Carbon emission management method based on residence area and equipment stock turnover analysis

Abstract

The invention discloses a carbon emission management method based on residence area and equipment stock turnover analysis. The method comprises the steps of collecting existing residence building stock data, building updating and reconstruction data and terminal equipment data in a building within a statistical range; building an effective stock change model of the residential building based on the dynamic material flow model; the energy efficiency and the carbon emission level of each type of equipment are determined based on terminal equipment data analysis; based on the effective stock change model and the energy efficiency and the carbon emission level of the equipment, performing prediction calculation on the total energy consumption and the carbon emission in any residential building area to obtain a calculation result; and performing carbon emission management on the residential building area according to the calculation result and a preset carbon emission management strategy. According to the invention, by considering the double influence of building updating and vacancy and combining the energy efficiency management of the building terminal equipment, theoretical support and a practical scheme are provided for improving the building energy utilization efficiency and reducing carbon emission.

Description

Technical Field

[0001] The present invention belongs to the technical field of urban planning, and in particular relates to a carbon emission management method based on residential area and equipment stock turnover analysis. Background Art

[0002] With the acceleration of urbanization, the number of residential buildings is increasing, and the efficiency and environmental protection of building stock management and equipment turnover are receiving increasing attention. Traditional building stock and equipment management usually relies on experience or static models, which cannot effectively consider changes in the building life cycle (such as new construction, demolition, renovation, maintenance, etc.), resulting in resource waste and increased environmental burden. Therefore, how to achieve accurate turnover management of residential buildings and their terminal equipment based on the principle of dynamic material flow and reduce energy consumption and carbon emissions has become a technical problem that needs to be solved urgently. Summary of the invention

[0003] In view of this, the present invention proposes a carbon emission management method based on residential area and equipment stock turnover analysis. By considering the dual impact of building renewal and vacancy, and combining the energy efficiency management of building terminal equipment, it provides theoretical support and practical solutions for improving building energy efficiency and reducing carbon emissions.

[0004] In order to achieve the above object, the present invention provides the following technical solutions:

[0005] The present invention provides a carbon emission management method based on residential area and equipment inventory turnover analysis, comprising:

[0006] Collect data on the stock of existing residential buildings within the statistical scope, data on building renovation and reconstruction, and data on terminal equipment in buildings;

[0007] Constructing the effective stock change model of residential buildings based on the dynamic material flow model;

[0008] Determine the energy efficiency and carbon emission level of each type of equipment based on terminal equipment data analysis;

[0009] Based on the effective stock change model and the energy efficiency and carbon emission levels of the equipment, the total energy consumption and carbon emissions in any residential building area are predicted and calculated to obtain the calculation results;

[0010] Carbon emissions management is carried out for residential building areas based on the calculation results and preset carbon emissions management strategies.

[0011] Preferably, the data on the stock of existing residential buildings, the renovation and reconstruction data of buildings, and the terminal equipment data in the buildings collected within the statistical scope include:

[0012] Collect information on the construction age, area, structural type and usage status of existing residential buildings;

[0013] Collecting historical information on building renovation and reconstruction, wherein the historical information on renovation and reconstruction includes renovation time, renovation content and renovation status information;

[0014] Collect detailed information on terminal equipment in the building, including equipment type, energy efficiency rating, age, and maintenance records;

[0015] Based on the collected information, determine the existing residential building stock data, building renovation data, and terminal equipment data within the statistical scope.

[0016] Preferably, constructing an effective stock change model of residential buildings based on a dynamic material flow model includes:

[0017] Based on the principle of dynamic material flow, a building stock change model considering new construction, demolition and renewal factors is established:

[0018] S t =S t―1 +B t ―(D t ―U t )

[0019] U t =D t ×θ

[0020] Among them, S t represents the building stock area at time t, B t represents the newly built area counted at time t, D t represents the demolition area counted at time t, U t represents the renewal area at time t, and θ represents the renewal rate of residential renovation.

[0021] Preferably, determining the energy efficiency and carbon emission level of each type of equipment based on the terminal equipment data analysis includes:

[0022] Determine the equipment type, equipment model, energy efficiency rating, energy consumption data, equipment life, usage history data, and maintenance record data based on the terminal equipment data;

[0023] Classify devices according to device type and model, and calculate the energy consumption per unit time of each type of device through energy efficiency rating, energy consumption data and usage history data;

[0024] The carbon emission rate of the equipment is calculated by the equipment's energy consumption per unit time and the carbon emission factor, where the carbon emission factor refers to the carbon emission corresponding to each unit of energy consumption;

[0025] The collected data and calculation results are comprehensively analyzed to determine the energy efficiency and carbon emission levels of each type of equipment.

[0026] Preferably, based on the effective stock change model and the energy efficiency and carbon emission level of the equipment, the total energy consumption and carbon emission in any residential building area are predicted and calculated, and the calculation results include:

[0027] Determine the change trend of the effective residential area in any residential building area based on the effective stock change model, where the effective residential area refers to the residential area that remains normally used for living during the predicted time period;

[0028] Based on the equipment life, usage history data and maintenance record data of all terminal devices within the effective residential area of ​​the residential building area, the update needs of each terminal device within the effective residential area in the future period are predicted; wherein, the updated terminal devices must meet the minimum standards of the carbon emission management strategy formulated for the residential building area;

[0029] Based on the changing trend of the effective residential area, the energy efficiency of the terminal equipment within the effective residential area, the carbon emission level and the predicted results of the renewal demand, the total energy efficiency and carbon emission level of the effective residential area in the future time period are predicted and calculated to obtain the calculation results.

[0030] Preferably, according to the calculation results and the preset carbon emission management strategy, the carbon emission management of the residential building area includes:

[0031] According to the calculation results, it is determined whether the total energy efficiency and carbon emission level of the effective residential area of ​​any residential building area in the future time period exceeds the preset threshold level;

[0032] When a preset threshold level is exceeded, carbon emissions are managed for the residential building area, where the carbon emissions management strategy is determined by:

[0033] Determine the number and type of terminal devices that need to be updated based on the update requirements of each terminal device in the residential building area in the future period;

[0034] Based on the number and type of terminal equipment in this part, calculate the total energy efficiency and carbon emission level currently generated by this part of terminal equipment;

[0035] Set energy efficiency levels for each type of equipment in the part of terminal equipment so that the total energy efficiency and carbon emission levels generated by all updated terminal equipment are lower than the preset threshold level;

[0036] A carbon emission management strategy corresponding to the residential building area is generated according to the energy efficiency level set for each type of equipment.

[0037] Preferably, the carbon emission management strategy also includes:

[0038] According to the total energy efficiency and carbon emission level of the effective residential area in the residential building area in the future period, restrict the new construction management of residential building stock;

[0039] According to the total energy efficiency and carbon emission levels of the effective residential area of ​​the residential building area in the future period, the installation of terminal equipment in residential buildings will be restricted or it will be recommended to upgrade and update the inefficient terminal equipment.

[0040] Preferably, in the process of predicting and calculating the total energy consumption and carbon emissions in any residential building area, the following is also included:

[0041] For the planned residential buildings, determine the residential type of the residential buildings and perform parametric modeling in R language;

[0042] Determine the energy consumption behavior type of residents in the residential building area through the pre-collected terminal device data, and use it as the condition input for the energy consumption simulation of the parameterized model;

[0043] Determine the value ranges of residential geometric characteristic parameters, envelope structure thermal parameters, internal heat source parameters, indoor air design parameters and equipment energy efficiency parameters based on relevant standards for residential type construction and equipment energy efficiency levels;

[0044] The Latin hypercube sampling method is used to generate energy consumption simulation model groups with different energy consumption behaviors under different residential types according to various parameters, and EnergyPlus software is used to simulate and calculate the cooling load of these models throughout the year;

[0045] A sensitivity analysis was conducted on the simulation results to obtain the key factors affecting the annual cooling load of various residential types;

[0046] SPSS software was used to establish a multiple linear regression model of key influencing factors for residential cooling load throughout the year;

[0047] The residential operation carbon emission prediction model is obtained by combining the energy efficiency ratio of various types of household equipment in the region and the carbon emission factor of electricity;

[0048] The residential operation carbon emission prediction model is used to predict the carbon emission behavior of the planned residential buildings after completion and occupancy, and the prediction results are obtained.

[0049] The present invention has achieved at least the following beneficial effects:

[0050] 1. Combine the stock management of residential buildings with the turnover management of terminal equipment to provide a comprehensive building life cycle management model. The model can comprehensively consider factors such as building stock changes, renovation and equipment turnover, so as to accurately predict the energy efficiency, carbon emissions and resource use of buildings in the next few years.

[0051] 2. The comprehensive model provides a scientific basis for policymakers through reasonable calculation of various data (such as building life, demolition rate, new construction rate, renewal rate, equipment usage, etc.), and provides strong support for the construction industry to achieve carbon reduction goals.

[0052] Other advantages, objectives and features of the present invention will be described in the following description and will be apparent to those skilled in the art to some extent, or those skilled in the art may be taught from the practice of the present invention. The objectives and other advantages of the present invention may be realized and obtained through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] In order to make the purpose, technical solution and beneficial effects of the present invention clearer, the present invention provides the following drawings for illustration:

[0054] Figure 1 The present invention is a flowchart of the steps of a carbon emission management method based on residential area and equipment inventory turnover analysis in an embodiment of the present invention. DETAILED DESCRIPTION

[0055] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0056] The present invention provides a carbon emission management method based on residential area and equipment inventory turnover analysis, comprising:

[0057] Collect data on the stock of existing residential buildings within the statistical scope, data on building renovation and reconstruction, and data on terminal equipment in buildings;

[0058] Constructing the effective stock change model of residential buildings based on the dynamic material flow model;

[0059] Determine the energy efficiency and carbon emission level of each type of equipment based on terminal equipment data analysis;

[0060] Based on the effective stock change model and the energy efficiency and carbon emission levels of the equipment, the total energy consumption and carbon emissions in any residential building area are predicted and calculated to obtain the calculation results;

[0061] Carbon emissions management is carried out for residential building areas based on the calculation results and preset carbon emissions management strategies.

[0062] The working principle and beneficial effects of the above technical solution are as follows: The present invention provides a method for turnover management of residential building stock and terminal equipment based on a dynamic material flow model, which aims to consider the dual impact of building renewal and vacancy, and combine the energy efficiency management of building terminal equipment to provide theoretical support and practical solutions for improving building energy efficiency and reducing carbon emissions. Among them, the turnover model of residential building stock without considering renewal: In this model, the turnover of residential building stock is affected by inflow (new buildings), outflow (demolished buildings) and historical stock, and is estimated using a dynamic material flow model. The effective stock turnover model of residential buildings considering renewal: The present invention defines the concept of "renewal" as extending the life of the building and avoiding large-scale demolition by transforming and optimizing existing buildings (such as envelope structures, pipelines, etc.). Based on this, the present invention proposes an effective stock turnover model for residential buildings considering renewal, which further accurately predicts changes in building stock. Classification and turnover management of terminal equipment in residential buildings: This method also takes into account the terminal equipment in residential buildings. By combining with technical parameters such as building energy efficiency and carbon emissions, the energy consumption and carbon emissions of various types of equipment are analyzed, and management is carried out based on the equipment turnover. A carbon emission management method based on residential area and equipment stock analysis proposed in the present invention aims to accurately predict and effectively manage the total energy consumption and carbon emissions in the residential building area by accurately analyzing the data of residential building stock and terminal equipment. The method first involves collecting the existing residential building stock data, building renovation data, and terminal equipment data in the building within the statistical scope. These data include the area, type, age, renovation content, equipment type, energy efficiency grade, and service life of the building. Then, an effective stock change model of residential buildings is constructed based on a dynamic material flow model. The model comprehensively considers the impact of factors such as new construction, demolition, and renovation on residential stock, and dynamically calculates the change in stock. In addition, the energy efficiency and carbon emission levels of each type of equipment are determined by analyzing the terminal equipment data, providing a basis for the prediction of energy consumption and carbon emissions. Then, combined with the effective stock change model and the energy efficiency and carbon emission level of the equipment, the total energy consumption and carbon emissions in any residential building area are predicted and calculated to obtain accurate calculation results. Finally, based on these calculation results and the preset carbon emission management strategy, carbon emission management is carried out in the residential building area, which may include formulating emission reduction plans, optimizing energy use, and promoting high-efficiency equipment. The beneficial effect of this method is that it can accurately predict the energy consumption and carbon emissions of residential buildings, provide a scientific basis for carbon emission management in residential building areas, help managers formulate more effective emission reduction strategies, improve overall energy efficiency, and promote environmental sustainable development. At the same time, it provides data support and scientific basis for the government and relevant agencies to formulate carbon emission-related policies and regulations, enhance residents and managers' understanding and attention to carbon emission issues, and promote the improvement of environmental awareness.

[0063] In a specific embodiment, the residential building stock turnover model without considering the renewal of the building stock is affected by the demolition and construction of the building without considering the renewal of the building. Assume that in a specific year, the stock of residential buildings is mainly determined by the following factors:

[0064] Newly constructed building area: Newly constructed residential buildings will increase the stock area.

[0065] Demolished building area: As buildings age, those that have reached the end of their life cycle will be demolished.

[0066] Historical stock area: residential building area built in the previous period.

[0067] The model is based on the principle of dynamic material flow and dynamically calculates the changes in stock through the flow of area of ​​newly built and demolished buildings.

[0068] Changes in stock area: At each time point, the stock area of ​​the building is calculated based on the inflow (new construction area) and outflow (demolition area). The formula is as follows:

[0069] Existing area t = existing area t-1 + new construction area t- demolished area t

[0070] Calculation of new construction area: The area of ​​new buildings is usually predicted based on factors such as urban population growth, residential demand and land development. The new construction area can be expressed as:

[0071] Newly built area t = population t × per capita living area t

[0072] Calculation of demolition area: The demolition area is usually predicted by the life cycle of residential buildings. Assuming that the life cycle of the building follows a normal distribution, the area to be demolished each year is calculated based on the life of the building and the demolition rate.

[0073] Historical data accounting: Using the national statistical yearbook and local statistical data, we analyzed the newly built and demolished building areas in the past few years to provide preliminary data for the model.

[0074] Future Forecast: Based on historical data and urban population growth trends, combined with building life distribution, the building stock and demolition area are predicted in the next few years.

[0075] In the traditional model without considering building renewal, demolition and new construction are the only influencing factors. In order to more accurately reflect urban development and building life cycle, considering the impact of urban renewal (building renovation), the present invention proposes the concept of "effective stock".

[0076] Effective stock refers to the stock of buildings that have been renovated or upgraded to keep them in service. Although such buildings have not been completely demolished, their service life has been extended through renovation and updating of enclosure structures, pipe network systems, etc.

[0077] Definition of building renewal: Building renewal refers to the renovation of old residential buildings to extend their service life and avoid complete demolition. Based on the renewal rate, the number of buildings that are renewed each year can be determined.

[0078] Setting the renewal rate: The renewal rate refers to the proportion of buildings selected for renovation each year, which is usually set based on factors such as local policies, urban development plans and market demand.

[0079] Calculation of updated residential stock: When considering the updated situation, the effective stock of residential buildings will be divided into two categories: updated stock and non-updated stock. Updated stock refers to buildings that have been renovated, and non-updated stock refers to buildings that still need to be demolished. The formula is as follows:

[0080] Effective stock area t = historical stock area t-1 + new construction area t-(demolition area t-renewal area t)

[0081] Among them, the renewal area refers to the building area that is being renewed and renovated.

[0082] Calculation of renewal area: The renewal area is determined by factors such as the age of the building, the degree of renovation, and the type of building. The formula is as follows: Renewal area t = demolished area t × renewal rate

[0083] Forecast of urban renewal rate: Based on the city’s renewal plan and related policies, the building renewal rate in the next few years is predicted.

[0084] Adjustment of effective stock: By adjusting the renewal rate, the annual change in effective stock area is calculated to obtain the updated residential building stock situation.

[0085] Classification and turnover management of residential building terminal equipment,

[0086] Terminal equipment classification: Terminal equipment in residential buildings includes but is not limited to electrical equipment, HVAC equipment, plumbing systems, lighting systems, etc. Each type of equipment has different energy efficiency requirements and carbon emission levels during the life cycle of the building.

[0087] Equipment energy efficiency analysis: The energy efficiency of equipment is closely related to the overall energy efficiency of the building. Especially in the process of renovating old houses, the renewal of terminal equipment and the improvement of energy efficiency are crucial. By managing the energy efficiency of equipment, the carbon emissions of buildings can be effectively reduced and the efficiency of resource utilization can be improved.

[0088] Equipment turnover model: Equipment turnover refers to the process of updating, replacing or modifying equipment during use. The calculation formula for equipment turnover rate is as follows:

[0089] Equipment turnover rate t = number of replaced equipment / total number of equipment / total number of equipment

[0090] The equipment turnover rate is calculated by estimating the age, replacement plan and life cycle of each type of equipment in the building, thereby predicting future equipment updates.

[0091] Carbon emission management of equipment: Based on the energy efficiency and usage of each type of equipment, the carbon emissions of the equipment during its life cycle can be calculated. The update of terminal equipment can not only improve energy efficiency, but also effectively reduce the carbon emissions of buildings. The carbon emission management formula of equipment is as follows:

[0092] Equipment carbon emissions t = equipment energy efficiency × equipment service life × energy efficiency improvement rate

[0093] The working principle and beneficial effects of the above technical solution are as follows: The embodiment of the present invention combines the stock management of residential buildings with the turnover management of terminal equipment to provide a comprehensive building life cycle management model. The model can comprehensively consider factors such as building stock changes, renovation and equipment turnover, so as to accurately predict the energy efficiency, carbon emissions and resource usage of the building in the next few years.

[0094] This comprehensive model provides a scientific basis for policymakers through reasonable calculation of various data (such as building life, demolition rate, new construction rate, renewal rate, equipment usage, etc.), and provides strong support for the construction industry to achieve carbon reduction goals.

[0095] In a preferred embodiment, the collection of existing residential building stock data, building renovation data, and terminal equipment data within the statistical scope includes:

[0096] Collect information on the construction age, area, structural type and usage status of existing residential buildings;

[0097] Collecting historical information on building renovation and reconstruction, wherein the historical information on renovation and reconstruction includes renovation time, renovation content and renovation status information;

[0098] Collect detailed information on terminal equipment in the building, including equipment type, energy efficiency rating, age, and maintenance records;

[0099] Based on the collected information, determine the existing residential building stock data, building renovation data, and terminal equipment data within the statistical scope.

[0100] The working principle and beneficial effects of the above technical solution are as follows: first, it involves collecting detailed information of existing residential buildings, including the construction age, area, structural type and usage status, so as to understand the basic characteristics and energy consumption of the buildings. Then, the historical information of building renovation is collected, covering the renovation time, content and status, and the impact of the renovation on the building energy efficiency and carbon emissions is evaluated. In addition, detailed information of terminal equipment in the building is also collected, including equipment type, energy efficiency rating, service life and maintenance records, which is crucial for determining the energy efficiency and carbon emission level of each type of equipment. Based on these detailed data, the technical solution of the present invention can determine the existing residential building stock data, building renovation data and terminal equipment data in the building within the statistical scope, and then construct a dynamic material flow model to reflect the effective stock changes of residential buildings. By analyzing the terminal equipment data, the energy efficiency and carbon emission level of each type of equipment are determined, and then combined with the effective stock change model, the total energy consumption and carbon emissions in any residential building area are predicted and calculated to obtain accurate calculation results. Finally, according to these calculation results and the preset carbon emission management strategy, carbon emission management is carried out for the residential building area. The technical solution of the present invention provides an innovative solution for carbon emission management of residential buildings through precise data analysis and scientific management methods, which helps to achieve the goals of energy conservation, emission reduction and sustainable development.

[0101] In a preferred embodiment, constructing an effective stock change model of residential buildings based on a dynamic material flow model includes:

[0102] Based on the principle of dynamic material flow, a building stock change model considering new construction, demolition and renewal factors is established:

[0103] S t =S t―1 +B t ―(D t ―U t )

[0104] U t =D t ×θ

[0105] Among them, S t represents the building stock area at time t, B t represents the newly built area counted at time t, D t represents the demolition area counted at time t, U t represents the renewal area at time t, and θ represents the renewal rate of residential renovation.

[0106] In a preferred embodiment, determining the energy efficiency and carbon emission level of each type of equipment based on the terminal equipment data analysis includes:

[0107] Determine the equipment type, equipment model, energy efficiency rating, energy consumption data, equipment life, usage history data, and maintenance record data based on the terminal equipment data;

[0108] Classify devices according to device type and model, and calculate the energy consumption per unit time of each type of device through energy efficiency rating, energy consumption data and usage history data;

[0109] The carbon emission rate of the equipment is calculated by the equipment's energy consumption per unit time and the carbon emission factor, where the carbon emission factor refers to the carbon emission corresponding to each unit of energy consumption;

[0110] The collected data and calculation results are comprehensively analyzed to determine the energy efficiency and carbon emission levels of each type of equipment.

[0111] The working principle and beneficial effects of the above technical solution are as follows: The process of determining the energy efficiency and carbon emission level of each type of equipment based on the analysis of terminal equipment data is a comprehensive technical solution designed to accurately evaluate the energy efficiency and carbon emission levels of various types of terminal equipment in residential buildings. This solution first involves collecting detailed data about terminal equipment, including key information such as equipment type, model, energy efficiency rating, energy consumption data, equipment life, usage history, and maintenance records. Subsequently, the equipment is classified according to the equipment type and model so that specific energy efficiency and carbon emission calculation methods can be applied to different categories of equipment. The energy consumption per unit time of each type of equipment is calculated using the energy efficiency rating, energy consumption data, and usage history data. This is a key step in evaluating the energy efficiency of the equipment because it is directly related to the energy consumption when the equipment is running. Then, the carbon emission rate of the equipment is calculated based on the energy consumption per unit time of the equipment and the carbon emission factor, where the carbon emission factor refers to the carbon emission corresponding to each unit of energy consumption, which is usually determined by the energy type and equipment efficiency. Finally, the collected data and calculation results are comprehensively analyzed to determine the energy efficiency and carbon emission level of each type of equipment. The working principle of this technical solution is that through detailed data analysis and calculation, it can more accurately evaluate the energy efficiency and carbon emission levels of various types of terminal equipment, and provide accurate data support for carbon emission management. Its beneficial effects include improving prediction accuracy, optimizing energy use, supporting decision-making, promoting sustainable development, and raising environmental awareness. By accurately managing and reducing carbon emissions, the technical solution of the present invention promotes sustainable development in the residential building sector, in line with the goal of responding to global climate change, and at the same time provides decision-making support for residential building managers and policy makers, helping them to develop more effective energy management and carbon emission reduction strategies.

[0112] In a preferred embodiment, based on the effective stock change model and the energy efficiency and carbon emission level of the equipment, the total energy consumption and carbon emission in any residential building area are predicted and calculated, and the calculation results include:

[0113] Determine the change trend of the effective residential area in any residential building area based on the effective stock change model, where the effective residential area refers to the residential area that remains normally used for living during the predicted time period;

[0114] Based on the equipment life, usage history data and maintenance record data of all terminal devices within the effective residential area of ​​the residential building area, the update needs of each terminal device within the effective residential area in the future period are predicted; wherein, the updated terminal devices must meet the minimum standards of the carbon emission management strategy formulated for the residential building area;

[0115] Based on the changing trend of the effective residential area, the energy efficiency of the terminal equipment within the effective residential area, the carbon emission level and the predicted results of the renewal demand, the total energy efficiency and carbon emission level of the effective residential area in the future time period are predicted and calculated to obtain the calculation results.

[0116] The working principle and beneficial effects of the above technical solution are as follows: first, the change trend of the effective residential area in the residential building area is determined by the effective stock change model, where the effective residential area refers to the residential area that remains normally used for living within the predicted time period. This step is crucial for accurately evaluating the actual use of residential buildings because it directly affects the basic data for calculating energy consumption and carbon emissions. Subsequently, based on the lifespan, usage history data and maintenance record data of all terminal devices in the effective residential area of ​​the residential building area, the update requirements of each terminal device in the effective residential area in the future time period are predicted to ensure that the updated terminal devices meet the minimum standards of the carbon emission management strategy formulated for the residential building area, thereby ensuring that the updated equipment is more energy-efficient and environmentally friendly. Finally, based on the change trend of the effective residential area, the energy efficiency of the internal terminal equipment, the carbon emission level and the prediction results of the update demand, the total energy efficiency and carbon emission level of the effective residential area in the future time period are predicted and calculated to obtain accurate calculation results. The working principle of this technical solution is to predict the energy consumption and carbon emissions of residential buildings through precise modeling and data analysis, combined with the changes in residential building stock and equipment update needs. Its beneficial effects include improving prediction accuracy, optimizing energy management, promoting energy conservation and emission reduction, supporting policy formulation, and enhancing environmental awareness. By accurately managing and reducing carbon emissions, the technical solution of the present invention provides an innovative solution for carbon emission management of residential buildings, which helps to achieve the goals of energy conservation and emission reduction and sustainable development.

[0117] In a preferred embodiment, according to the calculation results and the preset carbon emission management strategy, the carbon emission management of the residential building area includes:

[0118] According to the calculation results, it is determined whether the total energy efficiency and carbon emission level of the effective residential area of ​​any residential building area in the future time period exceeds the preset threshold level;

[0119] When a preset threshold level is exceeded, carbon emissions are managed for the residential building area, where the carbon emissions management strategy is determined by:

[0120] Determine the number and type of terminal devices that need to be updated based on the update requirements of each terminal device in the residential building area in the future period;

[0121] Based on the number and type of terminal equipment in this part, calculate the total energy efficiency and carbon emission level currently generated by this part of terminal equipment;

[0122] Set energy efficiency levels for each type of equipment in the part of terminal equipment so that the total energy efficiency and carbon emission levels generated by all updated terminal equipment are lower than the preset threshold level;

[0123] A carbon emission management strategy corresponding to the residential building area is generated according to the energy efficiency level set for each type of equipment.

[0124] The working principle and beneficial effects of the above technical solution are as follows: first, the calculation results are used to determine whether the total energy consumption and carbon emission levels of the effective residential area in the residential building area in the future time period exceed the preset threshold level. Once exceeded, the system will automatically execute the carbon emission management strategy, which determines the number and type of equipment that needs to be updated by analyzing the update requirements of each terminal device in the residential building area in the future time period, and calculates the total energy consumption and carbon emission levels generated by these devices. Then, an energy efficiency level is set for each type of equipment to ensure that the total energy consumption and carbon emission levels of all equipment after the update are lower than the preset threshold level. Finally, a carbon emission management strategy for the residential building area is generated according to the set energy efficiency level, so as to achieve effective management of carbon emissions in the residential building area. Carbon emission management strategies are formulated and implemented by dynamically monitoring and analyzing the energy consumption and carbon emission data in the residential building area, combining the energy efficiency and carbon emission data of the equipment and the update demand forecast. This method can not only monitor the energy consumption and carbon emissions of residential buildings in real time, but also adjust the management strategy according to the forecast results to ensure that carbon emissions are controlled below the preset threshold level. Its beneficial effects include improving energy efficiency, reducing carbon emissions, supporting carbon emission management policies of governments and relevant institutions, enhancing environmental awareness of residents and managers, and promoting technological innovation. By accurately managing and reducing carbon emissions, the technical solution of the present invention provides an innovative solution for carbon emission management of residential buildings, which helps to achieve the goals of energy conservation, emission reduction and sustainable development, and provides a solid foundation for the formulation and implementation of relevant policies.

[0125] In a preferred embodiment, the process of predicting and calculating the total energy consumption and carbon emissions in any residential building area also includes:

[0126] For the planned residential buildings, determine the residential type of the residential buildings and perform parametric modeling in R language;

[0127] Determine the energy consumption behavior type of residents in the residential building area through the pre-collected terminal device data, and use it as the condition input for the energy consumption simulation of the parameterized model;

[0128] Determine the value ranges of residential geometric characteristic parameters, envelope structure thermal parameters, internal heat source parameters, indoor air design parameters and equipment energy efficiency parameters based on relevant standards for residential type construction and equipment energy efficiency levels;

[0129] The Latin hypercube sampling method is used to generate energy consumption simulation model groups with different energy consumption behaviors under different residential types according to various parameters, and EnergyPlus software is used to simulate and calculate the cooling load of these models throughout the year;

[0130] A sensitivity analysis was conducted on the simulation results to obtain the key factors affecting the annual cooling load of various residential types;

[0131] SPSS software was used to establish a multiple linear regression model of key influencing factors for residential cooling load throughout the year;

[0132] The residential operation carbon emission prediction model is obtained by combining the energy efficiency ratio of various types of household equipment in the region and the carbon emission factor of electricity;

[0133] The residential operation carbon emission prediction model is used to predict the carbon emission behavior of the planned residential buildings after completion and occupancy, and the prediction results are obtained.

[0134] The working principle and beneficial effects of the above technical solution are as follows: First, a detailed residential type analysis is conducted on the planned residential buildings, and parametric modeling is performed in R language to ensure that the model can accurately reflect the characteristics of residential buildings. Then, the energy consumption behavior type of residents in the residential building area is determined by the pre-collected terminal equipment data, and these behavior data are used as conditional inputs for the energy consumption simulation of the parametric model to simulate the energy consumption pattern of residents. Then, according to the relevant standards for residential type construction and equipment energy efficiency level, the value ranges of residential geometric characteristic parameters, envelope structure thermal parameters, internal heat source parameters, indoor air design parameters and indoor air equipment energy efficiency parameters are determined to provide accurate input parameters for energy consumption simulation. The Latin hypercube sampling method is used to generate energy consumption simulation model groups with different energy consumption behaviors under different residential types for each parameter, and the EnergyPlus software is used to simulate and calculate the cooling load throughout the year for these models to evaluate the energy demand and potential carbon emissions of residential buildings. A sensitivity analysis was conducted on the simulation results to identify the key factors affecting the annual cooling load of various types of residential buildings. SPSS software was used to establish a multiple linear regression model of the key factors for the annual cooling load of residential buildings to quantify the specific impact of different factors on energy consumption. Finally, the residential operation carbon emission prediction model was obtained by combining the energy efficiency ratio of various types of household equipment in the region and the carbon emission factor of electricity. The model can predict the carbon emission behavior of residential buildings after completion and occupancy, providing a scientific basis for building design and energy management. The working principle of this method is to provide a comprehensive prediction of energy consumption and carbon emissions for residential buildings through precise parametric modeling, energy consumption simulation, sensitivity analysis and multiple linear regression analysis. Its beneficial effects include improving prediction accuracy, optimizing building design, supporting energy management, promoting energy conservation and emission reduction, and enhancing environmental awareness. It provides an innovative solution for the energy consumption and carbon emission management of residential buildings, helps to achieve the goals of energy conservation and emission reduction and sustainable development, and provides a solid foundation for the formulation and implementation of relevant policies.

[0135] Finally, it should be noted that the above preferred embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail through the above preferred embodiments, those skilled in the art should understand that various changes can be made in form and details without departing from the scope defined by the claims of the present invention.

Claims

1. A carbon emission management method based on residential area and equipment inventory turnover analysis, characterized in that: include: Collect data on the stock of existing residential buildings within the statistical scope, data on building renovation and reconstruction, and data on terminal equipment in buildings; Constructing the effective stock change model of residential buildings based on the dynamic material flow model; Determine the energy efficiency and carbon emission level of each type of equipment based on terminal equipment data analysis; Based on the effective stock change model and the energy efficiency and carbon emission levels of the equipment, the total energy consumption and carbon emissions in any residential building area are predicted and calculated to obtain the calculation results; Carbon emissions management is carried out for residential building areas based on the calculation results and preset carbon emissions management strategies.

2. A carbon emission management method based on residential area and equipment inventory turnover analysis according to claim 1, characterized in that: The data collected for the stock of existing residential buildings, renovation and reconstruction of buildings, and terminal equipment in buildings include: Collect information on the construction age, area, structural type and usage status of existing residential buildings; Collecting historical information on building renovation and reconstruction, wherein the historical information on renovation and reconstruction includes renovation time, renovation content and renovation status information; Collect detailed information on terminal equipment in the building, including equipment type, energy efficiency rating, age, and maintenance records; Based on the collected information, determine the existing residential building stock data, building renovation data, and terminal equipment data within the statistical scope.

3. The carbon emission management method based on residential area and equipment inventory turnover analysis according to claim 1 is characterized in that: The effective stock change model of residential buildings based on the dynamic material flow model includes: Based on the principle of dynamic material flow, a building stock change model considering new construction, demolition and renewal factors is established: S t =S t―1 +B t ―(D t ―U t ) Among them, S t represents the building stock area at time t, B t represents the newly built area counted at time t, D t represents the demolition area counted at time t, U t represents the renewal area at time t, and θ represents the renewal rate of residential renovation.

4. The carbon emission management method based on residential area and equipment inventory turnover analysis according to claim 1 is characterized in that: The energy efficiency and carbon emission levels of each type of equipment are determined based on the terminal equipment data analysis, including: Determine the equipment type, equipment model, energy efficiency rating, energy consumption data, equipment life, usage history data, and maintenance record data based on the terminal equipment data; Classify devices according to device type and model, and calculate the energy consumption per unit time of each type of device through energy efficiency rating, energy consumption data and usage history data; The carbon emission rate of the equipment is calculated by the equipment's energy consumption per unit time and the carbon emission factor, where the carbon emission factor refers to the carbon emission corresponding to each unit of energy consumption; The collected data and calculation results are comprehensively analyzed to determine the energy efficiency and carbon emission levels of each type of equipment.

5. A carbon emission management method based on residential area and equipment inventory turnover analysis according to claim 4, characterized in that: Based on the effective stock change model and the energy efficiency and carbon emission levels of the equipment, the total energy consumption and carbon emissions in any residential building area are predicted and calculated, and the calculation results include: Determine the change trend of the effective residential area in any residential building area based on the effective stock change model, where the effective residential area refers to the residential area that remains normally used for living during the predicted time period; Based on the equipment life, usage history data and maintenance record data of all terminal devices within the effective residential area of ​​the residential building area, the update needs of each terminal device within the effective residential area in the future period are predicted; wherein, the updated terminal devices must meet the minimum standards of the carbon emission management strategy formulated for the residential building area; Based on the changing trend of the effective residential area, the energy efficiency of the terminal equipment within the effective residential area, the carbon emission level and the predicted results of the renewal demand, the total energy efficiency and carbon emission level of the effective residential area in the future time period are predicted and calculated to obtain the calculation results.

6. A carbon emission management method based on residential area and equipment inventory turnover analysis according to claim 5, characterized in that: Based on the calculation results and the preset carbon emission management strategy, carbon emission management for residential building areas includes: According to the calculation results, it is determined whether the total energy efficiency and carbon emission level of the effective residential area of ​​any residential building area in the future time period exceeds the preset threshold level; When a preset threshold level is exceeded, carbon emissions are managed for the residential building area, where the carbon emissions management strategy is determined by: Determine the number and type of terminal devices that need to be updated based on the update requirements of each terminal device in the residential building area in the future period; Based on the number and type of terminal equipment in this part, calculate the total energy efficiency and carbon emission level currently generated by this part of terminal equipment; Set energy efficiency levels for each type of equipment in the part of terminal equipment so that the total energy efficiency and carbon emission levels generated by all updated terminal equipment are lower than the preset threshold levels; A carbon emission management strategy corresponding to the residential building area is generated according to the energy efficiency level set for each type of equipment.

7. A carbon emission management method based on residential area and equipment inventory turnover analysis according to claim 6, characterized in that: Carbon emissions management strategies also include: According to the total energy efficiency and carbon emission level of the effective residential area in the residential building area in the future period, restrict the new construction management of residential building stock; According to the total energy efficiency and carbon emission levels of the effective residential area of ​​the residential building area in the future period, the installation of terminal equipment in residential buildings will be restricted or it will be recommended to upgrade and update the inefficient terminal equipment.

8. The carbon emission management method based on residential area and equipment inventory turnover analysis according to claim 1 is characterized in that: The process of predicting total energy consumption and carbon emissions for any residential building area also includes: For the planned residential buildings, determine the residential type of the residential buildings and perform parametric modeling in R language; Determine the energy consumption behavior type of residents in the residential building area through the pre-collected terminal device data, and use it as the condition input for the energy consumption simulation of the parameterized model; Determine the value ranges of residential geometric characteristic parameters, envelope structure thermal parameters, internal heat source parameters, indoor air design parameters and equipment energy efficiency parameters based on relevant standards for residential type construction and equipment energy efficiency levels; The Latin hypercube sampling method is used to generate energy consumption simulation model groups with different energy consumption behaviors under different residential types according to various parameters, and EnergyPlus software is used to simulate and calculate the cooling load of these models throughout the year; A sensitivity analysis was conducted on the simulation results to obtain the key factors affecting the annual cooling load of various residential types; SPSS software was used to establish a multiple linear regression model of key influencing factors for residential cooling load throughout the year; The residential operation carbon emission prediction model is obtained by combining the energy efficiency ratio of various types of household equipment in the region and the carbon emission factor of electricity; The residential operation carbon emission prediction model is used to predict the carbon emission behavior of the planned residential buildings after completion and occupancy, and the prediction results are obtained.

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