Multi-level and multi-dimensional building carbon reduction technology selection method

Abstract

The invention discloses a multi-level and multi-dimensional building carbon reduction technology selection method, which starts from four dimensions of technical characteristics, city characteristics, building characteristics and carbon reduction targets, takes cost reduction and benefit improvement as a screening standard, and comprises the following steps: firstly, establishing three carbon reduction technology menu libraries according to three classification principles; and then optimizing a building carbon reduction technology selection method, establishing a building carbon reduction technology multi-level and multi-dimensional optimization model from four angles of urban partition level, building block level, building application level and carbon reduction target level, and optimizing an optimal carbon reduction technology combination according to a carbon reduction target to realize technology optimization on the carbon reduction target level.

Description

Technical Field

[0001] This invention relates to a multi-level, multi-dimensional method for selecting building carbon reduction technologies, belonging to the field of building energy conservation technology. Background Technology

[0003] Building carbon reduction technology is key to the transformation and upgrading of the construction industry. However, the following problems exist in the selection and efficient application of technology: 1) The spatial distribution of building carbon reduction technology application is unbalanced; 2) Urban building types are diverse and the application objects of technology are complex. The matching of different functions and areas of buildings with different technical solutions is not the same, making it difficult to select the best one; 3) Different technologies themselves have significant differences in energy-saving and carbon reduction capabilities, costs and other aspects, making it difficult to select the technical solution that maximizes benefits. Summary of the Invention

[0004] This invention provides a multi-level, multi-dimensional method for selecting building carbon reduction technologies. It starts from four dimensions: technical characteristics, urban characteristics, building characteristics, and carbon reduction goals. It uses cost reduction and efficiency improvement as the screening criteria to optimize the selection method for building carbon reduction technologies, aiming to better achieve the goal of low-carbon transformation in the construction industry.

[0005] To solve the above-mentioned technical problems, the present invention adopts the following technical solution:

[0006] In a first aspect, the present invention provides a multi-level, multi-dimensional method for selecting building carbon reduction technologies, the method comprising the following steps:

[0007] Step 1: Establish a menu library of carbon reduction technologies;

[0008] Step 2: Construct an optimal carbon reduction technology model;

[0009] Step 3: Select carbon reduction technologies based on the carbon reduction technology optimization model constructed in Step 2.

[0010] Furthermore, the method for constructing the carbon reduction technology menu library in step 1 is as follows:

[0011] First, all carbon reduction technologies are classified according to the building life cycle. Then, they are classified a second time according to the logic of technical characteristics. Finally, they are classified a third time according to the logic of independent and mutually exclusive classification.

[0012] Furthermore, the carbon reduction technology optimization model in step 2 includes a city zoning level optimization model, a building block level optimization model, a building application level optimization model, and a carbon reduction target level optimization model.

[0013] Furthermore, the urban zoning hierarchical optimization model is established based on fuzzy comprehensive analysis, using technical applicability, cost-effectiveness, and carbon reduction and environmental protection as the first-level evaluation indicators to comprehensively evaluate each carbon reduction technology in the first technology menu library;

[0014] The technical applicability indicators are further refined into three secondary indicators: technical reliability, technical implementability, and technical maintainability;

[0015] The evaluation level of technical reliability is divided into three levels: excellent, good, and poor. The standards are as follows: excellent means that it has national standards; good means that it has local standards but no national standards; poor means that it has no standards.

[0016] The evaluation level of technical feasibility is divided into three levels: excellent, good, and poor. The evaluation criteria are based on the natural environment and climate characteristics of the implementing city and are determined by expert knowledge.

[0017] The evaluation level of technical maintainability is divided into three levels: excellent, good, and poor. The evaluation criteria are based on the resource conditions of the city where the maintenance and operation are implemented and are determined by expert knowledge.

[0018] The aforementioned cost-related indicators are further refined into a second-level indicator: economic matching. The evaluation level of economic matching is divided into three levels: excellent, good, and poor, with the following standards: excellent represents that the per capita GDP of the city's province ranks in the top 1 / 3 of the country; good represents that the per capita GDP of the city's province ranks in the middle 1 / 3 of the country; and poor represents that the per capita GDP of the city's province ranks in the bottom 1 / 3 of the country.

[0019] The carbon reduction and environmental protection indicators are further refined into two secondary indicators: technological carbon reduction and environmental pollution.

[0020] The evaluation level of carbon reduction technology is divided into three levels: excellent, good, and poor. The standards are as follows: excellent represents the top 1 / 3 of buildings with the best technology in terms of total energy consumption reduction; good represents the middle 1 / 3 of buildings with the best technology in terms of total energy consumption reduction; and poor represents the bottom 1 / 3 of buildings with the best technology in terms of total energy consumption reduction.

[0021] The environmental pollution level is divided into three levels: excellent, good, and poor. The standards are as follows: excellent means that the technology has no impact on the environment; good means that the use beyond the set time limit will have an impact on the environment; poor means that the use within the set time limit will have an impact on the environment.

[0022] Furthermore, the construction of the building block hierarchy optimization model includes: modeling the target building and its surrounding buildings in the energy consumption simulation software DesignBuilder to form a building block; performing energy consumption simulation on the target building in the environment of the building block; and using the energy consumption simulation results as evaluation indicators to evaluate each carbon reduction technology in the second technology menu library.

[0023] Furthermore, the building application hierarchy optimization model is established based on the multi-objective decision analysis method TOPSIS, using application indicators, technical indicators, and environmental indicators as the first-level evaluation indicators to comprehensively evaluate each carbon reduction technology in the second technology menu library;

[0024] The applicability indicators are further refined into three second-level indicators: completeness, feasibility, and maintainability;

[0025] The evaluation level of completeness is divided into three levels: excellent, good, and poor. The standards are as follows: excellent means that it has national-level standards; good means that it has local-level standards but no national-level standards; poor means that it has no standards at all.

[0026] The feasibility evaluation level is divided into three levels: excellent, good, and poor. The evaluation criteria are based on the natural environment and climate characteristics of the implementing city and are determined according to expert knowledge.

[0027] The maintenance performance evaluation is divided into three levels: excellent, good, and poor. The evaluation criteria are based on the resource conditions of the city implementing the maintenance and operation, and are determined according to expert knowledge.

[0028] The technical indicators are further subdivided into two secondary indicators: equipment purchase cost and maintenance and operation cost;

[0029] The environmental indicators are further subdivided into two secondary indicators: energy savings and pollution level.

[0030] The pollution level is divided into three levels: excellent, good, and poor. The standards are as follows: excellent means that the technology has no impact on the environment; good means that the use beyond the set time limit will have an impact on the environment; and poor means that the use within the set time limit will have an impact on the environment.

[0031] Furthermore, the carbon reduction target hierarchy optimization model includes: based on building energy conservation standards, when the target building meets the carbon reduction rate limit, ultra-low energy consumption building, near-zero energy consumption building, zero energy consumption building, and zero-carbon building standards, five optimized models are constructed using the lowest investment cost as the objective function and employing a 0-1 integer programming algorithm: carbon reduction investment optimization model, ultra-low energy consumption optimization model, near-zero energy consumption building optimization model, zero energy consumption building optimization model, and zero-carbon building optimization model.

[0032] Furthermore,

[0033] The carbon reduction investment optimization model includes two types: the model that maximizes the carbon reduction rate within the investment limit and the model that minimizes the investment within the carbon reduction rate limit. Specifically:

[0034] Max(η)

[0035]

[0036] Among them, carbon reduction rate E 节省购入电,i The carbon dioxide emissions generated by the savings in purchased electricity for accounting unit i in the target building; E 节省购入热,i The carbon dioxide emissions generated by the savings in purchased heat for accounting unit i in the target building; E 节省购入冷 , i The carbon dioxide emissions generated by the savings in purchased cooling capacity for accounting unit i in the target building; E 节省购入气,i The carbon dioxide emissions saved by purchasing natural gas in accounting unit i of the target building; δ is the carbon dioxide emissions generated by electricity consumption in the target building; α is the combined cost of carbon reduction technologies; D = {d j} represents the investment limit matrix; x i Let i be the decision variable representing whether carbon reduction technology i is selected.

[0037] Min(α)

[0038]

[0039] Where, E = {e k} represents the carbon reduction rate limit matrix;

[0040] The ultra-low energy consumption optimization model is specifically as follows:

[0041] min(α)

[0042]

[0043] Where, η e规范 The target building's energy efficiency rating is the specified value; f 电力 ε is the energy conversion factor for electricity, ε is the total electricity savings per unit area of ​​the optimal combination of carbon reduction technologies, ζ is the total electricity generation per unit area of ​​the optimal combination of carbon reduction technologies, and ER is the comprehensive building energy consumption value of the benchmark building.

[0044] The near-zero energy building optimization model is as follows:

[0045] Min(α)

[0046]

[0047] The specific optimization model for the zero-energy building is as follows:

[0048] Min(α)

[0049]

[0050] Where AE is the total energy consumption per unit area of ​​the benchmark building, a i Cost of carbon reduction technology i;

[0051] The zero-carbon building optimization model is specifically as follows:

[0052] Min(α)

[0053]

[0054] Where δ represents the amount of carbon dioxide generated by the electricity consumed by the baseline building; β represents the total reduction in carbon dioxide emissions from the optimal combination of carbon reduction technologies; and γ represents the total reduction in carbon dioxide emissions from the generation of green electricity from the optimal combination of carbon reduction technologies.

[0055] Furthermore, step 3 specifically includes:

[0056] Based on the city zoning hierarchical optimization model, select from the carbon reduction technology menu library to obtain the first selection result;

[0057] Based on the building block hierarchy optimization model, a second selection result is obtained by selecting from the first selection result;

[0058] Based on the building application hierarchical optimization model, a third selection result is obtained by selecting from the second selection result;

[0059] Based on the carbon reduction target hierarchy optimization model, the final carbon reduction technology selection result is obtained by selecting from the third selection result.

[0060] Secondly, the present invention also provides a multi-level, multi-dimensional building carbon reduction technology selection device, comprising:

[0061] Database unit, used to create a menu library of carbon reduction technologies;

[0062] Model building unit, used to build optimal models for carbon reduction technologies;

[0063] The selection unit is used to select carbon reduction technologies based on the carbon reduction technology optimization model.

[0064] Compared with existing technologies, this invention, employing the above technical solution, has the following technical effects: This invention organizes relevant policy documents on building carbon reduction, constructs a resource library of building carbon reduction technologies, improves the theory of carbon reduction technology optimization, and ultimately constructs a multi-level, multi-dimensional optimization model, providing cases and theoretical basis for the construction of subsequent optimization models. It overcomes the shortcomings of current building carbon reduction technology optimization methods, such as insufficient theoretical framework, unclear standards, and limited levels and dimensions, and alleviates the problems of limited technology options and weak classification specificity in the building carbon reduction technology menu. This optimization model conducts detailed evaluation and optimization at the city level, building block level, target building level, and carbon reduction target level, providing clear evaluation results and optimization guidance, exhibiting strong relevance. By applying relatively scientific methods to construct the optimization model, it guides actual engineering projects, objectively and comprehensively considering actual production methods, economic principles, and organizational principles. Detailed Implementation

[0065] The technical solution of the present invention will be further described in detail below with reference to specific embodiments:

[0066] The construction industry faces a development path of "low carbon - near-zero carbon - zero carbon," making the optimal selection of building carbon reduction technologies imperative. The selection of building carbon reduction technologies is a multi-step process involving the summarization and classification of carbon reduction technologies, the calculation of carbon reduction quantification, and the selection of the best technologies. Building carbon reduction technologies involve research across multiple stages, including design, construction, energy systems, and operation and maintenance. Therefore, this invention sets higher requirements for the application of existing building carbon reduction technologies. Optimizing carbon reduction technologies throughout the entire building lifecycle, targeting different levels of selection scope and different carbon reduction objectives, is crucial for building energy conservation and emission reduction.

[0067] This invention constructs a menu library of carbon reduction technologies under different classification principles. It establishes a multi-level carbon reduction technology evaluation model from the aspects of carbon reduction, cost, technical reliability, and technical maintainability. Taking ultra-low energy consumption buildings, near-zero energy consumption buildings, zero energy consumption buildings, and zero carbon buildings as targets, it evaluates all carbon reduction technologies to obtain the optimal combination of carbon reduction technologies, so as to achieve the goal of maximizing resource conservation, optimizing allocation, and obtaining the maximum carbon emission reduction.

[0068] This invention aims to establish a multi-level carbon reduction technology optimization model to assist architects in quickly selecting appropriate building carbon reduction technologies during architectural design, providing technical support for architectural design. Simultaneously, it offers the most ideal combinations of building carbon reduction technologies at different levels to meet diverse needs. This will enable the development of more rational low-carbon task plans and further optimize resource allocation and cost control in the construction industry.

[0069] The building carbon reduction technologies referred to in this invention include various technologies that can reduce building energy consumption and carbon emissions. These include passive technologies implemented during the building design phase, technologies to improve the thermal performance of building envelopes, technologies for efficient resource utilization, high-performance air conditioning technologies, and technologies for utilizing renewable energy, covering all stages of the building lifecycle: materials and components, planning and design, construction and transportation, and operation and maintenance. Whether traditional and regionally specific, or novel and technologically advanced, any mature, safe, reliable, and effective technology falls within the scope of this invention.

[0070] Establishing a comprehensive and extensive database of building carbon reduction technologies is the foundation and prerequisite for selecting the best building carbon reduction technologies. Currently, there are many types and a large number of building carbon reduction technologies, with significant differences between them. Therefore, it is necessary to classify these technologies. This invention first classifies current carbon reduction technologies according to three principles: technical characteristics, independent and mutually exclusive logic, and building life cycle, thus constructing a carbon reduction technology menu database.

[0071] Logical classification based on technical characteristics

[0072] There are significant differences between different types of building carbon reduction technologies. Defining these "types" can be considered from several perspectives: First, according to engineering fields. Building construction, from design to completion, includes stages such as design, construction, testing, operation, and management. Further subdivisions include materials (design), renewable energy (design), monitoring (construction), heating (operation), cooling (operation), lighting (operation), and equipment (operation). Following this logic, building carbon reduction technologies can be categorized. Second, according to passive and active methods. From the perspective of carbon reduction characteristics, building carbon reduction technologies can be divided into two parts. One part involves technologies that are deeply integrated into the overall layout and individual building design from the building's design stage; these are considered part of the design itself and are called passive building carbon reduction technologies. The other part requires consideration outside the building itself, applying facilities, primarily mechanical equipment, to an already completed building to assist in reducing carbon emissions; these are called active building carbon reduction technologies. Finally, according to the different energy consumption types of buildings. Analyzing a building's energy consumption can be categorized into four types: building envelope energy consumption, building electrical equipment energy consumption, building heating and cooling energy consumption, and building renewable resource (energy) energy consumption. Similarly, building carbon reduction technologies can be classified according to this approach to demonstrate in which aspects they reduce building carbon emissions.

[0073] Classified according to independent and mutually exclusive logic

[0074] This principle stems from a practical application perspective. Regardless of the classification principle used for technologies, the goal is to provide a clear, concise, and accurate understanding of the complex and diverse building carbon reduction technologies. However, when practically applying carbon reduction technologies, a crucial question must be considered: which technologies are applied independently without interference, and which technologies are mutually exclusive, requiring a choice among multiple options? The independent and mutually exclusive logic classification principle addresses this issue by categorizing carbon reduction technologies according to their independence and mutual exclusion. This facilitates the selection of the building carbon reduction technology with the highest overall value from among multiple mutually exclusive technologies after obtaining optimal results.

[0075] Independent solutions refer to solutions that are unrelated to each other; accepting or rejecting one solution does not affect the selection of other solutions or their technical effects. Mutually exclusive solutions refer to solutions that are mutually exclusive; once one solution is selected, no other solution can be selected. Thus, the relationships between all solutions can be divided into two types: independent and mutually exclusive.

[0076] If we consider the alternative energy-saving building technologies I0 as a set, I0 = {A, B, C, D, ...}, each capital letter in the set represents a category of technical solutions. Each category is independent of the others; accepting or rejecting a particular solution does not affect the selection or effectiveness of the other solutions. Each category of technical solutions is a set of numerous solutions. For example, if A represents external wall insulation technology, which is a set of numerous insulation technologies, A = {a1, a2, a3, ...}, a... i These represent different insulation technologies, and these technologies are mutually exclusive. Once one insulation technology is selected, other options cannot be chosen.

[0077] Classification by building life cycle

[0078] This principle is based on the perspective of architectural design. First, building carbon reduction technologies are classified according to the entire building life cycle, including the material and component stage, the planning and design stage, the construction and transportation stage, the operation and maintenance stage, and the demolition and disposal stage.

[0079] This classification principle is actually an extension, expansion and application of the independent and mutually exclusive classification principle. The purpose of building this library is to provide carbon reduction technology selection services from the architectural design process (the entire life cycle of a building). Its significance lies in its ability to qualitatively guide architects to think about the issue of reducing building carbon emissions from different perspectives.

[0080] The optimal selection of carbon reduction technologies needs to consider various levels. From a city perspective, China is vast and diverse, with significant differences in natural, economic, and climatic conditions among different cities. From a neighborhood perspective, the surrounding environments of similar buildings vary greatly. From a building perspective, the functions, areas, and shapes of buildings to which the technologies are applied differ significantly. From a carbon reduction target perspective, the carbon reduction standards for ultra-low energy buildings, near-zero energy buildings, zero energy buildings, and zero-carbon buildings vary considerably. Therefore, it is first necessary to clarify the selection levels and, based on specific selection models for each level, find the optimal technologies suitable for that level. In summary, the selection levels determined in this study are: city zoning level selection, building neighborhood level selection, building application level selection, and carbon reduction target level selection.

[0081] Multi-level optimization breaks down complex optimization problems into smaller, more manageable ones, simplifying the process and enabling a divide-and-conquer approach. Based on practical considerations, the optimization problem is broken down into four levels: city, neighborhood, building, and carbon reduction targets. Each level has different optimization objectives and evaluation indicators, requiring different solutions and optimization models, necessitating case-by-case analysis. These four levels are both independent and interconnected: on the one hand, optimization can be performed independently at a single level to obtain results; on the other hand, optimization can be performed comprehensively from macro to micro levels, progressing step by step to achieve a complete optimization result. The optimization results at each level are interrelated, with city, building, and carbon reduction targets progressing hierarchically. The output of the optimization model at the previous level determines the input data for the next level's optimization model.

[0082] Multi-dimensional optimization refers to the fact that each level of the optimization model has multiple evaluation indicators to comprehensively evaluate the value of the technology from multiple perspectives. For example, the urban zoning level optimization model includes three indicators: technology applicability, cost-effectiveness, and carbon reduction and environmental protection. These indicators respectively consider the safety and reliability of the technology itself, the city's acceptance of the technology's cost, the technology's carbon reduction potential, and the degree of environmental pollution.

[0083] City zoning hierarchy optimization

[0084] City-level zoning optimization is a multi-faceted and multi-factor-oriented process. It involves comprehensively considering various factors such as a city's natural environment, climate characteristics, and economic development to arrive at the combination of carbon reduction technologies with the highest overall value. In other words, this tiered optimization of technology combinations is highly targeted, with significant differences between different cities. Essentially, the optimization process involves combining a city's economic, climatic, environmental, and policy conditions to find the most suitable combination of carbon reduction technologies. This tier evaluates each building carbon reduction technology from the city's perspective, ultimately obtaining a comprehensive score for each city's carbon reduction technologies and identifying the technology with the highest overall value across all categories. Clearly, this optimization problem involves various influencing factors, which need to be transformed into corresponding evaluation indicators. These indicators are difficult to quantify. Therefore, the city zoning hierarchical optimization is a qualitative problem. This hierarchical optimization model selects the fuzzy comprehensive evaluation method to establish the optimization model, and determines the applicability of technology, cost, and carbon reduction and environmental protection as evaluation indicators. Each technology in the carbon reduction technology menu is scored, and the applicability of each technology in the city is determined according to three levels: excellent, good, and poor. Each carbon reduction technology is comprehensively evaluated from three aspects: whether the characteristics of the technology itself are in line with the city's conditions, whether the cost of the technology is in line with the city's economic development level, and whether the carbon reduction capacity and environmental protection level of the technology meet the city's requirements.

[0085] Analyzing the problem of optimal urban zoning hierarchy reveals the following important characteristics:

[0086] 1) There is no internal connection between the preferred candidates. The preferred candidates are various carbon reduction technologies, and the purpose of selection is to obtain the degree of matching between the technology and the city, and to clarify which technology belongs to the "good, medium and poor" evaluation for the city.

[0087] 2) The selection criteria exhibit a strong emphasis on qualitative rather than quantitative analysis. The selection model considers the relationship between cities and technologies, without taking into account specific architectural engineering cases; therefore, general applicability needs to be considered. In most cases, technologies need to be categorized into different levels to evaluate their merits.

[0088] 3) The selection process for each preferred option is independent. There is no inherent connection between the selected technologies; only the relationship between a single technology and the city needs to be considered. The selection process is independent, absolute, and closed. In other words, if any technology is added or deleted from the carbon reduction technology menu, the selection results of other technologies remain unchanged.

[0089] In summary, considering the characteristics of the optimal selection at this level, the fuzzy comprehensive evaluation method is selected as the algorithm.

[0090] Based on the interrelationship between carbon reduction technologies and urban zoning, the following evaluation indicators for the optimal selection of urban zoning levels are shown in Table 1.

[0091] Table 1. Optimization Index System for City Zoning Levels

[0092]

[0093] Based on the fuzzy comprehensive evaluation method, a set of evaluation comments (good, excellent, poor) for the city zoning-level optimization indicators is required. Among them, the comments for the building application level (target level) represent the optimization results of the evaluation object (carbon reduction technology). The meaning of each indicator in the system is explained below.

[0094] (1) Technical reliability (C11)

[0095] The selection of carbon reduction technologies must take into account their reliability. Technologies must meet the requirements of building designers in terms of safety, reliability, and maturity before being adopted. If a building carbon reduction technology has been certified by national or local government departments, it indicates that the technology is compliant, safe, and reliable. Furthermore, the same technology may have one or more sets of standards, with varying levels of compliant standards. Therefore, the evaluation standards for technology reliability (C11) are as follows: Excellent – ​​Possesses national-level standards; Good – No national-level standards, but has local-level standards; Poor – No standards whatsoever.

[0096] (2) Technical Implementation C12

[0097] This indicator indicates whether a technology can be implemented effectively, but this is limited by the different natural environments and climate characteristics of different cities; the same carbon reduction technology cannot be implemented in all cities. Given the different limitations of each carbon reduction technology, the evaluation criteria for this indicator cannot be uniform and should be determined individually for each technology.

[0098] (3) Technical maintainability (C13)

[0099] The maintainability of a technology indicates that after the implementation of carbon reduction technologies, the individual resource conditions of each city need to be considered to ensure the technology's maintenance and operation. Similarly, the resource conditions required for maintenance vary depending on the technology and must be determined based on the specific technology requirements. Therefore, the evaluation standard for this indicator cannot be standardized and should be determined individually for each technology.

[0100] (4) Economic compatibility (C21)

[0101] Based on the above analysis, to determine the economic matching (C21) rating level for each carbon reduction technology, it is necessary to clarify the city's economic development level. This study uses the per capita GDP of the province where the city is located as the basis for measuring the city's economic level, and stipulates the following rating standards for economic matching (C21): Excellent – ​​the per capita GDP of the city's province ranks in the top 1 / 3 nationwide; Good – the per capita GDP of the city's province ranks in the middle 1 / 3 nationwide; Poor – the per capita GDP of the city's province ranks in the bottom 1 / 3 nationwide. A summary of the per capita GDP of the provinces where five typical cities are located in 2022 is provided.

[0102] (5) Carbon reduction through technology (C31)

[0103] The carbon reduction of a technology represents its overall energy-saving potential from a city-wide perspective. Because this indicator is not specific to any particular building, a precise value cannot be obtained; however, since the energy-saving potential of a technology remains constant, the specific carbon reduction will always remain within a certain range regardless of the building type. Conversely, if precise energy-saving data for a particular building in various cities were available, then a detailed analysis could be conducted, and the ranking of technology energy-saving amounts could reflect the overall energy-saving potential of the technology. The evaluation criteria for C31 carbon reduction of a technology are as follows: Excellent – ​​technology saving the top 1 / 3 of total building energy consumption; Good – technology saving the middle 1 / 3 of total building energy consumption; Poor – technology saving the bottom 1 / 3 of total building energy consumption. It should be noted that some building carbon reduction technologies need to be completed by the architect during the design phase, exhibiting high flexibility and complexity, making it difficult to determine their total building energy savings. Therefore, a comprehensive judgment based on the building's thermal zoning and the characteristics of the technology is required, and the C31 evaluation level for such technologies should be qualitatively analyzed.

[0104] (6) Environmental pollution (C32)

[0105] Some building carbon reduction technologies will have environmental impacts during operation, including emissions of harmful gases, carbon dioxide, excess water, excess heat, and light pollution. These impacts may cause environmental pollution. However, considering the natural environment's self-regulating capacity, the environmental pollution level (C32) of the technology is determined based on a combination of the carbon reduction technology's impact and the natural environment's regulatory capacity. The evaluation criteria are as follows: Excellent – ​​The technology has a negligible environmental impact; Good – Long-term use will have a significant environmental impact; Poor – Short-term use will have a significant environmental impact.

[0106] The city zoning hierarchical optimization index system is the evaluation index set U. The first-level index set being evaluated is:

[0107] U = (B1, B2, B3)

[0108] The three primary indicators mentioned above each contain a different number of elements, and their respective sets are established as follows:

[0109] B1 = (C11, C12, C13)

[0110] B2 = (C21)

[0111] B3 = (C31, C32)

[0112] The weights of each level of indicators in the city zoning hierarchical optimization model are determined according to the Analytic Hierarchy Process (AHP):

[0113] The first-level indicator weight set is as follows:

[0114] W = (w1, w2, w3)

[0115] In the formula, w1 = 0.1428, w1 = 0.4286, w1 = 0.4286.

[0116] The set of weights for the second-level indicators is:

[0117] w1 = (w11, w12, w13)

[0118] w2 = (w21)

[0119] w3 = (w31, w32)

[0120] In the formula, w11 = 0.2897, w12 = 0.6554, w13 = 0.0549, w21 = 1, w31 = 0.75, and w32 = 0.25.

[0121] The fuzzy comprehensive evaluation method stipulates that the evaluation set is the sum of the possible evaluation levels that each evaluated object may belong to. It is stipulated that the evaluation set is based on a 3-level scale, V = (v1, v2, v3), where v1, v2, and v3 are "excellent, good, and poor" respectively.

[0122] The six secondary indicators require three membership vectors to be determined based on the set of comments. These 18 membership vectors are then aggregated into R, where the membership vector sets for each secondary indicator are R1, R2, and R3, respectively.

[0123] R = (R1, R2, R3)

[0124]

[0125] R2=(r211r212r213)

[0126]

[0127] The membership degrees of second-level indicators are often fuzzy. After establishing the membership degree set, the next step is to determine the membership degree of the second-level indicators for each evaluation object. This invention uses the indicator refinement method to determine the membership degree. The indicator refinement method refers to refining the fuzzy membership level indicators until the membership degree of the refined indicators can be obtained relatively easily. The membership degree of the higher-level indicator is calculated by determining the membership degree of each sub-indicator. This invention further subdivides the fuzzy second-level indicators into third-level indicators. First, the membership degrees of the relatively easy-to-obtain third-level indicators are determined, and then they are summarized to obtain the membership degree of the second-level indicators.

[0128] The comprehensive membership vector of the first-level indicator is obtained by summing the comprehensive membership degrees of all second-level indicators belonging to it. The comprehensive membership degrees C1, C2, and C3 of B1, B2, and B3 are calculated according to the following formula:

[0129]

[0130] C2=W2×R2=w21×(r211r212r213)=(c21,c22,c23)

[0131]

[0132] In the formula, c11 represents the membership degree of the first-level indicator B1 under the v1 comment, and so on.

[0133] To calculate the target-level membership vector, the membership degrees of each level of indicators need to be calculated and then summed together. The following formula is the comprehensive membership vector M of the target-level indicators:

[0134]

[0135] The membership vector N of the target level indicator is calculated as follows:

[0136]

[0137] The comprehensive membership level N of the above target level is the evaluation matrix of the evaluation object. From it, we can know the membership degree of each comment of the evaluation object. Among them, the comment with the largest membership degree is the comment of the evaluation object.

[0138] Architectural Block Hierarchy Selection

[0139] Building block hierarchy optimization also needs to consider multiple factors, mainly including the climatic impact of the block environment on the target building, such as solar radiation, rainfall shielding, and wind. Since the surrounding blocks of a specific building are also clearly defined, the key issue is to accurately characterize the adjacent buildings around the target building and clarify their climatic impact on it. This hierarchy optimization lies between urban zoning hierarchy optimization and building application hierarchy optimization, serving as a bridge between the two. It does not evaluate the technology itself but rather supplements the building application hierarchy. This hierarchy considers the surrounding environment of the target building, especially the climatic impact of surrounding buildings. Clearly, the factors involved in this optimization problem are all quantifiable; therefore, building block hierarchy optimization is a quantitative problem. This hierarchy optimization model uses energy consumption simulation software modeling. The surrounding buildings are modeled in the energy consumption simulation software DesignBuilder, considering their impact. The scope of the surrounding buildings is defined based on the standard that the building projection can cover the target building.

[0140] The application of carbon reduction technologies in building block hierarchy optimization is reflected in the various impacts of surrounding buildings on the selected building. These impacts change over time, and the same impact can have vastly different degrees of effect on different carbon reduction technologies, making them difficult to quantify accurately. The present invention utilizes building energy consumption simulation software. Since the energy consumption of the benchmark building and the energy savings of each carbon reduction technology are calculated hourly using DesignBuilder, the surrounding buildings of the benchmark building can be modeled and included in the simulation calculations within the software. The software will then feed back the microclimate impacts of the surrounding buildings into the energy consumption of the benchmark building.

[0141] In summary, the building block hierarchy optimization model involves setting up the actual environment surrounding the research object in detail in DesignBuilder to create a realistic building block, with the block's boundaries determined according to the actual master plan.

[0142] Optimal Architectural Application Level

[0143] The top-level selection of building applications primarily considers the target building's own requirements for carbon reduction technologies, including carbon reduction capacity, investment cost, technological reliability, and maintainability. This level evaluates each carbon reduction technology for the target building, starting with the selection of the target building, and ultimately obtains a comprehensive score for the target building's carbon reduction technologies, identifying the technology with the highest overall value across all categories. Since the above requirements are quantifiable, this top-level selection is a quantitative problem. The Multi-Objective Decision Analysis (TOPSIS) algorithm is selected to determine three indicators: applicability, technicality, and environmental impact. These indicators respectively consider the safety and reliability of the technology itself, the target building's acceptance of the technology's cost, the technology's sustainability potential, and the degree of environmental pollution.

[0144] A hierarchical evaluation index system for building applications was established, as shown in Table 2.

[0145] Table 2 Evaluation Index System for Building Application Levels

[0146]

[0147] The seven secondary indicators in the second-level indicator layer of the above evaluation indicator system are also indicators of the building application hierarchical optimization model. The definitions of these seven indicators will be introduced below.

[0148] (1) Perfection C11

[0149] This indicator is qualitative, representing whether the technology itself is safe, reliable, and mature. If a building carbon reduction technology has been certified by national or local government departments, then the technology is considered compliant, safe, and reliable. Furthermore, the same technology may have one or more sets of standards, with varying levels of these standards. Therefore, the evaluation criteria for completeness (C11) are as follows: Excellent – ​​Possesses national-level standards, value 0.8; Good – No national-level standards, but has local-level standards, value 0.6; Poor – No standards, value 0.3.

[0150] (2) Feasibility C12

[0151] This is a qualitative indicator, representing whether a technology can be implemented normally in the target building. Due to the different natural environments and climate characteristics of the cities where the target buildings are located, the same carbon reduction technology cannot be implemented in all cities. Considering that the limitations of each carbon reduction technology are different, the evaluation standard for this indicator cannot be unified and should be determined separately for each technology. The evaluation level is specified as "Excellent," "Good," and "Poor," with values ​​of 0.8, 0.6, and 0.3 respectively.

[0152] (3) Maintainability C13

[0153] This is a qualitative indicator, representing the ease or difficulty of maintenance after a technology is applied to a target building. It primarily depends on the resource conditions of the city where the target building is located, in order to coordinate the maintenance and operation of the technology. Similarly, different technologies require different resource conditions for maintenance, which must be determined in conjunction with the specific technological needs. Therefore, the evaluation standard for this indicator cannot be standardized and should be determined individually for each technology.

[0154] (4) Equipment purchase cost C21

[0155] This indicator represents the cost incurred when each carbon reduction technology is applied to an actual engineering project and functions properly, expressed in ten thousand yuan. The costs vary depending on the specific characteristics of each carbon reduction technology and require discussion on a technology-specific basis. These costs include, but are not limited to, material costs, equipment costs, and labor installation costs. Due to differences in prices in different cities, the costs for the same technology will vary.

[0156] (5) Maintenance and operation costs C22

[0157] This indicator represents the cost, expressed in ten thousand yuan, of each carbon reduction technology applied to an actual engineering project and operating normally for one year. Since different carbon reduction technologies exist, this cost varies and needs to be considered in conjunction with the actual operational status of the technology. This includes, but is not limited to, water and electricity costs, maintenance fees, and upkeep costs. Furthermore, the cost of the same technology will vary from city to city due to differences in local prices.

[0158] (6) Energy savings C31

[0159] This indicator represents the energy savings generated by each carbon reduction technology applied to an actual engineering project and operating normally for one year. For standardized calculation, it is converted into electrical energy, with the unit being kWh. This indicator reflects the energy-saving benefits of each technology in each city. Due to different weather conditions in each city, the energy-saving benefits of the same technology will also differ, and specific calculations need to consider the actual situation of each city. This value is obtained using the building energy consumption simulation software DesignBuilder. First, the benchmark building is simulated for one cycle (one year) in a specific city's weather environment to obtain the benchmark building's energy consumption, which is then converted into electrical energy. Second, all technologies in the building application level technology menu library are applied to the benchmark building individually, and the building energy consumption is obtained again and converted into electrical energy. Subtracting the second energy consumption from the first energy consumption yields the electrical energy savings C31.

[0160] (7) Polluting C32

[0161] This indicator is qualitative, representing the degree of environmental pollution caused by the technology after its application to the target building. Some building carbon reduction technologies will have environmental impacts during operation, including emissions of harmful gases, carbon dioxide, excess water, excess heat, and light pollution, which may cause environmental pollution. Meanwhile, the natural environment has a certain self-regulating capacity to address these impacts. Therefore, the evaluation criteria are as follows: Excellent – ​​the technology has a negligible impact on the environment, with a value of 0.8; Good – long-term use will have a significant impact on the environment, with a value of 0.6; Poor – short-term use will have a significant impact on the environment, with a value of 0.3.

[0162] 2) Establish a hierarchical optimization model for building applications.

[0163] Based on the TOPSIS method, seven indicators were extracted from the building application level evaluation index system, and a building application level optimization model was established, as shown in Table 3 below.

[0164] Table 3 Optimization Model for Building Application Hierarchy

[0165]

[0166]

[0167] Here are some explanations of the indicators in the table:

[0168] (1) Indicator weights: According to the TOPSIS algorithm, the relative weight of each indicator needs to be determined. The weight of each indicator in the model represents the relative importance of the indicator.

[0169] (2) Data type: The data type of each indicator needs to be determined according to the TOPSIS algorithm, which can be divided into very large, very small, etc. Very large data means that the larger the value of the indicator, the higher the performance evaluation of the indicator; very small data means that the smaller the value of the indicator, the lower the performance evaluation of the indicator.

[0170] (3) Standardized score: This indicator is the final result calculated by the TOPSIS algorithm. It represents the score of each technology after considering 7 indicators (with weights). The higher the score, the higher the comprehensive value of the technology.

[0171] 3) Calculation process of building application level optimization model score

[0172] The following will use Harbin as an example to introduce the standardized score calculation process. Based on Table 3, after summarizing the preliminary values, the calculation is performed according to the following steps:

[0173] (1) Data forwarding

[0174] Based on the data type, the data of the 7 indicators were positiveized, that is, all of them were converted into extremely large data, resulting in a positiveized matrix, as shown in Table 4 below.

[0175] Table 4. Forwarding Matrix

[0176]

[0177]

[0178] (2) Data normalization

[0179] To eliminate the influence of different dimensions on the evaluation results and to compare the seven indicators under the same dimension system, the original data was normalized to obtain a standardized matrix, as shown in Table 5 below.

[0180] Table 5 Standardization Matrix

[0181]

[0182]

[0183] (3) Determine the optimal vector Z + and the worst vector Z -

[0184] Take the maximum normalized value and minimum normalized value of each indicator as Z. + Z - as follows:

[0185] Z + =(0.1878,0.1751,0.7886,0.1956,0.1925,0.2165,0.2720)

[0186] Z - =(0.0000,0.0000,-0.0289,0.0000,0.0000,0.0000,0.0000)

[0187] (4) Calculate the distance between each scheme and the ideal point. and the distance from the negative ideal point Combining the above optimal vector Z + and the worst vector Z - The distances between each technique and the positive and negative ideal solutions are determined, as shown in Table 6 below.

[0188] Table 6 shows the distance between each technique and the positive and negative ideal solutions.

[0189]

[0190]

[0191] (5) Calculate the overall similarity c between each scheme and the ideal scheme. i :

[0192] Combining the distances of the above schemes to the ideal point and the distance from the negative ideal point Determine the fit of each technology as shown in Table 7 below.

[0193] Table 7. Fit of Various Technologies

[0194]

[0195]

[0196] 4) Calculation results of the building application level optimization model

[0197] First, write the TOPSIS method code in MATLAB. Then, obtain the specific values ​​of the seven indicators for each technology in each city separately. Finally, substitute them into MATLAB for calculation. The results are shown in Table 8 below.

[0198] Table 8 Evaluation Scoring of Building Application-Level Carbon Reduction Technologies

[0199]

[0200]

[0201] Carbon reduction target hierarchy optimization

[0202] Optimizing carbon reduction target levels is a practical application problem. The first three levels of optimization address which technologies have the highest overall value at each level. This level of optimization addresses how to achieve the required energy-saving effects with the lowest possible investment cost under current building energy efficiency standards.

[0203] First, it is necessary to clarify the current building energy conservation standards. These standards include the "Guidelines for the Identification and Evaluation of Zero-Carbon Buildings" (T / CASE00-2021) and the "Technical Standard for Near-Zero Energy Buildings" (GB / T51350-2019). These two standards clearly define four energy conservation targets: ultra-low energy buildings, near-zero energy buildings, zero energy buildings, and zero-carbon buildings, and specify calculation formulas. Based on this, the concept of zero-carbon buildings is extended to include the concept of carbon reduction rate, which stipulates that a carbon reduction rate of 100% qualifies a building as zero-carbon. Using minimum investment as a constraint, six carbon reduction targets are derived: maximum carbon reduction rate within investment limit, minimum investment within carbon reduction rate limit, minimum investment for ultra-low energy buildings, minimum investment for near-zero energy buildings, minimum investment for zero energy buildings, and minimum investment for zero-carbon buildings.

[0204] Secondly, the mathematical approach to this problem is clarified. This problem can be abstracted into a typical "knapsack problem" in operations research. Therefore, the 0-1 integer linear programming method is chosen, and mathematical models are written for the above six carbon reduction targets. Substituting the initial data, the final result of the optimal carbon reduction target hierarchy is obtained.

[0205] Carbon emissions during the building's operation phase should be determined based on the different types of energy consumption and their carbon emission factors. The total carbon emissions (C) during the building's operation phase should be calculated using the following formula. All greenhouse gas emissions should be converted to carbon dioxide equivalents. This study specifies that all building carbon reduction technologies related to energy consumption should utilize electrical energy.

[0206]

[0207] In the formula, E 购入电，i —The carbon dioxide emissions generated by the electricity purchased by accounting unit i;

[0208] E 购入热，i —The carbon dioxide emissions generated by the purchase of heat by accounting unit i;

[0209] E 购入冷，i —The carbon dioxide emissions generated by the purchase of cooling capacity by accounting unit i;

[0210] E 购入气，i —The carbon dioxide emissions generated by the purchase of natural gas by accounting unit i.

[0211] The solar photovoltaic technology used in this invention generates self-produced green electricity, calculated using the following formula:

[0212] E 绿电，i =AD 绿电，i ×EF 电

[0213] In the formula, E 绿电，i —Calculate the carbon dioxide emissions generated by green electricity introduced or self-generated green electricity in accounting unit i;

[0214] AD 绿电，i —The internal computing unit i outputs power during the accounting period;

[0215] EF 电 —The annual average power supply emission factor of the regional power grid.

[0216] Based on the above analysis, the carbon reduction rate η in this study is defined as follows:

[0217]

[0218] In the formula, E 节省购入电,i —The carbon dioxide emissions generated by the purchased electricity saved in accounting unit i;

[0219] E 节省购入热,i —The amount of carbon dioxide emissions generated from the purchased heat saved by accounting unit i;

[0220] E 节省购入冷，i —The carbon dioxide emissions generated by the savings in purchased cooling capacity in accounting unit i;

[0221] E 节省购入气,i —The amount of carbon dioxide emissions saved by accounting unit i from the purchase of natural gas;

[0222] δ — The amount of carbon dioxide generated by the electricity consumed by the benchmark building.

[0223] (1) Mathematical model for maximizing carbon reduction rate based on investment limit

[0224] 1) Establish an investment limit vector matrix

[0225] The investment limit D is set as a vector matrix with 11 vectors, as detailed in Table 9:

[0226] Table 9 Investment Limit Matrix

[0227]

[0228]

[0229] 2) Establish the optimal evaluation matrix

[0230] For each city, an optimization set is established to optimize carbon reduction technology menus based on carbon reduction investment. Each technology is treated as an element, and each element has four indicators, which are presented as a vector (see Table 10 for details). Here, X is the introduced decision variable, taking only 0 or 1, where 0 indicates not selecting the technology and 1 indicates selecting it.

[0231] Table 10 Optimization Evaluation Matrix for Carbon Reduction Investment

[0232]

[0233] 3) Four-term vector matrix of each carbon reduction technology

[0234] The cost composition vector matrix of each technology: A = [a1, a2, ..., a n Let α be the total cost of the optimal combination of carbon reduction technologies.

[0235]

[0236] The vector matrix consisting of the amount of carbon dioxide generated from the electricity saved by each technology is: B = [b1, b2, ..., b n], where β is defined as the total reduction in carbon dioxide emissions resulting from the optimal combination of carbon reduction technologies.

[0237]

[0238] The carbon dioxide emissions from the self-generated green electricity of each technology are composed of a vector matrix: C = [c1, c2, ..., c n ], where γ is defined as the total amount of carbon dioxide reduced by generating green electricity from the optimal combination of carbon reduction technologies.

[0239]

[0240] 4) Constraints and Objective Function

[0241] Based on the zero-carbon building calculation formula, the objective function and constraint conditions are as follows:

[0242] Max(η)

[0243]

[0244] In the formula, η represents the carbon reduction rate.

[0245] 5) Solving the optimization model

[0246] By writing the above optimization code into Lingo, the optimal solution for the combination of carbon reduction technologies is obtained when the benchmark building meets each investment limit standard.

[0247] (2) Mathematical model for minimum investment in carbon reduction rate limit

[0248] 1) Establish a carbon reduction rate limit vector matrix

[0249] The carbon reduction rate limit E is set as a vector matrix with 11 vectors. The results are detailed in Table 11.

[0250] Table 11 Carbon Reduction Rate Quota Matrix

[0251]

[0252] 2) Establish the optimal evaluation matrix

[0253] Same as (1).

[0254] 3) Four-term vector matrix of each carbon reduction technology

[0255] Same as (1).

[0256] 4) Constraints and Objective Function

[0257] Based on the zero-carbon building calculation formula, the objective function and constraint conditions are as follows:

[0258] Min(α)

[0259]

[0260] In the formula, η is the carbon reduction rate;

[0261] α – The total cost of the optimal combination of carbon reduction technologies.

[0262] 5) Solving the optimization model

[0263] By writing the above optimization code into Lingo, the optimal solution for the combination of carbon reduction technologies is obtained when the benchmark building meets each carbon reduction rate limit standard.

[0264] (3) Optimization model for near-zero energy buildings

[0265] The Technical Standard for Near-Zero Energy Buildings (GB / T51350-2019) specifies the following energy efficiency indicators for near-zero energy public buildings, as shown in Table 12.

[0266] Table 12 Energy Efficiency Indicators for Near-Zero Energy Public Buildings

[0267]

[0268] I. The overall building energy efficiency rate is calculated using the following formula:

[0269]

[0270] In the formula: η p —Overall building energy efficiency;

[0271] E D —Comprehensive building energy consumption value for the designed building, kWh / m³ 2 ;

[0272] E R —Comprehensive building energy consumption of the benchmark building, kWh / m² 2 ;

[0273] 1) The comprehensive energy consumption of the designed building is calculated using the following formula:

[0274]

[0275] In the formula: E D —Design building energy consumption (kWh / (m³)) 2 ·a);

[0276] E E —Comprehensive building energy consumption excluding renewable energy generation, kWh / (m³) 2 ·a);

[0277] A – For residential buildings, the area refers to the usable floor area; for non-residential buildings, the area refers to the gross floor area (m²). 2 ;

[0278] f i —The energy conversion factor for type i energy is shown in Table 13;

[0279] E r , i —Annual generation of type i renewable energy electricity, in kWh;

[0280] E rd , i —Annual generation of type i renewable energy power generated in the surrounding area, in kWh.

[0281] Table 13 Energy Conversion Factors

[0282]

[0283]

[0284] 2) The comprehensive energy consumption of buildings that do not generate electricity from renewable energy sources should be calculated using the following formula:

[0285]

[0286] In the formula: E h —Annual energy consumption of the heating system, kWh;

[0287] E c —Annual energy consumption of the cooling system, kWh;

[0288] E l —Annual energy consumption of lighting system, kWh;

[0289] E w —Annual energy consumption of domestic hot water system, kWh;

[0290] E e —Annual energy consumption of elevator system, kWh.

[0291] 3) The calculation parameters for the comprehensive building energy consumption of the benchmark building are shown in Table 14-16:

[0292] Table 14 Internal Heating Settings for School Building Rooms, Personnel, Equipment, and Lighting

[0293]

[0294]

[0295] Table 15 Benchmark Building Window-to-Wall Area Ratio

[0296]

[0297] Table 16 Standard Building Heating and Cooling System Types

[0298]

[0299] II. The building's energy efficiency rate is calculated using the following formula (when calculating, the comprehensive building energy consumption value of the designed building should not include renewable energy power generation):

[0300]

[0301] In the formula: η e —Building energy efficiency;

[0302] E E —Comprehensive building energy consumption (kWh / m³) excluding renewable energy generation. 2 ;

[0303] E R —Comprehensive building energy consumption of the benchmark building, kWh / m² 2 .

[0304] III. The utilization rate of renewable energy should be calculated according to the following formula:

[0305]

[0306] Where: REP p —Renewable energy utilization rate, %;

[0307] EP h —Renewable energy utilization in the heating system, kWh;

[0308] EP c —Renewable energy utilization in the cooling system, kWh;

[0309] EP w —Renewable energy utilization in domestic hot water systems, kWh;

[0310] Q h —Annual heating consumption, kWh;

[0311] Q c —Annual cooling capacity, kWh;

[0312] Q w —Annual domestic hot water consumption, kWh.

[0313] According to the regulations, two basic parameters need to be specified for benchmark buildings in each city. First, the comprehensive energy consumption value (ER) of the benchmark building; second, the total energy consumption value (AE) per unit area of ​​the benchmark building.

[0314] For the carbon reduction technology menu library, a corresponding optimization set is established, with each technology as one element and each element having four indicators as a vector, as detailed in Table 17.

[0315] Table 17 Optimization Evaluation Matrix for Near-Zero Energy Buildings

[0316]

[0317] The cost composition vector matrix of various carbon reduction technologies: A = [a1, a2, ..., a n Let α be the total cost of the optimal combination of carbon reduction technologies.

[0318]

[0319] The energy savings per unit area of ​​each carbon reduction technology are composed of a vector matrix: G = [g1, g2, ..., g n ], where ε is defined as the total energy saving per unit area of ​​the optimal combination of carbon reduction technologies.

[0320]

[0321] The vector matrix of electricity generation per unit area for each carbon reduction technology is: H = [h1, h2, ..., h n ], where ζ is defined as the total electricity generated per unit area of ​​the optimal combination of carbon reduction technologies.

[0322]

[0323] Based on the calculation formula for near-zero energy buildings, the objective function and constraint conditions are obtained, and the optimization model is constructed as follows:

[0324] Min(α)

[0325]

[0326] In the formula, η e规范 —Standardized values ​​for building energy efficiency;

[0327] f 电力 —The energy conversion factor for electrical energy is taken as 2.6;

[0328] By writing the above optimization code into Lingo, we obtain the optimal solution that minimizes the cost of the carbon reduction technology combination when the benchmark building meets the near-zero energy building standard.

[0329] (4) Optimization model for ultra-low energy consumption buildings

[0330] The Technical Standard for Near-Zero Energy Buildings (GB / T51350-2019) stipulates the following standards for ultra-low energy buildings, as shown in Table 18.

[0331] Table 18 Energy Efficiency Indicators for Ultra-Low Energy Public Buildings

[0332]

[0333] The relevant parameter matrix of the benchmark building, the optimization evaluation matrix, and the four-element vector matrix of each carbon reduction technology are all the same as (3). Based on the calculation formula of ultra-low energy consumption building, the objective function and constraint condition are obtained, and the optimization model is constructed as follows:

[0334] Min(α)

[0335]

[0336] In the formula, η e规范 —Standardized values ​​for building energy efficiency;

[0337] f 电力 —The energy conversion factor for electrical energy is taken as 2.6.

[0338] By writing the above optimization code into Lingo, we obtain the optimal solution that minimizes the cost of the carbon reduction technology combination when the benchmark building meets the ultra-low energy consumption building standard.

[0339] (5) Zero-energy building optimization model

[0340] The "Technical Standard for Near-Zero Energy Buildings" (GB / T51350-2019) specifies the following energy efficiency indicators for zero-energy public buildings, as shown in Table 19.

[0341] Table 19 Energy Efficiency Indicators for Zero-Energy Public Buildings

[0342]

[0343] 1) The relevant parameter matrix of the benchmark building, the optimization evaluation matrix, and the four-term vector matrix of each carbon reduction technology are all the same as (3). Based on the calculation formula of zero-energy building, the objective function and constraint condition are obtained, and the optimization model is constructed as follows:

[0344] Min(α)

[0345]

[0346] In the formula, η e规范 —Standardized values ​​for building energy efficiency.

[0347] f 电力 —The energy conversion factor for electrical energy is taken as 2.6;

[0348] 5) Solving the optimization model

[0349] By writing the above optimization code into Lingo, we obtain the optimal solution that minimizes the cost of the carbon reduction technology combination when the benchmark building meets the zero-energy building standard.

[0350] (6) Zero-carbon building optimization model

[0351] The reference basis is consistent with the carbon reduction investment optimization model.

[0352] Based on the zero-carbon building calculation formula, the objective function and constraint conditions are obtained, and the optimization model is constructed as follows:

[0353] Min(α)

[0354]

[0355] In the formula, α represents the total cost of the optimal combination of carbon reduction technologies;

[0356] δ—The amount of carbon dioxide generated by the electricity consumed by the benchmark building;

[0357] β – The total reduction in carbon dioxide emissions resulting from the optimal combination of carbon reduction technologies;

[0358] γ—The total amount of carbon dioxide reduced by the optimal combination of carbon reduction technologies that generate green electricity.

[0359] By writing the above optimization code into Lingo, we obtain the optimal solution that minimizes the cost of the carbon reduction technology combination when the benchmark building meets the zero-carbon building standard.

[0360] This invention integrates existing research on building carbon reduction technology optimization and national building energy conservation codes and standards, summarizes the methods for optimizing building carbon reduction technologies, and ultimately determines the optimization indicators for building carbon reduction technologies corresponding to different application objects and the carbon reduction targets that meet the standards, providing a theoretical basis for the construction of the optimization model. Furthermore, the research adopts a problem decomposition approach, gradually narrowing the evaluation scope from macro to micro, breaking down the complex problem of "technology optimization" into several optimization problems. It clarifies the multiple evaluation objects involved in the carbon reduction technology optimization process, including cities, neighborhoods, target buildings, and carbon reduction targets, and determines the optimization problem type based on the evaluation objects, selecting appropriate mathematical algorithms for the construction of the optimization model. It integrates existing research related to carbon reduction technology development and constructs a comprehensive and diverse technology menu library based on the characteristics of carbon reduction technologies themselves. The optimization models at each level are established according to a logic of progressively narrowing scope and mutual complementarity, forming a complete optimization model. This optimization model involves a wide range of technologies, comprehensive evaluation objects and perspectives, and the obtained optimization results have a certain degree of scientific validity and universality.

[0361] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any transformations or substitutions that can be conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A multi-level, multi-dimensional method for selecting building carbon reduction technologies, characterized in that, The method includes the following steps: Step 1: Establish a menu library of carbon reduction technologies; Step 2: Construct an optimal carbon reduction technology model; Step 3: Select carbon reduction technologies based on the carbon reduction technology optimization model constructed in Step 2.

2. The method for selecting multi-level, multi-dimensional building carbon reduction technologies as described in claim 1, characterized in that, The method for constructing the carbon reduction technology menu library in step 1 is as follows: First, all carbon reduction technologies are classified according to the building life cycle. Then, they are classified a second time according to the logic of technical characteristics. Finally, they are classified a third time according to the logic of independent and mutually exclusive classification.

3. The method for selecting multi-level, multi-dimensional building carbon reduction technologies as described in claim 1, characterized in that, The carbon reduction technology optimization model in step 2 includes a city zoning level optimization model, a building block level optimization model, a building application level optimization model, and a carbon reduction target level optimization model.

4. The method for selecting multi-level, multi-dimensional building carbon reduction technologies as described in claim 3, characterized in that, The city zoning hierarchical optimization model is established based on fuzzy comprehensive analysis. It uses technical applicability, cost-effectiveness, and carbon reduction and environmental protection as the first-level evaluation indicators to comprehensively evaluate each carbon reduction technology in the first technology menu library. The technical applicability indicators are further refined into three secondary indicators: technical reliability, technical implementability, and technical maintainability; The evaluation level of technical reliability is divided into three levels: excellent, good, and poor. The standards are as follows: excellent means that it has national standards; good means that it has local standards but no national standards; poor means that it has no standards. The evaluation level of technical feasibility is divided into three levels: excellent, good, and poor. The evaluation criteria are based on the natural environment and climate characteristics of the implementing city and are determined by expert knowledge. The evaluation level of technical maintainability is divided into three levels: excellent, good, and poor. The evaluation criteria are based on the resource conditions of the city where the maintenance and operation are implemented and are determined by expert knowledge. The aforementioned cost-related indicators are further refined into a second-level indicator: economic matching. The evaluation level of economic matching is divided into three levels: excellent, good, and poor, with the following standards: excellent represents that the per capita GDP of the city's province ranks in the top 1 / 3 of the country; good represents that the per capita GDP of the city's province ranks in the middle 1 / 3 of the country; and poor represents that the per capita GDP of the city's province ranks in the bottom 1 / 3 of the country. The carbon reduction and environmental protection indicators are further refined into two secondary indicators: technological carbon reduction and environmental pollution. The evaluation level of carbon reduction technology is divided into three levels: excellent, good, and poor. The standards are as follows: excellent represents the top 1 / 3 of buildings with the best technology in terms of total energy consumption reduction; good represents the middle 1 / 3 of buildings with the best technology in terms of total energy consumption reduction; and poor represents the bottom 1 / 3 of buildings with the best technology in terms of total energy consumption reduction. The environmental pollution level is divided into three levels: excellent, good, and poor. The standards are as follows: excellent means that the technology has no impact on the environment; good means that the use beyond the set time limit will have an impact on the environment; poor means that the use within the set time limit will have an impact on the environment.

5. The method for selecting multi-level, multi-dimensional building carbon reduction technologies as described in claim 3, characterized in that, The construction of the building block hierarchy optimization model includes: modeling the target building and its surrounding buildings in the energy consumption simulation software DesignBuilder to form a building block; performing energy consumption simulation on the target building in the environment of the building block; and using the energy consumption simulation results as evaluation indicators to evaluate each carbon reduction technology in the second technology menu library.

6. The method for selecting multi-level, multi-dimensional building carbon reduction technologies as described in claim 3, characterized in that, The building application hierarchy optimization model is established based on the multi-objective decision analysis method TOPSIS. It uses application indicators, technical indicators, and environmental indicators as the first-level evaluation indicators to comprehensively evaluate each carbon reduction technology in the second technology menu library. The applicability indicators are further refined into three second-level indicators: completeness, feasibility, and maintainability; The evaluation level of completeness is divided into three levels: excellent, good, and poor. The standards are as follows: excellent means that it has national-level standards; good means that it has local-level standards but no national-level standards; poor means that it has no standards at all. The feasibility evaluation level is divided into three levels: excellent, good, and poor. The evaluation criteria are based on the natural environment and climate characteristics of the implementing city and are determined according to expert knowledge. The maintenance performance evaluation is divided into three levels: excellent, good, and poor. The evaluation criteria are based on the resource conditions of the city implementing the maintenance and operation, and are determined according to expert knowledge. The technical indicators are further subdivided into two secondary indicators: equipment purchase cost and maintenance and operation cost; The environmental indicators are further subdivided into two secondary indicators: energy savings and pollution level. The pollution level is divided into three levels: excellent, good, and poor. The standards are as follows: excellent means that the technology has no impact on the environment; good means that the use beyond the set time limit will have an impact on the environment; and poor means that the use within the set time limit will have an impact on the environment.

7. The method for selecting multi-level, multi-dimensional building carbon reduction technologies as described in claim 3, characterized in that, The carbon reduction target hierarchy optimization model includes five optimized models: a carbon reduction investment optimization model, an ultra-low energy consumption optimization model, a near-zero energy consumption building optimization model, a zero energy consumption building optimization model, and a zero carbon building optimization model, constructed using a 0-1 integer programming algorithm, based on building energy conservation standards and when the target building meets the carbon reduction rate limit, ultra-low energy consumption building, near-zero energy consumption building, zero energy consumption building, and zero carbon building standards.

8. The method for selecting multi-level, multi-dimensional building carbon reduction technologies as described in claim 7, characterized in that, The carbon reduction investment optimization model includes two types: the model that maximizes the carbon reduction rate within the investment limit and the model that minimizes the investment within the carbon reduction rate limit. Specifically: Max(η) Among them, carbon reduction rate E 节省购入电,i The carbon dioxide emissions generated by the savings in purchased electricity for accounting unit i in the target building; E 节省购入热,i The carbon dioxide emissions generated by the savings in purchased heat for accounting unit i in the target building; E 节省购入冷 , i The carbon dioxide emissions generated by the savings in purchased cooling capacity for accounting unit i in the target building; E 节省购入气,i The carbon dioxide emissions saved by purchasing natural gas in accounting unit i of the target building; δ is the carbon dioxide emissions generated by electricity consumption in the target building; α is the combined cost of carbon reduction technologies; D = {d j } represents the investment limit matrix; x i Let i be the decision variable representing whether carbon reduction technology i is selected. Min(α) Where, E = {e k } represents the carbon reduction rate limit matrix; The ultra-low energy consumption optimization model is specifically as follows: Min(α) Where, η e规范 The target building's energy efficiency rating is the specified value; f 电力 ε is the energy conversion factor for electricity, ε is the total electricity savings per unit area of ​​the optimal combination of carbon reduction technologies, ζ is the total electricity generation per unit area of ​​the optimal combination of carbon reduction technologies, and ER is the comprehensive building energy consumption value of the benchmark building. The near-zero energy building optimization model is as follows: Min(α) The specific optimization model for the zero-energy building is as follows: Min(α) Where AE is the total energy consumption per unit area of ​​the benchmark building, a i Cost of carbon reduction technology i; The zero-carbon building optimization model is specifically as follows: Min(α) Where δ represents the amount of carbon dioxide generated by the electricity consumed by the baseline building; β represents the total reduction in carbon dioxide emissions from the optimal combination of carbon reduction technologies; and γ represents the total reduction in carbon dioxide emissions from the generation of green electricity from the optimal combination of carbon reduction technologies.

9. The method for selecting multi-level, multi-dimensional building carbon reduction technologies as described in claim 3, characterized in that, Step 3 specifically involves: Based on the city zoning hierarchical optimization model, select from the carbon reduction technology menu library to obtain the first selection result; Based on the building block hierarchy optimization model, a second selection result is obtained by selecting from the first selection result; Based on the building application hierarchical optimization model, a third selection result is obtained by selecting from the second selection result; Based on the carbon reduction target hierarchy optimization model, the final carbon reduction technology selection result is obtained by selecting from the third selection result.

10. A multi-level, multi-dimensional building carbon reduction technology selection device, characterized in that, include: Database unit, used to create a menu library of carbon reduction technologies; Model building unit, used to build optimal models for carbon reduction technologies; The selection unit is used to select carbon reduction technologies based on the carbon reduction technology optimization model.

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