WO2013091569A1

WO2013091569A1 - Smart energy network control method

Info

Publication number: WO2013091569A1
Application number: PCT/CN2012/087149
Authority: WO
Inventors: 甘中学; 宋臣; 冯程程; 郑鹏
Original assignee: 新奥科技发展有限公司
Priority date: 2011-12-23
Filing date: 2012-12-21
Publication date: 2013-06-27
Also published as: CN103177298A

Abstract

A smart energy network control method, comprising: acquiring field device information via a plurality of intelligent terminals, uploading progressively, receiving upper layer optimization and control information, controlling the field device, so that the smart energy flow (information flow, material flow and energy flow) information between respective smart energy devices is transmitted and realized according to a smart energy network transmission control protocol. Furthermore, the field device generates corresponding feedback information while executing an upper layer optimization policy; the feedback information is uploaded progressively to realize the evolution of the mutual-inducting layer, mutual-acting layer and mutual-intellectualizing layer of the smart energy network. The smart energy network control method of the present invention based on a smart energy gateway optimizes field device operation information, generates an optimization and control policy, and converts the disordered smart energy flow into an ordered one, thus achieving energy efficiency gain and collective intelligent evolution of the smart energy network.

Description

Ubiquitous network control method

The invention belongs to the field of ubiquitous energy networks, and in particular relates to a ubiquitous energy network control method based on a ubiquitous network management system. Background technique

The ubiquitous energy network is a smart energy network system that integrates information, energy and matter through synergistic coupling. The ubiquitous energy network technology is an intelligent collaborative technology that couples information networks, energy networks and physical networks into the same network, and maximizes the networked relationship between machine and machine interaction, human-computer interaction and mutual intelligence. The technology realizes the high-efficiency of energy by seamlessly connecting energy space, information space and material space through energy efficiency matching system, intelligent interactive control center and intelligent cloud service platform.

A multi-energy (multiple types of energy and energy) is disclosed in Chinese Patent Application No. 201010173519.1 (inventive name: "Energy-optimized utilization of ubiquitous energy network and methods for providing energy transactions and services") / or the use of energy from multiple geographic locations), the implementation of distributed energy management and decision-making, and the ubiquitous energy network for energy efficiency optimization throughout the entire process of energy use.

The ubiquitous energy network includes nodes connected together by a virtual pipe interconnection network architecture that transmits ubiquitous energy flows, and ubiquitous energy flows are transmitted bidirectionally between nodes. The node includes at least one of a system energy efficiency controller, and other nodes connected to the system energy efficiency controller, an energy production device, an energy storage device, an energy application device, and an energy regeneration device. Wherein, the system energy efficiency controller controls the input and output of the ubiquitous energy flow of at least one of the other nodes, the energy production device, the energy storage device, the energy application device, and the energy regeneration device.

The ubiquitous energy flow is a logical intelligent flow formed by the synergistic coupling of energy flow, material flow and information flow. The energy flow includes different secondary energy forms such as electricity, gas, and heat. Material flows include water, logistics, transportation, transportation, and the like. Information flow includes communication, control, data acquisition and transmission. Panergy The flow forms a closed-loop ubiquitous energy network system through the connection of the energy efficiency gainer, the energy efficiency controller, and the four phases of the energy life cycle (energy production, energy application, energy storage and transportation, energy regeneration).

A gateway, also known as a protocol converter, is an inter-network connector that translates high-level protocols, including the transport layer and higher. A gateway can connect multiple computer networks with different network architectures, such as interconnections between LANs, interconnections between LANs and WANs, and interconnections between two different WANs.

A ubiquitous gateway is a device that interacts with each other in the ubiquitous energy flow (energy flow, material flow, information flow) and controls the flow path of each component. For information exchange, material exchange, and energy exchange between energy systems, the ubiquitous gateway has the function of a conversion protocol to meet the needs of the intended energy system. At the same time as the conversion protocol, the ubiquitous gateway automatically selects and sets the route, selecting the optimal flow path for each component of the ubiquitous energy flow.

At present, the technology close to the ubiquitous energy network is the Internet and the Internet of Things technology. The technology close to the ubiquitous gateway is the Internet gateway and the Internet of Things gateway.

The Internet consists of a wide area network, a local area network, and a single unit in accordance with a certain communication protocol. Two or more computer terminals, clients, and servers are connected to each other through computer technology to form the Internet.

Internet gateway is a computer system or device that acts as a conversion task. Between different systems using different communication protocols, data formats or languages, and even completely different architectures, the Internet gateway is a translator for the information received. Repackage to accommodate the needs of the destination system. At the same time, Internet gateways can also provide filtering and security features.

The Internet-based network optimization device complements existing firewall, security and intrusion detection, load balancing, bandwidth management, network anti-virus and other network and network problems, and can be accessed through Internet access and other hardware and software operations. Parameter acquisition, data analysis, find out the reasons that affect the quality of the network, improve the network resources to obtain the best benefit through technical means or increase the corresponding hardware equipment and adjust the network to achieve the best operating conditions, and understand the growth trend of the network. Provide a better solution. Enables network application performance acceleration, secure content management, security event management, user management, network resource management and optimization, desktop system management, traffic pattern monitoring, measurement, tracking, analysis, and management, and improves the performance of application traffic over the WAN The product. It mainly includes three categories: network resource manager, application performance accelerator, and web performance accelerator. The network is optimized for different requirements and functional requirements. Network optimization equipment also Features such as supported protocols, network integration functions (serial mode, bypass mode), device monitoring functions (compressed data statistics, QOS, bandwidth management, data export, application reporting, uninterrupted work during failure, or through the network) Upgrade, etc.

The Internet of Things (IoT) uses information-sensing devices such as radio frequency identification (RFID), infrared sensors, global positioning systems, and laser scanners to exchange information and communicate at any time, any place, and any object in accordance with agreed protocols. Identify, locate, track, monitor, and manage. The Internet of Things is a network that connects the physical world with comprehensive sensing, reliable transmission, and intelligent processing features.

The IoT Gateway will play a very important role in the future Internet of Things era, and it will become the link between the connected sensing network and the traditional communication network. The IoT gateway can realize protocol conversion between the sensing network and the basic network and different types of sensing networks, which can realize wide area interconnection and local area interconnection.

From the perspective of technical architecture, the Internet of Things based on the IoT gateway can be divided into three layers: the sensing layer, the network layer and the application layer. The IoT gateway is in the sensing layer and has interfaces with the network layer and the application layer. The sensing layer consists of various sensors and sensor gateways, including carbon dioxide concentration sensors, temperature sensors, humidity sensors, QR code tags, RFID tags and readers, cameras, GPS and other sensing terminals. The function of the sensory layer is equivalent to the nerve endings of the human ear, nose, throat and skin. It is the source of the object that the Internet of Things recognizes and collects information. Its main function is to identify objects and collect information. The network layer is composed of various private networks and the Internet. It consists of wired and wireless communication networks, network management systems, and cloud computing platforms. It is equivalent to the human nerve center and brain. It is responsible for transmitting and processing the information acquired by the sensing layer. The application layer is the Internet of Things and users (including people, organizations and other systems). ) Interface, which combines with industry needs to implement intelligent applications for the Internet of Things.

Through the investigation of the prior art, it can be known that the problem of information communication solved by the Internet, the Internet of Things solves the problem of communication of matter and information, and the prior art does not involve energy problems. On the basis of the Internet and the Internet of Things, the ubiquitous energy network integrates information, material and energy into a synergistic coupling. The Internet gateway in the prior art only solves the problems of efficient transmission of information flow, standard conversion and routing control, and cannot provide an effective reference for the optimal control of material flow and energy flow of the ubiquitous energy network. The IoT Gateway proposes a three-layer structure for reference to the ubiquitous energy network, but the Internet of Things is more concerned with hardware technology and standards and material flow delivery processes, and cannot provide an energy-based optimization control method for ubiquitous energy networks. Summary of the invention

It is an object of the present invention to provide a ubiquitous energy network control method. According to the present invention, a ubiquitous energy network optimization control method based on a universal energy gateway is provided to achieve efficient use of energy.

According to an aspect of the present invention, a ubiquitous power network control method is provided, including:

S101, collecting sensing information; performing step S102, performing model prediction and fluctuation prediction, outputting operation information and prediction data; and in step S103, uploading operation information and prediction data to an energy efficiency control system of the interaction layer; step S104, energy efficiency The control system classifies and controls the collected data information and uploads it to the intelligent energy efficiency platform; in step S105, the intelligent energy efficiency platform optimizes the processing and dynamic simulation of the uploaded information; and in step S106, the parallel control system interacts with the intelligent energy efficiency platform; Step

5107, the intelligent energy efficiency platform uploads the generated data to the ubiquitous service platform of the mutual intelligence layer;

5108, the ubiquitous service platform obtains the intelligence data from the user terminal, and transmits the data and the intelligent energy efficiency platform upload data to the intelligence evolution engine; in step S109, the brain intelligence evolution engine processes the data through the brain intelligence evolution algorithm. Smart strategy and rewards and punishments, return to the ubiquitous service platform; Step S110, the mutual intelligence layer users get reward and punishment strategies can self-evolve, and feedback on the wise intelligence evolution strategy, so that the wise intelligence strategy is evolved; Step S111, for the interaction layer And the users of the mutual sensibility layer, the ubiquitous service platform sends the intelligence strategy and reward and punishment strategy to the interactive layer intelligent energy efficiency platform.

The step S101 collects sensing information of the field device through the production intelligent terminal, the storage intelligent terminal, the application intelligent terminal, and the regenerative intelligent terminal.

The step S102 is to upload the sensor information and the device information to the MPC controller of the universal energy gateway through the energy-matching center central controller of the ubiquitous gateway to implement model prediction and fluctuation prediction, and output the operation information and the prediction data.

In the step S103, the MPC controller uploads the operation information and the prediction data to the energy-efficient control system of the interaction layer in an OPC, Modbus or GPRS manner.

In the step S104, the energy-efficiency control system further allocates the received upper-layer control policy to the corresponding device.

The step S105 includes: the intelligent energy efficiency platform optimizes the information uploaded by the energy efficiency control system through the real-time optimization system and generates an optimization result; interacts the optimization result with the steady state optimization system, and the optimization result verified by the steady state optimization system The information is sent to the dynamic simulation system; the dynamic simulation system generates dynamic simulation data that interacts with the parallel control system (ACP).

The step S106 includes: the administrator passes the parallel control system ACP client to the smart The energy efficiency platform sends an energy efficiency diagnosis request, and the energy efficiency diagnosis system calls the expert system for analysis, and returns the ACP client to the management personnel after finding the optimal management and operation guidance; the customer sends the energy efficiency diagnosis request to the intelligent energy efficiency platform through the ACP client, and the energy efficiency diagnosis system calls The expert system analyzes and generates the optimal control strategy to pass the optimal feasible domain to the energy efficiency control system, which is delivered to the mutual inductance layer controller through the backbone Ethernet.

The data generated by the intelligent energy efficiency platform in the step S107 includes sensor information, behavior information, and operation information.

According to the ubiquitous energy network control method based on the ubiquitous power gateway, the information such as the operation of the field device can be optimized, and an optimal control strategy is generated, and the unordered ubiquitous energy flow is converted into an ordered ubiquitous energy flow to realize the energy efficiency gain effect, and Realize the evolution of the genius network. DRAWINGS

FIG. 1 is a schematic structural diagram of a ubiquitous energy network system based on a ubiquitous energy gateway;

2 is a schematic structural diagram of a universal energy gateway of the present invention;

3 is a schematic diagram showing the working principle of the universal energy gateway of the present invention;

FIG. 4 is a flow chart showing the ubiquitous energy network optimization control method of the present invention. detailed description

The present invention will be described in detail below with reference to the specific embodiments thereof and the accompanying drawings.

FIG. 1 shows a schematic diagram of a ubiquitous energy network system structure based on a ubiquitous energy gateway.

As shown in FIG. 1, the ubiquitous energy network system includes a mutual inductance layer 1, an interaction layer 2, and a mutual intelligence layer 3. These three layers are connected and communicated through the backbone Ethernet.

The mutual inductance layer 1 is located on the bottom layer, which implements basic control based on the rules of curing. In the present invention, the mutual inductance layer is preferably a star-ring hybrid topology, and the connection and communication between the devices are realized by the field bus.

The ubiquitous power gateway in the present invention is disposed in the mutual inductance layer 1, and serves as a communication interface of the mutual inductance layer 1 and the interaction layer 2.

The interaction layer 2 is located in the middle layer, which realizes human-machine association based on changes and dynamic changes of users' needs. The interaction layer 2 includes an energy efficiency control system 201, an intelligent energy efficiency platform 202, and a parallel control system. The ACP client 203, wherein the smart energy efficiency platform 202 includes functional modules such as energy efficiency diagnosis, energy efficiency monitoring, load forecasting, predictive optimization, and real-time optimization (RTO). The intelligent energy efficiency platform 202 is respectively connected to the energy-efficient control system 201, the ACP client 203, and the ubiquitous service platform 301 of the mutual intelligence layer 3 by means of Ethernet wired.

The energy efficiency control system 201 collects the information of the mutual inductance layer, uploads the information to the intelligent energy efficiency platform 202, and receives the optimization strategy issued by the intelligent energy efficiency platform 202, and distributes the policy to the mutual inductance layer 1.

The workflow of the intelligent energy efficiency platform 202 is as follows: The real-time optimization system optimizes the operation information, generates optimization results, and interacts with the steady-state optimization system. The steady-state optimization system sends the generated optimization result verification information to the dynamic simulation system, and the dynamic simulation system generates dynamic simulation data and interacts with the parallel control system (ACP).

The mutual intelligence layer 3 is located at the top level, which is based on the mutual influence and random factors of everyone to comprehensively optimize and control, and finally realize the synergistic optimization of energy flow, information flow and material flow in the mutual inductance layer, the interaction layer and the mutual intelligence layer.

The mutual intelligence layer 3 includes a ubiquitous service platform 301, a brainstorming evolution engine 302, and a mutual intelligence layer user 303. The ubiquitous service platform 301 communicates with the intelligent evolution engine 302 through an Ethernet connection, and the ubiquitous service platform 302 and the mutual intelligence layer user 303 perform intelligent data collection through a wired/wireless connection. The ubiquitous service platform 301 transmits the intelligence data obtained from the mutual intelligence layer user 303 and the sensor information, behavior information and the like obtained from the intelligent energy efficiency platform 202 of the interaction layer 2 to the brain evolution engine 302, and the intelligence evolution engine 302 passes The Jizhi evolutionary algorithm processes these data to obtain the episteer evolution strategy and returns it to the ubiquitous service platform 301. The ubiquitous service platform 301 modifies the wise evolution strategy through experts, administrators, etc., and forms a final strategy, which is sent to the interactive layer 2 intelligent energy efficiency platform 202. The interaction layer 2 generates corresponding control information according to the policy information, and transmits it to the mutual inductance layer 1. Finally, the mutual inductance layer 1 executes the control information command to control the field device and transmits the corresponding feedback information to the interaction layer 2. The interaction layer 2 enhances the intelligent learning ability by transmitting feedback information to the mutual intelligence layer.

Fig. 2 is a block diagram showing the structure of the universal energy gateway of the present invention.

The ubiquitous energy gateway of the invention is used for realizing ubiquitous energy conversion between different intelligent terminals, and adjusts the ubiquitous energy flow of each device according to the operation condition of the ubiquitous energy network system to achieve optimal energy efficiency.

As shown in FIG. 2, the ubiquitous energy gateway includes an energy efficiency matching center 100, a wireless base station 101, and a public A device such as a Public Land Mobil Network (PLMN) 102, a PLMN server 103, a router 104, a gateway 105, a switch 106, and a Model Predictive Control (MPC) 107. The energy efficiency matching center 100 connects the intelligent terminals used in the four links of the energy system, namely, the production intelligent terminal, the storage intelligent terminal, the application intelligent terminal, and the regenerative intelligent terminal, and completes the energy-efficient matching of the four links, for example, how much energy is produced in the production process. How much is used for the application process, how much is used for the storage link, and how much can be used for the regeneration process. The four-link intelligent terminal can sense device information and control the device.

The ubiquitous gateway connects the fieldbus and the backbone Ethernet through the following two information control methods to realize the information interaction between the mutual sensation layer and the interaction layer: (1) wired mode, four-link intelligent terminal through the wired router 104, wired gateway 105 and wired The switch 106 forwards the field information to the backbone Ethernet in a stepwise manner; (2) In the wireless mode, the intelligent terminal communicates through the wireless base station 101, and the field information is transmitted to the PLMN server 103 through the PLMN 102 to connect to the backbone Ethernet.

In the above two information control methods, the MPC controller 107 performs model prediction and fluctuation prediction on the information uploaded by the intelligent terminal, and uploads the device operation information and the prediction data to the interaction layer through the backbone Ethernet in an OPC/Modbus/GPRS manner. . Among them, the process control object is connected and embedded in OPC (Object Linking and Embedding (OLE) for Process Control) for process control OLE. Object Linking and Embedding (OLE) is called OLE technology. OLE is not only a desktop application integration, but also defines and implements a mechanism that allows applications to "connect" to each other as software "objects" (functions of data collection and operational data:). This connection mechanism and protocol is called Component Object Model (COM). Modbus is a bus protocol for industrial sites and was invented in 1979 by Modicon (now a brand of Schneider Electric). GPRS (General Packet Radio Service) General Packet Radio Service

FIG. 3 shows a schematic diagram of the working principle of the universal energy gateway of the present invention.

As shown in Figure 3, the unordered ubiquitous energy flow passes through the ubiquitous energy gateway, and the ubiquitous energy flow components (material flow, information flow, energy flow) interact with each other, and the ubiquitous energy gateway controls the flow path of the ubiquitous energy flow component. , output ordered ubiquitous energy flow, to the end user. The input and output of the ubiquitous energy stream is implemented through a ubiquitous energy conversion interface.

The invention mainly adopts the following four technologies as the technology used in the optimization control process of the ubiquitous energy network. Technology: Intelligent terminal technology, intelligent transmission control technology, collaborative optimization technology, and intelligent evolution technology. Intelligent terminal technology: In the mutual energy layer of ubiquitous energy network, based on MEMS technology (Micro-Electro & Mechenical System), it has information conversion and processing functions, can collect energy-matching center sensor information, and control equipment according to upper-layer strategy. .

Intelligent transmission control technology: In the mutual energy layer and interaction layer of ubiquitous energy network, according to the unique transmission control protocol of ubiquitous energy network, the energy characteristics are predicted by MPC (model prediction control) technology in the energy field, and the information exchange of ubiquitous energy flow is controlled. communication. The ubiquitous network transmission control protocol defines the way in which various ubiquitous devices access the ubiquitous network and the criteria for the transmission of ubiquitous energy between ubiquitous devices. The transmission of ubiquitous streams is achieved through a ubiquitous standard interface.

Collaborative optimization technology: Based on the ACP parallel control technology in the interactive layer of the ubiquitous energy network. Parallel control is a new way of thinking and solving new problems of complex system control and human-computer intelligence fusion. The core of the system is based on Artificial Systems, Computational Experiments, and the Parallel Execution ACP method. Through dynamic evolution and interactive learning, the human-machine system is collaboratively optimized.

Jizhi evolution technology: After the users of the ubiquitous energy network perform decision-making, they generate feedback information, and feedback to the intelligence-intelligence layer intelligence evolution engine. The group-optimization strategy is used to realize the intelligent decision-making, and the evolution of the wisdom-making decision is realized through reward punishment.

FIG. 4 is a flow chart showing the ubiquitous energy network optimization control method of the present invention.

The ubiquitous energy gateway of the present invention is used to implement a ubiquitous energy network optimization control flow based on the ubiquitous energy network system shown in FIG. 1. The ubiquitous energy network optimization control flow based on the ubiquitous energy gateway is as follows, wherein the function of the ubiquitous energy gateway is to The conversion and control of the energy flow is embodied by transmitting the sensor information to the upper layer and receiving the upper layer optimization control information:

Step S101, collecting sensing information.

Each intelligent terminal of the mutual inductance layer collects the sensing information of the field device and uploads it to the energy efficiency matching center to realize energy efficiency control, link control, and regular control.

Step S102, performing model prediction and fluctuation prediction.

The energy efficiency matching center central controller uploads sensor information and device information to the MPC controller to implement model prediction and fluctuation prediction, and outputs operational information and prediction data.

Step S103: Upload the operation information and the prediction data to the energy efficiency control system of the interaction layer.

The MPC controller passes the operation information and prediction data in OPC/Modbus/GPRS mode. Energy efficiency control system passed to the interactive layer.

Step S104: The energy efficiency control system performs classification control processing on the collected data information, and uploads to the intelligent energy efficiency platform.

The energy-efficiency control system is used for data collection and policy allocation, that is, the energy-efficient control system classifies the collected information (operation information and prediction data) and then uploads it; assigns the received upper-layer control policy to the corresponding device.

Step S105: The intelligent energy efficiency platform optimizes and dynamically simulates the uploaded information. The intelligent energy efficiency platform optimizes the information uploaded by the energy efficiency control system through the real-time optimization system, generates optimization results, and interacts with the steady-state optimization system, and the steady-state optimization system sends the verification result verification information generated to the dynamic simulation system, and the dynamic simulation system Generate dynamic simulation data and interact with the Parallel Control System (ACP).

Step S106, the parallel control system interacts with the intelligent energy efficiency platform.

Through the parallel control system, the ACP client sends an energy efficiency diagnosis request to the intelligent energy efficiency platform. The energy efficiency diagnosis system calls the expert system for analysis, finds the optimal management and operation guidance, and returns to the ACP client to the management personnel. The customer sends an energy efficiency diagnosis request to the intelligent energy efficiency platform through the ACP client, and the energy efficiency diagnosis system calls the expert system for analysis, and generates an optimal control strategy to pass the energy efficiency control system to the energy efficiency control system, and is delivered to the mutual inductance layer controller through the backbone Ethernet.

Step S107: The intelligent energy efficiency platform uploads the generated data to the ubiquitous service platform of the mutual intelligence layer.

The data generated by the intelligent energy efficiency platform includes sensor information, behavior information, operational information, and the like. Step S108: The ubiquitous service platform obtains the intelligence data from the user terminal, and transmits the data and the intelligent energy efficiency platform upload data to the intelligence evolution engine.

Step S109, the intelligence evolution engine collects the data through the intelligent evolution algorithm to obtain the wisdom strategy and rewards and punishments, and returns to the ubiquitous service platform.

Step S110, the users of the mutual intelligence layer get the reward and punishment strategy to self-evolve, and feedback the intelligence evolution strategy to make the brainstorming strategy evolve.

Step S111, for the interaction layer and the mutual Sense layer user, the ubiquitous service platform sends the wise intelligence strategy and the reward and punishment strategy to the interactive layer intelligent energy efficiency platform.

The intelligent energy efficiency platform generates corresponding control information according to the control strategy, through the energy efficiency control system, The MPC controller is sent to the central controller. The central controller of the energy efficiency matching center generates optimized control parameters according to the control strategy, and sends them to the intelligent terminal of the energy efficiency matching center to optimize the control of the field devices and generate corresponding feedback information.

In this way, the energy efficiency matching center collects feedback information through the intelligent terminal, and uploads it step by step. The interaction layer self-evolates through the mutual intelligence layer reward and punishment information, and the mutual intelligence layer carries out the intelligence evolution through the interactive layer feedback information; the mutual inductance layer is transmitted through the interaction layer. Mutual intelligence layer reward and punishment information self-evolution, and through the interactive layer feedback information to the mutual intelligence layer for intellectual evolution.

In the above process, the energy-matching center intelligent terminal collects the field device information, uploads it step by step, and receives the upper layer optimization control information to control the field device. This process is implemented by the smart terminal technology. The ubiquitous flow (information flow, material flow, energy flow) information is transmitted between the various ubiquitous devices according to the ubiquitous energy transmission control protocol, and is realized by the intelligent transmission control protocol. The interaction between the parallel control system and the intelligent energy efficiency platform is achieved through collaborative optimization techniques. The field device implements the upper-level optimization strategy and generates corresponding feedback information. The feedback information is uploaded step by step to realize the evolution of the ubiquitous energy network mutual interaction layer, interaction layer and mutual intelligence layer. This process is realized by the intelligent evolution technology.

In summary, in the control process of the ubiquitous energy network, the ubiquitous gateway collects the on-site sensing information and transmits it upwards step by step. Correspondingly, the ubiquitous energy gateway receives the optimal control information generated by the upper optimization system and controls the scene accordingly. Thereby achieving optimal control of the entire ubiquitous energy network.

The above-described embodiments of the present invention are intended to be illustrative or not to limit the invention. Therefore, any modifications, equivalent substitutions, improvements, etc., which are made without departing from the spirit and scope of the invention, are intended to be included within the scope of the invention. Rather, the scope of the appended claims is intended to cover all such modifications and modifications

Claims

A method for controlling a ubiquitous energy network, comprising:

Step S101, collecting sensing information;

Step S102, performing model prediction and fluctuation prediction, outputting operation information and prediction data; and in step S103, uploading the operation information and the prediction data to the energy efficiency control system of the interaction layer; Step S104, the energy efficiency control system collects the data information Perform classification control processing and upload to the intelligent energy efficiency platform;

Step S105, the intelligent energy efficiency platform optimizes the processing and dynamic simulation of the uploaded information; Step S106, the parallel control system interacts with the intelligent energy efficiency platform;

Step S107, the intelligent energy efficiency platform uploads the generated data to the ubiquitous service platform of the mutual intelligence layer.

Step S108: The ubiquitous service platform obtains the intelligence data from the user terminal, and transmits the data and the intelligent energy efficiency platform upload data to the intelligence evolution engine;

Step S109, the intelligence evolution engine collects the data through the intelligence evolution algorithm to obtain the wisdom strategy and reward and punishment, and returns to the ubiquitous service platform;

Step S110, the users of the mutual intelligence layer get the reward and punishment strategy to self-evolve, and feedback the intelligence evolution strategy to make the brainstorming strategy evolve;

The method according to claim 1, wherein the step S101 collects sensing information of the field device through the production intelligent terminal, the storage intelligent terminal, the application intelligent terminal, and the regenerative intelligent terminal.

The method according to claim 1, wherein the step S102 is to upload the sensor information and the device information to the MPC controller of the universal energy gateway through the energy efficiency matching center central controller of the ubiquitous energy gateway to implement model prediction and The fluctuation prediction is performed, and the operation information and the prediction data are output.

The method according to claim 1, wherein, in the step S103, the MPC controller uploads the operation information and the prediction data to the interaction layer in an OPC, Modbus or GPRS manner. The system also assigns the received upper layer control policy to the corresponding device.

The method according to claim 1, wherein the step S105 comprises: the intelligent energy efficiency platform optimizes the information uploaded by the energy efficiency control system through a real-time optimization system and generates an optimization result;

The optimization result is interacted with the steady-state optimization system, and the steady-state optimization system sends the verification result of the optimized result to the dynamic simulation system;

The dynamic simulation system generates dynamic simulation data that interacts with the Parallel Control System (ACP).

The method according to claim 1, wherein the step S106 comprises: the administrator sends an energy-efficient diagnosis request to the intelligent energy-efficiency platform through the parallel control system ACP client, and the energy-efficient diagnosis system calls the expert system to analyze and find the optimal Return to the ACP client to the management after management and operation instructions;

The customer sends an energy-efficient diagnosis request to the intelligent energy-efficiency platform through the ACP client, and the energy-efficient diagnosis system calls the expert system for analysis, and generates an optimal control strategy, and the optimal feasible domain is transmitted to the energy-efficient control system, and is delivered to the mutual-inductive layer controller through the backbone Ethernet.

The method according to claim 1, wherein the data generated by the intelligent energy efficiency platform in the step S107 comprises sensor information, behavior information, and operation information.