Abnormality monitoring method and system for optical storage and charging micro-grid system

Abstract

The invention belongs to the technical field of optical storage and charging microgrids, provides an abnormality monitoring method and system for an optical storage and charging microgrid system, and aims to solve the problem that judgment cannot be performed or the judgment precision is relatively low when haze factors affect the generating capacity. Primary data correction is carried out on the generating capacity of the photovoltaic panel according to the haze size; performing secondary data correction on the generating capacity of the photovoltaic panel according to the haze value under the influence of the wind speed; performing data correction on the generating capacity of the photovoltaic panel for three times according to the haze value under the influence of the humidity, performing data correction on the generating capacity of the photovoltaic panel for four times according to the haze value under the influence of the temperature, and performing abnormality judgment by using the generating capacity of the photovoltaic panel after the data correction for four times; according to the method, the abnormality judgment when the generating capacity is reduced due to the haze factor is realized, the data change caused by multiple factors such as environment wind speed, temperature and humidity is considered, the generating capacity correction value under the influence of the factors is determined, and the accuracy of abnormality monitoring judgment is greatly improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of photovoltaic energy storage and charging microgrids, and particularly relates to an abnormal monitoring method and system for a photovoltaic energy storage and charging microgrid system. Background Art

[0002] A photovoltaic energy storage and charging microgrid system is an energy supply system that integrates photovoltaic power generation, energy storage, and charging facilities. By integrating devices such as solar photovoltaic panels, energy storage batteries, and charging piles, it realizes the autonomous production, storage, and distribution of energy, providing stable and reliable power supply for users. For the power generation of photovoltaic panels, real-time monitoring is required, and when abnormalities occur, maintenance or repair of the photovoltaic panels is carried out.

[0003] Currently, when monitoring abnormal power generation, the power generation reduction caused by haze factors cannot be accurately judged. Even if a judgment is made, the judgment accuracy is low. The size of the haze will cause data changes due to multiple factors such as environmental wind speed, temperature, and humidity, greatly affecting the judgment accuracy. Summary of the Invention

[0004] In order to solve the above problems, the present invention proposes an abnormal monitoring method and system for a photovoltaic energy storage and charging microgrid system. The present invention realizes the abnormal judgment when the power generation is reduced due to haze factors, takes into account the data changes caused by multiple factors such as environmental wind speed, temperature, and humidity, and determines the power generation correction value under the influence of each factor, greatly improving the accuracy of abnormal monitoring judgment.

[0005] To achieve the above object, the present invention is implemented through the following technical solutions: In the first aspect, the present invention provides an abnormal monitoring method for a photovoltaic energy storage and charging microgrid system, including: An abnormal monitoring method for a photovoltaic energy storage and charging microgrid system, including: Obtain the power generation of the photovoltaic panel, the environmental haze value, the environmental wind speed, the environmental temperature, and the environmental humidity; Perform primary data correction on the power generation of the photovoltaic panel according to the size of the haze; Obtain the haze value affected by the wind speed through the environmental wind speed, and perform secondary data correction on the power generation of the photovoltaic panel according to the haze value affected by the wind speed; If the wind speed is lower than the preset value, obtain the haze value affected by the humidity through the environmental humidity, perform tertiary data correction on the power generation of the photovoltaic panel according to the haze value affected by the humidity, and obtain the haze value affected by the temperature through the environmental temperature, perform quaternary data correction on the power generation of the photovoltaic panel according to the haze value affected by the temperature, and use the power generation of the photovoltaic panel after the quaternary data correction for abnormal judgment; otherwise, use the power generation of the photovoltaic panel after the secondary data correction for abnormal judgment.

[0006] Further, when performing the first data correction on the power generation of the photovoltaic panel: ; ; Wherein, is the power generation of the photovoltaic panel affected by haze; is the maximum power generation of the photovoltaic panel affected by haze; is the environmental haze; is the maximum environmental haze; is the power generation of the photovoltaic panel; is the power generation of the photovoltaic panel after the first correction.

[0007] Further, when performing the second data correction on the power generation of the photovoltaic panel: ; ; ; Wherein, is the environmental haze value affected by wind speed; is the environmental haze value after being affected by wind speed; is the environmental wind speed; is the maximum environmental wind speed; is the power generation of the photovoltaic panel after the second correction.

[0008] Further, when performing the third data correction on the power generation of the photovoltaic panel: ; ; , ; Wherein, is the power generation of the photovoltaic panel after the third correction, is the environmental haze value after being affected by humidity, is the environmental haze value affected by humidity, is the environmental humidity, is the maximum environmental humidity, is the minimum wind speed.

[0009] Further, when performing the fourth data correction on the power generation of the photovoltaic panel: ; ; , ; Wherein, is the power generation of the photovoltaic panel after the fourth correction, is the environmental haze value after being affected by temperature, is the environmental haze value affected by temperature, is the environmental temperature, is the maximum environmental temperature.

[0010] Furthermore, if the power generation of the photovoltaic panel after correction exceeds the preset limit value, no alarm is given; otherwise, an alarm is given.

[0011] In a second aspect, the present invention further provides an abnormal monitoring system for a photovoltaic energy storage charging microgrid system, including: An abnormal monitoring system for a photovoltaic energy storage charging microgrid system, including: A data acquisition module, configured to: obtain the power generation of the photovoltaic panel, the environmental haze value, the environmental wind speed, the environmental temperature, and the environmental humidity; A primary data correction module, configured to: perform primary data correction on the power generation of the photovoltaic panel according to the haze level; A secondary data correction module, configured to: perform primary data correction on the power generation of the photovoltaic panel according to the haze level; obtain the haze value affected by the wind speed through the environmental wind speed, and perform secondary data correction on the power generation of the photovoltaic panel according to the haze value affected by the wind speed; An abnormal judgment module, configured to: if the wind speed is lower than the preset value, obtain the haze value affected by the humidity through the environmental humidity, perform tertiary data correction on the power generation of the photovoltaic panel according to the haze value affected by the humidity, and obtain the haze value affected by the temperature through the environmental temperature, perform quaternary data correction on the power generation of the photovoltaic panel according to the haze value affected by the temperature, and use the power generation of the photovoltaic panel after quaternary data correction to perform abnormal judgment; otherwise, use the power generation of the photovoltaic panel after secondary data correction to perform abnormal judgment.

[0012] In a third aspect, the present invention further provides a computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, the steps of the abnormal monitoring method for a photovoltaic energy storage charging microgrid system described in the first aspect are implemented.

[0013] In a fourth aspect, the present invention further provides an electronic device, including a memory, a processor, and a computer program stored on the memory and capable of running on the processor, and when the processor executes the program, the steps of the abnormal monitoring method for a photovoltaic energy storage charging microgrid system described in the first aspect are implemented.

[0014] In a fifth aspect, the present invention further provides a computer program product, the computer program product includes a computer program, and when the computer program is executed by a processor, the steps of the abnormal monitoring method for a photovoltaic energy storage charging microgrid system described in the first aspect are implemented.

[0015] Compared with the prior art, the beneficial effects of the present invention are as follows: In the present invention, primary data correction of the power generation of the photovoltaic panel is performed according to the size of the haze; the haze value affected by the wind speed is obtained through the environmental wind speed, and secondary data correction of the power generation of the photovoltaic panel is performed according to the haze value affected by the wind speed; if the wind speed is lower than the preset value, the haze value affected by the humidity is obtained through the environmental humidity, and tertiary data correction of the power generation of the photovoltaic panel is performed according to the haze value affected by the humidity, and the haze value affected by the temperature is obtained through the environmental temperature, and quaternary data correction of the power generation of the photovoltaic panel is performed according to the haze value affected by the temperature, and abnormal judgment is performed using the power generation of the photovoltaic panel after the quaternary data correction; otherwise, abnormal judgment is performed using the power generation of the photovoltaic panel after the secondary data correction, realizing abnormal judgment when the power generation is reduced due to haze factors, and considering data changes caused by multiple factors such as environmental wind speed, temperature, and humidity, and determining the power generation correction value under the influence of each factor, greatly improving the accuracy of abnormal monitoring and judgment. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The accompanying drawings forming a part of this embodiment are used to provide a further understanding of this embodiment. The schematic embodiments and descriptions thereof of this embodiment are used to explain this embodiment and do not constitute an improper limitation of this embodiment.

[0017] Figure 1 It is a flowchart of the method of Embodiment 1 of the present invention; Figure 2 It is a schematic diagram of the connection relationship of the optical storage and charging microgrid system module of Embodiment 2 of the present invention; Figure 3 It is a schematic diagram of the connection relationship between the optical storage and charging microgrid system and the abnormal monitoring system of Embodiment 2 of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0018] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0019] It should be noted that the following detailed description is exemplary and is intended to provide further explanation of the present application. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the technical field to which the present application belongs.

[0020] Embodiment 1: This embodiment provides an abnormal monitoring method for a photovoltaic-storage-charging microgrid system. The more severe the haze is, the greater the impact on the power generation of the photovoltaic panels, and the less the power generation. At this time, the data of the power generation of the photovoltaic panels is corrected once to obtain the true power generation after removing the haze factor. The abnormal judgment can be relatively accurate, avoiding alarms caused by haze, and accurately determining the data of the power generation of the photovoltaic panels. When there is haze, the greater the wind speed, the smaller the haze. Therefore, by optimizing the haze value, the data of the power generation of the photovoltaic panels can be further refined, and the true power generation can be accurately judged. When the wind speed is low, the humidity of the environment gradually rises. At this time, due to the influence of humidity, the haze value increases relatively. Therefore, the haze value data is optimized again to make the final power generation data more accurate and the abnormal judgment more precise, eliminating the phenomenon that the data affected by haze affects the abnormal judgment. After the wind speed decreases, the temperature around the photovoltaic panels increases relatively. After the increase, the haze dissipates quickly, so that the haze value decreases relatively. At this time, the true power generation of the photovoltaic panels is corrected again to measure the final high-precision data, and the measurement of the haze data is more accurate, fully eliminating the haze factor. By refining the haze data, it can be judged whether the power generation data truly exceeds the system set value, improving the accuracy of the alarm and greatly enhancing the accuracy of the judgment of power generation abnormalities. Optionally, the monitoring method of this embodiment includes the following steps: S1. Perform photovoltaic power generation through the photovoltaic panels to obtain the power generation of the photovoltaic panels.

[0021] S2. Identify the power generation of the photovoltaic panels and correct the power generation data of the photovoltaic panels.

[0022] S3. Identify the environmental haze value through the network, calculate the affected power generation according to the size of the haze, and then perform a data correction on the power generation of the photovoltaic panels once.

[0023] S4. Identify the environmental wind speed through the network, measure the affected haze value, calculate the affected power generation according to the haze value, and perform a secondary data correction on the power generation of the photovoltaic panels. When the wind speed is low, enter step S5; otherwise, enter step S7.

[0024] S5. The environmental humidity rises, so the increased haze value is measured according to the humidity, and then the affected power generation is measured according to the haze value, and a tertiary data correction is performed on the power generation of the photovoltaic panels.

[0025] S6. At the same time, the environmental temperature gradually increases, that is, the haze value is reduced. The affected power generation is measured according to the reduced haze value, and a quaternary data correction is performed on the power generation of the photovoltaic panels.

[0026] In this embodiment, the detection and acquisition of the environmental haze value, environmental wind speed, environmental temperature, and environmental humidity can be realized by corresponding conventional sensors, which will not be elaborated here.

[0027] S7. Identify whether the power generation data of the corrected photovoltaic panel exceeds the limit value and issue an alarm to the terminal, thereby identifying whether there is an abnormality in photovoltaic power generation.

[0028] S8. Store the electricity generated by the photovoltaic panel and distribute the stored electricity to the charging pile.

[0029] Optionally, in steps S2 and S3, when performing a first data correction on the power generation of the photovoltaic panel: ; ; where is the power generation of the photovoltaic panel affected by haze; is the maximum power generation of the photovoltaic panel affected by haze; is the environmental haze; is the maximum environmental haze; is the power generation of the photovoltaic panel; is the power generation of the photovoltaic panel after the first correction; that is, perform a first data correction on the power generation of the photovoltaic panel.

[0030] Optionally, in step S4, when performing a second data correction on the power generation of the photovoltaic panel: ; ; ; where is the environmental haze value affected by wind speed; is the environmental haze value after being affected by wind speed; is the environmental wind speed; is the maximum environmental wind speed; is the power generation of the photovoltaic panel after the second correction; that is, the level of wind speed affects haze. The greater the wind speed, the lower the haze, thereby correcting the environmental haze data and performing a second data correction on the power generation of the photovoltaic panel.

[0031] Optionally, in steps S4 and S5: Assume is the normal wind speed. When the environmental wind speed : ; ; , ; where is the power generation of the photovoltaic panel after the third correction, is the environmental haze value affected by humidity, is the environmental haze value affected by humidity, is the environmental humidity, is the maximum environmental humidity, is the lowest wind speed; that is, when the wind speed is low, the environmental humidity increases, which makes the haze worse and the power generation data is further corrected; when : .

[0032] Optionally, in steps S4, S5 and S6: when , is the normal wind speed: ; ; , ; wherein, is the power generation of the photovoltaic panel after four corrections, is the environmental haze value affected by temperature, is the environmental haze value affected by temperature, is the environmental temperature, is the maximum environmental temperature; that is, when the wind speed is low, the temperature gradually rises, which makes the haze relatively reduced and the power generation data is corrected again; when : .

[0033] Optionally, in step S7, assuming that is the power generation data limited by the system, when and / or , if the corrected power generation data exceeds the system set value, no alarm is issued; when and / or , if the corrected power generation data does not exceed the system set value, an alarm is issued.

[0034] In this embodiment, by precisifying the haze data, it can be judged whether the power generation data truly exceeds the system set value, which can improve the accuracy of the alarm and greatly enhance the accuracy of judging power generation anomalies.

[0035] Embodiment 3: This embodiment provides an abnormal monitoring system for a photovoltaic-storage-charging microgrid system. Optionally, the photovoltaic-storage-charging microgrid system includes a photovoltaic panel module, a battery module and a power distribution module; the abnormal monitoring system is electrically connected to the photovoltaic panel module.

[0036] The photovoltaic panel module is used for generating electricity through the photovoltaic panel. The battery module is used for storing the electricity generated by the photovoltaic panel. The power distribution module is used for distributing the stored electricity to the charging pile. The abnormal monitoring system includes a power generation amount identification module, an alarm module, an information correction module, and a terminal module. The power generation amount identification module is electrically connected to the photovoltaic panel module. Both the information correction module and the power generation amount identification module are electrically connected to the alarm module. The alarm module is electrically connected to the terminal module. The power generation amount identification module is used for identifying the power generation amount of the photovoltaic panel. The alarm module is used for setting a limit value and sending an alarm by identifying whether the power generation amount of the photovoltaic panel exceeds the limit value. The information correction module is used for correcting the power generation amount data of the photovoltaic panel according to various parameters. The terminal module is used for receiving the alarm sent by the alarm module to identify whether there is an abnormality in the photovoltaic power generation.

[0037] 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 for identifying the environmental haze value through the network. The wind speed identification unit is used for identifying the environmental wind speed through the network. The data correction unit is used for performing data correction on the power generation amount of the photovoltaic panel.

[0038] The operation method of the photovoltaic energy storage charging microgrid system and the abnormal monitoring system includes: Step S1: Generate electricity through the photovoltaic panel, and input the power generation amount of the photovoltaic panel into the abnormal monitoring system; Step S2: Identify the power generation amount of the photovoltaic panel through the power generation amount identification module, and then correct the power generation amount data of the photovoltaic panel through the information correction module; Step S3: Identify the environmental haze value through the network, then calculate the affected power generation amount according to the haze size, and then perform a first data correction on the power generation amount of the photovoltaic panel through the data correction unit; Step S4: Identify the environmental wind speed through the network, measure the affected haze value, then calculate the affected power generation amount according to the haze value, and perform a second data correction on the power generation amount of the photovoltaic panel. When the wind speed is low, enter Step S5; otherwise, enter Step S7; Step S5: The environmental humidity rises, so calculate the increased haze value according to the humidity, then calculate the affected power generation amount according to the haze value, and perform a third data correction on the power generation amount of the photovoltaic panel; Step S6: At the same time, the temperature gradually increases, which reduces the haze value. Calculate the affected power generation amount according to the reduced haze value, and perform a fourth data correction on the power generation amount of the photovoltaic panel; Step S7: Identify whether the corrected power generation amount data of the photovoltaic panel exceeds the limit value, and then send an alarm to the terminal to identify whether there is an abnormality in the photovoltaic power generation; Step S8: The battery module stores the electricity generated by the photovoltaic panels and distributes the stored electricity to the charging piles through the power distribution module.

[0039] Optionally, in steps S2 and S3, when performing a first data correction on the power generation of the photovoltaic panels: ; ; Wherein, is the power generation of the photovoltaic panels affected by haze; is the maximum power generation of the photovoltaic panels affected by haze; is the environmental haze; is the maximum environmental haze; is the power generation of the photovoltaic panels; is the power generation of the photovoltaic panels after the first correction; that is, a first data correction is performed on the power generation of the photovoltaic panels.

[0040] Optionally, in step S4, when performing a second data correction on the power generation of the photovoltaic panels: ; ; ; Wherein, is the environmental haze value affected by wind speed; is the environmental haze value after being affected by wind speed; is the environmental wind speed; is the maximum environmental wind speed; is the power generation of the photovoltaic panels after the second correction; that is, the level of wind speed affects haze, the greater the wind speed, the lower the haze, thus correcting the environmental haze data and performing a second data correction on the power generation of the photovoltaic panels.

[0041] Optionally, in steps S4 and S5: Assume is the normal wind speed. When the environmental wind speed : ; ; , ; Wherein, is the power generation of the photovoltaic panels after the third correction, is the environmental haze value after being affected by humidity, is the environmental haze value affected by humidity, is the environmental humidity, is the maximum environmental humidity, is the minimum wind speed; that is, when the wind speed is low, the environmental humidity increases, which makes the haze worse and further corrects the power generation data; when : .

[0042] Optionally, in steps S4, S5 and S6: when : is the normal wind speed: ; ; , ; wherein, is the power generation of the photovoltaic panel after four corrections, is the environmental haze value affected by temperature, is the environmental haze value affected by temperature, is the environmental temperature, is the maximum environmental temperature; that is, when the wind speed is low, the temperature gradually rises, which makes the haze relatively decrease and the power generation data is corrected again; when : .

[0043] Optionally, in step S7, assuming that is the power generation data limited by the system, when and / or , if the corrected power generation data exceeds the system setting value, no alarm is issued; when and / or , if the corrected power generation data does not exceed the system setting value, an alarm is issued.

[0044] Embodiment 3: This embodiment provides an abnormal monitoring system for a photovoltaic-storage-charging microgrid system, including: A data acquisition module, configured to: acquire the power generation of the photovoltaic panel, the environmental haze value, the environmental wind speed, the environmental temperature and the environmental humidity; A primary data correction module, configured to: perform primary data correction on the power generation of the photovoltaic panel according to the haze size; A secondary data correction module, configured to: perform primary data correction on the power generation of the photovoltaic panel according to the haze size; obtain the haze value affected by the wind speed through the environmental wind speed, and perform secondary data correction on the power generation of the photovoltaic panel according to the haze value affected by the wind speed; Anomaly judgment module, configured to: if the wind speed is lower than a preset value, obtain the haze value affected by the humidity based on the ambient humidity, perform three data corrections on the power generation of the photovoltaic panel according to the haze value affected by the humidity, and obtain the haze value affected by the temperature based on the ambient temperature, perform four data corrections on the power generation of the photovoltaic panel according to the haze value affected by the temperature, and use the power generation of the photovoltaic panel after four data corrections to perform anomaly judgment; otherwise, use the power generation of the photovoltaic panel after two data corrections to perform anomaly judgment.

[0045] The working method of the system is the same as the anomaly monitoring method for the photovoltaic energy storage and charging microgrid system in Embodiment 1, and will not be elaborated here.

[0046] Embodiment 4: This embodiment provides a computer-readable storage medium, on which a computer program is stored. When the program is executed by a processor, the steps of the anomaly monitoring method for the photovoltaic energy storage and charging microgrid system described in Embodiment 1 are implemented.

[0047] Embodiment 5: This embodiment provides an electronic device, including a memory, a processor, and a computer program stored on the memory and capable of running on the processor. When the processor executes the program, the steps of the anomaly monitoring method for the photovoltaic energy storage and charging microgrid system described in Embodiment 1 are implemented.

[0048] Embodiment 6: This embodiment provides a computer program product, the computer program product includes a computer program, and when the computer program is executed by a processor, the steps of the anomaly monitoring method for the photovoltaic energy storage and charging microgrid system described in Embodiment 1 are implemented.

[0049] The above are only the preferred embodiments of this embodiment and are not used to limit this embodiment. For those skilled in the art, this embodiment can have various changes and modifications. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of this embodiment shall be included within the protection scope of this embodiment.

Claims

1. An abnormal monitoring method for a photovoltaic-storage-charging microgrid system, characterized in that, Including: Obtain the power generation of the photovoltaic panel, the environmental haze value, the environmental wind speed, the environmental temperature, and the environmental humidity; Perform primary data correction on the power generation of the photovoltaic panel according to the haze level; Obtain the haze value affected by the wind speed through the environmental wind speed, and perform secondary data correction on the power generation of the photovoltaic panel according to the haze value affected by the wind speed; If the wind speed is lower than the preset value, obtain the haze value affected by the humidity through the environmental humidity, perform tertiary data correction on the power generation of the photovoltaic panel according to the haze value affected by the humidity, and obtain the haze value affected by the temperature through the environmental temperature, perform quaternary data correction on the power generation of the photovoltaic panel according to the haze value affected by the temperature, and use the power generation of the photovoltaic panel after quaternary data correction to perform anomaly judgment; otherwise, use the power generation of the photovoltaic panel after secondary data correction to perform anomaly judgment.

2. The abnormal monitoring method for a photovoltaic-storage-charging microgrid system according to claim 1, wherein When performing primary data correction on the power generation of the photovoltaic panel: ； ； Among them, is the power generation of the photovoltaic panel affected by haze; is the maximum power generation of the photovoltaic panel affected by haze; is the environmental haze; is the maximum environmental haze; is the power generation of the photovoltaic panel; is the power generation of the photovoltaic panel after the first correction.

3. The abnormal monitoring method for a photovoltaic-storage-charging microgrid system according to claim 2, wherein When performing secondary data correction on the power generation of the photovoltaic panel: ； ； ； Among them, is the environmental haze value affected by wind speed; is the environmental haze value after being affected by wind speed; is the environmental wind speed; is the maximum environmental wind speed; is the power generation of the photovoltaic panel after secondary correction.

4. The abnormal monitoring method for a photovoltaic-storage-charging microgrid system according to claim 3, characterized in that, When performing tertiary data correction on the power generation of the photovoltaic panel: ； ； ， ； Among them, is the power generation of the photovoltaic panel after three corrections, is the environmental haze value affected by humidity, is the environmental haze value affected by humidity, is the environmental humidity, is the maximum environmental humidity, is the lowest wind speed.

5. The abnormal monitoring method for a photovoltaic-storage-charging microgrid system according to claim 4, characterized in that, When performing quaternary data correction on the power generation of the photovoltaic panel: ； ； ， ； Among them, is the power generation of the photovoltaic panel after four corrections, is the environmental haze value affected by temperature, is the environmental haze value affected by temperature, is the environmental temperature, is the maximum environmental temperature.

6. The abnormal monitoring method for a photovoltaic-storage-charging microgrid system according to claim 1, wherein, If the power generation of the photovoltaic panel after correction exceeds the preset limit value, no alarm is issued; otherwise, an alarm is issued.

7. An abnormal monitoring system for a photovoltaic-storage-charging microgrid system, characterized in that, Including: A data acquisition module, configured to: obtain the power generation of the photovoltaic panel, the environmental haze value, the environmental wind speed, the environmental temperature, and the environmental humidity; A primary data correction module, configured to: perform primary data correction on the power generation of the photovoltaic panel according to the haze level; A secondary data correction module, configured to: perform primary data correction on the power generation of the photovoltaic panel according to the haze level; obtain the haze value affected by the wind speed through the environmental wind speed, and perform secondary data correction on the power generation of the photovoltaic panel according to the haze value affected by the wind speed; An anomaly judgment module, configured to: if the wind speed is lower than the preset value, obtain the haze value affected by the humidity through the environmental humidity, perform tertiary data correction on the power generation of the photovoltaic panel according to the haze value affected by the humidity, and obtain the haze value affected by the temperature through the environmental temperature, perform quaternary data correction on the power generation of the photovoltaic panel according to the haze value affected by the temperature, and use the power generation of the photovoltaic panel after quaternary data correction to perform anomaly judgment; otherwise, use the power generation of the photovoltaic panel after secondary data correction to perform anomaly judgment.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, the steps of the anomaly monitoring method for the photovoltaic-storage-charging microgrid system described in any one of claims 1-6 are implemented.

9. An electronic device, comprising a memory, a processor, and a computer program stored on the memory and capable of running on the processor, characterized in that, When the processor executes the program, the steps of the anomaly monitoring method for the photovoltaic-storage-charging microgrid system described in any one of claims 1-6 are implemented.

10. A computer program product, characterized in that, The computer program product includes a computer program, and when the computer program is executed by the processor, the steps of the anomaly monitoring method for the photovoltaic-storage-charging microgrid system described in any one of claims 1-6 are implemented.

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