Carbon footprint dynamic accounting method, device, equipment, storage medium and product thereof

Abstract

The application discloses a carbon footprint dynamic accounting method and device, equipment, storage medium and product thereof, and relates to the technical field of carbon footprint accounting. The method comprises the following steps: receiving carbon source data and zero-carbon source data collected by a collection terminal in a dynamic accounting period in a total metering type zero-carbon park, wherein the collection terminal comprises a fixed collection terminal and a mobile supplementary collection terminal; performing carbon emission accounting on the carbon source data to obtain carbon emission; performing dynamic deduction accounting on the zero-carbon source data to obtain zero-carbon deduction; and obtaining real-time net carbon footprint data of the total metering type zero-carbon park based on the carbon emission and the zero-carbon deduction. Thus, dynamic and accurate accounting of the carbon footprint of the total metering type zero-carbon park is realized without the support of complex models and a large amount of basic data.

Description

Technical Field

[0001] This application relates to the field of carbon footprint accounting technology, and in particular to methods, apparatus, equipment, storage media and products for dynamic carbon footprint accounting. Background Technology

[0002] As an important vehicle for carbon emission reduction, the accuracy and real-time nature of carbon footprint accounting in zero-carbon industrial parks are the core prerequisites for achieving zero-carbon goals.

[0003] Currently, carbon footprint accounting methods are mainly aimed at zero-carbon industrial parks with itemized metering. These methods are mostly static and involve complex models with numerous parameters, requiring specialized accounting teams and substantial amounts of basic data. Applying these methods to zero-carbon industrial parks with aggregate metering ignores the dynamic changes in carbon emission sources, weak data collection capabilities, low accounting costs, and the presence of distributed renewable energy in these parks. This results in low accuracy in calculating the carbon footprint of zero-carbon industrial parks with aggregate metering.

[0004] The above content is only used to help understand the technical solution of this application and does not represent an admission that the above content is prior art. Summary of the Invention

[0005] The main purpose of this application is to provide a method, apparatus, equipment, storage medium and product for dynamic carbon footprint accounting, which aims to solve the technical problem of low carbon footprint and accounting accuracy in total meter-based zero-carbon parks.

[0006] To achieve the above objectives, this application proposes a method for dynamic carbon footprint accounting, the method comprising: The system receives carbon source data and zero carbon source data collected by the data acquisition terminal in the zero-carbon park within the total metering type during the dynamic accounting cycle. The data acquisition terminal includes a fixed data acquisition terminal and a mobile supplementary data acquisition terminal. Carbon emission calculations are performed on the carbon source data to obtain the carbon emission amount; The zero-carbon source data is dynamically deducted to obtain the zero-carbon deduction amount; Based on the carbon emissions and the zero carbon credit, the real-time net carbon footprint data of the total metering zero-carbon park is obtained.

[0007] In one embodiment, the step of dynamically calculating the zero-carbon source data to obtain the zero-carbon deduction amount includes: The zero-carbon source data is classified to determine the deduction type of the zero-carbon source; Based on the zero-carbon source data and the corresponding dynamic deduction coefficient, the deductible carbon emissions of each of the deduction types of zero-carbon sources are determined. The dynamic deduction coefficient changes dynamically with the dynamic accounting cycle. The carbon emission credits of each of the zero carbon sources are summed up to obtain the zero carbon credit amount.

[0008] In one embodiment, before the step of classifying the zero-carbon source data and determining the deduction type of the zero-carbon source, the method further includes: Obtain historical data of zero carbon sources within the previous dynamic accounting period; Based on the historical data of the zero carbon sources, the utilization rate of each zero carbon source and the stability coefficient of the energy generated by each zero carbon source in the previous dynamic accounting period were analyzed. Based on the utilization rate and the stability coefficient, the historical dynamic deduction coefficients of each of the zero carbon sources used in the previous dynamic accounting cycle are adjusted to obtain the dynamic deduction coefficients required for the current dynamic accounting cycle.

[0009] In one embodiment, the method for analyzing the stability coefficient of energy generated by each of the zero-carbon sources in the previous dynamic accounting period based on the historical data of the zero-carbon sources includes: Environmental sensing data matching the type of zero carbon source are selected from the historical data of the zero carbon source, as well as the power generation time series of each of the zero carbon sources; The power generation time series is time-aligned with the environmental sensing data to construct an environment-power generation correlation curve, and the goodness-of-fit index of the environment-power generation correlation curve is determined. If the goodness-of-fit index is lower than the preset equipment health threshold, the stability coefficient of the corresponding zero carbon source will be set to the attenuation correction coefficient determined based on the equipment's operating years. If the goodness-of-fit index is not lower than the device health threshold, the stability coefficient is calculated based on the volatility of the environmental perception data in the previous dynamic accounting period.

[0010] In one embodiment, before the step of receiving carbon source data and zero carbon source data collected by the data acquisition terminal in the master metering-type zero-carbon park during the dynamic accounting cycle, the method further includes: Obtain the park planning map of the total metering-type zero-carbon park; Identify the boundary of the total metering-type zero-carbon park from the park planning map, and identify the carbon emission sources and zero-carbon sources within the boundary of the park. Then, classify the emission sources and the zero-carbon sources respectively to obtain the classification results. Based on the classification results, a carbon source-zero carbon source list for a total table-based zero-carbon park is constructed. The step of receiving carbon source data and zero carbon source data collected by the data acquisition terminal in the metering-type zero-carbon park during the dynamic accounting cycle also includes: The system receives carbon source data and zero carbon source data collected by the data acquisition terminal in the master metering-type zero carbon park within the dynamic accounting cycle, based on the carbon source-zero carbon source list.

[0011] In one embodiment, after the step of receiving the carbon source data and zero carbon source data collected by the data acquisition terminal in the total metering type zero carbon park during the dynamic accounting cycle, the method further includes: Based on the preset Laida criterion, outliers in the carbon source data and the zero carbon source data are removed to obtain preprocessed carbon source data and preprocessed zero carbon source data. Missing values ​​are identified from the preprocessed carbon source data and the preprocessed zero carbon source data, and the missing values ​​are filled in to obtain complete carbon source data and complete zero carbon source data. The complete carbon source data and the complete zero carbon source data are standardized to obtain standardized carbon source data and zero carbon source data.

[0012] Furthermore, to achieve the above objectives, this application also proposes a dynamic carbon footprint accounting device, which includes: The receiving module is used to receive carbon source data and zero carbon source data collected by the data collection terminal in the total metering zero carbon park during the dynamic accounting cycle. The data collection terminal includes a fixed data collection terminal and a mobile supplementary data collection terminal. The accounting module is used to perform carbon emission accounting on the carbon source data to obtain carbon emission amounts; and to perform dynamic deduction accounting on the zero carbon source data to obtain zero carbon deduction amounts. The summary module is used to obtain real-time net carbon footprint data of the total metering zero-carbon park based on the carbon emissions and the zero carbon deduction.

[0013] In addition, to achieve the above objectives, this application also proposes a dynamic carbon footprint accounting device, the device comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the dynamic carbon footprint accounting method as described above.

[0014] In addition, to achieve the above objectives, this application also proposes a storage medium, which is a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, it implements the steps of the dynamic carbon footprint accounting method described above.

[0015] In addition, to achieve the above objectives, this application also provides a computer program product, which includes a computer program that, when executed by a processor, implements the steps of the dynamic carbon footprint accounting method described above.

[0016] One or more technical solutions proposed in this application have at least the following technical effects: Addressing the characteristics of zero-carbon parks with total metering, such as dynamic changes in carbon emission sources, weak data collection capabilities, sensitivity to accounting costs, and the presence of distributed renewable energy, this method receives carbon source data and zero-carbon source data collected by fixed and mobile supplementary collection terminals during the dynamic accounting period. Carbon emission accounting is performed on the carbon source data to obtain carbon emissions, while dynamic deduction accounting is performed on the zero-carbon source data to obtain zero-carbon deductions. Based on these carbon emissions and zero-carbon deductions, real-time net carbon footprint data for the total metering zero-carbon park is calculated. In other words, this application adopts a data acquisition strategy that combines master table data collection with supplementary data collection. This strategy enhances the coverage of key carbon flows while ensuring limited data collection capabilities. By calculating carbon emissions and zero carbon credits separately and then dynamically integrating them, the calculation results can reflect the synergistic impact of load changes and the output of zero-carbon power sources such as distributed photovoltaic and wind power in the park in real time. At the same time, by replacing fixed time periods with dynamic calculation cycles, the granularity of the calculation is adaptively adjusted according to the operating status, balancing efficiency and accuracy. Therefore, without the need for complex models and a large amount of basic data support, dynamic and accurate calculation of the carbon footprint of master table-based zero-carbon parks is achieved. Attached Figure Description

[0017] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0018] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 A flowchart illustrating the first embodiment of the dynamic carbon footprint calculation method of this application; Figure 2 A flowchart illustrating the second embodiment of the dynamic carbon footprint accounting method of this application; Figure 3 A flowchart illustrating the third embodiment of the dynamic carbon footprint calculation method of this application; Figure 4 This is a schematic diagram of the module structure of the carbon footprint dynamic accounting device according to an embodiment of this application; Figure 5 This is a schematic diagram of the equipment structure of the hardware operating environment involved in the dynamic carbon footprint accounting method in the embodiments of this application.

[0020] The realization of the purpose, functional features and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0021] It should be understood that the specific embodiments described herein are merely illustrative of the technical solutions of this application and are not intended to limit this application.

[0022] To better understand the technical solution of this application, a detailed description will be provided below in conjunction with the accompanying drawings and specific implementation methods.

[0023] It should be noted that the executing entity in this embodiment can be a computing service device with data processing, network communication, and program execution functions, such as a tablet computer, personal computer, or mobile phone, or an electronic device or edge gateway capable of performing the above functions. The following description uses an edge gateway as an example to illustrate this embodiment and the subsequent embodiments.

[0024] Based on this, embodiments of this application provide a method for dynamic carbon footprint calculation, referring to... Figure 1 , Figure 1 This is a flowchart illustrating the first embodiment of the dynamic carbon footprint accounting method of this application.

[0025] In this embodiment, the dynamic carbon footprint calculation method includes steps S10 to S40: Step S10: Receive carbon source data and zero carbon source data collected by the data acquisition terminal in the total metering type zero carbon park during the dynamic accounting cycle. The data acquisition terminal includes a fixed data acquisition terminal and a mobile supplementary data acquisition terminal. It should be noted that a master metering-based zero-carbon park is a small-scale zero-carbon park characterized by a small boundary area, dispersed and singular carbon emission sources (mainly including building energy consumption, park transportation, production energy consumption, and waste treatment), an energy structure dominated by distributed renewable energy (such as distributed photovoltaic or small-scale energy storage), weak data collection capabilities, and limited budget for accounting costs. The data collection terminal is a sensing and communication device used to collect raw data related to carbon footprint accounting in real time or periodically.

[0026] Among them, fixed collection terminals are collection terminals deployed at core carbon source and zero carbon source locations; mobile supplementary collection terminals are used to supplement collection from dispersed and temporary carbon sources (such as temporary construction machinery and temporary electrical equipment in the park). The terminals can be mobile terminals with functions such as taking pictures, recording videos, inputting information, and communicating.

[0027] It should be noted that the dynamic accounting cycle is the time granularity for carbon footprint accounting, which can be dynamically adjusted according to the park's operational characteristics, such as 15 minutes, 1 hour, or 1 day. This dynamic accounting cycle supports high-frequency, near real-time carbon emission and deduction calculations, adapting to fluctuations in park load and changes in renewable energy output. Carbon source data comes from activities that directly or indirectly generate carbon dioxide equivalents, such as fossil fuel consumption, purchased electricity / heat, and industrial process emissions. Zero-carbon source data includes positive environmental benefit data that can deduct carbon emissions, such as renewable energy power generation, green electricity purchase certificates, and carbon sink projects within the park; for example, photovoltaic power generation, wind power generation, biomass heat production, and the number of certified green certificates.

[0028] Understandably, by combining fixed acquisition terminals with mobile supplementary acquisition terminals in a master metering-type zero-carbon park, comprehensive coverage of data acquisition scenarios for various carbon sources and zero carbon sources within the park can be achieved. Specifically, fixed acquisition terminals can achieve continuous and stable monitoring of major energy nodes, while mobile supplementary acquisition terminals can flexibly collect carbon activity data (carbon source data and zero carbon source data) from temporary, mobile, blind-spot, or dispersed carbon and zero carbon sources. By integrating data from both fixed and mobile acquisition terminals, a high spatiotemporal resolution panoramic view of the park's carbon flow can be constructed, reducing data loss and boundary leakage, providing a reliable data foundation for accurate accounting, and improving the robustness and adaptability of the entire zero-carbon park carbon management system.

[0029] Understandably, acquiring carbon source data and zero-carbon source data simultaneously within a dynamic accounting cycle ensures consistency and timeliness in carbon footprint accounting, thereby avoiding accounting errors caused by delayed or incomplete data collection. Furthermore, by introducing dynamic accounting cycles (hourly or daily), real-time dynamic accounting of the carbon footprint can be achieved, allowing for timely capture of dynamic changes in carbon emission sources.

[0030] In practical implementation, low-cost fixed data acquisition terminals can be deployed at core carbon source / zero carbon source locations to achieve real-time acquisition of core data. For indirect carbon sources, power acquisition terminals can be deployed in the park's main power distribution room to collect real-time data on purchased electricity, purchased renewable energy electricity, and distributed photovoltaic power generation within the park. Heat acquisition terminals can be deployed at heat inlets to collect data on purchased heat consumption. For direct carbon sources, fuel consumption acquisition terminals can be deployed at small boilers and forklift refueling points to collect real-time data on fossil fuel consumption. Waste acquisition terminals can be deployed at waste transfer stations to collect real-time data on waste generation and landfill / incineration. For zero carbon sources, output acquisition terminals can be deployed at distributed photovoltaic power stations and small energy storage systems to collect real-time data on renewable energy power generation and energy storage charging and discharging. Fixed monitoring points can be established in the park's green areas to collect data on green area and vegetation type.

[0031] For dispersed and temporary carbon sources (such as temporary construction machinery and temporary electrical equipment in the park), supplementary data collection is carried out using mobile software (lightweight data collection software that supports manual input and photo upload). Park management personnel upload data daily at set times, reducing the deployment cost of fixed terminals.

[0032] Step S20: Perform carbon emission accounting on the carbon source data to obtain the carbon emission amount; It should be noted that carbon emission accounting is the process of converting carbon source data into corresponding carbon dioxide equivalent emissions based on national or international standards and localized emission factors.

[0033] Understandably, standardized carbon emission accounting based on received carbon source data can convert raw energy or material consumption data into a unified carbon dioxide equivalent unit, thereby achieving comparability and additivity between different energy types and emission sources. Furthermore, by adopting emission factors and accounting methods that comply with national or industry standards, the authority and compliance of carbon emission calculation results are ensured, which facilitates the park's participation in carbon trading, green certification, or policy supervision.

[0034] In practice, the system can also automatically call up the grid emission factor or regional emission parameters for the corresponding time period according to the dynamic accounting cycle, so that the carbon emissions reflect the real environmental impact, thereby avoiding systematic overestimation or underestimation caused by using static average values, and thus improving the scientific nature of carbon management decisions.

[0035] In practical implementation, a simplified accounting formula adapted to small industrial parks is adopted for various carbon emission sources (avoiding complex parameters and improving accounting efficiency). The specific formula for calculating total carbon emissions is as follows: Indirect carbon source (purchased electricity, heat) carbon emission accounting (E 间接 ): E 间接 =E 外购电力 +E 外购热力 , of which E 外购电力 = Purchased electricity consumption (kWh) × Average grid carbon emission factor (tCO2 / kWh) - Purchased renewable energy electricity consumption (kWh) × Renewable energy carbon emission factor (tCO2 / kWh, valued at 0); E 外购热力 = Purchased heat consumption (GJ) × Thermal carbon emission factor (tCO2 / GJ); The grid average carbon emission factor and thermal carbon emission factor adopt the latest regional carbon emission factor released locally, which does not require self-calculation and reduces the difficulty of calculation; Direct carbon source (fossil fuel combustion) carbon emission accounting (E 化石燃料 ): ,in, Let be the consumption amount (kg) of the i-th type of fossil fuel. Let be the carbon emission factor (tCO2 / kg) for the i-th fossil fuel (e.g., 0.00235tCO2 / kg for gasoline and 0.00263tCO2 / kg for diesel); where the carbon emission factor adopts the basic carbon emission factor uniformly published by the state.

[0036] Direct carbon source (waste treatment) carbon emission accounting (E 废弃物 ): Among them, E 填埋 = Waste landfill volume (kg) × Landfill carbon emission factor (tCO2 / kg, valued at 0.0003tCO2 / kg); E 焚烧 = Waste incineration volume (kg) × incineration carbon emission factor (tCO2 / kg, valued at 0.0011tCO2 / kg), to suit the characteristics of small-scale and single-method waste treatment in small industrial parks.

[0037] Step S30: Perform dynamic deduction calculation on the zero-carbon source data to obtain the zero-carbon deduction amount; It should be noted that dynamic deduction accounting is based on factors such as the type of zero carbon source, operating status, and environmental conditions, and uses a deduction coefficient that is dynamically adjusted over time to convert zero carbon source data into deductible carbon emissions.

[0038] It is understandable that the effective power generation capacity of zero-carbon sources such as photovoltaic and wind power fluctuates due to factors such as weather, equipment aging, and operation and maintenance status. If all of them are fully deducted without differentiation, the net carbon footprint will be underestimated. However, using dynamic deduction accounting for zero-carbon source data can more accurately reflect the actual carbon reduction benefits of renewable energy.

[0039] Step S40: Based on the carbon emissions and the zero carbon credit, obtain the real-time net carbon footprint data of the total metering zero-carbon park.

[0040] It should be noted that the real-time net carbon footprint data is the net carbon emission value of the park calculated by "carbon emissions - zero carbon credit" at the end of any dynamic accounting period.

[0041] Understandably, by calculating the difference between carbon emissions and zero carbon credits in real time, the net carbon footprint data of the park under the current dynamic accounting cycle can be obtained, allowing managers to immediately grasp whether the park is in a net emission, carbon neutral, or negative carbon state.

[0042] In practical implementation, real-time net carbon footprint data (E) 净碳足迹 The formula for calculating ) is: Among them, E 零碳抵扣This is a zero-carbon deduction.

[0043] Optionally, real-time net carbon footprint data can also be displayed to park management personnel through a visual interface, including real-time net carbon footprint, carbon emission ratio of each carbon source, zero carbon source deduction effect, carbon footprint change trend, etc.; at the same time, a linkage mechanism between accounting results and carbon emission reduction measures can be established to achieve closed-loop optimization.

[0044] If the real-time net carbon footprint exceeds the preset threshold (set according to the park's zero-carbon target), the system will automatically identify the sources of excessive carbon emissions (such as excessive external power purchases or excessive fossil fuel consumption during a certain period) and output optimization suggestions (such as prioritizing the use of distributed photovoltaic power and reducing the frequency of forklift use). If the amount of zero carbon source deduction is lower than expected, the system will prompt you to optimize the utilization efficiency of zero carbon sources (such as adjusting the energy storage charging and discharging strategy and replanting green vegetation). Based on the optimization suggestions, the park management personnel adjusted the carbon control measures. The effects of the adjustments were fed back through the dynamic accounting results of the next accounting cycle, forming a closed-loop mechanism of "data collection - dynamic accounting - result feedback - measure optimization - re-accounting" to continuously promote carbon emission reduction in the park and achieve the zero-carbon goal.

[0045] The dynamic accounting results can also be verified monthly. Specifically, this involves on-site verification and data comparison: on-site verification of the actual consumption and output of core carbon sources / zero carbon sources, and comparison of the deviation between the data collected from fixed terminals and the actual on-site data; at the same time, the monthly summary accounting results are compared with the results of traditional static accounting methods (such as annual accounting methods). If the deviation exceeds the set deviation threshold (5%), the parameters of the dynamic accounting model (such as carbon emission factor and zero carbon source deduction coefficient) are corrected to ensure the accuracy of the accounting results and adapt to the management and control needs of small parks.

[0046] This embodiment provides a dynamic carbon footprint accounting method. Addressing the characteristics of zero-carbon parks with total metering, such as dynamic changes in carbon emission sources, weak data collection capabilities, sensitivity to accounting costs, and the inclusion of distributed renewable energy, the method receives carbon source data and zero-carbon source data collected by fixed and mobile supplementary collection terminals within a dynamic accounting period. It calculates carbon emissions from the carbon source data to obtain the carbon emission amount, and simultaneously performs dynamic deduction calculations on the zero-carbon source data to obtain the zero-carbon deduction amount. Finally, based on the carbon emission amount and the zero-carbon deduction amount, the real-time net carbon footprint data of the total metering zero-carbon park is calculated. In other words, this application adopts a data acquisition strategy that combines master table data collection with supplementary data collection. This strategy enhances the coverage of key carbon flows while ensuring limited data collection capabilities. By calculating carbon emissions and zero carbon credits separately and then dynamically integrating them, the calculation results can reflect the synergistic impact of load changes and the output of zero-carbon power sources such as distributed photovoltaic and wind power in the park in real time. At the same time, by replacing fixed time periods with dynamic calculation cycles, the granularity of the calculation is adaptively adjusted according to the operating status, balancing efficiency and accuracy. Therefore, without the need for complex models and a large amount of basic data support, dynamic and accurate calculation of the carbon footprint of master table-based zero-carbon parks is achieved.

[0047] Based on the first embodiment of this application, in the second embodiment of this application, the content that is the same as or similar to that in Embodiment 1 above can be referred to the above description, and will not be repeated hereafter. Based on this, please refer to... Figure 2 Step S30 also includes steps S01 to S03: Step S01: Classify the zero-carbon source data and determine the deduction type of the zero-carbon source; Step S02: Based on the zero-carbon source data and the corresponding dynamic deduction coefficient, determine the deductible carbon emissions of each of the deduction types of zero-carbon sources. The dynamic deduction coefficient changes dynamically with the dynamic accounting cycle. Step S03: The carbon emission offsets of each of the zero carbon sources are summed to obtain the zero carbon offset amount.

[0048] It should be noted that the deduction type is used to distinguish the applicable rules and weights for different zero-carbon sources in carbon deduction accounting, including distributed photovoltaic or small-scale wind power, energy storage systems, and industrial park carbon sinks (green vegetation), etc. The dynamic deduction factor is a proportional factor used to convert unit zero-carbon source data into deductible carbon emissions. The deductible carbon emissions are the deductible carbon dioxide equivalent value corresponding to a specific deduction type of zero-carbon source within the current dynamic accounting period after conversion by the dynamic deduction factor.

[0049] Understandably, by classifying zero-carbon source data in a refined manner and assigning clear deduction types, a logical basis can be provided for subsequent differentiated accounting, avoiding the confusion between highly reliable local green electricity and low-transparency external carbon sinks. This enables the application of different regulatory requirements and incentive strategies to different types of zero-carbon sources, thereby improving the dynamic and accurate accounting of the carbon footprint of total meter-based zero-carbon parks.

[0050] Understandably, by introducing a dynamic deduction coefficient, the edge gateway can automatically reduce the deduction weight of inefficient or abnormal zero-carbon sources, thereby preventing false zero-carbon phenomena and enhancing the credibility of carbon deduction results.

[0051] In practice, the formula for calculating the zero-carbon deduction is as follows: Where Pj is the real-time output of the j-th zero-carbon source (e.g., distributed photovoltaic power generation kWh, carbon sequestration tCO2), k j Let be the dynamic deduction coefficient for the j-th zero-carbon source. The dynamic deduction coefficient can be dynamically adjusted based on the utilization efficiency and stability of the zero-carbon source.

[0052] Specifically, for distributed photovoltaic and small-scale wind power: k j = Average grid carbon emission factor (tCO2 / kWh), which is the amount of carbon emissions offset by the corresponding grid power generation for every 1kWh of electricity generated; For energy storage systems: kj = the proportion of renewable energy released by energy storage × average grid carbon emission factor, only offsetting the carbon emissions of the renewable energy portion; For park carbon sinks (green vegetation): k j =1.0, P j The annual carbon sequestration by vegetation (tCO2) is averaged quarterly and then distributed to daily and hourly levels to achieve dynamic offsetting.

[0053] Furthermore, prior to step S01, the dynamic carbon footprint accounting method further includes: Obtain historical data of zero carbon sources within the previous dynamic accounting period; Based on the historical data of the zero carbon sources, the utilization rate of each zero carbon source and the stability coefficient of the energy generated by each zero carbon source in the previous dynamic accounting period were analyzed. Based on the utilization rate and the stability coefficient, the historical dynamic deduction coefficients of each of the zero carbon sources used in the previous dynamic accounting cycle are adjusted to obtain the dynamic deduction coefficients required for the current dynamic accounting cycle.

[0054] It should be noted that the previous dynamic accounting cycle is a complete accounting time window preceding the current dynamic accounting cycle in which carbon footprint accounting is being conducted. Historical zero-carbon source data refers to the operational data of various zero-carbon sources recorded and stored by the data acquisition terminal during the previous dynamic accounting cycle. Utilization rate is the ratio of the actual energy output of a zero-carbon source during the previous dynamic accounting cycle to its theoretical maximum output. The stability coefficient is a quantitative indicator characterizing the stability or predictability of the energy output of a zero-carbon source during the previous dynamic accounting cycle. The historical dynamic deduction coefficient is the dynamic deduction coefficient actually used to calculate the zero-carbon deduction amount in the previous dynamic accounting cycle, serving as the benchmark value for coefficient adjustments in the current cycle.

[0055] Understandably, by dynamically adjusting the deduction coefficient based on historical operating performance, the zero-carbon deduction amount can truly reflect the current effective carbon reduction capacity of zero-carbon sources, thus improving the accuracy and timeliness of carbon accounting.

[0056] Understandably, by quantifying utilization rate and stability coefficient, it is possible to distinguish whether low output is due to insufficient resources or equipment failure, thereby making a reasonable assessment of offsetting capacity and avoiding misjudging low power generation caused by weather as efficient equipment operation.

[0057] Furthermore, the method for analyzing the stability coefficient of energy generated by each of the zero-carbon sources in the previous dynamic accounting period based on the historical data of the zero-carbon sources includes: Environmental sensing data matching the type of zero carbon source are selected from the historical data of the zero carbon source, as well as the power generation time series of each of the zero carbon sources; The power generation time series is time-aligned with the environmental sensing data to construct an environment-power generation correlation curve, and the goodness-of-fit index of the environment-power generation correlation curve is determined. If the goodness-of-fit index is lower than the preset equipment health threshold, the stability coefficient of the corresponding zero carbon source will be set to the attenuation correction coefficient determined based on the equipment's operating years. If the goodness-of-fit index is not lower than the device health threshold, the stability coefficient is calculated based on the volatility of the environmental perception data in the previous dynamic accounting period.

[0058] It should be noted that environmental sensing data refers to external natural environmental parameters directly related to a specific type of zero-carbon source. Power generation time series data is the instantaneous or average power generation data of a specific zero-carbon source, recorded continuously in chronological order within the previous dynamic accounting period. Time series alignment involves synchronizing the power generation time series data with the environmental sensing data in the time dimension, ensuring that the power generation value at each moment has the same timestamp as its corresponding environmental parameter value. The environment-power generation correlation curve is a functional relationship curve between environmental sensing data and power generation established through mathematical modeling methods (such as linear regression, multinomial fitting, and machine learning models). The goodness-of-fit index is a statistical indicator used to quantify the degree of agreement between the environment-power generation correlation curve and actual observed data.

[0059] The equipment health threshold is a preset goodness-of-fit critical value used to determine whether zero-carbon source equipment is in a normal and healthy operating state. The attenuation correction coefficient is a performance reduction factor calculated based on the equipment's operating years and industry experience or manufacturer attenuation curves; it is used to conservatively estimate the effective output capacity when the equipment malfunctions. Volatility is the degree of change in environmental sensing data within the previous dynamic accounting period, usually expressed as the ratio of standard deviation to mean; it measures the stability of environmental conditions, thus affecting the predictability of zero-carbon source output.

[0060] Understandably, by accurately screening and matching environmental sensing data according to the type of zero carbon source, interference from irrelevant environmental parameters can be avoided, thereby improving the relevance and accuracy of subsequent correlation modeling.

[0061] Understandably, when equipment deviates from normal operating conditions, using a degradation correction factor based on the number of years of operation as a stability factor can avoid overestimating the deduction capacity of faulty equipment. Under the premise of healthy equipment, calculating the stability factor based on environmental volatility can reasonably distinguish between power generation fluctuations caused by unstable weather and problems with the equipment itself, making the deduction calculation fairer and more scientific. Furthermore, due to the inherent intermittency of renewable energy, reasonable deductions in carbon accounting can also avoid misjudging uncontrollable natural factors as management failures, thereby increasing the park's confidence in accepting a high proportion of renewable energy.

[0062] Based on the first and second embodiments of this application, the same or similar content as the above embodiments in the third embodiment of this application can be referred to the above description, and will not be repeated hereafter. Based on this, please refer to... Figure 3 Before step S10, the dynamic carbon footprint accounting method further includes steps S1 to S3: Step S1: Obtain the park planning map of the total metering type zero-carbon park; Step S2: Identify the boundary of the total metering zero-carbon park from the park planning map, and the carbon emission sources and zero-carbon sources within the boundary of the park, and classify the emission sources and zero-carbon sources respectively to obtain the classification results; Step S3: Based on the classification results, construct the carbon source-zero carbon source list for the total table-based zero-carbon park.

[0063] It should be noted that the park planning map is a digital drawing or building information model file provided by the park's developer or manager, containing the park's geographical layout, building distribution, infrastructure locations, and energy pipeline routes. The park boundary is a closed geographical outline defining the spatial scope of the master-scale metered zero-carbon park. It clarifies the scope of responsibility for carbon accounting, ensuring that all carbon sources and zero-carbon sources included in the accounting are located within this boundary, avoiding external interference or omissions. The carbon source-zero-carbon source inventory is a structured data table generated based on the classification results, recording the unique identifier, spatial location, type label, metering method, associated data collection terminal ID, and accounting parameters of all carbon emission sources and zero-carbon sources within the park.

[0064] It is understandable that by clearly defining the physical boundaries of small zero-carbon parks (based on the park's planning red line, clearly defining the scope of all buildings, facilities, and sites within the park, and excluding related areas outside the park), calculation errors caused by ambiguous boundaries can be avoided.

[0065] Understandably, by constructing a structured carbon source-zero carbon source inventory, the transformation from static drawings to dynamic accounting objects is realized, providing a data skeleton for full life cycle carbon management. This ensures that all subsequent dynamic data are bound to the correct physical entities and accounting rules, fundamentally guaranteeing the accuracy and compliance of carbon footprint results.

[0066] Optionally, step S10 further includes: The system receives carbon source data and zero carbon source data collected by the data acquisition terminal in the master metering-type zero carbon park within the dynamic accounting cycle, based on the carbon source-zero carbon source list.

[0067] Understandably, by strictly binding data collection to the carbon source-zero carbon source list, it is ensured that the received carbon source data and zero carbon source data come from certified accounting objects, fundamentally eliminating accounting distortion caused by the drift of the collection scope or the mixing of non-park data.

[0068] Understandably, by using a technology approach that drives data collection based on inventory, the results of spatial identification and classification in the early stages can be effectively transferred to the data collection stage, forming a closed-loop data chain of planning, inventory, collection, and accounting, thereby ensuring that carbon footprint accounting has high fidelity from the source.

[0069] Optionally, after step S10, the dynamic carbon footprint accounting method further includes: Based on the preset Laida criterion, outliers in the carbon source data and the zero carbon source data are removed to obtain preprocessed carbon source data and preprocessed zero carbon source data. Missing values ​​are identified from the preprocessed carbon source data and the preprocessed zero carbon source data, and the missing values ​​are filled in to obtain complete carbon source data and complete zero carbon source data. The complete carbon source data and the complete zero carbon source data are standardized to obtain standardized carbon source data and zero carbon source data.

[0070] It should be noted that the Laida criterion is an outlier detection method based on statistical principles. Outliers are data points in carbon source or zero-carbon source data that significantly deviate from the normal fluctuation range due to sensor malfunction, communication interference, human error, or extreme events. Examples include a sudden increase in photovoltaic power generation to 200% of installed capacity or negative gas consumption in a given minute. Preprocessed carbon source and zero-carbon source data are preliminary clean datasets obtained after removing outliers using the Laida criterion. They retain the original data's temporal structure and valid information, but may still contain missing data. Missing values ​​are carbon source or zero-carbon source data points that were not successfully reported within the dynamic accounting period due to reasons such as offline acquisition terminals, communication interruptions, or equipment downtime. Imputation is the process of reasonably estimating and filling in missing values ​​using mathematical or machine learning methods, aiming to restore data integrity and avoid accounting bias caused by missing values. Complete carbon source and zero-carbon source data are continuous time series data without gaps or outliers, obtained after removing outliers and imputing missing values. These can be used for subsequent standardization and accounting. Standardization is the process of converting carbon source and zero-carbon source data of different dimensions and magnitudes into a unified format or unit. Standardized carbon source data and standardized zero-carbon source data are the final input data after standardization, possessing consistent units, time granularity, and data structure, and can be directly used for carbon emission accounting and dynamic deduction calculations.

[0071] Understandably, by introducing the Raida criterion to filter outliers in the raw data, distorted data introduced by equipment failure or communication errors is effectively eliminated, preventing distorted data from causing serious distortions in subsequent calculations of carbon emissions or deductions.

[0072] Optionally, physical constraints (such as the upper limit of installed capacity) can be combined to perform secondary verification of the original data, so that the anomaly detection not only relies on statistical regularities but also conforms to engineering practice, thereby improving the accuracy of data cleaning.

[0073] Understandably, by performing context-aware intelligent imputation of missing values, the underestimation of the accounting or the break in the time series caused by simple deletion or zero filling is avoided, thereby ensuring the continuity and integrity of carbon footprint calculation.

[0074] It should be noted that the above examples are only for understanding this application and do not constitute a limitation on the dynamic carbon footprint accounting method of this application. Any simple modifications based on this technical concept are within the protection scope of this application.

[0075] This application also provides a dynamic carbon footprint calculation device; please refer to [reference needed]. Figure 4 The carbon footprint dynamic accounting device includes: The receiving module 10 is used to receive carbon source data and zero carbon source data collected by the data acquisition terminal in the total metering type zero carbon park during the dynamic accounting cycle. The data acquisition terminal includes a fixed data acquisition terminal and a mobile supplementary data acquisition terminal. The calculation module 20 is used to perform carbon emission calculation on the carbon source data to obtain carbon emission amount; and to perform dynamic deduction calculation on the zero carbon source data to obtain zero carbon deduction amount; The summary module 30 is used to obtain real-time net carbon footprint data of the total metering zero-carbon park based on the carbon emissions and the zero carbon deduction.

[0076] Optionally, the accounting module 20 is further configured to classify the zero-carbon source data and determine the deduction type of the zero-carbon source; based on the zero-carbon source data and the corresponding dynamic deduction coefficient, determine the deductible carbon emission amount of each deduction type of zero-carbon source, wherein the dynamic deduction coefficient changes dynamically with the dynamic accounting cycle; and accumulate the deductible carbon emission amounts of each zero-carbon source to obtain the zero-carbon deduction amount.

[0077] Optionally, the accounting module 20 is further configured to acquire historical data of zero carbon sources in the previous dynamic accounting cycle; based on the historical data of zero carbon sources, analyze the utilization rate of each zero carbon source in the previous dynamic accounting cycle, and the stability coefficient of the energy generated by each zero carbon source; based on the utilization rate and the stability coefficient, adjust the historical dynamic deduction coefficient of each zero carbon source used in the previous dynamic accounting cycle to obtain the dynamic deduction coefficient required for the current dynamic accounting cycle.

[0078] Optionally, the calculation module 20 is further configured to: filter environmental sensing data matching the type of the zero-carbon source from the historical data of the zero-carbon source, and the power generation time series of each of the zero-carbon sources; align the power generation time series with the environmental sensing data to construct an environment-power generation correlation curve, and determine the goodness-of-fit index of the environment-power generation correlation curve; if the goodness-of-fit index is lower than a preset equipment health threshold, then set the stability coefficient of the corresponding zero-carbon source to a decay correction coefficient determined based on the equipment's operating years; if the goodness-of-fit index is not lower than the equipment health threshold, calculate the stability coefficient based on the volatility of the environmental sensing data in the previous dynamic calculation period.

[0079] Optionally, the receiving module 10 is further configured to acquire the park planning map of the total metering type zero-carbon park; identify the park boundary of the total metering type zero-carbon park from the park planning map, and the carbon emission sources and zero carbon sources within the park boundary range, and classify the emission sources and the zero carbon sources respectively to obtain classification results; construct the carbon source-zero carbon source list of the total metering type zero-carbon park based on the classification results; and receive carbon source data and zero carbon source data collected by the data acquisition terminal in the total metering type zero-carbon park based on the carbon source-zero carbon source list during the dynamic accounting cycle.

[0080] Optionally, the receiving module 10 is further configured to, based on a preset Laida criterion, remove outliers from the carbon source data and the zero carbon source data to obtain preprocessed carbon source data and preprocessed zero carbon source data; identify missing values ​​from the preprocessed carbon source data and the preprocessed zero carbon source data, and fill in the missing values ​​to obtain complete carbon source data and complete zero carbon source data; and perform standardization processing on the complete carbon source data and the complete zero carbon source data to obtain standardized carbon source data and zero carbon source data.

[0081] The carbon footprint dynamic accounting device provided in this application, employing the carbon footprint dynamic accounting method described in the above embodiments, can solve the technical problem of low carbon footprint and accounting accuracy for total metering-based zero-carbon parks. Compared with the prior art, the beneficial effects of the carbon footprint dynamic accounting device provided in this application are the same as those of the carbon footprint dynamic accounting method provided in the above embodiments, and other technical features in the carbon footprint dynamic accounting device are the same as those disclosed in the methods of the above embodiments, and will not be repeated here.

[0082] This application provides a dynamic carbon footprint calculation device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the dynamic carbon footprint calculation method in the first embodiment described above.

[0083] The following is for reference. Figure 5The diagram illustrates a structural schematic suitable for implementing the dynamic carbon footprint accounting device of the embodiments of this application. The dynamic carbon footprint accounting device in the embodiments of this application may include, but is not limited to, mobile terminals such as mobile phones, laptops, digital radio receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Description), PMPs (Portable Media Players), in-vehicle terminals (e.g., in-vehicle navigation terminals), and fixed terminals such as digital TVs and desktop computers. Figure 5 The carbon footprint dynamic accounting device shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of this application.

[0084] like Figure 5 As shown, the carbon footprint dynamic accounting device may include a processing unit 1001 (e.g., a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 1002 or a program loaded from a storage device 1003 into a random access memory (RAM) 1004. The RAM 1004 also stores various programs and data required for the operation of the carbon footprint dynamic accounting device. The processing unit 1001, ROM 1002, and RAM 1004 are interconnected via a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to the I / O interface 1006: input devices 1007 including, for example, a touchscreen, touchpad, keyboard, mouse, image sensor, microphone, accelerometer, gyroscope, etc.; output devices 1008 including, for example, a liquid crystal display (LCD), speaker, vibrator, etc.; storage devices 1003 including, for example, magnetic tape, hard disk, etc.; and communication devices 1009. Communication device 1009 allows the carbon footprint dynamic accounting device to communicate wirelessly or wiredly with other devices to exchange data. While the figure shows carbon footprint dynamic accounting devices with various systems, it should be understood that implementation or possession of all the systems shown is not required. More or fewer systems may be implemented alternatively.

[0085] Specifically, according to the embodiments disclosed in this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments disclosed in this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device, or installed from storage device 1003, or installed from ROM 1002. When the computer program is executed by processing device 1001, it performs the functions defined in the methods of the embodiments disclosed in this application.

[0086] The carbon footprint dynamic accounting device provided in this application, employing the carbon footprint dynamic accounting method described in the above embodiments, can solve the technical problem of low carbon footprint and accounting accuracy for total metering-based zero-carbon parks. Compared with the prior art, the beneficial effects of the carbon footprint dynamic accounting device provided in this application are the same as those of the carbon footprint dynamic accounting method provided in the above embodiments, and other technical features in this carbon footprint dynamic accounting device are the same as those disclosed in the previous embodiment method, and will not be repeated here.

[0087] It should be understood that the various parts disclosed in this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any suitable manner in one or more embodiments or examples.

[0088] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0089] This application provides a computer-readable storage medium having computer-readable program instructions (i.e., a computer program) stored thereon, which are used to execute the dynamic carbon footprint calculation method in the above embodiments.

[0090] The computer-readable storage medium provided in this application may be, for example, a USB flash drive, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, system, or device. The program code contained on the computer-readable storage medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination thereof.

[0091] The aforementioned computer-readable storage medium may be included in the carbon footprint dynamic accounting device; or it may exist independently and not be assembled into the carbon footprint dynamic accounting device.

[0092] The aforementioned computer-readable storage medium carries one or more programs. When these programs are executed by the carbon footprint dynamic accounting device, the carbon footprint dynamic accounting device: receives carbon source data and zero carbon source data collected by data collection terminals within the total metering-type zero-carbon park during the dynamic accounting period, wherein the data collection terminals include fixed data collection terminals and mobile supplementary data collection terminals; performs carbon emission accounting on the carbon source data to obtain carbon emission amounts; performs dynamic deduction accounting on the zero carbon source data to obtain zero carbon deduction amounts; and obtains real-time net carbon footprint data of the total metering-type zero-carbon park based on the carbon emission amounts and the zero carbon deduction amounts.

[0093] Computer program code for performing the operations of this application can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a Local Area Network (LAN) or a Wide Area Network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0094] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0095] The modules described in the embodiments of this application can be implemented in software or hardware. The names of the modules do not necessarily limit the functionality of the unit itself.

[0096] The readable storage medium provided in this application is a computer-readable storage medium that stores computer-readable program instructions (i.e., a computer program) for executing the above-described dynamic carbon footprint accounting method, which can solve the technical problem of low carbon footprint and accounting accuracy in total metering-type zero-carbon parks. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as the beneficial effects of the dynamic carbon footprint accounting method provided in the above embodiments, and will not be repeated here.

[0097] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the dynamic carbon footprint calculation method described above.

[0098] The computer program product provided in this application can solve the technical problem of low carbon footprint and accounting accuracy in total metering-based zero-carbon parks. Compared with the prior art, the beneficial effects of the computer program product provided in this application are the same as those of the dynamic carbon footprint accounting method provided in the above embodiments, and will not be repeated here.

[0099] The above description is only a part of the embodiments of this application and does not limit the scope of protection of this application. All equivalent structural transformations made under the technical concept of this application and using the content of this application specification and drawings, or direct / indirect applications in other related technical fields, are included in the scope of protection of this application.

Claims

1. A method for dynamic carbon footprint accounting, characterized in that, The method includes: The system receives carbon source data and zero carbon source data collected by the data acquisition terminal in the zero-carbon park within the total metering type during the dynamic accounting cycle. The data acquisition terminal includes a fixed data acquisition terminal and a mobile supplementary data acquisition terminal. Carbon emission calculations are performed on the carbon source data to obtain the carbon emission amount; The zero-carbon source data is dynamically deducted to obtain the zero-carbon deduction amount; Based on the carbon emissions and the zero carbon credit, the real-time net carbon footprint data of the total metering zero-carbon park is obtained.

2. The method as described in claim 1, characterized in that, The step of dynamically calculating the zero-carbon source data to obtain the zero-carbon deduction amount includes: The zero-carbon source data is classified to determine the deduction type of the zero-carbon source; Based on the zero-carbon source data and the corresponding dynamic deduction coefficient, the deductible carbon emissions of each of the deduction types of zero-carbon sources are determined. The dynamic deduction coefficient changes dynamically with the dynamic accounting cycle. The carbon emission credits of each of the zero carbon sources are summed up to obtain the zero carbon credit amount.

3. The method as described in claim 2, characterized in that, Before the step of classifying the zero-carbon source data and determining the deduction type of the zero-carbon source, the method further includes: Obtain historical data of zero carbon sources within the previous dynamic accounting period; Based on the historical data of the zero carbon sources, the utilization rate of each zero carbon source and the stability coefficient of the energy generated by each zero carbon source in the previous dynamic accounting period were analyzed. Based on the utilization rate and the stability coefficient, the historical dynamic deduction coefficients of each of the zero carbon sources used in the previous dynamic accounting cycle are adjusted to obtain the dynamic deduction coefficients required for the current dynamic accounting cycle.

4. The method as described in claim 3, characterized in that, The method for analyzing the stability coefficient of energy generated by each zero-carbon source in the previous dynamic accounting period based on the historical data of the zero-carbon source includes: Environmental sensing data matching the type of zero carbon source are selected from the historical data of the zero carbon source, as well as the power generation time series of each of the zero carbon sources; The power generation time series is time-aligned with the environmental sensing data to construct an environment-power generation correlation curve, and the goodness-of-fit index of the environment-power generation correlation curve is determined. If the goodness-of-fit index is lower than the preset equipment health threshold, the stability coefficient of the corresponding zero carbon source will be set to the attenuation correction coefficient determined based on the equipment's operating years. If the goodness-of-fit index is not lower than the device health threshold, the stability coefficient is calculated based on the volatility of the environmental perception data in the previous dynamic accounting period.

5. The method as described in claim 1, characterized in that, Before the step of receiving carbon source data and zero carbon source data collected by the data acquisition terminal in the zero-carbon park within the dynamic accounting cycle, the method further includes: Obtain the park planning map of the total metering-type zero-carbon park; Identify the boundary of the total metering-type zero-carbon park from the park planning map, and identify the carbon emission sources and zero-carbon sources within the boundary of the park. Then, classify the emission sources and the zero-carbon sources respectively to obtain the classification results. Based on the classification results, a carbon source-zero carbon source list for a total table-based zero-carbon park is constructed. The step of receiving carbon source data and zero carbon source data collected by the data acquisition terminal in the metering-type zero-carbon park during the dynamic accounting cycle also includes: The system receives carbon source data and zero carbon source data collected by the data acquisition terminal in the master metering-type zero carbon park within the dynamic accounting cycle, based on the carbon source-zero carbon source list.

6. The method as described in claim 1, characterized in that, After the step of receiving the carbon source data and zero carbon source data collected by the data acquisition terminal in the zero-carbon park within the dynamic accounting cycle, the method further includes: Based on the preset Laida criterion, outliers in the carbon source data and the zero carbon source data are removed to obtain preprocessed carbon source data and preprocessed zero carbon source data. Missing values ​​are identified from the preprocessed carbon source data and the preprocessed zero carbon source data, and the missing values ​​are filled in to obtain complete carbon source data and complete zero carbon source data. The complete carbon source data and the complete zero carbon source data are standardized to obtain standardized carbon source data and zero carbon source data.

7. A dynamic carbon footprint accounting device, characterized in that, The device includes: The receiving module is used to receive carbon source data and zero carbon source data collected by the data collection terminal in the total metering zero carbon park during the dynamic accounting cycle. The data collection terminal includes a fixed data collection terminal and a mobile supplementary data collection terminal. The accounting module is used to perform carbon emission accounting on the carbon source data to obtain carbon emission amounts; and to perform dynamic deduction accounting on the zero carbon source data to obtain zero carbon deduction amounts. The summary module is used to obtain real-time net carbon footprint data of the total metering zero-carbon park based on the carbon emissions and the zero carbon deduction.

8. A dynamic carbon footprint accounting device, characterized in that, The device includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the dynamic carbon footprint accounting method as described in any one of claims 1 to 6.

9. A storage medium, characterized in that, The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, it implements the steps of the dynamic carbon footprint accounting method as described in any one of claims 1 to 6.

10. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the steps of the dynamic carbon footprint accounting method as described in any one of claims 1 to 6.

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