A visual distributed energy data collection method, system and storage medium

Abstract

The present invention discloses a visual distributed energy data collection method, system and storage medium, the method includes each data collection terminal collecting the operation data of distributed photovoltaic components based on a preset communication protocol; each data collection terminal packages and processes the operation data according to the communication protocol and the pre-configured collection strategy to generate a data packet; each data collection terminal sends its own device address and data packet to the cloud; the cloud receives all device addresses and data packets, and authenticates the data collection terminal according to the device address, and decodes the data packet to obtain the operation data after the identity authentication is passed. This method can realize the unified collection and processing of distributed energy data, can realize the real-time monitoring and management of photovoltaic inverters, and improve the efficiency and stability of the system.

Description

Technical Field

[0001] The present invention relates to the technical field of data collection, and in particular to a visualized distributed energy data collection method. Background Art

[0002] At present, distributed photovoltaic power stations are mainly built on roofs, carports, mountains, and vegetable greenhouses. 、 Deserts, fish ponds, hilly areas, where the inverter is the core component of the photovoltaic power station, its role is to convert the direct current generated by the photovoltaic modules into alternating current, transmit it to the local load or power grid, and has related protection functions. The performance of the photovoltaic inverter directly affects the efficiency and stability of the entire photovoltaic power generation system, and remote data collection of the inverter is of great significance.

[0003] At present, when managing multiple power stations, since the brands of photovoltaic inverters used in each power station are not necessarily the same, it is necessary to switch back and forth between the platforms provided by various inverter brands, which brings troubles to data management. At the same time, the data between platforms are not interoperable, and big data cannot be sorted and analyzed, which will miss important information, such as abnormal power generation information, equipment failure information, etc., which is not conducive to the stable and reliable operation of the photovoltaic system. Summary of the invention

[0004] The present invention provides a visual distributed energy data collection method, system and storage medium to achieve unified collection and processing of distributed energy data, which can realize real-time monitoring and management of photovoltaic inverters and improve system efficiency and stability.

[0005] In a first aspect, in order to solve the above technical problems, the present invention provides a visual distributed energy data collection method, comprising:

[0006] Each data collection terminal collects the operating data of the distributed photovoltaic components based on a preset communication protocol; wherein each photovoltaic component corresponds to a data collection terminal, and the operating data includes photovoltaic power generation, user-side power consumption, excess online power, power generation efficiency, inverter state parameters and line load;

[0007] Each data collection terminal packages the operation data according to the communication protocol and the pre-configured collection strategy to generate a data packet;

[0008] Each data collection terminal sends its own device address and the data packet to the cloud;

[0009] The cloud receives all the device addresses and the data packets, and performs identity authentication on the data acquisition terminal according to the device address. When the identity authentication is passed, the data packet is decoded to obtain the operation data.

[0010] Preferably, the collection strategy is configured to: obtain the collection priority value generated by the cloud, and perform the collection operation in a corresponding order according to the collection priority value.

[0011] Preferably, the method further comprises:

[0012] The cloud obtains the historical operation data of each photovoltaic module corresponding to each data collection terminal based on the acquired historical data packets;

[0013] The collection priority value is calculated based on the historical operation data.

[0014] Preferably, the calculation formula of the acquisition priority value is:

[0015]

[0016] Among them, F is the collection priority value; n is the historical line load; Q1 is the historical photovoltaic power generation, Q2 is the historical photovoltaic power consumption, S is the historical energy storage, S = Q1-Q2; k1 is the fault risk coefficient, k2 is the power generation abnormality coefficient, m1 and m2 are weight coefficients.

[0017] Preferably, the method further comprises:

[0018] The cloud calls a preset abnormality analysis model to obtain an analysis result based on the operation data obtained by decoding;

[0019] When it is determined that the analysis result is within the power generation abnormality interval, generating abnormality warning information;

[0020] When it is determined that the analysis result is not within the power generation abnormality interval, the operation data is displayed.

[0021] Preferably, the calling of a preset abnormality analysis model to obtain an analysis result includes:

[0022] Compare and analyze the decoded operating data with the operating data in the abnormal analysis model to obtain analysis results;

[0023] Among them, through the historical operation data and equipment usage data information, the fault data and / or power generation abnormality data corresponding to the equipment historical data are analyzed, and the abnormal analysis model is generated through training.

[0024] Preferably, the displaying of the operating data includes:

[0025] Obtaining a distributed energy storage network topology diagram, and generating a position mark according to the arrangement position of each electric energy meter in the network topology diagram;

[0026] At the corresponding position mark, the collected operating data of the distributed photovoltaic components are displayed in real time.

[0027] Preferably, the method further comprises:

[0028] The cloud starts the data storage operation according to the order of the collection priority values;

[0029] The cloud obtains different types of memories and corresponding data indexes in the preset memory, classifies and stores several operating data with the same data source in the same type of memory, and configures the address index of each operating data in a corresponding order according to the priority value setting level.

[0030] In a second aspect, the present invention provides a visual distributed energy data collection system, including a cloud, a plurality of photovoltaic modules and a plurality of data collection terminals, each photovoltaic module corresponding to a data collection terminal:

[0031] The data acquisition terminal is used to collect the operating data of the distributed photovoltaic components based on a preset communication protocol; wherein the operating data includes photovoltaic power generation, user-side power consumption, excess online power, power generation efficiency, inverter status parameters, dual carbon indicators and line load;

[0032] The data acquisition terminal is further used to package the operation data according to the communication protocol and the pre-configured acquisition strategy to generate a data packet;

[0033] The data collection terminal is also used to send its own device address and the data packet to the cloud;

[0034] The cloud is used to receive all the device addresses and the data packets, and authenticate the data acquisition terminal according to the device address, and decode the data packet to obtain the operation data after the identity authentication is passed.

[0035] In a third aspect, the present invention further provides a computer-readable storage medium, which includes a stored computer program, wherein when the computer program is running, the device where the computer-readable storage medium is located is controlled to execute any one of the above-mentioned visualized distributed energy data collection methods.

[0036] Compared with the prior art, the present invention has the following beneficial effects:

[0037] The present invention provides a visualized distributed energy data collection method, including each data collection terminal collecting the operating data of distributed photovoltaic components based on a preset communication protocol; wherein each photovoltaic component corresponds to a data collection terminal, and the operating data includes photovoltaic power generation, user-side power consumption, excess online power, power generation efficiency, inverter status parameters, dual-carbon indicators and line load; each data collection terminal packages and processes the operating data according to the communication protocol and a pre-configured collection strategy to generate a data packet; each data collection terminal sends its own device address and the data packet to the cloud; the cloud receives all the device addresses and the data packets, and authenticates the data collection terminal according to the device address, and decodes the data packet to obtain the operating data after the identity authentication is passed.

[0038] The data collection method provided by the present invention can realize real-time monitoring and management of photovoltaic inverters through data collection and processing, and adopts Internet of Things technology to remotely collect equipment data, perform remote operation and maintenance, and realize unattended operation, thereby improving power generation efficiency and facilitating stable operation of power stations. At the same time, data collection is performed according to a preset collection strategy to avoid too much data being imported into the cloud at the same time, which is conducive to improving the computing efficiency of the cloud. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 It is a schematic diagram of the flow of a visualized distributed energy data collection method provided by the first embodiment of the present invention;

[0040] Figure 2 It is a distributed energy storage network topology diagram provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0041] 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.

[0042] Reference Figure 1 The first embodiment of the present invention provides a visual distributed energy data collection method, comprising the following steps:

[0043] S11, each data collection terminal collects the operating data of the distributed photovoltaic components based on a preset communication protocol; wherein each photovoltaic component corresponds to a data collection terminal, and the operating data includes photovoltaic power generation, user-side power consumption, excess online power, power generation efficiency, inverter state parameters, dual carbon indicators and line load;

[0044] S12, each data collection terminal packages the operation data according to the communication protocol and the pre-configured collection strategy to generate a data packet;

[0045] S13, each data collection terminal sends its own device address and the data packet to the cloud;

[0046] S14, the cloud receives all the device addresses and the data packets, and authenticates the data acquisition terminal according to the device address, and decodes the data packet to obtain the operation data after the identity authentication is passed.

[0047] The data collection method provided by the present invention can realize real-time monitoring and management of photovoltaic inverters, photovoltaic energy meters, and user-side energy meters through data collection and processing, and adopts Internet of Things technology to remotely collect equipment data, perform remote operation and maintenance, and realize unattended operation, which can improve power generation efficiency and be beneficial to the stable operation of power stations. At the same time, data collection is performed according to a preset collection strategy to avoid too much data being imported into the cloud at the same time, which is beneficial to improving the computing efficiency of the cloud.

[0048] In the specific implementation, the data acquisition terminal includes a 4G gateway with a 485 communication interface, a 485 serial port line, a power supply, a 4G SIM card, a server, etc. The optional communication protocols include: MQTT (Message Queuing Telemetry Transport), Q / GDW_376.1-2013 power protocol, Modbus-RTU, Modbus-TCP, DL / T645-1997, DL / T645-2007, DL / T698.45-2017, etc.

[0049] In this embodiment, the collection strategy is configured to: obtain the collection priority value generated by the cloud, and perform the collection operation in a corresponding order according to the collection priority value.

[0050] Exemplarily, the cloud obtains the historical operation data of each photovoltaic component corresponding to each data collection terminal based on the acquired historical data packets;

[0051] The collection priority value is calculated based on the historical operation data.

[0052] Specifically, the calculation formula of the acquisition priority value is:

[0053]

[0054] Among them, F is the collection priority value; n is the historical line load; Q1 is the historical photovoltaic power generation, Q2 is the historical photovoltaic power consumption, S is the historical energy storage, S = Q1-Q2; k1 is the fault risk coefficient, k2 is the power generation abnormality coefficient, m1 and m2 are weight coefficients.

[0055] It should be noted that in order to avoid too much data being collected into the cloud at the same time, it is necessary to sort the data according to the collection priority value, and perform the collection operation in the order of the collection priority value. For example, the data collection terminal ranked first performs the collection operation at the first moment, obtains the operation data of the corresponding photovoltaic component and sends it to the cloud; the data collection terminal ranked second performs the collection operation at the second moment, obtains the operation data of the corresponding photovoltaic component and sends it to the cloud, and so on.

[0056] In order to facilitate the understanding of the present invention, some preferred embodiments of the present invention are further described below.

[0057] In one implementation, the method further includes:

[0058] The cloud calls a preset abnormality analysis model to obtain an analysis result based on the operation data obtained by decoding;

[0059] When it is determined that the analysis result is within the power generation abnormality interval, generating abnormality warning information;

[0060] When it is determined that the analysis result is not within the power generation abnormality interval, the operation data is displayed.

[0061] The calling of a preset abnormality analysis model to obtain an analysis result includes:

[0062] Compare and analyze the decoded operating data with the operating data in the abnormal analysis model to obtain analysis results;

[0063] Among them, through the historical operation data and equipment usage data information, the fault data and / or power generation abnormality data corresponding to the equipment historical data are analyzed, and the abnormal analysis model is generated through training.

[0064] In one implementation, through the equipment management platform, functions such as map overview, total number of power stations, power station reports, power station overview, inverter status, smart operation and maintenance, and comprehensive management are realized, and the collected data can effectively count the equipment operation status and grasp the equipment operation status in real time. By running the accumulated equipment usage data information, analyzing the equipment historical data and fault data, forming a fault model, and comparing and analyzing the real-time collected data information with the fault model, an equipment fault alarm system is formed to help enterprises to carry out remote operation and maintenance and predictive maintenance in a timely manner, reduce equipment losses, and reduce operation and maintenance service costs.

[0065] In one implementation, it is also possible to build a digital twin of the photovoltaic component by establishing a data middle platform, conduct statistical analysis and mechanism analysis on the equipment's full life cycle operation figures, obtain explicit and implicit data, and package these data, make a data API interface, connect with third-party equipment, and quickly build an abnormality analysis system.

[0066] In one implementation, presenting the operating data includes:

[0067] Obtaining a distributed energy storage network topology diagram, and generating a position mark according to the arrangement position of each electric energy meter in the network topology diagram;

[0068] At the corresponding position mark, the collected operating data of the distributed photovoltaic components are displayed in real time.

[0069] like Figure 2 As shown, the electric energy meter obtains the electric energy data through infrared. After obtaining the network topology map, the network topology map is mapped to the display interface, and the data is displayed in real time at the corresponding position mark. Among them, the display interface can be configured on the smart photovoltaic energy storage integrated platform connected to the cloud, and can also be the display interface of the mobile terminal device.

[0070] In another implementation, the method further includes:

[0071] The cloud starts the data storage operation according to the order of the collection priority values;

[0072] The cloud obtains different types of memories and corresponding data indexes in the preset memory, classifies and stores several operating data with the same data source in the same type of memory, and configures the address index of each operating data in a corresponding order according to the priority value setting level.

[0073] The second embodiment of the present invention provides a visual distributed energy data collection system, including a cloud, a plurality of photovoltaic modules and a plurality of data collection terminals, each photovoltaic module corresponds to a data collection terminal:

[0074] The data acquisition terminal is used to collect the operating data of the distributed photovoltaic components based on a preset communication protocol; wherein the operating data includes photovoltaic power generation, user-side power consumption, excess online power, power generation efficiency, inverter status parameters, dual carbon indicators and line load;

[0075] The data acquisition terminal is further used to package the operation data according to the communication protocol and the pre-configured acquisition strategy to generate a data packet;

[0076] The data collection terminal is also used to send its own device address and the data packet to the cloud;

[0077] The cloud is used to receive all the device addresses and the data packets, and authenticate the data acquisition terminal according to the device address, and decode the data packet to obtain the operation data after the identity authentication is passed.

[0078] It should be noted that a visualized distributed energy data collection system provided in an embodiment of the present invention is used to execute all process steps of a visualized distributed energy data collection method in the above embodiment, and the working principles and beneficial effects of the two correspond one to one, so they will not be repeated here.

[0079] The embodiment of the present invention further provides a terminal device. The terminal device includes: a processor, a memory, and a computer program stored in the memory and executable on the processor, such as a visualized distributed energy data collection program. When the processor executes the computer program, the steps in the above-mentioned visualized distributed energy data collection method embodiments are implemented, such as Figure 1 Alternatively, the processor implements the functions of each module / unit in the above-mentioned system embodiments when executing the computer program.

[0080] Exemplarily, the computer program may be divided into one or more modules / units, which are stored in the memory and executed by the processor to implement the present invention. The one or more modules / units may be a series of computer program instruction segments capable of implementing specific functions, which are used to describe the execution process of the computer program in the terminal device.

[0081] The terminal device may be a computing device such as a desktop computer, a notebook, a PDA, and a smart tablet. The terminal device may include, but is not limited to, a processor and a memory. Those skilled in the art will appreciate that the above components are merely examples of terminal devices and do not constitute a limitation on the terminal device. The terminal device may include more or fewer components than the above components, or may combine certain components, or different components. For example, the terminal device may also include input and output devices, network access devices, buses, etc.

[0082] The processor may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor, etc. The processor is the control center of the terminal device, and uses various interfaces and lines to connect various parts of the entire terminal device.

[0083] The memory can be used to store the computer program and / or module, and the processor realizes various functions of the terminal device by running or executing the computer program and / or module stored in the memory, and calling the data stored in the memory. The memory can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, an application required for at least one function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area can store data created according to the use of the mobile phone (such as audio data, a phone book, etc.), etc. In addition, the memory can include a high-speed random access memory, and can also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0084] Wherein, if the module / unit integrated in the terminal device is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on such an understanding, the present invention implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. Wherein, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or system capable of carrying the computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electric carrier signal, telecommunication signal and software distribution medium. It should be noted that the content contained in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electric carrier signals and telecommunication signals.

[0085] It should be noted that the system embodiment described above is merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. In addition, in the drawings of the system embodiment provided by the present invention, the connection relationship between the modules indicates that there is a communication connection between them, which may be specifically implemented as one or more communication buses or signal lines. A person of ordinary skill in the art may understand and implement it without paying any creative effort.

[0086] The specific embodiments described above further illustrate the purpose, technical solutions and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. It is particularly pointed out that for those skilled in the art, any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the scope of protection of the present invention.

Claims

1. A visual distributed energy data collection method, characterized in that: include: Each data collection terminal collects the operating data of the distributed photovoltaic components based on a preset communication protocol; wherein each photovoltaic component corresponds to a data collection terminal, and the operating data includes photovoltaic power generation, photovoltaic power consumption, power generation efficiency, inverter state parameters and line load; Each data collection terminal packages the operation data according to the communication protocol and the pre-configured collection strategy to generate a data packet; Each data collection terminal sends its own device address and the data packet to the cloud; The cloud receives all the device addresses and the data packets, and authenticates the data acquisition terminal according to the device address, and decodes the data packet to obtain the operation data after the identity authentication is passed; The collection strategy is configured to: obtain the collection priority value generated by the cloud, and perform the collection operation in a corresponding order according to the collection priority value; The method further includes: obtaining, by the cloud, historical operation data of each photovoltaic component corresponding to each data collection terminal according to the acquired historical data packets; and calculating the collection priority value according to the historical operation data; The calculation formula of the acquisition priority value is: Among them, F is the collection priority value; n is the historical line load; S is the historical storage energy, ; Q1 is the historical photovoltaic power generation, Q2 is the historical photovoltaic power consumption, k1 is the fault risk coefficient, k2 is the power generation abnormality coefficient, m1 and m2 are weight coefficients.

2. The visual distributed energy data collection method according to claim 1 is characterized in that: The method further comprises: The cloud calls a preset abnormality analysis model to obtain an analysis result based on the operation data obtained by decoding; When it is determined that the analysis result is within the power generation abnormality interval, generating abnormality warning information; When it is determined that the analysis result is not within the power generation abnormality interval, the operation data is displayed.

3. The visual distributed energy data collection method according to claim 2 is characterized in that: The calling of a preset abnormality analysis model to obtain an analysis result includes: Compare and analyze the decoded operating data with the operating data in the abnormal analysis model to obtain analysis results; Among them, through the historical operation data and equipment usage data information, the fault data and / or power generation abnormality data corresponding to the equipment historical data are analyzed, and the abnormal analysis model is generated through training.

4. The visual distributed energy data collection method according to claim 2 is characterized in that: The displaying of the operation data includes: Obtaining a distributed energy storage network topology diagram, and generating a position mark according to the arrangement position of each electric energy meter in the network topology diagram; At the corresponding position mark, the collected operating data of the distributed photovoltaic components are displayed in real time.

5. The visual distributed energy data collection method according to claim 1 is characterized in that: The method further comprises: The cloud starts the data storage operation according to the order of the collection priority values; The cloud obtains different types of memories and corresponding data indexes in the preset memory, classifies and stores several operating data with the same data source in the same type of memory, and configures the address index of each operating data in a corresponding order according to the priority value setting level.

6. A visual distributed energy data acquisition system, characterized in that: It includes the cloud, several photovoltaic modules and several data collection terminals. Each photovoltaic module corresponds to a data collection terminal: The data acquisition terminal is used to collect the operating data of the distributed photovoltaic components based on a preset communication protocol; wherein the operating data includes photovoltaic power generation, photovoltaic power consumption, power generation efficiency, inverter state parameters and line load; The data acquisition terminal is further used to package the operation data according to the communication protocol and the pre-configured acquisition strategy to generate a data packet; The data collection terminal is also used to send its own device address and the data packet to the cloud; The cloud is used to receive all the device addresses and the data packets, and authenticate the data acquisition terminal according to the device address, and decode the data packet to obtain the operation data after the identity authentication is passed; The collection strategy is configured to: obtain the collection priority value generated by the cloud, and perform the collection operation in a corresponding order according to the collection priority value; The cloud is also used to: obtain the historical operation data of each photovoltaic component corresponding to each data collection terminal according to the acquired historical data packets; calculate the collection priority value according to the historical operation data; The calculation formula of the acquisition priority value is: Among them, F is the collection priority value; n is the historical line load; S is the historical storage energy, ; Q1 is the historical photovoltaic power generation, Q2 is the historical photovoltaic power consumption, k1 is the fault risk coefficient, k2 is the power generation abnormality coefficient, m1 and m2 are weight coefficients.

7. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored computer program, wherein when the computer program is executed, the device where the computer-readable storage medium is located is controlled to execute the visualized distributed energy data collection method as described in any one of claims 1 to 5.

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