Park energy consumption and carbon emission automatic accounting system

Abstract

The invention relates to the technical field of energy management, in particular to a park energy consumption and carbon emission automatic accounting system which comprises a region division module, an energy monitoring module, a data processing module, an intelligent matching module, a dynamic carbon factor adjustment module, a cross-region cooperation module and a report generation module. Wherein the region division module is used for dividing a park into a plurality of sub-regions; the energy monitoring module is used for monitoring energy consumption data; the data processing module is used for generating a standardized data set; the intelligent proportioning module is used for generating a reference proportioning model; the dynamic carbon factor adjusting module is used for dynamically adjusting the carbon emission factor of each area; and the cross-region collaboration module is used for integrating the carbon emission data of the plurality of sub-regions. According to the method, the data accuracy and the management efficiency are improved by monitoring and dynamically adjusting the carbon emission factors, and meanwhile, the data consistency is ensured by unifying the cross-region accounting rule, so that the energy management is optimized, and the environmental compliance risk is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of energy management, and in particular to an automatic accounting system for energy consumption and carbon emissions in a park. Background Art

[0002] With the increasing attention paid to environmental protection and sustainable development around the world, energy consumption and carbon emission management in parks has become a key issue. Currently, there are many types of parks, such as industrial parks, commercial parks, and comprehensive parks, with complex energy consumption structures and significant differences. Traditional energy consumption and carbon emission monitoring methods often rely on manual data collection and static calculation methods, which cannot reflect the dynamic energy consumption of each sub-area in the park in real time. Especially when it involves multiple energy types (such as electricity, water and gas) and cross-regional management, the existing system lacks unified monitoring standards and accounting rules, making it difficult to achieve accurate and efficient management.

[0003] Existing technologies have many deficiencies in solving carbon emission accounting in complex energy scenarios and carbon emission management in cross-regional parks. First, due to the different functional attributes and energy usage patterns of different sub-regions, large errors are easily generated in the monitoring and accounting process, and the actual carbon emissions of each sub-region cannot be accurately reflected. Secondly, due to the inconsistency of carbon emission standards and management rules in cross-regional parks, carbon emission data is difficult to integrate, which ultimately affects the overall carbon emission management effect.

[0004] Therefore, there is an urgent need for a system that can comprehensively consider the complex energy usage scenarios within the park and achieve unified carbon emission accounting under cross-regional conditions, so as to solve the problems of inaccurate data and inconsistent management in existing technologies, thereby improving the accuracy and efficiency of energy consumption and carbon emission management. Summary of the invention

[0005] Based on the above purpose, the present invention provides an automatic accounting system for park energy consumption and carbon emissions.

[0006] The automatic accounting system for energy consumption and carbon emissions in the park includes a regional division module, an energy monitoring module, a data processing module, an intelligent ratio module, a dynamic carbon factor adjustment module, a cross-regional collaboration module and a report generation module, among which:

[0007] Area division module: used to divide the park into multiple sub-areas, assign a unique identifier to each sub-area, classify the areas based on geographical location, functional attributes and energy usage patterns, and pass the classification information to the energy monitoring module and the intelligent allocation module;

[0008] Energy monitoring module: connected with the regional division module, based on the classification information provided by the regional division module, it monitors the energy consumption data of each sub-region in real time, and transmits the data to the data processing module after marking it by region;

[0009] Data processing module: receives the labeled data from the energy monitoring module, performs data cleaning and preliminary processing, and generates a standardized data set;

[0010] Intelligent matching module: Based on the regional information provided by the regional division module and the data processed by the data processing module, it generates a benchmark matching model to correct the deviation in the monitoring data;

[0011] Dynamic carbon factor adjustment module: receives the benchmark matching model generated by the intelligent matching module and the processed data provided by the data processing module, and dynamically adjusts the carbon emission factor of each area based on the real-time energy consumption and carbon emission standards of each sub-area;

[0012] Cross-regional collaboration module: receives carbon emission factor data provided by the dynamic carbon factor adjustment module, and integrates carbon emission data of multiple sub-regions to ensure that the accounting rules between multiple sub-regions are consistent;

[0013] Report generation module: Generates energy consumption and carbon emission reports for each sub-region and across regions based on the energy consumption data provided by the data processing module and the unified accounting rules provided by the cross-regional collaboration module.

[0014] Optionally, the region division module includes a region identification unit, a classification calculation unit and an identifier allocation unit; wherein:

[0015] Area identification unit: Based on the geographic information system data of the park, it identifies and divides the physical areas of the park, divides the park into multiple sub-areas using the pre-stored geographic location data, and transmits the boundary information of these sub-areas to the classification calculation unit;

[0016] Classification calculation unit: receives the sub-region boundary information provided by the region identification unit, calculates the energy use type and intensity of each sub-region based on the functional attributes and historical energy consumption patterns of each sub-region, and classifies each sub-region according to the calculation results;

[0017] Identifier allocation unit: receives the classification result of the classification calculation unit, and assigns a unique identifier to each sub-region, wherein the identifier includes a code indicating the geographic location of the sub-region, a functional attribute tag, and an energy use mode tag.

[0018] Optionally, the classification calculation unit includes:

[0019] Calculate the functional attribute weight: Receive the sub-region boundary information provided by the region recognition unit and obtain the functional attribute parameter F related to each sub-region i , where the functional attribute parameters include the use type of the sub-area and the functional attribute weight W is calculated F , the formula is: Among them, W F represents the weight of functional attributes, n is the number of functional attributes, k i Represents the weight coefficient of each functional attribute, F i Indicates the specific value of each functional attribute;

[0020] Calculate the weight of historical energy consumption patterns: Obtain the historical energy consumption data of each sub-region from the database and calculate the average consumption of each energy source E j , and then calculate the historical energy consumption pattern weight W by the following formula E , the formula is: Among them, W E represents the weight of historical energy consumption pattern, m is the number of energy types, c j Indicates the consumption coefficient of each energy source, E j Indicates the average consumption of each energy source;

[0021] Calculate the comprehensive energy intensity: Substitute the functional attribute weight W F and historical energy consumption pattern weight W E The comprehensive energy intensity S of each sub-region is calculated by synthesis, and the formula is: S = α × W F +β×W E , where S represents the comprehensive energy intensity, α and β are the functional attribute weights W F and historical energy consumption pattern weight W E The adjustment coefficient of

[0022] According to the calculation results of the comprehensive energy use intensity S, the sub-areas are divided into high energy consumption areas, medium energy consumption areas, and low energy consumption areas according to the preset classification standards.

[0023] Optionally, the energy monitoring module includes an energy consumption collection unit, a data marking unit and a data transmission unit; wherein:

[0024] Energy consumption collection unit: used to arrange energy monitoring equipment in each sub-area based on the classification information provided by the area division module, and collect energy consumption data of each sub-area in real time, including the consumption of electricity, water and gas;

[0025] Data marking unit: receives the real-time energy consumption data provided by the energy consumption collection unit, and adds a unique area identifier to the energy consumption data of each sub-area according to the sub-area classification information provided by the area division module, so as to ensure that each energy consumption data is marked as the corresponding sub-area data;

[0026] Data transmission unit: receives the energy consumption data marked by the data marking unit, and transmits the data to the data processing module by region through a wired or wireless network.

[0027] Optionally, the data processing module includes a data receiving unit, a data cleaning unit, a data standardization unit and a data storage unit; wherein:

[0028] Data receiving unit: used to receive energy consumption data marked by region from the energy monitoring module, including real-time consumption data of electricity, water and gas;

[0029] Data cleaning unit: used to check the integrity and accuracy of the data after receiving the data transmitted by the data receiving unit, and correct the data by eliminating or correcting abnormal values, duplicate data and missing data;

[0030] Data standardization unit: used to receive the cleaned data transmitted by the data cleaning unit, unify the units and align the time series of the energy consumption data of each sub-area, and generate a standardized data set;

[0031] Data storage unit: used to receive the standardized data set generated by the data standardization unit, and store the data by sub-region and energy type through a structured database or data warehouse.

[0032] Optionally, the intelligent matching module includes a regional analysis unit, a historical data analysis unit, a benchmark matching model generation unit and a data correction unit; wherein:

[0033] Regional analysis unit: used to receive regional information provided by the regional division module, including the geographical location, functional attributes and energy use type of each sub-region, and analyze and determine the energy demand characteristics and potential energy consumption patterns of each sub-region;

[0034] Historical data analysis unit: receives the standardized data set processed by the data processing module, and analyzes the historical energy consumption data of each sub-region in combination with the regional information provided by the regional analysis unit, and calculates the usage ratio P of each energy type in different periods. j ;

[0035] Benchmark ratio model generation unit: receives the historical energy usage ratio P from the historical data analysis unit j, combined with the regional characteristic information provided by the regional analysis unit, a benchmark ratio model reflecting the energy use characteristics of each sub-region is generated; the expression of the benchmark ratio model is: Among them, M k represents the benchmark ratio model of the kth sub-region, P j is the historical energy use ratio, W j is the weight of each energy type;

[0036] Data correction unit: receives the benchmark ratio model provided by the benchmark ratio model generation unit, and compares it with the real-time monitoring data to correct the deviation in the monitoring data.

[0037] Optionally, the regional analysis unit specifically includes:

[0038] Regional feature extraction: Receive regional information provided by the regional division module, including the geographical location, functional attributes, building area and use type data of the sub-region, and extract the characteristic parameters of each sub-region through analysis, including the functional attribute weight of the sub-region, building density and energy demand coefficient related to use;

[0039] Demand forecasting unit: Based on the extracted characteristic parameters and combined with the historical energy usage data of each sub-region, the energy demand of the sub-region is predicted using the following formula: Among them, E pred represents the predicted energy demand of the sub-region, R i is the energy demand correlation coefficient of the ith sub-region, A i is the parameter related to demand, n is the number of factors affecting energy demand;

[0040] Consumption pattern recognition: Receive the predicted energy demand data, and use the pattern recognition algorithm to identify the energy consumption pattern of each sub-region in combination with the functional attribute weights provided by the regional feature extraction; the pattern recognition algorithm first compares the historical energy consumption data with the predicted energy demand data to identify the historical consumption pattern that best matches the current regional characteristics: then, based on the matching results of the historical patterns and the characteristics of the current region, predict the future energy consumption pattern, the formula is: Among them, E mode is the predicted energy consumption pattern, P j is the usage ratio of the jth energy in the historical model, F j is the corresponding functional attribute influence coefficient, and m is the number of energy types.

[0041] Optionally, the dynamic carbon factor adjustment module includes a real-time data receiving unit, a carbon emission factor calculation unit and a dynamic adjustment unit; wherein:

[0042] Real-time data receiving unit: used to receive the benchmark matching model from the intelligent matching module and the standardized processing data provided by the data processing module, including the real-time energy consumption data of each sub-region. The real-time data receiving unit associates the received benchmark matching model with the standardized processing data, and transmits the associated data to the carbon emission factor calculation unit;

[0043] Carbon emission factor calculation unit: Based on the associated data transmitted by the real-time data receiving unit, the carbon emission calculation is performed on the energy consumption data of each sub-region according to the preset carbon emission standard. Specifically, the carbon emission C of each energy source is calculated based on the energy consumption data of each sub-region. j ; Then the carbon emissions of each energy type are integrated into the total carbon emissions of each sub-region C total , the formula is: Among them, C total is the total carbon emission of a sub-region, m is the total number of energy types in the sub-region, and the calculated total carbon emission will be transferred to the dynamic adjustment unit for dynamic adjustment;

[0044] Dynamic adjustment unit: Receives the total carbon emissions of each sub-region provided by the carbon emission factor calculation unit, and dynamically adjusts the carbon emission factors of each region in combination with the benchmark matching model generated by the intelligent matching module. Specifically, the difference value D is calculated by comparing the actual carbon emissions of each sub-region with the expected carbon emissions under the benchmark matching model. k , the formula is: D k =C total -C expected , where D k is the carbon emission difference value of the kth sub-region, C total is the actual total carbon emissions, C expected is the expected carbon emissions under the benchmark matching model; and according to the difference value D k The carbon emission factor of each sub-region is dynamically adjusted to ensure that the adjusted carbon emissions are consistent with the benchmark ratio model. The adjusted carbon emission factor is set as F j ′, the calculation formula is: Among them, F j ′ is the adjusted carbon emission factor, F j is the original carbon emission factor, D k is the difference value, C expected is the expected carbon emissions.

[0045] Optionally, the cross-regional collaboration module includes a data integration unit, a rule consistency checking unit and an inter-regional balancing unit; wherein:

[0046] Data integration unit: used to receive the carbon emission factor data of each sub-region from the dynamic carbon factor adjustment module, and make a preliminary summary, and generate a cross-regional carbon emission factor data set by classifying and combining the carbon emission factor data of different sub-regions according to the predetermined regional grouping rules;

[0047] Rule consistency check unit: Receives the cross-regional carbon emission factor data set generated by the data integration unit, and checks whether the carbon emission factor of each sub-region complies with the preset unified accounting rules one by one, ensuring that all regions use consistent standards when calculating carbon emissions. Specifically, the following formula is used to verify consistency:

[0048] in, represents the consistency check coefficient, F actual is the carbon emission factor actually used, F standard is the preset standard carbon emission factor, when When the range of deviation from 1 exceeds the preset tolerance value, the factor of the corresponding area will be marked as inconsistent;

[0049] Inter-regional balancing unit: used to adjust the areas marked as inconsistent by the rule consistency check unit to ensure that the carbon emission accounting rules between different sub-regions are consistent. Specifically, the carbon emission factors of inconsistent areas are adjusted to meet the standard carbon emission factors. The adjustment formula is: Among them, F adjusted ′ is the adjusted carbon emission factor, ΔF is the difference between the actual factor and the standard factor, and F standard as the standard factor; and globally balance the adjusted carbon emission factors to ensure that the total carbon emissions between regions are relatively consistent, and ultimately form a unified cross-regional carbon emission factor data set.

[0050] Optionally, the report generation module includes a data aggregation unit, a report formatting unit and a report output unit; wherein:

[0051] Data aggregation unit: used to receive the standardized energy consumption data from the data processing module and the unified carbon emission factor data provided by the cross-regional collaboration module, comprehensively aggregate the data according to the sub-regional and cross-regional dimensions, associate the energy consumption data of each sub-region with the corresponding carbon emission factor, generate the energy consumption and carbon emission data set for each sub-region, and integrate the data sets of all sub-regions into a unified cross-regional energy consumption and carbon emission data set;

[0052] Report formatting unit: receives the energy consumption and carbon emission data sets of each sub-region and across regions generated by the data aggregation unit, and formats the data according to the preset report template. The preset report template includes regional data collation, cross-regional data integration and formatting;

[0053] The sub-regional data arrangement is used to arrange the energy consumption data and carbon emission data in the order of the sub-regions;

[0054] Cross-regional data integration is used to integrate cross-regional energy consumption and carbon emission data to generate an overview chart of overall energy consumption and carbon emissions;

[0055] Formatting is used to standardize the report content according to preset format requirements, including PDF or Excel;

[0056] Report output unit: used to receive the report data processed by the report formatting unit, and output the report in multiple formats according to user needs, including PDF, Excel and web page formats.

[0057] Beneficial effects of the present invention:

[0058] The present invention significantly improves the real-time and accuracy of energy management and carbon emission accounting by integrating advanced monitoring and data processing technologies. By realizing real-time monitoring of energy consumption in each sub-area and dynamic adjustment of carbon emission factors, it can provide more accurate energy usage and carbon emission data. This precise data feedback mechanism not only helps park managers to make immediate energy adjustments and optimize decisions, but also significantly reduces environmental compliance risks caused by data errors.

[0059] The present invention ensures the consistency of carbon emission management across regions by unifying accounting rules, and effectively solves the accounting problems caused by inconsistent standards in traditional methods. This feature makes the system particularly suitable for large parks across multiple administrative or functional areas, and provides highly consistent and standardized outputs for data reporting within the park and with external regulatory agencies. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only for the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0061] Figure 1 A schematic diagram of a system for automatically calculating energy consumption and carbon emissions in a park according to an embodiment of the present invention;

[0062] Figure 2 Schematic diagram of a region division module according to an embodiment of the present invention. DETAILED DESCRIPTION

[0063] The present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments. At the same time, it is explained here that in order to make the embodiments more detailed, the following embodiments are the best and preferred embodiments, and those skilled in the art may also adopt other alternatives to implement some known technologies; and the accompanying drawings are only for more specific description of the embodiments, and are not intended to specifically limit the present invention.

[0064] It should be noted that the references to "one embodiment", "an embodiment", "an exemplary embodiment", "some embodiments" and the like in the specification indicate that the embodiments described may include specific features, structures or characteristics, but not every embodiment may include the specific features, structures or characteristics. In addition, when a specific feature, structure or characteristic is described in conjunction with an embodiment, it should be within the knowledge of a person skilled in the art to implement such feature, structure or characteristic in conjunction with other embodiments (whether or not explicitly described).

[0065] In general, a term can be understood, at least in part, from its use in context. For example, depending, at least in part, on the context, the term "one or more" as used herein can be used to describe any feature, structure, or characteristic in the singular sense, or can be used to describe a combination of features, structures, or characteristics in the plural sense. Additionally, the term "based on" can be understood as not necessarily intended to convey an exclusive set of factors, but can instead, depending, at least in part, on the context, allow for the presence of other factors that are not necessarily explicitly described.

[0066] like Figure 1-Figure 2 As shown in the figure, the automatic accounting system for energy consumption and carbon emissions in the park includes a regional division module, an energy monitoring module, a data processing module, an intelligent ratio module, a dynamic carbon factor adjustment module, a cross-regional collaboration module and a report generation module, among which:

[0067] Regional division module: used to divide the park into multiple sub-areas and assign a unique identifier to each sub-area. It classifies the areas based on geographical location, functional attributes and energy usage patterns, and transmits the classification information to the energy monitoring module and the intelligent allocation module to guide subsequent monitoring and data analysis.

[0068] Energy monitoring module: connected with the regional division module, based on the classification information provided by the regional division module, it monitors the energy consumption data of each sub-region in real time, and transmits the data to the data processing module after marking it by region for further analysis and processing;

[0069] Data processing module: receives the marked data from the energy monitoring module, performs data cleaning and preliminary processing, generates a standardized data set, and transmits the data set to the intelligent proportioning module and the dynamic carbon factor adjustment module, while retaining detailed data records for report generation;

[0070] Intelligent matching module: Based on the regional information provided by the regional division module and the data processed by the data processing module, it generates a benchmark matching model to correct the deviation in the monitoring data, and feeds the corrected data back to the data processing module to ensure the accuracy of the data;

[0071] Dynamic carbon factor adjustment module: receives the benchmark matching model generated by the intelligent matching module and the processed data provided by the data processing module, dynamically adjusts the carbon emission factor of each area based on the real-time energy consumption and carbon emission standards of each sub-area, and returns the adjusted factor data to the data processing module;

[0072] Cross-regional collaboration module: Receives carbon emission factor data provided by the dynamic carbon factor adjustment module, integrates carbon emission data of multiple sub-regions, ensures consistency of accounting rules among multiple sub-regions, and passes the integrated unified rules to the report generation module;

[0073] Report generation module: Based on the energy consumption data provided by the data processing module and the unified accounting rules provided by the cross-regional collaboration module, it generates energy consumption and carbon emission reports for each sub-region and across regions, and supports output in multiple formats to meet user needs.

[0074] The region division module includes a region identification unit, a classification calculation unit and an identifier allocation unit; wherein:

[0075] Area identification unit: Based on the park's geographic information system (GIS) data, it identifies and divides the park's physical areas, divides the park into multiple sub-areas using pre-stored geographic location data, and transmits the boundary information of these sub-areas to the classification calculation unit;

[0076] Classification calculation unit: receives the sub-region boundary information provided by the region identification unit, calculates the energy use type and intensity of each sub-region based on the functional attributes (such as industry, commerce, office, etc.) and historical energy consumption patterns of each sub-region, and classifies each sub-region according to the calculation results, and transmits the classification results to the identifier allocation unit;

[0077] Identifier allocation unit: Receives the classification results of the classification calculation unit and assigns a unique identifier to each sub-area. The identifier includes a code indicating the geographical location of the sub-area, a functional attribute tag, and an energy usage pattern tag, which is used to uniquely identify and manage each sub-area in the subsequent energy monitoring and data processing process. Through the organic combination of the above units, the regional division module can accurately and systematically divide the park into multiple sub-areas and assign a unique identifier to each sub-area, thereby realizing accurate classification and management based on geographical location, functional attributes and energy usage patterns.

[0078] The classification calculation unit includes:

[0079] Calculate the functional attribute weight: Receive the sub-region boundary information provided by the region recognition unit and obtain the functional attribute parameter F related to each sub-region i , where the functional attribute parameters include the use type of the sub-area (such as industry, commerce, office, etc.), and the functional attribute weight W is calculated F , the formula is: Among them, W F represents the weight of functional attributes, n is the number of functional attributes, k i Represents the weight coefficient of each functional attribute, F i Indicates the specific value of each functional attribute;

[0080] Calculate the weight of historical energy consumption patterns: Obtain the historical energy consumption data of each sub-region from the database and calculate the average consumption of each energy source E j (including electricity, water, gas, etc.), and then calculate the historical energy consumption pattern weight W through the following formula E , the formula is: Among them, W E represents the weight of historical energy consumption pattern, m is the number of energy types, c j Indicates the consumption coefficient of each energy source, E j Indicates the average consumption of each energy source;

[0081] Calculate the comprehensive energy intensity: Substitute the functional attribute weight W F and historical energy consumption pattern weight W E The comprehensive energy intensity S of each sub-region is calculated by synthesis, and the formula is: S = α × W F +β×W E , where S represents the comprehensive energy intensity, α and β are the functional attribute weights W F and historical energy consumption pattern weight W E The adjustment coefficient is used to adjust the impact ratio of functional attributes and historical energy consumption according to specific needs;

[0082] Based on the calculation results of the comprehensive energy intensity S, the sub-areas are divided into high energy consumption area, medium energy consumption area and low energy consumption area according to the preset classification standards;

[0083] The preset classification criteria are as follows:

[0084] When the comprehensive energy usage intensity S is greater than the preset upper limit When , the sub-area is classified as a high energy consumption area;

[0085] When the comprehensive energy use intensity S is between the preset upper limit With the preset lower limit S low When it is between , the sub-area is classified as medium energy consumption area;

[0086] When the comprehensive energy use intensity S is less than the preset lower limit S low , the sub-area is classified as a low energy consumption area, where Indicates the preset upper limit of comprehensive energy intensity, S low Represents the preset lower limit of the comprehensive energy use intensity. These two values ​​are set according to the specific management requirements and energy use targets of the park. Through the above steps, the classification calculation unit can accurately calculate the energy use type and intensity of each sub-area, and divide each sub-area into different categories based on clear classification standards, thereby providing a scientific basis for the energy management and carbon emission accounting of the park.

[0087] The energy monitoring module includes an energy consumption collection unit, a data marking unit and a data transmission unit; wherein:

[0088] Energy consumption collection unit: Based on the classification information provided by the area division module, energy monitoring equipment is arranged in each sub-area to collect the energy consumption data of each sub-area in real time, including the consumption of electricity, water and gas. The energy consumption collection unit obtains the instant consumption data of each energy by connecting with the monitoring equipment of the electricity meter, water meter and gas meter, and stores these data separately for subsequent processing;

[0089] Data marking unit: receives the real-time energy consumption data provided by the energy consumption collection unit, and adds a unique regional identifier to the energy consumption data of each sub-region according to the sub-region classification information provided by the regional division module, so as to ensure that each energy consumption data is marked as the corresponding sub-region data, thereby ensuring the accuracy and traceability of the data in the subsequent processing process;

[0090] Data transmission unit: Receives energy consumption data marked by the data marking unit, and transmits the data to the data processing module by region through a wired or wireless network. The data transmission unit uses an encryption protocol to ensure the security of the data during transmission, and generates a transmission log for monitoring after the data transmission is completed. Through the synergy of the above units, the energy monitoring module can monitor the energy consumption data of each sub-region in real time and accurately based on the classification information provided by the regional division module, and after adding a regional identifier to the data, the data is securely transmitted to the data processing module for subsequent analysis and processing.

[0091] The data processing module includes a data receiving unit, a data cleaning unit, a data standardization unit and a data storage unit; wherein:

[0092] Data receiving unit: used to receive energy consumption data marked by region from the energy monitoring module, including real-time consumption data of electricity, water and gas, ensure the integrity and accuracy of all data packets through a stable network connection, and pass the received data to the data cleaning unit;

[0093] Data cleaning unit: used to check the integrity and accuracy of the data after receiving the data transmitted by the data receiving unit, and correct the data by eliminating or correcting abnormal values, duplicate data and missing data;

[0094] The integrity check is used to check whether each data record contains all the required field information. If the data is missing, it is marked as invalid data. The integrity index is calculated by the following formula: Among them, C represents the integrity index, N f is the number of records containing complete data fields, N t is the total number of data records, when C <C min When (C min is a preset integrity threshold), the data is marked as invalid;

[0095] The accuracy check is used to verify the range of each data value to ensure that it is within a reasonable range. If the data exceeds the preset range, it is corrected to the most recent valid value, or corrected based on historical data interpolation. The following algorithm is used for correction:

[0096]

[0097] Among them, D c is the corrected data, D is the original data, and D min and D max is the reasonable range of the data. If the data D is missing, the two valid data points before and after D are used. prev and D nextThe average value is interpolated, and the cleaned data is passed to the data standardization unit for further processing;

[0098] Data standardization unit: used to receive the cleaned data transmitted by the data cleaning unit, unify the units and align the time series of the energy consumption data of each sub-region, ensure the comparability of data between different sub-regions and energy types, and generate a standardized data set and transmit it to the data storage unit;

[0099] Unit unification is used to convert different types of energy consumption data into the same unit (such as converting all energy consumption into standard coal equivalent). The conversion formula is: E s =E×U f , where E s is the standardized energy consumption data after unification, E is the original energy consumption data, U f The unit conversion factor for the corresponding energy type (for example, the factor for converting electrical energy into standard coal equivalent);

[0100] Time series alignment is used to align the energy consumption data at different time intervals to ensure that the energy consumption data of all sub-areas are compared on the same time scale. The alignment formula is: Among them, E a (t) is the energy consumption data after alignment, Δt is the time interval, E i (t i ) is the original energy consumption data, n is the number of data points in the time period;

[0101] Data storage unit: used to receive the standardized data set generated by the data standardization unit, and store the data by sub-region and energy type through a structured database or data warehouse to ensure the security and scalability of the data for the intelligent matching module and the dynamic carbon factor adjustment module to call; through the synergy of the above units, the data processing module can effectively receive and process the labeled data from the energy monitoring module, clean and standardize the data through preset rules and algorithms, and generate a unified, structured, standardized data set, providing a reliable data basis for subsequent energy analysis and carbon emission calculations.

[0102] The intelligent matching module includes a regional analysis unit, a historical data analysis unit, a benchmark matching model generation unit and a data correction unit; wherein:

[0103] Regional analysis unit: used to receive regional information provided by the regional division module, including the geographical location, functional attributes and energy use type of each sub-region, and analyze and determine the energy demand characteristics and potential energy consumption patterns of each sub-region, and transmit the analysis results to the historical data analysis unit;

[0104] Historical data analysis unit: receives the standardized data set processed by the data processing module, and analyzes the historical energy consumption data of each sub-region in combination with the regional information provided by the regional analysis unit, and calculates the usage ratio P of each energy type in different periods. j , the formula is: Among them, P j represents the proportion of the jth energy used in a specific sub-region, E j is the consumption of the jth energy in the sub-region during a certain period of time, and m is the total number of energy types used in the sub-region;

[0105] Benchmark ratio model generation unit: receives the historical energy usage ratio P from the historical data analysis unit j , combined with the regional characteristic information provided by the regional analysis unit, a benchmark ratio model reflecting the energy use characteristics of each sub-region is generated; the expression of the benchmark ratio model is: Among them, M k represents the benchmark ratio model of the kth sub-region, P j is the historical energy use ratio, W j is the weight of each energy type, which is set according to the functional attributes and energy usage characteristics of the region;

[0106] Data correction unit: receives the benchmark ratio model provided by the benchmark ratio model generation unit, and compares it with the real-time monitoring data to correct the deviation in the monitoring data. The formula is: Among them, D c is the corrected data, D m For real-time monitoring of energy consumption data, M k is the benchmark ratio model value, M r It is the current ratio model value corresponding to the real-time monitoring data; when the monitoring data deviates from the benchmark ratio model, the data correction unit adjusts the data to eliminate errors caused by factors such as equipment aging or environmental changes, and the corrected data will be passed back to the data processing module for further processing; through the synergy of the above units, the intelligent ratio module can generate a benchmark ratio model reflecting the energy usage characteristics of each sub-region based on the regional information provided by the regional division module and the data processed by the data processing module, and use the model to correct the deviations in the monitoring data, thereby ensuring the accuracy and reliability of the energy consumption data.

[0107] The energy demand characteristics and potential energy consumption patterns of each sub-region analyzed and determined in the regional analysis unit include:

[0108] Regional feature extraction: Receive regional information provided by the regional division module, including the geographical location, functional attributes, building area and use type data of the sub-region, and extract the characteristic parameters of each sub-region through analysis, including the functional attribute weight of the sub-region, building density and energy demand coefficient related to use;

[0109] Demand forecasting unit: Based on the extracted characteristic parameters and combined with the historical energy usage data of each sub-region, the energy demand of the sub-region is predicted using the following formula: Among them, E pred represents the predicted energy demand of the sub-region, R i is the energy demand correlation coefficient of the ith sub-region, A i is a parameter related to demand (such as building area or population density), and n is the number of factors affecting energy demand;

[0110] Consumption pattern recognition: Receive the predicted energy demand data, and use the pattern recognition algorithm to identify the energy consumption pattern of each sub-region in combination with the functional attribute weights provided by the regional feature extraction; the pattern recognition algorithm first compares the historical energy consumption data with the predicted energy demand data to identify the historical consumption pattern that best matches the current regional characteristics: then, based on the matching results of the historical patterns and the characteristics of the current region, predict the future energy consumption pattern, the formula is: Among them, E mode is the predicted energy consumption pattern, P j is the usage ratio of the jth energy in the historical model, F j is the corresponding functional attribute influence coefficient, and m is the number of energy types; through the combination of the above steps, the regional analysis unit can receive and analyze the regional information provided by the regional division module, accurately extract key regional features, predict the energy demand of each sub-region, and identify potential energy consumption patterns, thereby providing the necessary basic data for generating an accurate benchmark ratio model.

[0111] The dynamic carbon factor adjustment module includes a real-time data receiving unit, a carbon emission factor calculation unit and a dynamic adjustment unit; wherein:

[0112] Real-time data receiving unit: used to receive the benchmark matching model from the intelligent matching module and the standardized processing data provided by the data processing module, including the real-time energy consumption data of each sub-region. The real-time data receiving unit associates the received benchmark matching model with the standardized processing data, and transmits the associated data to the carbon emission factor calculation unit;

[0113] Carbon emission factor calculation unit: Based on the associated data transmitted by the real-time data receiving unit, the carbon emission calculation is performed on the energy consumption data of each sub-region according to the preset carbon emission standard. Specifically, the carbon emission C of each energy source is calculated based on the energy consumption data of each sub-region.j , the formula is: C j =E j ×F j , where C j represents the carbon emissions of the jth energy source, E j is the consumption of the jth energy source, F j is the carbon emission factor of the energy source; then the carbon emissions of each energy type are integrated into the total carbon emissions of each sub-region C total , the formula is: Among them, C total is the total carbon emission of a sub-region, m is the total number of energy types in the sub-region, and the calculated total carbon emission will be transferred to the dynamic adjustment unit for dynamic adjustment;

[0114] Dynamic adjustment unit: Receives the total carbon emissions of each sub-region provided by the carbon emission factor calculation unit, and dynamically adjusts the carbon emission factors of each region in combination with the benchmark matching model generated by the intelligent matching module. Specifically, the difference value D is calculated by comparing the actual carbon emissions of each sub-region with the expected carbon emissions under the benchmark matching model. k , the formula is: D k =C total -C expected , where D k is the carbon emission difference value of the kth sub-region, C total is the actual total carbon emissions, C expected is the expected carbon emissions under the benchmark matching model; and according to the difference value D k The carbon emission factor of each sub-region is dynamically adjusted to ensure that the adjusted carbon emissions are consistent with the benchmark ratio model. The adjusted carbon emission factor is set as F j ′, the calculation formula is: Among them, F j ′ is the adjusted carbon emission factor, F j is the original carbon emission factor, D k is the difference value, C expected The expected carbon emissions; through the synergy of the above units, the dynamic carbon factor adjustment module can dynamically adjust the carbon emission factor of each area based on the real-time energy consumption data and carbon emission standards of each sub-area, thereby ensuring that the system can reflect the carbon emissions of each sub-area in real time and make timely adjustments to maintain accurate accounting of carbon emissions.

[0115] The cross-regional collaboration module includes a data integration unit, a rule consistency check unit, and an inter-regional balance unit; among them:

[0116] Data integration unit: used to receive the carbon emission factor data of each sub-region from the dynamic carbon factor adjustment module and make a preliminary summary. By classifying and combining the carbon emission factor data of different sub-regions according to the predetermined regional grouping rules, a cross-regional carbon emission factor data set is generated. This data set will serve as the basis for subsequent rule consistency checks and inter-regional balance;

[0117] Rule consistency check unit: Receives the cross-regional carbon emission factor data set generated by the data integration unit, and checks whether the carbon emission factor of each sub-region complies with the preset unified accounting rules one by one, ensuring that all regions use consistent standards when calculating carbon emissions. Specifically, the following formula is used to verify consistency:

[0118] in, represents the consistency check coefficient, F actual is the carbon emission factor actually used, F standard is the preset standard carbon emission factor, when When the range of deviation from 1 exceeds the preset tolerance value, the factor of the corresponding area will be marked as inconsistent, and the inter-area balancing unit will be notified to make adjustments;

[0119] Inter-regional balancing unit: used to adjust the areas marked as inconsistent by the rule consistency check unit to ensure that the carbon emission accounting rules between different sub-regions are consistent. Specifically, the carbon emission factors of inconsistent areas are adjusted to meet the standard carbon emission factors. The adjustment formula is: Among them, F adjusted ′ is the adjusted carbon emission factor, ΔF is the difference between the actual factor and the standard factor, and F standard as the standard factor; and globally balance the adjusted carbon emission factors to ensure that the total carbon emissions between regions are relatively consistent, and finally form a unified cross-regional carbon emission factor data set; through the synergy of the above units, the cross-regional collaborative module can effectively receive and integrate the carbon emission factor data provided by the dynamic carbon factor adjustment module, ensure that the accounting rules between multiple sub-regions are consistent, thereby realizing the unified management and report generation of cross-regional carbon emission data.

[0120] The report generation module includes a data summary unit, a report formatting unit and a report output unit; wherein:

[0121] Data aggregation unit: used to receive the standardized energy consumption data from the data processing module and the unified carbon emission factor data provided by the cross-regional collaboration module, comprehensively aggregate the data according to the sub-regional and cross-regional dimensions, associate the energy consumption data of each sub-region with the corresponding carbon emission factor, generate the energy consumption and carbon emission data set for each sub-region, and integrate the data sets of all sub-regions into a unified cross-regional energy consumption and carbon emission data set for subsequent report generation;

[0122] Report formatting unit: receives the energy consumption and carbon emission data sets of each sub-region and across regions generated by the data aggregation unit, and formats the data according to the preset report template. The preset report template includes regional data collation, cross-regional data integration and formatting;

[0123] Regional data collation is used to layout energy consumption data and carbon emission data in the order of sub-regions to ensure that the data information of each sub-region is clearly presented;

[0124] Cross-regional data integration is used to integrate cross-regional energy consumption and carbon emission data, generate an overview chart of overall energy consumption and carbon emissions, and clearly present the comparison between sub-regions and overall trend analysis in the report;

[0125] Formatting is used to standardize the report content according to preset format requirements, including PDF or Excel, to ensure the readability and professionalism of the report;

[0126] Report output unit: used to receive report data processed by the report formatting unit, and output the report in multiple formats according to user needs, including PDF, Excel and web page formats, to ensure that the report content can meet the needs of different users. The report output unit also provides automatic report generation and timed output functions. Users can preset the time period, and the system will automatically generate and send the report at the specified time.

[0127] The present invention covers any substitution, modification, equivalent method and scheme made on the essence and scope of the present invention. In order to make the public have a thorough understanding of the present invention, specific details are described in detail in the following preferred embodiments of the present invention, but those skilled in the art can fully understand the present invention without the description of these details. In addition, in order to avoid unnecessary confusion about the essence of the present invention, well-known methods, processes, procedures, components and circuits are not described in detail.

[0128] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. The automatic accounting system for park energy consumption and carbon emissions is characterized by: It includes regional division module, energy monitoring module, data processing module, intelligent proportioning module, dynamic carbon factor adjustment module, cross-regional collaboration module and report generation module, among which: Area division module: used to divide the park into multiple sub-areas, assign a unique identifier to each sub-area, classify the areas based on geographical location, functional attributes and energy usage patterns, and pass the classification information to the energy monitoring module and the intelligent allocation module; Energy monitoring module: connected with the regional division module, based on the classification information provided by the regional division module, it monitors the energy consumption data of each sub-region in real time, and transmits the data to the data processing module after marking it by region; Data processing module: receives the labeled data from the energy monitoring module, performs data cleaning and preliminary processing, and generates a standardized data set; Intelligent matching module: Based on the regional information provided by the regional division module and the data processed by the data processing module, it generates a benchmark matching model to correct the deviation in the monitoring data; Dynamic carbon factor adjustment module: receives the benchmark matching model generated by the intelligent matching module and the processed data provided by the data processing module, and dynamically adjusts the carbon emission factor of each region based on the real-time energy consumption and carbon emission standards of each sub-region; Cross-regional collaboration module: receives carbon emission factor data provided by the dynamic carbon factor adjustment module, and integrates carbon emission data of multiple sub-regions to ensure that the accounting rules among multiple sub-regions are consistent; Report generation module: Generates energy consumption and carbon emission reports for each sub-region and across regions based on the energy consumption data provided by the data processing module and the unified accounting rules provided by the cross-regional collaboration module.

2. The automatic calculation system for park energy consumption and carbon emissions according to claim 1 is characterized in that: The region division module includes a region identification unit, a classification calculation unit and an identifier allocation unit; wherein: Area identification unit: Based on the geographic information system data of the park, it identifies and divides the physical areas of the park, divides the park into multiple sub-areas using the pre-stored geographic location data, and transmits the boundary information of these sub-areas to the classification calculation unit; Classification calculation unit: receives the sub-region boundary information provided by the region identification unit, calculates the energy use type and intensity of each sub-region based on the functional attributes and historical energy consumption patterns of each sub-region, and classifies each sub-region according to the calculation results; Identifier allocation unit: receives the classification result of the classification calculation unit, and assigns a unique identifier to each sub-region, wherein the identifier includes a code indicating the geographic location of the sub-region, a functional attribute tag, and an energy use mode tag.

3. The automatic calculation system for park energy consumption and carbon emissions according to claim 2 is characterized in that: The classification calculation unit comprises: Calculate the functional attribute weight: receive the sub-region boundary information provided by the region recognition unit, and obtain the functional attribute parameter F related to each sub-region i , where the functional attribute parameters include the use type of the sub-area and the functional attribute weight W is calculated F , the formula is: Among them, W F represents the weight of functional attributes, n is the number of functional attributes, k i Represents the weight coefficient of each functional attribute, F i Indicates the specific value of each functional attribute; Calculate the weight of historical energy consumption patterns: Obtain the historical energy consumption data of each sub-region from the database and calculate the average consumption of each energy source E j , and then calculate the historical energy consumption pattern weight W by the following formula E , the formula is: Among them, W E represents the weight of historical energy consumption pattern, m is the number of energy types, c j Indicates the consumption coefficient of each energy source, E j Indicates the average consumption of each energy source; Calculate the comprehensive energy intensity: Substitute the functional attribute weight W F and historical energy consumption pattern weight W E The comprehensive energy intensity S of each sub-region is calculated by synthesis, and the formula is: S = α × W F +β×W E , where S represents the comprehensive energy intensity, α and β are the functional attribute weights W F and historical energy consumption pattern weight W E The adjustment coefficient of According to the calculation results of the comprehensive energy use intensity S, the sub-areas are divided into high energy consumption areas, medium energy consumption areas, and low energy consumption areas according to the preset classification standards.

4. The automatic calculation system for park energy consumption and carbon emissions according to claim 1 is characterized in that: The energy monitoring module includes an energy consumption collection unit, a data marking unit and a data transmission unit; wherein: Energy consumption collection unit: used to arrange energy monitoring equipment in each sub-area based on the classification information provided by the area division module, and collect energy consumption data of each sub-area in real time, including the consumption of electricity, water and gas; Data marking unit: receives the real-time energy consumption data provided by the energy consumption collection unit, and adds a unique area identifier to the energy consumption data of each sub-area according to the sub-area classification information provided by the area division module, so as to ensure that each energy consumption data is marked as the corresponding sub-area data; Data transmission unit: receives the energy consumption data marked by the data marking unit, and transmits the data to the data processing module by region through a wired or wireless network.

5. The automatic calculation system for park energy consumption and carbon emissions according to claim 1 is characterized in that: The data processing module includes a data receiving unit, a data cleaning unit, a data standardization unit and a data storage unit; wherein: Data receiving unit: used to receive energy consumption data marked by region from the energy monitoring module, including real-time consumption data of electricity, water and gas; Data cleaning unit: used to check the integrity and accuracy of the data after receiving the data transmitted by the data receiving unit, and correct the data by eliminating or correcting abnormal values, duplicate data and missing data; Data standardization unit: used to receive the cleaned data transmitted by the data cleaning unit, unify the units and align the time series of the energy consumption data of each sub-area, and generate a standardized data set; Data storage unit: used to receive the standardized data set generated by the data standardization unit, and store the data by sub-region and energy type through a structured database or data warehouse.

6. The automatic calculation system for park energy consumption and carbon emissions according to claim 1 is characterized in that: The intelligent matching module includes a regional analysis unit, a historical data analysis unit, a benchmark matching model generation unit and a data correction unit; wherein: Regional analysis unit: used to receive regional information provided by the regional division module, including the geographical location, functional attributes and energy use type of each sub-region, and analyze and determine the energy demand characteristics and potential energy consumption patterns of each sub-region; Historical data analysis unit: receives the standardized data set processed by the data processing module, and analyzes the historical energy consumption data of each sub-region in combination with the regional information provided by the regional analysis unit, and calculates the usage ratio P of each energy type in different periods. j ; Benchmark ratio model generation unit: receives the historical energy usage ratio P from the historical data analysis unit j , combined with the regional characteristic information provided by the regional analysis unit, a benchmark ratio model reflecting the energy use characteristics of each sub-region is generated; the expression of the benchmark ratio model is: Among them, M k represents the benchmark ratio model of the kth sub-region, P j is the historical energy use ratio, W j is the weight of each energy type; Data correction unit: receives the benchmark ratio model provided by the benchmark ratio model generation unit, and compares it with the real-time monitoring data to correct the deviation in the monitoring data.

7. The automatic calculation system for park energy consumption and carbon emissions according to claim 6 is characterized in that: The regional analysis unit specifically includes: Regional feature extraction: Receive regional information provided by the regional division module, including the geographical location, functional attributes, building area and use type data of the sub-region, and extract the characteristic parameters of each sub-region through analysis, including the functional attribute weight of the sub-region, building density and energy demand coefficient related to use; Demand forecasting unit: Based on the extracted characteristic parameters and combined with the historical energy usage data of each sub-region, the energy demand of the sub-region is predicted using the following formula: Among them, E pred represents the predicted energy demand of the sub-region, R i is the energy demand correlation coefficient of the ith sub-region, A i is the parameter related to demand, n is the number of factors affecting energy demand; Consumption pattern recognition: Receive the predicted energy demand data, and use the pattern recognition algorithm to identify the energy consumption pattern of each sub-region in combination with the functional attribute weights provided by the regional feature extraction; the pattern recognition algorithm first compares the historical energy consumption data with the predicted energy demand data to identify the historical consumption pattern that best matches the current regional characteristics: then, based on the matching results of the historical patterns and the characteristics of the current region, predict the future energy consumption pattern, the formula is: Among them, E mode is the predicted energy consumption pattern, P j is the usage ratio of the jth energy in the historical model, F j is the corresponding functional attribute influence coefficient, and m is the number of energy types.

8. The automatic calculation system for park energy consumption and carbon emissions according to claim 1 is characterized in that: The dynamic carbon factor adjustment module includes a real-time data receiving unit, a carbon emission factor calculation unit and a dynamic adjustment unit; wherein: Real-time data receiving unit: used to receive the benchmark matching model from the intelligent matching module and the standardized processing data provided by the data processing module, including the real-time energy consumption data of each sub-region. The real-time data receiving unit associates the received benchmark matching model with the standardized processing data, and transmits the associated data to the carbon emission factor calculation unit; Carbon emission factor calculation unit: Based on the associated data transmitted by the real-time data receiving unit, the carbon emission calculation is performed on the energy consumption data of each sub-region according to the preset carbon emission standard. Specifically, the carbon emission C of each energy source is calculated based on the energy consumption data of each sub-region. j ; Then the carbon emissions of each energy type are integrated into the total carbon emissions of each sub-region C total , the formula is: Among them, C total is the total carbon emission of a sub-region, m is the total number of energy types in the sub-region, and the calculated total carbon emission will be transferred to the dynamic adjustment unit for dynamic adjustment; Dynamic adjustment unit: Receives the total carbon emissions of each sub-region provided by the carbon emission factor calculation unit, and dynamically adjusts the carbon emission factors of each region in combination with the benchmark matching model generated by the intelligent matching module. Specifically, the difference value D is calculated by comparing the actual carbon emissions of each sub-region with the expected carbon emissions under the benchmark matching model. k , the formula is: D k =C total -C expected , where D k is the carbon emission difference value of the kth sub-region, C total is the actual total carbon emissions, C expected is the expected carbon emissions under the benchmark matching model; and according to the difference value D k The carbon emission factor of each sub-region is dynamically adjusted to ensure that the adjusted carbon emissions are consistent with the benchmark ratio model. The adjusted carbon emission factor is set as F j ′, the calculation formula is: Among them, F j ′ is the adjusted carbon emission factor, F j is the original carbon emission factor, D k is the difference value, C expected is the expected carbon emissions.

9. The automatic calculation system for park energy consumption and carbon emissions according to claim 1 is characterized in that: The cross-regional collaboration module includes a data integration unit, a rule consistency check unit and an inter-regional balance unit; wherein: Data integration unit: used to receive the carbon emission factor data of each sub-region from the dynamic carbon factor adjustment module, and make a preliminary summary, and generate a cross-regional carbon emission factor data set by classifying and combining the carbon emission factor data of different sub-regions according to the predetermined regional grouping rules; Rule consistency check unit: Receives the cross-regional carbon emission factor data set generated by the data integration unit, and checks whether the carbon emission factor of each sub-region complies with the preset unified accounting rules one by one, ensuring that all regions use consistent standards when calculating carbon emissions. Specifically, the following formula is used to verify consistency: Among them, R check represents the consistency check coefficient, F actual is the carbon emission factor actually used, F standard is the preset standard carbon emission factor, when R check When the range of deviation from 1 exceeds the preset tolerance value, the factor of the corresponding area will be marked as inconsistent; Inter-regional balancing unit: used to adjust the areas marked as inconsistent by the rule consistency check unit to ensure that the carbon emission accounting rules between different sub-regions are consistent. Specifically, the carbon emission factors of inconsistent areas are adjusted to meet the standard carbon emission factors. The adjustment formula is: Among them, F adjusted ′ is the adjusted carbon emission factor, ΔF is the difference between the actual factor and the standard factor, and F standard as the standard factor; and globally balance the adjusted carbon emission factors to ensure that the total carbon emissions between regions are relatively consistent, and ultimately form a unified cross-regional carbon emission factor data set.

10. The automatic calculation system for park energy consumption and carbon emissions according to claim 1 is characterized in that: The report generation module includes a data aggregation unit, a report formatting unit and a report output unit; wherein: Data aggregation unit: used to receive the standardized energy consumption data from the data processing module and the unified carbon emission factor data provided by the cross-regional collaboration module, comprehensively aggregate the data according to the sub-regional and cross-regional dimensions, associate the energy consumption data of each sub-region with the corresponding carbon emission factor, generate the energy consumption and carbon emission data set for each sub-region, and integrate the data sets of all sub-regions into a unified cross-regional energy consumption and carbon emission data set; Report formatting unit: receives the energy consumption and carbon emission data sets of each sub-region and across regions generated by the data aggregation unit, and formats the data according to the preset report template. The preset report template includes regional data collation, cross-regional data integration and formatting; The regional data arrangement is used to arrange the energy consumption data and carbon emission data in the order of the sub-regions; Cross-regional data integration is used to integrate cross-regional energy consumption and carbon emission data to generate an overview chart of overall energy consumption and carbon emissions; Formatting is used to standardize the report content according to preset format requirements, including PDF or Excel; Report output unit: used to receive the report data processed by the report formatting unit, and output the report in multiple formats according to user needs, including PDF, Excel and web page formats.

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