Building thermal performance intelligent energy-saving analysis method based on BIM

Abstract

The invention provides an intelligent energy-saving analysis method for thermal performance of a building based on BIM (Building Information Modeling). The intelligent energy-saving analysis method comprises the following steps of: scanning the building in all directions by using a three-dimensional laser scanning technology to obtain three-dimensional geometric data of the building, and constructing a BIM model in BIM software based on the three-dimensional geometric data of the building; thermal performance parameters of the building envelope are integrated in the BIM model; based on the thermal performance parameters, utilizing a thermal performance simulation algorithm to simulate heat conduction, a heat bridge effect and a solar heat gaining condition of the building; and automatically generating an energy-saving optimization strategy according to a simulation result of the thermal performance simulation algorithm by utilizing machine learning and an energy-saving optimization algorithm. According to the method, a comprehensive, accurate and automatic analysis and optimization method can be provided for the field of building energy conservation, remarkable improvement of building energy efficiency and effective reduction of energy cost are facilitated, and meanwhile, convenient, efficient and personalized service experience is provided for users.

Description

Technical Field

[0001] The present invention relates to the field of building energy conservation, and in particular to a building thermal performance intelligent energy conservation analysis method based on BIM. Background Art

[0002] With the continuous growth of global energy consumption and the increasingly serious environmental problems, building energy conservation has become an important issue that cannot be ignored in building design, construction and operation. The energy consumption of buildings during their life cycle accounts for a considerable proportion. Therefore, improving building energy efficiency and reducing building energy consumption have significant economic and environmental value. Traditional building energy conservation analysis mainly relies on empirical estimation and simplified calculations. These methods often fail to fully consider the complexity and variability of buildings, making it difficult to achieve refined and personalized energy-saving design. Summary of the invention

[0003] In order to overcome the defects in the above-mentioned prior art, the purpose of the present invention is to provide a BIM-based intelligent energy-saving analysis method for building thermal performance.

[0004] In order to achieve the above-mentioned object of the present invention, the present invention provides a method for intelligent energy-saving analysis of building thermal performance based on BIM, comprising the following steps:

[0005] Use 3D laser scanning technology to scan the building in all directions to obtain the 3D geometric data of the building, and build a BIM model based on the 3D geometric data of the building in the BIM software;

[0006] Integrate thermal performance parameters of building envelope into BIM models;

[0007] Based on the thermal performance parameters, a thermal performance simulation algorithm is used to simulate the heat conduction, thermal bridge effect and solar heat gain of the building;

[0008] Using machine learning and energy-saving optimization algorithms, energy-saving optimization strategies are automatically generated based on the simulation results of thermal performance simulation algorithms;

[0009] Deploy a multidisciplinary collaborative work platform that integrates real-time communication and data sharing capabilities;

[0010] Integrating the BIM model with the energy management system results in a building life cycle energy management system that continuously tracks, analyzes and optimizes the energy usage and maintenance of the building throughout its life cycle.

[0011] Optionally, the thermal performance simulation algorithm includes:

[0012] Based on finite element analysis (FEA), the building components are discretized into a finite number of elements and nodes, and a mathematical model of heat conduction is established. The material property data in the BIM model is used as the input parameter of the finite element analysis (FEA) to calculate the heat transfer path and temperature distribution under different materials and structural configurations;

[0013] A computational domain of a fluid dynamics (CFD) simulation is set in the BIM model based on the three-dimensional geometric data, air flow, temperature distribution and temperature change inside the building are simulated based on the fluid dynamics (CFD), and the influence of different ventilation strategies on the indoor thermal environment is evaluated;

[0014] The input parameters of the solar radiation model are adjusted based on the geographic information system (GIS) data. The impact of solar radiation on the building is calculated in the solar radiation model according to the building's geographical location, orientation and seasonal changes, providing a solar energy integration solution for building design.

[0015] This optional solution can comprehensively evaluate the thermal performance of a building, provide scientific decision-making support for building design and operation, and optimize and improve building energy efficiency.

[0016] Optionally, the energy-saving optimization strategy includes:

[0017] Taking the aesthetics, practicality, economy and energy efficiency of the building as the goals, the optimal building design solution is automatically calculated based on the multi-objective optimization algorithm;

[0018] Combine building life cycle cost analysis (LCCA) to evaluate the economic benefits of energy-saving optimization strategies;

[0019] The user interaction interface allows users to adjust energy-saving optimization strategies according to actual needs and preferences.

[0020] Optionally, the multidisciplinary collaborative work platform includes:

[0021] Integrated project management tools to track project progress and coordinate the work of various parties involved; allowing architects, engineers, contractors and facility managers to collaborate and make decisions in real time on the same BIM model;

[0022] A shared BIM model viewing and editing platform that supports people from different professions to access, comment on and modify models;

[0023] Communication and collaboration tools that support instant messaging, video conferencing, and document sharing among team members.

[0024] Optionally, the integration steps of the building life cycle energy management system are:

[0025] Establish a building energy usage database to record the building's energy consumption and conduct trend analysis;

[0026] Use data analytics and machine learning techniques to predict a building’s energy demand and energy-saving potential;

[0027] Develop appropriate energy-saving measures, implement energy audits and maintenance plans, optimize the energy efficiency of buildings, and regularly evaluate the effectiveness of energy-saving measures.

[0028] Optional: Energy-saving analysis and scheme design during the building design phase: Use the BIM model to conduct preliminary energy-saving analysis and evaluate the impact of different design schemes on building energy consumption;

[0029] Apply intelligent simulation algorithms, such as FEA and CFD, to predict the thermal comfort and energy demand of buildings under different design options;

[0030] Conduct scheme design based on simulation results and select the optimal building layout, materials and component configuration;

[0031] The expected outcome of the design phase is to form a set of energy-saving and functional building design solutions and generate a corresponding BIM model.

[0032] Optionally, this also includes construction simulation and material management during the building construction phase:

[0033] Use BIM models to perform three-dimensional simulation of the construction process and optimize the construction plan and sequence;

[0034] Apply BIM models for material management, including material procurement planning, inventory control and on-site logistics arrangements;

[0035] Through the integration of construction simulation with BIM models, possible conflicts and problems that may arise during the construction process can be identified and solutions can be formulated in advance; the expected results of the construction phase are to improve construction efficiency, reduce material waste, and ensure construction quality and safety.

[0036] Optionally, this also includes energy management and maintenance during the building operation phase:

[0037] Integrate building operation data including energy consumption, equipment status and maintenance records using BIM models;

[0038] Apply intelligent algorithms, such as predictive maintenance based on machine learning, to perform condition monitoring and fault diagnosis on building equipment;

[0039] Implement energy management strategies such as optimizing energy usage patterns, scheduled maintenance and equipment upgrades to extend equipment life and reduce energy consumption;

[0040] The expected results of the operation phase are to achieve efficient energy use in the building, reduce operating costs and improve the sustainable performance of the building.

[0041] Optionally, use virtual reality (VR) and augmented reality (AR) technologies to show users energy-saving optimization solutions, energy-saving analysis simulation results, and interactive experiences;

[0042] Use mobile devices and cloud technology to achieve anytime, anywhere access to BIM models and energy management;

[0043] Use blockchain technology to ensure the security, integrity and traceability of BIM model data.

[0044] Optionally, install sensors at key locations of the building to monitor indoor and outdoor temperature, humidity, etc., and use the Internet of Things technology to receive real-time meteorological data and indoor and outdoor environmental monitoring data, and dynamically adjust energy-saving optimization strategies;

[0045] Use machine learning technology to predict the failure and maintenance needs of building equipment by analyzing the equipment's operating data and maintenance history to predict potential failures and performance degradation;

[0046] Utilize sensors and data analysis technology to collect user behavior data, evaluate user responses and preferences to the building environment, optimize the building's energy usage patterns based on user behavior analysis, and adjust energy-saving optimization strategies based on user behavior data.

[0047] The beneficial effects of the present invention are as follows: the present invention can provide a comprehensive, accurate and automated analysis and optimization method for the field of building energy conservation, which helps to significantly improve building energy efficiency and effectively reduce energy costs, while providing users with a convenient, efficient and personalized service experience.

[0048] The present invention proposes a series of innovative solutions to the many technical problems existing in the field of building energy-saving analysis, including how to achieve efficient integration of building data, improve the accuracy of thermal performance simulation, promote real-time collaboration between multidisciplinary teams, achieve energy management throughout the life cycle of buildings, conduct real-time performance monitoring and response, predictively maintain building equipment, match user behavior with energy usage patterns, provide intuitive technical display and interactive experience, achieve integration of mobile access and cloud technology, ensure data security and integrity, provide services that meet personalized needs, achieve seamless integration with existing building design and energy simulation software, and develop a user-friendly operating interface. By constructing a detailed BIM model, intelligent simulation algorithm, establishing a multidisciplinary collaborative work platform, integrating real-time monitoring data, applying machine learning for predictive maintenance, analyzing user behavior to optimize energy use, using VR / AR technology to enhance experience, using mobile applications to achieve cloud access, using blockchain technology to ensure data security, providing customized services to meet different user needs, and designing an easy-to-use multilingual user interface, the present invention significantly improves the accuracy, efficiency and user interaction experience of building energy-saving analysis, while ensuring data security and software compatibility.

[0049] Additional aspects and advantages of the present invention will be given in part in the following description and in part will be obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] The above and / or additional aspects and advantages of the present invention will become apparent and easily understood from the description of the embodiments in conjunction with the following drawings, in which:

[0051] Figure 1 It is a schematic diagram of the framework of an embodiment;

[0052] Figure 2 It is a schematic diagram of the flow chart of the embodiment. DETAILED DESCRIPTION

[0053] Embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and cannot be understood as limiting the present invention.

[0054] In the description of the present invention, unless otherwise specified and limited, it should be noted that the terms "installed", "connected" and "connected" should be understood in a broad sense. For example, it can be a mechanical connection or an electrical connection, or it can be the internal connection between two components. It can be a direct connection or an indirect connection through an intermediate medium. For ordinary technicians in this field, the specific meanings of the above terms can be understood according to the specific circumstances.

[0055] like Figure 1 and Figure 2 As shown, the present invention provides an embodiment of an intelligent energy-saving analysis method for building thermal performance based on BIM.

[0056] Project initiation and demand analysis: Establish a project team and assign roles, including BIM modelers, energy analysts, software engineers, etc. Conduct demand analysis to determine project goals, schedules, and budgets. The demand analysis cycle is expected to be 1 week.

[0057] After project initiation and requirements analysis are completed, perform the following steps:

[0058] The 3D laser scanning technology is used to collect on-site data of the building, and the photogrammetry technology is used to collect the texture and color information of the building surface to enhance the realism and visual effect of the model. In this embodiment, a high-precision laser scanner is used to perform a full-scale scan of the existing building, collect point cloud data, including the precise geometric data of the building, including information such as size, shape and spatial layout. The scanning process includes internal and external structures to ensure that comprehensive data is obtained. It is expected to take 2 days. The building appearance image is obtained by drone photogrammetry to obtain the texture and color information of the building surface, which is expected to take 1 day.

[0059] Preliminary construction of BIM model: Based on the collected point cloud data, including the geometric shapes, spatial layout and appearance images of components such as walls, roofs, floors, windows, etc., a detailed three-dimensional BIM model is constructed in the BIM software to obtain a preliminary building model. The estimated preliminary modeling cycle is 2 weeks. The accuracy of the preliminary building model is verified to ensure consistency with the on-site data. The preliminary building model contains detailed information such as the building geometry, material properties, and component connection relationships. Through the parametric function of the BIM software, the building model can be dynamically updated to adapt to design changes and material replacements.

[0060] Input the material properties of building components in the BIM model, such as thermal conductivity, density, specific heat capacity, etc. These parameters are the basis for thermal performance simulation, and are crucial for subsequent thermal conduction, thermal bridge effect and solar heat gain simulation, and can provide basic data for subsequent thermal performance analysis. For example: the thermal conductivity of the wall material λ = 0.6W / m·K, and the expected input cycle is 1 week. The U value input for the building exterior window is 1.8W / m2·K, which is determined based on the characteristics of double-layer insulating glass.

[0061] Set environmental parameters and simulation conditions: According to the climate data of the building location, set the simulation conditions, including an annual average temperature of 15°C, humidity of 65%, wind speed of 2.5m / s, and solar radiation of 1100W / m2. The estimated condition setting period is 1 week.

[0062] Thermal performance simulation: Integrate the thermal performance parameters of the building envelope into the BIM model, including but not limited to thermal conductivity, heat capacity, thermal resistance, etc., to provide key input for thermal performance simulation and simulate the temperature changes of the building in a typical summer and winter day. The simulation cycle is expected to be 3 weeks.

[0063] For complex building components, such as double-glazed windows and composite walls, detailed thermal performance analysis is performed to ensure the accuracy of the BIM model and the reliability of the simulation results.

[0064] The database function of BIM software is used to store and manage thermal performance parameters, which facilitates parameter query, update and maintenance.

[0065] This embodiment adopts a comprehensive thermal performance simulation algorithm, which specifically includes the following aspects:

[0066] Heat conduction simulation algorithm based on finite element analysis (FEA): This algorithm establishes a mathematical model of heat conduction by discretizing building components into a finite number of elements and nodes. The material property data in the BIM model, such as thermal conductivity, specific heat capacity, etc., are used to provide the necessary input parameters for FEA. The algorithm can accurately calculate the heat transfer path and temperature distribution under different materials and structural configurations. The expected result is to generate a detailed heat conduction report, including heat loss, thermal bridge effect, and internal temperature field distribution.

[0067] Thermal bridge effect simulation: Thermal bridge effect refers to the local heat flow concentration phenomenon caused by the difference in thermal resistance at the junction of building components with different materials or different thicknesses. The simulation algorithm needs to take these factors into account to evaluate the impact of thermal bridges on the overall heat loss of the building.

[0068] Thermal bridge effect simulation algorithm combining building information modeling and computational fluid dynamics (CFD) technology: This algorithm integrates the three-dimensional geometric information of the BIM model and is used to set the calculation domain of the CFD simulation. The air flow, temperature distribution and humidity changes inside the building are simulated through CFD technology, taking into account the effects of natural ventilation and mechanical ventilation. The algorithm can evaluate the impact of different ventilation strategies on the indoor thermal environment and provide suggestions for optimizing the design of the ventilation system for building design. The expected result is to provide an indoor thermal comfort analysis report, including air flow rate, temperature distribution and humidity level.

[0069] Solar heat gain simulation algorithm using solar radiation model and geographic information system (GIS) data: This algorithm combines solar radiation model to calculate the impact of solar radiation on the building based on the building's geographical location, orientation and seasonal changes. GIS data, including terrain, building shading and climate conditions, are used to adjust the input parameters of the solar radiation model to improve the accuracy of the simulation. The algorithm can evaluate the efficiency of the building's use of solar energy, including the potential for solar heating, natural lighting and solar power generation. The expected result is to generate a solar utilization analysis report to provide solar integration solutions for building design, such as solar panel layout and window design.

[0070] Through the combined use of these three simulation algorithms, the intelligent energy-saving analysis method of the present invention can comprehensively evaluate the thermal performance of a building, provide scientific decision-making support for building design and operation, and achieve optimization and improvement of building energy efficiency.

[0071] The expected simulation results show that the maximum temperature inside the building will not exceed 28°C and the minimum temperature will not be lower than 18°C.

[0072] Automatic generation of energy-saving optimization strategies: Use machine learning and energy-saving optimization algorithms to analyze simulation results and automatically generate energy-saving optimization strategies. Strategies may include adjusting building design, material selection, component configuration, etc. to improve energy efficiency, such as increasing the thickness of the insulation layer, adjusting the size of windows, etc. The estimated strategy generation cycle is 4 weeks. It is expected that through optimization measures, the building energy consumption will be reduced by 15%.

[0073] The energy-saving optimization strategy includes:

[0074] Considering the aesthetics, practicality, economy and energy efficiency of the building as the goals, the optimal building design solution is automatically calculated based on machine learning and multi-objective optimization algorithms, including the thickness of the insulation layer of the wall and roof, the size and location of the windows, the selection and replacement of materials, etc. The specific algorithm here can use the existing algorithm. The user interaction interface allows users to adjust the energy-saving optimization strategy according to actual needs and preferences.

[0075] Combined with building life cycle cost analysis (LCCA), the economic benefits of energy-saving optimization strategies are evaluated, and the energy-saving effects and economic benefits are displayed in real time through visualization tools.

[0076] Deployment and testing of collaborative work platform: Deploy a multidisciplinary collaborative work platform, integrating real-time communication and data sharing functions, with an estimated deployment period of 1 month. Conduct platform testing to ensure that different professional teams can collaborate and make decisions in real time on the same BIM model without obstacles.

[0077] The multidisciplinary collaborative work platform includes:

[0078] An integrated project management tool for tracking project progress and coordinating the work of various parties involved; allowing architects, engineers, contractors, and facility managers to collaborate and make decisions in real time on the same BIM model, improving the efficiency of design and construction.

[0079] A shared BIM model viewing and editing platform that supports people from different disciplines to access, comment on and modify the model to achieve design integration and optimization, and reduce design conflicts and construction errors.

[0080] A communication and collaboration tool that supports instant messaging, video conferencing, and document sharing among team members to improve the efficiency of team collaboration and the success rate of projects.

[0081] Integration of the full life cycle energy management system: Integrate the BIM model with the energy management system to obtain a building full life cycle energy management system, which can continuously track, analyze and optimize the energy use and maintenance of the building throughout its life cycle. The integration cycle is expected to be 2 months. It is expected that real-time optimization of energy consumption can be achieved through the energy management system.

[0082] The integration steps of the building life cycle energy management system are:

[0083] Establish a building energy usage database to record the building's energy consumption and conduct trend analysis to identify energy saving opportunities and develop improvement measures;

[0084] Use data analytics and machine learning techniques to predict a building’s energy demand and energy-saving potential;

[0085] Develop appropriate energy-saving measures, implement energy audits and maintenance plans, such as equipment upgrades, behavioral adjustments, etc., to optimize the energy efficiency of buildings, and regularly evaluate the effectiveness of energy-saving measures.

[0086] Installation and scheduling of monitoring systems, real-time data integration: Install sensors at key locations in the building to monitor indoor and outdoor temperature, humidity, etc., and use the Internet of Things technology for real-time reception to obtain real-time meteorological data and indoor and outdoor environmental monitoring data. The estimated installation period is 2 weeks. Debug the monitoring system to ensure the accuracy and real-time nature of the data. Integrate real-time meteorological data and indoor and outdoor environmental monitoring data into the BIM model to provide real-time input for thermal performance analysis and energy management, so as to improve the accuracy and real-time nature of BIM simulation, realize dynamic thermal performance analysis, and dynamically adjust energy-saving optimization strategies.

[0087] Intelligent diagnosis and predictive maintenance: Use machine learning technology to predict the failure and maintenance needs of building equipment, reduce unexpected downtime and repair costs; predict potential failures and performance degradation by analyzing the equipment's operating data and maintenance history to achieve preventive maintenance and optimize maintenance plans. It is expected that through predictive maintenance, the unexpected failure rate will be reduced by 50%.

[0088] Collection and analysis of user behavior data: Collect user activity data in the building, such as lighting and air conditioning usage, with an estimated collection period of 1 month. Analyze user behavior data, adjust energy-saving optimization strategies, and optimize energy usage patterns.

[0089] In this embodiment, sensors and data analysis technology are used to collect user behavior data, such as indoor activities and energy usage habits, to evaluate user responses and preferences for the building environment. Combined with user behavior analysis, the energy usage pattern of the building is optimized to improve energy efficiency and user satisfaction. Based on user behavior data, energy usage strategies, such as lighting control and temperature adjustment, are adjusted to meet user needs and reduce energy consumption.

[0090] Application of virtual reality and augmented reality technology: Use virtual reality (VR) and augmented reality (AR) technology to show users energy-saving optimization solutions, energy-saving analysis simulation results and interactive experience, and enhance users' understanding of energy-saving design and optimization effects. Virtual reality (VR) and augmented reality (AR) applications allow users to view building models and energy-saving optimization solutions in a virtual environment for immersive design evaluation and decision-making. Through VR / AR technology, users' awareness and participation in energy-saving design can be improved.

[0091] Mobile devices and cloud technology applications: Using mobile devices and cloud technology to achieve anytime, anywhere access to BIM models and energy management, improve user convenience and flexibility. Allow users to access BIM models and energy management data through smartphones or tablets for remote monitoring and control. This will increase user access frequency and participation.

[0092] Application of blockchain technology: Use blockchain technology to ensure the security, integrity and traceability of BIM model data, and enhance the reliability and trust of data. Through blockchain technology, distributed storage and encryption protection of data can be achieved to prevent data tampering and unauthorized access, and ensure the long-term preservation and use of data. Blockchain technology can improve the transparency and trust of data.

[0093] Customized service: Provide personalized energy-saving analysis and optimization solutions according to the specific needs of users to meet the specific requirements of different users; customize energy-saving analysis and optimization strategies according to the user's geographical location, climate conditions, building type and usage requirements to achieve the best energy-saving effect and return on investment. Customized services will meet the personalized needs of users and improve user satisfaction.

[0094] Existing software integration and data exchange: Integrate existing building design software and energy simulation software to achieve seamless data exchange and sharing, improve work efficiency and data consistency. Through open APIs and data exchange formats, achieve interoperability with mainstream building design and energy simulation software, and facilitate users to migrate and integrate existing data and tools. Through existing software integration and data exchange, achieve seamless data exchange and improve data consistency by 100%.

[0095] Optimization of the user interface: The user interface design takes into account the needs of users with different professional backgrounds, provides intuitive operation instructions and feedback information, and helps users quickly understand and master the energy-saving analysis and optimization process; supports multi-language interfaces to meet the needs of users in different countries and regions, and promotes the international application of this energy-saving analysis method; simplifies the user operation process, improves user experience, reduces user operation difficulty, attracts more users to use this energy-saving analysis method, and improves ease of use and accessibility.

[0096] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "examples", "specific examples", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0097] Although the embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the claims and their equivalents.

Claims

1. A BIM-based intelligent energy-saving analysis method for building thermal performance, characterized in that: The following steps are involved: Use 3D laser scanning technology to scan the building in all directions to obtain the 3D geometric data of the building, and build a BIM model based on the 3D geometric data of the building in the BIM software; Integrate thermal performance parameters of building envelope into BIM models; Based on the thermal performance parameters, a thermal performance simulation algorithm is used to simulate the heat conduction, thermal bridge effect and solar heat gain of the building; Using machine learning and energy-saving optimization algorithms, energy-saving optimization strategies are automatically generated based on the simulation results of thermal performance simulation algorithms; Deploy a multidisciplinary collaborative work platform that integrates real-time communication and data sharing capabilities; Integrating the BIM model with the energy management system results in a building life cycle energy management system that continuously tracks, analyzes and optimizes the energy usage and maintenance of the building throughout its life cycle.

2. The intelligent energy-saving analysis method for building thermal performance based on BIM according to claim 1 is characterized in that: The thermal performance simulation algorithm includes: discretizing the building components into a finite number of elements and nodes based on finite element analysis (FEA), establishing a mathematical model of heat conduction, using the material property data in the BIM model as input parameters of the finite element analysis (FEA), and calculating the heat transfer path and temperature distribution under different materials and structural configurations; A computational domain of a fluid dynamics (CFD) simulation is set in the BIM model based on the three-dimensional geometric data, air flow, temperature distribution and temperature change inside the building are simulated based on the fluid dynamics (CFD), and the influence of different ventilation strategies on the indoor thermal environment is evaluated; The input parameters of the solar radiation model are adjusted based on the geographic information system (GIS) data. The impact of solar radiation on the building is calculated in the solar radiation model according to the building's geographical location, orientation and seasonal changes, providing a solar energy integration solution for building design.

3. The intelligent energy-saving analysis method for building thermal performance based on BIM according to claim 1 is characterized in that: The energy-saving optimization strategy includes: Taking the aesthetics, practicality, economy and energy efficiency of the building as the goals, the optimal building design solution is automatically calculated based on the multi-objective optimization algorithm; Evaluate the economic benefits of energy-saving optimization strategies by combining building life cycle cost analysis (LCCA); The user interactive interface allows users to adjust the energy-saving optimization strategy according to actual needs and preferences.

4. The intelligent energy-saving analysis method for building thermal performance based on BIM according to claim 1 is characterized in that: The multidisciplinary collaborative work platform includes: Integrated project management tools to track project progress and coordinate the work of various parties involved; allowing architects, engineers, contractors and facility managers to collaborate and make decisions in real time on the same BIM model; A shared BIM model viewing and editing platform that supports people from different disciplines to access, comment on and modify models; Communication and collaboration tools that support instant messaging, video conferencing, and document sharing among team members.

5. The intelligent energy-saving analysis method for building thermal performance based on BIM according to claim 1 is characterized in that: The integration steps of the building life cycle energy management system are: Establish a database of energy usage of buildings, record the energy consumption of buildings, and conduct trend analysis; Use data analytics and machine learning techniques to predict a building’s energy demand and energy-saving potential; Develop appropriate energy-saving measures, implement energy audits and maintenance plans, optimize the energy efficiency of buildings, and regularly evaluate the effectiveness of energy-saving measures.

6. The intelligent energy-saving analysis method for building thermal performance based on BIM according to claim 1 is characterized in that: Also included are construction simulation and material management during the building construction phase: Use BIM models to perform three-dimensional simulation of the construction process and optimize the construction plan and sequence; Apply BIM models for material management, including material procurement planning, inventory control and on-site logistics arrangements.

7. The intelligent energy-saving analysis method for building thermal performance based on BIM according to claim 1 is characterized in that: Use virtual reality (VR) and augmented reality (AR) technologies to show users energy-saving optimization solutions, energy-saving analysis simulation results and interactive experiences; Use mobile devices and cloud technology to achieve anytime, anywhere access to BIM models and energy management; Use blockchain technology to ensure the security, integrity and traceability of BIM model data.

8. The intelligent energy-saving analysis method for building thermal performance based on BIM according to claim 1 is characterized in that: Install sensors at key locations in buildings to monitor indoor and outdoor temperature and humidity, and use IoT technology to receive real-time meteorological data and indoor and outdoor environmental monitoring data to dynamically adjust energy-saving optimization strategies; Use machine learning technology to predict the failure and maintenance needs of building equipment by analyzing the equipment's operating data and maintenance history to predict potential failures and performance degradation; Utilize sensors and data analysis technology to collect user behavior data, evaluate user responses and preferences to the building environment, optimize the building's energy usage patterns based on user behavior analysis, and adjust energy-saving optimization strategies based on user behavior data.

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