Virtual power plant and comprehensive energy platform collaborative optimization scheduling method

Abstract

The invention relates to the technical field of smart power grids and energy systems, and discloses a virtual power plant and comprehensive energy platform collaborative optimization scheduling method, which establishes an objective energy consumption diagnosis and evaluation system and a smart operation and maintenance management system. A multi-scene energy monitoring module, a multi-scene energy data acquisition module, a multi-scene energy analysis module, a multi-scene energy diagnosis module and a platform collaborative optimization scheduling module are established in the system, all the modules are connected through the Internet of Things, and the multi-scene energy monitoring module is used for monitoring. The multi-scene energy data acquisition module acquires multi-scene energy data in the multi-scene energy monitoring module, the multi-scene energy analysis module serves as a computing platform of the multi-scene energy data acquisition module and transmits the computed data to the multi-scene energy diagnosis module, the computed data is compared in the multi-scene energy diagnosis module, and the multi-scene energy data is acquired. And a diagnosis analysis result is obtained, and the diagnosis result of the multi-scene energy diagnosis module is optimized in the platform collaborative optimization scheduling module.

Description

Technical Field

[0001] The present invention relates to the technical field of smart grids and energy systems, and specifically to a method for collaborative optimization and scheduling of a virtual power plant and an integrated energy platform. Background Art

[0002] In today's energy sector, the operation of power plants and integrated energy platforms faces a series of challenges, the three most prominent of which are insufficient energy utilization, low plant data security, and insufficient manual supervision.

[0003] Insufficient energy utilization is a common problem. In many power plants, due to aging equipment, backward technology or poor management, the energy utilization efficiency is low. This not only causes energy waste, but also increases the operating costs of power plants and causes unnecessary pressure on the environment. Therefore, how to improve energy utilization efficiency and reduce energy waste is an important problem that power plants and integrated energy platforms need to solve. The low security of plant data is also a serious problem. With the development of informatization, power plants and integrated energy platforms have generated a large amount of data, which is of great value to the operation and management of power plants. However, due to various reasons, such as weak network security awareness and insufficient protection measures, the security of these data is often difficult to be effectively guaranteed. Once the data is illegally obtained or destroyed, it will have a serious impact on the operation of the power plant. Insufficient manual supervision is also a problem. In the operation of power plants and integrated energy platforms, a large amount of manual supervision and management is required. However, due to the limitation of human resources, it is often difficult to achieve all-round supervision, which may lead to some problems, such as equipment failure and safety accidents. Therefore, how to make up for the lack of manual supervision through technical means, such as automation and intelligence, is a problem that power plants and integrated energy platforms need to solve.

[0004] In general, insufficient energy utilization, low plant data security and insufficient manual supervision are the three main problems faced by power plants and integrated energy platforms. Virtual power plants can improve energy efficiency and promote clean energy applications. The research on advanced applications of virtual power plants and coordinated optimization scheduling technology of integrated energy platforms is of great value. This technology can achieve coordinated operation among multiple energy sources, make full use of renewable energy, improve energy efficiency, reduce energy consumption and carbon emissions, and further promote clean energy, low carbonization and sustainable development. Summary of the invention

[0005] 1. Technical issues to be resolved

[0006] In view of the shortcomings of the existing technology, the present invention provides a method for collaborative optimization and scheduling of a virtual power plant and an integrated energy platform, which has the advantages of efficient energy utilization, high plant data security and intelligent management, and solves the problems of insufficient energy utilization, low plant data security and insufficient manual supervision.

[0007] (II) Technical solution

[0008] To achieve the above-mentioned purpose, the technical solution provided by the present invention is a method for collaborative optimization and scheduling of a virtual power plant and an integrated energy platform, comprising the following steps:

[0009] Step 1: Establish an objective energy consumption diagnosis and evaluation system and a smart operation and maintenance management system, which includes the functions of protocol access, device access, message communication, device monitoring, operation control, device operation and maintenance, system management, VPN management and log management;

[0010] Step 2: Establish a multi-scenario energy monitoring module, a multi-scenario energy data collection module, a multi-scenario energy analysis module, a multi-scenario energy diagnosis module and a platform collaborative optimization scheduling module in the system, and connect all modules through the Internet of Things;

[0011] Step 3: The multi-scenario energy monitoring module uses the functions of protocol access, device access, message communication, device monitoring, operation control, device operation and maintenance, system management, VPN management and log management in the all-round monitoring system of the Internet of Things, monitoring devices and sensors;

[0012] Step 4: The multi-scenario energy data collection module collects multi-scenario energy data in the multi-scenario energy monitoring module;

[0013] Step 5: The multi-scenario energy analysis module serves as a computing platform for the multi-scenario energy data acquisition module and transmits the calculated data to the multi-scenario energy diagnosis module;

[0014] Step 6: Set standard values ​​in the multi-scenario energy diagnosis module, compare the calculated data, and obtain diagnostic analysis results;

[0015] Step 7: Optimize the diagnostic results of the multi-scenario energy diagnosis module in the platform collaborative optimization scheduling module.

[0016] Preferably, the multi-scenario energy data acquisition module includes a power plant data acquisition unit, a bus data acquisition unit and a virtual data acquisition unit. The power plant data acquisition unit collects power plant data through online instruments and monitoring equipment, the bus data acquisition unit collects bus data through the Internet of Things, and the virtual data acquisition unit collects virtual data through analog-to-digital converters, digital signal processing chips and a variety of signal conditioning technologies. After the data in the power plant data acquisition unit, the bus data acquisition unit and the virtual data acquisition unit are numbered and counted, they are all connected to the multi-scenario energy analysis module through the Internet of Things.

[0017] Preferably, the multi-scenario energy analysis module includes an energy data maintenance unit, a bus data service unit and a virtual data integration unit. The energy data maintenance unit calculates the power plant data maintenance index Et based on the power plant data, the bus data service unit identifies the safety index Dt based on the bus data calculation system, and the virtual data integration unit calculates the system operation and management efficiency Ft based on the power plant data and the virtual data.

[0018] Preferably, the power plant data acquisition unit performs numbering and statistics on the normal operation time, total operation time, response time of the maintenance department, maintenance cost and spare parts availability data corresponding to all equipment in the power plant according to the power plant data characteristics, the power plant data acquisition unit performs numbering and statistics on the fuel consumption, power generation and emission standard data of the power plant according to the power plant data characteristics, and the power plant data acquisition unit performs numbering and statistics on the energy platform power plant data of the real scene according to the power plant data characteristics, and the energy platform power plant data of the real scene are numbered as L1, L2, L3, ...L n The normal operation time, total operation time, maintenance department response time, maintenance cost and spare parts availability data of all equipment in the power plant are numbered as Tx n 、Ty n 、Tv n , W n , G n The fuel consumption and power generation data of the power plant are numbered U1 and U2 respectively.

[0019] Preferably, the bus data acquisition unit numbers and counts the coefficient values ​​of physical security, network security and host security, application security and data backup security of the bus connection in the system according to the bus data characteristics, and the coefficient values ​​of physical security, network security and host security, application security and data backup security of the bus connection in the system are numbered H1, H2, H3, H4, and H5, respectively.

[0020] Preferably, the virtual data acquisition unit numbers the energy platform power plant data of the simulated scene according to the virtual data characteristics, and the energy platform power plant data of the simulated scene are numbered as J1, J2, J3, ... Jn .

[0021] Preferably, the energy data maintenance unit calculates the power plant data maintenance index Et according to the power plant data, and the calculation formula is:

[0022]

[0023] In the formula, Et represents the power plant data maintenance index, Tx n 、Ty n , TV n , W n , G n They represent the normal operation time, total operation time, maintenance department response time, maintenance cost and spare parts availability data of all equipment in the power plant, n represents the total number of equipment in the power plant, U1 and U2 represent the fuel consumption and power generation data of the power plant, respectively. represents the maintenance efficiency factor, Represents the energy efficiency factor.

[0024] Preferably, the bus data service unit identifies the safety index Dt according to the bus data calculation system, and the calculation formula is:

[0025]

[0026] In the formula, Dt represents the system identification security index, H1, H2, H3, H4, and H5 represent the coefficient values ​​of the physical security, network security, host security, application security, and data backup security of the bus connection in the system, respectively. i It represents the safety coefficient value of a certain item in the system identification security. b1, b2, b3, b4, and b5 respectively represent the weights of the coefficient values ​​of the physical security, network security, host security, application security, and data backup security of the bus connection in the system in the system identification security index. i Indicates the weight of a safety factor value in system identification safety.

[0027] Preferably, the virtual data integration unit calculates the system operation management efficiency Ft based on the power plant data and the virtual data, and the calculation formula is:

[0028]

[0029] In the formula, Ft represents the system operation and management efficiency, L1, L2, L3, ...L n Energy platform power plant data representing real scenarios, L i represents the power plant data of the energy platform in the i-th real scenario, W n represents the maintenance cost of all equipment in the power plant, W represents the total cost of the power plant, U1 and U2 represent the fuel consumption and power generation data of the power plant respectively, Represents energy efficiency factors, J1, J2, J3, …J n Represents the power plant data of the energy platform for the simulation scenario, L i represents the power plant data of the energy platform for the i-th simulation scenario, Indicates the reliability of power plant system operation.

[0030] Preferably, the multi-scenario energy diagnosis module diagnoses power plant maintenance problems based on the power plant data maintenance index Et. When the power plant data maintenance index Et is lower than a preset value, maintenance technicians are added. The power plant system Internet of Things monitoring problems are diagnosed based on the system identification safety index Dt. When the system identification safety index Dt is lower than a preset value, the internal system of the power grid is closed to prevent external network viruses from invading. The reliability of the power plant system is diagnosed based on the system operation and management efficiency Ft. When the system operation and management efficiency Ft is lower than a preset value, the operation and management mode is changed and the system function is increased.

[0031] Compared with the prior art, the present invention provides a method for collaborative optimization and scheduling of a virtual power plant and an integrated energy platform, which has the following beneficial effects:

[0032] 1. By calculating the power plant data maintenance index Et, the present invention integrates multiple key parameters of the power plant's operating efficiency, maintenance response speed, maintenance cost, spare parts supply, energy conversion efficiency, and maintenance and energy efficiency factors. The calculation formula enables the multi-scenario energy diagnosis module to automatically evaluate the maintenance status of the power plant and set a preset standard value in the system. When the power plant data maintenance index exceeds or falls below this preset range, the system will automatically trigger the function of increasing the technical improvement of maintenance personnel and notify the maintenance department to take corresponding measures to maintain different types of equipment. This method can not only maintain the stability of plant equipment, but also solve the problem of insufficient supervision of equipment maintenance personnel in the power plant area, thereby realizing intelligent management of the power plant.

[0033] 2. The present invention establishes an objective energy diagnosis and evaluation system and an intelligent operation and maintenance management system through multi-scenario and multi-system energy data collection, monitoring, diagnosis and analysis, and system application research on the group's comprehensive energy projects, so as to realize the refined energy management of each comprehensive energy project, improve energy utilization, reduce labor costs, and reduce unnecessary energy consumption. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 The figure is a flow chart of the method of the present invention. DETAILED DESCRIPTION

[0035] 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.

[0036] See also Figure 1 , a method for collaborative optimization and scheduling of a virtual power plant and an integrated energy platform, comprising the following steps:

[0037] Step 1: Establish an objective energy consumption diagnosis and evaluation system and a smart operation and maintenance management system, which includes functions such as protocol access, device access, message communication, device monitoring, operation control, device operation and maintenance, system management, VPN management, and log management.

[0038] Step 2: Establish a multi-scenario energy monitoring module, a multi-scenario energy data collection module, a multi-scenario energy analysis module, a multi-scenario energy diagnosis module and a platform collaborative optimization scheduling module in the system, and connect all modules through the Internet of Things;

[0039] Step 3: The multi-scenario energy monitoring module uses the functions of protocol access, device access, message communication, device monitoring, operation control, device operation and maintenance, system management, VPN management and log management in the all-round monitoring system of the Internet of Things, monitoring devices and sensors;

[0040] Step 4: The multi-scenario energy data collection module collects multi-scenario energy data in the multi-scenario energy monitoring module;

[0041] Step 5: The multi-scenario energy analysis module serves as a computing platform for the multi-scenario energy data acquisition module and transmits the calculated data to the multi-scenario energy diagnosis module;

[0042] Step 6: Set standard values ​​in the multi-scenario energy diagnosis module, compare the calculated data, and obtain diagnostic analysis results;

[0043] Step 7: Optimize the diagnostic results of the multi-scenario energy diagnosis module in the platform collaborative optimization scheduling module.

[0044] The multi-scenario energy data acquisition module includes a power plant data acquisition unit, a bus data acquisition unit and a virtual data acquisition unit. The power plant data acquisition unit collects power plant data through online instruments and monitoring equipment, the bus data acquisition unit collects bus data through the Internet of Things, and the virtual data acquisition unit collects virtual data through analog-to-digital converters, digital signal processing chips and a variety of signal conditioning technologies. After the data in the power plant data acquisition unit, the bus data acquisition unit and the virtual data acquisition unit are numbered and counted, they are all connected to the multi-scenario energy analysis module through the Internet of Things.

[0045] The multi-scenario energy analysis module includes an energy data maintenance unit, a bus data service unit and a virtual data integration unit. The energy data maintenance unit calculates the power plant data maintenance index Et based on the power plant data. The bus data service unit identifies the safety index Dt based on the bus data calculation system. The virtual data integration unit calculates the system operation and management efficiency Ft based on the power plant data and virtual data.

[0046] The power plant data acquisition unit numbers and counts the normal operation time, total operation time, response time of the maintenance department, maintenance cost and spare parts availability data corresponding to all equipment in the power plant according to the power plant data characteristics. The power plant data acquisition unit numbers and counts the fuel consumption, power generation and emission standard data of the power plant according to the power plant data characteristics. The power plant data acquisition unit numbers and counts the energy platform power plant data of the real scene according to the power plant data characteristics. The energy platform power plant data of the real scene are numbered as L1, L2, L3, ... L n The normal operation time, total operation time, maintenance department response time, maintenance cost and spare parts availability data of all equipment in the power plant are numbered as Tx n 、Ty n 、Tv n , W n , G n , the fuel consumption and power generation data of the power plant are numbered U1 and U2 respectively.

[0047] The bus data acquisition unit numbers and counts the coefficient values ​​of the physical security (selection of physical location, physical access control and anti-theft, fire prevention, waterproofing, lightning protection, temperature and humidity control, power supply, anti-static and electromagnetic protection), network security (structural safety, security audit, access control, boundary integrity check, malicious code prevention, intrusion prevention and network equipment protection) and host security (including identity authentication, access control, security audit, intrusion prevention, malicious code prevention and resource control), application security (identity authentication, access control, security audit, communication integrity, communication confidentiality, non-repudiation, software fault tolerance and resource control) and data backup security (security of all backup data connected to the system) of the bus connection in the system according to the bus data characteristics. The coefficient values ​​of the physical security, network security and host security, application security and data backup security of the bus connection in the system are numbered H1, H2, H3, H4 and H5 respectively.

[0048] The virtual data acquisition unit numbers the energy platform power plant data of the simulation scene according to the virtual data characteristics. The energy platform power plant data of the simulation scene are numbered as J1, J2, J3, ...J n .

[0049] The energy data maintenance unit calculates the power plant data maintenance index Et based on the power plant data. The calculation formula is:

[0050]

[0051] In the formula, Et represents the power plant data maintenance index, Tx n 、Ty n , TV n , W n , G n They represent the normal operation time, total operation time, maintenance department response time, maintenance cost and spare parts availability data of all equipment in the power plant, n represents the total number of equipment in the power plant, U1 and U2 represent the fuel consumption and power generation data of the power plant, respectively. represents the maintenance efficiency factor, Represents the energy efficiency factor.

[0052] The advantages are: by calculating the power plant data maintenance index Et, the calculation formula combines the power plant's operating efficiency, maintenance response speed, maintenance cost, spare parts supply, energy conversion efficiency, and maintenance and energy efficiency factors together for calculation. The maintenance status of the power plant can be evaluated based on the range of the index. When the value of the power plant data maintenance index Et is outside the preset value range, the maintenance of different types of equipment in the plant area is improved by increasing the number of maintenance technicians, thereby increasing the stability of the plant's maintenance part and solving the problem of insufficient supervision of plant equipment maintenance.

[0053] The bus data service unit identifies the safety index Dt according to the bus data calculation system, and its calculation formula is:

[0054]

[0055] In the formula, Dt represents the system identification security index, H1, H2, H3, H4, and H5 represent the coefficient values ​​of the physical security, network security, host security, application security, and data backup security of the bus connection in the system, respectively. i It represents the safety coefficient value of a certain item in the system identification security. b1, b2, b3, b4, and b5 respectively represent the weights of the coefficient values ​​of the physical security, network security, host security, application security, and data backup security of the bus connection in the system in the system identification security index. i Indicates the weight of a safety factor value in system identification safety.

[0056] The advantages are: by calculating the system identification security index Dt and taking into account multiple security dimensions (physical security, network security, host security, application security and data backup security), it is helpful to comprehensively evaluate the security of the entire system, which helps to identify potential weak links in the power plant's safety links and reflect them in the system in a timely manner, so as to take corresponding improvement measures to improve the security of power plant data.

[0057] The virtual data integration unit calculates the system operation management efficiency Ft based on the power plant data and virtual data. The calculation formula is:

[0058]

[0059] In the formula, Ft represents the system operation and management efficiency, L1, L2, L3, ...L n Energy platform power plant data representing real scenarios, L i represents the power plant data of the energy platform in the i-th real scenario, W n represents the maintenance cost of all equipment in the power plant, W represents the total cost of the power plant, U1 and U2 represent the fuel consumption and power generation data of the power plant respectively, Represents energy efficiency factors, J1, J2, J3, …J n Represents the power plant data of the energy platform for the simulation scenario, L i represents the power plant data of the energy platform for the i-th simulation scenario, Indicates the reliability of power plant system operation.

[0060] The advantages are: by calculating the system operation and management efficiency Ft, the energy utilization efficiency of the power plant can be evaluated, that is, the electricity generated per unit of fuel consumption; by adding the maintenance cost and total cost of the power plant to the calculation formula, the operating cost of the power plant can be comprehensively analyzed, thereby finding potential space for cost savings; by adding the reliability of the power plant system operation to the calculation formula, it can be ensured that while improving energy efficiency, the stable operation of the power plant is not affected; by comparing the data of real scenarios and simulated scenarios in the calculation formula, the energy efficiency performance under different operating conditions can be predicted, and the basis for energy efficiency issues can be provided for the power plant in advance; when the system operation and management efficiency Ft is reduced, timely measures can be taken to optimize equipment maintenance plans, improve fuel use strategies or adjust power generation to improve energy utilization; through continuous monitoring of the system operation and management efficiency and continuous optimization of measures, it is helpful to achieve continuous reduction in energy consumption and continuous improvement in energy efficiency.

[0061] The multi-scenario energy diagnosis module diagnoses power plant maintenance problems based on the power plant data maintenance index Et. When the power plant data maintenance index Et is lower than the preset value, maintenance technicians are added. The power plant system IoT monitoring problems are diagnosed based on the system identification safety index Dt. When the system identification safety index Dt is lower than the preset value, the internal system of the power grid is closed to prevent external network viruses from invading. The reliability of the power plant system is diagnosed based on the system operation and management efficiency Ft. When the system operation and management efficiency Ft is lower than the preset value, the operation and management mode is changed and the system functions are increased.

[0062] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for collaborative optimization and scheduling of a virtual power plant and an integrated energy platform, characterized in that: The following steps are involved: Step 1: Establish an objective energy consumption diagnosis and evaluation system and a smart operation and maintenance management system, which includes functions such as protocol access, device access, message communication, device monitoring, operation control, device operation and maintenance, system management, VPN management, and log management. Step 2: Establish a multi-scenario energy monitoring module, a multi-scenario energy data collection module, a multi-scenario energy analysis module, a multi-scenario energy diagnosis module and a platform collaborative optimization scheduling module in the system, and connect all modules through the Internet of Things; Step 3: The multi-scenario energy monitoring module uses the functions of protocol access, device access, message communication, device monitoring, operation control, device operation and maintenance, system management, VPN management and log management in the all-round monitoring system of the Internet of Things, monitoring devices and sensors; Step 4: The multi-scenario energy data collection module collects multi-scenario energy data in the multi-scenario energy monitoring module; Step 5: The multi-scenario energy analysis module serves as a computing platform for the multi-scenario energy data acquisition module and transmits the calculated data to the multi-scenario energy diagnosis module; Step 6: Set standard values ​​in the multi-scenario energy diagnosis module, compare the calculated data, and obtain diagnostic analysis results; Step 7: Optimize the diagnostic results of the multi-scenario energy diagnosis module in the platform collaborative optimization scheduling module.

2. A method for collaborative optimization and scheduling of a virtual power plant and an integrated energy platform according to claim 1, characterized in that: The multi-scenario energy data acquisition module includes a power plant data acquisition unit, a bus data acquisition unit and a virtual data acquisition unit; the power plant data acquisition unit collects power plant data through online instruments and monitoring equipment; the bus data acquisition unit collects bus data through the Internet of Things; the virtual data acquisition unit collects virtual data through analog-to-digital converters, digital signal processing chips and a variety of signal conditioning technologies; after the data in the power plant data acquisition unit, the bus data acquisition unit and the virtual data acquisition unit are numbered and counted, they are all connected to the multi-scenario energy analysis module through the Internet of Things.

3. The method for collaborative optimization and scheduling of a virtual power plant and an integrated energy platform according to claim 1, characterized in that: The multi-scenario energy analysis module includes an energy data maintenance unit, a bus data service unit and a virtual data integration unit; the energy data maintenance unit calculates the power plant data maintenance index Et based on the power plant data; the bus data service unit identifies the safety index Dt based on the bus data calculation system; the virtual data integration unit calculates the system operation and management efficiency Ft based on the power plant data and the virtual data.

4. The method for collaborative optimization and scheduling of a virtual power plant and an integrated energy platform according to claim 2, characterized in that: The power plant data acquisition unit performs numbering and statistics on normal operation time, total operation time, response time of the maintenance department, maintenance cost and spare parts availability data corresponding to all equipment in the power plant according to the power plant data characteristics; The power plant data collection unit performs numbering and statistics on the fuel consumption, power generation and emission standard data of the power plant according to the data characteristics of the power plant; The power plant data acquisition unit performs numbering and statistics on the energy platform power plant data of the real scene according to the power plant data characteristics, and the energy platform power plant data of the real scene are numbered as L1, L2, L3, ... L n ; The normal operation time, total operation time, maintenance department response time, maintenance cost and spare parts availability data of all equipment in the power plant are numbered as Tx n 、Ty n , TV n , W n , G n ; The fuel consumption and power generation data of the power plant are numbered U1 and U2 respectively.

5. The method for collaborative optimization and scheduling of a virtual power plant and an integrated energy platform according to claim 2, characterized in that: The bus data acquisition unit performs numbering and statistics on coefficient values ​​of physical security, network security and host security, application security and data backup security of bus connections in the system according to bus data characteristics; The coefficient values ​​of physical security, network security, host security, application security and data backup security of bus connection in the system are numbered H1, H2, H3, H4 and H5 respectively.

6. A method for collaborative optimization and scheduling of a virtual power plant and an integrated energy platform according to claim 2, characterized in that: The virtual data acquisition unit numbers the energy platform power plant data of the simulation scene according to the virtual data characteristics; the energy platform power plant data of the simulation scene are numbered as J1, J2, J3, ... J n .

7. A method for collaborative optimization and scheduling of a virtual power plant and an integrated energy platform according to claim 4, characterized in that: The energy data maintenance unit calculates the power plant data maintenance index Et according to the power plant data, and the calculation formula is: In the formula, Et represents the power plant data maintenance index, Tx n 、Ty n , TV n , W n , G n represents the normal operation time, total operation time, maintenance department response time, maintenance cost and spare parts availability data of all equipment in the power plant, n represents the total number of equipment in the power plant, U1 and U2 represent the fuel consumption and power generation data of the power plant respectively, represents the maintenance efficiency factor, Represents the energy efficiency factor.

8. The method for collaborative optimization and scheduling of a virtual power plant and an integrated energy platform according to claim 5, characterized in that: The bus data service unit identifies the safety index Dt according to the bus data calculation system, and the calculation formula is: In the formula, Dt represents the system identification security index, H1, H2, H3, H4, and H5 represent the coefficient values ​​of the physical security, network security, host security, application security, and data backup security of the bus connection in the system, respectively. i It represents the safety coefficient value of a certain item in the system identification security. b1, b2, b3, b4, and b5 respectively represent the weights of the coefficient values ​​of the physical security, network security, host security, application security, and data backup security of the bus connection in the system in the system identification security index. i Indicates the weight of a safety factor value in system identification safety.

9. A method for collaborative optimization and scheduling of a virtual power plant and an integrated energy platform according to claim 6, characterized in that: The virtual data integration unit calculates the system operation management efficiency Ft based on the power plant data and virtual data, and the calculation formula is: In the formula, Ft represents the system operation and management efficiency, L1, L2, L3, ...L n Energy platform power plant data representing real scenarios, L i represents the power plant data of the energy platform in the i-th real scenario, W n represents the maintenance cost of all equipment in the power plant, W represents the total cost of the power plant, U1 and U2 represent the fuel consumption and power generation data of the power plant respectively, Represents energy efficiency factors, J1, J2, J3, …J n Represents the power plant data of the energy platform for the simulation scenario, L i represents the power plant data of the energy platform for the i-th simulation scenario, Indicates the reliability of power plant system operation.

10. A method for collaborative optimization and scheduling of a virtual power plant and an integrated energy platform according to claim 9, characterized in that: The multi-scenario energy diagnosis module diagnoses power plant maintenance problems based on the power plant data maintenance index Et. When the power plant data maintenance index Et is lower than a preset value, maintenance technicians are added. The Internet of Things monitoring problems of the power plant system are diagnosed based on the system identification safety index Dt. When the system identification safety index Dt is lower than a preset value, the internal system of the power grid is closed to prevent external network viruses from invading. The reliability of the power plant system is diagnosed based on the system operation and management efficiency Ft. When the system operation and management efficiency Ft is lower than a preset value, the operation and management mode is changed and the system function is increased.

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