Method, device, medium and equipment for predicting and calculating carbon neutralization and carbon emission in operation stage of public building

Abstract

The invention relates to the technical field of prediction methods, in particular to a carbon neutralization and carbon emission prediction calculation method in a public building operation stage, which comprises the following steps: classifying direct, indirect and implicit emissions involved in accounting of the public building operation stage in the current year and sources of renewable energy utilization amount; after various classifications of direct emission, indirect emission, implicit emission and renewable energy utilization amount are subjected to accounting, equivalent substitution of power grid carbon emission factors based on accounting years is carried out on power grid carbon emission related parts in an accounting result, and the power grid carbon emission related parts are converted into activity data; performing activity data extraction on the carbon emission of the public building operation stage in each year, and predicting a power grid carbon emission factor according to an extraction result; and based on the classification accounting result of the public building operation stage in the current year, predicting the carbon emission of the building operation stage in the corresponding year by using the predicted power grid carbon emission factor.

Description

Technical Field

[0001] The present invention relates to the technical field of prediction methods, and specifically to a method, device, medium and equipment for predicting and calculating carbon neutrality carbon emissions during the operation phase of a public building. Background Art

[0004] At present, there are related building carbon emission prediction methods in the construction industry, such as the "A Building Carbon Emission Prediction Method" disclosed in the Chinese invention patent application with publication number CN115719123A. The patent includes building a building carbon emission online platform, filling it with carbon emission factor data and a large amount of actual project data, and using the latter as sample data for big data analysis, analyzing the sample data, analyzing the influencing factors, judging the factor parameters, forming a semi-empirical formula combined with the theoretical formula, and writing the semi-empirical formula into the carbon emission platform, so as to predict carbon emissions when new building data is input, and then generate a carbon emission analysis report, and finally give carbon reduction design suggestions for the building. This technical solution is to calculate and predict the design stage of building carbon emissions. The patent expands the engineering stage from the "construction drawing design stage" to "scheme design, preliminary design, construction drawing design" and "completion audit", a total of four stages. The first three stages are the design stage, and different prediction methods with gradually detailed required information and gradually accurate prediction results are used to predict building carbon emissions. The prediction results are verified with the data of the "completion audit" stage. The carbon emission forecast in this part is still based on the verification and forecast of existing data, rather than actual data monitoring, and the forecast accuracy is uncertain. At the same time, the forecast can only achieve short-term forecast, which has certain limitations.

[0005] At the same time, there are also related monitoring and calculation patents for the operation stage - the "A Method and System for Measuring and Monitoring the Management of Carbon Emissions from Building Operation" disclosed in the Chinese invention patent application with publication number CN118671267A, which collects energy consumption data or carbon emissions of various energy-using equipment in the building in real time through a preset carbon emission monitoring sensor network, and uploads the collected energy consumption data or carbon emissions of various energy-using equipment in the building to the edge computing device deployed near the carbon emission monitoring sensor network. The edge computing device deployed near the carbon emission monitoring sensor network is used to calculate the energy consumption data or carbon emissions of various energy-using equipment in the building in real time, obtain the carbon emissions of various energy-using equipment in the building and upload it to the cloud platform; the big data analysis algorithm in the cloud platform is used to analyze the carbon emissions of various energy-using equipment in the building in real time, obtain the carbon emission trend forecast of various energy-using equipment in the building, and the abnormal carbon emission warning of various energy-using equipment in the building, and generate a carbon emission analysis report of the energy-using equipment in the building; the carbon emission analysis report of the energy-using equipment in the building is displayed using the designed visual interface. This technical solution does not explain the carbon emission sources within the carbon emission accounting boundary of the building operation phase, and cannot monitor the various carbon source data within the carbon emission boundary of the building operation phase. Different carbon sources have different monitoring methods, and it is difficult to fully calculate the carbon emissions of the building operation phase. At the same time, the prediction method in this technical solution is based on the energy consumption trend of each energy-consuming equipment in the building. This results in this method being able to only perform short-term carbon emission predictions for the building operation phase, and cannot perform long-term carbon emission data predictions.

[0006] In the process of using the carbon digital management platform to assist in the implementation of carbon neutrality certification for public buildings, the inventors found that it was difficult to monitor and predict carbon emissions during the operation phase of public buildings through existing technologies. The reasons are as follows: 1. No monitoring system for carbon emissions has been established. Carbon sources within the carbon emission accounting boundary of the operation phase of public buildings should be monitored, and the monitoring equipment should be installed and monitored based on the classified carbon sources in the prediction model; 2. The existing carbon emission prediction method for the operation phase of public buildings can only predict future short-term or periodic carbon emissions from the operation phase of public buildings through big data analysis in the energy consumption monitoring platform. Summary of the invention

[0007] The purpose of the present invention is to overcome the shortcomings of the background technology and provide a method for predicting building carbon emissions.

[0008] The purpose of the present invention is to achieve the following technical solutions:

[0009] A method for predicting and calculating carbon emissions of carbon neutrality in the operation phase of public buildings.

[0010] Categorize the sources of direct, indirect and implicit emissions and renewable energy used in the operation of public buildings in the current year;

[0011] After calculating the direct emissions, indirect emissions, implicit emissions and renewable energy utilization, the grid carbon emissions in the calculation results are replaced by the grid carbon emission factors based on the calculation year and converted into activity data.

[0012] Extract activity data on carbon emissions during the operation phase of public buildings each year, and predict the carbon emission factors of the power grid based on the extraction results;

[0013] Based on the classified accounting results of the public building operation stage in the accounting year, the predicted grid carbon emission factor is used to predict the carbon emissions of the building operation stage in the corresponding year.

[0014] In a further scheme, the classification method divides direct, indirect and implicit emissions and renewable energy utilization into at least one sub-item respectively, and each sub-item is further divided into at least one first-level energy consumption node. The carbon emission data of direct, indirect and implicit emissions and renewable energy utilization are obtained by calculating the carbon emissions of nodes at each level.

[0015] In a further embodiment, the calculation formula for direct emissions is:

[0016]

[0017]

[0018] Where:

[0019] C GD —Direct carbon dioxide emissions (kgCO2 e)

[0020] —Direct non-electricity carbon emissions in year t (kgCO2e), where year t refers to the year from which the carbon emissions are to be predicted and calculated starting from the current year of accounting;

[0021] GD ele,t —Annual grid equivalent substitution activity data of the direct emission electricity part in year t (kWh), including grid equivalent substitution activity data of carbon emission of switch station;

[0022] EF k —Switch station grid carbon emission factor (kgCO2 e / kWh);

[0023] C t —Annual carbon dioxide emissions from heating gas in office buildings (kgCO2e);

[0024] Cm — Carbon dioxide emissions from fire extinguishing gas in office buildings (kgCO2e);

[0025] C r — Carbon dioxide emissions from refrigerant leakage in air conditioners in office buildings (kgCO2e);

[0026] C w —Amount of carbon dioxide produced by sewage treatment in office buildings (kgCO2e);

[0027] The grid carbon emission factor for the switch station is:

[0028] type Carbon emission intensity 110kv <![CDATA[25.66 kgCO2e / 10,000 kWh <!-- 2 -->]]> 220kv <![CDATA[26.05 kg CO2e / 10,000 kWh]]>

[0029] In a further embodiment, the calculation formula for the indirect emissions is:

[0030]

[0031] Where:

[0032] —Annual grid equivalent substitution activity data for indirect emissions in year t (kWh);

[0033] C zm,t —Lighting electricity consumption in year t (kWh);

[0034] C kt,t —Electricity consumption of air conditioner in year t (kWh);

[0035] C dl,t —Power consumption in year t (kWh);

[0036] C ts,t —Special electricity consumption in year t (kWh).

[0037] In a further solution, the calculation formula for the invisible carbon emissions is:

[0038]

[0039] Where:

[0040] C GE,t —Annual embodied carbon emissions in year t (kgCO2e)

[0041] —Annual emissions of non-electricity embodied carbon in year t (kgCO2e);

[0042] f(t)—regional grid carbon emission factor in year t (kgCO2 e / kWh);

[0043] GE ele,t—Grid equivalent substitution activity data of the electricity part with embodied carbon emissions in year t (kWh), including grid equivalent substitution activity data of carbon emissions from elevator processing;

[0044] C S —Annual carbon dioxide emissions from office building equipment maintenance in year t (kgCO2e);

[0045] C W —CO2 emissions from annual material maintenance of office buildings in year t (kgCO2e);

[0046] The grid carbon emission factor for elevator processing is:

[0047] type Energy intensity Elevator processing 168.78kWh / unit

[0048] In a further solution, the grid carbon emission factor is predicted using the following formula:

[0049] f (t) =[f (ti) -(f (tj) -f (ti) ) / n]×m

[0050] f (t) —Carbon emission factor of regional power grid in year t (kgCO2e / kWh);

[0051] f (ti) —Base year regional grid carbon emission factor (kgCO2e / kWh), where base year refers to the year of carbon neutral building application;

[0052] f (tj) —The predicted value of the regional grid carbon emission factor in the planning year (kgCO2 e / kWh), where the planning year refers to the year in which the building is planned to be carbon neutral;

[0053] n—the number of plan years and base years;

[0054] m—the annual number between year t and the base year.

[0055] In a further solution, the predicted grid carbon emission factor is used to predict the carbon emissions of the building operation phase in the corresponding year, and the prediction formula is:

[0056]

[0057] Where:

[0058] C B,t —Carbon emissions during the operation phase of the building in year t (kgCO2 e);

[0059] f(t)—predicted regional grid carbon emission factor in year t (kgCO2 e / kWh);

[0060] —Direct non-electricity carbon emissions in year t (kgCO2e);

[0061] —The carbon emissions of the non-electricity part of the embodied carbon emissions in year t (kgCO2e);

[0062] GD ele,t —Annual grid equivalent substitution activity data of the direct emission electricity portion in year t (kWh);

[0063] GIN ele,t —Annual grid equivalent substitution activity data for indirect emissions in year t (kWh);

[0064] —Annual carbon emissions of the electricity component implied in year t (kgCO2e);

[0065] AD t —Data on the equivalent grid substitution activity of renewable energy generated and consumed annually in year t (kWh);

[0066] AD t1 —Annual grid-connected equivalent substitution activity data of renewable energy in year t (kWh);

[0067] EF t —Annual grid-connected electricity loss coefficient of renewable energy in year t, 0.9454.

[0068] Another technical solution of the present invention is: a carbon neutral carbon emission prediction device for a public building operation phase, comprising:

[0069] The classification module is used to classify the sources of carbon emissions involved in the operation phase of public buildings in the current year;

[0070] The accounting conversion module calculates carbon emissions for each category based on the classification results of the classification module, and replaces the grid carbon emissions in the accounting results with the grid carbon emission factors based on the accounting year and converts them into activity data;

[0071] The grid carbon emission factor prediction module obtains the carbon emission data of public buildings in each year, extracts activity data, and predicts the grid carbon emission factor based on the extraction results;

[0072] The carbon emission prediction module predicts the carbon emissions of the building operation stage in the corresponding year based on the classified accounting results of the public building operation stage in the accounting year and the grid carbon emission factor predicted by the grid carbon emission factor prediction module.

[0073] Another technical solution of the present invention is: a storage medium storing a computer program executable by a processor, wherein the computer program implements the steps of the above-mentioned method when executed.

[0074] Another technical solution of the present invention is: a computer device having a memory and a processor, wherein the memory stores a computer program that can be executed by the processor, and the steps of the above-mentioned method are performed when the computer program is executed.

[0075] Compared with the existing technology, the advantages of the present invention are: it can clarify the carbon emission accounting boundaries of public buildings during the operation stage, build and improve the carbon emission monitoring system of public buildings, and complete the long-term prediction of carbon emissions during the operation stage of public buildings through the trend changes of electricity carbon emission factors.

[0076] Additional aspects and advantages of the present invention will be given in part in the following description, and in part will become apparent from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0077] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments of the present invention. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0078] Figure 1 The present invention provides a flow chart of a prediction method.

[0079] Figure 2 This is a curve chart of the prediction results of the case provided by the embodiment of the present invention. DETAILED DESCRIPTION

[0080] In order to make the purpose, technical solution and advantages of the embodiments of the present invention more clear, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0081] Carbon emissions during the operation stage of public buildings are mainly a collection of direct emissions, indirect emissions and implicit emissions during the operation of public buildings.

[0082] Indirect emissions in the operation phase are the main component of carbon emissions in the operation phase of public buildings, and in the process of building energy-saving transformation, more and more direct and implicit emissions will be transformed into indirect emissions. Therefore, indirect emissions are an important part of the calculation of carbon emissions in the operation phase of buildings. Among them, carbon emissions from electricity use account for more than 40% of indirect emissions in the operation phase.

[0083] Carbon emissions refers to an abbreviation for greenhouse gas emissions, of which the most important component is carbon dioxide (CO2). Since non-carbon dioxide is difficult to reduce in the process of building energy conservation and carbon reduction and is a necessary emission, the embodiment of the present invention divides the carbon emissions of the public building operation stage into carbon dioxide emissions and non-carbon dioxide emissions for calculation from the perspective of different greenhouse gases. The carbon dioxide part extracts the grid carbon emission factor as a variable to establish a new carbon emission prediction algorithm, and converts the direct, indirect and implicit emissions involved in the operation stage of public buildings into activity data based on the grid carbon emission factor of the accounting year. The purpose of predicting the carbon emissions of the building operation stage is achieved by calculating the variable (grid carbon emission factor).

[0084] Among non-carbon dioxide emissions, the main ones include emissions from air-conditioning refrigerants, substation operations and sewage discharge in the direct emissions during the building operation phase. This part can be calculated using "activity data × carbon emission factor × global warming potential".

[0085] The direct, indirect and implicit emissions involved in the operation of public buildings in the current year and the sources of renewable energy utilization are classified. The composition of carbon emissions from public buildings is shown in the following table:

[0086] Table 1 Classification calculation table of carbon emissions from public buildings

[0087]

[0088]

[0089] Based on the classification of carbon dioxide and non-carbon dioxide in the building operation stage, the carbon emissions in the building operation stage are predicted by extracting and predicting the carbon emission factors of the power grid. The carbon emissions in the tth year of the operation stage of public buildings mainly include:

[0090]

[0091] Where:

[0092] C B,t —Carbon emissions during the operation phase of the building in year t (kgCO2 e);

[0093] f(t)—predicted regional grid carbon emission factor in year t (kgCO2 e / kWh);

[0094] —Direct non-electricity carbon emissions in year t (kgCO2e);

[0095] —Carbon emissions from non-electricity part of embodied carbon emissions in year t (kgCO2e);

[0096] GD ele,t—Annual grid equivalent substitution activity data of the direct emission electricity portion in year t (kWh);

[0097] GIN ele,t —Annual grid equivalent substitution activity data for indirect emissions in year t (kWh);

[0098] —Annual carbon emissions of the electricity component implied in year t (kgCO2e);

[0099] AD t —Data on the equivalent grid substitution activity of renewable energy generated and consumed annually in year t (kWh);

[0100] AD t1 —Annual grid-connected equivalent substitution activity data of renewable energy in year t (kWh);

[0101] EF t —Annual grid-connected electricity loss coefficient of renewable energy in year t, 0.9454.

[0102] Based on the accounting of carbon emissions during the operation phase of public buildings in the current year, the data of carbon dioxide emissions are replaced by the carbon emission factor of the power grid, and the activity data of carbon emissions during the operation phase of public buildings in each year are extracted. The power factor prediction calculation formula is shown in formula (2):

[0103] f (t) =[f (ti) -(f (tj) -f (ti) ) / n]×m (Formula 2)

[0104] f (t) —Carbon emission factor of regional power grid in year t (kgCO2e / kWh);

[0105] f (ti) —Base year regional grid carbon emission factor (kgCO2e / kWh). The base year refers to the year of carbon neutral building application. Data verification is used to understand the building carbon emissions in the application year.

[0106] f (tj) —The predicted value of the regional grid carbon emission factor in the planning year (kgCO2 e / kWh), where the planning year refers to the year in which the building is planned to be carbon neutral;

[0107] n—the number of plan years and base years;

[0108] m—the annual number between year t and the base year.

[0109] The predicted values ​​of annual carbon dioxide emissions from power grids and other emission factors are shown in Table 2: This part of the data is based on the "Research on Carbon Dioxide Emission Factors of China's Regional Power Grids". The data in brackets are the upper and lower limits of the emission factors, representing the calculation results of the new energy rapid development scenario and the new energy policy development scenario respectively.

[0110]

[0111]

[0112]

[0113] The carbon emission calculation of each emission source is shown in formulas (3)-(7)

[0114] 1. Direct emissions:

[0115]

[0116]

[0117] Where:

[0118] C GD —Direct carbon dioxide emissions (kgCO2 e)

[0119] —Direct non-electricity carbon emissions in year t (kgCO2e);

[0120] GD ele,t —Annual grid equivalent substitution activity data of the direct emission electricity part in year t (kWh), including grid equivalent substitution activity data of carbon emission of switch station;

[0121] EF k —Switch station grid carbon emission factor (kgCO2 e / kWh);

[0122] C t —Annual carbon dioxide emissions from heating gas in office buildings (kgCO2e);

[0123] C m — Carbon dioxide emissions from fire extinguishing gas in office buildings (kgCO2e);

[0124] C r — Carbon dioxide emissions from leakage of air conditioning refrigerant in office buildings (kgCO2e); C w —Amount of carbon dioxide produced by wastewater treatment in office buildings (kgCO2e).

[0125] The grid carbon emission factors of the switch station are shown in Table 3:

[0126]

[0127]

[0128] 2. Indirect emissions

[0129] GIN ele,t =∑(C zm,t +C kt,t +C dl,t +C ts,t ) Formula (5)

[0130] Where:

[0131] —Annual grid equivalent substitution activity data for indirect emissions in year t (kWh);

[0132] C zm,t —Lighting electricity consumption in year t (kWh);

[0133] C kt,t —Electricity consumption of air conditioner in year t (kWh);

[0134] C dl,t —Power consumption in year t (kWh);

[0135] C ts,t —Special electricity consumption in year t (kWh).

[0136] 3. Hidden carbon emissions

[0137]

[0138] Where:

[0139] C GE,t —Annual embodied carbon emissions in year t (kgCO2e)

[0140] —Annual emissions of non-electricity embodied carbon in year t (kgCO2e);

[0141] f(t)—regional grid carbon emission factor in year t (kgCO2 e / kWh);

[0142] GE ele,t —Grid equivalent substitution activity data of the electricity part with embodied carbon emissions in year t (kWh), including grid equivalent substitution activity data of carbon emissions from equipment processing such as elevators;

[0143] C S —Annual carbon dioxide emissions from office building equipment maintenance in year t (kgCO2e);

[0144] C W—CO2 emissions from annual material maintenance of office buildings in year t (kgCO2e).

[0145] The power consumption of elevator processing is shown in Table 4:

[0146]

[0147] The following examples are used to illustrate the method provided in this embodiment.

[0148] 1. Project Overview:

[0149] China Power Construction Group East China Survey and Design Institute Co., Ltd. (hereinafter referred to as East China Institute) was established in 1954. It is a large-scale comprehensive Class A survey, design and research unit. East China Institute consists of five main buildings, namely Building 1 (office building), Building 2 (fitness center), Building 3 (catering center), Building 4 and Building 5 (office buildings) and basement. The project was put into use in 2015. The specific parameters are shown in the table below.

[0150]

[0151] 2. Energy and carbon data of Building 1

[0152] Building 1 is an office building with relatively uniform functions, so it is relatively easy to divide and analyze the building's energy consumption. Therefore, it is relatively easy to adopt targeted energy-saving plans and measures, and to obtain relatively accurate energy-saving and carbon-reduction data. The initial setting is to reduce carbon emissions by 30% for air conditioning and 40% for lighting.

[0153]

[0154]

[0155] 3. Carbon emissions accounting

[0156]

[0157]

[0158] 4. The power factor prediction and carbon emission prediction results are shown in the table below. The curve representation of the prediction results is shown in Figure 2 .

[0159]

[0160]

[0161] The present invention also provides a carbon neutral carbon emission prediction device for a public building operation phase, comprising:

[0162] The classification module is used to classify the sources of carbon emissions involved in the operation phase of public buildings in the current year;

[0163] The accounting conversion module calculates carbon emissions for each category based on the classification results of the classification module, and replaces the grid carbon emissions in the accounting results with the grid carbon emission factors based on the accounting year and converts them into activity data;

[0164] The grid carbon emission factor prediction module obtains the carbon emission data of public buildings in each year, extracts activity data, and predicts the grid carbon emission factor based on the extraction results;

[0165] The carbon emission prediction module predicts the carbon emissions of the building operation stage in the corresponding year based on the classified accounting results of the public building operation stage in the accounting year and the grid carbon emission factor predicted by the grid carbon emission factor prediction module.

[0166] The present invention also provides a storage medium on which a computer program executable by a processor is stored, and the steps of the method are implemented when the computer program is executed.

[0167] The present invention also provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program executable by the processor, and the steps of the method are implemented when the computer program is executed.

[0168] Based on the carbon emission accounting boundaries and related influencing factors in the operation stage of public buildings, the present invention divides carbon emissions into direct carbon emissions, indirect carbon emissions and implicit carbon emissions, extracts electricity carbon emission factors, and constructs a carbon emission prediction model for the operation stage of public buildings; at the same time, based on the carbon emission prediction model for the operation stage of public buildings, a sub-item metering system for electricity consumption in public buildings is established, and three-level energy consumption nodes are set up according to the energy consumption structure (during the implementation process, it is necessary to monitor the equipment in each secondary energy consumption, and the third-level energy consumption node refers to the monitoring of specific energy-consuming equipment), and an energy consumption monitoring system for the operation stage of public buildings is established based on the carbon emission monitoring calculation needs.

[0169] The present invention sets up sub-item metering for carbon emission and energy consumption monitoring of public buildings, so that the public building energy consumption data obtained through monitoring can be directly applied to the calculation, analysis and prediction of carbon emissions of public buildings; the present invention associates the direct emissions, indirect emissions and implicit emissions involved in the operation stage of public buildings with the electricity carbon emission factor, and achieves the effect of predicting carbon emissions of public buildings based on the changes in the trend of the electricity carbon emission factor.

[0170] The above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can understand that within the technical scope disclosed by the present invention, for those skilled in the art, equivalent replacements or changes to the technical solutions and inventive concepts of the present invention should fall within the protection scope of the present invention.

Claims

1. A method for predicting and calculating carbon emissions of carbon neutrality in the operation stage of public buildings, characterized in that: Categorize the sources of direct, indirect and implicit emissions and renewable energy used in the operation of public buildings in the current year; After calculating the direct emissions, indirect emissions, implicit emissions and renewable energy utilization, the grid carbon emissions in the calculation results are replaced by the grid carbon emission factors based on the calculation year and converted into activity data. Extract activity data on carbon emissions during the operation phase of public buildings each year, and predict the carbon emission factors of the power grid based on the extraction results; Based on the classified accounting results of the public building operation stage in the accounting year, the predicted grid carbon emission factor is used to predict the carbon emissions of the building operation stage in the corresponding year.

2. According to claim 1, a method for predicting and calculating carbon neutral carbon emissions during the operation phase of a public building, characterized in that: The classification method divides direct, indirect and implicit emissions and renewable energy utilization into at least one sub-item respectively, and each sub-item is further divided into at least one first-level energy consumption node. The carbon emission data of direct, indirect and implicit emissions and renewable energy utilization are obtained by calculating the carbon emissions of nodes at each level.

3. According to claim 2, a method for predicting and calculating carbon neutral carbon emissions during the operation phase of a public building, characterized in that: The calculation formula for direct emissions is: Where: C GD —Direct carbon dioxide emissions (kgCO2 e) —Direct non-electricity carbon emissions in year t (kgCO2e), where year t refers to the year from which the carbon emissions are to be predicted and calculated starting from the current year of accounting; GD ele,t —Annual grid equivalent substitution activity data of the direct emission electricity part in year t (kWh), including grid equivalent substitution activity data of carbon emission of switch station; EF k —Switch station grid carbon emission factor (kgCO2 e / kWh); C t —Annual carbon dioxide emissions from heating gas in office buildings (kgCO2e); C m — Carbon dioxide emissions from fire extinguishing gas in office buildings (kgCO2e); C r — Carbon dioxide emissions from refrigerant leakage in air conditioners in office buildings (kgCO2e); C w —Amount of carbon dioxide produced by sewage treatment in office buildings (kgCO2e); The grid carbon emission factor for the switch station is:

4. According to claim 3, a method for predicting and calculating carbon neutral carbon emissions during the operation phase of a public building, characterized in that: The calculation formula for the indirect emissions is: GIN ele,t =∑(C zm,t +C kt,t +C dl,t +C ts,t ) Where: —Annual grid equivalent substitution activity data for indirect emissions in year t (kWh); C zm,t —Lighting electricity consumption in year t (kWh); C kt,t —Electricity consumption of air conditioner in year t (kWh); C dl,t —Power consumption in year t (kWh); C ts,t —Special electricity consumption in year t (kWh).

5. According to claim 4, a method for predicting and calculating carbon neutral carbon emissions during the operation phase of a public building, characterized in that: The calculation formula for invisible carbon emissions is: Where: C GE,t —Annual embodied carbon emissions in year t (kgCO2e) —Annual emissions of non-electricity embodied carbon in year t (kgCO2e); f(t)—regional grid carbon emission factor in year t (kgCO2 e / kWh); GE ele,t —Grid equivalent substitution activity data of the electricity part with embodied carbon emissions in year t (kWh), including grid equivalent substitution activity data of carbon emissions from elevator processing; C S —Annual carbon dioxide emissions from office building equipment maintenance in year t (kgCO2e); C W —CO2 emissions from annual material maintenance of office buildings in year t (kgCO2e); The grid carbon emission factor for elevator processing is:

6. The method for predicting and calculating carbon neutral carbon emissions during the operation phase of a public building according to claim 5 is characterized in that: The grid carbon emission factor is predicted using the following formula: f (t) =[f (ti) -(f (tj) -f (ti) ) / n]×m f (t) —Carbon emission factor of regional power grid in year t (kgCO2e / kWh); f (ti) —Base year regional grid carbon emission factor (kgCO2e / kWh), where base year refers to the year of carbon neutral building application; f (tj) —The predicted value of the regional grid carbon emission factor in the planning year (kgCO2 e / kWh), where the planning year refers to the year in which the building is planned to be carbon neutral; n—the number of plan years and base years; m—the annual number between year t and the base year.

7. The method for predicting and calculating carbon neutral carbon emissions during the operation phase of a public building according to claim 6 is characterized in that: The predicted grid carbon emission factor is used to predict the carbon emissions of the building operation phase in the corresponding year, and the prediction formula is: Where: C B,t —Carbon emissions during the operation phase of the building in year t (kgCO2 e); f(t)—predicted regional grid carbon emission factor in year t (kgCO2 e / kWh); —Direct non-electricity carbon emissions in year t (kgCO2e); —The carbon emissions of the non-electricity part of the embodied carbon emissions in year t (kgCO2e); GD ele,t —Annual grid equivalent substitution activity data of the direct emission electricity portion in year t (kWh); GIN ele,t —Annual grid equivalent substitution activity data for indirect emissions in year t (kWh); —Annual carbon emissions of the electricity component implied in year t (kgCO2e); AD t —Data on the equivalent grid substitution activity of renewable energy generated and consumed annually in year t (kWh); AD t1 —Annual grid-connected equivalent substitution activity data of renewable energy in year t (kWh); EF t —Annual grid-connected electricity loss coefficient of renewable energy in year t, 0.9454.

8. A carbon neutral carbon emission prediction device for the operation stage of a public building, characterized in that: include: The classification module is used to classify the sources of carbon emissions involved in the operation phase of public buildings in the current year; The accounting conversion module calculates carbon emissions for each category based on the classification results of the classification module, and replaces the grid carbon emissions in the accounting results with the grid carbon emission factors based on the accounting year and converts them into activity data; The grid carbon emission factor prediction module obtains the carbon emission data of public buildings in each year, extracts activity data, and predicts the grid carbon emission factor based on the extraction results; The carbon emission prediction module predicts the carbon emissions of the building operation stage in the corresponding year based on the classified accounting results of the public building operation stage in the accounting year and the grid carbon emission factor predicted by the grid carbon emission factor prediction module.

9. A storage medium having stored thereon a computer program executable by a processor, characterized in that: When the computer program is executed, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer device comprising a memory and a processor, wherein the memory stores a computer program executable by the processor, wherein: When the computer program is executed, the steps of the method according to any one of claims 1 to 7 are implemented.

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