Hierarchical management and control Internet of Things method and device for distributed photovoltaic power station

Abstract

The invention discloses a distributed photovoltaic power station-oriented hierarchical management and control Internet of Things method and device, and provides a photovoltaic Internet of Things hierarchical management and control construction method based on a'cloud side management end 'aiming at the requirements of equipment security access, network security partition, data aggregation analysis and the like, which is beneficial to realizing three-level control of'headquarters + regions + stations'. The invention provides a hierarchical unified access method based on a digital intelligent photovoltaic equipment object model so as to realize unified access and convergence of data among power plants. The invention provides a distributed photovoltaic power plant network partition planning method to guarantee the network security of a digital intelligent photovoltaic power plant. The invention provides a photovoltaic internet-of-things data partitioning method so as to guarantee connectivity and safety of internet-of-things data.

Description

Technical Field

[0001] The present invention belongs to the field of distributed photovoltaic power station Internet of Things construction, and in particular relates to a hierarchical control Internet of Things method and device for distributed photovoltaic power stations. Background Art

[0002] At present, the construction of photovoltaic power stations based on the Internet of Things is highly praised by the market. For example, the photovoltaic agricultural Internet of Things information management system based on the cloud model uses cloud center servers instead of traditional servers to achieve remote professional and centralized management, avoid power outages and cause server data storage damage, and provide guarantees for big data intelligent analysis.

[0003] Distributed photovoltaic power generation system operation and maintenance intelligent management system based on cloud computing and the Internet of Things provides a distributed photovoltaic power generation system operation and maintenance intelligent management system based on cloud computing and the Internet of Things. Comprehensive detection and analysis of the operating parameters of each equipment and external environmental parameters of each power station are carried out to achieve intelligent adjustment of the light receiving area corresponding to the power generation battery group.

[0004] Gou Yi, Wang Peiyao, Ran Yinlin. Research on the application of cloud-edge based Internet of Things technology in "distributed photovoltaic operation service" [J]. The application of cloud-edge based Internet of Things technology in the new energy industrial Internet is proposed. Combined with the actual business needs of distributed photovoltaic operation services, distributed photovoltaic operation services based on cloud-edge Internet of Things technology are constructed.

[0005] "An Internet of Things Method for Realizing Safe Use of Cookware", "Internet of Things Method and System for Highway Operations", "An Internet of Things System for Testing Samples and Internet of Things Method for Testing Samples" and other articles have proposed Internet of Things methods for different fields. However, there are currently no similar Internet of Things methods in the photovoltaic field, let alone a hierarchically controlled Internet of Things method to provide unified, standardized, and hierarchically controllable Internet of Things data for photovoltaic equipment, monitoring equipment access, and real-time monitoring of power generation status.

[0006] The above patents and papers all focus on using the Internet of Things to realize the management and operation and maintenance functions of photovoltaic power stations, and are limited to the management and operation and maintenance of a single power station. However, due to the lack of a unified photovoltaic power station IoT access and management method between power stations, data from different manufacturers and different types of equipment are difficult to interconnect and interoperate, which in turn affects the regional centralized operation and maintenance of photovoltaic power stations and the intelligent analysis of the headquarters. The secure access, hierarchical use, and centralized analysis of photovoltaic data have become important trends in the field of digital photovoltaic operations, but these existing technologies do not provide a detailed description of the distributed photovoltaic IoT method, nor do they propose a hierarchical management and control method for equipment access, network planning, and data aggregation in distributed photovoltaic power stations. Summary of the invention

[0007] The purpose of the present invention is to address the deficiencies in the prior art and provide a hierarchical management and control Internet of Things method and device for distributed photovoltaic power stations.

[0008] The object of the present invention is to achieve the following technical solution: a hierarchical control and interconnection method for distributed photovoltaic power stations, comprising the following steps:

[0009] By building a three-level management system consisting of site-edge area-cloud headquarters for distributed photovoltaic power stations in the region;

[0010] The cloud headquarters is used to complete intelligent risk identification, site operation and maintenance evaluation, equipment selection, equipment life prediction, operation and maintenance plan recommendations and output prediction for each period based on a large amount of operating status, fault information, meteorological information and equipment parameter data collected by the photovoltaic system through model algorithms and data analysis, providing data solution support for user operation decisions;

[0011] The edge area is used to monitor the distributed photovoltaic power station in the area, monitor the power generation and output curve data, and display static information, dynamic measurement information and statistical information according to the monitoring results;

[0012] The site is used to monitor various devices in the distributed photovoltaic power station in the region, obtain real-time data of each device through the Internet of Things platform, and display the real-time operation status and environmental data of each device.

[0013] Furthermore, based on the three-level management and control, a logical architecture consisting of cloud, pipe, edge and end logical layers is constructed;

[0014] The cloud logic layer is provided with a unified IoT platform, and the edge logic layer is provided with an edge IoT platform;

[0015] The cloud logic layer is deployed on the unified IoT platform and the upper-layer applications it supports. It manages and operates various sensor layer devices through the unified IoT platform and provides standardized data services to the data center, knowledge platform and business system.

[0016] The management logic layer is various types of remote communication networks;

[0017] The edge logic layer is an edge IoT platform with edge computing capabilities deployed in distributed photovoltaic power stations in the region, which is used to realize the aggregation of various types of perception data of distributed photovoltaic power stations in the region, and realize standardized processing and uploading of perception data based on the object model, supporting local business processing and regional autonomy;

[0018] The end logic layer is a collection terminal, and the collection terminal includes industrial equipment of a distributed photovoltaic power station in the region.

[0019] Furthermore, the remote communication network includes power optical fiber, wireless private network, wireless public network or the Internet.

[0020] Furthermore, the industrial equipment includes a combiner box, an inverter, a transformer, a distribution cabinet, an SVG or an energy storage device.

[0021] The present invention also includes a hierarchical control and Internet of Things device for distributed photovoltaic power stations, including a memory and one or more processors, wherein the memory stores executable code, and when the one or more processors execute the executable code, it is used for the above-mentioned hierarchical control and Internet of Things method for distributed photovoltaic power stations.

[0022] The present invention also includes a computer-readable storage medium on which a program is stored. When the program is executed by a processor, the above-mentioned hierarchical control and interconnection method for distributed photovoltaic power stations is implemented.

[0023] The beneficial effects of the present invention are:

[0024] 1) Aiming at the requirements of digital photovoltaic for equipment security access, network security zoning, data aggregation and analysis, a photovoltaic Internet of Things hierarchical management and control construction method based on "cloud-edge-pipe-end" is proposed, which is conducive to the realization of the three-level control of "headquarters + region + plant station", and the panoramic display of the installed capacity, power generation, output, distributed photovoltaic power generation, weather warning in the supply area, equipment access, real-time alarm, channel conditions and other indicator information of distributed photovoltaic power stations in the region, realizing the three-level penetration from macro to micro, headquarters, region, and site, and assisting photovoltaic operating companies to clearly control the development of distributed photovoltaics in the operating area;

[0025] 2) In order to solve the problem of difficulty in interconnecting different photovoltaic power stations, a hierarchical unified access method based on the digital photovoltaic equipment object model is provided to achieve unified access and aggregation of data between power plants;

[0026] 3) Aiming at the network security requirements of digital photovoltaic power plants, the present invention proposes a distributed photovoltaic power plant network partition planning method based on the photovoltaic power plant construction requirements;

[0027] 4) In response to the data security requirements of photovoltaic power stations, the present invention provides a photovoltaic Internet of Things data partitioning method based on the network planning requirements of distributed photovoltaic plants to ensure the connectivity and security of Internet of Things data. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 This is a three-level management and control structure consisting of a site, edge area, and cloud headquarters.

[0029] Figure 2 This is a logical architecture diagram consisting of the cloud, pipe, edge, and end logical layers;

[0030] Figure 3 This is the cloud edge functional zoning diagram;

[0031] Figure 4 Hierarchical partition map for devices;

[0032] Figure 5 It is the network planning diagram of photovoltaic power plant;

[0033] Figure 6 Data Link Diagram

[0034] Figure 7 This is a structural diagram of a hierarchical control IoT device for distributed photovoltaic power stations. DETAILED DESCRIPTION

[0035] In order to make the purpose, technical scheme and advantages of the present invention more clear, the present invention is further described in detail in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0036] Example 1

[0037] like Figure 1 As shown, the present invention provides a hierarchical control IoT method for distributed photovoltaic power stations, forming a three-level control of "station-edge area-cloud headquarters".

[0038] At the cloud headquarters level: Based on the large amount of operating status, fault information, meteorological information, equipment parameters and other data collected by the system, through the application of model algorithms, data analysis and other applications, the system completes the construction of intelligent risk identification, station operation and maintenance evaluation, equipment selection, equipment life prediction, operation and maintenance plan recommendations, output forecasts for each period and other functions, providing data solution support for user operation decisions, improving station management level and increasing station operation income.

[0039] At the edge area level: monitor the distributed photovoltaic power stations in the region, monitor the power generation, output curve and other data, and display important operating information such as static information, dynamic measurement information, and statistical information based on the monitoring results. It also intuitively displays the number of distributed photovoltaic power stations in the region, power generation, output characteristics, and utilization hours.

[0040] Site level: Monitor distributed photovoltaic power station equipment and obtain real-time data through the IoT platform to display the real-time operation status and environmental data of the equipment, as well as voltage, current, temperature, irradiation and other data.

[0041] Example 2

[0042] The logical architecture involved in the hierarchical management and control method for distributed photovoltaic power stations provided by the present invention also includes a logical architecture composed of cloud, pipe, edge and end logical layers, such as Figure 2 shown.

[0043] The cloud logic layer refers to the unified IoT platform deployed in the cloud and the upper-layer applications it supports. Through the cloud-based unified IoT platform, various sensor layer devices are managed and maintained, unified access to IoT terminals is achieved, and standardized data services are provided to the data center, knowledge platform, and business system.

[0044] The management logic layer refers to various types of remote communication networks, mainly including power optical fiber, wireless private network, wireless public network and the Internet.

[0045] The edge logic layer refers to the logical tenants of the edge IoT platform or cloud-based unified IoT platform with edge computing capabilities deployed on the factory / power plant side. It can realize the local aggregation of various types of sensory data in a certain area, and realize the standardized processing and upload of sensory data based on the object model, supporting local business processing and regional autonomy.

[0046] The terminal logic layer refers to the acquisition terminal, which mainly includes industrial equipment of photovoltaic power plants, specifically combiner boxes, inverters, transformers, distribution cabinets, SVG, energy storage equipment, etc.

[0047] The cloud logic layer sets a unified IoT platform, and the edge logic layer sets an edge IoT platform; the unified IoT platform and the edge IoT platform cooperate with each other to unify the task of device access. Combined with the platform positioning and business needs, the functions of the unified IoT platform and the edge IoT platform are similar. The unified IoT platform focuses more on providing centralized data storage, processing and analysis capabilities, while the edge IoT platform focuses more on providing real-time data processing and decision-making capabilities.

[0048] Example 3

[0049] like Figure 3 As shown in the figure, the functions of the Industrial Internet of Things platform can be divided into cloud-edge common functions, cloud-unique functions, and edge-unique functions according to their areas.

[0050] The cloud-edge common functions mainly include: physical model management, device management, protocol conversion, rule engine, data service, data overview, cloud-edge collaboration and platform management. The above functions mainly realize device terminal physical model modeling, standard access, protocol conversion, data collection, data preprocessing, data storage and unified data services.

[0051] The cloud-specific functions mainly include: data dictionary. The data dictionary component is a component that defines and controls data consistency and accuracy, and specifies information such as the name, value type, and unit of the object. It provides a standard industry data dictionary interface to ensure the standardization of semantic descriptions of modules such as object models, device management, and rule engines.

[0052] The unique functions of the edge terminal mainly include: edge gateway function, which can meet the data collection needs of different scenarios and different types of device terminals, support lightweight deployment, and have built-in rich industrial protocols to directly collect device terminal data and forward device data (support MQTT, MQTTs, CoAP, HTTPs and other protocols) to the edge IoT platform.

[0053] Example 4

[0054] 1) End: Layered access of devices

[0055] The device hierarchical partition diagram is as follows Figure 4 As shown in the figure, the basic data collected by the photovoltaic system includes photovoltaic components, inverters, DC combiner boxes, AC combiner boxes, box transformers, step-up transformers, electric meters, tracking brackets (if any) and environmental monitoring equipment. This method first needs to establish a device object model for the above-mentioned collection objects to provide standard specifications and theoretical guidance for different types of photovoltaic terminals to go to the cloud. The specific access methods include the following four methods, which can almost cover all equipment data collection and equipment cloud scenarios in photovoltaic power stations: direct access refers to the way that the equipment data collection function is integrated into the industrial equipment terminal in the form of modules or chips and directly enters the cloud platform; gateway access refers to the way that the equipment data collection function and business function are separated, and the edge data is uniformly accessed to the cloud platform through the edge IoT gateway; application access refers to the way that the device data collected by the edge application is connected to the cloud platform by means of cloud-to-cloud docking; the edge platform type aims to deploy the edge IoT platform on the edge server to divert the cloud platform, and connect the industrial equipment data to the cloud platform under the premise of ensuring timely interaction between the edge and the stability and reliability of the cloud.

[0056] 2) Management: Network partition planning

[0057] like Figure 5 As shown in the figure, the photovoltaic plant network planning diagram includes:

[0058] Zone I belongs to the dispatching network. This area should at least include real-time encryption authentication devices, real-time switches, Zone I communication gateways, plant and station authentication and encryption devices, plant and station ring network switches, photovoltaic field equipment, SVG devices, environmental monitoring devices, monitoring hosts, integrated security and measurement devices, NCS servers, AGC / AVC servers, IEC acquisition gateways, and Zone I switches.

[0059] Zone II belongs to the dispatching network, and this area should at least include non-real-time encryption authentication devices, non-real-time switches, Zone II communication gateways, fault recording servers, power prediction servers, electric energy collection servers, and Zone II switches.

[0060] Zone III belongs to the plant local area network, which should at least include weather forecast server, video surveillance server, NCS client, and application platform edge server.

[0061] Zone IV belongs to the external network and should at least include the application platform cloud server.

[0062] In addition, the area security between Zone I and Zone II is protected by a hardware firewall; the area security between Zone III and Zone IV is protected by a hardware firewall; and the area isolation between Zone II and Zone III is achieved through forward isolation devices and reverse isolation devices.

[0063] 3) Cloud-edge: Data link partitioning

[0064] Data link diagram Figure 6 shown.

[0065] To ensure the connectivity and security of photovoltaic IoT data, the platform divides related systems and equipment into six data domains. Within a data domain, unless otherwise specified, each component is generally considered to have no data isolation, and data can be exchanged or stored on a secure and reliable channel; there are generally several data service links between data domains to ensure the synchronization and value sharing of IoT data.

[0066] The edge device data domain (data domain number: 1) is mainly composed of gateway sub-devices, smart devices and established point-like IoT systems. This data domain serves as the original data input of the Oriental Solar Industrial IoT platform and is the platform's main data source. Gateway sub-devices mainly include inverters, transformers, combiner boxes, distribution boxes, etc., which generally cannot exchange data messages through a three-layer switch, and mainly rely on physical layer or data link layer protocols such as Modbus, IEC, S7, etc. to exchange data with the outside world; smart devices mainly include smart meters, environmental sensors, etc., which usually have one or more (wireless / wired) network cards, and can access the local area network or the Internet through devices such as a two-layer switch, a three-layer switch or a router, and can rely on TCP / IP protocols and more application layer protocols such as MQTT, MQTTs, HTTPs, CoAP to exchange data with the outside world; established point-like IoT systems mainly include DCS, SCADA, WMS, etc., which mainly provide one-way data services to the outside world by exposing the corresponding Http / WebSocket API interface or OPC-UA port. This data domain is generally located in Zone 1 of the power network security zone.

[0067] The edge gateway data domain (data domain number: 2) is mainly composed of the platform's native edge soft gateway and the edge soft / hard gateway provided by external suppliers. This data domain serves as the relay for edge data aggregation and forwarding of the Oriental Solar Energy Industrial Internet of Things platform. It is responsible for collecting data sent by gateway sub-devices based on physical layer or data link layer protocols such as Modbus, IEC, S7, etc. from the south, completing message parsing and repackaging, and pushing IoT data to the north using application layer protocols such as MQTT, MQTTs, HTTPs, CoAP, etc. The relevant business data of the edge gateway is persisted in the system relational database; to ensure the reliability of the edge gateway, after the northbound forwarding fails, the edge soft gateway will cache the relevant time series data in an independent relational database so that the data can be retransmitted after the link is restored. This data domain is generally located in the power network security zone 1 (controllable), zone 2 (uncontrollable), and zone 3 (reverse isolation).

[0068] The data domain of the edge IoT platform (data domain number: 3) is mainly composed of the internal services of the edge IoT platform and related middleware. This data domain is responsible for obtaining data from the edge device data domain and the edge gateway data domain, and using the edge data processing and decision-making capabilities provided by the edge platform to precipitate edge IoT data assets and provide edge data services for the construction of the edge IoT system. The edge IoT platform includes 6 major components: protocol conversion, rule engine, object model management, device management, data service, and cloud-edge collaboration. It uses data storage middleware such as relationship library, timing library, and cache library (NoSQL). In terms of data storage, the business relationship data of protocol conversion, rule engine, object model management, device management, data service, and cloud-edge collaboration are all stored in the relationship library of the edge IoT platform, and the hot business data is cached in the cache library (NoSQL) of the edge IoT platform; the IoT data reported in time series in device management is persisted in the timing library of the edge IoT platform. In terms of component internal data dependency, the edge object model management component references the dictionary Rest API provided by the cloud IoT platform data domain data dictionary component to create the device object model, and then creates the device instance through the internal API provided by the object model component. The device instance receives the IoT time series data forwarded from the edge gateway data domain and the edge device data domain by the protocol conversion and rule engine component. After data processing by the device management component, the data is provided to the edge IoT application data domain and the cloud IoT platform data domain on demand through the cloud-edge collaboration and data service components. This data domain is generally located in the power network security zone 3.

[0069] The edge IoT application data domain (data domain number: 4) is mainly composed of incremental edge IoT systems. This data domain calls the HTTP / WebSocket API interface or OPC-UA service provided by the edge IoT platform data domain to obtain multiple categories of IoT data such as real-time data, historical data, statistical data, and alarm data, and builds IoT applications that meet the needs of business scenarios based on this. Most of the systems that constitute the edge IoT application data domain are business systems with high requirements for real-time, lightweight, and edge closure, usually including digital twin systems, output prediction systems, multi-mode diagnostic systems, plant safety monitoring systems, etc. This data domain is generally located in Zone 3 of the power network security zone.

[0070] The cloud IoT platform data domain (data domain number: 5) is mainly composed of the cloud IoT platform internal services and related middleware. This data domain gathers data from the edge IoT platform data domain, and through the centralized data storage, processing and analysis capabilities provided by the cloud IoT platform, it precipitates cloud IoT data assets and provides edge data services for the construction of the cloud IoT system. The cloud IoT platform includes 6 major components: data dictionary, rule engine, object model management, device management, data service, and cloud-edge collaboration. It uses data storage middleware such as relational library, time series library, and cache library (NoSQL). In terms of data storage, the business relationship data of the data dictionary, rule engine, object model management, device management, data service, and cloud-edge collaboration are all stored in the relationship library of the cloud IoT platform, and the hot business data is cached in the cache library (NoSQL) of the cloud IoT platform; the time series data of the device management component is persisted in the time series library of the cloud IoT platform. In terms of component internal data dependency, the physical model management component references the data dictionary API to create the device physical model, and then creates the device instance through the internal API provided by the physical model management component. The device instance receives the IoT time series data forwarded from the edge platform data domain by the cloud-edge collaboration and rule engine components, and after data processing by the device management component, the data is provided to the edge cloud platform / application data domain on demand through the data service component. This data domain is generally located in the power network security zone 4 or the external LAN.

[0071] The cloud platform / application data domain (data domain number: 6) is mainly composed of the cloud industrial application enabling platform and business application systems. This data domain calls the HTTP / WebSocket API interface or OPC-UA service provided by the cloud IoT platform data domain to obtain real-time data, historical data, statistical data, alarm data and other types of IoT data, and uses this as a basis to support the development of platforms and applications that are in line with the group's strategy. The platform base that constitutes the cloud platform / application data domain includes the industrial application development platform, industrial knowledge platform, industrial data platform, industrial safety platform, industrial twin platform, etc.; most of the systems included are statistical business systems with a high degree of data aggregation, usually including digital photovoltaic cloud platforms, smart energy carbon systems, output prediction systems, spare parts systems, infrastructure project management systems, and operation and maintenance service systems. This data domain is generally located in Zone 4 of the power network security zone or in an external LAN.

[0072] Among the above 6 data domains, there are 2 data domains in the cloud (power network security zone 4 or external LAN), and another 4 data domains are located at the edge (power network security zone 1, zone 2, zone 3). The edge IoT platform data domain and the cloud IoT platform data domain are the only relays between the cloud and the edge, and the 4 key channels in them need to be managed.

[0073] Channel 1: The channel between the cloud IoT platform data dictionary component and the edge IoT platform IoT model management component. The channel is essentially a REST API based on the HTTP protocol, which plays the role of reusing the cloud data dictionary and unifying standards.

[0074] Channel 2: The channel between the rule engine component of the cloud IoT platform and the data service component of the edge IoT platform. The channel is essentially an API based on the HTTP or WebSocket protocol, which is responsible for providing the current / historical / statistical data of each data domain at the edge to each data domain in the cloud.

[0075] Channel 3: The channel between the cloud IoT platform rule engine component and the edge IoT platform relational database. The channel is essentially an API based on the JDBC standard, which is responsible for providing the edge platform relational database directly to cloud-related services.

[0076] Channel 4: The channel between the cloud-edge collaborative component of the cloud IoT platform and the cloud-edge collaborative component of the edge IoT platform. The channel is essentially an information channel based on the MQTT / MQTTs protocol, which is responsible for synchronizing the original cloud-edge IoT data on time / by volume / on demand.

[0077] Example 5

[0078] The present embodiment relates to a hierarchical control and Internet of Things device for distributed photovoltaic power stations, including a memory and one or more processors, wherein the memory stores executable code, and when the one or more processors execute the executable code, a hierarchical control and Internet of Things method for distributed photovoltaic power stations according to the above-mentioned embodiment 1 is used; the device embodiment can be applied to any device with data processing capabilities, and the any device with data processing capabilities can be a device or apparatus such as a computer.

[0079] like Figure 7 At the hardware level, the model watermark device includes a processor, an internal bus, a network interface, a memory, and a non-volatile memory, and may also include other hardware required for the business. The processor reads the corresponding computer program from the non-volatile memory into the memory and then runs it to achieve the above Figure 1 Of course, in addition to the software implementation, the present invention does not exclude other implementations, such as logic devices or a combination of software and hardware, etc., that is, the execution subject of the following processing flow is not limited to each logic unit, but can also be hardware or logic devices.

[0080] For the improvement of a technology, it can be clearly distinguished whether it is a hardware improvement (for example, improvement of the circuit structure of diodes, transistors, switches, etc.) or a software improvement (improvement of the method flow). However, with the development of technology, many improvements of the method flow today can be regarded as direct improvements of the hardware circuit structure. Designers almost always obtain the corresponding hardware circuit structure by programming the improved method flow into the hardware circuit. Therefore, it cannot be said that the improvement of a method flow cannot be implemented with a hardware entity module. For example, a programmable logic device (PLD) (such as a field programmable gate array (FPGA)) is such an integrated circuit whose logical function is determined by the user's programming of the device. Designers can "integrate" a digital system on a PLD by programming themselves, without having to ask chip manufacturers to design and make dedicated integrated circuit chips. Moreover, nowadays, instead of manually making integrated circuit chips, this kind of programming is mostly implemented by "logic compiler" software, which is similar to the software compiler used when developing and writing programs, and the original code before compilation must also be written in a specific programming language, which is called hardware description language (HDL). There is not only one HDL, but many kinds, such as ABEL (Advanced Boolean Expression Language), AHDL (Altera Hardware Description Language), Confluence, CUPL (Cornell University Programming Language), HDCal, JHDL (Java Hardware Description Language), Lava, Lola, MyHDL, PALASM, RHDL (Ruby Hardware Description Language), etc. The most commonly used ones are VHDL (Very-High-Speed ​​Integrated Circuit Hardware Description Language) and Verilog. Those skilled in the art should also know that it is only necessary to program the method flow slightly in the above-mentioned hardware description languages ​​and program it into the integrated circuit, and then it is easy to obtain the hardware circuit that implements the logic method flow.

[0081] The controller can be implemented in any appropriate manner, for example, the controller can take the form of a microprocessor or processor and a computer-readable medium storing a computer-readable program code (such as software or firmware) that can be executed by the (micro)processor, a logic gate, a switch, an application-specific integrated circuit (ASIC), a programmable logic controller, and an embedded microcontroller. Examples of controllers include, but are not limited to, the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicone Labs C8051F320. The memory controller can also be implemented as part of the control logic of the memory. Those skilled in the art also know that in addition to implementing the controller in a purely computer-readable program code manner, the controller can be implemented in the form of a logic gate, a switch, an application-specific integrated circuit, a programmable logic controller, and an embedded microcontroller by logically programming the method steps. Therefore, this controller can be considered as a hardware component, and the devices included therein for implementing various functions can also be regarded as structures within the hardware component. Or even, the devices for implementing various functions can be regarded as both software modules for implementing the method and structures within the hardware component.

[0082] The systems, devices, modules or units described in the above embodiments may be implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer. Specifically, the computer may be, for example, a personal computer, a laptop computer, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

[0083] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0084] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0085] The present invention may be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. The present invention may also be practiced in distributed computing environments where tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules may be located in local and remote computer storage media, including storage devices.

[0086] Example 6

[0087] An embodiment of the present invention further provides a computer-readable storage medium having a program stored thereon. When the program is executed by a processor, the hierarchical control and interconnection method for distributed photovoltaic power stations of the above-mentioned embodiment 1 is implemented.

[0088] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A hierarchical control and interconnection method for distributed photovoltaic power stations, characterized in that: The following steps are involved: By building a three-level management system consisting of site-edge area-cloud headquarters for distributed photovoltaic power stations in the region; The cloud headquarters is used to complete intelligent risk identification, site operation and maintenance evaluation, equipment selection, equipment life prediction, operation and maintenance plan recommendations and output prediction for each period based on a large amount of operating status, fault information, meteorological information and equipment parameter data collected by the photovoltaic system through model algorithms and data analysis, providing data solution support for user operation decisions; The edge area is used to monitor the distributed photovoltaic power station in the area, monitor the power generation and output curve data, and display static information, dynamic measurement information and statistical information according to the monitoring results; The site is used to monitor various devices in the distributed photovoltaic power station in the region, obtain real-time data of each device through the Internet of Things platform, and display the real-time operation status and environmental data of each device.

2. According to claim 1, a hierarchical control and interconnection method for distributed photovoltaic power stations is characterized in that: Based on the three-level management and control, a logical architecture consisting of cloud, pipe, edge, and end logical layers is constructed; The cloud logic layer is provided with a unified IoT platform, and the edge logic layer is provided with an edge IoT platform; The cloud logic layer is deployed on the unified IoT platform and the upper-layer applications it supports. It manages and operates various sensor layer devices through the unified IoT platform and provides standardized data services to the data center, knowledge platform and business system. The management logic layer is various types of remote communication networks; The edge logic layer is an edge IoT platform with edge computing capabilities deployed in distributed photovoltaic power stations in the region, which is used to realize the aggregation of various types of perception data of distributed photovoltaic power stations in the region, and realize standardized processing and uploading of perception data based on the object model, supporting local business processing and regional autonomy; The end logic layer is a collection terminal, and the collection terminal includes industrial equipment of a distributed photovoltaic power station in the region.

3. A hierarchical control and interconnection method for distributed photovoltaic power stations according to claim 2, characterized in that: The remote communication network includes power optical fiber, wireless private network, wireless public network or the Internet.

4. A hierarchical control and interconnection method for distributed photovoltaic power stations according to claim 2, characterized in that: The industrial equipment includes a combiner box, an inverter, a transformer, a distribution cabinet, an SVG or an energy storage device.

5. A hierarchical control IoT device for distributed photovoltaic power stations, characterized in that: It includes a memory and one or more processors, wherein the memory stores executable code, and when the one or more processors execute the executable code, it is used to implement a hierarchical management and control Internet of Things method for distributed photovoltaic power stations as described in any one of claims 1-4.

6. A computer-readable storage medium, characterized in that: A program is stored thereon, and when the program is executed by a processor, a hierarchical control Internet of Things method for distributed photovoltaic power stations as described in any one of claims 1-4 is implemented.

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