Construction method of large digital twin reservoir management system

Abstract

The invention provides a large-scale digital twin reservoir management system construction method, which comprises an entity project, an information infrastructure, a digital twin platform and an intelligent application, and is characterized in that the entity project comprises a project dam area, a reservoir area, upstream and downstream influence areas, buildings and electromechanical equipment; the information infrastructure comprises monitoring sensing equipment, a communication network, engineering automation control and an engineering basic environment, the digital twin platform comprises a model base, a knowledge base and a multi-dimensional multi-spatio-temporal data model, and the intelligent application comprises flood control benefit-making intelligent forecast scheduling, engineering safety intelligent analysis and early warning and production operation intelligent comprehensive management. According to the invention, it is ensured that reservoir management personnel can know current water and rain conditions, gates, safety monitoring and video monitoring information of a reservoir in real time, and can also timely predict future reservoir area water level change conditions and dam body safety and stability conditions through model calculation; and a manager is reminded to timely link the PLC system to open the gate for flood discharge.

Description

Technical Field

[0001] This invention relates to the field of digital twin construction technology for large reservoirs, and specifically to a method for constructing a large digital twin reservoir management system. Background Technology

[0002] Against the backdrop of smart water conservancy construction, the construction of digital twin projects is being carried out in an orderly manner through a model of "pilot projects first, key breakthroughs, steady progress, and overall development," promoting high-quality development of water conservancy in the new stage. The overall goal of building digital twin water conservancy projects is to create online virtual objects of physical projects through digital twin-related technologies, focusing on the two key issues of flood control and safety of the projects themselves, and achieving precise mapping, virtual-real interaction, dynamic simulation, and intelligent feedback.

[0003] Based on the above, this invention proposes a method for constructing a large-scale digital twin reservoir management system, which can effectively achieve the aforementioned digital twin project objectives. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention proposes a method for constructing a large-scale digital twin reservoir management system, which solves the problem of exploring and constructing digital twin projects for large reservoirs. The system improves the safety, innovation, and advancement of large-scale reservoir management.

[0005] To solve the above-mentioned technical problems, the present invention is achieved through the following technical solution: A method for constructing a large-scale digital twin reservoir management system includes the construction of a physical engineering project, the construction of a digital twin project, and an intelligent decision support system. The construction of the digital twin project includes the establishment of an information infrastructure, a digital twin platform, and a data processing architecture. The physical works include the construction of buildings and ancillary electromechanical equipment within the project area. The information infrastructure includes a data acquisition and sensing system, a data transmission and access framework, an engineering automation control system, and engineering infrastructure support. The digital twin platform includes a model library to support intelligent simulation, a knowledge base containing a water conservancy knowledge engine, and a multi-dimensional, multi-temporal data model for constructing digital scenarios. The data processing architecture includes data aggregation and data governance steps. The intelligent decision support system integrates and analyzes data from the digital twin project to achieve data-driven real-time optimization, intelligent decision-making, and long-term strategic planning for engineering operations.

[0006] As a preferred technical solution of the present invention, the engineering area includes the engineering dam area, the engineering reservoir area, and the upstream and downstream influence areas of the project.

[0007] As a preferred technical solution of the present invention, the data aggregation step is based on Building Information Modeling (BIM), Geographic Information System (GIS) and oblique photogrammetry to construct a continuous spatial data model covering the sky, ground and underwater, which is used to create an L3 level data base for the engineering area.

[0008] As a preferred technical solution of the present invention, the information infrastructure includes constructing a three-dimensional perception system based on a data acquisition and perception system, building an Internet of Things perception network based on a data transmission and access framework, and monitoring and controlling the engineering process in real time based on an engineering automation control system.

[0009] As a preferred technical solution of the present invention, the model library for supporting intelligent simulation includes a hydrological forecasting and scheduling model, which is used to realize real-time forecasting and scheduling of reservoirs, integrate forecast rainfall results, and extend the forecast period.

[0010] As a preferred technical solution of the present invention, a knowledge graph for reservoir safety monitoring is established through the knowledge base containing the water conservancy knowledge engine, the relationships between monitoring objects are analyzed, and a basic knowledge graph for safety monitoring based on digital twin technology is constructed.

[0011] As a preferred technical solution of the present invention, an AI image recognition system is established through the multidimensional and spatiotemporal data model and knowledge base of the digital twin platform, realizing an end-to-end integrated system of data annotation, algorithm training and application deployment.

[0012] As a preferred technical solution of the present invention, the intelligent decision support system is used for functions such as intelligent forecasting and scheduling for flood control and benefit utilization, intelligent analysis and early warning of engineering safety, intelligent comprehensive management of production and operation, intelligent inspection and supervision of reservoir area, and three-dimensional display and consultation decision-making.

[0013] Compared with the prior art, the present invention has the following advantages and beneficial effects: This invention employs high-precision remote sensing modeling of the large-scale environment surrounding a reservoir, conducts oblique photogrammetry of the dam and reservoir area, performs unmanned surface vessel mapping of the underwater topography, and creates BIM models of the main buildings and equipment. It then seamlessly integrates the remote sensing model, underwater topography, and BIM model using 3D fusion technology to create a Level 3 data base for the project. Furthermore, by combining IoT sensing technology, hydrological forecasting and scheduling models, safety monitoring knowledge graphs, and artificial intelligence technologies, and based on the integration of internal hardware, software, and data, it achieves unified portal integration, completing a digital twin reservoir management system. Attached Figure Description

[0014] Figure 1 This is a schematic diagram of the system technical architecture of the present invention.

[0015] Figure 2This is a schematic diagram of the system network topology of the present invention. Detailed Implementation

[0016] The present invention will now be described in detail with reference to the accompanying drawings and specific embodiments. The illustrative embodiments and descriptions of the present invention are used to explain the present invention, but are not intended to limit the present invention.

[0017] like Figure 1 As shown, this invention specifically discloses a method for constructing a large-scale digital twin reservoir management system. This method includes the construction of a physical engineering project, the construction of a digital twin project, and an intelligent decision support system. The construction of the digital twin project includes the establishment of an information infrastructure, a digital twin platform, and a data processing architecture, wherein: The physical works include the construction of buildings and ancillary electromechanical equipment within the project area. The information infrastructure includes a data acquisition and sensing system, a data transmission and access framework, an engineering automation control system, and engineering infrastructure support. The digital twin platform includes a model library to support intelligent simulation, a knowledge base containing a water conservancy knowledge engine, and a multi-dimensional, multi-temporal data model for constructing digital scenarios. The data processing architecture includes data aggregation and data governance steps. The intelligent decision support system integrates and analyzes data from the digital twin project to achieve data-driven real-time optimization, intelligent decision-making, and long-term strategic planning for engineering operations.

[0018] Figure 2This paper presents a preferred embodiment of the digital twin engineering component of the present invention. In the information infrastructure, the data acquisition and sensing system includes a hydrological and rainfall monitoring subsystem for the hydrological bureau's hydrological and rainfall monitoring station, a drone and unmanned vessel patrol subsystem, a water quality monitoring subsystem for the environmental protection bureau, and a meteorological monitoring subsystem. The data transmission and access framework includes Internet zone 1, government extranet zone 2, and local management network zone 3. The engineering automation control system includes an IP broadcast subsystem, a gate opening telemetry gateway, an IP broadcast subsystem, and an access control subsystem. The output terminals of the water and rainfall monitoring stations connected to Internet Zone 1 are respectively connected to the hydrological bureau's water and rainfall subsystem and the environmental protection bureau's water quality monitoring subsystem connected to the government extranet 2. The output terminals of the drone / unmanned vessel and gate opening telemetry gateway connected to Internet Zone 1 are respectively connected to the safety monitoring subsystem and video surveillance subsystem connected to the local management network 3. The output terminals of the water and rainfall subsystem, water quality monitoring subsystem, and meteorological monitoring subsystem connected to the government extranet 2 are respectively connected to the digital twin reservoir management system. The video surveillance subsystem connected to the local management network 3 is also directly connected to the water resources bureau's video aggregation platform connected to the government extranet 2 via a dedicated video line. The IP broadcasting subsystem and access control subsystem connected to the local management zone 3 are connected to the digital twin reservoir management system contained in the digital twin platform connected to the government extranet 2.

[0019] Furthermore, the digital twin reservoir management system is deployed on the government extranet 2 cloud. The video signal is transmitted to the water resources bureau's video aggregation platform through the 200M video dedicated line, and then transmitted to the digital twin system's cloud database and the project management personnel's mobile terminal.

[0020] Furthermore, the gate opening telemetry gateway and the UAV / unmanned vessel patrol subsystem in Internet Zone 1 are all connected to the government extranet 2 and the local management network 3 through firewalls for network security settings; the government extranet 2 and the local management network 3 are interconnected through a dedicated fiber optic line to ensure the overall security of the digital twin reservoir management system.

[0021] Its working process: The buildings and auxiliary electromechanical equipment installed in the project area, such as water and rainfall monitoring stations, gate opening telemetry gateways, drones and unmanned boats, and video surveillance, serve as components of the information infrastructure. They collect real-time work data about the project area and transmit the data to the digital twin reservoir management system located in the government extranet area 2 via wireless / wired means. The digital twin system analyzes and processes different data in modules such as safety monitoring, flood forecasting, and operation and maintenance management according to different data types. The processed data is displayed in real-time on the large screen in the central computer room of the local management network 3 through a 3D scene, enabling managers to monitor the safety of the reservoir site in real time, realize real-time operation optimization based on data, and become an intelligent decision support system with intelligent decision-making and long-term strategic planning functions.

[0022] Unless otherwise specified, the technical features of the water and rainfall monitoring equipment, safety monitoring equipment, video surveillance, etc. (the constituent units / elements of this invention) described in this invention are obtained from conventional commercial channels or manufactured by conventional methods. Their specific structures, working principles, and possible control methods and spatial arrangements can adopt conventional choices in the field and should not be regarded as the innovation points of this invention. This is understandable to those skilled in the art, and this invention patent will not be further elaborated in detail.

[0023] The technical solutions disclosed in the embodiments of the present invention have been described in detail above. Specific embodiments have been used to illustrate the principles and implementation methods of the embodiments of the present invention. The description of the above embodiments is only for helping to understand the principles of the embodiments of the present invention. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the embodiments of the present invention. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A method for constructing a large-scale digital twin reservoir management system, characterized in that, This construction method includes the construction of physical engineering projects and the construction of digital twin projects. The construction of digital twin projects includes the establishment of information infrastructure, digital twin platforms, and data processing architectures, wherein: The construction of the physical project includes the construction of buildings and ancillary electromechanical equipment within the project area. The information infrastructure includes a data acquisition and sensing system, a data transmission and access framework, an engineering automation control system, and an engineering basic environment. The digital twin platform includes a model library to support intelligent simulation, a knowledge base containing a water conservancy knowledge engine, and a multi-dimensional, multi-temporal data model for constructing digital scenarios. The data processing architecture includes data aggregation and data governance steps. The construction method integrates and analyzes data from the digital twin project through an intelligent decision support system, enabling data-driven real-time optimization, intelligent decision-making, and long-term strategic planning for project operations.

2. The method for constructing a large-scale digital twin reservoir management system according to claim 1, characterized in that, The project area includes the dam area, the reservoir area, and the upstream and downstream impact areas.

3. The method for constructing a large-scale digital twin reservoir management system according to claim 1, characterized in that, The data aggregation step is based on Building Information Modeling (BIM), Geographic Information System (GIS) and oblique photogrammetry to construct a continuous spatial data model covering the sky, ground and underwater, which is used to create an L3 level data base for the engineering area.

4. The method for constructing a large-scale digital twin reservoir management system according to claim 1, characterized in that, The information infrastructure includes a three-dimensional sensing system built on a data acquisition and sensing system, an Internet of Things sensing network built on a data transmission and access framework, and real-time monitoring and control of the engineering process based on an engineering automation control system.

5. The method for constructing a large-scale digital twin reservoir management system according to claim 1, characterized in that, The model library used to support intelligent simulation includes a hydrological forecasting and scheduling model, which is used to realize real-time forecasting and scheduling of reservoirs, integrate forecast rainfall results, and extend the forecast period.

6. The method for constructing a large-scale digital twin reservoir management system according to claim 1, characterized in that, By using the knowledge base containing the water conservancy knowledge engine, a knowledge graph for reservoir safety monitoring is established, the relationships between monitoring objects are analyzed, and a basic knowledge graph for safety monitoring based on digital twin technology is constructed.

7. The method for constructing a large-scale digital twin reservoir management system according to claim 1, characterized in that, By leveraging the multidimensional, multi-temporal data models and knowledge base of the digital twin platform, an AI image recognition system is established, realizing an end-to-end integrated system encompassing data annotation, algorithm training, and application deployment.

8. The method for constructing a large-scale digital twin reservoir management system according to claim 1, characterized in that, The intelligent decision support system is used for intelligent forecasting and scheduling of flood control and water conservancy, intelligent analysis and early warning of engineering safety, intelligent comprehensive management of production and operation, intelligent inspection and supervision of reservoir area, and three-dimensional display and consultation decision-making.

Images