Information physical system based on Boosting enhanced integration

Abstract

The invention discloses an information physical system based on Boosting enhanced integration. The information physical system comprises a heat supply system service platform, a data acquisition module, a model construction module and a system evaluation optimization module, the heat supply system service platform comprises micro-grid combination optimization modeling, the micro-grid combination optimization modeling takes important load heat supply recovery capability as a target and provides a standby heat supply path for the heat supply system, and the data acquisition module performs data acquisition based on an Internet of Things sensor arranged by the system and transmits the acquired data to the micro-grid combination optimization modeling. The data acquisition module is used for acquiring real-time data and historical data and uploading the real-time data and the historical data to a heat supply system service platform for data processing and fusion, and the model construction module is used for generating learning samples for the acquired real-time data and historical data based on NATAF transformation. According to the system, a Boosting enhanced integration algorithm is used as a foundation architecture, a coping strategy is provided for the nonlinear characteristic, the large time delay phenomenon and the strong coupling problem in the heat supply system, mutual coordination operation is achieved through the Internet of Things communication mode, real-time sensing, dynamic adjustment and information service of the system are achieved, the indoor environment comfort degree is improved, and the energy utilization efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the field of heating technology, and in particular to a cyber-physical system based on Boosting enhanced integration. Background Art

[0002] With the development of energy internet, the construction of communication infrastructure in integrated energy systems has been continuously improved, and information networks have become increasingly complex, making integrated energy systems evolve into typical cyber-physical systems. In the Integrated Energy Cyber-Physical System (IECPS), there is not only the coupling of multiple energy forms such as electricity, gas, and heat, but also the coupling of energy networks and information networks.

[0003] Any problem in any link of the closed-loop process of state perception, data transmission, optimized decision-making, and command execution in the information network will have an adverse impact on the safe and stable operation of the energy network; at the same time, there are nonlinear characteristics, large time lags, and strong coupling problems in the heating system. Summary of the invention

[0004] The purpose of the present invention is to provide an information-physical system based on Boosting enhanced integration to solve the problems raised in the above background technology.

[0005] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: an information-physical system based on Boosting enhanced integration, including a heating system service platform, a data acquisition module, a model building module and a system evaluation and optimization module; the heating system service platform includes a microgrid combination optimization modeling, the microgrid combination optimization modeling takes the important load heating recovery capacity as a goal, and provides a backup heating path for the heating system, the data acquisition module performs data acquisition based on the Internet of Things sensors set by the system, and uploads the data to the heating system service platform for data processing and fusion, the model building module is used to generate learning samples for the collected real-time data and historical data based on NATAF transformation, expand the original samples to all feasible spaces considering the correlation of variables, and design a two-layer feedforward deep neural network based on the Boosting perceptron principle, adjust the weights of the deep neural network through the hierarchical iterative traversal of neurons, and use a cross-voting mechanism to upgrade the binary perception learning to multi-classification learning, and construct a heating evaluation model, the system evaluation and optimization module optimizes the operating parameters based on the operating effects of the microgrid combination optimization modeling and the heating evaluation model, and guides the heating system to operate in a stable and efficient range through online analysis to achieve operating condition adaptation.

[0006] Preferably, the heating system service platform also includes modeling the mechanism of the heating system, generating a corresponding digital simulation model in a virtual space, and forming a virtual-reality mapping with the real system.

[0007] Preferably, the digital simulation model: based on the operating principle of the heating system, combines the laws of thermodynamics, mass, momentum and energy conservation laws of fluid mechanics to analyze the functional characteristics, structural characteristics and operating characteristics of the heating system, and determines the subsystem set, structural characteristics and operating parameters of the heating system;

[0008] Based on the actual structural design of the heating system and the analysis of the physical object entities, a digital simulation model of the heating system is generated in the virtual space through mechanism modeling, and communication between the virtual space and the physical entity is established to form a virtual-reality mapping between the virtual space and the system entity, and create a jet pump heating system service platform.

[0009] Preferably, the data acquisition module at least includes the acquisition of heat metering data, supply and return water pressure difference, water supply flow rate and circulation flow rate data.

[0010] Preferably, the data material module includes a data processing unit, which is used to process the collected real-time data and historical data, remove redundant data, integrate heterogeneous data, classify and store the data information, and then upload it to the jet pump heating system service platform through the communication network.

[0011] Preferably, the heating system service platform is functionally divided into a perception layer, a transmission layer and an internet layer. By establishing a communication channel model for energy station operation data in an energy network and an interface model connecting the perception layer and the internet layer, a transmission layer model describing the data transmission process is established.

[0012] Preferably, based on the digital simulation model of the heating system, a circulation flow evaluation model of the insulation system is established using real-time simulation and process data. The circulation flow evaluation model is used to select and match the heating system equipment and to regulate and control the operation of the heating system equipment.

[0013] Preferably, the digital simulation model includes a structural model, a physical model, a behavioral model and a rule model, and the learning algorithm of the digital simulation model includes a neural network algorithm.

[0014] Compared with the prior art, the present invention has the following beneficial effects:

[0015] With the Boosting enhanced integration algorithm as the fundamental architecture, countermeasures are proposed for the nonlinear characteristics, large time lag and strong coupling problems in the heating system. Through the Internet of Things communication method, the system's real-time perception, dynamic adjustment and information services are realized, thereby improving the comfort of the indoor environment and enhancing energy efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a schematic diagram of the structure of the present invention. DETAILED DESCRIPTION

[0017] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0018] See also Figure 1 The present invention provides a technical solution: an information-physical system based on Boosting enhanced integration, including a heating system service platform, a data acquisition module, a model building module and a system evaluation and optimization module; the heating system service platform includes a microgrid combination optimization modeling, the microgrid combination optimization modeling takes the important load heating recovery capacity as a goal, and provides a backup heating path for the heating system, the data acquisition module performs data acquisition based on the Internet of Things sensors set by the system, and uploads the data to the heating system service platform for data processing and fusion, the model building module is used to generate learning samples for the collected real-time data and historical data based on NATAF transformation, expand the original samples to all feasible spaces considering the correlation of variables, and design a two-layer feedforward deep neural network based on the Boosting perceptron principle, adjust the weights of the deep neural network through the hierarchical iterative traversal of neurons, and use a cross-voting mechanism to upgrade the binary perception learning to multi-classification learning, and construct a heating evaluation model. The system evaluation and optimization module optimizes the operating parameters based on the operating effects of the microgrid combination optimization modeling and the heating evaluation model, and guides the heating system to operate in a stable and efficient range through online analysis to achieve operating condition adaptation.

[0019] In the present invention, the heating system service platform also includes modeling the mechanism of the heating system, generating a corresponding digital simulation model in a virtual space, and forming a virtual-reality mapping with the real system.

[0020] In the present invention, the digital simulation model: based on the operating principle of the heating system, combined with the laws of thermodynamics, mass, momentum and energy conservation laws of fluid mechanics, analyzes the functional characteristics, structural characteristics and operating characteristics of the heating system, and determines the subsystem set, structural characteristics and operating parameters of the heating system;

[0021] Based on the actual structural design of the heating system and the analysis of the physical object entities, a digital simulation model of the heating system is generated in the virtual space through mechanism modeling, and communication between the virtual space and the physical entity is established to form a virtual-reality mapping between the virtual space and the system entity, and create a jet pump heating system service platform.

[0022] In the present invention, the data acquisition module at least includes the acquisition of heat metering data, supply and return water pressure difference, water supply flow rate and circulation flow rate data.

[0023] In the present invention, the data material module includes a data processing unit, which is used to process the collected real-time data and historical data, remove redundant data, integrate heterogeneous data, classify and store the data information, and then upload it to the jet pump heating system service platform through the communication network.

[0024] In the present invention, the heating system service platform is functionally divided into a perception layer, a transmission layer and an internet layer. By establishing a communication channel model for energy station operation data in an energy network and an interface model connecting the perception layer and the internet layer, a transmission layer model describing the data transmission process is established.

[0025] In the present invention, based on the digital simulation model of the heating system, a circulation flow evaluation model of the insulation system is established using real-time simulation and process data. The circulation flow evaluation model is used to select and match the heating system equipment and regulate and control the operation of the heating system equipment.

[0026] In the present invention, the digital simulation model includes a structural model, a physical model, a behavioral model and a rule model, and the learning algorithm of the digital simulation model includes a neural network algorithm.

[0027] The present invention: takes the important load heating recovery capacity as the goal through microgrid combination optimization modeling, and provides a backup heating path for the heating system, collects data based on the Internet of Things sensors set up in the system, and uploads it to the heating system service platform for data processing and fusion, generates learning samples based on NATAF transformation for the collected real-time data and historical data, expands the original samples to all feasible spaces considering variable correlation, and designs a two-layer feedforward deep neural network based on the Boosting perceptron principle, adjusts the weights of the deep neural network through hierarchical iterative traversal of neurons, and upgrades the binary perception learning to multi-classification learning by using a cross-voting mechanism, constructs a heating evaluation model, optimizes the operating parameters based on the operating effects of the microgrid combination optimization modeling and the heating evaluation model, and guides the heating system to operate in a stable and efficient range through online analysis, so as to achieve self-adaptation of operating conditions; the present invention takes the Boosting enhanced integrated algorithm as the fundamental architecture, integrates the deep neural network algorithm system, proposes coping strategies for the nonlinear characteristics, large time lag phenomena and strong coupling problems in the heating system, and successfully provides a solution that meets the needs.

[0028] The contents not described in detail in this specification belong to the prior art known to professional and technical personnel in the field. Although the embodiments of the present invention have been shown and described, it is understood by ordinary technicians in the field that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principle and spirit of the present invention. The scope of the present invention is defined by the attached claims and their equivalents.

Claims

1. A cyber-physical system based on boosting enhancement integration, characterized by: It includes a heating system service platform, a data acquisition module, a model building module and a system evaluation and optimization module; the heating system service platform includes a microgrid combination optimization modeling, which takes the important load heating recovery capacity as a goal and provides a backup heating path for the heating system. The data acquisition module collects data based on the Internet of Things sensors set up by the system, and uploads it to the heating system service platform for data processing and fusion. The model building module is used to generate learning samples for the collected real-time data and historical data based on NATAF transformation, expand the original samples to all feasible spaces considering variable correlation, and design a two-layer feedforward deep neural network based on the Boosting perceptron principle. The weights of the deep neural network are adjusted through hierarchical iterative traversal of neurons, and the cross-voting mechanism is used to upgrade the binary perception learning to multi-classification learning to build a heating evaluation model. The system evaluation and optimization module optimizes the operating parameters based on the operating effects of the microgrid combination optimization modeling and the heating evaluation model, and guides the heating system to operate in a stable and efficient range through online analysis to achieve operating condition adaptation.

2. The information-physical system based on Boosting enhanced integration according to claim 1, characterized in that: The heating system service platform also includes modeling the mechanism of the heating system, generating a corresponding digital simulation model in a virtual space, and forming a virtual-reality mapping with the real system.

3. The information-physical system based on Boosting enhanced integration according to claim 2, characterized in that: The digital simulation model: based on the operating principle of the heating system, combined with the laws of thermodynamics, mass, momentum and energy conservation in fluid mechanics, analyzes the functional characteristics, structural characteristics and operating characteristics of the heating system, and determines the subsystem set, structural characteristics and operating parameters of the heating system; Based on the actual structural design of the heating system and the analysis of the physical object entities, a digital simulation model of the heating system is generated in the virtual space through mechanism modeling, and communication between the virtual space and the physical entity is established to form a virtual-reality mapping between the virtual space and the system entity, and create a jet pump heating system service platform.

4. The information-physical system based on Boosting enhanced integration according to claim 1, characterized in that: The data acquisition module at least includes the acquisition of heat metering data, supply and return water pressure difference, water supply flow rate and circulation flow rate data.

5. The information-physical system based on Boosting enhanced integration according to claim 1, characterized in that: The data material module includes a data processing unit, which is used to process the collected real-time data and historical data, remove redundant data, integrate heterogeneous data, classify and store the data information, and upload it to the jet pump heating system service platform through the communication network.

6. The information-physical system based on Boosting enhanced integration according to claim 1, characterized in that: The heating system service platform is functionally divided into a perception layer, a transmission layer and an internet layer. By establishing a communication channel model for energy station operation data in an energy network and an interface model connecting the perception layer and the internet layer, a transmission layer model describing the data transmission process is established.

7. The information-physical system based on Boosting enhanced integration according to claim 2, characterized in that: Based on the digital simulation model of the heating system, a circulation flow evaluation model for the insulation system is established using real-time simulation and process data. The circulation flow evaluation model is used to select and match the heating system equipment and to regulate and control the operation of the heating system equipment.

8. The information-physical system based on Boosting enhanced integration according to claim 2, characterized in that: The digital simulation model includes a structural model, a physical model, a behavioral model and a rule model, and the learning algorithm of the digital simulation model includes a neural network algorithm.

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