Urban area carbon emission data management method and system based on big data

Abstract

The invention discloses an urban regional carbon emission data management method and system based on big data, and relates to the technical field of urban carbon emission monitoring, the system is connected with an enterprise system through an API interface, manufacturing data is acquired in real time and preprocessed, a production data set is generated, and the comprehensive production carbon emission index stp is calculated to obtain the urban regional carbon emission data. And performing preliminary production carbon emission evaluation on whether the carbon emission meets the standard or not in the production process according to the preset production carbon emission standard threshold value Z. On the premise that carbon emission in the production process is qualified, air conditioner operation data are extracted and processed, an operation data set is obtained, load power and air conditioner efficiency are analyzed, air conditioner operation carbon emission evaluation is conducted by calculating an operation carbon emission index ytp and combining the operation carbon emission index ytp with a preset operation carbon emission threshold value X, and it is ensured that environmental protection standards are met in the production and use processes. According to the invention, carbon emission is accurately monitored and managed by using a big data technology and a multi-dimensional evaluation method, and carbon emission reduction and sustainable development goals of urban areas are effectively supported.

Description

Technical Field

[0001] The present invention relates to the technical field of urban carbon emission monitoring, and specifically to a method and system for managing urban area carbon emission data based on big data. Background Art

[0002] With the continuous increase in the global demand for environmental protection and sustainable development, the management of urban area carbon emission data based on big data has gradually become an important means to address climate change and promote green development. Especially in urban areas, the production, consumption of energy, and the management and monitoring of carbon emissions are particularly important. To address the carbon emission problem in the urban environment, an integrated carbon emission management system has been gradually constructed, especially its application in the field of heating, ventilation, and air conditioning, which can effectively reduce carbon emissions during the production process and improve energy utilization efficiency. Therefore, the development and application of an efficient carbon emission monitoring and management system are not only the needs for enterprises to fulfill their social responsibilities and achieve green transformation, but also an important measure to respond to global environmental protection policies and promote the sustainable development of the industry.

[0003] Although many enterprises have established a preliminary data monitoring system in carbon emission management, there are generally problems such as incomplete data collection, inaccurate analysis and processing, and inconsistent evaluation criteria. In the monitoring of carbon emissions during the manufacturing process, traditional methods often rely on manual records and local equipment data, making it difficult to achieve full-process and real-time data tracking and evaluation. In the monitoring of operating carbon emissions, there is a lack of effective operating efficiency evaluation tools, and the operating status of equipment and the actual load conditions are not effectively combined, resulting in a significant reduction in the accuracy and reliability of evaluation results. In addition, the existing carbon emission management systems mostly focus on a single production link or equipment, ignoring the overall optimization of the production line and the carbon emission management throughout the life cycle of air conditioner operation. Therefore, there is an urgent need for a big data-based, comprehensive, and systematic carbon emission monitoring solution to address the deficiencies in existing methods. Summary of the Invention

[0004] In view of the deficiencies of the prior art, the present invention provides a method and system for managing urban area carbon emission data based on big data, which solves the problems in the above-mentioned background art.

[0005] To achieve the above objectives, the present invention is realized through the following technical solutions: A big data-based urban area carbon emission data management system includes a production data acquisition module, a production carbon emission analysis module, a production carbon emission evaluation module, an operation analysis module, and an operation carbon emission evaluation module;

[0006] The production data acquisition module is used to construct a data analysis system, establish a communication connection with the enterprise system through an API interface, obtain manufacturing data in real time, and perform preprocessing to obtain a production data set;

[0007] The production carbon emission analysis module is used to perform summary calculations based on the obtained production data set to obtain the energy efficiency production mapping coefficient snx, the material thermal variation coefficient cxh, and the energy efficiency emission response coefficient nxx;

[0008] The production carbon emission assessment module is used to perform summary calculations based on the obtained energy efficiency production mapping coefficient snx, the material thermal variation coefficient cxh, and the energy efficiency emission response coefficient nxx to obtain the comprehensive production carbon emission index stp, and conduct a preliminary production carbon emission assessment with the preset carbon emission production standard threshold Z;

[0009] When the preliminary production carbon emission assessment indicates that the carbon emission meets the standard, the operation analysis module is used to extract the operation experiment data of the production air conditioner through the data analysis system, perform preprocessing to obtain the operation data set, and then perform summary calculations based on the operation data set to obtain the load power index fgz and the air conditioner efficiency index sbx;

[0010] The operation carbon emission assessment module is used to perform summary calculations based on the obtained load power index fgz and the air conditioner efficiency index sbx to obtain the operation carbon emission index ytp, and conduct an air conditioner operation carbon emission assessment with the preset operation carbon emission threshold X.

[0011] Preferably, the production data acquisition module includes a data acquisition unit, a data processing unit, and a data storage unit;

[0012] The data acquisition unit is used to construct a data analysis system and establish a communication connection with the enterprise system through the API interface to extract the manufacturing data of the enterprise in real time;

[0013] The enterprise system includes a manufacturing execution system MES, an energy management system EMS, and an industrial Internet of Things platform IIoT.

[0014] Preferably, the data processing unit is used to perform data cleaning, time synchronization, and dimensionless processing on the obtained manufacturing data to obtain the production data set;

[0015] The production data set includes an energy efficiency production data set, a material thermal data set, and an energy efficiency data set;

[0016] The energy efficiency production data set includes energy consumption nx, equipment energy efficiency sn, and production speed sd;

[0017] The material thermal data set includes material consumption density xm, material processing time sj, and production temperature wd;

[0018] The energy efficiency data set includes energy carbon emission coefficient pf, energy conversion efficiency zh, and energy input amount nx;

[0019] The data storage unit is used to construct a data repository according to the data analysis system, and input the obtained production data group into the data repository for storage in real time.

[0020] Preferably, the production carbon emission analysis module includes an energy efficiency production analysis unit, a material thermal analysis unit, and an energy efficiency analysis unit;

[0021] The energy efficiency production analysis unit is used to perform summary calculations based on the obtained energy efficiency production data group, obtain the energy efficiency production mapping coefficient snx, and analyze the combined impact of production equipment energy efficiency and production speed on carbon emissions;

[0022] The energy efficiency production mapping coefficient snx is obtained through the following formula;

[0023]

[0024] In the formula, I represents the total types of production equipment, nx i represents the energy consumption input by the i-th type of production equipment, sn i represents the equipment energy efficiency of the i-th type of production equipment, exp represents the exponential decay function, k1 represents the impact index of production speed on carbon emissions, k2 represents the non-linear growth factor of production speed, the value ranges of k1 and k2 are set by the user, and sd0 represents the production speed under standard conditions;

[0025] The material thermal analysis unit is used to perform summary calculations based on the obtained material thermal data group, obtain the material thermal variation coefficient cxh, and analyze the combined impact of production temperature fluctuations on material consumption and processing time;

[0026] The material thermal variation coefficient cxh is obtained through the following formula;

[0027]

[0028] In the formula, M represents the total types of materials required, xm m represents the consumption density of the m-th type of material, tp represents the carbon emission coefficient of material consumption, which is obtained from the chemical properties of the material itself, sj m represents the processing time of the m-th type of material, wd0 represents the standard temperature of material processing, Δwd represents the temperature fluctuation during the production process, and exp represents the exponential decay function;

[0029] The energy efficiency analysis unit is used to perform summary calculations based on the obtained energy efficiency data group, obtain the energy efficiency emission response coefficient nxx, and analyze the carbon emission effects of different energy sources during production in terms of energy type and conversion efficiency;

[0030] The energy efficiency emission response coefficient nxx is obtained through the following formula;

[0031]

[0032] In the formula, J represents the total types of energy, pf j represents the carbon emission coefficient of the j-th type of energy, zh j represents the conversion efficiency of the j-th type of energy, ɑ j represents the adjustment coefficient of the consumption of the j-th type of energy, ns j represents the energy input of the j-th type of energy, ns 0，j represents the standard energy input of the j-th type of energy under standard conditions, and ln represents the standard logarithmic function.

[0033] Preferably, the production carbon emission assessment module includes a production carbon emission analysis unit and a production carbon emission assessment unit;

[0034] The production carbon emission analysis unit is used to perform summary calculations based on the obtained energy efficiency production mapping coefficient snx, material thermal variation coefficient cxh, and energy efficiency emission response coefficient nxx, obtain the comprehensive production carbon emission index stp, and analyze the non-linear change of carbon emissions under the comprehensive influence of different factors;

[0035] The comprehensive production carbon emission index stp is obtained through the following formula;

[0036]

[0037] In the formula, a1 represents the influence coefficient of the energy efficiency production mapping coefficient snx on carbon emissions, a2 represents the influence coefficient of the material thermal variation coefficient cxh on carbon emissions, a3 represents the adjustment constant of energy consumption in total carbon emissions, and the value ranges of a1, a2, and a3 are set by the user, and exp represents the exponential decay function.

[0038] Preferably, the production carbon emission assessment unit presets a preset carbon emission production standard threshold Z based on the carbon emission benchmark of the production industry, and conducts a preliminary production carbon emission assessment with the obtained comprehensive production carbon emission index stp to analyze whether the carbon emissions during the production process meet the standards. The specific assessment scheme is as follows;

[0039] When the comprehensive production carbon emission index stp ≥ the carbon emission production standard threshold Z, the carbon emissions exceed the standard, and rectification measures are immediately taken;

[0040] When the comprehensive production carbon emission index stp < the carbon emission production standard threshold Z, the carbon emissions meet the standards, and at this time, further monitoring of the carbon emissions during the operation of the produced air conditioner is carried out.

[0041] Preferably, the operation analysis module includes an operation data acquisition unit and an operation carbon emission analysis unit;

[0042] The operating data acquisition unit is used to obtain the operation experiment data of the manufacturer for the production of air conditioners through the equipment management system EAM and the thermal management analysis software when the preliminary production carbon emission assessment meets the carbon emission standards, and perform data cleaning, time synchronization, and dimensionless processing on the operation experiment data to obtain an operation data set;

[0043] The operation data set includes a load data set and an efficiency data set;

[0044] The load data set includes power consumption gl and load factor fz;

[0045] The efficiency data set includes operation duration ys, ambient temperature yw, heat loss coefficient rs, heat response coefficient rx, and outer surface area wb.

[0046] Preferably, the operating carbon emission analysis unit is used to perform summary calculations based on the obtained load data set and efficiency data set to obtain a load power index fgz and an air conditioner efficiency index sbx. The specific formulas are as follows;

[0047]

[0048] In the formula, Q represents the total number of air conditioners produced, gl q represents the power consumption of the qth air conditioner, fz q represents the load factor of the qth air conditioner, gl q，d represents the power consumption of the qth air conditioner in the standby state, ys q represents the operation duration of the qth air conditioner, Δyw represents the ambient temperature fluctuation, exp represents the exponential decay function, wb q represents the outer surface area of the qth air conditioner.

[0049] Preferably, the operating carbon emission assessment module includes an operating carbon emission analysis unit and an operating carbon emission assessment unit;

[0050] The operating carbon emission analysis unit is used to perform summary calculations based on the obtained load power index fgz and air conditioner efficiency index sbx to obtain an operating carbon emission index ytp, and analyze the comprehensive impact of different factors on the operation of the air conditioner;

[0051] The operating carbon emission index ytp is calculated through the following formula;

[0052]

[0053] In the formula, b represents the adjustment coefficient of the relative proportional difference between the load power index fgz and the air conditioner efficiency index sbx on the comprehensive carbon emission impact, and ln represents the logarithmic function;

[0054] The described operating carbon emission assessment unit presets an operating carbon emission threshold X based on industry carbon emission standards, conducts air conditioner operating carbon emission assessment with the obtained operating carbon emission index ytp, and generates corresponding decisions based on the assessment results. The specific assessment scheme is as follows;

[0055] When the operating carbon emission index ytp < the operating carbon emission threshold X, the operating carbon emissions meet the environmental protection standards, meet the environmental protection requirements, and can be put into use;

[0056] When the operating carbon emission index ytp ≥ the operating carbon emission threshold X, the operating carbon emissions do not meet the environmental protection standards. Mark this air conditioner as having unqualified carbon emissions and take rectification measures.

[0057] A method for managing carbon emission data in urban areas based on big data includes the following steps:

[0058] S1. Construct a data analysis system, establish a communication connection with the enterprise system through the API interface, obtain manufacturing data in real time, and perform preprocessing to obtain a production data set;

[0059] S2. Perform summary calculations based on the obtained production data set to obtain the energy efficiency production mapping coefficient snx, the material thermal variation coefficient cxh, and the energy efficiency emission response coefficient nxx;

[0060] S3. Perform summary calculations based on the obtained energy efficiency production mapping coefficient snx, the material thermal variation coefficient cxh, and the energy efficiency emission response coefficient nxx to obtain the comprehensive production carbon emission index stp, and conduct preliminary production carbon emission assessment with the preset carbon emission production standard threshold Z;

[0061] S4. When the preliminary production carbon emission assessment shows that the carbon emissions meet the standards, extract the operating experiment data of the produced air conditioner through the data analysis system, perform preprocessing to obtain an operating data set, and then perform summary calculations based on the operating data set to obtain the load power index fgz and the air conditioner efficiency index sbx;

[0062] S5. Perform summary calculations based on the obtained load power index fgz and the air conditioner efficiency index sbx to obtain the operating carbon emission index ytp, and conduct air conditioner operating carbon emission assessment with the preset operating carbon emission threshold X.

[0063] The present invention provides a method and system for managing carbon emission data in urban areas based on big data. It has the following beneficial effects:

[0064] (1) The production data acquisition module of this system establishes an API interface communication connection with the enterprise system, collects real-time data during the enterprise manufacturing process in real-time, and performs cleaning, time synchronization, and dimensionless processing to generate a production data set, including an energy efficiency production capacity data set, a material heat data set, and an energy efficiency data set. These data provide basic support for subsequent analysis.

[0065] (2) The production carbon emission analysis module of this system aggregates and calculates the obtained production data set to obtain the energy efficiency production capacity mapping coefficient snx, the material heat variation coefficient cxh, and the energy efficiency emission response coefficient nxx. The energy efficiency production capacity mapping coefficient snx reflects the combined impact of production equipment energy efficiency and production speed on carbon emissions. The material heat variation coefficient cxh takes into account the impact of temperature fluctuations during the production process on material consumption and processing time. The energy efficiency emission response coefficient nxx is used to analyze the response of different energy types and their conversion efficiencies to carbon emissions. Through these coefficients, the system can comprehensively evaluate the carbon emission level during the production process. The production carbon emission assessment module aggregates and calculates the comprehensive production carbon emission index stp based on the energy efficiency production capacity mapping coefficient snx, the material heat variation coefficient cxh, and the energy efficiency emission response coefficient nxx, and compares it with the preset carbon emission production standard threshold Z. If the carbon emissions during the production process exceed the standard threshold, the system will immediately trigger rectification measures; if the carbon emissions meet the standard, the system will enter the carbon emission assessment during the air-conditioning operation stage.

[0066] (3) The operation analysis module of this system is responsible for collecting and processing the operation experimental data of the air conditioner. The data is sourced from the equipment management system EAM and the thermal management analysis software. After cleaning, timestamp marking, and time synchronization, a set of operation data is generated. The operation carbon emission assessment module calculates the load power index fgz and the air-conditioning efficiency index sbx through the operation data set, and then obtains the operation carbon emission index ytp of the air conditioner, and compares it with the preset operation carbon emission threshold X to evaluate whether the air-conditioning operation meets the environmental protection standard. If the operation carbon emissions of the air conditioner are unqualified, the system will mark the air conditioner and start the detection and rectification program. This system can not only identify carbon emission over-standard problems in a timely manner during the production process, but also detect and analyze carbon emission situations in real-time during the actual operation of the air conditioner. In addition, the real-time monitoring ability of the system helps to improve energy efficiency, reduce energy costs, and at the same time promote the enterprise to achieve the goals of green manufacturing and sustainable development. Description of the Drawings

[0067] Figure 1 It is a schematic flowchart of the urban area carbon emission data management system based on big data of the present invention;

[0068] Figure 2 It is a schematic diagram of the steps of the urban area carbon emission data management method based on big data of the present invention. Detailed Embodiments

[0069] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0070] Embodiment 1

[0071] Please refer to Figure 1 , the present invention provides a big data-based urban area carbon emission data management system. To achieve the above objectives, the present invention is realized through the following technical solutions: including a production data acquisition module, a production carbon emission analysis module, a production carbon emission assessment module, an operation analysis module, and an operation carbon emission assessment module;

[0072] The production data acquisition module is used to construct a data analysis system, establish a communication connection with the enterprise system through an API interface, obtain manufacturing data in real time, and perform preprocessing to obtain a production data group;

[0073] The production carbon emission analysis module is used to perform summary calculations based on the obtained production data group to obtain an energy efficiency production mapping coefficient snx, a material thermal variation coefficient cxh, and an energy efficiency emission response coefficient nxx;

[0074] The production carbon emission assessment module is used to perform summary calculations based on the obtained energy efficiency production mapping coefficient snx, material thermal variation coefficient cxh, and energy efficiency emission response coefficient nxx to obtain a comprehensive production carbon emission index stp, and perform a preliminary production carbon emission assessment with a preset carbon emission production standard threshold Z;

[0075] When the preliminary production carbon emission assessment indicates that the carbon emission meets the standard, the operation analysis module is used to extract the operation experiment data of the production air conditioner through the data analysis system, perform preprocessing to obtain an operation data group, and then perform summary calculations based on the operation data group to obtain a load power index fgz and an air conditioner efficiency index sbx;

[0076] The operation carbon emission assessment module is used to perform summary calculations based on the obtained load power index fgz and air conditioner efficiency index sbx to obtain an operation carbon emission index ytp, and perform an air conditioner operation carbon emission assessment with a preset operation carbon emission threshold X.

[0077] In this embodiment, the production data acquisition module establishes an API interface connection with the enterprise system to obtain manufacturing data in real time, and preprocesses this data to generate a production data set. The production carbon emission analysis module calculates the energy efficiency production mapping coefficient snx, the material thermal variation coefficient cxh, and the energy efficiency emission response coefficient nxx through the production data set, so as to evaluate the specific impact of each factor on carbon emissions during the production process. The production carbon emission assessment module further conducts a summary calculation based on the calculated energy efficiency production mapping coefficient snx, the material thermal variation coefficient cxh, and the energy efficiency emission response coefficient nxx to obtain the comprehensive production carbon emission index stp, and conducts a preliminary production carbon emission assessment with the preset carbon emission production standard threshold Z. If the comprehensive production carbon emission index stp exceeds the standard, the system will promptly initiate rectification measures; if the carbon emissions meet the standards, the system will enter the next stage of operation analysis. The operation analysis module obtains the operation experiment data of the air conditioner from the equipment management system EAM and the thermal management analysis software, and preprocesses it to generate an operation data set, calculates the load power index fgz and the air conditioner efficiency index sbx, providing accurate data support for subsequent operation carbon emission assessment. Compared with traditional static carbon emission monitoring technologies, this system greatly improves the efficiency and accuracy of carbon emission monitoring through real-time data collection, dynamic analysis, and instant feedback. The operation carbon emission assessment module calculates the operation carbon emission index ytp based on the load power index fgz and the air conditioner efficiency index sbx, and compares it with the preset operation carbon emission threshold X to determine whether the air conditioner meets the environmental protection requirements. This comprehensive carbon emission assessment mechanism not only effectively improves environmental compliance, but also provides strong guarantees for enterprises to optimize production processes, improve energy efficiency, and reduce operating costs, thus promoting the realization of green manufacturing and sustainable development.

[0078] Embodiment 2

[0079] This embodiment is an explanatory description based on Embodiment 1. Please refer to Figure 1 , specifically: The production data acquisition module includes a data acquisition unit, a data processing unit, and a data storage unit;

[0080] The data acquisition unit is used to construct a data analysis system and establish a communication connection with the enterprise system through the API interface to extract the manufacturing data of the enterprise in real time;

[0081] The enterprise system includes a manufacturing execution system MES, an energy management system EMS, and an industrial Internet of Things platform IIoT;

[0082] The data analysis system extracts various data during the production process, including equipment energy efficiency sn, production speed sd, material processing time sj, and material consumption density xm, through the enterprise's Manufacturing Execution System (MES). It extracts energy usage data of the production line, including energy consumption nx, energy carbon emission coefficient pf, energy conversion efficiency zh, and energy input ns, through the enterprise's Energy Management System (EMS). The environmental temperature wd during manufacturing is obtained through the Industrial Internet of Things platform (IIoT).

[0083] The data processing unit is used to perform data cleaning, time synchronization, and dimensionless processing on the acquired manufacturing data to obtain a production data set;

[0084] The production data set includes an energy efficiency production data set, a material thermal data set, and an energy efficiency data set;

[0085] The energy efficiency production data set includes energy consumption nx, equipment energy efficiency sn, and production speed sd;

[0086] The material thermal data set includes material consumption density xm, material processing time sj, and production temperature wd;

[0087] The energy efficiency data set includes energy carbon emission coefficient pf, energy conversion efficiency zh, and energy input nx;

[0088] The data storage unit is used to construct a data repository based on the data analysis system and input the acquired production data set into the data repository for storage in real time.

[0089] In this embodiment, the data acquisition unit is connected to the enterprise system through an API interface and extracts manufacturing data during the production process in real time through multiple channels such as the Manufacturing Execution System (MES), the Energy Management System (EMS), and the Industrial Internet of Things platform (IIoT). This multi-channel data collection method ensures the comprehensiveness and real-time nature of the data, providing a solid foundation for subsequent carbon emission analysis. The data processing unit further cleans, synchronizes the time, and performs dimensionless processing on the collected data to obtain a production data set, ensuring the consistency and accuracy of the data during the analysis process. In addition, the data storage unit stores the processed data in the database in real time, ensuring the security and efficient access of the data. Through these data management functions, the system can provide high-quality raw data for carbon emission assessment and support efficient and accurate real-time analysis, thereby helping enterprises monitor and optimize carbon emissions in real time during the production process and ultimately achieve the goals of green manufacturing and sustainable development.

[0090] Embodiment 3

[0091] This embodiment is an explanatory description based on Embodiment 2. Please refer to Figure 1, specifically: the production carbon emission analysis module includes an energy efficiency production analysis unit, a material thermal analysis unit, and an energy efficiency analysis unit;

[0092] The energy efficiency production analysis unit is used to perform summary calculations based on the obtained energy efficiency production data set, obtain the energy efficiency production mapping coefficient snx, and analyze the combined impact of production equipment energy efficiency and production speed on carbon emissions;

[0093] The energy efficiency production mapping coefficient snx is obtained through the following formula;

[0094]

[0095] In the formula, I represents the total types of production equipment, nx i represents the energy consumption input by the i-th type of production equipment, sn i represents the equipment energy efficiency of the i-th type of production equipment, exp represents the exponential decay function, k1 represents the impact index of production speed on carbon emissions, k2 represents the non-linear growth factor of production speed, the value ranges of k1 and k2 are set by the user, and sd0 represents the production speed under standard conditions;

[0096] The material thermal analysis unit is used to perform summary calculations based on the obtained material thermal data set, obtain the material thermal variation coefficient cxh, and analyze the combined impact of production temperature fluctuations on material consumption and processing time;

[0097] The material thermal variation coefficient cxh is obtained through the following formula;

[0098]

[0099] In the formula, M represents the total types of materials required, xm m represents the consumption density of the m-th type of material, tp represents the carbon emission coefficient of material consumption, which is obtained from the chemical properties of the material itself, sj m represents the processing time of the m-th type of material, wd0 represents the standard temperature of material processing, Δwd represents the temperature fluctuation during the production process, and exp represents the exponential decay function;

[0100] The energy efficiency analysis unit is used to perform summary calculations based on the obtained energy efficiency data set, obtain the energy efficiency emission response coefficient nxx, and analyze the carbon emission effects of different energy sources during production in terms of energy type and conversion efficiency;

[0101] The energy efficiency emission response coefficient nxx is obtained through the following formula;

[0102]

[0103] In the formula, J represents the total types of energy sources, pfj represents the carbon emission coefficient of the j-th type of energy, zh j represents the conversion efficiency of the j-th type of energy, ɑ j represents the adjustment coefficient of the consumption of the j-th type of energy, ns j represents the energy input of the j-th type of energy, ns 0，j represents the standard energy input of the j-th type of energy under standard conditions, and ln represents the standard logarithmic function.

[0104] In this embodiment, the energy efficiency production analysis unit reveals the comprehensive impact of production equipment energy efficiency and production speed on carbon emissions by calculating the energy efficiency production mapping coefficient snx, and then optimizes the equipment configuration and production speed settings to achieve the purpose of reducing carbon emissions. The material thermal analysis unit analyzes the combined impact of production temperature fluctuations on material consumption and processing time by calculating the material thermal variation coefficient cxh, thereby providing a theoretical basis for temperature control optimization in the production process and effectively reducing carbon emissions caused by temperature fluctuations. The energy efficiency analysis unit evaluates the impact of different energy types and conversion efficiencies on carbon emissions by calculating the energy efficiency emission response coefficient nxx, providing data support for enterprises in energy selection and optimizing energy conversion efficiency. The close cooperation of these three analysis units makes the carbon emission assessment in the production process more scientific and accurate, providing strong support for realizing green production and sustainable development, helping enterprises improve the overall production efficiency and resource utilization rate while reducing energy consumption and emissions.

[0105] Embodiment 4

[0106] This embodiment is an explanatory note based on Embodiment 3, please refer to Figure 1 , specifically: the production carbon emission assessment module includes a production carbon emission analysis unit and a production carbon emission assessment unit;

[0107] The production carbon emission analysis unit is used to perform a summary calculation based on the obtained energy efficiency production mapping coefficient snx, material thermal variation coefficient cxh, and energy efficiency emission response coefficient nxx, obtain the comprehensive production carbon emission index stp, and analyze the non-linear change of carbon emissions under the comprehensive influence of different factors;

[0108] The comprehensive production carbon emission index stp is obtained through the following formula;

[0109]

[0110] In the formula, a1 represents the influence coefficient of the energy efficiency production mapping coefficient snx on carbon emissions, a2 represents the influence coefficient of the material thermal variation coefficient cxh on carbon emissions, a3 represents the adjustment constant of energy consumption in total carbon emissions, and the value ranges of a1, a2, and a3 are set by the user, and exp represents the exponential decay function.

[0111] The production carbon emission assessment unit presets a carbon emission production standard threshold Z based on the carbon emission benchmark of the production industry, and conducts a preliminary production carbon emission assessment with the obtained comprehensive production carbon emission index stp to analyze whether the carbon emissions in the production process meet the standards. The specific assessment plan is as follows;

[0112] When the comprehensive production carbon emission index stp ≥ the carbon emission production standard threshold Z, the carbon emissions exceed the standard, and rectification measures are immediately taken;

[0113] When the comprehensive production carbon emission index stp < the carbon emission production standard threshold Z, the carbon emissions meet the standards. At this time, the carbon emissions during the operation of the produced air conditioners are further monitored.

[0114] In this embodiment, through the production carbon emission assessment module, the carbon emission level in the production process can be accurately evaluated, and the comprehensive production carbon emission index stp is calculated based on the comprehensive influence of different factors. This process not only considers the influence of the energy efficiency production mapping coefficient snx, the material thermal variation coefficient cxh, and the energy efficiency emission response coefficient nxx on carbon emissions, but also can analyze the non-linear changes of these factors, providing more detailed and accurate carbon emission predictions. Through the preliminary production carbon emission assessment with the preset carbon emission production standard threshold Z, the system can judge in real time whether the production process meets the environmental protection requirements. When the carbon emissions exceed the standard, the system can quickly trigger rectification measures to avoid excessive carbon emissions and ensure that the production activities meet the green development goals. This refined and dynamic carbon emission monitoring and assessment method improves the enterprise's capabilities in environmental protection compliance, carbon emission control, and production process optimization, helps the enterprise better achieve the sustainable development goals, and effectively reduces potential environmental protection risks and costs.

[0115] Embodiment 5

[0116] This embodiment is an explanatory description based on Embodiment 4. Please refer to Figure 1 , specifically: The operation analysis module includes an operation data acquisition unit and an operation carbon emission analysis unit;

[0117] The operation data acquisition unit is used to obtain the operation experiment data of the produced air conditioners by the manufacturer through the equipment management system EAM and the thermal management analysis software when the preliminary production carbon emission assessment shows that the carbon emissions meet the standards, and perform data cleaning, time synchronization, and dimensionless processing on the operation experiment data to obtain an operation data set;

[0118] The operation data set includes a load data set and an efficiency data set;

[0119] The load data set includes power consumption gl and a load factor fz;

[0120] The performance data group includes the running duration ys, the ambient temperature yw, the heat loss coefficient rs, the heat response coefficient rx, and the outer surface area wb.

[0121] The running carbon emission analysis unit is used to perform summary calculations based on the obtained load data group and performance data group respectively to obtain the load power index fgz and the air-conditioning performance index sbx. The specific formulas are as follows;

[0122]

[0123] In the formula, Q represents the total number of air conditioners produced, gl q represents the power consumption of the qth air conditioner, fz q represents the load factor of the qth air conditioner, gl q，d represents the power consumption of the qth air conditioner in the standby state, ys q represents the running duration of the qth air conditioner, Δyw represents the ambient temperature fluctuation, exp represents the exponential decay function, wb q represents the outer surface area of the qth air conditioner.

[0124] In this embodiment, the operation analysis module obtains the operation experiment data of the produced air conditioners through the equipment management system EAM and the thermal management analysis software. After data cleaning, time synchronization, and dimensionless processing, the operation data group is obtained, including the load data group and the performance data group, providing detailed and high-quality data support. The running carbon emission analysis unit calculates the load power index fgz and the air-conditioning performance index sbx based on these data, providing an accurate basis for the evaluation of the running carbon emissions of the air conditioner. This system can not only monitor the carbon emission qualification rate of the air conditioner but also adjust and optimize the energy efficiency of the air conditioner in real time according to the specific operation data. This refined data processing and real-time evaluation mechanism not only improve the environmental compliance of air-conditioning products, reduce the risks caused by unqualified carbon emissions, but also provide more efficient decision-making support for enterprises in energy conservation and emission reduction, further promoting the realization of green production and sustainable development.

[0125] Embodiment 6

[0126] This embodiment is an explanatory description based on Embodiment 5. Please refer to Figure 1 , specifically: The running carbon emission evaluation module includes a running carbon emission analysis unit and a running carbon emission evaluation unit;

[0127] The running carbon emission analysis unit is used to perform summary calculations based on the obtained load power index fgz and air-conditioning performance index sbx to obtain the running carbon emission index ytp, and analyze the comprehensive influence of different factors on the operation of the air conditioner;

[0128] The running carbon emission index ytp is calculated and obtained through the following formula;

[0129]

[0130] In the formula, b represents the adjustment coefficient of the influence of the relative proportional difference between the load power index fgz and the air-conditioning energy efficiency index sbx on the comprehensive carbon emissions, and ln represents the logarithmic function;

[0131] The operating carbon emissions assessment unit presets an operating carbon emissions threshold X based on the industry carbon emission standard, and conducts an air-conditioning operating carbon emissions assessment with the obtained operating carbon emissions index ytp, and generates corresponding decisions according to the assessment results. The specific assessment scheme is as follows;

[0132] When the operating carbon emissions index ytp < the operating carbon emissions threshold X, the operating carbon emissions meet the environmental protection standards, meet the environmental protection requirements, and can be put into use;

[0133] When the operating carbon emissions index ytp ≥ the operating carbon emissions threshold X, the operating carbon emissions do not meet the environmental protection standards. Mark the carbon emissions of this air-conditioning as unqualified and take rectification measures.

[0134] In this embodiment, through the comprehensive implementation of the operating carbon emissions assessment module, the system can accurately analyze and real-time evaluate the operating carbon emissions level of the air-conditioning, so as to ensure that the air-conditioning products meet the environmental protection requirements during use. The operating carbon emissions analysis unit calculates the operating carbon emissions index ytp through the summary calculation of the load power index fgz and the air-conditioning energy efficiency index sbx, and further improves the accuracy of the assessment by considering the comprehensive influence of different factors through the adjustment coefficient b. The operating carbon emissions assessment unit compares the preset operating carbon emissions threshold X with the operating carbon emissions index ytp according to the industry standard to generate a real-time assessment result. This accurate carbon emissions assessment mechanism ensures the environmental protection compliance of air-conditioning products, thereby reducing the carbon emissions risk, improving the production efficiency, and enhancing the overall market competitiveness and sustainable development ability of the products.

[0135] Embodiment 7

[0136] Please refer to Figure 2 , A method for managing urban area carbon emission data based on big data, including the following steps:

[0137] S1. Construct a data analysis system, establish a communication connection with the enterprise system through the API interface, obtain manufacturing data in real time, and perform preprocessing to obtain a production data group;

[0138] S2. Perform summary calculation based on the obtained production data group to obtain the energy efficiency production mapping coefficient snx, the material thermal variation coefficient cxh, and the energy efficiency emission response coefficient nxx;

[0139] S3. Based on the obtained energy efficiency production mapping coefficient snx, material thermal variation coefficient cxh, and energy efficiency emission response coefficient nxx, perform a summary calculation to obtain the comprehensive production carbon emission index stp, and conduct a preliminary production carbon emission assessment with the preset carbon emission production standard threshold Z;

[0140] S4. When the preliminary production carbon emission assessment indicates that the carbon emissions meet the standards, extract the operation experimental data of the produced air conditioner through the data analysis system, perform preprocessing to obtain the operation data set, and then perform a summary calculation based on the operation data set to obtain the load power index fgz and the air conditioner efficiency index sbx;

[0141] S5. Based on the obtained load power index fgz and air conditioner efficiency index sbx, perform a summary calculation to obtain the operation carbon emission index ytp, and conduct an air conditioner operation carbon emission assessment with the preset operation carbon emission threshold X.

[0142] Although the embodiments of the present invention have been shown and described, for those of ordinary skill in the art, it can be understood that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. The urban area carbon emission data management system based on big data is characterized by: It includes production data acquisition module, production carbon emission analysis module, production carbon emission assessment module, operation analysis module and operation carbon emission assessment module; The production data acquisition module is used to build a data analysis system and establish a communication connection with the enterprise system through an API interface to acquire manufacturing data in real time and perform preprocessing to obtain a production data group; The production carbon emission analysis module is used to perform summary calculations based on the acquired production data group to obtain the energy efficiency capacity mapping coefficient snx, the material thermal variation coefficient cxh and the energy efficiency emission response coefficient nxx; The production carbon emission assessment module is used to perform summary calculations based on the obtained energy efficiency capacity mapping coefficient snx, material thermal variation coefficient cxh and energy efficiency emission response coefficient nxx, obtain the comprehensive production carbon emission index stp, and perform preliminary production carbon emission assessment with the preset carbon emission production standard threshold Z; The operation analysis module is used to extract the operation experimental data of the production air conditioner through the data analysis system when the preliminary production carbon emission assessment shows that the carbon emission meets the standard, and perform preprocessing to obtain the operation data group, and then perform summary calculation based on the operation data group to obtain the load power index fgz and the air conditioner efficiency index sbx; The operation carbon emission assessment module is used to perform summary calculation based on the obtained load power index fgz and air conditioning efficiency index sbx, obtain the operation carbon emission index ytp, and perform air conditioning operation carbon emission assessment with the preset operation carbon emission threshold value X.

2. The urban area carbon emission data management system based on big data according to claim 1 is characterized by: The production data acquisition module includes a data acquisition unit, a data processing unit and a data storage unit; The data acquisition unit is used to build a data analysis system and establish a communication connection with the enterprise system through an API interface to extract the enterprise's manufacturing data in real time; The enterprise system includes the manufacturing execution system MES, the energy management system EMS and the industrial Internet of Things platform IIoT.

3. The urban area carbon emission data management system based on big data according to claim 2 is characterized by: The data processing unit is used to perform data cleaning, time synchronization and dimensionless processing on the acquired manufacturing data to obtain a production data group; The production data group includes an energy efficiency and production capacity data group, a material thermal data group and an energy efficiency data group; The energy efficiency and production capacity data group includes energy consumption nx, equipment energy efficiency sn and production speed sd; The material thermal data set includes material consumption density xm, material processing time sj and production temperature wd; The energy efficiency data set includes energy carbon emission coefficient pf, energy conversion efficiency zh and energy input nx; The data storage unit is used to construct a data storage repository according to the data analysis system, and input the acquired production data group into the data storage repository in real time for storage.

4. The urban area carbon emission data management system based on big data according to claim 3 is characterized by: The production carbon emission analysis module includes an energy efficiency and capacity analysis unit, a material thermal analysis unit and an energy efficiency analysis unit; The energy efficiency and capacity analysis unit is used to perform summary calculations based on the acquired energy efficiency and capacity data group, obtain the energy efficiency and capacity mapping coefficient snx, and analyze the combined impact of production equipment energy efficiency and production speed on carbon emissions; The energy efficiency and capacity mapping coefficient snx is calculated and obtained by the following formula: In the formula, I represents the total types of production equipment, nx i represents the energy consumption of the input of the i-th production equipment, sn i represents the equipment energy efficiency of the i-th type of production equipment, exp represents the exponential decay function, k1 represents the impact index of production speed on carbon emissions, k2 represents the nonlinear growth factor of production speed, the value range of k1 and k2 is set by the user, and sd0 represents the production speed under standard conditions; The material thermal analysis unit is used to perform summary calculations based on the acquired material thermal data group, obtain the material thermal variation coefficient cxh, and analyze the combined impact of production temperature fluctuations on material consumption and processing time; The material thermal variation coefficient cxh is calculated by the following formula: In the formula, M represents the total type of materials required, xm m represents the consumption density of the mth material, tp represents the carbon emission coefficient of material consumption, which is obtained from the chemical properties of the material itself, and sj m represents the processing time of the mth material, wd0 represents the standard temperature of material processing, Δwd represents the temperature fluctuation during the production process, and exp represents the exponential decay function; The energy efficiency analysis unit is used to perform summary calculations based on the acquired energy efficiency data group, obtain the energy efficiency emission response coefficient nxx, and analyze the carbon emission effects of energy types and conversion efficiencies on different energy sources in the production process; The energy efficiency emission response coefficient nxx is calculated and obtained by the following formula: Where J represents the total type of energy, pf j represents the carbon emission coefficient of the jth energy source, zh j represents the conversion efficiency of the jth energy source, ɑ j represents the adjustment coefficient of the j-th energy consumption, ns j represents the energy input of the jth energy source, ns 0，j It represents the standard energy input of the j-th energy under standard conditions, and ln represents the standard logarithmic function.

5. The urban area carbon emission data management system based on big data according to claim 4 is characterized by: The production carbon emission assessment module includes a production carbon emission analysis unit and a production carbon emission assessment unit; The production carbon emission analysis unit is used to perform summary calculations based on the obtained energy efficiency capacity mapping coefficient snx, material thermal variation coefficient cxh and energy efficiency emission response coefficient nxx, obtain the comprehensive production carbon emission index stp, and analyze the nonlinear changes of carbon emissions under the combination of different factors; The comprehensive production carbon emission index stp is calculated by the following formula: In the formula, a1 represents the influence coefficient of the energy efficiency capacity mapping coefficient snx on carbon emissions, a2 represents the influence coefficient of the material thermal variation coefficient cxh on carbon emissions, a3 represents the adjustment constant of energy consumption in total carbon emissions, the value range of a1, a2 and a3 is set by the user, and exp represents the exponential decay function.

6. The urban area carbon emission data management system based on big data according to claim 5 is characterized by: The production carbon emission assessment unit presets the carbon emission production standard threshold Z based on the production industry carbon emission benchmark, and performs a preliminary production carbon emission assessment with the obtained comprehensive production carbon emission index stp to analyze whether the carbon emissions in the production process meet the standards. The specific assessment plan is as follows; When the comprehensive production carbon emission index stp ≥ the carbon emission production standard threshold Z, the carbon emission exceeds the standard and corrective measures are taken immediately; When the comprehensive production carbon emission index stp is less than the carbon emission production standard threshold Z, the carbon emissions meet the standards. At this time, the air conditioners produced are further monitored for carbon emissions from air conditioning operation.

7. The urban area carbon emission data management system based on big data according to claim 6 is characterized by: The operation analysis module includes an operation data acquisition unit and an operation carbon emission analysis unit; The operation data acquisition unit is used to obtain the manufacturer's operation test data of the production air conditioner through the equipment management system EAM and thermal management analysis software when the preliminary production carbon emission assessment shows that the carbon emission meets the standard, and perform data cleaning, time synchronization and dimensionless processing on the operation test data to obtain the operation data group; The operation data group includes a load data group and an efficiency data group; The load data set includes power consumption gl and load factor fz; The performance data set includes operating time ys, ambient temperature yw, heat loss coefficient rs, thermal response coefficient rx and external surface area wb.

8. The urban area carbon emission data management system based on big data according to claim 7 is characterized by: The operation carbon emission analysis unit is used to perform summary calculations based on the acquired load data group and efficiency data group to obtain the load power index fgz and the air conditioning efficiency index sbx. The specific formula is as follows: Where Q represents the total number of air conditioners produced, gl q represents the power consumption of the qth air conditioner, fz q represents the load factor of the qth air conditioner, gl q，d represents the power consumption of the qth air conditioner in standby mode, d represents the air conditioner standby symbol, ys q represents the operating time of the qth air conditioner, Δyw represents the ambient temperature fluctuation, exp represents the exponential decay function, and wb q Represents the external surface area of ​​the qth air conditioner.

9. The urban area carbon emission data management system based on big data according to claim 8 is characterized by: The operation carbon emission assessment module includes an operation carbon emission analysis unit and an operation carbon emission assessment unit; The operation carbon emission analysis unit is used to perform summary calculation based on the obtained load power index fgz and air conditioning efficiency index sbx, obtain the operation carbon emission index ytp, and analyze the comprehensive impact of different factors on the air conditioning operation; The operation carbon emission index ytp is calculated and obtained by the following formula: In the formula, b represents the adjustment coefficient of the relative proportion difference between the load power index fgz and the air conditioning efficiency index sbx on the comprehensive carbon emissions, and ln represents the logarithmic function; The operation carbon emission assessment unit presets the operation carbon emission threshold value X based on the industry carbon emission standard, and performs air conditioning operation carbon emission assessment with the obtained operation carbon emission index ytp, and generates corresponding decisions based on the assessment results. The specific assessment scheme is as follows; When the operating carbon emission index ytp < the operating carbon emission threshold X, the operating carbon emission meets the environmental protection standards and requirements and can be put into use; When the operating carbon emission index ytp ≥ the operating carbon emission threshold X, the operating carbon emission does not meet the environmental protection standards, the air conditioner is marked as unqualified in carbon emission, and corrective measures are taken.

10. A method for managing urban area carbon emission data based on big data, applied to the urban area carbon emission data management system based on big data according to any one of claims 1 to 9, characterized in that: The following steps are involved: S1. Build a data analysis system and establish a communication connection with the enterprise system through the API interface to obtain manufacturing data in real time and perform preprocessing to obtain production data groups; S2. Perform summary calculation based on the obtained production data group to obtain the energy efficiency capacity mapping coefficient snx, the material thermal variation coefficient cxh and the energy efficiency emission response coefficient nxx; S3. Based on the obtained energy efficiency capacity mapping coefficient snx, material thermal variation coefficient cxh and energy efficiency emission response coefficient nxx, a summary calculation is performed to obtain the comprehensive production carbon emission index stp, and a preliminary production carbon emission assessment is performed with the preset carbon emission production standard threshold Z; S4. When the preliminary production carbon emission assessment shows that the carbon emission meets the standard, the operation experimental data of the production air conditioner is extracted through the data analysis system, and pre-processed to obtain the operation data group, and then the operation data group is summarized and calculated to obtain the load power index fgz and the air conditioner efficiency index sbx; S5. Perform summary calculation based on the obtained load power index fgz and air conditioning efficiency index sbx to obtain the operation carbon emission index ytp, and evaluate the air conditioning operation carbon emission with the preset operation carbon emission threshold X.

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