Controllable intelligent photovoltaic management architecture

Abstract

This invention discloses a controllable intelligent photovoltaic (PV) management architecture, belonging to the field of photovoltaic energy technology. The architecture includes an edge layer, a platform layer, and an application layer. The edge layer is used to collect equipment operation data and business management data in PV management. The platform layer is used for centralized storage, processing, analysis, and application of the data collected by the edge layer. The application layer provides intelligent operation and maintenance, management decision-making, and business empowerment based on the data and analysis results from the platform layer. This invention reduces the operation and maintenance costs and difficulty of PV power plants and avoids the problem of data silos.

Description

Technical Field

[0001] This invention relates to the field of photovoltaic energy technology, and more specifically to a controllable intelligent photovoltaic management architecture. Background Technology

[0002] Against the backdrop of global energy structure transformation, the accelerated pace of industrialization and urbanization has led to a sustained increase in global energy demand. Simultaneously, growing environmental awareness and the severe challenges of global climate change have made the development and utilization of renewable energy a focus of international attention. Photovoltaic power generation, with its advantages of being clean and pollution-free, widely distributed, highly renewable, and easily implemented in distributed generation, is gradually shifting from a supplementary energy source to a mainstream energy source, becoming a crucial force in optimizing the global energy structure.

[0003] However, with the increasing scale of photovoltaic power plant construction, especially the rise of centralized photovoltaic power plants, a series of operation and maintenance management problems have emerged. Centralized photovoltaic power plants are often located in areas with abundant solar resources but in remote geographical locations. This not only requires a large area for the power plant but also brings the challenge of frequent on-site travel for operation and maintenance personnel, greatly increasing operation and maintenance costs. In addition, traditional manual operation and maintenance methods rely heavily on the personal experience and intuition of operation and maintenance personnel, lacking scientific data support and intelligent decision-making assistance, resulting in low operation and maintenance efficiency and difficulty in achieving real-time monitoring of the power plant's operating status and timely detection and handling of potential faults.

[0004] Even more serious is the fact that photovoltaic power plant operation and maintenance data are often scattered across various independent subsystems, lacking a unified management platform and effective data integration mechanisms, resulting in severe data silos. This not only hinders data sharing and interoperability but also limits the full exploitation and utilization of data value, hindering the improvement of the precision and intelligence level of power plant operation and maintenance management.

[0005] Meanwhile, the operation of photovoltaic power plants is affected by a variety of environmental factors, including sunlight intensity, temperature, wind speed, and humidity. Fluctuations in these environmental factors not only directly affect the power plant's power generation efficiency and energy output, but may also pose a potential threat to the safe and stable operation of the power plant equipment. However, due to the lack of intelligent management systems and advanced predictive analytics technologies, power plants often struggle to accurately monitor and effectively respond to these environmental factors, thus limiting the optimization of energy utilization and the reduction of power plant operation and maintenance costs.

[0006] In summary, facing challenges such as high operation and maintenance costs, high difficulty, severe data silos, and insufficient energy utilization optimization in photovoltaic power plants, traditional manual operation and maintenance methods are no longer sufficient to meet the needs of efficient and refined management. Summary of the Invention

[0007] To address the problems of high operation and maintenance costs, high difficulty, and severe data silos in existing photovoltaic power plant technologies, this invention provides a controllable intelligent photovoltaic management architecture that reduces the operation and maintenance costs and difficulty of photovoltaic power plants and avoids the problem of data silos.

[0008] To achieve the above objectives, the present invention provides the following technical solution.

[0009] This invention provides a controllable intelligent photovoltaic management architecture, including an edge layer, a platform layer, and an application layer. The edge layer is used to collect equipment operation data and business management data in photovoltaic management. The platform layer is used to centrally store, process, analyze, and apply the data collected by the edge layer. The application layer is used to provide intelligent operation and maintenance, management decision-making, and business empowerment through the data and analysis results of the platform layer.

[0010] As a further improvement of the present invention, the edge layer includes a data acquisition module, an edge computing module, and a data uploading module; the data acquisition module is used to collect real-time operating data from the equipment in photovoltaic management; the edge computing module is used to perform preliminary processing and analysis on the data collected by the data acquisition module; and the data uploading module is used to upload the data processed by the edge computing module to the platform layer.

[0011] As a further improvement of the present invention, the edge computing module is used to perform preliminary processing and analysis on the data collected by the data acquisition module, including cleaning, compressing and encrypting the data collected by the data acquisition module.

[0012] As a further improvement of the present invention, the platform layer includes: a visualization platform, a microservice component library, a big data platform, a model library, an edge access platform, and a general PaaS platform; the visualization platform is used for intuitive data display and interactive operation; the microservice component library is used to provide alarm management, fault management, device management, and statistical analysis; the big data platform is used to utilize distributed storage and computing technologies to store, compute, and analyze data received by the platform layer; the model library is used to perform in-depth data mining and intelligent analysis on data received by the platform layer; the edge access platform is used to interface with the edge layer; and the general PaaS platform is used to provide middleware resources, cluster management, image repository, and sustainable integration and deployment capabilities.

[0013] As a further improvement of the present invention, the visualization platform includes a mobile terminal and a display.

[0014] As a further improvement of the present invention, the microservice component library includes alarm management, fault management, equipment cases, equipment information, industrial models, equipment documentation, statistical analysis, system management, and access control.

[0015] As a further improvement of the present invention, the big data platform includes big data access, big data storage, big data computing, big data management, and industrial modeling and analysis.

[0016] As a further improvement of the present invention, the model library includes a big data model and a mechanism diagnostic model; the big data model is used for early warning, prediction, and measure recommendation; the mechanism diagnostic model is used to diagnose the remaining life of photovoltaics, inverters, and transformers.

[0017] As a further improvement of the present invention, the edge access platform includes production monitoring, edge device management, smart gateway management, and edge computing management.

[0018] As a further improvement of the present invention, the application layer includes an intelligent operation and maintenance module, a management decision-making module, and a business empowerment module; the intelligent operation and maintenance module is used to utilize the data and analysis results provided by the platform layer to perform real-time monitoring, fault warning, fault location, and repair suggestions for the equipment; the management decision-making module is used to provide management with business insights and decision support through visualization and data analysis; the business empowerment module is used to interconnect with the platform to achieve data sharing and exchange.

[0019] Compared with the prior art, the present invention has the following beneficial effects: Through intelligent data acquisition and processing at the edge layer, this invention can obtain the operating status and performance parameters of various equipment within a photovoltaic power station in real time and accurately, effectively reducing the frequency and intensity of manual inspections. Simultaneously, the centralized data storage and analysis functions at the platform layer enable maintenance personnel to quickly locate fault points, improving maintenance efficiency and significantly reducing maintenance costs. Secondly, this invention utilizes advanced data processing and analysis technologies to deeply mine and intelligently analyze the large amount of data collected at the edge layer, providing maintenance personnel with intuitive and easy-to-understand maintenance reports and fault warnings. This not only makes maintenance work more convenient and efficient but also reduces the professional skills required of maintenance personnel, effectively alleviating the difficulty of maintenance. Furthermore, this invention breaks the traditional data fragmentation and isolation in photovoltaic power stations through data interaction between the edge layer and the platform layer, and data sharing between the platform layer and the application layer. By constructing a complete data link, this invention achieves interconnection and interoperability of various types of data within the photovoltaic power station, providing comprehensive and accurate data support for intelligent maintenance and management decisions. The data processing and analysis functions at the platform layer can provide a scientific and reliable basis for management decisions. By mining and analyzing historical data, this invention can predict the future power generation and operation and maintenance needs of photovoltaic power plants, providing forward-looking guidance for the operation and management of the plants. Simultaneously, the intelligent operation and maintenance and management decision-making functions provided at the application layer can dynamically adjust operation and maintenance strategies based on real-time data, improving the accuracy and timeliness of management decisions. Through the business empowerment functions provided at the application layer, this invention can transform the results of intelligent operation and maintenance and management decisions into actual productivity. This not only helps improve the operational efficiency and economic benefits of photovoltaic power plants but also promotes the innovative development of the photovoltaic industry, injecting new vitality into the industry's sustainable development. Attached Figure Description

[0020] The accompanying drawings described herein are for illustrative purposes only and are not intended to limit the scope of the invention in any way. In the drawings: Figure 1 This is a schematic diagram of the overall architecture of a controllable intelligent photovoltaic management architecture according to the present invention. Detailed Implementation

[0021] To enable those skilled in the art to better understand the technical solutions of this invention, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. The described embodiments are merely some embodiments of this invention, and not all embodiments. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of this invention.

[0022] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0023] To address the problems of high operation and maintenance costs, high difficulty, and severe data silos in existing photovoltaic power plant technologies, this invention provides a controllable intelligent photovoltaic management architecture, such as... Figure 1 As shown, the architecture includes an edge layer, a platform layer, and an application layer.

[0024] The edge layer is used to receive models from the platform and realize intelligent edge analysis; The platform layer is used to build model libraries and microservice component libraries with edge access platforms, general PaaS platforms, big data platforms, visualization platforms and unified operation platforms as core capabilities. It supports the intelligent analysis and application of systems such as basic technology platforms, comprehensive display and navigation functions, integration with existing systems, and artificial intelligence applications in photovoltaic and inverter transformers.

[0025] The application layer is used to provide intelligent operation and maintenance, management decision-making, and business empowerment by integrating data and analysis results from the platform layer.

[0026] As the front end of the photovoltaic big data monitoring and management system, the edge layer is primarily responsible for data acquisition, preprocessing, and preliminary analysis. Through edge computing systems deployed on the devices, it enables real-time acquisition of equipment operation data and business management data, and performs intelligent edge analysis based on models, improving the system's response speed and accuracy.

[0027] Specifically, the edge layer uses the data acquisition, edge computing, and data cloud uploading modules of the edge computing system to collect device operation data and business management data, and based on the model, realizes the edge intelligent analysis capabilities of the access devices.

[0028] Data acquisition module: Utilizes sensors, smart devices, and other means to collect real-time operational data from photovoltaic power plants, inverters, and other equipment, as well as business management-related data.

[0029] Edge computing module: Deploy an edge computing module on the device to perform preliminary processing and analysis on the collected data, and perform operations such as data cleaning, compression, and encryption.

[0030] Data Cloud Module: Uploads processed data to the platform layer via secure and reliable transmission methods, providing data support for subsequent intelligent analysis and applications.

[0031] The platform layer is the core of the photovoltaic big data monitoring and management system, responsible for the centralized storage, processing, analysis, and application of data. By building a visualization platform, microservice component library, big data platform, and model library, it achieves comprehensive data management and in-depth mining, providing strong support for intelligent operation and maintenance, management decision-making, and business empowerment.

[0032] Specifically, the platform layer includes a visualization platform, a microservice component library, a big data platform, a model library, an edge access platform, and a general PaaS platform, as detailed below.

[0033] Visualization platform: Provides access methods for various terminal devices such as PCs, mobile phones, and large screens, enabling intuitive data display and interactive operation.

[0034] Microservice Component Library: Provides microservice components such as alarm management, fault management, equipment management, and statistical analysis, supporting the rapid construction and deployment of operation and maintenance-related applications and services. Sub-components include alarm management, fault management, equipment cases, equipment information, industrial models, equipment documentation, statistical analysis, system management, and access control.

[0035] Big Data Platform: Utilizing distributed storage and computing technologies, it enables rapid access, storage, computation, and analysis of massive amounts of data. A big data platform includes big data access, big data storage, big data computation, big data management, and industrial modeling and analysis.

[0036] Model Library: This library includes big data models for intelligent early warning, intelligent prediction, and measure recommendation, as well as mechanism diagnostic models for photovoltaic (PV) remaining lifespan, inverters, and transformers, supporting in-depth data mining and intelligent analysis. The model library includes big data models for intelligent early warning, intelligent prediction, and measure recommendation; and mechanism diagnostic models covering PV remaining lifespan, inverters, and transformers.

[0037] Edge Access Platform: Enables seamless integration with the edge layer, supporting functions such as production monitoring, edge device management, smart gateway management, and edge computing management. The edge access platform includes production monitoring, edge device management, smart gateway management, and edge computing management.

[0038] A general-purpose PaaS platform provides capabilities such as middleware resources, cluster management, image repositories, and sustainable integration and deployment, supporting rapid system deployment and expansion. The general-purpose PaaS platform includes middleware resources, cluster management, image repositories, and sustainable integration and deployment.

[0039] The application layer is the final presentation layer of the photovoltaic big data monitoring and management system, directly facing users and management. By integrating data and analysis results from the platform layer, it provides application services such as intelligent operation and maintenance, management decision-making, and business empowerment, realizing the value of data and business innovation.

[0040] Specifically, the application layer includes: intelligent operation and maintenance module, management decision-making module, and business empowerment module.

[0041] Intelligent Operation and Maintenance Module: Utilizing the data and analysis results provided by the platform layer, it enables functions such as real-time monitoring of equipment, fault early warning, fault location, and repair suggestions, thereby improving operation and maintenance efficiency and equipment reliability.

[0042] Management Decision Module: Through visualization and data analysis, this module provides management with business insights and decision support, helping to optimize resource allocation and improve operational efficiency.

[0043] Business Empowerment Module: Supports the automation, intelligentization, and digitalization of business processes, improving business processing efficiency and customer experience. Simultaneously, through interconnection with other systems and platforms, it enables data sharing and exchange, driving business innovation and development.

[0044] In summary, the edge layer's function is to receive models from the platform layer and perform intelligent edge analysis. As the system front-end, it is responsible for data acquisition, preprocessing, and preliminary analysis. It collects device operation data and business management data in real time through the edge computing system and performs intelligent analysis based on the models, thereby improving the system's response speed and accuracy.

[0045] As the core of the system, the platform layer possesses key capabilities such as an edge access platform, a general PaaS platform, a big data platform, a visualization platform, and a unified operation platform. It builds a model library and a microservice component library, supports the development of basic technology platforms, comprehensive display and navigation functions, and integration with existing systems, while promoting the application of artificial intelligence in equipment such as photovoltaics and inverter transformers.

[0046] The application layer integrates data and analysis results from the platform layer to provide users with services such as intelligent operation and maintenance, management decision-making, and business empowerment.

[0047] Specifically, the edge layer utilizes edge computing systems deployed on devices to achieve real-time data acquisition and model-based intelligent edge analysis. Data acquisition includes real-time collection of operational data from photovoltaic power plants, inverters, and other equipment, as well as related business management data, through sensors, smart devices, and other means. Edge computing performs preliminary data processing on the device side, including operations such as cleaning, compression, and encryption. Data uploading to the cloud refers to uploading the processed data to the platform layer through secure and reliable transmission methods, providing basic data support for subsequent intelligent analysis and applications.

[0048] The platform layer, through the construction of a visualization platform, microservice component library, big data platform, and model library, achieves comprehensive data management and in-depth mining, supporting intelligent operation and maintenance, management decision-making, and business empowerment. Specifically, the visualization platform provides access methods from multiple terminal devices, enabling intuitive data display; the microservice component library provides components such as alarm management and fault management, supporting the rapid construction of operation and maintenance-related applications; the big data platform utilizes distributed technology to achieve rapid processing of massive amounts of data; the model library contains various big data models and mechanism diagnostic models for in-depth data mining and intelligent analysis; and the edge access platform ensures seamless connectivity with the edge layer, supporting functions such as production monitoring and edge device management.

[0049] Many embodiments and applications beyond the examples provided will be apparent to those skilled in the art upon reading the foregoing description. Therefore, the scope of this teaching should not be determined by reference to the foregoing description, but rather by reference to the foregoing claims and the full scope of their equivalents. For purposes of completeness, all articles and references, including patent applications and publications, are incorporated herein by reference. The omission of any aspect of the subject matter disclosed herein in the foregoing claims is not intended as a waiver of that subject matter, nor should it be construed as an indication that the applicant has not considered that subject matter as part of the disclosed inventive subject matter.

[0050] The above content provides a further detailed description of the present invention. It should not be construed that the specific embodiments of the present invention are limited to this. For those skilled in the art, several simple deductions or substitutions can be made without departing from the concept of the present invention, and all such deductions or substitutions should be considered to fall within the scope of protection of the present invention as defined by the submitted claims.

Claims

1. A controllable intelligent photovoltaic management architecture, characterized in that, Includes the edge layer, platform layer, and application layer; The edge layer is used to collect equipment operation data and business management data in photovoltaic management; The platform layer is used for centralized storage, processing, analysis, and application of data collected from the edge layer; The application layer is used to provide intelligent operation and maintenance, management decision-making, and business empowerment through the data and analysis results from the platform layer.

2. The controllable intelligent photovoltaic management architecture according to claim 1, characterized in that, The edge layer includes a data acquisition module, an edge computing module, and a data uploading module to the cloud; The data acquisition module is used to collect real-time operating data from the equipment in photovoltaic management. The edge computing module is used to perform preliminary processing and analysis on the data collected by the data acquisition module; The data upload module is used to upload the data processed by the edge computing module to the platform layer.

3. The controllable intelligent photovoltaic management architecture according to claim 2, characterized in that, The edge computing module is used to perform preliminary processing and analysis on the data collected by the data acquisition module, including cleaning, compressing and encrypting the data collected by the data acquisition module.

4. The controllable intelligent photovoltaic management architecture according to claim 1, characterized in that, The platform layer includes: a visualization platform, a microservice component library, a big data platform, a model library, an edge access platform, and a general PaaS platform; The visualization platform is used for intuitive data display and interactive operation; The microservice component library is used to provide alarm management, fault management, device management, and statistical analysis; The big data platform is used to store, compute, and analyze data received by the platform layer by utilizing distributed storage and computing technologies. The model library is used for in-depth data mining and intelligent analysis of the data received by the platform layer; The edge access platform is used to interface with the edge layer; The general-purpose PaaS platform is used to provide middleware resources, cluster management, image repository, and the ability to continuously integrate and deploy.

5. The controllable intelligent photovoltaic management architecture according to claim 4, characterized in that, The visualization platform includes a mobile terminal and a display.

6. The controllable intelligent photovoltaic management architecture according to claim 4, characterized in that, The microservice component library includes alarm management, fault management, equipment cases, equipment information, industrial models, equipment documentation, statistical analysis, system management, and access control.

7. The controllable intelligent photovoltaic management architecture according to claim 4, characterized in that, The big data platform includes big data access, big data storage, big data computing, big data management, and industrial modeling and analysis.

8. The controllable intelligent photovoltaic management architecture according to claim 1, characterized in that, The model library includes big data models and mechanism diagnostic models; The big data model is used for early warning, prediction, and measure recommendation; The mechanism diagnostic model is used to diagnose the remaining life of photovoltaics, inverters, and transformers.

9. A controllable intelligent photovoltaic management architecture according to claim 4, characterized in that, The edge access platform includes production monitoring, edge device management, smart gateway management, and edge computing management.

10. The controllable intelligent photovoltaic management architecture according to claim 1, characterized in that, The application layer includes an intelligent operation and maintenance module, a management decision-making module, and a business empowerment module; The intelligent operation and maintenance module is used to utilize the data and analysis results provided by the platform layer to perform real-time monitoring, fault warning, fault location and repair suggestions for the equipment; The management decision-making module is used to provide management with business insights and decision support through visualization and data analysis; The business enabling module is used to interconnect with the platform to achieve data sharing and exchange.

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