A hierarchical energy carbon virtual power plant management system for government-enterprise cooperation

Abstract

The application discloses a kind of government-enterprise coordination's layered energy carbon virtual power plant management system, belong to carbon emission control technical field, comprising: resource layer, for gathering energy consumption data and carbon emission data, output original energy carbon data;Data layer, for processing the original energy carbon data, output standardized energy carbon data set;Support layer, for calculating based on the standardized energy carbon data set, output energy carbon management support result;Application service layer, for providing energy carbon management service according to the energy carbon management support result;User layer, for distributing the access authority of energy carbon management service according to user role.The application solves the problem that the existing energy carbon management system lacks government-enterprise coordination mechanism, the data island of each level is serious, it is difficult to realize the unified collection of energy carbon data at regional and enterprise level, accurate prediction, intelligent diagnosis and layered service, leading to the lack of effective linkage between government regulation and enterprise emission reduction.

Description

Technical Field

[0001] This invention relates to a hierarchical energy and carbon virtual power plant management system for government-enterprise collaboration, belonging to the field of carbon emission control technology. Background Technology

[0002] With the increasingly severe global climate change problem, carbon peaking and carbon neutrality strategies have become a common choice for countries around the world to address climate change. As a major carbon emitter, my country bears significant responsibility for emission reduction. Statistics show that while industrial parks at all levels across the country contribute significantly to GDP, they also consume a large amount of energy and emit significant amounts of carbon. Provincial and national-level industrial parks account for 31% of total carbon emissions. Against this backdrop, energy and carbon management systems are gradually becoming important tools to support government regulation and corporate emission reduction. Currently, existing energy and carbon management systems typically adopt a layered architecture. They collect energy consumption and carbon emission data by deploying IoT gateways and smart meters at the resource layer, clean and store the data at the data layer, and provide users with basic functions such as energy and carbon monitoring and reporting at the application layer. Some systems also integrate simple data analysis modules to display energy consumption trends and carbon emission indicators. Furthermore, some systems have introduced third-party interfaces to connect with power supply, gas supply, and water supply platforms, achieving preliminary capabilities for multi-source data aggregation.

[0003] However, existing energy and carbon management systems still have significant shortcomings in practical applications. First, these systems generally lack government-enterprise collaboration mechanisms, with applications on the government and enterprise sides operating in isolation. Data circulates only within their respective systems, making it difficult to form a closed-loop linkage of "government supervision, enterprise implementation, and data feedback." Second, data silos exist between different levels. Multi-source, heterogeneous data collected at the resource layer lacks standardized cleaning and sharing mechanisms after entering the data layer, resulting in inconsistent data quality and difficulty in supporting comprehensive analysis across levels and regions. Third, existing systems lack sufficient support capabilities, mostly remaining at the level of data display and simple statistics. They lack intelligent models for carbon peak prediction and extrapolation, energy and carbon forecasting, energy conservation and carbon reduction diagnosis, and carbon trading strategies, failing to achieve accurate prediction and intelligent diagnosis after unified collection of energy and carbon data at the regional and enterprise levels. These shortcomings make it difficult for the government to effectively supervise and make scientific decisions regarding enterprise carbon emissions within the region, and for enterprises to obtain targeted emission reduction guidance and carbon asset management services. Ultimately, this results in a lack of effective linkage between government supervision and enterprise emission reduction, failing to meet the refined management needs under dual carbon objectives. Summary of the Invention

[0004] The purpose of this invention is to provide a hierarchical energy and carbon virtual power plant management system for government-enterprise collaboration. By constructing a hierarchical energy and carbon virtual power plant management system that includes a resource layer, a data layer, a support layer, an application service layer, and a user layer, it achieves unified collection, standardized processing, multi-model intelligent analysis, and hierarchical application of energy and carbon data. This addresses the problem that existing energy and carbon management systems lack government-enterprise collaboration mechanisms, suffer from severe data silos at each level, and are unable to achieve unified collection, accurate prediction, intelligent diagnosis, and hierarchical services of energy and carbon data at the regional and enterprise levels, resulting in a lack of effective linkage between government supervision and enterprise emission reduction.

[0005] To solve the above-mentioned technical problems, the present invention is implemented using the following technical solution.

[0006] This invention provides a hierarchical energy and carbon virtual power plant management system for government-enterprise collaboration, comprising:

[0007] The resource layer includes an IoT access module, a third-party interface module, and a manual data entry module. The resource layer is used to collect energy consumption data and carbon emission data and output raw energy and carbon data.

[0008] The data layer includes a data cleaning module, a data storage module, and a data sharing and exchange module. The input end of the data layer is connected to the output end of the resource layer. The data layer is used to process the raw energy and carbon data and output a standardized energy and carbon dataset.

[0009] The support layer includes a carbon peak prediction and extrapolation model, an energy carbon prediction model, an energy conservation and carbon reduction diagnostic model, and a carbon trading strategy model. The input end of the support layer is connected to the output end of the data layer. The support layer is used to perform calculations based on the standardized energy carbon dataset and output energy carbon management support results.

[0010] The application service layer includes a government-side application module and an enterprise-side application module. The input end of the application service layer is connected to the output end of the support layer. The application service layer is used to provide energy and carbon management services based on the energy and carbon management support results.

[0011] The user layer includes a role-based access control module, which is connected to the application service layer. The user layer is used to assign access permissions for the energy and carbon management service according to the user's role.

[0012] Furthermore, the IoT access module includes an MQTT protocol adaptation unit, a LoRa protocol adaptation unit, and an RS485 protocol adaptation unit. The IoT access module is used to collect energy consumption data and cold storage energy supply data.

[0013] The third-party interface module includes a RESTful API interface unit and an SSL / TLS encrypted transmission unit, used to obtain data from third-party platforms;

[0014] The manual data entry module includes a standardized data entry template unit, a web-based data entry interface unit, and a mobile data entry interface unit, used to receive data to be entered.

[0015] The resource layer is connected to the IoT access module, the third-party interface module, and the manual data entry module, respectively, and is used to integrate the energy consumption data and cold storage energy supply data collected by the IoT access module, the third-party platform data obtained by the third-party interface module, and the data entry data received by the manual data entry module to form the raw energy carbon data.

[0016] Furthermore, the third-party interface module is connected to the power supply company platform, gas company platform, and water company platform.

[0017] Furthermore, the data cleaning module includes a data deduplication unit, an outlier filtering unit, and a missing value interpolation and completion unit. The input end of the data cleaning module is connected to the output end of the resource layer, and the output end of the data cleaning module outputs the cleaned raw energy and carbon data.

[0018] The data storage module includes a distributed database Hadoop and a time-series database InfluxDB. The input end of the data storage module is connected to the output end of the data cleaning module. The data storage module partitions and stores the cleaned raw energy and carbon data according to the time field and the enterprise number field.

[0019] The data sharing and exchange module includes a data publishing unit, a data subscription unit, a data query unit, and an HTTPS transmission protocol unit. The input end of the data sharing and exchange module is connected to the output end of the data storage module. The data sharing and exchange module is used to provide the government with an aggregated data view of enterprises in the region and to provide the enterprises with a detailed data view of their own enterprises based on the cleaned raw energy and carbon data.

[0020] Furthermore, the carbon peak prediction and extrapolation model is an LSTM network model. The input of the carbon peak prediction and extrapolation model is historical carbon emissions, energy structure, industrial structure and time series data. The output of the carbon peak prediction and extrapolation model is the carbon emissions, peak year and carbon peak value in the first future time period. The unit of the first future time period is years.

[0021] The energy and carbon prediction model is an LSTM network model. The input of the energy and carbon prediction model is historical electricity consumption, historical heat consumption, historical water consumption, historical gas consumption, meteorological data and production load data. The output of the energy and carbon prediction model is the energy consumption and carbon emissions in the second future time period, and the unit of the second future time period is hours.

[0022] The energy-saving and carbon-reduction diagnostic model is a K-Means clustering model. The input of the energy-saving and carbon-reduction diagnostic model is the enterprise's equipment energy consumption data and enterprise carbon emission data. The output of the energy-saving and carbon-reduction diagnostic model is the energy consumption equipment clustering result and the emission reduction priority ranking result.

[0023] The carbon trading strategy model includes a rules engine unit and a Pearson correlation analysis unit. The input of the carbon trading strategy model is carbon price data, enterprise emission data, and enterprise quota data. The output of the carbon trading strategy model is trading timing and trading volume.

[0024] Furthermore, the government-side application module includes:

[0025] The regional energy carbon cockpit unit includes a map display subunit, a bar chart display subunit, and a line chart display subunit. The input end of the regional energy carbon cockpit unit is connected to the output end of the support layer.

[0026] The regional carbon emission inventory management unit is used to store direct and indirect carbon emission data of enterprises within the region.

[0027] The regional energy and carbon analysis tool unit includes a comparative analysis subunit, a trend analysis subunit, and a factor analysis subunit. The input end of the regional energy and carbon analysis tool unit is connected to the output end of the data sharing and exchange module.

[0028] The carbon peaking pilot evaluation unit includes an evaluation index storage subunit and a monitoring and evaluation subunit. The input end of the carbon peaking pilot evaluation unit is connected to the output end of the carbon peaking prediction and extrapolation model.

[0029] A carbon peak prediction and management unit, wherein the input end of the carbon peak prediction and management unit is connected to the output end of the carbon peak prediction and prediction model.

[0030] Furthermore, the enterprise-side application module includes:

[0031] The corporate carbon account unit includes a dashboard unit, the input of which is connected to the output of the data sharing and exchange module;

[0032] The energy and carbon monitoring unit includes a multi-dimensional data display subunit and a threshold judgment subunit. The input end of the energy and carbon monitoring unit is connected to the output end of the Internet of Things access module. The threshold judgment subunit outputs a prompt signal when the energy consumption data exceeds a preset threshold.

[0033] The organization's carbon footprint accounting unit includes a data acquisition subunit, an emission factor management subunit, a carbon emission accounting subunit, and a report generation subunit. The input end of the organization's carbon footprint accounting unit is connected to the output end of the data sharing and exchange module.

[0034] A carbon assessment management unit, wherein the input end of the carbon assessment management unit is connected to the output end of the data sharing and exchange module, and the output end of the carbon assessment management unit outputs the carbon efficiency level classification results;

[0035] The carbon governance unit includes a strategy recommendation subunit and a project tracking subunit. The input of the strategy recommendation subunit is connected to the output of the energy-saving and carbon-reduction diagnostic model, and the input of the project tracking subunit is connected to the output of the data sharing and exchange module.

[0036] Furthermore, the role-based access control module includes:

[0037] The role storage unit is used to store the roles of super administrator, government administrator, enterprise administrator, and platform operation and maintenance personnel.

[0038] The permission allocation unit, connected to the role storage unit, is used to allocate permissions to each role;

[0039] The permission verification unit is connected to the application service layer and is used to output permission control signals to the application service layer according to the user's role when the user logs in.

[0040] Compared with the prior art, the beneficial effects achieved by the present invention are as follows:

[0041] 1. This invention constructs a five-layer architecture consisting of a resource layer, a data layer, a support layer, an application service layer, and a user layer. The resource layer, through an IoT access module, a third-party interface module, and a manual data entry module, achieves unified collection of multi-source energy carbon data. The data layer, through a data cleaning module and a data sharing and exchange module, outputs standardized energy carbon datasets. The support layer, based on the standardized energy carbon datasets, outputs energy carbon management support results through carbon peak prediction and extrapolation models, energy carbon prediction models, energy conservation and carbon reduction diagnostic models, and carbon trading strategy models. The application service layer, through government-side application modules and enterprise-side application modules, provides differentiated energy carbon management services to the government and enterprises respectively. The user layer, through a role-based access control module, assigns corresponding access permissions to different user roles, forming a closed-loop government-enterprise collaboration mechanism of "government supervision, enterprise execution, and data feedback." This solves the problems of lacking a government-enterprise collaboration mechanism and severe data silos at various levels in existing technologies, achieving unified collection, accurate prediction, intelligent diagnosis, and tiered services of energy carbon data at the regional and enterprise levels, and promoting effective linkage between government supervision and enterprise emission reduction.

[0042] 2. This invention sets up an IoT access module, a third-party interface module, and a manual data entry module at the resource layer. The IoT access module includes an MQTT protocol adaptation unit, a LoRa protocol adaptation unit, and an RS485 protocol adaptation unit for collecting energy consumption data and cold storage energy supply data. The third-party interface module obtains data from third-party platforms such as the power supply company platform, gas company platform, and water company platform through a RESTful API interface unit and an SSL / TLS encrypted transmission unit. The manual data entry module receives the data through a standardized data entry template unit, a web-based entry interface unit, and a mobile entry interface unit. The resource layer integrates the data to form raw energy and carbon data, realizing the comprehensive aggregation and unified collection of multi-source heterogeneous data, and solving the problems of scattered data sources and single collection methods in the prior art.

[0043] 3. This invention establishes a carbon peak prediction and extrapolation model, an energy-carbon prediction model, an energy-saving and carbon reduction diagnostic model, and a carbon trading strategy model through a support layer. The carbon peak prediction and extrapolation model uses an LSTM network model to input historical carbon emissions, energy structure, industrial structure, and time-series data, outputting the carbon emissions, peak year, and peak carbon value for the first future time period. The energy-carbon prediction model uses an LSTM network model to input historical electricity consumption, historical heat consumption, historical water consumption, historical gas consumption, meteorological data, and production load data, outputting energy consumption and carbon emissions for the second future time period. The energy-saving and carbon reduction diagnostic model uses a K-Means clustering model to input enterprise equipment energy consumption data and enterprise carbon emission data, outputting energy-consuming equipment clustering results and emission reduction priority ranking results. The carbon trading strategy model, through a rule engine unit and a Pearson correlation analysis unit, inputs carbon price data, enterprise emission data, and enterprise quota data, outputting trading opportunities and trading volumes. This achieves accurate prediction, intelligent diagnosis, and carbon trading strategy support for energy-carbon data at the regional and enterprise levels, solving the problems of insufficient artificial intelligence algorithm support and inadequate prediction and decision-making capabilities in existing technologies.

[0044] 4. This invention sets up government-side and enterprise-side application modules through the application service layer, and assigns access permissions through the user layer's role-based access control module. The government-side application module provides the government with aggregated data views of enterprises within the region and carbon peaking simulation management services through the regional energy and carbon dashboard unit, regional carbon emission inventory management unit, regional energy and carbon analysis tool unit, carbon peaking pilot evaluation unit, and carbon peaking simulation management unit. The enterprise-side application module provides enterprises with detailed data views of their own enterprises and energy-saving and carbon-reduction strategy recommendations through the enterprise carbon account unit, energy and carbon monitoring unit, organizational carbon footprint accounting unit, carbon evaluation management unit, and carbon governance unit. At the same time, the user layer stores the roles of super administrator, government management personnel, enterprise management personnel, and platform operation and maintenance personnel through the role storage unit, and implements hierarchical access control through the permission allocation unit and permission verification unit. This forms a government-enterprise collaborative closed loop of "government supervision, enterprise execution, and data feedback", which solves the problem of the disconnect and lack of effective linkage between government-side and enterprise-side applications in the existing technology, and realizes layered services and refined management at the regional and enterprise levels. Attached Figure Description

[0045] Figure 1 This is a schematic diagram of a hierarchical energy and carbon virtual power plant management system for government-enterprise collaboration provided in an embodiment of the present invention. Detailed Implementation

[0046] The technical solution of the present invention will be described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the embodiments of the present invention and the specific features in the embodiments are detailed descriptions of the technical solution of the present invention, rather than limitations thereof. In the absence of conflict, the embodiments of the present invention and the technical features in the embodiments can be combined with each other.

[0047] Example 1

[0048] like Figure 1 As shown in the figure, this embodiment introduces a hierarchical energy and carbon virtual power plant management system for government-enterprise collaboration, including:

[0049] The resource layer includes an IoT access module, a third-party interface module, and a manual data entry module. This resource layer is used to collect energy consumption data and carbon emission data, and output raw energy and carbon data. In this embodiment, the resource layer is configured with an IoT access module, a third-party interface module, and a manual data entry module. The IoT access module collects energy consumption data and cold storage energy supply data, the third-party interface module acquires data from third-party platforms, and the manual data entry module receives and submits data. The resource layer integrates the aforementioned multi-source data to form raw energy and carbon data, achieving comprehensive aggregation and unified collection of energy and carbon emission data. This solves the problems of scattered data sources, single collection methods, and difficulty in integrating multi-source data in existing technologies.

[0050] In this embodiment, the IoT access module includes an MQTT protocol adaptation unit, a LoRa protocol adaptation unit, and an RS485 protocol adaptation unit. The IoT access module is used to collect energy consumption data and cold storage energy supply data. The third-party interface module includes a RESTful API interface unit and an SSL / TLS encrypted transmission unit, used to acquire data from third-party platforms. The manual data entry module includes a standardized data entry template unit, a web-based entry interface unit, and a mobile entry interface unit, used to receive data. The resource layer is connected to the IoT access module, the third-party interface module, and the manual data entry module, respectively, and is used to integrate the energy consumption data and cold storage energy supply data collected by the IoT access module, the third-party platform data acquired by the third-party interface module, and the data received by the manual data entry module to form the raw energy carbon data.

[0051] In this embodiment, the third-party interface module is connected to the power supply company platform, the gas company platform, and the water company platform.

[0052] The data layer includes a data cleaning module, a data storage module, and a data sharing and exchange module. The input end of the data layer is connected to the output end of the resource layer. The data layer is used to process the raw energy carbon data and output a standardized energy carbon dataset. In this embodiment, the data layer is configured with a data cleaning module, a data storage module, and a data sharing and exchange module. The data cleaning module cleans the raw energy carbon data through a data deduplication unit, an outlier filtering unit, and a missing value interpolation and completion unit. The data storage module stores the data in partitions according to the time field and the enterprise number field using the distributed database Hadoop and the time-series database InfluxDB. The data sharing and exchange module provides the government with an aggregated data view of enterprises within the region and provides the enterprises with a detailed data view of their own enterprises through a data publishing unit, a data subscription unit, a data query unit, and an HTTPS transmission protocol unit. This realizes the standardized processing and hierarchical sharing of raw energy carbon data, and solves the problems of inconsistent data quality and difficulties in cross-level data sharing in the prior art.

[0053] In this embodiment, the data cleaning module includes a data deduplication unit, an outlier filtering unit, and a missing value interpolation and completion unit. The input of the data cleaning module is connected to the output of the resource layer, and the output of the data cleaning module outputs the cleaned raw energy and carbon data. The data storage module includes a distributed database Hadoop and a time-series database InfluxDB. The input of the data storage module is connected to the output of the data cleaning module, and the data storage module partitions the cleaned raw energy and carbon data according to a time field and an enterprise number field. The data sharing and exchange module includes a data publishing unit, a data subscription unit, a data query unit, and an HTTPS transmission protocol unit. The input of the data sharing and exchange module is connected to the output of the data storage module, and the data sharing and exchange module is used to provide the government with an aggregated data view of enterprises within the region and to provide enterprises with a detailed data view of their own enterprises based on the cleaned raw energy and carbon data.

[0054] The support layer includes a carbon peak prediction and extrapolation model, an energy carbon prediction model, an energy conservation and carbon reduction diagnostic model, and a carbon trading strategy model. The input end of the support layer is connected to the output end of the data layer. The support layer is used to perform calculations based on the standardized energy carbon dataset and output energy carbon management support results. In this embodiment, by setting up a carbon peak prediction and extrapolation model, an energy carbon prediction model, an energy conservation and carbon reduction diagnostic model, and a carbon trading strategy model in the support layer, and performing calculations based on the standardized energy carbon dataset to output energy carbon management support results, accurate prediction, intelligent diagnosis, and carbon trading strategy support for regional and enterprise-level energy carbon data are achieved. This solves the problems of insufficient artificial intelligence algorithm support and inadequate prediction and decision-making capabilities in existing technologies.

[0055] In this embodiment, the carbon peak prediction model is an LSTM network model. The input to the carbon peak prediction model includes historical carbon emissions, energy structure, industrial structure, and time series data. The output of the carbon peak prediction model is the carbon emissions, peak year, and peak carbon value for a first future time period, where the unit of the first future time period is years. The energy carbon prediction model is also an LSTM network model. The input to the energy carbon prediction model includes historical electricity consumption, historical heat consumption, historical water consumption, historical gas consumption, meteorological data, and production load data. The output of the energy carbon prediction model is the carbon emissions for a second future time period. The energy consumption and carbon emissions within a given time period, with the unit for the future second time period being hours; the energy conservation and carbon reduction diagnostic model is a K-Means clustering model, with inputs including enterprise equipment energy consumption data and enterprise carbon emission data, and outputs energy consumption equipment clustering results and emission reduction priority ranking results; the carbon trading strategy model includes a rule engine unit and a Pearson correlation analysis unit, with inputs including carbon price data, enterprise emission data, and enterprise quota data, and outputs trading opportunities and trading volume.

[0056] The application service layer includes a government-side application module and an enterprise-side application module. The input end of the application service layer is connected to the output end of the support layer. The application service layer is used to provide energy and carbon management services based on the energy and carbon management support results. In this embodiment, by setting up government-side application modules and enterprise-side application modules in the application service layer, differentiated energy and carbon management services are provided to the government and enterprises respectively based on the energy and carbon management support results. This achieves two-way empowerment of government supervision and enterprise emission reduction, and solves the problem of the disconnect and lack of coordination between government-side and enterprise-side applications in the prior art.

[0057] In this embodiment, the government-side application module includes: a regional energy and carbon dashboard unit, comprising a map display subunit, a bar chart display subunit, and a line chart display subunit, the input end of which is connected to the output end of the support layer; a regional carbon emission inventory management unit, used to store direct and indirect carbon emission data of enterprises within the region; a regional energy and carbon analysis tool unit, comprising a comparative analysis subunit, a trend analysis subunit, and a factor analysis subunit, the input end of which is connected to the output end of the data sharing and exchange module; a carbon peaking pilot evaluation unit, comprising an evaluation index storage subunit and a monitoring and evaluation subunit, the input end of which is connected to the output end of the carbon peaking prediction and extrapolation model; and a carbon peaking extrapolation management unit, the input end of which is connected to the output end of the carbon peaking prediction and extrapolation model.

[0058] The user layer includes a role-based access control module. This user layer is connected to the application service layer and is used to assign access permissions for energy and carbon management services based on user roles. This embodiment achieves hierarchical access control for super administrators, government administrators, enterprise administrators, and platform maintenance personnel by setting up a role-based access control module at the user layer and assigning access permissions for energy and carbon management services according to user roles. This ensures system data security and operational compliance, and solves the problems of chaotic access management and high risk of unauthorized data access in existing technologies.

[0059] In this embodiment, the enterprise-side application module includes: an enterprise carbon account unit, including a dashboard unit, the input of which is connected to the output of the data sharing and exchange module; an energy carbon monitoring unit, including a multi-dimensional data display subunit and a threshold judgment subunit, the input of which is connected to the output of the IoT access module, and the threshold judgment subunit outputs a prompt signal when energy consumption data exceeds a preset threshold; an organizational carbon footprint accounting unit, including a data acquisition subunit, an emission factor management subunit, a carbon emission accounting subunit, and a report generation subunit, the input of which is connected to the output of the data sharing and exchange module; a carbon assessment management unit, the input of which is connected to the output of the data sharing and exchange module, and the output of which outputs the carbon efficiency level classification result; and a carbon governance unit, including a strategy recommendation subunit and a project tracking subunit, the input of which is connected to the output of the energy-saving and carbon-reduction diagnostic model, and the input of which is connected to the output of the data sharing and exchange module.

[0060] In this embodiment, the role-based access control module includes: a role storage unit for storing super administrator roles, government administrator roles, enterprise administrator roles, and platform operation and maintenance personnel roles; a permission allocation unit connected to the role storage unit for allocating permissions to each role; and a permission verification unit connected to the application service layer for outputting permission control signals to the application service layer according to the user's role when the user logs in.

[0061] Example 2

[0062] Based on the same inventive concept as other embodiments, this embodiment describes a computer-readable storage medium having computer instructions stored thereon, which, when executed by a processor, implement the steps of the method described in Embodiment 1 above.

[0063] Example 3

[0064] Based on the same inventive concept as other embodiments, this embodiment describes a computer program product, including computer instructions that, when executed by a processor, implement the steps of the method described in Embodiment 1.

[0065] In summary, this invention constructs a five-layer architecture comprising a resource layer, a data layer, a support layer, an application service layer, and a user layer. The resource layer, through an IoT access module, a third-party interface module, and a manual data entry module, achieves unified collection of multi-source energy carbon data. The data layer, through a data cleaning module and a data sharing and exchange module, outputs standardized energy carbon datasets. The support layer, based on the standardized energy carbon datasets, outputs energy carbon management support results through carbon peak prediction and extrapolation models, energy carbon prediction models, energy conservation and carbon reduction diagnostic models, and carbon trading strategy models. The application service layer, through government-side application modules and enterprise-side application modules, provides differentiated energy carbon management services to the government and enterprises respectively. The user layer, through a role-based access control module, assigns corresponding access permissions to different user roles, forming a closed-loop government-enterprise collaboration mechanism of "government supervision, enterprise execution, and data feedback." This solves the problems of lacking a government-enterprise collaboration mechanism and severe data silos at various levels in existing technologies, achieving unified collection, accurate prediction, intelligent diagnosis, and tiered services of energy carbon data at the regional and enterprise levels, and promoting effective linkage between government supervision and enterprise emission reduction.

[0066] This invention establishes an IoT access module, a third-party interface module, and a manual data entry module at the resource layer. The IoT access module includes an MQTT protocol adaptation unit, a LoRa protocol adaptation unit, and an RS485 protocol adaptation unit for collecting energy consumption data and cold storage energy supply data. The third-party interface module obtains data from third-party platforms such as the power supply company platform, gas company platform, and water company platform via a RESTful API interface unit and an SSL / TLS encrypted transmission unit. The manual data entry module receives data through a standardized data entry template unit, a web-based entry interface unit, and a mobile entry interface unit. The resource layer integrates the data to form raw energy and carbon data, achieving comprehensive aggregation and unified collection of multi-source heterogeneous data. This solves the problems of scattered data sources and single collection methods in existing technologies.

[0067] This invention establishes a carbon peak prediction and extrapolation model, an energy-carbon prediction model, an energy-saving and carbon reduction diagnostic model, and a carbon trading strategy model through a support layer. The carbon peak prediction and extrapolation model uses an LSTM network model to input historical carbon emissions, energy structure, industrial structure, and time-series data, outputting the carbon emissions, peak year, and peak carbon value for the first future time period. The energy-carbon prediction model uses an LSTM network model to input historical electricity consumption, historical heat consumption, historical water consumption, historical gas consumption, meteorological data, and production load data, outputting energy consumption and carbon emissions for the second future time period. The energy-saving and carbon reduction diagnostic model uses a K-Means clustering model to input enterprise equipment energy consumption data and enterprise carbon emission data, outputting energy-consuming equipment clustering results and emission reduction priority ranking results. The carbon trading strategy model, through a rule engine unit and a Pearson correlation analysis unit, inputs carbon price data, enterprise emission data, and enterprise quota data, outputting trading opportunities and trading volumes. This achieves accurate prediction, intelligent diagnosis, and carbon trading strategy support for energy-carbon data at the regional and enterprise levels, solving the problems of insufficient artificial intelligence algorithm support and inadequate prediction and decision-making capabilities in existing technologies.

[0068] This invention sets up government-side and enterprise-side application modules in the application service layer, and assigns access permissions through a role-based access control module in the user layer. The government-side application module provides the government with aggregated data views of enterprises within the region and carbon peaking simulation management services through the regional energy and carbon dashboard unit, regional carbon emission inventory management unit, regional energy and carbon analysis tool unit, carbon peaking pilot evaluation unit, and carbon peaking simulation management unit. The enterprise-side application module provides enterprises with detailed data views of their own enterprises and energy-saving and carbon-reduction strategy recommendations through the enterprise carbon account unit, energy and carbon monitoring unit, organizational carbon footprint accounting unit, carbon evaluation management unit, and carbon governance unit. At the same time, the user layer stores the roles of super administrator, government management personnel, enterprise management personnel, and platform operation and maintenance personnel through the role storage unit, and implements hierarchical access control through the permission allocation unit and permission verification unit. This forms a closed loop of government-enterprise collaboration of "government supervision, enterprise execution, and data feedback", which solves the problem of the disconnect and lack of effective linkage between government-side and enterprise-side applications in the existing technology, and realizes layered services and refined management at the regional and enterprise levels.

[0069] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0070] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0071] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0072] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0073] The embodiments of the present invention have been described above with reference to the accompanying drawings. However, the present invention is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of the present invention without departing from the spirit and scope of the claims. All of these forms are within the protection scope of the present invention.

Claims

1. A hierarchical energy and carbon virtual power plant management system for government-enterprise collaboration, characterized in that, include: The resource layer includes an IoT access module, a third-party interface module, and a manual data entry module. The resource layer is used to collect energy consumption data and carbon emission data and output raw energy and carbon data. The data layer includes a data cleaning module, a data storage module, and a data sharing and exchange module. The input end of the data layer is connected to the output end of the resource layer. The data layer is used to process the raw energy and carbon data and output a standardized energy and carbon dataset. The support layer includes a carbon peak prediction and extrapolation model, an energy carbon prediction model, an energy conservation and carbon reduction diagnostic model, and a carbon trading strategy model. The input end of the support layer is connected to the output end of the data layer. The support layer is used to perform calculations based on the standardized energy carbon dataset and output energy carbon management support results. The application service layer includes a government-side application module and an enterprise-side application module. The input end of the application service layer is connected to the output end of the support layer. The application service layer is used to provide energy and carbon management services based on the energy and carbon management support results. The user layer includes a role-based access control module, which is connected to the application service layer. The user layer is used to assign access permissions for energy and carbon management services according to user roles.

2. The hierarchical energy and carbon virtual power plant management system for government-enterprise collaboration according to claim 1, characterized in that, The IoT access module includes an MQTT protocol adaptation unit, a LoRa protocol adaptation unit, and an RS485 protocol adaptation unit. The IoT access module is used to collect energy consumption data and cold storage energy supply data. The third-party interface module includes a RESTful API interface unit and an SSL / TLS encrypted transmission unit, used to obtain data from third-party platforms; The manual data entry module includes a standardized data entry template unit, a web-based data entry interface unit, and a mobile data entry interface unit, used to receive data to be entered. The resource layer is connected to the IoT access module, the third-party interface module, and the manual data entry module, respectively, and is used to integrate the energy consumption data and cold storage energy supply data collected by the IoT access module, the third-party platform data obtained by the third-party interface module, and the data entry data received by the manual data entry module to form the raw energy carbon data.

3. The hierarchical energy and carbon virtual power plant management system for government-enterprise collaboration according to claim 2, characterized in that, The third-party interface module is connected to the power supply company platform, gas company platform, and water company platform.

4. The hierarchical energy and carbon virtual power plant management system for government-enterprise collaboration according to claim 3, characterized in that, The data cleaning module includes a data deduplication unit, an outlier filtering unit, and a missing value interpolation and completion unit. The input end of the data cleaning module is connected to the output end of the resource layer, and the output end of the data cleaning module outputs the cleaned raw energy and carbon data. The data storage module includes a distributed database Hadoop and a time-series database InfluxDB. The input end of the data storage module is connected to the output end of the data cleaning module. The data storage module partitions and stores the cleaned raw energy and carbon data according to the time field and the enterprise number field. The data sharing and exchange module includes a data publishing unit, a data subscription unit, a data query unit, and an HTTPS transmission protocol unit. The input end of the data sharing and exchange module is connected to the output end of the data storage module. The data sharing and exchange module is used to provide the government with an aggregated data view of enterprises in the region and to provide the enterprises with a detailed data view of their own enterprises based on the cleaned raw energy and carbon data.

5. The hierarchical energy and carbon virtual power plant management system for government-enterprise collaboration according to claim 4, characterized in that, The carbon peak prediction and extrapolation model is an LSTM network model. The input of the carbon peak prediction and extrapolation model is historical carbon emissions, energy structure, industrial structure and time series data. The output of the carbon peak prediction and extrapolation model is the carbon emissions, peak year and carbon peak value in the first future time period. The unit of the first future time period is years. The energy and carbon prediction model is an LSTM network model. The input of the energy and carbon prediction model is historical electricity consumption, historical heat consumption, historical water consumption, historical gas consumption, meteorological data and production load data. The output of the energy and carbon prediction model is the energy consumption and carbon emissions in the second future time period, and the unit of the second future time period is hours. The energy-saving and carbon-reduction diagnostic model is a K-Means clustering model. The input of the energy-saving and carbon-reduction diagnostic model is the enterprise's equipment energy consumption data and enterprise carbon emission data. The output of the energy-saving and carbon-reduction diagnostic model is the energy consumption equipment clustering result and the emission reduction priority ranking result. The carbon trading strategy model includes a rules engine unit and a Pearson correlation analysis unit. The input of the carbon trading strategy model is carbon price data, enterprise emission data, and enterprise quota data. The output of the carbon trading strategy model is trading timing and trading volume.

6. The hierarchical energy and carbon virtual power plant management system for government-enterprise collaboration according to claim 5, characterized in that, The government-side application module includes: The regional energy carbon cockpit unit includes a map display subunit, a bar chart display subunit, and a line chart display subunit. The input end of the regional energy carbon cockpit unit is connected to the output end of the support layer. The regional carbon emission inventory management unit is used to store direct and indirect carbon emission data of enterprises within the region. The regional energy and carbon analysis tool unit includes a comparative analysis subunit, a trend analysis subunit, and a factor analysis subunit. The input end of the regional energy and carbon analysis tool unit is connected to the output end of the data sharing and exchange module. The carbon peaking pilot evaluation unit includes an evaluation index storage subunit and a monitoring and evaluation subunit. The input end of the carbon peaking pilot evaluation unit is connected to the output end of the carbon peaking prediction and extrapolation model. A carbon peak prediction and management unit, wherein the input end of the carbon peak prediction and management unit is connected to the output end of the carbon peak prediction and prediction model.

7. The hierarchical energy and carbon virtual power plant management system for government-enterprise collaboration according to claim 6, characterized in that, The enterprise-side application module includes: The corporate carbon account unit includes a dashboard unit, the input of which is connected to the output of the data sharing and exchange module; The energy and carbon monitoring unit includes a multi-dimensional data display subunit and a threshold judgment subunit. The input end of the energy and carbon monitoring unit is connected to the output end of the Internet of Things access module. The threshold judgment subunit outputs a prompt signal when the energy consumption data exceeds a preset threshold. The organization's carbon footprint accounting unit includes a data acquisition subunit, an emission factor management subunit, a carbon emission accounting subunit, and a report generation subunit. The input end of the organization's carbon footprint accounting unit is connected to the output end of the data sharing and exchange module. A carbon assessment management unit, wherein the input end of the carbon assessment management unit is connected to the output end of the data sharing and exchange module, and the output end of the carbon assessment management unit outputs the carbon efficiency level classification results; The carbon governance unit includes a strategy recommendation subunit and a project tracking subunit. The input of the strategy recommendation subunit is connected to the output of the energy-saving and carbon-reduction diagnostic model, and the input of the project tracking subunit is connected to the output of the data sharing and exchange module.

8. The hierarchical energy and carbon virtual power plant management system for government-enterprise collaboration according to claim 7, characterized in that, The role-based access control module includes: The role storage unit is used to store the roles of super administrator, government administrator, enterprise administrator, and platform operation and maintenance personnel. The permission allocation unit, connected to the role storage unit, is used to allocate permissions to each role; The permission verification unit is connected to the application service layer and is used to output permission control signals to the application service layer according to the user's role when the user logs in.

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