Virtual power plant data management system and method

Abstract

The invention discloses a virtual power plant data management system and method, and particularly relates to the technical field of virtual power plants. Comprising a data acquisition and transmission module, a data processing and storage module, a data analysis and prediction module, a carbon footprint tracking and emission reduction optimization unit, an energy management and scheduling module, an energy market analysis and transaction module, a block chain energy transaction and settlement module, a fault diagnosis and early warning module and a user interaction and display module. A safety and operation and maintenance management module; and a VR and AR training module. By calculating and tracking the carbon footprint in the operation process of the virtual power plant, an emission reduction suggestion and an optimization scheme are provided, the virtual power plant is helped to reduce carbon emission, the environmental protection goal is achieved, the sustainable development capability of the virtual power plant is enhanced, the VR and AR training module is utilized to provide immersive training and simulation drilling environment for operation personnel and maintenance personnel, and the development efficiency of the virtual power plant is improved. The training effect is improved, the training cost is reduced, and the ability to deal with emergencies is enhanced.

Description

Technical Field

[0001] The present invention relates to the technical field of virtual power plants, and more specifically, to a virtual power plant data management system and method thereof. Background Art

[0002] In the context of energy transformation and smart grid development, virtual power plants, as a new energy management model, achieve efficient, flexible and intelligent energy management by integrating distributed energy resources (such as solar power generation, wind power generation, energy storage systems, electric vehicles, etc.) and utilizing advanced information and communication technologies and control strategies.

[0003] However, with the expansion of virtual power plants and the diversification of energy types, how to effectively collect, process, analyze and utilize these energy data has become an important challenge facing virtual power plant operations. Traditional energy management systems often have problems such as data silos, low processing efficiency, inaccurate analysis and prediction, and it is difficult to meet the needs of virtual power plants for comprehensive, efficient and intelligent management of energy data. Therefore, a new type of virtual power plant data management system and method is urgently needed to solve the above problems and realize the intelligent operation and sustainable development of virtual power plants. Summary of the invention

[0004] In order to overcome the above-mentioned defects of the prior art, the present invention provides a virtual power plant data management system and method thereof.

[0005] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: a virtual power plant data management system, comprising a data acquisition and transmission module, a data processing and storage module, a data analysis and prediction module, a carbon footprint tracking and emission reduction optimization unit, an energy management and scheduling module, an energy market analysis and trading module, a blockchain energy trading and settlement module, a fault diagnosis and early warning module, a user interaction and display module, a safety and operation and maintenance management module, and a VR and AR training module, wherein the output end of the data acquisition and transmission module is connected to the input end of the data processing and storage module; The output end of the data processing and storage module is connected to the input end of the data analysis and prediction module; The output end of the data analysis and prediction module is connected to the input end of the carbon footprint tracking and emission reduction optimization unit; The output end of the carbon footprint tracking and emission reduction optimization unit is connected to the input end of the energy management and scheduling module; The output end of the energy management and scheduling module is connected to the input end of the energy market analysis and trading module; The connection end of the energy market analysis and transaction module interacts with the connection end of the blockchain energy transaction and settlement module; The connection end of the blockchain energy transaction and settlement module interacts with the connection end of the energy management and scheduling module; The connection end of the fault diagnosis and early warning module interacts with the connection end of the energy management and scheduling module; The connection end of the user interaction and display module interacts with the connection ends of the data processing and storage module and the energy management and scheduling module; The connection end of the security and operation and maintenance management module interacts with the connection end of the data acquisition and transmission module, the data processing and storage module, the data analysis and prediction module, the carbon footprint tracking and emission reduction optimization unit, the energy management and scheduling module, the energy market analysis and trading module, the blockchain energy trading and settlement module, the fault diagnosis and early warning module, the user interaction and display module and the VR and AR training module; The connection end of the VR and AR training module interacts with the connection end of the security and operation and maintenance management module.

[0006] As a further improvement of the technical solution of the present invention, the data acquisition and transmission module is used to collect real-time data from various energy devices, sensors, and users, including power, voltage, current, temperature, humidity, and fuel consumption, and transmit these data safely and reliably to the data processing center; the data processing and storage module is used to clean, verify, convert and store the collected data to ensure the accuracy, completeness and availability of the data, and at the same time, provide a data access interface to support data query and analysis requirements of other modules.

[0007] As a further improvement of the technical solution of the present invention, the data analysis and prediction module is used to use machine learning, statistical analysis and other methods to conduct in-depth analysis of the processed data, explore the patterns of energy use, predict future energy demand and price trends, and at the same time, combine carbon footprint tracking data to evaluate the environmental performance of energy use.

[0008] As a further improvement of the technical solution of the present invention, the carbon footprint tracking and emission reduction optimization unit calculates and tracks the carbon footprint of the virtual power plant during operation based on energy usage data and emission factors, and proposes emission reduction suggestions and optimization plans to help the virtual power plant reduce carbon emissions and achieve environmental protection goals. The implementation steps of the carbon footprint tracking and emission reduction optimization unit are as follows: S1. Determine the tracking scope, clarify the energy equipment, network, users, etc. covered by the virtual power plant, and identify the main carbon emission sources in the region, such as power generation equipment, energy storage systems, transmission line losses, etc.; S2. Data collection and integration: Obtain detailed energy usage data from the data collection and transmission module, including electricity, heat, fuel consumption, etc., collect carbon emission factors of various energy types, which are usually provided by the government or industry organizations and are used to convert energy usage into carbon emissions. They also include equipment operating time, efficiency, load, etc., to more accurately calculate carbon emissions; S3. Establish a carbon emission model. Based on energy usage data and emission factors, establish an activity-based carbon emission model to calculate the carbon emissions of each activity or equipment, and consider the carbon emissions of the equipment throughout its life cycle from production, operation to scrapping, so as to more comprehensively evaluate the carbon footprint; S4. Real-time monitoring and dynamic updating: Use IoT sensors to monitor the operating status and emissions of energy equipment in real time, ensuring that the carbon emission model can be dynamically updated as new data arrives to reflect actual carbon emissions; S5. Spatial analysis and visualization: using GIS technology to combine carbon emission data with geographic spatial information for spatial analysis and visualization; S6. Emission reduction optimization and strategy formulation: evaluate the feasibility and cost-effectiveness of various emission reduction technologies, such as improving energy efficiency and adopting clean energy, and formulate specific emission reduction strategies and implementation plans based on carbon emission data and emission reduction technology assessment results.

[0009] As a further improvement of the technical solution of the present invention, the energy management and scheduling module is used to formulate and execute energy management and scheduling plans based on data analysis and prediction results and carbon footprint tracking information, including energy distribution, equipment scheduling, energy storage charging and discharging strategies, etc., to ensure efficient, stable and environmentally friendly use of energy; the energy market analysis and trading module is used to monitor and analyze energy market prices, supply and demand conditions, policy dynamics, etc. in real time, to provide decision support for virtual power plants to participate in energy market transactions, and at the same time, automatically or assist in formulating trading strategies based on market conditions and the energy conditions of the virtual power plant, and conduct trading operations such as energy buying and selling, energy storage charging and discharging.

[0010] As a further improvement of the technical solution of the present invention, the blockchain energy trading and settlement module is used to utilize the decentralization, transparency and immutability of blockchain technology to build a distributed ledger for energy transactions, realize instant settlement of energy transactions, execution of smart contracts and establishment of a credit system, reduce transaction costs, improve transaction efficiency, and enhance the transparency and fairness of the energy market; the fault diagnosis and early warning module is used to timely detect equipment failures or abnormal conditions through real-time monitoring and analysis of equipment operating status, energy usage data, etc., and issue early warning signals. At the same time, it provides fault diagnosis and positioning functions to help operation and maintenance personnel quickly find the problem, reduce fault handling time, and improve system reliability.

[0011] As a further improvement of the technical solution of the present invention, the user interaction and display module provides a friendly user interface and interactive mode to display the operation status, energy usage, carbon emission data and emission reduction results of the virtual power plant. At the same time, it supports functions such as user query, report generation and customized services; the security and operation and maintenance management module is responsible for the system's security protection, fault monitoring, backup and recovery, and daily operation and maintenance management, ensuring the stable operation of the system and the security and reliability of data.

[0012] As a further improvement of the technical solution of the present invention, the VR and AR training module is used to utilize VR and AR technologies to provide an immersive training and simulation environment for operators and maintenance personnel, thereby improving training effectiveness, reducing training costs, and enhancing the ability to respond to emergencies by simulating equipment operation, troubleshooting, and the like in real scenarios.

[0013] A virtual power plant data management method, the specific method steps are as follows: Step 1: Data collection and transmission: using the Internet of Things technology and sensor networks to collect raw data from energy equipment, sensors, users, etc. in real time, and transmit the data to the data processing and storage module through a secure and reliable communication protocol; Step 2: Data processing and storage: clean, verify, convert and store the original data to ensure the accuracy and completeness of the data, establish a data warehouse and database to provide support for subsequent data analysis and prediction; Step 3: Data analysis and prediction: Use machine learning algorithms and statistical analysis tools to conduct in-depth analysis of the processed data, predict future energy demand and price trends, and evaluate the environmental performance of energy use; Step 4: Carbon footprint tracking and emission reduction optimization: Based on the data analysis results, calculate and track the carbon footprint of the virtual power plant during operation, put forward emission reduction suggestions and optimization plans, reduce carbon emissions and achieve environmental protection goals; Step 5: Energy management and scheduling: Based on data analysis and prediction results and carbon footprint tracking information, formulate energy management and scheduling plans, adjust energy distribution and equipment scheduling in real time, and ensure efficient, stable and environmentally friendly use of energy; Step 6: User interaction and display: Through the user interface and interactive methods, the operation status, energy usage, carbon emission data, etc. of the virtual power plant are displayed, and user query, report generation and customization services are provided to enhance user participation and satisfaction. Step 7: Security and operation and maintenance management: implement system security protection measures, monitor fault conditions, perform backup and recovery and daily operation and maintenance in a timely manner, and use VR / AR training modules to improve the skills of operation and maintenance personnel and their ability to respond to emergencies; Step 8: Energy market analysis and trading: real-time monitoring and analysis of energy market prices and supply and demand, providing decision support for energy trading, and using blockchain technology to achieve transparent, secure and efficient settlement of energy transactions; Step 9: Fault diagnosis and early warning: monitor the operating status of equipment, promptly detect and warn of faults, quickly respond to faults, and reduce downtime and maintenance costs.

[0014] Beneficial effects of the present invention: The system of the present invention can collect raw data from various energy equipment, sensors and users in real time and accurately, and conduct in-depth analysis of the processed data, explore the laws of energy use, predict future energy demand and price trends, and provide a scientific basis for energy management and scheduling. At the same time, it evaluates the environmental performance of energy use, helps virtual power plants achieve green operation, and proposes emission reduction suggestions and optimization plans by calculating and tracking the carbon footprint during the operation of virtual power plants, helping virtual power plants reduce carbon emissions and achieve environmental protection goals, thereby enhancing the sustainable development capabilities of virtual power plants. It monitors and analyzes energy market prices, supply and demand conditions in real time, and provides decision-making support for virtual power plants to participate in energy market transactions. At the same time, it uses blockchain technology to achieve transparent, secure and efficient settlement of energy transactions, reduces transaction costs, and improves transaction efficiency. It uses VR and AR training modules to provide operators and maintenance personnel with an immersive training and simulation environment, and simulates equipment operation, fault handling and other situations in real scenarios to improve training effects, reduce training costs, and enhance the ability to respond to emergencies. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 Schematic diagram of the virtual power plant data management system of the present invention.

[0016] Figure 2 This is a flow chart of the virtual power plant data management method of the present invention.

[0017] The accompanying drawings are marked as follows: 1. Data acquisition and transmission module; 2. Data processing and storage module; 3. Data analysis and prediction module; 4. Carbon footprint tracking and emission reduction optimization unit; 5. Energy management and scheduling module; 6. Energy market analysis and trading module; 7. Blockchain energy trading and settlement module; 8. Fault diagnosis and early warning module; 9. User interaction and display module; 10. Security and operation and maintenance management module; 11. VR and AR training module. DETAILED DESCRIPTION

[0018] 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.

[0019] As attached Figure 1 A virtual power plant data management system shown includes a data acquisition and transmission module 1, a data processing and storage module 2, a data analysis and prediction module 3, a carbon footprint tracking and emission reduction optimization unit 4, an energy management and scheduling module 5, an energy market analysis and trading module 6, a blockchain energy trading and settlement module 7, a fault diagnosis and early warning module 8, a user interaction and display module 9, a safety and operation and maintenance management module 10 and a VR and AR training module 11, wherein the output end of the data acquisition and transmission module 1 is connected to the input end of the data processing and storage module 2; The output end of the data processing and storage module 2 is connected to the input end of the data analysis and prediction module 3; The output end of the data analysis and prediction module 3 is connected to the input end of the carbon footprint tracking and emission reduction optimization unit 4; The output end of the carbon footprint tracking and emission reduction optimization unit 4 is connected to the input end of the energy management and scheduling module 5; The output end of the energy management and scheduling module 5 is connected to the input end of the energy market analysis and transaction module 6; The connection end of the energy market analysis and transaction module 6 interacts with the connection end of the blockchain energy transaction and settlement module 7; The connection end of the blockchain energy transaction and settlement module 7 interacts with the connection end of the energy management and scheduling module 5; The connection end of the fault diagnosis and early warning module 8 interacts with the connection end of the energy management and scheduling module 5; The connection end of the user interaction and display module 9 interacts with the connection ends of the data processing and storage module 2 and the energy management and scheduling module 5; The connection end of the security and operation and maintenance management module 10 interacts with the connection end of the data acquisition and transmission module 1, the data processing and storage module 2, the data analysis and prediction module 3, the carbon footprint tracking and emission reduction optimization unit 4, the energy management and scheduling module 5, the energy market analysis and transaction module 6, the blockchain energy transaction and settlement module 7, the fault diagnosis and early warning module 8, the user interaction and display module 9 and the VR and AR training module 11; The connection end of the VR and AR training module 11 interacts with the connection end of the security and operation and maintenance management module 10 .

[0020] The data acquisition and transmission module 1 is used to collect real-time data from various energy devices, sensors, and users, including power, voltage, current, temperature, humidity, and fuel consumption, and transmit these data to the data processing center safely and reliably; Among them, the data processing and storage module 2 is used to clean, verify, convert and store the collected data to ensure the accuracy, completeness and availability of the data. At the same time, it provides a data access interface to support the data query and analysis needs of other modules.

[0021] Among them, the data analysis and prediction module 3 is used to use machine learning, statistical analysis and other methods to conduct in-depth analysis of the processed data, explore the patterns of energy use, predict future energy demand and price trends, and at the same time, combine carbon footprint tracking data to evaluate the environmental performance of energy use.

[0022] Among them, the carbon footprint tracking and emission reduction optimization unit 4 calculates and tracks the carbon footprint of the virtual power plant during operation based on energy usage data and emission factors, and puts forward emission reduction suggestions and optimization plans to help the virtual power plant reduce carbon emissions and achieve environmental protection goals. The implementation steps of the carbon footprint tracking and emission reduction optimization unit 4 are as follows: S1. Determine the tracking scope, clarify the energy equipment, network, users, etc. covered by the virtual power plant, and identify the main carbon emission sources in the region, such as power generation equipment, energy storage systems, transmission line losses, etc.; S2. Data collection and integration: Obtain detailed energy usage data from the data collection and transmission module, including electricity, heat, fuel consumption, etc., collect carbon emission factors of various energy types, which are usually provided by the government or industry organizations and are used to convert energy usage into carbon emissions. They also include equipment operating time, efficiency, load, etc., to more accurately calculate carbon emissions; S3. Establish a carbon emission model. Based on energy usage data and emission factors, establish an activity-based carbon emission model to calculate the carbon emissions of each activity or equipment, and consider the carbon emissions of the equipment throughout its life cycle from production, operation to scrapping, so as to more comprehensively evaluate the carbon footprint; S4. Real-time monitoring and dynamic updating: Use IoT sensors to monitor the operating status and emissions of energy equipment in real time, ensuring that the carbon emission model can be dynamically updated as new data arrives to reflect actual carbon emissions; S5. Spatial analysis and visualization: using GIS technology to combine carbon emission data with geographic spatial information for spatial analysis and visualization; S6. Emission reduction optimization and strategy formulation: evaluate the feasibility and cost-effectiveness of various emission reduction technologies, such as improving energy efficiency and adopting clean energy, and formulate specific emission reduction strategies and implementation plans based on carbon emission data and emission reduction technology assessment results.

[0023] Among them, the energy management and scheduling module 5 is used to formulate and implement energy management and scheduling plans based on data analysis and prediction results and carbon footprint tracking information, including energy distribution, equipment scheduling, energy storage charging and discharging strategies, etc., to ensure efficient, stable and environmentally friendly use of energy; Among them, the energy market analysis and transaction module 6 is used to monitor and analyze energy market prices, supply and demand, policy dynamics, etc. in real time, and provide decision support for virtual power plants to participate in energy market transactions. At the same time, according to market conditions and the energy status of virtual power plants, trading strategies are automatically or assisted to carry out trading operations such as energy buying and selling, energy storage charging and discharging, etc.

[0024] Among them, the blockchain energy transaction and settlement module 7 is used to utilize the decentralization, transparency and immutability of blockchain technology to build a distributed ledger for energy transactions, realize instant settlement of energy transactions, smart contract execution and establishment of a credit system, reduce transaction costs, improve transaction efficiency, and enhance the transparency and fairness of the energy market; Among them, the fault diagnosis and early warning module 8 is used to timely detect equipment failures or abnormal conditions and issue early warning signals through real-time monitoring and analysis of equipment operating status, energy usage data, etc. At the same time, it provides fault diagnosis and positioning functions to help operation and maintenance personnel quickly find the problem, reduce fault handling time, and improve system reliability.

[0025] Among them, the user interaction and display module 9 provides a friendly user interface and interactive mode to display the operation status, energy usage, carbon emission data and emission reduction results of the virtual power plant, and supports user query, report generation and customized service functions; The security and operation and maintenance management module 10 is responsible for the system's security protection, fault monitoring, backup and recovery, and daily operation and maintenance management to ensure the stable operation of the system and the security and reliability of data.

[0026] Among them, the VR and AR training module 11 is used to use VR and AR technology to provide an immersive training and simulation environment for operators and maintenance personnel. By simulating equipment operation, troubleshooting and other situations in real scenarios, it improves training effectiveness, reduces training costs, and enhances the ability to respond to emergencies.

[0027] As attached Figure 2 As shown, a virtual power plant data management method, the specific method steps are as follows: Step 1: Data collection and transmission: using the Internet of Things technology and sensor networks to collect raw data from energy equipment, sensors, users, etc. in real time, and transmit the data to the data processing and storage module through a secure and reliable communication protocol; Step 2: Data processing and storage: clean, verify, convert and store the original data to ensure the accuracy and completeness of the data, establish a data warehouse and database to provide support for subsequent data analysis and prediction; Step 3: Data analysis and prediction: Use machine learning algorithms and statistical analysis tools to conduct in-depth analysis of the processed data, predict future energy demand and price trends, and evaluate the environmental performance of energy use; Step 4: Carbon footprint tracking and emission reduction optimization: Based on the data analysis results, calculate and track the carbon footprint of the virtual power plant during operation, put forward emission reduction suggestions and optimization plans, reduce carbon emissions and achieve environmental protection goals; Step 5: Energy management and scheduling: Based on data analysis and prediction results and carbon footprint tracking information, formulate energy management and scheduling plans, adjust energy distribution and equipment scheduling in real time, and ensure efficient, stable and environmentally friendly use of energy; Step 6: User interaction and display: Through the user interface and interactive methods, the operation status, energy usage, carbon emission data, etc. of the virtual power plant are displayed, and user query, report generation and customization services are provided to enhance user participation and satisfaction. Step 7: Security and operation and maintenance management: implement system security protection measures, monitor fault conditions, perform backup and recovery and daily operation and maintenance in a timely manner, and use VR and AR training modules 11 to improve the skills of operation and maintenance personnel and their ability to respond to emergencies; Step 8: Energy market analysis and trading: real-time monitoring and analysis of energy market prices and supply and demand, providing decision support for energy trading, and using blockchain technology to achieve transparent, secure and efficient settlement of energy transactions; Step 9: Fault diagnosis and early warning: monitor the operating status of equipment, promptly detect and warn of faults, quickly respond to faults, and reduce downtime and maintenance costs.

[0028] In summary, the present invention uses the data acquisition and transmission module 1, the system can collect raw data from various energy devices, sensors and users in real time and accurately, and clean, verify, convert and store the data through the data processing and storage module 2, ensuring the accuracy, integrity and availability of the data, and providing a solid foundation for subsequent data analysis and prediction; Data analysis and prediction module 3 uses machine learning algorithms and statistical analysis tools to conduct in-depth analysis of processed data, explore energy usage patterns, and predict future energy demand and price trends, providing a scientific basis for energy management and scheduling. It also evaluates the environmental performance of energy use and helps virtual power plants achieve green operations. Carbon footprint tracking and emission reduction optimization module 4 calculates and tracks the carbon footprint of virtual power plants during operation, proposes emission reduction suggestions and optimization plans, helps virtual power plants reduce carbon emissions, achieve environmental protection goals, and enhance the sustainable development capabilities of virtual power plants; Energy management and scheduling module 5 formulates and implements energy management and scheduling plans based on data analysis and prediction results and carbon footprint tracking information, ensuring efficient, stable and environmentally friendly use of energy and improving the operational efficiency and economic benefits of the virtual power plant; Energy market analysis and transaction module 6 monitors and analyzes energy market prices, supply and demand in real time, provides decision support for virtual power plants to participate in energy market transactions, and uses blockchain technology to achieve transparent, secure and efficient settlement of energy transactions, reducing transaction costs and improving transaction efficiency; Fault diagnosis and early warning module 8 monitors and analyzes equipment operation status and energy usage data in real time, promptly discovers and warns of faults, helps operation and maintenance personnel quickly find and handle problems, reduces downtime and maintenance costs, and improves system reliability and stability; The user interaction and display module 9 provides a friendly user interface and interactive mode, showing the operation status, energy usage, carbon emission data, etc. of the virtual power plant, enhancing user participation and satisfaction, and also establishing a good social image for the virtual power plant; The security and operation and maintenance management module 10 is responsible for the system's security protection, fault monitoring, backup and recovery, and daily operation and maintenance management, ensuring the stable operation of the system and the security and reliability of data. At the same time, the VR and AR training module 11 is used to improve the skills of the operation and maintenance personnel and their ability to respond to emergencies, further improving the system's operation and maintenance efficiency.

[0029] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A virtual power plant data management system, characterized by: It comprises a data collection and transmission module (1), a data processing and storage module (2), a data analysis and prediction module (3), a carbon footprint tracking and emission reduction optimization unit (4), an energy management and scheduling module (5), an energy market analysis and trading module (6), a blockchain energy trading and settlement module (7), a fault diagnosis and early warning module (8), a user interaction and display module (9), a safety and operation and maintenance management module (10) and a VR and AR training module (11), wherein the output end of the data collection and transmission module (1) is connected to the input end of the data processing and storage module (2); The output end of the data processing and storage module (2) is connected to the input end of the data analysis and prediction module (3); The output end of the data analysis and prediction module (3) is connected to the input end of the carbon footprint tracking and emission reduction optimization unit (4); The output end of the carbon footprint tracking and emission reduction optimization unit (4) is connected to the input end of the energy management and scheduling module (5); The output end of the energy management and scheduling module (5) is connected to the input end of the energy market analysis and transaction module (6); The connection end of the energy market analysis and transaction module (6) interacts with the connection end of the blockchain energy transaction and settlement module (7); The connection end of the blockchain energy transaction and settlement module (7) interacts with the connection end of the energy management and scheduling module (5); The connection end of the fault diagnosis and early warning module (8) interacts with the connection end of the energy management and scheduling module (5); The connection end of the user interaction and display module (9) interacts with the connection ends of the data processing and storage module (2) and the energy management and scheduling module (5); The connection end of the security and operation and maintenance management module (10) interacts with the connection ends of the data acquisition and transmission module (1), the data processing and storage module (2), the data analysis and prediction module (3), the carbon footprint tracking and emission reduction optimization unit (4), the energy management and scheduling module (5), the energy market analysis and trading module (6), the blockchain energy trading and settlement module (7), the fault diagnosis and early warning module (8), the user interaction and display module (9) and the VR and AR training module (11); The connection end of the VR and AR training module (11) interacts with the connection end of the security and operation and maintenance management module (10).

2. The virtual power plant data management system according to claim 1, characterized in that: The data acquisition and transmission module (1) is used to collect real-time data from various energy devices, sensors, and users, including power, voltage, current, temperature, humidity, and fuel consumption, and to transmit these data securely and reliably to a data processing center; the data processing and storage module (2) is used to clean, verify, convert, and store the collected data.

3. The virtual power plant data management system according to claim 1, characterized in that: The data analysis and prediction module (3) is used to use machine learning or statistical analysis methods to conduct in-depth analysis on the processed data, explore energy use patterns, predict future energy demand and price trends, and at the same time, combine carbon footprint tracking data to evaluate the environmental performance of energy use.

4. The virtual power plant data management system according to claim 1, characterized in that: The carbon footprint tracking and emission reduction optimization unit (4) calculates and tracks the carbon footprint of the virtual power plant during operation based on energy usage data and emission factors, and proposes emission reduction suggestions and optimization plans to help the virtual power plant reduce carbon emissions. The implementation steps of the carbon footprint tracking and emission reduction optimization unit (4) are as follows: S1. Determine the tracking scope, clarify the energy equipment, network, and user scope covered by the virtual power plant, and identify the main carbon emission sources in the region; S2, data collection and integration, obtain detailed energy usage data from the data collection and transmission module, including electricity, heat, fuel consumption, and collect carbon emission factors of various energy types; S3. Establish a carbon emission model. According to energy usage data and emission factors, establish an activity-based carbon emission model to calculate the carbon emissions of each activity or equipment; S4. Real-time monitoring and dynamic updating: IoT sensors are used to monitor the operating status and emissions of energy equipment in real time, so that the carbon emission model can be dynamically updated as new data is input; S5. Spatial analysis and visualization: using GIS technology to combine carbon emission data with geographic spatial information for spatial analysis and visualization; S6. Emission reduction optimization and strategy formulation: evaluate the feasibility and cost-effectiveness of various emission reduction technologies, such as improving energy efficiency and adopting clean energy, and formulate specific emission reduction strategies and implementation plans based on carbon emission data and emission reduction technology assessment results.

5. The virtual power plant data management system according to claim 1, characterized in that: The energy management and scheduling module (5) is used to formulate and execute energy management and scheduling plans based on data analysis and prediction results and carbon footprint tracking information; the energy market analysis and trading module (6) is used to monitor and analyze energy market prices, supply and demand conditions, and policy trends in real time, and provide decision support for virtual power plants to participate in energy market transactions.

6. The virtual power plant data management system according to claim 1, characterized in that: The blockchain energy transaction and settlement module (7) is used to utilize the decentralization, transparency and immutability of blockchain technology to construct a distributed ledger for energy transactions, thereby realizing instant settlement of energy transactions, execution of smart contracts and establishment of a credit system; the fault diagnosis and early warning module (8) is used to timely detect equipment failures or abnormal conditions and issue early warning signals through real-time monitoring and analysis of equipment operating status and energy usage data.

7. The virtual power plant data management system according to claim 1, characterized in that: The user interaction and display module (9) is used to provide a user-friendly interface and interactive mode to display the operating status, energy usage, carbon emission data and emission reduction results of the virtual power plant; the security and operation and maintenance management module (10) is responsible for the system's security protection, fault monitoring, backup and recovery, and daily operation and maintenance management.

8. The virtual power plant data management system according to claim 1, characterized in that: The VR and AR training module (11) is used to provide an immersive training and simulation environment for operating personnel and maintenance personnel using VR and AR technologies.

9. A virtual power plant data management method, according to a virtual power plant data management system according to any one of claims 1 to 8, characterized in that: The specific steps are as follows: Step 1: Data collection and transmission: using the Internet of Things technology and sensor networks to collect raw data from energy equipment, sensors, and users in real time, and transmit the data to the data processing and storage module through a secure and reliable communication protocol; Step 2: Data processing and storage: clean, verify, convert and store the original data, establish a data warehouse and database to provide support for subsequent data analysis and prediction; Step 3: Data analysis and prediction: Use machine learning algorithms and statistical analysis tools to conduct in-depth analysis of the processed data, predict future energy demand and price trends, and evaluate the environmental performance of energy use; Step 4: Carbon footprint tracking and emission reduction optimization: Based on the data analysis results, calculate and track the carbon footprint of the virtual power plant during operation, and put forward emission reduction suggestions and optimization plans; Step 5: Energy management and scheduling: Based on data analysis and prediction results and carbon footprint tracking information, formulate energy management and scheduling plans, and adjust energy distribution and equipment scheduling in real time; Step 6: User interaction and display: Through the user interface and interactive methods, the operation status, energy usage, and carbon emission data of the virtual power plant are displayed, and user query, report generation, and customization services are provided; Step 7: Security and operation and maintenance management: implement system security protection measures, monitor fault conditions, perform backup and recovery and daily operation and maintenance in a timely manner, and use VR / AR training modules to improve the skills of operation and maintenance personnel and their ability to respond to emergencies; Step 8: Energy market analysis and trading: real-time monitoring and analysis of energy market prices and supply and demand, providing decision support for energy trading, and using blockchain technology to achieve transparent, secure and efficient settlement of energy transactions; Step 9: Fault diagnosis and early warning: monitor the equipment operating status, and promptly detect and warn of faults.

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