A clean heating carbon asset full life cycle intelligent management and control platform and implementation method

Abstract

The present application belongs to the field of carbon asset management, and in particular to a clean heating carbon asset whole life cycle intelligent management and control platform and implementation method, comprising a perception layer, a transmission layer, a platform layer and an application layer, the perception layer, the transmission layer, the platform layer and the application layer are interconnected, the perception layer comprises an Internet of Things perception terminal, which is used for real-time acquisition of heating, operation, energy consumption and environmental parameters of clean heating projects; the transmission layer comprises a communication module, an edge computing gateway and a blockchain data transmission node, which are used for data preprocessing, encrypted transmission and chain storage. The present application realizes the whole life cycle intelligent management and control of clean heating carbon assets from data acquisition, emission reduction calculation, authentication declaration to transaction matching, verification and supervision, solves the information island problem at each link, improves the accuracy of carbon asset accounting and operation efficiency, and realizes the maximization of carbon asset value.

Description

Technical Field

[0001] This invention relates to the field of carbon asset management technology, and in particular to an intelligent management and control platform and implementation method for the entire life cycle of clean heating carbon assets. Background Technology

[0002] Clean heating has become an important direction for the low-carbon energy transition, and the carbon emission reductions it generates form tradable carbon assets, which are the core carriers for enhancing the value of clean heating projects.

[0003] Currently, carbon asset management for clean heating suffers from several technical deficiencies: First, carbon asset data collection relies on manual input, which is disconnected from the operational data of clean heating equipment, resulting in data lag and large errors, making real-time calculation of emission reductions impossible. Second, existing carbon asset management systems only cover a single stage, lacking the ability to manage the entire lifecycle of carbon assets from generation, accounting, certification to trading and write-off, with data not being shared between stages, creating information silos. Third, emission reduction calculation methods are not deeply integrated with the actual operating conditions of clean heating projects, often using fixed emission factors without considering dynamic factors such as equipment energy efficiency and ambient temperature, resulting in insufficient accuracy of calculation results. Fourth, carbon asset trading matching, risk warning, and policy compatibility analysis lack intelligent support, making it difficult to maximize the value of carbon assets. Fifth, the write-off management of carbon assets such as green certificates and CCERs is disconnected from the operational monitoring of clean heating projects, easily leading to problems such as duplicate carbon asset gains and irregular write-offs. Furthermore, existing management platforms lack data analysis and intelligent decision-making capabilities for the entire lifecycle of clean heating carbon assets, failing to provide precise guidance for project owners on carbon asset operation.

[0004] Therefore, there is an urgent need for a platform and implementation method that can achieve intelligent management and control of carbon assets throughout the entire process of clean heating, real-time data exchange, and accurate and efficient accounting, in order to solve the above-mentioned defects of existing technologies and become a key requirement for the development of the industry. Summary of the Invention

[0005] The purpose of this invention is to address the technical shortcomings of existing clean heating carbon asset management, such as lagging data collection, low accounting accuracy, information silos in various stages, non-standard carbon asset supervision, and insufficient intelligent decision support. This invention provides a smart management platform and implementation method for the entire lifecycle of clean heating carbon assets, enabling intelligent management of carbon assets from data collection, emission reduction calculation, certification and declaration to trading matching and write-off supervision. This breaks down information silos, improves the accuracy of carbon emission reduction calculation and the efficiency of carbon asset management and operation, and maximizes the value of clean heating carbon assets.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: A smart management platform for the entire lifecycle of carbon assets in clean heating includes a sensing layer, a transmission layer, a platform layer, and an application layer. These layers are interconnected, enabling bidirectional data transmission. The sensing layer includes IoT sensing terminals for real-time collection of heating, operation, energy consumption, and environmental parameters of clean heating projects. These IoT sensing terminals include calorimeters, flow meters, electricity meters, temperature sensors, and energy efficiency monitoring modules, with a data collection frequency of seconds / minutes, all conforming to national / industry metrological verification standards. The transmission layer includes a communication module, an edge computing gateway, and blockchain data transmission nodes. The edge computing gateway communicates bidirectionally with the IoT sensing terminals through the communication module, performing preprocessing on the data collected by the sensing layer, including deduplication, noise reduction, and anomaly data removal. The module encrypts and transmits the preprocessed data to the platform layer. The blockchain data transmission node synchronously uploads the original collected data and preprocessed results to the blockchain for evidence storage. The platform layer includes a data middle platform, an algorithm engine, and a blockchain evidence storage module. The data middle platform interfaces with the transmission layer communication module to achieve multi-source data fusion storage. The algorithm engine has built-in dynamic emission reduction accounting model, carbon asset value assessment model, and transaction matching model. The blockchain evidence storage module interfaces with the blockchain data transmission node to achieve tamper-proof evidence storage of key data throughout the entire process. The application layer includes a carbon asset accounting module, a certification and application module, a transaction management module, a write-off supervision module, an intelligent decision-making module, and a policy adaptation module. Each module is linked with the platform layer data middle platform and algorithm engine to achieve one-stop management of carbon assets throughout their entire lifecycle, from data collection to write-off supervision.

[0007] Preferably, the communication module is a 5G communication module, the blockchain data transmission node adopts a consortium blockchain architecture to enable inter-node communication among project parties, regulatory agencies, certification bodies, and trading institutions, and the blockchain evidence storage module adopts the Fabric framework. The evidence storage objects include data collected by the perception layer, preprocessed data by the transmission layer, carbon emission reduction calculation results, certification application materials, carbon asset trading records, and write-off regulatory information.

[0008] Preferably, the dynamic emission reduction calculation model refers to the national / industry carbon emission reduction calculation standard corresponding to the clean heating project, and has a built-in core calculation formula ERy=BEy-PEy, where ERy is the carbon emission reduction within the statistical period, BEy is the baseline emission within the statistical period, and PEy is the actual emission of the project within the statistical period. The model also adds an energy efficiency correction coefficient α and a temperature correction coefficient β to dynamically correct the emission factor. The corrected emission factor is EF=EF0×α×β, where EF0 is the national / industry standard basic emission factor.

[0009] Preferably, the energy efficiency correction coefficient α = actual operating energy efficiency of the equipment / rated energy efficiency of the equipment, with a value range of 0.7-1.3; the temperature correction coefficient β is linearly corrected based on the difference between the actual ambient temperature and the design heating temperature. When the actual ambient temperature is lower than the design heating temperature, β is 1.0-1.2; when the actual ambient temperature is higher than the design heating temperature, β is 0.8-1.0; and when the actual ambient temperature is the same as the design heating temperature, β = 1.0.

[0010] Preferably, the data platform adopts a Hadoop distributed storage architecture, supporting real-time, monthly, and annual data analysis and retrieval for multiple statistical periods; the carbon asset valuation model is a multiple regression model, with input parameters including real-time carbon market conditions, project carbon emission reduction trends, and clean heating project types, and outputting carbon asset pricing suggestions; the transaction matching model is a collaborative filtering algorithm model, which achieves intelligent matching based on the carbon asset demand, price expectations, and transaction cycle requirements of both buyers and sellers.

[0011] Preferably, the application layer is configured with four types of user permissions: project owner, regulatory agency, trading institution, and certification authority. Each user can only view and operate the corresponding module functions. Among them, the regulatory agency has the full node data traceability and verification permission of the blockchain evidence storage module, while the project owner only has the permission to view and operate its own project data.

[0012] This invention also discloses a method for intelligent management and control of clean heating carbon assets throughout their entire lifecycle, implemented based on any of the aforementioned intelligent management and control platforms for clean heating carbon assets throughout their entire lifecycle, comprising the following steps: Step 1: The perception layer collects multi-source data on heating, operation, energy consumption and environment of the clean heating project in real time at a frequency of seconds / minutes through IoT sensing terminals; Step 2: The edge computing gateway of the transmission layer performs preprocessing on the collected raw data, including deduplication, noise reduction, and abnormal data removal. The preprocessing completion standard is an abnormal data removal rate of ≥99% and data integrity of ≥98%. The communication module transmits the preprocessed data to the platform layer data middleware through an encryption protocol. At the same time, the blockchain data transmission node synchronizes the raw data and the preprocessing results to the blockchain evidence storage module. Step 3: Enter basic information about the clean heating project through the application layer. The platform layer data middleware will automatically match the corresponding national / industry carbon emission reduction accounting standards and basic emission factor EF0 according to the project type. Step 4: The platform-level algorithm engine calls the dynamic emission reduction calculation model, combines the real-time data from the data platform to calculate the energy efficiency correction coefficient α and the temperature correction coefficient β, dynamically corrects the basic emission factor EF0, and calculates the carbon emission reduction according to ERy=BEy-PEy. It supports real-time, monthly, and annual multi-cycle calculations. All calculation results are uploaded to the blockchain notarization module for tamper-proof notarization. The calculation factors and value basis of the baseline emission amount BEy and the actual emission amount PEy of the project are consistent with the national / industry carbon emission reduction calculation standards corresponding to the project type. The calculation results are measured in tons of CO2. Step 5: The application layer certification application module automatically generates standardized carbon asset certification application materials based on the accounting results and blockchain evidence information, supporting project parties to submit to carbon asset certification agencies with one click. The platform tracks the application progress in real time and records key node information and uploads it to the blockchain simultaneously. Step 6: After carbon assets are certified, the application layer transaction management module enters them into the carbon asset trading pool. The algorithm engine provides pricing suggestions through the carbon asset valuation model, and then realizes intelligent matching between buyers and sellers through the transaction matching model. After the transaction is completed, the transaction information is completely stored on the blockchain. Step 7: The application layer write-off supervision module connects with the national carbon asset write-off system. After the carbon asset is written off, the asset status is automatically marked as "written off". The module continuously monitors the project operation data. When the monthly fluctuation of carbon emission reduction exceeds ±15%, it issues an abnormal warning to the project party and regulatory agency to prevent duplicate write-off of carbon assets. Step 8: The application layer intelligent decision-making module analyzes the project's carbon emission reduction trend and trading revenue, generates a visualized operation analysis report, and proposes equipment energy efficiency optimization suggestions; the policy adaptation module updates the clean heating subsidy policy and carbon market trading policy in real time, providing policy compatibility analysis and application suggestions for project owners. Step 9: Regulatory agencies retrieve the full-process data from the blockchain evidence storage module through the application-layer regulatory interface to achieve full-process data traceability and compliance verification of carbon assets from collection to write-off. The full-process data traceability and verification includes full-dimensional traceability of data collection time, data preprocessing process, accounting standard matching records, emission reduction calculation process, declaration material submission records, transaction information, and write-off status. The verification results can generate a standardized verification report and be stored on the blockchain.

[0013] Preferably, the method is applicable to clean heating projects of geothermal, photovoltaic, air source, and biomass types. The sensing layer monitoring indicators and platform layer calculation parameters can be flexibly configured according to the project type. For photovoltaic heating projects, photovoltaic power generation and photoelectric conversion efficiency monitoring indicators are added, and for biomass heating projects, biomass fuel consumption and combustion efficiency monitoring indicators are added.

[0014] The beneficial effects of this invention are: 1. This invention constructs an intelligent management and control platform with a four-layer architecture of perception, transmission, platform, and application. Each layer achieves bidirectional data interaction, breaking down information silos in various aspects of clean heating carbon asset management, realizing data sharing, and improving the overall efficiency of carbon asset management. By combining IoT real-time sensing technology with edge computing, it achieves second-level / minute-level data acquisition and standardized preprocessing of clean heating project data. The preprocessing completion standard is an abnormal data removal rate of ≥99% and data integrity of ≥98%, which solves the problems of lag and large errors in traditional manual data entry, and provides accurate raw data for carbon emission reduction accounting.

[0015] 2. This invention designs a dynamic emission reduction calculation model, adapting the calculation standards to the type of clean heating project. Based on dynamic factors such as real-time equipment energy efficiency and ambient temperature, the emission factors are dynamically corrected using an energy efficiency correction coefficient α and a temperature correction coefficient β. The correction formula is EF = EF0 × α × β. Compared to traditional fixed-factor calculation methods, the accuracy of the calculation results is improved by more than 30%, better reflecting the actual operating conditions of clean heating projects. Furthermore, it incorporates blockchain technology, adopting a consortium blockchain architecture and the Fabric framework to store key data throughout the entire lifecycle of carbon assets on the blockchain, achieving data immutability and full traceability. This effectively prevents carbon asset data falsification and duplicate write-offs, improving the compliance and credibility of carbon assets.

[0016] 3. This invention achieves intelligent value assessment and transaction matching of carbon assets through the multivariate regression value assessment model and collaborative filtering transaction matching model built into the algorithm engine. It provides project owners with precise and intelligent decision support for carbon asset operation, and can maximize the economic value of clean heating carbon assets. At the same time, it provides regulatory agencies with full-node data traceability and verification permissions, providing a visualized regulatory means and improving the intelligence and convenience of carbon asset supervision.

[0017] 4. The platform and method of this invention are applicable to various clean heating projects such as geothermal, photovoltaic, air source, and biomass. Monitoring indicators and calculation parameters can be flexibly configured according to different project types. Among them, photovoltaic heating projects add monitoring indicators of photovoltaic power generation and photoelectric conversion efficiency, and biomass heating projects add monitoring indicators of biomass fuel consumption and combustion efficiency. It has good compatibility and scalability and a wide range of applications. Attached Figure Description

[0018] Figure 1 This is a block diagram of a clean heating carbon asset full life cycle intelligent management and control platform proposed in this invention.

[0019] 1-Sensing layer, 11-IoT sensing terminal, 111-Heat meter, 112-Flow meter, 113-Electricity meter, 114-Temperature sensor, 115-Energy efficiency monitoring module; 2-Transport layer, 21-Communication module, 22-Edge computing gateway, 23-Blockchain data transmission node; 3-Platform layer, 31-Data middle platform, 32-Algorithm engine, 321-Dynamic emission reduction accounting model, 322-Carbon asset valuation model, 323-Transaction matching model, 33-Blockchain evidence storage module; 4-Application Layer, 41-Carbon Asset Accounting Module, 42-Certification and Application Module, 43-Transaction Management Module, 44-Write-off Supervision Module, 45-Intelligent Decision-making Module, 46-Policy Adaptation Module; Detailed Implementation

[0020] The technical solution of the present invention will now be clearly and completely described with reference to specific embodiments. Obviously, the described embodiments are merely some embodiments of the present invention, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0021] Example 1: Application of Geothermal Heating Project 1. Sensing Layer Deployment: Deploy IoT sensing terminals at key nodes of geothermal extraction wells, reinjection wells, heating stations, and heating pipe networks in geothermal heating projects. These terminals include heat meters conforming to JJG225 standards, electromagnetic flow meters conforming to JJG1033 standards, smart energy meters conforming to JJG596 standards, temperature sensors, and energy efficiency monitoring modules. These terminals collect data in real time, such as heating heat (HSBLy), geothermal fluid flow rate, equipment power consumption (EGy), ambient temperature, and heat exchanger energy efficiency. The data collection frequency is set to once every 1 minute. 2. Transmission Layer Configuration: A transmission network is formed by 5G communication modules and edge computing gateways. The edge computing gateways perform deduplication and noise reduction processing on the raw data collected by the perception layer, and remove abnormal data. The preprocessing completion standard is that the abnormal data removal rate is ≥99% and the data integrity is ≥98%. The data is transmitted to the platform layer through an encryption protocol. At the same time, the raw data and preprocessing results are stored on the blockchain through blockchain data transmission nodes. A consortium blockchain architecture is adopted to realize the interoperability of nodes of project parties, regulatory agencies, certification agencies and trading institutions. 3. Platform Layer Development: The data platform adopts a Hadoop distributed storage architecture to achieve the fusion and storage of multi-source data, supporting real-time, monthly, and annual data analysis and retrieval for multiple statistical periods. The algorithm engine is developed based on Python, and the dynamic emission reduction calculation model refers to the NB_T11963-2025 geothermal heating carbon emission reduction calculation method. It has built-in baseline emission formula BEy=HS×EFCO2,y and project emission formula PEy=FCy×Ncvg,Y×EFgco2,y+EGy×EFgrid,CM,y, and adds energy efficiency correction coefficient α and temperature correction coefficient β. α=actual operating energy efficiency of heat exchanger / rated energy efficiency of heat exchanger, and β is linearly corrected according to the difference between the actual ambient temperature and the design heating temperature. The corrected emission factor EF=EF0×α×β realizes dynamic calculation. The blockchain evidence storage module adopts the Fabric framework to put collected data, calculation results, application materials, and transaction records on the blockchain. 4. Application Layer Development: Develop visual operation interfaces for both web and mobile devices, setting four user permissions: project owner, regulatory agency, trading institution, and certification agency. Users with different permissions can view and operate the corresponding modules. The application layer will input basic information about the geothermal heating project: heating area of ​​100,000 square meters, replacing coal-fired heating; project boundaries include geothermal extraction wells, heating stations, and heating pipe networks. The platform layer will automatically match the NB_T11963-2025 accounting standard with the basic emission factor EF0 for coal-fired heating. The algorithm engine's dynamic emission reduction calculation model will call data from... The platform calculates α and β based on real-time data, and calculates monthly carbon emission reductions according to ERy=BEy-PEy. The calculation results are measured in tons of CO2 and automatically stored on the blockchain. The certification application module automatically generates carbon emission reduction certification application materials for the geothermal heating project based on the calculation results, including monitoring reports, accounting reports, and blockchain data traceability certificates. The project owner submits these materials to the carbon asset certification agency with one click through the platform. The platform tracks the application progress in real time and records key milestones. After the project's carbon assets pass CCER certification, the transaction management module enters them into the carbon asset trading pool for value assessment. The model combines real-time carbon market data, project emission reduction trends, and geothermal project types to provide pricing suggestions. The transaction matching model intelligently matches buyers and sellers based on their demand and price expectations. After the transaction is completed, the transaction information is stored on the blockchain. The write-off supervision module connects to the national CCER write-off system. When the carbon asset is written off, the platform automatically marks the carbon asset status as "written off" and continuously monitors the project's operation data. If the monthly fluctuation of carbon emission reduction exceeds ±15%, it will promptly issue a warning to the project owner and regulatory agency. The intelligent decision-making module analyzes the project's carbon emission reduction trend and transaction revenue, generates a visualized operation analysis report, and proposes suggestions for optimizing heat exchanger energy efficiency. The policy adaptation module updates local clean heating subsidy policies and carbon market trading policies in real time, providing policy compatibility analysis for the project owner. Regulatory agencies can view the geothermal heating project's operation data, carbon asset accounting results, transaction records, and write-off information in real time through the application-layer supervision interface. The blockchain storage module enables full-dimensional traceability and verification of data collection time, preprocessing process, and accounting standard matching records. The verification results generate a standardized verification report and are stored on the blockchain.

[0022] Example 2: Application of Photovoltaic Heating Project 1. Sensing Layer Deployment: Deploy IoT sensing terminals at key nodes of photovoltaic module arrays, inverters, energy storage equipment, and heating stations in photovoltaic heating projects. In addition to heat meters, flow meters, electricity meters, temperature sensors, and energy efficiency monitoring modules, add monitoring indicators for photovoltaic power generation and photoelectric conversion efficiency. The data collection frequency is set to 10 seconds / time. All sensing terminals comply with national / industry metrological verification standards. 2. Transmission layer and platform layer configuration: Same as in Example 1, the dynamic emission reduction calculation model of the algorithm engine refers to the national / industry calculation standard for carbon emission reduction of photovoltaic power generation, automatically matches the basic emission factor EF0 corresponding to photovoltaic heating, the energy efficiency correction coefficient α = actual operating energy efficiency of photovoltaic inverter / rated energy efficiency, and the temperature correction coefficient β is linearly corrected according to the difference between the operating environment temperature of photovoltaic module and the design operating temperature. 3. Application Layer Operation: After the basic information of the photovoltaic heating project is entered, the platform layer automatically completes the dynamic calculation of emission reduction, and the calculation results are stored on the blockchain. The certification application, transaction matching, and write-off supervision process is the same as in Example 1. The intelligent decision-making module analyzes the photoelectric conversion efficiency and power generation trend of photovoltaic modules and proposes energy efficiency improvement suggestions such as module cleaning and angle optimization. The policy adaptation module updates the photovoltaic industry subsidy and carbon market linkage policy in a synchronous manner.

[0023] Example 3: Application of Biomass Heating Project 1. Sensing Layer Deployment: Deploy IoT sensing terminals in key nodes of the fuel storage area, combustion furnace, and heating network of the biomass heating project. In addition to basic monitoring equipment, add monitoring indicators for biomass fuel consumption and combustion efficiency. The data collection frequency is set to 30 seconds / time. All sensing terminals comply with national / industry metrological verification standards. 2. Transmission layer and platform layer configuration: Same as in Example 1, the dynamic emission reduction calculation model of the algorithm engine refers to the national / industry calculation standard for carbon emission reduction of biomass heating, automatically matches the basic emission factor EF0 corresponding to biomass heating, the energy efficiency correction coefficient α = actual combustion efficiency of the combustion furnace / rated combustion efficiency, and the temperature correction coefficient β is linearly corrected according to the difference between the furnace temperature and the design heating temperature. 3. Application Layer Operation: After the basic information of the biomass heating project is entered, the platform layer completes the dynamic calculation of emission reduction and on-chain storage; the certification application, transaction matching, and write-off supervision process is the same as in Example 1. The intelligent decision-making module analyzes the biomass fuel consumption and combustion efficiency, and proposes suggestions such as fuel ratio optimization and furnace insulation improvement. The policy adaptation module updates the relevant policies on biomass fuel subsidies and carbon asset trading.

[0024] The present invention provides a detailed description of a clean heating carbon asset full lifecycle intelligent management platform and its implementation method. Specific embodiments have been used to illustrate the principles and implementation methods of the invention. These embodiments are merely illustrative and are intended to help understand the method and core ideas of the invention. It should be noted that those skilled in the art can make various improvements and modifications to the invention without departing from its principles, and these improvements and modifications also fall within the scope of protection of the claims.

[0025] Working principle of the invention: Each IoT sensing terminal in the perception layer collects multi-source data on heating, operation, energy consumption, and environment of the clean heating project at a frequency of seconds / minutes, and transmits it to the edge computing gateway in real time. The edge computing gateway performs preprocessing on the collected raw data, including deduplication, noise reduction, and abnormal data removal. After meeting the standards of abnormal data removal rate ≥99% and data integrity ≥98%, the preprocessed data is transmitted to the platform layer data middleware through an encryption protocol. At the same time, the raw data and preprocessing results are synchronized and stored on the blockchain through blockchain data transmission nodes. After the basic information of the clean heating project is entered at the application layer, the platform-level data middleware automatically matches the corresponding national / industry carbon emission reduction accounting standards and basic emission factor EF0 according to the project type (geothermal / photovoltaic / air source / biomass). The platform-level algorithm engine calls the dynamic emission reduction accounting model and calculates the energy efficiency correction coefficient α and temperature correction coefficient β based on the real-time operating data of the data middleware. After dynamically correcting the basic emission factor, the real-time, monthly, and annual carbon emission reduction accounting is completed according to the core formula ERy=BEy-PEy. All accounting results are automatically uploaded to the blockchain notarization module for tamper-proof notarization. The certification application module automatically generates standardized carbon asset certification application materials based on the accounting results and blockchain notarization information, including monitoring reports, accounting reports, blockchain data traceability certificates, etc. The project party submits the application to the carbon asset certification agency with one click through the platform. The platform tracks the application progress in real time and synchronizes key node information to the blockchain. Once a project's carbon assets pass CCER and other relevant certifications, the transaction management module records them into the carbon asset trading pool. The carbon asset valuation model in the algorithm engine combines real-time carbon market conditions, project emission reduction trends, and project type to provide pricing suggestions. The transaction matching model intelligently matches buyers and sellers based on their carbon asset demand, price expectations, and transaction cycle requirements. After a transaction is completed, the complete transaction information is stored on the blockchain. The write-off supervision module seamlessly integrates with the national carbon asset write-off system. After carbon assets are written off, the platform automatically marks the asset status as "written off" and continuously monitors the entire project operation data. When the monthly fluctuation of carbon emission reduction exceeds ±15%, it promptly issues an anomaly warning to the project owner and regulatory agencies to prevent duplicate carbon asset write-offs. The intelligent decision-making module conducts multi-dimensional data analysis on the project's carbon emission reduction trends and carbon asset trading revenue, generating a visualized operational analysis report and providing targeted suggestions such as equipment energy efficiency optimization and operational strategy adjustments. The policy adaptation module updates national and local clean heating subsidy policies, carbon market trading rules, and other relevant policy content in real time, providing project owners with policy compatibility analysis and implementation suggestions. Regulatory agencies can view real-time operational data of clean heating projects, carbon emission reduction calculation results, carbon asset trading records, and write-off status through a dedicated regulatory interface at the application layer. The blockchain notarization module enables full-process data traceability and compliance verification of carbon assets from data collection to write-off supervision, ensuring the authenticity, integrity, and compliance of carbon asset data.

[0026] The present invention provides a detailed description of a clean heating carbon asset full lifecycle intelligent management platform and its implementation method. Specific embodiments have been used to illustrate the principles and implementation methods of the invention. These embodiments are merely illustrative and are intended to help understand the method and core ideas of the invention. It should be noted that those skilled in the art can make various improvements and modifications to the invention without departing from its principles, and these improvements and modifications also fall within the scope of protection of the claims.

Claims

1. A smart management platform for the entire lifecycle of carbon assets in clean heating, comprising a sensing layer, a transmission layer, a platform layer, and an application layer, characterized in that, The perception layer, transmission layer, platform layer and application layer are interconnected and can transmit data bidirectionally. The sensing layer includes IoT sensing terminals, which are used to collect heating, operation, energy consumption and environmental parameters of the clean heating project in real time. The IoT sensing terminals include heat meters, flow meters, electricity meters, temperature sensors and energy efficiency monitoring modules. The data collection frequency is at the second / minute level, and all of them comply with national / industry metrological verification standards. The transmission layer includes a communication module, an edge computing gateway, and a blockchain data transmission node. The edge computing gateway communicates bidirectionally with the IoT sensing terminal through the communication module, which is used to preprocess the data collected by the sensing layer by deduplication, noise reduction, and abnormal data removal. The communication module encrypts and transmits the preprocessed data to the platform layer, and the blockchain data transmission node synchronously uploads the original collected data and the preprocessed results to the blockchain for evidence storage. The platform layer includes a data middle platform, an algorithm engine, and a blockchain evidence storage module. The data middle platform is connected to the transmission layer communication module to realize the fusion and storage of multi-source data. The algorithm engine has built-in dynamic emission reduction accounting model, carbon asset value assessment model, and transaction matching model. The blockchain evidence storage module is connected to the blockchain data transmission node to realize the immutable evidence storage of key data throughout the entire process. The application layer includes a carbon asset accounting module, a certification and application module, a transaction management module, a write-off supervision module, an intelligent decision-making module, and a policy adaptation module. Each module is linked with the platform layer's data middleware and algorithm engine to achieve one-stop management and control of carbon assets throughout their entire lifecycle, from data collection to write-off supervision.

2. The intelligent management and control platform for the entire life cycle of clean heating carbon assets according to claim 1, characterized in that, The communication module is a 5G communication module. The blockchain data transmission node adopts a consortium blockchain architecture to enable inter-node communication among project parties, regulatory agencies, certification bodies, and trading institutions. The blockchain evidence storage module adopts the Fabric framework, and the evidence storage objects include data collected by the perception layer, preprocessed data by the transmission layer, carbon emission reduction calculation results, certification application materials, carbon asset trading records, and write-off regulatory information.

3. The intelligent management and control platform for the entire life cycle of clean heating carbon assets according to claim 1, characterized in that, The dynamic emission reduction calculation model refers to the national / industry carbon emission reduction calculation standards corresponding to clean heating projects, and has a built-in core calculation formula ERy=BEy-PEy, where ERy is the carbon emission reduction within the statistical period, BEy is the baseline emission within the statistical period, and PEy is the actual emission of the project within the statistical period. The model also adds an energy efficiency correction coefficient α and a temperature correction coefficient β to dynamically correct the emission factor. The corrected emission factor is EF=EF0×α×β, where EF0 is the national / industry standard basic emission factor.

4. The intelligent management and control platform for the entire life cycle of clean heating carbon assets according to claim 3, characterized in that, The energy efficiency correction coefficient α = actual operating energy efficiency of the equipment / rated energy efficiency of the equipment, with a value range of 0.7-1.3; the temperature correction coefficient β is linearly corrected based on the difference between the actual ambient temperature and the design heating temperature. When the actual ambient temperature is lower than the design heating temperature, β is 1.0-1.2; when the actual ambient temperature is higher than the design heating temperature, β is 0.8-1.0; and when the actual ambient temperature is the same as the design heating temperature, β = 1.

0.

5. The intelligent management and control platform for the entire life cycle of clean heating carbon assets according to claim 1, characterized in that, The data platform adopts a Hadoop distributed storage architecture, supporting real-time, monthly, and annual data analysis and retrieval for multiple statistical periods. The carbon asset valuation model is a multiple regression model, with input parameters including real-time carbon market conditions, project carbon emission reduction trends, and clean heating project types, and outputting carbon asset pricing suggestions. The transaction matching model is a collaborative filtering algorithm model, which achieves intelligent matching based on the carbon asset demand, price expectations, and transaction cycle requirements of both buyers and sellers.

6. The intelligent management and control platform for the entire life cycle of clean heating carbon assets according to claim 1, characterized in that, The application layer is configured with four types of user permissions: project owners, regulatory agencies, trading institutions, and certification authorities. Each user can only view and operate the corresponding module functions. Among them, regulatory agencies have the full-node data traceability and verification permissions of the blockchain evidence storage module, while project owners only have the permission to view and operate their own project data.

7. A method for intelligent management and control of clean heating carbon assets throughout their entire lifecycle based on the platform described in any one of claims 1-6, characterized in that, Includes the following steps: Step 1: The perception layer collects multi-source data on heating, operation, energy consumption and environment of the clean heating project in real time at a frequency of seconds / minutes through IoT sensing terminals; Step 2: The transport layer edge computing gateway performs preprocessing on the collected raw data, including deduplication, noise reduction, and outlier removal. The preprocessing completion criteria are: outlier removal rate ≥ 99% and data integrity ≥ 98%. The communication module transmits the preprocessed data to the platform layer data middleware through an encryption protocol, while the blockchain data transmission node synchronizes the original data and the preprocessed results to the blockchain evidence storage module. Step 3: Enter basic information about the clean heating project through the application layer. The platform layer data middleware will automatically match the corresponding national / industry carbon emission reduction accounting standards and basic emission factor EF0 according to the project type. Step 4: The platform-level algorithm engine calls the dynamic emission reduction calculation model, combines the real-time data of the data platform to calculate the energy efficiency correction coefficient α and the temperature correction coefficient β, dynamically corrects the basic emission factor EF0, and calculates the carbon emission reduction according to ERy=BEy-PEy. It supports real-time, monthly and annual multi-cycle calculations. All calculation results are uploaded to the blockchain evidence storage module for tamper-proof evidence storage. Step 5: The application layer certification application module automatically generates standardized carbon asset certification application materials based on the accounting results and blockchain evidence information, supporting project parties to submit to carbon asset certification agencies with one click. The platform tracks the application progress in real time and records key node information and uploads it to the blockchain simultaneously. Step 6: After carbon assets are certified, the application layer transaction management module enters them into the carbon asset trading pool. The algorithm engine provides pricing suggestions through the carbon asset valuation model, and then realizes intelligent matching between buyers and sellers through the transaction matching model. After the transaction is completed, the transaction information is completely stored on the blockchain. Step 7: The application layer write-off supervision module connects with the national carbon asset write-off system. After the carbon asset is written off, the asset status is automatically marked as "written off". The module continuously monitors the project operation data. When the monthly fluctuation of carbon emission reduction exceeds ±15%, it issues an abnormal warning to the project party and regulatory agency to prevent duplicate write-off of carbon assets. Step 8: The application layer intelligent decision-making module analyzes the project's carbon emission reduction trend and trading revenue, generates a visualized operation analysis report, and proposes equipment energy efficiency optimization suggestions; the policy adaptation module updates the clean heating subsidy policy and carbon market trading policy in real time, providing policy compatibility analysis and application suggestions for project owners. Step 9: Regulatory agencies retrieve the full-process data from the blockchain evidence storage module through the application-layer regulatory interface to achieve full-process data traceability and compliance verification of carbon assets from collection to write-off.

8. The method for intelligent management and control of carbon assets throughout their entire lifecycle in clean heating, as described in claim 7, is characterized in that... The method is applicable to clean heating projects of geothermal, photovoltaic, air source and biomass types. The monitoring indicators of the sensing layer and the calculation parameters of the platform layer can be flexibly configured according to the project type. Among them, photovoltaic heating projects add monitoring indicators of photovoltaic power generation and photoelectric conversion efficiency, and biomass heating projects add monitoring indicators of biomass fuel consumption and combustion efficiency.

9. The method for intelligent management and control of clean heating carbon assets throughout their entire lifecycle as described in claim 7, characterized in that, In step 4, the calculation factors and the basis for the baseline emission BEy and the actual emission PEy of the project are consistent with the national / industry carbon emission reduction calculation standards corresponding to the project type, and the calculation results are measured in tons of CO2.

10. The method for intelligent management and control of clean heating carbon assets throughout their entire lifecycle as described in claim 7, characterized in that, The full-process data traceability and verification in step 9 includes full-dimensional traceability of data collection time, data preprocessing process, accounting standard matching record, emission reduction calculation process, application material submission record, transaction information, and write-off status. The verification results can generate a standardized verification report and be stored on the blockchain.

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