Evaluation and design method for existing residence reconstruction project based on carbon emission

Abstract

The invention relates to the technical field of building energy conservation, in particular to an existing residence reconstruction project evaluation and design method based on carbon emission. The technical problems that in a residence low-carbon transformation design method in the prior art, project selection is blind, carbon emission calculation is one-sided, and collaborative optimization of economical efficiency and carbon reduction efficiency is insufficient exist. According to the technical scheme, the existing residence reconstruction project evaluation and design method based on carbon emission comprises the steps of calculation and analysis of a carbon reduction sensitivity coefficient beta of each project and multi-factor orthogonal test optimization; according to the method, by calculating the carbon reduction sensitivity coefficient beta of each project, the influence degree of a transformation project on carbon emission is quantified, and blind project selection is avoided; comprehensive evaluation of the carbon reduction effect is ensured through full-life-cycle carbon emission modeling; a scheme of lowest annual average carbon emission and optimal cost effectiveness is screened through combination of multi-factor orthogonal test optimization and a Pareto optimal solution, and cooperation of economical efficiency and carbon reduction efficiency is realized.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of building energy saving, and particularly relates to a method for evaluating and designing existing residential reconstruction projects based on carbon emissions. BACKGROUND

[0002] In the prior art in the field of building energy saving, residential low-carbon reconstruction design methods mainly rely on two types of modes: one is the "top-down" guidance based on macro policy or industry experience; the other is the "bottom-up" calculation for specific buildings, that is, first select reconstruction projects (such as external wall insulation, equipment updating, etc.), and then calculate the carbon emissions item by item; however, the above methods have significant defects:

[0003] First, the existing technology is not specific enough for specific buildings; macro guidance type methods (such as only stipulating "improve the thermal performance of the envelope") do not combine with building individual characteristics (such as climate zoning, existing structure state), resulting in "one size fits all" reconstruction schemes that are difficult to adapt to the actual needs of different residences; while the "bottom-up" calculation mode is specific to specific buildings, the project selection relies on manual experience or simple rules (such as only reconstructing the system with the highest energy consumption), lacking a systematic screening mechanism, which is easy to miss key carbon reduction projects or include inefficient projects;

[0004] Second, the carbon emission calculation of the prior art has limitations; on the one hand, some methods only focus on operating phase energy consumption (such as heating, air conditioning), ignoring whole life cycle carbon emissions of building materials production, construction, maintenance, etc., resulting in one-sided evaluation of carbon reduction effect; on the other hand, even if whole life cycle calculation is used, there is no "sensitivity analysis" mechanism for reconstruction projects, which cannot quantify the influence degree of different projects on overall carbon emissions (such as some projects reduce carbon emissions by 20% after reconstruction, while others only reduce by 2%), making it difficult to prioritize high-sensitivity projects;

[0005] Third, the prior art lacks coordination and optimization of economic efficiency and carbon reduction efficiency; most methods only take "lowest carbon emissions" as a single target, without combining cost data (such as material cost, construction cost) for multi-objective optimization, resulting in some schemes that have significant carbon reduction effect but high cost (such as using high-end equipment leading to a payback period of more than 10 years), or low cost but limited carbon reduction efficiency (such as replacing inefficient equipment), which cannot achieve "economic-carbon reduction" balance.

[0006] To solve the above problems, the present application provides a kind of existing residential reconstruction project evaluation and design method based on carbon emission, which quantifies the influence degree of reconstruction project on carbon emission by calculating the carbon reduction sensitivity coefficient β of each project, avoids blind selection of project;By full life cycle carbon emission modeling, ensure the comprehensive evaluation of carbon reduction effect;Through multi-factor orthogonal test optimization combined with pareto optimal solution, the scheme with "lowest annual carbon emission and optimal cost benefit" is screened, the synergy of economy and carbon reduction efficiency is realized;It is suitable for the low-carbon reconstruction scene of existing residential, especially suitable for the project with limited reconstruction budget and precise investment, which can effectively solve the problems of "blind project selection, one-sided calculation and insufficient optimization" in prior art, and provide data-driven precise decision support for residential low-carbon reconstruction. SUMMARY

[0007] In order to overcome the problems of blind project selection, one-sided carbon emission calculation and insufficient synergy optimization of economy and carbon reduction efficiency in the existing residential low-carbon reconstruction design method.

[0008] The technical scheme of the present application is: a kind of existing residential reconstruction project evaluation and design method based on carbon emission, which is executed by computer equipment, including the following steps:

[0009] S1: obtain the list of reconstructable projects of the residential to be reconstructed, and collect the building data before the reconstruction of each project;

[0010] S2: at least one standard reconstruction scheme is proposed for each reconstructable project, and a carbon emission model of each scheme is established;

[0011] S3: calculate the life cycle carbon emission before and after the reconstruction of each project by building energy consumption simulation software, and generate a carbon emission table;

[0012] S4: calculate the carbon reduction sensitivity coefficient β of each project:

[0013] β=(Q1-Q2) / Q1×100%;

[0014] Wherein, Q1 is the life cycle carbon emission before reconstruction (kgCO2e / m 2 ), Q2 is the life cycle carbon emission after reconstruction (kgCO2e / m 2 );

[0015] S5: select the project with sensitivity coefficient | β | ≥5% as high significant reconstruction candidate set;

[0016] S6: multiple refined reconstruction schemes are proposed for high significant projects, and the carbon reduction effect is verified;

[0017] S7: take high significant projects as factors, and the refined reconstruction schemes of each project as levels, to construct an orthogonal test matrix;

[0018] S8: Calculate the annual carbon emissions of each scheme combination:

[0019] Annual carbon emissions = (production process carbon emissions + operating stage carbon emissions) / service life;

[0020] S9: Compare the economic efficiency and carbon reduction efficiency of each scheme combination combined with cost data;

[0021] S10: Select the scheme with the lowest annual carbon emissions and the most cost-effective as the final retrofit scheme.

[0022] In step S1, the list of retrofitable items of the house to be transformed is obtained, and the architectural data before the transformation of each item is collected, including the following steps:

[0023] S101: Obtain the basic information of the building recorded through field investigation, including climate division, building layers, structure type, construction year, service life;

[0024] S102: Extract the building envelope parameters through the building information model (BIM), including the wall material and thickness, the window type and heat transfer coefficient, the roof structure and heat transfer coefficient, and the ground insulation method;

[0025] S103: Obtain the operating stage energy consumption data through field monitoring equipment, including the annual energy consumption values of the heating system, air conditioning system, and lighting system;

[0026] S104: Obtain at least four of the following items: external wall thermal performance, external window thermal performance, roof thermal performance, heating equipment energy efficiency ratio, and service life;

[0027] S105: Obtain the building life cycle data, including the carbon emission factor of the building material production stage and the main building material consumption of the construction stage.

[0028] In steps S2-S3, at least one standard retrofit scheme is proposed for each retrofitable item, a carbon emission model is established for each scheme, the life cycle carbon emissions before and after the transformation of each item are calculated through building energy consumption simulation software, and a carbon emission table is generated, including the following steps:

[0029] S201: Determine the type of standard retrofit scheme for the retrofitable item, design a standardized retrofit scheme for each retrofitable item that meets industry standards and carbon reduction goals;

[0030] S202: Collect the basic data of the standard retrofit scheme to provide quantitative input for the carbon emission model and ensure the accuracy of the calculation results;

[0031] S203: Build a full life cycle carbon emission model to quantify the carbon emissions of the standard retrofit scheme in the full life cycle and provide a basis for subsequent sensitivity analysis;

[0032] S204: Verify the accuracy of the carbon emission model to ensure that the model calculation results are consistent with the actual or simulated data, and improve the credibility of the scheme;

[0033] S205: Output the carbon emission table of the standard modification scheme, and provide quantitative basis for subsequent sensitivity analysis and scheme optimization.

[0034] In step S4, the carbon reduction sensitivity coefficient β of each item is calculated, which includes the following steps:

[0035] S401: Extract the carbon emission data before and after the modification, that is, obtain Q1 (carbon emission before modification) and Q2 (carbon emission after modification) in the carbon emission table generated in step S3, to provide basic data for sensitivity coefficient calculation, which includes:

[0036] Extract the Q1 value of the target item from the carbon emission table;

[0037] Extract the Q2 value of the same item under the standard modification scheme;

[0038] S402: Substitute the formula to calculate β value, evaluate the sensitivity of the project to carbon reduction by quantifying the change of carbon emission before and after the modification, which is:

[0039] Substitute Q1 and Q2 into the formula: β = (Q1-Q2) / Q1×100%;

[0040] S403: Determine the sign and size of β value to clarify the influence direction (promote / hinder) and sensitivity level of the modified project on carbon emission, which includes:

[0041] Sign determination:

[0042] β>0: indicates that carbon emission decreases after modification, and the project promotes carbon reduction;

[0043] β<0: indicates that carbon emission increases after modification, and the project hinders carbon reduction;

[0044] Absolute value size determination:

[0045] |β|≥5%: the project is a high significant influencing factor;

[0046] |β|<5%: the project is a low significant influencing factor;

[0047] S404: Record and summarize the β value to provide structured data support for step S5 screening.

[0048] In step S5, the items with sensitivity coefficient |β|≥5% are selected as the high significant modification candidate set, which includes the following steps:

[0049] S501: Obtain the calculated β values of each item in step S4 to provide basic data for screening;

[0050] S502: Set the screening threshold and conditions to determine the criteria for high-significance items and ensure that the screening results meet the actual engineering needs;

[0051] S503: Screen high-significance items in multiple dimensions, considering carbon reduction effect, engineering feasibility, and economy, to select practical candidate items;

[0052] S504: Record and summarize the screening results to generate a structured list of high-significance items for subsequent steps.

[0053] In step S6, multiple refined modification schemes are proposed for high-significance items to verify their carbon reduction effect, including the following steps:

[0054] S601: Determine the type of refined scheme for high-significance items;

[0055] S602: Collect basic data for refined schemes to provide quantitative input for the carbon emission model and ensure accurate calculation results;

[0056] S603: Build a carbon emission model for the refined scheme;

[0057] S604: Verify the carbon reduction effect of the refined scheme by comparing the carbon emission data of the refined scheme with the original scheme (or standard scheme) to confirm whether the carbon reduction effect meets the expectations, specifically:

[0058] Input refined scheme parameters through DesignBuilder to simulate energy consumption during the operation phase and verify the consistency of the carbon emission calculated by the model with the software output results;

[0059] S605: Generate a structured data table for the refined scheme to provide input for the orthogonal test in step S7.

[0060] In step S7, high-significance items are used as factors, and the refined modification schemes for each item are used as levels to build an orthogonal test matrix, including the following steps:

[0061] S701: Determine the factors and levels of the orthogonal test to clarify the test variables and their value ranges, providing a basis for building an orthogonal table, including:

[0062] Select at least 3 high-significance items from step S5 as test factors;

[0063] Level setting: For each factor, select at least 3 refined modification schemes as level values;

[0064] S702: Select an orthogonal table and construct a test matrix, reduce the number of tests through orthogonal design, efficiently cover multi-factor multi-level combinations, specifically including:

[0065] Orthogonal table selection: according to the number of factors m and the number of levels n, select L k (n m ) orthogonal table (K groups of tests, each group of m factors and n levels);

[0066] Matrix construction: map factors and levels to the orthogonal table to generate test combinations;

[0067] S703: Simulate and verify the carbon emissions of each test combination, quantify the carbon emissions of each scheme combination through building energy simulation software, and provide data for subsequent annual carbon emissions calculation, specifically including:

[0068] Parameter input: input each factor level parameter in the orthogonal table into the DesignBuilder software;

[0069] Simulation run: simulate building operation energy consumption and calculate the operation phase carbon emissions of each combination;

[0070] Data integration: combine the carbon emissions data in the production, construction, and maintenance stages in step S6 to generate a full life cycle carbon emissions table for each test combination;

[0071] S704: Calculate the annual average carbon emissions: convert the full life cycle carbon emissions into an annual average value for ease of economic comparison, specifically:

[0072] According to the formula "annual average carbon emissions = (production carbon emissions + operation carbon emissions x service life) / service life", calculate the annual average value of each test combination;

[0073] S705: Output the orthogonal test results to generate a structured test data table to provide input for subsequent scheme optimization, specifically:

[0074] Create an orthogonal test result table containing test number, factor level combination, total carbon emissions, annual average carbon emissions, and cost data.

[0075] In steps S9-S10, compare the economic efficiency and carbon reduction efficiency of each scheme combination based on cost data, and select the scheme with the lowest annual carbon emissions and the most optimal cost benefit as the final modification scheme, specifically including the following steps:

[0076] S901: Obtain the quantitative cost of each scheme combination in the orthogonal test to provide a basis for economic and carbon reduction efficiency comparison;

[0077] S902: Build an economic and carbon reduction efficiency comparison model to quantify the cost benefit and carbon reduction effect of each scheme combination to provide a basis for multi-objective optimization, specifically including:

[0078] Index definition:

[0079] Annual average carbon emissions: calculated from step S8;

[0080] Unit area cost: total cost / building area;

[0081] Model construction:

[0082] Draw a scatter plot with "annual average carbon emissions" as the vertical axis and "unit area cost" as the horizontal axis, and mark the coordinate points of each test combination;

[0083] S903: Under the dual targets of carbon emissions and cost, filter out the scheme combination without substitution advantage to determine the Pareto optimal solution set, specifically including:

[0084] Compare all schemes, if the annual average carbon emissions of scheme A ≤ scheme B, and the unit area cost ≤ scheme B, then A dominates B, B is eliminated;

[0085] The remaining undominated schemes constitute the Pareto frontier;

[0086] S904: Select the scheme with the lowest annual average carbon emissions and the most cost-effective from the Pareto frontier, specifically including:

[0087] Sensitivity analysis:

[0088] If the user prefers to reduce carbon, select the scheme with the lowest carbon emissions;

[0089] If the user prefers cost, select the scheme with the lowest unit cost;

[0090] Comprehensive balance:

[0091] Calculate the "carbon reduction cost efficiency" (kgCO2e / yuan) of each scheme = annual average carbon emissions reduction amount / (unit cost-base cost);

[0092] Select the scheme with the highest efficiency;

[0093] S905: Summarize the technical parameters, carbon emission data and cost data of the final scheme to provide a basis for construction.

[0094] As preferred, in step S1:

[0095] Building data includes: climate zone, building structure, building envelope heat transfer coefficient and equipment energy efficiency ratio;

[0096] The collection method includes building information model (BIM) data extraction and field monitoring.

[0097] As preferred, in step S3, the life cycle carbon emissions are calculated using:

[0098] Carbon emissions = Activity data x Emission factor;

[0099] Wherein, the activity data includes the amount of building materials and the energy consumption value of equipment, and the emission factor is referenced from the building carbon emission standard database.

[0100] As preferred, in step S4, the determination criteria of the sensitivity coefficient is specifically:

[0101] β>0 indicates that the reconstruction promotes carbon reduction, and β<0 indicates that it hinders carbon reduction;

[0102] The greater the value of |β| is, the higher the sensitivity is.

[0103] As preferred, the screening criteria in step S5 specifically includes:

[0104] The sensitivity coefficient |β|≥5%;

[0105] The project reconstruction engineering difficulty level ≤ the preset threshold value;

[0106] The project economic cost recovery period ≤10 years.

[0107] As preferred, in step S6, the reconstruction scheme verification specifically includes adjusting the material thickness, replacing the equipment type, and optimizing the construction method, and recalculating the carbon emissions.

[0108] As preferred, the orthogonal test design in step S7 satisfies:

[0109] The factors include at least 3 of the thermal performance of external walls, the thermal performance of external windows, the thermal performance of roof, and the energy efficiency ratio of heating equipment;

[0110] Each factor is set to at least 3 levels, and the level value is the heat transfer coefficient or energy efficiency ratio of different materials or structures;

[0111] The number of factors m≥3, the number of levels n≥3, and the orthogonal table satisfies L k (n m ) structure (m≥k);

[0112] Wherein, L represents the orthogonal table, and k represents the number of experiments.

[0113] As preferred, in the calculation of the annual average carbon emissions in step S8, the production process carbon emissions cover the building material production and transportation carbon emissions, and the operation stage carbon emissions cover the carbon emissions of heating, air conditioning, and lighting energy consumption.

[0114] As preferred, the building energy consumption simulation software in step S3 is DesignBuilder, and the carbon reduction effect verification in step S6 is realized through the DesignBuilder software simulation.

[0115] As preferred, the selection of the optimal scheme in step S10 adopts a Pareto optimal solution, and the frontier solution set is selected in the carbon emission-cost two-dimensional space.

[0116] Advantages of the present application:

[0117] 1、The present application calculates the life cycle carbon emissions of each project before and after the reconstruction through building energy consumption simulation software, generates a carbon emission table, calculates the carbon reduction sensitivity coefficient β of each project, and selects the projects with a sensitivity coefficient |β|≥5% as a high-significance reconstruction candidate set, thereby quantifying the carbon reduction efficiency of each reconstruction project through the sensitivity coefficient β, and solving the problem of "blindness in reconstruction project selection" in the prior art.

[0118] 2、The present application proposes multiple refined reconstruction schemes for high-significance projects, verifies the carbon reduction effect, takes the high-significance projects as factors, and takes the refined reconstruction schemes of each project as levels to construct an orthogonal test matrix, calculates the annual average carbon emissions of each scheme combination, compares the economic efficiency and carbon reduction efficiency of each scheme combination in combination with the cost data, and selects the scheme with the lowest annual average carbon emissions and the optimal cost benefit as the final reconstruction scheme. BRIEF DESCRIPTION OF DRAWINGS

[0119] Figure 1 The present application provides a carbon emission-based existing residential reconstruction project evaluation and design method step flowchart.

[0120] Figure 2 The present application provides a carbon emission-based existing residential reconstruction project evaluation and design method sensitivity coefficient calculation and analysis step flowchart. DETAILED DESCRIPTION

[0121] The present application will be further described below in combination with the drawings and examples.

[0122] Please refer to Figure 1 and Figure 2 The present application provides an embodiment: a carbon emission-based existing residential reconstruction project evaluation and design method executed by a computer device, comprising the following steps:

[0123] S1: obtaining a list of reconstructable projects of a to-be-reconstructed residence, and collecting building data before reconstruction of each project;

[0124] S2: proposing at least one standard reconstruction scheme for each reconstructable project, and establishing a carbon emission model of each scheme;

[0125] S3: Calculate the life cycle carbon emissions of each project before and after the renovation through building energy consumption simulation software, and generate a carbon emission table;

[0126] S4: Calculate the carbon reduction sensitivity coefficient β of each project:

[0127] β = (Q1-Q2) / Q1x100%;

[0128] Wherein, Q1 is the life cycle carbon emissions before renovation (kgCO2e / m 2 ), Q2 is the life cycle carbon emissions after renovation (kgCO2e / m 2 );

[0129] S5: Select projects with sensitivity coefficient |β|≥5% as high significance renovation candidates;

[0130] S6: Propose multiple refined renovation schemes for high significance projects and verify their carbon reduction effect;

[0131] S7: Construct an orthogonal test matrix with high significance projects as factors and refined renovation schemes of each project as levels;

[0132] S8: Calculate the annual average carbon emissions of each scheme combination:

[0133] Annual average carbon emissions = (production process carbon emissions + operating stage carbon emissions) / service life;

[0134] S9: Compare the economic efficiency and carbon reduction efficiency of each scheme combination combined with cost data;

[0135] S10: Select the scheme with the lowest annual average carbon emissions and the most optimal cost benefit as the final renovation scheme.

[0136] In step S1, obtain the list of renovable projects of the residential building to be renovated, and collect the building data before renovation of each project, including the following steps:

[0137] S101: Obtain the basic information of the building recorded through site investigation, including climate zone, building layers, structure type, construction year, service life;

[0138] S102: Extract the envelope structure parameters through building information modeling (BIM), including external wall material and thickness, external window type and heat transfer coefficient, roof structure and heat transfer coefficient, ground insulation method;

[0139] S103: Obtain the operating stage energy consumption data through field monitoring equipment, including the annual energy consumption values of heating system, air conditioning system, and lighting system;

[0140] S104: Obtain the reformed project, including at least four of the thermal performance of the outer wall, the thermal performance of the outer window, the thermal performance of the roof, the energy efficiency ratio of the heating equipment and the service life;

[0141] S105: Obtain the building life cycle data, including the carbon emission factor of the building material production stage and the main building material consumption of the construction stage.

[0142] In steps S2-S3, at least one standard reform scheme is proposed for each reformable project, a carbon emission model of each scheme is established, the life cycle carbon emissions before and after the reform of each project are calculated through building energy consumption simulation software, and a carbon emission table is generated, including the following steps:

[0143] S201: Determine the standard reform scheme type of the reformable project, design a standardized reform scheme that meets the industry specifications and carbon reduction goals for each reformable project, including:

[0144] For the thermal performance of the outer wall: propose to increase the standard thickness range of the insulation material, or replace the high-performance wall material;

[0145] For the thermal performance of the outer window: design different glass combinations and standard configurations of window frame materials;

[0146] For the energy efficiency ratio of the heating equipment: select standard equipment models that meet the "Energy-saving Product Government Procurement List";

[0147] For the service life adjustment: according to the "Unified Standard for Reliability Design of Building Structures", set the standard value of extending the service life;

[0148] S202: Collect the basic data of the standard reform scheme to provide quantitative input for the carbon emission model and ensure the accuracy of the calculation results, including:

[0149] Material data: obtain the unit weight carbon emission factor of the insulation material and the carbon footprint data of the glass through the material test report provided by the manufacturer or the "Building Carbon Emission Calculation Standard";

[0150] Equipment data: refer to the "Public Building Energy-saving Design Standard" to obtain the rated energy consumption and energy efficiency ratio of the heating equipment;

[0151] Construction data: according to the "Construction Engineering Quantity List Valuation Specification", estimate the construction energy consumption and material loss rate of insulation material installation and outer window replacement;

[0152] S203: Construct a full life cycle carbon emission model to quantify the carbon emissions of the standard reform scheme in the full life cycle and provide a basis for subsequent sensitivity analysis, including:

[0153] Production stage carbon emissions:

[0154] Carbon emission of material production: material quantity x carbon emission factor of production;

[0155] Carbon emission of equipment production: equipment quantity x carbon emission factor of equipment unit;

[0156] Carbon emission of construction phase:

[0157] Carbon emission of construction energy consumption: construction energy consumption x carbon emission factor of power grid;

[0158] Carbon emission of material transportation: transportation distance x material weight x carbon emission factor of transportation;

[0159] Carbon emission of operation phase:

[0160] Simulate building operation energy consumption by DesignBuilder, and calculate annual energy consumption value;

[0161] Carbon emission of operation: annual energy consumption x carbon emission factor of operation;

[0162] Carbon emission of maintenance phase:

[0163] Estimate material replacement frequency, and calculate carbon emission in maintenance period;

[0164] S204: Verify the accuracy of the carbon emission model, ensure that the model calculation results are consistent with the actual or simulated data, and improve the credibility of the scheme, specifically including:

[0165] Input standard renovation scheme parameters by DesignBuilder, simulate operation phase energy consumption, and verify the consistency of the heating carbon emission calculated by the model with the software output results;

[0166] S205: Output the carbon emission amount table of the standard renovation scheme, and provide quantitative basis for subsequent sensitivity analysis and scheme optimization, specifically including:

[0167] Summarize the carbon emission data of each standard renovation scheme in the whole life cycle;

[0168] Generate a carbon emission amount table, including project name, scheme description, production carbon emission, construction carbon emission, operation carbon emission, maintenance carbon emission, and total carbon emission.

[0169] In step S4, the carbon reduction sensitivity coefficient β of each project is calculated, specifically including the following steps:

[0170] S401: Extract the carbon emission data before and after the renovation, that is, obtain Q1 (carbon emission before renovation) and Q2 (carbon emission after renovation) in the carbon emission amount table generated in step S3, and provide basic data for sensitivity coefficient calculation, specifically including:

[0171] Extract the Q1 value of the target project from the carbon emission amount table;

[0172] Extract the Q2 value of the same project under the standard retrofit scheme;

[0173] S402: Substitute the formula to calculate the β value, evaluate the sensitivity of the project to carbon reduction by quantifying the change of carbon emissions before and after the transformation, specifically:

[0174] Substitute Q1 and Q2 into the formula: β = (Q1-Q2) / Q1 x 100%;

[0175] S403: Determine the sign and size of the β value, clarify the influence direction (promote / hinder) and sensitivity level of the transformation project on carbon emissions, specifically including:

[0176] Sign determination:

[0177] β>0: indicates that carbon emissions decrease after transformation, and the project promotes carbon reduction;

[0178] β<0: indicates that carbon emissions increase after transformation, and the project hinders carbon reduction;

[0179] Absolute value size determination:

[0180] |β|≥5%: the project is a high significant influencing factor;

[0181] |β|<5%: the project is a low significant influencing factor;

[0182] S404: Record and summarize the β value, provide structured data support for step S5 screening, specifically including:

[0183] Record the β value, sign determination result and significance level (high / low) of each project to the sensitivity analysis table.

[0184] In step S5, select projects with sensitivity coefficient |β|≥5% as high significant transformation candidates, including the following steps:

[0185] S501: Obtain the β value of each project calculated in step S4 to provide basic data for screening, specifically including:

[0186] Extract the β value, sign determination result and significance level of all projects from the sensitivity analysis table generated in step S404;

[0187] S502: Set the screening threshold and conditions, clarify the determination criteria of high significant projects, and ensure that the screening results meet the actual engineering needs, specifically including:

[0188] Main threshold: set the β value threshold to 5%, that is, |β|≥5% projects are included in the candidate set;

[0189] Auxiliary conditions:

[0190] Engineering difficulty level: According to the "Building Engineering Construction Difficulty Evaluation Standard", the project transformation engineering difficulty level is ≤Ⅲ level;

[0191] Economic cost recovery period: The economic cost recovery period of the project is ≤10 years;

[0192] S503: Multi-dimensional screening of high significance projects, comprehensive consideration of carbon reduction effect, engineering feasibility and economy, screening of practical and operable candidate projects, including:

[0193] Preliminary screening: Exclude projects with |β| value <5%;

[0194] Engineering difficulty filtering: Exclude projects with engineering difficulty level >Ⅲ level;

[0195] Cost recovery period filtering: Exclude projects with cost recovery period >10 years;

[0196] S504: Record and summarize the screening results to generate a structured high significance project list to provide input for subsequent steps, including:

[0197] Create a high significance transformation candidate set table containing project name, β value, engineering difficulty level, cost recovery period and screening conclusion;

[0198] In step S6, multiple refined transformation schemes are proposed for high significance projects to verify their carbon reduction effect, including the following steps:

[0199] S601: Determine the type of refined scheme for high significance projects, specifically:

[0200] For high significance projects screened in step S5, design specific implementable transformation schemes to provide a basis for subsequent carbon reduction effect verification;

[0201] S602: Collect basic data for refined schemes to provide quantitative input for carbon emission models to ensure accurate calculation results;

[0202] S603: Build a carbon emission model for the refined scheme, specifically:

[0203] Quantify the carbon emissions of the refined transformation scheme throughout its life cycle (production, construction, operation, maintenance) to provide a basis for carbon reduction effect verification;

[0204] S604: Verify the carbon reduction effect of the refined scheme by comparing the carbon emission data of the refined scheme with the original scheme (or standard scheme) to confirm whether the carbon reduction effect meets expectations, specifically:

[0205] Input refined scheme parameters into DesignBuilder to simulate energy consumption during the operation phase and verify the consistency of the carbon emissions calculated by the model with the software output results;

[0206] S605: Generate structured retrofit scheme data table to provide input for orthogonal test in step S7, specifically:

[0207] Create retrofit scheme data table, including project name, scheme description, production carbon emissions, construction carbon emissions, operation carbon emissions, maintenance carbon emissions, and total carbon emissions.

[0208] In step S7, use high-significance projects as factors and the retrofit schemes of each project as levels to construct an orthogonal test matrix, specifically including the following steps:

[0209] S701: Determine the factors and levels of the orthogonal test. Clearly define the test variables and their value ranges to provide a basis for constructing the orthogonal table, specifically including:

[0210] Select at least 3 high-significance projects from step S5 as test factors;

[0211] Level setting: For each factor, select at least 3 retrofit schemes as level values;

[0212] S702: Select an orthogonal table and construct a test matrix to reduce the number of tests, efficiently covering multiple factor and level combinations, specifically including:

[0213] Orthogonal table selection: According to the number of factors m and the number of levels n, select an L k (n m ) orthogonal table (K test groups, each group with m factors and n levels);

[0214] Matrix construction: Map factors and levels to the orthogonal table to generate test combinations;

[0215] S703: Simulate and verify the carbon emissions of each test combination using building energy simulation software to quantify the carbon emissions of each scheme combination and provide data for subsequent annual carbon emissions calculations, specifically including:

[0216] Parameter input: Input each factor level parameter in the orthogonal table into the DesignBuilder software;

[0217] Simulation run: Simulate building operation energy consumption and calculate the operation phase carbon emissions of each combination;

[0218] Data integration: Combine the production, construction, and maintenance phase carbon emissions data from step S6 to generate a full life cycle carbon emissions table for each test combination;

[0219] S704: Calculate annual carbon emissions: Convert full life cycle carbon emissions to annual values for ease of economic comparison, specifically:

[0220] The annual average carbon emission of each test combination is calculated according to the formula "annual average carbon emission = (production carbon emission + operation carbon emission x service life) / service life";

[0221] S705: output the orthogonal test results to generate a structured test data table, and provide input for subsequent scheme optimization, specifically:

[0222] An orthogonal test result table is created, including test number, factor level combination, total carbon emission, annual average carbon emission, and cost data.

[0223] In steps S9-S10, the economic efficiency and carbon reduction efficiency of each scheme combination are compared in combination with cost data, and the scheme with the lowest annual average carbon emission and the most optimal cost benefit is selected as the final modification scheme, which specifically includes the following steps:

[0224] S901: obtain the quantitative cost of each scheme combination in the orthogonal test to provide a basis for economic efficiency and carbon reduction efficiency comparison, specifically including:

[0225] Cost type division:

[0226] Direct cost: material cost, equipment cost, construction cost;

[0227] Indirect cost: transportation cost, maintenance cost, demolition cost;

[0228] Data sources:

[0229] Market research: obtain quotes from building material suppliers and construction units;

[0230] Historical project data: refer to the actual cost of similar modification projects;

[0231] Cost database: refer to the quota standard in "Construction Engineering Quantity List Valuation Specification";

[0232] S902: build an economic efficiency and carbon reduction efficiency comparison model to quantify the cost benefit and carbon reduction effect of each scheme combination, and provide a basis for multi-objective optimization, specifically including:

[0233] Index definition:

[0234] Annual average carbon emission: calculated in step S8;

[0235] Unit area cost: total cost / building area;

[0236] Model construction:

[0237] Take "annual average carbon emission" as the vertical axis and "unit area cost" as the horizontal axis, draw a scatter plot, and mark the coordinate points of each test combination;

[0238] S903: Under the dual targets of carbon emissions and cost, screen out non-substitution advantage scheme combination to determine the Pareto optimal solution set, specifically including:

[0239] Compare all schemes, if the annual average carbon emissions of scheme A ≤ scheme B, and the unit area cost ≤ scheme B, then A dominates B, B is eliminated;

[0240] The remaining undominated schemes constitute the Pareto frontier;

[0241] S904: Select the scheme with the lowest annual average carbon emissions and the most cost-effective from the Pareto frontier, specifically including:

[0242] Sensitivity analysis:

[0243] If the user prefers to reduce carbon, select the scheme with the lowest carbon emissions;

[0244] If the user prefers cost, select the scheme with the lowest unit cost;

[0245] Comprehensive balance:

[0246] Calculate the "carbon reduction cost efficiency" (kgCO2e / yuan) of each scheme = annual average carbon emission reduction amount / (unit cost - baseline cost);

[0247] Select the scheme with the highest efficiency;

[0248] S905: Summarize the technical parameters, carbon emission data and cost data of the final scheme to provide basis for construction.

[0249] In step S1:

[0250] Building data includes: climate zone, building structure, building envelope heat transfer coefficient and equipment energy efficiency ratio;

[0251] The collection method includes building information model (BIM) data extraction and field monitoring.

[0252] In step S3, the calculation of life cycle carbon emissions uses:

[0253] Carbon emissions = activity data × emission factor;

[0254] Where, activity data includes building material consumption and equipment energy consumption value, and emission factor is referenced from the building carbon emission standard database.

[0255] In step S4, the determination standard of sensitivity coefficient is specifically:

[0256] β>0 indicates that the reconstruction promotes carbon reduction, and β<0 indicates that it hinders carbon reduction;

[0257] The larger the |β| value, the higher the sensitivity.

[0258] The screening criteria in step S5 specifically include:

[0259] The sensitivity coefficient |β| is greater than or equal to 5%;

[0260] The project reconstruction engineering difficulty level is less than or equal to a preset threshold value;

[0261] The project economic cost recovery period is less than or equal to 10 years.

[0262] In step S6, the reconstruction scheme verification specifically includes adjusting the material thickness, replacing the equipment type, and optimizing the construction method, and recalculating the carbon emissions.

[0263] The orthogonal test design in step S7 satisfies:

[0264] The factors include at least three of the following: thermal performance of external walls, thermal performance of external windows, thermal performance of roof, and energy efficiency ratio of heating equipment;

[0265] Each factor is set to at least three levels, and the level value is the heat transfer coefficient or energy efficiency ratio of different materials or structures;

[0266] The number of factors m is greater than or equal to 3, the number of levels n is greater than or equal to 3, and the orthogonal table satisfies L k (n m ) structure (m≥k);

[0267] Wherein, L represents the orthogonal table, and k represents the number of experiments.

[0268] In the calculation of the annual average carbon emissions in step S8, the production process carbon emissions cover building material production and transportation carbon emissions, and the operation stage carbon emissions cover heating, air conditioning, and lighting energy consumption carbon emissions.

[0269] The building energy consumption simulation software in step S3 is DesignBuilder, and the carbon reduction effect verification in step S6 is realized by simulating the DesignBuilder software.

[0270] In step S10, the optimal solution is selected by using the Pareto optimal solution, and the frontier solution set is selected in the two-dimensional space of carbon emissions-cost.

[0271] Through the above steps, building energy consumption simulation software is used to calculate the lifecycle carbon emissions of each project before and after the renovation, generating a carbon emission table. The carbon reduction sensitivity coefficient β of each project is calculated, and projects with a sensitivity coefficient |β| ≥ 5% are selected as a high-significance renovation candidate set. The sensitivity coefficient β is then used to quantify the carbon reduction efficiency of each renovation project, thereby solving the problem of "blindness in renovation project selection" in the prior art. A variety of detailed renovation plans are proposed for high-significance projects to verify their carbon reduction effects. An orthogonal test matrix is ​​constructed with the high-significance projects as factors and the detailed renovation plans of each project as levels. The annual average carbon emissions of each plan combination are calculated. The economic efficiency and carbon reduction efficiency of each plan combination are compared in combination with cost data. The plan with the lowest annual average carbon emissions and the best cost-effectiveness is selected as the final renovation plan. The present invention uses different approaches to high-significance projects as "levels" to conduct multi-factor combination experiments, outputting the plan with the lowest annual average carbon emissions and the best cost-effectiveness, thereby achieving a balance between economic efficiency and carbon reduction effects.

[0272] Example

[0273] Optionally, the present invention provides an embodiment, wherein a 6-story brick-concrete structure house (building area 1200m2) built in 2000 in a certain area is selected. 2 , with a service life of 22 years) was selected as the renovation object; the house is located in a cold area (climate zone II), the thermal performance of the enclosure structure is poor (the exterior wall has no insulation, and the exterior windows are single-glazed plastic steel windows), the heating equipment is an old gas boiler (energy efficiency ratio 0.85), and the annual heating energy consumption is as high as 110kWh / m 2 , which is a typical high-carbon emission existing residential building;

[0274] The specific implementation steps are as follows:

[0275] Step 1: Data collection and establishment of a list of transformable projects, including:

[0276] Collection of basic building information:

[0277] On-site investigation records: Climate zone II, 6-story brick-concrete structure, built in 2000, service life 22 years;

[0278] BIM extracted enclosure structure parameters: the exterior wall is 240mm clay brick (without insulation), the exterior window is single-glass plastic steel window (heat transfer coefficient 4.7W / (m 2 ·K)), the roof is 100mm cement perlite insulation (heat transfer coefficient 1.2W / (m 2 K)), no ground insulation;

[0279] On-site monitoring of operating energy consumption: annual energy consumption of the heating system is 132,000 kWh (110 kWh / m 2 ), the annual energy consumption of the air conditioning system is 48,000 kWh (40 kWh / m2 ), lighting system annual energy consumption 24000 kWh (20 kWh / m 2 );

[0280] Reformable projects identified:

[0281] 4 reformable projects identified: external wall thermal performance, external window thermal performance, roof thermal performance, heating equipment EER;

[0282] Life cycle data acquisition:

[0283] Building material carbon emission factors: XPS board (2.8 kgCO2e / kg), rock wool board (1.2 kgCO2e / kg), Low-E glass (3.5 kgCO2e / m 2 );

[0284] Construction data: external wall insulation construction energy consumption 5 kWh / m 2 , material loss rate 5%;

[0285] Step two: standard reform scheme design and carbon emission calculation, including:

[0286] Standard reform scheme design:

[0287] External wall: increase 80 mm XPS board insulation (standard thickness range 60-100 mm);

[0288] External window: replace with double glass Low-E plastic steel window (heat transfer coefficient 2.0 W / (m 2 ·K));

[0289] Roof: keep original 100 mm cement perlite insulation (heat transfer coefficient 1.2 W / (m 2 ·K));

[0290] Heating equipment: replace with air source heat pump (EER 3.0, in line with "Energy-saving product government procurement list");

[0291] Carbon emission model construction:

[0292] Production stage: XPS board consumption 7.57 t (carbon emission 21.2 kgCO2e), air source heat pump 1 (carbon emission 500 kgCO2e);

[0293] Construction stage: external wall insulation construction energy consumption 6000 kWh (carbon emission 3.6 kgCO2e, grid factor 0.6 kgCO2e / kWh);

[0294] Operation stage: DesignBuilder simulation heating energy consumption reduced to 60 kWh / m 2 (36 kgCO2e / m2 • a);

[0295] Maintenance phase: XPS board is replaced every 25 years (average annual carbon emissions 0.85 kg CO2e / m 2 • a);

[0296] Carbon emission table output, as follows:

[0297]

[0298]

[0299] Step three: carbon reduction sensitivity coefficient β calculation, including:

[0300] Data extraction and calculation:

[0301] Exterior wall project: Q1 = 120.0 kg CO2e / m 2 (total carbon emissions before renovation), Q2 = 85.05 kg CO2e / m 2 (total carbon emissions after renovation), β = (120-85.05) / 120 x 100% = 29.12%.

[0302] Heating equipment project: Q1 = 650.0 kg CO2e / m 2 (total carbon emissions before renovation), Q2 = 539.00 kg CO2e / m 2 , β = (650-539) / 650 x 100% = 17.08%;

[0303] As shown in the following table:

[0304]

[0305] Step four: high significance project screening, including:

[0306] Screening conditions:

[0307] Main threshold: β ≥ 5% (exterior wall 29.12%, exterior window 7.37%, heating equipment 17.08% all meet);

[0308] Auxiliary conditions: engineering difficulty level ≤ III level (exterior wall, exterior window, heating equipment renovation difficulty are all II level), cost recovery period ≤ 10 years (exterior wall renovation recovery period 8 years, exterior window 7 years, heating equipment 9 years);

[0309] High significance project list as shown in the following table:

[0310]

[0311] Step five: refinement of renovation scheme design, as shown in the following table:

[0312]

[0313]

[0314] Step six: Orthogonal test matrix construction, specifically including:

[0315] Test design:

[0316] Factors: thermal performance of external wall (A), thermal performance of external window (B), energy efficiency ratio of heating equipment (C);

[0317] Levels: A1 (80mm XPS), A2 (120mm XPS), A3 (rock wool board 100mm); B1 (double glass Low-E), B2 (triple glass Low-E); C1 (air source heat pump), C2 (ground source heat pump);

[0318] Orthogonal table: L9 (34 3 ), a total of 9 groups of tests;

[0319]

[0320]

[0321] Step seven: economic efficiency and carbon reduction efficiency optimization, specifically including:

[0322] Cost and carbon emission comparison:

[0323] Pareto frontier scheme: test 3 (annual average carbon emission 56.0 kgCO2e / m 2 ·a, cost 1.5 million yuan), test 5 (annual average carbon emission 55.5 kgCO2e / m 2 ·a, cost 1.6 million yuan), test 7 (annual average carbon emission 55.0 kgCO2e / m 2 ·a, cost 1.7 million yuan);

[0324] The highest carbon reduction cost efficiency scheme: test 7 (efficiency = (60-55) / (170-120) = 0.1 kgCO2e / yuan);

[0325] Specifically as follows:

[0326]

[0327] Final scheme determination:

[0328] Select test 7 (external wall 120mm XPS board + triple glass Low-E external window + ground source heat pump) as the final scheme, with an annual average carbon emission of 55.0 kgCO2e / m 2• a, cost 1.7 million yuan, the highest carbon reduction cost efficiency.

[0329] In this embodiment, the average annual carbon emissions of the residence are 120.0 kgCO2e / m2, which is reduced by 54.17% through the method of the present application, and the payback period is 9 years, achieving the balance of "high carbon reduction and low investment". 2 • a) reduced by 54.17%, with a cost recovery period of 9 years, achieving the balance of "high carbon reduction and low investment"; compared with the prior art (only modifying the outer wall or equipment), the present application avoids inefficient project investment through systematic screening and multi-factor optimization, verifying the effectiveness of solving the problems of "blind project selection, one-sided calculation, and insufficient optimization".

[0330] The embodiments of the present application are described in detail above in combination with the drawings, but the present application is not limited to the above embodiments, and various changes can be made within the knowledge of those skilled in the art without departing from the purpose of the present application.

Claims

1. A carbon emissions-based evaluation and design method for existing residential renovation projects, characterized by: The method is executed by a computer device and includes the following steps: S1: Obtain a list of renovable projects for the residential building to be renovated and collect the building data of each project before renovation; S2: Propose at least one standard renovation plan for each renovable project and establish a carbon emission model for each plan; S3: Calculate the lifecycle carbon emissions of each project before and after renovation using building energy consumption simulation software and generate a carbon emissions table; S4: Calculate the carbon reduction sensitivity coefficient β of each project: β=(Q1-Q2) / Q1×100%; Among them, Q1 is the life cycle carbon emission before transformation (kgCO2e / m 2 ), Q2 is the life cycle carbon emissions after transformation (kgCO2e / m 2 ); S5: Screen the projects with a sensitivity coefficient |β| ≥ 5% as high-significance transformation candidate sets; S6: Propose multiple detailed transformation plans for high-significance projects and verify their carbon reduction effects; S7: Construct an orthogonal test matrix with the highly significant projects as factors and the detailed transformation plans of each project as levels; S8: Calculate the average annual carbon emissions for each combination of options: Average annual carbon emissions = (carbon emissions during production + carbon emissions during operation) / years of use; S9: Compare the economic and carbon reduction efficiency of each option combination based on cost data; S10: Select the solution with the lowest annual carbon emissions and the best cost-effectiveness as the final transformation solution.

2. The carbon emission-based evaluation and design method for existing residential renovation projects according to claim 1 is characterized by: In step S1: Building data includes: climate zones, building structure, heat transfer coefficient of building envelope and equipment energy efficiency ratio; The collection methods include building information model (BIM) data extraction and on-site monitoring.

3. The carbon emission-based evaluation and design method for existing residential renovation projects according to claim 1 is characterized by: In step S3, the life cycle carbon emissions are calculated using: Carbon emissions = activity data × emission factor; Among them, activity data includes building material usage and equipment energy consumption, and emission factors are quoted from the building carbon emission standard database.

4. The carbon emission-based evaluation and design method for existing residential renovation projects according to claim 1 is characterized by: In step S4, the sensitivity coefficient determination criteria are specifically as follows: β>0 means that the transformation promotes carbon reduction, and β<0 means that it hinders carbon reduction; A larger |β| value indicates a higher sensitivity.

5. The carbon emission-based evaluation and design method for existing residential renovation projects according to claim 1 is characterized by: The screening criteria in step S5 specifically include: Sensitivity coefficient |β| ≥ 5%; The difficulty level of the project renovation project is ≤ the preset threshold; The project's economic cost recovery period is ≤ 10 years.

6. The carbon emission-based evaluation and design method for existing residential renovation projects according to claim 1 is characterized by: In step S6, the transformation plan verification specifically includes: adjusting material thickness, changing equipment type, optimizing construction practices, and recalculating carbon emissions.

7. The carbon emission-based evaluation and design method for existing residential renovation projects according to claim 1 is characterized by: The orthogonal experimental design in step S7 satisfies: Factors include at least three of the following: thermal performance of exterior walls, thermal performance of exterior windows, thermal performance of roofs, and energy efficiency ratio of heating equipment; Each factor is set to at least 3 levels, and the level value is the heat transfer coefficient or energy efficiency ratio of different materials or structures; The number of factors m≥3, the number of levels n≥3, and the orthogonal table satisfies L k (n m ) structure (m ≥ k); Where L represents the orthogonal array and k represents the number of experiments.

8. The carbon emission-based evaluation and design method for existing residential renovation projects according to claim 1 is characterized by: In the calculation of the average annual carbon emissions in step S8, the carbon emissions during the production process include the carbon emissions from the production and transportation of building materials, and the carbon emissions during the operation phase include the carbon emissions from heating, air conditioning, and lighting energy consumption.

9. The carbon emission-based evaluation and design method for existing residential renovation projects according to claim 1 is characterized by: The building energy consumption simulation software in step S3 is DesignBuilder, and the carbon reduction effect verification in step S6 is achieved through simulation using the DesignBuilder software.

10. The carbon emission-based evaluation and design method for existing residential renovation projects according to claim 1 is characterized by: The optimal solution in step S10 is selected by adopting the Pareto optimal solution, and the frontier solution set is selected in the carbon emission-cost two-dimensional space.

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