Carbon footprint dynamic accounting system for multi-source emission data

Abstract

The invention is suitable for the technical field of carbon emission monitoring and carbon footprint accounting, and provides a multi-source emission data-oriented carbon footprint dynamic accounting system, which comprises a data acquisition module, a compensation energy consumption index generation module, an abnormal temperature fluctuation identification module and a correction coefficient generation module, the sample selection module is used for acquiring initial carbon factor parameters when a target factory processes a current dairy product under the condition that the plate heat exchanger with the improved structure is adopted, extracting historical processing data of the target factory, and selecting a plurality of processing samples corresponding to the current dairy product and based on the process condition of the plate heat exchanger before improvement from the historical processing data. According to the method, a carbon factor dynamic correction mechanism based on the heat sealing section temperature fluctuation behavior is constructed, and the traditional static accounting mode that expected efficiency is improved only according to the structure of the plate heat exchanger, and carbon factor parameters are directly set is broken through.

Description

Technical Field

[0001] This invention belongs to the field of carbon emission monitoring and carbon footprint accounting technology, and in particular relates to a dynamic carbon footprint accounting system for multi-source emission data. Background Technology

[0002] With the continuous development of carbon emission tracking and carbon footprint accounting technologies, more and more manufacturing enterprises are beginning to pay attention to the energy consumption performance and corresponding carbon emission intensity of each stage of the production process. Taking the dairy processing stage as an example, the heat sealing stage is a key node for packaging sealing, and the stability of its temperature control is directly related to the product's sealing performance and quality safety. Since the heat source supply in the heat sealing process is usually affected by the output heat medium state of the preceding heat treatment equipment (such as plate heat exchangers), if the heat exchanger's response characteristics are lagging or the heat distribution is uneven, there is a certain probability that temperature fluctuations will occur in the heat sealing stage, which will lead to additional energy consumption behaviors such as rework and compensatory heating, resulting in an increase in carbon emissions per unit product.

[0003] To address the aforementioned issues, current mainstream carbon footprint accounting methods largely rely on the improved heat exchange efficiency resulting from heat exchanger structural improvements. Combined with equipment metering and process design data, a static unit product carbon emission factor (i.e., initial carbon factor parameter) is preset as the basic input for carbon labeling, carbon quota management, and energy conservation assessment. This method is relatively mature in engineering implementation and is suitable for quantitatively reflecting the direct energy consumption reduction brought about by the improvement in the thermal efficiency of the heat exchange equipment itself. However, the above accounting methods typically neglect the systemic synergistic effects of structural improvements, particularly failing to consider their optimization effect on the temperature fluctuation behavior of the heat-sealing section and their indirect carbon emission reduction effects.

[0004] In fact, the improved plate heat exchanger structure, due to its faster heat exchange response and enhanced heat transfer medium output stability, not only improves its own energy efficiency but also effectively mitigates temperature fluctuations in the heat-sealing section. This significantly reduces quality control measures such as temporary compensation heating, setting temperature adjustments, or product rework caused by these fluctuations. If the initial carbon factor, which does not incorporate these indirect effects, is still used for calculation, it may underestimate the effectiveness of the improvements, resulting in an inflated unit carbon emission level for the product. This is detrimental to the true representation of the value of process optimization and also affects the fairness of accounting and emission credit for enterprises in carbon footprint compliance, carbon trading participation, and carbon label competition. Summary of the Invention

[0005] The purpose of this invention is to provide a dynamic carbon footprint accounting system for multi-source emission data, aiming to solve the problems mentioned in the background art.

[0006] This invention is implemented as follows: a dynamic carbon footprint accounting system for multi-source emission data, the system comprising a data acquisition module, a compensation energy consumption index generation module, an abnormal temperature fluctuation identification module, and a correction coefficient generation module, wherein:

[0007] The data acquisition module is used to acquire the initial carbon factor parameters of the target factory when processing the current dairy products under the condition of using the structurally improved plate heat exchanger, and to extract the historical processing data of the target factory, and select several processing samples corresponding to the current dairy products and based on the process conditions of the plate heat exchanger before the improvement.

[0008] The energy consumption compensation index generation module is used to extract quality control operation information after abnormal temperature fluctuations occur in the heat sealing section for each processed sample, and generate an energy consumption index reflecting the impact of compensatory carbon emissions based on the quality control operation information.

[0009] The difference magnitude identification module is used to determine the temperature change of the heat-sealing section during the current processing, and compare it with the average temperature change of the processed sample to identify the difference magnitude of the current abnormal temperature fluctuation compared with the historical benchmark.

[0010] The correction coefficient generation module is used to generate correction coefficients based on energy consumption indicators and difference magnitudes, and to use these correction coefficients to correct the initial carbon factor parameters in order to obtain the final carbon factor parameters corresponding to the current processing.

[0011] As a further limitation of the technical solution of the present invention, the initial carbon factor parameter is a carbon emission benchmark factor calculated based on the expected improvement in thermal efficiency set after the improvement of the plate heat exchanger structure, according to the unit product processing capacity.

[0012] As a further limitation of the technical solution of the present invention, the historical dairy products in the processing sample are consistent with the background information of the target factory processing the current dairy products under the condition of using the structurally improved plate heat exchanger. The background information includes dairy product type, formula composition, target filling volume, preheating temperature set value, and environmental temperature and humidity data corresponding to the process batch.

[0013] As a further limitation of the technical solution of the present invention, the heat sealing section is a heating process section used for packaging and sealing dairy products. Its temperature control stability directly affects the requirements for heat treatment uniformity and sealing integrity in the product quality control process. The heat source required for the heat sealing section is provided by a plate heat exchanger. After the plate heat exchanger structure is improved, its heat exchange response characteristics change, thereby affecting the abnormal temperature fluctuation characteristics of the heat sealing section.

[0014] As a further limitation of the technical solution of this embodiment of the invention, the energy consumption compensation index generation module specifically includes:

[0015] The abnormal temperature fluctuation identification unit is used to analyze each processed sample, extract the temperature monitoring data of the dairy products after they entered the heat sealing stage after being processed by the plate heat exchanger before the structural improvement, and determine whether there is an abnormal temperature fluctuation phenomenon by analyzing the fluctuation amplitude of the temperature sequence and comparing it with the set threshold.

[0016] The quality control information extraction unit is used to obtain the quality control operation information corresponding to the processed sample with abnormal temperature fluctuations. The quality control operation information includes one or more of the following: temporary setting adjustment of heat sealing temperature, additional heating time, and rework ratio of the corresponding batch of dairy products.

[0017] The energy consumption index generation unit is used to generate energy consumption indexes that reflect the impact of compensatory carbon emissions based on the additional energy consumption parameters introduced by each operation in the above-mentioned quality control operation information.

[0018] As a further limitation of the technical solution of the present invention, in the abnormal temperature fluctuation identification unit, when the temperature change amplitude of the temperature monitoring data of the heat-sealing section exceeds the preset fluctuation threshold in any continuous time period, and the duration of the fluctuation exceeds the preset duration threshold, it is determined that there is an abnormal temperature fluctuation in the heat-sealing section of the processed sample.

[0019] As a further limitation of the technical solution of this embodiment of the invention, the difference amplitude recognition module specifically includes:

[0020] The heat-sealing section temperature extraction unit is used to acquire temperature monitoring data of the current dairy product after entering the heat-sealing section through the plate heat exchanger with improved structure, and calculate the corresponding temperature fluctuation amplitude index based on the combination characteristics of temperature change amplitude and duration; at the same time, it extracts the heat-sealing section temperature monitoring data of each processed sample, calculates its temperature fluctuation amplitude index in the same way, and then calculates the average value of the temperature fluctuation amplitude index of all historical samples as a historical benchmark.

[0021] The fluctuation difference quantification unit is used to compare the numerical difference between the current temperature fluctuation amplitude index and the historical benchmark to identify the difference magnitude of the current abnormal temperature fluctuation compared to the historical benchmark.

[0022] As a further limitation of the technical solution of this embodiment of the invention, in the fluctuation difference quantification unit, the difference between the current temperature fluctuation amplitude index and the historical benchmark is calculated by means of relative difference ratio or normalized offset. The normalized offset is the difference between the current temperature fluctuation amplitude index and the historical benchmark divided by the historical benchmark, which is used to quantify the relative deviation of the current processing process in the temperature stability of the heat sealing section.

[0023] As a further limitation of the technical solution of this embodiment of the invention, the correction coefficient generation module specifically includes:

[0024] The correction factor generation unit is used to calculate the average value of the energy consumption index of all processing samples with abnormal temperature fluctuations in the heat-sealing section, and multiply the average energy consumption index by the difference amplitude, and combine it with the preset control amplitude coefficient to generate a correction coefficient.

[0025] The parameter correction unit is used to correct the initial carbon factor parameters using the correction coefficient to obtain the final carbon factor parameters corresponding to the current processing.

[0026] As a further limitation of the technical solution of the present invention, the final carbon factor parameter is used in the whole-process carbon emission monitoring system of the target factory as the basis for dynamically adjusting the input parameters of the emission accounting model, and is further used to guide the carbon emission accounting of product units, evaluate the effectiveness of process energy-saving transformation, formulate carbon emission reduction strategies, or provide quantitative support for enterprises to participate in carbon management activities such as carbon quota trading, carbon label certification and carbon footprint compliance declaration.

[0027] Compared with the prior art, the present invention has the following beneficial effects:

[0028] This invention overcomes the traditional static calculation method of directly setting carbon factor parameters based solely on the expected performance of plate heat exchanger structural improvements by constructing a dynamic correction mechanism for the carbon factor based on the temperature fluctuation behavior of the heat-sealing section. By extracting the compensating energy consumption behavior when abnormal fluctuations exist before structural improvement, calculating its energy consumption index, and combining it with the temperature fluctuation difference amplitude during the current processing, a correction coefficient reflecting the actual improvement effect is generated, thereby achieving precise dynamic adjustment of the initial carbon factor.

[0029] This scheme can accurately reflect the degree of carbon emission improvement brought about by structural improvements, enhance the adaptability and credibility of carbon footprint accounting, and provide scientific and quantitative support for the evaluation of process optimization effectiveness, carbon label application and carbon trading, thus having significant application value. Attached Figure Description

[0030] Figure 1 Application architecture diagram of the system provided in the embodiments of the present invention;

[0031] Figure 2 This is a structural block diagram of the energy consumption compensation index generation module in the system provided in the embodiments of the present invention;

[0032] Figure 3 This is a structural block diagram of the difference amplitude recognition module in the system provided in the embodiments of the present invention;

[0033] Figure 4 This is a structural block diagram of the correction coefficient generation module in the system provided in the embodiment of the present invention. Detailed Implementation

[0034] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0035] Figure 1 An application architecture diagram of the system provided in an embodiment of the present invention is shown.

[0036] In another preferred embodiment of the present invention, a dynamic carbon footprint accounting system for multi-source emission data includes:

[0037] The data acquisition module 100 is used to acquire the initial carbon factor parameters of the target factory when processing the current dairy products under the condition of using the structurally improved plate heat exchanger, and to extract the historical processing data of the target factory, and select several processing samples corresponding to the current dairy products and based on the process conditions of the plate heat exchanger before the improvement.

[0038] The initial carbon factor parameter is a carbon emission baseline factor calculated based on the expected increase in thermal efficiency after the improvement of the plate heat exchanger structure, according to the unit product throughput.

[0039] The historical dairy products in the processing sample are consistent with the background information of the target factory processing the current dairy products under the condition of using the structurally improved plate heat exchanger. The background information includes dairy product type, formula composition, target filling volume, preheating temperature setpoint, and ambient temperature and humidity data corresponding to the process batch.

[0040] The heat-sealing section is a heating process section used for packaging and sealing dairy products. Its temperature control stability directly affects the requirements for heat treatment uniformity and sealing integrity in the product quality control process. The heat source required for the heat-sealing section is provided by a plate heat exchanger. After the plate heat exchanger structure is improved, its heat exchange response characteristics change, thereby affecting the abnormal temperature fluctuation characteristics of the heat-sealing section.

[0041] In this embodiment of the invention, the target factory typically refers to a modern processing plant equipped with dairy production lines, capable of standardized heating, filling, and sealing of different types of dairy products, and possessing a relatively complete equipment data acquisition system and process traceability capabilities. Dairy products include, but are not limited to, pasteurized milk, fermented milk, flavored milk, and milk-containing beverages, which require heating and sealing. Their composition, packaging methods, and process parameters typically need to remain stable to ensure consistent quality.

[0042] Plate heat exchangers are heating devices that exchange heat through fluid channels between multiple sets of metal plates. In the dairy industry, they are commonly used in processes such as raw material preheating, sterilization, and heating of heat-sealing sections. Their advantages include compact structure, high heat exchange efficiency, and precise temperature profile control. Structural improvements typically refer to optimizing the plate shape, flow channel arrangement, heat exchange area, material, or flow velocity control system of the plate heat exchanger to improve overall thermal efficiency, save energy and reduce emissions, or increase process response speed. Such structural improvements have been applied in existing technologies, such as adjusting the corrugated structure of the plates to optimize turbulence; however, their subsequent dynamic impact on process control lacks sufficient modeling and feedback mechanisms.

[0043] The purpose of this invention is to address the issue that, prior to structural improvements in plate heat exchangers, their heat exchange response characteristics may exhibit hysteresis or instability, particularly in the heat-sealing stage of dairy product filling processes. This can easily lead to uncertain temperature fluctuations, affecting seal integrity and heat treatment uniformity. To ensure product quality, factories typically need to implement compensatory operations such as rework, extended heating times, or adjustments to set temperatures, which incur additional carbon emissions.

[0044] After structural improvements, the thermal response capability of the plate heat exchanger is enhanced, temperature fluctuations in the heat-sealing section are effectively suppressed, and the necessity for quality control compensation is significantly reduced. Therefore, the actual carbon emission level of processing dairy products under the same background information conditions should be lower.

[0045] However, most existing carbon emission accounting models are based solely on the expected improvement in theoretical thermal efficiency after structural improvements, directly setting lower carbon emission factors. They fail to fully consider the actual existence of compensation behavior under historical operating conditions before the improvements and its impact on carbon emissions, which may lead to an underestimation or overestimation of the extent of carbon footprint improvement, affecting the accuracy and fairness of the accounting.

[0046] This invention constructs a dynamic accounting mechanism based on historical data to identify the carbon emission intensity corresponding to abnormal temperature fluctuations and compensation behaviors before structural improvements. After improvements, it generates a correction coefficient based on the fluctuation difference amplitude and dynamically adjusts the initial carbon factor parameters, thereby achieving a carbon footprint assessment that is more in line with actual operating conditions.

[0047] Historical processing data originates from complete production batch records archived in the target factory's production information system. This data primarily includes the following types: dairy product type, formula composition, batch-specific heat exchanger parameter settings, heat-sealing section temperature monitoring sequences, process settings and actual execution data, energy consumption metering information, rework or heating adjustment records, filling weight, and quality inspection results. Based on this historical data, a complete historical processing dataset can be constructed. All data required for the implementation of subsequent technical solutions can be directly extracted from this historical processing data. Furthermore, the relevant data acquisition methods are widely used in existing industrial information management systems, representing a mature data collection and archiving mechanism in current technology.

[0048] The initial carbon factor parameter refers to the unit product carbon emission factor calculated based on the design expectations of the target plant after implementing heat exchanger structural improvements. It is commonly found in carbon footprint accounting standards, such as PAS 2050 and ISO 14067, which measure emissions throughout the product's life cycle. In practice, the standard carbon emission value per unit of dairy product can be calculated through equipment metering systems and energy management platforms. This parameter has mature usage methods in existing technologies and is often used as basic input data for carbon labeling assessment and carbon quota management. It should be noted that in this invention, this parameter is only used to characterize the carbon emission behavior of dairy products in a specific process segment from the heat exchanger outlet to the end of the heat sealing section, and does not cover all emission sources throughout the entire production process.

[0049] The purpose of selecting historical treatment samples is to provide a set of comparative data for the current treatment process before structural improvements, but with consistent background information. This sample set can effectively help identify the degree of process fluctuations caused by the improvement measures and provide a basis for subsequent adjustments to the carbon factor parameters.

[0050] The heat-sealing section plays a crucial role in the dairy product processing, sealing containers after filling. It uses heating to create a stable thermal bond in the sealing area, a key process for ensuring product sealing, preventing secondary contamination, and extending shelf life. Because heat-sealing quality is highly dependent on the uniformity and accuracy of temperature control, the plate heat exchanger before structural improvements may exhibit lag or fluctuations in response speed and heat distribution, easily leading to localized overheating or temperature instability in the heat-sealing section, resulting in rework or quality fluctuations. After structural improvements, the heat exchange efficiency and response characteristics of the plate heat exchanger are significantly optimized, effectively suppressing temperature fluctuations in the heat-sealing section and greatly reducing the probability of triggering related quality control operations, thus leading to lower actual carbon emissions. Therefore, this invention, from a system modeling perspective, incorporates the temperature fluctuation behavior of the heat-sealing section into the dynamic carbon emission accounting logic. Based on historical sample comparative analysis, it accurately reflects the actual difference between the process performance after structural improvements and carbon factors, constructing a carbon footprint assessment mechanism that more closely reflects real-world operating conditions.

[0051] Furthermore, the carbon footprint dynamic accounting system for multi-source emission data also includes:

[0052] The energy consumption compensation index generation module 200 is used to extract quality control operation information after abnormal temperature fluctuations occur in the heat sealing section for each processed sample, and generate an energy consumption index reflecting the impact of compensatory carbon emissions based on the quality control operation information.

[0053] Specifically, Figure 2 The diagram shows the structural block diagram of the energy consumption compensation index generation module 200 in the system provided in the embodiment of the present invention.

[0054] In a preferred embodiment provided by the present invention, the energy consumption compensation index generation module 200 specifically includes:

[0055] The abnormal temperature fluctuation identification unit 201 is used to analyze each processed sample, extract the temperature monitoring data of the dairy products after they have been processed by the plate heat exchanger before the structural improvement and entered the heat sealing stage, and determine whether there is an abnormal temperature fluctuation phenomenon by analyzing the fluctuation amplitude of the temperature sequence and setting a threshold for comparison.

[0056] The quality control information extraction unit 202 is used to obtain the quality control operation information corresponding to the processed sample with abnormal temperature fluctuations. The quality control operation information includes one or more of the following: temporary setting adjustment of heat sealing temperature, additional heating time, and rework processing ratio of the corresponding batch of dairy products.

[0057] The energy consumption index generation unit 203 is used to generate an energy consumption index that reflects the impact of compensatory carbon emissions based on the additional energy consumption parameters introduced by each operation in the above-mentioned quality control operation information.

[0058] In the abnormal temperature fluctuation identification unit 201, when the temperature change amplitude of the temperature monitoring data of the heat-sealing section exceeds the preset fluctuation threshold in any continuous time period, and the duration of the fluctuation exceeds the preset duration threshold, it is determined that there is an abnormal temperature fluctuation in the heat-sealing section of the processed sample.

[0059] In this embodiment of the invention, each step in the energy consumption compensation index generation module 200 is implemented using the following technical means, and has clear technical significance and functional logic:

[0060] The abnormal temperature fluctuation identification unit 201 calls upon the continuous temperature sampling sequence of the heat-sealed section recorded in the temperature monitoring submodule. Based on pre-set fluctuation amplitude and duration thresholds, it uses sliding window analysis and rate of change statistics techniques to calculate the temperature fluctuation amplitude index within a continuous time period. Further, combining historical engineering experience or standard process settings, it marks situations where the fluctuation amplitude exceeds a preset value and the duration exceeds a set threshold as abnormal fluctuation events. This identification process does not rely on external sensors or new equipment; it is completed based on data collected from the existing temperature control system, exhibiting good deployability.

[0061] The technical significance of identifying abnormal temperature fluctuations lies in the fact that these phenomena often originate from the unstable structural response characteristics of plate heat exchangers, such as heat transfer delays, localized temperature deviations, or uneven heat transfer, causing the heat-sealing section to fail to quickly reach or maintain the target temperature. Such fluctuations, caused by structural deficiencies, directly affect sealing quality, triggering subsequent quality control compensation measures. Therefore, identifying these fluctuations not only reflects the conductive impact of plate heat exchanger performance on the downstream heat-sealing section but also provides a crucial criterion for subsequent dynamic correction of carbon emissions.

[0062] The quality control information extraction unit 202 retrieves adjustment behavior logs corresponding to the abnormal fluctuation period based on the operation records archived in the target factory's information management system or MES system. This includes heating parameter change instruction records, rework batch identification data, and system heating energy consumption cumulative logs. By setting keyword screening and time period alignment mechanisms, the system can automatically extract the details of compensation operations performed on that batch of products, ensuring data matching and completeness.

[0063] The energy consumption index generation unit 203 utilizes the extracted quality control behaviors and combines them with a preset operation-energy consumption comparison table, such as the energy consumption value corresponding to unit heating time and the energy consumption estimation function corresponding to rework batches, to cumulatively compensate for the energy consumption value corresponding to each operation. It then generates a compensatory carbon emission index for the abnormal temperature fluctuations during the batch processing. This index not only quantifies the carbon burden caused by the insufficient structural performance of the plate heat exchanger but also provides basic reference data for subsequent comparative analysis and factor correction after improvements.

[0064] Furthermore, the carbon footprint dynamic accounting system for multi-source emission data also includes:

[0065] The difference magnitude identification module 300 is used to determine the temperature change of the heat-sealing section during the current processing, and compare it with the average temperature change of the processed sample to identify the difference magnitude of the current abnormal temperature fluctuation compared with the historical benchmark.

[0066] Specifically, Figure 3 A structural block diagram of the difference amplitude recognition module 300 in the system provided by an embodiment of the present invention is shown.

[0067] In a preferred embodiment of the present invention, the difference amplitude recognition module 300 specifically includes:

[0068] The heat-sealing section temperature extraction unit 301 is used to acquire the temperature monitoring data of the current dairy product after entering the heat-sealing section through the plate heat exchanger with improved structure, and calculate the corresponding temperature fluctuation amplitude index based on the combination characteristics of temperature change amplitude and duration; at the same time, it extracts the heat-sealing section temperature monitoring data of each processed sample, calculates its temperature fluctuation amplitude index in the same way, and then calculates the average value of the temperature fluctuation amplitude index of all historical samples as a historical benchmark.

[0069] The fluctuation difference quantification unit 302 is used to compare the numerical difference between the current temperature fluctuation amplitude index and the historical benchmark in order to identify the difference amplitude of the current abnormal temperature fluctuation compared to the historical benchmark.

[0070] In the fluctuation difference quantification unit 302, the difference between the current temperature fluctuation amplitude index and the historical benchmark is calculated by using the relative difference ratio or normalized offset. The normalized offset is the difference between the current temperature fluctuation amplitude index and the historical benchmark divided by the historical benchmark, which is used to quantify the relative deviation of the current processing process in the temperature stability of the heat sealing section.

[0071] In this embodiment of the invention, the two functional units in the difference amplitude identification module 300, the heat-sealing section temperature extraction unit 301 and the fluctuation difference quantification unit 302, are implemented using the following specific methods, and have good engineering feasibility:

[0072] The heat-sealing section temperature extraction unit 301 collects real-time temperature monitoring sequences under the conditions of the improved plate heat exchanger by calling temperature sensor data configured in the dairy product heat-sealing process. This unit extracts each continuous temperature sample based on a sliding window mechanism and constructs a temperature fluctuation amplitude index using a joint amplitude calculation and duration analysis algorithm. Specifically, it obtains the temperature change amplitude by calculating the difference between the maximum and minimum values ​​within any continuous time interval; simultaneously, it records the duration of this fluctuation amplitude to eliminate misjudgments of short-term fluctuations. This temperature fluctuation amplitude index reflects the temperature control stability of the current heat-sealing section during operation. The same method is also applicable to the temperature sequence processing of historical samples, ultimately yielding a set of fluctuation amplitude indices for all historical samples, and calculating their average value as a statistically stable historical benchmark.

[0073] The fluctuation difference quantification unit 302 performs mathematical quantification on the relative difference between the current batch and the historical baseline based on the aforementioned temperature fluctuation amplitude index. This embodiment introduces a normalized offset calculation method, which involves subtracting the historical average baseline value from the current fluctuation amplitude index and then dividing by the baseline value to obtain the difference amplitude ratio. This ratio is scale-independent, facilitating unified comparison and identification of data across product categories or different factories. Simultaneously, this quantification method enables automatic calculation and visualization, adapting to the integration requirements of existing carbon footprint monitoring platforms or dairy factory MES systems.

[0074] The magnitude of the difference essentially reflects the degree of improvement or risk of deterioration in the temperature control stability of the heat-sealing section of the current batch of dairy products compared to historical operating conditions after structural improvements. If the magnitude of the difference is significantly negative, it indicates that the fluctuation range of the heat-sealing section is small and the thermal response is more stable, reflecting the significant effectiveness of the plate heat exchanger structural improvement, which can significantly reduce additional compensation behavior and has the potential to further reduce the carbon factor parameter. Conversely, if the magnitude of the difference is close to zero or positive, it indicates that the current operating conditions are not much different from the historical conditions, the improvement effect may not have been fully released, and potential rework energy consumption should be noted.

[0075] For example, if the temperature fluctuation range of a certain batch of dairy products in the heat-sealing stage is 1.5℃, and the average fluctuation range of historical samples is 2.4℃, then the normalized offset is (1.5-2.4) / 2.4=-0.375, indicating that the temperature control stability has improved by 37.5%. Therefore, a lower emission intensity weight can be assigned to this batch in subsequent carbon factor corrections. The above mechanism has clear physical meaning, measurability, and practical operability, and is one of the important foundational modules of the carbon footprint assessment system of this invention.

[0076] Furthermore, the carbon footprint dynamic accounting system for multi-source emission data also includes:

[0077] The correction coefficient generation module 400 is used to generate a correction coefficient based on the energy consumption index and the difference magnitude, and to use the correction coefficient to correct the initial carbon factor parameter in order to obtain the final carbon factor parameter corresponding to the current processing.

[0078] Specifically, Figure 4 A structural block diagram of the correction coefficient generation module 400 in the system provided in an embodiment of the present invention is shown.

[0079] In a preferred embodiment provided by the present invention, the correction coefficient generation module 400 specifically includes:

[0080] The correction factor generation unit 401 is used to calculate the average value of the energy consumption index of all processing samples with abnormal temperature fluctuations in the heat-sealing section, and multiply the average energy consumption index by the difference amplitude, and combine it with the preset control amplitude coefficient to generate a correction coefficient.

[0081] The parameter correction unit 402 is used to correct the initial carbon factor parameters using the correction coefficient to obtain the final carbon factor parameters corresponding to the current processing.

[0082] The final carbon factor parameters are used as the basis for dynamically adjusting the input parameters of the emission accounting model in the whole-process carbon emission monitoring system of the target factory. They are further used to guide the carbon emission accounting of product units, evaluate the effectiveness of process energy-saving transformation, formulate carbon emission reduction strategies, or provide quantitative support for enterprises to participate in carbon management activities such as carbon quota trading, carbon label certification and carbon footprint compliance declaration.

[0083] In this embodiment of the invention, the correction coefficient generation module 400 constructs a complete dynamic carbon factor correction mechanism through the correction factor generation unit 401 and the parameter correction unit 402, which aims to more accurately reflect the real impact of structural improvement measures on carbon emission levels during actual operation.

[0084] The core significance of the correction factor generation unit 401 lies in its ability to calculate the average energy consumption index of samples showing abnormal temperature fluctuations in the heat-sealing section across all historical processing data. This average is then multiplied by the difference identified in the current processing batch, forming a quantifiable composite factor of "deviation degree × impact of abnormal behavior." A preset control amplitude coefficient is further introduced to ensure that the magnitude of this correction factor fluctuates within a reasonable range, avoiding excessive amplification or weakening of the correction effect. This control amplitude coefficient is typically set based on the target plant's historical carbon emission accounting fluctuation range, equipment stability, and carbon management strategy sensitivity. It can be a fixed empirical value or a threshold set by experts for dynamic adjustment.

[0085] The parameter correction unit 402 multiplies the generated correction coefficients with the initial carbon factor parameters to output the final carbon factor parameters corresponding to the current batch processing, thereby achieving dynamic correction of the input parameters of the carbon footprint accounting model. This method effectively addresses the shortcomings of traditional models that rely solely on the expected effects of structural improvements without considering fluctuations during the operational phase, making the final evaluation results more realistic, reliable, and representative.

[0086] The design of this module fully aligns with the core technical objective of this invention, namely, to dynamically correct carbon factor parameters by quantifying the differences in temperature control stability before and after the improvement of the plate heat exchanger structure, and to accurately reflect the true degree of improvement in carbon emissions achieved by the improvement measures.

[0087] Here is a detailed numerical example:

[0088] Assumption:

[0089] 1. Among the historical samples processed, 15 batches showed abnormal temperature fluctuations;

[0090] 2. The unit of the energy consumption compensation index for each sample is kilograms of carbon dioxide equivalent. The energy consumption indices for the 15 samples are 2.3, 2.5, 2.7, 2.6, 2.4, 2.8, 2.9, 2.5, 2.6, 2.4, 2.5, 2.6, 2.3, 2.4, and 2.7, with an average value of 2.55.

[0091] 3. The normalized temperature fluctuation offset of the current batch, as determined by the difference magnitude identification module, is -0.35 (which is 35% better than the historical baseline).

[0092] 4. Set the control amplitude coefficient to 0.4;

[0093] 5. The initial carbon factor parameter is set to 0.96 kg CO2 / unit product.

[0094] The correction factor is calculated as follows:

[0095] Correction factor = average energy consumption index × difference range × control range coefficient = 2.55 × (-0.35) × 0.4 = -0.357;

[0096] Final carbon factor parameter = initial carbon factor parameter + correction factor = 0.96 + (-0.357) = 0.603 kg CO2 / unit product.

[0097] This result shows that after structural improvement, the temperature control stability of the heat-sealing section in the current batch is significantly improved, and the corresponding rework or compensation operations are significantly reduced. Therefore, the carbon factor parameter can be reduced from the original 0.96 to 0.603, which is closer to the carbon emission level under real working conditions.

[0098] The role of the final carbon factor parameter in the carbon management system is further explained below:

[0099] The final carbon factor parameters will be directly used in the target factory's full-process carbon emission monitoring system, becoming one of the important inputs to the dynamic accounting model, and have the following multiple application values:

[0100] 1. Product Unit Carbon Emission Accounting: The carbon emissions corresponding to each unit of dairy product will be calculated according to the final carbon factor parameters, realizing refined accounting by batch and laying a data foundation for the enterprise's product-level carbon footprint management.

[0101] 2. Evaluation of the effectiveness of process energy-saving retrofit: By comparing the final carbon factor parameters corresponding to different structural schemes (such as heat exchangers before and after the improvement), the actual emission reduction benefits of the retrofit measures on carbon emissions can be quantitatively evaluated, supporting investment return analysis and energy-saving technology evaluation.

[0102] 3. Basis for formulating carbon emission reduction strategies: The dynamic trend of the final carbon factor parameters can help carbon management departments formulate more targeted process optimization paths and energy efficiency improvement directions, such as prioritizing the transformation of equipment with large fluctuation impacts and optimizing rework processes.

[0103] 4. Carbon quota trading and carbon footprint compliance reporting: Accurate carbon factor parameters help improve the transparency and accuracy of carbon quota assessment, avoid the risk of over-allocation or misallocation of carbon quotas, and meet the high requirements for data authenticity in carbon footprint certification, carbon label application, and government compliance reports.

[0104] In summary, the correction coefficient generation module 400, through a two-factor analysis mechanism based on historical behavior and current operating status, not only achieves dynamic and accurate parameter correction, but also builds a comprehensive carbon management support system for the target factory that connects "pre-event prediction, in-event tracking, and post-event accounting".

[0105] It should be understood that although the steps in the flowcharts of the various embodiments of the present invention are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the various embodiments may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least a portion of the sub-steps or stages of other steps.

[0106] It should be noted that the final carbon factor parameter is not used to characterize the overall carbon emission level in the complete dairy product production process, but is limited to the carbon footprint accounting mechanism built based on the temperature fluctuation characteristics of the heat sealing section, in order to reflect the actual carbon emission improvement effect brought about by structural improvements in this key process stage.

[0107] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0108] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0109] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention. Therefore, the scope of protection of this patent should be determined by the appended claims.

[0110] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A dynamic carbon footprint accounting system for multi-source emission data, characterized in that, The system includes a data acquisition module, a compensation energy consumption index generation module, an abnormal temperature fluctuation identification module, and a correction coefficient generation module, wherein: The data acquisition module is used to acquire the initial carbon factor parameters of the target factory when processing the current dairy products under the condition of using the structurally improved plate heat exchanger, and to extract the historical processing data of the target factory, and select several processing samples corresponding to the current dairy products and based on the process conditions of the plate heat exchanger before the improvement. The energy consumption compensation index generation module is used to extract quality control operation information after abnormal temperature fluctuations occur in the heat sealing section for each processed sample, and generate an energy consumption index reflecting the impact of compensatory carbon emissions based on the quality control operation information. The difference magnitude identification module is used to determine the temperature change of the heat-sealing section during the current processing, and compare it with the average temperature change of the processed sample to identify the difference magnitude of the current abnormal temperature fluctuation compared with the historical benchmark. The correction coefficient generation module is used to generate correction coefficients based on energy consumption indicators and difference magnitudes, and to use these correction coefficients to correct the initial carbon factor parameters in order to obtain the final carbon factor parameters corresponding to the current processing.

2. The carbon footprint dynamic accounting system for multi-source emission data according to claim 1, characterized in that, The initial carbon factor parameter is a carbon emission baseline factor calculated based on the expected increase in thermal efficiency after the improvement of the plate heat exchanger structure, according to the unit product throughput.

3. The carbon footprint dynamic accounting system for multi-source emission data according to claim 1, characterized in that, The historical dairy products in the processing sample are consistent with the background information of the target factory processing the current dairy products under the condition of using the structurally improved plate heat exchanger. The background information includes dairy product type, formula composition, target filling volume, preheating temperature setpoint, and ambient temperature and humidity data corresponding to the process batch.

4. The carbon footprint dynamic accounting system for multi-source emission data according to claim 1, characterized in that, The heat-sealing section is a heating process section used for packaging and sealing dairy products. Its temperature control stability directly affects the requirements for heat treatment uniformity and sealing integrity in the product quality control process. The heat source required for the heat-sealing section is provided by a plate heat exchanger. After the plate heat exchanger structure is improved, its heat exchange response characteristics change, thereby affecting the abnormal temperature fluctuation characteristics of the heat-sealing section.

5. The carbon footprint dynamic accounting system for multi-source emission data according to claim 4, characterized in that, The energy consumption compensation index generation module specifically includes: The abnormal temperature fluctuation identification unit is used to analyze each processed sample, extract the temperature monitoring data of the dairy products after they entered the heat sealing stage after being processed by the plate heat exchanger before the structural improvement, and determine whether there is an abnormal temperature fluctuation phenomenon by analyzing the fluctuation amplitude of the temperature sequence and comparing it with the set threshold. The quality control information extraction unit is used to obtain the quality control operation information corresponding to the processed sample with abnormal temperature fluctuations. The quality control operation information includes one or more of the following: temporary setting adjustment of heat sealing temperature, additional heating time, and rework ratio of the corresponding batch of dairy products. The energy consumption index generation unit is used to generate energy consumption indexes that reflect the impact of compensatory carbon emissions based on the additional energy consumption parameters introduced by each operation in the above-mentioned quality control operation information.

6. The carbon footprint dynamic accounting system for multi-source emission data according to claim 5, characterized in that, In the abnormal temperature fluctuation identification unit, when the temperature change of the temperature monitoring data of the heat-sealing section exceeds the preset fluctuation threshold in any continuous time period, and the duration of the fluctuation exceeds the preset duration threshold, it is determined that there is an abnormal temperature fluctuation in the heat-sealing section of the processed sample.

7. The dynamic carbon footprint accounting system for multi-source emission data according to claim 6, characterized in that, The difference magnitude identification module specifically includes: The heat-sealing section temperature extraction unit is used to acquire temperature monitoring data of the current dairy product after entering the heat-sealing section through the plate heat exchanger with improved structure, and calculate the corresponding temperature fluctuation amplitude index based on the combination characteristics of temperature change amplitude and duration; at the same time, it extracts the heat-sealing section temperature monitoring data of each processed sample, calculates its temperature fluctuation amplitude index in the same way, and then calculates the average value of the temperature fluctuation amplitude index of all historical samples as a historical benchmark. The fluctuation difference quantification unit is used to compare the numerical difference between the current temperature fluctuation amplitude index and the historical benchmark to identify the difference magnitude of the current abnormal temperature fluctuation compared to the historical benchmark.

8. The carbon footprint dynamic accounting system for multi-source emission data according to claim 7, characterized in that, In the fluctuation difference quantification unit, the difference between the current temperature fluctuation amplitude index and the historical benchmark is calculated by using the relative difference ratio or normalized offset. The normalized offset is the difference between the current temperature fluctuation amplitude index and the historical benchmark divided by the historical benchmark, which is used to quantify the relative deviation of the current processing process in the temperature stability of the heat sealing section.

9. The dynamic carbon footprint accounting system for multi-source emission data according to claim 1, characterized in that, The correction coefficient generation module specifically includes: The correction factor generation unit is used to calculate the average value of the energy consumption index of all processing samples with abnormal temperature fluctuations in the heat-sealing section, and multiply the average energy consumption index by the difference amplitude, and combine it with the preset control amplitude coefficient to generate a correction coefficient. The parameter correction unit is used to correct the initial carbon factor parameters using the correction coefficient to obtain the final carbon factor parameters corresponding to the current processing.

10. The dynamic carbon footprint accounting system for multi-source emission data according to claim 9, characterized in that, The final carbon factor parameters are used as the basis for dynamically adjusting the input parameters of the emission accounting model in the whole-process carbon emission monitoring system of the target factory. They are further used to guide the carbon emission accounting of product units, evaluate the effectiveness of process energy-saving transformation, formulate carbon emission reduction strategies, or provide quantitative support for enterprises to participate in carbon management activities such as carbon quota trading, carbon label certification and carbon footprint compliance declaration.

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