Building energy-saving design method and system

Abstract

The invention discloses a building energy-saving design method and system, and relates to the technical field of building design, the system can accurately calculate the total heat transfer loss, the natural lighting amount and the equipment energy efficiency coefficient by building a building model in detail and extracting energy consumption data, and then the total energy consumption of a building is obtained. In the process, a heat loss algorithm formula, a natural lighting algorithm formula and an equipment energy efficiency algorithm formula are used, the total heat transfer loss Zcd, the natural lighting quantity Zrc and the equipment energy efficiency coefficient Jnx are calculated and obtained, the total energy consumption Zhnx of the building is calculated and obtained in an associated mode, and the accuracy of energy consumption data is ensured. The system can preliminarily compare the obtained total energy consumption Zhnx of the building with a preset energy consumption threshold value F1 of the building, and in this way, the abnormal phenomenon of energy consumption can be quickly distinguished and preliminarily evaluated. This not only increases the rate of energy-saving analysis, but also improves the performance of architectural design in terms of energy saving.

Description

Technical Field

[0001] The invention relates to the technical field of building design, and in particular to a building energy-saving design method and system. Background Art

[0002] BIM building information modeling technology is widely used in architectural design. Its main advantage is that it can build a three-dimensional digital model that contains geometric, physical and functional information of the building, and integrate it together to provide us with a platform for collaboration. Using this platform, we can integrate the BIM model with energy consumption simulation software to conduct in-depth analysis and estimation of the building's energy consumption. We can select the most effective energy-saving strategy after comparing the energy consumption feedback of various design solutions.

[0003] In the Chinese invention application with application publication number CN113204827B, a BIM-based building energy-saving design method and system are disclosed. A virtual three-dimensional model is established according to the actual external dimensions of the existing building; an airflow rising path is generated according to the positions of the fire passage, ventilation shaft, public position door leaf and public position window leaf, and the two ends of the airflow rising path have different heights; each airflow rising path is visualized in the virtual three-dimensional model, and the overlapping areas between each airflow rising path are marked; and an energy-saving facility setting plan is generated according to the distribution of the overlapping areas. The present invention analyzes the indoor gas flow direction of the existing building, sets the corresponding cooling points, so that a continuous gas flow path is formed in the building, and improves the energy saving of the existing building by additional means, reduces energy consumption, and can be applied to new or renovated projects, with strong practicality.

[0004] In combination with the prior art, the above application still has the following deficiencies: At the current stage, we usually set energy consumption optimization plans for traditional buildings based on experience, which makes the plan lack of systematicity and scientificity, thus affecting its optimization effect and making it difficult to fully realize the energy-saving potential of buildings. These problems increase the complexity and cost of the building design process, and may also cause the actual energy consumption of the building to exceed expectations. In addition, the existing energy consumption evaluation method is mainly static and does not take into account the dynamic energy consumption changes of buildings in various use environments. Therefore, its efficiency in achieving the preset energy-saving goals is low, which in turn affects the overall energy efficiency and life of the building. Summary of the invention

[0005] In view of the deficiencies in the prior art, the present invention provides a building energy-saving design method and system, which solves the problems mentioned in the background technology.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: including a building simulation data extraction module, an energy consumption simulation module, a total energy consumption evaluation module, an energy-saving optimization module and a design optimization module; The building simulation data extraction module is used to construct a building model using BIM modeling software, extract energy consumption data and energy-saving data of the building model, and pre-process the extracted energy consumption data; The energy consumption simulation module is used to input the constructed BIM building model into the energy consumption simulation software for energy consumption simulation, and calculate the total heat transfer loss Zcd, natural light amount Zrc and equipment energy efficiency coefficient Jnx of the current BIM building model by constructing heat loss algorithm formula, natural light algorithm formula and equipment energy efficiency algorithm formula, and then perform summary calculation to obtain the total building energy consumption Zhnx; The total energy consumption evaluation module is used to compare and evaluate the preset building energy consumption threshold F1 with the acquired building total energy consumption Zhnx, and analyze the energy-saving effect of the current building; The energy-saving optimization module is used to be triggered when abnormal energy consumption of the current building is detected. The optimization objective function formula is constructed by combining the actual energy consumption and the optimization effect, and the optimized energy consumption coefficient Yhnh is calculated based on the acquired energy-saving data; The design optimization module is used to perform a secondary comparative evaluation and analysis on the obtained optimized energy consumption coefficient Yhnh and the preset building energy consumption threshold F1, and then calculate the energy consumption of the building after energy-saving optimization. When the energy consumption of the building after energy-saving optimization is evaluated to be abnormal, the design scheme of the current building is further optimized by adopting a genetic algorithm.

[0007] Preferably, the building simulation data extraction module includes a BIM modeling unit and a data extraction unit; The BIM modeling unit is used to draw a three-dimensional model of the building according to the planning blueprint of the current building using BIM modeling software at the same scale as the planning blueprint, and add building components to the three-dimensional model, design the HVAC system, install electrical equipment, define building materials, configure equipment parameters and set building environmental parameters, and then generate an energy consumption analysis diagram of the building, including cooling load, heating load and lighting requirements, to construct a BIM building model; The adding of building components includes adding doors, windows, stairs and elevator building elements; The design of the HVAC system includes adding equipment such as air conditioning, adding a heating system, and adding a ventilation system; The installation of electrical equipment includes adding electrical facilities such as lighting, power sockets and distribution boards; Defining building materials includes setting material properties of building elements such as walls, floors, roofs, etc., such as thermal conductivity, thickness, etc.; The configuration equipment parameters include setting the model, specification and energy efficiency ratio of air conditioning and heating equipment; The setting of building environmental parameters includes indoor temperature, outdoor temperature, air specific heat capacity and light intensity; The data extraction unit is used to extract the energy consumption data and energy-saving data of the constructed BIM building model in real time according to the Revit cloud analysis service tool in the BIM modeling software, and perform data preprocessing on the extracted energy consumption data and energy-saving data, wherein the preprocessing method includes checking and processing abnormal values ​​in the data, unifying the data format, and converting the data into a data format suitable for the optimization algorithm; The energy consumption data includes heat transfer data, lighting data and building equipment energy efficiency data; The heat transfer data include wall heat transfer coefficient Cr, total wall surface area Cq, window heat transfer coefficient Cc, simulated indoor temperature Cs and simulated outdoor temperature Cw; The lighting data include solar radiation intensity Gt, total window area Gh, window stained glass transmittance Gs and building ground area Gd; The building equipment energy efficiency data includes equipment cooling capacity Sl, equipment heating capacity Sr and equipment input power Ss; The energy-saving data include ventilation frequency Jh, building volume Jv and air specific heat capacity Jb.

[0008] Preferably, the energy consumption simulation module includes an energy consumption simulation unit, an energy consumption calculation unit and an energy consumption comprehensive calculation unit; The energy consumption simulation unit is used to import the constructed BIM building model into EnergyPlus, and based on the open source tool of EnergyPlus, provides an intuitive user interface for building energy consumption modeling and analysis, and constructs heat loss algorithm formula, natural lighting algorithm formula and equipment energy efficiency algorithm formula to analyze the energy consumption related parameters of the building; The energy consumption calculation unit includes a building heat transfer loss calculation unit, a building natural lighting calculation unit and an equipment energy efficiency calculation unit; The building heat transfer loss calculation unit is used to load the heat transfer data extracted in real time according to the constructed heat loss algorithm formula, calculate and obtain the total heat transfer loss Zcd, and analyze and simulate the thermal conductivity performance of the building walls and windows; The total heat transfer loss Zcd is obtained by the following algorithm formula: ; Where dCq represents a small area element on the exterior surface of the building, which is used to integrate the total heat transfer loss, and Cq+Gh represents the boundary of the exterior surface area of ​​the building, which refers to the total surface of the building's exterior walls and windows.

[0009] Preferably, the building natural lighting calculation unit is used to calculate and obtain the natural lighting quantity Zrc according to the constructed natural lighting algorithm formula, and load the real-time extracted lighting data, and analyze the natural lighting of the simulated building in different time periods of a day; The natural light amount Zrc is obtained by the following algorithm formula: ; In the formula, T represents the time interval, It represents the transmittance of window glass. Its specific parameters are set by the user during BIM modeling. dt represents the time integral.

[0010] Preferably, the equipment energy efficiency calculation unit is used to calculate and obtain the equipment energy efficiency coefficient Jnx according to the constructed equipment energy efficiency algorithm formula, and load the real-time extracted building equipment energy efficiency data, and analyze the energy consumption of building equipment in different time periods; The equipment energy efficiency coefficient Jnx is obtained by the following algorithm formula; ; Where Sl i (t) represents the cooling capacity of the simulated equipment of the i-th equipment at time t, C cooling represents the cooling load factor, Ss i Indicates the device input power Ss, Sr of the simulated i-th device i (t) represents the heating capacity of the simulated i-th device at time t; The energy consumption comprehensive calculation unit is used to process the obtained total heat transfer loss Zcd, natural light amount Zrc and equipment energy efficiency coefficient Jnx dimensionlessly, and then calculate and obtain the total energy consumption Zhnx of the building, and summarize and calculate the total energy consumption of the simulated building within a certain period of time; The total building energy consumption Zhnx is obtained by the following algorithm formula; ; Wherein, a1, a2 and a3 represent the preset weight values ​​of total heat transfer loss Zcd, natural light amount Zrc and equipment energy efficiency coefficient Jnx respectively, and a1+a2+a3=1, and the specific parameters are set by the user.

[0011] Preferably, the total energy consumption evaluation module is used to preset the building energy consumption threshold F1 according to the energy consumption index, and make a preliminary comparative evaluation with the acquired building total energy consumption Zhnx, and analyze the total energy consumption of the building within a certain period of time. The specific evaluation scheme is as follows; When the total building energy consumption Zhnx> the building energy consumption threshold F1, it means that the total energy consumption of the current simulated building design is abnormal, and further design is performed at this time; When the total building energy consumption Zhnx ≤ the building energy consumption threshold F1, it means that the total energy consumption of the current simulated building design is normal and no optimization is required.

[0012] Preferably, the energy-saving optimization module includes an optimization objective function unit and an optimization evaluation unit; The optimization objective function unit is used to re-evaluate the building total energy consumption Zhnx when it is triggered by an abnormality, further use the optimization objective function, construct the optimization objective function formula, load the extracted energy-saving data into the objective function formula, and calculate to obtain the optimization energy consumption coefficient Yhnh; The optimized energy consumption coefficient Yhnh is obtained by the following algorithm formula; ; In the formula, lq represents cooling energy consumption, the energy consumption of the air conditioning system, which is calculated by the equipment cooling capacity Sl and the equipment energy efficiency Jnx; qn represents heating energy consumption, the energy consumption of the heating system, which is calculated by the equipment heat and energy efficiency ratio. Indicates the preset weight value of ventilation energy consumption, represents the preset weight value of cooling energy consumption lq and heating energy consumption qn, represents the energy-saving optimization coefficient, which is calculated through simulation and experimental data, Jb(t) represents the air specific heat capacity Jb at time t, dt represents the time integral variable, It represents ventilation energy consumption. The meaning of the formula is: by calculating the total energy consumption of the building after optimization measures, combining the actual energy consumption and optimization effect, it helps to evaluate the actual effect of energy-saving measures, and finds the design solution with the best energy efficiency by minimizing the optimization objective function.

[0013] Preferably, the optimization evaluation unit is used to perform a secondary comparative evaluation based on the obtained optimized energy consumption coefficient Yhnh and the preset building energy consumption threshold F1, and further analyze the energy consumption of the currently designed building after energy saving optimization. The specific evaluation scheme is as follows; When the optimized energy consumption coefficient Yhnh> the building energy consumption threshold F1, it means that the energy consumption effect of the currently designed building model after optimization is still abnormal. In this case, the building design is further optimized. When the optimized energy consumption coefficient Yhnh ≤ the building energy consumption threshold F1, it means that the energy consumption effect of the currently designed building model reaches normal after optimization, and the optimization is completed.

[0014] Preferably, the design optimization module is used to use a genetic algorithm GA to calculate and obtain the design optimization index f when the energy consumption of the simulated building is still abnormal after the energy consumption is optimized. Minimize (x) Optimize the design of the simulated building, adjust the building's basic structure, materials and energy-consuming equipment, and re-establish the BIM building model for specific analysis after the adjustment; The design optimization index f Minimize (x) is obtained through the following algorithm formula; ; Where Minimize represents the value of the optimized objective function, ObjectiveFunction represents the objective function, which is a mathematical function used to evaluate the quality of a design scheme, and xi represents the variable for optimizing the i-th objective, including but not limited to the location of doors and windows, the surface area of ​​doors and windows, the thickness of insulation materials, and the selection of energy-consuming equipment.

[0015] A building energy-saving design method comprises the following steps: S1. First, use BIM modeling software to create a three-dimensional model of the building according to the current building planning blueprint, add relevant parameters and equipment of the building model, and use Revit's cloud analysis service tool to extract energy consumption data and energy-saving data from the constructed BIM building model in real time, and then perform preprocessing after extraction; S2. Import the constructed BIM building model into EnergyPlus, conduct building energy consumption modeling and analysis through an intuitive user interface, construct an algorithm formula, and calculate the total heat transfer loss Zcd, natural light volume Zrc and equipment energy efficiency coefficient Jnx based on the real-time extracted energy consumption data, and perform related calculations to obtain the total building energy consumption Zhnx; S3, compare and evaluate the preset building energy consumption threshold F1 with the obtained total building energy consumption Zhnx, and analyze the energy-saving effect of the current building; S4. When abnormal energy consumption of the current building is detected, the optimization objective function formula is constructed by combining the actual energy consumption and the optimization effect, and the optimized energy consumption coefficient Yhnh is calculated based on the energy-saving data obtained, and the obtained optimized energy consumption coefficient Yhnh is evaluated again with the preset building energy consumption threshold F1 to analyze the energy consumption after optimization; S5. Finally, if the building energy-saving optimization effect is still abnormal, the genetic algorithm GA is further used for design optimization to obtain the design optimization index f Minimize (x) Optimize the design of the building, adjust the building design, and re-establish the BIM building model to conduct energy consumption analysis.

[0016] The present invention provides a building energy-saving design method and system. It has the following beneficial effects: (1) By constructing a detailed building model and extracting energy consumption data, the system can accurately calculate the total heat transfer loss, natural light and equipment energy efficiency coefficient, and then obtain the total energy consumption of the building. In this process, the heat loss algorithm, natural light algorithm and equipment energy efficiency algorithm formula are used to calculate the total heat transfer loss Zcd, natural light Zrc and equipment energy efficiency coefficient Jnx, and the total energy consumption Zhnx of the building is obtained by correlation calculation, ensuring the accuracy of the energy consumption data. The system can make a preliminary comparison between the total energy consumption Zhnx of the building and the preset building energy consumption threshold F1, so as to efficiently identify energy consumption abnormalities and make preliminary evaluations. This method not only improves the efficiency of energy-saving analysis, but also optimizes the energy-saving performance of building design, providing designers with a reliable data basis, thereby achieving efficient energy consumption analysis and optimization effects.

[0017] (2) The system can comprehensively and systematically construct a three-dimensional model of a building through the various functions in the building simulation data extraction module, such as adding building components, HVAC system design, electrical equipment installation, and building material definition. The module can also generate building energy consumption analysis diagrams that detail key data such as cooling load, heating load, and lighting demand. These functions, combined with the open source tools of EnergyPlus, can perform detailed energy consumption simulation analysis, including simulation of heat transfer, lighting, and equipment energy efficiency. Through multi-dimensional energy consumption data analysis, the system can fully support building energy-saving design work and provide designers with a complete energy-saving design tool to help optimize various aspects of building design and improve the comprehensiveness and accuracy of building energy-saving design.

[0018] (3) With the support of energy-saving optimization module and design optimization module, this system can not only detect abnormal building energy consumption, but also use optimization objective function and genetic algorithm for intelligent design optimization. Through in-depth analysis of energy-saving data, the system constructs the optimization objective function formula to calculate the optimized energy consumption coefficient Yhnh, and conducts secondary evaluation based on the optimized energy consumption coefficient Yhnh and the building energy consumption threshold F1. When the energy consumption after optimization is still abnormal, the system can use genetic algorithm to further optimize the design scheme. This process includes adjusting the building's basic structure, material selection, HVAC system and other energy-consuming equipment configuration, and then conducting specific energy consumption analysis in the BIM model. This intelligent optimization process can not only effectively solve the problem of abnormal energy consumption, but also help designers continuously improve the building design plan to ensure that the building design achieves the best effect in energy saving, thereby improving the intelligence level and sustainability of building design. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 A schematic diagram of a building energy-saving design system flow chart of the present invention; Figure 2The present invention is a schematic diagram of the steps of a building energy-saving design method. DETAILED DESCRIPTION

[0020] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0021] Example 1 See also Figure 1 The present invention provides a building energy-saving design system. To achieve the above purpose, the present invention is implemented through the following technical solutions: including a building simulation data extraction module, an energy consumption simulation module, a total energy consumption evaluation module, an energy-saving optimization module and a design optimization module; The building simulation data extraction module is used to construct a building model using BIM modeling software, extract energy consumption data and energy-saving data of the building model, and pre-process the extracted energy consumption data; The energy consumption simulation module is used to input the constructed BIM building model into the energy consumption simulation software for energy consumption simulation, and calculate the total heat transfer loss Zcd, natural light amount Zrc and equipment energy efficiency coefficient Jnx of the current BIM building model by constructing heat loss algorithm formula, natural light algorithm formula and equipment energy efficiency algorithm formula, and then perform summary calculation to obtain the total building energy consumption Zhnx; The total energy consumption evaluation module is used to compare and evaluate the preset building energy consumption threshold F1 with the acquired total building energy consumption Zhnx, and analyze the energy-saving effect of the current building; The energy-saving optimization module is used to be triggered when abnormal energy consumption of the current building is detected. The optimization objective function formula is constructed by combining the actual energy consumption and the optimization effect, and the optimized energy consumption coefficient Yhnh is calculated based on the energy-saving data obtained; The design optimization module is used to conduct a secondary comparative evaluation and analysis of the obtained optimized energy consumption coefficient Yhnh and the preset building energy consumption threshold F1, and then evaluate the energy consumption of the building after energy-saving optimization. When the energy consumption of the building after energy-saving optimization is evaluated to be abnormal, the design scheme of the current building is further optimized by using a genetic algorithm.

[0022] In this embodiment, the system uses the BIM modeling software to accurately construct the building model through the building simulation data extraction module, and extracts and preprocesses the energy consumption data, providing an accurate data basis for subsequent energy consumption simulation. Next, the energy consumption simulation module uses simulation tools and algorithms to perform a comprehensive energy consumption calculation on the building model, obtain the total heat transfer loss Zcd, the amount of natural light Zrc and the equipment energy efficiency coefficient Jnx, and perform related calculations to obtain the total building energy consumption Zhnx, and then compare and evaluate the obtained total building energy consumption Zhnx with the preset building energy consumption threshold F1 to analyze the energy-saving effect of the current building. This process significantly improves the accuracy and efficiency of energy consumption analysis compared with traditional methods. When the energy consumption is abnormal, the energy-saving optimization module constructs an optimization objective function formula and calculates the optimized energy consumption coefficient Yhnh. Finally, if the energy-saving optimization effect of the building is still abnormal, the genetic algorithm GA is further used for design optimization to obtain the design optimization index f Minimize (x) Optimize the design scheme of the building, adjust the building design scheme, and re-establish the BIM building model to conduct energy consumption analysis. Compared with traditional design methods, this module has higher intelligence and operability in energy-saving effect evaluation and adjustment. In the energy-saving optimization process, the design optimization module uses genetic algorithms to intelligently optimize the building design and adjust the structure, materials and energy-consuming equipment of the building design scheme. Compared with traditional manual adjustment methods, this method provides a more efficient and flexible design optimization method, which can find the best energy-saving design scheme in a shorter time and achieve sustainable improvement of building design. Overall, this system has significantly improved the accuracy, efficiency and sustainability of building energy-saving design by integrating BIM technology with energy consumption simulation and optimization algorithms, bringing significant technological progress to the field of building energy-saving design.

[0023] Example 2 This embodiment is explained in Example 1, please refer to Figure 1 ,Specifically: the building simulation data extraction module includes a BIM modeling unit and a data extraction unit; The BIM modeling unit is used to draw a three-dimensional model of the building according to the current building planning blueprint using BIM modeling software at the same scale as the planning blueprint, and to add building components to the three-dimensional model, design the HVAC system, install electrical equipment, define building materials, configure equipment parameters and set building environmental parameters, and then generate an energy consumption analysis diagram of the building, including cooling load, heating load and lighting requirements, to construct a BIM building model; Adding building components includes adding doors, windows, stairs and elevator building elements; Designing an HVAC system includes equipment such as adding air conditioning, adding heating systems, and adding ventilation systems; Installing electrical equipment includes adding electrical features such as lighting, electrical outlets, and distribution boards; Defining building materials includes setting material properties of building elements such as walls, floors, roofs, etc., such as thermal conductivity, thickness, etc. Configuring equipment parameters includes setting the model, specification and energy efficiency ratio of air conditioning and heating equipment; Setting building environmental parameters including indoor temperature, outdoor temperature, air specific heat capacity and light intensity; The data extraction unit is used to extract the energy consumption data and energy-saving data of the constructed BIM building model in real time according to the Revit cloud analysis service tool in the BIM modeling software, and perform data preprocessing on the extracted energy consumption data and energy-saving data. The preprocessing method includes checking and processing abnormal values ​​in the data, unifying the data format, and converting the data into a data format suitable for the optimization algorithm; Energy consumption data includes heat transfer data, lighting data, and building equipment energy efficiency data; The heat transfer data include wall heat transfer coefficient Cr, total wall surface area Cq, window heat transfer coefficient Cc, simulated indoor temperature Cs and simulated outdoor temperature Cw; The lighting data include solar radiation intensity Gt, total window area Gh, window stained glass transmittance Gs, and building ground area Gd; Building equipment energy efficiency data include equipment cooling capacity Sl, equipment heating capacity Sr and equipment input power Ss; Energy-saving data include ventilation frequency Jh, building volume Jv and air specific heat capacity Jb.

[0024] In this embodiment, the system creates a three-dimensional model of the building based on the planning blueprint through the BIM modeling unit in the building simulation data extraction module, and performs component addition, HVAC system design, electrical equipment installation, material property definition and environmental parameter setting to generate a detailed energy consumption analysis diagram of the building. By fully simulating the building environment, the unit provides accurate cooling load, heating load and lighting demand data, thereby improving the accuracy and reliability of building energy-saving design. Compared with traditional two-dimensional blueprints, BIM technology realizes the three-dimensional and comprehensive building information, significantly improving the accuracy and efficiency of the design stage. The data extraction unit uses the Revit cloud analysis tool to extract energy consumption and energy-saving data in the BIM model in real time, and performs data outlier processing, format unification and conversion. This automated data processing method improves the speed and accuracy of data extraction and reduces manual intervention. Compared with traditional manual data collection, this method not only speeds up the data processing process, but also provides a more accurate and consistent data basis for subsequent energy consumption simulation and optimization analysis. Through the comprehensive extraction of heat transfer, lighting and equipment energy efficiency data, the data extraction unit can conduct in-depth energy consumption analysis and evaluate the energy-saving effect of the building. By calculating the total energy consumption and energy-saving potential of the building.

[0025] Example 3 This embodiment is explained in Example 1, please refer to Figure 1 ,Specifically: the energy consumption simulation module includes an energy consumption simulation unit, an ,energy consumption calculation unit and an energy consumption comprehensive ,calculation unit; The energy consumption simulation unit is used to import the constructed BIM building model into EnergyPlus, and based on the open source tools of EnergyPlus, provides an intuitive user interface for building energy consumption modeling and analysis, and constructs heat loss algorithm formulas, natural lighting algorithm formulas and equipment energy efficiency algorithm formulas to analyze the energy consumption related parameters of the building; The energy consumption calculation unit includes the building heat transfer loss calculation unit, the building natural lighting calculation unit and the equipment energy efficiency calculation unit; The building heat transfer loss calculation unit is used to load the real-time extracted heat transfer data according to the constructed heat loss algorithm formula, calculate and obtain the total heat transfer loss Zcd, and analyze and simulate the thermal conductivity performance of the building walls and windows; The total heat transfer loss Zcd is obtained by the following algorithm formula; ; Where dCq represents a small area element on the exterior surface of the building, which is used to integrate the total heat transfer loss, and Cq+Gh represents the boundary of the exterior surface area of ​​the building, which refers to the total surface of the building's exterior walls and windows.

[0026] The building natural lighting calculation unit is used to calculate and obtain the natural lighting quantity Zrc according to the constructed natural lighting algorithm formula and load the real-time extracted lighting data, and analyze the natural lighting of the simulated building at different time periods in a day; The amount of natural light Zrc is obtained by the following algorithm formula; ; In the formula, T represents the time interval, It represents the transmittance of window glass. Its specific parameters are set by the user during BIM modeling. dt represents the time integral.

[0027] The equipment energy efficiency calculation unit is used to calculate and obtain the equipment energy efficiency coefficient Jnx based on the constructed equipment energy efficiency algorithm formula and load the real-time extracted building equipment energy efficiency data to analyze the energy consumption of building equipment in different time periods; The equipment energy efficiency coefficient Jnx is obtained through the following algorithm formula; ; Where Sl i (t) represents the cooling capacity of the simulated equipment of the i-th equipment at time t, C cooling represents the cooling load factor, Ss iIndicates the device input power Ss, Sr of the simulated i-th device i (t) represents the heating capacity of the simulated i-th device at time t; The energy consumption comprehensive calculation unit is used to process the total heat transfer loss Zcd, natural light Zrc and equipment energy efficiency coefficient Jnx dimensionlessly, and then calculate and obtain the total energy consumption Zhnx of the building, and summarize and calculate the total energy consumption of the simulated building within a certain period of time; The total building energy consumption Zhnx is obtained through the following algorithm formula; ; Wherein, a1, a2 and a3 represent the preset weight values ​​of total heat transfer loss Zcd, natural light amount Zrc and equipment energy efficiency coefficient Jnx respectively, and a1+a2+a3=1, and the specific parameters are set by the user.

[0028] In this embodiment, the system uses the energy consumption simulation unit of the energy consumption simulation module to import the BIM building model into the EnergyPlus platform, and uses its open source tools to model and analyze building energy consumption. The unit provides an intuitive user interface, and at the same time constructs the heat loss algorithm formula, the natural lighting algorithm formula and the equipment energy efficiency algorithm formula through the algorithm tool to calculate the total heat transfer loss Zcd, the natural lighting amount Zrc and the equipment energy efficiency coefficient Jnx of the building respectively, so as to comprehensively evaluate the energy consumption of the building in different time periods. Among them, the building heat transfer loss calculation unit analyzes the thermal conductivity performance of the building walls and windows through the heat loss algorithm formula, providing a more detailed heat loss analysis. The building natural lighting calculation unit uses the natural lighting algorithm formula to analyze the amount of natural lighting within a day, providing reliable data support for building lighting design. The equipment energy efficiency calculation unit calculates the energy efficiency coefficient of the equipment through the equipment energy efficiency algorithm formula, and evaluates the energy consumption performance of the building equipment in different time periods. The energy consumption comprehensive calculation unit performs dimensionless processing on the total heat transfer loss Zcd, the amount of natural light Zrc and the equipment energy efficiency coefficient Jnx, calculates the total energy consumption Zhnx of the building, summarizes the overall energy consumption of the simulated building within a certain period of time, and provides an effective tool for quantifying the total energy consumption Zhnx of the building, providing data support for subsequent energy-saving optimization design. Compared with traditional energy consumption assessment methods, this method is more comprehensive and systematic, and provides a scientific basis for the formulation of energy-saving optimization plans.

[0029] Example 4 This embodiment is explained in Example 1, please refer to Figure 1 ,Specifically: the total energy consumption evaluation module is used to preset the building ,energy consumption threshold F1 according to the energy consumption index, and make a preliminary ,comparison evaluation with the acquired building total energy consumption Zhnx, and ,analyze the total energy consumption of the building within a certain ,time. The specific evaluation scheme is as follows; When the total building energy consumption Zhnx> the building energy consumption threshold F1, it means that the total energy consumption of the current simulated building design is abnormal, and further design is performed at this time; When the total building energy consumption Zhnx ≤ the building energy consumption threshold F1, it means that the total energy consumption of the current simulated building design is normal and no optimization is required.

[0030] In this embodiment, the system not only improves the efficiency and accuracy of building design energy consumption assessment through the introduction of the total energy consumption assessment module, but also provides a scientific basis for energy-saving design through the automated threshold comparison assessment mechanism. Compared with the traditional energy consumption assessment method, this module performs a preliminary assessment of the total building energy consumption Zhnx by presetting the building energy consumption threshold F1, making the energy consumption analysis more objective and automated, and providing an effective support tool for subsequent optimization design. This method not only improves the overall effect of building energy-saving design, but also promotes the technological progress from manual experience judgment to data-driven optimization.

[0031] Example 5 This embodiment is explained in Example 1, please refer to Figure 1 ,Specifically: the energy saving optimization module includes an optimization ,objective function unit and an optimization evaluation unit; The optimization objective function unit is used to re-evaluate the building's total energy consumption Zhnx when it is triggered by an abnormality, and further use the optimization objective function to construct the optimization objective function formula, load the extracted energy-saving data into the objective function formula, and calculate to obtain the optimization energy consumption coefficient Yhnh; The optimized energy consumption coefficient Yhnh is obtained through the following algorithm formula; ; In the formula, lq represents cooling energy consumption, the energy consumption of the air conditioning system, which is calculated by the equipment cooling capacity Sl and the equipment energy efficiency Jnx; qn represents heating energy consumption, the energy consumption of the heating system, which is calculated by the equipment heat and energy efficiency ratio. Indicates the preset weight value of ventilation energy consumption, represents the preset weight value of cooling energy consumption lq and heating energy consumption qn, represents the energy-saving optimization coefficient, which is calculated through simulation and experimental data, Jb(t) represents the air specific heat capacity Jb at time t, dt represents the time integral variable, It represents ventilation energy consumption. The meaning of the formula is: by calculating the total energy consumption of the building after optimization measures, combining the actual energy consumption and optimization effect, it helps to evaluate the actual effect of energy-saving measures, and finds the design solution with the best energy efficiency by minimizing the optimization objective function.

[0032] The optimization evaluation unit is used to perform a secondary comparative evaluation based on the obtained optimized energy consumption coefficient Yhnh and the preset building energy consumption threshold F1, and further analyze the energy consumption of the currently designed building after energy saving optimization. The specific evaluation scheme is as follows; When the optimized energy consumption coefficient Yhnh> the building energy consumption threshold F1, it means that the energy consumption effect of the currently designed building model after optimization is still abnormal. In this case, the building design is further optimized. When the optimized energy consumption coefficient Yhnh ≤ the building energy consumption threshold F1, it means that the energy consumption effect of the currently designed building model reaches normal after optimization, and the optimization is completed.

[0033] In this embodiment, the system provides a systematic improvement plan for building energy efficiency design through the coordinated work of the optimization objective function unit and the optimization evaluation unit of the energy-saving optimization module. The optimization objective function unit accurately calculates the optimization energy consumption coefficient by establishing the objective function formula, combining the actual energy consumption data with the optimization algorithm, so as to achieve scientific evaluation and optimization of building energy consumption. This process not only reveals the energy-saving potential in building design, but also provides a basis for further design improvement through the comparative analysis of the optimized energy consumption coefficient Yhnh and the building energy consumption threshold F1. When the optimized energy consumption coefficient Yhnh exceeds the building energy consumption threshold F1, the module can identify the part of the design that still needs to be improved; when the optimized energy consumption coefficient Yhnh is or is equal to the building energy consumption threshold F1, it indicates that the design has achieved the energy-saving goal. On the whole, the module helps designers find the design plan with the best energy efficiency through a rigorous optimization evaluation mechanism, and realizes the comprehensive optimization of building energy-saving design. This method not only improves the energy efficiency performance of the building, but also ensures the actual effect of energy-saving measures through accurate energy consumption data analysis, and has high practical application value and technical innovation.

[0034] Example 6 This embodiment is explained in Example 1, please refer to Figure 1 Specifically: the design optimization module is used to use the genetic algorithm GA to calculate and obtain the design optimization index f when the energy consumption of the simulated building is still abnormal after the energy consumption is optimized. Minimize (x) Optimize the design of the simulated building, adjust the building's basic structure, materials and energy-consuming equipment, and re-establish the BIM building model for specific analysis after the adjustment; Design optimization index f Minimize (x) is obtained through the following algorithm formula; ; Where Minimize represents the value of the optimized objective function, ObjectiveFunction represents the objective function, which is a mathematical function used to evaluate the quality of a design scheme, and xi represents the variable for optimizing the i-th objective, including but not limited to the location of doors and windows, the surface area of ​​doors and windows, the thickness of insulation materials, and the selection of energy-consuming equipment.

[0035] In this embodiment, the system uses the genetic algorithm GA to comprehensively optimize the building design through the design optimization module, providing advanced calculation methods and systematic solutions for improving building energy efficiency. When abnormal energy consumption is still found after optimizing the building energy consumption, the module can effectively use the genetic algorithm to calculate the design optimization index f Minimize (x), and make adjustments to the building's infrastructure, material selection, and energy-consuming equipment, thereby re-establishing the BIM building model and conducting a detailed analysis. The genetic algorithm systematically explores design variables such as door and window locations, door and window surface areas, insulation material thickness, and energy-consuming equipment selection, optimizes the minimization of the objective function, and ensures the optimal choice of the building design solution. This module not only provides a scientific optimization framework to deal with energy efficiency issues, but also ensures the maximization of the actual effect and optimization effect of building energy efficiency design by combining multivariable optimization with simulation analysis. Overall, this method achieves full cycle coverage from the initial design stage to optimization and improvement, improves the energy efficiency performance of building design and the quality of design solutions, and has significant technical innovation and practical application value.

[0036] Example 7 See also Figure 1 and Figure 2 , a building energy-saving design method, comprising the following steps: S1. First, use BIM modeling software to create a three-dimensional model of the building according to the current building planning blueprint, add relevant parameters and equipment of the building model, and use Revit's cloud analysis service tool to extract energy consumption data and energy-saving data from the constructed BIM building model in real time, and then perform preprocessing after extraction; S2. Import the constructed BIM building model into EnergyPlus, conduct building energy consumption modeling and analysis through an intuitive user interface, construct an algorithm formula, and calculate the total heat transfer loss Zcd, natural light volume Zrc and equipment energy efficiency coefficient Jnx based on the real-time extracted energy consumption data, and perform related calculations to obtain the total building energy consumption Zhnx; S3, compare and evaluate the preset building energy consumption threshold F1 with the obtained total building energy consumption Zhnx, and analyze the energy-saving effect of the current building; S4. When abnormal energy consumption of the current building is detected, the optimization objective function formula is constructed by combining the actual energy consumption and the optimization effect, and the optimized energy consumption coefficient Yhnh is calculated based on the energy-saving data obtained, and the obtained optimized energy consumption coefficient Yhnh is evaluated again with the preset building energy consumption threshold F1 to analyze the energy consumption after optimization; S5. Finally, if the building energy-saving optimization effect is still abnormal, the genetic algorithm GA is further used for design optimization to obtain the design optimization index f Minimize (x) Optimize the design of the building, adjust the building design, and re-establish the BIM building model to conduct energy consumption analysis.

[0037] While the embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that many changes, modifications, substitutions and variations can be made to the embodiments without departing from the principles and spirit of the invention.

Claims

1. A building energy-saving design system, characterized in that: It includes building simulation data extraction module, energy consumption simulation module, total energy consumption assessment module, energy saving optimization module and design optimization module; The building simulation data extraction module is used to construct a building model using BIM modeling software, extract energy consumption data and energy-saving data of the building model, and pre-process the extracted energy consumption data; The energy consumption simulation module is used to input the constructed BIM building model into the energy consumption simulation software for energy consumption simulation, and calculate the total heat transfer loss Zcd, natural light amount Zrc and equipment energy efficiency coefficient Jnx of the current BIM building model by constructing heat loss algorithm formula, natural light algorithm formula and equipment energy efficiency algorithm formula, and then perform summary calculation to obtain the total building energy consumption Zhnx; The total energy consumption evaluation module is used to compare and evaluate the preset building energy consumption threshold F1 with the acquired building total energy consumption Zhnx, and analyze the energy-saving effect of the current building; The energy-saving optimization module is used to be triggered when abnormal energy consumption of the current building is detected. The optimization objective function formula is constructed by combining the actual energy consumption and the optimization effect, and the optimized energy consumption coefficient Yhnh is calculated based on the acquired energy-saving data; The design optimization module is used to perform a secondary comparative evaluation and analysis on the obtained optimized energy consumption coefficient Yhnh and the preset building energy consumption threshold F1, and then calculate the energy consumption of the building after energy-saving optimization. When the energy consumption of the building after energy-saving optimization is evaluated to be abnormal, the design scheme of the current building is further optimized by adopting a genetic algorithm.

2. A building energy-saving design system according to claim 1, characterized in that: The building simulation data extraction module includes a BIM modeling unit and a data extraction unit; The BIM modeling unit is used to draw a three-dimensional model of the building according to the planning blueprint of the current building using BIM modeling software at the same scale as the planning blueprint, and add building components to the three-dimensional model, design the HVAC system, install electrical equipment, define building materials, configure equipment parameters and set building environmental parameters, and then generate an energy consumption analysis diagram of the building, including cooling load, heating load and lighting requirements, to construct a BIM building model; The data extraction unit is used to extract the energy consumption data and energy-saving data of the constructed BIM building model in real time according to the Revit cloud analysis service tool in the BIM modeling software, and perform data preprocessing on the extracted energy consumption data and energy-saving data, wherein the preprocessing method includes checking and processing abnormal values ​​in the data, unifying the data format, and converting the data into a data format suitable for the optimization algorithm; The energy consumption data includes heat transfer data, lighting data and building equipment energy efficiency data; The heat transfer data include wall heat transfer coefficient Cr, total wall surface area Cq, window heat transfer coefficient Cc, simulated indoor temperature Cs and simulated outdoor temperature Cw; The lighting data include solar radiation intensity Gt, total window area Gh, window stained glass transmittance Gs and building ground area Gd; The building equipment energy efficiency data includes equipment cooling capacity Sl, equipment heating capacity Sr and equipment input power Ss; The energy-saving data include ventilation frequency Jh, building volume Jv and air specific heat capacity Jb.

3. A building energy-saving design system according to claim 2, characterized in that: The energy consumption simulation module includes an energy consumption simulation unit, an energy consumption calculation unit and an energy consumption comprehensive calculation unit; The energy consumption simulation unit is used to import the constructed BIM building model into EnergyPlus, and based on the open source tool of EnergyPlus, provides an intuitive user interface for building energy consumption modeling and analysis, and constructs heat loss algorithm formula, natural lighting algorithm formula and equipment energy efficiency algorithm formula to analyze the energy consumption related parameters of the building; The energy consumption calculation unit includes a building heat transfer loss calculation unit, a building natural lighting calculation unit and an equipment energy efficiency calculation unit; The building heat transfer loss calculation unit is used to load the heat transfer data extracted in real time according to the constructed heat loss algorithm formula, calculate and obtain the total heat transfer loss Zcd, and analyze and simulate the thermal conductivity performance of the building walls and windows; The total heat transfer loss Zcd is obtained by the following algorithm formula: ； In the formula, dCq represents the small area element on the outer surface of the building, and Cq+Gh represents the boundary of the outer surface area of ​​the building.

4. A building energy-saving design system according to claim 3, characterized in that: The building natural lighting calculation unit is used to calculate and obtain the natural lighting quantity Zrc according to the constructed natural lighting algorithm formula and load the real-time extracted lighting data, and analyze the natural lighting of the simulated building at different time periods in a day; The natural light amount Zrc is obtained by the following algorithm formula: ； In the formula, T represents the time interval, It represents the transmittance of window glass. Its specific parameters are set by the user during BIM modeling. dt represents the time integral.

5. The building energy-saving design system according to claim 3, characterized in that: The equipment energy efficiency calculation unit is used to calculate and obtain the equipment energy efficiency coefficient Jnx according to the constructed equipment energy efficiency algorithm formula, and load the real-time extracted building equipment energy efficiency data, analyze the energy consumption of building equipment in different time periods; The equipment energy efficiency coefficient Jnx is obtained by the following algorithm formula; ； Where Sl i (t) represents the cooling capacity of the simulated equipment of the i-th equipment at time t, C cooling represents the cooling load factor, Ss i Indicates the device input power Ss, Sr of the simulated i-th device i (t) represents the heating capacity of the simulated i-th device at time t; The energy consumption comprehensive calculation unit is used to process the obtained total heat transfer loss Zcd, natural light amount Zrc and equipment energy efficiency coefficient Jnx dimensionlessly, and then calculate and obtain the total energy consumption Zhnx of the building, and summarize and calculate the total energy consumption of the simulated building within a certain period of time; The total building energy consumption Zhnx is obtained by the following algorithm formula; ； Wherein, a1, a2 and a3 represent the preset weight values ​​of total heat transfer loss Zcd, natural light amount Zrc and equipment energy efficiency coefficient Jnx respectively, and a1+a2+a3=1, and the specific parameters are set by the user.

6. The building energy-saving design system according to claim 1, characterized in that: The total energy consumption evaluation module is used to preset the building energy consumption threshold F1 according to the energy consumption index, and make a preliminary comparative evaluation with the acquired building total energy consumption Zhnx, and analyze the total energy consumption of the building within a certain period of time. The specific evaluation scheme is as follows; When the total building energy consumption Zhnx> the building energy consumption threshold F1, it means that the total energy consumption of the current simulated building design is abnormal, and further design is performed at this time; When the total building energy consumption Zhnx ≤ the building energy consumption threshold F1, it means that the total energy consumption of the current simulated building design is normal and no optimization is required.

7. A building energy-saving design system according to claim 6, characterized in that: The energy-saving optimization module includes an optimization objective function unit and an optimization evaluation unit; The optimization objective function unit is used to re-evaluate the building total energy consumption Zhnx when it is triggered by an abnormality, further use the optimization objective function, construct the optimization objective function formula, load the extracted energy-saving data into the objective function formula, and calculate to obtain the optimization energy consumption coefficient Yhnh; The optimized energy consumption coefficient Yhnh is obtained by the following algorithm formula; ； In the formula, lq represents the cooling energy consumption, the energy consumption of the air conditioning system, and qn represents the heating energy consumption, the energy consumption of the heating system, which is calculated by the equipment heat and energy efficiency ratio. Indicates the preset weight value of ventilation energy consumption, represents the preset weight value of cooling energy consumption lq and heating energy consumption qn, represents the energy-saving optimization coefficient, Jb(t) represents the air specific heat capacity Jb at time t, and dt represents the time integral variable.

8. A building energy-saving design system according to claim 7, characterized in that: The optimization evaluation unit is used to perform a secondary comparative evaluation based on the obtained optimized energy consumption coefficient Yhnh and the preset building energy consumption threshold F1, and further analyze the energy consumption of the currently designed building after energy saving optimization. The specific evaluation scheme is as follows; When the optimized energy consumption coefficient Yhnh> the building energy consumption threshold F1, it means that the energy consumption effect of the currently designed building model after optimization is still abnormal. In this case, the building design is further optimized. When the optimized energy consumption coefficient Yhnh ≤ the building energy consumption threshold F1, it means that the energy consumption effect of the currently designed building model reaches normal after optimization, and the optimization is completed.

9. A building energy-saving design system according to claim 8, characterized in that: The design optimization module is used to use the genetic algorithm GA to calculate and obtain the design optimization index f when the energy consumption of the simulated building is still abnormal after the energy consumption is optimized. Minimize (x) Optimize the design of the simulated building, adjust the building's basic structure, materials and energy-consuming equipment, and re-establish the BIM building model for specific analysis after the adjustment; The design optimization index f Minimize (x) is obtained by the following algorithm formula; ； In the formula, Minimize represents the value of the optimized objective function, ObjectiveFunction represents the objective function, and xi represents the variable for optimizing the i-th objective.

10. A building energy-saving design method, comprising a building energy-saving design system according to any one of claims 1 to 9, characterized in that: The following steps are involved: S1. First, use BIM modeling software to create a three-dimensional model of the building according to the current building planning blueprint, add relevant parameters and equipment of the building model, and use Revit's cloud analysis service tool to extract energy consumption data and energy-saving data from the constructed BIM building model in real time, and then perform preprocessing after extraction; S2. Import the constructed BIM building model into EnergyPlus, conduct building energy consumption modeling and analysis through an intuitive user interface, construct an algorithm formula, and calculate the total heat transfer loss Zcd, natural light volume Zrc and equipment energy efficiency coefficient Jnx based on the real-time extracted energy consumption data, and perform related calculations to obtain the total building energy consumption Zhnx; S3, compare and evaluate the preset building energy consumption threshold F1 with the obtained total building energy consumption Zhnx, and analyze the energy-saving effect of the current building; S4. When abnormal energy consumption of the current building is detected, the optimization objective function formula is constructed by combining the actual energy consumption and the optimization effect, and the optimized energy consumption coefficient Yhnh is calculated based on the energy-saving data obtained, and the obtained optimized energy consumption coefficient Yhnh is evaluated again with the preset building energy consumption threshold F1 to analyze the energy consumption after optimization; S5. Finally, if the building energy-saving optimization effect is still abnormal, the genetic algorithm GA is further used for design optimization to obtain the design optimization index f Minimize (x) Optimize the design of the building, adjust the building design, and re-establish the BIM building model to conduct energy consumption analysis.

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