Carbon asset management system based on multi-layer collaborative awareness

Abstract

The invention discloses a carbon asset management system based on multi-layer collaborative perception, and relates to the technical field of carbon asset management, and the system comprises a multi-layer collaborative perception module which constructs data levels of a power generation end, a user end and industry energy consumption in a region based on the real-time collection and integration of multi-source data; and the scene modeling module is used for constructing scene models of climate, seasons, economic activities and the like under the support of data provided by the multi-layer sensing system, and predicting and analyzing carbon emission, load peak values and carbon emission risks according to different scenes. According to the invention, intelligent and dynamic comprehensive management of carbon emission and user interaction is realized. Through multi-layer collaborative perception and self-adaptive scene modeling, the system can monitor carbon emission in real time and pre-judge a high-carbon emission scene in advance; and energy storage priority scheduling and self-optimization functions are combined, so that reasonable allocation of energy storage resources under different load conditions is ensured, and system stability is guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of carbon asset management, and in particular to a carbon asset management system based on multi-layer collaborative perception. Background Art

[0002] Due to seasonal fluctuations in energy supply and demand, a high proportion of renewable energy, and strong dependence on tourism and economic activities, island regions face complex and real-time requirements for carbon emission monitoring and management. Traditional carbon asset management systems often fail to meet the real-time monitoring needs of island regions in terms of energy consumption, carbon intensity, and renewable energy synergy. Therefore, a multi-layer collaborative perception carbon asset management system, combined with an island electricity-carbon panoramic monitoring indicator system, has constructed a real-time monitoring and feedback mechanism covering multiple dimensions such as energy consumption, carbon emissions, and supply-demand synergy, providing systematic and refined technical support for regional low-carbon management in complex environments. Summary of the invention

[0003] In view of the problems existing in the existing carbon asset management based on multi-layer collaborative perception, the present invention is proposed.

[0004] Therefore, the problem to be solved by the present invention is that the traditional carbon asset management system often cannot meet the real-time monitoring needs of energy consumption, carbon intensity and renewable energy coordination in island areas.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0006] In a first aspect, an embodiment of the present invention provides a carbon asset management system based on multi-layer collaborative perception, which includes:

[0007] Multi-level collaborative perception module: Based on the real-time collection and integration of multi-source data, it builds a data hierarchy of power generation, user and industry energy consumption in the region;

[0008] Scenario modeling module: With the data support provided by the multi-layer perception system, scenario models such as climate, season, and economic activities are constructed to predict and analyze carbon emissions, load peaks, and carbon emission risks for different scenarios.

[0009] As a preferred solution of the carbon asset management system based on multi-layer collaborative perception described in the present invention, it also includes: through dynamic adjustment and strategy optimization, the optimization parameters output by the scenario modeling module are converted into load adjustment instructions, and the system enters the dynamic strategy adjustment stage according to the optimization parameters output by the scenario modeling module, and takes adjustment measures for the current climate load conditions, and outputs the optimized load adjustment instructions. According to the optimization parameters output by the scenario modeling module, the system enters the dynamic strategy adjustment stage and takes adjustment measures for the current climate load conditions;

[0010] Dynamic dispatch and real-time response of energy storage: Automatically switch to adaptive energy storage mode according to priority, including three modes: conventional energy-saving mode, emergency peak-shaving mode and carbon reduction mode;

[0011] Energy storage priority adjustment feedback: Based on the operating results of the energy storage scheduling mode, the system generates priority adjustment feedback data for redemption records in the points mall.

[0012] As a preferred solution of the carbon asset management system based on multi-layer collaborative perception described in the present invention, the dynamic scheduling and real-time response of energy storage include: the energy storage priority scheduling system receives the carbon emission changes of multi-dimensional indicators and the dynamic prediction of the scenario model in each time period, compares and evaluates whether the current mode is suitable, and automatically switches to the adaptive energy storage mode according to the priority.

[0013] As a preferred solution of the carbon asset management system based on multi-layer collaborative perception described in the present invention, it also includes: a panoramic carbon emission heat map and multi-dimensional indicator evaluation,

[0014] The panoramic carbon emission heat map and multi-dimensional indicator assessment are as follows: with the support of scenario modeling module and dynamic adjustment and strategy optimization, a real-time carbon emission heat map is generated, and through the heat map data output, a multi-level regional carbon emission assessment is constructed with a multi-dimensional indicator system.

[0015] As a preferred solution of the carbon asset management system based on multi-layer collaborative perception described in the present invention, it also includes comprehensive evaluation and trend analysis;

[0016] The comprehensive assessment and trend analysis includes time series analysis of carbon emission trends, automatic analysis of changes in supply and demand coordination, and identification of periods of mismatched carbon emission peaks, and output of redemption records for the points mall.

[0017] As a preferred solution of the carbon asset management system based on multi-layer collaborative perception described in the present invention, it also includes: a multi-stage energy storage priority scheduling mechanism;

[0018] The multi-stage energy storage priority scheduling mechanism includes three-level energy storage priority mode configuration, through comparison and evaluation of whether the current mode is suitable, dynamic scheduling and energy storage real-time response and energy storage priority adjustment feedback;

[0019] User interaction and carbon credit incentive mechanism and transparent carbon asset management and feedback loop based on blockchain.

[0020] As a preferred solution of the carbon asset management system based on multi-layer collaborative perception described in the present invention, wherein: the energy storage three-level priority mode configuration includes: energy storage three-level priority mode configuration, the system provides specific instructions and numerical benchmarks for multi-stage energy storage priority scheduling based on trend analysis and comprehensive evaluation reports, and the energy storage system operates in three modes;

[0021] Dynamic scheduling and real-time response of energy storage, combined with the optimized output results of energy storage scheduling, feedback results are used for redemption records in the points mall.

[0022] As a preferred solution of the carbon asset management system based on multi-layer collaborative perception described in the present invention, wherein: the user interaction and carbon credit incentive mechanism and the transparent carbon asset management and feedback closed loop based on blockchain include: a carbon credit incentive system;

[0023] The carbon credit incentive system includes carbon credits and health records on the chain, integrating user interaction modules, generating a prediction model for future user responses by analyzing user behavior data, credit records and health evaluation results, and quantifying user electricity usage habits and energy-saving behaviors through dual feedback from the health evaluation system and credit system;

[0024] Multi-level collaborative perception and adaptive scenario modeling, including a multi-level collaborative perception system and an adaptive scenario modeling system.

[0025] In a second aspect, an embodiment of the present invention provides a computer device, including a memory and a processor, wherein the memory stores a computer program, wherein: when the processor executes the computer program, it implements any step of the above-mentioned carbon asset management system based on multi-layer collaborative perception.

[0026] In a third aspect, an embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program is executed by a processor, any step of the above-mentioned carbon asset management system based on multi-layer collaborative perception is implemented.

[0027] The beneficial effects of the present invention are: it realizes all-round management of carbon emissions that is intelligent, dynamic and user-interactive. Through multi-layer collaborative perception and adaptive scenario modeling, the system can monitor carbon emissions in real time and predict high-carbon emission scenarios in advance; combined with energy storage priority scheduling and self-optimization functions, it ensures the reasonable allocation of energy storage resources under different load conditions to ensure system stability. Panoramic carbon emission heat maps and dynamic hotspot tracking enable managers to accurately locate high-carbon areas and take regulatory measures. At the same time, through carbon points and blockchain transparent management, users are encouraged to actively adjust their electricity usage habits, forming a low-carbon management closed loop with transparent data and timely feedback, effectively promoting intelligent control of carbon emissions in the region and low-carbon behavior of users. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. Among them:

[0029] Figure 1 This is a flow chart of a carbon asset management system based on multi-layer collaborative perception. DETAILED DESCRIPTION

[0030] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0031] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0032] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0033] The present invention is described in detail with reference to schematic diagrams. When describing the embodiments of the present invention, for the sake of convenience, the cross-sectional diagrams showing the device structure will not be partially enlarged according to the general scale, and the schematic diagrams are only examples, which should not limit the scope of protection of the present invention. In addition, in actual production, the three-dimensional dimensions of length, width and depth should be included.

[0034] At the same time, in the description of the present invention, it should be noted that the directions or positional relationships indicated by the terms "upper, lower, inner and outer" are based on the directions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific direction, be constructed and operated in a specific direction, and therefore cannot be understood as limiting the present invention. In addition, the terms "first, second or third" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0035] In the present invention, unless otherwise clearly specified and limited, the terms "install, connect, connect" should be understood in a broad sense, for example: it can be a fixed connection, a detachable connection or an integral connection; it can also be a mechanical connection, an electrical connection or a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0036] Example 1

[0037] Reference Figure 1 , which is the first embodiment of the present invention, and provides a carbon asset management system based on multi-layer collaborative perception, including:

[0038] Multi-level collaborative perception module: Based on the real-time collection and integration of multi-source data, it builds a data hierarchy for regional power generation, user and industry energy consumption.

[0039] Real-time collection of information such as load, power consumption, meteorological data, and user electricity usage habits in the island area will form a preliminary load status and carbon emission distribution to support the subsequent scenario modeling module. The output data includes power load fluctuations in different regions, carbon emission values ​​of various industries, and time-varying trends, providing real-time basic data for adaptive scenario modeling.

[0040] Scenario modeling module: With the data support provided by the multi-layer perception system, scenario models such as climate, season, and economic activities are constructed to predict and analyze carbon emissions, load peaks, and carbon emission risks for different scenarios.

[0041] Automatically analyze the matching scenarios of the current perception data, generate optimized scenario parameters and output them to the scheduling layer. For example, in the scenario of high temperature load peak, scenario modeling will provide the carbon emission characteristics, expected load peak and scheduling suggestions of the "high temperature load scenario". The output scenario model data provides an accurate basis for real-time energy storage allocation and carbon emission control strategies.

[0042] Dynamic adjustment and strategy optimization module: converts the optimization parameters output by the scenario modeling module into load adjustment instructions. Based on the optimization parameters output by the scenario modeling module, the system enters the dynamic strategy adjustment stage, takes adjustment measures according to the current climate load conditions, and outputs optimized load adjustment instructions. Based on the optimization parameters output by the scenario modeling module, the system enters the dynamic strategy adjustment stage, and takes adjustment measures according to the current climate load conditions.

[0043] For example, if scenario modeling determines that the current situation is one of sufficient wind energy and low load, dynamic strategy optimization will give priority to renewable energy and issue instructions to the energy storage module to increase the charging rate of the energy storage device. At the same time, the system generates expected carbon emissions data and electricity consumption distribution under this optimization strategy as input for panoramic heat maps and multi-dimensional indicator evaluation.

[0044] Dynamic dispatch and real-time response of energy storage: Automatically switch to adaptive energy storage mode according to priority, including three modes: conventional energy-saving mode, emergency peak-shaving mode and carbon reduction mode;

[0045] Dynamic scheduling and real-time response of energy storage include: the energy storage priority scheduling system receives the carbon emission changes of multi-dimensional indicators and dynamic predictions of scenario models in each time period, compares and evaluates whether the current mode is suitable, and automatically switches to an adaptive energy storage mode according to the priority.

[0046] Energy storage priority adjustment feedback: Based on the operating results of the energy storage scheduling mode, the system generates priority adjustment feedback data for redemption records in the points mall.

[0047] Also includes: Panoramic carbon emissions heat map and multi-dimensional indicator evaluation,

[0048] The panoramic carbon emission heat map and multi-dimensional indicator assessment are as follows: with the support of scenario modeling module and dynamic adjustment and strategy optimization, a real-time carbon emission heat map is generated, and through the heat map data output, a multi-level regional carbon emission assessment is constructed with a multi-dimensional indicator system.

[0049] Panoramic carbon emission heat map: With the support of scenario modeling and dynamic adjustment strategies, the system generates a real-time carbon emission heat map. The heat map shows the carbon emissions in different regions and time periods, including hot spots, electricity-intensive areas, renewable energy utilization, etc., and intuitively shows managers high-carbon and low-carbon areas through diagrams and color gradients. The heat map data output not only includes the current carbon emission intensity, but also estimates the trend of changes in the next time period. These heat map data then flow to the multi-dimensional indicator system to build a multi-level regional carbon emission assessment;

[0050] Construction and display of a multi-dimensional indicator system: The system uses heat maps and scenario data to calculate indicators such as energy intensity, carbon intensity, and supply-demand coordination, providing a multi-dimensional perspective for regional low-carbon management. The indicator system breaks down each indicator into time periods and regions, such as outputting "carbon intensity per unit of energy consumption" and "supply-demand coordination" during peak electricity consumption periods, or outputting "carbon intensity per capita of electricity consumption" and other indicators during the peak tourist season. These indicator data serve as input for the next comprehensive evaluation, showing the real-time low-carbon performance in the region and providing data support for scheduling and strategy optimization.

[0051] The comprehensive assessment and trend analysis includes time series analysis of carbon emission trends, automatic analysis of changes in supply and demand coordination, and identification of periods when carbon emission peaks do not match, and output of redemption records for the points mall;

[0052] Combining multi-dimensional indicator data, the system generates a comprehensive evaluation report, analyzes carbon emission trends through time series, automatically analyzes changes in supply and demand coordination, identifies periods of mismatched carbon emission peaks, and proposes specific improvement suggestions. The trend data and optimization suggestions output by the report will be further provided to the energy storage priority scheduling module to facilitate dynamic allocation of energy storage resources and optimize energy utilization efficiency.

[0053] Also included: a multi-stage energy storage priority dispatch mechanism;

[0054] The multi-stage energy storage priority scheduling mechanism includes three-level energy storage priority mode configuration, through comparison and evaluation of whether the current mode is suitable, dynamic scheduling and energy storage real-time response and energy storage priority adjustment feedback;

[0055] The energy storage three-level priority mode configuration includes: energy storage three-level priority mode configuration, the system provides specific instructions and numerical benchmarks for multi-stage energy storage priority scheduling based on trend analysis and comprehensive evaluation reports, and the energy storage system operates in three modes;

[0056] Dynamic scheduling and real-time response of energy storage, combined with the optimized output results of energy storage scheduling, feedback results are used for redemption records in the points mall.

[0057] The energy storage priority scheduling system receives dynamic predictions of carbon emission changes of multi-dimensional indicators and scenario models in each time period, compares and evaluates whether the current mode is suitable, and automatically switches to an adaptive energy storage mode according to the priority. For example, in emergencies such as high temperature and humidity or peak tourist seasons, the system automatically enters the "carbon reduction mode" to ensure priority power supply to key equipment by maximizing the deployment of energy storage. The optimized output results of energy storage scheduling will be fed back to the user end to ensure the stability of its electricity demand within the scheduling.

[0058] User interaction and carbon credit incentive mechanism and transparent carbon asset management and feedback closed loop based on blockchain;

[0059] Based on the operating results of the energy storage scheduling mode, the system will generate "priority adjustment feedback" data to analyze whether the scheduling results have achieved the expected carbon emission reduction effect. These feedback data include energy storage utilization efficiency, carbon emission reduction and scheduling response speed, and are then fed back to the carbon emission heat map and multi-dimensional evaluation system to provide data support for scenario modeling and energy storage configuration in the next period, forming a closed-loop management of energy storage scheduling.

[0060] The user interaction and carbon credit incentive mechanism and the transparent carbon asset management and feedback closed loop based on blockchain include: carbon credit incentive system;

[0061] The carbon credit incentive system includes carbon credits and health records on the chain, integrating user interaction modules, generating a prediction model for future user responses by analyzing user behavior data, credit records and health evaluation results, and quantifying user electricity usage habits and energy-saving behaviors through dual feedback from the health evaluation system and credit system;

[0062] Electricity health evaluation and improvement: Carbon credit data flows into the health evaluation system, and health scores are given based on multiple indicators such as the user's low-carbon electricity frequency and energy-saving response. The health score divides users into three groups: "low-carbon priority", "energy-saving compliance" and "high carbon emissions". Users can see real-time health trends on the interface and check the goals for the next level. The system provides improvement suggestions and further credit incentives. These data will be fed into the personalized suggestion module to generate targeted electricity suggestions.

[0063] Multi-level collaborative perception and adaptive scenario modeling, including a multi-level collaborative perception system and an adaptive scenario modeling system.

[0064] Based on the dual feedback from the health evaluation system and the points system, personalized energy-saving suggestions are generated and pushed to the user interface. For example, the system recommends that users use energy storage to charge during peak wind power periods, or prompts users to adjust their electricity usage habits during periods of low carbon intensity. The personalized energy-saving suggestion module generates new electricity usage suggestions in real time and adjusts the points increase based on user responses, forming a closed loop of user behavior feedback to enhance user active participation.

[0065] In summary, all-round management of carbon emissions has been achieved with intelligence, dynamism and user interaction. Through multi-layer collaborative perception and adaptive scenario modeling, the system can monitor carbon emissions in real time and predict high-carbon emission scenarios in advance; combined with energy storage priority scheduling and self-optimization functions, it ensures the reasonable allocation of energy storage resources under different load conditions to ensure system stability. Panoramic carbon emission heat maps and dynamic hotspot tracking enable managers to accurately locate high-carbon areas and take regulatory measures. At the same time, through carbon points and blockchain transparent management, users are encouraged to actively adjust their electricity habits, forming a low-carbon management closed loop with transparent data and timely feedback, effectively promoting intelligent control of carbon emissions in the region and low-carbon behavior of users.

[0066] Example 2

[0067] Based on the first embodiment;

[0068] This embodiment also provides a computer device, which is suitable for the case of a carbon asset management system based on multi-layer collaborative perception, including a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute computer-executable instructions to implement the carbon asset management system based on multi-layer collaborative perception as proposed in the above embodiment.

[0069] The computer device may be a terminal, and the computer device includes a processor, a memory, a communication interface, a display screen and an input device connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, an operator network, NFC (near field communication) or other technologies. The display screen of the computer device may be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device may be a touch layer covering the display screen, or a key, trackball or touchpad provided on the housing of the computer device, or an external keyboard, touchpad or mouse, etc.

[0070] This embodiment also provides a storage medium on which a computer program is stored. When the program is executed by a processor, the carbon asset management system based on multi-layer collaborative perception as proposed in the above embodiment is implemented.

[0071] The storage medium proposed in this embodiment and the data storage system proposed in the above embodiment belong to the same inventive concept. The technical details not fully described in this embodiment can be found in the above embodiment, and this embodiment has the same beneficial effects as the above embodiment.

[0072] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A carbon asset management system based on multi-layer collaborative perception, characterized by: include, Multi-level collaborative perception module: Based on the real-time collection and integration of multi-source data, it builds a data hierarchy of power generation, user and industry energy consumption in the region; Scenario modeling module: With the data support provided by the multi-layer perception system, scenario models such as climate, season, and economic activities are constructed to predict and analyze carbon emissions, load peaks, and carbon emission risks for different scenarios.

2. The carbon asset management system based on multi-layer collaborative perception as claimed in claim 1, characterized in that: It also includes a dynamic adjustment and strategy optimization module, which converts the optimization parameters output by the scenario modeling module into load adjustment instructions. According to the optimization parameters output by the scenario modeling module, the system enters the dynamic strategy adjustment stage, takes adjustment measures for the current climate load conditions, and outputs optimized load adjustment instructions. According to the optimization parameters output by the scenario modeling module, the system enters the dynamic strategy adjustment stage, and takes adjustment measures for the current climate load conditions; Dynamic dispatch and real-time response of energy storage: Automatically switch to adaptive energy storage mode according to priority, including three modes: conventional energy-saving mode, emergency peak-shaving mode and carbon reduction mode; Energy storage priority adjustment feedback: Based on the operating results of the energy storage scheduling mode, the system generates priority adjustment feedback data for redemption records in the points mall.

3. The carbon asset management system based on multi-layer collaborative perception as claimed in claim 2, characterized in that: The dynamic scheduling and real-time response of energy storage include: the energy storage priority scheduling system receives the carbon emission changes of multi-dimensional indicators and the dynamic prediction of the scenario model in each time period, compares and evaluates whether the current mode is suitable, and automatically switches to the adaptive energy storage mode according to the priority.

4. The carbon asset management system based on multi-layer collaborative perception as claimed in claim 3, characterized in that: Also includes: Panoramic carbon emission heat map and multi-dimensional indicator evaluation, The panoramic carbon emission heat map and multi-dimensional indicator assessment are as follows: with the support of scenario modeling module and dynamic adjustment and strategy optimization, a real-time carbon emission heat map is generated, and through the heat map data output, a multi-level regional carbon emission assessment is constructed with a multi-dimensional indicator system.

5. The carbon asset management system based on multi-layer collaborative perception as claimed in claim 4, characterized in that: It also includes comprehensive assessment and trend analysis; The comprehensive assessment and trend analysis includes time series analysis of carbon emission trends, automatic analysis of changes in supply and demand coordination, and identification of periods of mismatched carbon emission peaks, and output of redemption records for the points mall.

6. The carbon asset management system based on multi-layer collaborative perception as claimed in claim 5, characterized in that: Also includes: Multi-stage energy storage priority dispatch mechanism; The multi-stage energy storage priority scheduling mechanism includes three-level energy storage priority mode configuration, through comparison and evaluation of whether the current mode is suitable, dynamic scheduling and energy storage real-time response and energy storage priority adjustment feedback; User interaction and carbon credit incentive mechanism and transparent carbon asset management and feedback loop based on blockchain.

7. The carbon asset management system based on multi-layer collaborative perception as claimed in claim 6, characterized in that: The energy storage three-level priority mode configuration includes: energy storage three-level priority mode configuration, the system provides specific instructions and numerical benchmarks for multi-stage energy storage priority scheduling based on trend analysis and comprehensive evaluation reports, and the energy storage system operates in three modes; Dynamic scheduling and real-time response of energy storage, combined with the optimized output results of energy storage scheduling, feedback results are used for redemption records in the points mall.

8. The carbon asset management system based on multi-layer collaborative perception as claimed in claim 7, characterized in that: The user interaction and carbon credit incentive mechanism and the transparent carbon asset management and feedback closed loop based on blockchain include: carbon credit incentive system; The carbon credit incentive system includes carbon credits and health records on the chain, integrating user interaction modules, generating a prediction model for future user responses by analyzing user behavior data, credit records and health evaluation results, and quantifying user electricity usage habits and energy-saving behaviors through dual feedback from the health evaluation system and credit system; Multi-level collaborative perception and adaptive scenario modeling, including a multi-level collaborative perception system and an adaptive scenario modeling system.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the carbon asset management system based on multi-layer collaborative perception described in any one of claims 1 to 8 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the carbon asset management system based on multi-layer collaborative perception described in any one of claims 1 to 8 are implemented.

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