Data processing method of photovoltaic collector

Abstract

The invention provides a data processing method for a photovoltaic collector, and the method comprises the following steps: 1, collecting the operation data of an inverter through a photovoltaic collector, obtaining the collected data, packaging the collected data, and obtaining the packaged data; step 2, the photovoltaic collector sends the packaged data to a cloud platform; and step 3, the cloud platform analyzes the collected data, and performs data logic processing on the operation data obtained by analysis. According to the method, logic processing and data analysis are carried out on the cloud, so that the firmware upgrading frequency is greatly reduced, and the efficiency is improved.

Description

Technical Field

[0001] The present application relates to the field of photovoltaic power stations, and in particular to the field of photovoltaic collector data processing. Background Art

[0002] Inverter data is stored in the inverter's storage medium in the form of binary data at the inverter end. In order to display it on the cloud platform, the inverter device's external collector provides the inverter with the ability to upload data to the cloud. Traditional data processing logic is processed in the collector's local firmware. When the data processing logic is modified, the collector device firmware needs to be upgraded. At present, collectors are shipped in large quantities with inverter equipment. Large-scale upgrades of collector firmware are accompanied by certain risks and are inefficient.

[0003] In view of this, this application is proposed. Summary of the invention

[0004] The present application provides a data processing method for a photovoltaic collector, which effectively reduces the number of firmware upgrades.

[0005] The present application provides a data processing method for a photovoltaic collector, comprising the following steps:

[0006] Step 1: The photovoltaic collector collects the operating data of the inverter to obtain collected data, and encapsulates the collected data to obtain encapsulated data;

[0007] Step 2, the photovoltaic collector sends the packaging data to the cloud platform;

[0008] Step 3: The cloud platform analyzes the collected data and performs data logic processing on the operating data obtained through the analysis.

[0009] Furthermore, the photovoltaic collector in step 1 exchanges data with the inverter via the modbusRTU protocol;

[0010] The photovoltaic collector exchanges data with the cloud platform via the modbusRTU protocol.

[0011] Furthermore, in step 1, the photovoltaic collector only performs data collection and packaging, and does not perform data logic processing on the collected data.

[0012] Furthermore, packaging the collected data in step 1 includes: the photovoltaic collector packaging the collected data according to the modbusRTU protocol.

[0013] Furthermore, the cloud platform includes an access layer, a data parsing layer, a data cleaning layer, an application layer and a display layer which are connected in sequence.

[0014] Furthermore, the cloud platform in step 3 analyzes the packaged data including:

[0015] Step 3.1, the photovoltaic collector is connected to the cloud platform through the access layer, and the packaged data is sent to the data analysis layer;

[0016] Step 3.2, preliminarily parse the packaged data according to the standard modbusRTU protocol to obtain the slave address and register address;

[0017] Step 3.3, matching the slave address and the register address obtained in step 3.2 with the database to obtain a parsing rule, and further parsing according to the parsing rule to obtain parsed data;

[0018] Furthermore, in step 3.4, the data cleaning layer cleans the parsed data to obtain cleaned data.

[0019] Furthermore, in step 3.5, the application layer integrates and adjusts the cleansed data.

[0020] Furthermore, in step 3.6, the presentation layer presents the data integrated and adjusted by the application layer.

[0021] Compared with the prior art, the present invention has the following advantages:

[0022] The present invention places logic processing and data analysis in the cloud, so that when the data processing logic is modified and the data to be collected is increased, there is no need to upgrade the collector firmware. The data processing can be modified by directly publishing the cloud code or modifying the cloud configuration, which effectively reduces the number of firmware upgrades. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the embodiments of the present invention 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 invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0024] Figure 1 Schematic diagram of the working process of this embodiment. DETAILED DESCRIPTION

[0025] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0026] Figure 1 FIG. 2 shows a schematic diagram of the working process of this embodiment. Figure 1 As shown, this embodiment includes a cloud platform 10, multiple photovoltaic collectors 20, and multiple inverters 30, wherein a single inverter 30 corresponds to a single photovoltaic collector 20 one by one, and the photovoltaic collector 20 and the inverter 30, as well as the photovoltaic collector 20 and the cloud platform 10, all interact with data according to the standard modbusRTU protocol. For example, the inverter 30 provides corresponding data (such as operating data, etc.) to the photovoltaic collector 20 according to the requirements of the standard modbusRTU protocol, and the photovoltaic collector 20 encapsulates the data submitted by the inverter 30 according to the standard modbusRTU protocol, or the inverter 30 directly encapsulates the relevant data locally according to the standard modbusRTU protocol, and directly uploads the encapsulated data to the photovoltaic collector 20.

[0027] See again Figure 1 The cloud platform 10 includes a connection layer 101, a data parsing layer 102, a data cleaning layer 103, an application layer 104 and a presentation layer 105 which are connected in sequence.

[0028] The connection layer 101 is used to connect to the photovoltaic collector 20 to upload data of the photovoltaic collector 20 .

[0029] The data parsing layer 102 is used to parse the encapsulated data, obtain the slave address and the corresponding register address, and match the slave address and the register address in the database to obtain the parsing rules, and further parse according to the parsing rules to obtain the parsed data, wherein the database records the slave address and the register address, and the corresponding parsing rules. The above database can be modified at any time, such as adding or deleting the register address and the slave address, or modifying the parsing rules. The specific process can be:

[0030] (1) The parsing layer receives the inverter device binary data in the standard modbusRTU protocol.

[0031] (2) Parse the first byte slave address, the third and fourth bytes register start address (standard modbusRTU protocol)

[0032] (3) Match the parsed data with the parsing rule template. When the parsing rule template is matched, parse the received binary data according to the template.

[0033] Preferably, when the data analysis layer receives and identifies changes in the register data of the number of sub-devices (such as energy storage batteries) of the inverter, the data analysis layer will store the number of sub-devices in redis and compare the number of sub-devices in redis and automatically generate the configuration information of the sub-devices, store it in the database, and issue the collection sub-device instructions based on the generated sub-device configuration information.

[0034] Preferably, when the collector receives the instruction to collect the register range of the sub-device, it will read the register data of the sub-device range and then upload the data. This allows the sub-devices to be added or subtracted flexibly. The cloud platform can sense the increase or decrease of sub-devices and process the topological relationship between the inverter and the inverter sub-devices.

[0035] Preferably, the device data sent by the collector contains the sn of the parent device, and the data parsing layer will identify and assemble the sn of the parent device of the sent device, and finally generate topological relationship data according to the sn of the parent device.

[0036] The data cleaning layer 103 cleans the parsed data to extract abnormal data.

[0037] The application layer 104 integrates and adjusts the data cleansed by the data cleaning layer 103 .

[0038] The presentation layer 105 presents data based on the data integrated and adjusted by the application 104 .

[0039] On the other hand, this embodiment provides a data processing method based on the above device, comprising the following steps:

[0040] Step 1: The photovoltaic collector collects the operating data of the inverter to obtain collected data, and encapsulates the collected data to obtain encapsulated data;

[0041] Step 2: The photovoltaic collector sends the packaging data to the cloud platform;

[0042] Step 3: The cloud platform analyzes the collected data and performs data logic processing on the analyzed operating data.

[0043] Preferably, in step 1, the photovoltaic collector interacts with the inverter via the modbusRTU protocol; the photovoltaic collector interacts with the cloud platform via the modbusRTU protocol.

[0044] Preferably, in step 1, the photovoltaic collector only performs data collection and packaging, and does not perform data logic processing on the collected data.

[0045] Preferably, packaging the collected data in step 1 includes: the photovoltaic collector packaging the collected data according to the modbusRTU protocol.

[0046] Preferably, the cloud platform includes an access layer, a data parsing layer, a data cleaning layer, an application layer and a presentation layer which are connected in sequence.

[0047] Preferably, in step 3, the cloud platform analyzes the packaged data including:

[0048] Step 3.1, the photovoltaic collector is connected to the cloud platform through the access layer, and the packaged data is sent to the data analysis layer;

[0049] Step 3.2: Perform preliminary analysis on the packaged data according to the standard modbusRTU protocol to obtain the slave address and register address;

[0050] Step 3.3, the slave address and register address obtained in step 3.2 are matched in the database to obtain a parsing rule, and further parsed according to the parsing rule to obtain parsed data.

[0051] Step 3.4: The data cleaning layer cleans the parsed data to obtain cleaned data.

[0052] Step 3.5: The application layer integrates and adjusts the cleaned data.

[0053] Step 3.6: The presentation layer displays the data that has been integrated and adjusted by the application layer.

[0054] The "equal" or "same" or "equal" disclosed in the present invention must take into account the distribution of engineering parameters, and the error distribution is within ±30%; the definition of "parallel" of two line segments or two straight lines is that the angle between the two line segments or two straight lines is less than or equal to 45 degrees; the definition of "perpendicular" of two line segments or two straight lines is that the angle between the two line segments or two straight lines is within the range of [60, 120] degrees; the definition of "phase mismatch" also needs to take into account the distribution of engineering parameters, and the error distribution of the degree of mismatch is within ±30%. In addition, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. Without more constraints, an element defined by the phrase "comprising a ..." does not exclude the existence of other identical elements in the process, method, article or apparatus comprising the element.

[0055] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0056] The above description of the disclosed embodiments enables one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A data processing method for a photovoltaic collector, characterized in that: The following steps are involved: Step 1: The photovoltaic collector collects the operating data of the inverter to obtain collected data, and encapsulates the collected data to obtain encapsulated data; Step 2, the photovoltaic collector sends the packaging data to the cloud platform; Step 3: The cloud platform analyzes the collected data and performs data logic processing on the operating data obtained through the analysis.

2. The data processing method according to claim 1, characterized in that: The photovoltaic collector in step 1 performs data exchange with the inverter via the modbusRTU protocol; The photovoltaic collector exchanges data with the cloud platform via the modbusRTU protocol.

3. The data processing method according to claim 1, characterized in that: In step 1, the photovoltaic collector only performs data collection and packaging, and does not perform data logic processing on the collected data.

4. The data processing method according to claim 1, characterized in that: The step 1 of packaging the collected data includes: the photovoltaic collector packaging the collected data according to the modbusRTU protocol.

5. The data processing method according to claim 1, characterized in that: The cloud platform includes an access layer, a data parsing layer, a data cleaning layer, an application layer and a display layer which are connected in sequence.

6. The data processing method according to claim 5, characterized in that: The cloud platform in step 3 analyzes the packaged data including: Step 3.1, the photovoltaic collector is connected to the cloud platform through the access layer, and the packaged data is sent to the data analysis layer; Step 3.2, preliminarily parse the packaged data according to the standard modbusRTU protocol to obtain the slave address and register address; Step 3.3, the slave address and register address obtained in step 3.2 are matched in the database to obtain a parsing rule, and further parsed according to the parsing rule to obtain parsed data.

7. The data processing method according to claim 6, characterized in that: Also includes: Step 3.4: The data cleaning layer cleans the parsed data to obtain cleaned data.

8. The data processing method according to claim 7, characterized in that: Also includes Step 3.5: The application layer integrates and adjusts the cleansed data.

9. The data processing method according to claim 8, characterized in that: Also includes: Step 3.6: The presentation layer presents the data integrated and adjusted by the application layer.

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