CN113221456A - Digital twin modeling and multi-agent coordination control method for smart microgrid - Google Patents
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Abstract
The invention discloses a digital twin modeling and multi-agent coordination control method of a smart microgrid, and relates to the technical field of digital twin. Researching intelligent microgrid modeling simulation and operation control by using digital twin and multi-agent technologies, and designing a multi-communication-protocol interactive intelligent microgrid digital twin and multi-agent control architecture; and (4) in consideration of physical space, digital space and coupling relation, carrying out task decomposition on the full life cycle management process of the smart micro-grid, and constructing a regulation resource intelligent agent, a regulation process intelligent agent and a regulation service intelligent agent.
Description
Technical Field
The invention relates to the technical field of digital twinning, in particular to a digital twinning modeling and multi-agent coordination control method of a smart micro-grid.
Background
In recent years, with the wide application of emerging hot spot technologies such as cloud computing, artificial intelligence and big data, the digitization degree of the energy industry is higher and higher. How to monitor and utilize massive panoramic information obtained from physical equipment, such as load, weather, electric heat energy flow, equipment operation and the like, brings new challenges to the operation management of the intelligent energy system. With the increasing of panoramic information such as loads, weather, equipment, electricity/gas/heat multi-energy flows and the like in the operation of a power system, the traditional power system modeling simulation technology is difficult to adapt to the requirement of the operation control of a future intelligent energy system, and the technical problem can be effectively solved by combining machine learning, a communication network, high-performance analysis and calculation and a digital twin technology of the Internet of things.
The digital twin technology provides a feasible technical path for complexity and flexibility of the intelligent microgrid operation regulation and control system, however, how to construct an intelligent management and control platform and uniformly and integrally manage the original distributed energy resources still remains a great challenge. In the intelligent control process, essential differences still exist in the aspects of digital model construction, simulation, operation mode and driving mechanism of required test objects such as resources, processes, services and the like. The France Dacable company utilizes experimental data of fluid mechanics and aerodynamics to construct a power equipment simulation platform based on a digital twin, and a virtual mirror image model is applied to improve an actual product. The Flowenexa laboratory utilizes Flowenex software to construct a digital twin simulation model of the thermal power plant, and provides reference for manufacturing and maintaining the thermal power plant. The energy Internet research institute of Qinghua university constructs a simulation model based on digital twins in order to reduce the operation and maintenance cost of a comprehensive energy system. The literature discusses a multi-mode data analysis and acquisition strategy, and a power module and a database module are combined to enable a digital twin to have the capability of state perception. The literature introduces a key technology of the application of the digital twin in an information physical system, and discusses a specific implementation method of the digital twin in the full life cycle management of a product. The literature also discusses the specific application of the digital twin in the layered architecture of the energy system, and analyzes the interaction mechanism of the physical layer and the digital layer.
Accordingly, those skilled in the art have endeavored to develop a digital twin modeling and multi-agent coordination control method of a smart microgrid. Providing a digital twin-driven intelligent micro-grid multi-agent control architecture, and constructing a twin agent model component; and performing task decomposition on the full life cycle management process of the smart micro-grid, and constructing a regulation and control resource agent, a regulation and control process agent and a regulation and control service agent.
Disclosure of Invention
In view of the above defects in the prior art, the technical problem to be solved by the invention is to design and consider a digital twin and multi-agent control architecture of a smart microgrid with multiple communication protocol interaction aiming at the basic definition and application scenes of digital twin technology in different fields at home and abroad; and (4) in consideration of physical space, digital space and coupling relation, carrying out task decomposition on the full life cycle management process of the smart micro-grid, and constructing a regulation resource intelligent agent, a regulation process intelligent agent and a regulation service intelligent agent.
In order to achieve the purpose, the invention provides a digital twin modeling and multi-agent coordination control method of a smart micro-grid, which comprises the following steps:
step 1, designing a multi-communication-protocol interactive intelligent microgrid digital twin and multi-agent control architecture;
and 2, taking physical space, digital space and coupling relation into consideration, performing task decomposition on the full life cycle management process of the smart micro-grid, and constructing a regulation resource intelligent agent, a regulation process intelligent agent and a regulation service intelligent agent.
Further, the step 1 comprises the following steps:
step 1.1, panoramic information generated by a test entity is input into a database management module and a workstation through a data chain, local digital and physical twins are constructed, an optimization result obtained by simulation operation is input into the test entity to control equipment, and the running state of actual equipment can also be fed back to improve and optimize the twins;
and step 1.2, providing references for regulation and control operation, comprehensive evaluation, intelligent operation and maintenance and fault recovery of a micro-grid test entity by adopting machine learning and information physical system technology.
Further, the panoramic information comprises equipment state, network rack topology, line parameters, electric data, gas data, heat energy flow data, meteorological data and user historical data.
Further, the step 1.1 is to adopt different communication protocols when the sensor on the "source-load-store" element performs data chain transmission for different physical devices and application scenarios.
Further, the communication protocol includes a UDP protocol, an Open charge point protocol (OCPP protocol), and an OpenADR protocol (Open automatic demand response protocol).
Furthermore, the resource intelligent regulation and control body comprises a modeling function of various distributed energy sources, and digital modeling is carried out on various distributed energy sources through resource analysis, so that the dimensionality and precision of modeling and simulation of the physical twins and the digital twins are ensured.
Furthermore, the intelligent regulation and control process body comprises an operation control function of the energy router, and ensures multi-time scale coordination and multi-source data coupling of digital and physical twin body modeling through process analysis and process realization.
Furthermore, the intelligent regulation and control service agent comprises various visual environments, process management, data storage and prediction functions, and accurate prediction and optimization of digital and physical twin body modeling and simulation are ensured through service analysis and service realization.
Further, in the step 2, the regulation and control resource agent, the regulation and control process agent and the regulation and control service agent are dynamically and interactively fused through a multi-agent management system, so that the task decomposition and the intelligentization of the digital twin task are realized.
Further, the regulation and control resource agent, the regulation and control process agent and the regulation and control service agent can be further subdivided into child agents and grandchild agents step by step according to task needs.
In a preferred embodiment of the present invention, the present invention proposes a multi-communication protocol interactive intelligent microgrid digital twin and multi-agent control architecture. Panoramic information such as equipment state, network frame topology, line parameters, electricity, gas, heat energy flow, meteorological data, user historical data and the like generated by a test entity are input into a database management module and a workstation through a data chain to construct a local digital and physical twin body, an optimization result obtained by simulation operation is input into the test entity to control the equipment, and the running state of actual equipment can be fed back to improve and optimize the twin body; secondly, for different physical devices and application scenarios, when a sensor on a "source-load-store" element performs data link transmission, different communication protocols such as UDP, OCPP, OpenADR and the like are adopted, wherein the UDP is suitable for real-time control of distributed energy, and the Open charge protocol (Open charge protocol) protocol and the OpenADR protocol (Open automatic demand response) protocol are Open charge protocols for new energy electric vehicles; and finally, a machine learning and information physical system technology is adopted to provide references for the regulation and control operation, comprehensive evaluation, intelligent operation and maintenance, fault recovery and the like of a micro-grid test entity.
And (4) in consideration of physical space, digital space and coupling relation, carrying out task decomposition on the full life cycle management process of the smart micro-grid, and constructing a regulation resource intelligent agent, a regulation process intelligent agent and a regulation service intelligent agent. The resource intelligent agent comprises modeling functions of various distributed energy sources, digital modeling is carried out on the various distributed energy sources through resource analysis, and dimensionality and precision of modeling and simulation of physical twins and digital twins are guaranteed; the intelligent regulation and control process body comprises an operation control function of the energy router, and ensures multi-time scale coordination and multi-source data coupling of digital and physical twin body modeling through process analysis and process realization; the intelligent regulation and control service body comprises various visual environments, process management, data storage and prediction and other functions, and accurate prediction and optimization of digital and physical twin body modeling and simulation are ensured through service analysis and service realization. And finally, dynamically and interactively fusing the three through a multi-agent management system to realize task decomposition and intellectualization of a digital twin task. Meanwhile, each agent can be further subdivided into child agents and grandchild agents step by step according to task requirements.
Compared with the prior art, the invention has the following obvious substantive characteristics and obvious advantages:
1. a digital twin-driven intelligent micro-grid multi-agent control framework is provided, and a twin agent model component is constructed.
2. And performing task decomposition on the full life cycle management process of the smart micro-grid, and constructing a regulation and control resource agent, a regulation and control process agent and a regulation and control service agent.
The conception, the specific structure and the technical effects of the present invention will be further described with reference to the accompanying drawings to fully understand the objects, the features and the effects of the present invention.
Drawings
FIG. 1 is a diagram of a multi-communication protocol interactive intelligent microgrid digital twin and multi-agent control architecture in accordance with a preferred embodiment of the present invention;
FIG. 2 is a multi-agent system operating mechanism in a task decomposition paradigm in accordance with a preferred embodiment of the present invention.
Detailed Description
The technical contents of the preferred embodiments of the present invention will be more clearly and easily understood by referring to the drawings attached to the specification. The present invention may be embodied in many different forms of embodiments and the scope of the invention is not limited to the embodiments set forth herein.
In the drawings, structurally identical elements are represented by like reference numerals, and structurally or functionally similar elements are represented by like reference numerals throughout the several views. The size and thickness of each component shown in the drawings are arbitrarily illustrated, and the present invention is not limited to the size and thickness of each component. The thickness of the components may be exaggerated where appropriate in the figures to improve clarity.
The invention relates to a digital twin construction mode and a multi-agent coordination control scheme for an intelligent energy system. The intelligent microgrid multi-agent control architecture based on digital twin driving is provided by utilizing digital twin and multi-agent technologies to carry out research on modeling simulation and operation control of the intelligent microgrid. And (4) constructing a twin intelligent agent model component by considering the physical space, the digital space and the coupling relation.
As shown in fig. 1, a smart microgrid digital twin and multi-agent control architecture considering multi-communication protocol interaction is proposed. Panoramic information such as equipment state, network frame topology, line parameters, electricity, gas, heat energy flow, meteorological data, user historical data and the like generated by a test entity are input into a database management module and a workstation through a data chain to construct a local digital and physical twin body, an optimization result obtained by simulation operation is input into the test entity to control the equipment, and the running state of actual equipment can be fed back to improve and optimize the twin body; secondly, for different physical devices and application scenarios, when a sensor on a "source-load-store" element performs data link transmission, different communication protocols such as UDP, OCPP, OpenADR and the like are adopted, wherein the UDP is suitable for real-time control of distributed energy, and the Open charge protocol (Open charge protocol) protocol and the OpenADR protocol (Open automatic demand response) protocol are Open charge protocols for new energy electric vehicles; and finally, a machine learning and information physical system technology is adopted to provide references for the regulation and control operation, comprehensive evaluation, intelligent operation and maintenance, fault recovery and the like of a micro-grid test entity.
In consideration of the physical space, the digital space and the coupling relation, the task decomposition is carried out on the full life cycle management process of the smart micro-grid, and a regulation resource agent, a regulation process agent and a regulation service agent are constructed, as shown in fig. 2. The resource intelligent agent comprises modeling functions of various distributed energy sources, digital modeling is carried out on the various distributed energy sources through resource analysis, and dimensionality and precision of modeling and simulation of physical twins and digital twins are guaranteed; the intelligent regulation and control process body comprises an operation control function of the energy router, and ensures multi-time scale coordination and multi-source data coupling of digital and physical twin body modeling through process analysis and process realization; the intelligent regulation and control service body comprises various visual environments, process management, data storage and prediction and other functions, and accurate prediction and optimization of digital and physical twin body modeling and simulation are ensured through service analysis and service realization. And finally, dynamically and interactively fusing the three through a multi-agent management system to realize task decomposition and intellectualization of a digital twin task. Meanwhile, each agent can be further subdivided into child agents and grandchild agents step by step according to task requirements.
The invention provides a digital twin modeling and multi-agent coordination optimization control strategy oriented to a smart micro-grid. Firstly, aiming at the basic definition and application scenes of digital twin technology in different fields at home and abroad, a digital twin construction mode and a future development idea for an intelligent energy system are determined, and a digital twin and multi-agent control architecture of an intelligent microgrid considering multi-communication protocol interaction is designed; secondly, in consideration of physical space, digital space and coupling relation, performing task decomposition on the full life cycle management process of the smart micro-grid, and constructing a regulation resource intelligent agent, a regulation process intelligent agent and a regulation service intelligent agent; then, constructing digital and physical twins of the system, updating a database management module by utilizing distributed elements acquired by a sensor and various twins of the surrounding environment, and performing combined power prediction and multi-objective optimization decision; and finally, constructing an Opal-RT semi-physical simulation platform-based smart micro-grid test model, and verifying the provided control strategy in 2 working scenes of micro-grid synchronization and isolated island by using UDP (User Datagram Protocol) communication Protocol real-time perception test data.
The foregoing detailed description of the preferred embodiments of the invention has been presented. It should be understood that numerous modifications and variations could be devised by those skilled in the art in light of the present teachings without departing from the inventive concepts. Therefore, the technical solutions available to those skilled in the art through logic analysis, reasoning and limited experiments based on the prior art according to the concept of the present invention should be within the scope of protection defined by the claims.
Claims (10)
1. A digital twin modeling and multi-agent coordination control method of a smart micro-grid is characterized by comprising the following steps:
step 1, designing a multi-communication-protocol interactive intelligent microgrid digital twin and multi-agent control architecture;
and 2, taking physical space, digital space and coupling relation into consideration, performing task decomposition on the full life cycle management process of the smart micro-grid, and constructing a regulation resource intelligent agent, a regulation process intelligent agent and a regulation service intelligent agent.
2. The digital twin modeling and multi-agent coordination control method of smart microgrid according to claim 1, characterized in that said step 1 includes the steps of:
step 1.1, panoramic information generated by a test entity is input into a database management module and a workstation through a data chain, local digital and physical twins are constructed, an optimization result obtained by simulation operation is input into the test entity to control equipment, and the running state of actual equipment can also be fed back to improve and optimize the twins;
and step 1.2, providing references for regulation and control operation, comprehensive evaluation, intelligent operation and maintenance and fault recovery of a micro-grid test entity by adopting machine learning and information physical system technology.
3. The method of digital twin modeling and multi-agent coordinated control of a smart microgrid of claim 2 wherein said panoramic information includes device status, rack topology, line parameters, electrical data, gas data, thermal multi-energy flow data, meteorological data, user historical data.
4. The method for digital twin modeling and multi-agent coordination control of a smart microgrid according to claim 2, characterized in that said step 1.1 employs different communication protocols for sensors on "source-load-store" elements in data chain transmission for different physical devices and application scenarios.
5. The method according to claim 4, wherein the communication protocol includes a UDP protocol, an OCPP protocol (Open charge point protocol) and an OpenADR protocol (Open automated demand response protocol).
6. The method as claimed in claim 1, wherein the resource-regulating agent comprises modeling functions of various distributed energy sources, and the physical and digital twin modeling and simulation dimensions and precision are ensured by performing digital modeling on various distributed energy sources through resource analysis.
7. The method as claimed in claim 1, wherein the controlling process agent comprises an operation control function of an energy router, and ensures multi-time scale coordination and multi-source data coupling of digital and physical twin modeling through process analysis and process implementation.
8. The method as claimed in claim 1, wherein the intelligent agent for controlling coordination of the intelligent micro-grid comprises various visual environments, process management, data storage and prediction functions, and accurate prediction and optimization of digital and physical twin modeling and simulation are ensured through service analysis and service implementation.
9. The method for digital twin modeling and multi-agent coordination control of a smart microgrid according to claim 1, wherein step 2 is implemented by a multi-agent management system to dynamically and interactively fuse the regulation resource agent, the regulation process agent and the regulation service agent, so as to realize task decomposition and intelligentization of digital twin tasks.
10. The method of claim 1, wherein the regulatory resource agent, the regulatory process agent and the regulatory service agent are further subdivided into child agents and grandchild agents according to task requirements.
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