Multi-source heterogeneous carbon emission data fusion method

Abstract

The invention discloses a multi-source heterogeneous carbon emission data fusion method, which comprises the following steps of S1, acquiring energy consumption data of different power sources of each enterprise in a park, and performing data cleaning; s2, data conversion: converting the energy consumption data of different power sources into carbon emission data of different power sources; s3, data fusion: calculating the total carbon emission of the enterprise according to the power contract decomposition data and the carbon emission data from the same enterprise; and S4, adding the enterprise total carbon emissions, calculated in the step S3, of the plurality of enterprises in the park to obtain the total carbon emission of the park. By adopting the multi-source heterogeneous carbon emission data fusion method, integration, storage, processing and analysis of a plurality of heterogeneous data sources in a park are realized, so that the accuracy and practicability of the carbon emission data are improved, and reliable support is provided for making a carbon emission reduction policy, implementing carbon transactions and the like.

Description

Technical Field

[0001] The present invention relates to the technical field of carbon emission data processing, and particularly to a method for integrating multi-source heterogeneous carbon emission data. Background Art

[0002] In recent years, with the increasing attention paid to global climate change by governments and social organizations around the world, and the increase in carbon emissions, more and more countries, enterprises and organizations have joined the global carbon emission reduction ranks, making the monitoring and reduction of carbon emissions an important task for governments of various countries. In this process, the accurate acquisition and processing of carbon emission data are very important for environmental protection and carbon emission management.

[0003] At present, more and more carbon emission data are made public and widely used in various policy-making, evaluation and management. However, due to the diversity of carbon emission sources and the heterogeneity of data sources, it is difficult to ensure the accuracy and reliability of data, resulting in complex and difficult collection and processing of carbon emission data.

[0004] At the same time, the current carbon emission data processing technologies mainly focus on the processing of single-source or homogeneous data, and it is difficult to integrate multiple heterogeneous data sources in the park, resulting in insufficient accuracy of the final results.

[0005] Moreover, traditional carbon emission data processing methods mostly adopt simple data inheritance, derivation and linear interpolation and other methods, which have problems such as data redundancy, loss and weakness, and cannot effectively give full play to the value of carbon emission data, affecting the accuracy and effectiveness of decision-making. Summary of the Invention

[0006] To solve the above problems, the present invention provides a method for integrating multi-source heterogeneous carbon emission data, which realizes the integration, storage, processing and analysis of multiple heterogeneous data sources in the park, thereby improving the accuracy and practicality of carbon emission data, and providing reliable support for formulating carbon emission reduction policies and implementing carbon trading, etc.

[0007] To achieve the above object, the present invention provides a method for integrating multi-source heterogeneous carbon emission data, including the following steps:

[0008] S1. Collect the energy consumption data of different power sources of each enterprise in the park and perform data cleaning;

[0009] S2. Data conversion: Convert the energy consumption data of different power sources into carbon emission data of different power sources;

[0010] S3. Data fusion: Calculate the total carbon emissions of the enterprise according to the power contract decomposition data and carbon emission data from the same enterprise;

[0011] S4. Add up the total carbon emissions of multiple enterprises in the park calculated in step S3 to obtain the total carbon emissions of the park.

[0012] Preferably, the data cleaning in step S1 includes the following steps: selecting subsets; renaming column names; deleting duplicate values; handling missing values; handling outliers.

[0013] Among them, selecting subsets means selecting the data columns in the dataset that need to be analyzed and hiding the remaining data columns that do not participate in the analysis.

[0014] Renaming column names means that if there are the same column names or two column names with the same meaning in the dataset, then rename the column names of the data columns with the above same column names or two column names with the same meaning.

[0015] Deleting duplicate values means deleting the duplicate data values in the data column and only retaining the first data in the duplicate data column.

[0016] Handling missing values means that when there are missing data values in the original data, that is, there are data cells without data in the dataset, the missing data values are filled in.

[0017] Handling outliers means re-obtaining or replacing the outliers.

[0018] Preferably, the carbon emission data of different power sources in step S2 includes at least one of wind, light, water, nuclear, biomass, coal, oil, gas and any combination thereof.

[0019] Among them, the carbon emission calculation formula for different power sources is as follows:

[0020] C m =Q m ×δ m (1)

[0021] In the formula, m is the type of power energy, m = 1, 2... 8, respectively representing coal, oil, gas, wind, light, water, nuclear, biomass; C m is the carbon emission generated by the power generation of the mth type of energy; Q m is the decomposed electricity volume of the power contract of the mth type of energy, with the unit of megawatt-hour; δ m is the carbon emission factor of the power generation of the mth type of energy, with the unit of tons of carbon dioxide per megawatt-hour, where the δ m value of wind, light, water, and nuclear is 0.

[0022] Preferably, step S3 specifically includes the following steps:

[0023] S31. Decompose the power contract;

[0024] S32. Calculate the remaining carbon emission factors;

[0025] S33. Calculate the total carbon emissions of the enterprise according to the decomposed power contract and the remaining carbon emission factors.

[0026] Preferably, the power contracts described in step S31 are divided into bilateral trading contracts, agency power purchase contracts, and on-site trading contracts according to the trading method;

[0027] The decomposition steps of the bilateral trading contract are as follows: First, import the decomposed curve according to the bilateral trading electricity volume, trading price, and the 96 - period decomposition curve of the bilateral custom day. Decompose the annual contract electricity volume month by month to obtain the monthly curve, and then decompose the monthly curve into 96 periods per day according to the all - day average curve, peak - hour curve, and flat - period curve respectively;

[0028] Among them, the decomposition formula for the all - day average electricity consumption is as follows:

[0029]

[0030] In the formula, e bi,1 is the electricity consumption at the 15 - minute time node in the all - day average; D1 is the all - day average curve; d1 is the number of working days in this month; d2 is the number of rest days; and the electricity consumption ratio between rest days and working days is : 1;

[0031] Decompose the daily electricity volume evenly into the peak period, and the rest of the periods are 0. Assuming the peak - hour electricity consumption time is α hours, the decomposition formula for the peak - hour electricity consumption is as follows:

[0032]

[0033] In the formula, e bi,2 is the electricity consumption at the 15 - minute time node in the peak period; D2 is the peak - hour curve;

[0034] Decompose the daily electricity volume evenly into the flat period, and the rest of the periods are 0. Assuming the flat - period electricity consumption time in this area is β hours, the decomposition formula for the flat - period electricity consumption is as follows:

[0035]

[0036] In the formula, e bi,3 is the electricity consumption at the 15 - minute time node in the flat period; D3 is the flat - period curve;

[0037] The decomposed electricity volume e bi,t of the bilateral trading user at time t is:

[0038] e bi,t = a * e bi,1 + b * e bi,2 + c * e bi,3(5)

[0039] Wherein, during the average time period of the whole day, a = 1, b = c = 0; during the peak time period, a = b = 1, c = 0; during the flat time period, a = c = 1, b = 0;

[0040] The steps for decomposing the user-side contract of the power purchase agency contract are as follows: The power purchase agency users include the entrusted agency contract with curve and the entrusted agency contract without curve. Among them, the decomposition of the entrusted agency contract with curve is the same as that of the bilateral transaction contract. The entrusted agency contract without curve is allocated proportionally according to the total transaction volume of the entrusted power purchase agency. The calculation method is as follows:

[0041]

[0042] Wherein, is the total power purchased by the energy-consuming entity i from the entrusted agency, and η is the proportion of the power generation energy that enters the carbon footprint tracking scope in the total transaction volume of the entrusted power purchase agency.

[0043] Decomposition of the on-site trading contract: Industrial and commercial power users above 10 kV participate in market-based trading and are decomposed according to the same-time trading power sales-side transaction ratio of the annual and monthly transaction volumes. The calculation method is as follows:

[0044]

[0045] Wherein, e fi is the power volume for the decomposition of the on-site centralized trading contract participated by all energy-consuming entities; i is the energy-consuming entity; N is the number of users who conclude transactions in the same batch as the energy-consuming entity; E 绿电 is the power generation volume of the new energy unit in the same-time trading; is the total power purchased by the energy-consuming entity i through the on-site centralized trading method; E 总 is the total power generation volume in the same time period;

[0046] According to the annual and monthly trading volumes, the new energy unit is corrected according to the predicted power volume of the trading target. The corrected power volume is absorbed by the peak shaving of the thermal power unit. The calculation method for decomposing the power sales-side power volume ratio in the same time period after correction is as follows:

[0047]

[0048] Wherein, E' 绿电 is the power generation volume of the new energy unit in the same-time trading after correction.

[0049] Preferably, the calculation formula for the remaining carbon emission factor described in step S32 is as follows:

[0050]

[0051] Wherein, Fe,c is the remaining carbon emission factor, E I is the total electricity consumption accounted for in a certain region, E i,g is the consumption of green electricity traced through contracts; C e,i is the carbon emission corresponding to the electricity consumption within the region.

[0052] Preferably, the calculation formula for the total carbon emissions of the enterprise described in step S33 is as follows:

[0053]

[0054] In the formula, C i is the total carbon emissions of the i-th energy-consuming entity; e bi is the decomposed electricity quantity of bilateral transactions; e′ fi is the decomposed electricity quantity of on-site transactions; e agi is the decomposed electricity quantity of agency power purchase; E0 is the total electricity consumption accounted for by the enterprise.

[0055] Preferably, the calculation formula for the total carbon emissions of the park described in step S4 is as follows:

[0056]

[0057] In the formula, C is the total carbon emissions of the park.

[0058] The present invention has the following beneficial effects:

[0059] It realizes the integration, storage, processing and analysis of multiple heterogeneous data sources within the park, thereby improving the accuracy and practicability of carbon emission data, and providing reliable support for formulating carbon emission reduction policies and implementing carbon trading, etc.

[0060] Next, through the drawings and embodiments, the technical solutions of the present invention will be further described in detail. Description of the Drawings

[0061] Figure 1 is the principle block diagram of a method for integrating multi-source heterogeneous carbon emission data according to the present invention. Detailed Embodiments

[0062] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the following further describes the embodiments of the present invention in detail with reference to the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the embodiments of the present invention, and are not used to limit the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in this application without creative efforts belong to the scope protected by this application. The examples of the embodiments are shown in the drawings, where the same or similar reference numerals represent the same or similar elements or elements with the same or similar functions throughout.

[0063] It should be noted that the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or server that includes a series of steps or units need not be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products, or devices.

[0064] As Figure 1 shown, a method for integrating multi-source heterogeneous carbon emission data includes the following steps:

[0065] S1. Collect the energy consumption data of different power sources of each enterprise in the park and perform data cleaning;

[0066] It should be noted that the energy consumption data in this embodiment is sourced from the provincial energy big data center, the national power trading platform, and the e-trading unified service platform.

[0067] The data cleaning described in step S1 includes the following steps: selecting a subset; renaming column names; deleting duplicate values; handling missing values; handling outliers;

[0068] Among them, selecting a subset means selecting the data columns in the dataset that need to be analyzed and hiding the remaining data columns that do not participate in the analysis to avoid interference;

[0069] Renaming column names means that if the same column name appears in the dataset, or two column names with the same meaning, then to avoid interfering with the analysis results, rename the column names of the data columns with the same column name or the same meaning;

[0070] Deleting duplicate values means deleting the duplicate data values in the data column, which will affect the results during data analysis, so only the first data in the duplicate data column is retained;

[0071] Handling missing values means that when there are missing data values in the original data, that is, there are data cells without data in the dataset, fill in the missing data values. The filling method can be to obtain data from relevant units again. If it cannot be obtained, the average value of the first three and the last three data in the column where the data is located can be used or a value can be estimated according to the actual situation to fill in the position of the missing value;

[0072] Handling outliers means re-obtaining or replacing outliers. Re-obtaining means obtaining data from relevant units again. If it cannot be obtained, the average value of the first three and the last three data in the column where the data is located can be used or a value can be estimated according to the actual situation to replace the outliers.

[0073] S2. Data conversion: Convert the energy consumption data of different power sources into carbon emission data of different power sources;

[0074] The carbon emission data of different power sources described in step S2 includes at least one of wind, light, water, nuclear, biomass, coal, oil, and gas and any combination thereof;

[0075] Among them, the carbon emission calculation formula for different power sources is as follows:

[0076] C m =Q m ×δ m (1)

[0077] In the formula, m is the type of power energy, m = 1, 2... 8, respectively representing coal, oil, gas, wind, light, water, nuclear, and biomass; C m is the carbon emission generated by the power generation of the mth type of energy; Q m is the decomposed electricity volume of the power contract of the mth type of energy, with the unit of megawatt-hour; δ m is the power generation carbon emission factor of the mth type of energy, with the unit of tons of carbon dioxide per megawatt-hour, where the δ m value of wind, light, water, and nuclear is 0.

[0078] S3. Data fusion: Calculate the total carbon emissions of the enterprise based on the decomposed power contract data and carbon emission data from the same enterprise;

[0079] Step S3 specifically includes the following steps:

[0080] S31. Decompose the power contract;

[0081] The power contracts described in step S31 are divided into bilateral trading contracts, agency power purchase contracts, and on-site trading contracts according to the trading method, where the on-site trading contracts include centralized bidding contracts and rolling matching contracts;

[0082] The decomposition steps of the bilateral trading contract are as follows: First, import the bilateral trading electricity volume, trading price, and the 96-hour decomposition curve of the bilateral custom day, and decompose the annual contract electricity volume month by month according to the decomposition curve signed for the bilateral trading contract and reported to the trading center to obtain the monthly curve, and then decompose the monthly curve into 96 hours of each day according to the all-day average curve, peak-hour curve, and flat-section curve respectively;

[0083] Among them, the decomposition formula for the all-day average electricity consumption is as follows:

[0084]

[0085] In the formula, e bi,1is the power consumption with a 15-minute time node in the average daily electricity consumption; D1 is the average daily curve; d1 is the number of working days in the month; d2 is the number of rest days; and the electricity consumption ratio between rest days and working days is : 1;

[0086] The daily electricity consumption is evenly decomposed into the peak period, and the electricity consumption in other periods is 0. Assuming the peak electricity consumption time is α hours, the decomposition formula for the electricity consumption in the peak period is as follows:

[0087]

[0088] In the formula, e bi,2 is the power consumption with a 15-minute time node in the peak period; D2 is the curve in the peak period;

[0089] The daily electricity consumption is evenly decomposed into the flat period, and the electricity consumption in other periods is 0. Assuming the flat period electricity consumption time in this area is β hours, the decomposition formula for the electricity consumption in the flat period is as follows:

[0090]

[0091] In the formula, e bi,3 is the power consumption with a 15-minute time node in the flat period; D3 is the curve in the flat period;

[0092] The decomposed electricity consumption e of bilateral trading users at time t bi,t is:

[0093]

[0094] In the formula, a = 1, b = c = 0 in the average daily period; a = b = 1, c = 0 in the peak period; a = c = 1, b = 0 in the flat period; it should be noted that the division of peak, flat, and valley periods is verified according to the regulations of the trading center in the province where the user is located.

[0095] The contract decomposition steps on the user side of the agency power purchase contract are as follows: Agency power purchase users include commission agency contracts with curves and commission agency contracts without curves. Among them, the decomposition of commission agency contracts with curves is the same as that of bilateral trading contracts. Commission agency contracts without curves are proportionally allocated according to the total transaction volume of the commissioning power purchase agency. The calculation method is as follows:

[0096]

[0097] In the formula, is the total power purchase volume of the energy-consuming entity i from the commissioning agency, and η is the proportion of the power generation energy entering the carbon footprint tracking scope in the total transaction volume of the commissioning power purchase agency.

[0098] Decomposition of on-site trading contracts: Industrial and commercial power users above 10 kV participate in market-based trading, and are decomposed according to the proportion of the electricity sold on the selling side of the same-time trading in the annual and monthly traded electricity volumes. The calculation method is as follows:

[0099]

[0100] In the formula, e fi is the electricity volume decomposed for all energy-consuming entities participating in the on-site centralized trading contract; i is the energy-consuming entity; N is the number of users who traded in the same batch as the energy-consuming entity; E 绿电 is the generated electricity volume of new energy units in the same-time trading; is the total electricity purchased by the energy-consuming entity i through on-site centralized trading; E 总 is the total generated electricity volume in the same time period;

[0101] According to the annual and monthly trading volumes, the new energy units are corrected according to the predicted electricity volume of the trading target. The corrected electricity volume is absorbed by the peaking of thermal power units. The calculation method for decomposing the electricity volume ratio on the selling side of the same-time trading after correction is as follows:

[0102]

[0103] In the formula, E′ 绿电 is the generated electricity volume of the new energy units in the same-time trading after correction.

[0104] S32. To avoid the problem of double counting of the green electricity environmental rights and interests attributes generated by calculating carbon emissions using regional carbon emission factors, the remaining carbon emission factors are calculated;

[0105] The calculation formula for the remaining carbon emission factors described in step S32 is as follows:

[0106]

[0107] In the formula, F e,c is the remaining carbon emission factor, E I is the total electricity volume accounted for in a certain region, E i,g is the green electricity consumption traced through contracts; C e,i is the carbon emission corresponding to the electricity consumption in the region.

[0108] S33. Calculate the total carbon emissions of the enterprise according to the decomposed power contract and the remaining carbon emission factors.

[0109] The calculation formula for the total carbon emissions of the enterprise described in step S33 is as follows:

[0110]

[0111] In the formula, C i is the total carbon emissions of the i-th energy-consuming entity; ebi is the decomposed electricity quantity for bilateral transactions; e' fi is the decomposed electricity quantity for on-site transactions; e agi is the decomposed electricity quantity for proxy electricity purchase; E0 is the total electricity quantity accounted for by the enterprise.

[0112] S4. Add up the total carbon emissions of multiple enterprises in the park calculated in step S3 to obtain the total carbon emissions of the park.

[0113] The calculation formula for the total carbon emissions of the park described in step S4 is as follows:

[0114]

[0115] In the formula, C is the total carbon emissions of the park.

[0116] Therefore, by adopting the above method for integrating multi-source heterogeneous carbon emission data, the present invention realizes the integration, storage, processing and analysis of multiple heterogeneous data sources in the park, thereby improving the accuracy and practicality of carbon emission data, and providing reliable support for formulating carbon emission reduction policies and implementing carbon trading, etc.

[0117] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that they can still modify or equivalently replace the technical solutions of the present invention, and these modifications or equivalent replacements cannot make the modified technical solutions deviate from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for integrating multi-source heterogeneous carbon emission data, characterized by: The following steps are involved: S1. Collect energy consumption data of different power sources of each enterprise in the park and clean the data; S2, data conversion: converting energy consumption data of different electricity sources into carbon emission data of different electricity sources; S3. Data fusion: Calculate the total carbon emissions of an enterprise based on the electricity contract decomposition data and carbon emission data from the same enterprise; S4. Add the total carbon emissions of multiple enterprises in the park calculated in step S3 to obtain the total carbon emissions of the park.

2. The method for integrating multi-source heterogeneous carbon emission data according to claim 1, characterized in that: The data cleaning described in step S1 includes the following steps: Select subsets; rename columns; delete duplicate values; handle missing values; handle outliers; Selecting a subset means selecting the data columns in the data set that need to be analyzed, and hiding the remaining data columns that do not participate in the analysis; Duplicate column names means that if the same column name or two column names with the same meaning appear in the data set, the column names of the data columns with the same column name or two column names with the same meaning will be renamed; Deleting duplicate values ​​means deleting duplicate data values ​​in a data column and only retaining the first data in the duplicate data column; Missing value processing refers to filling in the missing data values ​​when there are missing data values ​​in the original data, that is, when there are data cells with no data in the data set; Outlier processing refers to retrieving or replacing outliers.

3. The method for integrating multi-source heterogeneous carbon emission data according to claim 1, characterized in that: The carbon emission data of different electricity sources described in step S2 includes at least one of wind, solar, water, nuclear, biomass, coal, oil, and gas, and any combination thereof; The calculation formula for carbon emissions from different electricity sources is as follows: C m =Q m ×δ m (1) Where m is the type of electric energy, m = 1, 2...8, representing coal, oil, gas, wind, light, water, nuclear, and biomass respectively; C m is the carbon emissions generated by the mth energy source; Q m is the electricity contract decomposition quantity of the mth energy source, in MWh; δ m is the carbon emission factor of power generation of the mth energy source, in tons of carbon dioxide per megawatt-hour, among which the δ m The value is 0.

4. The method for integrating multi-source heterogeneous carbon emission data according to claim 3 is characterized by: Step S3 specifically includes the following steps: S31. Decomposing the electricity contract; S32. Calculate the remaining carbon emission factor; S33. Calculate the total carbon emissions of the enterprise based on the decomposed electricity contract and the remaining carbon emission factor.

5. The method for integrating multi-source heterogeneous carbon emission data according to claim 4 is characterized by: The power contract in step S31 is divided into bilateral transaction contracts, agency power purchase contracts and on-site transaction contracts according to the transaction mode; The steps of decomposing bilateral trading contracts are as follows: first, the decomposition curves of the purchase and sale of bilateral trading electricity, trading prices, and 96 periods of bilateral custom days are imported, and the decomposition curves based on the signing of bilateral trading contracts and reporting to the trading center are imported. The annual contract electricity is decomposed month by month to obtain the monthly curve, and then the monthly curve is decomposed into 96 periods per day according to the full-day average curve, peak period curve, and flat period curve; The decomposition formula of the average daily electricity consumption is as follows: In the formula, e bi,1 is the power consumption at 15 minutes as the time node in the whole day average; D1 is the whole day average curve; d1 is the number of working days in the month; d2 is the number of rest days; and the ratio of power consumption on rest days to working days is The daily electricity consumption is evenly decomposed into the peak period, and the rest of the time is 0. Assuming that the peak electricity consumption time is α hours, the peak period electricity consumption decomposition formula is as follows: In the formula, e bi,2 It is the electricity consumption at the peak time with 15 minutes as the time node; D2 is the peak time curve; The daily electricity consumption is evenly decomposed into flat periods, and the rest of the time is 0. Assuming that the flat period electricity consumption time in this area is β hours, the flat period electricity consumption decomposition formula is as follows: Where eb i ,3 is the electricity consumption in the flat section with 15 minutes as the time node; D3 is the flat section curve; Bilateral transaction users decompose the amount of electricity e at time t bi,t for: And bi,t =a*e bi,1 +b*e bi,2 +c*e bi,3 (5) In the formula, a=1, b=c=0 in the average period of the day; a=b=1, c=0 in the peak period; a=c=1, b=0 in the flat period; The steps for decomposing the user side of the power purchasing agent contract are as follows: the power purchasing agent includes the agency contract with curve and the agency contract without curve. The decomposition steps of the agency contract with curve are the same as those of the bilateral transaction contract. The agency contract without curve is allocated in the same proportion as the total transaction volume of the agency power purchasing agent. The calculation method is as follows: In the formula, is the total amount of electricity purchased by the energy user i from the entrusted agent, η is the proportion of power generation energy that enters the carbon footprint tracking scope in the total transaction volume of the entrusted power purchase agent, Decomposition of on-site trading contracts: For industrial and commercial power users of 10kV and above who participate in market-based trading, the transaction ratio of the electricity sales side in the same period of the annual and monthly transaction volume is decomposed. The calculation method is as follows: In the formula, e fi is the electricity quantity decomposed by all energy users participating in the centralized trading contract on the market; i is the energy user; N is the number of users who traded with the energy user in the same batch; E 绿电 To trade the power generation of new energy units in the same period; E is the total amount of electricity purchased by energy user i through centralized trading on the market; 总 is the total power generation in the same period; According to the annual and monthly transaction volume, the new energy units are corrected according to the predicted power of the transaction target, and the corrected power is consumed by the peak load regulation of the thermal power units. The calculation method for the proportion of power sales side in the transaction during the same period after correction is as follows: In the formula, E′ 绿电 It is the power generation amount of new energy units traded in the same period after correction.

6. A method for integrating multi-source heterogeneous carbon emission data according to claim 5, characterized in that: The calculation formula of the remaining carbon emission factor in step S32 is as follows: In the formula, F e,c is the residual carbon emission factor, E I Calculate the total electricity consumption for a certain area, E i,g is the green electricity consumption traced through the contract; C e,i is the carbon emissions corresponding to electricity consumption in the region.

7. The method for integrating multi-source heterogeneous carbon emission data according to claim 6, characterized in that: The calculation formula for the total carbon emissions of the enterprise described in step S33 is as follows: In the formula, C i is the total carbon emissions of the i-th energy user; e bi is the decomposed electricity of bilateral transactions; e′ fi The decomposed electricity volume of on-site transactions; agi It is the decomposed electricity quantity of the power purchased by the agent; E0 is the total electricity quantity calculated by the enterprise.

8. The method for integrating multi-source heterogeneous carbon emission data according to claim 7, characterized in that: The total carbon emissions calculation formula of the park described in step S4 is as follows: Where C is the total carbon emissions of the park.

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