtain the dust thickness on the surface of the photovoltaic panel in real time based on the dust sensors installed on the photovoltaic panel;

[0013] The efficiency acquisition unit is used to obtain voltage and current data based on the inverter installed on the photovoltaic panel, and to calculate the power generation efficiency based on the voltage and current data;

[0014] The meteorological data acquisition unit is used to obtain weather data based on meteorological data from the connected photovoltaic panels;

[0015] The visual acquisition unit is used to acquire surface image data of the photovoltaic panel based on visual technology.

[0016] Preferably, the pollution prediction module includes:

[0017] The model training unit is used to train the initial prediction model by acquiring historical dust thickness, historical power generation efficiency, historical weather data, and historical surface image data and their corresponding photovoltaic panel pollution data from historical data, so as to obtain the target prediction model.

[0018] The model prediction unit is used to input dust thickness, power generation efficiency, weather data, and surface image data into the target prediction model to obtain the pollution status of the photovoltaic panel in the future.

[0019] Preferably, the time determination module includes:

[0020] The predictive information acquisition unit is used to obtain the predicted dust thickness distribution and predicted power generation efficiency trend from the pollution situation of photovoltaic panels in the future, and to obtain the predicted weather trend of photovoltaic panels in the future from meteorological data.

[0021] The time determination unit is used to determine the cleaning time point for photovoltaic panels based on the predicted dust thickness distribution, predicted power generation efficiency trend, and predicted weather trend, combined with historical cleaning time setting information.

[0022] Preferably, the path determination module includes:

[0023] The priority determination unit is used to divide the photovoltaic panel into several clean areas of the same area based on the arrangement characteristics of the photovoltaic panel, and to divide the clean areas into cleaning priorities based on the pollution status of each clean area to obtain the cleaning priority.

[0024] The path determination unit is used to establish multiple initial paths that satisfy the maximum allowable invalid cleaning movement distance based on cleaning priority and the distribution characteristics of the cleaning area.

[0025] The path evaluation unit is used to evaluate multiple initial paths based on the cleaning requirements of photovoltaic panels, the usage specifications of cleaning equipment, and cost control requirements, and select the final cleaning path based on the evaluation results.

[0026] Preferably, the cleaning control module includes:

[0027] The instruction creation unit is used to create timing information based on cleaning time points, create cleaning control information based on cleaning paths, and create timing control instructions based on the timing information and cleaning control information.

[0028] The automatic cleaning unit is used to send timed control commands to the cleaning equipment to achieve automatic cleaning of the photovoltaic panels.

[0029] Preferably, the time determination unit includes:

[0030] The relationship determination unit is used to determine the correspondence between cleaning time points and photovoltaic panel characteristics from historical cleaning time setting information and historical photovoltaic panel conditions;

[0031] The time matching unit is used to determine the characteristics of future photovoltaic panels based on the predicted dust thickness distribution, predicted power generation efficiency trend and predicted weather trend, and to obtain the initial cleaning time point that matches the characteristics of future photovoltaic panels based on the correspondence.

[0032] The difference determination unit is used to obtain the equipment difference information between the current basic information and the historical basic information of the cleaning equipment, and to obtain the demand difference information between the current demand and the historical demand of photovoltaic power generation.

[0033] The time difference determination unit is used to determine the first unit time difference caused by equipment difference information, determine the second unit time difference caused by demand difference information, determine the first specific time difference based on the characteristics of the future photovoltaic panel and the first unit time difference, and determine the second specific time difference based on the characteristics of the future photovoltaic panel and the second unit time difference.

[0034] The correction unit is used to correct the initial cleaning time point based on the first specific time difference and the second specific time difference to obtain the cleaning time point for the photovoltaic panel.

[0035] Preferably, the path evaluation unit includes:

[0036] The indicator determination unit is used to determine the first indicator in the cleaning requirement dimension from the cleaning requirements of photovoltaic panels, the second indicator in the equipment dimension based on the usage specifications of the cleaning equipment, and the third indicator in the cost dimension based on cost control requirements.

[0037] The structure determination unit is used to hierarchically divide the first, second, and third indicators based on the causal relationship between the evaluation dimensions and the indicators, thereby obtaining the indicator hierarchy structure. Based on the degree of influence between the evaluation dimensions and the indicators, the indicator hierarchy structure is weighted to obtain the weighted indicator hierarchy structure.

[0038] The static establishment unit is used to establish a weighted comprehensive evaluation system for each evaluation dimension based on the normalization relationship between indicators and the weighted indicator hierarchy structure, and to determine the static evaluation structure based on the weighted comprehensive evaluation system.

[0039] The dynamic analysis unit is used to acquire the dynamic indicators among the first, second and third indicators, and to establish fuzzy control rules for the dynamic indicators based on the impact of the dynamic indicators on the evaluation dimensions. The fuzzy control rules are then added to the structural position of the dynamic indicators in the static evaluation structure to obtain the dynamic evaluation structure.

[0040] The model building unit is used to weight the dynamic evaluation structure based on the allocation ratio of the evaluation dimensions to obtain a weighted dynamic evaluation structure, and to establish an initial path evaluation model based on the weighted dynamic evaluation structure.

[0041] The model adjustment unit is used to input path information from historical data into the initial path evaluation model to obtain the predicted cleaning result. Based on the difference between the predicted cleaning result and the actual cleaning result, the weight coefficients of the initial path evaluation model are adjusted to obtain the target path evaluation model.

[0042] The model evaluation unit is used to input multiple initial paths into the target path evaluation model for evaluation, obtain pre-learning and evaluation results, and select the initial path corresponding to the best prediction and evaluation results as the final clean path.

[0043] Preferably, after obtaining the cleaning path, the system further includes: a method determination unit.

[0044] Used to determine the cleaning movement trajectory for each cleaning area based on the cleaning path, and to determine the cleaning intensity in the cleaning area in combination with the regional characteristics of the cleaning area;

[0045] Based on the cleaning intensity of every two adjacent cleaning areas, the moving speed between two adjacent unit areas is set, and the cleaning speed under the cleaning path is finally determined.

[0046] The cleaning method is determined based on the cleaning path, cleaning intensity, and cleaning speed.

[0047] A fully automated mobile cleaning method for photovoltaic panels based on timed control includes:

[0048] S1: Real-time dust thickness, power generation efficiency, weather data, and surface image data of photovoltaic panels are obtained through sensors;

[0049] S2: Based on dust thickness, power generation efficiency, weather data, and surface image data, combined with historical data, predict the pollution status of photovoltaic panels in the future.

[0050] S3: Determine the cleaning time point for photovoltaic panels based on the pollution status and usage of the photovoltaic panels in the future;

[0051] S4: Based on the arrangement characteristics of photovoltaic panels, combined with the pollution situation and cleaning time points, determine the cleaning path of the cleaning equipment for the photovoltaic panels;

[0052] S5: Establish timed control based on cleaning time points and cleaning paths, and use cleaning equipment to automatically clean photovoltaic panels.

[0053] Compared with the prior art, the present invention has achieved the following beneficial effects:

[0054] By acquiring real-time dust thickness, power generation efficiency, weather data, and surface image data of photovoltaic (PV) panels using sensors, a data foundation is provided for the timing design of fully automated mobile PV panel cleaning. Based on dust thickness, power generation efficiency, weather data, and surface image data, combined with historical data, the pollution level of PV panels in the future can be predicted. This comprehensive data enables accurate prediction of PV panel conditions, providing accurate information for automatic cleaning control. Based on the future pollution level and usage of the PV panels, the cleaning time points are determined to ensure the rationality of the cleaning schedule. Based on the arrangement characteristics of the PV panels, combined with the pollution level and cleaning time points, the cleaning path for the cleaning equipment is determined to ensure the rationality of the cleaning path. A timing control system is established based on the cleaning time points and cleaning path, allowing the cleaning equipment to automatically clean the PV panels, thereby reducing energy consumption for PV panel cleaning while maintaining power generation efficiency.

[0055] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in this application.

[0056] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0057] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings:

[0058] Figure 1 This is a structural diagram of a fully automatic mobile cleaning system for photovoltaic panels based on timed control, as described in an embodiment of the present invention.

[0059] Figure 2 This is a structural diagram of the time determination module described in an embodiment of the present invention;

[0060] Figure 3 This is a flowchart of a fully automatic mobile cleaning method for photovoltaic panels based on timed control, as described in an embodiment of the present invention. Detailed Implementation

[0061] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0062] Example 1:

[0063] This invention provides a fully automatic mobile cleaning system for photovoltaic panels based on timed control, which, as follows: Figure 1 As shown, it includes:

[0064] The data acquisition module is used to acquire real-time dust thickness, power generation efficiency, weather data, and surface image data of photovoltaic panels through sensors;

[0065] The pollution prediction module is used to predict the pollution level of photovoltaic panels in the future based on dust thickness, power generation efficiency, weather data, and surface image data, combined with historical data.

[0066] The timing module determines the cleaning time for the photovoltaic panels based on their pollution levels and usage over a future period.

[0067] The path determination module is used to determine the cleaning path of the cleaning equipment for the photovoltaic panels based on the arrangement characteristics of the photovoltaic panels, combined with the contamination situation and cleaning time points;

[0068] The cleaning control module is used to establish timed control based on cleaning time points and cleaning paths, and to automatically clean photovoltaic panels using cleaning equipment.

[0069] In this embodiment, the dust thickness on the surface of the photovoltaic panel is obtained in real time based on the dust sensor installed on the photovoltaic panel, the power generation efficiency data is obtained based on the current and voltage data of the photovoltaic panel obtained by the inverter, the image data of the surface of the photovoltaic panel is obtained based on visual detection, and the real-time weather information is obtained based on the accessed meteorological data.

[0070] In this embodiment, the contamination status of the photovoltaic panel over a period of time includes dust thickness and dust distribution.

[0071] In this embodiment, the timing of cleaning the photovoltaic panels is determined not only by the amount of dust, but also by the impact of cleaning on photovoltaic power generation, and cleaning is carried out during peak power generation periods.

[0072] The beneficial effects of the above design scheme are as follows: By acquiring real-time dust thickness, power generation efficiency, weather data, and surface image data of the photovoltaic panels through sensors, a data foundation is provided for the timing design of fully automated mobile cleaning of the photovoltaic panels. Based on dust thickness, power generation efficiency, weather data, and surface image data, combined with historical data, the pollution level of the photovoltaic panels in the future can be predicted. This comprehensive data enables accurate prediction of the photovoltaic panel's condition, providing accurate information for automatic cleaning control. Based on the future pollution level and usage of the photovoltaic panels, the cleaning time points are determined to ensure the rationality of the cleaning time. Based on the arrangement characteristics of the photovoltaic panels, combined with the pollution level and cleaning time points, the cleaning path of the cleaning equipment is determined to ensure the rationality of the cleaning path. Based on the cleaning time points and cleaning path, a timing control system is established, allowing the cleaning equipment to automatically clean the photovoltaic panels, thereby reducing energy consumption for cleaning while maintaining power generation efficiency.

[0073] Example 2:

[0074] Based on Embodiment 1, this embodiment of the invention provides a fully automatic mobile cleaning system for photovoltaic panels based on timed control. The data acquisition module includes:

[0075] The dust data acquisition unit is used to obtain the dust thickness on the surface of the photovoltaic panel in real time based on the dust sensors installed on the photovoltaic panel;

[0076] The efficiency acquisition unit is used to obtain voltage and current data based on the inverter installed on the photovoltaic panel, and to calculate the power generation efficiency based on the voltage and current data;

[0077] The meteorological data acquisition unit is used to obtain weather data based on meteorological data from the connected photovoltaic panels;

[0078] The visual acquisition unit is used to acquire surface image data of the photovoltaic panel based on visual technology.

[0079] In this embodiment, the visual technology may be a camera, an infrared thermal imager, etc.

[0080] The beneficial effects of the above design scheme are: to obtain real-time dust thickness, power generation efficiency, weather data and surface image data of photovoltaic panels through sensors, providing a basis for the next step of pollution prediction.

[0081] Example 3:

[0082] Based on Embodiment 1, this embodiment of the invention provides a fully automatic mobile cleaning system for photovoltaic panels based on timed control. The pollution prediction module includes:

[0083] The model training unit is used to train the initial prediction model by acquiring historical dust thickness, historical power generation efficiency, historical weather data, and historical surface image data and their corresponding photovoltaic panel pollution data from historical data, so as to obtain the target prediction model.

[0084] The model prediction unit is used to input dust thickness, power generation efficiency, weather data, and surface image data into the target prediction model to obtain the pollution status of the photovoltaic panel in the future.

[0085] The beneficial effects of the above design scheme are as follows: by obtaining historical dust thickness, historical power generation efficiency, historical weather data, and historical surface image data and their corresponding photovoltaic panel pollution data from historical data, the initial prediction model is trained to obtain the target prediction model. By inputting dust thickness, power generation efficiency, weather data, and surface image data into the target prediction model, the pollution status of the photovoltaic panel in the future period can be obtained. Based on comprehensive data, accurate prediction of the photovoltaic panel can be achieved, providing accurate photovoltaic panel information for automatic cleaning control.

[0086] Example 4:

[0087] Based on Embodiment 1, this embodiment of the invention provides a fully automatic mobile cleaning system for photovoltaic panels based on timed control, such as... Figure 2 As shown, the time determination module includes:

[0088] The predictive information acquisition unit is used to obtain the predicted dust thickness distribution and predicted power generation efficiency trend from the pollution situation of photovoltaic panels in the future, and to obtain the predicted weather trend of photovoltaic panels in the future from meteorological data.

[0089] The time determination unit is used to determine the cleaning time point for photovoltaic panels based on the predicted dust thickness distribution, predicted power generation efficiency trend, and predicted weather trend, combined with historical cleaning time setting information.

[0090] In this embodiment, the determination of the cleaning time point for the photovoltaic panel takes into account the relationship between the predicted dust thickness distribution and the predicted power generation efficiency trend, as well as the impact of weather, the peak power generation period of the photovoltaic panel, and the wear and tear of the photovoltaic panel to comprehensively determine the time point, ensuring the optimal cleaning time point.

[0091] The beneficial effects of the above design scheme are: by obtaining the predicted dust thickness distribution and predicted power generation efficiency trend from the pollution status of photovoltaic panels in the future, and obtaining the predicted weather trend of photovoltaic panels in the future from meteorological data, based on the predicted dust thickness distribution, predicted power generation efficiency trend and predicted weather trend, combined with historical cleaning time setting information, the cleaning time point of photovoltaic panels is determined, ensuring the rationality of the cleaning time, so as to minimize resource consumption through cleaning time.

[0092] Example 5:

[0093] Based on Embodiment 1, this embodiment of the invention provides a fully automatic mobile cleaning system for photovoltaic panels based on timed control. The path determination module includes:

[0094] The priority determination unit is used to divide the photovoltaic panel into several clean areas of the same area based on the arrangement characteristics of the photovoltaic panel, and to divide the clean areas into cleaning priorities based on the pollution status of each clean area to obtain the cleaning priority.

[0095] The path determination unit is used to establish multiple initial paths that satisfy the maximum allowable invalid cleaning movement distance based on cleaning priority and the distribution characteristics of the cleaning area.

[0096] The path evaluation unit is used to evaluate multiple initial paths based on the cleaning requirements of photovoltaic panels, the usage specifications of cleaning equipment, and cost control requirements, and select the final cleaning path based on the evaluation results.

[0097] In this embodiment, the maximum allowable ineffective cleaning movement distance is the movement generated during the alternation of cleaning areas. The more of these movements there are, the more likely it is to lead to reduced cleaning efficiency and increased energy consumption.

[0098] In this embodiment, the cleaning requirements for photovoltaic panels include, for example, the control of cleaning time and the requirements for cleaning effect.

[0099] In this embodiment, the usage specifications for the cleaning equipment include requirements for the number of turns and path smoothness.

[0100] In this embodiment, cost control requirements include energy consumption and wear and tear on cleaning equipment.

[0101] In this embodiment, the greater the contamination in the clean area, the higher the cleaning priority.

[0102] The beneficial effects of the above design scheme are as follows: By dividing the photovoltaic panels into several clean areas of equal area based on the arrangement characteristics of the photovoltaic panels, the cleaning priority of each clean area is determined based on the pollution status of each clean area, and the power generation efficiency of the photovoltaic panels is guaranteed by the cleaning sequence. Based on the cleaning priority and the distribution characteristics of the clean areas, multiple initial paths are established to meet the maximum allowable cleaning ineffective movement distance, thereby realizing the planning and determination of the cleaning path. Based on the cleaning requirements of the photovoltaic panels, the usage specifications of the cleaning equipment, and the cost control requirements, the multiple initial paths are evaluated, and the final cleaning path is selected according to the evaluation results. The superiority of the final cleaning path is guaranteed from multiple perspectives. The energy consumption of cleaning the photovoltaic panels is reduced while ensuring power generation efficiency through the selection of the cleaning path.

[0103] Example 6:

[0104] Based on Embodiment 1, this embodiment of the invention provides a fully automatic mobile cleaning system for photovoltaic panels based on timed control. The cleaning control module includes:

[0105] The instruction creation unit is used to create timing information based on cleaning time points, create cleaning control information based on cleaning paths, and create timing control instructions based on the timing information and cleaning control information.

[0106] The automatic cleaning unit is used to send timed control commands to the cleaning equipment to achieve automatic cleaning of the photovoltaic panels.

[0107] The beneficial effects of the above design scheme are: by establishing timing information based on cleaning time points, establishing cleaning control information based on cleaning paths, and establishing timing control commands based on timing information and cleaning control information, the timing control commands are sent to the cleaning equipment to realize automatic cleaning of photovoltaic panels. By using the cleaning equipment to automatically clean photovoltaic panels, the energy consumption of cleaning photovoltaic panels can be reduced while ensuring power generation efficiency.

[0108] Example 7:

[0109] Based on Embodiment 4, this embodiment of the invention provides a fully automatic mobile cleaning system for photovoltaic panels based on timed control, wherein the time determination unit includes:

[0110] The relationship determination unit is used to determine the correspondence between cleaning time points and photovoltaic panel characteristics from historical cleaning time setting information and historical photovoltaic panel conditions;

[0111] The time matching unit is used to determine the characteristics of future photovoltaic panels based on the predicted dust thickness distribution, predicted power generation efficiency trend and predicted weather trend, and to obtain the initial cleaning time point that matches the characteristics of future photovoltaic panels based on the correspondence.

[0112] The difference determination unit is used to obtain the equipment difference information between the current basic information and the historical basic information of the cleaning equipment, and to obtain the demand difference information between the current demand and the historical demand of photovoltaic power generation.

[0113] The time difference determination unit is used to determine the first unit time difference caused by equipment difference information, determine the second unit time difference caused by demand difference information, determine the first specific time difference based on the characteristics of the future photovoltaic panel and the first unit time difference, and determine the second specific time difference based on the characteristics of the future photovoltaic panel and the second unit time difference.

[0114] The correction unit is used to correct the initial cleaning time point based on the first specific time difference and the second specific time difference to obtain the cleaning time point for the photovoltaic panel.

[0115] In this embodiment, the equipment differences between the current basic information and the historical basic information mainly come from the wear and tear caused by the long-term use of the cleaning equipment, such as differences in water spray volume and cleaning range.

[0116] In this embodiment, the demand difference information between current and historical demands is determined based on the actual situation, such as time requirements and cleaning effect requirements.

[0117] In this embodiment, the first unit time difference is the time difference caused by equipment limitations when completing the preset unit cleaning, and the second unit time difference is the time difference caused by different cleaning requirements when completing the preset unit cleaning. The first specific time difference is determined based on the quantitative relationship between the preset unit cleaning and the current cleaning, and the second specific time difference is determined based on the quantitative relationship between the preset unit cleaning and the current cleaning. The preset unit cleaning can be set independently. For example, the preset unit cleaning is used to complete the cleaning of photovoltaic panels with specific area and specific pollution. When the area increases and the degree of pollution increases, the cleaning time of the preset unit cleaning is increased proportionally.

[0118] In this embodiment, the initial cleaning time point is corrected based on the first specific time difference and the second specific time difference by adding the first specific time difference, the second specific time difference, and the initial cleaning time point to obtain the final cleaning time point.

[0119] The beneficial effects of the above design scheme are as follows: by determining the characteristics of future photovoltaic panels based on the predicted dust thickness distribution, predicted power generation efficiency trend and predicted weather trend, the initial cleaning time point matching the characteristics of future photovoltaic panels is obtained based on the correspondence. Then, the time point is corrected according to both equipment difference information and demand difference information to ensure the rationality of the obtained cleaning time point for photovoltaic panels. This not only ensures power generation efficiency but also reduces unnecessary cleaning that causes resource loss.

[0120] Example 8:

[0121] Based on Embodiment 5, this embodiment of the invention provides a fully automatic mobile cleaning system for photovoltaic panels based on timed control, wherein the path evaluation unit includes:

[0122] The indicator determination unit is used to determine the first indicator in the cleaning requirement dimension from the cleaning requirements of photovoltaic panels, the second indicator in the equipment dimension based on the usage specifications of the cleaning equipment, and the third indicator in the cost dimension based on cost control requirements.

[0123] The structure determination unit is used to hierarchically divide the first, second, and third indicators based on the causal relationship between the evaluation dimensions and the indicators, thereby obtaining the indicator hierarchy structure. Based on the degree of influence between the evaluation dimensions and the indicators, the indicator hierarchy structure is weighted to obtain the weighted indicator hierarchy structure.

[0124] The static establishment unit is used to establish a weighted comprehensive evaluation system for each evaluation dimension based on the normalization relationship between indicators and the weighted indicator hierarchy structure, and to determine the static evaluation structure based on the weighted comprehensive evaluation system.

[0125] The dynamic analysis unit is used to acquire the dynamic indicators among the first, second and third indicators, and to establish fuzzy control rules for the dynamic indicators based on the impact of the dynamic indicators on the evaluation dimensions. The fuzzy control rules are then added to the structural position of the dynamic indicators in the static evaluation structure to obtain the dynamic evaluation structure.

[0126] The model building unit is used to weight the dynamic evaluation structure based on the allocation ratio of the evaluation dimensions to obtain a weighted dynamic evaluation structure, and to establish an initial path evaluation model based on the weighted dynamic evaluation structure.

[0127] The model adjustment unit is used to input path information from historical data into the initial path evaluation model to obtain the predicted cleaning result. Based on the difference between the predicted cleaning result and the actual cleaning result, the weight coefficients of the initial path evaluation model are adjusted to obtain the target path evaluation model.

[0128] The model evaluation unit is used to input multiple initial paths into the target path evaluation model for evaluation, obtain pre-learning and evaluation results, and select the initial path corresponding to the best prediction and evaluation results as the final clean path.

[0129] In this embodiment, the evaluation dimensions include cleaning efficiency, cleaning cost, and adaptability of cleaning equipment.

[0130] In this embodiment, dynamic indicators include, for example, the impact of weather and changes in demand.

[0131] In this embodiment, the weighting of the indicator hierarchy structure is to apply weights to each indicator node, and the weighting of the dynamic evaluation structure is to apply weights to each dimension node.

[0132] In this embodiment, the weight coefficients of the initial path evaluation model are adjusted, for example, by adjusting the weights of the indicator nodes or dimension nodes.

[0133] In this embodiment, the normalization relationship between indicators is to standardize the indicator values ​​under the same dimension to eliminate the differences caused by different units.

[0134] The beneficial effects of the above design scheme are as follows: By hierarchically dividing the first, second, and third indicators based on the causal relationship between evaluation dimensions and indicators, a hierarchical indicator structure is obtained. Furthermore, based on the degree of influence between evaluation dimensions and indicators, the hierarchical indicator structure is weighted to obtain a weighted hierarchical indicator structure. This achieves the integration and weighting of indicators, ensuring that the obtained weighted hierarchical indicator structure accurately evaluates from an indicator perspective. It also obtains dynamic indicators from the first, second, and third indicators, and establishes fuzzy control rules for the dynamic indicators based on their impact on evaluation dimensions. These fuzzy control rules are then added to the structural position of the dynamic indicators within the static evaluation structure, resulting in a dynamic evaluation structure. This achieves dynamic control over the evaluation process, allowing the evaluation to adapt to different cleaning environments. The allocation ratio of evaluation dimensions is also considered. The dynamic evaluation structure is weighted to obtain a weighted dynamic evaluation structure. An initial path evaluation model is established based on the weighted dynamic evaluation structure to accurately evaluate from multiple dimensions. Path information from historical data is input into the initial path evaluation model to obtain predicted cleaning results. Based on the difference between the predicted cleaning results and the actual cleaning results, the weight coefficients of the initial path evaluation model are adjusted to obtain the target path evaluation model. The model is optimized based on historical data to improve its evaluation capabilities. Multiple initial paths are input into the target path evaluation model for evaluation to obtain preliminary and evaluation results. The initial path corresponding to the best predicted evaluation result is selected as the final clean path. The superiority of the final clean path is ensured by considering multiple factors. The selection of the clean path ensures power generation efficiency while reducing the energy consumption of photovoltaic panels for clean energy.

[0135] Example 9:

[0136] Based on Embodiment 5, this embodiment of the invention provides a fully automatic mobile cleaning system for photovoltaic panels based on timed control. After obtaining the cleaning path, it further includes: a mode determination unit.

[0137] Used to determine the cleaning movement trajectory for each cleaning area based on the cleaning path, and to determine the cleaning intensity in the cleaning area in combination with the regional characteristics of the cleaning area;

[0138] Calculate the cleaning difficulty K in the cleaning area using the following formula;

[0139]

[0140] Where n represents the number of turns in the cleaning trajectory, α i Let β represent the turning angle of the i-th turn, β represent the slope of the cleaning trajectory, H0 represent the uniformity of the ash layer distribution in the cleaning area, and σ represent the turning angle of the ith turn. max σ represents the maximum dust thickness in the cleaned area. min The minimum dust thickness in the clean area is represented by Δσ, the reference thickness difference is represented by A, the trajectory weight is represented by B, and the contamination weight is represented by B.

[0141] Based on the cleaning difficulty of a unit area, the cleaning intensity F in the cleaning area is calculated according to the following formula;

[0142]

[0143] Where e represents the natural constant, with a value of 2.72, L0 represents the reference trajectory length, M0 represents the reference area, L represents the trajectory length of the cleaning movement trajectory, and M represents the area of ​​the cleaning area;

[0144] Based on the cleaning intensity of every two adjacent cleaning areas, the moving speed between two adjacent unit areas is set, and the cleaning speed under the cleaning path is finally determined.

[0145] The cleaning method is determined based on the cleaning path, cleaning intensity, and cleaning speed.

[0146] In this embodiment, the trajectory weight and pollution weight are flexibly set according to actual needs and circumstances.

[0147] The beneficial effects of the above design scheme are as follows: the cleaning difficulty of the cleaning area is determined by the number of turns, turning angle, slope of the cleaning movement trajectory, and uniformity of dust distribution in the cleaning area, providing a basis for determining the cleaning intensity. The cleaning intensity is determined by combining the trajectory length of the cleaning movement trajectory and the area of ​​the cleaning area. Based on the cleaning intensity in every two adjacent cleaning areas, the movement speed in two adjacent unit areas is set, and finally the cleaning speed under the cleaning path is determined. Based on the cleaning path, cleaning intensity, and cleaning speed, the cleaning method is determined, ensuring the rationality of the obtained cleaning method, achieving targeted cleaning, and minimizing energy consumption while ensuring cleaning effect.

[0148] Example 10:

[0149] A fully automated mobile cleaning method for photovoltaic panels based on timed control, such as... Figure 3 As shown, it includes:

[0150] S1: Real-time dust thickness, power generation efficiency, weather data, and surface image data of photovoltaic panels are obtained through sensors;

[0151] S2: Based on dust thickness, power generation efficiency, weather data, and surface image data, combined with historical data, predict the pollution status of photovoltaic panels in the future.

[0152] S3: Determine the cleaning time point for photovoltaic panels based on the pollution status and usage of the photovoltaic panels in the future;

[0153] S4: Based on the arrangement characteristics of photovoltaic panels, combined with the pollution situation and cleaning time points, determine the cleaning path of the cleaning equipment for the photovoltaic panels;

[0154] S5: Establish timed control based on cleaning time points and cleaning paths, and use cleaning equipment to automatically clean photovoltaic panels.

[0155] In this embodiment, the dust thickness on the surface of the photovoltaic panel is obtained in real time based on the dust sensor installed on the photovoltaic panel, the power generation efficiency data is obtained based on the current and voltage data of the photovoltaic panel obtained by the inverter, the image data of the surface of the photovoltaic panel is obtained based on visual detection, and the real-time weather information is obtained based on the accessed meteorological data.

[0156] In this embodiment, the contamination status of the photovoltaic panel over a period of time includes dust thickness and dust distribution.

[0157] In this embodiment, the timing of cleaning the photovoltaic panels is determined not only by the amount of dust, but also by the impact of cleaning on photovoltaic power generation, and cleaning is carried out during peak power generation periods.

[0158] The beneficial effects of the above design scheme are as follows: By acquiring real-time dust thickness, power generation efficiency, weather data, and surface image data of the photovoltaic panels through sensors, a data foundation is provided for the timing design of fully automated mobile cleaning of the photovoltaic panels. Based on dust thickness, power generation efficiency, weather data, and surface image data, combined with historical data, the pollution level of the photovoltaic panels in the future can be predicted. This comprehensive data enables accurate prediction of the photovoltaic panel's condition, providing accurate information for automatic cleaning control. Based on the future pollution level and usage of the photovoltaic panels, the cleaning time points are determined to ensure the rationality of the cleaning time. Based on the arrangement characteristics of the photovoltaic panels, combined with the pollution level and cleaning time points, the cleaning path of the cleaning equipment is determined to ensure the rationality of the cleaning path. Based on the cleaning time points and cleaning path, a timing control system is established, allowing the cleaning equipment to automatically clean the photovoltaic panels, thereby reducing energy consumption for cleaning while maintaining power generation efficiency.

[0159] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of this application and its equivalents, this invention also intends to include these modifications and variations.

Claims

1. A fully automatic mobile cleaning system for photovoltaic panels based on timed control, characterized in that, include: The data acquisition module is used to acquire real-time dust thickness, power generation efficiency, weather data, and surface image data of photovoltaic panels through sensors; The pollution prediction module is used to predict the pollution level of photovoltaic panels in the future based on dust thickness, power generation efficiency, weather data, and surface image data, combined with historical data. The timing module determines the cleaning time for the photovoltaic panels based on their pollution levels and usage over a future period, including: The predictive information acquisition unit is used to obtain the predicted dust thickness distribution and predicted power generation efficiency trend from the pollution situation of photovoltaic panels in the future, and to obtain the predicted weather trend of photovoltaic panels in the future from meteorological data. The time determination unit is used to determine the cleaning time point for photovoltaic panels based on the predicted dust thickness distribution, predicted power generation efficiency trend, and predicted weather trend, combined with historical cleaning time setting information. The time determination unit includes: The relationship determination unit is used to determine the correspondence between cleaning time points and photovoltaic panel characteristics from historical cleaning time setting information and historical photovoltaic panel conditions; The time matching unit is used to determine the characteristics of future photovoltaic panels based on the predicted dust thickness distribution, predicted power generation efficiency trend and predicted weather trend, and to obtain the initial cleaning time point that matches the characteristics of future photovoltaic panels based on the correspondence. The difference determination unit is used to obtain the equipment difference information between the current basic information and the historical basic information of the cleaning equipment, and to obtain the demand difference information between the current demand and the historical demand of photovoltaic power generation. The time difference determination unit is used to determine the first unit time difference caused by equipment difference information, determine the second unit time difference caused by demand difference information, determine the first specific time difference based on the characteristics of the future photovoltaic panel and the first unit time difference, and determine the second specific time difference based on the characteristics of the future photovoltaic panel and the second unit time difference. The correction unit is used to correct the initial cleaning time point based on the first specific time difference and the second specific time difference to obtain the cleaning time point for the photovoltaic panel. The path determination module is used to determine the cleaning path of the cleaning equipment for the photovoltaic panels based on the arrangement characteristics of the photovoltaic panels, combined with the contamination status and cleaning time points, including: The priority determination unit is used to divide the photovoltaic panel into several clean areas of the same area based on the arrangement characteristics of the photovoltaic panel, and to divide the clean areas into cleaning priorities based on the pollution status of each clean area to obtain the cleaning priority. The path determination unit is used to establish multiple initial paths that satisfy the maximum allowable invalid cleaning movement distance based on cleaning priority and the distribution characteristics of the cleaning area. The path evaluation unit is used to evaluate multiple initial paths based on the cleaning requirements of photovoltaic panels, the usage specifications of cleaning equipment, and cost control requirements, and select the final cleaning path based on the evaluation results. The path evaluation unit includes: The indicator determination unit is used to determine the first indicator in the cleaning requirement dimension from the cleaning requirements of photovoltaic panels, the second indicator in the equipment dimension based on the usage specifications of the cleaning equipment, and the third indicator in the cost dimension based on cost control requirements. The structure determination unit is used to hierarchically divide the first, second, and third indicators based on the causal relationship between the evaluation dimensions and the indicators, thereby obtaining the indicator hierarchy structure. Based on the degree of influence between the evaluation dimensions and the indicators, the indicator hierarchy structure is weighted to obtain the weighted indicator hierarchy structure. The static establishment unit is used to establish a weighted comprehensive evaluation system for each evaluation dimension based on the normalization relationship between indicators and the weighted indicator hierarchy structure, and to determine the static evaluation structure based on the weighted comprehensive evaluation system. The dynamic analysis unit is used to acquire the dynamic indicators among the first, second and third indicators, and to establish fuzzy control rules for the dynamic indicators based on the impact of the dynamic indicators on the evaluation dimensions. The fuzzy control rules are then added to the structural position of the dynamic indicators in the static evaluation structure to obtain the dynamic evaluation structure. The model building unit is used to weight the dynamic evaluation structure based on the allocation ratio of the evaluation dimensions to obtain a weighted dynamic evaluation structure, and to establish an initial path evaluation model based on the weighted dynamic evaluation structure. The model adjustment unit is used to input path information from historical data into the initial path evaluation model to obtain the predicted cleaning result. Based on the difference between the predicted cleaning result and the actual cleaning result, the weight coefficients of the initial path evaluation model are adjusted to obtain the target path evaluation model. The model evaluation unit is used to input multiple initial paths into the target path evaluation model for evaluation, obtain pre-learning and evaluation results, and select the initial path corresponding to the best prediction and evaluation results as the final cleaning path. The cleaning control module is used to establish timed control based on cleaning time points and cleaning paths, and to automatically clean photovoltaic panels using cleaning equipment.

2. The fully automatic mobile cleaning system for photovoltaic panels based on timed control according to claim 1, characterized in that, The data acquisition module includes: The dust data acquisition unit is used to obtain the dust thickness on the surface of the photovoltaic panel in real time based on the dust sensors installed on the photovoltaic panel; The efficiency acquisition unit is used to obtain voltage and current data based on the inverter installed on the photovoltaic panel, and to calculate the power generation efficiency based on the voltage and current data; The meteorological data acquisition unit is used to obtain weather data based on meteorological data from the connected photovoltaic panels; The visual acquisition unit is used to acquire surface image data of the photovoltaic panel based on visual technology.

3. The fully automatic mobile cleaning system for photovoltaic panels based on timed control according to claim 1, characterized in that, The pollution prediction module includes: The model training unit is used to train the initial prediction model by acquiring historical dust thickness, historical power generation efficiency, historical weather data, and historical surface image data and their corresponding photovoltaic panel pollution data from historical data, so as to obtain the target prediction model. The model prediction unit is used to input dust thickness, power generation efficiency, weather data, and surface image data into the target prediction model to obtain the pollution status of the photovoltaic panel in the future.

4. The fully automatic mobile cleaning system for photovoltaic panels based on timed control according to claim 1, characterized in that, The cleaning control module includes: The instruction creation unit is used to create timing information based on cleaning time points, create cleaning control information based on cleaning paths, and create timing control instructions based on the timing information and cleaning control information. The automatic cleaning unit is used to send timed control commands to the cleaning equipment to achieve automatic cleaning of the photovoltaic panels.

5. The fully automatic mobile cleaning system for photovoltaic panels based on timed control according to claim 1, characterized in that, After obtaining the cleaning path, the system also includes: a method determination unit. Used to determine the cleaning movement trajectory for each cleaning area based on the cleaning path, and to determine the cleaning intensity in the cleaning area in combination with the regional characteristics of the cleaning area; Based on the cleaning intensity of every two adjacent cleaning areas, the moving speed between two adjacent unit areas is set, and the cleaning speed under the cleaning path is finally determined. The cleaning method is determined based on the cleaning path, cleaning intensity, and cleaning speed.

6. A fully automatic mobile cleaning method for photovoltaic panels based on timed control, specifically used in the fully automatic mobile cleaning system as described in any one of claims 1-5, characterized in that, include: S1: Real-time dust thickness, power generation efficiency, weather data, and surface image data of photovoltaic panels are obtained through sensors; S2: Based on dust thickness, power generation efficiency, weather data, and surface image data, combined with historical data, predict the pollution status of photovoltaic panels in the future. S3: Determine the cleaning time point for photovoltaic panels based on the pollution status and usage of the photovoltaic panels in the future; S4: Based on the arrangement characteristics of photovoltaic panels, combined with the pollution situation and cleaning time points, determine the cleaning path of the cleaning equipment for the photovoltaic panels; S5: Establish timed control based on cleaning time points and cleaning paths, and use cleaning equipment to automatically clean photovoltaic panels.

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