New energy equipment quality monitoring system based on cloud computing

Abstract

The invention discloses a new energy equipment quality monitoring system based on cloud computing, relates to the technical field of new energy equipment monitoring, and provides powerful data support for subsequent monitoring of target new energy equipment by classifying the new energy equipment and analyzing data of the new energy equipment in each historical period. The target new energy equipment is monitored in the current period, and meanwhile, the operation condition of the next period is predicted, so that power system faults and economic losses caused by equipment faults are avoided in time, and resource waste caused by excessive maintenance is also avoided; a targeted maintenance scheme is formulated according to monitoring and prediction results of the target new energy equipment, the equipment maintenance efficiency is greatly improved, whether the maintenance scheme is effective or not is analyzed after maintenance is finished, the completeness and comprehensiveness of the system are ensured, and finally all data are uploaded to a cloud database, so that the maintenance efficiency is improved. And a data basis is provided for the development of the new energy power generation industry.

Description

Technical Field

[0001] The present application relates to the technical field of new energy equipment monitoring, and in particular to a new energy equipment quality monitoring system based on cloud computing. Background Art

[0002] How to monitor the quality of new energy equipment has become a problem that needs to be solved. Therefore, this application proposes a new energy equipment quality monitoring system based on cloud computing.

[0003] Prior art, such as the invention application patent with announcement number: CN117312294A, discloses a new energy equipment quality monitoring system based on cloud computing. A preprocessing module is provided to preprocess the data acquired by the data acquisition module to obtain preprocessed data. Conventional data is eliminated and only the required data is retained, thereby reducing the cardinality of data analysis samples, laying a foundation for improving the data analysis speed of the subsequent data analysis module. At the same time, a quality monitoring module is provided. When the result analyzed by the data analysis module is that the ambient temperature or operating temperature of the new energy equipment is abnormal, the data acquisition frequency and acquisition period of the data acquisition module are automatically adjusted, so as to better monitor the working condition of the new energy equipment. In this way, the acquisition frequency of the data acquisition module is dynamically adjusted, thereby reducing the energy consumed by the data acquisition module and extending the service life of the data acquisition module.

[0004] Regarding the above scheme, there are the following technical problems: 1. The current technology mainly pre-processes the collected data, eliminates routine data, and retains only the required data. Although the speed of subsequent analysis is guaranteed, the lack of data will lead to a decrease in the accuracy of the analysis results, which in turn leads to the lack of accuracy and completeness of the current technology.

[0005] 2. The current technology mainly monitors the ambient temperature and operating temperature of new energy equipment to monitor the quality of new energy. The monitoring data is relatively simple and there is no direct monitoring of the power generation of new energy equipment, which may lead to inaccurate monitoring results. Summary of the invention

[0006] The purpose of this application is to provide a new energy equipment quality monitoring system based on cloud computing, which solves the problems existing in the background technology.

[0007] To solve the above technical problems, the present application adopts the following technical solution: The present application provides a new energy equipment quality monitoring system based on cloud computing, including a historical data analysis module: used to analyze the working data of each new energy equipment and store it in a cloud database.

[0008] Target equipment monitoring module: used to analyze the comprehensive operation quality of the target new energy equipment in the current cycle, and then predict the comprehensive operation quality of the target new energy equipment in the next cycle.

[0009] Target equipment maintenance module: used to formulate a maintenance plan for the target new energy equipment based on the analysis results of the target equipment monitoring module, and then analyze whether the maintenance plan is effective and feed it back to the cloud database.

[0010] Cloud database: used to store data from the historical data analysis module, target device monitoring module, and target device maintenance module.

[0011] Preferably, the historical data analysis module includes: a historical power generation data analysis unit: used to obtain the environmental information and equipment information of each new energy device in each historical period, and then classify each new energy device to obtain each type of new energy equipment, and then analyze and obtain the first power generation threshold value and the second power generation threshold value of each type of new energy equipment, and store them in the cloud database.

[0012] Historical operation data analysis unit: used to obtain the comprehensive operation quality evaluation coefficients of various types of new energy equipment in various historical periods based on the operation data analysis of various types of new energy equipment, and store them in the cloud database.

[0013] Preferably, the new energy devices are classified to obtain various types of new energy devices, and the specific process is as follows: based on the environmental information of each new energy device, each environmental feature word of each new energy device is extracted to obtain an environmental feature set of each new energy device.

[0014] The device feature words of the new energy devices are extracted based on the device information of each new energy device to obtain a device feature set of each new energy device.

[0015] Based on the environmental characteristic word library stored in the cloud database, the synonyms of the environmental characteristic words of each new energy device are obtained to obtain the environmental characteristic synonym set of each new energy device.

[0016] The environmental feature set of each new energy device is matched with the device feature set to obtain a feature description set of each new energy device.

[0017] The feature description sets of each new energy device are matched with each other, and the new energy devices with the same matching results are recorded as new energy devices of the same type. Based on this, the new energy devices are classified to obtain various types of new energy devices.

[0018] Preferably, the analysis obtains the first power generation thresholds and the second power generation thresholds of each type of new energy equipment. The specific process is as follows: the power generation of a certain type of new energy equipment in each historical period is obtained from the power dispatching center, the power generation of this type of new energy equipment in each historical period is normally distributed, and the middle value after the normal distribution is recorded as the middle value of the power generation of this type of new energy equipment, and a power generation data is obtained from the left and right sides of the middle value of the power generation of this type of new energy equipment, which are respectively recorded as the secondary power generation threshold and the first power generation threshold of this type of new energy equipment, thereby obtaining the secondary power generation thresholds and the first power generation thresholds of each type of new energy equipment.

[0019] Preferably, the comprehensive operation quality of the target new energy equipment in the current cycle is analyzed, and the specific process is as follows: based on the environmental information of the target new energy equipment in the current cycle, the environmental keywords of the target new energy equipment are extracted to obtain the environmental feature set of the target new energy equipment.

[0020] Based on the equipment information of the target new energy equipment in the current period, equipment keywords of the target new energy equipment are extracted to obtain an equipment feature set of the target new energy equipment.

[0021] The environmental feature set and device feature set of the target new energy equipment are combined to obtain the feature description set of the target new energy equipment, and the feature description set of the target new energy equipment is matched with the feature description sets of various types of new energy equipment stored in the cloud database. When the description keyword set of the target new energy equipment successfully matches the feature description set of a certain type of new energy equipment in the cloud database, this type of new energy equipment is recorded as the reference device of the target new energy equipment.

[0022] The comprehensive operation quality assessment coefficient of the target new energy equipment is obtained by analysis, and the comprehensive operation quality assessment coefficient of the target new energy equipment is compared with the comprehensive operation quality assessment coefficient threshold of the reference equipment. When the comprehensive operation quality assessment coefficient of the target new energy equipment is greater than or equal to the comprehensive operation quality assessment coefficient of the reference equipment, it indicates that the comprehensive operation quality of the target new energy equipment is normal, and it is recorded as a maintenance-free equipment; otherwise, it indicates that the comprehensive operation quality of the target new energy equipment is abnormal, and it is recorded as a maintenance-to-be-maintained equipment.

[0023] Preferably, the maintenance plan for the target new energy equipment is formulated according to the analysis result of the target equipment monitoring module, and the specific process is as follows: when the target new energy equipment is maintenance-free equipment, no maintenance is performed on it.

[0024] When the target new energy equipment is the equipment to be maintained, the environmental feature keywords and equipment feature keywords of the target new energy equipment are extracted based on the feature description set of the target new energy equipment, and the environment and equipment information of the target new energy equipment are obtained accordingly, and a targeted maintenance plan is formulated based on the environment and equipment information of the target new energy equipment.

[0025] The beneficial effects of the present application are: 1. A new energy equipment quality monitoring system based on cloud computing provided by the present application provides strong data support for the monitoring of subsequent target new energy equipment by classifying each new energy equipment and analyzing the data of each historical period. It also monitors the target new energy equipment in the current period and predicts its operation in the next period, thereby timely avoiding power system failures and economic losses caused by equipment failures, and also avoiding waste of resources caused by excessive maintenance. Targeted maintenance plans are formulated based on the monitoring and prediction results of the target new energy equipment, which greatly improves the efficiency of equipment maintenance. After the maintenance, the effectiveness of the maintenance plan is analyzed to ensure the completeness and comprehensiveness of the system. Finally, all data are uploaded to the cloud database, providing a data basis for the development of the new energy power generation industry.

[0026] 2. This application obtains the environmental information and equipment information, power generation data and operation data of each new energy equipment from the power dispatching center, and obtains the environmental information and equipment information, power generation data and operation data of the target new energy equipment, thereby providing a data basis for the subsequent comprehensive operation quality analysis of the target new energy equipment.

[0027] 3. This application analyzes the environmental information and equipment information of each new energy device in each historical period, and then classifies each new energy device, and classifies and summarizes the data of different types of new energy equipment. On the one hand, it ensures the comprehensiveness of the data stored in the cloud database, and provides strong data support for the comprehensive operation quality monitoring of subsequent target new energy equipment. On the other hand, it ensures the orderliness of the data and improves the speed of subsequent data comparison, thereby greatly improving the work efficiency of the new energy equipment monitoring system.

[0028] 4. This application monitors the comprehensive operating quality of the target new energy equipment in the current cycle and predicts the comprehensive operating quality in the next cycle, thereby effectively ensuring the working status of the target new energy equipment and ensuring that the target new energy equipment can be discovered and maintained in time when a failure occurs, thereby avoiding power system failures and economic losses caused by equipment failures, and avoiding waste of resources caused by excessive maintenance, greatly improving the service life and work efficiency of the target new energy equipment, and ensuring the continuity of power supply to the power system.

[0029] 5. This application ensures the accuracy of maintenance of target new energy equipment by formulating maintenance plans based on the monitoring and prediction results of the comprehensive operating quality of target new energy equipment, avoiding the waste of resources and inefficiency caused by blind maintenance. At the same time, after the maintenance, the comprehensive operating quality of the target new energy equipment is continuously monitored to determine whether the maintenance plan is effective, which greatly ensures the completeness and comprehensiveness of the monitoring system and is also beneficial to the long-term development of the new energy power generation industry. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0031] Figure 1 This is a schematic diagram of the system structure connection for this application. DETAILED DESCRIPTION

[0032] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0033] Reference Figure 1 As shown, the present application provides a new energy equipment quality monitoring system based on cloud computing, including the following modules: a historical data analysis module: used to analyze the working data of each new energy equipment and store it in a cloud database.

[0034] It should be noted that the working data includes power generation data and operation data, among which the power generation data includes power generation, voltage and current, etc.; the operation data includes characteristic data and values ​​corresponding to the characteristic data, among which the characteristic data includes wind speed, light intensity and other parameters that can reflect the power generation quality of new energy equipment. If the new energy equipment is solar power generation equipment, the characteristic data is light intensity; if the new energy equipment is wind power generation equipment, the characteristic data is wind speed.

[0035] In a specific example, the historical data analysis module includes: a historical power generation data analysis unit: used to obtain the environmental information and equipment information of each new energy device in each historical period, and then classify each new energy device to obtain each type of new energy equipment, and then analyze and obtain the first power generation threshold value and the second power generation threshold value of each type of new energy equipment, and store them in the cloud database.

[0036] Historical operation data analysis unit: used to obtain the comprehensive operation quality evaluation coefficients of various types of new energy equipment in various historical periods based on the operation data analysis of various types of new energy equipment, and store them in the cloud database.

[0037] It should be noted that the cycle duration is set by the relevant staff, such as 6 hours, one day, one month or three months, and there is no specific restriction here.

[0038] It should be noted that environmental information includes environment type, such as mountainous area, desert, coastal area, etc.; equipment information includes manufacturer, equipment model and equipment working parameters, etc.

[0039] In a specific example, the new energy devices are classified to obtain various types of new energy devices. The specific process is as follows: based on the environmental information of each new energy device, each environmental feature word of each new energy device is extracted to obtain an environmental feature set of each new energy device.

[0040] The device feature words of the new energy devices are extracted based on the device information of each new energy device to obtain a device feature set of each new energy device.

[0041] Based on the environmental characteristic word library stored in the cloud database, the synonyms of the environmental characteristic words of each new energy device are obtained to obtain the environmental characteristic synonym set of each new energy device.

[0042] The environmental feature set of each new energy device is matched with the device feature set to obtain a feature description set of each new energy device.

[0043] The feature description sets of each new energy device are matched with each other, and the new energy devices with the same matching results are recorded as new energy devices of the same type. Based on this, the new energy devices are classified to obtain various types of new energy devices.

[0044] It should be noted that the consistent matching results indicate that the device feature keywords in the feature description set are consistent and the environment feature keywords are consistent or are synonyms of each other.

[0045] In a specific example, the analysis obtains the first power generation thresholds and the second power generation thresholds of each type of new energy equipment. The specific process is as follows: the power generation of a certain type of new energy equipment in each historical period is obtained from the power dispatching center, the power generation of this type of new energy equipment in each historical period is normally distributed, and the middle value after the normal distribution is recorded as the middle value of the power generation of this type of new energy equipment, and a power generation data is obtained from the left and right sides of the middle value of the power generation of this type of new energy equipment, which are respectively recorded as the secondary power generation threshold and the first power generation threshold of this type of new energy equipment, thereby obtaining the secondary power generation thresholds and the first power generation thresholds of each type of new energy equipment.

[0046] It should be noted that in order to improve the working quality of new energy equipment, the middle value of power generation can be set as the secondary power generation threshold, and the peak value of power generation can be set as the primary power generation threshold, without specific restrictions here.

[0047] In a specific example, the comprehensive operation quality evaluation coefficients of various types of new energy equipment in various historical periods are obtained based on the operation data analysis of various types of new energy equipment. The specific analysis process is as follows: the theoretical power generation and actual power generation of a certain type of new energy equipment in a certain historical period are obtained from the power dispatching center, and the average value is taken after subtracting the actual power generation from the theoretical power generation. The average value is recorded as the power generation loss value of this type of new energy equipment, and the power generation loss value of each type of new energy equipment in each historical period is obtained based on this. ,in Indicates the serial number of various new energy equipment. , is any integer greater than 2, Indicates the number of each historical period, , is any integer greater than 2.

[0048] Based on the operation data of various new energy equipment, the characteristic data peak value and characteristic data valley value of each historical period are extracted and recorded as and , according to the calculation formula: The power generation stability evaluation coefficients of various types of new energy equipment in each historical period are obtained through analysis. ,in Represented as the setting The threshold value of the characteristic data value per unit time of this type of new energy equipment.

[0049] It should be noted that the threshold value of the unit time characteristic data value is set by the staff themselves. The higher the threshold value of the unit time characteristic data value, the higher the quality requirements for the monitored new energy equipment. For example, the unit time characteristic data values ​​of each historical period of each type of equipment can be normally distributed, and the middle value after the normal distribution can be taken as the threshold value of the unit time characteristic data value of each type of equipment.

[0050] It should be noted that Based on the power generation data of various new energy equipment, the power generation of each historical period of each new energy equipment is extracted and recorded as , and integrate the threshold values ​​of each level of power generation of new energy data and each secondary power generation threshold , according to the calculation formula: The power generation quality assessment coefficients of various types of new energy equipment in each historical period are obtained through analysis .

[0051] Comprehensively consider the power generation stability assessment coefficient, power generation quality assessment coefficient and power generation loss value of various new energy equipment, according to the calculation formula: The comprehensive operation quality evaluation coefficients of various new energy equipment are obtained through analysis. ,in is the standard value of power generation loss per unit time, For the Category 1 New Energy Equipment The length of a historical cycle.

[0052] It should be noted that the standard value of power generation loss per unit time is set by relevant staff. For example, in order to ensure the power generation quality of new energy equipment, the standard value of power generation loss per unit time can be set to 0. No specific restrictions are made here.

[0053] Target equipment monitoring module: used to analyze the comprehensive operation quality of the target new energy equipment in the current cycle, and then predict the comprehensive operation quality of the target new energy equipment in the next cycle.

[0054] In a specific example, the comprehensive operating quality of the target new energy equipment in the current cycle is analyzed and whether the target new energy equipment needs maintenance is determined. The specific process is as follows: based on the environmental information of the target new energy equipment in the current cycle, the environmental keywords of the target new energy equipment are extracted to obtain the environmental feature set of the target new energy equipment.

[0055] Based on the equipment information of the target new energy equipment in the current period, equipment keywords of the target new energy equipment are extracted to obtain an equipment feature set of the target new energy equipment.

[0056] The environmental feature set and device feature set of the target new energy equipment are combined to obtain the feature description set of the target new energy equipment, and the feature description set of the target new energy equipment is matched with the feature description sets of various types of new energy equipment stored in the cloud database. When the description keyword set of the target new energy equipment successfully matches the feature description set of a certain type of new energy equipment in the cloud database, this type of new energy equipment is recorded as the reference device of the target new energy equipment.

[0057] It should be noted that the match is successful when the environmental keywords of the target new energy equipment are consistent with the environmental keywords of a certain type of new energy equipment or are synonyms of each other and the equipment keywords are consistent.

[0058] The comprehensive operation quality assessment coefficient of the target new energy equipment is obtained by analysis, and the comprehensive operation quality assessment coefficient of the target new energy equipment is compared with the comprehensive operation quality assessment coefficient threshold of the reference equipment. When the comprehensive operation quality assessment coefficient of the target new energy equipment is greater than or equal to the comprehensive operation quality assessment coefficient of the reference equipment, it indicates that the comprehensive operation quality of the target new energy equipment is normal, and it is recorded as a maintenance-free equipment; otherwise, it indicates that the comprehensive operation quality of the target new energy equipment is abnormal, and it is recorded as a maintenance-to-be-maintained equipment.

[0059] It should be noted that the analysis method of the comprehensive operation quality assessment coefficient of the target new energy equipment is the same as the analysis method of the comprehensive operation quality assessment coefficient of each type of new energy equipment in each historical period, so it will not be repeated here.

[0060] It should be noted that the threshold of the comprehensive operation quality assessment coefficient of the reference equipment is set by the relevant staff. The higher the threshold of the comprehensive operation quality assessment coefficient of the reference equipment, the higher the requirements for the operating status of the monitored target new energy equipment. For example, the comprehensive power generation assessment coefficients of each historical period of the reference equipment can be normally distributed, and the middle value after the normal distribution can be recorded as the threshold of the comprehensive operation quality assessment coefficient of the reference equipment.

[0061] In a specific example, the comprehensive operation quality of the target new energy equipment in the next cycle is predicted, and the specific process is as follows: A1. Obtaining the comprehensive operation quality evaluation coefficients of each cycle of the target new energy equipment , and fit it into the comprehensive operation quality change curve of the target new energy equipment, and obtain the endpoint coordinates of the comprehensive operation quality change curve of the target new energy equipment And calculate the slope ,in is the abscissa of the endpoint of the comprehensive operation quality change curve of the target new energy equipment, It is the ordinate of the endpoint of the comprehensive operation quality evaluation change curve of the target new energy equipment.

[0062] A2. Endpoint coordinates of the comprehensive operation quality change curve based on the target new energy equipment and slope , according to the calculation formula: Predict the comprehensive operation quality evaluation coefficient of the next cycle target new energy equipment .

[0063] A3. The comprehensive operation quality evaluation coefficient of the predicted target new energy equipment Compare with the comprehensive operation quality evaluation coefficient of the target new energy equipment in the previous cycle ,like , it indicates that the comprehensive operation quality of the target new energy equipment is good, and the target new energy equipment is recorded as equipment that does not require maintenance. Otherwise, it indicates that the comprehensive operation quality of the target new energy equipment is gradually declining, and the target new energy equipment is recorded as equipment to be maintained.

[0064] Target equipment maintenance module: used to formulate a maintenance plan for the target new energy equipment based on the analysis results of the target equipment monitoring module, and then analyze whether the maintenance plan is effective and feed it back to the cloud database.

[0065] In a specific example, the maintenance plan for the target new energy equipment is formulated according to the analysis result of the target equipment monitoring module. The specific process is as follows: when the target new energy equipment is a maintenance-free equipment, no maintenance is performed on it.

[0066] When the target new energy equipment is the equipment to be maintained, the environmental feature keywords and equipment feature keywords of the target new energy equipment are extracted based on the feature description set of the target new energy equipment, and the environment and equipment information of the target new energy equipment are obtained accordingly, and a targeted maintenance plan is formulated based on the environment and equipment information of the target new energy equipment.

[0067] It should be noted that a targeted maintenance plan is formulated based on the environment and equipment information of the target new energy equipment. For example, when the target new energy equipment is a solar power generation equipment in a desert area, it is necessary to use a high-pressure water gun or a cleaning agent to clean the surface of the target new energy equipment to maintain light transmittance; when the target new energy equipment is a wind power generation equipment in a coastal area, it is necessary to clean the marine organisms and salt particles attached to the surface of the equipment, and replace the corroded parts of the equipment.

[0068] In a specific example, the analysis of whether the maintenance plan is effective is as follows: at the end of the next cycle after the target new energy equipment is maintained, the comprehensive operation quality evaluation coefficient of the target new energy equipment in the cycle is analyzed, and the comprehensive operation quality evaluation coefficient of the target new energy equipment in the cycle is compared with the comprehensive operation quality evaluation coefficient of the adjacent previous cycle. When the ratio of the comprehensive operation quality evaluation coefficient of the target new energy equipment in the cycle to the comprehensive operation quality evaluation coefficient of the adjacent previous cycle is in the interval If the maintenance plan is valid, it indicates that the maintenance plan is effective; otherwise, it indicates that the maintenance plan is invalid.

[0069] In a specific example, the feedback to the cloud database includes the maintenance status, maintenance plan and maintenance effect of the target new energy equipment, wherein the maintenance status is maintenance-free and maintenance-pending.

[0070] Cloud database: used to store data from the historical data analysis module, target device monitoring module, and target device maintenance module.

[0071] The present application provides a cloud computing-based new energy equipment quality monitoring system, which provides strong data support for the subsequent monitoring of target new energy equipment by classifying each new energy equipment and analyzing the data of its historical cycles. It also monitors the target new energy equipment in the current cycle and predicts its operation in the next cycle, thereby timely avoiding power system failures and economic losses caused by equipment failures, and also avoiding waste of resources caused by excessive maintenance. Targeted maintenance plans are formulated based on the monitoring and prediction results of the target new energy equipment, which greatly improves the efficiency of equipment maintenance. After the maintenance is completed, the effectiveness of the maintenance plan is analyzed to ensure the completeness and comprehensiveness of the system. Finally, all data are uploaded to the cloud database, providing a data basis for the development of the new energy power generation industry.

[0072] The above contents are merely examples and explanations of the concept of the present application. The technicians in this technical field may make various modifications or additions to the described specific embodiments or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined in the present application, they should all fall within the protection scope of the present application.

Claims

1. A new energy equipment quality monitoring system based on cloud computing, characterized in that: include: Historical data analysis module: used to analyze the working data of each new energy equipment and store it in the cloud database; Target equipment monitoring module: used to analyze the comprehensive operation quality of the target new energy equipment in the current cycle, and then predict the comprehensive operation quality of the target new energy equipment in the next cycle; Target equipment maintenance module: used to formulate a maintenance plan for the target new energy equipment based on the analysis results of the target equipment monitoring module, and then analyze whether the maintenance plan is effective and feed it back to the cloud database; Cloud database: used to store data from the historical data analysis module, target device monitoring module, and target device maintenance module.

2. According to the cloud computing-based new energy equipment quality monitoring system of claim 1, it is characterized in that: The historical data analysis module includes: Historical power generation data analysis unit: used to obtain environmental information and equipment information of each new energy device in each historical period, and then classify each new energy device to obtain various types of new energy devices, and then analyze and obtain each first power generation threshold and each second power generation threshold of each type of new energy device, and store them in the cloud database; Historical operation data analysis unit: used to obtain the comprehensive operation quality evaluation coefficients of various types of new energy equipment in various historical periods based on the operation data analysis of various types of new energy equipment, and store them in the cloud database.

3. A cloud computing-based new energy equipment quality monitoring system according to claim 2, characterized in that: The new energy equipment is classified to obtain various new energy equipment. The specific process is as follows: Extracting characteristic words of the environment in which each new energy device is located based on the environmental information of each new energy device, and obtaining an environmental characteristic set of each new energy device; Extracting device feature words of each new energy device based on device information of each new energy device to obtain a device feature set of each new energy device; Based on the environmental characteristic word library stored in the cloud database, each synonym of each environmental characteristic word of each new energy device is obtained to obtain a set of environmental characteristic synonyms of each new energy device; Matching the environmental feature set of each new energy device with the device feature set to obtain a feature description set of each new energy device; The feature description sets of each new energy device are matched with each other, and the new energy devices with the same matching results are recorded as new energy devices of the same type. Based on this, the new energy devices are classified to obtain various types of new energy devices.

4. The cloud computing-based new energy equipment quality monitoring system according to claim 3 is characterized in that: The analysis obtains the first power generation thresholds and the second power generation thresholds of various types of new energy equipment. The specific process is as follows: The power generation of a certain type of new energy equipment in each historical period is obtained from the power dispatching center, the power generation of this type of new energy equipment in each historical period is normally distributed, and the middle value after the normal distribution is recorded as the middle value of the power generation of this type of new energy equipment, and a power generation data is obtained from the left and right sides of the middle value of the power generation of this type of new energy equipment, which are respectively recorded as the secondary power generation threshold and the primary power generation threshold of this type of new energy equipment, and the secondary power generation thresholds and the primary power generation thresholds of each type of new energy equipment are obtained accordingly.

5. The cloud computing-based new energy equipment quality monitoring system according to claim 4 is characterized in that: The above-mentioned comprehensive operation quality evaluation coefficients of various types of new energy equipment in various historical periods are obtained based on the operation data analysis of various types of new energy equipment. The specific analysis process is as follows: Obtain the theoretical power generation and actual power generation of a certain type of new energy equipment in a certain historical period from the power dispatching center, subtract the actual power generation from the theoretical power generation and take the average value, record the average value as the power generation loss value of this type of new energy equipment, and obtain the power generation loss value of each type of new energy equipment in each historical period based on this. ,in Indicates the serial number of various new energy equipment. , is any integer greater than 2, Indicates the number of each historical period, , is any integer greater than 2; Based on the operation data of various new energy equipment, the characteristic data peak value and characteristic data valley value of each historical period are extracted and recorded as and , according to the calculation formula: The power generation stability evaluation coefficients of various types of new energy equipment in each historical period are obtained through analysis. ,in Represented as the setting Threshold value of characteristic data per unit time of new energy equipment; Based on the power generation data of various new energy equipment, the power generation of each historical period of each new energy equipment is extracted and recorded as , and integrate the threshold values ​​of each level of power generation of new energy data and each secondary power generation threshold , according to the calculation formula: The power generation quality assessment coefficients of various types of new energy equipment in each historical period are obtained through analysis ; Comprehensively consider the power generation stability assessment coefficient, power generation quality assessment coefficient and power generation loss value of various new energy equipment, according to the calculation formula: The comprehensive operation quality evaluation coefficients of various new energy equipment are obtained through analysis. ,in is the standard value of power generation loss per unit time, For the Category 1 New Energy Equipment The length of a historical cycle.

6. A cloud computing-based new energy equipment quality monitoring system according to claim 5, characterized in that: The specific process of analyzing the comprehensive operation quality of the target new energy equipment in the current cycle and determining whether the target new energy equipment needs maintenance is as follows: Extracting the environment keywords of the target new energy equipment based on the environment information of the current cycle of the target new energy equipment, and obtaining the environment feature set of the target new energy equipment; Extracting device keywords of target new energy equipment based on device information of target new energy equipment in the current cycle, and obtaining a device feature set of the target new energy equipment; The target new energy equipment's environmental feature set and equipment feature set are integrated to obtain a feature description set of the target new energy equipment, and the feature description set of the target new energy equipment is matched with the feature description sets of various types of new energy equipment stored in the cloud database. When the description keyword set of the target new energy equipment successfully matches the feature description set of a certain type of new energy equipment in the cloud database, the new energy equipment of this type is recorded as a reference device of the target new energy equipment; The comprehensive operation quality assessment coefficient of the target new energy equipment is obtained by analysis, and the comprehensive operation quality assessment coefficient of the target new energy equipment is compared with the comprehensive operation quality assessment coefficient threshold of the reference equipment. When the comprehensive operation quality assessment coefficient of the target new energy equipment is greater than or equal to the comprehensive operation quality assessment coefficient of the reference equipment, it indicates that the comprehensive operation quality of the target new energy equipment is normal, and it is recorded as a maintenance-free equipment; otherwise, it indicates that the comprehensive operation quality of the target new energy equipment is abnormal, and it is recorded as a maintenance-to-be-maintained equipment.

7. A cloud computing-based new energy equipment quality monitoring system according to claim 6, characterized in that: The specific process of predicting the comprehensive operation quality of the target new energy equipment in the next cycle is as follows: A1. Obtain the comprehensive operation quality evaluation coefficients of each cycle of the target new energy equipment , and fit it into the comprehensive operation quality change curve of the target new energy equipment, and obtain the endpoint coordinates of the comprehensive operation quality change curve of the target new energy equipment And calculate the slope ,in is the abscissa of the endpoint of the comprehensive operation quality change curve of the target new energy equipment, The ordinate of the endpoint of the comprehensive operation quality evaluation change curve of the target new energy equipment; A2. Endpoint coordinates of the comprehensive operation quality change curve based on the target new energy equipment and slope , according to the calculation formula: Predict the comprehensive operation quality evaluation coefficient of the next cycle target new energy equipment ; A3. The comprehensive operation quality evaluation coefficient of the predicted target new energy equipment Compare with the comprehensive operation quality evaluation coefficient of the target new energy equipment in the previous cycle ,like , it indicates that the comprehensive operation quality of the target new energy equipment is good, and the target new energy equipment is recorded as equipment that does not require maintenance. Otherwise, it indicates that the comprehensive operation quality of the target new energy equipment is gradually declining, and the target new energy equipment is recorded as equipment to be maintained.

8. The cloud computing-based new energy equipment quality monitoring system according to claim 7, characterized in that: The maintenance plan for the target new energy equipment is formulated according to the analysis results of the target equipment monitoring module. The specific process is as follows: When the target new energy equipment is maintenance-free equipment, no maintenance will be performed on it; When the target new energy equipment is the equipment to be maintained, the environmental feature keywords and equipment feature keywords of the target new energy equipment are extracted based on the feature description set of the target new energy equipment, and the environment and equipment information of the target new energy equipment are obtained accordingly, and a targeted maintenance plan is formulated based on the environment and equipment information of the target new energy equipment.

9. The cloud computing-based new energy equipment quality monitoring system according to claim 8, characterized in that: The analysis and maintenance plan is effective. The specific process is as follows: At the end of the next cycle after the target new energy equipment is maintained, the comprehensive operation quality assessment coefficient of the target new energy equipment in the cycle is analyzed and compared with the comprehensive operation quality assessment coefficient of the adjacent previous cycle. When the ratio of the comprehensive operation quality assessment coefficient of the target new energy equipment in the cycle to the comprehensive operation quality assessment coefficient of the adjacent previous cycle is within the interval If the maintenance plan is valid, it indicates that the maintenance plan is effective; otherwise, it indicates that the maintenance plan is invalid.

10. A cloud computing-based new energy equipment quality monitoring system according to claim 9, characterized in that: The feedback to the cloud database includes the maintenance status, maintenance plan and maintenance effect of the target new energy equipment, wherein the maintenance status is maintenance-free and maintenance-pending.

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