A photovoltaic array multi-dimensional data merging and collecting and state evaluation edge intelligent terminal

Abstract

The application provides a photovoltaic array multi-dimensional data merging acquisition and state evaluation edge intelligent terminal, which comprises a voltage / current acquisition unit, a solar radiation unit, a wind speed acquisition unit, an environmental temperature acquisition unit, a data merging unit, a state evaluation unit and a data transmission unit; the voltage / current acquisition unit is connected with a direct current convergence part of the photovoltaic array and is used for acquiring the voltage and the current of the direct current convergence part of the photovoltaic array; the voltage / current acquisition unit, the solar radiation unit, the wind speed acquisition unit, the environmental temperature acquisition unit and the data merging unit are connected and are used for merging the photovoltaic array high-dimensional data stream formed by the acquired voltage and current information, the current solar radiation intensity information, the current wind speed intensity information and the environmental temperature information, and transmitting the photovoltaic array high-dimensional data stream in two parallel ways.

Description

Technical Field

[0001] This invention belongs to the technical fields of photovoltaic systems and intelligent power equipment, and specifically relates to an edge intelligent terminal for multi-dimensional data merging, acquisition and status assessment of photovoltaic arrays. Background Technology

[0002] Traditional photovoltaic (PV) systems consist of a set of photovoltaic panels, an inverter, and additional equipment. The photovoltaic panels convert solar radiation into direct current (DC), which is then converted back to alternating current (AC) by the inverter for use by equipment or the power grid. However, this type of PV system has several challenges. First, PV efficiency is affected by many factors, such as light intensity, temperature, panel orientation, and angle. Second, data acquisition, processing, and system optimization become extremely complex when the system scales up or the environment becomes complex and non-standardized. Due to the complexity of PV arrays and their large-scale applications, effectively collecting and processing diverse, multi-dimensional data, and providing in-depth and detailed condition assessments, are key issues in the current PV field.

[0003] Current technologies primarily process data through central cluster nodes. However, this approach cannot handle large and complex datasets in real time, and data transmission delays and loss can negatively impact the accuracy of the final assessment. Furthermore, as photovoltaic arrays expand in scale and data dimensions increase, traditional data acquisition and processing methods are becoming increasingly inadequate. Summary of the Invention

[0004] To address the shortcomings and deficiencies of existing technologies, this invention proposes an edge intelligent terminal for multi-dimensional data merging, acquisition, and status assessment of photovoltaic arrays. This solution can comprehensively collect and process multi-dimensional data from photovoltaic arrays and perform real-time status assessments, overcoming many limitations of traditional methods. This is also a significant improvement to photovoltaic array technology, effectively promoting further technological development in the photovoltaic field. Its main structure comprises a photovoltaic array 1, a voltage / current acquisition unit 2, a solar irradiance unit 3, a wind speed acquisition unit 4, an ambient temperature acquisition unit 5, a data merging unit 6, a status assessment unit 7, and a data transmission unit 8. The voltage / current acquisition unit 2 is connected to the DC busbar of the photovoltaic array; the voltage / current acquisition unit 2, solar irradiance unit 3, wind speed acquisition unit 4, and ambient temperature acquisition unit 5 are connected to the data merging unit 6; the data merging unit is connected to the status assessment unit 7; and the status assessment unit 7 is connected to the data transmission unit 8. Correspondingly, a photovoltaic multi-dimensional data merging and acquisition and status assessment process based on edge intelligence is announced. First, the multi-dimensional data stream of the photovoltaic array is merged and acquired by the data merging unit and transmitted in two parallel paths. One path generates a detection message through downsampling compression, and the other path forms a feature vector through graph embedding. The generated feature vector enters the status assessment unit to complete abnormal time sequence diagnosis, fault classification and location, and generate status messages. The detection message generated by the merging acquisition unit and the status message generated by the status assessment unit are merged and sent through the data transmission unit.

[0005] The specific technical solution adopted by this invention to solve its technical problem is as follows:

[0006] A photovoltaic array multi-dimensional data merging, acquisition, and status assessment edge intelligent terminal includes: a voltage / current acquisition unit, a solar irradiance unit, a wind speed acquisition unit, an ambient temperature acquisition unit, a data merging unit, a status assessment unit, and a data transmission unit. The voltage / current acquisition unit is connected to the DC busbar of the photovoltaic array and is used to acquire the voltage and current of the DC busbar. The voltage / current acquisition unit, solar irradiance unit, wind speed acquisition unit, and ambient temperature acquisition unit are connected to the data merging unit to merge the high-dimensional data stream of the photovoltaic array formed by the acquired voltage and current information, current solar irradiance intensity information, current wind speed intensity information, and ambient temperature information, and transmit it in parallel via two paths: one path generates a detection message through downsampling compression, and the other path forms a feature vector through graph embedding. The data merging unit is connected to the status assessment unit and is used to input the generated feature vector into the status assessment unit to complete abnormal timing diagnosis for fault classification and location, and generate a status message. The status assessment unit is connected to the data transmission unit and is used to merge the detection message generated by the acquisition unit and the status message generated by the status assessment unit and send them together via the data transmission unit.

[0007] Furthermore, in the first transmission, the data merging unit downsamples the multi-dimensional data stream, and the downsampled data is further compressed by a compression algorithm to generate a detection message. The detection message contains detection information on anomalies, errors, or faults in the photovoltaic array. In the second transmission, the data merging unit converts the multi-dimensional data stream into a graph embedding feature vector. The graph embedding algorithm is used to convert the multi-dimensional data into a high-dimensional feature vector to capture key features and patterns in the data.

[0008] Furthermore, in the status assessment unit, the feature vector first undergoes abnormal timing diagnosis processing. Based on the results of the abnormal timing diagnosis, fault classification and location are performed to identify the specific fault type occurring in the photovoltaic array and locate the location of the fault. Finally, a corresponding status message is generated based on the diagnosis and location results.

[0009] Furthermore, a method for multi-dimensional data merging, acquisition, and status assessment of photovoltaic arrays:

[0010] The multi-dimensional data streams of the photovoltaic array are merged and collected and transmitted in two parallel paths. One path generates detection messages through downsampling and compression, and the other path forms feature vectors through graph embedding.

[0011] The generated feature vectors are subjected to anomaly timing diagnosis to classify and locate faults and generate status messages.

[0012] The detection message and status message are then merged and sent through the data transmission unit.

[0013] Furthermore, in the first transmission, the multi-dimensional data stream is downsampled, and the downsampled data is further compressed by a compression algorithm to generate a detection message. The detection message contains detection information on anomalies, errors, or faults in the photovoltaic array. In the second transmission, the multi-dimensional data stream is converted into a graph embedding to form a feature vector. The graph embedding algorithm is used to convert the multi-dimensional data into a high-dimensional feature vector to capture key features and patterns in the data.

[0014] Furthermore, the feature vector first undergoes abnormal timing diagnosis processing. Based on the results of the abnormal timing diagnosis, fault classification and location are performed to identify the specific fault type occurring in the photovoltaic array and locate the location of the fault. Finally, a corresponding status message is generated based on the diagnosis and location results.

[0015] Compared to existing technologies, this invention and its preferred embodiment achieve comprehensive collection and processing of multi-dimensional data from photovoltaic arrays, enabling real-time status assessment and overcoming many limitations of traditional methods. This is also a significant improvement to photovoltaic array technology, effectively promoting further technological development in the photovoltaic field. Attached Figure Description

[0016] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments:

[0017] Figure 1 This is a flowchart of the photovoltaic array multi-dimensional data merging and acquisition and status assessment method according to an embodiment of the present invention;

[0018] Figure 2 This is a schematic diagram of an edge intelligent terminal device for multi-dimensional data merging, acquisition, and status assessment of photovoltaic arrays according to an embodiment of the present invention;

[0019] Figure 3 This is a schematic diagram of the signal reception of the wind speed acquisition unit in an embodiment of the present invention;

[0020] Figure 4 This is a schematic diagram of the temperature acquisition unit receiving data according to an embodiment of the present invention;

[0021] Figure 5 This is a schematic diagram of the solar radiation acquisition unit receiving data according to an embodiment of the present invention;

[0022] Figure 6 This is a schematic diagram of data collection by the current and voltage acquisition unit in an embodiment of the present invention;

[0023] Figure 7 This is a structural diagram of the photovoltaic data merging and evaluation unit in an embodiment of the present invention. Detailed Implementation

[0024] To make the features and advantages of the present invention more apparent and understandable, specific embodiments are described below in detail:

[0025] It should be noted that the following detailed descriptions are illustrative and intended to provide further explanation of this application. Unless otherwise specified, all technical and scientific terms used in this specification have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains.

[0026] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the exemplary embodiments according to this application. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Furthermore, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0027] This invention provides a design for an edge intelligent terminal for multi-dimensional data merging, acquisition, and status assessment of photovoltaic arrays. Figure 2As shown, it mainly includes a photovoltaic array 1, a voltage / current acquisition unit 2, a solar irradiance unit 3, a wind speed acquisition unit 4, an ambient temperature acquisition unit 5, a data merging unit 6, a status assessment unit 7, and a data transmission unit 8. The system includes a voltage / current acquisition unit 2 connected to the DC busbar of the photovoltaic array, used to acquire the voltage and current of the DC busbar of the photovoltaic array; a voltage / current acquisition unit 2, a solar irradiance unit 3, a wind speed acquisition unit 4, and an ambient temperature acquisition unit 5 connected to a data merging unit 6, used to merge and acquire the high-dimensional data stream of the photovoltaic array formed by the voltage and current acquired from the DC busbar of the photovoltaic array, the current solar irradiance intensity information, the current wind speed intensity information, and the ambient temperature information, and transmit it in two parallel paths, one path generating a detection message through downsampling compression, and the other path generating a feature vector through graph embedding; a data merging unit 6 connected to a status assessment unit 7, used to input the generated feature vector into the status assessment unit to complete abnormal timing diagnosis, fault classification and location, and generate a status message; a status assessment unit 7 connected to a data transmission unit 8, used to merge the detection message generated by the acquisition unit and the status message generated by the status assessment unit and send them through the data transmission unit.

[0028] During operation, the multi-dimensional data streams from the photovoltaic array are first collected and merged by a data merging unit, and then transmitted in two parallel paths. One path generates detection messages through downsampling and compression, while the other path forms feature vectors through graph embedding. Specifically, data from various dimensions of the photovoltaic array, including voltage / current information of the photovoltaic busbar, solar irradiance, ambient wind speed, and temperature information, are collected and transmitted to a data merging unit. The solar irradiance, wind speed, and temperature information are as follows: Figure 3 , Figure 4 , Figure 5 As shown, the current and voltage information is as follows: Figure 6 As shown, the data merging unit integrates and merges the collected data. In the first transmission, the data merging unit downsamples the multi-dimensional data stream, and then the downsampled data undergoes further compression using a compression algorithm to generate a smaller detection message. This message contains detection information about anomalies, errors, or faults in the photovoltaic array. In the second transmission, the data merging unit transforms the multi-dimensional data stream into a graph embedding feature vector. This process uses a graph embedding algorithm to convert the multi-dimensional data into a high-dimensional feature vector, capturing key features and patterns in the data to generate the feature vector.

[0029] In a preferred embodiment, a data merging unit is connected to a status assessment unit. This connection allows the generated feature vectors to be fed into the status assessment unit for anomaly timing diagnosis, fault classification, and location, ultimately generating a status message. Specifically, in the status assessment unit, the feature vectors first undergo anomaly timing diagnosis processing. Based on the results of the anomaly timing diagnosis, the status assessment unit performs fault classification and location, identifying the specific fault type occurring in the photovoltaic array and pinpointing the fault's location. Finally, the status assessment unit generates a corresponding status message based on the diagnosis and location results. The preferred structure of the data merging unit and the status assessment unit is as follows: Figure 7 As shown:

[0030] As a preferred design, the data merging unit can integrate a multi-channel photovoltaic data collection unit to perform at least data augmentation and data segmentation on downsampled status detection messages and various types of data directly acquired.

[0031] The state evaluation unit preferably normalizes the temporal and spatial features respectively, then passes them through a neural network with a multi-channel attention mechanism. After fusion, the network is processed by gate control to predict the importance of each channel, perform feature allocation and state output, and obtain the judgment result.

[0032] In a preferred embodiment, a state evaluation unit is connected to a data transmission unit to merge the detection messages generated by the acquisition unit and the state messages generated by the state evaluation unit before sending them together. Specifically, the data transmission unit merges the detection messages and the state messages, and the merged data is transmitted or stored through network transmission, message queues, databases, or other means.

[0033] Compared to the above edge intelligent terminal design, this embodiment of the invention also provides a flowchart of a method for multi-dimensional data merging, acquisition, and status assessment of photovoltaic arrays, as follows: Figure 1 As shown, it includes the following steps:

[0034] S01 first merges and acquires the multi-dimensional data streams from the photovoltaic array through a data merging unit and transmits them in two parallel paths. One path generates a detection message through downsampling and compression, while the other path forms a feature vector through graph embedding. Specifically, it collects data from various dimensions of the photovoltaic array, including voltage / current information of the photovoltaic busbar, solar irradiance, ambient wind speed, and temperature information, as follows: Figure 3 , Figure 4 , Figure 5 , Figure 6As shown, the collected data is transmitted to a data merging unit. The data merging unit integrates and merges the collected data. In the first transmission, the data merging unit downsamples the multi-dimensional data stream, and then the downsampled data undergoes further compression using a compression algorithm to generate a smaller detection message. This message contains detection information about anomalies, errors, or faults in the photovoltaic array. In the second transmission, the data merging unit transforms the multi-dimensional data stream into a graph embedding feature vector. This process uses a graph embedding algorithm to convert the multi-dimensional data into a high-dimensional feature vector, capturing key features and patterns in the data to generate the feature vector.

[0035] S02 is connected to the status assessment unit via the data merging unit. It is used to input the generated feature vectors into the status assessment unit to complete anomaly timing diagnosis, fault classification and location, and generate status messages. Specifically, in the status assessment unit, the feature vectors first undergo anomaly timing diagnosis processing. Based on the results of the anomaly timing diagnosis, the status assessment unit performs fault classification and location, identifying the specific fault type occurring in the photovoltaic array and locating the fault location. Finally, in the status assessment unit, the corresponding status message is generated based on the diagnosis and location results. The structure of the data merging and assessment unit is as follows: Figure 7 As shown;

[0036] S03 is connected to the data transmission unit via the status assessment unit, and is used to merge the detection messages generated by the acquisition unit and the status messages generated by the status assessment unit before sending them through the data transmission unit. Specifically, the data transmission unit merges the detection messages and status messages, and the merged data is transmitted or stored through network transmission, message queues, databases, or other means.

[0037] The above methods can be implemented using the edge intelligent terminal provided by this invention, or through other similar or equivalent designs.

[0038] It should be noted that, unless otherwise defined, the technical or scientific terms used in this invention should have the ordinary meaning understood by one of ordinary skill in the art to which this invention pertains. The terms "first," "second," and similar terms used in this invention do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Terms such as "comprising" or "including" mean that the element or object preceding the word encompasses the elements or objects listed following the word and their equivalents, without excluding other elements or objects. Terms such as "connected" or "linked" are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. Terms such as "upper," "lower," "left," and "right" are used only to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0039] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention in any other way. Any person skilled in the art may make changes or modifications to the above-disclosed technical content to create equivalent embodiments. However, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the protection scope of the present invention.

[0040] This invention is not limited to the preferred embodiment described above. Anyone inspired by this invention can derive other forms of a photovoltaic array multi-dimensional data merging and acquisition and status assessment edge intelligent terminal. All equivalent changes and modifications made within the scope of this invention should be included in the scope of this invention.

Claims

1. A photovoltaic array multi-dimensional data merging, acquisition, and status assessment edge intelligent terminal, characterized in that, include: The system comprises a voltage / current acquisition unit, a solar irradiance acquisition unit, a wind speed acquisition unit, an ambient temperature acquisition unit, a data merging unit, a status assessment unit, and a data transmission unit. The voltage / current acquisition unit is connected to the DC busbar of the photovoltaic array and is used to acquire the voltage and current of the DC busbar. The voltage / current acquisition unit, solar irradiance acquisition unit, wind speed acquisition unit, and ambient temperature acquisition unit are connected to the data merging unit to merge the high-dimensional data stream of the photovoltaic array formed by the acquired voltage and current information, current solar irradiance information, current wind speed information, and ambient temperature information. This data stream is then transmitted in two parallel paths: one path generates a detection message through downsampling compression, and the other path forms a feature vector through graph embedding. The data merging unit is connected to the status assessment unit and is used to input the generated feature vector into the status assessment unit to complete abnormal timing diagnosis, perform fault classification and location, and generate a status message. The status assessment unit is connected to the data transmission unit and is used to merge the detection message generated by the acquisition unit and the status message generated by the status assessment unit and send them together through the data transmission unit.

2. The edge intelligent terminal for multi-dimensional data merging, acquisition, and status assessment of photovoltaic arrays according to claim 1, characterized in that: In the first transmission, the data merging unit downsamples the multi-dimensional data stream. The downsampled data is then further compressed using a compression algorithm to generate a detection message. This detection message contains detection information about anomalies, errors, or faults in the photovoltaic array. In the second transmission, the data merging unit converts the multi-dimensional data stream into a graph embedding feature vector. The graph embedding algorithm is used to convert the multi-dimensional data into a high-dimensional feature vector to capture key features and patterns in the data.

3. The edge intelligent terminal for multi-dimensional data merging, acquisition, and status assessment of photovoltaic arrays according to claim 1, characterized in that: In the status assessment unit, the feature vector first undergoes abnormal timing diagnosis processing. Based on the results of the abnormal timing diagnosis, fault classification and location are performed to identify the specific fault type occurring in the photovoltaic array and locate the location of the fault. Finally, a corresponding status message is generated based on the diagnosis and location results.

4. A method for multi-dimensional data merging, acquisition, and status assessment of photovoltaic arrays, based on an edge intelligent terminal for multi-dimensional data merging, acquisition, and status assessment of photovoltaic arrays as described in claim 1, characterized in that: The multi-dimensional data streams of the photovoltaic array are merged and collected and transmitted in two parallel paths. One path generates detection messages through downsampling and compression, and the other path forms feature vectors through graph embedding. The generated feature vectors are subjected to anomaly timing diagnosis to classify and locate faults and generate status messages. The detection message and status message are then merged and sent through the data transmission unit.

5. The method for multi-dimensional data merging, acquisition, and status assessment of a photovoltaic array according to claim 4, characterized in that: In the first transmission, the multi-dimensional data stream is downsampled, and the downsampled data is further compressed by a compression algorithm to generate a detection message. The detection message contains detection information on anomalies, errors, or faults in the photovoltaic array. In the second transmission, the multi-dimensional data stream is converted into a graph embedding to form a feature vector. The graph embedding algorithm is used to convert the multi-dimensional data into a high-dimensional feature vector to capture key features and patterns in the data.

6. The method for multi-dimensional data merging, acquisition, and status assessment of a photovoltaic array according to claim 4, characterized in that: The feature vector first undergoes abnormal timing diagnosis processing. Based on the results of the abnormal timing diagnosis, fault classification and location are performed to identify the specific fault type occurring in the photovoltaic array and locate the fault location. Finally, a corresponding status message is generated based on the diagnosis and location results.

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