Photovoltaic intelligent detection method and system based on Internet of Things

Abstract

The invention relates to the technical field of photovoltaic detection, and particularly discloses a photovoltaic intelligent detection method and system based on the Internet of Things. According to the invention, photovoltaic environment monitoring and operation monitoring are carried out based on the Internet of Things technology; extracting schedule environment data, schedule operation data, current environment data and current operation data; performing association analysis, calculating a plurality of environment association values, and screening associated operation data; and performing comparison detection on the current operation data based on the associated operation data, and performing photovoltaic ash removal prompt when ash deposition is abnormal. According to the method, correlation analysis can be performed on schedule environment data and current environment data, a plurality of environment correlation values are calculated and compared, correlation operation data are screened, then comparison detection is performed on the current operation data, whether dust deposition abnormity exists or not is judged, and subsequent processing is performed, so that automatic photovoltaic dust comparison detection is realized, and the detection efficiency is improved. The method does not need to depend on a manual mode, has objective standards and comparison reference targets, and effectively improves the detection precision.

Description

Technical Field

[0001] The present invention belongs to the technical field of photovoltaic detection, and in particular relates to a photovoltaic intelligent detection method and system based on the Internet of Things. Background Art

[0002] Photovoltaic testing is the process of comprehensively and systematically monitoring and evaluating the various components and their operating status within a photovoltaic power generation system, aiming to ensure efficient, safe, and stable operation of the system. This testing encompasses multiple aspects, including testing the electrical performance of photovoltaic modules, identifying visual defects, assessing environmental impact factors, and checking the integrity of the electrical system.

[0003] Especially among environmental factors, dust detection is an important part of ensuring power generation efficiency. By detecting the degree of dust adhesion on the surface of photovoltaic panels, the cleaning plan can be optimized and energy loss can be reduced.

[0004] However, in the existing technology, dust detection in photovoltaic inspection mostly relies on manual methods. The common method is for staff to observe the surface condition of photovoltaic panels on site and judge the degree of dust coverage based on experience or visual inspection. There is a lack of objective standards and comparative reference targets. The evaluation results are easily affected by personnel experience and have the defect of large detection errors. Summary of the Invention

[0005] The purpose of the embodiments of the present invention is to provide a photovoltaic intelligent detection method and system based on the Internet of Things, aiming to solve the problems raised in the background technology.

[0006] To achieve the above objectives, the embodiments of the present invention provide the following technical solutions: The photovoltaic intelligent detection method based on the Internet of Things specifically includes the following steps: Based on the Internet of Things technology, it conducts photovoltaic environment monitoring and photovoltaic operation monitoring and control, receives uploaded environmental monitoring data and operation monitoring data, and obtains dust cleaning record data; extracting scheduled environmental data, scheduled operation data, current environmental data, and current operation data from the environmental monitoring data and the operation monitoring data according to the dust cleaning record data; Performing correlation analysis on the schedule environment data and the current environment data, calculating a plurality of environment correlation values, performing correlation comparison, and filtering the correlated operation data from the schedule operation data; Based on the associated operation data, the current operation data is compared and detected to determine whether there is a dust accumulation abnormality, and when there is a dust accumulation abnormality, a photovoltaic dust cleaning prompt is issued.

[0007] As a further limitation of the technical solution of the embodiment of the present invention, the photovoltaic environment monitoring and photovoltaic operation monitoring and control based on the Internet of Things technology, receiving uploaded environmental monitoring data and operation monitoring data, and obtaining dust cleaning record data specifically include the following steps: Based on the Internet of Things technology, periodic photovoltaic environment monitoring and control are carried out; Based on the Internet of Things technology, periodic photovoltaic operation monitoring and control are carried out; Receive uploaded periodic monitoring data, update and record environmental monitoring data and operation monitoring data; Get the cleaning record data.

[0008] As a further limitation of the technical solution of the embodiment of the present invention, extracting the scheduled environment data, the scheduled operation data, the current environment data, and the current operation data from the environmental monitoring data and the operation monitoring data based on the dust cleaning record data specifically includes the following steps: determining a plurality of cleaning schedules based on the cleaning record data; Planning a plurality of standard schedules based on the plurality of dust cleaning schedules; extracting schedule environment data and schedule operation data from the environment monitoring data and the operation monitoring data according to the plurality of standard schedules; Current environment data and current operation data are extracted from the environment monitoring data and the operation monitoring data.

[0009] As a further limitation of the technical solution of the embodiment of the present invention, the performing correlation analysis on the schedule environment data and the current environment data, calculating multiple environment correlation values, performing correlation comparison, and screening the correlated operation data from the schedule operation data specifically includes the following steps: Identify multiple associated environmental factors; According to the plurality of associated environmental factors, performing an association analysis on the schedule environmental data and the current environmental data, and calculating the association values of the plurality of factors; Obtaining association weights corresponding to a plurality of the associated environmental factors; Calculating a plurality of environment association values according to the plurality of factor association values and the plurality of association weights; comparing the plurality of environment-related values and selecting a target related value; determining a target schedule based on the target association value; According to the target schedule, relevant operation data is filtered from the schedule operation data.

[0010] As a further limitation of the technical solution of the embodiment of the present invention, the calculation formula of the correlation values of the multiple factors is: ; in, Representative Related environmental factors, Representative A standard schedule, For the The associated environmental factors are The factor correlation value of a standard schedule, For the The current monitoring value of the associated environmental factors, For the The associated environmental factors are Schedule monitoring value of a standard schedule; For the The maximum correlation value of the associated environmental factors, For the The minimum correlation value of the associated environmental factors; The calculation formula for the multiple environmental association values is: ; in, For the The environmental relevance value of a standard schedule, For the preset The association weights corresponding to the associated environmental factors.

[0011] As a further limitation of the technical solution of the embodiment of the present invention, the comparing and detecting the current operating data based on the associated operating data to determine whether there is a dust accumulation abnormality, and providing a photovoltaic dust cleaning prompt when there is a dust accumulation abnormality specifically includes the following steps: Identify several key operation types; According to the plurality of key operation types, comparing the current operation data with the associated operation data to determine whether there is dust accumulation abnormality; Acquire meteorological data when there is dust accumulation anomaly; According to the meteorological data, the photovoltaic cleaning time is planned and the photovoltaic cleaning reminder is provided.

[0012] The photovoltaic intelligent detection system based on the Internet of Things specifically includes a photovoltaic monitoring and control module, a data extraction and processing module, a correlation calculation and comparison module, and a comparison detection and judgment module, wherein: Photovoltaic monitoring and control module, used for photovoltaic environmental monitoring and photovoltaic operation monitoring and control based on Internet of Things technology, receiving uploaded environmental monitoring data and operation monitoring data, and obtaining dust cleaning record data; a data extraction and processing module, configured to extract, from the environmental monitoring data and the operation monitoring data, scheduled environmental data, scheduled operation data, current environmental data, and current operation data according to the dust cleaning record data; A correlation calculation and comparison module is used to perform correlation analysis on the schedule environment data and the current environment data, calculate multiple environment correlation values, perform correlation comparison, and filter the correlation operation data from the schedule operation data; The comparison detection judgment module is used to compare and detect the current operation data based on the associated operation data, judge whether there is a dust accumulation abnormality, and issue a photovoltaic dust cleaning prompt when there is a dust accumulation abnormality.

[0013] As a further limitation of the technical solution of the embodiment of the present invention, the photovoltaic monitoring control module specifically includes: Environmental monitoring control unit, used for periodic photovoltaic environmental monitoring and control based on Internet of Things technology; Operation monitoring control unit, used for periodic photovoltaic operation monitoring and control based on Internet of Things technology; Update recording unit, used to receive uploaded periodic monitoring data, update and record environmental monitoring data and operation monitoring data; The dust cleaning record data acquisition unit is used to acquire the dust cleaning record data.

[0014] As a further limitation of the technical solution of the embodiment of the present invention, the data extraction and processing module specifically includes: a cleaning schedule determining unit, configured to determine a plurality of cleaning schedules based on the cleaning record data; A standard schedule planning unit, configured to plan a plurality of standard schedules based on the plurality of dust cleaning schedules; a schedule data extraction unit, configured to extract schedule environment data and schedule operation data from the environment monitoring data and the operation monitoring data according to the plurality of standard schedules; The current data extraction unit is used to extract current environment data and current operation data from the environment monitoring data and the operation monitoring data.

[0015] As a further limitation of the technical solution of the embodiment of the present invention, the association calculation and comparison module specifically includes: a factor determination unit, for determining a plurality of associated environmental factors; a factor correlation value calculation unit, configured to perform correlation analysis on the schedule environment data and the current environment data according to the plurality of correlation environment factors, and calculate a plurality of factor correlation values; An association weight obtaining unit, configured to obtain association weights corresponding to a plurality of the association environmental factors; an environment association value calculation unit, configured to calculate a plurality of environment association values according to the plurality of factor association values and the plurality of association weights; a correlation value comparison unit, configured to compare the plurality of environment correlation values and select a target correlation value; a target schedule determining unit, configured to determine a target schedule according to the target association value; The associated operation data screening unit is configured to screen associated operation data from the schedule operation data according to the target schedule.

[0016] Compared with the prior art, the present invention has the following beneficial effects: (1) The present invention can perform correlation analysis on the scheduled environmental data and the current environmental data, calculate and compare multiple environmental correlation values, screen the correlation operation data, and then perform comparative detection on the current operation data to determine whether there is dust accumulation abnormality and perform subsequent processing, thereby realizing automatic photovoltaic dust comparison detection without relying on manual methods, and having objective standards and comparison reference targets, effectively improving detection accuracy; (2) The present invention can determine multiple cleaning schedules based on cleaning record data, and then plan standard schedules based on the multiple cleaning schedules. Then, according to the multiple standard schedules, the present invention can extract schedule environmental data and schedule operation data from the environmental monitoring data and operation monitoring data, thereby providing an effective data basis for subsequent correlation comparison; (3) The present invention can perform correlation analysis on schedule environmental data and current environmental data according to multiple correlated environmental factors, calculate multiple factor correlation values, and then calculate multiple environmental correlation values based on the multiple factor correlation values and multiple correlation weights. It can then compare the multiple environmental correlation values, select the target correlation value, determine the target schedule, and filter the correlated operation data, thereby providing an accurate and effective comparison reference target for subsequent dust accumulation abnormality judgment. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention.

[0018] Figure 1 The figure shows a flow chart of a photovoltaic intelligent detection method based on the Internet of Things provided by an embodiment of the present invention.

[0019] Figure 2 The application architecture diagram of the photovoltaic intelligent detection system based on the Internet of Things provided by an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0020] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0021] It is understandable that in the existing technology, dust detection in photovoltaic inspection mostly relies on manual methods. The common method is for staff to observe the surface condition of the photovoltaic panels on site and judge the degree of dust coverage based on experience or visual inspection. There is a lack of objective standards and comparative reference targets. The evaluation results are easily affected by personnel experience and have the defect of large detection errors.

[0022] To address the above-mentioned issues, embodiments of the present invention utilize Internet of Things technology to perform photovoltaic environmental monitoring and photovoltaic operation monitoring and control, receive uploaded environmental monitoring data and operation monitoring data, and obtain dust cleaning record data. Based on the dust cleaning record data, the system extracts scheduled environmental data, scheduled operation data, current environmental data, and current operation data from the environmental monitoring data and operation monitoring data. Correlation analysis is performed on the scheduled environmental data and current environmental data, multiple environmental correlation values are calculated and compared, and correlated operation data is filtered from the scheduled operation data. Based on the correlated operation data, the system compares and detects the current operation data to determine whether there is an abnormal dust accumulation. If an abnormal dust accumulation is detected, a photovoltaic dust cleaning prompt is issued. By performing correlation analysis on the scheduled environmental data and current environmental data, calculating and comparing multiple environmental correlation values, filtering the correlated operation data, and then comparing and detecting the current operation data, determining whether there is an abnormal dust accumulation, and performing subsequent processing, the system achieves automatic photovoltaic dust comparison detection without manual intervention, and provides objective standards and comparison reference targets, effectively improving detection accuracy.

[0023] Figure 1 The figure shows a flow chart of a photovoltaic intelligent detection method based on the Internet of Things provided by an embodiment of the present invention.

[0024] Specifically, in a preferred embodiment of the present invention, a photovoltaic intelligent detection method based on the Internet of Things comprises the following steps: Step S101: Based on the Internet of Things technology, photovoltaic environment monitoring and photovoltaic operation monitoring and control are performed, uploaded environmental monitoring data and operation monitoring data are received, and dust cleaning record data is obtained.

[0025] In an embodiment of the present invention, according to a preset monitoring cycle, based on the Internet of Things technology, periodic photovoltaic environmental monitoring and control and photovoltaic operation monitoring and control are performed, and uploaded periodic monitoring data is received. According to the two major categories of environment and operation, the periodic monitoring data is updated and recorded for data classification to obtain environmental monitoring data and operation monitoring data. In addition, the cleaning work of the photovoltaic panels needs to be recorded and uploaded so that the cleaning record data can be obtained.

[0026] It can be understood that the environmental monitoring data, operation monitoring data and cleaning record data are all time-series recorded data.

[0027] Specifically, in a preferred embodiment of the present invention, the photovoltaic environment monitoring and photovoltaic operation monitoring control based on the Internet of Things technology, receiving uploaded environmental monitoring data and operation monitoring data, and obtaining dust cleaning record data specifically include the following steps: Based on the Internet of Things technology, periodic photovoltaic environment monitoring and control are carried out; Based on the Internet of Things technology, periodic photovoltaic operation monitoring and control are carried out; Receive uploaded periodic monitoring data, update and record environmental monitoring data and operation monitoring data; Get the cleaning record data.

[0028] Furthermore, the photovoltaic intelligent detection method based on the Internet of Things also includes the following steps: Step S102 : extracting scheduled environment data, scheduled operation data, current environment data, and current operation data from the environment monitoring data and the operation monitoring data according to the dust cleaning record data.

[0029] In an embodiment of the present invention, based on the cleaning record data, multiple cleaning schedules with cleaning work are determined, and then based on the multiple cleaning schedules, standard schedules after the multiple cleaning schedules are planned, and then according to the multiple standard schedules and the preset associated comparison time, the schedule environmental data and schedule operation data of the associated comparison time of the multiple standard schedules are extracted from the environmental monitoring data and the operation monitoring data, and according to the associated comparison time, the current environmental data and current operation data of the most recent schedule are extracted from the environmental monitoring data and the operation monitoring data.

[0030] It is understandable that the multiple standard schedules are the day after the corresponding dust cleaning schedules.

[0031] It is understandable that, in the embodiment of the present invention, the associated comparison time is 12 o'clock.

[0032] It can be understood that if today's time exceeds 12 o'clock, the current environment data and current operation data are the data at 12 o'clock today; if today's time does not exceed 12 o'clock, the current environment data and current operation data are the data at 12 o'clock yesterday.

[0033] Specifically, in a preferred embodiment provided by the present invention, extracting the scheduled environment data, scheduled operation data, current environment data, and current operation data from the environmental monitoring data and the operation monitoring data based on the dust cleaning record data specifically includes the following steps: determining a plurality of cleaning schedules based on the cleaning record data; Planning a plurality of standard schedules based on the plurality of dust cleaning schedules; extracting schedule environment data and schedule operation data from the environment monitoring data and the operation monitoring data according to the plurality of standard schedules; Current environment data and current operation data are extracted from the environment monitoring data and the operation monitoring data.

[0034] Furthermore, the photovoltaic intelligent detection method based on the Internet of Things also includes the following steps: Step S103 , performing correlation analysis on the schedule environment data and the current environment data, calculating a plurality of environment correlation values, performing correlation comparison, and filtering the correlated operation data from the schedule operation data.

[0035] In an embodiment of the present invention, multiple associated environmental factors are determined, and then, according to the multiple associated environmental factors, an association analysis is performed on the schedule environmental data and the current environmental data, multiple factor association values are calculated, and association weights corresponding to the multiple associated environmental factors are obtained. Subsequently, multiple environmental association values are calculated based on the multiple factor association values and the multiple association weights. The multiple environmental association values are compared to select the largest environmental association value and mark it as the target association value. The standard schedule corresponding to the target association value is then marked as the target schedule. Then, the associated operation data corresponding to the target schedule is screened from the schedule operation data. Specifically, the calculation formula for the multiple factor association values is: ; in, Representative Related environmental factors, Representative A standard schedule, For the The associated environmental factors are The factor correlation value of a standard schedule, For the The current monitoring value of the associated environmental factors, For the The associated environmental factors are Schedule monitoring value of a standard schedule; For the The maximum correlation value of the associated environmental factors, For the The minimum correlation value of the associated environmental factors; The calculation formula for multiple environmental association values is: ; in, For the The environmental relevance value of a standard schedule, For the preset The association weights corresponding to the associated environmental factors.

[0036] It is understandable that there are multiple related environmental factors, including temperature, humidity, radiation intensity, etc.

[0037] It is understandable that according to Calculate factor association value, current monitoring value and schedule monitoring values The smaller the difference is, the better the current The first of the standard schedule The greater the correlation of the associated environmental factors, the closer the factor correlation value is to 1; the current monitoring value and schedule monitoring values The greater the difference between the current The first of the standard schedule The smaller the correlation between the two associated environmental factors, the closer the factor correlation value is to 0.

[0038] It is understandable that according to Calculating the environmental correlation value is a fusion calculation of the factor correlation value and the corresponding correlation weight, so that the calculation result can reflect the fusion correlation characteristics of all associated environmental factors and the current one under different standard schedules. The larger the calculated environmental correlation value, the greater the fusion correlation between all associated environmental factors of the corresponding standard schedule and the current one, indicating that the corresponding standard schedule is closer to the current comprehensive environment.

[0039] Specifically, in a preferred embodiment of the present invention, performing correlation analysis on the schedule environment data and the current environment data, calculating multiple environment correlation values, and performing correlation comparison, and screening the correlated operation data from the schedule operation data, specifically includes the following steps: Identify multiple associated environmental factors; According to the plurality of associated environmental factors, performing an association analysis on the schedule environmental data and the current environmental data, and calculating the association values of the plurality of factors; Obtaining association weights corresponding to a plurality of the associated environmental factors; Calculating a plurality of environment association values according to the plurality of factor association values and the plurality of association weights; comparing the plurality of environment-related values and selecting a target related value; determining a target schedule based on the target association value; According to the target schedule, relevant operation data is filtered from the schedule operation data.

[0040] Furthermore, the photovoltaic intelligent detection method based on the Internet of Things also includes the following steps: Step S104 : Based on the associated operation data, the current operation data is compared and tested to determine whether there is abnormal dust accumulation, and if there is abnormal dust accumulation, a photovoltaic dust cleaning prompt is issued.

[0041] In an embodiment of the present invention, a plurality of key operating types are determined, and according to the plurality of key operating types, the current operating data and the associated operating data are compared and detected to determine whether there is a dust accumulation abnormality. Specifically, by calculating the numerical difference between the current operating data and the plurality of key operating types of the associated operating data, when the numerical difference is greater than a preset standard difference, it is determined that there is a dust accumulation abnormality; when the numerical difference is not greater than the preset standard difference, it is determined that there is no dust accumulation abnormality; in the case of determining that there is a dust accumulation abnormality, meteorological data is obtained, and based on the meteorological data, a photovoltaic cleaning time is planned in which it will not rain in the next three days, and a photovoltaic cleaning prompt is issued.

[0042] It is understandable that there are multiple key operating types, including: current, voltage, power, etc.

[0043] Specifically, in a preferred embodiment provided by the present invention, the current operation data is compared and detected based on the associated operation data to determine whether there is a dust accumulation abnormality, and a photovoltaic dust cleaning prompt is issued when there is a dust accumulation abnormality, which specifically includes the following steps: Identify several key operation types; According to the plurality of key operation types, comparing the current operation data with the associated operation data to determine whether there is dust accumulation abnormality; Acquire meteorological data when there is dust accumulation anomaly; According to the meteorological data, the photovoltaic cleaning time is planned and the photovoltaic cleaning reminder is provided.

[0044] Further, Figure 2 The application architecture diagram of the photovoltaic intelligent detection system based on the Internet of Things provided by an embodiment of the present invention is shown.

[0045] Among them, in another preferred embodiment provided by the present invention, the photovoltaic intelligent detection system based on the Internet of Things includes: The photovoltaic monitoring and control module 101 is used to perform photovoltaic environmental monitoring and photovoltaic operation monitoring and control based on the Internet of Things technology, receive uploaded environmental monitoring data and operation monitoring data, and obtain dust cleaning record data.

[0046] In an embodiment of the present invention, the photovoltaic monitoring and control module 101 performs periodic photovoltaic environmental monitoring and control and photovoltaic operation monitoring and control according to a preset monitoring cycle based on the Internet of Things technology, and receives uploaded periodic monitoring data. It updates and records the periodic monitoring data according to the two major categories of environment and operation, obtains environmental monitoring data and operation monitoring data, and needs to record and upload the cleaning work of the photovoltaic panels so as to obtain the cleaning record data.

[0047] Specifically, in a preferred embodiment of the present invention, the photovoltaic monitoring control module 101 specifically includes: Environmental monitoring control unit, used for periodic photovoltaic environmental monitoring and control based on Internet of Things technology; Operation monitoring control unit, used for periodic photovoltaic operation monitoring and control based on Internet of Things technology; Update recording unit, used to receive uploaded periodic monitoring data, update and record environmental monitoring data and operation monitoring data; The dust cleaning record data acquisition unit is used to acquire the dust cleaning record data.

[0048] Furthermore, the photovoltaic intelligent detection system based on the Internet of Things also includes: The data extraction processing module 102 is configured to extract schedule environment data, schedule operation data, current environment data, and current operation data from the environment monitoring data and the operation monitoring data according to the dust cleaning record data.

[0049] In an embodiment of the present invention, the data extraction and processing module 102 determines multiple cleaning schedules with cleaning work based on the cleaning record data, and then plans a standard schedule after the multiple cleaning schedules based on the multiple cleaning schedules, and then extracts the schedule environmental data and schedule operation data of the associated comparison times of the multiple standard schedules from the environmental monitoring data and the operation monitoring data according to the multiple standard schedules and the preset associated comparison time, and extracts the current environmental data and current operation data of the most recent schedule from the environmental monitoring data and the operation monitoring data according to the associated comparison time.

[0050] Specifically, in the preferred embodiment provided by the present invention, the data extraction processing module 102 specifically includes: a cleaning schedule determining unit, configured to determine a plurality of cleaning schedules based on the cleaning record data; A standard schedule planning unit, configured to plan a plurality of standard schedules based on the plurality of dust cleaning schedules; a schedule data extraction unit, configured to extract schedule environment data and schedule operation data from the environment monitoring data and the operation monitoring data according to the plurality of standard schedules; The current data extraction unit is used to extract current environment data and current operation data from the environment monitoring data and the operation monitoring data.

[0051] Furthermore, the photovoltaic intelligent detection system based on the Internet of Things also includes: The correlation calculation and comparison module 103 is used to perform correlation analysis on the schedule environment data and the current environment data, calculate multiple environment correlation values, perform correlation comparison, and filter the correlated operation data from the schedule operation data.

[0052] In an embodiment of the present invention, the association calculation and comparison module 103 determines multiple associated environmental factors, then performs an association analysis on the schedule environmental data and the current environmental data according to the multiple associated environmental factors, calculates multiple factor association values, and obtains association weights corresponding to the multiple associated environmental factors. Subsequently, multiple environmental association values are calculated based on the multiple factor association values and the multiple association weights. The multiple environmental association values are compared to select the largest environmental association value and mark it as the target association value. The standard schedule corresponding to the target association value is then marked as the target schedule. Then, the associated operation data corresponding to the target schedule is screened from the schedule operation data. Specifically, the calculation formula for the multiple factor association values is as follows: ; in, Representative Related environmental factors, Representative A standard schedule, For the The associated environmental factors are The factor correlation value of a standard schedule, For the The current monitoring value of the associated environmental factors, For the The associated environmental factors are Schedule monitoring value of a standard schedule; For the The maximum correlation value of the associated environmental factors, For the The minimum correlation value of the associated environmental factors; The calculation formula for multiple environmental association values is: ; in, For the The environmental relevance value of a standard schedule, For the preset The association weights corresponding to the associated environmental factors.

[0053] Specifically, in a preferred embodiment of the present invention, the association calculation and comparison module specifically includes: a factor determination unit, for determining a plurality of associated environmental factors; a factor correlation value calculation unit, configured to perform correlation analysis on the schedule environment data and the current environment data according to the plurality of correlation environment factors, and calculate a plurality of factor correlation values; An association weight obtaining unit, configured to obtain association weights corresponding to a plurality of the association environmental factors; an environment association value calculation unit, configured to calculate a plurality of environment association values according to the plurality of factor association values and the plurality of association weights; a correlation value comparison unit, configured to compare the plurality of environment correlation values and select a target correlation value; a target schedule determining unit, configured to determine a target schedule according to the target association value; The associated operation data screening unit is configured to screen associated operation data from the schedule operation data according to the target schedule.

[0054] Furthermore, the photovoltaic intelligent detection system based on the Internet of Things also includes: The comparison detection judgment module 104 is used to perform a comparison detection on the current operation data based on the associated operation data to determine whether there is a dust accumulation abnormality, and to issue a photovoltaic dust cleaning prompt if there is a dust accumulation abnormality.

[0055] In an embodiment of the present invention, the comparison detection judgment module 104 determines multiple key operation types, and compares and detects the current operation data with the associated operation data according to the multiple key operation types to determine whether there is a dust accumulation abnormality. Specifically, by calculating the numerical difference between the current operation data and the multiple key operation types of the associated operation data, when the numerical difference is greater than the preset standard difference, it is determined that there is a dust accumulation abnormality; when the numerical difference is not greater than the preset standard difference, it is determined that there is no dust accumulation abnormality; when it is determined that there is a dust accumulation abnormality, meteorological data is obtained, and according to the meteorological data, a photovoltaic cleaning time is planned in which it will not rain in the next three days, and a photovoltaic cleaning prompt is issued.

[0056] The technical features of the above-mentioned embodiments can be combined arbitrarily. In order to make the description concise, not all possible combinations of the technical features in the above-mentioned embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

Claims

1. Photovoltaic intelligent detection method based on Internet of Things, characterized in that: The method specifically comprises the following steps: Based on the Internet of Things technology, it conducts photovoltaic environment monitoring and photovoltaic operation monitoring and control, receives uploaded environmental monitoring data and operation monitoring data, and obtains dust cleaning record data; extracting scheduled environmental data, scheduled operation data, current environmental data, and current operation data from the environmental monitoring data and the operation monitoring data according to the dust cleaning record data; Performing correlation analysis on the schedule environment data and the current environment data, calculating a plurality of environment correlation values, performing correlation comparison, and filtering the correlated operation data from the schedule operation data; Based on the associated operation data, the current operation data is compared and detected to determine whether there is a dust accumulation abnormality, and when there is a dust accumulation abnormality, a photovoltaic dust cleaning prompt is issued.

2. The photovoltaic intelligent detection method based on the Internet of Things according to claim 1 is characterized in that: The photovoltaic environment monitoring and photovoltaic operation monitoring control based on the Internet of Things technology, receiving uploaded environmental monitoring data and operation monitoring data, and obtaining dust cleaning record data specifically include the following steps: Based on the Internet of Things technology, periodic photovoltaic environment monitoring and control are carried out; Based on the Internet of Things technology, periodic photovoltaic operation monitoring and control are carried out; Receive uploaded periodic monitoring data, update and record environmental monitoring data and operation monitoring data; Get the cleaning record data.

3. The photovoltaic intelligent detection method based on the Internet of Things according to claim 1 is characterized in that: The extracting of scheduled environment data, scheduled operation data, current environment data, and current operation data from the environment monitoring data and the operation monitoring data according to the dust cleaning record data specifically includes the following steps: determining a plurality of cleaning schedules based on the cleaning record data; Planning a plurality of standard schedules based on the plurality of dust cleaning schedules; extracting schedule environment data and schedule operation data from the environment monitoring data and the operation monitoring data according to the plurality of standard schedules; Current environment data and current operation data are extracted from the environment monitoring data and the operation monitoring data.

4. The photovoltaic intelligent detection method based on the Internet of Things according to claim 3 is characterized in that: The method of performing correlation analysis on the schedule environment data and the current environment data, calculating multiple environment correlation values, and performing correlation comparison, and screening the correlated operation data from the schedule operation data, specifically includes the following steps: Identify multiple associated environmental factors; According to the plurality of associated environmental factors, performing an association analysis on the schedule environmental data and the current environmental data, and calculating the association values of the plurality of factors; Obtaining association weights corresponding to a plurality of the associated environmental factors; Calculating a plurality of environment association values according to the plurality of factor association values and the plurality of association weights; comparing the plurality of environment-related values and selecting a target related value; determining a target schedule based on the target association value; According to the target schedule, relevant operation data is filtered from the schedule operation data.

5. The photovoltaic intelligent detection method based on the Internet of Things according to claim 4 is characterized in that: The calculation formula for the correlation values of multiple factors is: ； in, Representative Related environmental factors, Representative A standard schedule, For the The associated environmental factors are The factor correlation value of a standard schedule, For the The current monitoring value of the associated environmental factors, For the The associated environmental factors are Schedule monitoring value of a standard schedule; For the The maximum correlation value of the associated environmental factors, For the The minimum correlation value of the associated environmental factors; The calculation formula for the multiple environmental association values is: ； in, For the The environmental relevance value of a standard schedule, For the preset The association weights corresponding to the associated environmental factors.

6. The photovoltaic intelligent detection method based on the Internet of Things according to claim 1 is characterized in that: The method of comparing and detecting the current operation data based on the associated operation data to determine whether there is abnormal dust accumulation and providing a photovoltaic dust cleaning prompt when there is abnormal dust accumulation specifically includes the following steps: Identify several key operation types; According to the plurality of key operation types, comparing the current operation data with the associated operation data to determine whether there is dust accumulation abnormality; Acquire meteorological data when there is dust accumulation anomaly; According to the meteorological data, the photovoltaic cleaning time is planned and the photovoltaic cleaning reminder is provided.

7. Photovoltaic intelligent detection system based on Internet of Things, characterized by: The system specifically includes a photovoltaic monitoring and control module, a data extraction and processing module, a correlation calculation and comparison module, and a comparison detection and judgment module, wherein: Photovoltaic monitoring and control module, used for photovoltaic environmental monitoring and photovoltaic operation monitoring and control based on Internet of Things technology, receiving uploaded environmental monitoring data and operation monitoring data, and obtaining dust cleaning record data; a data extraction and processing module, configured to extract, from the environmental monitoring data and the operation monitoring data, scheduled environmental data, scheduled operation data, current environmental data, and current operation data according to the dust cleaning record data; A correlation calculation and comparison module is used to perform correlation analysis on the schedule environment data and the current environment data, calculate multiple environment correlation values, perform correlation comparison, and filter the correlation operation data from the schedule operation data; The comparison detection judgment module is used to compare and detect the current operation data based on the associated operation data, judge whether there is a dust accumulation abnormality, and issue a photovoltaic dust cleaning prompt when there is a dust accumulation abnormality.

8. The photovoltaic intelligent detection system based on the Internet of Things according to claim 7 is characterized in that: The photovoltaic monitoring control module specifically includes: Environmental monitoring control unit, used for periodic photovoltaic environmental monitoring and control based on Internet of Things technology; Operation monitoring control unit, used for periodic photovoltaic operation monitoring and control based on Internet of Things technology; Update recording unit, used to receive uploaded periodic monitoring data, update and record environmental monitoring data and operation monitoring data; The dust cleaning record data acquisition unit is used to acquire the dust cleaning record data.

9. The photovoltaic intelligent detection system based on the Internet of Things according to claim 7, characterized in that: The data extraction processing module specifically includes: a cleaning schedule determining unit, configured to determine a plurality of cleaning schedules based on the cleaning record data; A standard schedule planning unit, configured to plan a plurality of standard schedules based on the plurality of dust cleaning schedules; a schedule data extraction unit, configured to extract schedule environment data and schedule operation data from the environment monitoring data and the operation monitoring data according to the plurality of standard schedules; The current data extraction unit is used to extract current environment data and current operation data from the environment monitoring data and the operation monitoring data.

10. The photovoltaic intelligent detection system based on the Internet of Things according to claim 9, characterized in that: The association calculation and comparison module specifically includes: a factor determination unit, for determining a plurality of associated environmental factors; a factor correlation value calculation unit, configured to perform correlation analysis on the schedule environment data and the current environment data according to the plurality of correlation environment factors, and calculate a plurality of factor correlation values; An association weight obtaining unit, configured to obtain association weights corresponding to a plurality of the association environmental factors; an environment association value calculation unit, configured to calculate a plurality of environment association values according to the plurality of factor association values and the plurality of association weights; a correlation value comparison unit, configured to compare the plurality of environment correlation values and select a target correlation value; a target schedule determining unit, configured to determine a target schedule according to the target association value; The associated operation data screening unit is configured to screen associated operation data from the schedule operation data according to the target schedule.

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