An anomaly monitoring method and system for photovoltaic-storage-charging microgrid systems

Abstract

This invention belongs to the field of photovoltaic-storage-charging microgrid technology, and provides an anomaly monitoring method and system for photovoltaic-storage-charging microgrid systems. It addresses the problem of inability to accurately detect or detect the impact of haze on power generation. This invention performs a first data correction on photovoltaic panel power generation based on haze intensity; a second data correction based on haze values ​​influenced by wind speed; a third data correction based on haze values ​​influenced by humidity; and a fourth data correction based on haze values ​​influenced by temperature. Anomalies are then detected using the four corrected photovoltaic panel power generation figures. This invention achieves anomaly detection when haze causes a decrease in power generation, and considers multiple factors such as environmental wind speed, temperature, and humidity that cause data changes, determining the power generation correction values ​​under the influence of each factor, greatly improving the accuracy of anomaly monitoring and detection.

Description

Technical Field

[0001] This invention belongs to the field of photovoltaic-storage-charging microgrid technology, and particularly relates to an anomaly monitoring method and system for photovoltaic-storage-charging microgrid systems. Background Technology

[0002] A photovoltaic-storage-charging microgrid system is an energy supply system that integrates photovoltaic power generation, energy storage, and charging facilities. By integrating solar photovoltaic panels, energy storage batteries, and charging piles, it achieves autonomous energy production, storage, and distribution, providing users with a stable and reliable power supply. The power generation of the photovoltaic panels needs to be monitored in real time, and maintenance or repair of the photovoltaic panels should be carried out when abnormalities occur.

[0003] Currently, when monitoring abnormal power generation, factors such as smog can cause a decrease in power generation. Such abnormalities are generally impossible to identify, and even if they are identified, the accuracy is low. The magnitude of smog can vary due to multiple factors such as wind speed, temperature, and humidity, which greatly affects the accuracy of the assessment. Summary of the Invention

[0004] To address the aforementioned problems, this invention proposes an anomaly monitoring method and system for photovoltaic-storage-charging microgrid systems. This invention enables anomaly detection when power generation is reduced due to haze, and considers multiple factors such as environmental wind speed, temperature, and humidity that cause data changes. It also determines the power generation correction value under the influence of these factors, greatly improving the accuracy of anomaly monitoring and detection.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solution:

[0006] In a first aspect, the present invention provides an anomaly monitoring method for a photovoltaic-storage-charging microgrid system, comprising:

[0007] An anomaly monitoring method for a photovoltaic-storage-charging microgrid system includes:

[0008] Acquire data on photovoltaic panel power generation, ambient haze levels, ambient wind speed, ambient temperature, and ambient humidity;

[0009] The power generation of the photovoltaic panels is corrected once based on the severity of the smog.

[0010] The haze value under the influence of wind speed is obtained by obtaining the haze value under the influence of wind speed, and the power generation of photovoltaic panels is corrected in a secondary data manner based on the haze value under the influence of wind speed.

[0011] If the wind speed is lower than the preset value, the haze value under the influence of humidity is obtained through the ambient humidity. The power generation of the photovoltaic panel is corrected three times based on the haze value under the influence of humidity. The haze value under the influence of temperature is obtained through the ambient temperature. The power generation of the photovoltaic panel is corrected four times based on the haze value under the influence of temperature. The power generation of the photovoltaic panel after the four data corrections is used to determine anomalies. Otherwise, the power generation of the photovoltaic panel after the two data corrections is used to determine anomalies.

[0012] Furthermore, when making a data correction for the photovoltaic panel power generation:

[0013] ;

[0014] ;

[0015] in, The amount of electricity generated by photovoltaic panels affected by smog; The photovoltaic panel power generation most affected by smog; For environmental smog; The greatest environmental smog; The amount of electricity generated by the photovoltaic panels; This represents the power generation from the photovoltaic panels after a one-time correction.

[0016] Furthermore, when performing secondary data correction on the photovoltaic panel power generation:

[0017] ;

[0018] ;

[0019] ;

[0020] in, The environmental haze value is affected by wind speed; The environmental haze value after the influence of wind speed; For ambient wind speed; Maximum ambient wind speed; This is the photovoltaic power generation after secondary correction.

[0021] Furthermore, when performing three data corrections on the photovoltaic panel power generation:

[0022] ;

[0023] ;

[0024] , ;

[0025] in, This is the photovoltaic panel power generation after three revisions. The environmental haze value after the influence of humidity. The environmental haze value is affected by humidity. For ambient humidity, For maximum ambient humidity, This is the lowest wind speed.

[0026] Furthermore, when performing four data corrections on the photovoltaic panel power generation:

[0027] ;

[0028] ;

[0029] , ;

[0030] in, This represents the photovoltaic panel power generation after four revisions. This represents the environmental haze value after temperature influence. The environmental haze value is affected by temperature. For ambient temperature, This represents the maximum ambient temperature.

[0031] Furthermore, if the corrected photovoltaic panel power generation exceeds the preset limit, no alarm will be triggered; otherwise, an alarm will be triggered.

[0032] Secondly, the present invention also provides an anomaly monitoring system for a photovoltaic-storage-charging microgrid system, comprising:

[0033] An anomaly monitoring system for a photovoltaic-storage-charging microgrid system includes:

[0034] The data acquisition module is configured to acquire data on photovoltaic panel power generation, ambient haze levels, ambient wind speed, ambient temperature, and ambient humidity.

[0035] The data correction module is configured to: correct the photovoltaic panel power generation data based on the level of smog;

[0036] The secondary data correction module is configured to: perform a first data correction on the photovoltaic panel power generation based on the smog level; obtain the smog value under the influence of wind speed through the ambient wind speed, and perform a second data correction on the photovoltaic panel power generation based on the smog value under the influence of wind speed.

[0037] The anomaly detection module is configured as follows: if the wind speed is lower than the preset value, the fog value affected by the humidity is obtained through the ambient humidity, and the photovoltaic power generation is corrected three times based on the fog value affected by the humidity. The fog value affected by the temperature is obtained through the ambient temperature, and the photovoltaic power generation is corrected four times based on the fog value affected by the temperature. The anomaly detection is performed using the photovoltaic power generation after the four data corrections. Otherwise, the anomaly detection is performed using the photovoltaic power generation after the two data corrections.

[0038] Thirdly, the present invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the anomaly monitoring method for a photovoltaic-storage-charging microgrid system described in the first aspect.

[0039] Fourthly, the present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and capable of running on the processor, wherein the processor executes the program to implement the steps of the abnormal monitoring method for a photovoltaic-storage-charging microgrid system described in the first aspect.

[0040] Fifthly, the present invention also provides a computer program product, the computer program product comprising a computer program, which, when executed by a processor, implements the steps of the abnormal monitoring method for a photovoltaic-storage-charging microgrid system described in the first aspect.

[0041] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0042] In this invention, the photovoltaic panel power generation is corrected once based on the amount of smog; the smog value under the influence of wind speed is obtained through ambient wind speed, and the photovoltaic panel power generation is corrected a second time based on the smog value under the influence of wind speed; if the wind speed is lower than a preset value, the smog value under the influence of humidity is obtained through ambient humidity, and the photovoltaic panel power generation is corrected a third time based on the smog value under the influence of humidity; and the smog value under the influence of temperature is obtained through ambient temperature, and the photovoltaic panel power generation is corrected a fourth time based on the smog value under the influence of temperature. The photovoltaic panel power generation after the four data corrections is used for anomaly detection; otherwise, the photovoltaic panel power generation after the second data correction is used for anomaly detection. This invention realizes the anomaly detection when the power generation is reduced due to smog, and considers multiple factors such as ambient wind speed, temperature, and humidity that cause data changes, and determines the power generation correction value under the influence of each factor, which greatly improves the accuracy of anomaly monitoring and judgment. Attached Figure Description

[0043] The accompanying drawings, which form part of this embodiment, are used to provide a further understanding of this embodiment. The illustrative embodiments and their descriptions are used to explain this embodiment and do not constitute an improper limitation of this embodiment.

[0044] Figure 1 This is a flowchart of the method in Embodiment 1 of the present invention;

[0045] Figure 2 This is a schematic diagram of the module connection relationship of the photovoltaic-storage-charging microgrid system according to Embodiment 2 of the present invention;

[0046] Figure 3 This is a schematic diagram showing the connection relationship between the photovoltaic-storage-charging microgrid system and the anomaly monitoring system in Embodiment 2 of the present invention. Detailed Implementation

[0047] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0048] It should be noted that the following detailed descriptions are exemplary and intended to provide further explanation of this application. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains.

[0049] Example 1:

[0050] This embodiment provides an anomaly monitoring method for a photovoltaic-storage-charging microgrid system. The more severe the smog, the greater the impact on photovoltaic power generation, resulting in less power output. Therefore, the photovoltaic power generation data is corrected to obtain the true power generation after removing the smog factor, leading to more accurate anomaly detection and avoiding alarms caused by smog. When smog is present, higher wind speeds result in less smog, allowing for further optimization of smog values ​​to more accurately determine the photovoltaic power generation data and more precise judgment of the true power generation. Conversely, when wind speeds are low, environmental humidity gradually increases, leading to a relative increase in smog values. This requires further optimization of smog value data, resulting in more accurate final power generation data and more precise anomaly detection, preventing smog-affected data from influencing anomaly judgment. As wind speed decreases, the temperature around the photovoltaic panels increases, causing faster smog dissipation and a relative decrease in smog values. This allows for further correction of the true photovoltaic power generation data to obtain the final high-precision data, making smog data calculation more accurate and effectively eliminating the smog factor. By refining the accuracy of haze data, it is possible to determine whether the generated electricity data truly exceeds the system's set value, thereby improving the accuracy of alarms and significantly enhancing the precision of detecting power generation anomalies. Optionally, the monitoring method in this embodiment includes the following steps:

[0051] S1. Generate photovoltaic power through photovoltaic panels and obtain the power generated by the photovoltaic panels.

[0052] S2. Identify the power generation of the photovoltaic panel and correct the power generation data of the photovoltaic panel.

[0053] S3. Identify the environmental haze value through the network, calculate the power generation affected by the haze level, and then perform a data correction on the photovoltaic panel power generation.

[0054] S4. Identify the ambient wind speed through the network, measure the haze value, measure the power generation affected by the haze value, and perform secondary data correction on the photovoltaic power generation. When the wind speed is low, proceed to step S5; otherwise, proceed to step S7.

[0055] S5. As the ambient humidity increases, the increased haze value is measured based on the humidity, and the affected power generation is measured based on the haze value. The power generation of the photovoltaic panel is then corrected three times.

[0056] S6. At the same time, the ambient temperature gradually increases, which reduces the haze value. The power generation affected by the reduced haze value is measured, and the power generation of the photovoltaic panel is corrected four times.

[0057] In this embodiment, the detection and acquisition of environmental haze value, environmental wind speed, environmental temperature and environmental humidity can be achieved by corresponding conventional sensors, which will not be described in detail here.

[0058] S7. By identifying whether the corrected photovoltaic panel power generation data exceeds the limit value, an alarm is sent to the terminal to identify whether there is an abnormality in photovoltaic power generation.

[0059] S8. Store the electricity generated by the photovoltaic panels and distribute the stored electricity to the charging piles.

[0060] Optionally, in steps S2 and S3, when performing a data correction on the photovoltaic panel's power generation:

[0061] ;

[0062] ;

[0063] in, The amount of electricity generated by photovoltaic panels affected by smog; The photovoltaic panel power generation most affected by smog; For environmental smog; The greatest environmental smog; The amount of electricity generated by the photovoltaic panels; This represents the revised power generation of the photovoltaic panel; that is, the power generation of the photovoltaic panel is corrected once.

[0064] Optionally, in step S4, when performing secondary data correction on the photovoltaic panel power generation:

[0065] ;

[0066] ;

[0067] ;

[0068] in, The environmental haze value is affected by wind speed; The environmental haze value after the influence of wind speed; For ambient wind speed; Maximum ambient wind speed; The data represents the photovoltaic power generation after secondary correction. This is because wind speed affects smog levels; higher wind speeds result in lower smog levels. Therefore, the environmental smog data is corrected, and the photovoltaic power generation data is also corrected a second time.

[0069] Optionally, in steps S4 and S5: assuming Normal wind speed, when the ambient wind speed hour:

[0070] ;

[0071] ;

[0072] , ;

[0073] in, This is the photovoltaic panel power generation after three revisions. The environmental haze value after the influence of humidity. The environmental haze value is affected by humidity. For ambient humidity, For maximum ambient humidity, This represents the minimum wind speed; that is, when the wind speed is low, the ambient humidity increases, thus worsening the smog, requiring further adjustments to the power generation data; when hour: .

[0074] Optionally, in steps S4, S5, and S6: when hour, Normal wind speed:

[0075] ;

[0076] ;

[0077] , ;

[0078] in, This represents the photovoltaic panel power generation after four revisions. This represents the environmental haze value after temperature influence. The environmental haze value is affected by temperature. For ambient temperature, The maximum ambient temperature; that is, when the wind speed is low, the temperature gradually rises, thus relatively reducing smog, and the power generation data is revised again; when hour: .

[0079] Optionally, in step S7, it is assumed that... For the system-defined power generation data, when and / or If the corrected power generation data exceeds the system setting value, no alarm will be issued; when and / or If the corrected power generation data does not exceed the system setting value, an alarm will be issued.

[0080] This embodiment improves the accuracy of alarms and greatly enhances the accuracy of judging abnormal power generation by refining the haze data to determine whether the generated power data actually exceeds the system's set value.

[0081] Example 3:

[0082] This embodiment provides an anomaly monitoring system for a photovoltaic-storage-charging microgrid system. Optionally, the photovoltaic-storage-charging microgrid system includes photovoltaic panel modules, battery modules, and power distribution modules; the anomaly monitoring system is electrically connected to the photovoltaic panel modules.

[0083] The photovoltaic panel module is used to generate photovoltaic power through the photovoltaic panel. The battery module is used to store the electricity generated by the photovoltaic panel. The power distribution module is used to distribute the stored electricity to the charging pile. The abnormal monitoring system includes a power generation identification module, an alarm module, an information correction module, and a terminal module. The power generation identification module is electrically connected to the photovoltaic panel module. The information correction module and the power generation identification module are both electrically connected to the alarm module. The alarm module is electrically connected to the terminal module. The power generation identification module is used to identify the power generation of the photovoltaic panel. The alarm module is used to set a limit value and issue an alarm by identifying whether the power generation of the photovoltaic panel exceeds the limit value. The information correction module is used to correct the power generation data of the photovoltaic panel according to various parameters. The terminal module is used to receive the alarm issued by the alarm module, thereby identifying whether there is an abnormality in photovoltaic power generation.

[0084] Optionally, the information correction module includes a haze identification unit, a wind speed identification unit, and a data correction unit. The haze identification unit, the wind speed identification unit, and the data correction unit are electrically connected to each other. The haze identification unit is used to identify the ambient haze value through the network, the wind speed identification unit is used to identify the ambient wind speed through the network, and the data correction unit is used to correct the photovoltaic panel power generation data.

[0085] The operation method of the photovoltaic-storage-charging microgrid system and the anomaly monitoring system includes:

[0086] Step S1: Photovoltaic power generation is carried out through photovoltaic panels, and the power generated by the photovoltaic panels is input into the anomaly monitoring system;

[0087] Step S2: Identify the power generation of the photovoltaic panel through the power generation identification module, and then correct the power generation data of the photovoltaic panel through the information correction module;

[0088] Step S3: Identify the environmental haze value through the network, calculate the power generation affected by the haze size, and then correct the photovoltaic panel power generation data once through the data correction unit.

[0089] Step S4: Identify the ambient wind speed through the network, measure the haze value, measure the power generation affected by the haze value, and perform secondary data correction on the photovoltaic power generation. When the wind speed is low, proceed to step S5; otherwise, proceed to step S7.

[0090] Step S5: As the ambient humidity increases, the increased haze value is measured based on the humidity. Then, the power generation affected by the haze value is measured, and the power generation of the photovoltaic panel is corrected three times.

[0091] Step S6: At the same time, the temperature gradually increases, which reduces the haze value. The power generation affected by the reduced haze value is measured, and the power generation of the photovoltaic panel is corrected four times.

[0092] Step S7: By identifying whether the corrected photovoltaic panel power generation data exceeds the limit value, an alarm is sent to the terminal to identify whether there is an abnormality in photovoltaic power generation;

[0093] Step S8: The battery module stores the electricity generated by the photovoltaic panel and distributes the stored electricity to the charging pile through the power distribution module.

[0094] Optionally, in steps S2 and S3, when performing a data correction on the photovoltaic panel's power generation:

[0095] ;

[0096] ;

[0097] in, The amount of electricity generated by photovoltaic panels affected by smog; The photovoltaic panel power generation most affected by smog; For environmental smog; The greatest environmental smog; The amount of electricity generated by the photovoltaic panels; This represents the revised power generation of the photovoltaic panel; that is, the power generation of the photovoltaic panel is corrected once.

[0098] Optionally, in step S4, when performing secondary data correction on the photovoltaic panel power generation:

[0099] ;

[0100] ;

[0101] ;

[0102] in, The environmental haze value is affected by wind speed; The environmental haze value after the influence of wind speed; For ambient wind speed; Maximum ambient wind speed; The data represents the photovoltaic power generation after secondary correction. This is because wind speed affects smog levels; higher wind speeds result in lower smog levels. Therefore, the environmental smog data is corrected, and the photovoltaic power generation data is also corrected a second time.

[0103] Optionally, in steps S4 and S5: assuming Normal wind speed, when the ambient wind speed hour:

[0104] ;

[0105] ;

[0106] , ;

[0107] in, This is the photovoltaic panel power generation after three revisions. The environmental haze value after the influence of humidity. The environmental haze value is affected by humidity. For ambient humidity, For maximum ambient humidity, This represents the minimum wind speed; that is, when the wind speed is low, the ambient humidity increases, thus worsening the smog, requiring further adjustments to the power generation data; when hour: .

[0108] Optionally, in steps S4, S5, and S6: when hour, Normal wind speed:

[0109] ;

[0110] ;

[0111] , ;

[0112] in, This represents the photovoltaic panel power generation after four revisions. This represents the environmental haze value after temperature influence. The environmental haze value is affected by temperature. For ambient temperature, The maximum ambient temperature; that is, when the wind speed is low, the temperature gradually rises, thus relatively reducing smog, and the power generation data is revised again; when hour: .

[0113] Optionally, in step S7, it is assumed that... For the system-defined power generation data, when and / or If the corrected power generation data exceeds the system setting value, no alarm will be issued; when and / or If the corrected power generation data does not exceed the system setting value, an alarm will be issued.

[0114] Example 3:

[0115] This embodiment provides an anomaly monitoring system for a photovoltaic-storage-charging microgrid system, including:

[0116] The data acquisition module is configured to acquire data on photovoltaic panel power generation, ambient haze levels, ambient wind speed, ambient temperature, and ambient humidity.

[0117] The data correction module is configured to: correct the photovoltaic panel power generation data based on the level of smog;

[0118] The secondary data correction module is configured to: perform a first data correction on the photovoltaic panel power generation based on the smog level; obtain the smog value under the influence of wind speed through the ambient wind speed, and perform a second data correction on the photovoltaic panel power generation based on the smog value under the influence of wind speed.

[0119] The anomaly detection module is configured as follows: if the wind speed is lower than the preset value, the fog value affected by the humidity is obtained through the ambient humidity, and the photovoltaic power generation is corrected three times based on the fog value affected by the humidity. The fog value affected by the temperature is obtained through the ambient temperature, and the photovoltaic power generation is corrected four times based on the fog value affected by the temperature. The anomaly detection is performed using the photovoltaic power generation after the four data corrections. Otherwise, the anomaly detection is performed using the photovoltaic power generation after the two data corrections.

[0120] The working method of the system is the same as the anomaly monitoring method for the photovoltaic-storage-charging microgrid system in Example 1, and will not be repeated here.

[0121] Example 4:

[0122] This embodiment provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the abnormal monitoring method for a photovoltaic-storage-charging microgrid system described in Embodiment 1.

[0123] Example 5:

[0124] This embodiment provides an electronic device, including a memory, a processor, and a computer program stored in the memory and capable of running on the processor. When the processor executes the program, it implements the steps of the abnormal monitoring method for a photovoltaic-storage-charging microgrid system described in Embodiment 1.

[0125] Example 6:

[0126] This embodiment provides a computer program product, which includes a computer program. When the computer program is executed by a processor, it implements the steps of the abnormal monitoring method for a photovoltaic-storage-charging microgrid system described in Embodiment 1.

[0127] The above description is merely a preferred embodiment of this practice and is not intended to limit the scope of this practice. Various modifications and variations can be made to this practice by those skilled in the art. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of this practice should be included within the protection scope of this practice.

Claims

1. A method for anomaly monitoring in a photovoltaic-storage-charging microgrid system, characterized in that, include: Acquire data on photovoltaic panel power generation, ambient haze levels, ambient wind speed, ambient temperature, and ambient humidity; The power generation of the photovoltaic panels is corrected once based on the severity of the smog. The haze value under the influence of wind speed is obtained by obtaining the haze value under the influence of wind speed, and the power generation of photovoltaic panels is corrected in a secondary data manner based on the haze value under the influence of wind speed. If the wind speed is lower than the preset value, the smog value affected by the humidity is obtained through the ambient humidity. The power generation of the photovoltaic panel is corrected three times based on the smog value affected by the humidity. The smog value affected by the temperature is obtained through the ambient temperature. The power generation of the photovoltaic panel is corrected four times based on the smog value affected by the temperature. The power generation of the photovoltaic panel after the four data corrections is used to determine anomalies. Otherwise, the power generation of the photovoltaic panel after the two data corrections is used to determine anomalies. When performing a data correction on the photovoltaic panel power generation: ； ； in, The amount of electricity generated by photovoltaic panels affected by smog; The photovoltaic panel power generation most affected by smog; Environmental haze level; This represents the maximum environmental haze value. The amount of electricity generated by the photovoltaic panels; This represents the power generation from the photovoltaic panels after a one-time correction.

2. The anomaly monitoring method for a photovoltaic-storage-charging microgrid system as described in claim 1, characterized in that, When performing secondary data correction on photovoltaic panel power generation: ； ； ； in, Environmental haze value affected by wind speed; The environmental haze value after the influence of wind speed; For ambient wind speed; Maximum ambient wind speed; This is the photovoltaic power generation after secondary correction.

3. The anomaly monitoring method for a photovoltaic-storage-charging microgrid system as described in claim 2, characterized in that, When performing three data corrections on the photovoltaic panel power generation: ； ； ， ； in, This is the photovoltaic panel power generation after three corrections. The environmental haze value after humidity influence. The environmental haze value is affected by humidity. For ambient humidity, For maximum ambient humidity, This is the lowest wind speed.

4. The anomaly monitoring method for a photovoltaic-storage-charging microgrid system as described in claim 3, characterized in that, When performing four data corrections on the photovoltaic panel power generation: ； ； ， ； in, This represents the photovoltaic panel power generation after four revisions. This represents the environmental haze value after temperature influence. The environmental haze value is affected by temperature. For ambient temperature, This represents the maximum ambient temperature.

5. The anomaly monitoring method for a photovoltaic-storage-charging microgrid system as described in claim 1, characterized in that, If the corrected power generation of the photovoltaic panel exceeds the preset limit, no alarm will be triggered; otherwise, an alarm will be triggered.

6. An anomaly monitoring system for a photovoltaic-storage-charging microgrid system, characterized in that, include: The data acquisition module is configured to acquire data on photovoltaic panel power generation, ambient haze levels, ambient wind speed, ambient temperature, and ambient humidity. The data correction module is configured to: correct the photovoltaic panel power generation data based on the level of smog; The secondary data correction module is configured to: perform a first data correction on the photovoltaic panel power generation based on the smog level; obtain the smog value under the influence of wind speed through the ambient wind speed, and perform a second data correction on the photovoltaic panel power generation based on the smog value under the influence of wind speed. The anomaly detection module is configured as follows: if the wind speed is lower than a preset value, the module obtains the haze value affected by humidity based on the ambient humidity, performs three data corrections on the photovoltaic panel power generation based on the haze value affected by humidity, and obtains the haze value affected by temperature based on the ambient temperature, performs four data corrections on the photovoltaic panel power generation based on the haze value affected by temperature, and uses the photovoltaic panel power generation after four data corrections for anomaly detection; otherwise, the module uses the photovoltaic panel power generation after two data corrections for anomaly detection. When performing a data correction on the photovoltaic panel power generation: ； ； in, The amount of electricity generated by photovoltaic panels affected by smog; The photovoltaic panel power generation most affected by smog; Environmental haze level; This represents the maximum environmental haze value. The amount of electricity generated by the photovoltaic panels; This represents the power generation from the photovoltaic panels after a one-time correction.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by the processor, the program implements the steps of the anomaly monitoring method for a photovoltaic-storage-charging microgrid system as described in any one of claims 1-5.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and capable of running on the processor, characterized in that, When the processor executes the program, it implements the steps of the abnormal monitoring method for a photovoltaic-storage-charging microgrid system as described in any one of claims 1-5.

9. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the steps of the abnormal monitoring method for a photovoltaic-storage-charging microgrid system as described in any one of claims 1-5.

Images