A large public building carbon emission monitoring management platform and implementation method

Abstract

This invention discloses a carbon emission monitoring and management platform and its implementation method for large public buildings. The platform, from bottom to top, connects a data acquisition layer, an infrastructure layer, a core service layer, a carbon management application layer, and a security management system and operation and maintenance management system that run through all levels. The implementation method includes multi-source data acquisition and preprocessing, data standardization and structured storage, accurate carbon emission calculation, multi-dimensional carbon emission analysis, carbon emission monitoring and anomaly alarms, carbon emission management and planning, and full-process security and operation and maintenance assurance. This invention enables dynamic monitoring and accurate calculation of carbon emissions, supports scientific decision-making and regulatory innovation in government departments, empowers carbon management and asset application for building entities, and promotes technological innovation and industry collaborative development.

Description

Technical Field

[0001] This invention relates to a carbon emission monitoring and management platform, specifically a carbon emission monitoring and management platform and implementation method for large public buildings, belonging to the field of carbon emission monitoring technology. Background Technology

[0002] In the field of carbon emission monitoring and management of large public buildings, although existing technologies have carried out some research on carbon emission data collection and basic accounting, they are still difficult to effectively solve the difficulties in carbon reduction caused by the large size, high energy intensity and complex management chain of public buildings.

[0003] Regarding the monitoring and management of carbon emissions from large public buildings, the existing technologies and challenges are as follows:

[0004] 1) The real-time online monitoring and management system for carbon emissions of cement enterprises disclosed in CN106647514A uses physical sensors such as temperature and humidity sensors and gas flow sensors to collect data, analyzes and processes the data through a single-chip microcomputer, and transmits the data through a GPRS wireless network and a cloud server. However, its technical solution focuses on solving the problems of sensor spatial registration and system error estimation. Its core is real-time monitoring rather than full-process carbon emission management. It has not built a complete architecture of data acquisition layer, infrastructure layer, core service layer and carbon management application layer, and lacks the ability to define the carbon emission accounting boundary and build differentiated baselines for public buildings.

[0005] 2) A carbon emission monitoring and management system and method disclosed in CN109727000A adopts a general architecture of information management module, monitoring plan module, login module, data processing module and data storage module, and realizes the functions of displaying carbon emission data, issuing plans and summarizing and storing data. However, the system only provides a simple modular design, does not clearly define the carbon emission accounting boundary for the building sector, and does not build a multi-dimensional carbon emission analysis function and a differentiated carbon emission baseline, which makes it unable to support the refined accounting of carbon emissions of public buildings and horizontal benchmarking of similar buildings.

[0006] 3) The carbon emission online monitoring and management system based on the industrial internet disclosed in CN116338086A adopts a three-part architecture of management screen, platform and data acquisition system. It focuses on the functions of carbon emission data acquisition, processing and uploading. It is mainly aimed at enterprise carbon emission monitoring scenarios. It has not built a full-process technology stack from data acquisition to carbon management application for large public buildings, and lacks the ability to analyze and plan carbon emissions from multiple dimensions.

[0007] 4) The urban road carbon emission monitoring and management system based on big data disclosed in CN117271992A obtains the predicted road carbon emission curve by combining the vehicle carbon emission prediction module with the camera unit, vehicle speed detection unit and preset model, and performs correlation matching analysis with the meteorological state monitoring terminal and the environmental parameter monitoring terminal. It is mainly used for real-time monitoring and adjustment of road vehicle carbon emissions, rather than carbon emission management for the operation phase of public buildings, and does not involve technical features such as building carbon emission accounting boundary, emission factor method calculation and differentiated baseline construction.

[0008] 5) The building operation carbon emission metering monitoring and management method and system disclosed in CN118671267A uses a carbon emission monitoring sensor network to collect energy consumption data of various energy-consuming equipment inside the building in real time, calculates carbon emissions through edge computing devices and uploads them to the cloud platform for data analysis and trend prediction, and finally displays the analysis report through a visual interface. However, this technical solution only adopts a three-layer architecture of "sensor network - edge computing - cloud platform", focuses on real-time monitoring and abnormal early warning of individual energy-consuming equipment, does not disclose a complete carbon emission accounting boundary setting method, and does not build a differentiated carbon emission baseline based on historical emission method and industry benchmark method. Moreover, its application function is limited to trend prediction and abnormal warning, and lacks the ability to deeply mine and plan carbon emissions in multiple dimensions.

[0009] 6) A carbon emission monitoring and management platform for enterprises, disclosed in publication number CN119443553A, integrates emission source data through a data acquisition module and sets short-term and long-term low-carbon adjustment schemes based on high-energy-consuming nodes and energy consumption cycles. It aims to solve the problems of carbon emission data mining and emission reduction strategy optimization during changes in enterprise scale or business model. However, this platform is primarily geared towards enterprise scenarios. Its architecture consists of a data acquisition module, a data collection module, a first low-carbon adjustment module, a second low-carbon adjustment module, and a monitoring and management module. Its focus is on dynamically adjusting emission reduction schemes based on energy consumption changes, rather than building a complete "data acquisition - infrastructure - core services - carbon" system for large public buildings. The system employs a four-layer technology stack for "management applications," but it does not use the emission factor method for accurate carbon emission accounting, nor does it define complete accounting boundaries for Scope 1, Scope 2, and Scope 3. Furthermore, it does not provide multi-dimensional mining functions such as carbon emission correlation analysis, trend analysis, composition analysis, and attribution analysis. It also lacks digital ledger management and carbon emission planning modules for individual buildings. As a result, it is unable to address core challenges in carbon emission management of public buildings, such as inconsistent data collection standards leading to difficulties in cross-departmental energy data integration, carbon emission accounting relying solely on historical data and ignoring the building's completion year and scale characteristics, resulting in inaccurate calculations, and a lack of low-carbon compliance verification and personalized operation and maintenance strategies at the application level, leading to a missing management loop.

[0010] In summary, existing technologies generally suffer from several prominent problems, including inconsistent data collection standards leading to difficulties in cross-departmental energy data integration; carbon emission accounting relying solely on historical data while ignoring building completion years and scale characteristics, resulting in inaccurate calculations; and a lack of low-carbon compliance verification and personalized operation and maintenance strategies at the application level, leading to a missing management loop. Specifically, current carbon emission management of public buildings faces three core challenges: First, data collection is difficult. The accuracy of basic building information is low, and energy usage boundaries are unclear. Energy data is scattered across multiple departmental systems, including electricity, water, gas, and housing and construction. Reliance on manual reporting makes it difficult to obtain accurate data, cross-industry integration, and quality assurance. First, data calculation is difficult. The carbon emission baseline construction method is singular, relying solely on historical data for estimation, which cannot reflect the impact of key factors such as building type, scale, and commissioning time. Furthermore, the lack of a unified digital platform to support real-time monitoring and dynamic analysis makes it difficult to make horizontal comparisons of similar buildings, ultimately leading to inaccurate calculations, ineffective control, and unrealistic reductions. Second, data application is difficult. After buildings are put into operation, there is a lack of effective means to verify their low-carbon compliance and the ability to formulate personalized operation and maintenance strategies based on the characteristics of individual buildings. The lack of high-quality data support for diversified scenarios such as green building evaluation by competent authorities and carbon finance monetization by financial institutions seriously restricts the realization of the value of carbon management. Summary of the Invention

[0011] The purpose of this invention is to provide a large-scale public building carbon emission monitoring and management platform and implementation method to solve the current difficulties of "difficult data collection, difficult calculation, and difficult application" in the management of carbon emissions in public buildings. This will form a digital governance foundation for carbon emissions in public buildings with full coverage of data collection, full chain of data governance, and full scenarios of data application, promote the transformation of carbon emission management in the building sector from dual control of energy consumption to dual control of carbon emissions, and improve the level of refined, intelligent, and collaborative governance of carbon emission management.

[0012] The present invention achieves the above objectives through the following technical solution: a carbon emission monitoring and management platform for large public buildings, comprising a monitoring and management platform, which includes a data acquisition layer, an infrastructure layer, a core service layer, a carbon management application layer, and a security management system and an operation and maintenance management system that run through each layer from bottom to top;

[0013] The data acquisition layer serves as the data supply base for the monitoring and management platform, connecting with external multi-source energy data systems and manual reporting terminals to achieve the original aggregation, preliminary treatment, and reliable transmission of energy consumption and basic data of public buildings.

[0014] The infrastructure layer provides the platform with computing, storage, and network resources to support the cloud architecture, ensuring the platform's efficient and stable operation.

[0015] The core service layer serves as the central hub of business logic and the engine for data value transformation. It connects downwards to the standardized data of the data acquisition layer to complete data governance and algorithm execution, and upwards to provide business function interfaces for the carbon management application layer. At the same time, it ensures the compliance and stability of the service through permission, algorithm, and storage management.

[0016] The carbon management application layer serves as the business value terminal, providing users with a full-process carbon management function encompassing "accounting-statistics-analysis-planning" of carbon emissions. It transforms the data analysis results from the core service layer into actionable and decision-making carbon management capabilities. The security management system and operation and maintenance management system ensure the platform's data security, stability, compliance, and efficient operation from the perspectives of security protection and full lifecycle operation, respectively.

[0017] As a further aspect of this invention: the data acquisition layer adopts a hybrid acquisition method of online automatic acquisition and offline collaborative data entry. The online automatic acquisition connects to the information systems of energy companies, including electricity, water, and gas companies, through a RESTful API interface, supporting the reception of hourly energy consumption data by item. The offline collaborative data entry includes two forms: online data entry and report upload. The platform has functions for format verification, logical verification, and consistency comparison of manually collected data in offline collaborative data entry. If the verification fails, the platform will prompt the error reason and support resubmission after correction.

[0018] As a further aspect of the present invention: the infrastructure layer encompasses network communication facilities, cloud infrastructure, and computing power infrastructure;

[0019] The network communication facilities are responsible for communication between various architectural layers within the monitoring and management platform and between the monitoring and management platform and external data sources. The network communication facilities integrate VPC virtual network and SLB server load balancing resources to ensure low latency, no loss, and no damage in data transmission.

[0020] Cloud infrastructure includes computing resource modules, storage resource modules, and service management modules;

[0021] The computing resource module is based on physical server virtualization to form virtual machines, which supports elastic scaling of CPU and memory resources and automatically adjusts resource configuration according to changes in business load.

[0022] The storage resource module adopts a tiered storage architecture: structured data is stored in an internal RDS for MySQL database, and table partitioning is used when the data volume is large; unstructured data is stored in OSS object storage service.

[0023] The service management module provides full lifecycle resource management capabilities for cloud infrastructure. Through the cloud resource management platform, it enables automated deployment, monitoring, expansion, and operation and maintenance of virtual machines, servers, distributed storage, and cloud disks.

[0024] As a further aspect of the present invention, the core functions of the core service layer include:

[0025] Data governance: Cleaning, deduplication, completion, and verification of raw data; screening and marking missing values, erroneous records, and outliers; and incorporating outlier data into the review process.

[0026] Data standardization: Built-in standard model for energy and carbon emission data of public buildings, which converts multi-source heterogeneous data into a unified format of the platform, makes data mapping relationships traceable, and supports unified maintenance of data dictionary;

[0027] Algorithm execution: Run the core algorithms, including carbon emission accounting, statistics, analysis and baseline construction, and transform standardized data into a basis for business decisions;

[0028] Access Control: A role-based access control model enables fine-grained management of users, roles, and permissions, ensuring compliance of data and function access; supports custom roles, with permission granularity refined to the region and building level; authentication supports username / password and two-factor authentication.

[0029] Data lifecycle management: Enables data storage, archiving, cleaning, backup and recovery, with fault tolerance capabilities and 100% test case coverage.

[0030] As a further embodiment of the present invention: the carbon management application layer includes a carbon emission accounting module, a carbon emission statistics module, a carbon emission analysis module, a carbon emission alarm module, a single building module, and a carbon emission planning module;

[0031] The carbon emission accounting module clarifies the accounting boundaries and uses the emission factor method to calculate carbon emissions and carbon emission intensity. The accounting boundaries include at least the reporting entity, organizational boundaries, operational boundaries, and base year. The operational boundaries cover Scope 1 (direct emissions), Scope 2 (indirect emissions), and Scope 3 (other indirect emissions) are extended to include Scope 3.

[0032] The formula for calculating carbon emissions using the emission factor method is as follows:

[0033]

[0034] In the formula, i represents the year; j represents the type of energy; and k represents the number of buildings. Let K be the total carbon emissions of the k-th building in year i. Let J be the energy consumption of the k-th building in the i-th year for the j-th type of energy. Let be the emission factor for the j-th energy source;

[0035] The formula for calculating carbon emission intensity is:

[0036]

[0037] In the formula, Let the carbon emission intensity of building k in year i be . Let K be the building area of ​​the kth building;

[0038] The carbon emission accounting module has a built-in national, local, and enterprise-level three-level carbon emission factor library, and has the ability to expand new methodologies through configuration. The accounting dimensions cover buildings, energy types, equipment, and time, and support multi-dimensional combined accounting.

[0039] The carbon emission analysis module, through multi-dimensional data mining and algorithm model application, analyzes the patterns, anomalies, and potential of carbon emissions, providing scientific and actionable quantitative support for carbon reduction decisions in public buildings. Specifically, it includes:

[0040] Correlation analysis: to explore the degree of correlation between carbon emissions and external variables, including region, building type, scale, and commissioning time;

[0041] Trend Analysis: Using time series analysis, we analyzed the trends in total carbon emissions and intensity of buildings over the past five years, identifying cyclical characteristics and peaks and troughs.

[0042] Compositional analysis: Deconstructing the carbon emission structure from the dimensions of energy type, building area, and equipment type to identify core emission sources;

[0043] Attribution analysis: By comparing with similar buildings and industry benchmarks, the emission differences are quantified and the current emission status is analyzed using root cause analysis.

[0044] The results of the carbon emission analysis module are presented in visual formats including bar charts, pie charts, heat maps, and trend line charts.

[0045] The carbon emission alarm module supports threshold alarms and equipment malfunction alarms, and the alarm rules, content, and levels can be customized.

[0046] The alarm levels are divided into four levels: emergency, important, general, and alert. Different levels correspond to different notifications, handling priorities, and time limits. The carbon emission alarm module supports alarm confirmation and full traceability of handling records.

[0047] The individual building module establishes a metadata digital ledger for each building, including building ID, name, address, and area. It collects hourly energy consumption data for each device and branch, and displays the carbon emission percentage and annual / monthly / daily trends of each item through visual charts, covering energy types including electricity, water, gas, and renewable energy.

[0048] The carbon emission planning module is used to realize the whole process of emission reduction planning from "target setting - path optimization - task implementation - effect tracking". It analyzes the quota surplus based on building carbon quota data and cumulative carbon emissions, and formulates carbon reduction targets by combining policy requirements, industry benchmarks, historical building emission data and the feasibility of emission reduction measures.

[0049] The carbon emission planning module displays the carbon emission intensity per unit building area, annual / monthly baseline emissions, and planned reduction rate. It accurately quantifies and displays the emission proportions of carbon emission range one and range two, supports the generation and download of carbon emission reports, restores the actual building structure, and realizes the linkage display of energy data and building models.

[0050] As a further aspect of the present invention: the security management system adopts a four-dimensional protection strategy of "network-data-application-compliance", including network security protection, encryption of core network transmission, encrypted storage of sensitive data and user passwords, and fine-grained access control based on the RBAC model.

[0051] The operation and maintenance management system adopts a four-dimensional management strategy of "monitoring-disaster recovery-version-process", which includes full data backup, data recovery by time point, version iteration and rollback of platform / service / algorithm, and standardized operation and maintenance process. The operation and maintenance process includes all nodes of "submission-acceptance-processing-verification-closure", with node status updated in real time and processing records left trace throughout the process.

[0052] As a further aspect of the present invention: the monitoring and management platform constructs a differentiated carbon emission baseline calculation model, and combines historical emission methods and industry benchmark methods to establish the baseline;

[0053] The historical emissions method is based on the building’s own historical emissions data, selecting the average emissions of a single year or multiple consecutive years as a benchmark.

[0054] The industry benchmark method uses the carbon emission intensity benchmark values ​​for each type of public building, and also provides the quartile data of the carbon emission intensity benchmark for each type.

[0055] A method for implementing a carbon emission monitoring and management platform for large public buildings, comprising the monitoring and management platform, the method comprising the following steps:

[0056] S1: Multi-source data acquisition and preprocessing. Acquire basic information of public buildings and energy consumption data of electricity / water / gas through automatic collection and manual entry. Perform unit conversion, time format unification and field standardization preprocessing on the raw data. Screen and process missing values, erroneous records and out-of-format values.

[0057] S2: Data standardization and structured storage transforms pre-processed multi-source heterogeneous data into a unified data model for the platform. The data is precisely associated with building entities through a unique code consisting of a 6-digit district / county administrative code and a 9-digit sequence code. The processed data is then stored in a building carbon emission database for structured storage.

[0058] S3: Accurate carbon emission accounting, setting accounting boundaries, using the emission factor method to calculate building carbon emissions and carbon emission intensity per unit area, and combining historical building data with industry standards to build a differentiated carbon emission baseline;

[0059] S4: Multi-dimensional carbon emission analysis, which deeply mines and analyzes carbon emission data from four dimensions: correlation, trend, composition and attribution, and presents the analysis results in a visual form;

[0060] S5: Carbon emission monitoring and anomaly alarm, real-time monitoring of building carbon emission data, identification of data anomalies based on custom rules and graded alarms, confirmation, handling and recording of alarm information throughout the process;

[0061] S6: Carbon emission management and planning. Based on accounting and analysis results, establish a digital ledger for individual buildings to achieve refined management. Combine carbon quota data, policy requirements and industry benchmarks to formulate building carbon reduction targets and planning schemes to realize the quantification and value of emission reduction results.

[0062] S7: End-to-end security and operation and maintenance assurance. It implements security protection measures such as encryption and access control throughout the entire process of data collection, transmission, storage and application. At the same time, it carries out data backup, version management and process control to ensure the stable and compliant operation of the platform.

[0063] As a further aspect of the present invention: the setting of accounting boundaries includes determining the reporting subject, organizational boundaries, operational boundaries, and base year, wherein the operational boundaries at least cover direct emissions in Scope 1 and indirect emissions in Scope 2. Scope 1 is the carbon dioxide emissions generated by the combustion of fossil fuels at fixed combustion sources during the operation phase of public buildings, and Scope 2 is the carbon dioxide emissions generated by production processes using purchased electricity, steam, heat, or cold during the operation phase of public buildings.

[0064] As a further aspect of this invention: after the carbon reduction target is set, the platform tracks the gap between the actual carbon emissions of buildings and the carbon reduction target in real time, quantitatively displays the proportion of carbon emissions in range one and range two, generates a carbon emission report, and provides differentiated data support and application services for different entities, including government departments, building owners, and research institutions, to achieve multi-party collaboration among government, industry, academia, and research.

[0065] The beneficial effects of this invention are:

[0066] 1) Achieve dynamic monitoring and accurate accounting of carbon emissions: By automatically collecting, integrating, analyzing and intelligently calculating multi-source metering data such as electricity, water, gas and heat during the operation of public buildings, a carbon emission monitoring network covering the operation of public buildings can be constructed to achieve dynamic tracking and scientific assessment of the total amount and intensity of carbon emissions from public buildings.

[0067] 2) Supporting scientific decision-making and regulatory innovation in government departments: By unifying the data base and carbon emission analysis results through the platform, it provides data support and basis for government departments to improve local carbon emission assessment systems, carry out industry carbon control, and formulate energy conservation and carbon reduction policies, thereby promoting the transformation of the construction sector from "dual control of energy consumption" to "dual control of carbon emissions".

[0068] 3) Empowering carbon management and asset application of building entities: Based on the high-quality carbon emission data generated by the platform, it provides support for building owners or their agents to conduct carbon emission self-inspection, energy-saving renovation, carbon performance evaluation and carbon asset management, so as to realize the quantification and value of emission reduction results;

[0069] 4) Promote technological innovation and industry collaboration: Provide standardized and traceable data support for scientific research institutions, design and consulting agencies and energy-saving service companies, promote carbon emission analysis, carbon-saving technology research and development and application of results, and build an innovative ecosystem for building carbon emission management that is collaborative among government, industry, academia and research. Attached Figure Description

[0070] Figure 1 This is a schematic diagram of the platform architecture of the present invention;

[0071] Figure 2 This is a flowchart illustrating the operation of the monitoring and management platform of the present invention.

[0072] Figure 3 This is the homepage of the carbon emission status module in the carbon emission monitoring and management of large public buildings of this invention;

[0073] Figure 4 This is the homepage of the carbon emission management module in the carbon emission monitoring and management of large public buildings of this invention;

[0074] Figure 5 This invention presents the carbon inventory data of a large enterprise office building in operation for a specific year.

[0075] Figure 6 This is a ranking chart of building projects in the carbon assessment of building projects according to the present invention. Detailed Implementation

[0076] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0077] Example 1, as Figure 1As shown in the figure, this embodiment provides a carbon emission monitoring and management platform for large public buildings. This platform is designed with the core concepts of end-to-end data connectivity and full-scenario business coverage, constructing an integrated architecture of "four progressive layers, two-system guarantees, and one foundation support." This includes a data acquisition layer, infrastructure layer, core service layer, carbon management application layer, and a security management system and operation and maintenance management system that run through all layers, connected sequentially from bottom to top. Through this monitoring and management platform, a closed-loop management system for the entire carbon emission data chain—from acquisition and transmission to processing, application, security, and operation and maintenance—is achieved. It also enables the creation of a province-wide and city-wide public building carbon emission monitoring overview video wall, carbon emission status, carbon emission management, individual building carbon emissions, and carbon emission applications, achieving unified monitoring, analysis, and management of carbon emissions from public buildings within the region.

[0078] Specifically, this monitoring and management platform includes:

[0079] I. The data acquisition layer is the starting point and source of the data link of the platform (monitoring and management platform). It is the data supply base of the upper-level architecture, directly connecting to the data acquisition systems of various energy-consuming units (Internet of Things management platform of power grid company, electricity information acquisition system, smart water system of water company, data management system of gas supplier, etc.) as well as manual reporting terminals. It is the connection interface between the platform and external data sources, undertaking the core functions of "raw data aggregation, preliminary data treatment, and reliable transmission", and providing reliable data support for the platform.

[0080] The data acquisition layer employs a hybrid approach of online automatic collection and offline collaborative data entry. Automatic collection connects to the information systems of energy companies, including those providing electricity, water, and gas, via a RESTful API interface to retrieve energy data. The API call response time is ≤3 seconds, the collection frequency is configurable, and an interface authentication mechanism is supported to ensure secure data transmission. It supports hourly-level segmented energy consumption data reception; specifically, it obtains segmented data from the IoT management platform uploaded by the RESTful API interface for various public building applications, including electricity, cooling, heating, water, coal, oil, and gas data for different application scenarios such as new energy power generation, power supply, air conditioning, lighting, and cooking.

[0081] Manual data entry includes both online submission and report upload. The platform provides format verification, logical validation, and consistency comparison for manually collected data. Failed data submissions are accompanied by error messages explaining the reasons for the errors and allow for corrections and resubmission. Online submission involves registered users logging in with their username and password to enter energy and carbon data. The platform features data format and integrity checks, logical validation, and error message explanations for failed data submissions. Users can correct and resubmit the data. The platform supports online data entry and submission, and includes functions for saving, drafting, and undoing modifications. Non-compliant data is flagged for rectification, and queries are supported. The entire process is traceable through log records. Report upload involves registered users logging in with their username and password to upload reports in a template format. Excel files are supported, with a maximum file size of 100MB. The platform also features data format, integrity, and logical validation. Failed data submissions are accompanied by error messages explaining the reasons for the errors and allow for corrections and resubmission.

[0082] Second, the infrastructure layer is the resource foundation for the platform's stable operation, providing computing, storage, and network resources to support the cloud architecture and ensure the platform's efficient and stable operation. The infrastructure layer encompasses network communication facilities, cloud infrastructure, and computing power infrastructure.

[0083] As the "main artery" of platform data transmission, network communication infrastructure undertakes communication tasks between the data acquisition layer, core service layer, carbon management application layer, and between the platform and external data sources. By integrating existing VPC virtual networks and network SLB load balancing resources, network communication infrastructure further enhances the low-latency characteristics of data transmission, ensuring that data is not lost or damaged during transmission and comprehensively guaranteeing data transmission quality.

[0084] Cloud infrastructure serves as the "virtual carrier" for platform data storage and business service operation. Through virtualization and distributed technologies, it provides elastic and scalable computing and storage resources, supporting on-demand resource allocation and dynamic scheduling to meet the platform's resource needs in different business scenarios. Simultaneously, it integrates existing virtual machines, servers, distributed storage, cloud disks, and other resources to improve resource utilization efficiency and service reliability. Cloud infrastructure includes computing resource modules, storage resource modules, and service management modules.

[0085] The computing resource module uses existing servers as its physical foundation and abstracts physical server resources into multiple independent virtual machines through virtualization technology. This enables flexible allocation and efficient utilization of computing resources, supporting elastic scaling of CPU and memory resources. It can automatically adjust the number of CPU cores and memory capacity of virtual machines according to changes in business load (such as peak carbon emission accounting periods or large-scale data processing tasks), meeting the high demands of computing resources for computationally intensive tasks. For example, when performing monthly or annual carbon emission accounting, the platform can quickly expand computing resources, shorten the accounting cycle, and improve business processing efficiency.

[0086] The storage resource module adopts a tiered storage architecture: structured data is stored in the internal RDS for MySQL database, and table partitioning is used when the data volume is large; unstructured data is stored in OSS object storage service.

[0087] The service management module provides full lifecycle resource management capabilities for cloud infrastructure. Through the cloud resource management platform, it enables automated deployment, monitoring, scaling, and operation and maintenance of resources such as virtual machines, servers, distributed storage, and cloud disks.

[0088] III. The core service layer, serving as the central hub of business logic and the engine for data value transformation, connects downwards to the standardized data from the data acquisition layer to complete data governance and algorithm execution; it also provides business function interfaces to the carbon management application layer, while ensuring service compliance and stability through permission, algorithm, and storage management. The core functions of the core service layer include:

[0089] Data governance involves cleaning, deduplicating, completing, and validating raw data; screening and marking missing values, erroneous records, and outliers; and incorporating outlier data into the review process to improve data quality and lay the foundation for subsequent business processing.

[0090] Data Standardization: The built-in standard model for energy and carbon emission data of public buildings converts heterogeneous data from multiple sources (such as different formats of electricity, water, and gas data) into a unified format on the platform, ensuring semantic consistency and format compatibility. The standard model for energy and carbon emission data of public buildings includes dimensions such as energy type, carbon emission factor, building type, building area, and commissioning time. It supports flexible model expansion, and the mapping relationship between the converted data and the original data is traceable. At the same time, it supports unified maintenance of the data dictionary, and performs unified maintenance of enumerated data such as equipment type, energy unit, and carbon emission factor.

[0091] Algorithm execution: Run the core algorithms, including carbon emission accounting, statistics, analysis and baseline construction, and transform standardized data into a basis for business decisions.

[0092] Access Control: A role-based access control model enables fine-grained management of users, roles, and permissions, ensuring compliance of data and function access; it supports custom roles, with permission granularity refined to the region and building level, and identity authentication supports username / password and two-factor authentication.

[0093] Data lifecycle management: Enables data storage, archiving, cleaning, backup and recovery, ensuring data reliability and accessibility; possesses fault tolerance capability with 100% test case coverage, and special tests should be conducted for issues such as memory overflow and resource non-release.

[0094] IV. The carbon management application layer is the platform's business value terminal, directly providing users with full-process carbon management functions encompassing "accounting-statistics-analysis-planning." It transforms the data analysis results from the core service layer into actionable and decision-making carbon management capabilities, making it a key layer for achieving refined control and carbon reduction decisions in public buildings. The carbon management application layer includes modules for carbon emission accounting, carbon emission statistics, carbon emission analysis, carbon emission alarms, individual building modules, and carbon emission planning.

[0095] The carbon emission accounting module clearly defines the accounting boundaries and uses the emission factor method to calculate carbon emissions and carbon emission intensity. Specifically, it calculates carbon emissions by statistically analyzing the energy consumption or material usage of specific activities and combining this with the corresponding carbon emission intensity (factor), thus completing the quantification of carbon emissions across all dimensions of buildings and providing benchmark data for carbon statistics and analysis. The accounting boundaries include at least the reporting entity, organizational boundaries, operational boundaries, and a base year. The operational boundaries cover direct emissions (Scope 1), indirect emissions (Scope 2), and extend to include other indirect emissions (Scope 3).

[0096] Direct emissions refer to carbon dioxide emissions from the combustion of fossil fuels at stationary combustion sources during the operation of public buildings, such as boilers, stoves, and generators. Specifically, this includes coal, natural gas, and oil consumed in boiler rooms or water boiler rooms, and natural gas, liquefied petroleum gas, and coal consumed in canteens. Indirect emissions are carbon dioxide emissions from production processes that use purchased electricity, steam, heat, or cooling during the operation of public buildings. Specifically, this includes purchased electricity (excluding renewable energy sources such as photovoltaics and wind power) consumed in public building lighting, air conditioning (fresh air), elevators, electric water heaters, water pumps, and communication equipment rooms, as well as purchased heat (hot water or steam) (excluding renewable energy sources such as solar thermal) consumed for heating and domestic hot water. Other indirect emissions arise throughout the building's value chain (including upstream and downstream activities). For example, carbon dioxide emissions from the use of purchased production and office water during the operation of public buildings.

[0097] The formula for calculating carbon emissions using the emission factor method is as follows:

[0098]

[0099] In the formula, i represents the year; j represents the type of energy, such as electricity or natural gas; and k represents the number of buildings. Let K be the total carbon emissions of the k-th building in year i. Let J be the energy consumption of the k-th building in the i-th year for the j-th type of energy. For the emission factor of the j-th energy source, select the latest data released by the Ministry of Ecology and Environment or the emission factor released by the local authoritative agency; for example, the carbon dioxide emission factor of electricity should be the average carbon dioxide emission factor of electricity released by the municipal administrative department of the project area in the previous year or the provincial average carbon dioxide emission factor of electricity in the project area released by the Ministry of Ecology and Environment.

[0100] The formula for calculating carbon emission intensity is:

[0101]

[0102] In the formula, Let the carbon emission intensity of building k in year i be . Let K be the building area of ​​the kth building;

[0103] The carbon emission accounting module has a built-in three-level carbon emission factor library at the national, local, and enterprise levels. It has the ability to expand new methodologies through configuration. The accounting dimensions cover building (individual / regional / building), energy type (electricity, water, gas, heat, etc.), equipment, and time (day / week / month / year), and support multi-dimensional combined accounting.

[0104] The carbon emission analysis module utilizes multi-dimensional data mining and algorithmic models to analyze the patterns, anomalies, and potential of carbon emissions, providing scientific and actionable quantitative support for carbon reduction decisions in public buildings. The results of the carbon emission analysis module are presented through visualizations including bar charts, pie charts, heatmaps, and trend line graphs. Specifically, this includes:

[0105] Correlation analysis: This involves exploring the correlation between carbon emissions and external variables, including region, building type, scale, and commissioning time. Specifically, it includes: visually presenting the emission scale through a bar chart of annual total carbon emissions; displaying the intensity information of building classifications above a certain scale to understand the carbon emission characteristics of different building types; examining the carbon emission distribution of each building type by completion year to explore the correlation between building usage time and carbon emissions; analyzing the carbon emission share of different building types within a province to understand the emission structure of different building types, thus contributing to precise emission reduction; and selecting the factors with the greatest impact on carbon emissions from multiple dimensions to provide a scientific basis for emission reduction strategies.

[0106] Trend Analysis: Using time series analysis, this study analyzes the trends in total carbon emissions and intensity of buildings over the past five years, identifying cyclical characteristics, peaks, and troughs. Specifically, it compares and analyzes historical data for different building types to understand the differences and evolution in carbon emission intensity and structure during this period. This provides a basis for predicting future carbon emissions and developing targeted emission reduction measures, analyzing the patterns of carbon emission changes over time. The implementation involves using time series analysis to identify emission patterns within monthly and annual cycles, analyzing carbon emission trends. This assists in developing periodic operation and maintenance strategies and provides trend references for long-term emission reduction planning.

[0107] Composition analysis: The carbon emission structure is broken down from the dimensions of energy type (electricity, natural gas, etc.), building area (zoning, floors, functional areas), and equipment type (air conditioning, lighting, elevators, etc.) to identify the core emission sources and provide clear targets for emission reduction.

[0108] Attribution analysis: By comparing with similar buildings (same region, same type, same scale) and industry benchmarks, the emission differences are quantified and the root cause analysis method is used to analyze the current emission status from the dimensions of building characteristics, management strategies and other dimensions.

[0109] The carbon emission alarm module serves as the risk control hub of the carbon management application layer. Individual buildings can monitor abnormal fluctuations in carbon emission data in real time, achieving full-process control from "anomaly identification – tiered early warning – rapid response – closed-loop management." This aims to control abnormal carbon emission risks at their inception, avoiding energy waste and increased costs caused by abnormal emissions. The carbon emission alarm module specifically includes:

[0110] Alarm rules: Supports threshold alarms and device malfunction alarms. Rules, alarm content, and alarm levels can be customized.

[0111] Alarm levels are divided into four levels: Emergency, Important, General, and Alert. Different levels correspond to different notifications, priorities, and processing time limits.

[0112] Handling process: Supports alarm confirmation and full traceability of handling records.

[0113] The individual building module is the basic management unit for carbon emission monitoring and management of public buildings. It displays basic information about individual public buildings and daily and monthly carbon emission trends. It also supports visualization to summarize energy consumption and carbon emission information for different equipment locations within the public building. Public buildings capable of measuring individual energy consumption and carbon emissions are one of the core objects of the platform's data collection, management, and analysis. The individual building module specifically includes:

[0114] Carbon data collection: Hourly energy consumption data of individual building branches and equipment is collected through an IoT physical platform to achieve total energy consumption and data collection of key equipment.

[0115] Data Scope: Divided into multiple usage scenarios such as power consumption, air conditioning consumption, office lighting consumption, and canteen gas consumption, the data uses pie charts to display the carbon emission percentage of each item and line graphs to display the annual / monthly / day carbon emission change trends of each item. It covers building energy types including electricity, water, gas, and renewable energy; data on all equipment (air conditioning, lighting, elevators, kitchen equipment, etc.); and auxiliary data such as basic building information (building area, number of floors, and building year).

[0116] Building Information Management: Establish a "digital ledger" for individual buildings, including metadata such as building ID, name, address, use, and area.

[0117] The carbon emission planning module serves as the strategic decision-making hub of the carbon management application layer. Focusing on the entire process of "goal setting – path optimization – task implementation – effect tracking," it provides scientific and feasible planning solutions for long-term carbon reduction efforts in public buildings, helping users shift from "passive emission reduction" to "proactive carbon control." The carbon emission planning module specifically includes:

[0118] Carbon reduction target setting: Based on the annual and monthly carbon allowance data of maintained public buildings, as well as the annual and monthly cumulative carbon emission data, analyze the allowance surplus.

[0119] The development logic is based on setting targets according to policy requirements and industry benchmarks, combined with historical building emissions data and the feasibility of emission reduction measures.

[0120] Visual presentation: Restore the real structure of public buildings and realize the linkage display of data such as water, gas, power electricity, lighting electricity, and air conditioning electricity with the model.

[0121] Scientific decision-making includes, but is not limited to, displaying carbon emission intensity per unit building area, annual baseline emissions, monthly baseline emissions, and planned reduction rates.

[0122] Carbon Emissions Report: In terms of data coverage and percentage display, it accurately focuses on the core scope of carbon emission accounting, clearly distinguishes and quantifies the carbon emission percentage of carbon emission category one (direct emissions, such as carbon emissions from burning natural gas) and carbon emission category two (indirect emissions, such as carbon emissions from purchased electricity and heat).

[0123] The security management system and the operation and maintenance management system ensure the platform's data security, stability, compliance, and efficient operation from the perspectives of security protection and full lifecycle operation, respectively.

[0124] V. The security management system serves as a "protective barrier" for the platform's stable operation throughout its entire lifecycle. It permeates the data acquisition layer, infrastructure layer, core service layer, and carbon management application layer, ensuring platform data security, system stability, and compliant operation through four-dimensional protection: "network-data-application-compliance." Specifically, it includes:

[0125] Network security protection: Build a secure defense line at the network boundary and within internal transmission to prevent network risks such as illegal intrusion and data leakage.

[0126] Encrypted transmission: Core network transmissions employ encryption protocols, prohibiting the transmission of sensitive data in plaintext.

[0127] Storage Encryption: Sensitive data and user passwords are stored in encrypted form.

[0128] Access control: Fine-grained data access control is implemented based on the RBAC model, with data access restricted by user authentication and permission verification.

[0129] VI. The operation and maintenance management system is the "central guarantee" for the efficient operation of the platform throughout its entire lifecycle. Through four-dimensional management—"monitoring, disaster recovery, version control, and process control"—it achieves efficient operation and maintenance, automated handling, and standardized processes for platform equipment, services, and applications. Specifically, it includes:

[0130] Data backup: Ensures that the platform's data is not lost and its business is not interrupted in the event of failure or disaster.

[0131] Recovery capability: Supports data recovery by time point, with a 100% data recovery success rate.

[0132] Version management: The version iteration process of platform systems, services, and algorithms, ensuring a smooth and rollback-able upgrade process.

[0133] Operation and maintenance process management: Standardize operation and maintenance procedures to achieve closed-loop management of issues and knowledge accumulation. The processing flow includes the nodes of "submission - acceptance - processing - verification - closure", with the status of each node updated in real time and the entire processing record kept.

[0134] This platform has constructed a differentiated carbon emission baseline calculation model, which combines the historical emission method and the industry benchmark method to establish the baseline. The historical emission method is based on the building's own historical emission data and selects the average emission of a single year or multiple consecutive years as the benchmark. The industry benchmark method adopts the carbon emission intensity benchmark value of each type of public building, and at the same time provides the quartile data of the carbon emission intensity benchmark for each type.

[0135] Example 2, as Figure 2 As shown, a method for implementing a carbon emission monitoring and management platform for large public buildings is described. This method is implemented using the carbon emission monitoring and management platform for large public buildings described in Example 1, and specifically includes the following steps:

[0136] S1: Multi-source Data Acquisition and Preprocessing: Basic information on public buildings and energy consumption data (electricity, water, gas) are acquired through automated collection and manual entry. Raw data undergoes unit conversion, time format standardization, and field standardization preprocessing to ensure consistent measurement standards and comparability across different sources. Missing values, erroneous records, and outliers are screened and processed, specifically recording relevant parameters and error information to provide a basis for quality traceability and data correction. Potentially abnormal data is extracted separately and included in the review process. Source verification and manual comparison are used to ensure the data is authentic, accurate, and verifiable.

[0137] S2: Data Standardization and Structured Storage: After completing the collection, standardization, and quality verification of multi-source data, a unified database is constructed to achieve precise association, structured storage, and traceable management of building entities and energy consumption data, providing stable data support for carbon emission accounting and analysis. Specifically, the pre-processed multi-source heterogeneous data is converted into a unified data model on the platform. A unique code consisting of a 6-digit district / county administrative code and a 9-digit sequence code is used to precisely associate the data with building entities. The processed data is then stored in a structured building carbon emission database. The database adopts a cloud platform architecture and supports multi-source data integration, including but not limited to building basic information tables, energy consumption tables, carbon emission factor tables, and data log tables.

[0138] S3: Precise Carbon Emission Accounting: This involves setting accounting boundaries, using the emission factor method to calculate building carbon emissions and carbon emission intensity per unit area, and constructing differentiated carbon emission baselines by combining historical building data with industry standards. Setting accounting boundaries includes determining the reporting entity, organizational boundaries, operational boundaries, and base year. The operational boundaries must cover at least two categories: Scope 1 (direct emissions) and Scope 2 (indirect emissions). Scope 1 refers to carbon dioxide emissions from the combustion of fossil fuels at stationary combustion sources during the operation of public buildings, while Scope 2 refers to carbon dioxide emissions from production processes using purchased electricity, steam, heat, or cooling during the operation of public buildings.

[0139] S4: Multidimensional carbon emission analysis: Deeply mine and analyze carbon emission data from four dimensions: correlation, trend, composition, and attribution, and present the analysis results in a visual format.

[0140] S5: Carbon Emission Monitoring and Anomaly Alarm: Real-time monitoring of building carbon emission data, identification of data anomalies based on custom rules and tiered alarms, confirmation, handling and recording of alarm information throughout the process.

[0141] S6: Carbon Emission Management and Planning: Based on accounting and analysis results, establish a digital ledger for individual buildings to achieve refined management. Combine carbon quota data, policy requirements, and industry benchmarks to formulate building carbon reduction targets and planning schemes, realizing the quantification and value of emission reduction results. After the carbon reduction targets are set, the platform can track the gap between the actual carbon emissions of buildings and the carbon reduction targets in real time, quantitatively display the proportion of carbon emission range one and range two, generate carbon emission reports, and provide differentiated data support and application services for different entities such as government departments, building owners, and research institutions, realizing multi-party collaboration among government, industry, academia, and research.

[0142] S7: End-to-end security and operation and maintenance assurance: Implement security protection measures such as encryption and access control throughout the entire process of data collection, transmission, storage and application, and at the same time carry out operation and maintenance work such as data backup, version management and process control to ensure the stable and compliant operation of the platform.

[0143] Example 3, as Figure 3 and Figure 4 As shown, a carbon emission monitoring and management platform for large public buildings is presented. This embodiment demonstrates the application of the platform and its implementation method.

[0144] To address the needs of refined carbon emission management and multi-scenario applications during the operation of public buildings, the platform constructs a carbon emission implementation process covering all stages of public building operation, based on the "data-accounting-analysis-application" framework. This process, implemented in phases and modularly, provides a unified data foundation and technical support for subsequent applications such as monitoring and management of large public buildings, evaluation of large corporate office buildings, carbon assessment of building projects, and the establishment of carbon emission baselines. Specifically, it includes the following four phases:

[0145] Data acquisition phase: Collect basic information about the building and energy data such as electricity, water, and gas to form the basic data source for energy consumption during the building's operation phase.

[0146] Data governance phase: Unify, verify and correlate multi-source energy consumption data and building information, handle abnormal and missing data, and ensure data integrity and consistency.

[0147] Carbon emission accounting phase: Based on standardized carbon emission accounting methods, the carbon emissions corresponding to various energy consumptions during the building operation phase are calculated, and the carbon emission intensity is calculated in combination with the building area to form core carbon emission indicators.

[0148] Analysis and presentation phase: The current status, trends and benchmarking results of building carbon emissions are presented in a centralized manner through visualization, which intuitively reflects the building carbon emission level.

[0149] Application Scenario 1 – Carbon Emission Monitoring and Management of Large Public Buildings

[0150] Provincial and municipal video walls can display the distribution of various building samples in different cities, review historical carbon emissions, rank public building carbon emissions, analyze the composition of emission sources, compare regional emission intensity, and help to understand the carbon emission situation.

[0151] The carbon emission status module displays the carbon emissions, carbon emission intensity, and emission structure of public buildings from multiple dimensions, including building type, city distribution, and building scale, providing users with a comprehensive understanding of the overall carbon emission situation of buildings in the region.

[0152] The carbon emission management module allows for easy searching by entering the building number or name in the search box. It displays basic building information in a list format, including total carbon emissions, carbon emission intensity, and carbon emission baseline. It shows the building's emission level and ranking among similar buildings, and also allows users to view emission status from different dimensions such as building area and building type. Users can also adjust the factors corresponding to each energy source through carbon emission factor management.

[0153] The carbon emissions application module presents building rankings in tabular form, allowing users to query the carbon emission intensity levels of buildings in different cities. Through carbon emission characteristic analysis, it aims to dissect the distribution of different samples (such as different types of buildings, buildings in different regions, etc.) within carbon emission-related data. The building carbon emission correlation trend analysis explores the relationship between multiple factors and carbon emissions. By combining historical carbon emission data of individual buildings, a carbon emission reference baseline is calculated, providing benchmark values ​​for carbon emission intensity across different industries for comparison and evaluation.

[0154] Example 4, as Figure 5 As shown, a carbon emission monitoring and management platform for large public buildings is evaluated using a large enterprise office building as an example.

[0155] To promote energy consumption transparency and refined operation of office buildings, large enterprises have incorporated their office buildings into the large public building carbon emission monitoring and management platform. By accessing real-time data on electricity, water, and gas, the platform enables carbon inventory of enterprises and full-process monitoring of energy consumption, carbon emissions, carbon emission intensity, and energy use structure during the operation of pilot buildings.

[0156] With the support of the platform, large enterprises can view the carbon emission composition of the office buildings of their subsidiaries, the basic information of pilot buildings, the annual carbon emission change trend, and the sub-item energy consumption structure. They can also fully grasp the operating status through visual charts (carbon emission trend chart, intensity comparison chart, sub-item proportion chart, etc.), providing a data foundation for energy-saving diagnosis, budget management and operational performance evaluation.

[0157] This system enables multi-building carbon emission assessment within enterprises, supporting visualized carbon emission inventory and internal building operation evaluation for large enterprise office buildings. It provides year-on-year and month-on-month comparisons of energy consumption, carbon emissions, and historical data for different energy types and sub-items within individual buildings. It also assists in analyzing trends in energy use and carbon emissions across different sub-items, providing a basis for energy conservation and carbon reduction decisions.

[0158] Example 5, such as Figure 6 As shown, a carbon emission monitoring and management platform for large public buildings is presented, taking carbon assessment of building projects as an example.

[0159] To comprehensively understand the carbon emission levels of building projects during their operation, accurately identify high-emission stages and assess their carbon-saving potential, and meet the needs of refined supervision, energy conservation and carbon reduction analysis, and carbon asset management, it is necessary to conduct systematic carbon emission assessments of building projects. By analyzing the performance of building projects on key indicators such as annual carbon emissions, carbon emission intensity, baseline emission deviation, and quota gaps, ranking and comparing buildings, calculating benchmarks, generating reports, and calculating quotas, this provides a scientific basis for operational diagnosis of building projects and supports government departments in conducting regulatory evaluations and enterprises in implementing carbon asset management strategies.

[0160] By analyzing the carbon emissions of building projects, we can conduct overall rankings, benchmarking rankings of similar buildings, and rankings by regional distribution, thus constructing a multi-dimensional comparison of project carbon assessments to support the selection of key projects.

[0161] By automatically aggregating annual energy data from multiple sources such as electricity, water, and gas, the system calculates key indicators such as annual carbon emissions and carbon intensity in real time. It also generates evaluation reports by presenting the current status of building energy consumption, energy management, and energy-saving potential in graphical form.

[0162] By visually displaying key indicators such as annual baseline emissions, monthly baseline emissions, and planned reduction rates for buildings, the system presents the carbon emission baselines and reduction targets for buildings at different time scales, providing reliable data support for subsequent quota calculations and performance evaluations.

[0163] Based on the benchmark carbon emission level of buildings, it provides a visualization function of carbon quotas. By comparing the actual emissions of buildings with the estimated quotas, it presents the possible quota surplus or deficit in carbon trading, further assists in identifying compliance risks, and provides support for building projects to formulate quota management strategies.

[0164] Working Principle: The platform is designed with the core concepts of end-to-end data connectivity and full coverage of business scenarios. It constructs a complete technology stack from the bottom up, consisting of a data acquisition layer, infrastructure layer, core service layer, and carbon management application layer. Through a security management system and an operation and maintenance management system, it achieves full-process security protection and efficient operation and maintenance, realizing a closed-loop management of the entire chain of carbon emission data acquisition, transmission, processing, application, security, and operation and maintenance. Through the acquisition, cleaning, and standardized storage of multi-source data, a unified building carbon data foundation is formed. Carbon emission calculations are carried out through accounting boundaries and emission factor methods. Combining historical data, industry standards, and building characteristics, multiple types of baselines are constructed to support building energy conservation and carbon reduction analysis and management.

[0165] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered in all respects as exemplary and non-limiting, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the present invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

[0166] Furthermore, it should be understood that although this specification describes embodiments, not every embodiment contains only one independent technical solution. This narrative style is merely for clarity. Those skilled in the art should consider the specification as a whole, and the technical solutions in each embodiment can also be appropriately combined to form other embodiments that can be understood by those skilled in the art.

Claims

1. A carbon emission monitoring and management platform for large public buildings, comprising a monitoring and management platform, characterized in that: The monitoring and management platform includes a data acquisition layer, an infrastructure layer, a core service layer, a carbon management application layer, and a security management system and an operation and maintenance management system that run through all levels, connected sequentially from bottom to top. The data acquisition layer serves as the data supply base for the monitoring and management platform, connecting to external multi-source energy data systems and manual data entry terminals to achieve the original aggregation, preliminary management, and reliable transmission of energy consumption and basic data of public buildings. The infrastructure layer provides the monitoring and management platform with cloud-based computing, storage, and network resources to ensure the platform's efficient and stable operation. The core service layer serves as the business logic hub and data value transformation engine. It connects to the standardized data of the data acquisition layer to complete data governance and algorithm execution, and provides business function interfaces to the carbon management application layer. At the same time, it ensures the compliance and stability of the service through permission, algorithm, and storage management. The carbon management application layer is the business value terminal, providing users with full-process carbon management functions of "accounting-statistics-analysis-planning" of carbon emissions, and transforming the data analysis results of the core service layer into actionable and decision-making carbon management capabilities; The security management system and operation and maintenance management system ensure the platform's data security, stability, compliance, and efficient operation from the perspectives of security protection and full lifecycle operation.

2. The carbon emission monitoring and management platform for large public buildings according to claim 1, characterized in that: The data acquisition layer adopts a hybrid acquisition method of online automatic acquisition and offline collaborative data entry; The online automatic data collection is achieved by connecting to the information systems of energy companies, including those in the power, water, and gas sectors, via a RESTful API interface, supporting the reception of hourly energy consumption data by item. The offline collaborative reporting includes two forms: online reporting and report uploading. The monitoring and management platform has functions for format verification, logical verification, and consistency comparison of manually collected data in offline collaborative reporting. If the verification fails, the error reason will be displayed and the data can be corrected and resubmitted.

3. The carbon emission monitoring and management platform for large public buildings according to claim 1, characterized in that: The infrastructure layer encompasses network communication facilities, cloud infrastructure, and computing power infrastructure; The network communication facility undertakes the communication tasks between various architectural layers within the monitoring and management platform and between the monitoring and management platform and external data sources. The network communication facility integrates VPC virtual network and SLB server load balancing resources to ensure low latency, no loss, and no damage in data transmission. The cloud infrastructure includes a computing resource module, a storage resource module, and a service management module; The computing resource module is based on physical server virtualization to form a virtual machine, which supports elastic scaling of CPU and memory resources and automatically adjusts resource configuration according to changes in business load. The storage resource module adopts a hierarchical storage architecture: structured data is stored in the internal RDS for MySQL database, and table partitioning is used when the data volume is large; unstructured data is stored in OSS object storage service. The service management module provides full lifecycle resource management capabilities for cloud infrastructure. Through the cloud resource management platform, it enables automated deployment, monitoring, expansion, and operation and maintenance of virtual machines, servers, distributed storage, and cloud disks.

4. The carbon emission monitoring and management platform for large public buildings according to claim 1, characterized in that, The core functions of the core service layer include: Data governance: Cleaning, deduplication, completion, and verification of raw data; screening and marking missing values, erroneous records, and outliers; and incorporating outlier data into the review process. Data standardization: Built-in standard model for energy and carbon emission data of public buildings, which converts multi-source heterogeneous data into a unified format of the platform, makes data mapping relationships traceable, and supports unified maintenance of data dictionary; Algorithm execution: Run the core algorithms, including carbon emission accounting, statistics, analysis and baseline construction, and transform standardized data into a basis for business decisions; Access Control: A role-based access control model enables fine-grained management of users, roles, and permissions, ensuring compliance of data and function access; supports custom roles, with permission granularity refined to the region and building level; authentication supports username / password and two-factor authentication. Data lifecycle management: Enables data storage, archiving, cleaning, backup and recovery, with fault tolerance capabilities and 100% test case coverage.

5. The carbon emission monitoring and management platform for large public buildings according to claim 1, characterized in that: The carbon management application layer includes a carbon emission accounting module, a carbon emission statistics module, a carbon emission analysis module, a carbon emission alarm module, a single building module, and a carbon emission planning module. The carbon emission accounting module defines the accounting boundaries and uses the emission factor method to calculate carbon emissions and carbon emission intensity. The accounting boundaries include at least the reporting entity, organizational boundaries, operational boundaries, and base year. The operational boundaries cover direct emissions in scope one, indirect emissions in scope two, and extend to include other indirect emissions in scope three. The formula for calculating carbon emissions using the emission factor method is as follows: In the formula, i represents the year; j represents the type of energy; and k represents the number of buildings. Let K be the total carbon emissions of the k-th building in year i. Let J be the energy consumption of the k-th building in the i-th year for the j-th type of energy. Let be the emission factor for the j-th energy source; The formula for calculating carbon emission intensity is: In the formula, Let the carbon emission intensity of building k in year i be . Let k be the building area of ​​the kth building; The carbon emission accounting module has a built-in national, local, and enterprise-level three-level carbon emission factor library, and has the ability to expand new methodologies through configuration. The accounting dimensions cover buildings, energy types, equipment, and time, and support multi-dimensional combined accounting. The carbon emission analysis module, through multi-dimensional data mining and algorithm model application, analyzes the patterns, anomalies, and potential of carbon emissions, providing scientific and actionable quantitative support for carbon reduction decisions in public buildings. Specifically, it includes: Correlation analysis: to explore the degree of correlation between carbon emissions and external variables, including region, building type, scale, and commissioning time; Trend Analysis: Using time series analysis, we analyzed the trends in total carbon emissions and intensity of buildings over the past five years, identifying cyclical characteristics and peaks and troughs. Compositional analysis: Deconstructing the carbon emission structure from the dimensions of energy type, building area, and equipment type to identify core emission sources; Attribution analysis: By comparing with similar buildings and industry benchmarks, the emission differences are quantified and the current emission status is analyzed using root cause analysis. The results of the carbon emission analysis module are presented in visual formats including bar charts, pie charts, heat maps, and trend line charts. The carbon emission alarm module supports threshold alarms and equipment malfunction alarms, and the alarm rules, content, and levels can be customized. The alarm levels are divided into four levels: emergency, important, general, and alert. Different levels correspond to different notifications, handling priorities, and time limits. The carbon emission alarm module supports alarm confirmation and full traceability of handling records. The individual building module establishes a metadata digital ledger for each building, including building ID, name, address, and area. It collects hourly energy consumption data for each device and branch, and displays the carbon emission percentage and annual / monthly / daily trends of each item through visual charts, covering energy types including electricity, water, gas, and renewable energy. The carbon emission planning module is used to realize the whole process of emission reduction planning from "target setting - path optimization - task implementation - effect tracking". It analyzes the quota surplus based on building carbon quota data and cumulative carbon emissions, and formulates carbon reduction targets by combining policy requirements, industry benchmarks, historical building emission data and the feasibility of emission reduction measures. The carbon emission planning module displays the carbon emission intensity per unit building area, annual / monthly baseline emissions, and planned reduction rate. It accurately quantifies and displays the emission proportions of carbon emission range one and range two, supports the generation and download of carbon emission reports, restores the actual building structure, and realizes the linkage display of energy data and building models.

6. The carbon emission monitoring and management platform for large public buildings according to claim 1, characterized in that: The security management system adopts a four-dimensional protection strategy of "network-data-application-compliance", including network security protection, encryption of core network transmission, encrypted storage of sensitive data and user passwords, and fine-grained access control based on the RBAC model. The operation and maintenance management system adopts a four-dimensional management strategy of "monitoring-disaster recovery-version-process", including full data backup, data recovery by time point, version iteration and rollback of platform / service / algorithm, and standardized operation and maintenance process. The operation and maintenance process includes all nodes of "submission-acceptance-processing-verification-closure", with node status updated in real time and processing records left trace throughout the process.

7. The carbon emission monitoring and management platform for large public buildings according to claim 1, characterized in that: The monitoring and management platform has a differentiated carbon emission baseline calculation model, which combines historical emission methods and industry benchmark methods to establish the baseline. The historical emissions method is based on the building’s own historical emissions data, and selects the average emissions of a single year or multiple consecutive years as a benchmark. The industry benchmark method uses the carbon emission intensity benchmark values ​​for each type of public building, and also provides the quartile data of the carbon emission intensity benchmark for each type.

8. A method for implementing a carbon emission monitoring and management platform for large public buildings, comprising the carbon emission monitoring and management platform for large public buildings as described in any one of claims 1-7, characterized in that, The implementation method includes the following steps: S1: Multi-source data acquisition and preprocessing. Acquire basic information of public buildings and energy consumption data of electricity / water / gas through automatic collection and manual entry. Perform unit conversion, time format unification and field standardization preprocessing on the raw data. Screen and process missing values, erroneous records and out-of-format values. S2: Data standardization and structured storage transforms pre-processed multi-source heterogeneous data into a unified data model for the platform. The data is precisely associated with building entities through a unique code consisting of a 6-digit district / county administrative code and a 9-digit sequence code. The processed data is then stored in a building carbon emission database for structured storage. S3: Accurate carbon emission accounting, setting accounting boundaries, using the emission factor method to calculate building carbon emissions and carbon emission intensity per unit area, and combining historical building data with industry standards to build a differentiated carbon emission baseline; S4: Multi-dimensional carbon emission analysis, which deeply mines and analyzes carbon emission data from four dimensions: correlation, trend, composition and attribution, and presents the analysis results in a visual form; S5: Carbon emission monitoring and anomaly alarm, real-time monitoring of building carbon emission data, identification of data anomalies based on custom rules and graded alarms, confirmation, handling and recording of alarm information throughout the process; S6: Carbon emission management and planning. Based on accounting and analysis results, establish a digital ledger for individual buildings to achieve refined management. Combine carbon quota data, policy requirements and industry benchmarks to formulate building carbon reduction targets and planning schemes to realize the quantification and value of emission reduction results. S7: End-to-end security and operation and maintenance assurance. Encryption and access control security measures are implemented throughout the entire process of data collection, transmission, storage and application. At the same time, data backup, version management and process control are carried out to ensure the stable and compliant operation of the platform.

9. The implementation method according to claim 8, characterized in that: In S3, the setting of accounting boundaries includes determining the reporting subject, organizational boundaries, operational boundaries, and base year. The operational boundaries at least cover direct emissions in Scope 1 and indirect emissions in Scope 2. Scope 1 is the carbon dioxide emissions generated by the combustion of fossil fuels at stationary combustion sources during the operation of public buildings, and Scope 2 is the carbon dioxide emissions generated by production processes using purchased electricity, steam, heat, or cold during the operation of public buildings.

10. The implementation method according to claim 8, characterized in that: In S6, after the carbon reduction target is set, the monitoring and management platform tracks the gap between the actual carbon emissions of buildings and the carbon reduction target in real time, quantitatively displays the proportion of carbon emissions in range one and range two, generates a carbon emission report, and provides differentiated data support and application services for different entities, including government departments, building owners, and research institutions, to achieve multi-party collaboration among government, industry, academia, and research.

Images