A carbon emission prediction calculation method, device, medium and equipment for carbon neutralization in a public building operation stage

Abstract

The application relates to the technical field of prediction methods, in particular to a carbon neutral carbon emission prediction and calculation method for a public building operation stage, which classifies the sources of direct, indirect and implicit emission amounts and renewable energy utilization amounts involved in the public building operation stage in the current year; after the classification of the direct emission amount, the indirect emission amount, the implicit emission amount and the renewable energy utilization amount is calculated, the part of the calculation result related to the power grid carbon emission is replaced by the equivalent of the power grid carbon emission factor based on the calculation year, and is converted into activity data; the activity data of the carbon emission of the public building operation stage in each year is extracted, the power grid carbon emission factor is predicted according to the extraction result; and based on the classification calculation result of the public building operation stage in the current year, the predicted power grid carbon emission factor is used to predict the carbon emission amount of the building operation stage in the corresponding year.

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

[0002] Currently, relevant building carbon emission prediction methods exist within the construction industry, such as the Chinese invention patent application CN115719123A, titled "A Method for Predicting Building Carbon Emissions." This patent involves constructing an online building carbon emissions platform, populating it with carbon emission factor data and a large amount of actual project data. The latter serves as sample data for big data analysis. The platform analyzes the sample data, identifies influencing factors, determines factor parameters, and develops a semi-empirical formula that combines this with a theoretical formula. This semi-empirical formula is then embedded in the carbon emission platform, enabling carbon emissions to be predicted when new building data is input. This in turn generates a carbon emission analysis report and ultimately provides carbon reduction design recommendations for the building. This technical solution targets the design phase of building carbon emissions. The patent expands the engineering phase from "construction drawing design" to four stages: scheme design, preliminary design, construction drawing design, and completion audit. The first three stages are the design phase, employing different prediction methods with increasingly detailed information and increasingly accurate prediction results. The prediction results are then verified using data from the completion audit phase. The carbon emissions forecasts in this section are still based on verification and prediction of existing data, rather than actual data monitoring, so the forecast accuracy is uncertain. At the same time, the forecast can only be achieved in the short term, which has certain limitations.

[0003] There is also a related monitoring and calculation patent for the operation phase—the Chinese invention patent application with publication number CN118671267A, entitled "A Method and System for Measuring and Monitoring Building Operation Carbon Emissions." This system uses a pre-set carbon emission monitoring sensor network to collect real-time energy consumption data or carbon emissions from each energy-consuming device within the building. This data is then uploaded to an edge computing device deployed near the carbon emission monitoring sensor network. The edge computing device deployed near the carbon emission monitoring sensor network calculates the real-time energy consumption data or carbon emissions from each energy-consuming device within the building, obtains the carbon emissions of each device within the building, and uploads it to a cloud platform. The cloud platform's big data analysis algorithms analyze the real-time carbon emissions of each device within the building, obtain carbon emission trend forecasts for each device within the building, and alerts for abnormal carbon emissions. This generates a carbon emission analysis report for each device within the building. The report is then displayed using a 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 various energy-consuming equipment in the building. This results in this method only being able to perform short-term carbon emission predictions during the building operation phase, and cannot perform long-term carbon emission data predictions.

[0004] 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 various classified carbon sources in the prediction model; 2. The existing method for predicting carbon emissions during the operation phase of public buildings can only predict future short-term or periodic carbon emissions during the operation phase of public buildings through big data analysis in the energy consumption monitoring platform. Summary of the Invention

[0005] The purpose of the present invention is to overcome the shortcomings of the background technology and provide a method for predicting building carbon emissions.

[0006] The purpose of the present invention is to achieve through the following technical solutions:

[0007] A method for predicting and calculating carbon neutral carbon emissions during the operation phase of public buildings.

[0008] Categorize the sources of direct, indirect and implicit emissions and renewable energy use involved in the operation of public buildings in the current year;

[0009] After calculating each category of direct emissions, indirect emissions, implicit emissions, and renewable energy utilization, the grid carbon emissions portion of the calculation results is replaced with an equivalent grid carbon emission factor based on the accounting year and converted into activity data;

[0010] Extract activity data on carbon emissions from public building operations each year, and predict grid carbon emission factors based on the extraction results;

[0011] 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.

[0012] In a further solution, 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.

[0013] In a further solution, the calculation formula for the direct emissions is:

[0014]

[0015]

[0016] Where:

[0017] C GD —Direct carbon dioxide emissions (kgCO2 e)

[0018] —Direct non-power carbon emissions in year t (kgCO2e), where year t refers to the year from which carbon emissions are to be estimated and calculated starting from the current year of accounting;

[0019] GD ele,t —Annual grid equivalent substitution activity data for the directly emitted electricity portion in year t (kWh), including grid equivalent substitution activity data for carbon emissions from switch stations;

[0020] EF k —Switch station grid carbon emission factor (kgCO2 e / kWh);

[0021] C t —Annual carbon dioxide emissions from heating gas in office buildings (kgCO2e);

[0022] Cm — Carbon dioxide emissions from fire extinguishing gas in office buildings (kgCO2e);

[0023] C r —CO2 emissions from refrigerant leakage from air conditioners in office buildings (kgCO2e);

[0024] C w —Amount of carbon dioxide produced by wastewater treatment in office buildings (kgCO2e);

[0025] The grid carbon emission factor for the switch station is:

[0026] type Carbon emission intensity 110kv 25.66 kg CO2e / MWh 220kv <![CDATA[26.05kgCO2e / 万kWh]]>

[0027] In a further solution, the calculation formula for the indirect emissions is:

[0028]

[0029] Where:

[0030] —Annual grid equivalent substitution activity data for indirect emissions in year t (kWh);

[0031] C zm,t —Lighting electricity consumption in year t (kWh);

[0032] C kt,t —Electricity consumption of air conditioner in year t (kWh);

[0033] C dl,t —Power consumption in year t (kWh);

[0034] C ts,t —Special electricity consumption in year t (kWh).

[0035] In a further solution, the calculation formula for the invisible carbon emissions is:

[0036]

[0037] Where:

[0038] C GE,t —Annual embodied carbon emissions in year t (kgCO2e)

[0039] —Annual embodied carbon emissions from non-electricity sources in year t (kgCO2e);

[0040] f(t)—regional grid carbon emission factor in year t (kgCO2 e / kWh);

[0041] GE ele,t—Grid equivalent substitution activity data of the electricity portion of the embodied carbon emissions in year t (kWh), including grid equivalent substitution activity data of elevator processing carbon emissions;

[0042] C S — Annual carbon dioxide emissions from office building equipment maintenance in year t (kgCO2e);

[0043] C W —CO2 emissions from annual material maintenance of office buildings in year t (kgCO2e);

[0044] The grid carbon emission factor for elevator processing is:

[0045] type Energy consumption intensity Elevator processing 168.78kWh / unit

[0046] In a further solution, the grid carbon emission factor is predicted using the following formula:

[0047] f (t) =[f (ti) -(f (tj) -f (ti) ) / n]×m

[0048] f (t) —Carbon emission factor of regional power grid in year t (kgCO2e / kWh);

[0049] f (ti) —Base year regional grid carbon emission factor (kgCO2e / kWh), where the base year refers to the year of the carbon neutral building application;

[0050] f (tj) —The projected 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;

[0051] n—the number of plan years and base years;

[0052] m—the number of years between year t and the base year.

[0053] 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. The prediction formula is:

[0054]

[0055] Where:

[0056] C B,t —Carbon emissions during the building's operation phase in year t (kgCO2 e);

[0057] f(t)—predicted regional grid carbon emission factor in year t (kgCO2 e / kWh);

[0058] —Direct non-electricity carbon emissions in year t (kgCO2e);

[0059] —The amount of embodied carbon emissions from non-electricity sources in year t (kgCO2e);

[0060] GD ele,t —Annual grid equivalent substitution activity data of the directly emitted electricity portion in year t (kWh);

[0061] GIN ele,t —Annual grid equivalent substitution activity data for indirect emissions in year t (kWh);

[0062] —Annual carbon emissions from electricity in year t (kgCO2e);

[0063] AD t —Data on the equivalent grid substitution activity of renewable energy generated and consumed annually in year t (kWh);

[0064] AD t1 —Annual grid-equivalent substitution activity data of renewable energy in year t (kWh);

[0065] EF t —Annual grid-connected power loss coefficient of renewable energy in year t, 0.9454.

[0066] Another technical solution of the present invention is: a carbon neutral carbon emission prediction device for a public building in the operation phase, comprising:

[0067] The classification module is used to classify the sources of carbon emissions involved in the operation phase of public buildings in the current year;

[0068] The accounting conversion module calculates carbon emissions for each category based on the classification results of the classification module, and converts the grid carbon emissions in the accounting results into activity data by replacing them with the grid carbon emission factors based on the accounting year.

[0069] The grid carbon emission factor prediction module obtains carbon emission data for the operation phase of public buildings each year, extracts activity data, and predicts the grid carbon emission factor based on the extraction results;

[0070] The carbon emission prediction module, based on the classified accounting results of the public building operation phase in the accounting year, uses the grid carbon emission factor predicted by the grid carbon emission factor prediction module to predict the carbon emissions of the building operation phase in the corresponding year.

[0071] Another technical solution of the present invention is: a storage medium storing a computer program that can be executed by a processor, wherein the computer program implements the steps of the above-mentioned method when executed.

[0072] 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.

[0073] 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 by analyzing the trend changes of electricity carbon emission factors.

[0074] 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 learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0075] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following is a brief introduction to the drawings required for use in the embodiments of the present invention. It should be understood that the following drawings only illustrate certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other relevant drawings can be obtained based on these drawings without paying any creative work.

[0076] Figure 1 This is a flow chart of the prediction method provided by an embodiment of the present invention.

[0077] Figure 2 This is a curve chart of the prediction results of the case provided by the embodiment of the present invention. DETAILED DESCRIPTION

[0078] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention.

[0079] Carbon emissions during the operation stage of public buildings are mainly the aggregation of direct emissions, indirect emissions and implicit emissions during the operation of public buildings.

[0080] Indirect emissions during the operation phase are the primary component of public building carbon emissions. Furthermore, as more and more direct and implicit emissions are converted to indirect emissions during building energy-saving renovations, indirect emissions are a crucial component of calculating building carbon emissions during the operation phase. Electricity emissions account for over 40% of indirect emissions during the operation phase.

[0081] Carbon emissions is an abbreviation for greenhouse gas emissions, the most important of which is carbon dioxide (CO2). Since non-CO2 emissions are difficult to reduce in the process of building energy conservation and carbon reduction and are necessary emissions, the embodiment of the present invention divides the carbon emissions of public buildings during the operation phase into carbon dioxide emissions and non-CO2 emissions for calculation from the perspective of different greenhouse gases. The carbon dioxide portion extracts the grid carbon emission factor as a variable to establish a new carbon emission prediction algorithm. The direct, indirect, and implicit emissions involved in the operation phase of public buildings are converted into activity data based on the grid carbon emission factor of the accounting year. The purpose of predicting the carbon emissions of buildings during the operation phase is achieved by extrapolating the variable (grid carbon emission factor).

[0082] 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".

[0083] The direct, indirect and implicit emissions involved in the operation of public buildings in the current year, as well as the sources of renewable energy utilization, are classified. The composition of carbon emissions from public buildings is shown in the following table:

[0084] Table 1 Classification calculation table of carbon emissions of public buildings

[0085]

[0086]

[0087] Based on the classification of CO2 and non-CO2 during the building operation phase, the carbon emissions during the building operation phase are predicted by extracting and predicting the grid carbon emission factors. The carbon emissions of public buildings in the tth year during the operation phase mainly include:

[0088]

[0089] Where:

[0090] C B,t —Carbon emissions during the building's operation phase in year t (kgCO2 e);

[0091] f(t)—predicted regional grid carbon emission factor in year t (kgCO2 e / kWh);

[0092] —Direct non-electricity carbon emissions in year t (kgCO2e);

[0093] —The amount of embodied carbon emissions from non-electricity sources in year t (kgCO2e);

[0094] GD ele,tAnnual grid equivalent replacement activity data of direct emission electricity part in the tth year (kWh);

[0095] GIN ele,t Annual grid equivalent replacement activity data of indirect emission in the tth year (kWh);

[0096] Annual carbon emission of implicit electricity part in the tth year (kgCO2e);

[0097] AD t Annual grid equivalent replacement activity data of renewable self-generation in the tth year (kWh);

[0098] AD t1 Annual grid equivalent replacement activity data of renewable on-grid in the tth year (kWh);

[0099] EF t Renewable on-grid electricity loss coefficient in the tth year, 0.9454.

[0100] Based on the accounting of carbon emissions in the operation stage of public buildings in the current year, the data of the carbon dioxide emission part is equivalent to the carbon emission factor of the grid, and the activity data of the carbon emission of each annual public building in the operation stage is extracted. The power factor prediction calculation formula is shown in formula (2):

[0101] f (t) = [f (ti) -(f (tj) -f (ti) ) / n]×m (formula 2)

[0102] f (t) Regional grid carbon emission factor in the tth year (kgCO2e / kWh);

[0103] f (ti) Base year regional grid carbon emission factor (kgCO2e / kWh), the base year refers to the carbon neutral building application year, and the building carbon emission in the application year is understood through data verification;

[0104] f (tj) Forecast value of regional grid carbon emission factor in the planned year (kgCO2e / kWh), the planned year refers to the year when the building carbon neutralization is planned to be completed;

[0105] n—The number of years between the planned year and the base year;

[0106] m—The number of years between the tth year and the base year.

[0107] The annual grid equivalent emission factor of carbon dioxide emissions is shown in Table 2: The data in this part is based on the Research on Carbon Dioxide Emission Factors of China's Regional Power Grids. The data in the brackets are the upper and lower limits of the emission factor, representing the calculation results of the new energy high-speed development scenario and the new energy policy development scenario, respectively.

[0108]

[0109]

[0110]

[0111] The carbon emissions of each emission source are calculated by Formulas (3) - (7)

[0112] 1. Direct emissions:

[0113]

[0114]

[0115] In the formula:

[0116] C GD — Direct carbon dioxide emissions (kgCO2e)

[0117] — Direct carbon emissions of non-power part in the tth year (kgCO2e);

[0118] GD ele,t — Annual grid equivalent emission data of power part in the tth year (kWh), which includes the grid equivalent emission data of carbon emissions of switch station;

[0119] EF k — Grid carbon emission factor of switch station (kgCO2e / kWh);

[0120] C t — Annual carbon dioxide emissions of office building for heating gas (kgCO2e);

[0121] C m — Carbon dioxide emissions of office building for fire extinguishing gas (kgCO2e);

[0122] C r — Carbon dioxide emissions of office building for air conditioning refrigerant leakage (kgCO2e);C w — Carbon dioxide emissions of office building for sewage treatment (kgCO2e).

[0123] The grid carbon emission factor of switch station is shown in Table 3:

[0124]

[0125]

[0126] 2. Indirect emissions

[0127] GIN ele,t =∑(C zm,t +C kt,t +C dl,t +C ts,t ) Formula (5)

[0128] Where:

[0129] —Annual grid equivalent substitution activity data for indirect emissions in year t (kWh);

[0130] C zm,t —Lighting electricity consumption in year t (kWh);

[0131] C kt,t —Electricity consumption of air conditioner in year t (kWh);

[0132] C dl,t —Power consumption in year t (kWh);

[0133] C ts,t —Special electricity consumption in year t (kWh).

[0134] 3. Hidden carbon emissions

[0135]

[0136] Where:

[0137] C GE,t —Annual embodied carbon emissions in year t (kgCO2e)

[0138] —Annual embodied carbon emissions from non-electricity sources in year t (kgCO2e);

[0139] f(t)—regional grid carbon emission factor in year t (kgCO2 e / kWh);

[0140] GE ele,t —Grid equivalent substitution activity data for the electricity portion of the embodied carbon emissions in year t (kWh), including grid equivalent substitution activity data for carbon emissions from equipment such as elevators;

[0141] C S — Annual carbon dioxide emissions from office building equipment maintenance in year t (kgCO2e);

[0142] C W—CO2 emissions from annual material maintenance of office buildings in year t (kgCO2e).

[0143] The power consumption of elevator processing is shown in Table 4:

[0144]

[0145] The following examples illustrate the method provided in this embodiment.

[0146] 1. Project Overview:

[0147] Founded in 1954, PowerChina Huadong Engineering & Research Institute Co., Ltd. ("Huadong Institute") is a large-scale, comprehensive, Class-A national survey, design, and research institute. The institute comprises five main buildings: Building 1 (office building), Building 2 (fitness center), Building 3 (catering center), Buildings 4 and 5 (office buildings), and a basement. The project was put into operation in 2015. Specific parameters are shown in the table below.

[0148]

[0149] 2. Energy and carbon data of Building 1

[0150] Building 1 is an office building with relatively uniform functions, making it relatively easy to categorize and analyze its energy consumption. This makes it easier to implement targeted energy-saving plans and measures, resulting in more accurate energy-saving and carbon-reduction data. Initially, the carbon reduction targets for air conditioning are 30%, and for lighting are 40%.

[0151]

[0152]

[0153] 3. Carbon emissions accounting

[0154]

[0155]

[0156] 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 .

[0157]

[0158]

[0159] The present invention also provides a carbon neutrality carbon emission prediction device for a public building during its operation phase, comprising:

[0160] The classification module is used to classify the sources of carbon emissions involved in the operation phase of public buildings in the current year;

[0161] The accounting conversion module calculates carbon emissions for each category based on the classification results of the classification module, and converts the grid carbon emissions in the accounting results into activity data by replacing them with the grid carbon emission factors based on the accounting year.

[0162] The grid carbon emission factor prediction module obtains carbon emission data for the operation phase of public buildings each year, extracts activity data, and predicts the grid carbon emission factor based on the extraction results;

[0163] The carbon emission prediction module, based on the classified accounting results of the public building operation phase in the accounting year, uses the grid carbon emission factor predicted by the grid carbon emission factor prediction module to predict the carbon emissions of the building operation phase in the corresponding year.

[0164] The present invention also provides a storage medium storing a computer program executable by a processor, wherein the computer program implements the steps of the method when executed.

[0165] 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.

[0166] Based on the carbon emission accounting boundaries and related influencing factors during the operation stage of public buildings, the present invention divides carbon emissions into direct carbon emissions, indirect carbon emissions and implicit carbon emissions, extracts the carbon emission factors of electricity, 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 second-level 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.

[0167] The present invention sets up sub-item metering for public building carbon emission and energy consumption monitoring, so that the public building energy consumption data obtained from monitoring can be directly applied to the calculation, analysis and prediction of public building carbon emissions; 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 public building carbon emissions based on the changes in the trend of the electricity carbon emission factor.

[0168] The above is only a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any technician familiar with this 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 scope of protection of the present invention.

Claims

1. A method for predicting and calculating carbon neutral carbon emissions during the operation phase of a public building, characterized in that: Categorize the sources of direct, indirect and implicit emissions and renewable energy use involved in the operation of public buildings in the current year; After calculating each category of direct emissions, indirect emissions, implicit emissions, and renewable energy utilization, the grid carbon emissions portion of the calculation results is replaced with an equivalent grid carbon emission factor based on the accounting year and converted into activity data; Extract activity data on carbon emissions from public building operations each year, and predict grid carbon emission factors based on the extraction results; Based on the classified accounting results of the public building operation phase in the accounting year, the predicted grid carbon emission factors are used to predict the carbon emissions of the building operation phase in the corresponding year; The grid carbon emission factor is predicted using the following formula: ; —Regional power grid carbon emission factor in year t (kgCO2e / kWh); —Base year regional grid carbon emission factor (kgCO2e / kWh), where the base year refers to the year of the carbon neutral building application; —The projected value of the regional grid carbon emission factor (kgCO2e / kWh) in the planned year, where the planned 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 number of years between year t and the base year.

2. The carbon neutrality carbon emission prediction and calculation method for a public building in the operation phase according to claim 1 is 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. The carbon neutrality carbon emission prediction and calculation method for the operation phase of a public building according to claim 2 is characterized in that: The calculation formula for direct emissions is: ; ; Where: —Direct carbon dioxide emissions (kgCO2e); —Direct non-power carbon emissions in year t (kgCO2e), where year t refers to the year from which carbon emissions are to be predicted and calculated starting from the accounting year; —Annual grid equivalent substitution activity data for the directly emitted electricity portion in year t (kWh), including grid equivalent substitution activity data for carbon emissions from switch stations; —Switch station grid carbon emission factor (kgCO2e / kWh); C t —Annual carbon dioxide emissions from heating gas in office buildings (kgCO2e); C m —CO2 emissions from fire extinguishers in office buildings (kgCO2e); C r —CO2 emissions from refrigerant leakage from 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: When the type is 110kv, the carbon emission intensity is 25.66kgCO2e / 10,000kWh; When the type is 220kv, the carbon emission intensity is 26.05kgCO2e / 10,000kWh.

4. The carbon neutrality carbon emission prediction and calculation method for a public building in the operation phase according to claim 3 is characterized in that: The calculation formula for indirect emissions is: ; 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. The carbon neutrality carbon emission prediction and calculation method for the operation phase of a public building according to claim 4 is characterized in that: The calculation formula for the implied emissions is: ; ; Where: —Annual embodied carbon emissions in year t (kgCO2e) —Annual embodied carbon emissions from non-electricity sources in year t (kgCO2e); —Regional power grid carbon emission factor in year t (kgCO2e / kWh); —Grid equivalent substitution activity data of the electricity portion of the embodied carbon emissions in year t (kWh), including grid equivalent substitution activity data of elevator processing carbon emissions; 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: When the type is elevator processing, the energy consumption intensity is 168.78kWh / unit.

6. The carbon neutrality carbon emission prediction and calculation method for a public building in the operation phase according to claim 1 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. The prediction formula is: ; Where: C B t —Carbon emissions during the building's operation phase in year t (kgCO2e); —Predicted regional grid carbon emission factor in year t (kgCO2e / kWh); —Direct non-electricity carbon emissions in year t (kgCO2e); —The carbon emissions from non-electricity part of embodied carbon emissions in year t (kgCO2e); —Annual grid equivalent substitution activity data for the directly emitted electricity portion in year t (kWh); —Annual grid equivalent substitution activity data for indirect emissions in year t (kWh); —Annual carbon emissions from electricity in year t (kgCO2e); —Annual self-generation and self-consumption grid equivalent substitution activity data of renewable energy in year t (kWh); —Annual grid-equivalent substitution activity data of renewable energy in year t (kWh); —Annual grid-connected power loss coefficient of renewable energy in year t, 0.9454.

7. A carbon neutrality carbon emission prediction device for the operation phase 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 converts the grid carbon emissions in the accounting results into activity data by replacing them with the grid carbon emission factors based on the accounting year. The grid carbon emission factor prediction module obtains carbon emission data for the operation phase of public buildings each year, extracts activity data, and predicts the grid carbon emission factor based on the extraction results; The carbon emission prediction module uses the grid carbon emission factor predicted by the grid carbon emission factor prediction module to predict the carbon emissions of the building operation phase in the corresponding year based on the classified accounting results of the public building operation phase in the accounting year; The grid carbon emission factor is predicted using the following formula: ; —Regional power grid carbon emission factor in year t (kgCO2e / kWh); —Base year regional grid carbon emission factor (kgCO2e / kWh), where the base year refers to the year of the carbon neutral building application; —The projected value of the regional grid carbon emission factor (kgCO2e / kWh) in the planned year, where the planned 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 number of years between year t and the base year.

8. A storage medium storing 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 6 are implemented.

9. 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 6 are implemented.

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