Carbon emission evaluation method and device

Abstract

The application provides a carbon emission evaluation method and device, relates to the technical field of carbon emission, and comprises the following steps: collecting carbon emission basic data of an industrial enterprise in a pre-determined carbon emission accounting boundary and preprocessing the carbon emission basic data; the carbon emission basic data comprises energy consumption data, production process data and enterprise economic data; carbon emission accounting is performed based on the energy consumption data and the production process data, and carbon emission amount data is obtained; and the carbon emission level is comprehensively evaluated according to the energy consumption data, the production process data, the enterprise economic data and the carbon emission amount data, so that carbon emission evaluation results are obtained. The carbon emission evaluation method and device provided by the application realize comprehensive quantitative evaluation of the carbon emission level and efficiency of an industrial enterprise, and provide a scientific basis for low-carbon operation and optimization decision of the enterprise.

Description

Technical Field

[0001] This application relates to the field of carbon emission technology, and in particular to a carbon emission assessment method and apparatus. Background Technology

[0002] Against the backdrop of increasingly severe climate change issues, reducing greenhouse gas emissions and promoting the low-carbon transformation of the economy and society have become a general consensus. As an important basic industry of the economy, the steel industry has high energy consumption and complex processes in its production, making it one of the industrial sectors with the highest concentration of carbon emissions. Relevant statistics show that the steel industry accounts for a large proportion of carbon emissions in the manufacturing sector, and its pressure to reduce carbon emissions is particularly prominent.

[0003] Steel production typically involves multiple processes, including coking, sintering, ironmaking, steelmaking, and rolling, which consume large amounts of fossil fuels and involve complex physicochemical reactions. Different process paths, equipment operating conditions, and production load conditions can all significantly impact carbon emission levels. Furthermore, steel companies produce carbon-containing byproducts and carbon sequestration during production, resulting in a coexistence of emissions and carbon sequestration, further increasing the complexity of carbon emission accounting and assessment.

[0004] With increasingly stringent environmental standards, a gradually improving carbon trading mechanism, and increased attention from downstream markets to green products, steel companies not only need to accurately grasp their own carbon emission levels, but also urgently need to establish a scientific and reasonable carbon emission assessment system to support their refined management and low-carbon transformation decisions. However, existing carbon management and assessment technologies for steel companies still have many shortcomings.

[0005] In existing technologies, one type of approach focuses on calculating and statistically analyzing carbon emissions based on product batches or process levels, providing data support for product certification or production management by generating carbon footprint reports or process carbon emission indicators. However, this type of method is usually based on static production data and cannot fully reflect the impact of dynamic factors such as changes in equipment operating status and fluctuations in process parameters on carbon emissions, resulting in limited depth of analysis into the causes of carbon emission fluctuations.

[0006] Another approach involves constructing carbon flow models or predictive models based on historical data to predict and manage carbon emissions during the steel manufacturing process. While this method simplifies the carbon emission calculation process to some extent, it relies heavily on historical data. When production processes are adjusted, new equipment is put into operation, or unexpected production anomalies occur, the model's adaptability and predictive accuracy are insufficient, making it difficult to respond promptly to changes in the company's actual operations.

[0007] Some technical solutions target the entire enterprise, collecting energy consumption data and calculating carbon emissions, and evaluating the enterprise's carbon emission level through indicators such as total carbon emissions, intensity, or level. While these methods can achieve enterprise-level carbon emission monitoring and horizontal benchmarking, they mostly remain at the level of result statistics and indicator display, lacking in-depth diagnosis of abnormal carbon emissions or low efficiency, and have not yet formed an effective "monitoring-analysis-optimization" closed loop.

[0008] In addition, there are carbon emission assessment methods for industrial parks, integrated energy stations, transportation projects or specific industry scenarios. These methods improve the accuracy of assessment by introducing predictive models, weighted evaluation or full life cycle analysis. However, their application targets, evaluation boundaries or technical focus are significantly different from those of high-energy-consuming industrial enterprises such as steel, making it difficult to directly adapt to the complex scenarios of steel enterprises with multiple processes, multiple energy sources and multiple economic indicators.

[0009] In summary, existing carbon emission technologies for steel enterprises still have shortcomings in terms of real-time data acquisition, precision of accounting models, dynamic adaptability, and completeness of evaluation dimensions. They are still insufficient to achieve a comprehensive and systematic evaluation of the carbon emission status of steel enterprises under different energy structures, production conditions, and economic output levels.

[0010] This section is intended to provide background or context for the embodiments of the invention set forth in the claims. The description herein is not an admission that it is prior art simply because it is included in this section. Summary of the Invention

[0011] To address the problems in the prior art, this application provides a carbon emission evaluation method and apparatus, which can solve the problem that existing industrial enterprise carbon management schemes are unable to conduct correlation analysis between energy consumption, economic output and carbon emissions, and are unable to conduct comprehensive and refined evaluation of carbon emission efficiency under different production and economic conditions.

[0012] One aspect of the present invention provides a carbon emission assessment method, the method comprising:

[0013] Within a predetermined carbon emission accounting boundary, basic carbon emission data of industrial enterprises are collected and preprocessed; the basic carbon emission data includes energy consumption data, production process data, and enterprise economic data.

[0014] Carbon emission calculations are performed based on the energy consumption data and the production process data to obtain carbon emission data.

[0015] The carbon emission level is comprehensively evaluated based on the energy consumption data, production process data, enterprise economic data, and carbon emission data to obtain the carbon emission evaluation result.

[0016] Furthermore, the preprocessing of the carbon emission baseline data includes:

[0017] The carbon emission baseline data is cleaned to identify and remove outliers;

[0018] Missing values ​​were filled in the cleaned carbon emission baseline data.

[0019] The carbon emission baseline data after missing values ​​were filled was standardized.

[0020] Furthermore, the carbon emission calculation based on the energy consumption data and the production process data to obtain carbon emission data includes:

[0021] The corresponding carbon emission factor is determined based on the energy consumption data and the production process data.

[0022] Carbon emission data is obtained by using the energy consumption data, the production process data, and the carbon emission factor.

[0023] Furthermore, the comprehensive evaluation of carbon emission levels based on the energy consumption data, the production process data, the enterprise economic data, and the carbon emission data includes:

[0024] Based on the energy consumption data, the production process data, the enterprise economic data, and the carbon emission data, a log-mean Dijkstra exponential decomposition model is constructed to characterize changes in carbon emissions.

[0025] The impact of each factor on carbon emission changes was calculated using the log-mean Dijkstra index decomposition model.

[0026] Identify the causes of abnormal carbon emissions based on the degree of influence of each of the aforementioned factors on changes in carbon emissions.

[0027] Furthermore, the comprehensive evaluation of carbon emission levels also includes:

[0028] Based on the carbon emission data and the enterprise economic data, an evaluation index system is constructed from both the cost and benefit sides of carbon emissions.

[0029] The carbon emission economic efficiency index is calculated based on the evaluation index system.

[0030] Furthermore, it also includes:

[0031] Based on the carbon emission data and the carbon emission assessment results, the historical data stored in the carbon data warehouse is analyzed and processed to assess the carbon emission reduction potential of the industrial enterprise.

[0032] Carbon reduction strategies are generated based on the assessment results of carbon reduction potential.

[0033] In another aspect, the present invention provides a carbon emission assessment device, the device comprising:

[0034] The data acquisition unit is used to collect basic carbon emission data of industrial enterprises within a predetermined carbon emission accounting boundary and to preprocess the basic carbon emission data; the basic carbon emission data includes energy consumption data, production process data and enterprise economic data.

[0035] A carbon emission accounting unit is used to perform carbon emission accounting based on the energy consumption data and the production process data to obtain carbon emission data.

[0036] The carbon emission assessment unit is used to comprehensively evaluate the carbon emission level based on the energy consumption data, the production process data, the enterprise economic data, and the carbon emission data, and obtain the carbon emission assessment result.

[0037] Furthermore, the data acquisition unit includes:

[0038] The data cleaning module is used to clean the carbon emission baseline data, identify and remove outliers;

[0039] The missing value imputation module is used to impute missing values ​​in the cleaned carbon emission baseline data.

[0040] The standardization module is used to standardize the basic carbon emission data after missing values ​​have been filled in.

[0041] Furthermore, the carbon emission accounting unit includes:

[0042] A carbon emission factor determination module is used to determine the corresponding carbon emission factor based on the energy consumption data and the production process data.

[0043] The carbon emission accounting module is used to perform carbon emission accounting using the energy consumption data, the production process data, and the carbon emission factors to obtain carbon emission data.

[0044] Furthermore, the carbon emission assessment unit includes:

[0045] The model building module is used to build a log-mean Dijkstra exponential decomposition model to characterize changes in carbon emissions based on the energy consumption data, the production process data, the enterprise economic data, and the carbon emission data.

[0046] The factor impact calculation module is used to calculate the degree of influence of each factor on carbon emission changes using the log-mean Dijkstra index decomposition model.

[0047] The anomaly cause identification module is used to identify the causes of carbon emission anomalies based on the degree of influence of each factor on carbon emission changes.

[0048] Furthermore, the carbon emission assessment unit also includes:

[0049] The evaluation index system construction module is used to construct an evaluation index system from the carbon emission cost side and the benefit side based on the carbon emission data and the enterprise economic data.

[0050] The economic efficiency index calculation module is used to calculate the carbon emission economic efficiency index based on the evaluation index system.

[0051] Furthermore, it also includes:

[0052] A carbon emission reduction potential assessment unit is used to analyze and process historical data stored in a carbon data warehouse based on the carbon emission data and the carbon emission assessment results, and to assess the carbon emission reduction potential of the industrial enterprise.

[0053] The carbon emission reduction strategy generation unit is used to generate carbon emission reduction strategies based on the carbon emission reduction potential assessment results.

[0054] To achieve the above objectives, according to another aspect of the present invention, a computer device is also provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the carbon emission assessment method described above.

[0055] To achieve the above objectives, according to another aspect of the present invention, a computer-readable storage medium is also provided, on which a computer program / instructions are stored, which, when executed by a processor, implement the steps of the carbon emission assessment method described above.

[0056] To achieve the above objectives, according to another aspect of the present invention, a computer program product is also provided, comprising a computer program / instructions that, when executed by a processor, implement the steps of the carbon emission assessment method described above.

[0057] The beneficial effects of this invention are as follows:

[0058] This invention constructs a multi-source data acquisition system covering the entire steel production process. Utilizing the Internet of Things, sensors, and hybrid communication technologies, it collects carbon emission-related data in real time, including energy consumption, production processes, and corporate economics, and stores and manages this data uniformly on a cloud computing platform. By cleaning, standardizing, and monitoring the collected data, the consistency, integrity, and accuracy of the carbon data are ensured, providing a stable and reliable data foundation for subsequent carbon emission accounting, evaluation, and decision-making.

[0059] This invention constructs a carbon emission accounting model and introduces a dynamic correction mechanism. By combining real-time collected energy consumption data, production process data, and environmental data, the model parameters and emission factors are dynamically adjusted so that the carbon emission accounting results can reflect changes in the enterprise's production status in a timely manner, avoiding deviations caused by static accounting methods, thereby achieving more accurate carbon emission accounting that is closer to the actual production process.

[0060] This invention constructs a carbon emission economic evaluation index system from both cost and benefit perspectives, correlating corporate carbon emissions with corporate economic performance. This not only reflects the level of corporate carbon emissions but also assesses the economic rationality of carbon emission behavior. Furthermore, when a company's current carbon emissions are inconsistent with its historical economic development and carbon emission levels, or when there is excessive emissions, a diagnostic model of influencing factors is introduced to quantify the impact of factors such as economic development, energy structure, and energy efficiency on changes in carbon emissions. This accurately identifies the causes of excessive emissions, providing a clear basis for carbon management decisions.

[0061] Based on carbon emission accounting results and carbon emission assessment and diagnosis results, combined with historical data and external environmental data, this invention quantifies the carbon emission reduction potential of enterprises from multiple dimensions, such as improving energy efficiency, optimizing production processes, upgrading and transforming equipment, and recycling waste resources. It clarifies the emission reduction space and key directions of enterprises under existing technological conditions and resource constraints, and avoids blind or experience-based emission reduction decisions.

[0062] This invention utilizes big data analysis and multi-objective optimization algorithms to comprehensively evaluate the emission reduction effects, cost inputs, and technical feasibility of different carbon emission reduction measures. It then formulates short-term, medium-term, and long-term carbon emission reduction strategies that are suitable for the actual situation of enterprises, thereby achieving carbon emission reduction targets while taking into account the production stability and economic benefits of enterprises, and improving the feasibility and overall effectiveness of carbon emission reduction plans.

[0063] This invention establishes a carbon emission reduction strategy implementation monitoring and evaluation mechanism to continuously track the effectiveness of the emission reduction strategy, and optimizes and adjusts the carbon emission reduction strategy according to market changes, regulatory adjustments, and dynamic changes in enterprise production status, so as to ensure that carbon emission reduction targets can be achieved continuously and stably, while effectively controlling the emission reduction costs of enterprises and improving their environmental benefits and long-term competitiveness. Attached Figure Description

[0064] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. In the drawings:

[0065] Figure 1 This is a schematic diagram of the first process of the carbon emission assessment method provided in the embodiments of the present invention;

[0066] Figure 2 This is a schematic diagram of the second process of the carbon emission assessment method provided in the embodiments of the present invention;

[0067] Figure 3 This is a schematic diagram of the third process of the carbon emission assessment method provided in the embodiments of the present invention;

[0068] Figure 4 This is a schematic diagram of the fourth process of the carbon emission assessment method provided in the embodiments of the present invention;

[0069] Figure 5 This is a schematic diagram of the fifth process of the carbon emission assessment method provided in the embodiments of the present invention;

[0070] Figure 6 This is a schematic diagram of the sixth process of the carbon emission assessment method provided in the embodiments of the present invention;

[0071] Figure 7 This is a first structural schematic block diagram of the carbon emission assessment device provided in the embodiments of the present invention;

[0072] Figure 8 This is a schematic block diagram of the second structure of the carbon emission assessment device provided in the embodiments of the present invention;

[0073] Figure 9 This is a schematic block diagram of the third structure of the carbon emission assessment device provided in the embodiments of the present invention;

[0074] Figure 10 This is a schematic block diagram of the fourth structure of the carbon emission assessment device provided in the embodiments of the present invention;

[0075] Figure 11 This is a fifth structural schematic block diagram of the carbon emission assessment device provided in the embodiments of the present invention;

[0076] Figure 12 This is a sixth structural schematic block diagram of the carbon emission assessment device provided in the embodiments of the present invention;

[0077] Figure 13 This is a schematic diagram of the structure of the computer device provided in an embodiment of the present invention;

[0078] Figure 14 This is a schematic diagram of the "energy-economy-environment" carbon emission assessment process provided in the embodiments of the present invention. Detailed Implementation

[0079] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. 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 should fall within the scope of protection of the present invention.

[0080] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0081] It should be noted that the terms "comprising" and "having" and any variations thereof in the specification, claims and accompanying drawings of this invention are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are explicitly listed, but may include other steps or units that are not explicitly listed or that are inherent to such processes, methods, products or devices.

[0082] It should be noted that, unless otherwise specified, the embodiments and features described in the present invention can be combined with each other. The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0083] This invention, based on an energy-economy-environment synergy system, provides a system and method for carbon accounting and carbon emission assessment of steel products. By constructing a technical solution encompassing data acquisition and management, carbon emission accounting, carbon emission assessment and diagnosis, and carbon reduction strategy formulation, it enables real-time monitoring and accurate evaluation of carbon emissions from steel enterprises. This provides data support and decision-making basis for enterprises to formulate scientific and reasonable carbon reduction strategies, helping steel enterprises reduce production costs and enhance their overall competitiveness while meeting environmental standards, thus promoting green, low-carbon, and sustainable development.

[0084] The following describes the specific implementation process of the carbon emission assessment method provided in this application embodiment, using a server as the execution subject as an example.

[0085] Figure 1 This is a schematic diagram of the first process of the carbon emission assessment method provided in this embodiment of the invention, as shown below. Figure 1 As shown, in one embodiment of the present invention, the carbon emission assessment method of the present invention includes:

[0086] S101: Collect basic carbon emission data of industrial enterprises within a predetermined carbon emission accounting boundary and preprocess the basic carbon emission data; the basic carbon emission data includes energy consumption data, production process data and enterprise economic data.

[0087] S102: Based on the energy consumption data and the production process data, carbon emission calculation is performed to obtain carbon emission data;

[0088] S103: Based on the energy consumption data, the production process data, the enterprise economic data, and the carbon emission data, a comprehensive evaluation of the carbon emission level is conducted to obtain the carbon emission evaluation result.

[0089] from Figure 1 As shown in the flowchart, the carbon emission assessment method provided in this application collects basic carbon emission data of industrial enterprises within a pre-determined carbon emission accounting boundary and preprocesses the basic carbon emission data. The basic carbon emission data includes energy consumption data, production process data, and enterprise economic data. Carbon emission accounting is performed based on the energy consumption data and the production process data to obtain carbon emission data. The carbon emission level is comprehensively evaluated based on the energy consumption data, the production process data, the enterprise economic data, and the carbon emission data to obtain the carbon emission assessment result. This method achieves a comprehensive quantitative evaluation of the carbon emission level and efficiency of industrial enterprises, providing a scientific basis for enterprises' low-carbon operation and optimization decisions.

[0090] Each step is explained in detail below.

[0091] S101: Collect basic carbon emission data of industrial enterprises within a predetermined carbon emission accounting boundary and preprocess the basic carbon emission data; the basic carbon emission data includes energy consumption data, production process data and enterprise economic data.

[0092] Specifically, the server first collects basic carbon emission data from industrial enterprises within a pre-defined carbon emission accounting boundary and then preprocesses this data. The carbon emission accounting boundary is used to define the scope of production activities and energy use of enterprises participating in the carbon emission assessment, ensuring the accuracy and consistency of subsequent carbon emission accounting and assessment results.

[0093] Basic carbon emission data includes energy consumption data, production process data, and enterprise economic data. Energy consumption data reflects the use of various types of energy by enterprises during production and operation; production process data characterizes the technological conditions, production status, and operational characteristics of the enterprise's production process; and enterprise economic data reflects the enterprise's economic performance and cost-benefit situation. By collecting this multi-dimensional data, a comprehensive picture of the basic information related to carbon emissions from industrial enterprises can be drawn.

[0094] After data collection, the basic carbon emission data is preprocessed to improve data quality and eliminate the impact of data noise on subsequent analysis. Preprocessing ensures that raw data from different sources and in different formats have a unified analytical basis, providing reliable data support for carbon emission accounting and assessment.

[0095] Figure 2 This is a schematic diagram of the second process of the carbon emission assessment method provided in the embodiments of the present invention, as shown below. Figure 2 As shown, in one embodiment of the present invention, S101 includes:

[0096] S201: Perform data cleaning on the aforementioned carbon emission baseline data, identify and remove outliers;

[0097] Specifically, the server first performs data cleaning on the basic carbon emission data to improve the accuracy and reliability of the data.

[0098] Because carbon emission baseline data comes from diverse sources, including energy metering equipment, production equipment monitoring systems, and enterprise management systems, outliers or erroneous data may occur during data collection and transmission due to equipment malfunctions, communication abnormalities, or human error. Therefore, a data cleaning process is used to identify and remove outliers from the carbon emission baseline data.

[0099] In one embodiment, by setting reasonable data value ranges, change thresholds, and statistical distribution characteristics, data that deviates significantly from the normal range can be identified, thereby removing abnormal data that may interfere with subsequent analysis and ensuring that the data used in carbon emission accounting and evaluation has basic credibility.

[0100] S202: Fill in missing values ​​in the cleaned carbon emission baseline data;

[0101] Specifically, after the server completes data cleaning, it fills in missing values ​​in the cleaned carbon emission baseline data.

[0102] In the actual operating environment of industrial enterprises, some data may be missing due to sensor maintenance, system upgrades, or network outages. Ignoring missing data directly could result in incomplete data samples, affecting the continuity and accuracy of carbon emission accounting and assessment results.

[0103] Therefore, in this invention, missing data is appropriately filled in. By analyzing the time series characteristics and correlations of existing data, reasonable values ​​for missing data are calculated, ensuring the continuity and consistency of the data in terms of time dimension and logical relationship. This guarantees the integrity of basic carbon emission data and provides a continuous data foundation for subsequent analysis.

[0104] S203: Standardize the basic carbon emission data after filling in missing values.

[0105] Specifically, after filling in the missing values, the server performs standardization processing on the basic carbon emission data.

[0106] Because carbon emission baseline data includes various types of data, these different data differ significantly in dimensions, orders of magnitude, and forms of representation. For example, energy consumption data, production process data, and enterprise economic data have different units of measurement and value ranges. Directly integrating and analyzing these data can easily compromise the objectivity of the results due to inconsistencies in dimensions.

[0107] Therefore, data standardization transforms different types of data into a unified representation, making them comparable. Standardized carbon emission baseline data effectively eliminates the impact of dimensional differences on analysis results, providing unified and standardized data input conditions for subsequent carbon emission accounting and evaluation.

[0108] In one embodiment, the server adopts a multi-source data acquisition system to collect, transmit, preprocess, and centrally manage carbon emission-related data throughout the entire steel production process. This covers the entire steel production process, including raw material procurement, transportation, storage, smelting, processing, and product sales. By deploying sensors and smart devices at each stage, comprehensive collection of carbon emission-related information is achieved.

[0109] Install smart meters, gas meters, and water meters on energy supply equipment to collect real-time data on energy consumption such as electricity, natural gas, and water.

[0110] Production equipment, including but not limited to blast furnaces, converters, electric furnaces, and rolling mills, is equipped with temperature sensors, pressure sensors, flow sensors, and vibration sensors to acquire operating status parameters such as temperature, pressure, material flow rate, and equipment vibration. These operating status parameters are closely related to production process conditions and energy consumption, and can reflect equipment operating efficiency and potential changes in carbon emissions.

[0111] Weight sensors and humidity sensors are installed in the raw material storage area to monitor the inventory quantity and humidity information of raw materials. Factors such as the humidity of raw materials will affect their energy consumption and carbon emission levels in the subsequent production process.

[0112] In the transportation process, by deploying onboard GPS devices and related sensors on transport vehicles, data such as the vehicle's route, speed, and load are collected. This data is used to reflect the energy consumption and corresponding carbon emissions during transportation.

[0113] Through the collaborative collection of the above-mentioned multi-source data, it is possible to obtain a comprehensive and accurate range of basic data related to carbon emissions from steel production.

[0114] In one embodiment, in addition to production process-related data, the server collects enterprise economic data, including raw material costs, processing costs, transportation costs, product sales, enterprise turnover, process improvement costs, and equipment upgrade costs, to reflect the enterprise's economic operation and the economic impact related to carbon emissions.

[0115] Meanwhile, based on real-time changes in the carbon market, carbon market trading prices and carbon tax standards are dynamically updated; and energy prices are updated according to a preset cycle, distinguishing between high-carbon and low-carbon energy sources to ensure the timeliness and accuracy of economic data and price parameters.

[0116] In one embodiment, during the data transmission phase, a combination of wireless and wired communication technologies is used to transmit the data collected by the sensors to the data processing center in real time. The wireless communication technologies include, but are not limited to, 5G and LoRa, while the wired communication technologies include Industrial Ethernet. During data transmission, data encryption technologies and redundant transmission mechanisms are employed to ensure the security and integrity of the data during transmission, preventing data theft or loss.

[0117] In one embodiment, the carbon emission baseline data is preprocessed, specifically including:

[0118] First, data cleaning is performed, using statistical methods and machine learning algorithms to identify and remove outliers and erroneous data. For example, outlier data points can be detected by setting reasonable data value ranges and change thresholds, or outlier data that deviates significantly from other data can be identified by clustering algorithms.

[0119] Subsequently, missing data was filled in using a deep learning-based interpolation algorithm. Based on the time series characteristics of the data and the correlation between data, the missing data was predicted and filled in.

[0120] After imputing missing values, the data is standardized to convert data of different types and dimensions into a unified data format and standard for subsequent analysis and processing.

[0121] In one embodiment, the server builds a cloud-based distributed data management platform, employing big data processing frameworks such as Hadoop and Spark to achieve efficient storage and management of massive amounts of carbon emission-related data. A distributed file system is used to store raw and processed data to ensure data storage reliability and scalability; a NoSQL database is used to store unstructured and semi-structured data, including equipment operation logs and documents; and a relational database is used to store structured data, including production process parameters and carbon emission accounting results.

[0122] Data integration technology is used to consolidate data from different data sources and in different formats into a unified data management platform, forming a complete carbon data warehouse. Simultaneously, a data quality management system is established to monitor and evaluate the accuracy, completeness, and consistency of the data in real time, promptly identifying and addressing data quality issues.

[0123] S102: Based on the energy consumption data and the production process data, carbon emission calculation is performed to obtain carbon emission data;

[0124] Specifically, after completing the collection and preprocessing of basic carbon emission data, the server calculates the carbon emission status of industrial enterprises based on energy consumption data and production process data to obtain carbon emission data.

[0125] Energy consumption data reflects the scale and structure of consumption of different energy sources, while production process data reflects the process characteristics and operating status that may cause changes in carbon emissions during production. By comprehensively considering energy consumption and production process characteristics, a more accurate reflection of the carbon emission levels of industrial enterprises during actual production operations can be achieved.

[0126] Carbon emission accounting yields carbon emission data that characterizes a company's total carbon emissions and their composition over a specific evaluation period. This data serves as a crucial input for subsequent carbon emission assessments, providing a quantitative basis for analyzing a company's carbon emission levels and their changes.

[0127] Figure 3 This is a schematic diagram of the third process of the carbon emission assessment method provided in this embodiment of the invention, as shown below. Figure 3 As shown, in one embodiment of the present invention, S102 includes:

[0128] S301: Determine the corresponding carbon emission factor based on the energy consumption data and the production process data;

[0129] Specifically, before performing carbon emission accounting, the server first determines the carbon emission factor that matches the actual production situation of the enterprise based on energy consumption data and production process data.

[0130] Energy consumption data is used to characterize the consumption of different energy sources by industrial enterprises during the evaluation period, while production process data reflects the technological routes, operating conditions, and production status adopted during production. Because carbon emission characteristics differ under different energy types and production process conditions, a single, fixed carbon emission factor is insufficient to accurately reflect actual carbon emissions.

[0131] Therefore, by combining energy consumption data with production process data, the selection and matching of carbon emission factors are adjusted to ensure that the determined carbon emission factors more accurately reflect the carbon emission characteristics of enterprises under current production conditions. Carbon emission factors can be used to characterize the carbon emission level corresponding to a unit of energy consumption or a unit of production activity, providing basic parameters for subsequent carbon emission calculations.

[0132] S302: Calculate carbon emissions using the energy consumption data, the production process data, and the carbon emission factor to obtain carbon emission data.

[0133] Specifically, after determining the carbon emission factor, the server uses energy consumption data, production process data, and the carbon emission factor to calculate the carbon emissions of industrial enterprises in order to obtain carbon emission data.

[0134] In the carbon emission accounting process, energy consumption data is correlated with corresponding carbon emission factors, and production process data is used to correct the carbon emission results, thereby obtaining carbon emission data that reflects the actual production and operation status of the enterprise. This accounting process quantifies the carbon emission level of industrial enterprises during the evaluation period, providing reliable data input for subsequent carbon emission assessments.

[0135] By following the steps above, the carbon emission data of industrial enterprises can be obtained, enabling the carbon emission accounting results to take into account both energy use and production process characteristics, thereby improving the accuracy and applicability of the carbon emission calculation results.

[0136] In one embodiment, the server calculates the carbon emissions during the steel production process based on the acquired basic data on carbon emissions, and improves the accuracy and timeliness of the calculation results through a dynamic correction mechanism. A refined carbon emission calculation model is constructed for different stages and carbon emission sources in the steel production process. Carbon emissions are calculated using formulas (1) to (2):

[0137] E = AD × EF (1)

[0138] E CO2 =E燃烧 +E 过程 +E 购入电 +E 购入热 -E 固碳 -E 输出电 -E 输出热 (2)

[0139] In the formula: AD represents the amount of production or consumption activities that lead to greenhouse gas emissions, such as the consumption of each type of fossil fuel, the consumption of limestone raw materials, net purchased electricity, net purchased steam, etc.; EF represents the emission factor corresponding to the activity level data; E CO2 E represents total carbon dioxide emissions, expressed in tons of carbon dioxide (tCO2). 燃烧 E represents emissions from fuel combustion, expressed in tons of carbon dioxide (tCO2). 过程 E represents process emissions, expressed in tons of carbon dioxide (tCO2). 购入电 E represents the emissions corresponding to purchased electricity consumption, expressed in tons of carbon dioxide (tCO2). 购入热 E represents the emissions corresponding to the purchased heat consumption, expressed in tons of carbon dioxide (tCO2). 固碳 E represents the emissions of a company's carbon sequestration products, expressed in tons of carbon dioxide (tCO2). 输出电 E represents the emissions corresponding to the output electricity consumption, expressed in tons of carbon dioxide (tCO2). 输出热 This indicates the emissions corresponding to the output heat consumption, expressed in tons of carbon dioxide (tCO2).

[0140] In one embodiment, when performing carbon emission accounting, a differentiated emission factor acquisition method is adopted according to different types of emission sources.

[0141] For emissions sources that are fuels, raw materials, products, or by-products, emission factors can be obtained in one of the following ways: using the default emission factors published by the official competent authority; using emission factors obtained by entrusting a professional testing agency to conduct periodic testing in accordance with the relevant standards; or using the valid test values ​​provided in the settlement vouchers of the relevant parties.

[0142] For the emission factors of purchased electricity, the emission factors of the corresponding regional power grid published by the relevant official authorities in the most recent year shall be selected based on the power grid area to which the enterprise's production location belongs.

[0143] For the emission factors of purchased heat, the latest official emission factor data released by the competent authority shall be used.

[0144] By employing the above methods, we can ensure that the emission factors used are authoritative, traceable, and timely.

[0145] In one embodiment, different accounting considerations are used for carbon emissions from different sources during the carbon emission accounting process.

[0146] Carbon emissions from fuel combustion are considered comprehensively, taking into account the type of fuel, fuel composition, and relevant parameters of the combustion process. Fuel types include, but are not limited to, coke, pulverized coal, and natural gas; fuel composition includes carbon content and hydrogen content; and relevant parameters of the combustion process include combustion efficiency and actual combustion conditions.

[0147] For carbon emissions in industrial production processes, such as the chemical reactions occurring in iron ore smelting and steelmaking, factors such as raw material composition, reaction conditions, and reaction conversion rates are comprehensively considered. Reaction conditions include parameters such as temperature, pressure, and catalysts, and corresponding material balance and energy balance models are established to improve the accuracy of the calculation results.

[0148] For indirect carbon emissions from electricity and heat consumption, calculations are made based on the regional power grid emission factor and heat supply emission coefficient, combined with the actual electricity and heat consumption of enterprises, and the impact of changes in power grid structure and heat supply methods on emission factors is considered in the accounting process.

[0149] In one embodiment, a dynamic correction mechanism is introduced to reflect the changes in carbon emissions during the steel production process in real time.

[0150] During the dynamic correction process, parameters in the carbon emission accounting model are dynamically adjusted using real-time collected production process data, energy consumption data, and environmental data. For example, when changes in the operating status of production equipment lead to changes in energy consumption efficiency, the conversion coefficient between energy consumption and carbon emissions is adjusted accordingly; when factors such as ambient temperature and humidity affect fuel combustion efficiency, the combustion efficiency parameters are corrected.

[0151] At the same time, the carbon emission accounting model is adaptively adjusted based on the company's production plan adjustment information and equipment maintenance status, so that the accounting model can be consistent with the company's actual production and operation status.

[0152] By introducing the aforementioned dynamic correction mechanism, we can ensure that carbon emission accounting results can reflect changes in the production process in a timely manner, thereby improving the accuracy and timeliness of carbon emission accounting results.

[0153] S103: Based on the energy consumption data, the production process data, the enterprise economic data, and the carbon emission data, a comprehensive evaluation of the carbon emission level is conducted to obtain the carbon emission evaluation result.

[0154] Specifically, after obtaining carbon emission data, the server comprehensively evaluates the carbon emission level of industrial enterprises based on energy consumption data, production process data, enterprise economic data, and carbon emission data, and obtains carbon emission evaluation results.

[0155] In the comprehensive evaluation process, correlation analysis is conducted between the enterprise's energy use, production operation characteristics, economic operation level, and carbon emission data to reflect the intrinsic relationship between carbon emissions and the enterprise's production and operation activities. Through comprehensive analysis of multi-dimensional data, it is possible not only to evaluate the enterprise's current carbon emission level, but also to reflect the synergy between changes in carbon emissions and energy utilization, production processes, and economic operation.

[0156] Ultimately, this results in carbon emission assessments that characterize the carbon emission levels of industrial enterprises. These assessments can be used for enterprise carbon emission management, benchmarking analysis, and subsequent decision support, providing a basis for industrial enterprises to achieve low-carbon development.

[0157] Figure 4 This is a schematic diagram of the fourth process of the carbon emission assessment method provided in this embodiment of the invention, as shown below. Figure 4 As shown, in one embodiment of the present invention, S103 includes:

[0158] S401: Construct a log-mean Dijkstra exponential decomposition model to characterize changes in carbon emissions based on the energy consumption data, the production process data, the enterprise economic data, and the carbon emission data.

[0159] Specifically, the server constructs a Logarithmic Mean Divisia Index (LMDI) decomposition model to characterize changes in carbon emissions, based on energy consumption data, production process data, enterprise economic data, and carbon emission data.

[0160] Energy consumption data reflects the scale and structural characteristics of an enterprise's energy use; production process data characterizes the impact of process conditions and operating status on carbon emissions during production; enterprise economic data reflects the enterprise's economic output and cost input; and carbon emission data characterizes the enterprise's carbon emission level during the evaluation period. By incorporating the above multi-source data into the log-mean Dijkstra index decomposition model, the model can characterize the intrinsic driving factors of carbon emission changes from multiple dimensions.

[0161] By constructing a log-mean Dijkstra index decomposition model, the change in carbon emissions can be decomposed into several influencing factors with clear physical and economic meanings, providing a unified analytical framework for subsequent carbon emission change analysis.

[0162] S402: Calculate the degree of influence of each factor on the change in carbon emissions using the log-mean Dijkstra index decomposition model described above;

[0163] Specifically, the server uses a log-mean Dijkstra index decomposition model to decompose and calculate changes in carbon emissions in order to quantify the impact of different factors on changes in carbon emissions.

[0164] By substituting carbon emission data from different periods or under different evaluation conditions into the logarithmic mean Dijkstra index decomposition model, the contribution of factors such as changes in energy consumption scale, energy structure, energy efficiency, production processes, and economic development level to changes in carbon emissions can be calculated. This calculation process clarifies the positive or negative effects of each influencing factor on changes in carbon emissions.

[0165] By quantifying the degree of influence of each factor, changes in carbon emissions are no longer merely presented as results, but their formation mechanisms can be further revealed, providing quantitative evidence for subsequent analysis.

[0166] S403: Identify the causes of abnormal carbon emissions based on the degree of influence of each of the aforementioned factors on changes in carbon emissions.

[0167] Specifically, the server identifies the causes of abnormal carbon emissions from industrial enterprises based on the impact of various factors on changes in carbon emissions.

[0168] When the contribution of one or more factors to changes in carbon emissions deviates significantly from the normal range, the corresponding factors can be identified as important causes of abnormal carbon emissions. For example, when the scale of energy consumption or energy structure contributes significantly to the growth of carbon emissions, it indicates that there may be irrational energy use patterns; when production processes or energy efficiency have an adverse impact on changes in carbon emissions, it indicates that there may be room for optimization in the production and operation processes.

[0169] By identifying the causes of abnormal carbon emissions, a basis for subsequent carbon emission management and decision-making can be provided, enabling enterprises to focus on key factors that have a significant impact on changes in carbon emissions.

[0170] Figure 5 This is a schematic diagram of the fifth process of the carbon emission assessment method provided in this embodiment of the invention, as shown below. Figure 5 As shown, in one embodiment of the present invention, S103 further includes:

[0171] S501: Based on the carbon emission data and the enterprise economic data, construct an evaluation index system from the carbon emission cost side and the benefit side;

[0172] Specifically, the server further constructs an evaluation index system based on carbon emission data and corporate economic data, from the cost and benefit sides of carbon emissions, to reflect the impact of carbon emissions on corporate economic operations.

[0173] The cost-side indicators characterize the economic costs incurred by enterprises due to carbon emissions and related management activities, including carbon emission costs corresponding to energy consumption, production processes, and related management activities. The revenue-side indicators characterize the economic benefits obtained by enterprises through carbon emission management, carbon reduction measures, or low-carbon business practices. By linking carbon emission data with enterprise economic data, a multi-dimensional evaluation indicator system that reflects the economic attributes of carbon emissions is formed.

[0174] The evaluation index system expresses the costs and benefits related to carbon emissions in a structured way, so that carbon emissions are no longer just an environmental indicator, but can be combined with the economic operation of enterprises, providing a quantitative basis for subsequent evaluation.

[0175] S502: Calculate the carbon emission economic efficiency index based on the evaluation index system.

[0176] Specifically, after the server completes the evaluation index system for both the cost and benefit sides of carbon emissions, it calculates the carbon emission economic efficiency index based on the evaluation index system.

[0177] The carbon emission economic efficiency index is used to comprehensively reflect the economic rationality of a company's carbon emission behavior within a certain evaluation period. It generates an evaluation result that characterizes the level of carbon emission economic efficiency by comprehensively analyzing cost-side and revenue-side indicators. The carbon emission economic efficiency index can intuitively reflect the relationship between the economic input and output corresponding to carbon emissions under current production and operation conditions.

[0178] By calculating the carbon emission economic efficiency index, the carbon emission assessment results not only reflect the emission level itself, but also further reflect the impact of carbon emissions on corporate economic benefits, providing a reference for enterprises to carry out carbon emission management and economic decision-making.

[0179] In one embodiment, a carbon emission assessment method is constructed based on the synergistic development of the "Energy-Economic-Environment" triad, including influencing factor diagnosis and assessment and carbon emission economic efficiency index assessment.

[0180] When a company's current carbon emission level is inconsistent with its historical economic development and historical carbon emission levels, or when there is an over-emission situation, the causes of the abnormal carbon emissions are analyzed and judged. By constructing a Logarithmic Mean Divisia Index (LMDI) decomposition model, the factors affecting changes in economic development, energy consumption, and other key indicators are decomposed and analyzed, thereby identifying and quantifying the driving factors of carbon emission changes.

[0181] Carbon emissions from industrial enterprises are influenced by multiple factors, including economic output, energy intensity, and energy structure. Based on the logarithmic mean Dijkstra index method, carbon emission decomposition formulas are established as shown in formulas (3) to (4):

[0182] (3)

[0183] (4)

[0184] In the formula: C represents carbon emissions, in ten thousand tons; P represents energy cost, in yuan; This represents total energy consumption, expressed in ten thousand tons of electricity (tce). This represents the consumption of a certain energy source, expressed in ten thousand tons (tce). ΔC represents the final consumption of a certain energy source, in ten thousand tons (tce); ΔC represents the change in carbon emissions of a certain enterprise from year T-1 to year T, in ten thousand tons; C T and C T-1 ΔC represents the total carbon emissions in year T and year T-1, in ten thousand tons. gp Indicates the energy cost effect; ΔC eg Indicates the energy intensity effect; ΔC es Indicates the energy structure effect; ΔC ee Indicates the energy efficiency effect; ΔC ce This indicates the carbon emission intensity effect.

[0185] In formula (3), GP represents the energy cost effect; denoted as... Let be the sum of all energy costs required for the production of industrial products, representing the energy cost effect; (denoted as...) Let be the energy consumption per unit cost, representing the energy intensity effect; denoted as Let be the proportion of energy consumption i to the total energy consumption of industrial product production, representing the energy structure effect; denotes... Energy efficiency is the rate of effective energy utilization, representing the energy efficiency effect; denoted as... Carbon emission intensity represents the carbon emission intensity effect. The ratio of final energy consumption to total energy consumption reflects the degree of energy utilization. Improvements in energy processing and conversion efficiency and advancements in energy utilization technology can lead to greater carbon emission reductions. The carbon emission effect means that, with total energy consumption remaining constant, a higher proportion of fossil fuels with higher carbon content implies a larger average carbon emission factor, resulting in a greater carbon emission effect.

[0186] In formula (4), ΔC gp Representing the energy cost effect, ΔC eg Indicates the energy intensity effect, ΔC es Indicating the energy structure effect, ΔC ee Indicates the energy efficiency effect, ΔC ce This represents the carbon emission intensity effect. The calculation formulas are shown in formulas (5) to (9):

[0187] (5)

[0188] (6)

[0189] (7)

[0190] (8)

[0191] (9)

[0192] Where: GP T and GP T-1 These represent the energy costs in year T and year T-1, respectively; EG T and EG T-1 These represent the energy intensity in year T and year T-1, respectively; ES T and ES T-1 These represent the energy structures in year T and year T-1, respectively; EE T and EE T-1 These represent the energy efficiency in year T and year T-1, respectively; CE T and CE T-1 represents the carbon emission intensity in year T and year T-1, respectively; i represents the change, which varies according to the evaluation period. For example, if the carbon emissions over the five years from 2020 to 2024 are decomposed, then i=5.

[0193] For enterprises whose current carbon emissions are inconsistent with their historical economic development and historical carbon emission levels, or that exceed emission limits, an influencing factor diagnostic evaluation method is introduced to determine the causes of the abnormal situation. The positive / negative effects of each influencing factor on carbon emissions are calculated through model calculations, thereby enabling early warning of problems and the development of targeted solutions.

[0194] In one embodiment, an evaluation index system is constructed from both the cost and benefit sides to link corporate carbon emissions with corporate economic operations, providing support for companies to formulate more targeted carbon reduction strategies.

[0195] The cost side focuses on the direct and indirect costs incurred by enterprises due to carbon emissions. The core indicators are shown in Table 1.

[0196] Table 1

[0197]

[0198] The revenue side measures the direct and indirect benefits that enterprises gain through carbon management and carbon emission reduction. The core indicators are shown in Table 2.

[0199] Table 2

[0200]

[0201] A carbon emission economic efficiency index evaluation system is constructed based on core evaluation indicators from both the cost and benefit sides. This system integrates "cost-benefit-efficiency" to form a benchmarkable and predictable core evaluation index, with a value range of [0,1]. The closer the index is to 1, the better the carbon emission economic efficiency. The calculation of the carbon emission economic efficiency index is shown in formulas (10) to (12):

[0202] (10)

[0203] W CO2 =W 能源碳成本 +W 工艺碳成本 +W 设备年成本 +W 碳管理成本 +W 隐形碳成本 (11)

[0204] R CO2 =R 碳直接收益 +R 碳间接收益 -W CO2 (12)

[0205] In the formula: I 经济 For carbon emission economic efficiency index; W CO2 The total carbon emission cost, which integrates direct, indirect, and implicit carbon costs, reflects the comprehensive economic burden of a company's carbon emissions; R CO2 The net benefit of carbon emissions measures the actual economic value of carbon reduction measures and provide a basis for strategy selection; α, β, and γ are weighting coefficients, determined by the analytic hierarchy process (AHP) in combination with the characteristics of the enterprise's industry.

[0206] Figure 6 This is a schematic diagram of the sixth process of the carbon emission assessment method provided in this embodiment of the invention, as shown below. Figure 6 As shown, in one embodiment of the present invention, the carbon emission assessment method of the present invention further includes:

[0207] S601: Based on the carbon emission data and the carbon emission assessment results, analyze and process the historical data stored in the carbon data warehouse to assess the carbon emission reduction potential of the industrial enterprise.

[0208] Specifically, the server analyzes and processes historical data stored in the carbon data warehouse based on carbon emission data and carbon emission assessment results in order to assess the carbon emission reduction potential of industrial enterprises.

[0209] A carbon data warehouse is used to centrally store historical carbon emission data generated by industrial enterprises in different assessment periods, including carbon emission data for different time periods and corresponding carbon emission assessment results. By analyzing and processing historical data, long-term trends and periodic characteristics of changes in enterprise carbon emissions can be identified.

[0210] In assessing carbon emission reduction potential, carbon emission data and assessment results for the current evaluation period are compared and analyzed with historical data to determine whether enterprises have room for further carbon emission reduction under existing production conditions. By analyzing the changes in carbon emission levels over different periods, a basis is provided for the formulation of subsequent carbon emission reduction measures, thus forming an assessment result of the carbon emission reduction potential of industrial enterprises.

[0211] S602: Generate carbon reduction strategies based on the results of carbon reduction potential assessment.

[0212] Specifically, after completing the assessment of the carbon emission reduction potential of industrial enterprises, the server generates carbon emission reduction strategies based on the assessment results.

[0213] Carbon reduction strategies guide enterprises in carrying out carbon reduction activities during subsequent production and operation. Based on the assessed carbon reduction potential, they clarify the achievable carbon reduction targets and directions for enterprises within a certain period. By transforming the carbon reduction potential assessment results into corresponding strategic recommendations, enterprises can plan their carbon reduction efforts in a targeted manner.

[0214] By generating carbon reduction strategies, carbon emission assessment results can be further transformed into decision-making references for practical applications, providing support for industrial enterprises to implement carbon emission management and low-carbon development.

[0215] In one embodiment, the server analyzes and evaluates the carbon emission reduction potential of industrial enterprises based on the carbon emission data and carbon emission assessment and diagnosis results, and generates personalized carbon emission reduction strategies accordingly.

[0216] Big data analytics are used to conduct in-depth mining and analysis of historical data stored in the carbon data warehouse. This historical data includes carbon emission accounting data, carbon emission assessment results, and related production and operation data for different time periods.

[0217] By employing methods such as data clustering, association rule mining, and time series analysis, this study aims to uncover the inherent patterns and correlations of carbon emissions during steel production. For example, it analyzes the relationships between different production processes, equipment operating states, energy consumption patterns, and carbon emissions, as well as the trend characteristics of carbon emissions over time.

[0218] At the same time, by combining external data such as market demand data, raw material price data, and official standard data, a comprehensive analysis of the internal and external environment in which enterprises operate is conducted to identify the impact of changes in the external environment on the carbon emission levels of enterprises, thereby providing data support and decision-making basis for the formulation of subsequent carbon emission reduction strategies.

[0219] After completing the analysis of carbon emission patterns, a comprehensive assessment of the company's carbon reduction potential is conducted based on the results of big data analysis.

[0220] The assessment of carbon emission reduction potential is conducted from multiple dimensions, including improving energy efficiency, optimizing production processes, upgrading equipment, and recycling waste. During the assessment, energy consumption data is analyzed to identify production processes and equipment with significant energy waste, and the potential carbon emission reductions achievable through improved energy management measures or replacement with energy-efficient equipment are evaluated. Analysis of production process data determines the carbon emission reduction potential that can be achieved by optimizing process parameters or adopting new technologies. Analysis of waste generation and treatment data assesses the contribution of enhanced waste resource utilization to carbon emission reduction.

[0221] By quantitatively assessing the carbon reduction potential in the above-mentioned areas, we can clarify the key directions and objectives for carbon reduction for enterprises under current technological conditions and resource constraints.

[0222] After completing the carbon emission reduction potential assessment, a personalized carbon emission reduction strategy is formulated based on the company's development strategy and actual production and operation.

[0223] Carbon emission reduction strategies include short-term, medium-term, and long-term emission reduction targets and corresponding specific measures. These measures include, but are not limited to: implementing energy management projects, such as waste heat recovery and variable frequency speed control technology; promoting production process improvements, such as adopting advanced smelting technologies and optimizing furnace charge structure; carrying out equipment upgrades, such as replacing equipment with high-efficiency energy-saving equipment or retrofitting old equipment for energy conservation; strengthening the resource utilization of waste, such as steel slag recycling and waste heat power generation; and participating in carbon market trading.

[0224] During the strategy formulation process, multi-objective optimization algorithms are used to comprehensively evaluate and optimize different carbon emission reduction strategies. These algorithms include genetic algorithms and particle swarm optimization algorithms. By considering the carbon emission reduction effect while comprehensively weighing cost input, technical feasibility, and impact on production operations, the optimal combination of carbon emission reduction schemes is determined to maximize the economic benefits of enterprises under the given carbon emission reduction targets.

[0225] In one embodiment, a schematic diagram of the "energy-economy-environment" carbon emission assessment process is shown below. Figure 14 As shown.

[0226] In one embodiment, the impact of various influencing factors on a company's carbon emissions from 2019 to 2024 is shown in Table 3.

[0227] Table 3

[0228]

[0229] Using the influencing factor diagnostic evaluation model, it can be calculated that, for a certain enterprise's carbon emissions, the energy structure effect ( ) and energy intensity effect ( It has a significant inhibitory effect on carbon dioxide emissions, and the cost-effectiveness ( Energy efficiency effect ( ) and carbon emission effects ( This has contributed to the growth of carbon dioxide emissions. This indicates that improving energy utilization structure, increasing energy intensity, and enhancing technology to achieve greater industrial output with less energy consumption can lead to carbon emission reduction. However, enterprises still face problems such as overcapacity and reliance on fossil fuels, necessitating further cost reduction and efficiency improvement, the development of clean energy, and the substitution of fossil fuels.

[0230] In 2024, the company's carbon emissions reached 3 million tons, placing it on the list of key carbon emitters. Its output in 2024 was 1.2 million tons, with a total output value of 8.4 billion yuan. In 2025, a combined emission reduction retrofit project of "sintering waste heat recovery + efficient utilization of blast furnace gas" is planned, which is expected to reduce carbon emissions to 2.7 million tons of CO2 after the retrofit.

[0231] Based on the average CO2 price of 97.49 yuan / ton at the end of 2024, and a projected fluctuation range of ±5% in 2025, calculated at 95 yuan / ton. Coal prices are 1100 yuan / ton, natural gas 4.2 yuan / cubic meter, and purchased electricity 0.65 yuan / kWh. The subsidy rate for low-carbon transformation projects is 10%, and the penalty for exceeding carbon emission standards is 150 yuan / ton CO2. The total investment in carbon emission reduction projects is 80 million yuan (equipment purchase + installation and commissioning), with a service life of 15 years and an average annual depreciation of 5.3333 million yuan. Carbon management costs are 1.2 million yuan annually, and other non-energy costs total 4.2 billion yuan (raw materials, labor, etc.).

[0232] Calculations yielded a total carbon emission economic cost of 192.001 million yuan, a total carbon reduction benefit of 55.7 million yuan, a unit carbon reduction cost of 266.67 yuan / ton CO2, and a carbon reduction investment payback period of 1.62 years. The analytic hierarchy process (AHP) was used to determine the weighting coefficients: α = 0.4 (net benefit ratio), β = 0.3 (emission reduction cost efficiency), and γ = 0.3 (output carbon emission benefit). The carbon emission economic efficiency index is... = 0.307.

[0233] An evaluation of these results leads to the following conclusions:

[0234] 1. Cost structure analysis: Direct carbon costs account for 91.9% of total carbon costs, with coal combustion carbon emission costs dominating, reflecting the huge potential for energy structure optimization;

[0235] 2. Feasibility assessment of profitability: The payback period for carbon emission reduction investment is 1.62 years, which is much shorter than the equipment service life of 15 years, and the unit carbon emission reduction cost (266.67 yuan / ton) is lower than the long-term carbon price increase expectation, making the project economically feasible;

[0236] 3. Efficiency Index Warning: The carbon emission economic efficiency index is 0.307 < 0.5, indicating that further measures such as "coal-to-gas conversion" and "green electricity substitution" are needed to reduce the unit carbon cost.

[0237] It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases the steps shown or described may be executed in a different order than that shown here.

[0238] Based on the same inventive concept, embodiments of the present invention also provide a carbon emission assessment device, which can be used to implement the carbon emission assessment method described in the above embodiments, as described in the following embodiments. Since the principle by which the carbon emission assessment device solves the problem is similar to that of the carbon emission assessment method, embodiments of the carbon emission assessment device can refer to embodiments of the carbon emission assessment method, and repeated details will not be elaborated further. As used below, the terms "unit" or "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0239] Figure 7 This is a schematic block diagram of the first structure of the carbon emission assessment device provided in the embodiments of the present invention, as shown below. Figure 7 As shown, in one embodiment of the present invention, the carbon emission assessment device of the present invention includes:

[0240] The data acquisition unit 701 is used to collect basic carbon emission data of industrial enterprises within a predetermined carbon emission accounting boundary and to preprocess the basic carbon emission data; the basic carbon emission data includes energy consumption data, production process data and enterprise economic data.

[0241] Carbon emission accounting unit 702 is used to perform carbon emission accounting based on the energy consumption data and the production process data to obtain carbon emission data.

[0242] The carbon emission assessment unit 703 is used to comprehensively evaluate the carbon emission level based on the energy consumption data, the production process data, the enterprise economic data, and the carbon emission data, and obtain the carbon emission assessment result.

[0243] Figure 8 This is a schematic block diagram of the second structure of the carbon emission assessment device provided in the embodiments of the present invention. Figure 7Based on the embodiments, further, such as Figure 8 As shown, in one embodiment of the present invention, the data acquisition unit 701 includes:

[0244] The data cleaning module 801 is used to clean the carbon emission basic data, identify and remove outliers;

[0245] Missing value imputation module 802 is used to impute missing values ​​in the carbon emission basic data after data cleaning;

[0246] The standardization processing module 803 is used to standardize the basic carbon emission data after missing values ​​have been filled.

[0247] Figure 9 This is a schematic block diagram of the third structure of the carbon emission assessment device provided in the embodiments of the present invention. Figure 7 Based on the embodiments, further, such as Figure 9 As shown, in one embodiment of the present invention, the carbon emission accounting unit 702 includes:

[0248] Carbon emission factor determination module 901 is used to determine the corresponding carbon emission factor based on the energy consumption data and the production process data;

[0249] The carbon emission accounting module 902 is used to perform carbon emission accounting using the energy consumption data, the production process data and the carbon emission factor to obtain carbon emission data.

[0250] Figure 10 This is a schematic block diagram of the fourth structure of the carbon emission assessment device provided in the embodiments of the present invention. Figure 7 Based on the embodiments, further, such as Figure 10 As shown, in one embodiment of the present invention, the carbon emission assessment unit 703 includes:

[0251] The model building module 1001 is used to build a log-mean Dijkstra exponential decomposition model to characterize changes in carbon emissions based on the energy consumption data, the production process data, the enterprise economic data, and the carbon emission data.

[0252] The factor impact calculation module 1002 is used to calculate the degree of influence of each factor on the change in carbon emissions using the log-mean Dijkstra index decomposition model.

[0253] The anomaly cause identification module 1003 is used to identify the causes of carbon emission anomalies based on the degree of influence of each factor on carbon emission changes.

[0254] Figure 11 This is a fifth structural schematic block diagram of the carbon emission assessment device provided in the embodiments of the present invention. Figure 10Based on the embodiments, further, such as Figure 11 As shown, in one embodiment of the present invention, the carbon emission assessment unit 703 further includes:

[0255] The evaluation index system construction module 1101 is used to construct an evaluation index system from the carbon emission cost side and the benefit side based on the carbon emission data and the enterprise economic data.

[0256] The economic efficiency index calculation module 1102 is used to calculate the carbon emission economic efficiency index based on the evaluation index system.

[0257] Figure 12 This is a sixth structural schematic block diagram of the carbon emission assessment device provided in the embodiments of the present invention. Figure 7 Based on the embodiments, further, such as Figure 12 As shown, in one embodiment of the present invention, the carbon emission assessment device provided in this application further includes:

[0258] Carbon emission reduction potential assessment unit 1201 is used to analyze and process historical data stored in the carbon data warehouse based on the carbon emission data and the carbon emission assessment results, and to assess the carbon emission reduction potential of the industrial enterprise.

[0259] The carbon emission reduction strategy generation unit 1202 is used to generate carbon emission reduction strategies based on the carbon emission reduction potential assessment results.

[0260] Figure 13 This is a schematic diagram of the structure of the computer device provided in an embodiment of the present invention, such as... Figure 13 As shown, the electronic device may include: a processor 1301, a communication interface 1302, a memory 1303, and a communication bus 1304, wherein the processor 1301, the communication interface 1302, and the memory 1303 communicate with each other through the communication bus 1304. The processor 1301 can call logical instructions in the memory 1303 to execute the following methods: collecting basic carbon emission data of industrial enterprises within a predetermined carbon emission accounting boundary and preprocessing the basic carbon emission data; the basic carbon emission data includes energy consumption data, production process data, and enterprise economic data; performing carbon emission accounting based on the energy consumption data and the production process data to obtain carbon emission data; and comprehensively evaluating the carbon emission level based on the energy consumption data, the production process data, the enterprise economic data, and the carbon emission data to obtain a carbon emission evaluation result.

[0261] Furthermore, the logical instructions in the aforementioned memory 1303 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, a top-drive control center server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0262] This embodiment discloses a computer program product, which includes a computer program stored on a computer-readable storage medium. The computer program includes program instructions, and when the program instructions are executed by a computer, the computer can execute the methods provided in the above-described method embodiments, such as: collecting basic carbon emission data of industrial enterprises within a predetermined carbon emission accounting boundary and preprocessing the basic carbon emission data; the basic carbon emission data includes energy consumption data, production process data, and enterprise economic data; performing carbon emission accounting based on the energy consumption data and the production process data to obtain carbon emission data; and comprehensively evaluating the carbon emission level based on the energy consumption data, the production process data, the enterprise economic data, and the carbon emission data to obtain a carbon emission evaluation result.

[0263] This embodiment provides a computer-readable storage medium storing a computer program that causes a computer to execute the methods provided in the above-described method embodiments. For example, the methods include: collecting basic carbon emission data of industrial enterprises within a predetermined carbon emission accounting boundary and preprocessing the basic carbon emission data; the basic carbon emission data includes energy consumption data, production process data, and enterprise economic data; performing carbon emission accounting based on the energy consumption data and the production process data to obtain carbon emission data; and comprehensively evaluating the carbon emission level based on the energy consumption data, the production process data, the enterprise economic data, and the carbon emission data to obtain a carbon emission evaluation result.

[0264] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0265] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0266] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0267] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0268] In the description of this specification, the references to terms such as "an embodiment," "a specific embodiment," "some embodiments," "for example," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0269] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of this application. It should be understood that the above descriptions are merely specific embodiments of this application and are not intended to limit the scope of protection of this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A carbon emission assessment method, characterized in that, include: Collect basic carbon emission data of industrial enterprises within a predetermined carbon emission accounting boundary and preprocess the basic carbon emission data; The basic carbon emission data includes energy consumption data, production process data, and enterprise economic data. Carbon emission calculations are performed based on the energy consumption data and the production process data to obtain carbon emission data. The carbon emission level is comprehensively evaluated based on the energy consumption data, production process data, enterprise economic data, and carbon emission data to obtain the carbon emission evaluation result.

2. The carbon emission assessment method according to claim 1, characterized in that, The preprocessing of the carbon emission baseline data includes: The carbon emission baseline data is cleaned to identify and remove outliers; Missing values ​​were filled in the cleaned carbon emission baseline data. The carbon emission baseline data after missing values ​​were filled was standardized.

3. The carbon emission assessment method according to claim 1, characterized in that, The carbon emission calculation based on the energy consumption data and the production process data yields carbon emission data, including: The corresponding carbon emission factor is determined based on the energy consumption data and the production process data. Carbon emission data is obtained by using the energy consumption data, the production process data, and the carbon emission factor.

4. The carbon emission assessment method according to claim 1, characterized in that, The comprehensive evaluation of carbon emission levels based on the energy consumption data, production process data, enterprise economic data, and carbon emission data includes: Based on the energy consumption data, the production process data, the enterprise economic data, and the carbon emission data, a log-mean Dijkstra exponential decomposition model is constructed to characterize changes in carbon emissions. The impact of each factor on carbon emission changes was calculated using the log-mean Dijkstra index decomposition model. Identify the causes of abnormal carbon emissions based on the degree of influence of each of the aforementioned factors on changes in carbon emissions.

5. The carbon emission assessment method according to claim 4, characterized in that, The comprehensive evaluation of carbon emission levels also includes: Based on the carbon emission data and the enterprise economic data, an evaluation index system is constructed from both the cost and benefit sides of carbon emissions. The carbon emission economic efficiency index is calculated based on the evaluation index system.

6. The carbon emission assessment method according to claim 1, characterized in that, Also includes: Based on the carbon emission data and the carbon emission assessment results, the historical data stored in the carbon data warehouse is analyzed and processed to assess the carbon emission reduction potential of the industrial enterprise. Carbon reduction strategies are generated based on the assessment results of carbon reduction potential.

7. A carbon emission assessment device, characterized in that, include: The data acquisition unit is used to collect basic carbon emission data of industrial enterprises within a predetermined carbon emission accounting boundary and to preprocess the basic carbon emission data. The basic carbon emission data includes energy consumption data, production process data, and enterprise economic data. A carbon emission accounting unit is used to perform carbon emission accounting based on the energy consumption data and the production process data to obtain carbon emission data. The carbon emission assessment unit is used to comprehensively evaluate the carbon emission level based on the energy consumption data, the production process data, the enterprise economic data, and the carbon emission data, and obtain the carbon emission assessment result.

8. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program / instructions stored thereon, characterized in that, When the computer program / instructions are executed by the processor, they implement the steps of the method according to any one of claims 1 to 6.

10. A computer program product comprising a computer program / instructions, characterized in that, When the computer program / instructions are executed by the processor, they implement the steps of the method according to any one of claims 1 to 6.

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